From 1069aa420b424c58ab8b18911f9759ed2c089b2f Mon Sep 17 00:00:00 2001
From: Danilo Ferreira de Lima <danilo.enoque.ferreira.de.lima@xfel.de>
Date: Fri, 17 Dec 2021 16:13:42 +0100
Subject: [PATCH] Updated all notebooks with the correct emails, some clean up
and lots of details in the README about the Anaconda setup.
---
Gaussian Processes.ipynb | 3188 +++++++++++++++++++--
Mixture Models.ipynb | 4174 ++++++++++++++++++++++++++--
README.md | 130 +-
Representation Learning.ipynb | 3021 +++++++++++++++++++-
Supervised classification.ipynb | 3302 ++++++++++++++++++++--
Supervised regression.ipynb | 1520 +++++-----
Support Vector Machines.ipynb | 3378 ++++++++++++++++++++--
user_meeting_ml_intro_jan_2022.pdf | Bin 2747288 -> 2748868 bytes
8 files changed, 16950 insertions(+), 1763 deletions(-)
diff --git a/Gaussian Processes.ipynb b/Gaussian Processes.ipynb
index 014f5c5..cfcf974 100644
--- a/Gaussian Processes.ipynb
+++ b/Gaussian Processes.ipynb
@@ -24,18 +24,16 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "--2021-12-01 15:22:49-- https://gml.noaa.gov/webdata/ccgg/trends/co2/co2_weekly_mlo.txt\n",
+ "--2021-12-17 16:04:48-- https://gml.noaa.gov/webdata/ccgg/trends/co2/co2_weekly_mlo.txt\n",
"Resolving gml.noaa.gov (gml.noaa.gov)... 140.172.200.41, 2610:20:8800:6101::29\n",
"Connecting to gml.noaa.gov (gml.noaa.gov)|140.172.200.41|:443... connected.\n",
- "WARNING: cannot verify gml.noaa.gov's certificate, issued by ‘/C=US/O=Let's Encrypt/CN=R3’:\n",
- " Issued certificate has expired.\n",
"HTTP request sent, awaiting response... 200 OK\n",
- "Length: 190941 (186K) [text/plain]\n",
- "Saving to: ‘co2_weekly_mlo.txt.1’\n",
+ "Length: 191093 (187K) [text/plain]\n",
+ "Saving to: ‘co2_weekly_mlo.txt.4’\n",
"\n",
- "100%[======================================>] 190,941 432KB/s in 0.4s \n",
+ "co2_weekly_mlo.txt. 100%[===================>] 186,61K 67,4KB/s in 2,8s \n",
"\n",
- "2021-12-01 15:22:51 (432 KB/s) - ‘co2_weekly_mlo.txt.1’ saved [190941/190941]\n",
+ "2021-12-17 16:04:52 (67,4 KB/s) - ‘co2_weekly_mlo.txt.4’ saved [191093/191093]\n",
"\n"
]
}
@@ -83,7 +81,7 @@
"# \n",
"# Contact: Pieter Tans (303 497 6678; pieter.tans@noaa.gov)\n",
"# \n",
- "# File Creation: Tue Nov 30 05:00:14 2021\n",
+ "# File Creation: Fri Dec 17 05:00:13 2021\n",
"# \n",
"# RECIPROCITY\n",
"# \n",
@@ -152,20 +150,20 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "Requirement already satisfied: numpy in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (1.19.2)\n",
- "Requirement already satisfied: scikit-learn in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (0.24.2)\n",
- "Requirement already satisfied: pandas in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (1.3.0)\n",
- "Requirement already satisfied: matplotlib in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (3.4.2)\n",
- "Requirement already satisfied: joblib>=0.11 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from scikit-learn) (1.0.1)\n",
- "Requirement already satisfied: scipy>=0.19.1 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from scikit-learn) (1.6.2)\n",
- "Requirement already satisfied: threadpoolctl>=2.0.0 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from scikit-learn) (2.2.0)\n",
- "Requirement already satisfied: python-dateutil>=2.7.3 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from pandas) (2.8.2)\n",
- "Requirement already satisfied: pytz>=2017.3 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from pandas) (2021.1)\n",
- "Requirement already satisfied: six>=1.5 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from python-dateutil>=2.7.3->pandas) (1.16.0)\n",
- "Requirement already satisfied: kiwisolver>=1.0.1 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from matplotlib) (1.3.1)\n",
- "Requirement already satisfied: pillow>=6.2.0 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from matplotlib) (8.3.1)\n",
- "Requirement already satisfied: pyparsing>=2.2.1 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from matplotlib) (2.4.7)\n",
- "Requirement already satisfied: cycler>=0.10 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from matplotlib) (0.10.0)\n"
+ "Requirement already satisfied: numpy in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (1.19.2)\n",
+ "Requirement already satisfied: scikit-learn in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (0.24.2)\n",
+ "Requirement already satisfied: pandas in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (1.1.5)\n",
+ "Requirement already satisfied: matplotlib in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (3.3.4)\n",
+ "Requirement already satisfied: threadpoolctl>=2.0.0 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from scikit-learn) (2.2.0)\n",
+ "Requirement already satisfied: joblib>=0.11 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from scikit-learn) (1.0.1)\n",
+ "Requirement already satisfied: scipy>=0.19.1 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from scikit-learn) (1.5.2)\n",
+ "Requirement already satisfied: python-dateutil>=2.7.3 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from pandas) (2.8.2)\n",
+ "Requirement already satisfied: pytz>=2017.2 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from pandas) (2021.3)\n",
+ "Requirement already satisfied: pillow>=6.2.0 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from matplotlib) (8.3.1)\n",
+ "Requirement already satisfied: cycler>=0.10 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from matplotlib) (0.11.0)\n",
+ "Requirement already satisfied: kiwisolver>=1.0.1 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from matplotlib) (1.3.1)\n",
+ "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.3 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from matplotlib) (3.0.4)\n",
+ "Requirement already satisfied: six>=1.5 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from python-dateutil>=2.7.3->pandas) (1.16.0)\n"
]
}
],
@@ -180,13 +178,14 @@
"metadata": {},
"outputs": [],
"source": [
+ "%matplotlib notebook\n",
+ "\n",
"import matplotlib.pyplot as plt\n",
- "%matplotlib inline\n",
"\n",
"import pandas as pd\n",
"import numpy as np\n",
"from sklearn.gaussian_process import GaussianProcessRegressor\n",
- "from sklearn.gaussian_process.kernels import RBF, ExpSineSquared, WhiteKernel"
+ "from sklearn.gaussian_process.kernels import RBF, ExpSineSquared, WhiteKernel, RationalQuadratic"
]
},
{
@@ -337,30 +336,6 @@
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
- " <th>2475</th>\n",
- " <td>2021</td>\n",
- " <td>10</td>\n",
- " <td>24</td>\n",
- " <td>2021.8123</td>\n",
- " <td>413.90</td>\n",
- " <td>6</td>\n",
- " <td>411.63</td>\n",
- " <td>389.48</td>\n",
- " <td>136.92</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2476</th>\n",
- " <td>2021</td>\n",
- " <td>10</td>\n",
- " <td>31</td>\n",
- " <td>2021.8315</td>\n",
- " <td>414.17</td>\n",
- " <td>6</td>\n",
- " <td>411.93</td>\n",
- " <td>389.80</td>\n",
- " <td>136.85</td>\n",
- " </tr>\n",
- " <tr>\n",
" <th>2477</th>\n",
" <td>2021</td>\n",
" <td>11</td>\n",
@@ -370,7 +345,7 @@
" <td>7</td>\n",
" <td>412.97</td>\n",
" <td>390.09</td>\n",
- " <td>137.29</td>\n",
+ " <td>137.30</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2478</th>\n",
@@ -382,7 +357,7 @@
" <td>7</td>\n",
" <td>412.80</td>\n",
" <td>390.71</td>\n",
- " <td>136.84</td>\n",
+ " <td>136.86</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2479</th>\n",
@@ -394,11 +369,35 @@
" <td>7</td>\n",
" <td>413.55</td>\n",
" <td>390.78</td>\n",
- " <td>136.96</td>\n",
+ " <td>136.99</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2480</th>\n",
+ " <td>2021</td>\n",
+ " <td>11</td>\n",
+ " <td>28</td>\n",
+ " <td>2021.9082</td>\n",
+ " <td>416.16</td>\n",
+ " <td>7</td>\n",
+ " <td>414.36</td>\n",
+ " <td>391.33</td>\n",
+ " <td>137.45</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2481</th>\n",
+ " <td>2021</td>\n",
+ " <td>12</td>\n",
+ " <td>5</td>\n",
+ " <td>2021.9274</td>\n",
+ " <td>415.86</td>\n",
+ " <td>5</td>\n",
+ " <td>413.50</td>\n",
+ " <td>391.72</td>\n",
+ " <td>136.84</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
- "<p>2480 rows × 9 columns</p>\n",
+ "<p>2482 rows × 9 columns</p>\n",
"</div>"
],
"text/plain": [
@@ -409,11 +408,11 @@
"3 1974 6 9 1974.4370 332.20 7 -999.99 -999.99 \n",
"4 1974 6 16 1974.4562 332.37 7 -999.99 -999.99 \n",
"... ... ... ... ... ... ... ... ... \n",
- "2475 2021 10 24 2021.8123 413.90 6 411.63 389.48 \n",
- "2476 2021 10 31 2021.8315 414.17 6 411.93 389.80 \n",
"2477 2021 11 7 2021.8507 414.97 7 412.97 390.09 \n",
"2478 2021 11 14 2021.8699 414.88 7 412.80 390.71 \n",
"2479 2021 11 21 2021.8890 415.36 7 413.55 390.78 \n",
+ "2480 2021 11 28 2021.9082 416.16 7 414.36 391.33 \n",
+ "2481 2021 12 5 2021.9274 415.86 5 413.50 391.72 \n",
"\n",
" increase \n",
"0 50.40 \n",
@@ -422,13 +421,13 @@
"3 49.65 \n",
"4 50.06 \n",
"... ... \n",
- "2475 136.92 \n",
- "2476 136.85 \n",
- "2477 137.29 \n",
- "2478 136.84 \n",
- "2479 136.96 \n",
+ "2477 137.30 \n",
+ "2478 136.86 \n",
+ "2479 136.99 \n",
+ "2480 137.45 \n",
+ "2481 136.84 \n",
"\n",
- "[2480 rows x 9 columns]"
+ "[2482 rows x 9 columns]"
]
},
"execution_count": 6,
@@ -456,14 +455,972 @@
"outputs": [
{
"data": {
- "image/png": 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\n",
+ "application/javascript": [
+ "/* Put everything inside the global mpl namespace */\n",
+ "/* global mpl */\n",
+ "window.mpl = {};\n",
+ "\n",
+ "mpl.get_websocket_type = function () {\n",
+ " if (typeof WebSocket !== 'undefined') {\n",
+ " return WebSocket;\n",
+ " } else if (typeof MozWebSocket !== 'undefined') {\n",
+ " return MozWebSocket;\n",
+ " } else {\n",
+ " alert(\n",
+ " 'Your browser does not have WebSocket support. ' +\n",
+ " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+ " 'Firefox 4 and 5 are also supported but you ' +\n",
+ " 'have to enable WebSockets in about:config.'\n",
+ " );\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
+ " this.id = figure_id;\n",
+ "\n",
+ " this.ws = websocket;\n",
+ "\n",
+ " this.supports_binary = this.ws.binaryType !== undefined;\n",
+ "\n",
+ " if (!this.supports_binary) {\n",
+ " var warnings = document.getElementById('mpl-warnings');\n",
+ " if (warnings) {\n",
+ " warnings.style.display = 'block';\n",
+ " warnings.textContent =\n",
+ " 'This browser does not support binary websocket messages. ' +\n",
+ " 'Performance may be slow.';\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.imageObj = new Image();\n",
+ "\n",
+ " this.context = undefined;\n",
+ " this.message = undefined;\n",
+ " this.canvas = undefined;\n",
+ " this.rubberband_canvas = undefined;\n",
+ " this.rubberband_context = undefined;\n",
+ " this.format_dropdown = undefined;\n",
+ "\n",
+ " this.image_mode = 'full';\n",
+ "\n",
+ " this.root = document.createElement('div');\n",
+ " this.root.setAttribute('style', 'display: inline-block');\n",
+ " this._root_extra_style(this.root);\n",
+ "\n",
+ " parent_element.appendChild(this.root);\n",
+ "\n",
+ " this._init_header(this);\n",
+ " this._init_canvas(this);\n",
+ " this._init_toolbar(this);\n",
+ "\n",
+ " var fig = this;\n",
+ "\n",
+ " this.waiting = false;\n",
+ "\n",
+ " this.ws.onopen = function () {\n",
+ " fig.send_message('supports_binary', { value: fig.supports_binary });\n",
+ " fig.send_message('send_image_mode', {});\n",
+ " if (fig.ratio !== 1) {\n",
+ " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
+ " }\n",
+ " fig.send_message('refresh', {});\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onload = function () {\n",
+ " if (fig.image_mode === 'full') {\n",
+ " // Full images could contain transparency (where diff images\n",
+ " // almost always do), so we need to clear the canvas so that\n",
+ " // there is no ghosting.\n",
+ " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+ " }\n",
+ " fig.context.drawImage(fig.imageObj, 0, 0);\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onunload = function () {\n",
+ " fig.ws.close();\n",
+ " };\n",
+ "\n",
+ " this.ws.onmessage = this._make_on_message_function(this);\n",
+ "\n",
+ " this.ondownload = ondownload;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_header = function () {\n",
+ " var titlebar = document.createElement('div');\n",
+ " titlebar.classList =\n",
+ " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
+ " var titletext = document.createElement('div');\n",
+ " titletext.classList = 'ui-dialog-title';\n",
+ " titletext.setAttribute(\n",
+ " 'style',\n",
+ " 'width: 100%; text-align: center; padding: 3px;'\n",
+ " );\n",
+ " titlebar.appendChild(titletext);\n",
+ " this.root.appendChild(titlebar);\n",
+ " this.header = titletext;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
+ "\n",
+ "mpl.figure.prototype._init_canvas = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var canvas_div = (this.canvas_div = document.createElement('div'));\n",
+ " canvas_div.setAttribute(\n",
+ " 'style',\n",
+ " 'border: 1px solid #ddd;' +\n",
+ " 'box-sizing: content-box;' +\n",
+ " 'clear: both;' +\n",
+ " 'min-height: 1px;' +\n",
+ " 'min-width: 1px;' +\n",
+ " 'outline: 0;' +\n",
+ " 'overflow: hidden;' +\n",
+ " 'position: relative;' +\n",
+ " 'resize: both;'\n",
+ " );\n",
+ "\n",
+ " function on_keyboard_event_closure(name) {\n",
+ " return function (event) {\n",
+ " return fig.key_event(event, name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " canvas_div.addEventListener(\n",
+ " 'keydown',\n",
+ " on_keyboard_event_closure('key_press')\n",
+ " );\n",
+ " canvas_div.addEventListener(\n",
+ " 'keyup',\n",
+ " on_keyboard_event_closure('key_release')\n",
+ " );\n",
+ "\n",
+ " this._canvas_extra_style(canvas_div);\n",
+ " this.root.appendChild(canvas_div);\n",
+ "\n",
+ " var canvas = (this.canvas = document.createElement('canvas'));\n",
+ " canvas.classList.add('mpl-canvas');\n",
+ " canvas.setAttribute('style', 'box-sizing: content-box;');\n",
+ "\n",
+ " this.context = canvas.getContext('2d');\n",
+ "\n",
+ " var backingStore =\n",
+ " this.context.backingStorePixelRatio ||\n",
+ " this.context.webkitBackingStorePixelRatio ||\n",
+ " this.context.mozBackingStorePixelRatio ||\n",
+ " this.context.msBackingStorePixelRatio ||\n",
+ " this.context.oBackingStorePixelRatio ||\n",
+ " this.context.backingStorePixelRatio ||\n",
+ " 1;\n",
+ "\n",
+ " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+ "\n",
+ " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
+ " 'canvas'\n",
+ " ));\n",
+ " rubberband_canvas.setAttribute(\n",
+ " 'style',\n",
+ " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
+ " );\n",
+ "\n",
+ " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
+ " if (this.ResizeObserver === undefined) {\n",
+ " if (window.ResizeObserver !== undefined) {\n",
+ " this.ResizeObserver = window.ResizeObserver;\n",
+ " } else {\n",
+ " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
+ " this.ResizeObserver = obs.ResizeObserver;\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
+ " var nentries = entries.length;\n",
+ " for (var i = 0; i < nentries; i++) {\n",
+ " var entry = entries[i];\n",
+ " var width, height;\n",
+ " if (entry.contentBoxSize) {\n",
+ " if (entry.contentBoxSize instanceof Array) {\n",
+ " // Chrome 84 implements new version of spec.\n",
+ " width = entry.contentBoxSize[0].inlineSize;\n",
+ " height = entry.contentBoxSize[0].blockSize;\n",
+ " } else {\n",
+ " // Firefox implements old version of spec.\n",
+ " width = entry.contentBoxSize.inlineSize;\n",
+ " height = entry.contentBoxSize.blockSize;\n",
+ " }\n",
+ " } else {\n",
+ " // Chrome <84 implements even older version of spec.\n",
+ " width = entry.contentRect.width;\n",
+ " height = entry.contentRect.height;\n",
+ " }\n",
+ "\n",
+ " // Keep the size of the canvas and rubber band canvas in sync with\n",
+ " // the canvas container.\n",
+ " if (entry.devicePixelContentBoxSize) {\n",
+ " // Chrome 84 implements new version of spec.\n",
+ " canvas.setAttribute(\n",
+ " 'width',\n",
+ " entry.devicePixelContentBoxSize[0].inlineSize\n",
+ " );\n",
+ " canvas.setAttribute(\n",
+ " 'height',\n",
+ " entry.devicePixelContentBoxSize[0].blockSize\n",
+ " );\n",
+ " } else {\n",
+ " canvas.setAttribute('width', width * fig.ratio);\n",
+ " canvas.setAttribute('height', height * fig.ratio);\n",
+ " }\n",
+ " canvas.setAttribute(\n",
+ " 'style',\n",
+ " 'width: ' + width + 'px; height: ' + height + 'px;'\n",
+ " );\n",
+ "\n",
+ " rubberband_canvas.setAttribute('width', width);\n",
+ " rubberband_canvas.setAttribute('height', height);\n",
+ "\n",
+ " // And update the size in Python. We ignore the initial 0/0 size\n",
+ " // that occurs as the element is placed into the DOM, which should\n",
+ " // otherwise not happen due to the minimum size styling.\n",
+ " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
+ " fig.request_resize(width, height);\n",
+ " }\n",
+ " }\n",
+ " });\n",
+ " this.resizeObserverInstance.observe(canvas_div);\n",
+ "\n",
+ " function on_mouse_event_closure(name) {\n",
+ " return function (event) {\n",
+ " return fig.mouse_event(event, name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mousedown',\n",
+ " on_mouse_event_closure('button_press')\n",
+ " );\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseup',\n",
+ " on_mouse_event_closure('button_release')\n",
+ " );\n",
+ " // Throttle sequential mouse events to 1 every 20ms.\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mousemove',\n",
+ " on_mouse_event_closure('motion_notify')\n",
+ " );\n",
+ "\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseenter',\n",
+ " on_mouse_event_closure('figure_enter')\n",
+ " );\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseleave',\n",
+ " on_mouse_event_closure('figure_leave')\n",
+ " );\n",
+ "\n",
+ " canvas_div.addEventListener('wheel', function (event) {\n",
+ " if (event.deltaY < 0) {\n",
+ " event.step = 1;\n",
+ " } else {\n",
+ " event.step = -1;\n",
+ " }\n",
+ " on_mouse_event_closure('scroll')(event);\n",
+ " });\n",
+ "\n",
+ " canvas_div.appendChild(canvas);\n",
+ " canvas_div.appendChild(rubberband_canvas);\n",
+ "\n",
+ " this.rubberband_context = rubberband_canvas.getContext('2d');\n",
+ " this.rubberband_context.strokeStyle = '#000000';\n",
+ "\n",
+ " this._resize_canvas = function (width, height, forward) {\n",
+ " if (forward) {\n",
+ " canvas_div.style.width = width + 'px';\n",
+ " canvas_div.style.height = height + 'px';\n",
+ " }\n",
+ " };\n",
+ "\n",
+ " // Disable right mouse context menu.\n",
+ " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ " });\n",
+ "\n",
+ " function set_focus() {\n",
+ " canvas.focus();\n",
+ " canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " window.setTimeout(set_focus, 100);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var toolbar = document.createElement('div');\n",
+ " toolbar.classList = 'mpl-toolbar';\n",
+ " this.root.appendChild(toolbar);\n",
+ "\n",
+ " function on_click_closure(name) {\n",
+ " return function (_event) {\n",
+ " return fig.toolbar_button_onclick(name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " function on_mouseover_closure(tooltip) {\n",
+ " return function (event) {\n",
+ " if (!event.currentTarget.disabled) {\n",
+ " return fig.toolbar_button_onmouseover(tooltip);\n",
+ " }\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " fig.buttons = {};\n",
+ " var buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'mpl-button-group';\n",
+ " for (var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " /* Instead of a spacer, we start a new button group. */\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ " buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'mpl-button-group';\n",
+ " continue;\n",
+ " }\n",
+ "\n",
+ " var button = (fig.buttons[name] = document.createElement('button'));\n",
+ " button.classList = 'mpl-widget';\n",
+ " button.setAttribute('role', 'button');\n",
+ " button.setAttribute('aria-disabled', 'false');\n",
+ " button.addEventListener('click', on_click_closure(method_name));\n",
+ " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+ "\n",
+ " var icon_img = document.createElement('img');\n",
+ " icon_img.src = '_images/' + image + '.png';\n",
+ " icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
+ " icon_img.alt = tooltip;\n",
+ " button.appendChild(icon_img);\n",
+ "\n",
+ " buttonGroup.appendChild(button);\n",
+ " }\n",
+ "\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ "\n",
+ " var fmt_picker = document.createElement('select');\n",
+ " fmt_picker.classList = 'mpl-widget';\n",
+ " toolbar.appendChild(fmt_picker);\n",
+ " this.format_dropdown = fmt_picker;\n",
+ "\n",
+ " for (var ind in mpl.extensions) {\n",
+ " var fmt = mpl.extensions[ind];\n",
+ " var option = document.createElement('option');\n",
+ " option.selected = fmt === mpl.default_extension;\n",
+ " option.innerHTML = fmt;\n",
+ " fmt_picker.appendChild(option);\n",
+ " }\n",
+ "\n",
+ " var status_bar = document.createElement('span');\n",
+ " status_bar.classList = 'mpl-message';\n",
+ " toolbar.appendChild(status_bar);\n",
+ " this.message = status_bar;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
+ " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+ " // which will in turn request a refresh of the image.\n",
+ " this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.send_message = function (type, properties) {\n",
+ " properties['type'] = type;\n",
+ " properties['figure_id'] = this.id;\n",
+ " this.ws.send(JSON.stringify(properties));\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.send_draw_message = function () {\n",
+ " if (!this.waiting) {\n",
+ " this.waiting = true;\n",
+ " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+ " var format_dropdown = fig.format_dropdown;\n",
+ " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+ " fig.ondownload(fig, format);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
+ " var size = msg['size'];\n",
+ " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
+ " fig._resize_canvas(size[0], size[1], msg['forward']);\n",
+ " fig.send_message('refresh', {});\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
+ " var x0 = msg['x0'] / fig.ratio;\n",
+ " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
+ " var x1 = msg['x1'] / fig.ratio;\n",
+ " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
+ " x0 = Math.floor(x0) + 0.5;\n",
+ " y0 = Math.floor(y0) + 0.5;\n",
+ " x1 = Math.floor(x1) + 0.5;\n",
+ " y1 = Math.floor(y1) + 0.5;\n",
+ " var min_x = Math.min(x0, x1);\n",
+ " var min_y = Math.min(y0, y1);\n",
+ " var width = Math.abs(x1 - x0);\n",
+ " var height = Math.abs(y1 - y0);\n",
+ "\n",
+ " fig.rubberband_context.clearRect(\n",
+ " 0,\n",
+ " 0,\n",
+ " fig.canvas.width / fig.ratio,\n",
+ " fig.canvas.height / fig.ratio\n",
+ " );\n",
+ "\n",
+ " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
+ " // Updates the figure title.\n",
+ " fig.header.textContent = msg['label'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
+ " var cursor = msg['cursor'];\n",
+ " switch (cursor) {\n",
+ " case 0:\n",
+ " cursor = 'pointer';\n",
+ " break;\n",
+ " case 1:\n",
+ " cursor = 'default';\n",
+ " break;\n",
+ " case 2:\n",
+ " cursor = 'crosshair';\n",
+ " break;\n",
+ " case 3:\n",
+ " cursor = 'move';\n",
+ " break;\n",
+ " }\n",
+ " fig.rubberband_canvas.style.cursor = cursor;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
+ " fig.message.textContent = msg['message'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
+ " // Request the server to send over a new figure.\n",
+ " fig.send_draw_message();\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
+ " fig.image_mode = msg['mode'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
+ " for (var key in msg) {\n",
+ " if (!(key in fig.buttons)) {\n",
+ " continue;\n",
+ " }\n",
+ " fig.buttons[key].disabled = !msg[key];\n",
+ " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
+ " if (msg['mode'] === 'PAN') {\n",
+ " fig.buttons['Pan'].classList.add('active');\n",
+ " fig.buttons['Zoom'].classList.remove('active');\n",
+ " } else if (msg['mode'] === 'ZOOM') {\n",
+ " fig.buttons['Pan'].classList.remove('active');\n",
+ " fig.buttons['Zoom'].classList.add('active');\n",
+ " } else {\n",
+ " fig.buttons['Pan'].classList.remove('active');\n",
+ " fig.buttons['Zoom'].classList.remove('active');\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function () {\n",
+ " // Called whenever the canvas gets updated.\n",
+ " this.send_message('ack', {});\n",
+ "};\n",
+ "\n",
+ "// A function to construct a web socket function for onmessage handling.\n",
+ "// Called in the figure constructor.\n",
+ "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
+ " return function socket_on_message(evt) {\n",
+ " if (evt.data instanceof Blob) {\n",
+ " /* FIXME: We get \"Resource interpreted as Image but\n",
+ " * transferred with MIME type text/plain:\" errors on\n",
+ " * Chrome. But how to set the MIME type? It doesn't seem\n",
+ " * to be part of the websocket stream */\n",
+ " evt.data.type = 'image/png';\n",
+ "\n",
+ " /* Free the memory for the previous frames */\n",
+ " if (fig.imageObj.src) {\n",
+ " (window.URL || window.webkitURL).revokeObjectURL(\n",
+ " fig.imageObj.src\n",
+ " );\n",
+ " }\n",
+ "\n",
+ " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+ " evt.data\n",
+ " );\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " } else if (\n",
+ " typeof evt.data === 'string' &&\n",
+ " evt.data.slice(0, 21) === 'data:image/png;base64'\n",
+ " ) {\n",
+ " fig.imageObj.src = evt.data;\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " var msg = JSON.parse(evt.data);\n",
+ " var msg_type = msg['type'];\n",
+ "\n",
+ " // Call the \"handle_{type}\" callback, which takes\n",
+ " // the figure and JSON message as its only arguments.\n",
+ " try {\n",
+ " var callback = fig['handle_' + msg_type];\n",
+ " } catch (e) {\n",
+ " console.log(\n",
+ " \"No handler for the '\" + msg_type + \"' message type: \",\n",
+ " msg\n",
+ " );\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " if (callback) {\n",
+ " try {\n",
+ " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+ " callback(fig, msg);\n",
+ " } catch (e) {\n",
+ " console.log(\n",
+ " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
+ " e,\n",
+ " e.stack,\n",
+ " msg\n",
+ " );\n",
+ " }\n",
+ " }\n",
+ " };\n",
+ "};\n",
+ "\n",
+ "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+ "mpl.findpos = function (e) {\n",
+ " //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+ " var targ;\n",
+ " if (!e) {\n",
+ " e = window.event;\n",
+ " }\n",
+ " if (e.target) {\n",
+ " targ = e.target;\n",
+ " } else if (e.srcElement) {\n",
+ " targ = e.srcElement;\n",
+ " }\n",
+ " if (targ.nodeType === 3) {\n",
+ " // defeat Safari bug\n",
+ " targ = targ.parentNode;\n",
+ " }\n",
+ "\n",
+ " // pageX,Y are the mouse positions relative to the document\n",
+ " var boundingRect = targ.getBoundingClientRect();\n",
+ " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
+ " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
+ "\n",
+ " return { x: x, y: y };\n",
+ "};\n",
+ "\n",
+ "/*\n",
+ " * return a copy of an object with only non-object keys\n",
+ " * we need this to avoid circular references\n",
+ " * http://stackoverflow.com/a/24161582/3208463\n",
+ " */\n",
+ "function simpleKeys(original) {\n",
+ " return Object.keys(original).reduce(function (obj, key) {\n",
+ " if (typeof original[key] !== 'object') {\n",
+ " obj[key] = original[key];\n",
+ " }\n",
+ " return obj;\n",
+ " }, {});\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.mouse_event = function (event, name) {\n",
+ " var canvas_pos = mpl.findpos(event);\n",
+ "\n",
+ " if (name === 'button_press') {\n",
+ " this.canvas.focus();\n",
+ " this.canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " var x = canvas_pos.x * this.ratio;\n",
+ " var y = canvas_pos.y * this.ratio;\n",
+ "\n",
+ " this.send_message(name, {\n",
+ " x: x,\n",
+ " y: y,\n",
+ " button: event.button,\n",
+ " step: event.step,\n",
+ " guiEvent: simpleKeys(event),\n",
+ " });\n",
+ "\n",
+ " /* This prevents the web browser from automatically changing to\n",
+ " * the text insertion cursor when the button is pressed. We want\n",
+ " * to control all of the cursor setting manually through the\n",
+ " * 'cursor' event from matplotlib */\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
+ " // Handle any extra behaviour associated with a key event\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.key_event = function (event, name) {\n",
+ " // Prevent repeat events\n",
+ " if (name === 'key_press') {\n",
+ " if (event.which === this._key) {\n",
+ " return;\n",
+ " } else {\n",
+ " this._key = event.which;\n",
+ " }\n",
+ " }\n",
+ " if (name === 'key_release') {\n",
+ " this._key = null;\n",
+ " }\n",
+ "\n",
+ " var value = '';\n",
+ " if (event.ctrlKey && event.which !== 17) {\n",
+ " value += 'ctrl+';\n",
+ " }\n",
+ " if (event.altKey && event.which !== 18) {\n",
+ " value += 'alt+';\n",
+ " }\n",
+ " if (event.shiftKey && event.which !== 16) {\n",
+ " value += 'shift+';\n",
+ " }\n",
+ "\n",
+ " value += 'k';\n",
+ " value += event.which.toString();\n",
+ "\n",
+ " this._key_event_extra(event, name);\n",
+ "\n",
+ " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
+ " return false;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
+ " if (name === 'download') {\n",
+ " this.handle_save(this, null);\n",
+ " } else {\n",
+ " this.send_message('toolbar_button', { name: name });\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
+ " this.message.textContent = tooltip;\n",
+ "};\n",
+ "\n",
+ "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
+ "// prettier-ignore\n",
+ "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
+ "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+ "\n",
+ "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
+ "\n",
+ "mpl.default_extension = \"png\";/* global mpl */\n",
+ "\n",
+ "var comm_websocket_adapter = function (comm) {\n",
+ " // Create a \"websocket\"-like object which calls the given IPython comm\n",
+ " // object with the appropriate methods. Currently this is a non binary\n",
+ " // socket, so there is still some room for performance tuning.\n",
+ " var ws = {};\n",
+ "\n",
+ " ws.close = function () {\n",
+ " comm.close();\n",
+ " };\n",
+ " ws.send = function (m) {\n",
+ " //console.log('sending', m);\n",
+ " comm.send(m);\n",
+ " };\n",
+ " // Register the callback with on_msg.\n",
+ " comm.on_msg(function (msg) {\n",
+ " //console.log('receiving', msg['content']['data'], msg);\n",
+ " // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
+ " ws.onmessage(msg['content']['data']);\n",
+ " });\n",
+ " return ws;\n",
+ "};\n",
+ "\n",
+ "mpl.mpl_figure_comm = function (comm, msg) {\n",
+ " // This is the function which gets called when the mpl process\n",
+ " // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+ "\n",
+ " var id = msg.content.data.id;\n",
+ " // Get hold of the div created by the display call when the Comm\n",
+ " // socket was opened in Python.\n",
+ " var element = document.getElementById(id);\n",
+ " var ws_proxy = comm_websocket_adapter(comm);\n",
+ "\n",
+ " function ondownload(figure, _format) {\n",
+ " window.open(figure.canvas.toDataURL());\n",
+ " }\n",
+ "\n",
+ " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
+ "\n",
+ " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+ " // web socket which is closed, not our websocket->open comm proxy.\n",
+ " ws_proxy.onopen();\n",
+ "\n",
+ " fig.parent_element = element;\n",
+ " fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+ " if (!fig.cell_info) {\n",
+ " console.error('Failed to find cell for figure', id, fig);\n",
+ " return;\n",
+ " }\n",
+ " fig.cell_info[0].output_area.element.on(\n",
+ " 'cleared',\n",
+ " { fig: fig },\n",
+ " fig._remove_fig_handler\n",
+ " );\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
+ " var width = fig.canvas.width / fig.ratio;\n",
+ " fig.cell_info[0].output_area.element.off(\n",
+ " 'cleared',\n",
+ " fig._remove_fig_handler\n",
+ " );\n",
+ " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
+ "\n",
+ " // Update the output cell to use the data from the current canvas.\n",
+ " fig.push_to_output();\n",
+ " var dataURL = fig.canvas.toDataURL();\n",
+ " // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+ " // the notebook keyboard shortcuts fail.\n",
+ " IPython.keyboard_manager.enable();\n",
+ " fig.parent_element.innerHTML =\n",
+ " '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ " fig.close_ws(fig, msg);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
+ " fig.send_message('closing', msg);\n",
+ " // fig.ws.close()\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
+ " // Turn the data on the canvas into data in the output cell.\n",
+ " var width = this.canvas.width / this.ratio;\n",
+ " var dataURL = this.canvas.toDataURL();\n",
+ " this.cell_info[1]['text/html'] =\n",
+ " '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function () {\n",
+ " // Tell IPython that the notebook contents must change.\n",
+ " IPython.notebook.set_dirty(true);\n",
+ " this.send_message('ack', {});\n",
+ " var fig = this;\n",
+ " // Wait a second, then push the new image to the DOM so\n",
+ " // that it is saved nicely (might be nice to debounce this).\n",
+ " setTimeout(function () {\n",
+ " fig.push_to_output();\n",
+ " }, 1000);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var toolbar = document.createElement('div');\n",
+ " toolbar.classList = 'btn-toolbar';\n",
+ " this.root.appendChild(toolbar);\n",
+ "\n",
+ " function on_click_closure(name) {\n",
+ " return function (_event) {\n",
+ " return fig.toolbar_button_onclick(name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " function on_mouseover_closure(tooltip) {\n",
+ " return function (event) {\n",
+ " if (!event.currentTarget.disabled) {\n",
+ " return fig.toolbar_button_onmouseover(tooltip);\n",
+ " }\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " fig.buttons = {};\n",
+ " var buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'btn-group';\n",
+ " var button;\n",
+ " for (var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " /* Instead of a spacer, we start a new button group. */\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ " buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'btn-group';\n",
+ " continue;\n",
+ " }\n",
+ "\n",
+ " button = fig.buttons[name] = document.createElement('button');\n",
+ " button.classList = 'btn btn-default';\n",
+ " button.href = '#';\n",
+ " button.title = name;\n",
+ " button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
+ " button.addEventListener('click', on_click_closure(method_name));\n",
+ " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+ " buttonGroup.appendChild(button);\n",
+ " }\n",
+ "\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ "\n",
+ " // Add the status bar.\n",
+ " var status_bar = document.createElement('span');\n",
+ " status_bar.classList = 'mpl-message pull-right';\n",
+ " toolbar.appendChild(status_bar);\n",
+ " this.message = status_bar;\n",
+ "\n",
+ " // Add the close button to the window.\n",
+ " var buttongrp = document.createElement('div');\n",
+ " buttongrp.classList = 'btn-group inline pull-right';\n",
+ " button = document.createElement('button');\n",
+ " button.classList = 'btn btn-mini btn-primary';\n",
+ " button.href = '#';\n",
+ " button.title = 'Stop Interaction';\n",
+ " button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
+ " button.addEventListener('click', function (_evt) {\n",
+ " fig.handle_close(fig, {});\n",
+ " });\n",
+ " button.addEventListener(\n",
+ " 'mouseover',\n",
+ " on_mouseover_closure('Stop Interaction')\n",
+ " );\n",
+ " buttongrp.appendChild(button);\n",
+ " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
+ " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
+ " var fig = event.data.fig;\n",
+ " if (event.target !== this) {\n",
+ " // Ignore bubbled events from children.\n",
+ " return;\n",
+ " }\n",
+ " fig.close_ws(fig, {});\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function (el) {\n",
+ " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
+ " // this is important to make the div 'focusable\n",
+ " el.setAttribute('tabindex', 0);\n",
+ " // reach out to IPython and tell the keyboard manager to turn it's self\n",
+ " // off when our div gets focus\n",
+ "\n",
+ " // location in version 3\n",
+ " if (IPython.notebook.keyboard_manager) {\n",
+ " IPython.notebook.keyboard_manager.register_events(el);\n",
+ " } else {\n",
+ " // location in version 2\n",
+ " IPython.keyboard_manager.register_events(el);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
+ " var manager = IPython.notebook.keyboard_manager;\n",
+ " if (!manager) {\n",
+ " manager = IPython.keyboard_manager;\n",
+ " }\n",
+ "\n",
+ " // Check for shift+enter\n",
+ " if (event.shiftKey && event.which === 13) {\n",
+ " this.canvas_div.blur();\n",
+ " // select the cell after this one\n",
+ " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
+ " IPython.notebook.select(index + 1);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+ " fig.ondownload(fig, null);\n",
+ "};\n",
+ "\n",
+ "mpl.find_output_cell = function (html_output) {\n",
+ " // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+ " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+ " // IPython event is triggered only after the cells have been serialised, which for\n",
+ " // our purposes (turning an active figure into a static one), is too late.\n",
+ " var cells = IPython.notebook.get_cells();\n",
+ " var ncells = cells.length;\n",
+ " for (var i = 0; i < ncells; i++) {\n",
+ " var cell = cells[i];\n",
+ " if (cell.cell_type === 'code') {\n",
+ " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
+ " var data = cell.output_area.outputs[j];\n",
+ " if (data.data) {\n",
+ " // IPython >= 3 moved mimebundle to data attribute of output\n",
+ " data = data.data;\n",
+ " }\n",
+ " if (data['text/html'] === html_output) {\n",
+ " return [cell, data, j];\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "// Register the function which deals with the matplotlib target/channel.\n",
+ "// The kernel may be null if the page has been refreshed.\n",
+ "if (IPython.notebook.kernel !== null) {\n",
+ " IPython.notebook.kernel.comm_manager.register_target(\n",
+ " 'matplotlib',\n",
+ " mpl.mpl_figure_comm\n",
+ " );\n",
+ "}\n"
+ ],
"text/plain": [
- "<Figure size 576x576 with 1 Axes>"
+ "<IPython.core.display.Javascript object>"
]
},
- "metadata": {
- "needs_background": "light"
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "text/html": [
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\" width=\"800\">"
+ ],
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ]
},
+ "metadata": {},
"output_type": "display_data"
}
],
@@ -500,73 +1457,1044 @@
"outputs": [
{
"data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 576x576 with 1 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "fig, ax = plt.subplots(figsize=(8, 8))\n",
- "data.plot(x=\"decimal\", y=\"co2\", legend=False, ax=ax)\n",
- "ax.set(xlabel=\"Time [years]\", ylabel=r\"CO$_2$ [ppm]\", title=\"Atmospheric CO$_2$ concentration in Mauna Loa\")\n",
- "plt.show()"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "c62fd7f3",
- "metadata": {},
- "source": [
- "That's better.\n",
- "\n",
- "We can now try to model this behaviour with Gaussian Processes. The key parameter we must choose is the covariance matrix analytic form, which establishes how correlated two points in the time axis are.\n",
- "\n",
- "One simple assumption would be that two values of the CO2 concentration are highly correlated they happened at close by times. We use a Gaussian-based model (named here \"Radial Basis Function\", as this does not refer to a probability distribution) to establish that if two points are one year apart they are likely to be highly correlated. \n",
- "\n",
- "We also assume the data within an year from each other is highly correlated and should show a periodicity of 1 year."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 10,
- "id": "a31d7eca",
- "metadata": {},
- "outputs": [],
- "source": [
- "# Kernel with parameters given in GPML book\n",
- "\n",
- "# these hyper parameters are optimised in the GP fit\n",
- "# we provide here only a starting value\n",
- "\n",
- "# long term smooth rising trend\n",
- "k1 = 66.0**2 * RBF(length_scale=67.0)\n",
- "\n",
- "# seasonal component\n",
- "k2 = (2.4**2 * RBF(length_scale=90.0) * ExpSineSquared(length_scale=1.3, periodicity=1.0))\n",
- "\n",
- "# add some white noise\n",
- "kn = WhiteKernel(noise_level=0.19**2)\n",
- "\n",
- "kernel = k1 + k2 + kn"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "0ad8ddf0",
- "metadata": {},
- "source": [
- "The kernel hyper-parameters are:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 12,
+ "application/javascript": [
+ "/* Put everything inside the global mpl namespace */\n",
+ "/* global mpl */\n",
+ "window.mpl = {};\n",
+ "\n",
+ "mpl.get_websocket_type = function () {\n",
+ " if (typeof WebSocket !== 'undefined') {\n",
+ " return WebSocket;\n",
+ " } else if (typeof MozWebSocket !== 'undefined') {\n",
+ " return MozWebSocket;\n",
+ " } else {\n",
+ " alert(\n",
+ " 'Your browser does not have WebSocket support. ' +\n",
+ " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+ " 'Firefox 4 and 5 are also supported but you ' +\n",
+ " 'have to enable WebSockets in about:config.'\n",
+ " );\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
+ " this.id = figure_id;\n",
+ "\n",
+ " this.ws = websocket;\n",
+ "\n",
+ " this.supports_binary = this.ws.binaryType !== undefined;\n",
+ "\n",
+ " if (!this.supports_binary) {\n",
+ " var warnings = document.getElementById('mpl-warnings');\n",
+ " if (warnings) {\n",
+ " warnings.style.display = 'block';\n",
+ " warnings.textContent =\n",
+ " 'This browser does not support binary websocket messages. ' +\n",
+ " 'Performance may be slow.';\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.imageObj = new Image();\n",
+ "\n",
+ " this.context = undefined;\n",
+ " this.message = undefined;\n",
+ " this.canvas = undefined;\n",
+ " this.rubberband_canvas = undefined;\n",
+ " this.rubberband_context = undefined;\n",
+ " this.format_dropdown = undefined;\n",
+ "\n",
+ " this.image_mode = 'full';\n",
+ "\n",
+ " this.root = document.createElement('div');\n",
+ " this.root.setAttribute('style', 'display: inline-block');\n",
+ " this._root_extra_style(this.root);\n",
+ "\n",
+ " parent_element.appendChild(this.root);\n",
+ "\n",
+ " this._init_header(this);\n",
+ " this._init_canvas(this);\n",
+ " this._init_toolbar(this);\n",
+ "\n",
+ " var fig = this;\n",
+ "\n",
+ " this.waiting = false;\n",
+ "\n",
+ " this.ws.onopen = function () {\n",
+ " fig.send_message('supports_binary', { value: fig.supports_binary });\n",
+ " fig.send_message('send_image_mode', {});\n",
+ " if (fig.ratio !== 1) {\n",
+ " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
+ " }\n",
+ " fig.send_message('refresh', {});\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onload = function () {\n",
+ " if (fig.image_mode === 'full') {\n",
+ " // Full images could contain transparency (where diff images\n",
+ " // almost always do), so we need to clear the canvas so that\n",
+ " // there is no ghosting.\n",
+ " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+ " }\n",
+ " fig.context.drawImage(fig.imageObj, 0, 0);\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onunload = function () {\n",
+ " fig.ws.close();\n",
+ " };\n",
+ "\n",
+ " this.ws.onmessage = this._make_on_message_function(this);\n",
+ "\n",
+ " this.ondownload = ondownload;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_header = function () {\n",
+ " var titlebar = document.createElement('div');\n",
+ " titlebar.classList =\n",
+ " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
+ " var titletext = document.createElement('div');\n",
+ " titletext.classList = 'ui-dialog-title';\n",
+ " titletext.setAttribute(\n",
+ " 'style',\n",
+ " 'width: 100%; text-align: center; padding: 3px;'\n",
+ " );\n",
+ " titlebar.appendChild(titletext);\n",
+ " this.root.appendChild(titlebar);\n",
+ " this.header = titletext;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
+ "\n",
+ "mpl.figure.prototype._init_canvas = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var canvas_div = (this.canvas_div = document.createElement('div'));\n",
+ " canvas_div.setAttribute(\n",
+ " 'style',\n",
+ " 'border: 1px solid #ddd;' +\n",
+ " 'box-sizing: content-box;' +\n",
+ " 'clear: both;' +\n",
+ " 'min-height: 1px;' +\n",
+ " 'min-width: 1px;' +\n",
+ " 'outline: 0;' +\n",
+ " 'overflow: hidden;' +\n",
+ " 'position: relative;' +\n",
+ " 'resize: both;'\n",
+ " );\n",
+ "\n",
+ " function on_keyboard_event_closure(name) {\n",
+ " return function (event) {\n",
+ " return fig.key_event(event, name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " canvas_div.addEventListener(\n",
+ " 'keydown',\n",
+ " on_keyboard_event_closure('key_press')\n",
+ " );\n",
+ " canvas_div.addEventListener(\n",
+ " 'keyup',\n",
+ " on_keyboard_event_closure('key_release')\n",
+ " );\n",
+ "\n",
+ " this._canvas_extra_style(canvas_div);\n",
+ " this.root.appendChild(canvas_div);\n",
+ "\n",
+ " var canvas = (this.canvas = document.createElement('canvas'));\n",
+ " canvas.classList.add('mpl-canvas');\n",
+ " canvas.setAttribute('style', 'box-sizing: content-box;');\n",
+ "\n",
+ " this.context = canvas.getContext('2d');\n",
+ "\n",
+ " var backingStore =\n",
+ " this.context.backingStorePixelRatio ||\n",
+ " this.context.webkitBackingStorePixelRatio ||\n",
+ " this.context.mozBackingStorePixelRatio ||\n",
+ " this.context.msBackingStorePixelRatio ||\n",
+ " this.context.oBackingStorePixelRatio ||\n",
+ " this.context.backingStorePixelRatio ||\n",
+ " 1;\n",
+ "\n",
+ " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+ "\n",
+ " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
+ " 'canvas'\n",
+ " ));\n",
+ " rubberband_canvas.setAttribute(\n",
+ " 'style',\n",
+ " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
+ " );\n",
+ "\n",
+ " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
+ " if (this.ResizeObserver === undefined) {\n",
+ " if (window.ResizeObserver !== undefined) {\n",
+ " this.ResizeObserver = window.ResizeObserver;\n",
+ " } else {\n",
+ " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
+ " this.ResizeObserver = obs.ResizeObserver;\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
+ " var nentries = entries.length;\n",
+ " for (var i = 0; i < nentries; i++) {\n",
+ " var entry = entries[i];\n",
+ " var width, height;\n",
+ " if (entry.contentBoxSize) {\n",
+ " if (entry.contentBoxSize instanceof Array) {\n",
+ " // Chrome 84 implements new version of spec.\n",
+ " width = entry.contentBoxSize[0].inlineSize;\n",
+ " height = entry.contentBoxSize[0].blockSize;\n",
+ " } else {\n",
+ " // Firefox implements old version of spec.\n",
+ " width = entry.contentBoxSize.inlineSize;\n",
+ " height = entry.contentBoxSize.blockSize;\n",
+ " }\n",
+ " } else {\n",
+ " // Chrome <84 implements even older version of spec.\n",
+ " width = entry.contentRect.width;\n",
+ " height = entry.contentRect.height;\n",
+ " }\n",
+ "\n",
+ " // Keep the size of the canvas and rubber band canvas in sync with\n",
+ " // the canvas container.\n",
+ " if (entry.devicePixelContentBoxSize) {\n",
+ " // Chrome 84 implements new version of spec.\n",
+ " canvas.setAttribute(\n",
+ " 'width',\n",
+ " entry.devicePixelContentBoxSize[0].inlineSize\n",
+ " );\n",
+ " canvas.setAttribute(\n",
+ " 'height',\n",
+ " entry.devicePixelContentBoxSize[0].blockSize\n",
+ " );\n",
+ " } else {\n",
+ " canvas.setAttribute('width', width * fig.ratio);\n",
+ " canvas.setAttribute('height', height * fig.ratio);\n",
+ " }\n",
+ " canvas.setAttribute(\n",
+ " 'style',\n",
+ " 'width: ' + width + 'px; height: ' + height + 'px;'\n",
+ " );\n",
+ "\n",
+ " rubberband_canvas.setAttribute('width', width);\n",
+ " rubberband_canvas.setAttribute('height', height);\n",
+ "\n",
+ " // And update the size in Python. We ignore the initial 0/0 size\n",
+ " // that occurs as the element is placed into the DOM, which should\n",
+ " // otherwise not happen due to the minimum size styling.\n",
+ " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
+ " fig.request_resize(width, height);\n",
+ " }\n",
+ " }\n",
+ " });\n",
+ " this.resizeObserverInstance.observe(canvas_div);\n",
+ "\n",
+ " function on_mouse_event_closure(name) {\n",
+ " return function (event) {\n",
+ " return fig.mouse_event(event, name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mousedown',\n",
+ " on_mouse_event_closure('button_press')\n",
+ " );\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseup',\n",
+ " on_mouse_event_closure('button_release')\n",
+ " );\n",
+ " // Throttle sequential mouse events to 1 every 20ms.\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mousemove',\n",
+ " on_mouse_event_closure('motion_notify')\n",
+ " );\n",
+ "\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseenter',\n",
+ " on_mouse_event_closure('figure_enter')\n",
+ " );\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseleave',\n",
+ " on_mouse_event_closure('figure_leave')\n",
+ " );\n",
+ "\n",
+ " canvas_div.addEventListener('wheel', function (event) {\n",
+ " if (event.deltaY < 0) {\n",
+ " event.step = 1;\n",
+ " } else {\n",
+ " event.step = -1;\n",
+ " }\n",
+ " on_mouse_event_closure('scroll')(event);\n",
+ " });\n",
+ "\n",
+ " canvas_div.appendChild(canvas);\n",
+ " canvas_div.appendChild(rubberband_canvas);\n",
+ "\n",
+ " this.rubberband_context = rubberband_canvas.getContext('2d');\n",
+ " this.rubberband_context.strokeStyle = '#000000';\n",
+ "\n",
+ " this._resize_canvas = function (width, height, forward) {\n",
+ " if (forward) {\n",
+ " canvas_div.style.width = width + 'px';\n",
+ " canvas_div.style.height = height + 'px';\n",
+ " }\n",
+ " };\n",
+ "\n",
+ " // Disable right mouse context menu.\n",
+ " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ " });\n",
+ "\n",
+ " function set_focus() {\n",
+ " canvas.focus();\n",
+ " canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " window.setTimeout(set_focus, 100);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var toolbar = document.createElement('div');\n",
+ " toolbar.classList = 'mpl-toolbar';\n",
+ " this.root.appendChild(toolbar);\n",
+ "\n",
+ " function on_click_closure(name) {\n",
+ " return function (_event) {\n",
+ " return fig.toolbar_button_onclick(name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " function on_mouseover_closure(tooltip) {\n",
+ " return function (event) {\n",
+ " if (!event.currentTarget.disabled) {\n",
+ " return fig.toolbar_button_onmouseover(tooltip);\n",
+ " }\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " fig.buttons = {};\n",
+ " var buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'mpl-button-group';\n",
+ " for (var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " /* Instead of a spacer, we start a new button group. */\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ " buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'mpl-button-group';\n",
+ " continue;\n",
+ " }\n",
+ "\n",
+ " var button = (fig.buttons[name] = document.createElement('button'));\n",
+ " button.classList = 'mpl-widget';\n",
+ " button.setAttribute('role', 'button');\n",
+ " button.setAttribute('aria-disabled', 'false');\n",
+ " button.addEventListener('click', on_click_closure(method_name));\n",
+ " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+ "\n",
+ " var icon_img = document.createElement('img');\n",
+ " icon_img.src = '_images/' + image + '.png';\n",
+ " icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
+ " icon_img.alt = tooltip;\n",
+ " button.appendChild(icon_img);\n",
+ "\n",
+ " buttonGroup.appendChild(button);\n",
+ " }\n",
+ "\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ "\n",
+ " var fmt_picker = document.createElement('select');\n",
+ " fmt_picker.classList = 'mpl-widget';\n",
+ " toolbar.appendChild(fmt_picker);\n",
+ " this.format_dropdown = fmt_picker;\n",
+ "\n",
+ " for (var ind in mpl.extensions) {\n",
+ " var fmt = mpl.extensions[ind];\n",
+ " var option = document.createElement('option');\n",
+ " option.selected = fmt === mpl.default_extension;\n",
+ " option.innerHTML = fmt;\n",
+ " fmt_picker.appendChild(option);\n",
+ " }\n",
+ "\n",
+ " var status_bar = document.createElement('span');\n",
+ " status_bar.classList = 'mpl-message';\n",
+ " toolbar.appendChild(status_bar);\n",
+ " this.message = status_bar;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
+ " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+ " // which will in turn request a refresh of the image.\n",
+ " this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.send_message = function (type, properties) {\n",
+ " properties['type'] = type;\n",
+ " properties['figure_id'] = this.id;\n",
+ " this.ws.send(JSON.stringify(properties));\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.send_draw_message = function () {\n",
+ " if (!this.waiting) {\n",
+ " this.waiting = true;\n",
+ " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+ " var format_dropdown = fig.format_dropdown;\n",
+ " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+ " fig.ondownload(fig, format);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
+ " var size = msg['size'];\n",
+ " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
+ " fig._resize_canvas(size[0], size[1], msg['forward']);\n",
+ " fig.send_message('refresh', {});\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
+ " var x0 = msg['x0'] / fig.ratio;\n",
+ " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
+ " var x1 = msg['x1'] / fig.ratio;\n",
+ " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
+ " x0 = Math.floor(x0) + 0.5;\n",
+ " y0 = Math.floor(y0) + 0.5;\n",
+ " x1 = Math.floor(x1) + 0.5;\n",
+ " y1 = Math.floor(y1) + 0.5;\n",
+ " var min_x = Math.min(x0, x1);\n",
+ " var min_y = Math.min(y0, y1);\n",
+ " var width = Math.abs(x1 - x0);\n",
+ " var height = Math.abs(y1 - y0);\n",
+ "\n",
+ " fig.rubberband_context.clearRect(\n",
+ " 0,\n",
+ " 0,\n",
+ " fig.canvas.width / fig.ratio,\n",
+ " fig.canvas.height / fig.ratio\n",
+ " );\n",
+ "\n",
+ " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
+ " // Updates the figure title.\n",
+ " fig.header.textContent = msg['label'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
+ " var cursor = msg['cursor'];\n",
+ " switch (cursor) {\n",
+ " case 0:\n",
+ " cursor = 'pointer';\n",
+ " break;\n",
+ " case 1:\n",
+ " cursor = 'default';\n",
+ " break;\n",
+ " case 2:\n",
+ " cursor = 'crosshair';\n",
+ " break;\n",
+ " case 3:\n",
+ " cursor = 'move';\n",
+ " break;\n",
+ " }\n",
+ " fig.rubberband_canvas.style.cursor = cursor;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
+ " fig.message.textContent = msg['message'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
+ " // Request the server to send over a new figure.\n",
+ " fig.send_draw_message();\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
+ " fig.image_mode = msg['mode'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
+ " for (var key in msg) {\n",
+ " if (!(key in fig.buttons)) {\n",
+ " continue;\n",
+ " }\n",
+ " fig.buttons[key].disabled = !msg[key];\n",
+ " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
+ " if (msg['mode'] === 'PAN') {\n",
+ " fig.buttons['Pan'].classList.add('active');\n",
+ " fig.buttons['Zoom'].classList.remove('active');\n",
+ " } else if (msg['mode'] === 'ZOOM') {\n",
+ " fig.buttons['Pan'].classList.remove('active');\n",
+ " fig.buttons['Zoom'].classList.add('active');\n",
+ " } else {\n",
+ " fig.buttons['Pan'].classList.remove('active');\n",
+ " fig.buttons['Zoom'].classList.remove('active');\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function () {\n",
+ " // Called whenever the canvas gets updated.\n",
+ " this.send_message('ack', {});\n",
+ "};\n",
+ "\n",
+ "// A function to construct a web socket function for onmessage handling.\n",
+ "// Called in the figure constructor.\n",
+ "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
+ " return function socket_on_message(evt) {\n",
+ " if (evt.data instanceof Blob) {\n",
+ " /* FIXME: We get \"Resource interpreted as Image but\n",
+ " * transferred with MIME type text/plain:\" errors on\n",
+ " * Chrome. But how to set the MIME type? It doesn't seem\n",
+ " * to be part of the websocket stream */\n",
+ " evt.data.type = 'image/png';\n",
+ "\n",
+ " /* Free the memory for the previous frames */\n",
+ " if (fig.imageObj.src) {\n",
+ " (window.URL || window.webkitURL).revokeObjectURL(\n",
+ " fig.imageObj.src\n",
+ " );\n",
+ " }\n",
+ "\n",
+ " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+ " evt.data\n",
+ " );\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " } else if (\n",
+ " typeof evt.data === 'string' &&\n",
+ " evt.data.slice(0, 21) === 'data:image/png;base64'\n",
+ " ) {\n",
+ " fig.imageObj.src = evt.data;\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " var msg = JSON.parse(evt.data);\n",
+ " var msg_type = msg['type'];\n",
+ "\n",
+ " // Call the \"handle_{type}\" callback, which takes\n",
+ " // the figure and JSON message as its only arguments.\n",
+ " try {\n",
+ " var callback = fig['handle_' + msg_type];\n",
+ " } catch (e) {\n",
+ " console.log(\n",
+ " \"No handler for the '\" + msg_type + \"' message type: \",\n",
+ " msg\n",
+ " );\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " if (callback) {\n",
+ " try {\n",
+ " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+ " callback(fig, msg);\n",
+ " } catch (e) {\n",
+ " console.log(\n",
+ " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
+ " e,\n",
+ " e.stack,\n",
+ " msg\n",
+ " );\n",
+ " }\n",
+ " }\n",
+ " };\n",
+ "};\n",
+ "\n",
+ "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+ "mpl.findpos = function (e) {\n",
+ " //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+ " var targ;\n",
+ " if (!e) {\n",
+ " e = window.event;\n",
+ " }\n",
+ " if (e.target) {\n",
+ " targ = e.target;\n",
+ " } else if (e.srcElement) {\n",
+ " targ = e.srcElement;\n",
+ " }\n",
+ " if (targ.nodeType === 3) {\n",
+ " // defeat Safari bug\n",
+ " targ = targ.parentNode;\n",
+ " }\n",
+ "\n",
+ " // pageX,Y are the mouse positions relative to the document\n",
+ " var boundingRect = targ.getBoundingClientRect();\n",
+ " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
+ " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
+ "\n",
+ " return { x: x, y: y };\n",
+ "};\n",
+ "\n",
+ "/*\n",
+ " * return a copy of an object with only non-object keys\n",
+ " * we need this to avoid circular references\n",
+ " * http://stackoverflow.com/a/24161582/3208463\n",
+ " */\n",
+ "function simpleKeys(original) {\n",
+ " return Object.keys(original).reduce(function (obj, key) {\n",
+ " if (typeof original[key] !== 'object') {\n",
+ " obj[key] = original[key];\n",
+ " }\n",
+ " return obj;\n",
+ " }, {});\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.mouse_event = function (event, name) {\n",
+ " var canvas_pos = mpl.findpos(event);\n",
+ "\n",
+ " if (name === 'button_press') {\n",
+ " this.canvas.focus();\n",
+ " this.canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " var x = canvas_pos.x * this.ratio;\n",
+ " var y = canvas_pos.y * this.ratio;\n",
+ "\n",
+ " this.send_message(name, {\n",
+ " x: x,\n",
+ " y: y,\n",
+ " button: event.button,\n",
+ " step: event.step,\n",
+ " guiEvent: simpleKeys(event),\n",
+ " });\n",
+ "\n",
+ " /* This prevents the web browser from automatically changing to\n",
+ " * the text insertion cursor when the button is pressed. We want\n",
+ " * to control all of the cursor setting manually through the\n",
+ " * 'cursor' event from matplotlib */\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
+ " // Handle any extra behaviour associated with a key event\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.key_event = function (event, name) {\n",
+ " // Prevent repeat events\n",
+ " if (name === 'key_press') {\n",
+ " if (event.which === this._key) {\n",
+ " return;\n",
+ " } else {\n",
+ " this._key = event.which;\n",
+ " }\n",
+ " }\n",
+ " if (name === 'key_release') {\n",
+ " this._key = null;\n",
+ " }\n",
+ "\n",
+ " var value = '';\n",
+ " if (event.ctrlKey && event.which !== 17) {\n",
+ " value += 'ctrl+';\n",
+ " }\n",
+ " if (event.altKey && event.which !== 18) {\n",
+ " value += 'alt+';\n",
+ " }\n",
+ " if (event.shiftKey && event.which !== 16) {\n",
+ " value += 'shift+';\n",
+ " }\n",
+ "\n",
+ " value += 'k';\n",
+ " value += event.which.toString();\n",
+ "\n",
+ " this._key_event_extra(event, name);\n",
+ "\n",
+ " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
+ " return false;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
+ " if (name === 'download') {\n",
+ " this.handle_save(this, null);\n",
+ " } else {\n",
+ " this.send_message('toolbar_button', { name: name });\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
+ " this.message.textContent = tooltip;\n",
+ "};\n",
+ "\n",
+ "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
+ "// prettier-ignore\n",
+ "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
+ "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+ "\n",
+ "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
+ "\n",
+ "mpl.default_extension = \"png\";/* global mpl */\n",
+ "\n",
+ "var comm_websocket_adapter = function (comm) {\n",
+ " // Create a \"websocket\"-like object which calls the given IPython comm\n",
+ " // object with the appropriate methods. Currently this is a non binary\n",
+ " // socket, so there is still some room for performance tuning.\n",
+ " var ws = {};\n",
+ "\n",
+ " ws.close = function () {\n",
+ " comm.close();\n",
+ " };\n",
+ " ws.send = function (m) {\n",
+ " //console.log('sending', m);\n",
+ " comm.send(m);\n",
+ " };\n",
+ " // Register the callback with on_msg.\n",
+ " comm.on_msg(function (msg) {\n",
+ " //console.log('receiving', msg['content']['data'], msg);\n",
+ " // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
+ " ws.onmessage(msg['content']['data']);\n",
+ " });\n",
+ " return ws;\n",
+ "};\n",
+ "\n",
+ "mpl.mpl_figure_comm = function (comm, msg) {\n",
+ " // This is the function which gets called when the mpl process\n",
+ " // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+ "\n",
+ " var id = msg.content.data.id;\n",
+ " // Get hold of the div created by the display call when the Comm\n",
+ " // socket was opened in Python.\n",
+ " var element = document.getElementById(id);\n",
+ " var ws_proxy = comm_websocket_adapter(comm);\n",
+ "\n",
+ " function ondownload(figure, _format) {\n",
+ " window.open(figure.canvas.toDataURL());\n",
+ " }\n",
+ "\n",
+ " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
+ "\n",
+ " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+ " // web socket which is closed, not our websocket->open comm proxy.\n",
+ " ws_proxy.onopen();\n",
+ "\n",
+ " fig.parent_element = element;\n",
+ " fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+ " if (!fig.cell_info) {\n",
+ " console.error('Failed to find cell for figure', id, fig);\n",
+ " return;\n",
+ " }\n",
+ " fig.cell_info[0].output_area.element.on(\n",
+ " 'cleared',\n",
+ " { fig: fig },\n",
+ " fig._remove_fig_handler\n",
+ " );\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
+ " var width = fig.canvas.width / fig.ratio;\n",
+ " fig.cell_info[0].output_area.element.off(\n",
+ " 'cleared',\n",
+ " fig._remove_fig_handler\n",
+ " );\n",
+ " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
+ "\n",
+ " // Update the output cell to use the data from the current canvas.\n",
+ " fig.push_to_output();\n",
+ " var dataURL = fig.canvas.toDataURL();\n",
+ " // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+ " // the notebook keyboard shortcuts fail.\n",
+ " IPython.keyboard_manager.enable();\n",
+ " fig.parent_element.innerHTML =\n",
+ " '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ " fig.close_ws(fig, msg);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
+ " fig.send_message('closing', msg);\n",
+ " // fig.ws.close()\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
+ " // Turn the data on the canvas into data in the output cell.\n",
+ " var width = this.canvas.width / this.ratio;\n",
+ " var dataURL = this.canvas.toDataURL();\n",
+ " this.cell_info[1]['text/html'] =\n",
+ " '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function () {\n",
+ " // Tell IPython that the notebook contents must change.\n",
+ " IPython.notebook.set_dirty(true);\n",
+ " this.send_message('ack', {});\n",
+ " var fig = this;\n",
+ " // Wait a second, then push the new image to the DOM so\n",
+ " // that it is saved nicely (might be nice to debounce this).\n",
+ " setTimeout(function () {\n",
+ " fig.push_to_output();\n",
+ " }, 1000);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var toolbar = document.createElement('div');\n",
+ " toolbar.classList = 'btn-toolbar';\n",
+ " this.root.appendChild(toolbar);\n",
+ "\n",
+ " function on_click_closure(name) {\n",
+ " return function (_event) {\n",
+ " return fig.toolbar_button_onclick(name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " function on_mouseover_closure(tooltip) {\n",
+ " return function (event) {\n",
+ " if (!event.currentTarget.disabled) {\n",
+ " return fig.toolbar_button_onmouseover(tooltip);\n",
+ " }\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " fig.buttons = {};\n",
+ " var buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'btn-group';\n",
+ " var button;\n",
+ " for (var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " /* Instead of a spacer, we start a new button group. */\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ " buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'btn-group';\n",
+ " continue;\n",
+ " }\n",
+ "\n",
+ " button = fig.buttons[name] = document.createElement('button');\n",
+ " button.classList = 'btn btn-default';\n",
+ " button.href = '#';\n",
+ " button.title = name;\n",
+ " button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
+ " button.addEventListener('click', on_click_closure(method_name));\n",
+ " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+ " buttonGroup.appendChild(button);\n",
+ " }\n",
+ "\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ "\n",
+ " // Add the status bar.\n",
+ " var status_bar = document.createElement('span');\n",
+ " status_bar.classList = 'mpl-message pull-right';\n",
+ " toolbar.appendChild(status_bar);\n",
+ " this.message = status_bar;\n",
+ "\n",
+ " // Add the close button to the window.\n",
+ " var buttongrp = document.createElement('div');\n",
+ " buttongrp.classList = 'btn-group inline pull-right';\n",
+ " button = document.createElement('button');\n",
+ " button.classList = 'btn btn-mini btn-primary';\n",
+ " button.href = '#';\n",
+ " button.title = 'Stop Interaction';\n",
+ " button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
+ " button.addEventListener('click', function (_evt) {\n",
+ " fig.handle_close(fig, {});\n",
+ " });\n",
+ " button.addEventListener(\n",
+ " 'mouseover',\n",
+ " on_mouseover_closure('Stop Interaction')\n",
+ " );\n",
+ " buttongrp.appendChild(button);\n",
+ " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
+ " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
+ " var fig = event.data.fig;\n",
+ " if (event.target !== this) {\n",
+ " // Ignore bubbled events from children.\n",
+ " return;\n",
+ " }\n",
+ " fig.close_ws(fig, {});\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function (el) {\n",
+ " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
+ " // this is important to make the div 'focusable\n",
+ " el.setAttribute('tabindex', 0);\n",
+ " // reach out to IPython and tell the keyboard manager to turn it's self\n",
+ " // off when our div gets focus\n",
+ "\n",
+ " // location in version 3\n",
+ " if (IPython.notebook.keyboard_manager) {\n",
+ " IPython.notebook.keyboard_manager.register_events(el);\n",
+ " } else {\n",
+ " // location in version 2\n",
+ " IPython.keyboard_manager.register_events(el);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
+ " var manager = IPython.notebook.keyboard_manager;\n",
+ " if (!manager) {\n",
+ " manager = IPython.keyboard_manager;\n",
+ " }\n",
+ "\n",
+ " // Check for shift+enter\n",
+ " if (event.shiftKey && event.which === 13) {\n",
+ " this.canvas_div.blur();\n",
+ " // select the cell after this one\n",
+ " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
+ " IPython.notebook.select(index + 1);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+ " fig.ondownload(fig, null);\n",
+ "};\n",
+ "\n",
+ "mpl.find_output_cell = function (html_output) {\n",
+ " // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+ " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+ " // IPython event is triggered only after the cells have been serialised, which for\n",
+ " // our purposes (turning an active figure into a static one), is too late.\n",
+ " var cells = IPython.notebook.get_cells();\n",
+ " var ncells = cells.length;\n",
+ " for (var i = 0; i < ncells; i++) {\n",
+ " var cell = cells[i];\n",
+ " if (cell.cell_type === 'code') {\n",
+ " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
+ " var data = cell.output_area.outputs[j];\n",
+ " if (data.data) {\n",
+ " // IPython >= 3 moved mimebundle to data attribute of output\n",
+ " data = data.data;\n",
+ " }\n",
+ " if (data['text/html'] === html_output) {\n",
+ " return [cell, data, j];\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "// Register the function which deals with the matplotlib target/channel.\n",
+ "// The kernel may be null if the page has been refreshed.\n",
+ "if (IPython.notebook.kernel !== null) {\n",
+ " IPython.notebook.kernel.comm_manager.register_target(\n",
+ " 'matplotlib',\n",
+ " mpl.mpl_figure_comm\n",
+ " );\n",
+ "}\n"
+ ],
+ "text/plain": [
+ "<IPython.core.display.Javascript object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
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\" width=\"800\">"
+ ],
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "fig, ax = plt.subplots(figsize=(8, 8))\n",
+ "data.plot(x=\"decimal\", y=\"co2\", legend=False, ax=ax)\n",
+ "ax.set(xlabel=\"Time [years]\", ylabel=r\"CO$_2$ [ppm]\", title=\"Atmospheric CO$_2$ concentration in Mauna Loa\")\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "c62fd7f3",
+ "metadata": {},
+ "source": [
+ "That's better.\n",
+ "\n",
+ "We can now try to model this behaviour with Gaussian Processes. The key parameter we must choose is the covariance matrix analytic form, which establishes how correlated two points in the time axis are.\n",
+ "\n",
+ "One simple assumption would be that two values of the CO2 concentration are highly correlated they happened at close by times. We use a Gaussian-based model (named here \"Radial Basis Function\", as this does not refer to a probability distribution) to establish that if two points are one year apart they are likely to be highly correlated.\n",
+ "\n",
+ "Additionally, we assume that there is a correlation between points within certain period, since we know that data from the same season in an year is expected to be correlated to data if that same season in the year (ie: CO$_2$ emissions have a rough periodicity of one year due to the season changes).\n",
+ "\n",
+ "Another term of the covariance matrix must be related to the random noise appearing in the data.\n",
+ "\n",
+ "All those assumptions can be motivated by an analysis of the covariance matrix of the data. That is, we can take the covariance matrix of all the data points and analyse it to establish whether our assumptions here are valid or not. A very long and detailed explanation on this point can be found in Bishop (2006), which has a very pedagogical chapter on Gaussian Processes. Online resources can be found on: http://www.gaussianprocess.org/\n",
+ "\n",
+ "Note that all of those are very strong assumptions, but they are made directly on the covariance matrix of the fit function. The actual numbers used below are taken from an example, but they will be optimized in the fit below (unless explicitly asked not to).\n",
+ "\n",
+ "Note: this notebook is a simplified example with extra explanations, with lots of material taken from https://scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpr_co2.html -- take a look at the original example for more details.\n",
+ "\n",
+ "We also assume the data within an year from each other is highly correlated and should show a periodicity of 1 year."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "id": "a31d7eca",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Kernel with parameters given in GPML book\n",
+ "\n",
+ "# these hyper parameters are optimised in the GP fit\n",
+ "# we provide here only a starting value\n",
+ "\n",
+ "# Kernel with optimized parameters\n",
+ "k1 = 50.0 ** 2 * RBF(length_scale=50.0) # long term smooth rising trend\n",
+ "k2 = (\n",
+ " 2.0 ** 2\n",
+ " * RBF(length_scale=100.0)\n",
+ " * ExpSineSquared(length_scale=1.0, periodicity=1.0, periodicity_bounds=\"fixed\")\n",
+ ") # seasonal component\n",
+ "# medium term irregularities\n",
+ "k3 = 0.5 ** 2 * RationalQuadratic(length_scale=1.0, alpha=1.0)\n",
+ "k4 = 0.1 ** 2 * RBF(length_scale=0.1) + WhiteKernel(\n",
+ " noise_level=0.1 ** 2, noise_level_bounds=(1e-5, np.inf)\n",
+ ") # noise terms\n",
+ "kernel = k1 + k2 + k3 + k4"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "0ad8ddf0",
+ "metadata": {},
+ "source": [
+ "The kernel hyper-parameters are:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
"id": "032ada0d",
"metadata": {},
"outputs": [
@@ -574,7 +2502,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "66**2 * RBF(length_scale=67) + 2.4**2 * RBF(length_scale=90) * ExpSineSquared(length_scale=1.3, periodicity=1) + WhiteKernel(noise_level=0.0361)\n"
+ "50**2 * RBF(length_scale=50) + 2**2 * RBF(length_scale=100) * ExpSineSquared(length_scale=1, periodicity=1) + 0.5**2 * RationalQuadratic(alpha=1, length_scale=1) + 0.1**2 * RBF(length_scale=0.1) + WhiteKernel(noise_level=0.01)\n"
]
}
],
@@ -584,21 +2512,12 @@
},
{
"cell_type": "code",
- "execution_count": 13,
+ "execution_count": 12,
"id": "4412a9a7",
"metadata": {},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "/home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages/sklearn/gaussian_process/kernels.py:418: ConvergenceWarning: The optimal value found for dimension 0 of parameter k1__k1__k1__constant_value is close to the specified upper bound 100000.0. Increasing the bound and calling fit again may find a better value.\n",
- " ConvergenceWarning)\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
- "gp = GaussianProcessRegressor(kernel=kernel)\n",
+ "gp = GaussianProcessRegressor(kernel=kernel, normalize_y=True)\n",
"time = data.decimal.to_numpy()[:, np.newaxis]\n",
"co2 = data.co2.to_numpy()[:, np.newaxis]\n",
"gp = gp.fit(time, co2)"
@@ -614,7 +2533,7 @@
},
{
"cell_type": "code",
- "execution_count": 14,
+ "execution_count": 13,
"id": "667db862",
"metadata": {},
"outputs": [
@@ -622,8 +2541,8 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "GPML kernel: 316**2 * RBF(length_scale=81.2) + 2.36**2 * RBF(length_scale=49.3) * ExpSineSquared(length_scale=0.0522, periodicity=23) + WhiteKernel(noise_level=0.14)\n",
- "Log-marginal-likelihood: -1677.717\n"
+ "GPML kernel: 3.02**2 * RBF(length_scale=41.1) + 0.114**2 * RBF(length_scale=174) * ExpSineSquared(length_scale=1.31, periodicity=1) + 0.283**2 * RationalQuadratic(alpha=0.000977, length_scale=6.57) + 0.0101**2 * RBF(length_scale=0.019) + WhiteKernel(noise_level=0.000142)\n",
+ "Log-marginal-likelihood: 6639.404\n"
]
}
],
@@ -642,7 +2561,7 @@
},
{
"cell_type": "code",
- "execution_count": 15,
+ "execution_count": 14,
"id": "ef6b7762",
"metadata": {},
"outputs": [],
@@ -653,20 +2572,978 @@
},
{
"cell_type": "code",
- "execution_count": 16,
+ "execution_count": 15,
"id": "5b263358",
"metadata": {},
"outputs": [
{
"data": {
- "image/png": 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\n",
+ "application/javascript": [
+ "/* Put everything inside the global mpl namespace */\n",
+ "/* global mpl */\n",
+ "window.mpl = {};\n",
+ "\n",
+ "mpl.get_websocket_type = function () {\n",
+ " if (typeof WebSocket !== 'undefined') {\n",
+ " return WebSocket;\n",
+ " } else if (typeof MozWebSocket !== 'undefined') {\n",
+ " return MozWebSocket;\n",
+ " } else {\n",
+ " alert(\n",
+ " 'Your browser does not have WebSocket support. ' +\n",
+ " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+ " 'Firefox 4 and 5 are also supported but you ' +\n",
+ " 'have to enable WebSockets in about:config.'\n",
+ " );\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
+ " this.id = figure_id;\n",
+ "\n",
+ " this.ws = websocket;\n",
+ "\n",
+ " this.supports_binary = this.ws.binaryType !== undefined;\n",
+ "\n",
+ " if (!this.supports_binary) {\n",
+ " var warnings = document.getElementById('mpl-warnings');\n",
+ " if (warnings) {\n",
+ " warnings.style.display = 'block';\n",
+ " warnings.textContent =\n",
+ " 'This browser does not support binary websocket messages. ' +\n",
+ " 'Performance may be slow.';\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.imageObj = new Image();\n",
+ "\n",
+ " this.context = undefined;\n",
+ " this.message = undefined;\n",
+ " this.canvas = undefined;\n",
+ " this.rubberband_canvas = undefined;\n",
+ " this.rubberband_context = undefined;\n",
+ " this.format_dropdown = undefined;\n",
+ "\n",
+ " this.image_mode = 'full';\n",
+ "\n",
+ " this.root = document.createElement('div');\n",
+ " this.root.setAttribute('style', 'display: inline-block');\n",
+ " this._root_extra_style(this.root);\n",
+ "\n",
+ " parent_element.appendChild(this.root);\n",
+ "\n",
+ " this._init_header(this);\n",
+ " this._init_canvas(this);\n",
+ " this._init_toolbar(this);\n",
+ "\n",
+ " var fig = this;\n",
+ "\n",
+ " this.waiting = false;\n",
+ "\n",
+ " this.ws.onopen = function () {\n",
+ " fig.send_message('supports_binary', { value: fig.supports_binary });\n",
+ " fig.send_message('send_image_mode', {});\n",
+ " if (fig.ratio !== 1) {\n",
+ " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
+ " }\n",
+ " fig.send_message('refresh', {});\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onload = function () {\n",
+ " if (fig.image_mode === 'full') {\n",
+ " // Full images could contain transparency (where diff images\n",
+ " // almost always do), so we need to clear the canvas so that\n",
+ " // there is no ghosting.\n",
+ " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+ " }\n",
+ " fig.context.drawImage(fig.imageObj, 0, 0);\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onunload = function () {\n",
+ " fig.ws.close();\n",
+ " };\n",
+ "\n",
+ " this.ws.onmessage = this._make_on_message_function(this);\n",
+ "\n",
+ " this.ondownload = ondownload;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_header = function () {\n",
+ " var titlebar = document.createElement('div');\n",
+ " titlebar.classList =\n",
+ " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
+ " var titletext = document.createElement('div');\n",
+ " titletext.classList = 'ui-dialog-title';\n",
+ " titletext.setAttribute(\n",
+ " 'style',\n",
+ " 'width: 100%; text-align: center; padding: 3px;'\n",
+ " );\n",
+ " titlebar.appendChild(titletext);\n",
+ " this.root.appendChild(titlebar);\n",
+ " this.header = titletext;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
+ "\n",
+ "mpl.figure.prototype._init_canvas = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var canvas_div = (this.canvas_div = document.createElement('div'));\n",
+ " canvas_div.setAttribute(\n",
+ " 'style',\n",
+ " 'border: 1px solid #ddd;' +\n",
+ " 'box-sizing: content-box;' +\n",
+ " 'clear: both;' +\n",
+ " 'min-height: 1px;' +\n",
+ " 'min-width: 1px;' +\n",
+ " 'outline: 0;' +\n",
+ " 'overflow: hidden;' +\n",
+ " 'position: relative;' +\n",
+ " 'resize: both;'\n",
+ " );\n",
+ "\n",
+ " function on_keyboard_event_closure(name) {\n",
+ " return function (event) {\n",
+ " return fig.key_event(event, name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " canvas_div.addEventListener(\n",
+ " 'keydown',\n",
+ " on_keyboard_event_closure('key_press')\n",
+ " );\n",
+ " canvas_div.addEventListener(\n",
+ " 'keyup',\n",
+ " on_keyboard_event_closure('key_release')\n",
+ " );\n",
+ "\n",
+ " this._canvas_extra_style(canvas_div);\n",
+ " this.root.appendChild(canvas_div);\n",
+ "\n",
+ " var canvas = (this.canvas = document.createElement('canvas'));\n",
+ " canvas.classList.add('mpl-canvas');\n",
+ " canvas.setAttribute('style', 'box-sizing: content-box;');\n",
+ "\n",
+ " this.context = canvas.getContext('2d');\n",
+ "\n",
+ " var backingStore =\n",
+ " this.context.backingStorePixelRatio ||\n",
+ " this.context.webkitBackingStorePixelRatio ||\n",
+ " this.context.mozBackingStorePixelRatio ||\n",
+ " this.context.msBackingStorePixelRatio ||\n",
+ " this.context.oBackingStorePixelRatio ||\n",
+ " this.context.backingStorePixelRatio ||\n",
+ " 1;\n",
+ "\n",
+ " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+ "\n",
+ " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
+ " 'canvas'\n",
+ " ));\n",
+ " rubberband_canvas.setAttribute(\n",
+ " 'style',\n",
+ " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
+ " );\n",
+ "\n",
+ " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
+ " if (this.ResizeObserver === undefined) {\n",
+ " if (window.ResizeObserver !== undefined) {\n",
+ " this.ResizeObserver = window.ResizeObserver;\n",
+ " } else {\n",
+ " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
+ " this.ResizeObserver = obs.ResizeObserver;\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
+ " var nentries = entries.length;\n",
+ " for (var i = 0; i < nentries; i++) {\n",
+ " var entry = entries[i];\n",
+ " var width, height;\n",
+ " if (entry.contentBoxSize) {\n",
+ " if (entry.contentBoxSize instanceof Array) {\n",
+ " // Chrome 84 implements new version of spec.\n",
+ " width = entry.contentBoxSize[0].inlineSize;\n",
+ " height = entry.contentBoxSize[0].blockSize;\n",
+ " } else {\n",
+ " // Firefox implements old version of spec.\n",
+ " width = entry.contentBoxSize.inlineSize;\n",
+ " height = entry.contentBoxSize.blockSize;\n",
+ " }\n",
+ " } else {\n",
+ " // Chrome <84 implements even older version of spec.\n",
+ " width = entry.contentRect.width;\n",
+ " height = entry.contentRect.height;\n",
+ " }\n",
+ "\n",
+ " // Keep the size of the canvas and rubber band canvas in sync with\n",
+ " // the canvas container.\n",
+ " if (entry.devicePixelContentBoxSize) {\n",
+ " // Chrome 84 implements new version of spec.\n",
+ " canvas.setAttribute(\n",
+ " 'width',\n",
+ " entry.devicePixelContentBoxSize[0].inlineSize\n",
+ " );\n",
+ " canvas.setAttribute(\n",
+ " 'height',\n",
+ " entry.devicePixelContentBoxSize[0].blockSize\n",
+ " );\n",
+ " } else {\n",
+ " canvas.setAttribute('width', width * fig.ratio);\n",
+ " canvas.setAttribute('height', height * fig.ratio);\n",
+ " }\n",
+ " canvas.setAttribute(\n",
+ " 'style',\n",
+ " 'width: ' + width + 'px; height: ' + height + 'px;'\n",
+ " );\n",
+ "\n",
+ " rubberband_canvas.setAttribute('width', width);\n",
+ " rubberband_canvas.setAttribute('height', height);\n",
+ "\n",
+ " // And update the size in Python. We ignore the initial 0/0 size\n",
+ " // that occurs as the element is placed into the DOM, which should\n",
+ " // otherwise not happen due to the minimum size styling.\n",
+ " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
+ " fig.request_resize(width, height);\n",
+ " }\n",
+ " }\n",
+ " });\n",
+ " this.resizeObserverInstance.observe(canvas_div);\n",
+ "\n",
+ " function on_mouse_event_closure(name) {\n",
+ " return function (event) {\n",
+ " return fig.mouse_event(event, name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mousedown',\n",
+ " on_mouse_event_closure('button_press')\n",
+ " );\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseup',\n",
+ " on_mouse_event_closure('button_release')\n",
+ " );\n",
+ " // Throttle sequential mouse events to 1 every 20ms.\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mousemove',\n",
+ " on_mouse_event_closure('motion_notify')\n",
+ " );\n",
+ "\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseenter',\n",
+ " on_mouse_event_closure('figure_enter')\n",
+ " );\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseleave',\n",
+ " on_mouse_event_closure('figure_leave')\n",
+ " );\n",
+ "\n",
+ " canvas_div.addEventListener('wheel', function (event) {\n",
+ " if (event.deltaY < 0) {\n",
+ " event.step = 1;\n",
+ " } else {\n",
+ " event.step = -1;\n",
+ " }\n",
+ " on_mouse_event_closure('scroll')(event);\n",
+ " });\n",
+ "\n",
+ " canvas_div.appendChild(canvas);\n",
+ " canvas_div.appendChild(rubberband_canvas);\n",
+ "\n",
+ " this.rubberband_context = rubberband_canvas.getContext('2d');\n",
+ " this.rubberband_context.strokeStyle = '#000000';\n",
+ "\n",
+ " this._resize_canvas = function (width, height, forward) {\n",
+ " if (forward) {\n",
+ " canvas_div.style.width = width + 'px';\n",
+ " canvas_div.style.height = height + 'px';\n",
+ " }\n",
+ " };\n",
+ "\n",
+ " // Disable right mouse context menu.\n",
+ " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ " });\n",
+ "\n",
+ " function set_focus() {\n",
+ " canvas.focus();\n",
+ " canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " window.setTimeout(set_focus, 100);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var toolbar = document.createElement('div');\n",
+ " toolbar.classList = 'mpl-toolbar';\n",
+ " this.root.appendChild(toolbar);\n",
+ "\n",
+ " function on_click_closure(name) {\n",
+ " return function (_event) {\n",
+ " return fig.toolbar_button_onclick(name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " function on_mouseover_closure(tooltip) {\n",
+ " return function (event) {\n",
+ " if (!event.currentTarget.disabled) {\n",
+ " return fig.toolbar_button_onmouseover(tooltip);\n",
+ " }\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " fig.buttons = {};\n",
+ " var buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'mpl-button-group';\n",
+ " for (var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " /* Instead of a spacer, we start a new button group. */\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ " buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'mpl-button-group';\n",
+ " continue;\n",
+ " }\n",
+ "\n",
+ " var button = (fig.buttons[name] = document.createElement('button'));\n",
+ " button.classList = 'mpl-widget';\n",
+ " button.setAttribute('role', 'button');\n",
+ " button.setAttribute('aria-disabled', 'false');\n",
+ " button.addEventListener('click', on_click_closure(method_name));\n",
+ " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+ "\n",
+ " var icon_img = document.createElement('img');\n",
+ " icon_img.src = '_images/' + image + '.png';\n",
+ " icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
+ " icon_img.alt = tooltip;\n",
+ " button.appendChild(icon_img);\n",
+ "\n",
+ " buttonGroup.appendChild(button);\n",
+ " }\n",
+ "\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ "\n",
+ " var fmt_picker = document.createElement('select');\n",
+ " fmt_picker.classList = 'mpl-widget';\n",
+ " toolbar.appendChild(fmt_picker);\n",
+ " this.format_dropdown = fmt_picker;\n",
+ "\n",
+ " for (var ind in mpl.extensions) {\n",
+ " var fmt = mpl.extensions[ind];\n",
+ " var option = document.createElement('option');\n",
+ " option.selected = fmt === mpl.default_extension;\n",
+ " option.innerHTML = fmt;\n",
+ " fmt_picker.appendChild(option);\n",
+ " }\n",
+ "\n",
+ " var status_bar = document.createElement('span');\n",
+ " status_bar.classList = 'mpl-message';\n",
+ " toolbar.appendChild(status_bar);\n",
+ " this.message = status_bar;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
+ " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+ " // which will in turn request a refresh of the image.\n",
+ " this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.send_message = function (type, properties) {\n",
+ " properties['type'] = type;\n",
+ " properties['figure_id'] = this.id;\n",
+ " this.ws.send(JSON.stringify(properties));\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.send_draw_message = function () {\n",
+ " if (!this.waiting) {\n",
+ " this.waiting = true;\n",
+ " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+ " var format_dropdown = fig.format_dropdown;\n",
+ " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+ " fig.ondownload(fig, format);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
+ " var size = msg['size'];\n",
+ " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
+ " fig._resize_canvas(size[0], size[1], msg['forward']);\n",
+ " fig.send_message('refresh', {});\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
+ " var x0 = msg['x0'] / fig.ratio;\n",
+ " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
+ " var x1 = msg['x1'] / fig.ratio;\n",
+ " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
+ " x0 = Math.floor(x0) + 0.5;\n",
+ " y0 = Math.floor(y0) + 0.5;\n",
+ " x1 = Math.floor(x1) + 0.5;\n",
+ " y1 = Math.floor(y1) + 0.5;\n",
+ " var min_x = Math.min(x0, x1);\n",
+ " var min_y = Math.min(y0, y1);\n",
+ " var width = Math.abs(x1 - x0);\n",
+ " var height = Math.abs(y1 - y0);\n",
+ "\n",
+ " fig.rubberband_context.clearRect(\n",
+ " 0,\n",
+ " 0,\n",
+ " fig.canvas.width / fig.ratio,\n",
+ " fig.canvas.height / fig.ratio\n",
+ " );\n",
+ "\n",
+ " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
+ " // Updates the figure title.\n",
+ " fig.header.textContent = msg['label'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
+ " var cursor = msg['cursor'];\n",
+ " switch (cursor) {\n",
+ " case 0:\n",
+ " cursor = 'pointer';\n",
+ " break;\n",
+ " case 1:\n",
+ " cursor = 'default';\n",
+ " break;\n",
+ " case 2:\n",
+ " cursor = 'crosshair';\n",
+ " break;\n",
+ " case 3:\n",
+ " cursor = 'move';\n",
+ " break;\n",
+ " }\n",
+ " fig.rubberband_canvas.style.cursor = cursor;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
+ " fig.message.textContent = msg['message'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
+ " // Request the server to send over a new figure.\n",
+ " fig.send_draw_message();\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
+ " fig.image_mode = msg['mode'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
+ " for (var key in msg) {\n",
+ " if (!(key in fig.buttons)) {\n",
+ " continue;\n",
+ " }\n",
+ " fig.buttons[key].disabled = !msg[key];\n",
+ " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
+ " if (msg['mode'] === 'PAN') {\n",
+ " fig.buttons['Pan'].classList.add('active');\n",
+ " fig.buttons['Zoom'].classList.remove('active');\n",
+ " } else if (msg['mode'] === 'ZOOM') {\n",
+ " fig.buttons['Pan'].classList.remove('active');\n",
+ " fig.buttons['Zoom'].classList.add('active');\n",
+ " } else {\n",
+ " fig.buttons['Pan'].classList.remove('active');\n",
+ " fig.buttons['Zoom'].classList.remove('active');\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function () {\n",
+ " // Called whenever the canvas gets updated.\n",
+ " this.send_message('ack', {});\n",
+ "};\n",
+ "\n",
+ "// A function to construct a web socket function for onmessage handling.\n",
+ "// Called in the figure constructor.\n",
+ "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
+ " return function socket_on_message(evt) {\n",
+ " if (evt.data instanceof Blob) {\n",
+ " /* FIXME: We get \"Resource interpreted as Image but\n",
+ " * transferred with MIME type text/plain:\" errors on\n",
+ " * Chrome. But how to set the MIME type? It doesn't seem\n",
+ " * to be part of the websocket stream */\n",
+ " evt.data.type = 'image/png';\n",
+ "\n",
+ " /* Free the memory for the previous frames */\n",
+ " if (fig.imageObj.src) {\n",
+ " (window.URL || window.webkitURL).revokeObjectURL(\n",
+ " fig.imageObj.src\n",
+ " );\n",
+ " }\n",
+ "\n",
+ " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+ " evt.data\n",
+ " );\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " } else if (\n",
+ " typeof evt.data === 'string' &&\n",
+ " evt.data.slice(0, 21) === 'data:image/png;base64'\n",
+ " ) {\n",
+ " fig.imageObj.src = evt.data;\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " var msg = JSON.parse(evt.data);\n",
+ " var msg_type = msg['type'];\n",
+ "\n",
+ " // Call the \"handle_{type}\" callback, which takes\n",
+ " // the figure and JSON message as its only arguments.\n",
+ " try {\n",
+ " var callback = fig['handle_' + msg_type];\n",
+ " } catch (e) {\n",
+ " console.log(\n",
+ " \"No handler for the '\" + msg_type + \"' message type: \",\n",
+ " msg\n",
+ " );\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " if (callback) {\n",
+ " try {\n",
+ " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+ " callback(fig, msg);\n",
+ " } catch (e) {\n",
+ " console.log(\n",
+ " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
+ " e,\n",
+ " e.stack,\n",
+ " msg\n",
+ " );\n",
+ " }\n",
+ " }\n",
+ " };\n",
+ "};\n",
+ "\n",
+ "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+ "mpl.findpos = function (e) {\n",
+ " //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+ " var targ;\n",
+ " if (!e) {\n",
+ " e = window.event;\n",
+ " }\n",
+ " if (e.target) {\n",
+ " targ = e.target;\n",
+ " } else if (e.srcElement) {\n",
+ " targ = e.srcElement;\n",
+ " }\n",
+ " if (targ.nodeType === 3) {\n",
+ " // defeat Safari bug\n",
+ " targ = targ.parentNode;\n",
+ " }\n",
+ "\n",
+ " // pageX,Y are the mouse positions relative to the document\n",
+ " var boundingRect = targ.getBoundingClientRect();\n",
+ " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
+ " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
+ "\n",
+ " return { x: x, y: y };\n",
+ "};\n",
+ "\n",
+ "/*\n",
+ " * return a copy of an object with only non-object keys\n",
+ " * we need this to avoid circular references\n",
+ " * http://stackoverflow.com/a/24161582/3208463\n",
+ " */\n",
+ "function simpleKeys(original) {\n",
+ " return Object.keys(original).reduce(function (obj, key) {\n",
+ " if (typeof original[key] !== 'object') {\n",
+ " obj[key] = original[key];\n",
+ " }\n",
+ " return obj;\n",
+ " }, {});\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.mouse_event = function (event, name) {\n",
+ " var canvas_pos = mpl.findpos(event);\n",
+ "\n",
+ " if (name === 'button_press') {\n",
+ " this.canvas.focus();\n",
+ " this.canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " var x = canvas_pos.x * this.ratio;\n",
+ " var y = canvas_pos.y * this.ratio;\n",
+ "\n",
+ " this.send_message(name, {\n",
+ " x: x,\n",
+ " y: y,\n",
+ " button: event.button,\n",
+ " step: event.step,\n",
+ " guiEvent: simpleKeys(event),\n",
+ " });\n",
+ "\n",
+ " /* This prevents the web browser from automatically changing to\n",
+ " * the text insertion cursor when the button is pressed. We want\n",
+ " * to control all of the cursor setting manually through the\n",
+ " * 'cursor' event from matplotlib */\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
+ " // Handle any extra behaviour associated with a key event\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.key_event = function (event, name) {\n",
+ " // Prevent repeat events\n",
+ " if (name === 'key_press') {\n",
+ " if (event.which === this._key) {\n",
+ " return;\n",
+ " } else {\n",
+ " this._key = event.which;\n",
+ " }\n",
+ " }\n",
+ " if (name === 'key_release') {\n",
+ " this._key = null;\n",
+ " }\n",
+ "\n",
+ " var value = '';\n",
+ " if (event.ctrlKey && event.which !== 17) {\n",
+ " value += 'ctrl+';\n",
+ " }\n",
+ " if (event.altKey && event.which !== 18) {\n",
+ " value += 'alt+';\n",
+ " }\n",
+ " if (event.shiftKey && event.which !== 16) {\n",
+ " value += 'shift+';\n",
+ " }\n",
+ "\n",
+ " value += 'k';\n",
+ " value += event.which.toString();\n",
+ "\n",
+ " this._key_event_extra(event, name);\n",
+ "\n",
+ " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
+ " return false;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
+ " if (name === 'download') {\n",
+ " this.handle_save(this, null);\n",
+ " } else {\n",
+ " this.send_message('toolbar_button', { name: name });\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
+ " this.message.textContent = tooltip;\n",
+ "};\n",
+ "\n",
+ "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
+ "// prettier-ignore\n",
+ "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
+ "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+ "\n",
+ "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
+ "\n",
+ "mpl.default_extension = \"png\";/* global mpl */\n",
+ "\n",
+ "var comm_websocket_adapter = function (comm) {\n",
+ " // Create a \"websocket\"-like object which calls the given IPython comm\n",
+ " // object with the appropriate methods. Currently this is a non binary\n",
+ " // socket, so there is still some room for performance tuning.\n",
+ " var ws = {};\n",
+ "\n",
+ " ws.close = function () {\n",
+ " comm.close();\n",
+ " };\n",
+ " ws.send = function (m) {\n",
+ " //console.log('sending', m);\n",
+ " comm.send(m);\n",
+ " };\n",
+ " // Register the callback with on_msg.\n",
+ " comm.on_msg(function (msg) {\n",
+ " //console.log('receiving', msg['content']['data'], msg);\n",
+ " // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
+ " ws.onmessage(msg['content']['data']);\n",
+ " });\n",
+ " return ws;\n",
+ "};\n",
+ "\n",
+ "mpl.mpl_figure_comm = function (comm, msg) {\n",
+ " // This is the function which gets called when the mpl process\n",
+ " // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+ "\n",
+ " var id = msg.content.data.id;\n",
+ " // Get hold of the div created by the display call when the Comm\n",
+ " // socket was opened in Python.\n",
+ " var element = document.getElementById(id);\n",
+ " var ws_proxy = comm_websocket_adapter(comm);\n",
+ "\n",
+ " function ondownload(figure, _format) {\n",
+ " window.open(figure.canvas.toDataURL());\n",
+ " }\n",
+ "\n",
+ " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
+ "\n",
+ " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+ " // web socket which is closed, not our websocket->open comm proxy.\n",
+ " ws_proxy.onopen();\n",
+ "\n",
+ " fig.parent_element = element;\n",
+ " fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+ " if (!fig.cell_info) {\n",
+ " console.error('Failed to find cell for figure', id, fig);\n",
+ " return;\n",
+ " }\n",
+ " fig.cell_info[0].output_area.element.on(\n",
+ " 'cleared',\n",
+ " { fig: fig },\n",
+ " fig._remove_fig_handler\n",
+ " );\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
+ " var width = fig.canvas.width / fig.ratio;\n",
+ " fig.cell_info[0].output_area.element.off(\n",
+ " 'cleared',\n",
+ " fig._remove_fig_handler\n",
+ " );\n",
+ " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
+ "\n",
+ " // Update the output cell to use the data from the current canvas.\n",
+ " fig.push_to_output();\n",
+ " var dataURL = fig.canvas.toDataURL();\n",
+ " // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+ " // the notebook keyboard shortcuts fail.\n",
+ " IPython.keyboard_manager.enable();\n",
+ " fig.parent_element.innerHTML =\n",
+ " '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ " fig.close_ws(fig, msg);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
+ " fig.send_message('closing', msg);\n",
+ " // fig.ws.close()\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
+ " // Turn the data on the canvas into data in the output cell.\n",
+ " var width = this.canvas.width / this.ratio;\n",
+ " var dataURL = this.canvas.toDataURL();\n",
+ " this.cell_info[1]['text/html'] =\n",
+ " '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function () {\n",
+ " // Tell IPython that the notebook contents must change.\n",
+ " IPython.notebook.set_dirty(true);\n",
+ " this.send_message('ack', {});\n",
+ " var fig = this;\n",
+ " // Wait a second, then push the new image to the DOM so\n",
+ " // that it is saved nicely (might be nice to debounce this).\n",
+ " setTimeout(function () {\n",
+ " fig.push_to_output();\n",
+ " }, 1000);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var toolbar = document.createElement('div');\n",
+ " toolbar.classList = 'btn-toolbar';\n",
+ " this.root.appendChild(toolbar);\n",
+ "\n",
+ " function on_click_closure(name) {\n",
+ " return function (_event) {\n",
+ " return fig.toolbar_button_onclick(name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " function on_mouseover_closure(tooltip) {\n",
+ " return function (event) {\n",
+ " if (!event.currentTarget.disabled) {\n",
+ " return fig.toolbar_button_onmouseover(tooltip);\n",
+ " }\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " fig.buttons = {};\n",
+ " var buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'btn-group';\n",
+ " var button;\n",
+ " for (var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " /* Instead of a spacer, we start a new button group. */\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ " buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'btn-group';\n",
+ " continue;\n",
+ " }\n",
+ "\n",
+ " button = fig.buttons[name] = document.createElement('button');\n",
+ " button.classList = 'btn btn-default';\n",
+ " button.href = '#';\n",
+ " button.title = name;\n",
+ " button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
+ " button.addEventListener('click', on_click_closure(method_name));\n",
+ " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+ " buttonGroup.appendChild(button);\n",
+ " }\n",
+ "\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ "\n",
+ " // Add the status bar.\n",
+ " var status_bar = document.createElement('span');\n",
+ " status_bar.classList = 'mpl-message pull-right';\n",
+ " toolbar.appendChild(status_bar);\n",
+ " this.message = status_bar;\n",
+ "\n",
+ " // Add the close button to the window.\n",
+ " var buttongrp = document.createElement('div');\n",
+ " buttongrp.classList = 'btn-group inline pull-right';\n",
+ " button = document.createElement('button');\n",
+ " button.classList = 'btn btn-mini btn-primary';\n",
+ " button.href = '#';\n",
+ " button.title = 'Stop Interaction';\n",
+ " button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
+ " button.addEventListener('click', function (_evt) {\n",
+ " fig.handle_close(fig, {});\n",
+ " });\n",
+ " button.addEventListener(\n",
+ " 'mouseover',\n",
+ " on_mouseover_closure('Stop Interaction')\n",
+ " );\n",
+ " buttongrp.appendChild(button);\n",
+ " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
+ " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
+ " var fig = event.data.fig;\n",
+ " if (event.target !== this) {\n",
+ " // Ignore bubbled events from children.\n",
+ " return;\n",
+ " }\n",
+ " fig.close_ws(fig, {});\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function (el) {\n",
+ " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
+ " // this is important to make the div 'focusable\n",
+ " el.setAttribute('tabindex', 0);\n",
+ " // reach out to IPython and tell the keyboard manager to turn it's self\n",
+ " // off when our div gets focus\n",
+ "\n",
+ " // location in version 3\n",
+ " if (IPython.notebook.keyboard_manager) {\n",
+ " IPython.notebook.keyboard_manager.register_events(el);\n",
+ " } else {\n",
+ " // location in version 2\n",
+ " IPython.keyboard_manager.register_events(el);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
+ " var manager = IPython.notebook.keyboard_manager;\n",
+ " if (!manager) {\n",
+ " manager = IPython.keyboard_manager;\n",
+ " }\n",
+ "\n",
+ " // Check for shift+enter\n",
+ " if (event.shiftKey && event.which === 13) {\n",
+ " this.canvas_div.blur();\n",
+ " // select the cell after this one\n",
+ " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
+ " IPython.notebook.select(index + 1);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+ " fig.ondownload(fig, null);\n",
+ "};\n",
+ "\n",
+ "mpl.find_output_cell = function (html_output) {\n",
+ " // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+ " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+ " // IPython event is triggered only after the cells have been serialised, which for\n",
+ " // our purposes (turning an active figure into a static one), is too late.\n",
+ " var cells = IPython.notebook.get_cells();\n",
+ " var ncells = cells.length;\n",
+ " for (var i = 0; i < ncells; i++) {\n",
+ " var cell = cells[i];\n",
+ " if (cell.cell_type === 'code') {\n",
+ " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
+ " var data = cell.output_area.outputs[j];\n",
+ " if (data.data) {\n",
+ " // IPython >= 3 moved mimebundle to data attribute of output\n",
+ " data = data.data;\n",
+ " }\n",
+ " if (data['text/html'] === html_output) {\n",
+ " return [cell, data, j];\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "// Register the function which deals with the matplotlib target/channel.\n",
+ "// The kernel may be null if the page has been refreshed.\n",
+ "if (IPython.notebook.kernel !== null) {\n",
+ " IPython.notebook.kernel.comm_manager.register_target(\n",
+ " 'matplotlib',\n",
+ " mpl.mpl_figure_comm\n",
+ " );\n",
+ "}\n"
+ ],
"text/plain": [
- "<Figure size 576x576 with 1 Axes>"
+ "<IPython.core.display.Javascript object>"
]
},
- "metadata": {
- "needs_background": "light"
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
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\" width=\"800\">"
+ ],
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ]
},
+ "metadata": {},
"output_type": "display_data"
}
],
@@ -707,8 +3584,7 @@
"source": [
"### Contact us at the EuXFEL Data Analysis group at any time if you need help analysing your data!\n",
"\n",
- "#### Danilo Ferreira de Lima: danilo.enoque.ferreira.de.lima@xfel.eu\n",
- "#### Arman Davtyan: arman.davtyan@xfel.eu"
+ "#### Data Analysis group: da@xfel.eu"
]
},
{
@@ -736,7 +3612,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.7.10"
+ "version": "3.6.13"
}
},
"nbformat": 4,
diff --git a/Mixture Models.ipynb b/Mixture Models.ipynb
index 75ef86e..6af39c1 100644
--- a/Mixture Models.ipynb
+++ b/Mixture Models.ipynb
@@ -22,7 +22,7 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": 1,
"id": "44ca341e",
"metadata": {},
"outputs": [
@@ -30,20 +30,20 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "Requirement already satisfied: numpy in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (1.19.2)\n",
- "Requirement already satisfied: scikit-learn in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (0.24.2)\n",
- "Requirement already satisfied: pandas in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (1.3.0)\n",
- "Requirement already satisfied: matplotlib in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (3.4.2)\n",
- "Requirement already satisfied: joblib>=0.11 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from scikit-learn) (1.0.1)\n",
- "Requirement already satisfied: scipy>=0.19.1 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from scikit-learn) (1.6.2)\n",
- "Requirement already satisfied: threadpoolctl>=2.0.0 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from scikit-learn) (2.2.0)\n",
- "Requirement already satisfied: python-dateutil>=2.7.3 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from pandas) (2.8.2)\n",
- "Requirement already satisfied: pytz>=2017.3 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from pandas) (2021.1)\n",
- "Requirement already satisfied: six>=1.5 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from python-dateutil>=2.7.3->pandas) (1.16.0)\n",
- "Requirement already satisfied: kiwisolver>=1.0.1 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from matplotlib) (1.3.1)\n",
- "Requirement already satisfied: pillow>=6.2.0 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from matplotlib) (8.3.1)\n",
- "Requirement already satisfied: pyparsing>=2.2.1 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from matplotlib) (2.4.7)\n",
- "Requirement already satisfied: cycler>=0.10 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from matplotlib) (0.10.0)\n"
+ "Requirement already satisfied: numpy in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (1.19.2)\n",
+ "Requirement already satisfied: scikit-learn in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (0.24.2)\n",
+ "Requirement already satisfied: pandas in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (1.1.5)\n",
+ "Requirement already satisfied: matplotlib in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (3.3.4)\n",
+ "Requirement already satisfied: scipy>=0.19.1 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from scikit-learn) (1.5.2)\n",
+ "Requirement already satisfied: joblib>=0.11 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from scikit-learn) (1.0.1)\n",
+ "Requirement already satisfied: threadpoolctl>=2.0.0 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from scikit-learn) (2.2.0)\n",
+ "Requirement already satisfied: python-dateutil>=2.7.3 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from pandas) (2.8.2)\n",
+ "Requirement already satisfied: pytz>=2017.2 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from pandas) (2021.3)\n",
+ "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.3 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from matplotlib) (3.0.4)\n",
+ "Requirement already satisfied: kiwisolver>=1.0.1 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from matplotlib) (1.3.1)\n",
+ "Requirement already satisfied: cycler>=0.10 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from matplotlib) (0.11.0)\n",
+ "Requirement already satisfied: pillow>=6.2.0 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from matplotlib) (8.3.1)\n",
+ "Requirement already satisfied: six>=1.5 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from python-dateutil>=2.7.3->pandas) (1.16.0)\n"
]
}
],
@@ -53,13 +53,14 @@
},
{
"cell_type": "code",
- "execution_count": 21,
+ "execution_count": 2,
"id": "300cf8d3",
"metadata": {},
"outputs": [],
"source": [
+ "%matplotlib notebook\n",
+ "\n",
"import matplotlib.pyplot as plt\n",
- "%matplotlib inline\n",
"\n",
"import pandas as pd\n",
"import numpy as np\n",
@@ -77,7 +78,7 @@
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": 3,
"id": "4959a292",
"metadata": {},
"outputs": [],
@@ -94,7 +95,7 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": 4,
"id": "82929490",
"metadata": {},
"outputs": [
@@ -102,7 +103,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
- "/home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages/ipykernel_launcher.py:6: RuntimeWarning: covariance is not positive-semidefinite.\n",
+ "/home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages/ipykernel_launcher.py:6: RuntimeWarning: covariance is not positive-semidefinite.\n",
" \n"
]
}
@@ -131,7 +132,7 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": 5,
"id": "024fb65a",
"metadata": {},
"outputs": [
@@ -164,32 +165,32 @@
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
- " <td>4.703667</td>\n",
- " <td>-2.520675</td>\n",
+ " <td>5.653241</td>\n",
+ " <td>-1.382435</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
- " <td>5.725668</td>\n",
- " <td>-1.535801</td>\n",
+ " <td>4.623728</td>\n",
+ " <td>-2.254146</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
- " <td>4.529343</td>\n",
- " <td>-2.351627</td>\n",
+ " <td>5.313702</td>\n",
+ " <td>-1.596076</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
- " <td>5.457254</td>\n",
- " <td>-1.345677</td>\n",
+ " <td>4.830723</td>\n",
+ " <td>-1.521429</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
- " <td>6.294784</td>\n",
- " <td>-1.201564</td>\n",
+ " <td>4.716383</td>\n",
+ " <td>-1.686052</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
@@ -200,32 +201,32 @@
" </tr>\n",
" <tr>\n",
" <th>2995</th>\n",
- " <td>-5.394441</td>\n",
- " <td>-6.048515</td>\n",
+ " <td>-5.327421</td>\n",
+ " <td>-0.196162</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2996</th>\n",
- " <td>-5.993827</td>\n",
- " <td>-2.207523</td>\n",
+ " <td>-6.919531</td>\n",
+ " <td>-1.834852</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2997</th>\n",
- " <td>-4.935977</td>\n",
- " <td>-3.538230</td>\n",
+ " <td>-6.075992</td>\n",
+ " <td>-0.312784</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2998</th>\n",
- " <td>-3.583106</td>\n",
- " <td>2.184044</td>\n",
+ " <td>-3.835365</td>\n",
+ " <td>5.404520</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2999</th>\n",
- " <td>-3.930869</td>\n",
- " <td>-2.551996</td>\n",
+ " <td>-3.402078</td>\n",
+ " <td>-3.187637</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" </tbody>\n",
@@ -235,22 +236,22 @@
],
"text/plain": [
" x y source\n",
- "0 4.703667 -2.520675 0.0\n",
- "1 5.725668 -1.535801 0.0\n",
- "2 4.529343 -2.351627 0.0\n",
- "3 5.457254 -1.345677 0.0\n",
- "4 6.294784 -1.201564 0.0\n",
+ "0 5.653241 -1.382435 0.0\n",
+ "1 4.623728 -2.254146 0.0\n",
+ "2 5.313702 -1.596076 0.0\n",
+ "3 4.830723 -1.521429 0.0\n",
+ "4 4.716383 -1.686052 0.0\n",
"... ... ... ...\n",
- "2995 -5.394441 -6.048515 2.0\n",
- "2996 -5.993827 -2.207523 2.0\n",
- "2997 -4.935977 -3.538230 2.0\n",
- "2998 -3.583106 2.184044 2.0\n",
- "2999 -3.930869 -2.551996 2.0\n",
+ "2995 -5.327421 -0.196162 2.0\n",
+ "2996 -6.919531 -1.834852 2.0\n",
+ "2997 -6.075992 -0.312784 2.0\n",
+ "2998 -3.835365 5.404520 2.0\n",
+ "2999 -3.402078 -3.187637 2.0\n",
"\n",
"[3000 rows x 3 columns]"
]
},
- "execution_count": 4,
+ "execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
@@ -269,20 +270,978 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 6,
"id": "e63b38c5",
"metadata": {},
"outputs": [
{
"data": {
- "image/png": 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\n",
+ "application/javascript": [
+ "/* Put everything inside the global mpl namespace */\n",
+ "/* global mpl */\n",
+ "window.mpl = {};\n",
+ "\n",
+ "mpl.get_websocket_type = function () {\n",
+ " if (typeof WebSocket !== 'undefined') {\n",
+ " return WebSocket;\n",
+ " } else if (typeof MozWebSocket !== 'undefined') {\n",
+ " return MozWebSocket;\n",
+ " } else {\n",
+ " alert(\n",
+ " 'Your browser does not have WebSocket support. ' +\n",
+ " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+ " 'Firefox 4 and 5 are also supported but you ' +\n",
+ " 'have to enable WebSockets in about:config.'\n",
+ " );\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
+ " this.id = figure_id;\n",
+ "\n",
+ " this.ws = websocket;\n",
+ "\n",
+ " this.supports_binary = this.ws.binaryType !== undefined;\n",
+ "\n",
+ " if (!this.supports_binary) {\n",
+ " var warnings = document.getElementById('mpl-warnings');\n",
+ " if (warnings) {\n",
+ " warnings.style.display = 'block';\n",
+ " warnings.textContent =\n",
+ " 'This browser does not support binary websocket messages. ' +\n",
+ " 'Performance may be slow.';\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.imageObj = new Image();\n",
+ "\n",
+ " this.context = undefined;\n",
+ " this.message = undefined;\n",
+ " this.canvas = undefined;\n",
+ " this.rubberband_canvas = undefined;\n",
+ " this.rubberband_context = undefined;\n",
+ " this.format_dropdown = undefined;\n",
+ "\n",
+ " this.image_mode = 'full';\n",
+ "\n",
+ " this.root = document.createElement('div');\n",
+ " this.root.setAttribute('style', 'display: inline-block');\n",
+ " this._root_extra_style(this.root);\n",
+ "\n",
+ " parent_element.appendChild(this.root);\n",
+ "\n",
+ " this._init_header(this);\n",
+ " this._init_canvas(this);\n",
+ " this._init_toolbar(this);\n",
+ "\n",
+ " var fig = this;\n",
+ "\n",
+ " this.waiting = false;\n",
+ "\n",
+ " this.ws.onopen = function () {\n",
+ " fig.send_message('supports_binary', { value: fig.supports_binary });\n",
+ " fig.send_message('send_image_mode', {});\n",
+ " if (fig.ratio !== 1) {\n",
+ " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
+ " }\n",
+ " fig.send_message('refresh', {});\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onload = function () {\n",
+ " if (fig.image_mode === 'full') {\n",
+ " // Full images could contain transparency (where diff images\n",
+ " // almost always do), so we need to clear the canvas so that\n",
+ " // there is no ghosting.\n",
+ " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+ " }\n",
+ " fig.context.drawImage(fig.imageObj, 0, 0);\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onunload = function () {\n",
+ " fig.ws.close();\n",
+ " };\n",
+ "\n",
+ " this.ws.onmessage = this._make_on_message_function(this);\n",
+ "\n",
+ " this.ondownload = ondownload;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_header = function () {\n",
+ " var titlebar = document.createElement('div');\n",
+ " titlebar.classList =\n",
+ " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
+ " var titletext = document.createElement('div');\n",
+ " titletext.classList = 'ui-dialog-title';\n",
+ " titletext.setAttribute(\n",
+ " 'style',\n",
+ " 'width: 100%; text-align: center; padding: 3px;'\n",
+ " );\n",
+ " titlebar.appendChild(titletext);\n",
+ " this.root.appendChild(titlebar);\n",
+ " this.header = titletext;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
+ "\n",
+ "mpl.figure.prototype._init_canvas = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var canvas_div = (this.canvas_div = document.createElement('div'));\n",
+ " canvas_div.setAttribute(\n",
+ " 'style',\n",
+ " 'border: 1px solid #ddd;' +\n",
+ " 'box-sizing: content-box;' +\n",
+ " 'clear: both;' +\n",
+ " 'min-height: 1px;' +\n",
+ " 'min-width: 1px;' +\n",
+ " 'outline: 0;' +\n",
+ " 'overflow: hidden;' +\n",
+ " 'position: relative;' +\n",
+ " 'resize: both;'\n",
+ " );\n",
+ "\n",
+ " function on_keyboard_event_closure(name) {\n",
+ " return function (event) {\n",
+ " return fig.key_event(event, name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " canvas_div.addEventListener(\n",
+ " 'keydown',\n",
+ " on_keyboard_event_closure('key_press')\n",
+ " );\n",
+ " canvas_div.addEventListener(\n",
+ " 'keyup',\n",
+ " on_keyboard_event_closure('key_release')\n",
+ " );\n",
+ "\n",
+ " this._canvas_extra_style(canvas_div);\n",
+ " this.root.appendChild(canvas_div);\n",
+ "\n",
+ " var canvas = (this.canvas = document.createElement('canvas'));\n",
+ " canvas.classList.add('mpl-canvas');\n",
+ " canvas.setAttribute('style', 'box-sizing: content-box;');\n",
+ "\n",
+ " this.context = canvas.getContext('2d');\n",
+ "\n",
+ " var backingStore =\n",
+ " this.context.backingStorePixelRatio ||\n",
+ " this.context.webkitBackingStorePixelRatio ||\n",
+ " this.context.mozBackingStorePixelRatio ||\n",
+ " this.context.msBackingStorePixelRatio ||\n",
+ " this.context.oBackingStorePixelRatio ||\n",
+ " this.context.backingStorePixelRatio ||\n",
+ " 1;\n",
+ "\n",
+ " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+ "\n",
+ " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
+ " 'canvas'\n",
+ " ));\n",
+ " rubberband_canvas.setAttribute(\n",
+ " 'style',\n",
+ " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
+ " );\n",
+ "\n",
+ " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
+ " if (this.ResizeObserver === undefined) {\n",
+ " if (window.ResizeObserver !== undefined) {\n",
+ " this.ResizeObserver = window.ResizeObserver;\n",
+ " } else {\n",
+ " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
+ " this.ResizeObserver = obs.ResizeObserver;\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
+ " var nentries = entries.length;\n",
+ " for (var i = 0; i < nentries; i++) {\n",
+ " var entry = entries[i];\n",
+ " var width, height;\n",
+ " if (entry.contentBoxSize) {\n",
+ " if (entry.contentBoxSize instanceof Array) {\n",
+ " // Chrome 84 implements new version of spec.\n",
+ " width = entry.contentBoxSize[0].inlineSize;\n",
+ " height = entry.contentBoxSize[0].blockSize;\n",
+ " } else {\n",
+ " // Firefox implements old version of spec.\n",
+ " width = entry.contentBoxSize.inlineSize;\n",
+ " height = entry.contentBoxSize.blockSize;\n",
+ " }\n",
+ " } else {\n",
+ " // Chrome <84 implements even older version of spec.\n",
+ " width = entry.contentRect.width;\n",
+ " height = entry.contentRect.height;\n",
+ " }\n",
+ "\n",
+ " // Keep the size of the canvas and rubber band canvas in sync with\n",
+ " // the canvas container.\n",
+ " if (entry.devicePixelContentBoxSize) {\n",
+ " // Chrome 84 implements new version of spec.\n",
+ " canvas.setAttribute(\n",
+ " 'width',\n",
+ " entry.devicePixelContentBoxSize[0].inlineSize\n",
+ " );\n",
+ " canvas.setAttribute(\n",
+ " 'height',\n",
+ " entry.devicePixelContentBoxSize[0].blockSize\n",
+ " );\n",
+ " } else {\n",
+ " canvas.setAttribute('width', width * fig.ratio);\n",
+ " canvas.setAttribute('height', height * fig.ratio);\n",
+ " }\n",
+ " canvas.setAttribute(\n",
+ " 'style',\n",
+ " 'width: ' + width + 'px; height: ' + height + 'px;'\n",
+ " );\n",
+ "\n",
+ " rubberband_canvas.setAttribute('width', width);\n",
+ " rubberband_canvas.setAttribute('height', height);\n",
+ "\n",
+ " // And update the size in Python. We ignore the initial 0/0 size\n",
+ " // that occurs as the element is placed into the DOM, which should\n",
+ " // otherwise not happen due to the minimum size styling.\n",
+ " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
+ " fig.request_resize(width, height);\n",
+ " }\n",
+ " }\n",
+ " });\n",
+ " this.resizeObserverInstance.observe(canvas_div);\n",
+ "\n",
+ " function on_mouse_event_closure(name) {\n",
+ " return function (event) {\n",
+ " return fig.mouse_event(event, name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mousedown',\n",
+ " on_mouse_event_closure('button_press')\n",
+ " );\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseup',\n",
+ " on_mouse_event_closure('button_release')\n",
+ " );\n",
+ " // Throttle sequential mouse events to 1 every 20ms.\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mousemove',\n",
+ " on_mouse_event_closure('motion_notify')\n",
+ " );\n",
+ "\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseenter',\n",
+ " on_mouse_event_closure('figure_enter')\n",
+ " );\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseleave',\n",
+ " on_mouse_event_closure('figure_leave')\n",
+ " );\n",
+ "\n",
+ " canvas_div.addEventListener('wheel', function (event) {\n",
+ " if (event.deltaY < 0) {\n",
+ " event.step = 1;\n",
+ " } else {\n",
+ " event.step = -1;\n",
+ " }\n",
+ " on_mouse_event_closure('scroll')(event);\n",
+ " });\n",
+ "\n",
+ " canvas_div.appendChild(canvas);\n",
+ " canvas_div.appendChild(rubberband_canvas);\n",
+ "\n",
+ " this.rubberband_context = rubberband_canvas.getContext('2d');\n",
+ " this.rubberband_context.strokeStyle = '#000000';\n",
+ "\n",
+ " this._resize_canvas = function (width, height, forward) {\n",
+ " if (forward) {\n",
+ " canvas_div.style.width = width + 'px';\n",
+ " canvas_div.style.height = height + 'px';\n",
+ " }\n",
+ " };\n",
+ "\n",
+ " // Disable right mouse context menu.\n",
+ " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ " });\n",
+ "\n",
+ " function set_focus() {\n",
+ " canvas.focus();\n",
+ " canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " window.setTimeout(set_focus, 100);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var toolbar = document.createElement('div');\n",
+ " toolbar.classList = 'mpl-toolbar';\n",
+ " this.root.appendChild(toolbar);\n",
+ "\n",
+ " function on_click_closure(name) {\n",
+ " return function (_event) {\n",
+ " return fig.toolbar_button_onclick(name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " function on_mouseover_closure(tooltip) {\n",
+ " return function (event) {\n",
+ " if (!event.currentTarget.disabled) {\n",
+ " return fig.toolbar_button_onmouseover(tooltip);\n",
+ " }\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " fig.buttons = {};\n",
+ " var buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'mpl-button-group';\n",
+ " for (var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " /* Instead of a spacer, we start a new button group. */\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ " buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'mpl-button-group';\n",
+ " continue;\n",
+ " }\n",
+ "\n",
+ " var button = (fig.buttons[name] = document.createElement('button'));\n",
+ " button.classList = 'mpl-widget';\n",
+ " button.setAttribute('role', 'button');\n",
+ " button.setAttribute('aria-disabled', 'false');\n",
+ " button.addEventListener('click', on_click_closure(method_name));\n",
+ " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+ "\n",
+ " var icon_img = document.createElement('img');\n",
+ " icon_img.src = '_images/' + image + '.png';\n",
+ " icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
+ " icon_img.alt = tooltip;\n",
+ " button.appendChild(icon_img);\n",
+ "\n",
+ " buttonGroup.appendChild(button);\n",
+ " }\n",
+ "\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ "\n",
+ " var fmt_picker = document.createElement('select');\n",
+ " fmt_picker.classList = 'mpl-widget';\n",
+ " toolbar.appendChild(fmt_picker);\n",
+ " this.format_dropdown = fmt_picker;\n",
+ "\n",
+ " for (var ind in mpl.extensions) {\n",
+ " var fmt = mpl.extensions[ind];\n",
+ " var option = document.createElement('option');\n",
+ " option.selected = fmt === mpl.default_extension;\n",
+ " option.innerHTML = fmt;\n",
+ " fmt_picker.appendChild(option);\n",
+ " }\n",
+ "\n",
+ " var status_bar = document.createElement('span');\n",
+ " status_bar.classList = 'mpl-message';\n",
+ " toolbar.appendChild(status_bar);\n",
+ " this.message = status_bar;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
+ " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+ " // which will in turn request a refresh of the image.\n",
+ " this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.send_message = function (type, properties) {\n",
+ " properties['type'] = type;\n",
+ " properties['figure_id'] = this.id;\n",
+ " this.ws.send(JSON.stringify(properties));\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.send_draw_message = function () {\n",
+ " if (!this.waiting) {\n",
+ " this.waiting = true;\n",
+ " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+ " var format_dropdown = fig.format_dropdown;\n",
+ " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+ " fig.ondownload(fig, format);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
+ " var size = msg['size'];\n",
+ " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
+ " fig._resize_canvas(size[0], size[1], msg['forward']);\n",
+ " fig.send_message('refresh', {});\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
+ " var x0 = msg['x0'] / fig.ratio;\n",
+ " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
+ " var x1 = msg['x1'] / fig.ratio;\n",
+ " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
+ " x0 = Math.floor(x0) + 0.5;\n",
+ " y0 = Math.floor(y0) + 0.5;\n",
+ " x1 = Math.floor(x1) + 0.5;\n",
+ " y1 = Math.floor(y1) + 0.5;\n",
+ " var min_x = Math.min(x0, x1);\n",
+ " var min_y = Math.min(y0, y1);\n",
+ " var width = Math.abs(x1 - x0);\n",
+ " var height = Math.abs(y1 - y0);\n",
+ "\n",
+ " fig.rubberband_context.clearRect(\n",
+ " 0,\n",
+ " 0,\n",
+ " fig.canvas.width / fig.ratio,\n",
+ " fig.canvas.height / fig.ratio\n",
+ " );\n",
+ "\n",
+ " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
+ " // Updates the figure title.\n",
+ " fig.header.textContent = msg['label'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
+ " var cursor = msg['cursor'];\n",
+ " switch (cursor) {\n",
+ " case 0:\n",
+ " cursor = 'pointer';\n",
+ " break;\n",
+ " case 1:\n",
+ " cursor = 'default';\n",
+ " break;\n",
+ " case 2:\n",
+ " cursor = 'crosshair';\n",
+ " break;\n",
+ " case 3:\n",
+ " cursor = 'move';\n",
+ " break;\n",
+ " }\n",
+ " fig.rubberband_canvas.style.cursor = cursor;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
+ " fig.message.textContent = msg['message'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
+ " // Request the server to send over a new figure.\n",
+ " fig.send_draw_message();\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
+ " fig.image_mode = msg['mode'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
+ " for (var key in msg) {\n",
+ " if (!(key in fig.buttons)) {\n",
+ " continue;\n",
+ " }\n",
+ " fig.buttons[key].disabled = !msg[key];\n",
+ " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
+ " if (msg['mode'] === 'PAN') {\n",
+ " fig.buttons['Pan'].classList.add('active');\n",
+ " fig.buttons['Zoom'].classList.remove('active');\n",
+ " } else if (msg['mode'] === 'ZOOM') {\n",
+ " fig.buttons['Pan'].classList.remove('active');\n",
+ " fig.buttons['Zoom'].classList.add('active');\n",
+ " } else {\n",
+ " fig.buttons['Pan'].classList.remove('active');\n",
+ " fig.buttons['Zoom'].classList.remove('active');\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function () {\n",
+ " // Called whenever the canvas gets updated.\n",
+ " this.send_message('ack', {});\n",
+ "};\n",
+ "\n",
+ "// A function to construct a web socket function for onmessage handling.\n",
+ "// Called in the figure constructor.\n",
+ "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
+ " return function socket_on_message(evt) {\n",
+ " if (evt.data instanceof Blob) {\n",
+ " /* FIXME: We get \"Resource interpreted as Image but\n",
+ " * transferred with MIME type text/plain:\" errors on\n",
+ " * Chrome. But how to set the MIME type? It doesn't seem\n",
+ " * to be part of the websocket stream */\n",
+ " evt.data.type = 'image/png';\n",
+ "\n",
+ " /* Free the memory for the previous frames */\n",
+ " if (fig.imageObj.src) {\n",
+ " (window.URL || window.webkitURL).revokeObjectURL(\n",
+ " fig.imageObj.src\n",
+ " );\n",
+ " }\n",
+ "\n",
+ " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+ " evt.data\n",
+ " );\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " } else if (\n",
+ " typeof evt.data === 'string' &&\n",
+ " evt.data.slice(0, 21) === 'data:image/png;base64'\n",
+ " ) {\n",
+ " fig.imageObj.src = evt.data;\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " var msg = JSON.parse(evt.data);\n",
+ " var msg_type = msg['type'];\n",
+ "\n",
+ " // Call the \"handle_{type}\" callback, which takes\n",
+ " // the figure and JSON message as its only arguments.\n",
+ " try {\n",
+ " var callback = fig['handle_' + msg_type];\n",
+ " } catch (e) {\n",
+ " console.log(\n",
+ " \"No handler for the '\" + msg_type + \"' message type: \",\n",
+ " msg\n",
+ " );\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " if (callback) {\n",
+ " try {\n",
+ " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+ " callback(fig, msg);\n",
+ " } catch (e) {\n",
+ " console.log(\n",
+ " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
+ " e,\n",
+ " e.stack,\n",
+ " msg\n",
+ " );\n",
+ " }\n",
+ " }\n",
+ " };\n",
+ "};\n",
+ "\n",
+ "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+ "mpl.findpos = function (e) {\n",
+ " //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+ " var targ;\n",
+ " if (!e) {\n",
+ " e = window.event;\n",
+ " }\n",
+ " if (e.target) {\n",
+ " targ = e.target;\n",
+ " } else if (e.srcElement) {\n",
+ " targ = e.srcElement;\n",
+ " }\n",
+ " if (targ.nodeType === 3) {\n",
+ " // defeat Safari bug\n",
+ " targ = targ.parentNode;\n",
+ " }\n",
+ "\n",
+ " // pageX,Y are the mouse positions relative to the document\n",
+ " var boundingRect = targ.getBoundingClientRect();\n",
+ " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
+ " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
+ "\n",
+ " return { x: x, y: y };\n",
+ "};\n",
+ "\n",
+ "/*\n",
+ " * return a copy of an object with only non-object keys\n",
+ " * we need this to avoid circular references\n",
+ " * http://stackoverflow.com/a/24161582/3208463\n",
+ " */\n",
+ "function simpleKeys(original) {\n",
+ " return Object.keys(original).reduce(function (obj, key) {\n",
+ " if (typeof original[key] !== 'object') {\n",
+ " obj[key] = original[key];\n",
+ " }\n",
+ " return obj;\n",
+ " }, {});\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.mouse_event = function (event, name) {\n",
+ " var canvas_pos = mpl.findpos(event);\n",
+ "\n",
+ " if (name === 'button_press') {\n",
+ " this.canvas.focus();\n",
+ " this.canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " var x = canvas_pos.x * this.ratio;\n",
+ " var y = canvas_pos.y * this.ratio;\n",
+ "\n",
+ " this.send_message(name, {\n",
+ " x: x,\n",
+ " y: y,\n",
+ " button: event.button,\n",
+ " step: event.step,\n",
+ " guiEvent: simpleKeys(event),\n",
+ " });\n",
+ "\n",
+ " /* This prevents the web browser from automatically changing to\n",
+ " * the text insertion cursor when the button is pressed. We want\n",
+ " * to control all of the cursor setting manually through the\n",
+ " * 'cursor' event from matplotlib */\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
+ " // Handle any extra behaviour associated with a key event\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.key_event = function (event, name) {\n",
+ " // Prevent repeat events\n",
+ " if (name === 'key_press') {\n",
+ " if (event.which === this._key) {\n",
+ " return;\n",
+ " } else {\n",
+ " this._key = event.which;\n",
+ " }\n",
+ " }\n",
+ " if (name === 'key_release') {\n",
+ " this._key = null;\n",
+ " }\n",
+ "\n",
+ " var value = '';\n",
+ " if (event.ctrlKey && event.which !== 17) {\n",
+ " value += 'ctrl+';\n",
+ " }\n",
+ " if (event.altKey && event.which !== 18) {\n",
+ " value += 'alt+';\n",
+ " }\n",
+ " if (event.shiftKey && event.which !== 16) {\n",
+ " value += 'shift+';\n",
+ " }\n",
+ "\n",
+ " value += 'k';\n",
+ " value += event.which.toString();\n",
+ "\n",
+ " this._key_event_extra(event, name);\n",
+ "\n",
+ " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
+ " return false;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
+ " if (name === 'download') {\n",
+ " this.handle_save(this, null);\n",
+ " } else {\n",
+ " this.send_message('toolbar_button', { name: name });\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
+ " this.message.textContent = tooltip;\n",
+ "};\n",
+ "\n",
+ "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
+ "// prettier-ignore\n",
+ "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
+ "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+ "\n",
+ "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
+ "\n",
+ "mpl.default_extension = \"png\";/* global mpl */\n",
+ "\n",
+ "var comm_websocket_adapter = function (comm) {\n",
+ " // Create a \"websocket\"-like object which calls the given IPython comm\n",
+ " // object with the appropriate methods. Currently this is a non binary\n",
+ " // socket, so there is still some room for performance tuning.\n",
+ " var ws = {};\n",
+ "\n",
+ " ws.close = function () {\n",
+ " comm.close();\n",
+ " };\n",
+ " ws.send = function (m) {\n",
+ " //console.log('sending', m);\n",
+ " comm.send(m);\n",
+ " };\n",
+ " // Register the callback with on_msg.\n",
+ " comm.on_msg(function (msg) {\n",
+ " //console.log('receiving', msg['content']['data'], msg);\n",
+ " // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
+ " ws.onmessage(msg['content']['data']);\n",
+ " });\n",
+ " return ws;\n",
+ "};\n",
+ "\n",
+ "mpl.mpl_figure_comm = function (comm, msg) {\n",
+ " // This is the function which gets called when the mpl process\n",
+ " // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+ "\n",
+ " var id = msg.content.data.id;\n",
+ " // Get hold of the div created by the display call when the Comm\n",
+ " // socket was opened in Python.\n",
+ " var element = document.getElementById(id);\n",
+ " var ws_proxy = comm_websocket_adapter(comm);\n",
+ "\n",
+ " function ondownload(figure, _format) {\n",
+ " window.open(figure.canvas.toDataURL());\n",
+ " }\n",
+ "\n",
+ " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
+ "\n",
+ " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+ " // web socket which is closed, not our websocket->open comm proxy.\n",
+ " ws_proxy.onopen();\n",
+ "\n",
+ " fig.parent_element = element;\n",
+ " fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+ " if (!fig.cell_info) {\n",
+ " console.error('Failed to find cell for figure', id, fig);\n",
+ " return;\n",
+ " }\n",
+ " fig.cell_info[0].output_area.element.on(\n",
+ " 'cleared',\n",
+ " { fig: fig },\n",
+ " fig._remove_fig_handler\n",
+ " );\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
+ " var width = fig.canvas.width / fig.ratio;\n",
+ " fig.cell_info[0].output_area.element.off(\n",
+ " 'cleared',\n",
+ " fig._remove_fig_handler\n",
+ " );\n",
+ " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
+ "\n",
+ " // Update the output cell to use the data from the current canvas.\n",
+ " fig.push_to_output();\n",
+ " var dataURL = fig.canvas.toDataURL();\n",
+ " // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+ " // the notebook keyboard shortcuts fail.\n",
+ " IPython.keyboard_manager.enable();\n",
+ " fig.parent_element.innerHTML =\n",
+ " '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ " fig.close_ws(fig, msg);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
+ " fig.send_message('closing', msg);\n",
+ " // fig.ws.close()\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
+ " // Turn the data on the canvas into data in the output cell.\n",
+ " var width = this.canvas.width / this.ratio;\n",
+ " var dataURL = this.canvas.toDataURL();\n",
+ " this.cell_info[1]['text/html'] =\n",
+ " '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function () {\n",
+ " // Tell IPython that the notebook contents must change.\n",
+ " IPython.notebook.set_dirty(true);\n",
+ " this.send_message('ack', {});\n",
+ " var fig = this;\n",
+ " // Wait a second, then push the new image to the DOM so\n",
+ " // that it is saved nicely (might be nice to debounce this).\n",
+ " setTimeout(function () {\n",
+ " fig.push_to_output();\n",
+ " }, 1000);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var toolbar = document.createElement('div');\n",
+ " toolbar.classList = 'btn-toolbar';\n",
+ " this.root.appendChild(toolbar);\n",
+ "\n",
+ " function on_click_closure(name) {\n",
+ " return function (_event) {\n",
+ " return fig.toolbar_button_onclick(name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " function on_mouseover_closure(tooltip) {\n",
+ " return function (event) {\n",
+ " if (!event.currentTarget.disabled) {\n",
+ " return fig.toolbar_button_onmouseover(tooltip);\n",
+ " }\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " fig.buttons = {};\n",
+ " var buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'btn-group';\n",
+ " var button;\n",
+ " for (var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " /* Instead of a spacer, we start a new button group. */\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ " buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'btn-group';\n",
+ " continue;\n",
+ " }\n",
+ "\n",
+ " button = fig.buttons[name] = document.createElement('button');\n",
+ " button.classList = 'btn btn-default';\n",
+ " button.href = '#';\n",
+ " button.title = name;\n",
+ " button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
+ " button.addEventListener('click', on_click_closure(method_name));\n",
+ " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+ " buttonGroup.appendChild(button);\n",
+ " }\n",
+ "\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ "\n",
+ " // Add the status bar.\n",
+ " var status_bar = document.createElement('span');\n",
+ " status_bar.classList = 'mpl-message pull-right';\n",
+ " toolbar.appendChild(status_bar);\n",
+ " this.message = status_bar;\n",
+ "\n",
+ " // Add the close button to the window.\n",
+ " var buttongrp = document.createElement('div');\n",
+ " buttongrp.classList = 'btn-group inline pull-right';\n",
+ " button = document.createElement('button');\n",
+ " button.classList = 'btn btn-mini btn-primary';\n",
+ " button.href = '#';\n",
+ " button.title = 'Stop Interaction';\n",
+ " button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
+ " button.addEventListener('click', function (_evt) {\n",
+ " fig.handle_close(fig, {});\n",
+ " });\n",
+ " button.addEventListener(\n",
+ " 'mouseover',\n",
+ " on_mouseover_closure('Stop Interaction')\n",
+ " );\n",
+ " buttongrp.appendChild(button);\n",
+ " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
+ " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
+ " var fig = event.data.fig;\n",
+ " if (event.target !== this) {\n",
+ " // Ignore bubbled events from children.\n",
+ " return;\n",
+ " }\n",
+ " fig.close_ws(fig, {});\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function (el) {\n",
+ " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
+ " // this is important to make the div 'focusable\n",
+ " el.setAttribute('tabindex', 0);\n",
+ " // reach out to IPython and tell the keyboard manager to turn it's self\n",
+ " // off when our div gets focus\n",
+ "\n",
+ " // location in version 3\n",
+ " if (IPython.notebook.keyboard_manager) {\n",
+ " IPython.notebook.keyboard_manager.register_events(el);\n",
+ " } else {\n",
+ " // location in version 2\n",
+ " IPython.keyboard_manager.register_events(el);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
+ " var manager = IPython.notebook.keyboard_manager;\n",
+ " if (!manager) {\n",
+ " manager = IPython.keyboard_manager;\n",
+ " }\n",
+ "\n",
+ " // Check for shift+enter\n",
+ " if (event.shiftKey && event.which === 13) {\n",
+ " this.canvas_div.blur();\n",
+ " // select the cell after this one\n",
+ " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
+ " IPython.notebook.select(index + 1);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+ " fig.ondownload(fig, null);\n",
+ "};\n",
+ "\n",
+ "mpl.find_output_cell = function (html_output) {\n",
+ " // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+ " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+ " // IPython event is triggered only after the cells have been serialised, which for\n",
+ " // our purposes (turning an active figure into a static one), is too late.\n",
+ " var cells = IPython.notebook.get_cells();\n",
+ " var ncells = cells.length;\n",
+ " for (var i = 0; i < ncells; i++) {\n",
+ " var cell = cells[i];\n",
+ " if (cell.cell_type === 'code') {\n",
+ " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
+ " var data = cell.output_area.outputs[j];\n",
+ " if (data.data) {\n",
+ " // IPython >= 3 moved mimebundle to data attribute of output\n",
+ " data = data.data;\n",
+ " }\n",
+ " if (data['text/html'] === html_output) {\n",
+ " return [cell, data, j];\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "// Register the function which deals with the matplotlib target/channel.\n",
+ "// The kernel may be null if the page has been refreshed.\n",
+ "if (IPython.notebook.kernel !== null) {\n",
+ " IPython.notebook.kernel.comm_manager.register_target(\n",
+ " 'matplotlib',\n",
+ " mpl.mpl_figure_comm\n",
+ " );\n",
+ "}\n"
+ ],
"text/plain": [
- "<Figure size 576x576 with 2 Axes>"
+ "<IPython.core.display.Javascript object>"
]
},
- "metadata": {
- "needs_background": "light"
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
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\" width=\"800\">"
+ ],
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ]
},
+ "metadata": {},
"output_type": "display_data"
}
],
@@ -331,7 +1290,7 @@
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": 7,
"id": "0837b3ff",
"metadata": {},
"outputs": [],
@@ -341,7 +1300,7 @@
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 8,
"id": "8798f857",
"metadata": {},
"outputs": [
@@ -351,7 +1310,7 @@
"GaussianMixture(max_iter=20, n_components=3)"
]
},
- "execution_count": 7,
+ "execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
@@ -370,19 +1329,19 @@
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": 9,
"id": "fb5796e5",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "array([[ 4.99888254, -1.99794087],\n",
- " [ 0.95551226, 4.96478507],\n",
- " [-5.0404056 , -1.08228231]])"
+ "array([[-5.00533402, -1.00291721],\n",
+ " [ 4.98736078, -1.99324473],\n",
+ " [ 0.99263505, 4.95370197]])"
]
},
- "execution_count": 8,
+ "execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
@@ -393,24 +1352,24 @@
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": 10,
"id": "182904d1",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "array([[[ 0.20670445, 0.10147787],\n",
- " [ 0.10147787, 0.20500901]],\n",
+ "array([[[ 1.97696177, -0.14298004],\n",
+ " [-0.14298004, 5.08432238]],\n",
"\n",
- " [[ 0.97604778, 0.48471245],\n",
- " [ 0.48471245, 1.0206679 ]],\n",
+ " [[ 0.19127883, 0.09340703],\n",
+ " [ 0.09340703, 0.18650429]],\n",
"\n",
- " [[ 1.9641727 , -0.01924111],\n",
- " [-0.01924111, 5.0262459 ]]])"
+ " [[ 1.00348273, 0.47652348],\n",
+ " [ 0.47652348, 0.98154818]]])"
]
},
- "execution_count": 9,
+ "execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
@@ -421,17 +1380,17 @@
},
{
"cell_type": "code",
- "execution_count": 10,
+ "execution_count": 11,
"id": "2faa1f72",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "array([0.33333333, 0.3341058 , 0.33256087])"
+ "array([0.33306256, 0.33333333, 0.33360411])"
]
},
- "execution_count": 10,
+ "execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
@@ -450,7 +1409,7 @@
},
{
"cell_type": "code",
- "execution_count": 14,
+ "execution_count": 12,
"id": "cc8fc1f1",
"metadata": {},
"outputs": [],
@@ -468,7 +1427,7 @@
},
{
"cell_type": "code",
- "execution_count": 15,
+ "execution_count": 13,
"id": "88982b21",
"metadata": {},
"outputs": [],
@@ -478,107 +1437,2023 @@
},
{
"cell_type": "code",
- "execution_count": 16,
+ "execution_count": 14,
"id": "333581b5",
"metadata": {},
"outputs": [
{
"data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 1152x1152 with 4 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "fig, ax = plt.subplots(figsize=(16, 16), ncols=2)\n",
- "data.plot.scatter(x=\"x\", y=\"y\", c=\"guess\", colormap='viridis', ax=ax[0])\n",
- "data.plot.scatter(x=\"x\", y=\"y\", c=\"source\", colormap='viridis', ax=ax[1])\n",
- "ax[0].set(xlabel=\"x\", ylabel=r\"y\", title=\"Guessed source\")\n",
- "ax[1].set(xlabel=\"x\", ylabel=r\"y\", title=\"True association\")\n",
- "plt.show()"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "9b1363ec",
- "metadata": {},
- "source": [
- "Note that if the sample clusters were not \"blobs\" of data, but were in concentric circles, the assumption of this method would be false and the method would simply not work well. This is why it is important to understand the underlying assumptions made in the method."
- ]
- },
- {
- "cell_type": "markdown",
- "id": "7076f779",
- "metadata": {},
- "source": [
- "## K-Means\n",
- "\n",
- "Another common method used for clustering is the K-Means, on which one simply tries to find the cluster centers which minimize in-cluster distances (in an Euclidean sense) while maximizing distances between the centers. It can be shown that this method is a special case of the Gaussian Mixture Model when the covariance matrices are diagonal, which would mean that within each blob, there is no correlation between the variables (see https://en.wikipedia.org/wiki/K-means_clustering#Gaussian_mixture_model and references).\n",
- "\n",
- "While this is an approximation of the GMM model, it is still a very useful approach, since there are faster algorithms to achieve the clustering than for GMMs.\n",
- "\n",
- "The scikit-learn module also provides an easy-to-use implementation of this algorithm:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 18,
- "id": "2f280e1d",
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
+ "application/javascript": [
+ "/* Put everything inside the global mpl namespace */\n",
+ "/* global mpl */\n",
+ "window.mpl = {};\n",
+ "\n",
+ "mpl.get_websocket_type = function () {\n",
+ " if (typeof WebSocket !== 'undefined') {\n",
+ " return WebSocket;\n",
+ " } else if (typeof MozWebSocket !== 'undefined') {\n",
+ " return MozWebSocket;\n",
+ " } else {\n",
+ " alert(\n",
+ " 'Your browser does not have WebSocket support. ' +\n",
+ " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+ " 'Firefox 4 and 5 are also supported but you ' +\n",
+ " 'have to enable WebSockets in about:config.'\n",
+ " );\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
+ " this.id = figure_id;\n",
+ "\n",
+ " this.ws = websocket;\n",
+ "\n",
+ " this.supports_binary = this.ws.binaryType !== undefined;\n",
+ "\n",
+ " if (!this.supports_binary) {\n",
+ " var warnings = document.getElementById('mpl-warnings');\n",
+ " if (warnings) {\n",
+ " warnings.style.display = 'block';\n",
+ " warnings.textContent =\n",
+ " 'This browser does not support binary websocket messages. ' +\n",
+ " 'Performance may be slow.';\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.imageObj = new Image();\n",
+ "\n",
+ " this.context = undefined;\n",
+ " this.message = undefined;\n",
+ " this.canvas = undefined;\n",
+ " this.rubberband_canvas = undefined;\n",
+ " this.rubberband_context = undefined;\n",
+ " this.format_dropdown = undefined;\n",
+ "\n",
+ " this.image_mode = 'full';\n",
+ "\n",
+ " this.root = document.createElement('div');\n",
+ " this.root.setAttribute('style', 'display: inline-block');\n",
+ " this._root_extra_style(this.root);\n",
+ "\n",
+ " parent_element.appendChild(this.root);\n",
+ "\n",
+ " this._init_header(this);\n",
+ " this._init_canvas(this);\n",
+ " this._init_toolbar(this);\n",
+ "\n",
+ " var fig = this;\n",
+ "\n",
+ " this.waiting = false;\n",
+ "\n",
+ " this.ws.onopen = function () {\n",
+ " fig.send_message('supports_binary', { value: fig.supports_binary });\n",
+ " fig.send_message('send_image_mode', {});\n",
+ " if (fig.ratio !== 1) {\n",
+ " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
+ " }\n",
+ " fig.send_message('refresh', {});\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onload = function () {\n",
+ " if (fig.image_mode === 'full') {\n",
+ " // Full images could contain transparency (where diff images\n",
+ " // almost always do), so we need to clear the canvas so that\n",
+ " // there is no ghosting.\n",
+ " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+ " }\n",
+ " fig.context.drawImage(fig.imageObj, 0, 0);\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onunload = function () {\n",
+ " fig.ws.close();\n",
+ " };\n",
+ "\n",
+ " this.ws.onmessage = this._make_on_message_function(this);\n",
+ "\n",
+ " this.ondownload = ondownload;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_header = function () {\n",
+ " var titlebar = document.createElement('div');\n",
+ " titlebar.classList =\n",
+ " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
+ " var titletext = document.createElement('div');\n",
+ " titletext.classList = 'ui-dialog-title';\n",
+ " titletext.setAttribute(\n",
+ " 'style',\n",
+ " 'width: 100%; text-align: center; padding: 3px;'\n",
+ " );\n",
+ " titlebar.appendChild(titletext);\n",
+ " this.root.appendChild(titlebar);\n",
+ " this.header = titletext;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
+ "\n",
+ "mpl.figure.prototype._init_canvas = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var canvas_div = (this.canvas_div = document.createElement('div'));\n",
+ " canvas_div.setAttribute(\n",
+ " 'style',\n",
+ " 'border: 1px solid #ddd;' +\n",
+ " 'box-sizing: content-box;' +\n",
+ " 'clear: both;' +\n",
+ " 'min-height: 1px;' +\n",
+ " 'min-width: 1px;' +\n",
+ " 'outline: 0;' +\n",
+ " 'overflow: hidden;' +\n",
+ " 'position: relative;' +\n",
+ " 'resize: both;'\n",
+ " );\n",
+ "\n",
+ " function on_keyboard_event_closure(name) {\n",
+ " return function (event) {\n",
+ " return fig.key_event(event, name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " canvas_div.addEventListener(\n",
+ " 'keydown',\n",
+ " on_keyboard_event_closure('key_press')\n",
+ " );\n",
+ " canvas_div.addEventListener(\n",
+ " 'keyup',\n",
+ " on_keyboard_event_closure('key_release')\n",
+ " );\n",
+ "\n",
+ " this._canvas_extra_style(canvas_div);\n",
+ " this.root.appendChild(canvas_div);\n",
+ "\n",
+ " var canvas = (this.canvas = document.createElement('canvas'));\n",
+ " canvas.classList.add('mpl-canvas');\n",
+ " canvas.setAttribute('style', 'box-sizing: content-box;');\n",
+ "\n",
+ " this.context = canvas.getContext('2d');\n",
+ "\n",
+ " var backingStore =\n",
+ " this.context.backingStorePixelRatio ||\n",
+ " this.context.webkitBackingStorePixelRatio ||\n",
+ " this.context.mozBackingStorePixelRatio ||\n",
+ " this.context.msBackingStorePixelRatio ||\n",
+ " this.context.oBackingStorePixelRatio ||\n",
+ " this.context.backingStorePixelRatio ||\n",
+ " 1;\n",
+ "\n",
+ " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+ "\n",
+ " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
+ " 'canvas'\n",
+ " ));\n",
+ " rubberband_canvas.setAttribute(\n",
+ " 'style',\n",
+ " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
+ " );\n",
+ "\n",
+ " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
+ " if (this.ResizeObserver === undefined) {\n",
+ " if (window.ResizeObserver !== undefined) {\n",
+ " this.ResizeObserver = window.ResizeObserver;\n",
+ " } else {\n",
+ " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
+ " this.ResizeObserver = obs.ResizeObserver;\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
+ " var nentries = entries.length;\n",
+ " for (var i = 0; i < nentries; i++) {\n",
+ " var entry = entries[i];\n",
+ " var width, height;\n",
+ " if (entry.contentBoxSize) {\n",
+ " if (entry.contentBoxSize instanceof Array) {\n",
+ " // Chrome 84 implements new version of spec.\n",
+ " width = entry.contentBoxSize[0].inlineSize;\n",
+ " height = entry.contentBoxSize[0].blockSize;\n",
+ " } else {\n",
+ " // Firefox implements old version of spec.\n",
+ " width = entry.contentBoxSize.inlineSize;\n",
+ " height = entry.contentBoxSize.blockSize;\n",
+ " }\n",
+ " } else {\n",
+ " // Chrome <84 implements even older version of spec.\n",
+ " width = entry.contentRect.width;\n",
+ " height = entry.contentRect.height;\n",
+ " }\n",
+ "\n",
+ " // Keep the size of the canvas and rubber band canvas in sync with\n",
+ " // the canvas container.\n",
+ " if (entry.devicePixelContentBoxSize) {\n",
+ " // Chrome 84 implements new version of spec.\n",
+ " canvas.setAttribute(\n",
+ " 'width',\n",
+ " entry.devicePixelContentBoxSize[0].inlineSize\n",
+ " );\n",
+ " canvas.setAttribute(\n",
+ " 'height',\n",
+ " entry.devicePixelContentBoxSize[0].blockSize\n",
+ " );\n",
+ " } else {\n",
+ " canvas.setAttribute('width', width * fig.ratio);\n",
+ " canvas.setAttribute('height', height * fig.ratio);\n",
+ " }\n",
+ " canvas.setAttribute(\n",
+ " 'style',\n",
+ " 'width: ' + width + 'px; height: ' + height + 'px;'\n",
+ " );\n",
+ "\n",
+ " rubberband_canvas.setAttribute('width', width);\n",
+ " rubberband_canvas.setAttribute('height', height);\n",
+ "\n",
+ " // And update the size in Python. We ignore the initial 0/0 size\n",
+ " // that occurs as the element is placed into the DOM, which should\n",
+ " // otherwise not happen due to the minimum size styling.\n",
+ " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
+ " fig.request_resize(width, height);\n",
+ " }\n",
+ " }\n",
+ " });\n",
+ " this.resizeObserverInstance.observe(canvas_div);\n",
+ "\n",
+ " function on_mouse_event_closure(name) {\n",
+ " return function (event) {\n",
+ " return fig.mouse_event(event, name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mousedown',\n",
+ " on_mouse_event_closure('button_press')\n",
+ " );\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseup',\n",
+ " on_mouse_event_closure('button_release')\n",
+ " );\n",
+ " // Throttle sequential mouse events to 1 every 20ms.\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mousemove',\n",
+ " on_mouse_event_closure('motion_notify')\n",
+ " );\n",
+ "\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseenter',\n",
+ " on_mouse_event_closure('figure_enter')\n",
+ " );\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseleave',\n",
+ " on_mouse_event_closure('figure_leave')\n",
+ " );\n",
+ "\n",
+ " canvas_div.addEventListener('wheel', function (event) {\n",
+ " if (event.deltaY < 0) {\n",
+ " event.step = 1;\n",
+ " } else {\n",
+ " event.step = -1;\n",
+ " }\n",
+ " on_mouse_event_closure('scroll')(event);\n",
+ " });\n",
+ "\n",
+ " canvas_div.appendChild(canvas);\n",
+ " canvas_div.appendChild(rubberband_canvas);\n",
+ "\n",
+ " this.rubberband_context = rubberband_canvas.getContext('2d');\n",
+ " this.rubberband_context.strokeStyle = '#000000';\n",
+ "\n",
+ " this._resize_canvas = function (width, height, forward) {\n",
+ " if (forward) {\n",
+ " canvas_div.style.width = width + 'px';\n",
+ " canvas_div.style.height = height + 'px';\n",
+ " }\n",
+ " };\n",
+ "\n",
+ " // Disable right mouse context menu.\n",
+ " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ " });\n",
+ "\n",
+ " function set_focus() {\n",
+ " canvas.focus();\n",
+ " canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " window.setTimeout(set_focus, 100);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var toolbar = document.createElement('div');\n",
+ " toolbar.classList = 'mpl-toolbar';\n",
+ " this.root.appendChild(toolbar);\n",
+ "\n",
+ " function on_click_closure(name) {\n",
+ " return function (_event) {\n",
+ " return fig.toolbar_button_onclick(name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " function on_mouseover_closure(tooltip) {\n",
+ " return function (event) {\n",
+ " if (!event.currentTarget.disabled) {\n",
+ " return fig.toolbar_button_onmouseover(tooltip);\n",
+ " }\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " fig.buttons = {};\n",
+ " var buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'mpl-button-group';\n",
+ " for (var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " /* Instead of a spacer, we start a new button group. */\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ " buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'mpl-button-group';\n",
+ " continue;\n",
+ " }\n",
+ "\n",
+ " var button = (fig.buttons[name] = document.createElement('button'));\n",
+ " button.classList = 'mpl-widget';\n",
+ " button.setAttribute('role', 'button');\n",
+ " button.setAttribute('aria-disabled', 'false');\n",
+ " button.addEventListener('click', on_click_closure(method_name));\n",
+ " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+ "\n",
+ " var icon_img = document.createElement('img');\n",
+ " icon_img.src = '_images/' + image + '.png';\n",
+ " icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
+ " icon_img.alt = tooltip;\n",
+ " button.appendChild(icon_img);\n",
+ "\n",
+ " buttonGroup.appendChild(button);\n",
+ " }\n",
+ "\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ "\n",
+ " var fmt_picker = document.createElement('select');\n",
+ " fmt_picker.classList = 'mpl-widget';\n",
+ " toolbar.appendChild(fmt_picker);\n",
+ " this.format_dropdown = fmt_picker;\n",
+ "\n",
+ " for (var ind in mpl.extensions) {\n",
+ " var fmt = mpl.extensions[ind];\n",
+ " var option = document.createElement('option');\n",
+ " option.selected = fmt === mpl.default_extension;\n",
+ " option.innerHTML = fmt;\n",
+ " fmt_picker.appendChild(option);\n",
+ " }\n",
+ "\n",
+ " var status_bar = document.createElement('span');\n",
+ " status_bar.classList = 'mpl-message';\n",
+ " toolbar.appendChild(status_bar);\n",
+ " this.message = status_bar;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
+ " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+ " // which will in turn request a refresh of the image.\n",
+ " this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.send_message = function (type, properties) {\n",
+ " properties['type'] = type;\n",
+ " properties['figure_id'] = this.id;\n",
+ " this.ws.send(JSON.stringify(properties));\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.send_draw_message = function () {\n",
+ " if (!this.waiting) {\n",
+ " this.waiting = true;\n",
+ " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+ " var format_dropdown = fig.format_dropdown;\n",
+ " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+ " fig.ondownload(fig, format);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
+ " var size = msg['size'];\n",
+ " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
+ " fig._resize_canvas(size[0], size[1], msg['forward']);\n",
+ " fig.send_message('refresh', {});\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
+ " var x0 = msg['x0'] / fig.ratio;\n",
+ " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
+ " var x1 = msg['x1'] / fig.ratio;\n",
+ " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
+ " x0 = Math.floor(x0) + 0.5;\n",
+ " y0 = Math.floor(y0) + 0.5;\n",
+ " x1 = Math.floor(x1) + 0.5;\n",
+ " y1 = Math.floor(y1) + 0.5;\n",
+ " var min_x = Math.min(x0, x1);\n",
+ " var min_y = Math.min(y0, y1);\n",
+ " var width = Math.abs(x1 - x0);\n",
+ " var height = Math.abs(y1 - y0);\n",
+ "\n",
+ " fig.rubberband_context.clearRect(\n",
+ " 0,\n",
+ " 0,\n",
+ " fig.canvas.width / fig.ratio,\n",
+ " fig.canvas.height / fig.ratio\n",
+ " );\n",
+ "\n",
+ " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
+ " // Updates the figure title.\n",
+ " fig.header.textContent = msg['label'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
+ " var cursor = msg['cursor'];\n",
+ " switch (cursor) {\n",
+ " case 0:\n",
+ " cursor = 'pointer';\n",
+ " break;\n",
+ " case 1:\n",
+ " cursor = 'default';\n",
+ " break;\n",
+ " case 2:\n",
+ " cursor = 'crosshair';\n",
+ " break;\n",
+ " case 3:\n",
+ " cursor = 'move';\n",
+ " break;\n",
+ " }\n",
+ " fig.rubberband_canvas.style.cursor = cursor;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
+ " fig.message.textContent = msg['message'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
+ " // Request the server to send over a new figure.\n",
+ " fig.send_draw_message();\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
+ " fig.image_mode = msg['mode'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
+ " for (var key in msg) {\n",
+ " if (!(key in fig.buttons)) {\n",
+ " continue;\n",
+ " }\n",
+ " fig.buttons[key].disabled = !msg[key];\n",
+ " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
+ " if (msg['mode'] === 'PAN') {\n",
+ " fig.buttons['Pan'].classList.add('active');\n",
+ " fig.buttons['Zoom'].classList.remove('active');\n",
+ " } else if (msg['mode'] === 'ZOOM') {\n",
+ " fig.buttons['Pan'].classList.remove('active');\n",
+ " fig.buttons['Zoom'].classList.add('active');\n",
+ " } else {\n",
+ " fig.buttons['Pan'].classList.remove('active');\n",
+ " fig.buttons['Zoom'].classList.remove('active');\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function () {\n",
+ " // Called whenever the canvas gets updated.\n",
+ " this.send_message('ack', {});\n",
+ "};\n",
+ "\n",
+ "// A function to construct a web socket function for onmessage handling.\n",
+ "// Called in the figure constructor.\n",
+ "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
+ " return function socket_on_message(evt) {\n",
+ " if (evt.data instanceof Blob) {\n",
+ " /* FIXME: We get \"Resource interpreted as Image but\n",
+ " * transferred with MIME type text/plain:\" errors on\n",
+ " * Chrome. But how to set the MIME type? It doesn't seem\n",
+ " * to be part of the websocket stream */\n",
+ " evt.data.type = 'image/png';\n",
+ "\n",
+ " /* Free the memory for the previous frames */\n",
+ " if (fig.imageObj.src) {\n",
+ " (window.URL || window.webkitURL).revokeObjectURL(\n",
+ " fig.imageObj.src\n",
+ " );\n",
+ " }\n",
+ "\n",
+ " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+ " evt.data\n",
+ " );\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " } else if (\n",
+ " typeof evt.data === 'string' &&\n",
+ " evt.data.slice(0, 21) === 'data:image/png;base64'\n",
+ " ) {\n",
+ " fig.imageObj.src = evt.data;\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " var msg = JSON.parse(evt.data);\n",
+ " var msg_type = msg['type'];\n",
+ "\n",
+ " // Call the \"handle_{type}\" callback, which takes\n",
+ " // the figure and JSON message as its only arguments.\n",
+ " try {\n",
+ " var callback = fig['handle_' + msg_type];\n",
+ " } catch (e) {\n",
+ " console.log(\n",
+ " \"No handler for the '\" + msg_type + \"' message type: \",\n",
+ " msg\n",
+ " );\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " if (callback) {\n",
+ " try {\n",
+ " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+ " callback(fig, msg);\n",
+ " } catch (e) {\n",
+ " console.log(\n",
+ " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
+ " e,\n",
+ " e.stack,\n",
+ " msg\n",
+ " );\n",
+ " }\n",
+ " }\n",
+ " };\n",
+ "};\n",
+ "\n",
+ "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+ "mpl.findpos = function (e) {\n",
+ " //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+ " var targ;\n",
+ " if (!e) {\n",
+ " e = window.event;\n",
+ " }\n",
+ " if (e.target) {\n",
+ " targ = e.target;\n",
+ " } else if (e.srcElement) {\n",
+ " targ = e.srcElement;\n",
+ " }\n",
+ " if (targ.nodeType === 3) {\n",
+ " // defeat Safari bug\n",
+ " targ = targ.parentNode;\n",
+ " }\n",
+ "\n",
+ " // pageX,Y are the mouse positions relative to the document\n",
+ " var boundingRect = targ.getBoundingClientRect();\n",
+ " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
+ " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
+ "\n",
+ " return { x: x, y: y };\n",
+ "};\n",
+ "\n",
+ "/*\n",
+ " * return a copy of an object with only non-object keys\n",
+ " * we need this to avoid circular references\n",
+ " * http://stackoverflow.com/a/24161582/3208463\n",
+ " */\n",
+ "function simpleKeys(original) {\n",
+ " return Object.keys(original).reduce(function (obj, key) {\n",
+ " if (typeof original[key] !== 'object') {\n",
+ " obj[key] = original[key];\n",
+ " }\n",
+ " return obj;\n",
+ " }, {});\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.mouse_event = function (event, name) {\n",
+ " var canvas_pos = mpl.findpos(event);\n",
+ "\n",
+ " if (name === 'button_press') {\n",
+ " this.canvas.focus();\n",
+ " this.canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " var x = canvas_pos.x * this.ratio;\n",
+ " var y = canvas_pos.y * this.ratio;\n",
+ "\n",
+ " this.send_message(name, {\n",
+ " x: x,\n",
+ " y: y,\n",
+ " button: event.button,\n",
+ " step: event.step,\n",
+ " guiEvent: simpleKeys(event),\n",
+ " });\n",
+ "\n",
+ " /* This prevents the web browser from automatically changing to\n",
+ " * the text insertion cursor when the button is pressed. We want\n",
+ " * to control all of the cursor setting manually through the\n",
+ " * 'cursor' event from matplotlib */\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
+ " // Handle any extra behaviour associated with a key event\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.key_event = function (event, name) {\n",
+ " // Prevent repeat events\n",
+ " if (name === 'key_press') {\n",
+ " if (event.which === this._key) {\n",
+ " return;\n",
+ " } else {\n",
+ " this._key = event.which;\n",
+ " }\n",
+ " }\n",
+ " if (name === 'key_release') {\n",
+ " this._key = null;\n",
+ " }\n",
+ "\n",
+ " var value = '';\n",
+ " if (event.ctrlKey && event.which !== 17) {\n",
+ " value += 'ctrl+';\n",
+ " }\n",
+ " if (event.altKey && event.which !== 18) {\n",
+ " value += 'alt+';\n",
+ " }\n",
+ " if (event.shiftKey && event.which !== 16) {\n",
+ " value += 'shift+';\n",
+ " }\n",
+ "\n",
+ " value += 'k';\n",
+ " value += event.which.toString();\n",
+ "\n",
+ " this._key_event_extra(event, name);\n",
+ "\n",
+ " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
+ " return false;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
+ " if (name === 'download') {\n",
+ " this.handle_save(this, null);\n",
+ " } else {\n",
+ " this.send_message('toolbar_button', { name: name });\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
+ " this.message.textContent = tooltip;\n",
+ "};\n",
+ "\n",
+ "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
+ "// prettier-ignore\n",
+ "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
+ "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+ "\n",
+ "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
+ "\n",
+ "mpl.default_extension = \"png\";/* global mpl */\n",
+ "\n",
+ "var comm_websocket_adapter = function (comm) {\n",
+ " // Create a \"websocket\"-like object which calls the given IPython comm\n",
+ " // object with the appropriate methods. Currently this is a non binary\n",
+ " // socket, so there is still some room for performance tuning.\n",
+ " var ws = {};\n",
+ "\n",
+ " ws.close = function () {\n",
+ " comm.close();\n",
+ " };\n",
+ " ws.send = function (m) {\n",
+ " //console.log('sending', m);\n",
+ " comm.send(m);\n",
+ " };\n",
+ " // Register the callback with on_msg.\n",
+ " comm.on_msg(function (msg) {\n",
+ " //console.log('receiving', msg['content']['data'], msg);\n",
+ " // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
+ " ws.onmessage(msg['content']['data']);\n",
+ " });\n",
+ " return ws;\n",
+ "};\n",
+ "\n",
+ "mpl.mpl_figure_comm = function (comm, msg) {\n",
+ " // This is the function which gets called when the mpl process\n",
+ " // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+ "\n",
+ " var id = msg.content.data.id;\n",
+ " // Get hold of the div created by the display call when the Comm\n",
+ " // socket was opened in Python.\n",
+ " var element = document.getElementById(id);\n",
+ " var ws_proxy = comm_websocket_adapter(comm);\n",
+ "\n",
+ " function ondownload(figure, _format) {\n",
+ " window.open(figure.canvas.toDataURL());\n",
+ " }\n",
+ "\n",
+ " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
+ "\n",
+ " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+ " // web socket which is closed, not our websocket->open comm proxy.\n",
+ " ws_proxy.onopen();\n",
+ "\n",
+ " fig.parent_element = element;\n",
+ " fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+ " if (!fig.cell_info) {\n",
+ " console.error('Failed to find cell for figure', id, fig);\n",
+ " return;\n",
+ " }\n",
+ " fig.cell_info[0].output_area.element.on(\n",
+ " 'cleared',\n",
+ " { fig: fig },\n",
+ " fig._remove_fig_handler\n",
+ " );\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
+ " var width = fig.canvas.width / fig.ratio;\n",
+ " fig.cell_info[0].output_area.element.off(\n",
+ " 'cleared',\n",
+ " fig._remove_fig_handler\n",
+ " );\n",
+ " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
+ "\n",
+ " // Update the output cell to use the data from the current canvas.\n",
+ " fig.push_to_output();\n",
+ " var dataURL = fig.canvas.toDataURL();\n",
+ " // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+ " // the notebook keyboard shortcuts fail.\n",
+ " IPython.keyboard_manager.enable();\n",
+ " fig.parent_element.innerHTML =\n",
+ " '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ " fig.close_ws(fig, msg);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
+ " fig.send_message('closing', msg);\n",
+ " // fig.ws.close()\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
+ " // Turn the data on the canvas into data in the output cell.\n",
+ " var width = this.canvas.width / this.ratio;\n",
+ " var dataURL = this.canvas.toDataURL();\n",
+ " this.cell_info[1]['text/html'] =\n",
+ " '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function () {\n",
+ " // Tell IPython that the notebook contents must change.\n",
+ " IPython.notebook.set_dirty(true);\n",
+ " this.send_message('ack', {});\n",
+ " var fig = this;\n",
+ " // Wait a second, then push the new image to the DOM so\n",
+ " // that it is saved nicely (might be nice to debounce this).\n",
+ " setTimeout(function () {\n",
+ " fig.push_to_output();\n",
+ " }, 1000);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var toolbar = document.createElement('div');\n",
+ " toolbar.classList = 'btn-toolbar';\n",
+ " this.root.appendChild(toolbar);\n",
+ "\n",
+ " function on_click_closure(name) {\n",
+ " return function (_event) {\n",
+ " return fig.toolbar_button_onclick(name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " function on_mouseover_closure(tooltip) {\n",
+ " return function (event) {\n",
+ " if (!event.currentTarget.disabled) {\n",
+ " return fig.toolbar_button_onmouseover(tooltip);\n",
+ " }\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " fig.buttons = {};\n",
+ " var buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'btn-group';\n",
+ " var button;\n",
+ " for (var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " /* Instead of a spacer, we start a new button group. */\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ " buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'btn-group';\n",
+ " continue;\n",
+ " }\n",
+ "\n",
+ " button = fig.buttons[name] = document.createElement('button');\n",
+ " button.classList = 'btn btn-default';\n",
+ " button.href = '#';\n",
+ " button.title = name;\n",
+ " button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
+ " button.addEventListener('click', on_click_closure(method_name));\n",
+ " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+ " buttonGroup.appendChild(button);\n",
+ " }\n",
+ "\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ "\n",
+ " // Add the status bar.\n",
+ " var status_bar = document.createElement('span');\n",
+ " status_bar.classList = 'mpl-message pull-right';\n",
+ " toolbar.appendChild(status_bar);\n",
+ " this.message = status_bar;\n",
+ "\n",
+ " // Add the close button to the window.\n",
+ " var buttongrp = document.createElement('div');\n",
+ " buttongrp.classList = 'btn-group inline pull-right';\n",
+ " button = document.createElement('button');\n",
+ " button.classList = 'btn btn-mini btn-primary';\n",
+ " button.href = '#';\n",
+ " button.title = 'Stop Interaction';\n",
+ " button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
+ " button.addEventListener('click', function (_evt) {\n",
+ " fig.handle_close(fig, {});\n",
+ " });\n",
+ " button.addEventListener(\n",
+ " 'mouseover',\n",
+ " on_mouseover_closure('Stop Interaction')\n",
+ " );\n",
+ " buttongrp.appendChild(button);\n",
+ " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
+ " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
+ " var fig = event.data.fig;\n",
+ " if (event.target !== this) {\n",
+ " // Ignore bubbled events from children.\n",
+ " return;\n",
+ " }\n",
+ " fig.close_ws(fig, {});\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function (el) {\n",
+ " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
+ " // this is important to make the div 'focusable\n",
+ " el.setAttribute('tabindex', 0);\n",
+ " // reach out to IPython and tell the keyboard manager to turn it's self\n",
+ " // off when our div gets focus\n",
+ "\n",
+ " // location in version 3\n",
+ " if (IPython.notebook.keyboard_manager) {\n",
+ " IPython.notebook.keyboard_manager.register_events(el);\n",
+ " } else {\n",
+ " // location in version 2\n",
+ " IPython.keyboard_manager.register_events(el);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
+ " var manager = IPython.notebook.keyboard_manager;\n",
+ " if (!manager) {\n",
+ " manager = IPython.keyboard_manager;\n",
+ " }\n",
+ "\n",
+ " // Check for shift+enter\n",
+ " if (event.shiftKey && event.which === 13) {\n",
+ " this.canvas_div.blur();\n",
+ " // select the cell after this one\n",
+ " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
+ " IPython.notebook.select(index + 1);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+ " fig.ondownload(fig, null);\n",
+ "};\n",
+ "\n",
+ "mpl.find_output_cell = function (html_output) {\n",
+ " // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+ " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+ " // IPython event is triggered only after the cells have been serialised, which for\n",
+ " // our purposes (turning an active figure into a static one), is too late.\n",
+ " var cells = IPython.notebook.get_cells();\n",
+ " var ncells = cells.length;\n",
+ " for (var i = 0; i < ncells; i++) {\n",
+ " var cell = cells[i];\n",
+ " if (cell.cell_type === 'code') {\n",
+ " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
+ " var data = cell.output_area.outputs[j];\n",
+ " if (data.data) {\n",
+ " // IPython >= 3 moved mimebundle to data attribute of output\n",
+ " data = data.data;\n",
+ " }\n",
+ " if (data['text/html'] === html_output) {\n",
+ " return [cell, data, j];\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "// Register the function which deals with the matplotlib target/channel.\n",
+ "// The kernel may be null if the page has been refreshed.\n",
+ "if (IPython.notebook.kernel !== null) {\n",
+ " IPython.notebook.kernel.comm_manager.register_target(\n",
+ " 'matplotlib',\n",
+ " mpl.mpl_figure_comm\n",
+ " );\n",
+ "}\n"
+ ],
+ "text/plain": [
+ "<IPython.core.display.Javascript object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
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BtkjR47o7LPP9gron3766QlfopaTkyOXy6V//OMffpeZNWuWXC6X5syZI6n8DMKFF15Y7R7tqk72HnRfXnzxRblcLhUUFMgYo6ZNm+qKK67waqry8/N13nnn6de//rXntffff1+nn36612WEJSUlatWqVVABXSq/B/3ss8/2edl/pWCPDQA4RagBvW3bttUmTlu0aJFcLpdXQD+Zz8PKq8pWrVrl9fr9998fVP244oordO211/r9+6q1b/jw4XK5XJoxY4bXcv/973/lcrm0YMECScfuQX/zzTcD/vyqAf3ll19W48aNvep/YWGhZ9LU4wP6VVddpU6dOlVbp6970Lt06aImTZp43QJmjNFll13m8x50AjoQPwjoQBCGDh2qunXrqkOHDkpOTtaiRYu0ZMkSTZgwQd27d5fL5dLw4cM9yy9fvlwul0v333+/5s+frwkTJuiKK65Qs2bNvAJ6WVmZfvOb3+icc87R22+/rblz52rhwoUaO3asevbs6Wk4hg4dqgceeEBjx47V4sWL9eWXX3qanfnz50sqb6iee+45TZo0SSkpKZo8ebKuuOIKnXXWWZ7J0Q4dOqRmzZopISFBQ4YM0aJFizRnzhwNHjxYd999t/bv3y+p/L7tNm3a6KyzztKgQYM0f/58vfDCC0HP4t6pUye98847mjVrllJSUjRs2DCde+65XrcKVM7iftddd2n27NmaMmWK54z/8bO47969W/Xq1dNNN92kOXPmaPr06eratauaN28edECvnMW9RYsWGjFihBYvXqyJEyfq4Ycf9lxKGeyxAQCnCDWg//vf/9Zpp52mN998UwsXLlRycrLns/74gH4yn4eVX0Z37NhRM2bM0Oeff66HHnpIrVu39qofGzZs0I033qjk5GTNnTtXixYt0htvvKHTTz9d//znPyUFV/sqZ3E/88wz1a9fPy1YsEC9e/dWvXr1/M7i/uSTT+qzzz7T/Pnz9cEHHyg5Odnr+B0f0Cu/wLj//vv11VdfaeLEibr66qs9+3N8QO/Zs6caNGigSZMm6bvvvtMPP/wgKfAs7tddd52mTp2q2bNn64477vA7izsBHYgfBHQgSOvXr9djjz2m5s2bq0GDBmrYsKFatWqlP//5zz5ny/3444/Vrl07NWzYUO3bt9fkyZN93k/tdrvVt29fz3NZGzdurISEBPXq1Us7duyQJK1atUr33XefmjVrpgYNGujcc89V165d9dlnn3n9vJtvvlnnn3++6tevrwsvvFA9evTwNAiVDh8+rOeff17NmzdXvXr1dM455+jqq6/WG2+84fWM2gMHDqh79+5q3LixzjzzTHXv3l0rV64MKqC/9tpruuaaa3T22WerQYMGatGihV566SUdOXLEa7lZs2bpuuuuU8OGDXXGGWfo1ltv1YoVK6qt78svv9QVV1yhRo0aqUWLFho0aFDA56D7snnzZj3wwAM699xzVb9+fV188cV69NFHva5yCPbYAIAThBrQS0pK9Morr+iiiy5So0aN1LVrV61fv97nc9BP5vNw5cqV6tKli372s5/pl7/8pZ544gmtXbvWq36kp6fr0UcfVUJCgs444ww1btxYl19+ufr376+ysjJJwdU+qfw56E899ZQuuOAC1a1bV82aNdPrr7/u8zno/fv3V4cOHVS/fn2dddZZ6tKliz7//HOv41f1MvXRo0erbdu2nnr2/vvv66OPPqoW0Pfu3atu3brpzDPPlMsV/HPQzzjjDDVq1EidO3f22haJgA7EIwI6AAAAAAAOQEAHAAAAAMABCOgAAAAAADgAAR0AAAAAAAcgoAMAEEHvvfeerrnmGjVu3Fi//OUv9bvf/c7zjONAli5dqquuukoNGjRQ8+bNNXTo0GrLTJs2Te3atVP9+vXVrl27ao+aAgCgKuqSsxHQAQCIoDvuuENjxozRxo0btX79et199926+OKLA86EvXv3bv3sZz/TCy+8oM2bN2vkyJGqV6+epk2b5llm5cqVqlOnjt577z1t2bJF7733nurWratvvvmmNnYLABCjqEvORkAHAKAWZWRkyOVyKSUlxe8yr7zyihISErxe69Wrlzp37uz57x49eujOO+/0WuaOO+7QQw89FN4NBgCc0qhLzkJAjzPGGO3fv185OTnKzc1lMBiMsI+cnBzt379fxpiT+rwqKiqK+r4E2seqr1V95rI/O3bskMvl0o8//uh3mRtvvFHPP/+812szZsxQ3bp1VVpaKkm66KKL1K9fP69l+vXrp4svvjjEIx191CYGgxHpQW3yj7rkLAT0OLN//365XC4Gg8GI+Ni/f/8Jf1YVFRWpyXl1or4P/kbjxo2rvda7d+8a98taq3vvvVc33HBDwOVat26td9991+u1FStWyOVy6dChQ5KkevXqafz48V7LjB8/XvXr1w/tYDsAtYnBYNTWoDZ5oy45DwE9zuTk5Hg+nKL9LR+DwTg1R2XYysnJOeHPqtzcXLlcLu1bc4myt7dw1Ni35hKfn6PBnKV45pln1KxZsxobxNatW+u9997zem358uVyuVxKTU2VVN4ITZgwwWuZTz/9VA0aNAjxaEcftYnBYER6UJt8oy45DwE9zlR+sOTm5kZ7UwCcosLxOVO5juztLWRSWztqZG9vcUL799e//lW/+tWvtHv37hqXjbdLCalNACKN2lQddcmZCOhxhiYIQKTRBHmz1urZZ5/VhRdeqO3btwf1nldeeUXt2rXzeu2pp56qNhnPb37zG69l7rzzzpicjIfaBCDSqE3HUJecjYAeZ2iCAERaOJugzO3N5U5t6aiRub15SPv39NNP66yzztLSpUuVmprqGYWFhZ5lXnvtNT3yyCOe/658nM1LL72kzZs366OPPqr2OJsVK1aoTp06+uCDD7RlyxZ98MEHMfs4G2oTgEijNh1DXXI2AnqcoQkCEGk0Qd78TeYzZswYzzI9e/ZU165dvd63dOlSXXnllapfv74uueQSDR06tNq6p06dqrZt26pevXpKSEjQ9OnTT/iYRxO1CUCkUZuOoS45GwE9ztAEAYg0miCEitoEINKoTYgVBPQ4QxMEINLC2QRlbGum4kPNHTUytjXjczTMqE0AIo3ahFhBQI8zNEEAIo0mCKGiNgGINGoTYgUBPc7QBAGINJoghIraBCDSqE2IFQT0OEMTBCDSwtkEpW27WIWHLnHUSNt2MZ+jYUZtAhBp1CbECgJ6nKEJAhBpNEEIFbUJQKRRmxArCOhxhiYIQKTRBCFU1CYAkUZtQqwgoMcZmiAAkRbOJujQtl8p/9DFjhqHtv2Kz9EwozYBiDRqE2IFAT3O0AQBiDSaIISK2gQg0qhNiBUE9DhDEwQg0miCECpqE4BIozYhVhDQ4wxNEIBIC2cTtH9rU+UevMhRY//WpnyOhhm1CUCkUZsQKwjocYYmCECk0QQhVNQmAJFGbUKsIKDHGZogAJFGE4RQUZsARBq1CbGCgB5naIIARFo4m6B9Wy9U9sFfOWrs23ohn6NhRm0CEGnUJsQKAnqcoQkCEGk0QQgVtQlApFGbECsI6HGGJghApNEEIVTUJgCRRm1CrCCgxxmaIACRFs4maM/WC3TkYFNHjT1bL+BzNMyoTQAijdqEWEFAjzM0QQAijSYIoaI2AYg0ahNiBQE9ztAEAYg0miCEitoEINKoTYgVBPQ4QxMEINLC2QTt2tpEGQcvdNTYtbUJn6NhRm0CEGnUJsQKAnqcoQkCEGk0QQgVtQlApFGbECsI6HGGJghApNEEIVTUJgCRRm1CrCCgxxmaIACRFs4maPuW85V64AJHje1bzudzNMyoTQAijdqEWEFAjzM0QQAijSYIoaI2AYg0ahNiBQE9ztAEAYg0miCEitoEINKoTYgVBPQ4QxMEBM+aPNm84TJHHpA58qBs/hhZWxjtzXK8cDZBW7ecr4MHLnDU2EoTFHbUJiB4e7Kz1HvJQt0z4RM9Nmu65u3cLmtttDfL8ahNiBUE9DhDEwQEx5qjMod/I5PaVia1dcVoI3O4u6wtivbmORpNEEJFbQKC80N6mtoPHqBWyYlqntRXLSv+/GB5SrQ3zfGoTYgVBPQ4QxMEBMfmDa4Szo+FdJs/Ltqb52g0QQgVtQkITvcpEzyhvOrYlZUZ7c1zNGoTYgUBPc7QBAHBMYd/6yOcV5xFz/xztDfP0cLZBG3acp5+OtDEUWPTlvP4HA0zahNQs5yiIp/BvPJM+vDvv4v2JjoatQmxgoAeZ2iCgOAQ0E8cTRBCRW0CakZAPznUJsQKAnqcoQkCgsMl7ieOJgihojYBweES9xNHbUKsIKDHGZogIDimeKVM2nXVz54zSVyNwtkE/bD5PO3Z38RR44fNNEHhRm0CauY2RsO//06tB/ZTi+POnDNJXHCoTYgVBPQ4QxMEBGatkcn5Z0Ugb1seylNby6RdL5M3msesBYEmCKGiNgGBZRUW6s5Px6p5Ul/PDO7Nk/rq7vGfaD6PWQsKtQmxgoAeZ2iCgMBs4Ww/9563li2aF+3Niwk0QQgVtQkI7OX5X3oF8+ZJfdUiqa/aDOynwwUF0d68mEBtQqwgoMcZmiAgMJP5iJ97z9vKZP5F1mTL5n8sk/u+bME0WUNjVFU4m6D1m8/Trv1NHDXW0wSFHbUJ8K/Y7Vbrgf183nfeIqmvPl6/VruyMpX0zUq9vzxFKXv3yHBGvRpqE2IFAT3O0AQBgZnD9/g9g24yfiOT1rHisvd25a+lXy/r3hPtzXYUmiCEitoE+JddVOh39vZWyYn688ypnv9dGeT/OGOKit3uaG+6o1CbECsI6HGGJggIzOS+I5Oa4PsMeuplPs6uJ8gc7h7tzXYUmiCEitoE+GetVdexIz0TwwUzWiYnqv+qFdHedEehNiFWENDjDE0QEJh1/ySTdmWVkJ5Qcebcz5n11Nay7r3R3nTHCGcTtHbz+dq+/wJHjbWbz+dzNMyoTUBgX2zb6rmk/fgQft2ooWqV5Puxa10+GhbtzXYUahNiBQE9ztAEATWzpdtkMv+/ikvZ28hk/kUmb2TggF66Idqb7Rg0QQgVtQmo2Zc7tun2cWPUPKmv2g8eoLeWLtKL876oNnlc5bh0SFK0N9lRqE2IFQT0OEMTBATP2hJZW1r+v937jj1yrepI68jj145DE4RQUZuA4BW73Z5J4Cb+uMHvvek9Z06L8pY6C7UJsYKAHmdogoATZ3Je9xnSbd6IaG+ao4SzCfp+0/na+tMFjhrfb6IJCjdqE3BiCktLddPYUV5n0VtWTBa39tDBaG+eo1CbECsI6FHSrFkzuVyuauOZZ57xufySJUt8Lr9ly5aQfi5NEHDirHXL5g2SSetUMYN7V9mCibI8zsYLTVDsojYBsSejIF9/m/+l2gzsr+ZJfXX/lAn69sD+aG+W41CbECsI6FGSkZGh1NRUz1iwYIFcLpeWLFnic/nKJmjbtm1e7ysrKwvp59IEASfPWltx+TvB3BeaoNhFbQJiV5kxKg3x3148oTYhVhDQHeKFF15Qy5Yt/Tb8lU1Qdnb2Sf0cmiAAkRbOJujbTU206acLHTW+3dQkbj5HqU0AThXUJsQKAroDlJSU6Nxzz9W7777rd5nKJuiSSy5RkyZNdMstt2jx4sUh/yyaICA0pmStTPYrMpl/lsl9V9a9L9qb5Hg0QacGahPgTMZazdyySU9+NlN/njlVI9esVm5xcbQ3y/GoTYgVBHQHmDx5surUqaODB/1P5rF161aNGDFCa9as0cqVK/X000/rtNNOU0pKSsB1FxcXKzc31zP279/PP14gCLbsgMzh31eZEK6tTGoH2ZLvor15jkYTdGqgNgHO8/W+vbpy2KBqs7bfNHaUMgsLor15jkZtQqwgoDtAt27ddM8994T8vnvuuUf33ntvwGV69+7tcwIf/vEC/lmTLZPexc8zz9vIZNzO/ecBhLMJWrnpAv3wU1NHjZWbLoiLz1FqE+As3x7Yr5Z+nnneMqmv3k4J/eqVeEJtQqwgoEfZ3vzsOPoAACAASURBVL17dfrpp2vWrFkhv/ff//63EhISAi7DWQogdDZvhP9nnlc+Ws29M9qb6Vg0QbGP2gQ4z8PTJquFj3BeOa4dOSTam+ho1CbECgJ6lPXu3VtNmjSR2+0O+b3du3fXzTffHNJ7uM8P8GatlS1ZK1s0z3N/ucl6KmA4N6mtZbKekc0bLlt2OMp74Dw0QbGP2gREV7HbraV7dmvBrh3KLS6SJLUd1N9vOG+e1FcJgwbotYXzNX3zRhWfwL/dUx21CbGCgB5FxhhdfPHFevXVV6v93WuvvaZHHnnE89/9+/fXzJkztX37dm3cuFGvvfaaXC6Xpk+fHtLPpAkCjrHu3TIZd3oH7+wXZLL/LpOaUENIb1s+0i6XLVkT7V1xlHA2Qcs3Xqj1+37lqLF844Wn9OcotQmIrnk7t6vj0IHHBe/+GrX2e107ckjAgN48qa9aJ/dT86S+uv2T0dyTXgW1CbGCgB5F8+fP9zw/tqqePXuqa9eunv/+z3/+o5YtW6phw4Y6++yzdcMNN2jOnDkh/0yaIJyqrHuvbMFE2cIZsian5uWtWya9q48g3lYm8+maz6Afv3z6/8jasor1WtmSb2Vy35XJfU+25Lu4u1+dJii2UZuA8LDW6tsD+/XJhnVasGtHUM8o33bksFomJ/q8lP2ZObP93oNedbRKTtRrC+d71lvsdmvmlk3qvWSh+q9aob0n+WjEWERtQqwgoMcZmiCcaqw1MjlvVwnNl8oWzgz8vqKFAUL3pTK5fY87U15zULcla2RtmUz2yxWvJRwL/9mvyFpTS0ck+miCECpqE041mYUF+v2kT71Cc5dRw7TlcEbA9/VeslCtfITwlsmJemDKBD08bbLnv2sK6QmDBshaq4yCfN368UflZ9gH9lOr5ES1TE7UtM0ba+loOAO1CbGCgB5naIJwqrEFE/zOtm5Lt/t/X/6YgBPBWfdeWfcO2bxkmaN9ZfJGBQ7oxctkC6f7//vCz2rxqERXOJuglI1NtWbfRY4aKRub8jkaZtQmnGqe/HxmtaDdKjlR1380XG7j/wvbx2ZN9xu4u3w0TMZapezdo/8sX6ZB332jVxbMU+uB/fy+p8wYPT/3C5+hv1VyotLy8mrxqEQXtQmxgoAeZ2iCcKoxh+/yE7QTZHLf9SxnbZmsyfWcyTZFiwIE7g6yttDr51iTU35m3c8Zd2tyZDIf8XPGva1M5qO1elyiiSYIoaI24VSSkZ8fcLb1pXt2e5Ytdrt1tLjYcytU7yUL1dLPY9T+PHNqtZ+1cPdO349dS07UA1Mmqtjt9hnOK5cZtfb7Wjsu0UZtQqwgoMcZmiCcakzaNf7vDc9+vjyY5w06tlzatTKZj8mkXuU/oKddIVu8rNrPsnmDPWfnj//T5g0q35bDv/O/ziPda/vQRA1NEEJFbcKpZHNGesBLzydt/EGHCwr00rw5nrPft30yWg9Pn+w3TDdP6qtu48boQJV/I2XG6IEpE70ueW+ZnKhWyYn69sB+5RYXB7xPvf+qFVE6SrWP2oRYQUCPMzRBONUEOmtt84bK5PQOeCm7v8vjTWq7apfIW2tlC6ZWzPx+qUzGnbIFUz1nPkzuB/I9+3uCzNH/RuPwREU4m6DFGy/Sd/uaOWos3ngRn6NhRm3CqSSvpEQJgwb4DcZrDh3UbZ+MDhjG/QXqrmNGVptsrqC0VB+uWKZrRwxRwqD+emTGFH1/6ICk8rp1+7gxfs/or/xpXzQOUVRQmxArCOhxhiYIpxpbvMJHAG8rk3a1TMnWoCd58znSr5ctWhT8tpSllp+h9wrpCTJpnWTL0iJ4FJyFJgihojbhVPPhimU+Lyn/3+mTNXPL5pCCedXxwNSJ2n7kSNDbsnDXTrWouEz++G354/TJcfWUEWoTYgUBPc7QBOFUZIvmyqT/z3GXk98vW7pVtmjxiYfz4yd4K5gU/La498hkPS+T2r58ZD0v646fMxQSTRBCR23CqabMGPVd+bXaD07yBOIX532h3OJivbV0UcCJ3WoaLZL6qv3gATXOCH+8pXt26/eTPlWLpL66ctggfbA8RYWlpRE8As5DbUKsIKDHGZognKqsNbLuPbJlqcdeK1kbloBu0q6StcUhbo+NqzMTxwtnE7Tox4v1zd5LHDUW/Xgxn6NhRm3CqaqwtFQ7M48op6jI89qAb1aEfHm7r8vde30+K+Ttide6JFGbEDsI6HGGJgjxxFojk3Gbn/vCQzyLXrI22rsTM2iCECpqE+LJvpzsoJ5jXtNoN3hAtHclplCbECsI6HGGJgjxxpZukUnrVBG02x27L7zyXvWKx6rVGNBLNwX+Oe59siWrZU1WLe2Zc9EEIVTUJsSbaZs3qlVyomfG9cqz4pWXwzevuIw9UEC/YtjAgD/DWKsf09O09tBBFbvdtbRnzkVtQqwgoMcZmiDEI2sKZAunyxztL1s4U8YUyBYvk80fKZM/Rv6fb14R4jNurbhkvUy2YLzM4d/LpHeVyf67TNFKmSP/e9zy7WRy+8ja+G2GwtkEffVjM63Y29xR46sfm/E5GmbUJsSj1LyjGrlmtfqtWq7lP+1VfkmJZmzepOHff6cPl1efZK7qJe69lyyUJGUWFuiD5Sm6aewo3fLxR/rviq+1YNcO3TB6hGf5K4cP0ozNgb9oPtVRmxArCOhxhiYIOMaaPJnMx2t4DNvlsiVrZK2VyX6xYtk2x8J7ahsfM8W3iavHqlVFE4RQUZuAYw7k5uraEUMCBvTbPhmtrMJCZRcVquuYkV73tFc+Us3XZfTLf9ob7d2LGmoTYgUBPc7QBCHeWfdu2bxkmaxna760Pe0az6RztmRNiPetXy5ri2rYmlMTTRBCRW1CPLPWasVP+/TesiV6YOpEv88srxz/O32yZwb2/qtWBH0/e6vkRPWcOS3Kexs91CbECgJ6nKEJQiyyJl82f5xM1l9lcl6TLV5xQjPR2vwxfs54+xkZd3nea472D3myuXh7vFqlcDZBc39ormV7WjpqzP2hOZ+jYUZtQiw6kJurD1csU68vZundZUu0Kysz5HWUlpXpic9m+j3j7Wu8//VSz/vvmfBJSBPLdfloWDgPQUyhNiFWENDjDE0QYo0tO1IxE3vlpeUVITn3/dDWU7r1BGZvbyPj3lV+/3newBADentZkx+ho+JsNEEIFbUJsebbA/uVMGiAWiUnqkXF2enWA/tp4a6dIa1n1NrvazxjXnXc+vFHyi0uf/TnfZPHB/2+lsmJemjapEgcjphAbUKsIKDHGZogxBqT86bfYGxL1nsta22RbOkPsu495f9dul0m+x8yGbfIpP86+DPnVUd6V5m8YYGDfNWJ5XLejMLRcgaaIISK2oRYYqzVDaNHqGWVANwiqa86DhtYbcb0IwUFWp96SBkF5V/aLty9U3+aMUX/M2akOgxJOuHHrD0wZaL+vWxJSAF/3s7t0ThkjkBtQqwgoMcZmiDEGpN2hZ9QnCCT+55nOZs/VibtyuMuT79DJrV9yJelBxxZTx/72ZVBPO1amfSbqiz317i9/1wKbxM054cWWrqntaPGnB9a8DkaZtQmxJINaakBQ/DSPbslSYWlpfr7V3M9l663TE70XJIejuegt0xOVPvBSbq3Yp0tjpsgrtu4MbpsSLJn2TYD+2n4999F+chFF7UJsYKAHmdoghBr/D8CrZ1Mbm9Jki2cEb4QHvCe9FtkipbLZP9NJvNx2bwhsiZT1pryZ6AXzpF17/Zsuy39USb3A5nc3rJF82Xce2WLFsuWbonS0awdNEEIFbUJseS7g/sDBuf5FWepn5/7RViCeE0Tv/1r8QJN2fSj/vLZTD35+UxN27xRJWVlKiwt1cLdOzV3x3ZlFxVKktzGaP7O7Xpz8QK99/VSbUhL1Q/paVq8Z5dS845G87BGHLUJsYKAHmdoghBrTFYv/5e4F5U/A9Zk3Fw7AT21tawJ7t9O+aRylWfbfWz/ke6eGeJPNTRBCBW1CbGkyF2qy4cm+wzMbQb2U3ZRoQ7k5kY0mB8/7p7wSVDbXVhaqh5TJ6p5Ul+1HthPLZO8vzxomZyo1xbMU2lZWYSPYHRQmxArCOhxhiYITmJLt8gWzQt4Rrl8crfLq4TcNjKZf5IxJTLZr9daODepHWRtSc37VfJ9EOtKkDl89wnNRu904WyCPvuhpRbtaeOo8dkPLfkcDTNqE5zCbYxW/rRP83ZuV1pent/lJvy4wetS9co/B3/3jTLy83Xz2FG1Es5bJifq0VnBPTotmEeytUjqq/eXp4TrcDoKtQmxgoAeZ2iC4ATWZMocebjKGeWHZc2xR9RY907Z4uWyZamy7h3ll5Wnd5HJuK380nJbLJs3PDzBO/1/ZHLfV+BJ5NrK5PwrqP0zOb39nvWvdka+5NtIHeaooQlCqKhNcIK1hw6q86hhXuH37aWLZCq+SC0zRmsPHdSKn/Ypv6REi3bv0kPTJunqEYN13+Tx+mLbVknSg9MmVZtA7kRGz5nT9Pjs6TUuN3dHcBO//Xr08KB+bvvBSdUmujsVUJsQKwjocYYmCE5gjjziI8AmyBx+UCb/44oJ3o47W579N5+Trpn0G04+nB/5k6zJkiTZ0k3lz1pPvVLHZmav2M4jD8ga/2dTvLYr+281hP3jAnrBlLAeWyegCUKoqE2ItuyiQnUYkuzzDPPbSxfpP8uX6erhg48LsQP00drvq61nV1ZmWM6M913xtdzGSJLmbN+q+yZ9qoRB/T1nuSu3872vlwZ9JVbHYQOD/vkHj556/xapTYgVBPQ4QxOEaLPunScQpNvK5LxebV3VH28W6mjjNamb13aaLNmCCbJ5g8onhivZUD7BW9mh8r+3VtbkydrqZxlswaSgt8GWnHqz6oazCZq5obW+2p3gqDFzQ2s+R8OM2oRoG7t+TcjPI2+e1Fdztm/1Ws/yn/ae9CXrN44e4TlrX9XOzCMa9v23Grr6W23OyNCKn/Zp6Z7dyispv/2qzBgdLS72GdqfmTNbrYKYtI4z6DWvg9qESCKgxxmaIESbLV5ygmE6wXOmu5LJ+M3JhfQjf5YxhYG3171P5vA93mf0j/yvTMZtFf/dQSbn/7zOrltbWHEVQKDL3BNkDt/DPeg1rIMmKD5QmxBt76QsVuuB/UIO07+b9KnXelLzjp5Q0K8cLZL6qt/K5TXWhoW7duqq4YM872s3qL96zpymjkPLz5J3GjlEo9et8VrP5sMZShg0IGBIb5HUVx9wD3qN66A2IZII6HGGJgjRZt37TjhQ29KN3usq/OzkL3FPbStT+JnvbbXu8ker1Xg/edvyS+CtOfZek1l+L3raleXvT7u+ypcDDzCLexDroAmKD9QmRNv4H9afULC+fGhytXW9PP/Lk368WsehA7UvJ9vntu7IPKJWyYlBbW/SNyu93vtjepoemzVdbQb206VDkrxCfsvkRL2+cD6zuAexDmoTIomAHmdoguAE5Y9OC+4e7eND8PGTyFWyBZ/KpF1z8pe6l6VXX3fR4tC+QCheHnC/bdlB2eIU2dJtYTuWThTOJmj6hjaat7udo8b0DW34HA0zahOi7Whxsa4aPiioS8CPnW1O1L0+HnFW7Hbr9YXzQz4jX3V0GTXM55n0t5YuCno72w0e4Ln83RdrrTZlpGvpnt1Kzw9unpVYRW1CrCCgxxmaIDiBNXkyWc+GcHl6W5nsf/hfny0pn1zuZEJ67gfV15s/JoQvEhJk86qfSYlHNEEIFbUJTrDlcIa6jRsTUoietXWz3/VlFxXq+bmfn9SM7j+mp1Vb76OzpoW0jjWHDkbysMUMahNiBQE9ztAEwUnKzyh/I1M4O3D4PfJHmZx3ZHL7yBYv87qU3LMukyeTetmJB/TMZ6qvM6T75dvI5lc/kxKPaIIQKmoTnMJaq80Z6fpm/096e+liv5eRtxnYT8/P/UJvLl6g/674WtuPHPG5vmX79pzUWfT5O6s/Qu3tlMUhnenflVX96rN4RG1CrCCgxxmaIDiVLfxMJr3zscCbcYvM0ZEyWX+veK1dxWgtk9VL1pZWX0fBBM/Z7JADet6I6uuzZRWTwQWzvvY+L8GPR+FsgqZuSNCc3Zc6akzdkMDnaJhRm+BEbmP07rIlanvc483unzJBkzZu0G8+HavmSX3VemA/T1ge5eOxa9ZaPfXFbM/7Qw3ou7Ozqq1zV1amWg/sV+P6WvmYxC6eUZsQKwjocYYmCE5mbals6WZZ967yx5gFugc8+xXf96QXL5fJelImo1v5LO0hnAE3adfJHHlUtmi+5yy9de+XOfyHKstde+zS+9Q2MqntZIvmBb+fZamyeYNlcl6XzR91ygV7miCEitoEJ8stLtaP6Wmee7TfWrrI7yRw4zasU0mVSdbcxmj8D+v1h8njddsno/XAlAlBB/Q2A/vp+o+G6+9fzfW63H3Jnt26duSQY/eaD+qvdoMHeIJ586S+6jxqmPb4CPj+bEhLVZ+UJXp94XzN2rq52n7EOmoTYgUBPc7QBCGWmKwXajh7nSBz+PcyR+6XyX5dttT7XkCbNyKEe8irfgHwqtfkPLZ0q2zx17Jl6TJFS2RSL/dePudfsrbmZsYWL5dJ7VCxXQkVgf+qajPUxzKaIISK2oRYctnQ5IChusOQJN036VN1nzxB/VYt1+GCAq/3Pzxtslokndgs7zO3HKtzbmP03cH9WvHTPhWUlOiD5SleZ9XbDuyv6ZuDqy0DvllRfkVAcj/P5Hb3TPhEucXFYT120URtQqwgoMcZmiDEEpP5WAihOkEmNUG2aNGx9x/tf2KXu1cMW7yi2jbZslSZ1Evla4I7mz8q4P5YWyKT1snHe9vKZNxxyjwTPZxN0KT17fXZrsscNSatb8/naJhRmxArrLUhPUKtZXKiOo0cqgNHj/1/+54Jn5zwPentBw9Qvo9Z2b/YttXn8i2S+mqjj4nmjrchLdXvtv972ZJwH8KooTYhVhDQ4wxNEGKJzRsW4hnwNjLpXWStW5JkiuafcDg3qe1kcnr72KYh/rcp/cbA+1OcEvgLgdKtkTiMtY4mCKGiNiGWPDh1UkghvVVyol6e/6Xn/S/P//KEA3rzpL6a52PiuAemTPC5Ta2SE/XPRV8F3J8+KUvUOtn3I+GuGj447McvWqhNiBUE9DhDE4RYYk22TPqNIZ8FtyXrJUnmSIAz8Bl31BD+E2Ry/lltm0zOm/JMVufjPQH3p2huDdu9NiLHsbbRBCFU1CbEkm8P7Fer5MSQQnr7wUmSyu9n93eJfJuB/Tz3kQcaX2yr/mXu9R8N87v8Y7OmB9yfQM9sTxg0ICLHMBqoTYgVBPQ4QxMEp7PFKTKZPWXSbyh/vFrBNJnsV0IK6bZkrUzp7sDL5X9a83qK5lffvvxxPi9vN6ltZA7fHXjfytL9fymQdoWsLYzUYa1V4WyCJqzvoFm7OjpqTFjfgc/RMKM2wcncxujj9Wt11/iP1eWjYXpx3hxN2/SjHpo2KeiA3m5wedAd8f13fpe5ctgg9V6yMGDwbz2wnzILC6pt4/83e4bPR6+1Sk7U+8tTAu7f7K2b/Z75f3z2jIgc02igNiFWENDjDE0QnMwWTDp2T/Zxf9r8sbLuHcGF9LROMoWzApzlrhiFC8qfre7v7zP/7LlU3msbzVGZ9Ot8bost/LzGfTRH/3Ms0B/3p83/OBKHNCpogrylpKTonnvu0QUXXCCXy6WZM2cGXL5nz55yuVzVRvv27T3LjBkzxucyRUVFJ3zMo4naBKey1uqZOd6PSWuVnKiEQf21Pi1VE37cENQl7s99+bn+tXhBjcsezs/XvROr36Ne+bOHff+tz+389sD+ao9da5mcqHaDB2h/bk7AfSwpK9M9Ez7x+mKgVXKi2g7qrx9quH89llCbvFGbnIuAHmdoguBU1hbJpF3pJzC3kUntWEM4r5gRPW9YcGfac/4lSTIl38hkPV9xyXuH45a5RuboQFlrZMvSZEs3yJryJse6d8gc7n7clwLXyBaMD3I/rWzBeJmM22VSL5U5fE9QwT6W0AR5+/LLL/XGG29o+vTpQTVBOTk5Sk1N9Yz9+/frnHPOUe/evT3LjBkzRj//+c+9lktNTT3h4x1t1CY41XcH9/sM0i2S+urSwUmeZ6QHCudXDR+k975eGtSZ9q/37lFpWZkmb/xBj8ycql9/NFxtKi4/b5HUVzeOGamle3fLWqudmUe0MT3N8zi0Odu36bpRQz3ruu2T0fr+0IGg9jO3uFjvLluiq0cMVrvBA/T47BmnVDiXqE1VUZuci4AeZ2iC4FQmb2jQl7BXH5fLZL0gW7KuPGwH+76sv8qkXlbDcsf/fXuZnHdkbakkybr3yZZukrXVZ9SNZ+Fsgsatu0zTd17hqDFu3WUnvH/BNEFVzZw5U6eddpr27t3reW3MmDE666yzQv75TkVtghMVu916ZObUoC9jrzo6jRyqd5ct0f6cHF1ew6PZjj/r/fjs6dXOhlcdx6/vquGDNa3icWplxmjL4Qztyso8ZZ4MEi7UJv+oTc5CQI8zNEFwInN0wEmE84rLyytCssnodtLrCjzayOT+u9o+WGtli1fJ5o2QLZgua/Jq+zA6Rrw0Qfv371dubq5nFAfxvOATaYLuuece3X777V6vjRkzRnXq1NHFF1+spk2b6u6779batbE7ySC1CU5T7Hbr/ikTTjicN0/qqx5TJ0qScoqKTmo9wY7Fe3ZV248id6lmb92soau/1eI9u1RmTG0fSsegNvlHbXIWAnqcoQmCk1hrZAqmhiE0Jxx7tFpmrwgH9PIz6dYcPbYfJlfmSI+Kv6u4fz6to2zxymgd2qiKlyao6jj+Mj9/Qm2CDh06pDp16mjy5Mler69atUrjxo3T+vXrtWzZMnXv3l2NGjXS9u3VH78UC6hNcJKC0lK9PG/OSQfmP8+cKql8krn2QczOfrKj+2TvW602pqfpmhGDPZfaN0/qq9s/Ga20vPj8Apna5B+1yVkI6HGGJghOYW2ZTNZz4QnMmc8eW2/Jt7UQ0FvL5I2SyfxL+b3r6Tep+uzsbcpDehyeSQ9nEzR2XUdN2XmVo8bYdR1r7SzFe++9p3PPPVclJYFvozDGqGPHjnruueeCXreTUJvgFOn5eeo6ZmRYAvOkHzd41vvhimURD+itkvpq3IZ1+sPk8br9k9G6dEhStRnhWyUn6k8zpkTxCEcPtck/apOzENDjDE0QnMIWTg9fWM56wWvd5c8qr4WQHsSs8rZgapSOcPTESxMU6fv8rLVq1aqVXnzxxaCWf+KJJ3TnnXeGvE1OQG2CUzw/9wufjys7kTFry2bPekvLynTT2PAE/5pGTfevN0/qq4NH4+/fGrXJP2qTsxDQ4wxNEJzCZPb0cdb5REc7rzPVNm9IUOG5NobNGxrScbFlh2WOfiiT8RuZw7+XzR8la2Pr8SQ0Qf6F0gQtWbJELpdLP/74Y43LWmt1zTXX6LHHHgt5m5yA2gQnKC0rU+uKGdNPdrRMTtQDUyZ6rf+BKRNrJaAHM0Kdof3H9DS9MPcL3fLxR/rjjCmau2N7zE1CR23yj9rkLAT0OEMTBKcwR7qHNwwXzJQxRTLFS2Uyn4x6MD+2XZNrPhgVbFm6TPqvq3y50EbmyIMxNVN8OJug0Wuv1KQd1zhqjF57ZUj7l5eXp3Xr1mndunVyuVzq16+f1q1bp3379kmSXnvtNT3yyCPV3venP/1J1113nc91vvXWW5o3b5527dqldevW6bHHHlPdunX17be+n5HsdNQmOEFhaWlYQ/DlQ5O1KytThwsKNHPLJt32yeigzm7XxjgaxGXPlZbt3aNWyYmeKwsqL5vvv2pFBH8b4Udt8kZtci4CepyhCYJTmKP9A5xBv+IEA3Gb6AfyqiN/UvDHJLeP/J35t4UzIvjbCC+aIG+VZxuqjp49e0qSevbsqa5du3q9JycnR40aNdKIESN8rvPFF1/UxRdfrPr16+uXv/ylunXrppUrY3dSQmoTnOK3E8eppZ9Q22FIUtSDtb8RavDPLioM6nhYa3XT2FE+198iqa8OHT1a80ocgtrkjdrkXAT0OEMTBKewZUdk0q+vEkgTZNK7lJ9JPnJ/9MO1z9FBJrV98MvnfhD0MTHp/+NnPW1lsp+P4G8jvGiCECpqE5xi+U971TI50WtytZbJifrzzKk6Wlwctkvgwz06jRwS0vK7sjKDOh57s7MDrmficRPhOR21CbGCgB5naILgJLbskEz26zJpV8mkXSmT/aps2UFJkknv7IAwXmWkXSlTtES2YJrKz9YHcZ/70aSgj0f5bPD+Anpwk7E4QTiboJFrr9b4HZ0cNUauvZrP0TCjNsFJvj2wX3+aMUXtBg9Q51HDNOCbFSp2u7Uj80jUg7iv0W3cGP2Uk60X5n3h+UKhpvd8f+hAUMdif25OwPVM3vhDhH8b4UNtQqwgoMcZmiDECnP43ugHcp+jnWzpRtmSdTLZ/5A58qBM6mV+l7dFC4Lf56Mf+g39tnBOBI92eNEEIVTUJsSC3OLioMJvbY8WSX114+gRyi8p0eytm/X47On67cRxfpdvPbBfSJe43/npWJ/73So5UYcLCiJ81MOH2oRYQUCPMzRBcBJbvFwm61mZw7+XyfmnbOl2z9+Z3LcdEMZ9jTYyWd6Xm9uCCT6WS5DJuFPWuoM/HiZbJqObjt1LX/FnVi9ZWxa24x5pNEEIFbUJTlFaVqYJP27Qw9Mm6/eTPtWAb1Yoq/BYmK2tR6WdyKh6NvvJz2dWC9YtkvrqnZTFIR2TNYcOqt3gAZ5J4ir/HLNuTViOeW2hNiFWENDjDE0QnMLmjz4WZD1/tpMtLp8V1havcEAY9zPSb/TeF2tl8z+WSbv2uBDfS7YsI/TjYvJk8z+SyXxEJvMJ2cKZIYV8JwhnEzR87dX6ZPt1jhrDaYLCjtoEJ3Abo0dnTfME2crLxX89ergy8vMlSX2WGPUQuwAAIABJREFULYl6EPd3Fv2Nxd5XbBWUlur1hfM99823HzxAHyxPkduYkI/N3uxs9UlZogenTtJL8+bo2wP7w3LMaxO1CbGCgB5naILgBLbsiExqO99npzNuKw+8tkwm4xaF71np4QzoN/h87Jm1pbLuPbImy/d+2xLZovmy+WNki5fL2tCbpFhAE4RQUZvgBHO2b/MZflslJ+qtpYskSbuyMj1nkJ02npkz2+d+HS0u1u7sLBWWlvr8+6zCQk3e+IPGrl+jbUcOR+z4Rhu1CbGCgB5naILgBLZwZsAAbN27ypdz75TJ8DdxWpRHVi9Za4Pf59JtFc84P+7S9cN3y5alR+owRw1NEEJFbYITvDRvjt/wfd2ooZ7lvti2Ve0GD4h6IPc1xm1YF9I+z9yySW0G9ve6auDvX81V2QmcZXc6ahNiBQE9ztAEwQls4YygArqk8jPpWc8480x60WLZ0m2yNvBkO+VXA9yk6hPAJchkPhrpw13rwtkEDV17rcZu7+KoMXTttXyOhhm1CU7wYqCAPnKo17JHi4t13aihUQ/kVcflQwdq+5HD2pl5RKaGL5F3Zh7xO+ndqLXfR/JQRwW1CbGCgB5naILgBKZ4TYDge6lMcXljYEu3yBYvlSlaEP0wHmikdZTNG+j3kvWa7qevfLTcqYImCKGiNsEJ/r1ssd/ge/PYUcrIz1dpWZm+PbBfy/bt0X9XLHPkrO6V44bRI7Rw106/+/v+8hS/X0jcNHZULR752kFtQqwgoMcZmiBEmyn+7tgl3j5HG5nU9jIZd3m/lnFH9IN4DcPmDfW5zzVe0l+yvpZ/C5FFE4RQUZsQbYkrvw4YdlslJ6rzqGG6ZsQQz2vtBg1QZweeRa8cLZLKJ7lbe8j3l8Avz//Sb0C/dEhSLf8GIo/ahFhBQI8zNEGIJmuNTFrnIANvoBDv0JF2te/J40q3B3jfpbLmaBR+G5ETziZo0Jrr9NG2XztqDFpzHZ+jYUZtQjTtysqMepiO1GiVnKinvvA9edyotd977js/frRMTtSDUyfV8m8h8qhNiBUE9DhDE4RosiXrox+iI30WveyAz303WU/K5330uf+p5d9C5NEEIVTUJkRT8jcrox6kIzluGD3C537nFBXpmhFDqp1Fb5HUV8v27qndX0ItoDYhVhDQ4wxNEKLFuvfJHP591AN0ZEc7WZPve/9NgUzOv2RS21ecbe8oc3SArC2r5d9E5NEEIVTUJkTLkj27dcWwgVEP0ZEaNZ0N35WVqYenTfYK81/u2FaLv4HaQ21CrCCgxxmaINQ2694hk/2KfD/3/BQbh7v7vMTd63iYPFn3PllbXEu/gdoXziYoeU1njdx2g6NG8prOfI6GGbUJtW3Jnt26f8qEqAfo2hjvLVta4/E4XFCg/bk5Nc78HsuoTYgVBPQ4QxOE2mRLvpNJvVQxcT95eheZwiUyBVMqtvdEtrmNTGbPU/KseChoghAqahNq05DV30Q9NAc77pv0qfZmZen5uV+c0Psr7zEf9v230T7sUUdtQqwgoMcZmiDUFmutzOG75cjnl/scCTLZL5d/qZA/SibthhNely36KtqHP6poghAqahNqS1penqMfjeZrjP9hvRbt3qX/rvhaLZNObNtbD+ynrMLCaB/+qKI2IVYQ0OMMTRBqiy075IDQHaWgn/PPmo+PyZc52k8m/UaZtGtksl6Qde+ohd9M5IWzCer//fUatvV/HDX6f389n6NhRm1CbZm08YeTDsxtBvartXDe4riz4Cc7vti2tcbjszs7Sy/Nm6Mrhw9S51HD9P7XS5VbXFQLv5nIozYhVhDQ4wxNEGqLLUsNT+BN/7UDQncoo41Mzv8FPja2ROZwd3lfXZAgk3a5bGnsT85DE4RQUZtQWyaHIaBfOWyg3+eHO3nM27k94LHZk52ly4cme+1by+RE3fnpWBW5S2vpNxQ51CbECgJ6nKEJQm0pv8T9Hp3cJe4JMhkPyaTf4oDgffy4TAHvUS9aHvjYFH7uf3+znq2l31Dk0AQhVNQm1Jb0/LyA4TqYs9Udhw7Ug9Mmqf3gAVEP3ceP9oP8b0/L5ETllwSexPTvX831e2wm/rihln5DkUNtQqwgoMcZmiDUJluyRia1Q3nwTG19LKxn/kW2dKtM9j8CB92YHG1kjAl4XEzO68cdkyoj7Ypa+u1ETjiboL7f36DBW29y1Oj7/Q18joYZtQm1acSa79Q8qa8njLas+N/vf71UP+Xk6MbRI2o8Q97SAYE8lHH3hI9rPC7XjhziN9z/9cvPauE3E1nUJsQKAnqcoQlCbbPuXTI5vWUO3yeT9bRsccqxv7MlMkf/U3FGOtrBOhyjrUzWSzUeE5P7VoCAfl0kfx21giYIoaI2obYt27dHT30xS7+dOE7/XPSVdmQe8fzdoaNH9eTnM8N277cTxvTNG2s8JjeOGeHzva2SE/X3r+ZG8tdRK6hNiBUE9DhDEwQnMn4v+Y6l0VYm/XrZsoM17q8tWe1/Hbnv1sIRjyyaIISK2gQn+sdXc0+JkN5z5jSVltX8+M9+q5b7neF+6Z7dtXDEI4vahFhBQI8zNEFwEmuyZQtny2S/6oCAfZLj6CBZkxncflsrk/texXsT5Ln0//DdsiYnwkc98sLZBH24+kYN3HKzo8aHq2/kczTMqE1wkl1ZmZq08QfdNf7jqIfrkxlXDh+k6Zs3BhXOJSm/pES/mzjOc9a88jL/1xfOl7U2wkc98qhNiBUE9DhDE4Rose6dsiXfeQKoLZgok9o++sE6HCPtqpCbF2OMTO6HMmlXV5x9v0GmYApNUJV10ATFB2oTosFtjNanHtLaQwdVWlam0rIyvTz/y6gH63CMVsmJen7u5yEfk6zCQj0xe4YSBvVXq+RE/W7iOK07VPOVYbGA2oRYQUCPMzRBqG3WvU/m8B+OC7TtZbJejn6oDttoK3P0w9CPS97Aive38frT5g2PwG+hdtEEIVTUJtS2Rbt36bqRQz2B9urhg/XXLz87JS5prxzLf9ob0jEpM0b3T5ngdZl7q+REtR7YT2tOgZBObUKsIKDHGZog1CZrS2TSb5LvCdFiffb2iu3PfFzWFoV2XEy2/F890EHW5EXoN1I7wtkEfbC6qwZsudVR44PVXfkcDTNqE2rT5sMZapWceEqF8crRomIM+u6bkI/Lgl07fK6zZXKiHp42OQK/idpFbUKsIKDHGZog1CZbNNcBQTqCI62TTPa/ZPNGyJYdCP64FC8JuF5bvCKCv5XIowlCqKhNqE2vLZwfc49JC2V0GzdG7y5bqkk/blBeDc8+P97bKYvVemA/v8E/1m/BojYhVhDQ4wxNEMLNWrds8QrZonmyZalef3dsIrRTYQQ6499WJrWtbMGE4I5ZyXeBA3rJ+kj8qmoNTRBCRW1CuOUWF+urnTu0cPdOFZSW/v/svXd4E9e2/h9acm7uPffe870l95xz7/mdUGyThPSEdFKMgUAqtiGEEtKogRBCQiohpJAc22BjTMD03nuvxvTeezMlWLJl2bIlWW2v9/eHZNnCMyPJHmlmNPvzPOvBWDOjPXtgr/XO3nutgM8SZ05VXETLPWsu9rsHfhuHY4ZCkV4KJG33DtH67/eMH8sFOrhv4kQHLtB1Bg+COHJCzsNgxqcDhWrZSBB5QOQBMz6pAmEdXRFP7gvB+43cYMan4M/eXrP/jG1AxKLw9CKHnEHQT/tfQMbptqqyn/a/wMdRmeG+iSMnM44eRkL2GL+4vDcnE8vOnAIAXC41x+TSdjFrlpWOp6ZMhIcF9yvnTMWC12ielY4vt2yM9GOLONw3cbQCF+g6gwdBHLkgVgZmeFBAZLYAs6SBlX6sAsEcbUsAK/9HaP3n3A9W2MrXf75Sa4b7Qc5DEX5ykYcHQZxw4b6JIxf5BVdEZ5kXnzqJdrOnKS6albDd166G1H85B/b6RXnVbHrbmVNhttsj/OQiD/dNHK3ABbrO4EEQRy7IOhPiy77jJD6LZWsJVvZV6H3oMYAqcsDKPgdVTAB5iiL4xKIHD4I44cJ9E0cu3l2xRHCZdtNb/tSbrTl/NuQ+PGE0YNT2bfhs03osPn0SDrc7gk8senDfxNEKXKDrDB4EceTCu7+8Zf1FrTFRBcJaPiPbYqUfjeLIGQSN2v8i/nE6SVU2av+LfByVGe6bOHLx4owpsgja9rOnKy6q5bKmmWm4Uc7/b3HfxNEKXKDrDB4EceSCbPPlEbVlI8HMnyourOtvCWBFiWGXXItFeBDECRfumzhy0Xf1CtFEZ2HNOJ87g8SZ8oh9pcX58E3rlX4sqoD7Jo5W4AJdZ/AgiCMXxCrAjK0hXOM8DDM85vtZYC+7Ws3UC8w6B6z4Vd/vWoKVfhIzS9TrCw+COOHCfRNHLg78fkOWZezx2WP8NcWVFtmh2s/525CxZycey83B3ZneDO5j9uyCO4QEcXqA+yaOVuACXWfwIEjdMMY0VcaEXOfBijvWU/BqdK96+RhvHzAriEKvM6sH5AyCRu5LxC+n2qvKRu5L5OOozHDfpG60Vlli1bkzeHhituKCWQnbc/0aGBHKHY6QMrfrCe6bOFqBC3SdwYMgdXI07yQGP/MV2jZMRqd/eRuZ/XNRbq5QullBIWYBKx8DZnzel9Fdo2K7LmZ4MCxhTswCsk4HK/0UrPyXkMqxaRUeBHHChfsm9UFEINscsKLnvWOe8VmQdaomxPqFEhM+2bAGj+XmoOX4sYqL5mhZ08w0vL9yaVh9daXUjF935WPI+jWYeHA/Suy2CD0V5eG+iaMVuEDXGTwIUh/Htp9CUuNUJDVKQWKDZCQ2SEZS41T0eXAoXE6X0s0ThVgFWHEHaGpputzmDq1sDbkLfDXh4+DdEpAAVhgHsi2J8FNSBh4EccKF+yb1QRXjhMc9y89KN02Sk0YDWo4fK8s+dC3aE5N/C3kl3toL5/zl1JpnpaNpZjoe/C0bZ4pjc7sW900crcAFus7gQZD6GNLmmwBxXtO2zd+pdPNEIetUSJdZU4GAjrQZWoMceUH7ipX0gvBe/ZYgVhKFpxVd5AyCvt2XiJ9OdVCVfcuDINnhvkldECsHK7xXZOxLUHW+jZ7LFomKcy3tJ6+PvTJ3Jq5byiT7qcLpxD0CqwuaZ6Xj1XmzovS0ogv3TRytwAW6zuBBkPpIapwqKM7b3d4FWQNylW6eKKykp4RwfUhEkMaaxXlFtvuKaD8RM0ueT7Z50XtoUYIHQZxw4b5JXZBjj+TYR5WblW6iIB7GREV4s6x0tM6doLh4joY1z0rHizOmSO5BX3XujOQ1rpVJC3wtwn0TRytwga4zeBCkPl7/Uy9BgZ7UJBVTvpyjdPNEYSXvQnSm3Pi0CsRztCxBcskneQolzo0HWadG8alFBx4EccKF+yZ1Qa5T0gLduU/pJgrCiNBiXIaoaH1qykTFxXM0bXvBFdG+WnDyuOS550zF0XtwUYL7Jo5W4AJdZ/AgSH1MGDJNdBa94PR1pZsnCtkWS8wqP6AC4RxFM/cV7ycisKKXIPYyg1xnovjUooOcQdDXe5Pww8mOqrKv9ybxcVRmuG9SF95xKwm1V0LFe5PFkUfpJooycO0q3e4/r2lNM9Mw4+hh0X66VlYmutrgsdycmCzNxn0TRytwga4zeBCkPqwWGwY8Pty/rD2pcSoSGyZjaeYapZsmCZHLN4vuC9qqBGhRB+UFc1QtDswyWrqvKjf5+ic+8LzSoVF6WtGFB0GccOG+SX2Q6zSY4VFUbeVhhXHe6hXOI0o3TZIbFgta505AM59IrxLrKQvnKS6ao235EjPoADBi22a/mL87M83fZ0tPn4rOw4oy3DdxtAIX6DqDB0HqxOP2YOeyfcj5eBqmfzsf187eULpJIUHkAtmXg5n7g5n7gGwLwGzLgwjae8BM3VQgrOWyeJC7IHhfOXaBmbqDGR4AK3oRZJ0MIncUnlL04UEQJ1y4b1InxMpBttlgllEg63QQK1W6SSFhttsxfv9evLN8CT5evwb5BVfw2cZ1kjPrj+dOQNuZUxUX1XLZU1N+AwuSzZ0RYcbRw3hp5lTcm5OJzgvmYvPli1F6StGH+yaOVuACXWfwIIgTach1TlrQWkaDWRcjZjK9l2cp3eWqQ84g6Is97THyxCuqsi/2tOfjqMxw38SJNLmHDogu6X7ot2xk7duN9F07FBfWctmZIvVm2lcK7ps4WoELdJ3BgyBONBAvK9bCt1RSBcJaDjO0DmsvJhGB7KvBTKlgxqfASnqDHLsi+CSUgQdBnHDhvokTacx2Ox74bZx/GXdNa5qZFlP71gesWRlW31S6XcjevxcvzZyCJ6f8hs83rUdBqTZWS4QD900crcAFus7gQRCnvjB3IVh5JlhFFphLeCkcMYt32XvALHmMzJjXtMptYfUdVWT7zq3ai54AVhgHsocXTKkdHgRxwoX7Jk59OXTzd/y8Iw9TDx+C2W4XPOZUkRFJs6YpLqAjafHZY2BzOUPuNzdjSF00L2B1QfOsdNw/IQuXzCVyPR5VwH0TRytwga4zeBDEqStEBGYeXFukmvuL7qUmTyGYaLZ3rZrvRUPpJ6Ag+/sC+8IE0VUFxtYgcsn1qBRHziBo+J4OGHHiVVXZ8D0d+DgqM9w3cepKWaUdL0yffMuMeLpoBnMiwnmTCd9s3SQ4m641qxLWzbPS0TQzDYtPnwyr/9acPyt43eZZ6Ri8frUcj0g1cN/E0QpcoOsMHgTVH2uZFfmL9yBvwS5YTOVKNydqsPJMcdFaMT7gWHJfBNmWgCo3g1VuUYGolsFKuoMVdwQzdfPeW5hlhsi+SvL65Doh5+NSFB4EccKF+6b6Q+5rIPtKkCMPRKHPoGqd9rPFZ8SPGQr9xzEi7Ll+DQtOHsfBmzcwavtW0ZrpWrIeSxchadY09Fu9AvtuhF+a9bNN60WX97eaEFs5Vrhv4mgFLtB1Bg+C6se6KVvw8p3d/HXK29/RFYszVindrIhDRN7s46IC8xGQfSlYeY43U3nNz/xlelQgsutsT4BZfgAr/wfIVbfyM1S5IYhAPyfzU1MOHgRxwoX7prpD5AYr+zJwnDW2Bjn3K920iHPeZJIUrx+uWoZpRw4hbdcOPH/LLPtz03IVF9f1tZ5LF2HEts347eA+GK0VderDr7ZuEhXoj0waH/wCGoL7Jo5W4AJdZ/AgqO6c2nMOiQ2T/eK8pu1bK7yULlYgZg1RyAoJ8XjERmK4BPiXqJePrVsfGu4X7p+ixLCWy6sdOYOgYbs74uvjr6vKhu3uyMdRmeG+qe5QxXiBsTcezPAAiJmVbl5EWXfhfJ3FbfOsdNwzfiyaqUBo18dajMtAs6x0xGePwfYgdc+F2HXtqmj/fJe3Rf6HpiDcN3G0AhfoOoMHQXVndM8stGuSWkucJzVOxZcv/6h08yIKEQMrFBKXoVocmPl9EQGvUTM8BmYeFNaMOtlXewNn/170BLDCViDngQg+vejDgyBOuHDfVDeICMzYWnTcJesMpZsYUU4aDfUWuL2XLVZcZMtlTTPT8PTUiRi9YzuKbNaQ+pCI8MXmDX5R3tR3nRdnTEGJ3RbhJxhduG/iaAUu0BVixIgRuO222wLsrrvukjwnLy8PDz/8MO644w7cfffdmDBhQtjfy4OguvPxs18Lzp4nNkjGOwmDlG5exGHlafUQtC3BSt4BK3xMeWEtu8WDHDtD7kdynQWzjAQz9wEr/xXkDn/PoNrhQZB24b5JWxA5pcddy09KNzGiEBHa1jMr+8C1K2OqxFqVPZabE/KydyLClsuX8PH6NeizajmmHz2ECmfs5THgvomjFbhAV4gRI0bg3nvvRWFhod+KiopEj798+TLuvPNODB48GKdPn0Zubi6aNGmCxYsXh/W9PAiqO5n9cwVn0Ns1ScWo1HSlmxdxiNwCWdxjaEa8PmZ8PqaWqNcXOYOgobs64ctjb6jKhu7qFLPjKPdN2oMVPS86NpFtkdLNizhGa0WtLO7NMmNPcNfFRsbYEvX6wn0TRytwga4QI0aMwAMPPBDy8Z999hkSEhICftenTx888cQTYX2vWoOg84cuIWtALkampGHe6GWqzI5ecPo62t/eBW0bplQL9IbJaNsoBaf2xE6Cr2CQ53cw2zxv+bTKXcqLY5UYua8q/WhUAw+CtAv3TdUQMW9yx9KhYKVDQPYVqiyHSLZ5AmNSApjxKRCLrSXKYhARjhoKMfXIQWy7chm/7MwPqOutV3t0Uo7Sj0ZVcN/E0QpcoCvEiBEjcOedd+LPf/4z/v73v6NLly64dOmS6PHPPvssBg0KXEa9dOlSNG7cGC5X6AGDGoOgFePX+2ei2zZKQdtGKej83+/i+rnflW5aLQ5tOoZuf+/nF+ipf/kAO5buVbpZisEqZioujNVi5L6m9ONQDTwI0i7cN3kh8oCZB1SL3cJ478+mbiByKN28AIgIVDEpsNJG8Zsgt/hzi3W6L1mouDhWgz0yMbaysNcX7ps4WoELdIVYu3YtFi9ejOPHj2PTpk1o06YN7rrrLphMJsHjW7RogR9/DExEtmvXLtx22224efOm6Pc4HA5YLBa/Xb9+XVX/eYt/L0FSY+HEa5+1Hal08wRhjOHi0Ss4f+gSPO7wamHHEkQeMOOT4qK1YiaYQSx5UYyZoTVf4l4DOYOgj3e9is+PdVaVfbzrVVWNo3LCfZMXsq8Q+f8eB7JOUbp5ghCzgZxHQe4rSjdFUc6aikUFa/OsdCw9fUpx4Rwt+3zTeqUfh6rgvomjFbhAVwlWqxV33XUX0tOF9zK3aNECP/0UmOxl586duO2221BYWCh6XaGEP2r6z7ts3NrAJeO3WLm5bnU9OZGHPEXSotXyC2KjvFoIVpmv9ONQFTwIih306puY+UP4Z81vteLXlG4eR4Ilp09KitYFJ44pLpyjYS3GZcBstyv9OFQF900crcAFuopITExE3759BT+r6zJCtc9SLPzHCiQ1EhfoJYWxXcNVyxBVQjJJXMkHqC4nFsNWMVXpR6E6eBAUW+jRN7GSnuL/54vaKd08jgRrL5yTFK6Ze3crLp7vzkyL6B75+HFjcM5UrPSjUB3cN3G0AhfoKsHhcOCvf/0rRo4UXtb92WefoWXLlgG/69u3r+YT8Vw8ekVQmLdtmIL37v2YLxtWOZIz5CUfKC+eI2WGp8HKhut+KakYcgZBg3a+hmFHk1Vlg3a+pqpxNJLo1TeRdTKEX0AmgFlGK908jgRHCm9KitdhG9cpLs4jZS/PmYGxe3bB4lBXngS1wH0TRytwga4QQ4cORV5eHi5fvoy9e/eiU6dO+OMf/4iCggIAwPDhw9GjRw//8VWlbIYMGYLTp09jypQpMVPK5pde424R58lIapSC/euPKN00jgTkvgZmEC/vw0xviQS4MWAV05TuflXDgyDtwn2TF2LlYEWJt4xhcd58Ex6j0s3jiEBE2F5wWVLEDly7UnEhHSkrrFBfBRw1wX0TRytwga4QXbp0wZ///Gc0adIEf/nLX/Dmm2/i1KlT/s979eqFNm3aBJyTl5eHhx56CLfffjv+/ve/Y8KECWF/r9qCIABYOWG9YJK4fWsPw1pmReEVI9wut9LN5PggcoCVDglByMaoOC/kGduDwYMg7cJ9kxciBlbSp/b/f8MTIE8hyFPs/ZOv8lINV8tK0X72dMVFslL28MRs/u8xCNw3cbQCF+g6Q21BkLXMipf/6S3BJe4d7+yGtr796W/+Z28sGbNac86HiHD5eAGObD0BS0lsvNlmZSMhmjxJD1Y6TOlHoHrkDIIG7nwDQ4+mqsoG7nxDVeNoLKA230SOPJExID6wOkXRyyDHHqWbGzZELpDzEMh5EEROpZtTbzyM4YUZk9E8K11xoayUrTl/VunHoHq4b+JoBS7QdYbagqD8xXtEE8QJ2dLMNUo3OWSunb2BDx8c6m97+zu6IvfzWWCMKd20OkPMBlZ4r/IiWRF7BKxiCogYiGo/Q/IUgiomgFlGgGzzQMyqwBNSBzwI4oSL2nwTK/saoVWhiAMrbAlynQp+UZVAlevBjDVeMhgeB1WuU7pZ9WJ7wRXFBbJS9tKMqcgvuAIAYAKTGMeNBvy8cztG5m3BlsuX4NFwDFJfuG/iaAUu0HWG2oKg7Yt2hyXQO//3u5qoPe6sdKLLXz8QrPE+b/QypZtXZ8h9tY7iVusz7r5s9KVDwIo7+oLaR8HK00HkBDm2gRXe47tPX1BvfArkLlD6kSkCD4I44aI238TKvkLoVSgSwEo/UbrJIUGu475x6tYtSPEg1zGlm1dnZh07Uidxq/UZ9+ZZ6YjPHoPPNq7Ho5NyfIJ9Cpad8b4w+nVXvv+4FuMycHdmGrovXQiHW5/bBrlv4mgFLtB1htqCoHJzBTr8oWtYIr3ouknpZgdl8+x88ZcM/9Vbs7PoRHawwlbhidvizmBFSSoQ2ZGweLCS98AMDwoEvAlgpreUfmSKIGcQ1G/Hm/j4SBdVWb8db6pqHI0F1OabqHJreGNB0UtKNzkkWOmnIi8etPOSQYjd166GLW4/3bgW94wfq7jIltuqyrd9n7dV5PN0jN+/V+lHpgjcN3G0AhfoOkNtQRAALM9e508Ml9gg2b/vXMjaNekCu7Uyqu2zmMox58cl+Dzpe4xKTceeVQeD7oWf9vU8tLu9i+h9VJRqd/kzK/9VQIxK2T0qENJhmOl9Wa9HnkKlH1nU4UEQJ1zU5puIGJi5Kklc3C1/CryoM3WLfhvdF8As33lrtpeNALmC70Fmxa+Jj1fFr0Sh1ZGBEaH97OlhzYi3ysmMaC1yue3zTevDOj5uXAaaiXz2wvTJSj8yReC+iaMVuEDXGWoLgqo4tPk4RrzxKz64/xP80DUDnf7YHUm3CPWkxqn45Z1xUW2X8WoRuvz1A/9Lg6qXCNmDpkiet27qVlFx/vqfesHjUf8yfTGYpwisqIPyQjpi9lSYx0tjex83AAAgAElEQVS/rCDXeaUfWdThQRAnXNTom4jcINt8b8nI4lclq1eQfVV021a5Fd7tNFWz4QlghfGgyg2S5zHzYIjOoJsHRan1kSG/4Arun5CluJCOlHVZNF+2az0yabzSj0sRuG/iaAUu0HWGGoMgIY7nn8Zrf+rpFcU+cTz46a9gLYvuzPPP3TMF95EnNkjG6b3iwsturcSb/9m71rltGyZjxogFUbwDeSFy+vZga31PeRAztJbnHg2Pg8il9GOLOnIGQX3yO2PQ4a6qsj75nTUxjmoJrfgmsk5G9R5u38s5y+ioVhghcoEZnxB4ORgHZnhUMis7OQ+JvFSMAzkPRO0e5OZiiQn3jB8rOmMcK9ZMhj3zzbPS8dHa6L5QUgvcN3G0AhfoOkMrQRDgFblb5uRjUfpKHNt+qt4BUKXNgbMHLuLmZUNIxxMROvyhdgm4qqX2k4bNlDz/wpHL6N60f0DpuDF9J2oiyZ0YZF+lvHiOmtWcnZIS6/eBmT++Jej1/ky2eUo/MkXgQRAnXLTkm8hTCLLNAVlngNxXZbheMch1DMRKQjveeUBy7CLHTunz7UvADPfXeJF4P8i2uN73oSTDNq7TfMK3UCzOl+itSqiL3XPzrHS8uWAO2kzLDTimeVY6ErLH4qypWOlHpgjcN3G0AhfoOkNLQZBcEBHm/bwUr/yxu18sD3rqS9y8JC3UiQjtmgjPnrdr0gUThkwL+t2MMZzYcRo7l+3TRHK7YDDLdwit9JDWLQHMPACsdBhY0Utgpq5g1ulgxudriHdvxnaqXO9dCluRA2Z8yivOi16O+pJXNcGDIE646NI3sQqw0o9rvABMACsdDiLpPCvk2BNEoG8P4bttIMc2rzGbXLekGM9MnaS4eI6W/bxjO7ovXYg203PRd/UKTD18EAnZY9CsRqb2JyZPwJVSM4psVny+aT3uGT8WzbPS8c7yxThpDG2SIhbhvomjFbhA1xl6DIJWjF9fS2AnNU7FW3/rA2el+FJAAPj61Z9Fl7gf2nw8SnegHlh5BkIvPaRliwcrHVrr/okcIPtSMMsoUMUEwQRw0VzqqlbkDII+3J6CgYe6qco+3J6iu3E00ujRNzHzh6i9OicerHSY5HlElWCGh0TGrvtBTLtJSOtKx7kzNZXwrT625PTJWvdfZLNi4sH9GJm3BfNPHofNVXtrFfdN3DdxtAMX6DpDb0EQEaHr/34omrBt0yzpmYYrJ6/hlT92R1LVTHpDr337xi+6dHbkvojwMrhr2Eq/8tZCNg8AWSeDWJnS3a8ZeBDECRfd+Sb3JckXhOQJssLLtsh3bELAn2SbE6U7UBczjh5WXDhHy3IP7cdH61Zh0LrVWHXuDNwaLduqBNw3cbQCF+g6Q29BkL3CLl6y7fYumDx8dtBr3LhwE2M+/A09mg1Av0c/w/LsdZreR15fyDrTJ9IT4F/uXvwmmOHFGBTvCfAngzI+BXJfD+wLZgM59oCch0Gk338Tt8KDIE646M03UeUGybGHHHuCX8OxC6zkfbCiF8BK3gU58qPQcnXiZgx9V6/A3ZlpaJGV4d93PWzjOsUFdSSsWVa6fx96z2WL4LylMoyhogL5V6/gQon2t9bJCfdNHK3ABbrO0FsQxBjDa//eU1ikN0zGypz1irXN5XTh7IGLuHLymuZm48ldAKoYB2b5CVS5GYy5wSw/qkBQR1ism/tX94F1FpjhgerPjc+AHLsVfCrqQc4g6L3tqeh36G1V2XvbU3U1jkYDvfkmcp2QFujuAuXaxkpBzqMgz03F2lAXiAh7r1/Dzzvy8I9dO3DSaIDT40GH2dMVF9SRtrknjgEAHG43hm1cF5DtPXnhXBRWlCv8dNQB900crcAFus7QWxAEANO+noe2DQNrqrdtlIJX/rUHKkqjv1ev3FyBZePW4o3/eMffnncSBkmWbYsm5DGBKreCnAdBFHzpHLlO+UqvKS2go2HxIHKCKjcJfsYK76s1y65HeBDECRe9+SYiAit+HbVzeiSAlfRSpj3um2ClXyMgEWjJeyFnl480F0pM2HzpIi6GOCu8+PRJPDxxvOLiOdLWNDMNXRfPBwB8u3VTrVJszbPS0X72dM1NBEQC7ps4WoELdJ2htyAIANwuN0b3yAoQ6Mn//S5O7DwT1XZcOlaAIW2+EZzNT2qUgk7/8jaKbyi3HI2IgVlGBwaMRc+DXOLJ8IiVgBkeRuwtbZeY2WI2b1Z3wdJrCWDlaVF8auqEB0GccNGjbyLPzdovN02dQZ7o+gGyr/Yukxcc8xK8bVJQ3Jntdry9dGGA6OyxdBFKK+2i52y7cllx4RxNe33+bFgcDn8ZNiHbc/1aFJ+aOuG+iaMVuEDXGXoMgqq4ceEmNs7Mw941h+B2uaP63cZrxXj133qIZoSvyiw/Y8SCqLarJmSdIjwrbHgYxIT/vVDFRBGhGosWD2ZKAQAww+Mix8SBmQdE87GpEjmDoN55qehzsLuqrHceD4LkRq++iYhAzgMg+1LvsvIoC+Fge+H9LyadB6Parpp0X7qwVr3v5lnp6LVMvHZ718XzdZPVvVlWOrL27cZZU7HkcXOOH43iU1Mn3DdxtAIX6DpDr0GQ0uR+PktSnCc2SEbbhikYmaLM7CsRgRmfFhWdZBNOpsdKP0XslV17AszUHbVXBcSDVXqz/jNTMsRn0H+N5qNTJTwI4oQL903K4J3BD74CimzzFWnfxRKTpOi8XGoWPO+hidmKC2e5reuieXhyym8BLyuaZqbhkUnjUWy1wuKo9NdBF7Kd15TLa6AWuG/iaAUu0HUGD4KU4ZPnv5UU54kNkpHUJBW/DZ2hSPuIXBLBWQJY8atgRS+BFXcCVUwCUSWAqrroMTqDbniq9u+MbUAeA6hyrcA5cWCFLUHuq4o8QzXBgyBOuHDfFH2IPCGPh+TYoUgbt1y+JClaOy+Yi2emTkLXxfOx5vw5/wqETnNnKi6oI2FxWem4Lyez1u8/XLUcHsYwfPMGwT3oiTOngvE96Nw3cTQDF+g6gwdByvBD1wzpGfSGyWjXJBXXzt5QrI3M+KxEgBYX+LOpq1fUO/YqL6SjaglgpZ8DAMg6Gazw3hqC/nGQI0+x56cm5AyCem3rig8O9FSV9drWlY+jMsN9U/QhIl8OkSBjXtFLipWRvGQukRSsVWK0ajn72D27AADf5W1RXExH21aeOwO7y4UBa1cG/L7T3Jm4wf9fAeC+iaMduEDXGTwIUoZDm45Jzp6/8q/dkb9kr6JtJOv08MSqeWigQNWNtaruM2bxZrx37AaRS8Gnpy54EMQJF+6blIGV/wLJVVBFbUHuK4q28Z3li2vtQZeyTzfEZu1zKWuWlY6+q5f7++xqWSk2XbqAE0YDz95eA+6bOFqBC3SdwYMg5Zg9ajESG3pLvCU18pZ9+7zdKOxctg+VNofSzfPOppRngBXeUyNAi9Hl6/WyljzgCQIPgjjhwn2TMhBVgpW8U2O8927VYZbvQc59IZXajDRllZV4d8USxUWwmq1pZhreXbFE6Uelerhv4mgFLtB1Bg+ClOXmZQMWZ6zCgl+Xo+CUOkueECsFOXaCXMfBDI+qQBCryRLAzH2UfkSqR84gqMe2t/DegV6qsh7b3uLjqMxw36Qc3kzyB0EVE0C2uaqpe34rBaWlyC+4gh1XCxQXxGqzpplpmHnsiNKPSPVw38TRClyg6wweBHHCgZX0VoEoVoslgBnuB7nOKv1YVA8Pgjjhwn0TJ1SICK0mZCkuitVizbLS0X72dNhcfJtVMLhv4mgFLtB1Bg+COOHAnIdVIIzVYPeDlX4Ocl9S+pFoAh4EccKF+yZOOHy/XX9J4ITs8dwJyNizExaH8tvktAD3TRytwAW6zuBBECdcWEl/hFInN5aNnPuUfgyaQs4gqNvWbnhn/zuqsm5bu/FxVGa4b+KEQ7nDgcdyc/zZ2/Vo9+Vk8lnzMOG+iaMVuEDXGTwIkodycwWunrmhiuRukYbI6c30a3jAK1iNT4KVjQQrbAVvUqFYTCQXD1aY4P25bCRPChcmPAgKZPv27ejUqRP+/Oc/47bbbsOyZcskj9+2bRtuu+22WnbmzJmA4xYvXoyWLVvi9ttvR8uWLbF06dI697fScN8kD+QpBLkLVJHcLdLcKLegz6rl/lJrHefOwPDNG3B3prf2d6yJ96Y+a56VjuZZ6Vh74ZzSj0BzcN8UCPdN6oULdJ3Bg6D6YbXYMLpHFto18dY07/Qvb2Pa1/Pg8ShTIzaaELm8CeR8gR95DKCK8WClw8CKXo4doV76BVjpILCyz73J8rg4DxseBAWydu1afPXVV1iyZElYQdC5c+dQWFjot5rjzO7du9GoUSP89NNPOHPmDH766Sc0btwYe/cqW66xrnDfVD/IdQ7MlFw9jhmfA1WuV7pZUaHS7QpY4n3CaMD327diyPo1aDUhyy/gtWpNM9MQP24MRmzbgr6rV+CH/G24WGJSsMe1C/dNgXDfpF64QNcZPAiqH5++9B2SGqcG1jFvmIzJX8xRummKQqwCzPyB8uK6vmadonRXxgRyBkFdt3RHz33vqsq6bule5/sLJwgqLS0VPSY1NRXt27cP+F27du3QtWvXsNukBrhvqjvESnwVN259SRoHcuxSunmKctZUjDbTJysusutj94zPxL4b15XuypiA+yZxuG9SF1yg6wweBNWdcwcvBgrzGtbxzm6wV9hDvhZjDEfzTmLjjDycO3gxgq2OLuS+VKOmrvaMPAaluzAm4EGQOOEEQX//+9/xP//zP3jxxRexdevWgGP+7//+DxkZGQG/y8jIwN/+9rew26QGuG+qO1Txm4A4b+H9XUnP8K5FdlDlRpB9OchzM0Itji6MCPtvXMejE8crLrbrYi9Mn6x0F8YM3DeJw32TuuACXWfwIKjurJ28WVSgJzZIxsWjV0K6zs1LBvRuOTjg3I+f+waWkvLI3kAEIGIg22yw4o5ghY+BFXVSXGTX3e4FUaX3vpxHwCw/gJV9A6pcDyK3wj2tLfQSBF2/fh0Wi8VvjhAyKYcSBJ09exaTJk3CoUOHsHv3bvTr1w8NGjTA9u3b/cc0adIEc+YErtyZM2cObr/99rp1uMJw31R3WOkgEYHeAszwSMjXocqtYIaHAmbgmeVHTW7zKa204+cdeXhqykQ8PikHz03LVVxo18WaZaWjx9JFAACXx4PV587iyy0bMWr7Nhw1FCrcy9qD+yZxuG9SF1yg6wweBNWd/esOi4rztg1TUFJoDnoNIsK79wz272GvsqTGqfjmtV+icBfywsq+VIGwlsPiwSwjQERgltG+3yWAFbb0/mzqCqLQV0joHTmDoNQtPdB973uqstQtPQQT5YwYMSLofYUSBAnRqVMnvPLKK/6/N2nSBHPnzg04Zvbs2bjjjjvCvrYa4L6p7jDLj/AntQywOLDil0O6Brmv+8a72hU7yKatLVwVTidemjkFzTW+97zKNl26AKvTiTfmz8bdmWlokZWBFlkZuDszDWm7dyjd3ZqC+yZxuG9SF1yg6wweBNUdj9uDt/7Wp9Ye9KTGqfj2jdDE9fH80+Kz8A2TUXxDO4lfyHVOBcJaJjN/6F3a6dgjKuCpIkvpLtcMegmCIjVLIcQPP/yAhIQE/99jbRkh9011h9wXBIW1V1zPDX4BAKx8rLjIL2oX4TuQl8mHD8ZEBvfmWenI3u9NrPXLznzRezp083eFe1w7cN8kDvdN6oILdJ3Bg6D6cfl4Abr+74e+WXOvsB7w+HCUFYfWn5tn50sukz+1RztlU8g6VTQo1ISVDgPZFoJc1eVBWEkf8eOLXlCwt7WFXoKgSO3zE6Jz58544YXqf4Opqano0KFDwDHt27fXbCIe7pvqB9mXgRXeGzhmlX0Xcrk1VjpMRKC3ACtsFeHWy0vPZYsUF9f1sXH79mDJ6ZMoslr993RfTqbgsc0y0zFi22YFe1tbcN8kDvdN6oILdJ3Bg6D6s2/tIXz4wFC88q/d8e49g7F59vaQ9+hdOHJZVJy3a9IFFpN29qGTbY6mBTo5jwbeD6sIcj+PKdTT2kPOIChlS0902/u+qixlS8+w7q+iogJHjhzBkSNHcNtttyEjIwNHjhzB1atXAQDDhw9Hjx49/MePGTMGy5Ytw/nz53Hy5EkMHz4ct912G5YsWeI/ZteuXWjUqBFGjx6NM2fOYPTo0ZouZcN9U/0g8oBVTAIzPgtmeBCspBfIdSz08625EN7HHgdW/GYEWy4/H65aptnSag/+Ng4Od2DOk7wrl0WPb5qZhk83rlOop7UH902BcN+kXrhA1xk8CKofm2Zt9y9rT2yQjLaNUpDYIBkzRiwI+RqCpdoaJOOt/+uDglPXItj6QIgI5NwHqsgB2WaDWEl453uMEjMuarY4MHP/Wi9VmGWM9HklveXs/piGB0GBVGW+vdV69eoFAOjVqxfatGnjP/6XX35Bs2bN8Ic//AF/+tOf8Mwzz2DNmjW1rrto0SLEx8ejSZMmSEhICAiStAb3TfXDOwPeosZLRm8ODXLsCel8b6m2h4XH9JLeIFYR4Tuo0RZygOyrQBXjQfY1IHKGdf6Ks6cVF9rhWtXy9bknar9USZo1TfLchSePy9X1MQ/3TYFw36ReuEDXGTwIqjtulxud/6u34Ox3UuMUmA3idSFrUlFqxeftRwlcIxWv/aknjNeKI3wn3lI6rKRHjUAuDqzwHlBleG/iyTZXBYI7HGvlfSEhEPAxU5DycNYZcnV/zMODIE64cN9Ud8h1UvxlZNGrYVznlHcGvtZ14sFMXaKSzZ3cF8CMT9fwTS3AjM+A3JdDvoaHMfRbvUJx0R2OPTN1EtZeEN7ilpA9VvLcsspKubo/5uG+iaMVuEDXGTwIqjtSddATGyRj8vDZIV8rs98kwVn0pMapmPTZrAjehRdm+Qm1lzPGeWdcPOGVbiHXKbCyb8EMz6lAgAebOR8g3idl30qfb/kp5P2cekfOIKjz5l7ouucDVVnnzb34OCoz3DfVHfE66D6rkWdD8jpEYMbnRa9Djl2RvQ8isKL2qD2LnwBW3DGsFwSMCBsunkf/1SvQakKW4gI8mM05flT0Xp6Y/JvkzPvmSxfl6H5dwH0TRytwga4zeBBUdy6fuCop0Nvf0TXkWubv3TdE9DqDnvoyovdBRN49ioJBWDyoYlL417ROQWCColZg5iFghQ+oQJjXCDBtC8XvwX0h+PkVOfXpet3AgyBOuHDfVHeCJuw0pYZ2HVYiMf4lgCqyI3sfrmPS46/rVFjXq3S7MHDtqgBB++ik8fhyywbFBfmtIvu6pUz0PiYfOiB5frOsdBy8eaO+3a8LuG/iaAUu0HUGD4LqDhGhZ9xAyVroK3PWh3StoS+MQJJv/3qtkm0RrodO5JIIglqCWX6WPp+VgjxF/tkMqtwoPFutuv3p94KZB4PZ14vuaWTWIEv2DQ+BKHi5Er3DgyBOuHDfVHfIcyP4y0V3QfDrUKXXBwheIy7i9dCpcqv0PTjEa34TEYzWClgc1cu9v966qVayuOZZ6Xhk0njFRXlNe2xSDkZt34p9N64LrhLwMIa+q5aLnt88Kx3vr1wakWcSa3DfxNEKXKDrDB4E1Y8D649IZmGf/u38kK4jVW5t1/L9Eb4LgBW9LDrjQvbaCT8AgNwXa+xbbwFWlARWuRXM9BaEl1eqTaDXtHvAjM946587dgf2TUVOkED3UsSfj9aRMwh6Y1NvpO7uoyp7Y1NvPo7KDPdN9YOVfio9bjkPhnGdW8fuOLDCe0HMHNF7II9BxJd4/Ql5hPOzbLh4Hs9Pn+yfje6+dCFOFxsRNy5DcfEdrt2bk4k203Lx5ZaNuFIa2N9dFs8XPe/x3AkRfTaxAvdNHK3ABbrO4EFQ/SAifx10Idu98kDI1xnTd6J/1rxqP/pvQ2dEJxFP5XphQV3UTnB22Zvh93ER0X2vZGCobvMGg2RbFKRvqo8nFloyQD3DgyBOuHDfVD/IXSD5QpKY+BLqgOswM1jxK77zWqI6geimCN+BF1b2DWq/PI4DKxspeHz+1StomlmdBb3msnGlxXZ9rHlWOu7LycJZU/VLiS+3bERzgfJxTTPT8Oq8yOeuiQW4b+JoBS7QdQYPgurPuqlbBZemf3D/J/B4PGFd68Lhy5g5ciFmj1qMyyeuRqjFwpB9NVjRC9VC1TwY5DEJH1uRIzGzIWYaqpFueAhEdu+9khPM+ITA/SaAmQdH8xFpFh4EccKF+6b6w8yDhMfpINuWboXIA6rcAlY+BmSdIeoXIgGRC6w8A8zwkH9sZuVjQeQWPD5l4TzN1jwPRaS/u6J66fpxo0H02IWnTkTrEWka7ps4WoELdJ2h9yCIiHBy11lsmrUdZ/dfqPNs9ZrczUj9ywd+cT6qSwZKiwJnKIgILqdLjmZHDCICeUwgZpM8jpn7hym443yBonZEOjl2VveL6ziYsXXgiwZTCp89DxE5g6DXNr6L5F19VWWvbXxX1+NoJOC+yQmq3AqyrwR5fq/jNRxglh/ACu+rIW4zQeS55TiPqOBVC0QukKcYRNI+NFgJMiHRGzdujOLiO1RrlpUOViNOmXviGFr4lu5XrRIYmbclKivvYgHumzhagQt0naHnIKjougl9HhwaMPP90ZNf1hLWoeLxeGC8VgyrJVDcOuwOTPx0Bl79tx5IbJCM3i0HIW9BZMvTRBpvCbIw9pQbHg4izsOdjY+GQN8bcM/egHm9dwbJuZ8HQGHAgyBOuOjZN5FjJ5jh0cAXnGUj61zWkagS5LlZa7sSua+CmQf4xvI4sJLeINdpOW5BMZ6eMjEswfvwxGzRz9S4LL7FuIwAgQ4AJpsN808ex8xjR2rtU+dIw30TRytwga4z9BAE3bhwE2snb8a2+Tthr6hatkzo9+hnaNcktdbS9M+Svpftu4kIw9uPQtsaGdrbNvT+uXFmnmzfE22Clb/xm/EFMOs8xcV2eBYHZnhMNLM7J3x4EMQJl1j3TUQEch4A2eaDHDv9s9rkMfpmvGu/0CTrVPm+32MCM7S+5eVoApjhfpD7smzfE22y9+8NSegOXLsSI7ZtVqUIF7PmWekYuHal0l0cU3DfxNEKXKDrjFgOgjweDzL6/BYgwDv9y9vYuWwfzh28KFnD/PeLhbK0QSo7+1t/6wPG6jYjogbIOjM0wWvuA3VncK9pCWCF8aDKjUp3b0whZxD0ysb38OaufqqyVza+F7PjqFLEsm8iTzFY8RuBY09RIsh9FVQxAaIrioxtZGsDM38kPgaWfSXb90Qbl8cjWYKseuZ8vOrKqwlZ1QuEZlnpeCw3B9fK6rbCjyMM900crcAFus6I5SBoccYqJDa8RRg3TEa727tg1W8bJAX6ka3SCVaMV4swumcWOv7z23j5zm4Y1TUDNy7cDDjGYipHxzu7SX5P0fXoJduJBMwyJrjoLX5dBcJbwspzwcq+Bit5G6zsG5DrjNLdGnPwIIgTLrHsm1jJOwIvLRPAitqDlX4D8drj8UGvTc59YKZu3msYHgcr/7VWThFy7JIeE4teitStR41Oc2ZICl+1l1xrlpmOJadPoO/qFXhryQKM3bsLxTbp3DCc8OG+iaMVuEDXGbEcBHVv2l9QFCc1TkXWgFxR0dy2YQqKfy/xX6fS5sDulQeQv2QvLCXlMBvLkPrn9wOWxyc1TsUb/+8dGK9Vl0BZmLay9guCmt/TKAXWMqsSXSMb3jroUnvL48BKhwgEoyox41N13tfJCR0eBHHCJVZ9E7mvS49JZT+IjKlxYEUdAq/lMYAq14Ic+d4cGY5d8M6+15yBjwczdQsY51hJT+k2mDpHu1tkxenxCJYfC5xBz8ZLM6aodon7JxvWKt2NuoD7Jo5W4AJdZ8RqEAQAHf7QVVAYt2uSirR3x+PLjj/66437hXajFIzukeW/Rt6CXXjlX7v7P29/R1d81nZkrfOqRPqEIdP8547umRWw9/xWG/Hmrwr0irwwU5cQxbBSGdzjwIq7gxXeL/DZvWC2VSAWe//21YacQVDHDe/j9Z39VWUdN7wfs+OoUsSqbyLnQekxy7bIO/MtsMyd7Cu81yAGZvkx8Bhja7CidoLnscIWIMd2fxuY4THJNpBtnlLdIwsOtzskEdxC4XJs3ZcuFHxB8OzUSTj0+w24wizTygkf7ps4WoELdJ0Rq0EQAPR/7HNBgdy2YQqWjF0Nq8WGUV3S0bZhil9g/9o7Gw67AwBw6ViBpMAWsvdbDfF//+Qv5ggK+cQGyWh/exeYbmo/22p49dDvVUCg17T7wQpbe83wRGC7yn8FY3aQp6hWCSJO/eFBECdcYtU3ESuB1Ioicl8Auc6BFb9S/XvDQyDrjOprWKcLv4wUHftagpVXvxAOuPatVpQUE2NgOPXQmys8W/7wxGw8PDEbrXMnoFVOlv/3j07KwZrzZ2FxOGC225Xu0piE+yaOVuACXWfEahAEADuX7ROc5e78X71Rbq7wH1dSaMbpvedrlVfL7J9bK8u7lLVtmILBT1cn17lx4aZXoAssc1+csSpq/RBJiFnAil4KQ6QrbQlgxudEAmTf74xPgKwzeRk1GeFBECdcYtk3ectU3iqo48HMHwQcR+7LINcxEFUGnm98PsxxLx5UkVN9XdsCkePiwJznotIHkebwzd8Rnz0GzTKVnSUPxZr6Zs1bjMuQXHLfcc4M7Ll+TemujSm4b+JoBS7QdUYsB0EAsH7aViTf9V51nfMnvkDB6eshnftFhx/Cmj1PbJCMNZM2BVxj+6Ld6PjPNRLFNUxGZv9Jms7efivESsAs36tAfMtrcpY00jtyBkEd1n+AV3cMUJV1WP9BTI+jShDLvonICWYZhepVRfFgpZ+CWEXwkwGJF6JxAsLf+3tyX63x/eRbIl/z2Pv8S+hjhdNFRqQumqe4AA9HqEt93izTWwf9uNGgdNfGDNw3cbQCF+g6I5aDoCrcLnvOPjwAACAASURBVDeunLwGQ0FRWOdN+GQ6kgRm0Ns2SkGXv37g28/eBe2adEFig2R81/kf8LhrLw20WmzYMncH1uRulq18mxphZV+JBIcaNcOjvBa6TPAgiBMuevBNxCpArrMgFt52J+9ec5Gx1r99pyW8q4LiQNZZwt/vvg6yLQTZV4JYuRy3pDrcjOHZqZNUmwwuXGuelY7+a3gtdLngvomjFbhA1xl6CILqyo0LN9HhD11r70NvmIxDm4/h6LaTyB40BeMGTsbBjUdjala8LhDZwcx9wxPB5k8lZoOUN3IXKN2tMQEPgjjhwn2TOGRfIjBexYMZHgXzGEH25WBl34CVp4HcF5RuruJcMpfgmamTwhLCn29ar7gYF7MnJv+mdJfGDNw3cbQCF+g6gwdB0hzZegJv/72fX5y/+Z+9sWnW9uAn6hhWuQXM+FQIAjge5DGAGRIVF+LCFhf2zBZHGDmDoHbrPkSn/IGqsnbrPuTjqMxw3yQOEYGsk8EMD1SPV8Uvg1xnlG6aaiEijNmzEwnZY4IK4BdnTIEzxEzw0bammWnoNHem0t0ZM3DfxNEKXKDrDL0GQUXXTdg4Iw95C3bBarFJHssYw4XDl3F673m4nK4otVB+LKZyrJuyBcvGrUXBqcgmmmHMCVb6hfgyTNVbApi5f0T7SE/wIIgTLnr1TeQ6AbItBjl2BM2mTswGch4Cuc5rOqkluS96E3PaFoJYSUS/q7TSjrazpoac4b2uy9AjKdLnnjgW0T7SE9w3cbQCF+g6Q29BEBFh8vDZAcvWO97ZDVvn7azXdR12BwpOX0dZsTr7cePMPLS/o6s/23xig2SkvTceHpnrrBJVepMPGarqjitdWu2WJaChCPPCFmDFnUAek6x9o2d4EMQJF935JlYOZuoROB4VPV/vJerEzN7SbaS+Ml1EDKzsa/+KJe+fLUG2JbJ/19WyUry/cql/L3rcuAzFZ8NrzopL/b5ZVrr/hcLnm9aDafhljNrgvomjFbhA1xl6C4I2TN8mXCKtUQqunAx/VpkxhlnfL8Irf+zuv87I5H/AYop+wp3i30tw4chl2K2BJXkKTl8XrufeMBlLxq6WtQ3M/GGIQlgtwtwXFFbkemetKnJAjm0xUQdYTcgZBLVd2wcvb/9IVdZ2bR9djaPRQG++iZV+jNrlHxPAjG1A5A77esTKwMyDqsc/wwNg5Zkgim6uFCICuS/5ZvkDx1WyzhIdl8l1VrY2mO12PJabEzCz3VRCGKvBmmelIyF7LDZfuojJhw9iwoF9OF1klK1POF64b+JoBS7QdYbegqB+j34mKFaTmqRi/ODwy2rNHrVYsNb6wNbDw15yWNcliiWF5oCScB3/+W3MGLHAn7Ru4qczBLPRJzZIRq+4j+r0nYLtd51SgRivYcWvgJVnSh9T1A5UuUW2PuAIw4MgTrjoyTcRM0u+SCTHtvCuRwRm6iIg+FuAlWeGfa26+iZyHvRlnPd9t/FZUGV1KVJW1AHC26ASwCw/1uk7hZhwYJ9qxHizzDS8s3wxvti8QbJNfVYvxzlTsWx9wBGG+yaOVuACXWfoKQgCgM7//a7wDHpDb5m0KogI187ewNkDF+GsFC615ax04tV/6yFaE/1o3smg7XHYHZg8fDbe+H+90LZhMvo98hn2rj4Y8v0U3TDhjf94R/D75/zoXSb4c/dMJDUWFuiv/muPkL8rGGSbq7wor2mWX8EqN0gfY53MZ8ujAA+COOGiJ99ErvOS4xTZ5lYfSy6Q6yTIdU5UOJPzoPj1DA+AqFLwvIBruK+BmQeDFd4DVtgSzNwP5L4U8j0x+wYR8R0Pch7xHmN4RKSd8WClg0P+rmD0Wb1ccWFeZfeNz8TMo4cxbt8eSYF+is+WRwXumzhagQt0naGnIAgAhiWOFBSrSY1TMf3b+QCAy8cL0OfBof7PXvv3nlieva7WtW5cuCkqzts2SsHSzDWSbSEifN5uVMCMftXP+Uv2Br2XsmKL6AuHqna7nC4sTFspvGqgcQo+ef7bunWk0P1UrlVelAtaS5FAsWpW5xmQfYVs/cCpjZxBUOLaPmi/fZCqLJEHQbKjJ99EzApWeJ+4QHd6X9qSfRWYsXX1Z0WJ/s8CrmebLS343Rel2+Mp8n1PzRn4BDDDwyDPjeD349wvMebGg5kHAABYSS8IrxyIB1VMrENPCvPpxnWKC/O62OvzZ3OhHmG4b+JoBS7QdYaegiAAOLTpGBIb1hbnr/yxO4pvmFBursAb//GOoIi/NZFcRakV7USWjic2SEb+4j2SbTmef1r43IbepefBlhXO/G6hP+GbmBmvFsFSUo7O//Vu7XtqmIxDm+TLBktUqQIxXnerufSSIy88COKEi958Eyv/VUDUJoCZkr3LzB27BD6PBytsVUs0U+UmibEuHsRKg7RljIhwTgCzjAp+L6Zk6fG26AVvOx17fPcUF/gdhsdkzeY+/8QxxcV2XaxZVjpaTciCoaJCtr7gBMJ9E0crcIGuM/QWBAHAlrk7kPLn9/1C9f1WQ3B2vzdT7pIxqwVFb9tGKfjggU9qXUto+XhS41Qk3/UenA7pkmyzf1gsuvQ8sUFy0IzwHz3xhaQ4b39HV3/CuGtnb2BIm2/8n719d7+gLxDqAjM8Gj1RbZSzfnocWPEbsvcHxwsPgjjhojffROQGK/8F1ZUv4sDMfUHMDABgJb0huKe8MAGs/B+3XMsJZnxKQGQngJV+HLQt3v3rImNl8ctB7sMefLw1da8+vnIjWNELNT57q96Z62/lYokpaqL63pxMtKhDhvhmmcJJ65pmpiFjT/2qzHDE4b6JoxW4QNcZeguCqvC4Pbh0rADXz/0eMFOd/v4EtGvSRVjw3t6l1nWsZVZ80ubbgONS/uc9nD8UfK/esnFrRWfAkxqn1srGfivDXvpOODu7z8b0+a3WOWZDKW5eNvgTyMkNK08TmOWR2+K92YmL2tb9fJHPQtmbyQkfOYOgF9f0RVLeYFXZi2v66nIcjSR69U3EKkCuUyBPUcDvmfFp8THN/GHt67hO+UR6TWHcFcTKgraBlXwgMk7GgZnekm4/OUVeJNQYZyvX33IOA7mv17pnuSAivDxnBppFQaDPOHpY9msmzgw/gS0nNLhv4mgFLtB1hl6DIDFmj1qMpEbCs9o9mvUXPIeIcGrPOazMWY9dy/fD5ZSeOa/CbChFu9trvwxIapyK71PSgp6/bsoWUXH+3n1Dggr8SEDMVmP2RTpIq7OV9AFz5IOVfCj/tS0jo95neoAHQZxw4b4pEGZKFRHNCaLjFpELVLkZZJsDch4OORu7VD4Rsi0M3lbzIPHx3/JDWPctF+dMxXhk4ng09S0dl1tEN89Kx/d5W7HvxjXcl5Ml+/U3X5LOG8CpG9w3cbQCF+g6gwdBXq6cvIYJn0zHiDd/FV123vGfuyH7oymy1jjfMicfSY1TkdQ41S/We8V9hJJCc9BzPW4Pvnl1NBIbJKNdk1Qk+WbTBz/zFdyu8OvmygWR27tssex7MONzMovoBwID0zpdQ2qG/z4+ix4BeBDECRfum3wlzhx5YGVfgpneFh+3jM+ArFNlq0hBRN7v9I+zLb0/l34c0neQpxDM2MY31sZXv1goHytL++qKxeHAzGNHMGzjOiRkj5G19Np948f6f26ZPUZWcd4sKx09li1StO9iFe6bOFqBC3SdEQtB0N41hzCw9XC0v70Luvz1A8wetTjkWWwAWDt5MxIb+kRu41QkNvSWXRNbet47YZCss9OFV4yY9f0iZH80BZtmbRct6yaEx+PBzmX78Ms74/BLr3HIX7IXHo96yoYRqwArHX7LzI83G7D84joUuxfMPETyGPIUKt1tMYecQdDzq/shcdvHqrLnV/fT/DiqNrTum4g8IOtkn1BtCVb8KqiydjUQ8fMZWGnVWJUQwgvJOLCyr2RsP3nLtVlGg1l+Ajn2hlUPnVgFyDrDew+WkSDXcdnaJgfnTMXovGBugBBumT1WdnEdqr06bxaenPKb6OfPT5+sdJfFJNw3cbQCF+g6Q+tBUN7C3QHlyap+DmWJOACUFJoFM7EnNU711iYX2uPdMBkrc9YHvzgHAMBKh90irH0/l2eBVW6ReYZdyu4Hcx4BVW4VP8bwIFjp597kTBU5smYS1jM8COKEi9Z9Eyv7WvDlItkWhHQ+2VdLvKSUKMnmvhLZG4sRKpxOtJmWi+Y1lrs3y0pH3LgMbLp0AaN3bo+aOH9xxmRYnU6MzNsS0J4qa56Vjtfnz8bAtSvRf81KLDl9Ek4VvYjXMtw3cbQCF+g6Q8tBEGMMb9/dT3QfdiiJ2lbmrA9aqqxWRveGKRiZHJg11+V04dKxAty8ZKjz/WybvxMfPfEFku96D0NfGIF9aw/X+VpqgdyXJcTwI2DMEeIy+LrMnMeBWX4EK88Gs6/zL81k7hve7xY9r2qmKh7M8DjIfVnhXtQ+PAjihIuWfRO5r0qMe4+DKPgKL2buC6mElqIC3TYvsC3M4k06V8eXjUSVoIocb1JO45NgpZ8GraOuBWYcPSy4xL15Vjr6rl4Ok80W0l71uDruZ598+ACy9u3G4cKb/jatPHe6Vptq/r1ZVro/0V3qonlwuJXbyhYrcN/E0QpcoOsMLQdBRddNoiI6qVEKFqWvDHqNhWkr/Xu3Q7V2TVLxyzvj/NdYN2UL3vzP3v7P+z36Ga6cvBbWvcz5cUnASoCqffBrJ28Ou1+iDbnOgJUO9ZbKMaWC7Ev9SyHJtlg6oCz7HszwVPDA09SvTgKd3NcD2+oxipQfkhDrJe8q0a0xhZxB0HOr+uPFrUNUZc+t6q/ZcVStaNk3kW2RtIh2nQ16DVbSqw5jXguQ3ev3iJxgZSPBCu+pfuFYOgTEQq+pTeT27X2/tU75/SDXuTr3T7TYcPE8ui1ZgGenTUKfVctx8GZ1vfiP1q0SFeD3TxiHr7duQkIIy91TFs4NS5g39S1Xv3W7QH7BlQAB7n8BIFKyrWlmGqYeORTtLo05uG/iaAUu0HWGloOgcnMFEkX2iic2TMaaSZuCXuPCkcsis+TJXtEtcv0DG44CAPKX7K19bqMUvPEf78BSEloyubJiC9oLZHNPbJCM1//UK6w96dGGnPt9AWDVrLMvkCv7zvt55YY6BZm1rHyC9Ex5YVzgzHdhC7DyX6vb6b4McuwGKxsB8b2cYrP0cWEFtZza8CCIEy5a9k1UuU5aRN/y4lDwGhWTRF4kJnhnsgXHsVb+sYqVfSMwpsWH9cJRfPxOADMLVzVRC9n79/pnnatmxptmpmHdhfMAgK+2bkLzLHHxG6rgzti9I+gxNdvQLCsd2654V2UxIhwtvIk9168icebUsJPWvT5/tpJdHBNw38TRClyg6wwtB0EA8MXLPwpmXW9/R9eQs63/9PbYgKRwSY1T0bZhCrYv2o2Pn/3aN2vexV8ffdzA6rff/R75THSmfVFG8Bl8ANixtLbIr2kndwWfbVEKVvya6Gw0uS+AyOFbTi4QKIYj0N3XwYqSxD+3zvLVRn8BzPQWyL7Km+TIY5TOfhzqrBQrVbqrNQ0PgjjhomXfRMzmzWdRa9xLADMlh3gNC1jRi7cI8QQww+Ngjt3eP/0vJr1WVV+cWInEi8gWIc9+s7Jv4c/gXsvuq3P/RJoim1VwL3fTzDS0njwBHsZw6Obv9d47fu/4TBTZrKLC+p7xY7H41AmkLpqPZ6dNQv81K3HU4E1Cuu/GdTw9dWK9vr/DnBkK97T24b6JoxW4QNcZWg6CAMBQUIS3/tbHl4W9i79k2Za5O0K+hsftwaL0lejZYiBe/dce+PSl73Bk6wn/Z9sX7UbaeznIGpCL4/mnA5amCdUxr7Ihbb4N6fv3rjkkKdBD2UuvBN4gUEzUxoOsud7jHLvgTWoUVyPYC6NEWnEnAEJJl3xmehuM1d7TSUS+FwihfJfY7Hk8WPHrUe3XWETOIOiZlQPw/JZPVGXPrByg6XFUjWjdN3mTUbb0vYxs6R1jjK1B7guhX8NjArOMBDO0BjM8ClY63D/7TqwMZJ0GVvY5WHkGyH21+jznQenxzhrazCuz/CA+fhoeDq9Dosjys6clhe3pIiMAIGvfbv/MdguRpeRS9uuufDg9Hjw/fbLg5xMO7AMTyHz/e7kFLcePrbWcXWpZvNCsfPrundHu2piD+yaOVuACXWdoPQhyu9zYOm8nRqWm48uXf8TUr+fh94vRK5P18j+9JSqsezQLbQmgs9KJ1/7Us9Zy+raNUtC9aX8wxiJ8F3WDWJmk4CXrtOpjPSaQdQqY5Uff/sx7QxPnhidBnkKQ64TEcb4AsvgNkCO/+judB8KbKTd1vUWse+v/knOfAr0bW/AgiBMuWvdNxMrAKqaAlbwPZv4IZJ0BYqGt6qovTCo5Z2ELsLLvQ7oOOQ+Jj7llIyJ7E/Vg9bmzkoL3vMnkP/asqRjpu3fix/xtmH/yeMjivNeyxXAzhpwDeyWPa56Vjn6rV6CgtHoVVsaenYIz/GLL45+dNing+OZZ6Xh66kSYbDYlujem4L6JoxW4QNcZWg6CCk5fR9f/6xOQXO2D+z+B6aY5Yt957ewNnNh5BtYyKwCg6/9+KCrQP3xwaMjX3bV8v7cOexNvHfakxql4+c5uOLb9VK1jrWVWzB61GH0e+hR9HvoUs39YDKtF3FF73B447I7wbzYEvMvHhWZYaidoCziv8P7QRHO5Nxkfs3wfwkx4vPd7fSKdbAtCmDX3XdPcH4w5QLY5YMWvghmfBjMPBLlORKTf9AYPgjjhomXfRPZVNV5C+l74lX7mryQh+/eRG+Q6DnId8/7MyqXHPsvYkK/tnUWvemHpy/dR1FYwKzy5L3tXOhW1BzO9DbIvl6ydTuQEkfw5ViwOBxKyx9YWu5nCCdqquFZWFrJAP2nwVmxpMy036LHNs9LxyMTxKLJ644YBa1ZKZohvmpnuF+Qzjh6G2W7Hzzu347lpuXhm6iT8kL8NRTar7P2mR7hv4mgFLtB1hlaDIMYYejQbUGv/eVLjVAxLHBnydawWGy4cuQyzQXqP8e8XCzGw9XD/93T4w1uY9vU8TPhkmnCSuUYpmPzFnLDu6drZG5jwyXSMeOMXTP5iDgwFRYLtfe/ejwMyz7dtlIL37hsCW7k94FiLqRxp7+Wgwx+6IrFBMvo8OFT20m3kOgdmeBjVe8q9gpcqJggfT04w80dhzGy3BLkvgJV+gtD2rcf5l6STY4+0mDcP9JYMqtwA5jwFZp0DVj4GrPQrsLKvQZVbQKTO1QtaQ84g6OkVA9Fm81BV2dMrBmpyHFUzWvVN5L4iMlbFgayTQ7+Ox+ArjyY9S0qVW32VKXzfY3wSzL4RzCies4Mce0NvBxHIsdO7lN48EGSdCWK1xaF3ldP9qJWss+wbgWNPgpX0qDEW9wW5C0JuUygsPHUCTX3iuEokJ2SPwb4bwi+Or5WV4aUZU0IW6M9OnQSr04kHJowLeSa8akn6LzvzRffIPzn5NwxYsxLfbtuMo4U3sb3gCqYdOYifd2zHsI3r8EP+NpzyLdHn1B/umzhagQt0naHVIOjotpOS+7YLr0g7MI/bg4mfzkAH3xL1tg1T8F3nXwUzrzsdLnT7//qiXZPayeimfj0Xb/5nb/8MfpVg7vzf70ZkJn/ez0sDvqvmdy74dbn/OJfThfdbDQl4gdG2UQraNkzB/vVHZG0TeQrByjO8ZYFKh0oGf6z81xCFdg0regGsYgbCqYXunZlh3pmcWjPvXnFOxLxJ7Mx9RWbjW4CVvB9SzWKONDwI4oSLVn0TK08TX+1T9GLQ88lTBFbyXo3zWoGVZwq+LCTXKf/KocCVQfFgFVMDZ/Crfi7pJTmrXef7NnUTHdvJVb0SjNwXvfcUcKw3+R15imVt0zFDIT7ftB5vL1mI77dvxZVSYZ9MRGg3e3rIy86rxPTXWzfh3RVLQj4vZaG3Rv3VslLEjcsQ3Fs+67jXP18pNaPN9Nqz81X71nMPHZC1r/QK900crcAFus5QcxB0YsdpfJ+Shg/u/wTfp6ThxM4z/s+2zMmXFOin9khnqZ00bCbaNgwUukmNUzH4ma9rBS/b5u8U/Z7O/9Ub18/9jh/eysDL//QWXv6nt/DDW2Nw87IhIn0y8IkvRNvy0VNf+o/LW7BLdGZ/wOPDI9K2YBC5fZmNwxDnVVa5Bcz4nHjgG2Ct/MEseW54l6wLHWdsA2buE/SFAVlnKdJfsQQPgjjholbfRMRA9iVgpu5gxZ28eTU8v/s/Z6WfSYxTrYJemxV3FDyfKnJqHc9Kh4t8VwJY6Scgxw4wU4pfALPyNBBVyt8nzCYxhiaAKrJrtPkLkTbHg5Vnyt62UKhrRveE7DHYe/2av3xasBn0D1Yt839n3pXLeHhituCxyQvmos303KDC/5K59jYDTnhw38TRClyg6wy1BkEbZ+b5MrN7Z4Cr9mZvnu3dX1xw+rqoUG1/R1eUm8XrVtvK7f6ZcyE7vfd8wPEzRizwfr/I8aHWO5eDQU99KdqOj5/92n9c9qApkhnmlUg8R8xSN3Fe2AJkXwby3PQtj5cS6QlgZYHZ84kIzLH3lqX4oVocmKlz1Psq1pAzCHpyxUd4dvOnqrInV3ykynFUy6jRNxERWOmn1YLSP/v7MMh90XuMVWy1TzyYKVX6+o588bHI8HCt/dqs+E3x433VL6IBkV3knr33XfPlAit6SbzNJT2i1uaarDkvnVROyopsVuy5fg2vzZvln1kXO3b9xcDYwunxYPLhA7XOCSW7e/OsdIzdu0uR/ooluG/iaAUu0HWGGoMgh92BV/+th6CwfO3fe8JZ6Q1SvnltdK096G0bJmPCJ9Mlr3/x6BXJ2fc1uZv9xxIRvuv8D9Fjk5qkoqw4en23OGNVrZn/qiX6S8au9h8387uFgvXhExsk49V/UyYIImLe5Gt1Eeg16vYSOUHM5ksCV5XozVe+rfg1EKv9PMSD5hCsqH00uykm4UEQJ1zU6JvEK0MkgJn7eY9hFjDjE4IvEsmRJ319a67kS8SaM/XEyn2risTGraSILGUXg5W8I/rytGZpOWZKFn+BYR4ctfbW5EKJqU7i/LHcHHhqvOy2uVywuZwYvH417s5MQ4usDP8s+LdbNwk+j97LQ18iX9NajMvAj/nbothLsQn3TRytwAW6zlBjEHRo0zFJAX14y3EAgN1aiYwPf0N730xxp395G1O+nAOPWzpTrtlYJriPu8pq7tFe8Otyyba0bZiCrzr9FNH+qEmlzYEBjw9H24bJATaw9XBU2qoztf9+sVDwHpMapyLn42lRa++tkHVmmAI5HqzkPfHrua+CKsaDWX4CVa4HkVvwOFb2uWjwKG0JYJYfI9UduoEHQZxwUaNvYuW/SIwjCdVba9xXvEvgqz4zPgeyrwl6fW/2d7Gx6J6AhHHe66tnew65L/hWKSVUj52FLcDKfw08zjZfvL1BXmBEkndXLJGc/Rb6bPrRQ4LXIiLs//06ft65Hb/uysdRg3jp10cmja/z7P22K5cj1R26gfsmjlbgAl1nqDEIOrT5uKQoPrI1sPSV1WLDjQs3wyol9n1qumAG+Lfv7gePxyvw3S433viPdyTbUmWpf/kA076ZB7tV/v19t+KwO7A8ex2GJX6HYYnfYXn2OsF7XzdlC5IapSCpcSraNfG+xBj09FewV9gFrhodiKhGvfFQLA6ssv5BGyv/Rx0EejyY4TGQ56YMd65v5AyCWi8fhKc3DVOVtV4+SHXjqNZRo2/yJrmUEuj/P3vnHR5Vlf5xCOAuu65u0d+u6+ouKkkERUUsa101BQREJAWk9957r9KkJXQEQu+9914jJVQjoYSaSTKZZJLJ9PN+f3/cySSTuffOnckkmXHO53nOo5Jzzz33Bu95v+d9z/s6ekjJmilsIiqsBkFkFM6KOwnvELCcwiNMZL6u/PuZ+Q1Iv7lMvOlCwtCpwjde0x1kOOL8TsgKlt2/iIgvFPJl6fEvTp7JhJrz4hSL47cXzLaXTSsJ9VYtk9wYkPrzV+Ono+mmdWDl+L5+K/C1ieMvcIEeYPiiEWQymNDoL61EhXDjv7aGyVjyrNq5mjz0/Wykw9jNq3VF6s3CEiyZj9SKxLld4FeKRs+PhsFiFvfilgfp9zOwdvJWLB66Guf3XCqXs+fFYbkzXXp+HFp6WIkNN7Lclb6npjOYqo6j1zytllCCzXLfS08d2HAjiOMuvrg2kemSdKSNprt37mG+7lg2La06WFZ7B+855W9yPxooV3nt89KGiECmJLDcmaC8eJA5ubynBABosGaFYoH+Stw0jDt2pMT3XH01SfIeHXdsRfXZM+z3ey1+Ot5bNA/TzpyE3syri3gDvjZx/AUu0AOM0jSCiAiZj7Ogy3Fvl5kxhqPrTiE8KNqeJC6ySgzCK0Xj2IYzXp1fcmIK9i45jJ/3J9k95wUY8o32GuLutGPreeIWOciS4rZx6Q2hTPrtYGk1Cj1LadWFsnBkEc61W1JAVufa85ySw40gjruU7tpkAlmfgEh51BURgTErWM6wQq+2PdLmfa/W8SYyg4xHQfkbQeabzj83nnJfoKeFgqxqr83xt0jC5YuyYe5iXvSSwogw/MhBB4959dkzsObaFQCA1mjALbUaeSaTi5E4nsDXJo6/wAV6gFFaRtDxjWfQ4pVuwjntStEY0XAS0u9Lix8iwq6FB9DyVeGa2Bc7Yk6vJZjUMg7dPxiCKa1nI/nn216dY3G06lwsGbYabUJ6ok1oLywdvgZT2syWTLYm6kWvHI3pHZzL4XiKL3i83YWIgcy/gszJkqGdpFvsHOIo14znvTM3pgHlbwDplvmM1yYQ8KYR9P7W3vjowCCfau9v7c2NIC9TGmsTkQUsd1aRco+1wLSTnLKjO1zD8sG0E8FU7wjXZDQSjsxktRcSnuX+CLKWTllN+xzMvwrZ49P/J2Ru160RN4fBOAAAIABJREFU/t3NYztk2Ou9OSkM2/cl9GYzrqWr8FCbI/pzk9WKtts220Wyq9Jpr8VP99rc7miysCzpItZeu4LM/HzXF3C8Al+bOP4CF+gBRmkYQed2XRBNTtb8P10dEpkVZc3ELULfoCLXBUVhTq8lXpuXHLmaPLSq3kM0K3yT/2vnlge97lOxmNNrCXRa14ts2r10TGs/D03+rx1iX+yI+f2WQavOxYlNZ9GxVj8hrP9vbbBk2Gp7aL9GlY1TW8/j4qGrLhPilTVkPAmW8b8i4emfSSb+IfMvYJquyoxLw3HP5kMmkPEsyHgSxEp+XpDjGdwI4rhLaaxNTDsBzhnEQ8CyB4r2J2Jg6u+LHY8JBksLBhkOe21ecpDpMlhaTRExXrPIRoPCpvoApFup6MgQmc4LmdlVdcAy6gqVMJgBlDfHlqW+upApXr+t8BrzLSFZp/lGab4StyEizP/5vMMZ8+gNa/Egx1moMyIcuXcHkSsTFHnRPT0HrtHrcfTeXfz8+JFDJnhO2cLXJo6/wAV6gFEaRlD394cgQiJL+p7Fh5z65+fqUf8P34tnSa8UjcxHpR+Wt3LcRsnM7uGVohFRJQb9vhiNIXXHY9HglRgSOV42E3xE5Ri0fK07en8yHC2qdcP4mOlOEQDpDzLR5Pm29jD+gutiXuhgzxBfdA4jGk7CokErHfpHv9ABV46XnzFEZAblLQLL+FLwRoklKUoLFTXYiKzKy64Z3D82QIbDtoRLBcZpLVD+am88NsdNuBHEcRdvr03EsmAvxyjynSLLQ+drJEPJg8EyvvbKvFzB1DGQztkRDKZ6DyyrFVhWNzDtHDDVRyKbEMWaugVY5tdgGWFCBYxiR3vIcBiFJSyLHAlKDys2tu3f834S5uBwj+hyPTKUodNh5JGDeHfRXNSYO0vU+/3x0oUwWpxzxtxSKyu79lr8dLfzoxARpp85ZT9bXi1uGj5euhCXnjx2fTHH6/C1ieMvcIEeYJSGQJcKCY+sEotZXRY69b928qasR/rEprNem5sU3d8frDgRXHhQNBr9uZU9HF9p6HtklRiHEm6zeyxGRBXl4fNSmwf1/9gcGlV2qb+johDT2UoO1ZA3BAvC2EU8VGT+RbnnJzfOvflZUmzGpbOhWp6lfAIVbxpBdbb0wYf7B/tUq7OlDzeCvIzXBbrxnOw3hgz7na5hubNEPNdFrmF5Xpmb5JxZnhsecpuIz6gLlvama5Fe9Lr0j0HWdOGeRGAZX7lxfXXbxkfxTYRQMHV0qb4fMe5ma9Bp51bF58i3JTuf8V90MdFleHtBu/DkkVvzW3nlsmhW9jfmxSNLz0Pbyxq+NnH8BS7QA4zSEOjR/2gv6VVePnq9U/+71+7LitCLB694bW5S9PpomGN4vSthHBSNtqG9sH3ePrcEdZuQnvYd95avdS+ROC8q0tdN2ebiCb0HkRVMHeueAZfZwHkcxcniQsFyhrs1R6YdJ2FYh4BltfbSm+AohRtBHHfxukB38b0hk3NNa9ItERGehaJU7uy6V+ZMejeFsu0blzMSLLufe9dofxDuaX3i5v3kW1mGuz/SavHWgtmKE71Vnz0DU0+fcBpnqRvJ4nbf+tWtOX6+7CfJrPA/XfzZW6+CoxC+NnH8BS7QA4zSEOjLR68XDf+OqByDJ3edk+kQETq82df5/HelaMS80KFMzllvnrUL4W4I9IKWcvkuvpYIz5dqafcET0WHN/t6RaBHPhWLmZ2dIxNKCyH80R0jLRRM09V5HCKwjHAZA7igBYPyV4FYnnAOMrs3WM4okOmSUGPYsBdkSrQnLRLOjcZIj5f+WZm9K44AN4I47lIqZ9Azm4hs3IWCZYSLhiqTNU1io088Kqg0YFntJeYg01TvgUwX3Lsm/X/CM7Ms7wp0w74yeU8AMProIbym0PNdIIpXXU1yGueRVqtYoN/N1uBBTg6mnj6BHnt2YNqZk3ikzcHltCfYfSsZKVmFR/T0ZrPkuNVnz8CIIwfL7F1xBPjaxPEXuEAPMErDCDKbzBjVeIo9JDwsSEicdnjNSclr7l5NxXfPtUVYkCA4wytFo+GfWuDaqV+8Ni85TAYT+nw6wm1xfPXETczsvNCtTO8FZ+rXTtoie+7d6c8lNhDCK0Vj04ydZfKeAAgZjSXPckoYacZTomORKREs7Q0ZAzRUqAlsvmPLWhxsE/Qi/TO+BMvf5JikTsxTlNW2zN4VR8CbRtC7m/vig31DfKq9u7kvN4K8TKlkcbc8sOXLqF74DUn/GGRJkb5Gv8X2zQkp/O5l1gOxLK/NS37Od225NNwLOSdiYOmfK9gALRDoX9nvydTNZb7JIkn25L795ltl8p4A4KvlS9wS5zXnxkFrNIiONf/n8/Zz5mLXvxo/HV13bceJ+/cQPHsGXoufjlfipuPV+OlOIrzd9s2Ym3jOIUmd2HwWX7pQZu+KI8DXJo6/wAV6gFGatWaTE1Owfuo27Fp4ADmZrsfXafOxY/5+zOm1BJtn7sLlI9cw4ptJaPB0c0T9vR0WDliuKDO6p5iMZuxdchhtQnsVbi7Iea6rxECfp0euJg+d3+5vjxKQu6bVa93t9zPqjfZNgYjKMfbkb0PrTUDjv7YRxHdQNMIrRSPyqVjE91gsGpXQ6C+toM3KLbX3UhyWG+emRycYTLdC8H5nNQdTfw/SJYCY8Lsky30w7SSwrNaCYVg0sZv6e0GcZ/dTcE9lhigZnUMaOaULN4I47lJaaxORGWQ4CMpbKETfKAhTJ8sDUN5cMO0EkH4XmH47WGYjsLQ3wTIiQflr3U4W5tacrZlguTOFjOqiIrn4ZmV94TpTEpiqNgoyz8teo/2xyPPeLrIpULAhGgyWPRjOieM+tnn5Rc6gl/FxokbrVrlVx/zN+fE4dPc2Jp08hu/Wr0b77Vuw7/Yt++/y3MMH6L9/D5pvXo/v1q9G6JyZqBY3DcGzZ2DwwX3I0etRZ9E8l/d09fNX46fjzfnx0Oj1Zfq+OHxt4vgPXKAHGKUp0EtCyqW7qFe1mYPgjagcg251BsFsMpf6/a+fTsbMzgtlS6yN+W6qvb/FbMHxjWcQ3/0nfF21meQ1SceuO9zHbDLj8OoTmNQiDkPr/YCudQY5inyb1zy+208gIqydvBX1/9jc/vM2IT2RnJhiL8FWFpDljpveHAnRntnILtIdxicrmH4HWGZjuzeo5PerDqZ6G5S/tszeE6cQbgRx3MVX1ybSrSgmkm3/zJ3q+uKS3pvMIP1OME0v+W+ivrDeObFsYXNU00vm+1gLxBw3eYlpQLqfhOuy2ggZ35086SFghn1C0tDs3o5z0nQEs2aCyDlLemmxPOmSYnEuJqALEsONO35EdHydyYS4c6fx3yULUC1uGt6Q8Yi70z5NWISktCdl9p44hfC1ieMvcIEeYPiqETSi4SRJb7RcqHxxDPlGnNh0FvuXHRU9/+6KpGPXBZFcLLz8u+faIj9PfLf74MrjCAsq4k23XTvwq7EYGDYWY6N+xOltiQ4el30JR2wec5nz7pfuAhDK0iUdu46LB69gcst41P1dU4RVjEKPD4Yg6eh10Tl5G9IlFHpJ7B6Vt9wW6aRb7Dy2KQniWYFLIs7fAxH3TpQX3jSCam/qh/f2DvWpVntTP5/8jvozvrg2ERlkao+HuFVWjKxpIP1WkH6XR9nghQzzIvPIaicxdwLLHlRsc8G2AarpBpbVAixnBMh8s9g1csnmgsHSPwCRufCZjGfB9Ads9eNta4SmF8ha+mXEzFYrOuzYYg9NfzVOENxvL5jttmi+mZHuNP6CC+e9IsjtnvO46ei0Y6vHtdQ5JYevTRx/gQv0AMMXjSAAknXRI6vEYnqH+YrGOLvzAr55tqWDNzqu2yIwxtyaS+K+y+hYq5/diz82aprL2uxJx65j1LdT0Oq1Huj/xWh8+7c29nPlBcI9rtsiAMImQsNnWrgMp188tLCGt1FvROvgng5l2sIrRSOicgyunXQuGyNF+oNMXDx0FY9S3N+9J/OvYLlTwXJGgvTbwTQ93BfO6iZO47KsDnA7KZJsCwFTN3P7+TjegxtBHHfxxbWJTJdkvzVk2ON6DCKw3BnFNiDfBOm3uzcXIpBuMVj6ByiIEGK5P8qG7BMxUP5GIYlmRhiYuk2xTdZQYaPBsNf2vOcVfWPJeK7wHuabYGk1iz1fKFj6JyCWo/zZzL+AjGfcPuvPiHDs3l2MOnoIY48dxqn7qXhzfrxbwvm1+OmYde60w7h6s1n2DLlHAj1+OuYmnpN4Ek5ZwNcmjr/ABXqA4YtGEAB893xbSYE+r0+Cy+tVqRmo+1SsqEd688xdHs0pL1sHo97o9nWTWsRJRgPcOJOMxH2XXSaWi6wSi/n9ltnH3LvksGi/iMoxGBg21uWc9DoDJjSb6RAZMDB8LLIzlBlQYggJidwUz5nfOY8j6aEq7vkREeKSGwExIKbz+Nk4JYMbQRx38cW1iczJLoTqMddj6LdJftvInOz+nMgqhLG7GUpOZAZL/1D8m6p6F0RGITeIgoSgRfN6CKH0Yhus4hFTTvOy3AXLbFjkutfBtJNA5Fk1lwc5OR55tmeedRToV1RpHp8zl/vZtDMnSzV/AUcevjZx/AUu0MuJiRMnok6dOnj66afx/PPPo1GjRkhOll+sjx49igoVKji1X35RnvncF40gAJjZeYFkkrbkROmMuwWsGLNBUhS3fLVbGTyBgFFvRN2nYiVF98IBy3HhQJJLgR5WUagHr1XnYtGglWj4J2mP+9dVXXuLxTYNIirHoPfH7tUbLwpTR7kQ0CKGXd4C53HSP5MW4OlfganeA8v4Ckzd1NF4VEeD6VZJGIchYNm9PX42TsnwphH0zqZ+qLNnqE+1d37DRhBfmwoRSkN+KbIZGGw7RuM64RxTN5H4ToaCaV1vrnoL5qJcJhlPgWknKxDotYQSmOZfwLL7yKwBwWAa+bWXyAiW/onoN5zy5nn0nFqj0X623J12Ld3xSFxqdrZs/y+WL8bbC+bgm7Ur8fXqZQ5e8kEH92HYof2S1268cc2jZ+OUHL42cfwFLtDLicjISCQkJOD69etISkpC/fr18fLLL0Onk/b6FRhBv/76K9LS0uzNalW+0+xrRpBOm48JTWc4eHbDg6IRWUUQuQkjlSX5mtJ6tkP4d9FW7/dNRa95ckeFA8uP4fT2RK8kXbty/AYa/62NrFd8Xp8EGPVGNPpzK1lxPqzBRGizcoWwdheZ4mP+2UF2XllpGsnybmEVo/DrhdsePS/lb3ZLnLP0/4qevaS82ZLecDI7nrEnli3UQLcI5/PJkiJzz2CQNc2jZ+OUDG4E+S98bRIg86+2zO3Fo3ZCwNJqKq4OwVQfSn+jNF2c70sEMl0E6TeDTBe84m0l3WKJjUzHaAAltdRJt9yWN6SmizFDwXKGys9Lv1P6elUdj73oPffsdKs+erfdO0THabx+tdM4r8ZNQ51Fc2Eq9nf7QU4Ozj96iIx84f+TpZcvSnrXv1qx1KPn4pQcvjZx/AUu0H2EjIwMVKhQAcePH5fsU2AEZWdne3wfXzOChn79g6gAbV+zD34577qeqiY9BxObz5KtL96l9kAY8o04svYUtsTtxtWTNzG17RyHfo3/1gaXjzjvaudkarFtzl6sGLMB53ZflDQ4czV5aPinFi5LtV08dBUAcHjNSYQHRYs+e7uavaHT6mTrphd9voQR8psYN84ky45xeLVnZciICCxnXBHDtViWYwdj6z0wi7hYJjIKWYMLwhttRp+i8EjDPhdG51mPno1TMrgR9NshENcmYjnCN0ts4zC7J8jqOocHmZKEs9+S36cQsNwZIKtKKNuWvxrMdNl5UyDzG5DVOeEpWVJAeQtAefNkQ+XJeELBBmotENPZksQNldlQGAAAtoRwrpN6kilR/h3lxUPOY+9p7flsgx6N1q2ye7SrxU1D9dkzRAVz7Ebpknn3sjX4cPEC+/WvxE1DzXlxOP/oocs5DD9yUPKer8VP9+i5OCWHr00cf4ELdB8hJSUFFSpUwLVr0qFPBUbQf/7zH/zjH//Al19+iSNHxMuDSOFLRlDqjQeSojGicgw0Knljz2Q0o+3rvV16mFeO34hv/9raLmilhG79P37vcCb77M4L+LpqMwePftd3ByFX4+wF3j53H8KD5MX0qMZTHAyBG2eSUc+Wkb14G/3dVHvNdLk24MsxLs/JZz7Okp2bko0QOchyW8jyrp0q4VEJATNdlh+DSAixzJ0Kyptj95C7vLf5hryBaHlQomfjeIY3jaC3NvVH7T3DfKq9tam/z3xHS5tAXJtIt0x8ozEtGCzzG9fXm2+Bpb0hI2JDwFS1hFrn9s1NqQ3OUDB1bOHYRGC5PxbZGLXdI2esqNBkms4uPN3VQflriozPwPIWS/fXbVAg+KuD8uJdvyf9VukxVO+UqGQbEeHUg1QsvJCIPvt2iQrl9xbNg8kifw+DxYxNN69j4sljWJ50CTkGg6L7L7hwXjLU/tOERR4/F6dk8LWJ4y9wge4DEBEaNmyITz75RLZfcnIyFi1ahIsXL+LMmTPo2rUrKlasKOvZMBqN0Gq19vbw4UOf+Z/32PrTsuLz6gn57OSH15yUvf6759pi6+zdaPTnVi4922EVhdD67h8MQZfaAzG8wUThLHmxpHMRlWMwpc1sp7ksHroakRJnz8MqRmHjjJ2wWhy970fWys+/3/9Gys51/7KjijPUj42e5rSREVklBl3rDPJawhqhPI+YIRgKph3nlXuI3lcdLXLfULCs9qV2T4483Aj6bRCoaxPLGSbj2X3d9fXZg+RFcUY9W/4M10LX3tTfg2V+a6t6ISGK9Tud55LZQEYE1wYZncuYsqxOMteInxkvKqyZWVnuASK9LXGdyBn/3FmKxnCFlTG8u3CuZHj7oTueHfFyRUa+Dq/PnSUq0pclXSyVe3Jcw9cmjr/ABboP0K1bN/z73//Gw4euw6aK06BBAzRs2FDy56NHjxZN3uML//PeOPurrEB1Vcd8Tq8lsqLYaDBh/7KjLoW5o/At9KhL9an7VKyT11pus6DZy53tIvje9QcY9e0U1P1dU5ee/3l9E6TnWSka0zsoT6Kj0+ZjeIOJDmP0+HAoMh97FkIoBsuIlDEuY10P4CFkTbclrCt6v5Yg5nm4LadkcCPot0Ggrk1yeTFYxpcur2cZX8l8C6NtoeR9XXq2nbzuoh72Ij/Pauk8l+zB0hunOSMKn9lwwBZeHyr97AX3cVFiU0n5Oft9zclCCbii4+eMKJH3vCgZOp2kOH8tfjrmJJbeMajzjx7ivZ/mOdxv0sljPIt7OcLXJo6/wAV6OdOjRw/861//wt27ykJ6izNhwgSEhoZK/tyXvRREhE5v9RfNLj6k7niX168av0lS5Db6SysAwJqJW1wKYU9a8fJkJqMZzat1Fb3Xjvn7AQAPbz0RzqkrnM8viSmIfqGD5M+jX5BPDifGw18f4/S2RKRc9uzvmxwsq52EYRcKlt3X6/crDplvgAx7QeZfS/1eHHm8aQTV2jgA7+we7lOt1sYBPvMdLS0Cem2yPgFLqyEqhkm3zOX1wtlziczttm8hUzdzz4OupGV+7fws5psQogGKzicYLK0GyCwcbyL9dhfiv2irAbI+kunrOjmc0xyJCYnxDAe9ntjTaLEgdM4sSZG+6eZ114OUALPVilMPUrE35RYyZBItcsoGvjZx/AUu0MsJIkL37t3xz3/+E7dueX4GuEmTJvjiiy8U9/elc36AUL+8fc0+DsKz53+HKarPnXYvXVTsRlSKxqKBKwBAUc1xd9v3/+kqugOuSs1A/y9GF24S/LkVVozdgGMbTuP09kRMbjUbkRKZ5p02GP7cCkSEyS3jJb35zat19frvoySQTBkfMiWCWB5Y7jShrI7qXTBNb7uByPltwY0g/4WvTQJkPAqmqu0oanPGgsj1sSLK3yT9LTSeAgAw7UQ3PeiuWihYzkiJZzlpKxdXEAXwFVj+RiGLuvEMmOpj5ffJ6iTMX/We9Dy0o732e/AGo48ecgo1fzV+Ot5aMBv5ZjPuaLLQZ99uvL1gDj5cvACTTh6D1qjsrDnHv+BrE8df4AK9nOjatSueffZZHDt2zKEsjV6vt/cZMmQIWrYsDFmbOXMmtm7dilu3buH69esYMmQIKlSogM2bNyu+r68ZQYBgEF45fgP7Eo7gl/O33Ar/OrjyOCKrxCC8UrRd/A74cgwM+UIIOmMMnd8ZICrk6/2+mUcC/cDyY7Jzynioxp0rqVgxdqNDTfTwIGXjhwdF4/SOn/H4dho2zdwl2ieicgyWDl8jO4/ygPLmFfOivw7SrQCRCSzzu2I/CwVT1eIe798g3AjyX/jaVAiRAWQ4ANJvBVkfuXEds51jt33nCr57Rc5Vk+UBWFqtYt/EYMgnjJMJO0+rJZtck4gJZSlN18Gyuni2CaCqDWZ5InjlJXOOuM7eXtbozWa0377FQaDXWTQXl548xt1sDd6cH+9QTu3V+Omou2oZDJaSl1/l+BZ8beL4C1yglxNiZ+8qVKiAhIQEe5/WrVvj888/t//3lClT8Oqrr+L3v/89/vKXv+CTTz7B7t273bqvLxpBJUX9RIPNs3ZhxZgNuHzkmpPAV6VmYMBXo+0J3xr/rQ02zdgJQ74Bty7ewaOUJ2j5ajfRTOfhQdGo+7tYu8f6wAp5cc4Yw5M7KuxZfFCx4A+vFI3vnmuLpv/qhFHfTsHJLefQ44Mh9p8XbDxEVI6xe9M7vzMAOm1+ab5WjyFrBih/s2DU2srkkH6HtLdF06OcZ8zxNt40gt7YMBBv7RrhU+2NDQN/c9/RAvja5D3IfEMog5a3UFQ8M8NRsIyIIp7tuiDjaRDLApmvgZmuSIj0EDDV24X/rW4GMktn2Qdsmw2We7YEdq5LpNlb+n/B0j8H0/4Alr9JiIAqsgFbuJFgE+sS2eR9gZsZ6Vh77QoO3E6x1zHvv3+PZM30ddeulPOMOd6Gr00cf4EL9ADD140gs8kMTXqOU8ZzTyAirJm4BQ2ebm4Xu11qD8T9X5wTHl04kITIKrEOYjisYhTWT92GtNQMaDJyJI0OVWoGFg9ZhS7vDECDp1t45JU/v+cSAMCQb0Tsix1Fw9rb1+yDcTHTsWfxIZel1XwNljNEOpxT9XZ5T4/jZbgRxHEXX1+biOlATOMV8UksDyy7dxHxHQqm6Q3G9E59hVJs1Yt8P0PB0t4UQtMtD8GsudL3MV0Cyx4Clv4V5OqNS7c3QExrGytJWtirvwfLGQwynvRZcS5FnUXzRMX5q/HT0XOPc1Z8jn/D1yaOv8AFeoDhq0aQyWjG/H7LUP+Pgpj+7rm2WDdlm+IyYmJsnb1HNDS82cudYTKYnPrfvZqKae3noUvtgRjRcBJGfTsFX1cVwuCb/F87bJy+w8n4uHnuFur/sbls1ndXLerv7XB0nXAuce/SI7J9E/fJ1xP3VZh2tLRAT//Q3o+saUI99cwGYOmfgqmbgvLXg4iHGvoT3AjiuIuvrk1kfWSrJW4T0xn1QEb5SCpXCKXSin8PQ8CyBzrfnwhkOASm6SRkWc/uZ0swZ5tPZn37uXaH63TLPAtjL9oym4DMN4Q5a3rLeN7fBFnTS/ROyotPli6SzPA+8OBee78rqjT02bcbXyxfjE+WLkKnnVtx6kFqOc6c4wl8beL4C1ygBxi+agSNj5kuKnKXjVrn0XhEhNgXO0oK3cOrT8heP7zBRNHa6WsmbnG4R4c3+yqqsS7bbKH3m2fuwoL+yxEpk+W9w5t9veqhICJcP52MHfP24cyOn2Exe6e0jdN9TIkShl0ImHaSrc9FwTMk1i+rrdfK7nBKH28aQTXXD0StnSN8qtVcz40gb+OLaxOxPGGj0EFMB4OlhYBM5z0b03JbRhSHyApdYtm2uuFi87lU2M+qci+MXWY+LK0myHxFvoxmWnWw3KkevQ8pTFYrDtxOwcorl5GU9qTUPPPTz5wSrVVeLW4aTqTeAwD8dPFnySzwCy/41nl7jjx8beL4C1ygBxi+aAQ9SH4kKUjr/+F75Oc6h/25Ij9XLzlm5FOxWDx0teS1KZfvSl7b8JkW9vDyRylPSibMi7UGTzfH+qnbXPbTZkmHNLpDriYPvT8e7jB27IsdceeK970CRGTLWlwQomkzMDMbgJhWSKpUNMuwSCP9dq/Pi1M6cCOI4y6+uDaRbgUkz4BntfJsTMM++e+c8Zz0tXmLJOYTCqbpVNgvf7VEPw9FelYbm9dfztsuXfPeXa6mqxzqh1eLm4Zmm9Yj1+j9o106kwmN1q60e80LzqMPP3wARIT7OdmS4rwgFF6Vl+f1eXFKB742cfwFLtADDF80gg6tOiErSJMTU9wekzGGRn9uJemx3rnggNM1mY/UmNNzCRo/10Z2Pnev3QcApN586FWBHlYxCkfXn7YnpRNr4ZWioddJl3/JydRi96KD2DRjp8ta5+NipovWoI99sWOpeNKJCGQ6D5YzAiy7Pyh/E4hs2fZNV10YicE8mZwfwY0gjrv44trEsgdCOnfGWx6NSWb5bx1Z7jtfY7oMpukKlvaG9LWq9wr765Z5UaDbRLr+iHwfdYz8c1tSQLploPw1slECRosFdRbNdfJqvxY/HQMO7JW8riQYLRZs/eUG+u7bjaGH9uPUg1S7xz7+/BlZgV4tbhrW8GRyfgNfmzj+AhfoAYYvGkE/70+SFa1P7qoc+t+7/gDjY6fj27+0QuyLHfHT4JWiGc2XDl/jlJk9olI0GjzdHLsXH0JyYop9Ec58pEb0P9ojwlWd8qAoqJ9oAABWqxXNXu5sD1GX6n94zUnU/V1TRQK95SvdsH/5UXHPf5UYjPp2iuR7PLTqhP0+BccFJjSdISq2czK1sufmz+z4uSS/Urcg/U4w1fsKBHq3MpsTp2R40wiqsW4Q3twx0qdajXWDfO476u+Mf8oOAAAgAElEQVT44trEtJOkBXr6/5z6k+EQmDpayLCe+TUof51TaDYRgWV+KzJuKFhmI5B+J8j6uLC/8aggkGVrpgeDZdQtvMZyx8X3NBQs/TOwvLXKRXrOcDBNH+mNhXzxqDSh5NzIwnkWhOTnrxLtv/tWsqQQrj57Rql40cWwMIZJp45LZngv2lZdTSqTOXFKDl+bOP4CF+gBhi8aQVaLFbEvdhT15vb9bKRD33vXH6DB080d+kZUjkHXdwfBZHRMJGYxWzC5ZXwxkevona77VCy+ebYlWr3W3WWit4jKMRhabwIAIDsjB4sGrUTMP6XPudf7fVMcWnUCp7aeV+xBD68UjUWDVmLrnD32DYWIyjEIC4pC05c6Q5Wa4fT+GGNYMmy1+HhB0Vg7aYvTNfeuP5Cdx475+734G5aGjMcUG4iUr7ymMqd84UYQx118cW0i868SnuhgUN4Cx775Gwu9zXYxWh0s13lTlaxPwDLrO4tmh/+uKZQ4U9VW9n3ULbfN+SZYdl/HMmxOmwufgMy3wHJGu+dpN5y0JcwreE7bnLM6iCbyJJYDpm4uPWfzVadrFl+6IHkmvFrcNNzPyfbSb1eeCSeO4hUXwrxa3DS8EjcNj3J95+8sRx6+NnH8BS7QAwxfNIIA4NcLt+2h5QUiutVr3ZF+31GQjouZ5iTkC9rBlcdFx3546wkOrDiG9jX7ILyyBwndbB7ydjV6Q/1EA606Fy1e6eY0j8gqsehUqx+mtpmDvUsO28+Kb/hxu+ScxVqzlzoDELLKz++3DJNbxWPbnL2Sdc/n9l4qO973L3dxusaQb7RnzBdrN84kl+TXqRimbgpFyYzUTUHknHmf45twI4jjLr66NlH+Wts3qkitb013B0FKZAJTvSfx/QoBWdOcxyUCmX4G062EELruSUi67Zrs/iCyCuOl1RAR+28Kmd+1E0GGA/a5s6xWbtwrFCxnJIiY4NXPGQaWMxRkOAgi57KoRCaRTYji441yuu70g/uSYrjW/HgYLaWfLFRrNCBkzkyX4rxa3DTMPHu61OfD8R58beL4C1ygBxi+agQBgmg8sOIYVo7biJNbzomGZkudK4+oHIMprWdLju3KY+yq/fD9LFitghGSMHKtqOAOrxSNDdN2ON379PZEt+7V5P/aKX5nGQ/VLj3/9ao2E702YcRap/D8iMox6P3JiDKrZSvr5UkLERLH5S0FkfS5e47v4U0j6PW1g/HG9lE+1V5fO9hnv6P+ii+vTWRNE85P580DmZzDmcl8Xd67LZPgknRLPRTnNpGrKwwVZ5mNJTc8yfyL072ZdoyImJcT1IOVvzP9Ftdjaro6X0eEb9auFA0tn5MonUDPm1xRpcmK8pA5M9F43Wrsv32rTObD8R58beL4C1ygBxi+bAQpIeaFDqIiNLJKLOK6LpK87tyuCyUS6GEVo3Bqq1BWp9Nb/SX79P18pNO9rRYrWr7aHZGuzrfbRP742OmK38ex9aflxwuKQq+Pholea7VakTByLRo83bzIvWcgV1N2GWmF0j0SWYm9XLaHU3ZwI4jjLv68NsmXTqsOMjgnJS2AaSeApb3uoUAPBkt7A2RVC+HkMpudxUPyhXmn2O6tcIPAjWNGLGeoC/EfAsqbK3ptlj4fXXZtt4eYvzEvDvHnz4CV0cZxWl6ubHg7r3/uv/C1ieMvcIEeYPizEQQAiwaukAwXv3L8huR1T+6oSiTOIyrHYHDEOABAt/cGS4jhaAwKHyt5/67vDlR2v6Ao/DR4pSIvduLeSy7HS9x7SXYMQ74RqTceQKv2Tvk2dxDKGEkYbxb5LPQc34UbQRx38ee1SUj89rWI9zoYTPUOiKRLhQoh9J6I88J7kG6pULNdTgzrFovf33BEJjy/eKsFMhxU9E6Y9gd5ga6qA7Jmyo6hzs/HLbUaBovz+fbSpv32LU5e/Nfip+OzhJ/KbKOA43342sTxF7hADzD82QgCAF2ODp3fGWAXzQVe6Xl9E1wK2tGNp8qeBQ+vFI1Gz0qUZqsYhXav9wYAbJi2wyk7fEEbXn8ihtabgB/bzsW1U44hhUSExs+1VbwpcGjVCZfvw2wyo8nz7UTD3Os+FYtjG3z7fJyQ4Xd0MePtDZB+V3lPjVMCvGkEhawZghrbRvtUC1kzxK+/o76Iv69NZL5uS+gWgsIEaq+7FLTE8sDSP3DhbZZrr4NpJwEAWFZr6XE0fcCy2oHlTgVZHjrMgZmT3fDYvw6yPlHwPq5Jj5P+Kcjs2+Hh6vx8NFq3ykGgf7x0IVKy1OU9NU4J4GsTx1/gAj3A8HcjCABMBhMOLD+Gya3iMavLQiQdu24X51aLFRt+3I4W1brh66rN0PO/w3Bu90UY8o1QP9FgQrOZsqJ4css40VD0yCoxmNQyDoDgce750TC717xAHEdUibH/e8EYm2bsdJj7rC4LFSWMC68ULRmaXpzLR66h/h++R3ilaEQ+FYvwoCh8+5fWLuug+xJkSRVKEum3g1jZe/I53oUbQRx3+S2sTWTNBOXNB8vuB5Y7zaGmObEsMO1oMNW7YKq3wDS9wMy3QSwXzHwTLKOBjLf5fbD0LyVD0Um/VbiHJQVMVaeIJ7+oWA8t8s9aINPlwrkRA0v/XHJ8paHpTu8jb16Re9rC+DMbg5jOuy++lCAinH/0EKuuJuHIvTuwMFbeU+KUEL42cfwFLtADDH81gkwGE1JvPIAmPUe239Q2cxBeNPFZsSRovT4eLptUbdnodfi66vcOfQpE+KhGk3Fo1QmYTWaYDCbs/ukQRjSchJGNJqN1cE/RcSMqRSPjYeGOe/qDTKHeugKR3uzlzorfT1aaBuumbENc10XYOnsP8rL9wwDi/DbhRhDHXfx1bSKWDbKkyIpOYnlgGWHFBHNIEUH8Opi6hbwwzlskKpaZ6i0hu7opUcgMb80Ay40Dy2oLlt0HQlZ3kesy6jlEnZHhCFzXW7fNVST7uuSzm38By50Kph0DMuwDUelnYedwpOBrE8df4AI9wPA3I4iIsG7KNnxTEHoeFIXhDSchK03j1Df1hutM7REy4jy8UjS6vjsIvT8ZgSZ/b+d0vrzg2q7vDnIoeZaTqZUeMyga2+bsdZhn5uMszO+3DG1CeyHq7+1Fw+Ujq8RgdGMhSdqD5EeI6/YTun8wBGOjp+HiIefasRyOL+FNIyh49RC8vnW0T7Xg1dwI8jZ+tzaxPLDs/kW81W8I4eMiApR0yxR4p12Um8xqBZb5DVjaWyJh57Zrc8Y5im79DtkxyXLPcZ6mJMGzn/GV7T4SHvv8tUJ/4ykwTXcwdRMw7Vin8TgcX4OvTRx/gQv0AMOfjCCL2YL1U7c5i+wqMWj/Rl972bMCts3Z6+g996AVeLbDK0Xjm2daSvYbEjnebgipn2hkRX/xMPeipD/IRMM/tXDYOAgPEq67cSYZV0/cRL2qzewh8wXz2zjduZwbh+MrcCPIkePHj6NBgwZ44YUXUKFCBWzdulW2/+bNmxEWFobnnnsOf/rTn/Dhhx9i3759Dn0SEhJQoUIFp2Yw+GdJQn9am4gMtvPeIknhtBOd+jNNZ4Xh464EvO1+6f+V7qdbWjhP/WZ5gS5zDpwM+0SuCQVL/wjE8kB5C4uErxf88w2QST4pKYdTnvC1yRG+NvkuXKAHGP5gBGU+UmNCsxmIqCxf3/vcrgsO1+1fdtQtMe6qfrirtmr8JphNZuRq8tCuZh/J8e7/8kj2eZN/vm1PfBdWMQotXumGszsvgIjQXmLc8KAorJ28Bfm50tmBOZzyghtBjuzZswfDhw/H5s2bFRlBvXv3xpQpU5CYmIhbt25h6NChqFKlCi5dKhQ/CQkJeOaZZ5CWlubQ/BV/WJvIlAimjnYhpGuCmOMzsOx+CkLHC7zhJRHxwhhkSgSxfDDLXQnPfLCQqI2sEk9qe978zY6bAermIMt9kDVN2uOveg9kOOxybA6nPOBrkyN8bfJduEAPMHzdCMrP1aN5ta4uz2hHVonB6h8ca7LmavLwddVmioR5+5p90KW2UPas/h++dzqrrtTbHvlULMIqRqHpvzoholJhVvkCUT27h3hpGzHS72fgUcoTMFsimid3XZeGi3mhAx7ecp1Rl8MpS7xpBFVfNQShW8b4VKu+yvMwQiVGkBg1atTA2LGFZRwTEhLw7LPPuj2Or+LraxOZr0BIdOYiFD2tOsh8xfFawxHlXvKs9mDpH9v++03PRLuqduG/p39RxANf4OkOBhn2K3tusoAsd0DW9MI/y1/rel5ZLUFk9OrvgMMpKXxtkoavTb4FF+gBhq8bQdvn7lMslvcvO+p0/dF1pxBROUZoMh7ytZO3YGbnhej4Vj+0DhFP8OZWs82510fD0OzlLujx4VDsSziiqJa5FI9vpynaJOj72cgSvHEOx/twI0gaT4wgxhheeuklzJ492/5nCQkJqFSpEl5++WW8+OKLqF+/voMXw9/w9bVJCFNX5gUnq6O3iIjAckY6CGTxa0PB9NuFe2XUB1N96AWPuhB6zjK/A0v/DEzTGWS6IPGUyqD8NQo2DoJBefNLdB8Ox9vwtUkavjb5FlygBxi+bgRNahnn0nseXikajf7SCnqd+HmWx7fTsHT4GkxtMweDwsfZhWzBuP3/Nwp1fxfr5O0uaQsPika7Gr298h6sFityMrVCdniJmutFW+YjXpuV4zsEihH08OFDaLVaezMaXXsMPTGCpk6dir/+9a9ITy/0Yp49exYrV65EUlISTpw4gSZNmqBq1aq4dcu360tL4etrk1C+TIEYzuooej0RgUznwbRjwLIHgWXULSbYQ22bAAV/5q2Qd9t4tlrpJYXIKJSFUzK3jHCv3JPD8RZ8bZKGr02+BRfoAYavG0Fzei0RrUNetH33XFvcOJOseMzUmw/xQ7OZaPB0c68IcVfNkO95WJ/VasWq8ZvQ+K+tEVYxCg2ebo6IStEuNxFSbz70+J4cjrfxphH02sqhCNk81qfaayuHiibBGT16tMvnctcIWrNmDf7whz/g4MGDsv0YY3jrrbfQs2dPxWP7Er6+NgmZzV0I0szvQCxL0XhEDMxwAkwdq9AzX8KmjirR8xPLAsseAHs9cyUbFukfluieHI634WuTNHxt8i24QA8wfN0IunXxjmQI+YhvJuPE5nMwGc1ujXn9dLIiL7Q3Wv0/fO+UXd4d5vdbJhri37xaV8l7Rv29PSxmXluW4zsEihFU2l6KdevWoWrVqti1a5ei/h06dEDdunUV9fU1fH1tErKWS3iNtVPsdcjdG3OuF0W4nEc7GEzT2fNnJzNYZv1iGwm2+6V/Ku21z+7v8T05nNKAr03S8LXJt+ACPcDwdSMIADZO34GwIFsStipCErZh9X9wW5gXMKbJjy698gUh6r0/GWH798Iz3uFB0Vg6Yg3m9UnArC4LsXzMeslz8pNbzXY9IQlyMrX253WaW6VojIueJlpGbu+Swx7fk8MpDQLFCCrNc35r1qzB73//e8UGExGhTp06aNu2rdtz8gV8fW0iMhULQReSrlHeIg/HMzsmc3MZLh4GxwR1oWCq98DyloDljALTjgbLGSN9vX6f60lJzVW05JpNpKfXtUUXFBXvIWBpb4IsKR7fk8MpDfjaJA1fm3wLLtADDF83ggp4lPIEq3/YjKXD1+DykWslSrbWOrinMg94UBQe30nDzgUH0Omt/mjyfFsMqTsBV47fcBgv/X6GpEd+5LeTPZ7nxYNXZOd3cut5LB+zHvWKZarv9dEwqJ9oPL4vh+NtvGkEvbpyKII3j/Wp9qqbRlBeXh4uX76My5cvo0KFCpgxYwYuX76M+/fvAwCGDBmCli1b2vuvWbMGlStXxty5cx3K1OTk5Nj7jBkzBvv27cOdO3dw+fJltG3bFpUrV8b58+c9fufliT+sTfZz5LkzQHnzQJZ7no9lVbkhzr8Cs+aA5f4Ilv45WPpHYDkjQVbHEp4sX6buuW6dx3NluVMLQ9vFmuUxmKZnMS9+MFjOKBDx6C6O78DXJkf42uS7cIEeYPiDEeRthtSd4DLxXFjFKLR9vTe0Wbkux9swbYfkmfCIStEw6j07g3476Z7s/G6cScaEZjOdniWySgy6vTe4RJsYHI434UaQI0ePHhU9F9i6dWsAQOvWrfH555/b+3/++eey/QGgT58+ePnll/HUU0/h+eefR0REBM6cOePx+y5vAm1tIjJCKKOmQKBrBoKIuRyTZbWGZN1z9feez1X3k8S41cFUtcCYXtg0cDpLHwyWO8vj+3I43oavTY7wtcl34QI9wAgUI8hkNNvPgp/bfVHxGfLm1bq5FLorxm6QDZnPy9Z5NGciQse3+jkJ8IjKMWgd3BPqJxrZs/Q3z/EMmRzfgBtBHHcJhLWJiEBksK8xTPuDtPAt3nKGuRyfqaOkr89s5Pm8rWkSHvQQMO14kH6H9H1V74DIs+NpHI634WsTx1/gAj3A+K0bQUlHr6Pnh0MRVjEKdX/XFFNaz4ZGlY3NM3eh7u+aKhLpK8dvlL3HtZM3Jc+wd6zVr0Tzf5D8CLEvdrR5xmPtSeDuXruPG2d/lZ33oVUnSnRvDsdbeNMIemXFMFTfNM6n2isrhv2mv6PlwW95bSIikG5lYUI11XugvDlgTAeW3Vt5qLslVfY+LHeWhOAPAcudWrJn0O8GS6sBe0m4tOpg6mYgpgPlzZYNgVea2Z7DKW342sTxF7hADzB+y0bQtVO/ILJKjEP4eYH32ZBvhDYrF8c3nsG2OXtkhe73/+4iex8iwoiGk5zuE14pGon7LgMAcjV5SBixFu1q9EG7Gn2QMGItcjV5ip7DZDDh8JqTWD56PQ6uPG4PmdeosmXLrSUn8oQ8HN+AG0Ecd/ktr02UN0887DxnuPBzy12QfidYzjgXXvQx8vexqsHSPy4Wah4Klv5fkDXddq8UsOzBYBlfgqmjQPnrFYXPF4xPuuWgvNkg42l7JADpd8p40N/l59A5PgNfmzj+AhfoAYa/GkEPkh9haps5aPpSJ3R4oy82TNsBs8kxbG5g2FjJs+arftiE+B6LMaHpDOxbdlQyC3tYxSh8XbWZy/ncu3EfXWoPtGd5b/Vad1w4kAQA0OXo0Cakp8NcIirHoE1IT4/D3wuY1CJO9Ax6jw+H8jPoHJ+BG0Ecd/HXtYmMx8GyWgnCWN0cZHCsCUxMJ3PWPBhMtw0su78gmvOWujiL3tXlfJh+O5jqk0JPt7oFyPpYmIspCSztjSIC3pbULXtwyd4BmUQ2BoTxKS++RGNzON6Er00cf4EL9ADDH42gu1dT0eDp5g7nvsODojGk7gQwVrjzX/8P30tmZy/+Z3JnyDu80ReA4AXfNGMnprSZjcVDV+NRyhMAQOqNB2j4pxaO86kUjcER43Dr4h0MbzBJ9J7hlaKxZuKWEr0Lvc6A8THTHcbv/8UoaFTZJRqXw/EmXjWClg9D9Y3jfKq9spwbQd7GH9cmyl9fGEJe5J+kW1rYx3RJeQh7UdEs9ue2MHWy3BUyumcPAumWgZjWNp/NovNheYtAxmNg6V9Kjk/mayV7F5Y7tlrpRTz32vEgspZoXA7Hm/C1ieMvcIEeYPijETSi4SRJz/j5PZfs/WL+2UFxMji5tnfJYdz/5RGaPN8O4UHRiKgcY28HVxzDgC/HKMoKL9Z6fDDEK+9ElZqBxH2Xcf+XR647czhlDDeCOO7ib2sTkQFM9Y6EmK4JYkJFELLccVOgS7VQkCXVFk4eYvNWhwqCO/1DMOM5MNXbno/tBU83EYHMN0DGkyCrusTjcTjehq9NHH+BC/QAw52Pk9VqxbndF7Fo4AqsGr/J7kEua+o+FSsqdiOrxGJOzyX2fgkj1sqe0RZr3zzT0mG8hBFrQUTo/clwj0W4ZAuKQp9PR5TLO+RwyhJuBHHcxZ2/M8R0gvdaOwmUv8ruQS5LyJQoK3rJcMTel2V+KxL+LdfehkOyN9W7IMMREMsGS6vpJcFfXKDPK/N3yOGUNXxt4vgLXKAHGEo/TnqdAX0+HSEI16diBbEaFIWts/eU0UwLqf/H5hICPQYLByy39zPqjRjw5Ri72FYisO9cTUXi3ks4seksNOk5AIDMR2rvCvOCEPegKGyN3wOr1Yo7V1KReuMBPzfO+U3iVSNo2XC8tmG8T7VXlg3nRpCXUfp3hsy3wNI/sAnL1wUPsqo2yJRURjO1zcN0WV6gG08W9rXcsdUJLzJnWcFcE8SyQIZ9IOMxEJmEcfI3lYI4t83XchvE8kDmayBrWpm+Sw6nrOBrE8df4AI9wFD6cVo0aCUixLzRQVFIvfmwjGYr8GPbOYiQODNevPY3Yww/70/CT4NXYtX4TRgfO0M+5Py/Q+1Z0gt4+OvjUhHovT8ZjiNrT9nLqIVVjELr4J64euKm2+8k7V46ZnVZiObVuqJ9zT5YO2mL03NwOOUFN4I47qLk7wwR2c45Fy8lFgKW/mmZnncmstoSoxUX28Fgqjp2UV3YXy+cEc+dAspfVVhyTarlznK+p26FAnHvTrONpZ0BljsTDsnsstraM7+79V5MiWCaTsLzqZuC9Lv5RjTHZ+BrE8df4AI9wFD6cfruubaSXuvFQ1eX0WwF1E80aP6frggPEjYMCjzj8/omAADMJjOSE1Nw92qqkyGQo86VTQgXVjHK7oVPf5CJnQsOYMf8fYj6R3vvec4rRWNczDSsm7JVSO4W5PizelWb4fFt5R6Lx7fT0PivbRw2LcIrRaPvZyNhMfNyNpzyhxtBHHdRJNDNyS681ufKcMYAGU9BqA1eEL4unAsvyOROLBtkumTPol4UJlearIgXnohApiRBnOsWe9lzXgtMO13IIi8S9s4y6ysuwQYAZNgDhzrpBUnz8mZ77Z1zOCWBr00cf4EL9ABD6ccpUurc91OxmNVlYRnNthBdjg4bpu3AyG8mY1LLOCTuuwwiwv5lR9H4b20cPNI3ziQ7XLtx2nZZAd3g6eZYMW6DfQOgrFtElRjM77dM8buY0nq2ZETB0XWnvP3qORy38aYRVC1hOF5dP96nWrUEbgR5G0UC3eW57/1lOGPbnCypYNpJYFmdhKzllhQQmW01zV8v4pFu55Q4jalj5QV0VlewrHaO3u4ybmQ8ruw9kAUs/b8S44SCrBml8fo5HLfgaxPHX+ACPcBQ+nHq+/lIyTPcB1cqW7BLm8S9l5zFbqVo1P9jc6Q/yLT3O7zmZLkIb3faoPCxip+76IaEw7NXjsGU1txTwSl/uBHEcRdFAp3lQjpJWojPnJ1m2okigjoULLOxQ5QXy+4jL5DTP4JzOH9ZthCQbrGiZybzTXmhr99eWq+bw1EMX5s4/gIX6AGG0o9T0rHriKgc45AVPaJyDNrX7AOT0VxGs5Wn/5ejRTcRIirHIGHkWnu/MzsSZcVx/T9+7/2M7W60yCoxmN5hvtPzPUh+hPFNZ6DhMy3w3XNtMLvHYuRkahEtEX4vNU5poUrNwJJhqzE2ehoWD1mFJ3dUZXZvjm/DjSCOuyhOEpcXLy4Cc8aV0UzlIZYns4lQHWRKtPdlmu4uBLI7md9LyYOu3+38jMajYOoYsLQ3wTK+BOmWgpl/lR/HUHYJZsl0CSxnJFh2L5BuOYjlldm9Ob4NX5s4/gIX6AGGOx+nS4evoscHQxBWMQpfV22Gae3nISfTd/6nb/K8+Dn58KAojGnyo73fjnn7ZAXyN8+29Fhce6UFRSE5McXh2R6lPME3z7Z03DgIikL0P9pjRucFkhsKifsul8m7v3zkGr6u2kzYxLHViq/7u6Zldn+Ob+NNI+g/S0fglXUTfKr9Z+kIbgR5GcUCnUg4j12QZC39Q1DegjJNECcHuRKq+YWbxyyrU7kLcNnNgfQPQeSYfJTsZ+eLefbV7cHSw5z/PK06WNqbZSaSKW9ekc2NYKGlf+4z0RWc8oWvTRx/gQv0AMOTj5PZZAZjyhPFlBXd3x8sWve86Jnuh7eeoHVwz/IV4DKtXtVm2Lv0iNOz/dhurmRyu8Z/a4MWr3QTzswHFSbNm9J6dplky7VarWj6r05O7z48KBpN/q8dT1TH4UYQx23c/TtDRCAy+VyGcKFWuXRYesGZbjIcAkurJSOQX5f5WRm09E9B5huOz0ZWsPRPpK/J/A4s7Q04Js0LBum3ls27t6RIbzZk9y2TOXB8G742cfwFLtADDG98nMoCs8mMw6tPYGrbOYjr9pNoKbJDq06ICtiIyjG4/8sjGPKNiH2xo6iIL+hXnuJ8fOx06HJ0os/f9F+dZD3uQ7/+AVvidmN4g4mY0HQGTm09X2abKDfOJMs+1+Uj18pkHhzfhRtBHHfxl7WJWBZI9xNY9gCw3Bkgy32nPix7gIhIDwXL+AJEVpApSVbEl3vLSwCR80YrWe65vjZ3DljuVLCs9mA5o5xEfmkiHH+QOhbwus9EWXDKD742cfwFLtADDH8wgvJz9ej+/mCEVRTOVUdWETLKz+ub4OAtISIsH73ewdPc8JkWOLFZKLWzd+kRWSFZtB55SVt4UBR+aD7LrWs6vNEX53ZfxMNfHzvVMG8T0svF/aKhzcot099LAZcOX5Wd27ndF8tlXhzfwatG0JKReGXtDz7V/rNkpM9/R/0Nf1ibyPwLmOpdFJYSCxWEn+GAYz+WJwjUogIxIxxkuQsAYFm9XAj0j7wruLO6uddf0xnMdA1kue9QZo2sKtfXZn5bpr+TorDcHyEXeVC8Nj0n8OBrE8df4AI9wPAHI2jJsNWS3u2kY9ed+mtU2Ti2/jROb0+EIV8QuqrUDMT8s4OskFwxZr3XBHqDPzXH2V0/y/YpOK8t9rOGf2qB5aPX273gq3/Y7FAvXaypUsunbI1eZ0CDp5uLzqle1WbIyxaPCuAEDtwI4riLP6xNLPMbEWEdDKZ6G8TynfqT+VeQfgfIlGgXumQ8IePlrQ6W2Qgs00X5NXdaZjMwTU/Pr0//3KF8HVM3lVI/3esAACAASURBVO+f8UWZ/T6KQ8YzEvMKAVN/X27z4vgOfG3i+AtcoAcY5WkEZTxUI67rIsT8syOavdQZC/ovh1bt7AVu9lJnUfEXWSUWMzstcHkfq8WKVtV7SIa2h1WMQpPn2yL559teEed1f9cUKZfuIr7HT/Jeb5n5hFWMQlhQlD37vFFvROfaAyT7Nv1XJ1it5ReutzV+j7DpYHumgmdbP3Vbuc2J4ztwI4jjLuW5NpHpIlhWRzDV+2CZX4N0K53CocmSKitMybDP9X0st2U9vMJZ6YGgvPneEefpXwml6VSflWAcIdEaGc/ZnuEOmErq7HwoWPaQUvkdKYGIhN+jQ4m7ULC0GiDTpXKbF8d34GsTx1/gAj3AKC8jSP1Eg5gXOjh4xiMqx6BNSE/otI6eh2//2lrSAz2pRZzLe53ZIe/JDqsYhZXjNgIAJrWIkxbUMh7siEpCgrb6f2yO66d/AQBMaDazxGK//h+bQ68zABA2GrrWGVRsToIQPrD8GADg7tVU7F92FIn7LsNqKVvBfnLLOfT6aBga/60Nenw4FMfWny7T+3N8F28aQf9ePBLV1vzgU+3fi7kR5G3Ka20SPNohRbzaNnGXPdixn8s631tc3otpx8p7z9Oqg0yXQEwLlv6FC9Es9TObhz8jAsSyhfuq3i+h2A8Fy2pT+ByW+2Cqd0SEcC2Q5Y5wzt54GpS/GWR2jnorTYhMoLxFYBnhYKr3wDTdy/QcPMe34WsTx1/gAj3AKC8jaEH/5aJh6+FB0dgwbYdD3/FNZ0iGuItlPC/Ohh+3yyaAGxs9zS5mrVYrtsbvQZvQnmj4TAt0fKsf+nw6wi1R3egvrbB70UHM7bNUtp/SpHR3r6ban8VkMGHx0NX49i/CpkX7mn1wbP1p6HUGjGg4ydGr/lJnpFy+691fHIfjAdwI4rhLeaxNRASWUVdS8JI5uUhfkyD4JAQzWR+5vB/LaiUvzvPXFd6PZYFpJ4GpPgRT1QZTNwNL+9I9YZ3xNZjhtPBPj8R+kaZ6z/HdWR+BaXpDiAgIBstqDzLfFKIEMorNU90SxMonZwqHUxS+NnH8BS7QA4zyEuhtX+8tKUgHho116Jt64wEaPN3cydvesVY/mAyuk7yc2HRW8l71ft/MKSFbURYOWO46FN2DNih8rOK++5cfdfKGE5HDn80UqYUeUTkGUX9vD5PR7OZvx5EbZ5IxrP4P+PavrdHqtR5YN2UbL53GcQtuBHHcpVwEujVD1hNNusWO/fM3OnqpC8Stdryi+7GcERIe9GAwdQvpeRLZRLa8992jpumiTKSn/xdkdq7QQcTsxwGIrGAZ/xOZZyhYdh83fjPi74D0m4U8AKraYOpokOFgicbkBB58beL4C1ygBxjlJdC71B4oHkZeKRojGk5y6n/v+gOMjZqGb55piai/t8eC/ssVJx8zm8xo+q9Ozh7roCj0/mQEMh+pJa+TSn7maav7VCzm9U2ARpWNhs+0cNm/IKy+XY3eUD/RIOXSXWyeuQt7Fh+yZ23X6wyo+7umkmMc23DG49/TpcNXEVklxuHdhQdFY/R3U32u3jDHd/GqEfTTSFRb/YNPtX//xI0gb1MuAp3lyHqWSbfS+RrDQTB1E+EcdkYEKH+VQ6Zz2fuZb9jEvYggzpkAIr34daafvS/M094D0+8BMxxR2L8g9L8/GDOBDEdAusUgw34QCZvCwnEBmQ0PluXx74rlzirm8Rc2SSh/rcdjcgIPvjZx/AUu0AOM8hLoG37cLpnB/NCqE16/X+rNh2gd3NNJoIcFRSHyqVhREZudkeNVcR5ROQY/DREMPLnM9FLXRr/Qwb6JERYkeP+PbTgDVWqG9HWVnI8MuEOX2gMlIwhunEl2PQCHA24EcdynvNYmIexczDMdArKqvH4/0u+ynd92vJfgpf7IXorN8ZrtXhfoBUnfhMz0CsPcC5rqg2Lz/kw4e56/Tv6eZs/WELKqJX5H1cFUtUEkHRXH4RSFr00cf4EL9ACjvIwgo96Ivp+NtInPaLtYHf3dVEXZyFWpGVjQfzl6fzwcY6J+ROJe1xlZiQgDw8eJCs7IKrFYN3krko5ex+PbaZjZaQGavdzZLRGtpLV4pRtuJ91zSvbmUQsS6sI/SH6Eb55tJdkvcd9lj35HOm2+7IbBirEbPBqXE3hwI4jjLuWWJM5yx5ZErcCzLQhBMe+56PWmC4JXWR0DljMaZElxeQ1juUKYtpMwDgXL+BKUv1YQvMazQj111Yfe96BrOoFZHnppvFCwjEgw40WZPjVBLM+z35Fhr7zwN3m25nECD742cfwFLtADjPIsZWM2mXFo1QlMaDYTk1rE4eSWc4rEecrlu2j4TAu7eC745/LR60X7Z6VpsHbSFvzYdo6i8+ThNs+6N4V5UVFdr2ozdHl3oGQEgbte+RVjNmDluI0imw4x6PBmX3stdXcx6o32smlinnleQo2jFG8aQS8vGoX/rJroU+3lRaO4EeRlyrXMGssC5S0A0/QA044WPWstel3+2kKBav9nDZBRvKIFmW+C5U4By+rghvh107vtzrgZYXCu616CZrwobFQ4ebuDwbSTPf/9GI/KC3TzTY/H5gQWfG3i+AtcoAcY5WkEeUrfz0ZKerYf305z6Jt07Drq/+F7hFeK9po3PPKp2BKL9A5v9vWa6G/xSjccWHkMY6Omod7vm9n/fHDkeKifaEr0rkc3niqZbT/tXnqJxuYEDtwI4riLv61NxLRgaTUlhO8XTufSKW9BERHvDVHspYRxGQ29N1ZWezDdJrDM74r8eU0w7UQQeZ5olMgIpnpXZLMiBCwjjOdH4SiGr00cf4EL9ADD34ygXE2etOe7UjQ2Ti88b221WBH9QgevZGEPD4rCyG8m48ldFeb3TZD1sPf5bASavdRJXuRXicWob6fY561U2CsV7FdOeKfOqyo1A03/1QnhQdGIqBSNyCqCWN88c5dXxucEBtwI4riLv61NpN/twqv7a2Ff8y/e9X7nzgOzZoGlR7gQzN3A0t6U76NuAZb+ucJ7u+nNV7cCs3pnY5cMRyCUdCvY4AgBU9Xi4e0ct+BrE8df4AI9wPA3I0iblSspTCMqRWPDj9vtfS8dvuo1L3VYxSjM6rIQRIQ9iw95JQR+cOQ47Fp4EC1f7S7bL/of7TG943zF40ZUjkHzal2dSrN5ii5Hhy1xuzGh2UzM6bkEty7e8cq4nMDB60bQyok+1bgR5H38bW0i/U4XAr0w7JrlTvWelzqtOshwAER6sOyBXhDUIUL5N90ymwCW6ZvZCCxLYVk2+9jDvffOLffBcn8Ey+4DyptdKkn8OL9t+NrE8Re4QA8w/M0IAoDu7w+RPBt9/5dH9n6ntp73qkC/ePAKEkas9dp4BXXKZ/dcIhl+365mb/u5/MNrTiLGlsldSTuz4+fy+hVxOA5wI4jjLv62NhHLkhC0wWDpn9prgwMAyxntWvwqbiFg1mwwdbT7Hm25MTUdwTK/lhgzxF7rncgCljvNjed5HcRyy+vXxOE4wNcmjr/ABXqA4W9GEADcOPsr6lVtZg+3LhDrc/ssdeinSc+x9ylpa/J/7aC6n+GVxG5FW3ilaCwavFKYp4hXfs/iQw7PlHL5ruJxN8/iYegc34AbQRx38ce1iXSLbSK0aJK4EJDB8TtOhj0l8HAXa5oeIP1mLwnzYi13psQcQ0GWVIdnYnkLFM9fSWZ7Dqcs4GsTx1/gAj3A8EcjCADO7rqAofUmoFVwTwz4agyOrD0lmhhm8dDVgmi1id9wD0PTB4WPxaaZO70qzguE9PjY6Tix+Rwa/qmFo3AftNLpmRhj+P7fXRRtFHSpPRBjmvyIk1vO8aQ5nHLFm0bQSwtH498rJvlUe2nhaL/8jvoy/rg2EVnBdEvAMpsI58Gz+4DMV0T6mcEyG8MxOZztHLW7Ij1vIZimZ7GxvNR064Us80XHVr0NMhxwfibLXeXeeXVzsJzhILN3cqVwOJ7C1yaOv8AFeoDhb0ZQ5uMs9P5kRKGQDYrG5FbxMBlMov2JCDvm7UPr6j0Q+VQs2tXsg/XTtrsvpm3l0eQF8QCPxp3dYzEAQK8z4OSWczi06gQyH6kl38H5PZcQWSVGUXRAQej8tA7zuEjnlBvcCOK4i7+tTWQ8B5b+aREhWwukWy7dn+WBaSeCqd4DS6sBltUGLGesZ0Ja9S6kz7S/BaZ626NxyXBYmKs1DaTfDjLsB5Fe8pmEs/UFmw1S4xZsQISCpQWD9Du9/rvgcJTC1yaOv8AFeoDhT0YQEaHz2/0RISJMR307RfE4q3/Y7FGSN6ls6+FBUehYqx8mtYjzaNxT284jP1fvloC+nXQPP7adg85v90eLV7spygSfdPS6J6+dwykx3AjiuItfrU3Wx2Bpb4h7v/M3KB6HZcZ66O2W8roH20Tzux6MGQLGdLKC3Ok9EIEMB4S67pn1wdI/UrC58BaI5Xvy2jmcEsPXJo6/wAV6gOFPRtCV4zdkBejZXRcUjTP6u6klD08vJsT7fzEKm+M8C4Fv8HRzhFWMQrOXO2PXwgOSQp0xhrM7L2Byq3hMaDoDe5cesUcOaFTZuHT4qkOYfNEWWSXW7qnncMoarxpBC0bj38sn+VR7aQE3gryNP61NLHeGjNe4BohplI3jqgSabKshLrK1k8E0PVx4tSUEeoFXXh0NMkknHSWWD8pfDZbdCyxnCMh42r6OkeUOmG61Ik89h1PW8LWJ4y9wgR5g+JMRtPunQ7JCt2OtfqLXZT7OQsrlu9DrDACAuK6LEFkl1mNx3u29waKe8sgqQlb2kpZgE6sxzhjD5JbxQth6lRh7YrxudQYhP7fQw1H/j80lBfqsLgtL5xfD4biAG0Ecd/GntYll95IXoHnxTtcQEchyB2S+Zc/wrrz+uISgVr0n7k1XvSsh4N0R66+DzNecn4NlgWWEF/Hk20S99ofCPqYkFwJ9f+n9cjgcGfjaxPEXuED/f/bOOj6qY4vjsDGKFQotbV8pngQpLbSPyquXJEBwsosFghYJTtHiGiSBYAGCu5cCpUBxL+4SnABx2ejazO/9sZtNbvbetaxm5/v5nM+D3blzZ+/0cc7vnpkzLoYjBkEKuQLXj9/GlSM3tKIaAG6cuGNQ3MpyZNr2KXGpGNd8hva7wDJdsX7ydty/FFP0DLoe61p9QJGub1sxBHKZgvNMzu29xNvW302M9ZO3a9tN7xQheGTbhf3GrTDQB9vHzjAHFgQxTMURfRMlqaCyU6Dyq6CUaD9XHzOmR+Ami7n9yC+DJPrnf5/wPWjuUVATKqGbbvVB4hoW4XpfkNRQnWdCpJMhtP+dyq+qfy+Va14e8I+LkvSizw3zTQwzYL6J4Swwge5iOFoQdH7fZbSv3FMrKluVC8b+5eqKsYQQtH0nRFDY+ruLoVQoAQAqlQq9GwznFatbZu3BvmWHBIVsUa1X/WFFytA3LRmEZ3decp7LrK4LBcfbvXZ+0BT78DXaVOzOaesnCsK45jO056mbOy/9G49C05JBaPdOCKLHbOS8DGEw9GHZIGgKqq0PcyirunyKQ/07WhxwJN9EKdUcOVbgrO+EH0DlN9TfK1/qF7cpIfl9KZ9DvV+94JJzb/XfZZdB0oYV+MySAt1bvTe8KH3Ef6nzbNTZeQFBrzkrHQBozn5wMuya30+z1uj0afy8qEAzV+TvdU9sCpq92+z+GK4H800MZ4EJdBfDkYKgZ3deIsBDwnsU2qVD1wEAg74aJyhqB/53jLavS39f05uhVsgVSIlLxZ6FB4ospq1hyW+4exandJgneLRap49+5bSNe5aAyIHR6F57EPp/Pgq7Fx6AQs7NyJvC6V0X1EK/QCE6PzcxxgRMZ1kLhlGwIIhhKo7km2j2Jh4B6gMS30idVac5XPFe2DJXavsi0pkCGWdfkNRB6vsp7oKkT7SwQK+Doi1zrwOSGKDzbIT3zdcFSZ/AfY7ySyCp/UASfwJJCQHNPV6kedF9Rt5FFv0M14L5JoazwAS6i+FIQdCi0Gjeo8P83SUYE6B+Ey9UBK1pySBMDZqv7WvbnL16M+QJL5O0bSMHrrRaNt1U83eXYLTfVJ1ns3/5EcF97wv6WW9vOaUU3esMEtxXf+v0Pavdm1F8YEEQw1QcyTeRxJ8Fs9I0ay2o4qZ+YZu9J7+vlG56BPDP2naUqkASfxEQ8/Ywb9Cs1brPJnWA4Bhp7iGrzQlVxkJwlUF8I1Caa7gThsvDfBPDWWAC3cVwpCBojP80QeHatfoAAECnqr/yfh/gIcHSoflvzY9tOSPYV/NSnZCbnb88OzdbhgmtZnPatH67GwLL6hZc83eXoEv1AQjwtGzWPa+/brVCOS8PCo7x109Hcl4k+HtI0K5SD7x5Go8Hlx/jn42ncPvsfYtmtdMS0/W+TNg8ky0nZBjGokFQ1BRUWxfmUFY1igVBlsZRfBOlVFgIxtUFkU7RLFsXFrdUdkLbH0kbIyBofUCSu3HvrXyi+3Ig4X8C9/FRn6VucWGuGWvqQFCquxKLKh6CxDcs9Jt8QJI7g5Ac9Z79nD9Blc8tOy85f+p/5opbFr0fo3jCfBPDWWAC3cVwlCAI0J9BH9tMnUFfN2mb4JnfD6881vYly5Ghw7u9dDLjfiIxwvtG8d7/yc3nOLjqKC7svwKlQomEl0no4TNYO4a85eTP775Et9qhFhPnUzrMw+rxm3Fi21mdpej3LsZgUts5EL/fG73qDUWfBsMRWKYLmpfqjBE/TsLdiw8x9H+/c/rr23AEEl4kWmROcrJyBVcX+InE2Lvkb4vch1G8YUEQw1QcyTcZyqADAEnqwCO8fUDim4BSubYvvRXNc3QzzpSqQGVnQbN3gMpvqKu/y06DxH+af4+4OiAp3UEUTy0rzqXTQTIWgsqvcF78UkpBc/aCJLUHSfgKJKkdSMLPIHH1QOI/A0kfByK/qHsOetpvnGdRFGjucf0CXfnMIvdhFG+Yb2I4C0yguxiOFAQ9vyu8B/3yYXUxHlmODAP/O1rn+1G/TNEGEIQQEELw8MpjtH2nh07bbrVCkfQ6Re9YpCkZ2DBlBwZ8Pgo9fIdgQuswHNtyRiugl49cL7gn3FRrX7kHnt+L1RnD1X9uIsBDwiuQ815StKvUQ+f7AA8J+jceZbFM+jTxfN4xNPPsiNSEolffZRR/WBDEMBVH8k00ezN/xlqzBx3QZLvjG+m2y1ye3w9VqjPyWdvAey556hBQqtQ/FuUjkPTxIInNQZIC1Rl5mVpAU0rVn1tKoCd3BKU5OmNQn/uufkEhmHHXKYSnaZ8Rbpk5oXKQ+CY8Y/AFSWpnkXswij/MNzGcBSbQXQxHCoIA4ML+K+jwLreK+4EVR7TfS1My0PrtbrxZ9A1TtmNyu7nwd1eL2nEtZqD5W5119k/7e0gwofVswTFIkzPQvXao9qzxvGzxkP/9rj3+LDU+DR0/4l9ub6r5u0vQuWo/jPx5Mia1mYPTuy5ApVKhV/2hRer3waVH2t8U9ywBMVefmFV5PSUuFSHe+SsJ/NzE8HMT49iWMyb3xXBNLBoELZuCamvDHMqqLmNBkKVxJN+kruK+EJwia4k/gipu5reRnRVeIp69BSSprfrv8Z9q9m0LZH6zNwmPQ34Z6uPSuJXQScaCAuM4x5PJN9e8QZLbgyR3AUkbC6q4BaqKFxDmRlp8I+2575SqQBUPNGfBm/5CmcouIL9IneZZxH8Jqnxk+GIGA8w3MZwHJtBdDEcKgvJQKpS4cfIOrv5zk3MOOgDsifxLMHPt5ybmHi8msBQ+T3BLUzI4fatUKpzfdxkDvxjNm8VvWjIIB1cd1bZPjU/Dwv4r0LJM/l71Du/1gvj93uYLa819B3yhu0rAVDu54zxeP47jLIFv/XY37Ji/z+Rg6J+NpxBYuou2nxalu3BenDAY+mBBEMNUHNE3UZIGKjsNKr/OOQcdAEhKbwFh7FPof4Uyz5rPk9ry3DcTJGuz5ixxvmu9QZX5q7Co4g5IcjA4leUTf4FwxXUjxXpcHZDEgCILf0oy1EvUE74vML6fQWXnTJsPSkDSJnKfScJ3nBcnDIY+mG9iOAtMoLsYjhgE6WNRaLTFCrQ9ufUMf0UfRfTYTVgyeJV2v7k+8Tz02wm84laanIFH159i2dA16PBeTzTz6oS2FUPQ4b1eFhmrORZz9TE6Ve3HuzzdFHEdc/WJ4MuOq0dZIR6GYVgQxDAVZ/NNJPFHy2StE34AVb4AzVqtPpItfTJIfGPD12Us0hkTpRRUFQciOw+SGgoS9ylIXH2Q+C+hXoJuiSy7qb/vGxD5Tc0Li4IvG7xB4uqZlP2mWav4X4jENwYlzvHfDcO+MN/EcBaYQHcxnC0I2r3ggN7MuLHWrlIPTkbYFOv8cX+sm7QNLx+80o4rN1uG3g2G2+W4tsLZfn93CcY2n4Ej608KXtOlen+js+jzei0VLN43oZXwVgEGIw+LBkFLp6LamjkOZVWXTnWqf0edAWfzTSSlF3j3lZtkviBJrc2/PikIJGuTdl88AFDFA6gz50Udmzmme0+atQ4kbQQEz4JPn2zU86aU6hahKyD29W0VYDDyYL6J4Swwge5iOFsQlJ6cUbQMukbMNvPqZBFxvHL0RlBKcWDFEZsLc393CbrVCsXsbou0AtpPJMY0yXxkpWdh5agNaKbnWRm7H3349xMF+wjxGWzlGWcUB1gQxDAVZ/NNJOegGQLWu5CYrW8hYdwANPeYelypoQJi2Fqm+U0pA0GSO+Z/Ht8QNHOp4UJ2yWKjnjelCj1jqAsinWnN6WYUE5hvYjgLTKC7GPYOglRKFbbP3Yuu1QegealOGPTlWFzYf0Ww/cUDV0wWsmObTUebCt3RtGQQevgMRnjfKJ3CcUWxM3su4rdfppjcp38RVgIElu6C6DEbIU1W76NPT5Li3sUYJL/Jz5z8seig4H79du+EGJ1BX/Drct4MeoCHBJPbzS3afwAMl4AFQQxTsbdvoqpkzfLyz0HiGoKkDta7/JpIp8O04mneBfate4OkhIAkd+fNOpsnkuuDqOJg2lJ27wJm5r0TvgXN3pJfCE75Qn08HMnKf1YpfQVeGviCpA03bn4oBUn4TvB30OytRfsPgOESMN/EcBaYQHcx7B0EzQlZzFminSdaj20+LdzeRGHbs+4QSFMytBXYt8zaY7Gl6H5uYrSp2N2ka4JrDsSF/Vdw4+Qd8+8tCkJaov4jzqQpGWhZtqvO8/JzE2PdpG1Gz9HTW8/5j78TBeHW6XvGTzbDZbFkEPTRkqn4ePUch7KPlrAgyNLY0zdRkqkpqubLFY/xnwmer60+8stEMZs2FoQoQanaN5HkzpbNZmvPSjfSkruCKp+DSMPMfzGQ1NLw85WdFOyDyi8bP09Z63n60Jw9TzKN7ofhujDfxHAWmEB3MewZBD2/+1JQgHb66FeoVCptW3muHNvm7EXrt7uZLGb93SVYPnK9tq+/Vv5jtPi2hIjPszkhi/Hq0RsQoq7+SynF4K/HC47ZUEb+1aM3Bp/xzVN30b5yT851Yd0WQanQf9ZuYc79eQlBVfKr07etGIJ/Np4yqQ+G68KCIIap2FWgZ60TyCL7gqSN5bZVvQGRTjE760xl6uMq1RXJBxcte82bETeiXe4xUFVCgd+UrEfcf6a/r4TvjHzGq8CpMh9XDzR7i2nzpD3+rsDWgMQAUMV9k/phuC7MNzGcBSbQXQx7BkF/Lj2kV4TmCVCVSoXffplSJMEs+bAvFHIFZnSKMKp9i7c6Y8GvyzGqiPctaKvGb8LaCVtx9Z+bWpGuVCgxvWME5x6dqvbD5UPXMaHVbMG+xO/3hkqp0vd4tchlCpzfdxk75v+JI+tPIuFFolnzpVQocfvsfdw8dVe7GoHBMAYWBDFMxZ6+iaT2Fxa3BQQoVb0BSfgS5u/x9gVJHw+qem388WXx/1OLUsEj10y1xiAZkaCZyzhL+InyNUhiS27b5K4gsn9BEn4Q/j1pvxn9nClJAcn+EyRzufolAckwfBFvP+mgsvOgirtmnafOcF2Yb2I4C0yguxj2DIL0VRlvWjIIKXHq/dRn9lw0WgQL7bluX7kH1k/eLvh9nvXwGYwrR25ox5glzUbvBsOLLtBF6ox83l7ukT9NRm52fpE2hVyB+//G4MnN51CpVBj81Ti9y/ALnscOADlZuYh9+BpZ0myd55yVnoWJbcI4Y5ncbi5vWwbDGlg0CFo8FR+vmuNQ9tFiFgRZGrsK9LSRwqI7sVl+u/TJRRDn+YKWJLU33E9KD1DVa+29qeIhinaueaFx5O19z1jIeRaUpIHKr4GqXoGqXoHENwL/PnlvkLhPdPbpU5ICqnymXcbP+U5xr9CLiQagmUuYyGbYDOabGM4CE+guhj2DoMy0LLQo3UUni+7vLsGIHydp2y3otwIBHoYrt/dpMIz38wAPCeb2WIL27/YUvDZ67Ea8eRLPGxgsCo026v6mmL+bBCtHb+R9Lpf+viZ4XTOvTji25Yy2rVKhxIrf1qPFW53V33t2RES/5cjJytW2GR84U0fs+7tLMLFNmAVnk8EQhgVBDFOx6xJ3wT3S3qCZK7TthIuUFbR6IAn+AqK2DkjmCv3X5/4DqkriHSdJsNDZ64WMys7y3086U/hFQsIPoIq7+c9QFa8pBqfJ8sf/FyRzQ/4WL5IBEv8Fb3+mLnVnMMyF+SaGs8AEuoth7yJxJ3ecR4CHBP7uEk0hMjHE7/dGbEz+/uolg1cLCuRW5YKxKDQarcoH8wthDwnavhOC2Iev9Qrm8YEztYFDYY5s4M/0+7mJ0emjX3lfMBizLL5dpR6891s3aZveFwJZ6fnVcBcNihZcFdC34Qj8sfig3jG8eRJv2QllMHhgQRDDVOwq0CkFSZ+iEYx1od0rndINlOavfCKJPwuIXB91wbeU3sLCPM4HJFkMkntMv2DO2iOYURbO9PuAJPxPlINoOAAAIABJREFUWEwbzOqP5L9fUjvh65JaF3h+CpBEP4H7e4Ok9AHJCIfgEv3Enyw7oQyGAMw3MZwFJtBdDHsLdAB48yQeayduxfxeS/HH4oMcAQqoC53xim93CSa01r9PO6JvFN48VYvQtu+EGMhqizG2+Qw8vvGMc395rhw9fYdwstB+IjH8RGL8+/dVrJ24FS3LdtWOSehlAZ/A5wu81k/ZrjeDrpCrlwqmJ0n1CnlDy/mblgzCpUPXrTOpDEYBLBoELZqGj6PnOpR9tGia3f8dLW7Y2zdRSkHll0Ck00DSJ4DmHgGl3OKaJCNCWICnDuIRoN7q9ol+6jPBSTaoKs4I0dwQJH0yKOGe3KFe5l6/0Bh81RXllY80Z6DnZbA/1fOyoJCl9OR9JiSpg/DLhpT8F84095DhlwBxdfW+QKCU/4U5g2FJmG9iOAtMoLsY9g6CjIFSisiBK7UCuKlILT671w7FGP9pvHu1AzwkiBywEoD6rPUzey4i6P3eBgWrv7sEgWW64sX9V5wxpCakY3ZwJAI81YK4zyfDcfGvq9rvc7Nl2DF/H/zdjSso5+cmxuCvx+n8VmlyBiQf9BEc27xeS7VthV5cmGKxD1/rjIHBsDQsCGKYilP4JpIBkpRXSM07XwCnDlaLaiHxmXtEc70UNHuz8ZntpJagVM4dg/wGSHKnAtnpvpyj4IgqCSRliAkZdB/QzMW6v1V+Sa/ApzkH8u+ZEQFuhXY+01PgzshK8AxGUWG+ieEsMIHuYjhDEASoRfrFv65idnAkJrYOw+4FB5AlzUb32qGC4nPkT5MhTc7Ar5+ONDqjnCee5/ZYojOG22fuYeh3E9BUFISWZbsicsBK/L3mGHr4DjFZGPuJxLh8+IbOPTbP3C24PL79uz2RkZp/tuurR2+Mv1+hPv09JBjtP82qc8Zg5MGCIIapOI9vygHN3gqSOgAkbag6e6x8rVdo08wVoPLrmoJrplVipzn7C92fqu+ftx894TuQzJUgGYtB4j83qW/tGeKqZJ3fqT6jXWCsKb05q8Fo9iYjf1eBlxoFf2PWGqvPG4MBMN/EcB6YQHcxnCUIEmJc8xmCGfQFvy7HnJDFequhC1mbCt0597l99r56r3wBoWvu8Wt+bmL0+WQ4lgxZzdlrDwDDvpsgeF23WqE6v3/49xPh72H493Wp1r/Qy4tJSE9yzjlnOB+WDIKqRk5DtZVzHcqqRrIgyNI4s2+iVKY3g05y/gJJ+EZvRlrQUvtz75W5zHBG2mhrCJIsAc1cCUqkBX4P0fvCgUhncMdE0jS/X9+YvDXHtX3K/Uw6iy1vZ9gM5psYzgIT6C6GMwdBAHD58A1BEXzv3xg08zSv+rqfKAiZBfbCW/I89IIvEZqX6oQbJ+4AAJ7efqFdQq9joiAM/O8Ynd+f9CoZfT4RPgbOz02MZl6d4Oem3jOf94Jhfu9luHbsFlQq485SZzCKAguCGKbi7L6JSMN4BKqvOsOde8J8EZ3wvfYelGTCcketFcqkJ/6kzaST7N36BXqho9kAgMrOg8Q3NnyfOF/Nc1If00YyokAV9202TwzXhvkmhrPABLqL4exBEADsizqMwDJdtaK0ZblgrBy9AQ+vPC6SgG7/bk/sifwLlFLt+eWWNj83MbrVCgWlFCN/mqxTEb6gRY/lP5aNEIKr/9xEeJ8obUX8vBcTLd7qrHcFQaeq/fDg0iPefhkMS8GCIIapOLtvolQOkjaGK9ITvgfJ3gKSvaNoAjqpPajsvGZfuKXFecHM+BT1Pvu4BvrbyvmLjVKSDZK9DyQ5OL9P7d50AxXmk7uCklQbzxrD1WC+ieEsMIHuYjh7EJRHTmYODq8/iRCfwRwBmlddvSi2YeoONC/VySoCPc/6NfrNYJuW5YIRG/Na8MgdAEiMTcaWWXuweNAq7F16SK/gb1oyCP7uYrSp2B1Z0mwbzhbD1bBoELRwGqqtmOtQVnUhC4IsTXHxTVT1RrMf/IsCArRe0TPccT4gWUUU+gbNW7P33NALg3YgJFevb6KKmyAZc9VnqWdEGveCIKW3DWeK4Yow38RwFphAdzGKTRBEKfo2HKGT6bbEsvQWpbsYFLqWyKQb2zawdBcs6LcCya9TIJcpBJ/Jsc2njetTFIQDK47YcLYYrgYLghimUmx8k+oV1EehWWKPeCGRntTaygI972WAkW0TvgHJXAWiygCl/NunKKXqgnpG9kmVL2w8YwxXgvkmhrPABLqLYesg6OntF/j34DUkvEi0aL+3Tt+zqoB2WBMF4feWs/D01nPsizqM0f7TMNpvKjZO32n0kW/NPDsiegz/8nkGwxKwIIhhKrb0TZQqQeWXQWVnQUmm4QtMgGQsgMHl3LYQzza3huoz5JXPQDLC1Zn41FAQ6WyT+qGy8xadDwajIMw3MZwFJtBdDFsFQYmxyRj81TiOsJzZZQFkOTKD12ZJs/H36mPYOG0nzu29BJVS9838obXH7S+W7WT+7hLtygE/UZBZ2f7D605YYdYZDDUWDYIWTEe15fMcyqoumM6CIAtjK99EZec0FdXzROEnoFmrjbtWGQuatRo0MwpUcZu3DUkb4eBC2prmA/We87zVA6a+qPAGVcVZcroZDA7MNzGcBSbQXQxbBEFCy8/93cQI7xul99rbZ+6h9dvd0FQUpL2+V72hSH7DLR5z9/wDq4lfS1dvdyTzd5dA8mFf5GYbflHCYJgLC4IYpmIT36Rn+TnN/Vv/tVmrkX+Ot0aAp43UWdpNMxdZSaBbesm8o5kPSNpQq809gwEw38RwHphAdzFsEQTdOHlHUCAGeHSENCWD9zp5rhztKvXQEcj+7hKMD5zFaUspxcD/jtE9E1ykySqbIlxFQdoq6JIP+yKwTBeThW/X6v1NvobzXPKOW7Py3vf+jUfh5YNXVpt7BgNgQRDDdGzhm0hGuEBW1wckOUjwOiq/ISgsadYGbltVHNRHoVlCpOdlpOuAJEvM6yPh5yKKe2st1y9o3iBpw0EJK17KsC7MNzGcBSbQXQxbBEF/RR/VKxIf33jGe93pXRf0iujU+DRO+5S4VIz8aZK2jZ9IjFFNpxgvij0kGPq/37Ev6jCix2zEX6uOIjdbhn6fjTRJ9LYqF4yrx24VTTyLgvDk1nOsGLXBKhXklwxZg+d3X1ptzhmMglg0CIqYjmpR8xzKqkawIMjS2ESgpw0RFqvxXwhflz5BWKgmBeq0p/JLIAk/FOi7IUhKNxOEsjeIdA5oZhSIdC5I7kkQosoX68ZacieQjIVFE9nJIaCy0yCpw6wgzOuCZG8HVcVbbc4ZjIIw38RwFphAdzEcOYO+L+qwXpH5/F4s73WxD1/j6j83kfQqGStHb0SAR0ejRGu/Rr/hzZN4rPhtvXpZfckgBNccqP2zKfbX6qMQv98H/oaWxwtkyP3cxMjJysXInyZZZYl9q3LByMnKtdqcMxgFYUEQw1Tsn0HvIHxdaqiwuE74ivcaSgmo/Aao7AIoyQJJamG8cE0boy62lhqqGa83SGIbMwXwHgMvBvKW7Qt8n9gMlEihXhVgaYHOjlZj2BbmmxjOAhPoLoa996DP77NM8LqYq08EBWabCt31HjF272IMwvtEIcR7MPxEhgXur5+ORG6ODONbzDR9SbyZpld4i4KwoN9yo/tqUdr0Zfi3z9yzxnQzGDqwIIhhKjbxTcpYCO9BPyh8XeZyARHrC5I6QPg6qgLN+UuduY//3IBY1YxJOhWUpIAkfKVfONvSpLOMbOtj4GUAn9W3xlQzGLww38RwFphAdzFsWcV9UKEq7jM6G67iPj5wFm8Wese8P3nbJ71OwfAfJpolmKNGrrOJMC9oeXvd+axl2a5G9TGxdZhZ9350/ak1pprB0MGiQVD4dFRbNs+hrGo4C4Isjf2quDcwWMU9XzD7FhKjdUEVN3mvIbKrIPHfmChWNZY+wwyhWxTzAYmrJ/CdL0hSSyNeFviAJLU3/aWCnq0FDIalYb7JuXj06BEOHTqEnJwcAOoEoKvABLqdWbp0KapXrw4vLy80btwYp0+f1tv+5MmTaNy4Mby8vFCjRg1ERemvil4Ym5+Dfus5/j14DfHPjTsHPTdbhiWDV2szxOL3e+OPRQd5/0+Z/CYVQVV6my2WrbHXW6+JgtD+3Z46KwsKWqvy+pfXjwuchbYVQ0y6r7+bGCHeg13qHzaGfWFBkPNTnH2T+hz0S6CyM0afg06Vz0FSeucL56Q2oLIL/G1lZwwIbEPiu5ENxblGhMd/Ifx9UivDfZh43rn2vtLplpxaBkMvzDc5B8nJyfjll19QsmRJiEQiPHnyBADQq1cvjBgxws6jsw1MoNuRbdu2wcPDA9HR0bh37x6GDh2KMmXK4MWLF7ztnz59itKlS2Po0KG4d+8eoqOj4eHhgV27dhl9T1sLdHORyxRIS0yHSqV7BnoeUcPXGlzO3qpcsG1FuAGb13MJ7+d+IjF6NxiOHfP38X7fvnJP7Is6jLhnCSbdz08UhFblg3H/3xgbzh7D1WFBkHPDfJMwlGSBknTh7ykFSQwwkDW2tQA3wrT73flEdBhISgh4s+NJrUBlZ0Gzd5l+z6SWep8lg2FpmG9yDrp164aAgADExsaibNmyWoF++PBh1KtXz86jsw1MoNuRJk2aoH///pzPfH19MXbsWN72o0ePhq+vL+ezfv364auv+IvU8OEsQZAxdK8zyKBAXTpsjd1FeUHr8F4vdKr6K/zddbPop3ddAKUUeyIPoF2lHmhaMgiBZbogesxGKOTq/feyHBmav9XZpHteO37bzjPFcDUsGgTNn45qS+c5lFWdXzyCoKtXr+LWrVvav+/duxdt2rTBBx98gL59+3LaMt9kHOpj1gwI00Q/zXJwoTZ2OPM8sQXUy9wLinAfkPhGoKrXoCQbJH0stEvhE74Dzdmb/7tlZ027X3wjEJJlx5liuCLMNzkHVapUwY0bNwCAI9CfPn2KMmXK2HNoNoMJdDshl8vh5uaGPXv2cD4fMmQIvv/+e95rvvvuOwwZMoTz2Z49e+Du7g6FQriAWkGKSxAEAL3rD9MrTHvXHwZpSgYCywjv7TZV7FrKutcZpBXpXWsMwLEtZwCoi921fUe9hN3fXb06IMR7MBJjk7W/e1FotOFq8Rrzd5cgasQ6e00Rw0VhQZBz8MUXX2iz3E+ePEGpUqXQsWNHlChRAoGB3OPDmG8yDqpKNiBOvUGkYaDy6wbaNbC9SI/zBkn8Jf/vyZ1BFeriojRrI/KLwGlEfOoQUKpUf09VmmuNP9KNyk7Zc6oYLgjzTc5B2bJlERMTo/1znkC/dOkS3nnnHXsOzWYwgW4nXr9+jRIlSuDcuXOcz2fOnAlvb2/ea+rUqYOZM2dyPjt37hxKlCiBN2/e8F4jk8kglUq1FhsbWyz+zwsAG6btEKyM7ucmxpUj6rdvi0KjhUWsKAjdaodqr7FVRfemJYNwdu8lpMSlghACAFDIFRC/3xv+boWq37tLMKrpVO3vzs2WYWIb4wrF+btLMKfHYrvMD8N1YUGQc1C+fHk8fvwYABAWFgZ/f3+tb3rvvfc4bZlvMh6SLBbOgid8DapS12QhCd/pEbCNQeI/s0NG/RMQ5UtQkqb9PVRxV1DQ06xV+e2UT0ESmxov0HP4i78yGNaC+SbnoEWLFpgwYQIAtUB/+vQpCCEQi8Xo0EH4SMziBBPodiIvCDp//jzn8xkzZsDHx4f3mjp16mDWrFmcz86ePYsSJUogLi6O95rJkyejRIkSOubM/+fNycpVF5ITyH63r9wTp3flF+8Z+dNkg0K276cjMKntHCwZshp3zz/Aphm7rCrW/dzEmBPCFc6ndl3Qe03CyyRO+6e3X+Dg6qPo+FFfvS8g9i8/YpN5YTDysGgQNG8Gqi2Z71BWdd4Mp/93FADKlSunzVI0bdoUCxcu1PomT09PTlvmmwxDlU9BUvoIi9KktiCKh9r2JK6h4Yx2UheQ1KEgGZEgylcgyV2sLtILC2eSPg6C1dkT/bjPgBJ1pfzMKAPZdG9QJX9NAwbDWjDf5BzcvXsX7777Lpo1awZPT08EBQWhbt26qFKlivalcnGHCXQ7Yasl7sUtS0EpxWi/qbx7uDtV7cc5H3zQl2MR+/A1WhpZKM7fXYIL+68AAHYvOKD/3HIL2OT2c7W/6+Cqo2j+lv6q8o+uqY9JI4RwKrInvUpGaJMxvL8nuOZA5GTl2naSGC4PC4Kcg59++gndu3fHhg0b4OHhgUePHkEul0MkEuHdd9/ltGW+ST9UlQQS34RHlHqDJPxQIAvuA5I2CkR+33jRnPANqEq9EoGk9LJ6Rp1mb1H/JqoASZ+gv3184/xnQAn3mcgugsT/l//FQ9oo200Og6GB+SbnIS4uDpMmTUJgYCCaN2+O33//XXBFVnGECXQ70qRJEwwYMIDzWd26dfUW4qlbty7ns/79+7tUIZ675x8YLYD93SXo8G5P47PaoiB0/rgfVCoVHl17alVx7icSY0/kXwCAq0dvGdV+UWg0RjWdAj83MZqX6ow5IYuR/CZV+2xObD+L3g2GaX67GP0bj8LWOX8gNYFVyWXYFhYEOQc3b95EgwYNUL58eUyZMkX7+XvvvYfatWtz2jLfpB+auUg4y6xjPiCJzUwQzb4g6b8DAEjmUutn0JXqDBXJmGv4ZUB8Y3WV97zK9QlfgmYuBqXqFzOEEJCMcJCELzXXfKquCJ+zD5TK7DZfDNeE+SaGs8AEuh3JO8pm9erVuHfvHoYNG4YyZcrg+fPnAICxY8eiW7du2vZ5R9kMHz4c9+7dw+rVq4vtUTZC7IrYb/XM9sS2c3gz9JYyf3cJutcORXZGDgBgfMtZZt3P30OCrjUGIEuarX0+KpUKs7stUot6NzGaioIQ4NkRB1cdtdeUMVwQSwZBH8+dgeqL5zuUfTy3eAdBGzZsgLu7O/NNJkBSelpXOMc3NlD53RLmDZI2GgBAqQwk3tASfH39cM8qJspETaX4OvkvMhK+BFXctcd0MVwU5pucgzVr1mDHjh06n+/YsQPr1rlG4WMm0O3M0qVLUa1aNXh6eqJx48Y4dSq/qmlISAh++OEHTvuTJ0+iUaNG8PT0RPXq1REVFWXS/Zw9CDqy4aRVxbm1LbBMFyzsv4KT1e5WK9QimXgA+GPRQTTl2zsvCsLTW8/tMWUMF4QFQc7By5cvERsbq/37v//+i6FDh2LFihXMN5kISRsJUyqYO5zFfweaFZ1flV31psh9UuWj/OeT0ofn+fiAJPxPm21nMKwN803Ogbe3N44fP67z+cmTJwWLlRY3mEB3MRwpCHpx/xXWTtiKRaHROL71rPasb31kZ+SgVblg+Imsm0W3ls0OjtT5TeNbzjJ7VYCfmxhTxfO1ffWqN5RXoAd4SLB06BqLzh+DIQQLgpyDb7/9Fhs2bACg3u9Xvnx5fP3116hUqRKmTp1q4GrL4ii+iVKqPtNbOgNEOgtUfoVT80PwOtl5+4vsoojpQoXhipZB1/SZvU3dlyoe+pbKU9kJa0wlg6ED803OgZeXF549e6bz+bNnz1CqVCnbD8gOMIHuYjhKELR3yd9oKlIv9w7w7IimJYPQt+EISFMyDF575cgNBJbpAj+RGAEe6mvbV+rBK16beXU0Suhac0l74TGlxKVyfo8xe9CFLMBDgvA++ZmqvDPU+e47o1OExeeRweDDokHQnBmovmi+Q9nHc4pHEFShQgU8ePAAABAZGYlvvvkGAHD48GHUqFHDpmNxBN9EqRIkNVQjHOtqrA5I+gTjRHrmovzMsDZb/F/o7k33BYn/giejzGc2OmItKVDn9xDprKIJ9NyD6ucieExbnpDfafG5ZDD4YL7JOahatSr+/FP3GMa9e/fiP//5jx1GZHuYQHcxHCEIevXoDW+W199dggX9Vui9VqVS4eapuziy4QTWTd6O/p+P0gr85qW4VdDbVeqBXQv3o3vtQVqRmifEo8duwtWjNzG9UwT6NfoNkg/72CyLfvvMPZ3f1crISvN8dvNU/h6+Mf7TeF82+LmJsX3uXovPJYPBBwuCnIMyZcposxStWrVCWFgYAODFixc2z1I4gm+i2Vv1iM1D+q8lWaC5x0Gyt4GkTwNJ/LnA9Q24/SW2AslYXuCccx+NEK8PknMEJHsnSEoPkKTAAm2sbfV1fhMxIKz1vlSIbwRKczTPJhsk7hPhZ6vQ9YkMhjVgvsk5GDVqFKpVq4bjx49DpVJBpVLh2LFjqFatGkaOHGnv4dkEJtBdDEcIgjZO2ymYsQ4s3UUwUxFz9Qm6Vh/AvYZH6E8Tz8e5Py9h04xdGuGfv3y8VblgXPr7mrZPuUyBXvWG2iyD3lSke545APT9ZAT/3nE9/TQtGYS1E7Zy+rlx8g78RGLOGe551eylyYZXJzAYloAFQc5BkyZNMGbMGJw+fRqlSpXCjRs3AAAXLlyweZbCEXwTSRYLZKx9QFIHCF5Hs3dC90xz70J/9gHJiACRXVSLb+3nmnaJfiCq/COEqCJGI+xtkUH31jnPHNAcHWfW/RuAyk5x+iIZC/mfa0pvy00gg2EA5pucA7lcDolEgpIlS8LDwwMeHh5wc3NDz549IZfL7T08m8AEuovhCEHQ8pHrtVlvPlMpVTrXZGfkoF2lHkYJ6ZZlg/HszgvBLP3ENmHIkmZj+9y9CPEZbLPMub+7BOMDZyL5TarOS4g/lx4yqa+2FUPw+MYz3ud7ft9ldK8zSNt25E+T8fLBK2tMJYPBCwuCnIMTJ06gQoUKEIlE6Nmzp/bzcePGoV27djYdiyP4Ju1RYXyW0pX3Giq/ZLwITumjP0ufvRlU+QJEOl3g/HArWuZKUJKm+0xS+8Gk4nfJnUBVibrPiRLQzGUg8Y00beuptw6QLIvPI4MhBPNNjg+lFM+fP0d2djZiYmKwY8cO7N+/X3uKiKvABLqL4QhB0Lk/L/GKTj83MQZ/PY73mr+ij5qUYV4UGi0s5kVB6Ok7xOrHtRW2NhW7a//cpVp/nNp5Xvv7Yq49Qeu3u5mUQc9MEw5sKKVIjE1GepLz/iPNcF5YEMTl1KlTaNmyJT744AOUKFECf/zxh8FrTp48icaNG8PLyws1atTgrYq+a9cu1K1bF56enqhbty727Nlj8nNWqVRITeXWxXj27BkSEhJM7qsoOIJvItKpAmLUBzRzMf81qYNMELD1QJK7CmSlvUESW0OdibdxNfj4JgUEtoRbfT1rI4w/370OSFJrvc+YUjmo6hUT5gy7wHwTF0f0TYQQeHh4ICYmxuhriiNMoLsYjhAEqVQqDP56HEdA+7uJ4ecmxrVjtwCoBeat0/ewdfYe7Is6jKVD1+jNuhe20QJ7sQvez5biXMh2hO9DTmYO2lfuafIy+z8WH7TbHDIY+mBBEJeDBw/i999/x+7du40KgvLOFR86dCju3buH6OhonXPFz58/Dzc3N8yaNQv379/HrFmz4O7ujosXL5r0nJVKJf755x8sX74cGRnqbTCvX79GZmamSf0UFUfwTVQZqz5vnCOQfUESvgElKeo2VA6a8xdo5jLQ3L9BEgNNE8NJrfV839A0MWw1qwuieAgqvyzwMkGfNQRV3LTbHDIY+mC+iYuj+qZ69erhwoULRrcvjri8QA8JCeGc71rccYQgCFAvWY8asQ5tK4bA302MYd9NwI0TdwAAudkyjPabqhbS7hJOtXZjs8tT2s/l/c7PTYwWb3W2uzAvOJ6tYX+Ytv+8oMCfv8+u88hg8GHJIKjanBmoETnfoaxaEZYRGhMEjR49Gm+//TbHN/Xr1w9fffWV9u8SiQTNmjXjXBcQEIBOnToZPZbnz5/D19cXpUuXhpubG548eQIAGDp0KPr162d0P5bAUXwTVT7WVHKvBxLXACRtJKjqdf53Cd/mC/e4OlAXPzNBVKcNE2hvo2rtxlrC13pWBxgaaz1Q+Q27ziODwQfzTcIY65t8fX05n1nDNx04cADffvstbt++bfQ1xQ2XF+jt27eHl5cXateujZkzZ+LVq+K9V9dRgqCCFN6PvXzket0Mtyhf0BojejfN2IXpHSPU12mu9feQoJlnR91Cc3a2QV+ONWl1QEELLNMFOZk5dpo5BoMfFgQJY0wQ9N1336FWrVoc3xQdHQ13d3coFAoA6mNoIiK4RydGRETg448/Nnosbdq0QXBwMORyOcqWLasV6CdPnkTt2rVN/GVFw9F8E6WU45sopSCJzXkEq4kZb9k5kMQfoZOlj//OwLV2EPAJP5l5rTdISg87zh6DwQ/zTcIY65uGDBnC+WzPnj0W900VKlSAp6cnRCIRSpUqhYoVK3LMFXB5gQ4AycnJWLhwIT777DO4u7ujWbNm2Llzp/Y/tuKEowVBhaGUCu7F9nMTox3PeeeFrZlXJyTGJkOlVGFP5F/o02A4xO/3xpQO8/DwymOsnbBVcDn5oK/G2lyg96o31OwMetOSQVg9frO9p43B4OAqQVBsbCykUqnWZDKZwd9lTBBUp04dzJw5k+Ob3NzcUKJECaxcuRIKhQIeHh7YvJn7//3NmzfD09PT6GdcqVIl7TnoBQX6s2fP8NZbbxndjyVweN+kuGlAlNY38L0PSFIrtfBXJYNIZ4IkfK826Uz1Z0nthAV/or6l8VaypJamv4AoYFRxx97TxmBwYL5JGFN8U0HOnTuHEiVK4M0b9SkUlvBN69at02uuABPohbh27RoGDRqEUqVKoXLlyhg2bFixKlTg6EGQUqEUFKIBnh2xcMBKvVn0wNJdcGH/Fd6+Xz54hVM7z+PKkZsI8R7MydL7icQY+N8xaF7atsvf/dzECOsWicAyXYvUz+ndpu07ZTCsiUWDoLCZqLEw3KGsWthMlChRQscmT55s8HcZGwTNmjWL89maNWtQokQJeHl5oXLlyhCJRDpZik2bNsHLy8voZ1yxYkXcvXsXAFegnzlzBu+9956UptZHAAAgAElEQVTR/VgCR/dNNPe4fkEqnWcgG90UVPlSt19KQOWXQXMPgeT8DfXRannZdY04Th1ie3EeVwdEGlm06+M/Ay1wdByDYW+YbxLGXN909uxZlChRAnFxcQDUAn3Lli2cNqb6JgYT6BzevHmDsLAweHt7o0yZMujevTv8/Pzg7u6uEwg5K44eBAFA7wbD4SfiF+Entp3F/N7LdES6n5sYvesP413unZ2RgwmtZnOz1vWHIWrkOgz4YjQGfzUOuyL2o1f9oTbPnjctGYSwbouKJvJFYvRr9JsdZorB4MdVgiBrZSkKLyN88+YNgoODUaJECZQuXRrdu3dHqVKldES6qcsIJRIJ+vbtC0At0J8+fYrMzEz8/PPP6NHDtkuUHd03UVW8nmyyL4jyNc/SdY2l/w5KiW6fihiQxKbctil9QdLHgyQFgqT0Ask5yN+nVc0bJO6/IElti9iPD0hGuB1mi8Hgh/kmYRxpifuLFy/0mivg8gJdoVBg165dCAwMhIeHBz7//HNERUVpq9kCwNatW1GhQgU7jtJyOHoQBACnd13QEaH+7hL09B0ChVwBea4c83otzV+mLgrCxNZhkKZk8PY3OzhSZ0m7v4cEveoNBSHqoOnRtae2F+eiIAz/YaJF+vJ3l9hyihgMvbhKEGTtQjwFfVPlypVRo0YNrW+SSCT47LPPOL6pWbNmJhXief36Nby9vVG3bl24u7vjq6++QqVKleDj4+OSx6wZgqRPgO5ecG+Q9CkAAKp8CZIsLvBdA5CMBfzinMpBEr7hEd8+INL8JaREGmaH7Hl9ze+wwL73lN42mx8GwxDMNwljrG+qW7cu57P+/fvrFIlr3rw5p42pvqlkyZIQiUSC5gq4vECvVKkSKlasiIEDB+L69eu8bVJTU1G9enUbj8w6OEMQBADHtpxBcM2BWvE5XRKO1Pg0TpvUhHTcOfcACS+TBPtJT5LqPb7s7B//AgAiB0bbTJjnZf8teQ57UBUWBDEcBxYEccnMzMT169dx/fp1lChRAhEREbh+/bo2EzB27Fh069ZN2/7p06fa5eydOnXC5MmTdY6yOXfuHNzc3FCxYkXcv38fYWFhZh2zlpOTg9WrVyM0NBQDBgxAdHQ0cnJsX3jSGXwTpQqQjHCQ+M80S7gbaQS4kttO+QxUfg2UCB9VR3MP6hG29UCI+jmQ+C9tnDnXvCSwVJ/p4606JwyGKTDfxMUc31S6dGkMHz4c9+7dw+rVqwV9U1hYmNm+6caNGxy7fPkyVq5cCV9fX+zevdvofpwZlxfoGzZsQG5urr2HYTOcIQjKg1KKlLhUwSrlKXGpuHLkBp7ees6ptitNycDq8Zsxv/cy7I48oD/z7CbGytEbMandHKuL8lblggWX7hfVFoVG22paGAyDWDQImj0TNRaEO5RVm21aEHTixAnefYEhISEA1Md9/vDDD5xrxo8fj88++wyenp6oXr06oqKidPrduXMnfHx84OHh4fSBi3P5JjmoKgGUyvm/Vz4ClZ0BVcVxPify+yDpk0HSp4Kkz+LJnhew+M/V56zH1bNDBt1yxo5bYzgSzDdxMcc3nTx5Eo0aNbKLbzpw4IDOeIorLi/QXQ1nCoKEUCqUWDhgBSczPuCL0XjzJB5bZu0xS+CODZhuswy6pS3AsyOyM7KR8DIJLx+8gkqlsvcUMVwcFgQ5B+vXr9drtqQ4+CaqigNJ7sjNSKeNAiHZIMndzRC4Puq96FYV0VZ8AZDUCpSqQJVPtGfJMxj2hPkm5yYmJgalS5e29zBsAhPoLkZxCIKix2zUyUQHeEjQ8T99zRa5QVV6oVW5YKuJ6G61Q4t0vb+7BOIP+vB+t2r8Zgz6Mv94uI7/6Ytjm0/be5oYLgwLgpyDChUqcKxMmTIoWbIkvLy8bH7WrLP7Jkqp5lgynj3liS31CFl9+7x9QVJ6WFegp/Qseh/xTQr9bm+18M9cAZLwbQHB3h5Ucd/eU8VwYZhvcg4KFriTSqVIT0/H/fv30bFjR3z66af2Hp5NYALdxXD2IEieK0fLskU7kkzIHlyKETyDvajWqlwwmnt1MumaZp4d1X8WBUHyQR8sH7kOayZsQaeqv8LPTYxe9Ydhf9RhtKvUg3ef/b8Hr9l7uhguikWDoFkzUSMi3KGs2qziEQTxERMTg19++QWHDh2y6X2d3TdR+b9mCty6+r9PloBkbTUg5M01H5DE9kW43hckMQAkMxokbRxI/Kealwo9QbI28ozZByS+Magq2d7TxXBRmG9yDviKxJUsWRIff/wxzp8/b+/h2QQm0F0MewRBcpkC/2w8hbk9l2DxoFW4c+6B2X3FP080WySHFsgyFzbx+73x79/XrJZBb1rS9KJwK0Zt0GTPxdosepsK3fHkZv6e++1z9/L26+8mxrDvJlhqChlOAKEUMqXScEMbwIIg5+by5cvw8fGx6T3t4ZsoSQHNXKlehp6xEFT1yvy+sreZL3ITfhIQ4L4gaWNApLOsJNDNyZb/r0DW3Tt/XEltQUmm1jeRlG7gLzbnA5q5zFJTyHAClAolVErH2HrHfJNzcPLkSY6dPn0a9+/fh9JBYhxbwAS6i2HrICgrPQv9G49C05LqZegBHuqs8Kqxm8zqT5YjQ2DpLhYXzzvm/YmlQ9dYrYiboInU55gXFtk9fYfwC293CYZ8k18Vl+8IuTxrVS7YUtPIcGCkslyMP3YEvksWokbkfARuWY/jz57Yd0wsCHJqrl27hnLlytn0nrb2TVRxByS+sUZE+mqsLqjshHn9yS5YJcNNFbd1z0q3qAkJ/y/4PxfcS+8DmrlE+zxIvMD1cT4gaUP0PElGceHJzecYGzAdfiJ10mBS2zmIjXlj1zEx38RwFphAdzFsHQSt+G29oIC8e968TPryket1xKu/uwSSD/uaLLD9PSRY/tt6EEKw4rf1thXnGls8eJXJ1+QdORc9ZiP/8xUFoYcPC4KKO0pC0HLLBtReFI4akfNRI3I+akaGo2bkfJx49hQAcOl1LMYfO4LBB/djw83ryJLzV562JJYMgqrPnIma4eEOZdVnFo8g6M8//+TY3r17ERUVhfr166NZs2Y2HYstfROlFCSxBU+G11u9BJvKzOiTgCQ2B+8e9CSxgFjVl6n+HDT3IACAJPxiH4GeHGxaX4n5/82oi9sJrAoocM47o3jy+nEcWpUL5sQn/u4StK/cE8lvUqFUKHFs82nM6roQc3osxrk/L4EQYvVxMd/kPDx+/BiDBg3CL7/8gqZNm2Lw4MF4/PixvYdlM5hAdzFsLdCDqvTmFZgBHh2xZPBqs/pUyBWY23MJR4z3bjAcsTFvcPGvK8bvURcFYWrQPG2/9y7G2FycN3+rM3rVG2ryi4W8s99jH74WfAHyx+KDFplDhuNy6HGMVpgXtJqR89FqywZEXDiLGpHzUXtROGotUgv3H9atQmJ2llXHxYIg56BkyZIcE4lEqFKlCjp37ow3b2yb6bKpQFc+0is0ae4x8/pVvQZJascVv6mDQWkOiHQOzwsBPZa9U9svSR9vRXHOJ6LzXiqYeB564s/5zyJ7q0A7H1DloyLPIcOxiRywEgEeurGJv7sE0WM3Yvj3E7V/99e0myYJt/opNMw3OQeHDh2Cp6cnmjRpguHDh2PYsGFo0qQJvLy8cOTIEXsPzyYwge5i2FqgC1VGD/CQYF7PpUXqO+FlEs7vu4wHlx9zzkGnlOL22fs4sOKIQaHb8aNfOX1aq0hcc69OOkLaTyTGokGmZ8+Daw7Q/l55rhy7Fx5A81LcAnQLB6y0ydtohn2ZefoE6iyO4BXpQlZ7UTjG/GPdAmAsCGKYik0FuuKmfoGes9/8vikFVdwFzT0GqnxZ6LtckNxjINKZBsSuL0h6fg0RonxtJYGet7SfR4hnRJjeX4HMOFGlgqSOKtSmAWjOn2Y/W4bz0LPuED0xzEDBpMTJ7eesOi7mm5yDzz77DGPGjNH5fMyYMWjUqJEdRmR7mEB3MWwt0Ce3myuY4T26yfJHgSW9SsaNk3fw+MYzSFMz9R+9JgpC34YjONcf3XTKKgLdTyTG+MBZaCrSvEX2kGB8i5mIffQmv1q7kbYzYj9UKhXWTtyK5m91zr+HmxgjfpqMJ7eea38PpZSdi16MWXLpImoVWN5e0OosjkAtAZHuu2Qh56WWpbFoEDRjJmrOD3coqz6jeARBw4cP57URI0Zg/PjxWLNmDVJSUmwyFtsucZeBxH8unOFVxVv4fhRU8RBEdhFE+RxEcdewcM6Yy+mDJFvgODQ+SwpSV2LXfvYpiHS6+kWCiX1RVTwoSQFJDQU3M/8JSOoYEFV6gWeiAqXsJXJxZdh3EwTr6AglQvzdJJjcbo5Vx8V8k3Pg5eWFmJgYnc8fPnwILy8vO4zI9jCB7mLYWqA/ufkcgaW76OxD6t94FOQyRZH6luXIcHDVUcwJWYwF/ZZjtP80+Im4/+CHeA/SK3Z3LdDNlCzsv8KyAl0UhO51BgEATu44h7bvhOg4LGP7aubZETlZuVg1dpNgm1FNpyItMR3hfZahhaag3sAvRuPSIXbsWnEjVprOK9BrLQpH883rBbPrtRaFg2gEeq5Sge13bmHE4YOYePwfXHljfiXrPFgQ5Bz8+OOPKF++PMqUKYPGjRujUaNGKFu2LN5++218+eWXqFChAipWrIi7d+9afSw2LxKnXYKdlz3WCMqMogsEqooHzVwCkjYSJH2yZm96oSXk8T/qF7sKbnBKiJynHwtk0KXT1XvypbOhe+SbCZXjk8TqffhJrQWvo1mr1EXvUkI0beqCpPYHKbTSgOH8/L3muGCMIvmwj+B3YwOma/tIfpOKjdN2YnZwJNZO2Iq4ZwlFHhfzTc7BRx99hB07duh8vn37dlStWtUOI7I9TKC7GPY4yubJzeeY0n4uWpULhvj9Plg5agOypNlF6jM9SYqedYfmC1yRsKgN8OqIAIEsdVi3RRj8zXj4u4nRrlIPRI/ZiNxsGR7feIrhP0xCq/L8S/RNtQMrjiA1Pg2BpbsUqVL8oK/G4f6lR2heqrPedl2r9+cV/oO/Goc/Fh/EnXMPrJpBZdiOHXdvo5Zmj3meIG+zdSMOxDwQFOfd9qgdX2pODvw3rtUufa+9SH19+PmzRRoTC4KcgwULFqB9+/ac3yGVShEUFISFCxciOzsbbdq0gb+/v9XHYpdj1nIPgSS1V2d4E5uBZm8t8r+LVH4FJK6hRvgb2sMtVOncG0Q6DSThR/WfE/1Bs3eBEBVI9j5Ngbt6RRTnaoFMlY9Bc48UXexL54LkHDDQ7hOQuPr8zyV1KEj2DlDlCwvNLsOeEEIQ1n2ROgbz6KjdZ7502BosGbKaNz7xE4mxM3wfAODu+QdoWbareo+6xpp5dcKlQ9eLNC7mm5yDqVOnokKFCggLC8Pp06dx5swZzJ49GxUqVMD06dMNd1AMYALdxbBHEGQOSoUSj288w8sHr3gDpgX9VpiUedZnBZdh+buJMfLnyVhgwSx6+8o98c+mk9gatsfks9DNMj0vKwpaaJOxSEtM53n6DGfjlVSKZZcvYvbZUzj65DFUhIBQiuA9O1AzMpyz/9x3yQLcjI8DAEw6cZRTAb6g5bUxB4sGQdNnoua8cIey6tOLRxD04Ycf8mbH79y5gw8//BAAcPXqVVSqVMnqY3EW30RJBqjiNqhKN5tHKQFJ+MEIYW6OmK4DkrEEJKmFaZltfX0mNgeR3wZJ7mqhMRvTh6E23iDpk9ny92IApRT3LsZg9fjNWDtxKx5dV58skvQqGR3e66WzsjLEezCypNkghKBbrVD4F4qX/ERitK/cEwq5+asvmW9yDiiliIiIwH/+8x9tEdOPPvoICxdad3ueI8EEuovhDEHQ0U2nOdXfezcYjgeXuFVfhYrPObK1frub9hx4RxDp/u4SjGs+w06zzLAFMqUSSy5dwA9ro9Fo+WK037YZY/75GyuvXsKbjAw0jFosUEguAjNPnzD7viwIcg7KlCmDEydO6Hx+4sQJlC1bFgDw5MkTm5yJ7ui+iVKlZhl4/XwhmdoflKTmt5HfsLAwL2xFzZoLWUMrj9t0o1nr7TjbDGuT8CIRC35djqAqvSH+oA9GNZ2KZcPW4O81x3H77H29scvlwzfMvi/zTc5BTk4OsrPVK20zMjJw8+ZNRERE4NAh6xa4dSSYQHcxHD0Iunz4Bq+QbFU+GEmv84sV8R3fYSmzSZbbzuK8oCW8SLTjjDOsDaEUkRfPc/aj14ycj1oaIc5bYG5RBCYc/8fse7IgyDno0qULatSogT179iA2NhavXr3Cnj17ULNmTQQHBwMAtm7dis8//9zqY3F030Qy5kA3c+0LkizWZnSo7KLdha1jW+Ez4vVY4i92nnGGtZEmZ2By+7k6MUmbCt31xixn9lw0/57MNzkFfn5+iIqKAgCkpaWhSpUq+Oijj1CqVCksW7bMzqOzDUyguxiOHgSN/Hky79J1f3cJNkzJLxgxxn+axZa46wh0kdhkketIZuoLhrvnH9hxxhmWQK5SYcvtm+i6ewckO7di+ZV/kSGTAQBmnDqh99g1oSrwBx89NHs8lgyCakybiVpzwx3KakwrHkFQZmYm+vTpA09PT4hEIohEInh6eqJv377IysoCAFy/fh3Xrxdt36cxOLJvoiQT+Zlznmyv/JqmXRYcMRvtGGbqsvxP7DzrDEuQGp+GtRO2Ysg34zGuxUyc2HYWhBAoFUr0bThCMMkgVKsnwKNjkbbmMd/kHFSqVAl37twBAERHR6Nhw4YghGDHjh3w9fW18+hsAxPoLoYjB0EA0L5yT0HRPDVonrbdg0uP0LyU7tnipohYfw+Jzh4ncwSu3YR4EYrNFXR20uQMO844o6goVCp03b1dR2A33bAGT1NTBPeY52XS1cXhwjmCvcOOLVAS8/eAsiDIucjMzMTNmzdx48YNZGZm2mUMjuybqOKBXjFJs7fmt81aY6YgrYP8/dm+PNf7giT8zwGEthFCPP7rIvbhA5LUwY4zzrAEcc8SEFSltzamyjtlZ27PJTix7axJCYe8eGf95O1FGhPzTc7BW2+9hRcv1AUjxWIxpkyZAgB4+fIl3nrrLXsOzWYwge5iOHIQBAD9G4/iFZ4BHhJEDV/LaRtz9QkGNhmj/Qe8ZdmumNdzCSQf6jn7vGQQBn89Dtvn7sXzuy/R03eIun/PjvB3l8DPTYyDq45i+9y9/GLdgTLrzUt1hp+7+SLdTyRGZGi0fSaaYTF23bsjKL6HHNxvMHs+5O/96H9gLxpGLcLXq5dj/vkzyFYo8CpDit+O/I1PohahwbJIjDx8EK+M/HeDBUEMU3Fk30RJCvQVN6OyU5z2JOdPrpiO/xYkbSIMLvFOHQKa8yeI7BzyK8HX1YjeL0DkN0FSeglc38ABxHmeFT6uzXSjueZvsWE4BrO6LhRMeEyThBtMsKwatwmhTcagdflu6PvpCBxaexyUUtw8dRe//TwFLd7qDMmHfbBu0jbIc+VGjYn5Jufgk08+QWRkJF6+fIny5cvj/PnzAIArV66gSpUqdh6dbWAC3cVw5CAIAA6t5Tk7U6Re4v78Xiyn7ZENJ3UyyX4iMSa1C0OH93rx/oMfVKU3sjNytH3Ic+XYGb4PA74Yjd4NhqFfo9/QqnwwWrzVBcO/n4hJbedgVNOpmNJhHvYu+RvP78ZaXXgXdFoBHh0R2mSMxe/hJwrC0qFrilQNlWF/bsbH4fu1KwUFeOMVS/QK9BqR87H/4X2dfhOzs9AkOoqTWa+9KBxfrFyGhCzDGVaLBkFTZ6HWnAiHshpTZzn0v6POiKP7JpI2jEdg+4Ik/AhKVYXajgQ3A675s3Q2BDPrKf25fSiTQNIngSQGaizvaLXP1SI95VeQ5O4g6WNBcg6CZO+2sQj/3AKZcj5rCJq925ZTy7AwKqUKZ/Zc1LsaccAXo/UKdD93MVLj03T6vvrPTfUKyALX+rmJMcZ/mlHVvZlvcg527twJDw8PiEQi+Pn5aT+fNWsWmjVrZseR2Q4m0F0MRw+CKKVYNXYT5x/2wDJdcXL7OU47lUqFjv/Rnynns7YVunNE6dk//lWf0Smw771VuWDEPnzNuXfXGgOsKtD93NTCfEanCNy/FCP4siHv5YXp/YuxfCSrkOvMUEox47T+veU1IufDZ3EEvl69XFjAL18CuUql0//882d496bXXhSOOWdPGxwfC4IYpuLwvolkgCR344rJxJ9BlY+57ZSP9IjPT8CfifcGSQnN74NSEOmM/JcAOu19QJLagNL8rCFRpQiLf4uZN0j8f0GkM0FkVqpYLztvszllWJ7sjBwM+nKswTik32e/6Y1fporn8/bfv/EoQeF//fhtg+Njvsl5iIuLw7Vr10AKbLf7999/cf++blKhOMIEuovh6EFQHkmvknFkw0mc2nkeOZk5Ot+/eRJvtgC+duwWts/di8WDVqGZVye9TsLfXYKO/+mLwNJd0Lp8MFq81dlg/wEeEkxoPduqIt5c83eXQPJhX9430wzn4dTzZwbFeZ7VX7pQ8LuvVi3n7b/ttk2C17TcssHg+FgQxDAVZ/FNVHEHNHs3qOysTuYcAGj2VvOEacIPIPLLIBnhIGlDjbzmO2iz6sZUSI9vDJLS08oivgjiP6Wvy5xxXFyJGrHOqNpAAR4dhbfoiYKwoJ+ub8rJytUbd62dsJVnRFyYb2I4C0yguxjOEgQZIi0x3e5iV8ixHF5/AilxqWheqpP9x1PAWrzVGfN7L0PCyyR7Tx+jiAw79Jfe4m/GWq1F4Rh79DBuJcRz+g/es4M3g14zcj467dpmcHwWDYKmzEKtsAiHshpTWBBkaYqLb6I5+80TpxbYt61fnDcCUT4GyTnsAGK88Ni+As1cwlkRwHBO2r4TYpF4pX3lHlg3eRuSXiVr+1bIFQjw7CiYfNga9ofB8THfxHAWmEB3MYpLEARY96i1opjkw75YNnytTavB+7mJMbtbpODz8BOJsXfJ3/aeMoaF6PXnniKL88K2/sY1bf9ChedqRM7H9ju3DI6PBUEMUykuvomSTJD4T+0venXMFyR1NEhigO3vLZ2l93uqfGbvaWNYCCEBbZaJgtCqXDDu/xuj7X9m5wW8cY6fmxhxzxIMjo/5JoazwAS6i1FcgiBAfYSH+P3edhfkfNap6q82v+fgr8djukBl1GaeHZGaYP7ZoQzHYsWVS6hpYYFea1E4Xmeo/11QEYLQv/ahRuR81FkcgTqLIlAjcj76H/jTqOPXWBDEMJXi5Jto7jHoq/puP2tknxcDGZEg8U14nokvSFJ7e08Xw4L89vMUiycfetUbqt36kPwmFd1rh6JpSfWy9gAPdbxjbAKC+SaGs8AEuotRnIIgANg65w/t2ZqOZNYuJFfY/N3EGNdiJlLiUtHDZ7DaeWmOjgvwkOD41rP2niqGmcRlZmDG6RPw27AGrbduxJrrV5GYlYW6SxZYVKDXjAzHmutXtfellOLU82eYcPwf/H78H5x6/gzEyP2hlgyCak6ehdqzIxzKak5mQZClKW6+iSR3dQBBXtg+s8M9vUGz1oPKLkJdJK/Acv6Er3SK7DGch3sXYzBdEo4Q78EYEzAdF/Zfwe0z96wS4xQ8xSc3W4aDq45ifq+lWDl6I57deWn0mJlvYjgLTKC7GMUtCDqw4ojVRK/Zwl8UhJVjNtp0iXvTkkFaES6XKXBs82ksHboGm2fuRsKLRDvPEsNcXkml+GLlUu1+85oa67ZnB8YfPWTxDPqyyxctMm4WBDFMpbj5JpIaCutUVfeGUQXh+CzhfyBJHaw0LuEMOlWplx5TkgKatRpEOh00eysoMXxkI8MxObf3EvzcxNoMdt7Kve1z9yKoip6TZ8y0mKtPLDJu5psYzgIT6C5GcQuCUuLTbCqCjbW/Vx9DiPdgq95D7RzV+73mhCzWHkUhy5Hh7oWHeHr7BauI68Q8SklG513beYu11YicjwZLIy2+D/12oWJx5sKCIIapFDffRLI32zFTrsdk56Gu/G5dUa42H9Cc/DPNqSoZVH4FVPXGjjPDKAqEEFw/fhvt3gnhPQHHGnWBOrzbk3M8blFgvonhLDCB7mIUtyAoMTbZ7mKczw6vO4HszBx0/Mj0vegrR2/AwyuPMa/nUog/6MPbpplXJ8ztuQTLhq3FjZN3QCmFSqnCwv4rOEfB9a4/zGJvnhm2QSqTocfeXQaWo1tWmNeInI/hh/6y3G+wZBA0aRZqz4pwKKs5iQVBlqa4+SaStd3KIti8Pe5UlQAivwmzsuiySyA5h0BSequrwvO1if8GJG0iSMZCUOVz9bNQJYAkdy5wT2+Q1H6ghNVFcSae3HyO4JoDbR5PHVl/0mK/gfkmhrPABLqLUdyCoFQrZtD93MTwFzqn04DlHQ0S+/A1OlXth6Ylg7TZbr1viqv01vmNB1YcgZ+o0DhE6mPTOn7UF+F9luHS39fQrnIPnf783cRoU6E70pOKx3wXNzLlciy9dBGBWzag+eb1WHDhHPr+n72zDm/jyvp/Y0jp3e1uu+377m93u20SQ6Bpm6aQMkRyoGFLccBxmJmZ47ATO3HSoIMNMzM3zNgw2jKzZMG9398fAlv2zIhGGim6n+c5z+7aQ/dO1ud85557zvYtvKvm7rAK8cbe5r337MCUk8ew6dYN5BYVuTQuFgQxHOVl801UvdWN4vxb585L/cqSVUU1e0wr6XamzGf1sx4fpSBZPXlE+qcgaTLQ/DkghRt5PiaEg2RES/FqGHbw4n4K4rstRPsqfdD3u5HYPm8vmr3X3qOdc379n1bo98MoTGkzB6smbMCZnRdg0BtcGhfzTQxfgQl0P+NlC4IAoF3lPh7/oitkin92tHo+bZEOR9aexIpx6/HbwOWC57b8b9cy4xvZcLKgU5QHKQT3u8sCFVg/fZunXgfDTgp1OtT/fbmVGHfHyrgzVrirgoIAACAASURBVDlxNg48uOf02FgQxHCUl803UZLt9Cq32yx7cKlnzAQtWAmanwiS1V343NyJ1udSDf8qusVsr9JT3S1PvhaGHTy89hgN/trasr+8zAKBp4wjhT66Yg8kP3B+KxbzTQxfgQl0P+NlC4IAYEPcDslFeUmb3j6R91n3LD1s8/z7Vx5ZnVMyZd0ZkwcpMb0d/zMxpCHp8kWvEeRcFjonDqp854o4iRoEjYpFyKQ4r7IKo1gQJDYvo28i6U2kF+VWYvgm/7Nm97Wx+v4lKC1evaTai+I8k3qHJ14FwwGG1Zvk0ZVyh+KZYCW6fDLA6fo6zDcxfAUm0P2MlzEImtRiluROo6StnrSJ91kfXn9i8/yDq45bndP47zEuPY8sUIEV49a7+zUwHKTlpnWSi3Ahq5gwE/PPn3VqbCwIYjjKy+abKNWBqD6XXJRbiWFDCv/zFiy1fT7JLD5ed1OcZ9Je9sTrYNiJQW/weAcaZ8zZ2jrMNzF8BSbQ/YyXLQgCgGbvid/Sw2kLiMTc3kssz5aZkoU1kzdjVuffsGnWTuRm5mFonYmC17h+wjrlL777Ipe+Ztd9LQppzzI8/VoYNojevMGrV9BD5sRh3NFDTo2NBUEMR3nZfBPV3ZVckJcRw5rDJZ7vJkjeVJCcMaCa3SCGTBBVDf7zVdVBqbb4fEpA0n6GS2n86Q1ZpxEvw2AweO3qeUk7s/OCU+NjvonhKzCB7md4Mgh6eO0xJreOR+sK3dHzq2HYs/SwpRWYmERX7CG5szCbPEhpWUG/fPg66r3REnJTOzRZoAKN347BrdN/clZClQUo0Da8d5mAZdPsnU4/T73XW+D8viuizznDdVZfu8IpjCvEz0BVN7RQc8Y23Lzu1NhEDYJGxiJkYpxXWYWRLAgSG0/6Jqo5AJIZDZL2k7GauPac+PcwvJBckJcR6LprxmfLn2f6WThISmWTWG4KUnS5+H9bWShIbqz1+KjeWM3drntz7EVP+5m1W/NSxjSZ5tUiXRagQOrTdKfGxnwTw1dgAt3P8FQQdOPUHdR9Laq4yIgpZSqu83zR77Vy/AaXUrLq/09L55wExz0jgpVYMnw1un460OjgShU5kQcp0aFqX7x4qEK9N8ret+V/uyIvq3jf773LDzkLpZR0VLUDIhET0hPjFTMtTrXOq1EYr5gJdYFG9PlmiEORXg/lhjUWUW62+r8vx9Y7tyQV5pUSZuLbpQuh0TvXe5YFQQxH8ZRvovkLTSIxrIRIDQVVi9dm0AzJUMCuCul8llrbifPCOO4ZDpImA8kZB5L6E/95uVNA1Ju5f5/Vx+rjMS1YzC28S94zJQQksytIemTxz1U1QfLmspVzL+b5vWQ0/Uc7Szxh/s+5vZdgdtcFkqbAywIVmBozx+mxMd/E8BWYQPczPBUE9fhiKOQ8f8QfXH0s2n2yVNkYr5jBeZ/Gb9u3d3tazByHnUSHqn0xvP6kYucVYEwljwnrZZfzmtdvGafwlgVEYkaHeTi46jjuXXqIOT0Xc7dnC4hE47+3wZgmU7F17h6o89UAgNzMPDy+9QzqAg0MegNObD6D3wYsx+pJm6B6nCbavDPEoUivx+prVxC9eQNablqHZVcuolBnFMVzz51ByJw4SQR6my0b8DzP9QCGBUEMe/GEb6Ikk2eFOMTUgsy5D1Kc99JeBklvwHOv7+0T25mdHRfo2aNAUn+0FsmpX4OkfGL7Y4HqS5DM1vzCO38RqHoHqCHFlN7Os1qeJgPJ7g+qOQRKjVlz1JAMqn8ASg2gJBe0cBVIbixo4RpQ4lwxSob7yEjOQtLINej3/SiMbjwVp7aeA6UUmsIijGo4RRJxXqd8FBL7LIW2yPn/nzLfxPAVmED3MzwRBOVnF/D+gZUHKfF77GZR7qPVaNE2rBfkwWVTsZYMX41hdYX3etcOiETUvztj3zLbldW5vuL2qjUM66ZvxbppW7FzwX6HUtE7f9zfruOavduOt8VJs3fb8c5NXlY+unw6ELXLRSKifHPIg5SQByqwb9kRUeae4RnSCwshX5nkUXGuWP+7y88tahA0IhYhE+K8yiqMYEGQ2HhEoKt3CQpUqnNuS0eZ++j+BEmpCuv92aEgKR+BFPwOksonbkscmz0YJHuQbVFdxqqBZPYEyV8Gmr8AVLMXJLOHndepZuc9wvg/dKSEl2nnZj03V0173UNN1wgFUX0BqrsjytwzPMONP+6gzqtRHhXo2xL3uPzczDcxfAUm0P0MTwRBhXlqfoEuYk/uAyuP8Qpv42q08Ep2h6p98exuMgpyCjjTze0R6bXLRWLngv0AgIG/jLXrPHmgAn2/GwmZQOq65R4CY+jxxRAAxiyCBQOXo21YL3Ss1g+rJmzE9HZzOfeQyYOUSH3CVtJ9hRd5uR5fPR/rZGG4krAgiOEoHhHomn02BLo4PblJ9kAnhHXJVfC+oFQNWnTMyWuEg6RUt4hefjFdylJ/gWNF33hW2vOMKchUd8PYvi3tJ5CMKJDCLabsgdL3CANJq8PS3n2IPUsOeVSc1y4XiXN7Lrn83Mw3MXwFJtD9DE+luA+qPY63yMiL+/ytXhxhTs/FiCjPkf5th7Du9HF/q2Dg6LpTkAcpbYp6Lmv89xgUqYvw6/+0svucaW3nuuys6r3WAtdO3ELDt6Kt0+UD+IW9PFCBtVO3Wsadm5GHrNQcUd4HQ3xupaV6VJxXiJ+BPzOcK75TEhYEMRzFMynu+SAp1bmFZtpPlnRsVyFpfPu87RC8uZOLn5dSkJzRzov0rG6ghueO3T+jpfMfFsyWrgApXGsS8KHF17ZxnrlPO6UE1KBiqe9ezLppWz0qzhX/7AiD3uDyczPfxPAVmED3Mzwl0B/feobGb8dYRLq5WNyqCRtFu8fyMescrjQqD1Ki4VvRuHf5YZnr3Tl/z+niJ472YhejQqosQOHwdSLKN8eiIStx/8oj9P1upOXnXT4diKvHbor2bhji8CQny6Ot2FptWgciwiqWmEFQxeGxCB0f51VWcTgLgsTGY0Xi1FtNYtG8wh0OklIVtOi0aPcgGc3sEqRlhW3DMqKUUgqSN8/xa6WEwJjuHu3gOVVcF+hOGi36A1S9AyT1B9PPwkwfGVSivRuGOLjSXcYZWzNZnK2RzDcxfAUm0P0MT7ayyUjOQtKoNRgsG4fJreNx+bA4+/vMvLifwluIjs8WDV3F2xP84sFrHnU4Utm+ZUfQ8K1oK3EvC1SgzqtRohbwY7gGIQTfJy3yeIr7kkvO9ZctCQuCGI7i0TZruhsgOSNAMtuA5E4C1T8S9/qF6xwTp6rPQQtXg1I15/VI3jTYnabuMXPiA4SgVTWmwJf5eThI2i+gtEjUd8Rwnse3nnEXr3WjyQIUosQnzDcxfAUm0P0MTwZBnmDfsiOICFZCFqiwrNLz/XHv/fVwzmsQQnD30gOsHL9ecvHMZfXfdK4NnFl4m/+7PEiJnl8OxcLBKzlX3iOClZjcOt7Db5DBBaEU0ZvXe1ycfxg/AzUWzMWJJ49hIM6n+7IgiOEoL5NvopSAZA8tFpiWPddcojYUND+R8zqEFIFoToBk9oZje8N90PJmg6T/yiv8qXqLh98ig4vstBw0eaetx+MgeaACg34Z67JIZ76J4Sswge5nvExBkJn0F5nYNGsnVoxdj4sHrqLzJwM4BWjUvzvj8c2nlvMopdg0e6dTBeI8aeZ2blbOyo7U9n7fj0LXGoNMIr8V5vRcjILcQsFidtEVe0j4Jhlmdt39UxJxXtK+W7rQ6f3oLAhiOMrL6Juo7gZofiJo/gKQopMgqo+5hXZmO1BSUHweKTBVcBd7lVpky4hx7sNB9nCQ1FrG/576HWjBchBiEDinMkjuBAnfJMPMzE7zJY+JhtWdaGkt6yjMNzF8BSbQ/QypgyB1vhq7Fh5AQo9FWDNlCzKSs0S/R352ATpVL9vGTB6kRNS/O0OnNfbQXD9ju6ATcKYAnTtMFqBAy/92tRLl9lSMH9tsOgBAr9NbFcSLbTWbM9tAZqoubyY7LQc3T/+J9OfcWwIAwKA3YOvcPehWczCiK/bArM6/4fm9ZNHfqb/RdedWyQV6pYSZqLXkN+gMjhfmYUEQw1Gk9k3UkAyaPw8kdxxo4UbedHNXINpb4C5SF2ZpTUYpNabeC4pcFyrEi2mqT42900sK6Qzbe95p4VpQSkGp1uKbKKUgqpo854SB5s8rflf6J6DaK4JF5Kghw7g1IE0Okl4PNH8uKzrnIpRS1Hu9heQxkTxIientubNObMF8E8NXYALdz5AyCHp+LxnK/9cJtQMiUad8c8gDFaj7WhTO7na9dUZJNIVFqCvgRI5vOgNtkQ6N/tZG0An0/3E06jgp0iPKu14EjlOsByoQ9Z/OyFJlo21YL34HFqhAQo9FnPNz+fB13vMOrDwGrUaLmR3nFfeXD4jE6MZTkZdVtnjRmKbTjBXkTVXkI4KVaPCX1nh4/Ymo79Tf+D5poeQC3WwHH9x3+PlZEMRwFCl9E9XsNYrLkv29U38ENYj7sZEWnRQU3ZRkg2ov2RbGmZ1cENafukGsm1b6M7uAGLJsC3TNQc75IXnTUXZF3ljQjxqSQfXPQDKUJX5XDSRvdpn2bNSQYSo0V/JDRpixCJ8bPrz4C4X5/C10PW0Rwc1RkFNg+6FLwXwTw1dgAt3PkDII6vv9qDKp2bKASDT4azTUBRrR7pPyKFVQuK6fsR2Pbz616QB6fDnUaeexduoWDK070W3Oqdm77ZDQY5HgMXcvPuCdozWTN0MWoDCaaZ96Yp+loJRiRod5ZarZy4OUGPjzWKtr8BXVkwcpMbLhZJ47M2xx9vkzyUW52SrEz8DyK45/QBM1CBoWi9BxcV5lFYexIEhspPJNlOQYhV6ZdPJwkMyO4t6rcI2wcNXdAclfYlsQZ7SGc6voYSCakyCqz9wg0k2W9itIZi9+IZ/6FSjVcs8PLQLJ7Fj8rCmhIClVQTV7QKkWJO1HznHTgsVW1zEW1eNKvQ8FLVgp6jv1J5JGrpFcmJe0Z3++cHgMzDcxfAUm0P0MqYKg1Kfpgn9oj67/Q7R7aTVa1HuDfwX90O8n0KvWcJt//Dt91F9wrzfX7+RBSqydusXyRT+2VbzbnJMsQIFuNQeXKdgiD1JiW+Jem/OkepyGzfG7sGHmdjy5/RyAMa1daMz3rzyynD+//zLeSq7yIGWZVQ2GfQw7uA+VEmZKLs7NdvrZU9sPXQoWBDEcRTKBXrhBcGWYkmzx7qU9J3CvyiBFp+wTz+kNBJ+Z8+eqz0CKzgIACNGCqL53n0hPCQHJ7FBWTKtqgmqvCM8RpaDay6AFi0AL14AS4zY4qtnNfy/VF6C0eCsOSZPzz01me9Hep78R9e/Okotys/36P62gKXS8sj/zTQxfgQl0P0OqIOjRDeEV612LuFPenEFbpOPfPx4Qif4/jipO3xawsc2mCR8TUPZne5cdtnoWSik2zdqJ5ibH1ujvbdDi/S6iVkE9s/MC/rxwH2unbsGWObsF94zb4sapO4L3OvT7CcuxCwev5BXodV6NYgLdSXrt3oGKXiDQK8TPQIPfVzj1HlkQxHAUyQR6wVJ+UZsSAmpwfJWOD1J0WUBk1jLu6banMFxGKwcFcxUQvfU4KMkFyR0DkvKR8ZjUb0BSv4Z4KfBVQfSZIJoDIPm/gaq3upReTvMTINRqjpLM4nlOr88v0LO6OP0M/k7Dv0ZLLszNtnTE706Ngfkmhq/ABLqfIVUQpNPq0PQf7Xj/2D6981y0e22O3+XyH39nenzKAxXo+/0ozmeilEJbpLMSOy3f7yrKc8Z3Wyja3KU9y+D88GC2G6fuWI69ffYu9zwEKxHbarZoz+RvrLh6GRW8YOW86brVSC8sdGoMYgZBlYbGImxsnFdZpaEsCBIbyQS67jq/yEz9HpQ6326wNCRD4brw5S2kJmRhoPnzucdPiVXKOdU/Fkmgh4Bq9os2d7Rwk8CcfAxKdcXH5ieCr7o8VW8S7Zn8jVGNppTZ/iaFze+/DAYnipcCzDcxfAcm0P0MKfeg71ywH7XLGVOzzX9oZQEKTGmT4NB1KKU4v+8KEnoswpyei3Hx4DUr4dvvh1GSOY5m79mfPrdq4kbb1www7tMXEuhzey+xuq5Wo4XqcZpT6V8AMKrhlDJp7hHBSnSq3r/Maurc3kuMotx0vCxQAeX/64TUJ2lO3dvfoZTiaU4Oai5IlFScd9y22aVxsCCI4ShS+iaS1b3UynWoScxtc+g6lKpBC9eD5IwAyZsJqn9Q4nfUuJItKGrdVZ09HCRniP3zkd7IjmtW4RXBxQK9VEYZyQM1vACleofm1XhugenjBEcRubxppY7NN40htISFgGS2txLyDPvR6/Q4v++K4Ad8T9jpXRddGgfzTQxfgQl0P0PqVjaHfj+BDtX6QhYQCcU/O2L1pE0w6O3/EmrQGzAucrpFnJpXumNbzQYhBPevPHLNgbhwrjxQgd5fD7d7LLuXHLTrulvm7Ebk/7bn/f3VYzeNc2MwIGnkGjT4S2vULheJuq+3wJyei1Gkdkyo52bmof+Po63u0fGjflA9Liu6KaU4veMCJihnYoh8PFZN3IicdOYYnGHv/bv4afliyVfOK8bPQKHOtSCWBUEMR5G0ijvVguTNBkn90ijm0huAavY5dg2DCiTtJ5NorGwS26GghRuMvy9cZYfgdYc4N6+g29+WimR1tX1N1fcguVPBnXYeCqL61JLSTg0ZIFk9i8V1ai3QwjUOzS9gynZI/db6Xtn9OYvOGT+WrDLuhc/qAqrezMS5ExgMBqwYt95m1xtPWIdqfV0eD/NNDF+BCXQ/Q2qBbsbZ/cm7F/OL2oOrjmNiizjBImcdq/XD6MZTy1aTFylt69gG+4vdLRu91q5U+osHriIjOQst/9vV8pzm55/VdYFlLuf3X1ZmtV0eqMAE5Uyn5vre5Yc4tPo4bpy6w/aTuxFKKRZcOCe5MDfbyEOup6WKHgSNifMqY0GQ+Pi6byJZvXhWwMNA9M9AVF8IC97cyaYPBFzXsGNfuoA4JynVQA0q+8eS3sSO64aCkgJT67gqJZ473PhBQL3LNJ96055wjurrpo8XjkCpHrToJKh6B6j+scPnM+xHq9FiZMPJkgtzs908fcf2Q9uA+SaGr8AEup/hLUGQs/T7YZRVinxJgT20zgS0+E8X3j/uEeWVyM3MQ25mHnrVGlb8u4BIRFfqgQg7CscJWZ9vR9oM7m6fvYsxTaah+b86odWH3e267rppWwEAac/SsXLCBgyrOxETlDNxats5y/1yM/MEe7Y/vyduP1+GOKQVFKDB7yskF+Ul7ZslC5Dh5N5zMywIYjiKL/smSjUC6d6hIHlxwmI3VWZMgddeNBVqM/+uGojqcxdXz0NB8uJtPD8FVW8HyYg0FYv7VmA8JQS27pbpua+A5I4DyWwLkjMaVHe7+NqaAwLj/oF9/PVSrh67icZ/j5FclJe0cZHTXf73wnwTw1dgAt3P8OUgCAA6fzyA9493r1rD0bXGIME/8HuTDluOkQcrLSvSY5pOE2UVPbHPUt5nv3jgKiKClcX7te1Mp187dQsGy8ZZ/nfvb0bg1pm7Vte+fuKW4DVmdJiHrXP3cKapM6Sj5aZ1XtVS7cP4GaiYMBPTT52w/fACsCCI4Si+7JuMvdT5hGw4SN4MG6vgVUE0J0BUNUqsQoeApHwKkt7UxRV0k5larHFR/AHBfB/b4pykhIAUrgdJkxU/c3Z/UENGqWvPhlD1dZI/z5h+TvLd/ZoYdpKXlY8Gf2ltd4ziSbty9IZLY2O+ieErMIHuZ/hyEAQACwYu50xhlwUqMDFqFmZ1+U3wj7ssQMG7z1wMgS4PUqIgtxCawiLsXLAfE5rPxPR2iTi/7zLaV+3LufovZHVeiyozXnmgAvVeb4HHN439qQkhWDJ8tfC1TMXmZAEKrBi7XuK3yACAR9lZkotxPvtq8XyXVipEDYKGxCJsdJxXWaUhLAgSG1/2TZRSkLS6/EI6f7Hp90KCl0vEhoGkuLqCbrK0usZnNaQYRXNWT5DcWJCiMwKCXODDgKoW98eItDqWPeGU5IBktLTxbKZ7qD4GLXLtwyBDHLbP2+twrOIpi23pWocY5psYvgIT6H6GLwdBAJD+PAPN3m3ncjq6O23jrB1oX7WvURQHKtzyrLIABUY3ngoAmNcvyeHzT++4IPGbZJx+9lRyIS5kcadPOj02FgQxHMXXfRPVHDaJTTtXn6Wwwj0gquqmZwyFuZCd49eycU7BGmPhvfRfHZiPUJCUaqAkS+pX6fcsGb4aEQJb5qQ0WYAClw9fd3pszDcxfAUm0P0MXw+CACD5gQqTW8ej/putIAtUeGUalqcs6t+dnTqv/4+jpX6Nfk9aYQEqell6e0kLmRPn9F50FgQxHOVl8E206CRIRhTParg/WSjPCrsdlr9Y6tfo9xxec1Ly2IZXoAcq0OML+1sGlob5JoavwAS6n/EyBEFm7l58ILmz8FWTBypYr3IvYOiBvV4t0vffv+fUuMQMgkIGxyJ8VJxXWchgFgSJzcvkm2j+bw6sHDOzstRvQSmR+hX6NdoiHVpX6C7YEUdqc7R9rBnmmxi+AhPofsbLFAQdXXdKcifh7cabXRAQiQUDl0v9Cv2evKIi1F+9XHIhzmcnnzrXxogFQQxHeZl8E8kZBu52acyMJpwiT4uc317DEIdbZ/5Es3fbSR7DcFlE+ebQ6/ROjYv5JoavwAS6n/EyBUHuXkEXErfevAfe/OyN/tZG8JhetYZL/Qr9noH796BCvPQr6BXK/O+ZqLlwHnQGg1PjYkEQw1FeJt8k7Qq6CBXf3WphNtLfw0Dz50r9Cv0aTWGRcQXdC+MceZASsa2cLxTHfBPDV2AC3c94qYIgStH76+FlxXIJYV3v9RZOO4K6r0VxVnyXBSrw9M5zXD9523iMFzgtbkfGX4VVHqS0FJljSMPzvNwywlhKgV4xYSYqJcxExYSZCJ87y+nVc0DkIGhQLMJHxnmVhQxiQZDYvFS+yZBeohgbjxBVfSy+CE/9EcSQDlKwyguEuLMfEUJBC1dL/Qr9mj1LD0sev5Q0S3vagEhEV+yBjGTnCwky38TwFZhA9zNepiAIALJSc9D/x9FWf8xHN54K1eNUPLn9HAsHrRAUqqVFq/nYKdHxgsfuWnwQa6ZsQYO/tPaQ2Bb/S/apbeekfn1+zb77dyUX5iUt4cwfGLBvN+LP/IHkvDyXxsaCIIajvGy+iWovgKR+X0J4VgXNTwTRPwfVPwZJb+DYqnNKKEhKFZCckcLHaq+D5IyyIYJFXhEXVbizSu5SE99toddUce/yyQDM778MU9vOwa6FB6Au0Lg0NuabGL4CE+h+xssWBJl5fOsZzu6+hOQHKqufLxqy0i5x27pCd0yNmYO5vZfgzvn7SH6gEjy+TUhPjzqpiGClfX3abVS0l5uusXDwSpf6XDNc50Lyc8lFudnC584GEfHfAwuCGI7yMvomSg2g2ougRcdBSY7V70h6ffsEa2ZrkOyBoPlzQA0poIW/2zjnUw+vhldxUIAL/a4qqOaQRG+LYWbF2PVeUSBOFhiJUY2miDo25psYvgIT6H7GyxgECXH9xC27HMGJzWeszkt+KCzQvc3M++UbvhUteFxin6V4fOuZRG+DURJKKX5evsQr0twbrVkp6tjEDIJCB8ai8og4r7LQgSwIEht/800kb7Ydq9wfgRpSSp0XL5JY9pSZVthVXwmM9yPQgpWgJFOit8EoSfJDlVcI9NrlIrF87HpRx8Z8E8NXYALdz/CFIOj5vWRMaZOApv9oh6h/d8bCwStRkFNg+X1GchYuHryGp3ee27wWpRQTo+L4HUBAJJaNXoslw1djdtcF2L/iKLQaLUY2mCy5Y3LE+nwzAhtmbsfD648hC+BeaVf+v04w6J0r+sUQnyuqFAw+sBeVE2dLLtA/jJ+B8y9s///JXlgQxHAUX/BNtOgESEZrEFUNkPR6oIVrrFqCUd1d0KJToIYM29ciOSCp3woI249BCpaD5I4HyZ0AWnQahBDjvSUX3Q5Ydm9QzW6QwvU8x4SDZA9252tjOIBBb8DxTWcwtM4E3ljCk9bwb9FOt1Tjgvkmhq/ABLqf4e1B0PN7yWj09zZWhd/kQUp0qt4feVn5mNZ2rlWqd7/vR9ksGLI3ib/giSxIgdoBpv3npuvWf6Ml6r/RUnLHZK/Jg5VYOGiFZbwLB680js3kXM3FVQ6vYa1rvAFKKcYfO4wP42egUkIcKpn6oIfOiZNMnFeMn4Hhh/aLNkYWBDEcxdt9E1XvtF4RNq8G504A1T8FSW9qLTpzxoJS4VZQJKungLj9ovha5nupvpZecDto5pZplGpB0pvAes96OIiqBqje+YKUDPEoyC1E98+HoHY5Yyszc6wl9Wr68Y2nRRsj800MX4EJdD/D24Og6e3m8rb26P/jqDL7sOVBSrR4vyv2rziKvKx8zmuunrRJcgfjTpMFKrBu2lbLeCml2Jt0GF0/G4Rm77bDoNrjcPHAVU+9QoYNjjx6KPlqOZf12LVdtDGKGgQNiEXl4XFeZaEDWBAkNt7smyg1gKR+wyNCQ0FSf0DZvuehIJntQTWHQamO87okI0pyAe12ga67VTyPJN+Y2p/6I0hqLZDsIaD6J556jQwbzOub5JWx0q5FB0UbI/NNDF+BCXQ/w5uDIABQ/F8HXhFqK92q7mtR2Jt0GAa9Aef2XMKeJYdw/cQtLBm2SnIHU3osYl4vIliJ9Oe2Uypt8eDqY8zttQRjmk7DirHrkf6C7Qd0B7337LSsmnuTJV2+KNoYWRDEcBRv9k1Uf981oZr6DajuFijJA1XvAFVvBtFeBclsB+n6pXN8aBD7emn1XC5GSikF1RwGyR5oTJcvXAdKXavkzeCm0d/aSB4fcZmYdXOYb2L4Ckyg+xnewCIjvgAAIABJREFUHAQBQKsPu3H+gXbkqy6fyPeEWJbC5EFKnNrqWsu0/SuOQhagMG4tMKX8N3wrGrfP3UPKo1TkZrjWdotRTNutGyUX46WtSuJs5BV56T4/FgT5Bd7sm6jhuYviNsy0d7yaFwhxD5rqK1D9U+fnnVKQ7MGm64XD8jEjvQGIIR1U/wSUFIr4pv0bb1w97/XVMFHHyHwTw1dgAt3P8OYgCACSRq3hdRJyscW0jZZktctFIurfndHp4wFoYKM6urMmVq9ReZASoxtPxb5lR6DTcqdT8pGfXYB6r7cQnqOASAyrOxGpT9Lc9Ob9h3nnz6Cil62gH3v8UNQxihoE9Y9F5WFxXmWh/VkQJDbe7pvK7p82mxSV00NB0iKNqeJuEf1ireqHgqi+AMkZClp0xvYkl4JqDttxj2oguRNBqdYNb92/6P/jaK8S6fXeaInCPHE/wDDfxPAVmED3M7w9CCrMU6N7zcEW0WkuFjez03xMjZkDeaBnnUebSj1Q59Uojzstczq/I1VUzcf2/W4ktBr7g5WDq47b/RGg5X+7QlMo3kqrP5KtUaPW4t8kF+UlbdThAy6nopaEBUEMR/F230R1t02r4GEmM63oFm4BSf0eZfegu9ky2hSLYK8V6GYzzU3ebIfmnGQPsnNew0CyB7npzfsP147f8qqsQnmwEofXnBB1jMw3MXwFJtD9DG8Ngh5ef4KV4zdg2ei1uH7yNvYvP4rYVrMxo8M8nN93BZRSqAs0GNtsusedhL0Oq86rzRH1n852i2pZoIL32hHBzTGywWS0DevllLjfGLfD5pxTSnFyy1l0/Ki/Q9ffs/SwB/5FvNy8yMuVXJSXtp+XL0FynjhbGVgQxHAUb/RNlBLQomMgeTNBCxaB6G6B5s8Hye4DkjsZVH/PeJz+AUhaHc8KdIesFkhKdR7h7YTAzx4EovrEqWehuj/tmHcNaEESiOpzB64dCmoQr1Wkv7I5YZfkwry0TW4dD71OuCOCvTDfxPAVmED3M7wtCKKUYtEQY1uwkivm09rOBSGE85wX91OwetImyZ2GkJi3WnHnSKWXBSoQEdwcg34Zy7s6f/XYTYxXznTqObp/PsTm3CeNXGP1zPZYRPnmSOixSOx/Bn6JfOVSyUV5SasQPwON164SZWxiBkFh/WJRZWicV1lYPxYEiY3X+SZSAJLR3CT+KsO8ak7Vm7iPpxRUewUkq48XCHKeVWa7xHk4iOp7EFVN7uuoPgEhBSCqz5x4hnCbq+iUFoFkKJ36cEA14lX79ldy0nO9ahW9drlIyAIisWLselHGx3wTw1dgAt3P8LYg6Myui7x/lG2t1J7YfAYt3u/i0h9+qfZb1X0tCnN6LcHTP1+gyTttLc9hXn1v+o+2WDd9KyL/t71T1+/4UT/BuUt+oLJrDz7XfK2auFHMfwJ+y447tyUX5Vx2K931OgMsCGI4irf5JpI7kUfUhoHq+atKU0qMrcRU1V0U1DV47u9mU30Oot4GqtltEsnmFHOTYE6rC1Kw3snrVwbJmyY477RwrdPPTnWsnagYDPxlrOSivLQ1/Uc7UbZhMd/E8BWYQPczvC0IGqeYwSmSZQEK9P56eJnjDXoDjq7/A5Oj4zGlTQKObTiNe5cfoPHbMZA5IThrl4tEv+9HSeZ0EnosQvrzDMzvvwz132zJKYgdvaYsUIH4bgsF531Lwm6H9rdbnidYidSn6e765+BXbLh5XXIxzmWHHz1weWwsCGI4ijf5JkopiOpjHiEYBpqfWPYckgtasAQkuzdI7lgQ7TkQ9U7nhXJqLZDU2p4X6ClhICmhoJp9xoyAzM7ifijQHBCce5LZCU6l3afVFbWOhj8z8GfvE+i1y0XCoDe4PDbmmxi+AhPofoY3BUEAMOCnMbx/jGNCe1odq9PqMCRigkW4msXriAaTcWrrWUQEN7ekyDtrJUWrPEgpfuX40hYQieSHKmyOd37fF186WrfPBuHB1cec875ljnMCvfMnAzzxz8IvGHZwn+RinCvN/bkIfxtEDYL6xqLKkDivsrC+LAgSG2/yTZQahFeBcydZH69/BpL6tUlYmgvIhRj3UedOMZ3nahG5kqLV3SvroSBpvxg/VGTGuHAdrjGHgWT1BiXc79n4QcAJgZ433RP/NPyCyP+1v1Wtp6x0POgszDcxfAUm0P0MbwqCAGBu7yWcAjMiWImZHedZHbt93l7etOw9Sw7hye3nSOyzFMPrx2JQ7XFQ/LOjg+LcuEIsD1ZCFqjAsHqTMPDnsW4X6XuWHkbXzwY5dW6/H0Zh4eCVnL3f5UFKNH47BtlpOWXmXfU4jVOgywMVaPpuO17xLgsQ5ys2Axhx+AAqeIEoL2m9dtsuLmgPLAhiOIo3+SZKqanoG7dQpJrdVseTrC48YjQURPcUtOgkSPZAkMwOIBlRICkfOShAw0oUZfsIJHs0PNJTXf/Y+XNzY0Gy+8FYnI5jPBnR3HNfuIF/DlJq8N8vs7Un/mn4BS3+49rWQXfYvmVHRBkb800MX4EJdD/DW4KgjOQsDJaN4/xDLA9Sov4bLfH0jnVF1r7fjeRMY5cFKjCo9rgy9zBXfo+u2MN+RxAQiZ2/7beI0CNrT7rd8Rzb8AdiHKjWHlFeiZYfdMWqCRst7dT6fjeS80OCLFCBNVO2cL6DFePWW+a7djnjx4n6b7TE9PaJvJkIEcFKGAxMoIvBRi9Lcf9lxRJo9DpRxsaCIIajeItvotpzIGm/8K8Ip9cHpcX/P6FULbDiGwZasLjsPagBRHfXcdGre2RJ4ybZQ+HelfRQEIPKwXOqgqQ3AVXvNI6T5Bl/xnM81d3kmBstSEbL4mcwi/O0CJC0hvzPmtnOTf8i/I8h8vGSC/KSNqPDPNsPbSfMNzF8BSbQ/QxvCIIIIehQrR/v/uqBP4/F3Ytl98EKrTL3Mu1Xp5QiIzkL+dkFlvO2z9trtyOQBSgwt9cSy7kGgwGdqjvWhswRq/dGS6gLNJjVdYF9zxeowKSWs8rMTcO3ojmPlwcpEduKv2ru2d2XMLrxVPT4Ygjm9FyM5/eScf/KI95rjVfOcOXVM0rw2/mzkoty8wr+z8sWI1NdKNrYRA2C+sSiyuA4r7KwPiwIEhtv8E1U/wTGlWku4VsZJHsoKMmyPofkCQjWcND8ucbjqBbUkAJKiyznkqyucCj1XVPcE5oa0uDWVfSMGOMzpv5g9zm00LrCPdVdFz6etyK+FrRwFUhmK5AMJWj+QlCSB1qwGLxZDYXiVPlmAH2+HSm5KJcHGRccpkQn8Hb0cQbmmxi+AhPofoY3BEHn9l7m/aPc4K+toS3iXsVbOuJ37oJygQqsHL8Bp7aeQ5uQnsafB0RieP1JSHmUCkopkkatQZ1Xo6zEppBIb/JOW7Sr3Adrpmxxa7qXPEiJtOcZyM8psHo+IeNqc9a+al/O9H95kBILB690+B2VbH1nnmPlPzsi5VGqw9dicDPr9CnJU9x/Xr4EG2/dQJFenB6zZlgQxHAUb/BNJDeWRzCHgWR24j8vvRGPqA8BKboImj8XRPWp6WcfgeROBKVFRnGf1cmxFWrVF8Y0+YKV7hPnKSEgqT8ZU/01h+wX6KUKwFFDKq+gJikhoEWnHHo/lKpBMiJhWTU3XzszBpRqnXrnjLL0+HKo5AJ9WL1JuHTomuiF/5hvYvgKTKD7Gd4QBG2YuV1wXzefCMxKzUHUvztbiWt5kBKtPuiG4xtPGwVqCZEqD1Ii6t+dUZinBgDkZubh3J5LuPnHHWyds8cuJyELUDjVjswRG9lgMgBgzeTNlq/GQnb77N0yc7N9/r6yxwYY5+DZny8cfkeUUpzfdwWxrWZjWN2JWDVxI3LS2R98MTn2+JFXrKBPPXkcBVpxg1sWBDEcxRt8E8lsKyBYf+A9jxb9YRL2JcV9KEhWL5DcqdyCP6t38fn6x6BFR0D1D0Cy7CmS5qH2a+qdxpTzzI52HF+NUyRzZwmEm4rQOb4ySmkRaOE6YzG5rG6g6s1WWw4YrjO93VzJBXqjv7fB7sUHmUBnvslvYQLdz/CGIOjYhj94/yjXeTUK6nw177npLzKR0GMRFP/XEcp/dsTcXkuQpco27cHmWBUPiMS2xL1lrkMpRUKPRZI7odrlIvHrX1pjx2/77Tq2yycDOeeFEILEPkutPibUf7MVjq7/Q7T3xhCX9TeuSS7QP4yfgYoJM9Fk3WrovTSNMLx3LKoOivMqC+/NgiCx8QbfRHJGcIhJkyDOaCV4LtVeNopr1ecgaXJjyzVDJgT3YOsflb0OKQBJa+AZAW7LMqJBsrrZ8cEgBCRvJve8kCyQDKX1sWk/gepdb+fIcA+jG0+VPC4y27LRa0UdG/NNDF+BCXQJePToEdq3b48PPvgAr732GipUqIDRo0dDa2MVKyYmBq+88oqVffnllw7d2xuCIG2RDsp/diyTZi4PUmJ21wVOXbPe6y04/7hHBCsxvV3ZnrUAcGH/FbscBKfwF9Hqvd4CTd6Osf0cwUrcu/RQcB5SHqViz9LDOLL2pCVzgAt1gYZVY5eYySePIWROnOQC3Wx77pXNzHAWFgT5Jv7um4x7pvkqt+9z/Hrai4Kilqq5uyYYW7O52pZNBEu350NBKEjqd1Z768vMA6Wg2sughetAi06AUm7fQykBJflOrawzxKNDtX6SC3Oz1SnfXNTsPeabGL4CE+gSsGfPHrRt2xb79u3DgwcPsG3bNrz33nsYMEC4x3RMTAzq1KmDlJQUi2VmZjp0b28IggDgwdXHaPnfrlZ/iEc1nAJNIb+TF6LF+105/7jLg5VYPHQV5zmFeWrUf6OlTQcREdwcQ+Tj0ehvbax+3vWzQRj4y1g0e6+9Sw6o40e2nWFMaC9c2H/FlSkHAJzYfAYdqva1fBiY1fk3q4J6DM+x6toVyfegmy1kThxGHzko2thYEOSbMN8EUPVmWLdBqwyaP9+5a+mfCAv0otPc5xWdtF9EZ5Zu8RYOktEaJL0ZSMrH9q1+8167I2ym02fGgBqec47D7nmietD8RGP2QUoISGot0IIlTKhLxOjGUwXr9HjaTm07J9rYmG9i+ApMoHsJ06ZNw4cffih4TExMDBo1auTSfbwlCAKMFdIv7L+C/SuO4tGNpy5da/WkTZy9u2WBijLt2kqyOX6XXQ4iulJxq7bunw+2qjI/t9cSRAQ3d8rxyAIUOL7ptOAx2+btFWUf1onNZyz3tHzACFKi++dDWOs0CXiSneU1Ar1SwkxMOXlMtLGJGgT1ikXVgXFeZeG9/CcI8kffREk+qGYPqHoHqCHDpWsZ+55z7cH+UXAl2d5930T1hem/h4Fk9gYxZBffO+0n58W56nOQgiRhga9/7NLcWJ4zZwz3ffLiRLk+wzHWTt0iuSgvaZcOXRNtbMw3MXwFJtC9hBEjRuCzzz4TPCYmJgZvvfUW3n33XYSEhKBjx45ITXWsqrY3BUFiotfpMV4xwyg6AxWQBSgQUb459i07YvPcYfUmCRaCkwUqIAu0FrWN345BRrKx3c6GmdudKiRX/82WOLf3MgCgW83BZb5YywIUaPS3NihSO5dVUJoOVftyfsSoXS4Sp3dcEOUeDPvQE4Ifly2WXJiXtFtp4lXoZ0HQywPzTa5BDS9A0mTFwty8Qqy7I3we1YKoajoorMNAMloW90rPjHFOnKdFgBqegxoyQFIqcxwTDpLVRaT5SRFYpa8KSl6ufw/ezvN7yU4vOLjDFP/XQdTteMw3MXwFJtC9gPv37+Ovf/0rFi0q2z6rJGvXrsXOnTtx/fp1bN++HR9//DGqVq2KoiJ+AVdUVITc3FyLPXv27KX+P++fF+5j3bSt2D5vL7JSc+w6Z3q7REQEc6dzmcV+mZ8HKS3FS07vuMArfIWs7mstcGqrMXXr0Y2naPqPdlaV6OVBSpzYclaUeVEXaHifIyK4ORYPWy3KfRj2Mf+c9D3QS9rcc9ypts7CgqCXA+abxIFSPajmEGj+AlD1TsH92iUhqV8JCGn+PepUewGUGkByJzsp0GtbPiBQ9VaTgC7R1iz1SxC9a2ntlrnR7BN8Flp0RpT7MGxDKcWAn8ZILsrNVufVKFw+fF3UMTLfxPAVmEAXkTFjxpQplFPazp8/b3XOixcvUKlSJXTo0MHh+yUnJyM4OBibNm1y+JnY/3mLObT6OLc4D1IKrowPrzcJOxfYV31dyDbN2gmDwYARv8aW+V2z99rj3hXhwnBc3Dl3D3N7LcGUNgnYtfAArhy9YZUFUNJkgQqsn7HdDTPLKAmlFKefPUXP3TskF+RmC5kTh2EH9yGtUNw6BGIGQZV7xqLagDivsso9fSsIYr7JNyHZgwWFOLeFGlPTs3o5n96eEgqSUg1Ue8XYy1z1Tdlj0qNASb5D4zF+qNgLkjPUWDFfcwQkL0FYoNvINGC4jlajxf4VR9Hrq2GSi3KzNX23LTbO2gGtxntbgDLfxHAnTKCLSHp6Om7fvi1oGo3GcvyLFy8QGhqK6OhoECdbHFWqVAlTpkzh/b0/rVI4innOdVodenwxxKo3uzxIibqvcVeGN1tsq9mo+1qUy46o3ustsC/pMO/vI4KVuH7ilt3j+j12s+m85lZp8zKejw0RwUqkv7Au6JSbmYfVkzZhwE9jMKrhFBxZe9Lpf6MMgFCK/nt3SS7IS1vFhJmomDATlRNn48wz1+pAlIQFQdwkJibigw8+wKuvvooaNWrg+PHjvMdyVUZ/5ZVXUKVKFcsxSUlJnMeU9DMA802+BKXUUhyN6h+BqGqUEulhtlPfOXuv8wlxoXT51iDZw/iPS/0OlNhXDNDYT92cch8ukNZeIkMg/dcy9Veo/h5I7hiQjJYg2UNAta4XT/VnslJz0K5yH8kFeWmTm7Ia24b1QpYq2/ZA7IT5prJI5ZcYwjCBLhHPnz9HSEgIoqKinC7QlZGRgVdffRXLly+3+xxf3OeX/ECFddO2YtWEjbh91rVWUJRSbJq9Ey3e74La5SLR8oOu2DJnNwpyC7Fk+Gq0+E8XNH47BhOaz8Ssrgt4V51rl4vEkhGrbTqZ9tX62rWfq2ct4S/XsoBIdK0xEMc2CPc1f3TjqWNOMEiBw2tOWs43GAw4sPKYsWK9OdXe1GZuSnSCKMXq/JGtd25JLsZtCfWaC+dBJ1KxQBYElWXt2rUIDg7GokWLcOvWLfTp0wdvvvkmnjx5wnl8Tk6OVVX0Z8+e4e2338aYMWMsxyQlJeGvf/2r1XEpKSlOzznAfJO9GFuHnQfNn2OsOG5Idu16JBckdyyIylR5PUMBWvQHqP4hSPZAoyhP/cbYgi2tobCwtrnyXgUkrZ6dIp6/j7tFSGd1A9UJf0SmBctsfBAoLf6/BtXfKzE/BaaU/dAS4j4cJCUUVM2fqcEQZmrMHK+q2F42RlFicut40cbLfJM1vuKX/BEm0CXAnDr4888/4/nz57z/gMPCwrB582YAQH5+PgYMGIA//vgDjx49wpEjR1CrVi3861//Ql5ent339qYgSJ2vxsLBK9Hsvfao+1oUBtUehxunrNPZ1k/fhtoBxr3gZicyqcUsh4qGpD5Nx7y+SehQrR+a/6sTpxOY3X0B/rxwH5NazEK78N4YEjEBMzrO401xlwcpsX/FUdGcUER5O4qymJ5l+3z+frxJo9Y45GxPbS9uX5KbmYdunw0WPP7igauOv2gG2mzZgIpeIMRt2fEnj0QZr6hBUI9YVOsf51VWuYfjAv2LL75A165drX4WHh6OoUOH2nX+li1bUK5cOTx+XFw5OykpCW+99Zbdz2AL5puMUP1DkKw+ICnVQVSfgGQPAzWoin9PtSBZnUutBoeBFq5x7D7aS8ZU9LQIkJRPuQWs+gCoehdIRrTxuOzBIOnN+cVuelOQnCE2BLojqe72HBcOklJNUKST9MYO3LcKKFWXmKcrIKrPBI6v7nC6PcNYXLeOPbGHxBZRvjm0RTpRxsx8kzW+4Jf8FSbQJYAv/eOVV6xfxyuvvIKkpCQAgFqthlwux7vvvovg4GC8//77iImJwdOnjqWleksQZDAY0PubEVZiUh6kRERwc0s6983Tf/IK1S0Ju+26z4v7KWjyTlu7RKssINJSLM58vJxjBV0WqMD09onISc+VxLk1+lsb3n1Z8/svs0/sm+z6yduWc6e0SRCcp4jg5pjddYHrL98PabJutaTCu+bCRNRcmGjzuF13/xRlvP4SBD179swqTZuvKJpWq0VgYKBF1Jrp3bs3vv/+e7vm49dff4VMJrP6WVJSEgIDA/H+++/jX//6F+rXr49Lly45N+FgvgkAqP4ZR1p5OEjq96DEmGpL8+fwiNdQUJ19WV5Us9t0DXuFdMlVY4ECceqdxn3eLotzR824ks4HSZM7cK1qxfNEdSCpX9v8WEA1/B+uGdxoCoskFd7yICVaftAN9d9safPYgtxCUcbMfFMxvuKX/BUm0P0MbwmCTm09x/0HO1CBft+PAgDM6vwbd3X1gEh0rNbPrvtMajFLME3dpgMJVBj3QgVEWq7ToVpf5GYaV4bWz9huJegdMidas5ntzrl7nOM9u/uS3ddo8k5b6LTGr9KawiKbqfgRwc0R12m+CG/f/5jxxwlUTJgpXQq76T+XXrqAynNn8aa5q/LFWYXylyCotJVM8yvJixcv8Morr+DUqVNWP580aRJCQ0NtzkVycjICAwOxbt06q5+fPn0aK1euxJUrV3D8+HE0a9YMr7/+Ou7edW0rkBR4i28iuWN4BHAYaL7x7x9J/Y5fpOZNs3kPSnUl+pc7Y2HW/c/N4jV7hGkPuwEks53lo4HHRLrqE4F5nWTnx4hwkKzexXNVdNSue1PNHtdfvh/StcYgl2IkV00WqEDDt6Kxff4+7t8HKNCpen/Rxst8UzHML3k3TKD7Gd4SBCX2Wcq70isLiAQhBGObTectbBb5v/ZVFhajiFtpIS0PUmJj3A7LPc7uvoTh9Sfh1/9p5TGn9uDqY9y79BBPbj/HpUPXENtqNgb+MhaLhqxEt5rCaepmG1pnIvKyjIIsS5Vt1zl/bD/PN9UMAdIKClBz4TxUklCkm63J2lX4MH4GKpT6+cRjR0Qbr6hBUPdYVOsX51VWubtjK+jmQOiPP6xrSEycOBFhYWE25yI2NhbvvPMOtFrhisaEEHz88cfo1auX/RPtJXiLbyJptfmFYGaM8ZiUj/jFZY7t1FCqvewmgfwZqPaC8R5UC1qwEiQj0nMCPbUWKMkF1V0D0T8HLdwIktkJJLM9SN5cENWndlwnFCQvrrhQnnqLHedUBSX2tVVlWHN+3xXIAhWc2YKetPpvtESbkJ7WxXpNbW7P7Loo2niZbyqG+SXvhgl0P8NbgqCkkfx7peu/2QqUUqyZsoXzy648SIkxTW2vUgBwqj+5vVa6svqM9vz91MUyeZASUf/pjKb/aFvq5wrL7+1NcZcHKdGpen9oNVoQQhD1ny6Cxw+rO9HpolEM4FluDvrs3YnwubMRPncWOm/fIolArxA/A58tTMRPyxajYsJMfLt0IZIuXwQRsQCgvwRB9o7PlVRCSikqVaqEvn372nWvjh07ok6dOnYd6014i28y7pXmWnUOA8nqYTwmozX4qpDbsw+daI67SSSHgahqgBLrdGBjiri7BXoYSHoTkJQq3KLbJKTtvl7uRAAA1T+weSwtWCr+PwQ/4tKha+j73UhEBCvR9B/t0Pvr4ZIJ9Y7V+qHpP9pBHqREr6+H48J+cav0M99UDPNL3g0T6H6GtwRBj29yVxuXBykt+5xzM/Kg+L8O1q3CAhWICG6OO+fv81770Y2nGNt0Guq/YXtfk7MWEazE1Jg5Vvc9v/eyaNcf1WgK9iYdRp1Xo0x785WQBSrcskq/f/lRAMCepdyt3n79SytsTthlSYdnuMaDrEzs/PMOzj1/htA5cZKJ9IUXz9l+WCdhQVBZvvjiC3TrZr1Ht3LlyjaL8Rw5cgSvvPIKrl+/bvMelFLUrFkT7dq1s/u5vAVv8U20YDmPQA8B1ew1HlN0Blap5SkhMO5T/xGUFPBfW3PAJGIru1UsU/U2q/uS3FjeMTls+XNM1zON2Zy2rvpK5HGEWirjk6ze4PwgklYbtOio+/4x+BGEEFw/cQtH153CiS1nJBPotcsZMwTdBfNN1jC/5L0wge5neEsQBADrpm0zifLiCu0dq/VDbmYedFodzuy8gA0ztmPAz2MsK+ndPx+CK0dv8F7z8uHrqPNqlFtXzs3WreZgDJaNQ73XWwgWOYmu0N2h6zZ7rz0KcgqgLdJh4eAVaPJOW9R9rQU6Ve+PLp8MELUlSkSwElPbFn9o2LfsCFp+0A21y0Wi7mtRmNlpvmjFWfwdtU6Hrju3Wgnlj+YlSJbqHr1lg9vGKmYQVKV7LD7qF+dVVsUJgW5uZ7NkyRLcunULffv2xZtvvmmpfjt06FBER0eXOa9169b48ssvOa85duxY7N27Fw8ePMDly5fRrl07BAUF4ezZs85NuoR4i2+iVAuS0a6EADWJ6Zzhxv3dJAtUvQMkbzpIWp3i1eOsnqAG/lZCJG+2W0W51Up2Vi+QtLowrlhX5zmuCojqc8eundnZOAeGFJCs7jCm+lc37XcX/6MDVW8vfid5U00t6EJAUr8ytrZjbT9F4dmfL9A2vLdVbFD39RaSiHNZoAIbZm5321iZb7KG+SXvhQl0P8NbgqCzuy9ZhGDtcpFo+FY0Fg9bDW2RDtdP3kaz99pb/dGe1GIWctKF95gdWXvSpcJrjjqR2gH2FYeb02uJ/dcOiMT9K49ACMEQ+XirFH93pM9HBDfHnJ6LreaRUorczDzR2powjAw7uM8jheIqxtu+R8WEmeiyY6vbxsqCIG4SExPx3//+F+XLl0eNGjVw7Ngxy+9iYmLwww8/WB2fk5OD119/HQsXLuS8Xt++ffH++++jfPnyePfddyGXy8vsJ/QVvME3UUrzDVYjAAAgAElEQVRB8+cVC8GUEGNBOPVu4+8KlpUSolVB8peAUo3gNUn2KA+Jc0fsI5CMTvYfn/oVCDGAGlQgqbVgXfCNO93fZYGuOVRqLnXGDySUbbUSC4PegFYfdnN7L3R5sNLObjoKwVayrsJ8U1mYX/JOmED3M7whCLp78YExZbvEKrcsUIE6r0bh1LZznNXEZQEKJI3k39uXlZrjUMuzHl8MQfJDlWPiucSzmgW6vaLb3muvHL8eAHBuj/3V2LnuZ17RlwXYLv5y87Q4rbUY/OQVFSHEA+nsm27dQLP1v+PD+Bk2C9Lt/POO28bLgiCGo3iDb6IFSzmEYjhImgwkfwG/kNTybxdxuOVZ7iQQ3V2QjJZwPC3dEaHsyLGhIFpjKqv91dh5rpNSFdYt48w/L3Wc6jNQyl10kSEeZ3ZecKswN8dMV4/dRLN329lc2IgIbo4sVbbbxst8E8NXYALdz/CGIGhydDznarA8yCjS+f5wN/57DAghnNfcOnePYFq7PEiJTh/3x7x+Sbh76YHVuRvjdthsMVbS2oT0dI8TC1BgWJ2J0BbpML9fkkP9zIudmxJ1Xo3Chf1XsHvxQYxuPBXjIqdjz9JD6P75EMsx5vEuHfG7J1653/MgK9Mjaetrrl+FnhDsu38XY48ewuQTR9FozUqLYK+UYPxI0HvPTlGLwpVG1CCoWyw+6hvnVValGwuCxEZq30SpAST1SydEZzhIVh/e65KszraFdmY7kLwEEENGiefRgmT1dOxZ0ps7vVpt0/LnG7MBHOpnXuqDQNqPILq7oPkJIJkdQXKGgRRuBlHVRHFP+DCQlCqgRcd455QhHlvm7PbIlkBKKQpyCrAtcS/iuy/CwsEr0fTddsZFBFOdndoBkdi9+KBbx8t8E8NXYALdz5A6CAKADtX6Of1HXp2vBiEEuxcfRI8vh6LVB90Q22o25vRcbDN96uKBq7zP9PDGEywcvMKuZ/jz/H2nxLO9Fvlee/T/YbTdx9d5LQrtKvdBm0o9MTk6Hg+uPsbFg9cwXjkDvb8ejsQ+S/Hifgr0Oj2OrD2JWZ1/w/x+Sby91Bnio9bpUDlxttsF+vHHj8rcW08Idt29gwH7dmPwgb04/OiB2/dusiCI4ShS+yZKMp0Xr+lNTdfINe41T5MbV93zpoOkN7NxfnVQks/7XER9ECSzi+1nUH0GojnlPoGeEgKSoXBw3/pnprmoA5I3A8SgAi1cB5LZFiSjJWjBIlCSD0qyjdkLOcNA8+cK7uVniMvFg9fcLs5rB0Ry+py8rHxsmLkdk1rOwvx+SXh4/Ynbx8t8E8NXYALdz5A6CAKA4fUncYtpG6ngUf/pAkopZnaaj9rlIi1ffUuuCPNZYp+lnA5Cr9NjVpff7N5/Vfe1FmhfpQ9iQnt5bL+7kMkCFFg60noVfO3UrahdrjiNTB6sRP03WuLWmbueesUMDiafOFqm97i4e89n4GLyC6mHCYAFQQzHkdo3UaoFf0E1IQsFyRkBSvJNReNKpo4b257xp5OHgmq499tSQwpIhgMr4qqaIOmNrPfPS21FF0rMr84ozM1zZv7PtAjWw1xCCCHoVL2/W/ugt3i/CzJTsqQeKgDmmxi+AxPofobUQRBgLBDHKzgFnMS2xL04u/si7xfahn+N5kzViu++iPdZFgxc7lR6l0N70N1sXT4daBlP2rMM7t7xgQp0rTHIE6+XUQIDIcjXakEpxe30NIQkuHcfeoX4GRhz5CDUOmkL/IkZBFXtGovqfeK8yqp2ZUGQ2HiDbzLury4tpku3UyttYSC6OyA543iOC4Wx2jnHPmvNYc7noJSApNeHc3u9RWqn5rKFg+TNLB6Tegv//OXFeeoVM0xoi3QoUhv3+G+avdPtcUq9N1pi/8pjklfeZ76J4Sswge5neEMQBADrpm21WvWOCG6OtuG9eP+4D68/CYl9lzolpBv9rQ1n0RFNYZFLvdKFPibY46wiS1Wqd9a61RxsGdP2+fsEPxykP88oMw8M8dHodZh0/AiqzovHh/Ez8N3ShWi0ZpXNwm1iWe3lS5ClVks2fhYEMRzFG3wTpRpT+7CSK9Ofgqi+4ReiBYtBMqJsiNWa3MI0owWnYKFFp6UT1qk/Q5yWaeEgebMtYzLOK08mQZrMk6/Zr0l+oMLoxlMtK+Z9vhmBhm+18diCwrS2cyUV6cw3MXwFJtD9DG8IgsxkpebgwMpjmNNrsUmkW6eZy0xCc8Svsdgyd499opljNVwWqMCqiRvL3D/5gUoUh+OMUI8o3xx9vh3hclqZLFCBtVOL22VtS9xrmTcuS32a7slX7Ld02LbZqqWaO1Pb+dLdxxxxb7EdIVgQxHAUb/JNVPcnaOEGkMz2PKvSpv+dvxQkqytsr3Tzr2pTXdnaKLTwd3EEsjPtz9Jql+jv7ppR3U3LmIzzxDMPab948vX6LTnpuVD8XwerLX2uLDTwmo3swlPb+LseuBvmmxi+AhPofoY3BUGAMc2qydsxnH/E67wahXN7L4NSivZV+gr+0ZcHKXl/LwtUYGKUMYXOYDBYvt6qCzSo93oLl51R3+9Giu/ghER5gMIowgMi0e2zwVAXFPfgTXmUyjkPskAFOlTrJ3l6mT9wLVXlUTHOZx//NkeyORA1COoSi+q947zKqnZhQZDYeJtvotor/GI7TQ6qf2zsCe5iSjkt3GDssV6itzctOum6QFZ9DpL6gxPnOjse83mmjxW5k6zns3A9/4eEvKmefr1+ye+xm90jyB0weZASsa1m235YN8F8E8NXYALdz/C2IOjK0RuCf8zP77sCAGjwl9aCX2vrv9lK8DqR/9ve8iGg2XvtsWrCRhj0BiT2WVrGYcmDlMb97HY6smF1J+LRjac4vvE0FP/s4DbH1vPLodiWuBdDIiZgsGwcts7dA01h2T6xSSPXWMZRu1xx67UrR254+vX6JcuuXPT4ijmXhc+dJdkcsCCI4Sje5ptIXhz4V8ZDQakeVHfNDuFaQ/j3qd/BuEc9BCS9Pqhmr3EPepqc4/5hICmf2i+a85eCas+CFG51XfALWe5EY/X6zFYgWT1ANYfKfAymVAuSoSz1ASAMJPVHUAPbeuUJRvwaK6k4Ny4wRGJME+k+yDDfxPAVmED3M7wtCLJXoPf+ejivYB70y1j0/W6Eg05CgWlt50JbpMOUNglWq85N3mmLGe3noeFb0XYXghssH4+OH9luH+dIv/Xa5Ywt1/p8MwJH15+ye04ppTix+QyGyMejfdW+mNZ2Lh5ee+yuV8goxdY7t+xKQTfvR//ktzmii/NKCTPRYdtmyeaABUEMR/E232SXQCc5ENyvnTsTjqWZG8UrVe8A1T8DSW9YSsz/ApI9zIHrVQfJ7CS8h95ZS/3emLau+9PuOaVUA1qwBCS9KUh6A5C82aAk041vkVGSqW3nQB7M3bFGFmjsRy4LUBiPCTB2rRFdpAdEYuvcPZLNAfNNDF+BCXQ/w9uCIKEU94ZvRVtWiE/vuMD7NbZXrWFoX6WPU87i+b1kAMD1k7fQ5B9tLQ6kdkAkZEEKNPirwMq9gza//zJjezYHzmn4VjSe3X2B32M3I7HPUhxYeQxajdblec9MycL1k7dZ0Tg3UKDVotq8hDKr6JUSZqLt1o1Yfe0KeuzajoH79+DAg3uWQnJiivPwubNxMy1VsjkQPQjqFedVxoIg8fE238Sf4h4OktXZchzJGQ/utPAqIFl9nBO/aT+CUgJKKUj+shIi33yfT3nu6aQV7nLwnDCQrM7GOcqbBpI7BbTojChbqKj+Pqj2omBveIZzXDnCsyASEIlVEzdi2ei1GNtsOub3X4Z9y46ILs7lQUq0r9IH6vyXpIAp800MN8IEup/hbUEQABxddwqyAIWlSFyE6evt/hVHrY7bt+wImnFUPrcURXOi7dm+ZUcAAINk48T/UlzyGQMVOL/vMhYNWWl3z/XS50eUN66+twnpifQXzq06qAs0iG01uzgbISASYyOnoyCnwNXXyCjB8SePUDlxNirEz0DIHGNrtZ+XL4Eq3zroPP74kSgr5XGnT+LrJQvw8W9z0H3XNtxKT5No5EZYEMRwFG/0TSRnRLEgNYtzVQ1Q/T3LMZTqQHInGAU554q42RwTzdSgAiUFsKS/u8tUX4DoVaa2bs6I/jBYsgiyelvtpXcEqn8Ikt64xHU/As2XtuL3y8iKsestYtkcc02MioPBYP3efhuw3OGMv9K2csJGTGs7F03eaQvlPztifv9lyM3Mk2jkRphvYvgKTKD7Gd4UBOWk5+LE5jM4t/cyrp24hdhWs9Hl04GY2CION07d4TknR3BvuKMFUE5tPYec9Fy3inOzEG78dgxSn6aj0d9ca2kiD1JiTNNpIISUcaq2mBgVV+YDgTxIieH1J9k+meEQWWo1ll+5hGmnjmPX3TvQcbyrk08f2y3Gufa1f75wHp7m5EgwOmFYEMRwFG/yTVR/H1SzB0R7BaRwO0hmW6N4zI0FNbzgPMf2Pm9HepqHgZJ8UPUO94pz83NldQMpOuGkQC/1YaFwjTH93wFhTakaJPVrzjmiBSvEeq0ME09uP8eqCRuRNGoNbv5xh/NdLRxs32KCLFCBuhzFdgfLxkGn1UkwOmGYb2L4Ckyg+xneEARRSrFi3Hqrr7NN3mmLs7sv2Tx327y9gs5iYlQcWlfojqh/d7YpmJu80xZajdZY+dzdAt1kqyduFO1a8iAlZIEKDK070a495qlP0wWzDJ7eeS7G62U4wL3MDIcKypU+drSErdSEEDMIqtY5Fh/3jPMqq9aZBUFi4xW+ieSDZHW2Fonpv4Lqn9k8l2S0FBCuoSBZfUFSvwVRfW2HYO5hvGb+Ag8IdNPz5U6FU23Zylh1mFfASc4YUGL7fVL1Jv7rpX7LVtElYO3ULU4vRsgCFJK2UhOC+SaGr8AEup/hDUHQ/hVHy36FDVCgTvnmSH6oEjx3aswcQedw9dhNJD9QYfeSgzbErQKXDl0DYGy95qnWI/1+GF2m37sYQr3BX1pb9tPzcfHgNcHrnNrqnQ71ZSZmy0ZUdCHFvUL8DDz3QkfMgiCGo3iDbyLZ/TlEajhIWh1QSoTPTRUS3qEghIDqroLkjBYWuKpvQA3G+hFEc9hDAj3Ejg8HzlgYSHojUKoXnru8aRAqtkepdHuW/RF1gUa4c44NkwUoEBPWyys/rDDfxPAVmED3M7whCOpaYxCnIJYHKbF42GrBcxcNXSXoGOxtI1L3tRYoUhe3KGv+Lxsr7iLZsPqTIHfDx4CIYCVmd10gOHfP7yULXuP+lUdivF6GneQWaURpx7b2xjWph1IGFgQxHEVq30RJpuAKMi06I3i+sS0an/itCZIWYZ+ozYguvibJ94w4T/0ODrVvc9CoZq/w3BeuBm96vepzmx9HGOJyfONpUeKS1CfS1kLhgvkmhq/ABLqfIXUQBACN/s69B1seqMDEqDjBc6+fvM3rDBr9vY1DBdhu/HEH66Zt9Yg4lwUoMKnlbGyfv8+pYnb2WNuw3jbnfrB8fJk2K/JgJXrVGi7W62XYSVpBgShV27fcvin1UMogahDUKRYf94jzKqvWiQVBYiO1b6K6m8Iis3CD4Pkkbza/yEypDvv3oFcDIQUg2YNRnC7uLjO3ddts3Ifu0D55e60ySK5wjRNKckFUn6LsB5JQ0Pw5Yr5mhh1wZTk6Y1mqbKmHUgbmmxi+AhPofobUQRAA9Ko1nHMVWR6kxIqx6wXPpZRiQvO4MuK37qtRDjuPduG93S7Ma5cz7nVPGrUGep0e6gINYkJ7OVXJ3dYHgJ5fDcXdiw+Q+jSdd/6y/z975x0fVZn9f0hRt+muu+7qfn+7uipJsIuKbcVVSUIvkhl6B6lSpINK7x2kg/QqRUGqdAERpPceanqfmUx7zuf3x0wmmcy9d+ZOJpmZzHm/Xs9rJdz7PM+9+X4553PPec5JzUavD750urfrWwO8rgrPeA8R4ZOli0oURY/+Ziqy8/P9/SgusBPEqMXftsldT3MyKddIIZEJkfpRMZEZBZHyjkpB+yZKvXJ7wUiNBxl+tO3ffAEi6UUJkVzSEQORMx5kPqd4Hp1Mp4odE4iCyB7sNj2e8T0pt1MRG+Z9pl9chBa9PvjS348hCdsmJlhggR5i+NsJAoCfNx51/Qc9XIPaf2juUV9uq8WK77/Zjs5V+qHZvztjbMvp+Gn5AVUGRKpdm69HXIQW968nuZzDykzJxqCao3y+Xo0iHyn6fjIMqXfl3+W1kzexd/UhXD5+PSDPiYUKe27ewLPTJ+G5GZM9EuQF1z0/YzKenT4J6y+e9/cjSMJOEKOWQLBNtvPhxaPgMRBpn3r07ySJDNt56tRPIFKrQ+ROthdfkxf+LqNUzoIXGykfQQij6/7NZ2x/V2prvwCRPQJEJun3RxaQ8RDIsBVk5aKl/mR278U2f8LDjL+C9rhx4Ro0fLw1bp677e9HkIRtExMssEAPMQLBCQKAzbN3oN5jLR3/uLd8rptsazUp7l9Pwtw+SzGo5ihM6zwPJ3464/kX37AENP1XJ++EsJr09LAETO8632XvhjwD6v6pRYm+UNs+AGhk+5TGR2rRJvpzWC3e9aRlyo5f7t5B843r8NLs6ai6YI6sOI/5ZiomHj6ITlu+x9B9u3ExNcXfW5fFl07Qyx3G4LWuUwJqvNyBnSBfEwi2icgEkT3IOYqc0Rpkdf/h2DGH6VdbenpGe1DeTAjdChUCtkrJxK+K6Dfl73Tdu/EX30XNHXsp/sEjCiJ7mC9/bUwpQETYPGcn2r3QC3X/1AKaJzvIZj52f2cgpneZj6ENx2P5iO8CMrW9ALZNTLDAAj3ECAQnqACjwYhzhy7h6okbEMLzIjCn959Hzd81daSJx0fa2o19/t5gj1LHa/+xORo83rrUI+jVK9p6hBZPH9+z8qB3gjxcY3u+sAQsHLwSiwavxPx+y5w+dBQfXJk9uDBbrfjvt/PxfLGI+rPTJ2HkgX0AgByjEcvOnMJXe3/CvN+OIVWv8++mJWAniFFLINkmsqaBTL+CLOqigJQ3u4hArWQXqW9CJFeFR+e7kz8uoTD2tI95FERabZf9i+wBnu1TUpBH2c6R5y2CyBkLkT1M4frKIBG4Io5x5ea5244oeXE/49h22/GPBzeSsWzYOszotgC7lu2HKV86U8KfsG1iggUW6CFGIDlB3iCEQItnu0pWga/9h2b4qv44p5/VeEg6wlxahdqkxpHNx5F0KwXLhq3DtM7zMLrpVK/mafT3tlg4aCVuXypM/ctIypS9Pj5SixWj1vvxt8V4w62sTMSvWOIkzvvu2g6T1Yor6Wl4Y94sPDt9EirNnILnZkxG5VnTcOROYKUTshPEqCXYbRNZbssI5BiI9MYQqTWLCWmpaHe0qii4d+K8yBBGkOk3iJzREDkjINISvFs7rRFItwgkMgvfh2GT4j1kPuPH3xbjDYc2/YqGf21TxOdqjs2zbRX6dy3b7wgixNv9rtZRnyMjKdPNrGUL2yYmWGCBHmIEuxN0/fQtRRF7aNOveHAzGce2n0TixbsY03wa4iKk0rI0Xrc7a/rvTo7ouG0u5aj9ilHrER+pdTJc3oz2L/V2eR8moxm1f99M9p5dS/f74bfElBQiwpnkJOy+eR33c3McP6u1cqlEdH0yqsz7BiZr4Bxn8KkT1H4MXusyJaDGy+3ZCfI1wW6bSLdAWVxb82yF0owHIKyp9qi6GiHsgXBP+QAuRepkr38FImtokQi4inPyxUfuJNf3YTyq+DGBrMl++C0xJcVkNOPE7rM4tv0kDHm2/vTpDzJt0XUXP0uLkW4685Q1bJuYYIEFeogR7E7Q5ePXFUXs2gk/OF3/2Wt9ZK9tV7knerw32BFRb/lcN2yevcOtUF4/dQt2rziIrm8NgPapDviq3ji0eK6ri1CPi9CixbNdnYq3OUbxCL4HEf2Gj7eG9p8dMOzTCbh8/LrjGWf1/NblY0NchAYN/9oGBl3gVfgOBYgIvz24h1EH92H4/j04kHgLQqLIVFa+AUfv3sHVdPdnXK9npCsWkNt760ZpPIpXsBPEqCXYbZMtvV1BRFvuF14rshXEa2WIzO52sV0QgW8CkTPZfZTcfBYi9xtbkbqUahDZA2X2FA2R8ZmigHb+MODm40DK+xApH0LkjAJZbb2viQREaixcU+ZjIDI7++vXFPKYTWbsW3MI07suwMJBK5F44Y7kdQ9uJuP0vvNIf+A+Ar5x+lbJrMYCPyhf71qQ0F+wbWKCBRboIUawO0EWs0WxArvmqQ6wmAvbsgxPmCT9ZTey8Muu1Wp1nIE35ZtQ/8/SfdqrV0xAm5geuH35HgbWKKzCXvfRlmj4tzZOBql6RVt7tdHNpymK7nqP2s6Pt6rUHbuW7cfcvkvcCvW4CC3iIxvj9D5bBW+jwYihn05wukb7VAdcPnat7H9BDIgIX+39Cf+ZPgmVZkxBpZlT8J/pk9Bh80aY7VFuQYSxP+9HlP3v/jN9EuquWoZbWfLO0OmkB4oCffOVS2X1iG5hJ4hRS7DbJnd91EVWv8JryWrv+y2T/m3vuU5kdlSPJ9MJN/OPABkPQ6TGF/4s+W04t2yzi+W0OhBpjeWFd/IbhddmtLRXd4/1IJoeA5FSDSRsdVfIkmgX6UWuSW/K58/9RF6WDp3sQYv4hxojzu4bbZj6o+Oa7LQcDKwx0uFLxIZrMK7lDBgN8iJ7xcj1jrmkRk56blk8nkewbWKCBRboIUawO0EAsGXuTkUB+8uW3xzXnt5/Xva6cz9fBADkZORi4/StmPPFEmxftAdrxm2Sj2L/tQ2a/L/P3Ka1f/q3tm6FdvWKCUi6lQKT0ezY79Khazy6LzZcgy5v9HN6L7fO38HOJftwdOsJp48UTNny041rkgL62emTsOT0CQDAN8eOuvQ/f37GZLz/7TwYLdK/O4PZjJdmT5ed+15u4Pz/tC+doFfajcHrnacE1HilHTtBvqY82CaR3kIxMk4ir/Da3CkSEfFoiOQ3QcJW+JEsN0B5MyByx0PkH4BIbyMfRU+tB0exNtmoeBREkvyHgcKIeDUQWUFks01EBJHWwAOBbn+G3MK0ZiIBMh4B6TeAzGe4racfmdl9oazvknjxLogIPf/7pWs2YLgGE9p8IzvvmQMXpP2UMFtQI5B+52ybmGCBBXqIUR6coJvnbiuK1x/n7XK6/sd5u5zOadf+fTNsXbAbAHD24EXU+WNzxIZrHOfDtf/siL6fDPNIKJd0fN1gvCP9y5RvQt1HW6i6PycjcL5MMza6bt3sck68QETXXb0cFiHw2tyZspHwLQqR8IUnf3PMVXTer/ftLsMndA87QYxayoNtEnkLFQRyJZClMJ2YyAyRNcD5+pRqIPM529/rFhSJetvPh6c3h0h+10OhXJIRBcqbV7hX03F196fVLfN3zyhDRKj7J2n/Ii5Ci8VfrsaV3+SPEMZFaJGZki0794C4EU5p7rHhGlQPC7xOMmybmGCBBXqIEShOUPqDTGyasQ0rRq3H2YMXVX1hNejyUfsPzWUNyaVfr7rco8vR49CmX3H4+2PQ59oKm5hNZjT6ezuXs1NxEVrF+X05YsMSMK2zzRG6d+2BuvvDEhzP4k+MBiN2Ld2PhQNX4Md5u6DL0ft7S36l5abvZMX3h0sWIF2vl/37SjOnYPrRI4rzr794Hp8sXYRnp0/Cu4vmYsGJ45Ln2/0JO0GMWgLFNpH5AihvDki3UH2bNaU+4slvgMi17RRZ7oIMW0HGX0Bkte/hnHx0utTFeZEPCvZe6aRX08u9EkR6o5L/InwAWVNAukUQuZNA+Xsc7zcUISLZc+LxDzXGNz0WuW0Be+GXK7LzGw1GLBy4Ag3/2gax4Rp0fWsAjm49UYZP6Blsm5hggQV6iBEITtCupfsdvcsLUqkG1hilqmfm4q9WuxRWi4vQos9HX3ss9o9uPVEmItzdqPFwE+hzDdBl6yTPy8t9zR5Yc5S3vwKfcffKfWj/2dFh5KuHJaD+X1qF9Pn3WceO4jmJCPrzMyZjyN6fYLZaZVPV/zN9EjZevODROoGUNlgcnzpBbcfg9U5TAmq80padIF/jb9tEJCCyBxcRwtH2SPIcFXMQRNqnkOolXjQi7Q6RM1pyjrIdURDpzWzPlb9bXfRdt0T1+/c1lL8NtsyDaDgyENLqg4R0FDgU6F3tK9nuNQc3HMWFI5cVggkapN3P8Ggdtk1sm5iSwwI9xPC3E3T/epKkgYgN1+DbIas8nkcIgaVD1zpStuIjtRjTfBp02TrHNaZ8ExIv3JFNy9q9QvlrcVmOT59oi3WTNmNcqxluz7dXr5iARk+0w92rD0r8+ygJRITOVfpJVK/XoMm/OsEaQG2/ypJMgwHvLprrlOb+/IzJeHnODCRm2YojTTh8UPIM+pvzZ8FgNrtZIfBhJ4hRi79tE+nXykeSTZ6n6ZLIhMj8vDDanfy6LSJfRLSQyAJZrjnOmhdHZPVXEOhlG0UXafUh8vfYKrV7snZ6MxD5t2o3WVMhkl6Q2F8MRNYgv+7Nn5w9eNHR8rXox/5uVQfAarGCiNDp9b4ugYK4CC2Ga1xb6QUjbJuYYIEFeojhbydoyddrZAVoo7+3Uz1fZko2lg5bi4ntZmHFqPVIvZsOIsLqsRtR7zFbhfTqYQn4su5YZCY7V459cCNZtr1ZHZmzWqU9ZvVYhH7Vhyte81X9cchO8/8/vokX7iju8+Ses/7eot94kJuLPju3ofKsaYiaOQWdf/we1zIKW6mZrVb0/2mHk0ivtngBLqal+nHXvoOdIEYt/rZNtsi31PnxGIis/urnM1+AyBkBkfUlSL8WJPQgkQeR9UURofsyRO5EEDkXhiT9Gnlxnlqz7CPpSVEQ+pVFWr/JjLz5kmn8ZQ3plsj8LitBJL0QEHv0F2cPXsQX//sacRFa1P9zK8zpvdjpWFrq3XR0eZPTNjUAACAASURBVLO/ky0fWHOUU/AjmGHbxAQLLNBDDH87QdO7LkB8ZGNJQRcXoVU1192rD6B9qgOqh9lbhkRoUePhJpjYbrbk3B1f+cIlqjup/WzEFhXp9v9eM+F7tHi2a5kL9PjIxshKzcbl49cdrU5iwzWOdzay8ZSAiUyf+/mi4rPsX6d8lpoB7uXmYPu1q/j13t2AO0deEnzqBLUZg9c/mxJQ45U27AT5Gn/bJpHyobzwzFD38Zjyt9sj4EXSq1OqQaRLtTaLgsgZ53w/GSBSqxeLotvnMuwsY4Fu32NaQxBZIAzbIVI/tv+8IIU8CqRf7ctfR4kQudMK37vEIMHFVZUgIlz57ToOrv8FiRfv+ns7PoVtExMssEAPMfztBO1YvFdSzMWGa9D97YGq5upV7SuXaHysTES8YPy67aTTHFaLFStGrkejJ2xt0Zr/pwt+nLcLRITt30rv1asR5n5vUnu8cSYRS75eg4WDVuLcoUsBdbZLl61Dzd81lf59hmmQcrt8RIMZ9bATxKjF37ZJZPWCdFp5NChvhsfzkMiGSHpJIoKrlB7+olMLNgAga5q9yrs9VTu9Cch03LbXzB4eiGrfp8IXRPqJrCDjPojcCaC82U7V6QMBMh6Q/9CQGhdQdpQpW9g2McECC/QQw99OkNFgRKvnuzkJ69gwm4AtLp6VSL2brlokx0VosXrsRsn5iAhmk+vZ3+8mb1acs8VzXREbpnFaIzZcI1kt9acVB3Bq7zmsn7JFcc7jO097/X7LmiVfu/Ztjw1LwOSOnhdWYsof7AQxavG3bSLzRbsYLipsYyCS3wJZPf/YSPr13olf83np+Ug4+pEX/sxg74kuN18MRNIrRZ5FLt07GiL5NQjTKQjjYYjMfoqCP1iELZGASE8o9ru0vQPK3+7v7TF+hG0TEyywQA8x/O0EAbYWayM0kxwivU1MD9W9MhMv3vUqkr1r2X5V67hL4y4aFa/5SBNM+WwOLvxyBb2rfeX4ueapDti1tHBdInLqy158rJv0g6o9+hMiwoapP0LzVAdUr5iAho+3xrJh62C1BEYaPuMffOkEvdp6DKp0nBJQ49XW7AT5mkCwTWQ6bj+LXpDa3gZkua5uDsXzz/Ip5GRNUbWOLY3bw/mT34TQfWtLj0/9X+HP0+o7fRgQ5ituPiJcVrVHf0IiFyL7a9iyGSpBpMaD8nf4e1uMn2HbxAQLLNBDjEBwggrI1xuRk57r1Vd5i9mCRn9v53n0PFyDBo+3hkGXr2qNuX2XqorQN/lXJ0ckPu1+Bu5cvicpVuvKFKGLDddgdLOpqt+HvyEiGPIMEEL4eytMAMBOEKOWQLJNJLJdUs49vtd8QaU4j4HI7KRuDWsaRHoTFWtEOwrdEQmQ5RbIek/13km/wat34k+ILCChd38hExKwbWKCBRboIUYgOUElZeuC3R6L50ZPtMOFX654PDcRYeinEzw+N150eFIcrU10D8l74yO1mN1rcQneCsP4H3aCGLWUJ9tka7PmYRQ9vRFIeNZfGgBIZNgL2qk9Yx7tdh2yJikLdKO6DDSGCTTYNjHBAgv0EKM8OUEAsH/tYST8QzqSHhehRafX++LnjUdhMqrrLX1633mvUujjIxtjxcj1knOePXgRg2uPhvafHdD0352k5whLwM2zib54NT4hL0uHlDtpAVM5ngkOfOoEtRqDKh2mBNR4tRU7Qb6mPNkmIhMobybke5lXgsj6AmQ6rjqDTORO8kKc2wW2ybW+CRGB9Osg0hpCpLwHkVxVYv5oiJT3XdrB+QsiAllTQdZ09xczTBHYNjHBAgv0EKM8OUEFDK41WlYwN/2XfOqgLluHTTO3YXqX+Vgz/nunPunz+y+XbQfnbuxdfchlrZ83HkVsmKawOF6RyHxcuAaxYRrER2qxdf5PpfKO1JL+IBNfNxjvKHbX5P995nSOnmGUYCeIUUt5tE3yAr0yRPbXsveR5TZE7nSInKEgw0YQGQvnTKvllTgXSdGSglZkD0fBOXiHGC8qzJMqQSRXlS1iV9aQ6RhEWt0iGQgJIPNZf2+LCRLYNjHBAgv0EKM8OkGT2s1CfKRWMhrdTaZ1282zifj0b21twvihxogN16D275vh1N5zAIBvh6ySntPNGXTNUx1w41wiNs/ZiZ1L9iEnIxdCCFvEXCZd/tshq7B59g5kJGU67dFituDQpl/x3eTN+GXLb2VWeM1sMqN11OcuLezkPj4wTHHYCWLUUh5tk0h5T/5MeK506zYybLAL4xg4enmnxjoqyYu0Bl6Jc5HRC2Q6BtItB+X/BCIzyHJT/p6U9yHy5oEMW0DkXLuFRDZI/x1It7hMhTuZr0Akvej6ESH5lYBr9cYEJmybmGCBBXqIUR6doAu/XJEVzXUfbYGLR686XU9EaFWpu1N7tIICbY2eaAezyYxrp26qjpzXkqjMXuPhJpjYfrbifZtnu1aWvXvlPpo93dm2L7uwb/l8NyTdUlfp1xv2rj4kuc/YMFvFfYZxhy+doNdajsYb7ScH1Hit5ehy9++ovymPtonyvpE/i55Wz+VMuLDck0lfj4HI7GmbU7dAfk7Z8ZKEAH8PIqOD8n0Sopfyt7vOl9kNRKZSf5+2vvBSWQkxEDmjS319Jvhh28QECyzQQ4zy5gTpcvSY88US1PlDcxlRqUHDv7ZxVG8XQmBowwmKgvnYdls/9gUDljsJ5NIacREaTGw3C3lZOgC2DwjtXugp2Uu93Qu9Sv2dzuu7FDUekk/vV3uenwk92Ali1FLebBNZrkFkdJER3AWiu3Ph9dZ0iJR3FQRzDIjy7T3QNV6muasdb4Dy5oNI2Pco9wGhEkTOuFJ/pyK1hvxe0xuX+vpM8MO2iQkWWKCHGMHsBD24kYwbZxIdbcwsZgu6vtlfMhW7+Php+QEAnlV+37fGlsa9e+VBWeHve5GuRde3BkAIgYtHrypee2L3mVJ9z+smbZb8OFC9YgLqPdbSq7Z4TGjBThCjlmC1TUQWkPmKrXWZ/d9GstyCSH5NJtpbdBT2P/ek8juJbBBZ7efG1UbRSzByp9meSykjICmm1G2DyGgl84EgBiLz81JdmykfsG1iggUW6CFGMDpBN8/dRpc3+ztE4qdPtMW2hbuxb410KraU+F09diMAoPs7g1xS250i7uEapN5Nx6VfrypeV1rj2I5TOPz9McVrRjebVqrvOyMpEzUebuJyZj42XIP5/ZaV6tpM+cCnTlCL0Xij3eSAGq+1YCfI1wSjbSLDj87nzNNqg8xnILIGeiDO7aLbfB4kchUi7faRGm+rXp43t+yEuWO8BBJ5ENlfKl9nPFq67zt/m/x7NHJ9FMY9bJuYYIEFeogRbE5QTkYuGv61jWSUfED8SI8rrf+6zZa23uLZrorXfdNjEQBgbMvpqovElXTER2qxbPg6JCemKl7Xr/rwUn/vh3845jhTH2ePpg+qOQpGg9H9zUzIw04Qo5Zgs01kPCwRTY6GSH4VIlmuOFzx8SJI5IKs990L+fzdICKIlLf9INArgUynIPLmKF+jW1q675wIIneCfb0ox6C82aW6LlN+YNvEBAss0EOMQHeCrBYr8vWFInD9lC2S6dax4RponmzvVkTHRWrR4eXejj7e41vPlL8nLAFnDl4AAHR7e6DsnErns0syYsM0joJxjZ5oK3vN1M/mlsnvIi9Lh+2L9mDdpM248MsVTm1nPIadIEYtgW6biIxOhdBERhuZKHm0vZe4O9EbBZEz1j63Vfn8efIbIJEFEno3c75aegLdkghhTXHzEcG14Gmp/C4siSDdEpBuGch6v0zWZMoHbJuYYIEFeogRKE5QXpYOG6b+iLEtp2Ne36U4f+QyJrabZUutrpiAz17tg6NbT2BiW5kWahUTHNfKjrAEDKk71ql92a3zd2Tviw1LQI/3BgOQF/LxkVqMbDwFfT8Z5pUIj4vQotET7Vw+OsSGJaDW75oiJz0XALBj8V7ZZ7ry23W//M4YxlN86QS93nw03mw7OaDG683ZCfI1gWKbyHILInciRFYfW8V04xGIjJaFojqzk+2alHfkxWpqTSifEX8ZIncCiCyF6+rXKIp5yptlj6ArrKtbbZvbayH+GlxT7WMg0rWOfYrMrtIfG1LeKZNK7gxTEtg2McECC/QQIxCcoHvXHkDzZHvEhmkQF6FFbITGERUvGiGvHpaAMc2nyRaBa/V8d6wYtd4hnAvub/Z0Z5zafx6ZyVmS609qP0tRROfrjbjy23XpyH2YBucPX0aval96Lsrt88SFa9Dh5d44uPEoulUdWLjvMA1q/a4pftnym2OPRISFA1c4nYOPi9RiwcAVJY5kG3T5WDVmIzq+/AXaRH+OuX2WuvRgZ5iSwE4Qo5ZAsE22FmIFPciLRsejnQVrclWItLoyIjwGInuYvaCZ/c8F12V0gDBeAgmd5Poi5X/y4jk9wbZH3QKJv4+2pb5bUmHrE+6JGI8q8lwvQWS0hTDshkh+y/6zgh7sH4EsdwvfkciFSG/uPFdyFYj83SV//5Y7ENlDIVI/gUhrANItBRF3DWF8B9smJlhggR5iBIIT1O+TYR5VXo8N1+CzV/sg/qHGLgXLqldMwMbpWwEAm+fudES7C8R+y+e6IeVOmuT6K0dvkF0/LlzjaCN24LsjaPjXNo6/a/CX1tiz8iAAuI/eV0xAXLhtjc9e7+uInhecmZ/RfQGObT+JZcPXYfPsHY7IOWDLLkhOTIXVYsWFI5fR+P86Os3b5c3+XgtqU74J3aoOdPr4EBehReP/64j0ByzSGd/AThCjFn/bJhJ5EEmvuIl8FxHEGZ1l/47Ml21p61lfuIrhzK6yolOkN5EX0xktbPskYT+HXblIxD7eVknedMxDcR5jOyuf9G7hnws+TBh+ABk2gvJmgvK3O+2VrCkgazKEEBC6JXDuhx4FkT0ERFbv3r/lhk3oOz6M2M+YZ3R0tHljmJLCtokJFlighxj+doKy03JUp4Uf+v5X1H20hVOa94xuCyCEQL7eiPp/buVScT0+UosBcSMk93D3yn3Z9PNhn05wutZsMmPXsv3o89FQ1PljczR4vDWmd5nvJNyLf1T49G9tUP/PrdCr2leY0mmubB/1oz/+5rRWZko2hidMdIjnhH+0Q9N/d5JMta/1+6ZYPW4TLGYL1CDXZi4uQovZvRarmoth5PCpE9RsNN5sMzmgxuvN2AnyNf62TWTYoi4dPL0FRO6kYtH1l0GGzbb5ZMVyFEj3rfQe9Ctk1yP9audrRQZE3iyItNq2qHnK/yByxijvOfktiOQ3IbL62D8GFD9DHwVbxXbn3wGZTkOkNSjyQaCm/QOBxMeMlA9B+btUv3+R2V1iP/ZnN+5XPR/DSMG2iQkWWKCHGP52glLupKkS5wV9tw26fBz47gh2LN6LBzeTHfPtX3tY8X65SPOqMRudUsxjwzVo/H8dkXQrxem6+9eTUP/PrZwi7nERWtT/SytH6nrxcfNsouP+TvbouZQgHtV0quM6q9WKjq984VFmgeNjQFgCvm44XjHlPSs1G2snfI+JbWdh2fB1GBg/UrZ9XPP/dPH218owTrATxKjF37aJ9OtUCPQYiMwetvusSbaIs+FHkMhzzCeyB8kIziiI1JrSeyBTkdT46ELxn9HW5Xw3GX4scl2xdHOXdaMhUt5znHknkSktrh0fA9YXrmNJhO1ce7TzM7h5R6Rfpfy+LddsmQDZg+zn7+VS8ytD5Az15lfKMC6wbWKCBRboIYbfnSAitHyum2TKulS6ubuo7qaZ2xTnSLx4V/be84cvY0rHORjWaCLWTfwBuZl5LtdM6TgHcTJF6pr/p4tN5D/U2CGs10/Z4nR/82e6yO5tUK3RjuuObD6uOrOgYJz7+aLk8109ccOWXRCuQXyk1nbeP1wjG9FvVam74rtmGE9hJ4hRi99tk+W2R8LT06iuyOggf3/Ku/L7IIstmp/VCyKrF8iwxamYnO0aAZFSTSFS/ob9WexR7uRXQaYThfdb7yk8WxRIt7jwOXKGy0a2laP1r4MoX/oZ9avt+yt61l/u3cdA5Izy4DfIMO5h28QECyzQQwx/O0EAcGjTr6geliAbyS0Ynav0gyHPIDtPcmIqmvy/z2Tv//RvbWE2eV9ghoig/WdH2fmH1BmDwz8cw5zei7Hk6zW4femeyxyTO8yWjIrHhmuwetwmGA1GrJv4AzRPdfBKnMdHarF06FrJvbet3NN1bRlxHhehxeIvV7vMwzDe4EsnqErT0Xir9eSAGlWashPkawLBNons4Z6Jz9wJiplLlL9XQdQWRt+93qf5hqLAFnkLQPpVEDmjbO3IhHMmma2t2wfyHx/MF0DWBxA5IxUi2x58xCjyUcCxtvU+XCvFK0flyXSsRO+LYQpg28QECyzQQ4xAcIIA4MTus/j83cGywlPzVAdH73I5en/4lWJK+KaZ22TvzUzJxvZv92Lbwt1IvZvu8vcXj15F+5d6y0f3I7QY3WyqxMzO3L36AHUfbeGSIt/kX52QkZyJ3tW+8jpyXjDXmvHfu6x782yi23sLKuXHhmnQ/qXe0GVLVxZmGLWwE8SoJRBsE5EA6ZZDJL8nL36zeivPIbJhSwmXE5wvgMwX5O83XwHpV9lT5vWuf69fYztHrphevsH9sxp+kBDGURCZ3W3V1JOryghpFQJd4jlJt9DNvAX7sV+TPaTEnUsYpgC2TUywwAI9xAgEJ6goi79a7UhnL4gIx0Vo8eu2k4r3JSemKorPWT2li/AAwMbpW50Kr8WGa7Bs+DrH36fcTkXtPzSXPWNeMIq2RVPi1vk7+LrBeNR4qDFq/74ZxreeibR76diz8qBHArxN9Ofy14Ql4MEN25l8q8WKzOQsmE1mXDhyWXHebz5fhK/qj8PAGqOwacY2xUwFhlELO0GMWgLJNhGZINK1xcRrjO0ctzVJ+V79GsVosDD+Ir9mZg/na5NfBxkPFl5j2OqBMH4RJLI9e878XRBp9eDoY543w7aPrH6eifOUT2T+Lhoi9ROHsCbKB1nTbR9A8mZAMWU+dzpERhvbh4L8XSzOGZ/CtokJFlighxiB5AQBtlTsA98dQZ+PhqLlc90wsvFkXD52ze19V367rihAdy2VPh945sAF2XsObfoVALBw0Eq3xdqmdJpbYsdhTPNpkr3Wi45ubw+EIc+Aa6duIuEf7REbZvuYUdCubf2ULRBCYOXoDWj4eGtUr5iAun9qgdm9FztXvi8m+rmlGlOa+NQJajIab7WaHFCjShN2gnxN4NmmfFDefFu/89Q4iJyxIGuK+/vy5igKULKmSt4ncqdKCHt7VXWrLctLvvd6wbXRIMMWyfnVYDvD7kac50wBEUHov0PhWXJ7YbvkV0CmkyCRBZHVF46WcCnVIHIny+8/rU6J984wSrBtYoIFFughRqA5Qd5i0OWjzh+bywrbO5ddz4MDwOhmUyXblsVFFLZlG1x7jOy8df7YHKf3n/fJV/1xrWYgLkJZoBf0XQcAXbYOG6dvxehmUzGz+0Jc+e06AGDhwBWS6etd3xpQmMpesfD8+fz+y0u8d4ZRgp0gRi3lxTaR8ReFiPMHkj29iUghbT0KpFsEAArCPwoirT7IkugytzeI5Lfcp68XOddOltu2lnNZvWxReGuy7Zx7Wn3pPacW/9BgE/ZFswUYpjRg28QECyzQQ4zy4gQBwMrRGySF6agmU2Tv6fXBl7JiuE20rXDPtM7zHBHq4nP3fH+Iz/Z/+PtjblPcpSq05+uN2LPyIFaP3Yh9aw6h5iNNZNPfN0zbik6v90Wt3zVFm+ge2DxnJ6cMMqUOO0GMWsqLbSIiiPSmkinicmfDiUwKYrgyRM4YAFCo3B4Nypvls2cQOUMVIvWVbBFyci3AStYUkG45SLcAQrdU/v7UjyByZ0Ck/Bci6SWIjBYg41Gf7Z9h5GDbxAQLLNBDjEBygm6eTcQPs3Zgz8qD0Ocqn4G+9OtVzOu7FN98vghHt56AEAJEhI3TtzoqoNd9tAUWDFiuWLl9Vs9vJdumxUdqMbbFdAC29mRy1c73rPrZZ88vhMDwhImyaejtXuiJX7Ycx9RO8zC9y3wc33kal49fw6d/a+u4xp3A37/2sM/2yzCe4ksn6I3Go1G15eSAGm80ZifI1wSKbSKygowHQbpltv8l+WKlRGZQ/g6InGEQuRNB5su2n4s8iOyhNvFpF6Rk2KS4rkitLiuKybDRNq9ugUxq+wtuz8aregfWNMWPASJ7uK1KfPYgW0V7yzV767QYR6p94d7kIvD8/ztM2cO2iQkWWKCHGIHgBJlNZozQTnZKu67zx+Y4+qNr0TUiwpwvlthFdGNHZHtgjVEwGW1CXAiB3Mw8WC3KVd8B4N61B6j1u2ZOZ79jw2xnuq+dvOm4bueSfaj1u6ZO0fPFX652G3026PKxbNg6tHq+G7T/7IiJ7Wbh3rUHstdbrVZsmbsTDf7S2klYt6rUHf0+Geby3EX35Mk4ve+823fCML6GnSBGLYFgm8h6z3bevKi4TI0FWe66XivyINIaFUa57anclDev8Boyg0SOR1lLZNgkIWRjIFI+dPQTJ7JCZA8pFs1+HZS/1/38ltsQWYMgUt6DSP0EInc6SMh37iCRbf/IUNl5vYx2EMnVCvfnTY/0pJckI/AMU9qwbWKCBRboIUYgOEFLvl7j0gM9NiwBNR5u4lK87PjO05LCMzZcg3UTf/Bq/fOHLzu1UGsd9TmO7zztcl1elg57Vv2MnUv2Ie2eayu24phNZnz+7iAn8R8fqUX9P7fC3avyIh2wfYi4cOQyti3cjRO7z2Lz7J2yUXxPRlyEFs2f6eK2VR3DlAbsBDFqCQTbJNI+lRCcMRBpDVxEtsgZK5nGLpKk24t5AulX2dubFYjhViCraz0VsiSC9OtB+TtA5L4DB1kSIZKrFHu2aIi0RiAyKd9LJlD+bpD+O5D5CkRmFy9FedEI/JdevR+GKSlsm5hggQV6iBEITlBBiraU6C7e09tWSE06lbvR39t53LubiGAymou0fSE8uJmMe9ce+OxM9u4V0m3T4iK0GNtyuqq5er4/BLFeCPSCSHujv7fD9dO3fPJcDKMWnzpB2tGo2mJyQI03tOwE+Rp/2yYyX1YUlsVFt2IhtYwOksXgJNclchLJRGaQ5bpHFeM9xVZJXVpUk+F79xMU7E3oZT9KKI+owvXTtSCR57NnYxg1sG1iggUW6CGGv50gq9UqLy4fauzSv/zrBuMVI8ntXujpVqTvWLwXLZ/rhuoVE9DgL63x7ZBViufUvSHlThqG1Bkj2zat4V/bAIDj7Lw7Or7yhWpxvnvlQawYuR4/LT8Ao8Ho0+djGDWwE8Soxd+2iYwHlAW6cZ/T9SLpRWVRmj1YeT3Kh8idAJH8emEqvQ9apDmvIUCWaxBJcm3TYiCy+jiudTufyPRCnFcF6VeD8maDjIe5SCnjV9g2McECC/QQw99OEAC0e6GnbHR4x2Lns3TfTd7skg5fPOq+crR0ZVwA2DRzm+Q9SpXe1ZByOxV9Ph7qVjw3+EtrdHq9L6pXTED9P7fC/H7LFEX0vL5LPSoCVzBqPtzEJ8/DML6AnSBGLf62TWRNglKPcbI6H1MSGa3dRpPJfEZ6LSKIjI7F7retTfr1vnke4yGI1I/dp5unNbSdS0+qBJH6iS2VXUZEExFEak2F9ySVTdDSJ8/DML6AbRMTLLBADzH87QQBwJ5VP0umgTd7urOLaNVl69D8P10UxWmXN/tLrmM2mdHw8day941sPBkZSZmS93qC2WRGy+e6uRXSBVH14tH1di/0hDFf+vxf2r10NHqinVPF+TiZ6HxsuAYT2n7j9XMwjK/xtRP0dvPJATXYCfI9gWCbRFZ/CdEdDZHV1+VaMp2STRt3RKdzp0muQ6bTyqI5d06JiqiR+Qpsxd1UCGmn6L/8GXEy7oNzpXblQYYfvX4OhvE1bJuYYIEFeogRCE4QAGxdsBsJ/2jvEJn9Y4cj6Zb0mbv0B5nQ2lupSY2ubw2QvO/W+TvKwjlMg+bPdEFupnfn4favO6Ic2bZnCdR4uIlsmv5nr/VxVKMvzoObyRjfeibqPdoS9R5riUntZ2HYpxPte09w/G/j/+uI1LuuRez0uQbk6znVnSl72Ali1BIItonIBJE9okj6+ou2lmIk/e+oMB7zTqDrvnUvnjN7eP0cInuw+48H7sR1rnyWGRmPQKQ3h0h6CSLlA4jcSRApEm3iMjqAyFLsHQuQyOYq7oxfYNvEBAss0EOMQHCCCrBarLh75T4yk7PcXrtp5jbZtPj+sSMk70m7l+42NTw2XIPVYzd6tf/FX612FGWTGr3+OwTjW890u4fNc3Z6vKYQAvvWHMKQOmPQu9pXWDZ8HbLTnH+X536+iG5VBzqe78u6Y3H/uu965DKMO9gJYtQSSLaJRB7IcsOjYma2VHUZwatbJT2/YYNn0WfzOa/2L9IaKMz7OkR6S4jMbu7XtyR6vCaJXFuf9ozmEBntbFXmi4hwIrJVqU953z7/KxA5ozyqQs8wvoJtExMssEAPMQLJCVKD0WB0FHqTGif3nJW8r8/HQ92moPf9ZJhXe/px3i7ZyLjSufnio5+X60tx9cQN1HiosVM6fVyEFgn/aI+c9FyfrcMwSvjUCdKMwtvNJgXUeEMzKij/HQ1kgtU2keUGRNIL0iI3+VVJkU8iFyLpZTdR9GiQboFXe7KJb6mPBlEyP5caUSDdwpK+nsJn1i2RfEaR0dFnazCMO9g2McECC/QQI1CcICLCvWsPcPvSPQjhWTuarlUHSArcuAgtxjSXTiVMupWC5s/In2GPC9fiq3rjVO8/OTEVV07cQL3HWkpWblcj0Ht/+JXbtX6YtQObZ+9Ayp00xWtHaCYhPtL1g0RsuAarx21S/ZwM4w3sBDFqCRzbZAKZr7oUhZO9XuQqCm0ySGdoUf5eKFeCQGD6hgAAIABJREFUjwLpV6jcu8X2wcDwo4ciXGlEg/LmKqxFINNJkG4JyPADSMh3UyEyQSS/qZApcF7VczKMt7BtYoIFFughRiA4QReOXEb7F3s5xGOzpzvj8A/H3N7X4tmusiK3f+xw2ftM+SaMbTFd9t59aw55vPerJ26gc5V+jnsTnuyAeo+19FiMSwn57yZvll1v6dC1iA3TIDYswT40WDHKucqv0WDEuUOXcPXEDWieai+71tcNxnv8nAxTEtgJYtQSCLaJ9Kud+5unNwZZbinfY73vJgouH4UmaxpEaryMwI8BWVM937thA0TKu4X3p3wMW6G4otFzdT3MyXxZei2ht1exr1S49+TXQMbDxZ4vHWQ6BmH8WXkdlR8iGMZb2DYxwQIL9BDD307Qg5vJqP37Zs5R5zBbhPfCEWlnoICxLadLRofjIrRY8vUaxXvNJjMGxI9E9YoJiI/UOs6Oj2k+zeMIftq9dNR9tIVzynyYbawetxHrp25Bn/8Nle2FLjXav9Qb+lzpM3iHfzgme9+x7ScBAFvm7kK9x1o5fl7jIekz8fGRWkzuMMej52SYkuJLJ+jNhFF4p+mkgBpvJrAT5Gv8bZvIsEVSJIuU99xEhy3Owri4+DT9pryu5Y79XHZB+nmMPXr+ned7z98pvffktyH0ayHy5tiKuamJoGd/LbueyBkmIfajIJJfAYkce7G9IR5/ECDDVo+flWFKAtsmJlhggR5i+NsJkuvvHR+pxdBPJyjee/PcbdR8pIlTu7G4CC0aPt7Go3ZpVqsVhzb9ikntZ2PqZ3NxfOdp2X6vAJCRlIk9q37GoU2/Il9vxOIvV0vuPS5Ciw4vfyH58UBpdHtrAHTZ8o7f4NqjZdcb2nCCtICXORNfvWICzh265PYdMYwvYCeIUYu/bZNIrSWbqk761Yr3kn61ZPRcpLdQtDGO+0UeSLcMIqsfRO54kOWa8vXmSyDD9yDjURAJe1E4mTR7xYJxMiNnhEIvdBNE0ksy90bZ3kX2CIn9SO0vGiK5Cojy3b4jhvEFbJuYYIEFeojhbyeof+xwWQHZ/Jkubu+/cOQyPn9vsEOMDowfiduX7vl0j0SEb4eschLHdR9tga5v9fc6lV1qnD+snDHw2at95MV91QHo9cGX0r3RwwqFfFyE1hbh97JSPcN4AztBjFr8aZuISF7gJlWGyHFfyJP06yBSqtnveQkie6hi5N2rfYo8iIw2zvtLjYV84Td1Ke22KLiyYCaRpXB/ZYiciZAtmlf0uqQoWxE941GfviOGUYJtExMssEAPMfwt0Ce1myWdph6ucVssrSi6HD0MOnVf3a1WK3776QyWj/wOm2ZsQ/oD6aj7rqX7Zc+Lx0V4nr7u8oyRWsezLxu2zu1+J3ecI/2uIrWY0W0BGv61jfQ+wzXo98kwLB/xHdaM/55brDFljk+doEaj8E6TSQE13mzETpCv8bdtEinvyYpcpWJpRSEikMgCkUnd2kIHof8elPeNreCajEAWWb0lRHdBWrzKKLlTVLuyfd6XQEblmixEQjldXrJau3PqvMidBtKvBgnuLMKULWybmGCBBXqI4W8n6OLRq7ICdv+6I6WypsVswaLBK517lofZ0up3LN7rcn2XN/pJVmF3165Nbmieao+jW09gTu/FWDR4JW6c8ay3bOKFO6j5SBPnlmnhGtT6XTPcvXIfXd8aIHnePS5Ci/n9l/v6NTKMx7ATxKjF37aJ8mbLpGW/CLIml86a1lSIjE6uIjblbZD5ovO1IkNlRFyphZt9ZPYD6dfaUtp1C0FW5S4hjr3o10jMFwORVgvCmq74wcDdBwCGKU3YNjHBAgv0EMPfThAAbJ3/E2o83MQp4rvk6zUendXzhkntZ8uK59hwDe5eue90vVJkusub/Z32Xj0sAT3eG6x49rt6xQTocvSq952TnoupneY6VYnv9HpfRzG9PSsPSkT5ExAf2Rh3r3rWIohhSgN2ghi1+Ns2EVkgsvo7C8rk10HG/aW0ngEi9RP51PTUj0BUWMCUzJeUxXaattjPXoFIre7mngZe7V2Yr0FktCiSyh4FkdkVZE23/X1WP+lIf2qs0zMxTFnDtokJFlighxj+doIc+8jIxU/LD2DH4r1Iu5deauskJ6Yqiue4CC2+HbLK6Z6iLeCKX7ts2DrkpOdi19L92Dr/JyTdSkH6g0zU+n1T2TXqPtoCVqtV1b4f3EiG5sn2jgh5QfS+6FlyIsKKkeudKrc3fLw1ftmiXDWYYUobXzpBbzUchXe1kwJqvNWQnSBfEyi2iSw3QPp1oPztIJLusOGTdfTr3Ea4yVTYftRtZNp0EmS5bksdN2y2FZ7L36swfwxEZlf1+87fYRffBXuxp8YX2SsJHURm52IfA2qDLLd98u4YxlvYNjHBAgv0ECNQnKCyYv/aw8rnwiO0mNKxsP3YytEbZM+f1/1TC6Tdz5Bc5/yhS5IF22LDNZjfb5nqfX9Zb6x0Sn1YAu5dc46OZ6fl4OeNR3Fs+0mYjGbVazGMr2EniFFLqNkmkT3Ybco65W8HYI/up7eQj7anJ8hmoImcST5LNyfKh0iu4lHEH7B/7MjfDjKdKrUMOYZRA9smJlhggR5ihJoTdGL3WbdnxLct3A0AyEzJlm2VFhehxfnDym3Kzhy4gAaPt3a6b1ijCapFs9FglO2lHhumwepxm7x+H2rJy9Jh2fB1+OzVPvjs1T5YPuI7xdZwDAOwE8SoJ9Rsk8id4EagR4EsdwEAlL9N/rqUD0BC+sOxY628BcWi7zEg3SLVe1aOyFcCmS949S68gSw3bB85UuMh0puCDBs5fZ5xC9smJlhggR5ihJoTZLVa0eRfnRAbLi3Om/+nC/L1RgDAnlU/Kwr5a6duul3PlG/CzxuPYuuC3bh5zrt0PkOeQXEfQxsq94v3FbocPdq90NOlSF37F3t5daaeCR186gQ1GIV3NZMCarzVgJ0gXxNqtonMV6FYyC2rn+NakT1APr09+Q3P1rOm20SsYaPjrLjqPefvUE7LN/zo1byq92E+C5H0cpF3Yn+P2UPKZH0meGHbxAQLLNBDjPLuBBERju04hfFtZmKEdjK2zN2FswddI9vVKyZgQPxIp/Pv+9cdURTGt87f8XpPRoNRVYpfuxd6yu4j4R/tIETpRwpWjdkoGcmPDddgzfjvS319JnhhJ4hRS/m3Tfm2iulZPSCy+oGM+yB0y50FZkG6eM5Yp1ZttnR4OYH+dgn2JEBk9Px6keHmo8JAr/eiBpHeVDb7oCyj+EzwwbaJCRZYoIcY5dkJIiJM7zof1SvaWqjFhmtQPSwB7V/sheTEVGyd/xMWDlqBH2bvQHZatsv9umwdav2+maQgbVWpu8cCO+1eOr4dsgoDa47C5+8OQqO/t0P1iglo9ERbrBi5HlaL+4JxBc8hN0qzsF4B3d8eKLv+5+8OLvX1meCFnSBGLeXaNolciLQ6RYqq2cV29iAI8x1Q3nyInMkQhh0QwlUwk/GAfKG3nBGe78N8BiJ7CERGa4i0BhBJL9nmSa0Fyt/p0Rwi5WN5gZ5a3eO9eAsJvUIUPwaU902p74EJXtg2McECC/QQozw7QSf3SJ83j4vQYs4XSzyaY8fivY4e6dUrJiAuUouav2uKMwc8+yp//fQt1HuspWzP9NiwBEzpNNftPNsW7pYvbBeuKZMU8x7vDZbeQ1gCen3wZamvzwQvvnSCqtYfhfcSJgXUqFqfnSBfU55tk8idKB/xNR5wez8RQWT1KSLw7VH31E/cnj93zKFfa49+S0XibVHxgqJ0is+S2UPmWaIg0jUe7aUkEBkUovgxoLzZpb4HJnhh28QECyzQQ4zy7ARN7TQP8ZGNJUVlwj/aezzP5ePXMbnDHPSrPhxzei/G/etJHt/7+buDZMV50UJvyYmpivPkZdmj+WGuHxuGJ0zyeD8lYcPUHxEbJpHiHqbBxulby2QPTHDCThCjlvJsm0RKNfkIeLZnaeFEwnYGPLMbREZbkG4hSOR6dq/IRGHPcvmidLY+5cqZYmTcJ18kTr/Go/2UFJHRVjblnyzXymQPTHDCtokJFlighxjl2Qka32ambBX2+n9uVerrZyRluq0YXzD2rz3sdr4jm4+jxsNNEBuuQby913nbyj2RmZxV6s8CAPl6oy3NPcwW+Y8Ns0XPP39vMIwGz88tMqEHO0GMWsqzbRLJb8uI2miIrN6lvj4ZNroR50UErlB+/0Rkr0Bv/8BQIJSz+oDI/fEtnzyP5RpE8htFIvn2PeSWzcdrJnhh28QECyzQQ4zy5gQREU7vP49pneeh1wdfSorh+EgtxjSf5vUamclZWDFqPUY1mYL5/Zbh7pX7ktel3EnzWKCf+OmMx2uvn7IF8/svx/51R2AxW7x+Dm8wGozYPHsH+seNQP+4Edg8ewdM+Sb3NzIhjU+doHoj8V6jiQE1qtYbWa7+HQ0Eyp9tMoEMmyCy+kGkxsqnuBs2eL+G+SJEziiIrF72iLprbRUAIP06DwV6ZafidMprX4LInQ6RO8Uvfc7JmgSROwkivRlEZneQcR/3WmfcwraJCRZYoIcY5ckJIiLM7r3YUchNTpzXe6wl7ly+59UaV0/csJ0pD9fYRqQWcRFaHPjuiOR+2sT0kEwLL3p+XPvPjh4VimOYYIWdIGlmzZqFZ555Bg8//DCqVKmCgwcPyl67b98+VKhQwWVcunTJ6br169ejcuXKeOihh1C5cmVs3LjRq/ftb8qVbRJ5EGmfOp3vlqzWntbQY0HssoZ+dZEz5dG2/055B2RJdL3Wel/h3HaRdPus/iV9dIYJaNg2ucJ2KTBhgR5ilCcn6MyBC7JCOP6hxtA82R4T2nyDu1cfeDU/EaHjK1+4nikPS0CdPzaHIc/gcs/xnacRH6l1SbW3pYhrUO+xlrjwy5WSPjrDBDTsBLmyZs0aREZGYsGCBbh48SJ69uyJP/zhD7h9+7bk9QWO0JUrV5CUlOQYVmvhx70jR44gPDwcY8aMwaVLlzBmzBhERETg6NGjXr93f1GebJPInaIgiF+GSP0IIncaSOR5NT9ZU2Qi8jEQGW1k9jS5WJG5Ss5/TqsDEpkleWyGCXjYNjnDdilwYYEeYpQnJ2ha53m2c9EyIv3ghpL9Y3D36gPFNHWpKLouR49jO05heMJENP13Z3SrOhCTOszGvL5L8cOsHcjL0pVoTwwTDPjSCXq77ki8/+nEgBpv11Uv0KtWrYrOnTs7/SwmJgYDB0oXCStwhLKy5GtOaLVa1KhRw+ln8fHxaNKkicf7ChTKk22SLwpni6J7WnldDtItV4yIFz9HTkQQ1nQI/TqI9Ca2/WW0g8gZBpE7AZS/E0Rle3yKYfwB2yZn2C4FLizQQ4zy5ASNbz1TUUCPbja1RPNfP31Lcf5+1YfjxO6zICIk3UrB4DpjHFXX21buiaM//uajJ2WY4IKdIGdMJhPCw8Nd0vx69OiBatWqSd5T4Ag988wzePLJJ/Hxxx9j7969Ttf861//wpQpU5x+NmXKFPz73/9W8aYDg/Jkm0TSG8qF2PTenzsHANItkD3TLpIqQWSPBFlu2q41HoJIq12YYp/RVjINnmFCAbZNhbBdCmxYoPuJp59+2uUMx4ABAxTvISIMHToUTz31FB555BF8+OGHOH/+vKp1y5MTtGvZfkUBPTxhYonmt5gtaPT3dvLnye2p76MaT0GT//eZUyp8bJgGsWEanNp7zkdPyzDBQ6g4QXfv3kVOTo5jGI3S3Q3u37+PChUq4PBh5+4No0ePRlRUlOQ9ly9fxvz583HixAkcOXIEXbp0QcWKFXHgQGHf7MjISKxcudLpvpUrV+Khhx7y+r2zbSo5IqOTG4G+ukTzk/mCm/Pk9jPpOVMK/7toGnzKOyBRNt1AGCaQYNtUSDDZpVCEBbqfePrppzFixAinMxx5ecrn0caNG4c//elP2LBhA86dO4fGjRvjqaeeQm6uZ71QgfLlBJmMZjR6Ql5Ab1+0p8RruPsIUPRcutTPm/67E3IyPP/9MEx5wKdOUJ2ReL/hxIAab9cZKVkoZ+jQoZLPUuAIHTnifCxm1KhRiI6O9vid1KlTB3Xr1nX8OTIyEqtWrXK6ZsWKFXj44Yc9f9HFYNtUcoT5mkIKehTI6l3RUqc1Mvt4WJldJtKe2QVEwgdPyzDBA9umQoLJLoUiLND9xNNPP42pUz1PwSYiPPnkkxg3bpzjZ0ajEY899hjmzp3r8TzlyQkCgMSLd1H7D82LFWTToFvVgT5pB/bgZrJrkTiVo23lnpIF5RimvBIqTpCnEXRvUgmlGDVqFGJiYhx/Lo1UQrZNvkHoV0kL49wJPprf09ZpCiN7iE/2wjDBAtumQoLJLoUiLND9xNNPP40nn3wSjz/+OF599VWMGjUKJpO8oLxx4wYqVKiAkydPOv28Xr16aNWqlcfrljcnCADS7qVjVs9v0fK5bmj3Qi+sGLUeBl1+iecVQmDh4JUlFuixYRpsnL5V1dpEhOM7T2NGtwWY2X0hTvx0RlWP1wc3krF2wvdYMXI9Lv16Ve2jM0yJCBUnSG2RuC5dujj9rHLlyrLFeKRo1KgRPvroI8eftVotatas6XRNjRo1SlSMh22T7yDTKYjMrraibOmNQYbNPunVTWSGSGvgQes094Ms11SubbD1Vc8eApE7CWS5ruJeApmOg/JmgnSLQFbvOqwwjLewbXImWOxSKMIC3U9MmTIF+/fvx5kzZ7BgwQL87W9/Q/v27WWvP3z4MCpUqID79+87/bxjx46Ii4uTvc9oNDp9Rbt79265c4LUcPNsIub3X46pn83FT8sPwGQ0u1yTm5mHqZ3modbvm5VImBdNfx9ce7THe7RarRihmWRrFxfZGPGRjW1F75pOdWplIce6iT+gepit53rBx4XRTady73WmzPClE/RO7ZH4b4OJATXeqe19m7VFixbh4sWL6NWrF/7whz8gMdFWsGvgwIFo2bKl4/qpU6di06ZNuHr1Ks6fP4+BAweiQoUK2LChsMDY4cOHER4ejnHjxuHSpUsYN25cidvZsG0qe4gEyLgPImcoRM4IkPGopJAn80WIjDY+EeaOdHvdUs/3aU2BSP3Yfm9l23n2pCiQfq0Hz2iCyPys8Bx8UjREUnSJz+MzjBrYNjkTLHYpFGGB7kOGDh0qefaj6Dh+/LjkvevXr0eFChWQnp4u+fcFTtCDB85fnDt06ID4+HjVewpFJ2j9lC0u58W1T3VAZnJhsRyrxYpOr/ctcdTcqZhcuAbDEyZ5vM/ti/bIzvXT8gOK91745YrsR4JNM7Z5/e4YRg3sBEkza9YsPP3003jooYdQpUoVp8I6rVu3xocffuj48/jx4/Hcc8/hkUcewV/+8hf897//xdatrpk43333HaKjoxEZGYmYmBgnR6kAtk2BC5G5iHAtMtLbOp0RJ8stiORX7OLWF+K8oGDdGo/3KjJ7yKwfDbImKT9n3jcyHxaiVEfxGcZb2Da54i+7xCjDAt2HpKWl4dKlS4ojP1869frevXuoUKGC7Bcmb9MIOUph487le7Kit+WzXR3RioMbjnosvGs83Njja6V6psvxxf++RmyYRlLoD4gboXjv1M/mIj5S4uNCWAI6vNS7RO+QYTyFnaDAgm1T4GLraS53Rnyo4zqR/ZUKcf6qh9dVBlmlP7y47JOMCutHg3TfKt4vUv4rc2+Mz87lM4w72DYxwQIL9ABhy5YtqFChAm7fvi359wWFeMaPH+/4mclkCvlCPJ6ydOhaRQF97ueLAIA5vRcj/iFl4a15qgN2Ld2PFaPWK589D9c40suF8LxabqfX+8rO2f2dQYr3Dms0EbEyFeUT/iGfpsowvsSnTlCtEfhv/QkBNd6pNSJk/h1l21S6iNT6CgI6BkT59uti3QvutPoQpnMQaZ+6uTba49T0AkjkKO8zb6bycya9LC/Qsz0/78owJYFtExMssED3A0eOHMGUKVNw6tQp3Lx5E2vXrsU///lP1KtXz+m66Ohop+qK48aNw2OPPYaNGzfi3LlzaNq0qV9b2ZzccxaDao5C0391whf/+xo/bwzc8yWzeixSFNMLB60AAKwYuV42vb3275sh8cIdWC1WmIxm1P9zK7cCfdmI71SJcwCY32+Z5B7iIrT4dsgqxXtXj9vk+DBQ/N6hn3KUgikb2AkKTsqDbSKygvSrbEXUUqpBZPUGmS+VaM7SRKS8r5yCbvrVdl26ViZFPBoivQ3IcheAvTCdOyGf/BqE8WdV+yQiiLTaMnuoBDIdU37O9OaQa/nG59CZsoJtExMssED3AydOnMDbb7+Nxx57DI888giio6MxdOhQ6PV6p+sqVKiAxYsXO/5MRBg6dCiefPJJPPzww6hWrRrOnTunam1fOUE/LT/gEH4F6dfVKyZgzfjvSzRvafHzRuXU9WXD1gGwt1WTEbgzuy90zJd0K8VtWntsmAYN/9pGshCdEmn3M9DoiXaIK5KqHhuWgDp/bI7Lx5XP6uWk50LzZHsngR8brkF8ZGNcPu55tV2GKQnsBAUn5cE2iaz+jrPNhQXJXgSZTpRo3tJCZHZ2I9BtRwdIoa0a5e9xzEf61R6ktsdAZH6ueq9k3Gd/r8WEdmoNCKvyxxgyHnVE7p32kfI/kNAr3sswvoJtExMssEAPMXzxj5PZZManf2srcy67CXLSPY+alBVWqxUN/9pGVkzfOn/Hce32RXscFdALKqh3f3sgdDmFTkTavXTEe1hI7tj2k1JbUuTBzWT0jxvh8pGgxsNNcHznacV7719Pwpd1xzoi6V3fGoDT+8+r3gPDeIsvnaB3a47AB/UmBNR4tyY7Qb7GF/83Q+az8ind6Rof7tZ3CMtNeSGd8i6IbN03iKwQWX2LfHSwnwfPGeNU8V0YNnog0AvS5117I7uDjIchUv5XZJ4o20j50H2hOOMBexTe/jvJ7O72HobxJWybmGCBBXqI4Yt/nC4evaooSA+u/8WHO/YdN8/dRp0/NncqnFa9YgIWf+maXpecmIrVYzdifv/lOLL5uKO9GRFhyddrUPN3TT0S59UrqisQV4DVakXTf3dySVePDdMg4R/tYTFb3M6RrzdCl61TvTbDlBR2ghi1+ESg530DpUJqJPJ8uGPfIXQrikWWoyCSKoOKpaHb+oifhMidDJE7DWS+UPh3Itsejfe8BZs374Ms1+Wj8llfeDaHyHGcrWeYsoRtExMssEAPMXzxj9O1kzcVBemRzdLtevzJqb3nMKbZNAxtOB5DG07AgBqjMK7VDJzYfVbVPI5WbR6O+EgtMpIyVe9Xtl2affy88Sj2rPoZu1ccRFZqtur5GaY0YSeIUYtvBPo82XPOIikKRAYf7rjkEFkh9GsgMrtCZHaDyOwEkd4eImc0yHJT1Vy2/uieVnmPgkir692e82YqrFMZwnwNpN8Ayt8NIpNXazBMacG2iQkWWKCHGL74x0kIgWbPdHEtRhaWgLqPtkC+Xn3aXGmRrzeiW9UBLgK35fPdnfqfe4IQApon26sS6AsHrvBq36f2nnMj/Bs7/fe6iT94tQ7DlAY+dYJqjMAHdScE1Hi3BjtBvsYnAt1ySz66m9HBh7stOcJ8DSL5Dde9ZvVy6n/uCWS+6nHU3PGxwnjIu33nTrQJcU/WSX7LUeSOYQIBtk1MsMACPcTwVSGeU3vPoeYjTRw9t+MjtYgN12D/2sM+2qlvGFJnjKzIndDmG1Vz6XL0qsR5nT82h8XiPhVdCkOewTkd34Px6zb1Z90ZpjRgJ4hRi8+quOfNKnJO237WObkqyHLLNxv1AUQGiOQq8qnnhi3q5svfrk6gZ8j3p3e7lvGIirWiIZJfBQl1H8MZprRg28QECyzQQwxftlm7fz0Jc/ssxeBaozG96wLcPJvogx36jpTbqYqCtsbDjVW1QBNCoMFfWqsSzdlp3r/njdO32orD2TMVYov9b9ERF6HF4DpjvF6LYXwJO0GMWnxpm8j0q62ae0YHUN4skDXdBzv0HaRf70ZAd1Q3n/mcOoGeVsv7vRNBZHQodtZd7liBPVqvW+b1egzjS9g2McECC/QQw5dOUKBzbPtJtwLak2JrRVny9RrEhrkKZKlR77GWsFqsJXqGg+t/Qfd3BqH+X1qh61sD0Or57rLrtX+pd4nWYhhf4Usn6L34EahWZ0JAjffi2QnyNaFkm0TOaGUBnd5U1Xy2HuWfengGPQYis2uJ9k9kAuXNgUj9GCL5TYiMzxTWqwyRO75E6zGMr2DbxAQLLNBDjFBygm6dv6MooDtX6at6TovZgkntZzsqwBdEtKWqrS8avNLnzzSt8zzHsYLixejGtpju8/UYxhvYCWLUEkq2iXTfKovo3Fnq57QmQaQ19CiCTsajvn0eIoiUDxVS9jf5dD2G8Ra2TUywwAI9xAglJwgAerw32ElMFx3nfr7o9bzJianYv/YwTu45iyu/XUfz/3RxKpY3oe03qqPznpB44Q5qPNzEKYofG6ZBfKQWV0/c8Pl6DOMN7AQxagkl20QiAyLpJZnCalW8PrNNRCDzGZDhR5D5Eki/ASL5lSLzvwzSu7YV9QWkXy0drU+p5lW/dYYpDdg2McECC/QQI5ScIABIu5eOjq984STM6z7aAod93ApOCIHT+8/j4PpfkJyY6tO5i3Nyz1m0fL6b43maPdMFR7eeKNU1GUYNPnWCYoejWq3xATXeix0eUv+OlgWhZpvIeMS1UFxKLITlvm/XETpQ/h5b27NS7ANPRCDdQojk151S9clyp9TWZBi1sG1iggUW6CFGqDlBgM1xOHvwIrYv2oOzBy+CiPy9pRJDREi8eBe3zt9RVeiOYcoCdoIYtYSmbTKC8neB9OsDqsp8SSDKB5kvgKz3/L0VhnGBbRMTLLBADzFC0QkKdPL1Rlw4chk3z90uFx8PGIadIEYtbJsCD7KmgUy/gaxJ/t4Kw/hBa7ivAAAgAElEQVQEtk1MsMACPcRgJyiw2DDtR9R9tIVTJfZrp276e1sMUyJ86gRVH45qNccH1HivOjtBvoZtU+BAlA+R1a9I+7QoiMwuIMG/Gya4YdvEBAss0EMMdoJKBhHhzuV7SLx4t8Sp5XtWHpTsZ97g8dbISc/10Y4ZpuxhJ4hRC9umkkFktBWGsz4o8VzO4rxIwbeM1iXfKMP4EbZNTLDAAj3EYCfIe07vO4/WUZ87xHTz/5SsOFvHV76Q7KkeG67B+ilbfLhzhilb2Ali1MK2yTtsxdmWOBecS28Kstz2bj5rqoQ4L9IyzXzFx0/AMGUH2yYmWGCBHmKwE+Qddy7fQ81Hmjj1Oy9ob3blt+tezVnjocaS7d/iIxtjcoc5Pn4Chik7fOkEvV99OD6sMT6gxvvsBPkctk3eQfp1Cu3N8tXPZzqm3EM9f1spPAXDlA1sm5hggQV6iMFOkHfM6LYA8ZFaCTGtxehm07yas2irtOJp7itGrffxEzBM2cFOEKMWtk3qISKI1I/kxbRho/o5rfeUBbr5TCk8CcOUDWybmGCBBXqIwU6Qd/R4b7CkmK5eMQHtKvf0as5NM7dJprfX+l1TpN1L9/ETMEzZwU4Qoxa2TeohMiqI6coQOeO8mldkdLBF4YtH5dMacKcRJqhh28QECyzQQwx2grxjdLOpkhH0uAgtBtUc5dWcQgjM7bPEKW3+07+1xYmfOELBBDc+dYI+GYYP48cF1Hj/k2H876iPYdukHiKCSH5TRqBHgXRLvZtXZEGkN3eeL60+t1tjgh62TUywwAI9xGAnyDvOHrwoG0E/+uNvJZo77X4G9q89jF+3nYTZZJa8RgiBswcvYu/qQ0i8cKdE6zFMacNOEKMWtk3eIXKn2dqgFRPnIullkMgs0dxkvgAybAGZTstGzokM+P/t3Xl0FfX9//GQBQS0VCvFpQq2AkFtaanFapU1m8Vq1RBUxJSCClYWxQqucQFcqqhfxaXU8rMqWgVsEXesSAURF9AqKCqFRkjYs0D2+bx+f0ACl9yL3GQm85k7z8c5n9PjdXLnnXvsfb3fmc1UvilT+bJMHWd+wW5kE4KCAT1kaIKa7h8PvRJxY7fstDw9c+cLnu+3cPUGDe8xNuKPAjecNVUV5RWe7xtoCpogxItsahpjauRsvzpyQC/+uUzVu97vu/I1OcU/izit3pQ/yGnwsBbZhKBgQA8ZmqDmKd1SpgVPLdLrf1uobcXbPd9fXV2dhv3oD8pKzWt0av1d+Q96vn+gKdxsgk4fcIv6Zd1p1Tp9AE2Q28im5jG1X8nsfF6m8jUZU9Ui+9t1nfq+R++7ylTM83z/QFOQTQgKBvSQoQkKlmWvLo95an12Wp5Kt5b5XSLQCE0Q4kU2BYtTOjXKjeR2n16/5Xy/ywOiIpsQFAzoIUMT5J662jqtW/WNNhV6d93dvIdfizmgZ7TK1X8/5Xp02IcmCPEim9xjnB0ytV/KOCWe7cPZOir2HeSLT/Fsv0BzkE0ICgb0kKEJcseCpxYp76hLGwblMaddr7UrC13dxxcffKUhe+1j33Vm2wu1s4zr0GEfV5ug/reoX+adVq3T+9MEuY1saj5jauSU3imn6KQ9j0bbfq2MU+7ufnY+J6fohBgDenc5Wy52dX+AW8gmBAUDesjQBO3f58u+1IyJT+rRCU/owwWfRL3ZzdL5H0R93Nr5HYerbJs7jVDZtnKdc+glja49b3heevJgPXLVTFf2BbiNJgjxIptiM6Z21w3ZSqfIKbtfpvbrqNs5pbdHuSa8u5ytI92rpWrxfp69vvsa9KqFru0PcBPZhKBgQA8ZmqDojDF6+KqZDdd2Z6ftulv7zefepdqa2ohtx5x6fcSzy/cemmdPe9GVel548GVlJjfeR/36vytnNKoLsAVNEOJFNkVnnHI5m89vuEt6/Y3Z9n3GuXG27/73MYbmmtWu1ONsvTTGtedd5RSdKLNztiv7AbxANiEoGNBDhiYouqUvfRh9GE7O1QsPvhyx7aD2F0XdNis1T3f9zp07q08f91dl7/VIt32X4ziu7AfwgptN0Bn9CtQ/4w6r1hn9CvgedRnZFJ1TOnnXUfAoN2MztV81bGeql+//qLZLd1Z3Ng2MvZ8tQ13ZB+AVsglBwYAeMjRB0U2+YFr008mTczXq53+M2PaS46+MOaA/fv3TrtSzvyPoFx57uSv7ALxCE4R4kU3ROcW9YgzE6XLK7mvYztSt3/+AXv2eO/XEPIKeLqfkJlf2AXiFbEJQMKCHDE1QdJNybo95tPri466I2HbOffOVkdx4kM9KzdP6r4pcqWd/16DPfeAlV/YBeIUmCPEimxozxsQ4er77dPfSWyO2d7b+PsrwnC5nU6aMceesq+jXoHeTU9RdpmaVK/sAvEI2ISgY0EOGJii6p6fMiXpdeXZanu4d+XDEtnV1dZp2+aMR2w1qd5Hefn6JqzV98cFXGvajPzTsI6f1EP3luqej3rgOsImrTVCfAvUfcIdV64w+NEFuI5uic7ZcGHNINxWRf6w1dZvlbP5t5Hab+sW8qVxTmZ3PySn+6V6PVfuFTOXrru4D8ALZhKBgQA8ZmqDoSreUacjRlyo7LS/ilPWzDh6qwi/WR/2ZwtUbNP+x1/Xm04u0o3SnJ3U5jqPP3v1Cy175SKVbyjzZB+A2miDEi2yKzlS/t3tA33tI7y5n89kypqbx9sbIVC+T2fm0TNVCGVPnTV2mQqbqHZmqpTKm2pN9AG4jmxAUDOghQxMU28Z1mzR16P3KaXOBslIG64azpmrNJ2v9LssV1VU12rCmmOemo0XQBCFeZFNspmqpnC1Ddp1KXvwTOaW3yDiJ8TkZp0ym9n9R/9gAuI1sQlAwoIcMTdC3M8YkzF3SHcfR3259Tmd3GNZwmvw9Ix9WRTmDOrzjZhPU54ybNaD/VKtWnzNu5nvUZWTTtzPGSZhLnIyzTc728XvODCj+hcyOmQnz+8FOZBOCggE9ZGiCwmXmjc9Evdv8pDMn+10aEhhNEOJFNoWHMY6czedGvRv8vs93B9xENiEoGNBDhiYoPCrKKzSoXfRntme0ytWXy9f4XSISFE0Q4kU2hYepeif2I+E2niJjav0uEQmKbEJQMKCHDE1QeHz50ZqYw3lGq1y98vibfpeIBOVqE3T6zRrQb6pVq8/pNEFuI5vCw5T/eT+Pj+sqU+fO40qBfZFNCAoG9JChCQqPzeu3Nn5e+17rvZc/8rtEJCiaIMSLbAoPUzE39hH0oh4yjjdPRQHIJgQFA3rI0ATZ65svN+jzZV+qcmeVa+95/aCpEY+Oq78G/YIfXKa6Wm8evwPQBCFeZJOdjKmTqflMpuZzGePOzVONs0NOca8oR9G7y9k+0ZV9ANGQTQgKBvSQoQmyz/8+/0ZX/GJiwwD9m+9crOfumefK3Wy3FW/X5T+doIxWucpMGayMVrnK7TSC68/hKVeboF/dpAF9p1i1+vzqJr5HXUY22cdUviZn42l7BuhN/WWqlrjz3tXLdg/pXfcM6lsukHHKXHl/IBqyCUHBgB4yNEF2qdhRqbwjRyorNa/RKegv/2WBK/twHEcfvvGxZk97UW8/v0TVVTxvFt6iCUK8yCa7mOrluwfnbnsd4e4mp+gEmdqv3dmHqZCpeFFmx19lqpfxiDV4jmxCUDCghwxNkF1e/suCmNeJD/vRFX6XBzQJTRDiRTbZxdk2Jupj0JyidDmlt/pdHtAkZBOCggE9ZGiC7PLw+JnKaT0k5o3cuE4cQeRmE9T3tJs0sM8Uq1bf02iC3EY22cXZlBH7Rm5bLvK7PKBJyCYEBQN6yAS9CarYUanXn1iopybP1pJ57wd+gJ1z3/yGa8P3XbmdRvhdHtAkNEGIV9CzydQVyex4Qqb8MZmaT/0up9mcrcNjPAotnRu5IbDIJgQFA3rIBLkJWvXeap37vd8po1Vuw53Jh/cYp83rt7ZoHf/99H967JondFf+g/rHQ69oR2nTHwlTsrlUZ7Uf2mhIz0zO1dNT5rhYNdByaIIQryBnk9n51F7Xa+8eardfJWNqW64GY2Sq3pZTcqOckutlKt+QMU3/A7ap/FeMI+jdZKpXuFg50HLIJgQFA3rIBLUJqqmu0eAjRigrdXCjR4ZNzLqtxep46c9vKCN51x8IslLzlJGcqwuOuVzFazdF3X5nWYWWzHtf7774gSrKK6Jus2Lhpzq/4+/3/F7Jubr30kcCf3YAwsvVJujUGzXwjMlWrb6n3hjI71GbBTWbTM1nMU8FNzv+2jI1mDo528fvOcJdf+341pEypjr6z9Stl6l8Vab6vZiPTzM7/iKnqMdev9NJMjuf9/JXATxFNiEoGNBDJqhN0LsvfhDzOu2MVrna/M0Wz2vYvH5r1LutZ6Xm6caz72i0/UszFmhQ+6EN25118FC98td/RX3vmuoaLX3pQy14apE2rCn2+lcBPEUThHgFNZuc0tti3Eytq5xNWS1Sg6mYF/uPBDufitzW1MgpuS7y7uyb+snUfBb9vZ1tMhXzZSpfkXHKW+LXATxDNiEoGNBDJqhN0CuPv7nfAf2rFf/1vIa5D7wU83rxzJTB2lm25wj5ioWfRq81OVf/eWeV57UeiB2lOzV72ou64aypmnzhfVoy730ecwNX0AQhXkHNJmf7uBjXaneVU/zzlqlh64gYNXSTsyU3ctuy+/Z5dNruo+7FvWWcpl+u5SZTu05O6Z1yto6UU1ogU/O53yUhQZBNCAoG9JAJahO05pO1MYfz3xxysSp3Vnlew6ypc6MeQa9f2zeVNGx7a+49ykprvG12Wp4mXzjN81q/zbaNJRr2oz8oM3lww1kAGa1ydd+oxxjS0WxuNkH9TrlRGb+abNXqdwpNkNuCmk27TgPfd+Dtumtg3toyN/p0tlwY+47rm3+9p1ZTK6f4Z/s52u7/fU9M1VI5RSfudVZCupyi7jIV8/0uDQmAbEJQMKCHTFCbIEm66Zy7oh7Bfur22S2y/1XvrY5+9Dx5sH5/wriIwfaynhNiDvJXnHxti9S7Pw+M/nPMPzasWBj8OxDDXzRBiFdQs8k4JXI2nrrPae67bhZnqj9omRrKp8e+43rpnsuvjFMSe5Av6iGn7P4WqTcWYxw5m/pF+YNHNznFP7XmCD+Ci2xCUDCgh0xQmyBJqqqo0kNjHtev216kjFa5Ou/w4XruT/9ssSO+xhjdcv6fGo461x95zkwerKXzIxuxKRfd33Cn+X2PoN/9u4dapN79+e2h+VGH8+y0IXrwyr/4XR4CjiYI8QpyNpnadbtPM+/WcNTaVC1quf072+Rs7LPPHwnS5Ww8RaauaM92pk5Oce/YR9ArXmyxmqPZ3w33nKKuMpULfK0PwUc2ISgY0EMmyE1QverKam0t2ubLXc5ra2r1zB1zNbTLaJ118FBdM+AWrXir8RHnz5d92fhof/KugX71h1+3eN37OuuQi2MO6Pdd9qjf5SHgXG2Cet+gjNNut2r1631D4L9HbZMI2WScchlnqy+XCZm6jXJKbpJTfLKc4l5ytk+UqS1svF35Y9GPtG88PeYd31uKqV7xLQP6K77Wh+AjmxAUDOghkwhNUFAsmrNU539/z+PTcjuN0OJ/LPO7LEnS7UPujXqEP6NVrt554T2/y0PA0QQhXmRTyzDGkVN2z+7rvOuvU/+tTO1//S5NxlTLKf5FzFPwjbPN7xIRcGQTgoIBPWRoglpWbU2tPlvyuT579wurnmv+v8+/0TnfvSTiRnaZKYN1zcBbVFdnT50IJpogxItsalnGKZGpXiZT+6XfpUQwFf/Y6+ZwXRuurTflj/ldGhIA2YSgYEAPGZog1Fv/VZGmXfqILuo8SiNPukp/v/sfqq709xRHJAZXm6Bf3KCMU2+3avX7BU2Q28gm1DNVS3Zd07/xDDlbhspUvup3SUgQZBOCggE9ZGiCAHiNJgjxIpsAeI1sQlAwoIcMTRAAr9EEIV5kEwCvkU0ICgb0kKEJAuA1N5ug/idfr8xf3mbV6n/y9XyPuoxsAuA1sglBwYAeMjRBALxGE4R4kU0AvEY2ISgY0EOGJgiA12iCEC+yCYDXyCYEBQN6yNAENbajZIdmTHxSF/zgMp13+HDdecn/qXD1Br/LAgLL1Sbo59cp85RbrVr9f34d36MuI5saM7Vfytl+1a5ng2/sI6dsmoyzw++ygMAimxAUDOghQxMUqaqiSpf1nKCs1D3PA89Oy9M5371E33zJkA40BU0Q4kU2RTI1q+UU/2Sv54Hvfib4llwZw+MwgaYgmxAUDOghQxMU6eW/LGgYzPde2Wl5+tPwh/wuDwgkmiDEi2yK5Gwbs89wvmeZihf9Lg8IJLIJQcGAHjI0QZEmXzBNWSmDow7puZ1G+F0eEEiuNkG9rlPmL261avXvRRPkNrIpklP806jDuVOULqdkkt/lAYFENiEoGNBDhiYo0t3DH1J2Wl7UAX3ocaNd3deGNcWa+8BLmnPffK5xR0KjCUK8yKZITvEpsQf00gLX9mOMkan+QGbHDJmdz8k4Ja69N2AbsglBwYAeMjRBkZa98lHU4TwrNU8zb3zGtf387dbnlJGcq8yUwcrcfcR+xsQnZYxxbR+ALWiCEC+yKZJTOmXXNefRTnGvXubKPoypkLP1d3uuby/qKqfoJJnKBa68P2AbsglBwYAeMjRBkYwxmnbZIw3XndffLO6Kk6/VzrIKV/YR648AGa1ytWj2u67sA7CJm03QgJ9NUtbJt1i1BvxsEt+jLiObIhmnRM7mQXsNz7uvRy+d7NofdqP/EaCbnKITZOo2u7IPwCZkE4KCAT1kaIIaM8bog9dX6J4RD2vq0Pv1+hMLVV1V49r733Le3RF3id/7KP3ErNtc2w9gC5ogxItsasyYSpmdz8nZfrWckhtkqt51bTg3xpFT3DPGafTdZHb81ZX9ADYhmxAUDOghQxPU8sacen3MI+gjTrrK7/IA19EEIV5kU8sypjLGcN5VTlEPOWV3+10i4DqyCUHBgB4yYWiCqiurteKtT7Vi4aeuHglvqofHz4x6BD07LU/3jnzY7/IA17naBP10krJ+XmDVGvBTmiC3hSGbjLNVpuodmZrPfL//iDFGzqbM3ae0R7nOvfJlX+sDvEA2ISgY0EMm0ZugN2f9W789NL9hCD73e7/TwueW+FrThq+LddbBQyOG9KyUwTqz7YVau7LQ19oAL9AEIV6JnE3G1O2+3nuv55pv+rVM7Vf+1lXxYvS7xG/KljH+/3EbcBvZhKBgQA+ZRG6CPlvyuTKTGz/TPDNlsD5/399G6IsPvtKYU69rqGn0ydfq08Wf+1oT4BWaIMQrkbPJlE+PPghvPE3GVPlbW8VcORvP2HMzum1XcoM4JCyyCUHBgB4yidwE3T5kWtRnmmen5emu/Aeb/L411TVa8NQi3XHxA/rT8Ola+tKHTT49cfumEm3byHNmkdhcbYJ6TlRWr5utWgN6TkzY71G/JGo2GVMnp/jkmNd7m4p5TX9vZ6tM+Z/lbB8np3SKTM0XTazRkakrknHKm1wLEARkE4KCAT1kErUJkqRLf3J1zJux/aH3xCa9Z+XOKo07/YaGu67X/wHgjosfkOM4Lv8GQGKgCUK8EjWbjLP9W27G9kDT3rf2SznFvXdfQ17/GLZuMjvnuPwbAImDbEJQMKCHTKI2QZJ02+B7Yh5Bv+PipjVBs6bOVWZK49PmM1rl6t9zl7r8GwCJgSYI8UrUbDKmVk5xr/0cQX+hSe/rbLkw8pr2vYZ+42x1+bcAEgPZhKBgQA8ZG5ug0q1leuSqmcrtNEK/PSxfd1z8gApXb4j7ff7z75XKSG48SGcmD9bKpaubVNvvTxgfdTjPSs3T7UPubdJ7AonO1SboxxOV9dObrVoDfkwT5DYbs8nUrJKz7Q+7BuyNv5JTdq+MsyPu93HKHohyt/R0ORt/KWMq46+rbvN+jsp3ldn5XNzvCYQB2YSgYEAPGduaoIodlfr9CeMi73CemqdzDr1E678qivv9Xn9ioX7znYsb3uuc716iN59e1OT6hh43Ovpp88m5uvE3dzT5fYFERhOEeNmWTabmMzlFJ+1zlLq7nC25cd/h3JhaOSUFu09Fr7+Le2bTrxmvLdzPgN5NZsffmvS+QKIjmxAUDOghY1sT9M/pr0Y96p2dlqd7RjTtGeGVO6v0/msr9MHrK1RV0bw75D5wxQxlRTltPjN5sF74P54TC0RDE4R42ZZNzrbLY5xC3lWm4qUmvaep2yhT+S+Z6hXNeg66MY6cTf1jP8Pc58e3AbYimxAUDOghY1sTVHDe3VEfjZbRKlcX/OAyv8vTxnWbdO73fhdxbXtWap6G9xinivIKv8sDrORmEzTwpGuV3fMmq9bAk6616ns0EdiWTU7Rj2McoU6XU3Kj3+XJVL6+e0BPbzhy7hR1lVNyg9+lAdYimxAUDOghY1sTdMewByJOb9975Xcb43d5kqQNa4p1z4iHdX7H4Rpy9KV6dMITKt1a5ndZgLVoghAv27Ip9qPR0uWUTvG7PEmSqXpXztZL5BT/XM6mHJkdT8oYni4CxEI2ISgY0EPGtiZo6fwPog7nmSmD9dTts/0uD0AT0AQhXrZlk1N6e+xT3KtX+F0egCYgmxAUDOghY1sTZIzRvZc+0nDdef3R9LG/ukGVO5t3/TgAf7jaBJ34R2X/5Ear1sAT/2jV92gisC6bnBI5mwftOWpeP6yX3eN3aQCaiGxCUDCgh4xtTZC0a0j/8I2Pdd9lj+qu/Af1r2feUW1Nrd9lAWgimqDopk+fri5duqhNmzbq1auXFi2K/YSJOXPmKCMjQ4cffrgOOeQQ/fKXv9Srr74asc3MmTOVlJTUaFVWxv/oLr/ZmU1VMjtny9l+jZzSApnqD/wuCUAzkE2NkUt2YkAPGRubIACJhSaosWeffVZpaWmaMWOGVq5cqXHjxql9+/Zat25d1O3HjRunu+66S8uWLdPq1at13XXXKS0tTR999FHDNjNnztR3vvMdFRUVRawgIpsAeI1sikQu2YsBPWRoggB4zdUm6IRrlP3jG6xaA0+4Ju7fr3fv3ho1alTEa+np6Zo0adIBv8cJJ5ygW2+9teGfZ86cqQ4dOhzwz9uMbALgNbIpErlkLwb0kKEJAuA1mqBI1dXVSklJ0dy5cyNeHzt2rPr06XNA7+E4jo455hg9+OCDDa/NnDlTKSkpOvbYY3X00Udr0KBBEUcygoRsAuA1smkPcsluDOghQxMEwGthaYIKCwtVWlrasKqqot/Ycv369UpKStLixYsjXp8yZYq6det2QJ/H3XffrcMOO0wbN25seO3dd9/Vk08+qRUrVmjRokU6//zz1bZtW61evbrJn7tfyCYAXiOb9iCX7MaAHjI0QQC85moT1GOCsk+63qo1sMeEqDfBKSgoiPq71DdCS5YsiXh98uTJ6t69+7d+FrNmzVK7du30xhtv7Hc7x3HUs2dPjRkz5oA/Z1uQTQC8RjbtQS7ZjQE9ZGiCAHgtLE3QgR5Bb86phM8++6zatm2r+fPnH9DnNnLkSOXk5BzYh2wRsgmA18imPcgluzGghwxNEACvhaUJivcmcaNHj454rUePHvu9Gc+sWbN00EEH6YUXXjigfRhjdPLJJ2v48OEHXJctyCYAXiObIpFL9mJADxmaIABec7UJ6j5B2Sdcb9Ua2D3+Ab3+cTaPP/64Vq5cqfHjx6t9+/Zau3atJGnSpEkaNmxYw/azZs1Samqqpk+fHvGompKSkoZtbrnlFr366qv6+uuvtXz5cg0fPlypqal67733mvy5+4VsAuA1sikSuWQvBvSQoQkC4DWaoOimT5+uzp07q3Xr1urVq5fefvvthn+Xn5+vvn37Nvxz3759o15LmJ+f37DN+PHjdeyxx6p169bq2LGjsrKyGl1PGBRkEwCvkU2NkUt2YkAPGZogAF6jCUK8yCYAXiObEBQM6CFDEwTAa242QRndrlZOj+usWhndruZ71GVkEwCvkU0ICgb0kKEJAuA1miDEi2wC4DWyCUHBgB4yNEEAvEYThHiRTQC8RjYhKBjQffDWW29FvclCUlKSli1bFvPn8vPzG21/yimnxLVvmiAAXnO1Cep6lXLSJ1m1MrpelZDfo2QTgERGNiEoGNB9UF1dHfF4gqKiIo0cOVJdunSRMSbmz+Xn5ysnJyfi57Zu3RrXvmmCAHiNJiiYyCYAiYxsQlAwoFugpqZG3//+93Xbbbftd7v8/Hydc845zdoXTRAAr9EEJQayCUAiIZsQFAzoFpg9e7aSk5P1v//9b7/b5efnq0OHDurYsaO6du2qkSNHauPGjXHtiyYIgNdcbYJ+NF453SZatTJ+ND4U36NkE4BEQjYhKBjQLXDmmWfqzDPP/Nbtnn32Wc2fP1//+c9/NG/ePPXs2VMnnniiqqqqYv5MVVWVSktLG1ZhYSH/5wXgKZqgxEA2AUgkZBOCggHdRQUFBTFvsFO/3n///YifKSwsVHJysmbPnh33/jZs2KC0tDTNmTMn7pr4Py8Ar9AE2YVsAgCyCcHBgO6izZs3a9WqVftdlZWVET9z2223qWPHjqqpqWnSPo8//njdeeedMf89RykAtDRXm6AfjlNO12utWhk/HBeo71GyCQDIJgQHA7qPjDE67rjjNGHChCb9/JYtW9SmTRs98cQTB/wzXOcHwGs0QcFGNgFIRGQTgoIB3UcLFixQUlKSVq5cGfXfd+/eXXPnzpUklZeXa8KECVqyZIn++9//6q233tKpp56qo48+WmVlZQe8T5ogAF6jCQo2sglAIiKbEBQM6D668MILddppp8X890lJSZo5c6YkqaKiQllZWerYsaPS0tJ07LHHKj8//1vvrrsvmiAAXnO3CRqrnOP/aNXK+OHYhP4eJZsAJCKyCUHBgB4yNEEAvEYThHiRTQC8RjYhKBjQQzaTNegAABe9SURBVMbWJqiivEL/7+ZndfEPr9DgI0borvwHVfjFer/LAtAENEGIl63ZZGrXytk+Uc7GU+Vs7Cen7D4Zp9zvsgA0AdmEoGBADxkbm6Ca6hpdecokZaUMVkarXGW0ylV2Wp7O7jBM//v8G7/LAxAnV5ug48Yo50fXWLUyjhtj3fdo0NmYTaZ2rZziXnKK0uUUdd29usvZfK6Mqfa7PABxIpsQFAzoIWNjE7TgqUUNg/neKys1T1OH3u93eQDiRBOEeNmYTc72a/cZzvcsUzHX7/IAxIlsQlAwoIeMjU3QXfkPKjstL+qQ/ttD8/0uD0CcaIIQLxuzySnuHXU4d4rS5Wy/2u/yAMSJbEJQMKCHjI1N0H2XParstCFRB/TBR4z0u7z9WjRnqS7/2TXKSs3TkKMv1dNT5qi2ptbvsgBfudoEdb5SOcdNsGpldL7Suu/RoLMxm5yNZ8Qe0Euu87u8mIypkSl/WM7GX+2qdfPZMpWv+V0W4DuyCUHBgB4yNjZBHy74JOYp7o9OeMLv8mJ67f+9pYxWucpM3nPtfGbyYN1x8QN+lwb4iiYI8bIxm5yyu3ddcx7tFPeqf/tdXkzO9qvkFHXbq95uu0/Lf8Hv0gBfkU0ICgb0kLGxCTLG6P7RjzXcHC4zZbAyknM18qSrVLbNzrvl1tXWafCRI6P+YSGjVa7++2l8zwAGEglNEOJlZTY5ZXI2n7Xn5nD116OXXC9jjN/lRWVqvohx1L+rnI2nyZg6v0sEfEM2ISgY0EPGxiZI2jWkv//aCt09/CHdPuRezX/sdVXurPK7rJgKV2+IOZxnJOfqn9Nf9btEwDeuNkHHXqGcLldZtTKOvcLK79EgszebKmV2/l3O9rFytl8rU/W2tcO5JJkdT+5z9HyfI/+1a/0uEfAN2YSgYEAPGVuboKDZsmFb7AG9Va4WPLXI7xIB39AEIV5kkztMxQuxj6AXdZWp2+x3iYBvyCYEBQN6yNAEuWdC/wJlpeY1Ono+qP1Q7Sjd6Xd5gG9oghAvsskdximTU/TjKEfR0+VsHeZ3eYCvyCYEBQN6yNAEuWf9V0UacvSlykjOVXbrIcpKzVN26yF654X3/C4N8JWrTdAxo5XTebxVK+OY0XyPuoxsco+pfE1OUY/d18332H39+a9katf5XRrgK7IJQcGAHjI0Qe6qKK/Qi4++rvtHPaYnb3teG9dt8rskwHc0QYgX2eQuU7depvwhOSU3y+x8RsbZ4XdJgO/IJgQFA3rI0AS1nEWz39XY065Xbqff66o+N2nJvPf9LgloETRBiBfZ1DKMqZYpf1TOpiw5G0+Vs/1qmZrVfpcFtAiyCUHBgB4yNEEt47k//XPXs9xTBkf877yHubs7Ep+rTdDRo5RzzDirVsbRo/gedRnZ5D1jHDlbf7fP9enpcop+LFPzmd/lAZ4jmxAUDOghQxPkvfLtO3TmQRdEvbv7b75zsdWPjwPcQBOEeJFN3jOV/4pxd/d0OVtH+l0e4DmyCUHBgB4yNEHeWzr/g/0+gm3FW5/6XSLgKZogxIts8p5Tevuem8ZFGdJtfr474AayCUHBgB4yNEHe+/CNj/c7oH/27hd+lwh4ytUm6KjLlfODsVatjKMu53vUZWST95yyu3ef0h5tQP+J3+UBniObEBQM6CFDE+S9muoanXf4cGUmRw7mmSmDdcExl6uurs7vEgFP0QQhXmST90zNJ7FPcd8+ye/yAM+RTQgKBvSQoQlqGUvnf6DstCHKSstTRnKuslLzdOZBF+ijNz/xuzTAczRBiBfZ1DJ2HUWvvzlct11rU3+ZOh4RisRHNiEoGNBDhiao5RSu3qDHrnlCBefdrRkTn9SGNcV+lwS0CFeboCMvV87RY6xaGUfSBLmNbGoZxhiZqnfllEySs+1KmR1PyDjlfpcFtAiyCUHBgB4yNEEAvEYThHiRTQC8RjYhKBjQQ4YmCIDXaIIQL7IJgNfIJgQFA3rI0AQB8JqrTdARlynnqCutWhlHXMb3qMvIJgBeI5sQFAzoIUMTBMBrNEGIF9kEwGtkE4KCAT1kaIIAeI0mCPEimwB4jWxCUDCghwxNEACvudoEfX+kco64wqqV8f2RfI+6jGwC4DWyCUHBgB4yNEEAvEYThHiRTQC8RjYhKBjQQ4YmCIDXaIIQL7IJgNfIJgQFA3rI0AQB8JqrTVDHEcrpNNqqldFxBN+jLiObAHiNbEJQMKCHDE0QAK/RBCFeZBMAr5FNCAoG9JChCQLgNZogxItsAuA1sglBwYAeMjRBALzmahN0+O+V8/1RVq2Mw3/P96jLyCYAXiObEBQM6CFDEwTAazRBiBfZBMBrZBOCggE9ZGiCAHiNJgjxIpsAeI1sQlAwoIcMTRAAr7naBB02XDmHX27VyjhsON+jLiObAHiNbEJQMKCHDE0QAK/RBCFeZBMAr5FNCAoG9JChCQLgNZogxItsAuA1sglBwYAeMjRB0mfvfqEpF96nUb3+qCkX3qfP3v3C75KAhOJmEzTw0Hxlf+9Sq9bAQ/ND/z3qtrBnkzGOTMU/5WzNl7P5t3JK75Cp2+B3WUBCIZsQFAzoIRP2JujNpxcpM3mwstPylNEqV9lpecpMHqw3Z/3b79KAhEEThHiFOZuMMXK2T5JT1FVOUffd/5sup/hkmdqv/S4PSBhkE4KCAT1kwtwEVVdW65zvXqKMVrmN1jmHXqLqymq/SwQSAk0Q4hXmbDLVH+4eyvdd6XK2jfa7PCBhkE0ICgb0kAlzE/Thgk+iDuf166M3P/G7RCAhuNoEffcSZR860qo18LuXhPZ71Cthzian7O5dw3iMId0Yx+8SgYRANiEoGNBDJsxNEAM60DJoghCvMGcTAzrQMsgmBAUDesiEuQniFHegZdAEIV5hziZOcQdaBtmEoGBAD5kwN0ESN4kDWoKrTVCHYcr+7gir1sAOw0L9PeqFMGfTrpvEXcdN4gCPkU0ICgb0kAlzE1SPx6wB3qIJQrzCnk27HrM2b6/HrN3JY9YAl5FNCAoG9JAJexMEwHs0QYgX2QTAa2QTgoIBPWRoggB4zdUm6JChyv7OcKvWwEOG8j3qMrIJgNfIJgQFA3rI0AQB8BpNEOJFNgHwGtmEoGBADxmaIABeowlCvMgmAF4jmxAUDOghQxMEwGuuNkEHX6TsQ35n1Rp48EV8j7qMbALgNbIJQcGAHjI0QQC8RhOEeJFNALxGNiEoGNBDhiYIgNdoghAvsgmA18gmBAUDesjQBAHwmptN0IB2Fyir/SVWrQHtLuB71GVkEwCvkU0ICgb0kKEJAuA1miDEi2wC4DWyCUHBgB4yNEEAvEYThHiRTQC8RjYhKBjQQ4YmCIDXXG2C2g5RVrthVq0BbYfwPeoysgmA18gmBAUDesjQBAHwGk0Q4kU2AfAa2YSgYEAPGZogAF6jCUK8yCYAXiObEBQM6CFDEwTAa642QW3ylHXQxVatAW3y+B51GdkEwGtkE4KCAT1kaIIAeI0mCPEimwB4jWxCUDCghwxNEACv0QQhXmQTAK+RTQgKBvSQoQkC4DVXm6DWg5XV5iKr1oDWg/kedRnZBMBrZBOCggE9ZGiCAHiNJgjxIpsAeI1sQlAwoIcMTRAAr9EEIV5kEwCvkU0ICgb0kKEJAuA1N5ug/qm5yky70KrVPzWX71GXkU0AvEY2ISgY0EOGJgiA12iCEC+yCYDXyCYEBQN6yNAEAfAaTRDiRTYB8BrZhKBgQA8ZmiAAXnO1CUo5T5mpQ6xa/VPO43vUZWQTAK+RTQgKBvSQoQkC4DWaIMSLbALgNbIJQcGAHjI0QQC8RhOEeJFNALxGNiEoGNBDhiYIgNfcbIL6tTpXGcl5Vq1+rc7le9RlZBMAr5FNCAoG9JChCQLgNZogxItsAuA1sglBwYAeMjRBALxGExTd9OnT1aVLF7Vp00a9evXSokWL9rv9woUL1atXL7Vp00bHHXecHnnkkUbbzJ49Wz169FDr1q3Vo0cPzZ07N66abEE2AfAa2dQYuWQnBvSQoQkC4DVXm6Ckc5TRKteq1S/pnLh/v2effVZpaWmaMWOGVq5cqXHjxql9+/Zat25d1O3XrFmjdu3aady4cVq5cqVmzJihtLQ0zZ49u2GbJUuWKCUlRVOnTtWqVas0depUpaamaunSpU3+3P1CNgHwGtkUiVyyFwN6yNAEAfAaTVBjvXv31qhRoyJeS09P16RJk6Juf+211yo9PT3itcsvv1y//OUvG/45Ly9POTk5EdtkZ2frggsuOOC6bEE2AfAa2RSJXLIXA3rIlJSUKCkpSYWFhSotLWWxWCzXV2FhoZKSklRSUtLk76rS0l1N0OlJv1a/pHOsWqcn/Trq92hVVVXU36W6ulopKSmNTvMbO3as+vTpE/VnzjjjDI0dOzbitblz5yo1NVU1NTWSpGOOOUbTpk2L2GbatGk69thjm/qx+4ZsYrFYXi+yaQ9yyW4M6CFT/+XEYrFYXq/CwsImf1dVVlbqiCOO8P13iLUOPvjgRq8VFBRE/V3Wr1+vpKQkLV68OOL1KVOmqFu3blF/pmvXrpoyZUrEa4sXL1ZSUpI2bNggSUpLS9PTTz8dsc3TTz+t1q1bN/FT9w/ZxGKxWmqRTeSS7RjQQ8ZxHBUWFqqkpKTRXxQ5ctG8v8jy+fH58fntWiUlJSosLJTjOM36vqqsrPT9d9nf77jva7GOoNc3QkuWLIl4ffLkyerevXvUn+nataumTp0a8do777yjpKQkFRUVSdrVCM2aNStim6eeekpt2rRp6kfuG7LJ/cXnx+fH5xe5yKY9yCW7MaBDpaVc+9ccfH7Nw+fXPHx+9uNUwqbhv+3m4fNrHj6/5uHzsxu5ZDcGdPAl2kx8fs3D59c8fH7B0Lt3b40ePTritR49euz3Zjw9evSIeG3UqFGNbsZz5plnRmyTk5OTMDfj4b/t5uHzax4+v+bh87MfuWQvBnTwJdpMfH7Nw+fXPHx+wVD/OJvHH39cK1eu1Pjx49W+fXutXbtWkjRp0iQNGzasYfv6x9lcddVVWrlypR5//PFGj7NZvHixUlJSdOedd2rVqlW68847E+pxNvy33Tx8fs3D59c8fH72I5fsxYAOVVVVqaCgIOb1k9g/Pr/m4fNrHj6/4Jg+fbo6d+6s1q1bq1evXnr77bcb/l1+fr769u0bsf3ChQv1s5/9TK1bt1aXLl30yCOPNHrP559/Xt27d1daWprS09M1Z84cr3+NFsN/283D59c8fH7Nw+cXDOSSnRjQAQAAAACwAAM6AAAAAAAWYEAHAAAAAMACDOgAAAAAAFiAAR0AAAAAAAswoIfc5MmTdeqpp6pt27bq0KFD1G3WrVuns846S+3atdP3vvc9jRkzRtXV1S1caTB07txZSUlJEWvixIl+l2W16dOnq0uXLmrTpo169eqlRYsW+V1SIBQUFDT6b61Tp05+lwW4gmxyF9kUH3Kp6cgmoPkY0EPu5ptv1rRp03T11VdHbYLq6up00kknqX///vroo4/0xhtv6KijjtKVV17pQ7X269y5s2677TYVFRU1rPLycr/Lslb9MzhnzJihlStXaty4cWrfvr3WrVvnd2nWKygo0Iknnhjx39qmTZv8LgtwBdnkLrLpwJFLzUM2Ac3HgA5J0syZM6M2QS+//LKSk5O1fv36hteeeeYZtWnTRqWlpS1ZYiB07txZ9913n99lBEbv3r01atSoiNfS09M1adIknyoKjoKCAvXs2dPvMgBPkU3uIJsOHLnUPGQT0HwM6JAUuwm66aab9JOf/CTitW3btikpKUn/+te/Wqq8wOjcubOOOOIIHXbYYerZs6cmT57MKZcxVFdXKyUlRXPnzo14fezYserTp49PVQVHQUGB2rVrpyOPPFJdunTRkCFD9PXXX/tdFuAqsskdZNOBIZeaj2wCmo8BHZJiN0GXXnqpMjMzG73eunVrzZo1qyVKC5Rp06Zp4cKF+vjjjzVjxgwdfvjhGjFihN9lWWn9+vVKSkrS4sWLI16fMmWKunXr5lNVwfHyyy9r9uzZ+uSTT/TGG2+ob9++6tSpk7Zs2eJ3aYBryCZ3kE0HhlxqPrIJaD4G9AQU7QYd+673338/4mf21wRlZWU1ej0tLU3PPPOMZ7+DTZryedabPXu2kpKSCKYo6huhJUuWRLw+efJkde/e3aeqgmvHjh3q1KmT7r33Xr9LAaIim9xFNrmPXHIf2QTEjwE9AW3evFmrVq3a76qsrIz4GU4jjK0pn2e9b775RklJSVq6dGkLV20/TiV0X0ZGRqNrJwFbkE3uIpvcRy55g2wC4sOADknffiOeDRs2NLz27LPPciOeA/Tiiy8qKSmJu7/G0Lt3b40ePTritR49enAzniaoqqrS0UcfrVtvvdXvUgDXkE3eIJtiI5fcRTYB8WNAD7l169Zp+fLluvXWW3XwwQdr+fLlWr58ecPjV+ofZTNw4EB99NFHWrBggX7wgx/wKJsolixZomnTpmn58uVas2aN/v73v+uoo47S2Wef7Xdp1qp/nM3jjz+ulStXavz48Wrfvr3Wrl3rd2nWmzBhghYuXKg1a9Zo6dKlOuuss3TIIYfw2SEhkE3uIZviQy41D9kENB8Desjl5+dHvW7trbfeathm3bp1GjRokNq2bavDDjtMV155paqqqvwr2lIffvihTjnlFHXo0EEHHXSQunfvroKCAu3cudPv0qw2ffp0de7cWa1bt1avXr309ttv+11SIAwZMkRHHnmk0tLSdNRRR+m8887TZ5995ndZgCvIJveQTfEjl5qObAKajwEdAAAAAAALMKADAAAAAGABBnQAAAAAACzAgA4AAAAAgAUY0AEAAAAAsAADOgAAAAAAFmBABwAAAADAAgzoAAAAAABYgAEdAAAAAAALMKADAAAAAGABBnQAAAAAACzAgA6gkU2bNqlTp06aMmVKw2tLly5VWlqaXnvtNR8rAwCEFdkEIAwY0AFE9dJLLyktLU3vv/++ysvLdfzxx2vcuHF+lwUACDGyCUCiY0AHENMVV1yhbt26aejQoTrppJNUWVnpd0kAgJAjmwAkMgZ0ADFVVFTohz/8odLS0vTxxx/7XQ4AAGQTgITGgA4gpk8//VQHHXSQUlJSNG/ePL/LAQCAbAKQ0BjQAURVXV2tnj17Kj8/X3fccYc6duyo4uJiv8sCAIQY2QQg0TGgA4jqmmuuUZcuXVRaWirHcdSnTx8NGjTI77IAACFGNgFIdAzoABp56623lJqaqn//+98Nr61bt04dOnTQww8/7GNlAICwIpsAhAEDOgAAAAAAFmBABwAAAADAAgzoAAAAAABYgAEdAAAAAAALMKADAAAAAGABBnQAAAAAACzAgA4AAAAAgAUY0AEAAAAAsAADOgAAAAAAFmBABwAAAADAAgzoAAAAAABYgAEdAAAAAAALMKADAAAAAGABBnQAAAAAACzAgA4AAAAAgAUY0AEAAAAAsAADOgAAAAAAFmBABwAAAADAAgzoAAAAAABYgAEdAAAAAAALMKADAAAAAGABBnQAAAAAACzAgA4AAAAAgAUY0AEAAAAAsAADOgAAAAAAFmBABwAAAADAAgzoAAAAAABYgAEdAAAAAAALMKADAAAAAGABBnQAAAAAACzAgA4AAAAAgAUY0AEAAAAAsAADOgAAAAAAFmBABwAAAADAAgzoAAAAAABYgAEdAAAAAAALMKADAAAAAGABBnQAAAAAACzAgA4AAAAAgAUY0AEAAAAAsAADOgAAAAAAFmBABwAAAADAAgzoAAAAAABYgAEdAAAAAAALMKADAAAAAGABBnQAAAAAACzAgA4AAAAAgAUY0AEAAAAAsAADOgAAAAAAFmBABwAAAADAAgzoAAAAAABYgAEdAAAAAAALMKADAAAAAGABBnQAAAAAACzAgA4AAAAAgAUY0AEAAAAAsAADOgAAAAAAFmBABwAAAADAAgzoAAAAAABYgAEdAAAAAAALMKADAAAAAGABBnQAAAAAACzAgA4AAAAAgAUY0AEAAAAAsAADOgAAAAAAFmBABwAAAADAAgzoAAAAAABYgAEdAAAAAAALMKADAAAAAGABBnQAAAAAACzw/wFNVcqXKoAIjQAAAABJRU5ErkJggg==\" width=\"1000\">"
+ ],
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "fig, ax = plt.subplots(figsize=(10, 10), ncols=2)\n",
+ "data.plot.scatter(x=\"x\", y=\"y\", c=\"guess\", colormap='viridis', ax=ax[0])\n",
+ "data.plot.scatter(x=\"x\", y=\"y\", c=\"source\", colormap='viridis', ax=ax[1])\n",
+ "ax[0].set(xlabel=\"x\", ylabel=r\"y\", title=\"Guessed source\")\n",
+ "ax[1].set(xlabel=\"x\", ylabel=r\"y\", title=\"True association\")\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "9b1363ec",
+ "metadata": {},
+ "source": [
+ "Note that if the sample clusters were not \"blobs\" of data, but were in concentric circles, the assumption of this method would be false and the method would simply not work well. This is why it is important to understand the underlying assumptions made in the method."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "7076f779",
+ "metadata": {},
+ "source": [
+ "## K-Means\n",
+ "\n",
+ "Another common method used for clustering is the K-Means, on which one simply tries to find the cluster centers which minimize in-cluster distances (in an Euclidean sense) while maximizing distances between the centers. It can be shown that this method is a special case of the Gaussian Mixture Model when the covariance matrices are diagonal, which would mean that within each blob, there is no correlation between the variables (see https://en.wikipedia.org/wiki/K-means_clustering#Gaussian_mixture_model and references).\n",
+ "\n",
+ "While this is an approximation of the GMM model, it is still a very useful approach, since there are faster algorithms to achieve the clustering than for GMMs.\n",
+ "\n",
+ "The scikit-learn module also provides an easy-to-use implementation of this algorithm:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 15,
+ "id": "2f280e1d",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
"KMeans(n_clusters=3)"
]
},
- "execution_count": 18,
+ "execution_count": 15,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "kmeans = KMeans(n_clusters=3)\n",
+ "kmeans.fit(data.loc[:, [\"x\", \"y\"]])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "id": "950a7eec",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "data.loc[:, \"guess_kmeans\"] = kmeans.predict(data.loc[:, [\"x\", \"y\"]])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 17,
+ "id": "16a56489",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "application/javascript": [
+ "/* Put everything inside the global mpl namespace */\n",
+ "/* global mpl */\n",
+ "window.mpl = {};\n",
+ "\n",
+ "mpl.get_websocket_type = function () {\n",
+ " if (typeof WebSocket !== 'undefined') {\n",
+ " return WebSocket;\n",
+ " } else if (typeof MozWebSocket !== 'undefined') {\n",
+ " return MozWebSocket;\n",
+ " } else {\n",
+ " alert(\n",
+ " 'Your browser does not have WebSocket support. ' +\n",
+ " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+ " 'Firefox 4 and 5 are also supported but you ' +\n",
+ " 'have to enable WebSockets in about:config.'\n",
+ " );\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
+ " this.id = figure_id;\n",
+ "\n",
+ " this.ws = websocket;\n",
+ "\n",
+ " this.supports_binary = this.ws.binaryType !== undefined;\n",
+ "\n",
+ " if (!this.supports_binary) {\n",
+ " var warnings = document.getElementById('mpl-warnings');\n",
+ " if (warnings) {\n",
+ " warnings.style.display = 'block';\n",
+ " warnings.textContent =\n",
+ " 'This browser does not support binary websocket messages. ' +\n",
+ " 'Performance may be slow.';\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.imageObj = new Image();\n",
+ "\n",
+ " this.context = undefined;\n",
+ " this.message = undefined;\n",
+ " this.canvas = undefined;\n",
+ " this.rubberband_canvas = undefined;\n",
+ " this.rubberband_context = undefined;\n",
+ " this.format_dropdown = undefined;\n",
+ "\n",
+ " this.image_mode = 'full';\n",
+ "\n",
+ " this.root = document.createElement('div');\n",
+ " this.root.setAttribute('style', 'display: inline-block');\n",
+ " this._root_extra_style(this.root);\n",
+ "\n",
+ " parent_element.appendChild(this.root);\n",
+ "\n",
+ " this._init_header(this);\n",
+ " this._init_canvas(this);\n",
+ " this._init_toolbar(this);\n",
+ "\n",
+ " var fig = this;\n",
+ "\n",
+ " this.waiting = false;\n",
+ "\n",
+ " this.ws.onopen = function () {\n",
+ " fig.send_message('supports_binary', { value: fig.supports_binary });\n",
+ " fig.send_message('send_image_mode', {});\n",
+ " if (fig.ratio !== 1) {\n",
+ " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
+ " }\n",
+ " fig.send_message('refresh', {});\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onload = function () {\n",
+ " if (fig.image_mode === 'full') {\n",
+ " // Full images could contain transparency (where diff images\n",
+ " // almost always do), so we need to clear the canvas so that\n",
+ " // there is no ghosting.\n",
+ " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+ " }\n",
+ " fig.context.drawImage(fig.imageObj, 0, 0);\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onunload = function () {\n",
+ " fig.ws.close();\n",
+ " };\n",
+ "\n",
+ " this.ws.onmessage = this._make_on_message_function(this);\n",
+ "\n",
+ " this.ondownload = ondownload;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_header = function () {\n",
+ " var titlebar = document.createElement('div');\n",
+ " titlebar.classList =\n",
+ " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
+ " var titletext = document.createElement('div');\n",
+ " titletext.classList = 'ui-dialog-title';\n",
+ " titletext.setAttribute(\n",
+ " 'style',\n",
+ " 'width: 100%; text-align: center; padding: 3px;'\n",
+ " );\n",
+ " titlebar.appendChild(titletext);\n",
+ " this.root.appendChild(titlebar);\n",
+ " this.header = titletext;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
+ "\n",
+ "mpl.figure.prototype._init_canvas = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var canvas_div = (this.canvas_div = document.createElement('div'));\n",
+ " canvas_div.setAttribute(\n",
+ " 'style',\n",
+ " 'border: 1px solid #ddd;' +\n",
+ " 'box-sizing: content-box;' +\n",
+ " 'clear: both;' +\n",
+ " 'min-height: 1px;' +\n",
+ " 'min-width: 1px;' +\n",
+ " 'outline: 0;' +\n",
+ " 'overflow: hidden;' +\n",
+ " 'position: relative;' +\n",
+ " 'resize: both;'\n",
+ " );\n",
+ "\n",
+ " function on_keyboard_event_closure(name) {\n",
+ " return function (event) {\n",
+ " return fig.key_event(event, name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " canvas_div.addEventListener(\n",
+ " 'keydown',\n",
+ " on_keyboard_event_closure('key_press')\n",
+ " );\n",
+ " canvas_div.addEventListener(\n",
+ " 'keyup',\n",
+ " on_keyboard_event_closure('key_release')\n",
+ " );\n",
+ "\n",
+ " this._canvas_extra_style(canvas_div);\n",
+ " this.root.appendChild(canvas_div);\n",
+ "\n",
+ " var canvas = (this.canvas = document.createElement('canvas'));\n",
+ " canvas.classList.add('mpl-canvas');\n",
+ " canvas.setAttribute('style', 'box-sizing: content-box;');\n",
+ "\n",
+ " this.context = canvas.getContext('2d');\n",
+ "\n",
+ " var backingStore =\n",
+ " this.context.backingStorePixelRatio ||\n",
+ " this.context.webkitBackingStorePixelRatio ||\n",
+ " this.context.mozBackingStorePixelRatio ||\n",
+ " this.context.msBackingStorePixelRatio ||\n",
+ " this.context.oBackingStorePixelRatio ||\n",
+ " this.context.backingStorePixelRatio ||\n",
+ " 1;\n",
+ "\n",
+ " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+ "\n",
+ " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
+ " 'canvas'\n",
+ " ));\n",
+ " rubberband_canvas.setAttribute(\n",
+ " 'style',\n",
+ " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
+ " );\n",
+ "\n",
+ " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
+ " if (this.ResizeObserver === undefined) {\n",
+ " if (window.ResizeObserver !== undefined) {\n",
+ " this.ResizeObserver = window.ResizeObserver;\n",
+ " } else {\n",
+ " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
+ " this.ResizeObserver = obs.ResizeObserver;\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
+ " var nentries = entries.length;\n",
+ " for (var i = 0; i < nentries; i++) {\n",
+ " var entry = entries[i];\n",
+ " var width, height;\n",
+ " if (entry.contentBoxSize) {\n",
+ " if (entry.contentBoxSize instanceof Array) {\n",
+ " // Chrome 84 implements new version of spec.\n",
+ " width = entry.contentBoxSize[0].inlineSize;\n",
+ " height = entry.contentBoxSize[0].blockSize;\n",
+ " } else {\n",
+ " // Firefox implements old version of spec.\n",
+ " width = entry.contentBoxSize.inlineSize;\n",
+ " height = entry.contentBoxSize.blockSize;\n",
+ " }\n",
+ " } else {\n",
+ " // Chrome <84 implements even older version of spec.\n",
+ " width = entry.contentRect.width;\n",
+ " height = entry.contentRect.height;\n",
+ " }\n",
+ "\n",
+ " // Keep the size of the canvas and rubber band canvas in sync with\n",
+ " // the canvas container.\n",
+ " if (entry.devicePixelContentBoxSize) {\n",
+ " // Chrome 84 implements new version of spec.\n",
+ " canvas.setAttribute(\n",
+ " 'width',\n",
+ " entry.devicePixelContentBoxSize[0].inlineSize\n",
+ " );\n",
+ " canvas.setAttribute(\n",
+ " 'height',\n",
+ " entry.devicePixelContentBoxSize[0].blockSize\n",
+ " );\n",
+ " } else {\n",
+ " canvas.setAttribute('width', width * fig.ratio);\n",
+ " canvas.setAttribute('height', height * fig.ratio);\n",
+ " }\n",
+ " canvas.setAttribute(\n",
+ " 'style',\n",
+ " 'width: ' + width + 'px; height: ' + height + 'px;'\n",
+ " );\n",
+ "\n",
+ " rubberband_canvas.setAttribute('width', width);\n",
+ " rubberband_canvas.setAttribute('height', height);\n",
+ "\n",
+ " // And update the size in Python. We ignore the initial 0/0 size\n",
+ " // that occurs as the element is placed into the DOM, which should\n",
+ " // otherwise not happen due to the minimum size styling.\n",
+ " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
+ " fig.request_resize(width, height);\n",
+ " }\n",
+ " }\n",
+ " });\n",
+ " this.resizeObserverInstance.observe(canvas_div);\n",
+ "\n",
+ " function on_mouse_event_closure(name) {\n",
+ " return function (event) {\n",
+ " return fig.mouse_event(event, name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mousedown',\n",
+ " on_mouse_event_closure('button_press')\n",
+ " );\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseup',\n",
+ " on_mouse_event_closure('button_release')\n",
+ " );\n",
+ " // Throttle sequential mouse events to 1 every 20ms.\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mousemove',\n",
+ " on_mouse_event_closure('motion_notify')\n",
+ " );\n",
+ "\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseenter',\n",
+ " on_mouse_event_closure('figure_enter')\n",
+ " );\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseleave',\n",
+ " on_mouse_event_closure('figure_leave')\n",
+ " );\n",
+ "\n",
+ " canvas_div.addEventListener('wheel', function (event) {\n",
+ " if (event.deltaY < 0) {\n",
+ " event.step = 1;\n",
+ " } else {\n",
+ " event.step = -1;\n",
+ " }\n",
+ " on_mouse_event_closure('scroll')(event);\n",
+ " });\n",
+ "\n",
+ " canvas_div.appendChild(canvas);\n",
+ " canvas_div.appendChild(rubberband_canvas);\n",
+ "\n",
+ " this.rubberband_context = rubberband_canvas.getContext('2d');\n",
+ " this.rubberband_context.strokeStyle = '#000000';\n",
+ "\n",
+ " this._resize_canvas = function (width, height, forward) {\n",
+ " if (forward) {\n",
+ " canvas_div.style.width = width + 'px';\n",
+ " canvas_div.style.height = height + 'px';\n",
+ " }\n",
+ " };\n",
+ "\n",
+ " // Disable right mouse context menu.\n",
+ " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ " });\n",
+ "\n",
+ " function set_focus() {\n",
+ " canvas.focus();\n",
+ " canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " window.setTimeout(set_focus, 100);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var toolbar = document.createElement('div');\n",
+ " toolbar.classList = 'mpl-toolbar';\n",
+ " this.root.appendChild(toolbar);\n",
+ "\n",
+ " function on_click_closure(name) {\n",
+ " return function (_event) {\n",
+ " return fig.toolbar_button_onclick(name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " function on_mouseover_closure(tooltip) {\n",
+ " return function (event) {\n",
+ " if (!event.currentTarget.disabled) {\n",
+ " return fig.toolbar_button_onmouseover(tooltip);\n",
+ " }\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " fig.buttons = {};\n",
+ " var buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'mpl-button-group';\n",
+ " for (var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " /* Instead of a spacer, we start a new button group. */\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ " buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'mpl-button-group';\n",
+ " continue;\n",
+ " }\n",
+ "\n",
+ " var button = (fig.buttons[name] = document.createElement('button'));\n",
+ " button.classList = 'mpl-widget';\n",
+ " button.setAttribute('role', 'button');\n",
+ " button.setAttribute('aria-disabled', 'false');\n",
+ " button.addEventListener('click', on_click_closure(method_name));\n",
+ " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+ "\n",
+ " var icon_img = document.createElement('img');\n",
+ " icon_img.src = '_images/' + image + '.png';\n",
+ " icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
+ " icon_img.alt = tooltip;\n",
+ " button.appendChild(icon_img);\n",
+ "\n",
+ " buttonGroup.appendChild(button);\n",
+ " }\n",
+ "\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ "\n",
+ " var fmt_picker = document.createElement('select');\n",
+ " fmt_picker.classList = 'mpl-widget';\n",
+ " toolbar.appendChild(fmt_picker);\n",
+ " this.format_dropdown = fmt_picker;\n",
+ "\n",
+ " for (var ind in mpl.extensions) {\n",
+ " var fmt = mpl.extensions[ind];\n",
+ " var option = document.createElement('option');\n",
+ " option.selected = fmt === mpl.default_extension;\n",
+ " option.innerHTML = fmt;\n",
+ " fmt_picker.appendChild(option);\n",
+ " }\n",
+ "\n",
+ " var status_bar = document.createElement('span');\n",
+ " status_bar.classList = 'mpl-message';\n",
+ " toolbar.appendChild(status_bar);\n",
+ " this.message = status_bar;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
+ " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+ " // which will in turn request a refresh of the image.\n",
+ " this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.send_message = function (type, properties) {\n",
+ " properties['type'] = type;\n",
+ " properties['figure_id'] = this.id;\n",
+ " this.ws.send(JSON.stringify(properties));\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.send_draw_message = function () {\n",
+ " if (!this.waiting) {\n",
+ " this.waiting = true;\n",
+ " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+ " var format_dropdown = fig.format_dropdown;\n",
+ " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+ " fig.ondownload(fig, format);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
+ " var size = msg['size'];\n",
+ " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
+ " fig._resize_canvas(size[0], size[1], msg['forward']);\n",
+ " fig.send_message('refresh', {});\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
+ " var x0 = msg['x0'] / fig.ratio;\n",
+ " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
+ " var x1 = msg['x1'] / fig.ratio;\n",
+ " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
+ " x0 = Math.floor(x0) + 0.5;\n",
+ " y0 = Math.floor(y0) + 0.5;\n",
+ " x1 = Math.floor(x1) + 0.5;\n",
+ " y1 = Math.floor(y1) + 0.5;\n",
+ " var min_x = Math.min(x0, x1);\n",
+ " var min_y = Math.min(y0, y1);\n",
+ " var width = Math.abs(x1 - x0);\n",
+ " var height = Math.abs(y1 - y0);\n",
+ "\n",
+ " fig.rubberband_context.clearRect(\n",
+ " 0,\n",
+ " 0,\n",
+ " fig.canvas.width / fig.ratio,\n",
+ " fig.canvas.height / fig.ratio\n",
+ " );\n",
+ "\n",
+ " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
+ " // Updates the figure title.\n",
+ " fig.header.textContent = msg['label'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
+ " var cursor = msg['cursor'];\n",
+ " switch (cursor) {\n",
+ " case 0:\n",
+ " cursor = 'pointer';\n",
+ " break;\n",
+ " case 1:\n",
+ " cursor = 'default';\n",
+ " break;\n",
+ " case 2:\n",
+ " cursor = 'crosshair';\n",
+ " break;\n",
+ " case 3:\n",
+ " cursor = 'move';\n",
+ " break;\n",
+ " }\n",
+ " fig.rubberband_canvas.style.cursor = cursor;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
+ " fig.message.textContent = msg['message'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
+ " // Request the server to send over a new figure.\n",
+ " fig.send_draw_message();\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
+ " fig.image_mode = msg['mode'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
+ " for (var key in msg) {\n",
+ " if (!(key in fig.buttons)) {\n",
+ " continue;\n",
+ " }\n",
+ " fig.buttons[key].disabled = !msg[key];\n",
+ " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
+ " if (msg['mode'] === 'PAN') {\n",
+ " fig.buttons['Pan'].classList.add('active');\n",
+ " fig.buttons['Zoom'].classList.remove('active');\n",
+ " } else if (msg['mode'] === 'ZOOM') {\n",
+ " fig.buttons['Pan'].classList.remove('active');\n",
+ " fig.buttons['Zoom'].classList.add('active');\n",
+ " } else {\n",
+ " fig.buttons['Pan'].classList.remove('active');\n",
+ " fig.buttons['Zoom'].classList.remove('active');\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function () {\n",
+ " // Called whenever the canvas gets updated.\n",
+ " this.send_message('ack', {});\n",
+ "};\n",
+ "\n",
+ "// A function to construct a web socket function for onmessage handling.\n",
+ "// Called in the figure constructor.\n",
+ "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
+ " return function socket_on_message(evt) {\n",
+ " if (evt.data instanceof Blob) {\n",
+ " /* FIXME: We get \"Resource interpreted as Image but\n",
+ " * transferred with MIME type text/plain:\" errors on\n",
+ " * Chrome. But how to set the MIME type? It doesn't seem\n",
+ " * to be part of the websocket stream */\n",
+ " evt.data.type = 'image/png';\n",
+ "\n",
+ " /* Free the memory for the previous frames */\n",
+ " if (fig.imageObj.src) {\n",
+ " (window.URL || window.webkitURL).revokeObjectURL(\n",
+ " fig.imageObj.src\n",
+ " );\n",
+ " }\n",
+ "\n",
+ " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+ " evt.data\n",
+ " );\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " } else if (\n",
+ " typeof evt.data === 'string' &&\n",
+ " evt.data.slice(0, 21) === 'data:image/png;base64'\n",
+ " ) {\n",
+ " fig.imageObj.src = evt.data;\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " var msg = JSON.parse(evt.data);\n",
+ " var msg_type = msg['type'];\n",
+ "\n",
+ " // Call the \"handle_{type}\" callback, which takes\n",
+ " // the figure and JSON message as its only arguments.\n",
+ " try {\n",
+ " var callback = fig['handle_' + msg_type];\n",
+ " } catch (e) {\n",
+ " console.log(\n",
+ " \"No handler for the '\" + msg_type + \"' message type: \",\n",
+ " msg\n",
+ " );\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " if (callback) {\n",
+ " try {\n",
+ " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+ " callback(fig, msg);\n",
+ " } catch (e) {\n",
+ " console.log(\n",
+ " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
+ " e,\n",
+ " e.stack,\n",
+ " msg\n",
+ " );\n",
+ " }\n",
+ " }\n",
+ " };\n",
+ "};\n",
+ "\n",
+ "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+ "mpl.findpos = function (e) {\n",
+ " //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+ " var targ;\n",
+ " if (!e) {\n",
+ " e = window.event;\n",
+ " }\n",
+ " if (e.target) {\n",
+ " targ = e.target;\n",
+ " } else if (e.srcElement) {\n",
+ " targ = e.srcElement;\n",
+ " }\n",
+ " if (targ.nodeType === 3) {\n",
+ " // defeat Safari bug\n",
+ " targ = targ.parentNode;\n",
+ " }\n",
+ "\n",
+ " // pageX,Y are the mouse positions relative to the document\n",
+ " var boundingRect = targ.getBoundingClientRect();\n",
+ " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
+ " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
+ "\n",
+ " return { x: x, y: y };\n",
+ "};\n",
+ "\n",
+ "/*\n",
+ " * return a copy of an object with only non-object keys\n",
+ " * we need this to avoid circular references\n",
+ " * http://stackoverflow.com/a/24161582/3208463\n",
+ " */\n",
+ "function simpleKeys(original) {\n",
+ " return Object.keys(original).reduce(function (obj, key) {\n",
+ " if (typeof original[key] !== 'object') {\n",
+ " obj[key] = original[key];\n",
+ " }\n",
+ " return obj;\n",
+ " }, {});\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.mouse_event = function (event, name) {\n",
+ " var canvas_pos = mpl.findpos(event);\n",
+ "\n",
+ " if (name === 'button_press') {\n",
+ " this.canvas.focus();\n",
+ " this.canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " var x = canvas_pos.x * this.ratio;\n",
+ " var y = canvas_pos.y * this.ratio;\n",
+ "\n",
+ " this.send_message(name, {\n",
+ " x: x,\n",
+ " y: y,\n",
+ " button: event.button,\n",
+ " step: event.step,\n",
+ " guiEvent: simpleKeys(event),\n",
+ " });\n",
+ "\n",
+ " /* This prevents the web browser from automatically changing to\n",
+ " * the text insertion cursor when the button is pressed. We want\n",
+ " * to control all of the cursor setting manually through the\n",
+ " * 'cursor' event from matplotlib */\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
+ " // Handle any extra behaviour associated with a key event\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.key_event = function (event, name) {\n",
+ " // Prevent repeat events\n",
+ " if (name === 'key_press') {\n",
+ " if (event.which === this._key) {\n",
+ " return;\n",
+ " } else {\n",
+ " this._key = event.which;\n",
+ " }\n",
+ " }\n",
+ " if (name === 'key_release') {\n",
+ " this._key = null;\n",
+ " }\n",
+ "\n",
+ " var value = '';\n",
+ " if (event.ctrlKey && event.which !== 17) {\n",
+ " value += 'ctrl+';\n",
+ " }\n",
+ " if (event.altKey && event.which !== 18) {\n",
+ " value += 'alt+';\n",
+ " }\n",
+ " if (event.shiftKey && event.which !== 16) {\n",
+ " value += 'shift+';\n",
+ " }\n",
+ "\n",
+ " value += 'k';\n",
+ " value += event.which.toString();\n",
+ "\n",
+ " this._key_event_extra(event, name);\n",
+ "\n",
+ " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
+ " return false;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
+ " if (name === 'download') {\n",
+ " this.handle_save(this, null);\n",
+ " } else {\n",
+ " this.send_message('toolbar_button', { name: name });\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
+ " this.message.textContent = tooltip;\n",
+ "};\n",
+ "\n",
+ "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
+ "// prettier-ignore\n",
+ "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
+ "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+ "\n",
+ "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
+ "\n",
+ "mpl.default_extension = \"png\";/* global mpl */\n",
+ "\n",
+ "var comm_websocket_adapter = function (comm) {\n",
+ " // Create a \"websocket\"-like object which calls the given IPython comm\n",
+ " // object with the appropriate methods. Currently this is a non binary\n",
+ " // socket, so there is still some room for performance tuning.\n",
+ " var ws = {};\n",
+ "\n",
+ " ws.close = function () {\n",
+ " comm.close();\n",
+ " };\n",
+ " ws.send = function (m) {\n",
+ " //console.log('sending', m);\n",
+ " comm.send(m);\n",
+ " };\n",
+ " // Register the callback with on_msg.\n",
+ " comm.on_msg(function (msg) {\n",
+ " //console.log('receiving', msg['content']['data'], msg);\n",
+ " // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
+ " ws.onmessage(msg['content']['data']);\n",
+ " });\n",
+ " return ws;\n",
+ "};\n",
+ "\n",
+ "mpl.mpl_figure_comm = function (comm, msg) {\n",
+ " // This is the function which gets called when the mpl process\n",
+ " // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+ "\n",
+ " var id = msg.content.data.id;\n",
+ " // Get hold of the div created by the display call when the Comm\n",
+ " // socket was opened in Python.\n",
+ " var element = document.getElementById(id);\n",
+ " var ws_proxy = comm_websocket_adapter(comm);\n",
+ "\n",
+ " function ondownload(figure, _format) {\n",
+ " window.open(figure.canvas.toDataURL());\n",
+ " }\n",
+ "\n",
+ " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
+ "\n",
+ " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+ " // web socket which is closed, not our websocket->open comm proxy.\n",
+ " ws_proxy.onopen();\n",
+ "\n",
+ " fig.parent_element = element;\n",
+ " fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+ " if (!fig.cell_info) {\n",
+ " console.error('Failed to find cell for figure', id, fig);\n",
+ " return;\n",
+ " }\n",
+ " fig.cell_info[0].output_area.element.on(\n",
+ " 'cleared',\n",
+ " { fig: fig },\n",
+ " fig._remove_fig_handler\n",
+ " );\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
+ " var width = fig.canvas.width / fig.ratio;\n",
+ " fig.cell_info[0].output_area.element.off(\n",
+ " 'cleared',\n",
+ " fig._remove_fig_handler\n",
+ " );\n",
+ " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
+ "\n",
+ " // Update the output cell to use the data from the current canvas.\n",
+ " fig.push_to_output();\n",
+ " var dataURL = fig.canvas.toDataURL();\n",
+ " // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+ " // the notebook keyboard shortcuts fail.\n",
+ " IPython.keyboard_manager.enable();\n",
+ " fig.parent_element.innerHTML =\n",
+ " '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ " fig.close_ws(fig, msg);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
+ " fig.send_message('closing', msg);\n",
+ " // fig.ws.close()\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
+ " // Turn the data on the canvas into data in the output cell.\n",
+ " var width = this.canvas.width / this.ratio;\n",
+ " var dataURL = this.canvas.toDataURL();\n",
+ " this.cell_info[1]['text/html'] =\n",
+ " '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function () {\n",
+ " // Tell IPython that the notebook contents must change.\n",
+ " IPython.notebook.set_dirty(true);\n",
+ " this.send_message('ack', {});\n",
+ " var fig = this;\n",
+ " // Wait a second, then push the new image to the DOM so\n",
+ " // that it is saved nicely (might be nice to debounce this).\n",
+ " setTimeout(function () {\n",
+ " fig.push_to_output();\n",
+ " }, 1000);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var toolbar = document.createElement('div');\n",
+ " toolbar.classList = 'btn-toolbar';\n",
+ " this.root.appendChild(toolbar);\n",
+ "\n",
+ " function on_click_closure(name) {\n",
+ " return function (_event) {\n",
+ " return fig.toolbar_button_onclick(name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " function on_mouseover_closure(tooltip) {\n",
+ " return function (event) {\n",
+ " if (!event.currentTarget.disabled) {\n",
+ " return fig.toolbar_button_onmouseover(tooltip);\n",
+ " }\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " fig.buttons = {};\n",
+ " var buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'btn-group';\n",
+ " var button;\n",
+ " for (var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " /* Instead of a spacer, we start a new button group. */\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ " buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'btn-group';\n",
+ " continue;\n",
+ " }\n",
+ "\n",
+ " button = fig.buttons[name] = document.createElement('button');\n",
+ " button.classList = 'btn btn-default';\n",
+ " button.href = '#';\n",
+ " button.title = name;\n",
+ " button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
+ " button.addEventListener('click', on_click_closure(method_name));\n",
+ " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+ " buttonGroup.appendChild(button);\n",
+ " }\n",
+ "\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ "\n",
+ " // Add the status bar.\n",
+ " var status_bar = document.createElement('span');\n",
+ " status_bar.classList = 'mpl-message pull-right';\n",
+ " toolbar.appendChild(status_bar);\n",
+ " this.message = status_bar;\n",
+ "\n",
+ " // Add the close button to the window.\n",
+ " var buttongrp = document.createElement('div');\n",
+ " buttongrp.classList = 'btn-group inline pull-right';\n",
+ " button = document.createElement('button');\n",
+ " button.classList = 'btn btn-mini btn-primary';\n",
+ " button.href = '#';\n",
+ " button.title = 'Stop Interaction';\n",
+ " button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
+ " button.addEventListener('click', function (_evt) {\n",
+ " fig.handle_close(fig, {});\n",
+ " });\n",
+ " button.addEventListener(\n",
+ " 'mouseover',\n",
+ " on_mouseover_closure('Stop Interaction')\n",
+ " );\n",
+ " buttongrp.appendChild(button);\n",
+ " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
+ " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
+ " var fig = event.data.fig;\n",
+ " if (event.target !== this) {\n",
+ " // Ignore bubbled events from children.\n",
+ " return;\n",
+ " }\n",
+ " fig.close_ws(fig, {});\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function (el) {\n",
+ " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
+ " // this is important to make the div 'focusable\n",
+ " el.setAttribute('tabindex', 0);\n",
+ " // reach out to IPython and tell the keyboard manager to turn it's self\n",
+ " // off when our div gets focus\n",
+ "\n",
+ " // location in version 3\n",
+ " if (IPython.notebook.keyboard_manager) {\n",
+ " IPython.notebook.keyboard_manager.register_events(el);\n",
+ " } else {\n",
+ " // location in version 2\n",
+ " IPython.keyboard_manager.register_events(el);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
+ " var manager = IPython.notebook.keyboard_manager;\n",
+ " if (!manager) {\n",
+ " manager = IPython.keyboard_manager;\n",
+ " }\n",
+ "\n",
+ " // Check for shift+enter\n",
+ " if (event.shiftKey && event.which === 13) {\n",
+ " this.canvas_div.blur();\n",
+ " // select the cell after this one\n",
+ " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
+ " IPython.notebook.select(index + 1);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+ " fig.ondownload(fig, null);\n",
+ "};\n",
+ "\n",
+ "mpl.find_output_cell = function (html_output) {\n",
+ " // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+ " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+ " // IPython event is triggered only after the cells have been serialised, which for\n",
+ " // our purposes (turning an active figure into a static one), is too late.\n",
+ " var cells = IPython.notebook.get_cells();\n",
+ " var ncells = cells.length;\n",
+ " for (var i = 0; i < ncells; i++) {\n",
+ " var cell = cells[i];\n",
+ " if (cell.cell_type === 'code') {\n",
+ " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
+ " var data = cell.output_area.outputs[j];\n",
+ " if (data.data) {\n",
+ " // IPython >= 3 moved mimebundle to data attribute of output\n",
+ " data = data.data;\n",
+ " }\n",
+ " if (data['text/html'] === html_output) {\n",
+ " return [cell, data, j];\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "// Register the function which deals with the matplotlib target/channel.\n",
+ "// The kernel may be null if the page has been refreshed.\n",
+ "if (IPython.notebook.kernel !== null) {\n",
+ " IPython.notebook.kernel.comm_manager.register_target(\n",
+ " 'matplotlib',\n",
+ " mpl.mpl_figure_comm\n",
+ " );\n",
+ "}\n"
+ ],
+ "text/plain": [
+ "<IPython.core.display.Javascript object>"
+ ]
+ },
"metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "kmeans = KMeans(n_clusters=3)\n",
- "kmeans.fit(data.loc[:, [\"x\", \"y\"]])"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 19,
- "id": "950a7eec",
- "metadata": {},
- "outputs": [],
- "source": [
- "data.loc[:, \"guess_kmeans\"] = kmeans.predict(data.loc[:, [\"x\", \"y\"]])"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 20,
- "id": "16a56489",
- "metadata": {},
- "outputs": [
+ "output_type": "display_data"
+ },
{
"data": {
- "image/png": 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\" width=\"1000\">"
+ ],
"text/plain": [
- "<Figure size 1152x1152 with 4 Axes>"
+ "<IPython.core.display.HTML object>"
]
},
- "metadata": {
- "needs_background": "light"
- },
+ "metadata": {},
"output_type": "display_data"
}
],
"source": [
- "fig, ax = plt.subplots(figsize=(16, 16), ncols=2)\n",
+ "fig, ax = plt.subplots(figsize=(10, 10), ncols=2)\n",
"data.plot.scatter(x=\"x\", y=\"y\", c=\"guess_kmeans\", colormap='viridis', ax=ax[0])\n",
"data.plot.scatter(x=\"x\", y=\"y\", c=\"source\", colormap='viridis', ax=ax[1])\n",
"ax[0].set(xlabel=\"x\", ylabel=r\"y\", title=\"Guessed source using K-Means\")\n",
@@ -604,7 +3479,7 @@
},
{
"cell_type": "code",
- "execution_count": 22,
+ "execution_count": 18,
"id": "0a8642bd",
"metadata": {},
"outputs": [],
@@ -616,25 +3491,983 @@
},
{
"cell_type": "code",
- "execution_count": 23,
+ "execution_count": 19,
"id": "ccbf4019",
"metadata": {},
"outputs": [
{
"data": {
- "image/png": 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\n",
+ "application/javascript": [
+ "/* Put everything inside the global mpl namespace */\n",
+ "/* global mpl */\n",
+ "window.mpl = {};\n",
+ "\n",
+ "mpl.get_websocket_type = function () {\n",
+ " if (typeof WebSocket !== 'undefined') {\n",
+ " return WebSocket;\n",
+ " } else if (typeof MozWebSocket !== 'undefined') {\n",
+ " return MozWebSocket;\n",
+ " } else {\n",
+ " alert(\n",
+ " 'Your browser does not have WebSocket support. ' +\n",
+ " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+ " 'Firefox 4 and 5 are also supported but you ' +\n",
+ " 'have to enable WebSockets in about:config.'\n",
+ " );\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
+ " this.id = figure_id;\n",
+ "\n",
+ " this.ws = websocket;\n",
+ "\n",
+ " this.supports_binary = this.ws.binaryType !== undefined;\n",
+ "\n",
+ " if (!this.supports_binary) {\n",
+ " var warnings = document.getElementById('mpl-warnings');\n",
+ " if (warnings) {\n",
+ " warnings.style.display = 'block';\n",
+ " warnings.textContent =\n",
+ " 'This browser does not support binary websocket messages. ' +\n",
+ " 'Performance may be slow.';\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.imageObj = new Image();\n",
+ "\n",
+ " this.context = undefined;\n",
+ " this.message = undefined;\n",
+ " this.canvas = undefined;\n",
+ " this.rubberband_canvas = undefined;\n",
+ " this.rubberband_context = undefined;\n",
+ " this.format_dropdown = undefined;\n",
+ "\n",
+ " this.image_mode = 'full';\n",
+ "\n",
+ " this.root = document.createElement('div');\n",
+ " this.root.setAttribute('style', 'display: inline-block');\n",
+ " this._root_extra_style(this.root);\n",
+ "\n",
+ " parent_element.appendChild(this.root);\n",
+ "\n",
+ " this._init_header(this);\n",
+ " this._init_canvas(this);\n",
+ " this._init_toolbar(this);\n",
+ "\n",
+ " var fig = this;\n",
+ "\n",
+ " this.waiting = false;\n",
+ "\n",
+ " this.ws.onopen = function () {\n",
+ " fig.send_message('supports_binary', { value: fig.supports_binary });\n",
+ " fig.send_message('send_image_mode', {});\n",
+ " if (fig.ratio !== 1) {\n",
+ " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
+ " }\n",
+ " fig.send_message('refresh', {});\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onload = function () {\n",
+ " if (fig.image_mode === 'full') {\n",
+ " // Full images could contain transparency (where diff images\n",
+ " // almost always do), so we need to clear the canvas so that\n",
+ " // there is no ghosting.\n",
+ " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+ " }\n",
+ " fig.context.drawImage(fig.imageObj, 0, 0);\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onunload = function () {\n",
+ " fig.ws.close();\n",
+ " };\n",
+ "\n",
+ " this.ws.onmessage = this._make_on_message_function(this);\n",
+ "\n",
+ " this.ondownload = ondownload;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_header = function () {\n",
+ " var titlebar = document.createElement('div');\n",
+ " titlebar.classList =\n",
+ " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
+ " var titletext = document.createElement('div');\n",
+ " titletext.classList = 'ui-dialog-title';\n",
+ " titletext.setAttribute(\n",
+ " 'style',\n",
+ " 'width: 100%; text-align: center; padding: 3px;'\n",
+ " );\n",
+ " titlebar.appendChild(titletext);\n",
+ " this.root.appendChild(titlebar);\n",
+ " this.header = titletext;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
+ "\n",
+ "mpl.figure.prototype._init_canvas = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var canvas_div = (this.canvas_div = document.createElement('div'));\n",
+ " canvas_div.setAttribute(\n",
+ " 'style',\n",
+ " 'border: 1px solid #ddd;' +\n",
+ " 'box-sizing: content-box;' +\n",
+ " 'clear: both;' +\n",
+ " 'min-height: 1px;' +\n",
+ " 'min-width: 1px;' +\n",
+ " 'outline: 0;' +\n",
+ " 'overflow: hidden;' +\n",
+ " 'position: relative;' +\n",
+ " 'resize: both;'\n",
+ " );\n",
+ "\n",
+ " function on_keyboard_event_closure(name) {\n",
+ " return function (event) {\n",
+ " return fig.key_event(event, name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " canvas_div.addEventListener(\n",
+ " 'keydown',\n",
+ " on_keyboard_event_closure('key_press')\n",
+ " );\n",
+ " canvas_div.addEventListener(\n",
+ " 'keyup',\n",
+ " on_keyboard_event_closure('key_release')\n",
+ " );\n",
+ "\n",
+ " this._canvas_extra_style(canvas_div);\n",
+ " this.root.appendChild(canvas_div);\n",
+ "\n",
+ " var canvas = (this.canvas = document.createElement('canvas'));\n",
+ " canvas.classList.add('mpl-canvas');\n",
+ " canvas.setAttribute('style', 'box-sizing: content-box;');\n",
+ "\n",
+ " this.context = canvas.getContext('2d');\n",
+ "\n",
+ " var backingStore =\n",
+ " this.context.backingStorePixelRatio ||\n",
+ " this.context.webkitBackingStorePixelRatio ||\n",
+ " this.context.mozBackingStorePixelRatio ||\n",
+ " this.context.msBackingStorePixelRatio ||\n",
+ " this.context.oBackingStorePixelRatio ||\n",
+ " this.context.backingStorePixelRatio ||\n",
+ " 1;\n",
+ "\n",
+ " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+ "\n",
+ " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
+ " 'canvas'\n",
+ " ));\n",
+ " rubberband_canvas.setAttribute(\n",
+ " 'style',\n",
+ " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
+ " );\n",
+ "\n",
+ " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
+ " if (this.ResizeObserver === undefined) {\n",
+ " if (window.ResizeObserver !== undefined) {\n",
+ " this.ResizeObserver = window.ResizeObserver;\n",
+ " } else {\n",
+ " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
+ " this.ResizeObserver = obs.ResizeObserver;\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
+ " var nentries = entries.length;\n",
+ " for (var i = 0; i < nentries; i++) {\n",
+ " var entry = entries[i];\n",
+ " var width, height;\n",
+ " if (entry.contentBoxSize) {\n",
+ " if (entry.contentBoxSize instanceof Array) {\n",
+ " // Chrome 84 implements new version of spec.\n",
+ " width = entry.contentBoxSize[0].inlineSize;\n",
+ " height = entry.contentBoxSize[0].blockSize;\n",
+ " } else {\n",
+ " // Firefox implements old version of spec.\n",
+ " width = entry.contentBoxSize.inlineSize;\n",
+ " height = entry.contentBoxSize.blockSize;\n",
+ " }\n",
+ " } else {\n",
+ " // Chrome <84 implements even older version of spec.\n",
+ " width = entry.contentRect.width;\n",
+ " height = entry.contentRect.height;\n",
+ " }\n",
+ "\n",
+ " // Keep the size of the canvas and rubber band canvas in sync with\n",
+ " // the canvas container.\n",
+ " if (entry.devicePixelContentBoxSize) {\n",
+ " // Chrome 84 implements new version of spec.\n",
+ " canvas.setAttribute(\n",
+ " 'width',\n",
+ " entry.devicePixelContentBoxSize[0].inlineSize\n",
+ " );\n",
+ " canvas.setAttribute(\n",
+ " 'height',\n",
+ " entry.devicePixelContentBoxSize[0].blockSize\n",
+ " );\n",
+ " } else {\n",
+ " canvas.setAttribute('width', width * fig.ratio);\n",
+ " canvas.setAttribute('height', height * fig.ratio);\n",
+ " }\n",
+ " canvas.setAttribute(\n",
+ " 'style',\n",
+ " 'width: ' + width + 'px; height: ' + height + 'px;'\n",
+ " );\n",
+ "\n",
+ " rubberband_canvas.setAttribute('width', width);\n",
+ " rubberband_canvas.setAttribute('height', height);\n",
+ "\n",
+ " // And update the size in Python. We ignore the initial 0/0 size\n",
+ " // that occurs as the element is placed into the DOM, which should\n",
+ " // otherwise not happen due to the minimum size styling.\n",
+ " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
+ " fig.request_resize(width, height);\n",
+ " }\n",
+ " }\n",
+ " });\n",
+ " this.resizeObserverInstance.observe(canvas_div);\n",
+ "\n",
+ " function on_mouse_event_closure(name) {\n",
+ " return function (event) {\n",
+ " return fig.mouse_event(event, name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mousedown',\n",
+ " on_mouse_event_closure('button_press')\n",
+ " );\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseup',\n",
+ " on_mouse_event_closure('button_release')\n",
+ " );\n",
+ " // Throttle sequential mouse events to 1 every 20ms.\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mousemove',\n",
+ " on_mouse_event_closure('motion_notify')\n",
+ " );\n",
+ "\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseenter',\n",
+ " on_mouse_event_closure('figure_enter')\n",
+ " );\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseleave',\n",
+ " on_mouse_event_closure('figure_leave')\n",
+ " );\n",
+ "\n",
+ " canvas_div.addEventListener('wheel', function (event) {\n",
+ " if (event.deltaY < 0) {\n",
+ " event.step = 1;\n",
+ " } else {\n",
+ " event.step = -1;\n",
+ " }\n",
+ " on_mouse_event_closure('scroll')(event);\n",
+ " });\n",
+ "\n",
+ " canvas_div.appendChild(canvas);\n",
+ " canvas_div.appendChild(rubberband_canvas);\n",
+ "\n",
+ " this.rubberband_context = rubberband_canvas.getContext('2d');\n",
+ " this.rubberband_context.strokeStyle = '#000000';\n",
+ "\n",
+ " this._resize_canvas = function (width, height, forward) {\n",
+ " if (forward) {\n",
+ " canvas_div.style.width = width + 'px';\n",
+ " canvas_div.style.height = height + 'px';\n",
+ " }\n",
+ " };\n",
+ "\n",
+ " // Disable right mouse context menu.\n",
+ " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ " });\n",
+ "\n",
+ " function set_focus() {\n",
+ " canvas.focus();\n",
+ " canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " window.setTimeout(set_focus, 100);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var toolbar = document.createElement('div');\n",
+ " toolbar.classList = 'mpl-toolbar';\n",
+ " this.root.appendChild(toolbar);\n",
+ "\n",
+ " function on_click_closure(name) {\n",
+ " return function (_event) {\n",
+ " return fig.toolbar_button_onclick(name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " function on_mouseover_closure(tooltip) {\n",
+ " return function (event) {\n",
+ " if (!event.currentTarget.disabled) {\n",
+ " return fig.toolbar_button_onmouseover(tooltip);\n",
+ " }\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " fig.buttons = {};\n",
+ " var buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'mpl-button-group';\n",
+ " for (var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " /* Instead of a spacer, we start a new button group. */\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ " buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'mpl-button-group';\n",
+ " continue;\n",
+ " }\n",
+ "\n",
+ " var button = (fig.buttons[name] = document.createElement('button'));\n",
+ " button.classList = 'mpl-widget';\n",
+ " button.setAttribute('role', 'button');\n",
+ " button.setAttribute('aria-disabled', 'false');\n",
+ " button.addEventListener('click', on_click_closure(method_name));\n",
+ " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+ "\n",
+ " var icon_img = document.createElement('img');\n",
+ " icon_img.src = '_images/' + image + '.png';\n",
+ " icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
+ " icon_img.alt = tooltip;\n",
+ " button.appendChild(icon_img);\n",
+ "\n",
+ " buttonGroup.appendChild(button);\n",
+ " }\n",
+ "\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ "\n",
+ " var fmt_picker = document.createElement('select');\n",
+ " fmt_picker.classList = 'mpl-widget';\n",
+ " toolbar.appendChild(fmt_picker);\n",
+ " this.format_dropdown = fmt_picker;\n",
+ "\n",
+ " for (var ind in mpl.extensions) {\n",
+ " var fmt = mpl.extensions[ind];\n",
+ " var option = document.createElement('option');\n",
+ " option.selected = fmt === mpl.default_extension;\n",
+ " option.innerHTML = fmt;\n",
+ " fmt_picker.appendChild(option);\n",
+ " }\n",
+ "\n",
+ " var status_bar = document.createElement('span');\n",
+ " status_bar.classList = 'mpl-message';\n",
+ " toolbar.appendChild(status_bar);\n",
+ " this.message = status_bar;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
+ " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+ " // which will in turn request a refresh of the image.\n",
+ " this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.send_message = function (type, properties) {\n",
+ " properties['type'] = type;\n",
+ " properties['figure_id'] = this.id;\n",
+ " this.ws.send(JSON.stringify(properties));\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.send_draw_message = function () {\n",
+ " if (!this.waiting) {\n",
+ " this.waiting = true;\n",
+ " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+ " var format_dropdown = fig.format_dropdown;\n",
+ " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+ " fig.ondownload(fig, format);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
+ " var size = msg['size'];\n",
+ " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
+ " fig._resize_canvas(size[0], size[1], msg['forward']);\n",
+ " fig.send_message('refresh', {});\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
+ " var x0 = msg['x0'] / fig.ratio;\n",
+ " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
+ " var x1 = msg['x1'] / fig.ratio;\n",
+ " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
+ " x0 = Math.floor(x0) + 0.5;\n",
+ " y0 = Math.floor(y0) + 0.5;\n",
+ " x1 = Math.floor(x1) + 0.5;\n",
+ " y1 = Math.floor(y1) + 0.5;\n",
+ " var min_x = Math.min(x0, x1);\n",
+ " var min_y = Math.min(y0, y1);\n",
+ " var width = Math.abs(x1 - x0);\n",
+ " var height = Math.abs(y1 - y0);\n",
+ "\n",
+ " fig.rubberband_context.clearRect(\n",
+ " 0,\n",
+ " 0,\n",
+ " fig.canvas.width / fig.ratio,\n",
+ " fig.canvas.height / fig.ratio\n",
+ " );\n",
+ "\n",
+ " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
+ " // Updates the figure title.\n",
+ " fig.header.textContent = msg['label'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
+ " var cursor = msg['cursor'];\n",
+ " switch (cursor) {\n",
+ " case 0:\n",
+ " cursor = 'pointer';\n",
+ " break;\n",
+ " case 1:\n",
+ " cursor = 'default';\n",
+ " break;\n",
+ " case 2:\n",
+ " cursor = 'crosshair';\n",
+ " break;\n",
+ " case 3:\n",
+ " cursor = 'move';\n",
+ " break;\n",
+ " }\n",
+ " fig.rubberband_canvas.style.cursor = cursor;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
+ " fig.message.textContent = msg['message'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
+ " // Request the server to send over a new figure.\n",
+ " fig.send_draw_message();\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
+ " fig.image_mode = msg['mode'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
+ " for (var key in msg) {\n",
+ " if (!(key in fig.buttons)) {\n",
+ " continue;\n",
+ " }\n",
+ " fig.buttons[key].disabled = !msg[key];\n",
+ " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
+ " if (msg['mode'] === 'PAN') {\n",
+ " fig.buttons['Pan'].classList.add('active');\n",
+ " fig.buttons['Zoom'].classList.remove('active');\n",
+ " } else if (msg['mode'] === 'ZOOM') {\n",
+ " fig.buttons['Pan'].classList.remove('active');\n",
+ " fig.buttons['Zoom'].classList.add('active');\n",
+ " } else {\n",
+ " fig.buttons['Pan'].classList.remove('active');\n",
+ " fig.buttons['Zoom'].classList.remove('active');\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function () {\n",
+ " // Called whenever the canvas gets updated.\n",
+ " this.send_message('ack', {});\n",
+ "};\n",
+ "\n",
+ "// A function to construct a web socket function for onmessage handling.\n",
+ "// Called in the figure constructor.\n",
+ "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
+ " return function socket_on_message(evt) {\n",
+ " if (evt.data instanceof Blob) {\n",
+ " /* FIXME: We get \"Resource interpreted as Image but\n",
+ " * transferred with MIME type text/plain:\" errors on\n",
+ " * Chrome. But how to set the MIME type? It doesn't seem\n",
+ " * to be part of the websocket stream */\n",
+ " evt.data.type = 'image/png';\n",
+ "\n",
+ " /* Free the memory for the previous frames */\n",
+ " if (fig.imageObj.src) {\n",
+ " (window.URL || window.webkitURL).revokeObjectURL(\n",
+ " fig.imageObj.src\n",
+ " );\n",
+ " }\n",
+ "\n",
+ " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+ " evt.data\n",
+ " );\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " } else if (\n",
+ " typeof evt.data === 'string' &&\n",
+ " evt.data.slice(0, 21) === 'data:image/png;base64'\n",
+ " ) {\n",
+ " fig.imageObj.src = evt.data;\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " var msg = JSON.parse(evt.data);\n",
+ " var msg_type = msg['type'];\n",
+ "\n",
+ " // Call the \"handle_{type}\" callback, which takes\n",
+ " // the figure and JSON message as its only arguments.\n",
+ " try {\n",
+ " var callback = fig['handle_' + msg_type];\n",
+ " } catch (e) {\n",
+ " console.log(\n",
+ " \"No handler for the '\" + msg_type + \"' message type: \",\n",
+ " msg\n",
+ " );\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " if (callback) {\n",
+ " try {\n",
+ " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+ " callback(fig, msg);\n",
+ " } catch (e) {\n",
+ " console.log(\n",
+ " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
+ " e,\n",
+ " e.stack,\n",
+ " msg\n",
+ " );\n",
+ " }\n",
+ " }\n",
+ " };\n",
+ "};\n",
+ "\n",
+ "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+ "mpl.findpos = function (e) {\n",
+ " //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+ " var targ;\n",
+ " if (!e) {\n",
+ " e = window.event;\n",
+ " }\n",
+ " if (e.target) {\n",
+ " targ = e.target;\n",
+ " } else if (e.srcElement) {\n",
+ " targ = e.srcElement;\n",
+ " }\n",
+ " if (targ.nodeType === 3) {\n",
+ " // defeat Safari bug\n",
+ " targ = targ.parentNode;\n",
+ " }\n",
+ "\n",
+ " // pageX,Y are the mouse positions relative to the document\n",
+ " var boundingRect = targ.getBoundingClientRect();\n",
+ " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
+ " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
+ "\n",
+ " return { x: x, y: y };\n",
+ "};\n",
+ "\n",
+ "/*\n",
+ " * return a copy of an object with only non-object keys\n",
+ " * we need this to avoid circular references\n",
+ " * http://stackoverflow.com/a/24161582/3208463\n",
+ " */\n",
+ "function simpleKeys(original) {\n",
+ " return Object.keys(original).reduce(function (obj, key) {\n",
+ " if (typeof original[key] !== 'object') {\n",
+ " obj[key] = original[key];\n",
+ " }\n",
+ " return obj;\n",
+ " }, {});\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.mouse_event = function (event, name) {\n",
+ " var canvas_pos = mpl.findpos(event);\n",
+ "\n",
+ " if (name === 'button_press') {\n",
+ " this.canvas.focus();\n",
+ " this.canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " var x = canvas_pos.x * this.ratio;\n",
+ " var y = canvas_pos.y * this.ratio;\n",
+ "\n",
+ " this.send_message(name, {\n",
+ " x: x,\n",
+ " y: y,\n",
+ " button: event.button,\n",
+ " step: event.step,\n",
+ " guiEvent: simpleKeys(event),\n",
+ " });\n",
+ "\n",
+ " /* This prevents the web browser from automatically changing to\n",
+ " * the text insertion cursor when the button is pressed. We want\n",
+ " * to control all of the cursor setting manually through the\n",
+ " * 'cursor' event from matplotlib */\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
+ " // Handle any extra behaviour associated with a key event\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.key_event = function (event, name) {\n",
+ " // Prevent repeat events\n",
+ " if (name === 'key_press') {\n",
+ " if (event.which === this._key) {\n",
+ " return;\n",
+ " } else {\n",
+ " this._key = event.which;\n",
+ " }\n",
+ " }\n",
+ " if (name === 'key_release') {\n",
+ " this._key = null;\n",
+ " }\n",
+ "\n",
+ " var value = '';\n",
+ " if (event.ctrlKey && event.which !== 17) {\n",
+ " value += 'ctrl+';\n",
+ " }\n",
+ " if (event.altKey && event.which !== 18) {\n",
+ " value += 'alt+';\n",
+ " }\n",
+ " if (event.shiftKey && event.which !== 16) {\n",
+ " value += 'shift+';\n",
+ " }\n",
+ "\n",
+ " value += 'k';\n",
+ " value += event.which.toString();\n",
+ "\n",
+ " this._key_event_extra(event, name);\n",
+ "\n",
+ " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
+ " return false;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
+ " if (name === 'download') {\n",
+ " this.handle_save(this, null);\n",
+ " } else {\n",
+ " this.send_message('toolbar_button', { name: name });\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
+ " this.message.textContent = tooltip;\n",
+ "};\n",
+ "\n",
+ "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
+ "// prettier-ignore\n",
+ "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
+ "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+ "\n",
+ "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
+ "\n",
+ "mpl.default_extension = \"png\";/* global mpl */\n",
+ "\n",
+ "var comm_websocket_adapter = function (comm) {\n",
+ " // Create a \"websocket\"-like object which calls the given IPython comm\n",
+ " // object with the appropriate methods. Currently this is a non binary\n",
+ " // socket, so there is still some room for performance tuning.\n",
+ " var ws = {};\n",
+ "\n",
+ " ws.close = function () {\n",
+ " comm.close();\n",
+ " };\n",
+ " ws.send = function (m) {\n",
+ " //console.log('sending', m);\n",
+ " comm.send(m);\n",
+ " };\n",
+ " // Register the callback with on_msg.\n",
+ " comm.on_msg(function (msg) {\n",
+ " //console.log('receiving', msg['content']['data'], msg);\n",
+ " // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
+ " ws.onmessage(msg['content']['data']);\n",
+ " });\n",
+ " return ws;\n",
+ "};\n",
+ "\n",
+ "mpl.mpl_figure_comm = function (comm, msg) {\n",
+ " // This is the function which gets called when the mpl process\n",
+ " // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+ "\n",
+ " var id = msg.content.data.id;\n",
+ " // Get hold of the div created by the display call when the Comm\n",
+ " // socket was opened in Python.\n",
+ " var element = document.getElementById(id);\n",
+ " var ws_proxy = comm_websocket_adapter(comm);\n",
+ "\n",
+ " function ondownload(figure, _format) {\n",
+ " window.open(figure.canvas.toDataURL());\n",
+ " }\n",
+ "\n",
+ " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
+ "\n",
+ " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+ " // web socket which is closed, not our websocket->open comm proxy.\n",
+ " ws_proxy.onopen();\n",
+ "\n",
+ " fig.parent_element = element;\n",
+ " fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+ " if (!fig.cell_info) {\n",
+ " console.error('Failed to find cell for figure', id, fig);\n",
+ " return;\n",
+ " }\n",
+ " fig.cell_info[0].output_area.element.on(\n",
+ " 'cleared',\n",
+ " { fig: fig },\n",
+ " fig._remove_fig_handler\n",
+ " );\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
+ " var width = fig.canvas.width / fig.ratio;\n",
+ " fig.cell_info[0].output_area.element.off(\n",
+ " 'cleared',\n",
+ " fig._remove_fig_handler\n",
+ " );\n",
+ " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
+ "\n",
+ " // Update the output cell to use the data from the current canvas.\n",
+ " fig.push_to_output();\n",
+ " var dataURL = fig.canvas.toDataURL();\n",
+ " // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+ " // the notebook keyboard shortcuts fail.\n",
+ " IPython.keyboard_manager.enable();\n",
+ " fig.parent_element.innerHTML =\n",
+ " '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ " fig.close_ws(fig, msg);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
+ " fig.send_message('closing', msg);\n",
+ " // fig.ws.close()\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
+ " // Turn the data on the canvas into data in the output cell.\n",
+ " var width = this.canvas.width / this.ratio;\n",
+ " var dataURL = this.canvas.toDataURL();\n",
+ " this.cell_info[1]['text/html'] =\n",
+ " '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function () {\n",
+ " // Tell IPython that the notebook contents must change.\n",
+ " IPython.notebook.set_dirty(true);\n",
+ " this.send_message('ack', {});\n",
+ " var fig = this;\n",
+ " // Wait a second, then push the new image to the DOM so\n",
+ " // that it is saved nicely (might be nice to debounce this).\n",
+ " setTimeout(function () {\n",
+ " fig.push_to_output();\n",
+ " }, 1000);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var toolbar = document.createElement('div');\n",
+ " toolbar.classList = 'btn-toolbar';\n",
+ " this.root.appendChild(toolbar);\n",
+ "\n",
+ " function on_click_closure(name) {\n",
+ " return function (_event) {\n",
+ " return fig.toolbar_button_onclick(name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " function on_mouseover_closure(tooltip) {\n",
+ " return function (event) {\n",
+ " if (!event.currentTarget.disabled) {\n",
+ " return fig.toolbar_button_onmouseover(tooltip);\n",
+ " }\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " fig.buttons = {};\n",
+ " var buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'btn-group';\n",
+ " var button;\n",
+ " for (var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " /* Instead of a spacer, we start a new button group. */\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ " buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'btn-group';\n",
+ " continue;\n",
+ " }\n",
+ "\n",
+ " button = fig.buttons[name] = document.createElement('button');\n",
+ " button.classList = 'btn btn-default';\n",
+ " button.href = '#';\n",
+ " button.title = name;\n",
+ " button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
+ " button.addEventListener('click', on_click_closure(method_name));\n",
+ " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+ " buttonGroup.appendChild(button);\n",
+ " }\n",
+ "\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ "\n",
+ " // Add the status bar.\n",
+ " var status_bar = document.createElement('span');\n",
+ " status_bar.classList = 'mpl-message pull-right';\n",
+ " toolbar.appendChild(status_bar);\n",
+ " this.message = status_bar;\n",
+ "\n",
+ " // Add the close button to the window.\n",
+ " var buttongrp = document.createElement('div');\n",
+ " buttongrp.classList = 'btn-group inline pull-right';\n",
+ " button = document.createElement('button');\n",
+ " button.classList = 'btn btn-mini btn-primary';\n",
+ " button.href = '#';\n",
+ " button.title = 'Stop Interaction';\n",
+ " button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
+ " button.addEventListener('click', function (_evt) {\n",
+ " fig.handle_close(fig, {});\n",
+ " });\n",
+ " button.addEventListener(\n",
+ " 'mouseover',\n",
+ " on_mouseover_closure('Stop Interaction')\n",
+ " );\n",
+ " buttongrp.appendChild(button);\n",
+ " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
+ " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
+ " var fig = event.data.fig;\n",
+ " if (event.target !== this) {\n",
+ " // Ignore bubbled events from children.\n",
+ " return;\n",
+ " }\n",
+ " fig.close_ws(fig, {});\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function (el) {\n",
+ " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
+ " // this is important to make the div 'focusable\n",
+ " el.setAttribute('tabindex', 0);\n",
+ " // reach out to IPython and tell the keyboard manager to turn it's self\n",
+ " // off when our div gets focus\n",
+ "\n",
+ " // location in version 3\n",
+ " if (IPython.notebook.keyboard_manager) {\n",
+ " IPython.notebook.keyboard_manager.register_events(el);\n",
+ " } else {\n",
+ " // location in version 2\n",
+ " IPython.keyboard_manager.register_events(el);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
+ " var manager = IPython.notebook.keyboard_manager;\n",
+ " if (!manager) {\n",
+ " manager = IPython.keyboard_manager;\n",
+ " }\n",
+ "\n",
+ " // Check for shift+enter\n",
+ " if (event.shiftKey && event.which === 13) {\n",
+ " this.canvas_div.blur();\n",
+ " // select the cell after this one\n",
+ " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
+ " IPython.notebook.select(index + 1);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+ " fig.ondownload(fig, null);\n",
+ "};\n",
+ "\n",
+ "mpl.find_output_cell = function (html_output) {\n",
+ " // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+ " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+ " // IPython event is triggered only after the cells have been serialised, which for\n",
+ " // our purposes (turning an active figure into a static one), is too late.\n",
+ " var cells = IPython.notebook.get_cells();\n",
+ " var ncells = cells.length;\n",
+ " for (var i = 0; i < ncells; i++) {\n",
+ " var cell = cells[i];\n",
+ " if (cell.cell_type === 'code') {\n",
+ " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
+ " var data = cell.output_area.outputs[j];\n",
+ " if (data.data) {\n",
+ " // IPython >= 3 moved mimebundle to data attribute of output\n",
+ " data = data.data;\n",
+ " }\n",
+ " if (data['text/html'] === html_output) {\n",
+ " return [cell, data, j];\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "// Register the function which deals with the matplotlib target/channel.\n",
+ "// The kernel may be null if the page has been refreshed.\n",
+ "if (IPython.notebook.kernel !== null) {\n",
+ " IPython.notebook.kernel.comm_manager.register_target(\n",
+ " 'matplotlib',\n",
+ " mpl.mpl_figure_comm\n",
+ " );\n",
+ "}\n"
+ ],
"text/plain": [
- "<Figure size 1152x1152 with 4 Axes>"
+ "<IPython.core.display.Javascript object>"
]
},
- "metadata": {
- "needs_background": "light"
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "text/html": [
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\" width=\"1000\">"
+ ],
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ]
},
+ "metadata": {},
"output_type": "display_data"
}
],
"source": [
- "fig, ax = plt.subplots(figsize=(16, 16), ncols=2)\n",
+ "fig, ax = plt.subplots(figsize=(10, 10), ncols=2)\n",
"data.plot.scatter(x=\"x\", y=\"y\", c=\"guess_bgmm\", colormap='viridis', ax=ax[0])\n",
"data.plot.scatter(x=\"x\", y=\"y\", c=\"source\", colormap='viridis', ax=ax[1])\n",
"ax[0].set(xlabel=\"x\", ylabel=r\"y\", title=\"Guessed source using Variation Inference GMM\")\n",
@@ -664,8 +4497,7 @@
"source": [
"### Contact us at the EuXFEL Data Analysis group at any time if you need help analysing your data!\n",
"\n",
- "#### Danilo Ferreira de Lima: danilo.enoque.ferreira.de.lima@xfel.eu\n",
- "#### Arman Davtyan: arman.davtyan@xfel.eu"
+ "#### Data Analysis group: da@xfel.eu"
]
},
{
@@ -693,7 +4525,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.7.10"
+ "version": "3.6.13"
}
},
"nbformat": 4,
diff --git a/README.md b/README.md
index d00bc85..bb9b0af 100644
--- a/README.md
+++ b/README.md
@@ -6,16 +6,134 @@ are also given in the notebooks.
Most of the notebooks require installing special software the following is a general setup that should work with most of the given notebooks.
The list of packages needed in each given notebook is given in the beginning of the notebook with a `!pip install ...` command.
+It is highly recommended to use Anaconda/Miniconda for the setup, as shown below. If you prefer a simpler configuration, details on the
+Virtualenv setup is also given at the end (but this tends to use a less optimized setup, which may affect the performance and some results).
+
+All the data used in the examples are produced on-the-fly for demonstration purposes, or are taken from public and open resources.
+None of the data comes from the EuXFEL, as the purpose of the examples is to show the idea behind the methods.
+
+## Anaconda configuration
+
+If you already know how to use Anaconda (or Miniconda), the following
+setup is recommended.
+If you are not used to Anaconda, see the following references on how to install and a quick start guide:
+
+ * https://conda.io/projects/conda/en/latest/user-guide/install/index.html
+ * https://conda.io/projects/conda/en/latest/user-guide/getting-started.html
+
+Here is a cut-and-paste installation guide for the impatient in Linux:
```
-pip install torchvision torch pandas numpy matplotlib ipympl torchbnn scikit-learn
+wget https://repo.anaconda.com/miniconda/Miniconda3-py37_4.10.3-Linux-x86_64.sh
+
+# or download it from: https://docs.conda.io/en/latest/miniconda.html#linux-installers
+bash Miniconda3-py37_4.10.3-Linux-x86_64.sh
+
+# follow the instructions
```
-All the data used in the examples are produced on-the-fly for demonstration purposes, or are taken from public and open resources.
-None of the data comes from the EuXFEL, as the purpose of the examples is to show the idea behind the methods.
+This creates a conda environment named `ml` (use whichever name your prefer instead) and install the packages needed.
+If you are using a Mac, please see the section below for a special configuration
+for Anaconda in a Mac (due to an incompatibility between some Mac libraries
+and Anaconda's default MKL installation).
+
+```
+# create the environment
+conda create --name ml python=3.6
+
+# activate it
+conda activate ml
+
+# install basic libraries
+conda install mkl
+
+# PyTorch (without the GPU acceleration):
+conda install pytorch torchvision cpuonly -c pytorch
+
+# Or, instead, if you have an NVIDIA GPU (for AMD GPUs, check https://pytorch.org/ and look for the ROCm platform):
+#conda install pytorch torchvision cudatoolkit=10.2 -c pytorch
+
+conda install numpy scipy pandas scikit-learn matplotlib jupyter
+
+# for the Bayesian Neural Network notebook:
+pip install torchbnn
+
+# play with the notebooks:
+jupyter notebook
+
+# when you are done:
+
+conda deactivate
+```
+
+### Special Anaconda setup in MacOS
+
+In MacOS, the standard optimization done in Anaconda for fast matrix multiplications using the MKL library clashes with a Mac-specific implementation.
+To avoid this issue, use the setup below.
+
+```
+# create the environment
+conda create --name ml python=3.6
+
+# activate it
+conda activate ml
+
+# remove MKL to avoid conflict in MacOS
+conda install nomkl
+
+# PyTorch (without the GPU acceleration):
+conda install pytorch torchvision cpuonly -c pytorch
+
+# Or, instead, if you have an NVIDIA GPU (will not work with an AMD or Intel GPU):
+#conda install pytorch torchvision cudatoolkit=10.2 -c pytorch
+
+conda install numpy scipy pandas scikit-learn matplotlib jupyter
+
+# for the Bayesian Neural Network notebook:
+pip install torchbnn
+
+# remove any MKL libraries installed as a dependency from the packages above:
+conda remove mkl mkl-service
+
+# play with the notebooks:
+jupyter notebook
+
+# when you are done:
+
+conda deactivate
+```
+
+More details on this can be found in:
+
+https://stackoverflow.com/questions/53014306/error-15-initializing-libiomp5-dylib-but-found-libiomp5-dylib-already-initial
+
+## Virtualenv setup
+
+It is preferrable to use a virtual environment to avoid any clashes between these
+packages and your current setup in your computer. Using a virtual environment,
+the setup would be the following (for an environment called `ml`, but use the name
+you prefer):
+
+```
+# create the environment ml
+virtualenv -p python3 ml
+
+# load it
+source ml/bin/activate
+
+# install some packages
+pip install numpy scipy pandas torch scikit-learn matplotlib torchvision torchbnn jupyter
+
+# play with the notebooks ...
+jupyter notebook
+
+# when you are done:
+deactivate
+```
+
+# Contact us!
-### Contact us at the EuXFEL Data Analysis group at any time if you need help analysing your data!
+#### Contact us at the EuXFEL Data Analysis group at any time if you need help analysing your data!
-#### Danilo Ferreira de Lima: danilo.enoque.ferreira.de.lima@xfel.eu
-#### Arman Davtyan: arman.davtyan@xfel.eu
+#### Email: da@xfel.eu
diff --git a/Representation Learning.ipynb b/Representation Learning.ipynb
index 95fd59c..7c4f153 100644
--- a/Representation Learning.ipynb
+++ b/Representation Learning.ipynb
@@ -24,7 +24,7 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": 1,
"id": "44ca341e",
"metadata": {},
"outputs": [
@@ -32,20 +32,20 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "Requirement already satisfied: numpy in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (1.19.2)\n",
- "Requirement already satisfied: scikit-learn in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (0.24.2)\n",
- "Requirement already satisfied: pandas in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (1.3.0)\n",
- "Requirement already satisfied: matplotlib in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (3.4.2)\n",
- "Requirement already satisfied: joblib>=0.11 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from scikit-learn) (1.0.1)\n",
- "Requirement already satisfied: scipy>=0.19.1 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from scikit-learn) (1.6.2)\n",
- "Requirement already satisfied: threadpoolctl>=2.0.0 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from scikit-learn) (2.2.0)\n",
- "Requirement already satisfied: python-dateutil>=2.7.3 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from pandas) (2.8.2)\n",
- "Requirement already satisfied: pytz>=2017.3 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from pandas) (2021.1)\n",
- "Requirement already satisfied: six>=1.5 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from python-dateutil>=2.7.3->pandas) (1.16.0)\n",
- "Requirement already satisfied: kiwisolver>=1.0.1 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from matplotlib) (1.3.1)\n",
- "Requirement already satisfied: pillow>=6.2.0 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from matplotlib) (8.3.1)\n",
- "Requirement already satisfied: pyparsing>=2.2.1 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from matplotlib) (2.4.7)\n",
- "Requirement already satisfied: cycler>=0.10 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from matplotlib) (0.10.0)\n"
+ "Requirement already satisfied: numpy in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (1.19.2)\n",
+ "Requirement already satisfied: scikit-learn in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (0.24.2)\n",
+ "Requirement already satisfied: pandas in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (1.1.5)\n",
+ "Requirement already satisfied: matplotlib in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (3.3.4)\n",
+ "Requirement already satisfied: scipy>=0.19.1 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from scikit-learn) (1.5.2)\n",
+ "Requirement already satisfied: threadpoolctl>=2.0.0 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from scikit-learn) (2.2.0)\n",
+ "Requirement already satisfied: joblib>=0.11 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from scikit-learn) (1.0.1)\n",
+ "Requirement already satisfied: python-dateutil>=2.7.3 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from pandas) (2.8.2)\n",
+ "Requirement already satisfied: pytz>=2017.2 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from pandas) (2021.3)\n",
+ "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.3 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from matplotlib) (3.0.4)\n",
+ "Requirement already satisfied: kiwisolver>=1.0.1 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from matplotlib) (1.3.1)\n",
+ "Requirement already satisfied: cycler>=0.10 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from matplotlib) (0.11.0)\n",
+ "Requirement already satisfied: pillow>=6.2.0 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from matplotlib) (8.3.1)\n",
+ "Requirement already satisfied: six>=1.5 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from python-dateutil>=2.7.3->pandas) (1.16.0)\n"
]
}
],
@@ -55,13 +55,14 @@
},
{
"cell_type": "code",
- "execution_count": 1,
+ "execution_count": 2,
"id": "300cf8d3",
"metadata": {},
"outputs": [],
"source": [
+ "%matplotlib notebook\n",
+ "\n",
"import matplotlib.pyplot as plt\n",
- "%matplotlib inline\n",
"\n",
"import pandas as pd\n",
"import numpy as np\n",
@@ -78,7 +79,7 @@
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": 3,
"id": "4959a292",
"metadata": {},
"outputs": [],
@@ -100,7 +101,7 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": 4,
"id": "024fb65a",
"metadata": {},
"outputs": [
@@ -207,7 +208,7 @@
"[500 rows x 2 columns]"
]
},
- "execution_count": 3,
+ "execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
@@ -232,14 +233,972 @@
"outputs": [
{
"data": {
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\n",
+ "application/javascript": [
+ "/* Put everything inside the global mpl namespace */\n",
+ "/* global mpl */\n",
+ "window.mpl = {};\n",
+ "\n",
+ "mpl.get_websocket_type = function () {\n",
+ " if (typeof WebSocket !== 'undefined') {\n",
+ " return WebSocket;\n",
+ " } else if (typeof MozWebSocket !== 'undefined') {\n",
+ " return MozWebSocket;\n",
+ " } else {\n",
+ " alert(\n",
+ " 'Your browser does not have WebSocket support. ' +\n",
+ " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+ " 'Firefox 4 and 5 are also supported but you ' +\n",
+ " 'have to enable WebSockets in about:config.'\n",
+ " );\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
+ " this.id = figure_id;\n",
+ "\n",
+ " this.ws = websocket;\n",
+ "\n",
+ " this.supports_binary = this.ws.binaryType !== undefined;\n",
+ "\n",
+ " if (!this.supports_binary) {\n",
+ " var warnings = document.getElementById('mpl-warnings');\n",
+ " if (warnings) {\n",
+ " warnings.style.display = 'block';\n",
+ " warnings.textContent =\n",
+ " 'This browser does not support binary websocket messages. ' +\n",
+ " 'Performance may be slow.';\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.imageObj = new Image();\n",
+ "\n",
+ " this.context = undefined;\n",
+ " this.message = undefined;\n",
+ " this.canvas = undefined;\n",
+ " this.rubberband_canvas = undefined;\n",
+ " this.rubberband_context = undefined;\n",
+ " this.format_dropdown = undefined;\n",
+ "\n",
+ " this.image_mode = 'full';\n",
+ "\n",
+ " this.root = document.createElement('div');\n",
+ " this.root.setAttribute('style', 'display: inline-block');\n",
+ " this._root_extra_style(this.root);\n",
+ "\n",
+ " parent_element.appendChild(this.root);\n",
+ "\n",
+ " this._init_header(this);\n",
+ " this._init_canvas(this);\n",
+ " this._init_toolbar(this);\n",
+ "\n",
+ " var fig = this;\n",
+ "\n",
+ " this.waiting = false;\n",
+ "\n",
+ " this.ws.onopen = function () {\n",
+ " fig.send_message('supports_binary', { value: fig.supports_binary });\n",
+ " fig.send_message('send_image_mode', {});\n",
+ " if (fig.ratio !== 1) {\n",
+ " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
+ " }\n",
+ " fig.send_message('refresh', {});\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onload = function () {\n",
+ " if (fig.image_mode === 'full') {\n",
+ " // Full images could contain transparency (where diff images\n",
+ " // almost always do), so we need to clear the canvas so that\n",
+ " // there is no ghosting.\n",
+ " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+ " }\n",
+ " fig.context.drawImage(fig.imageObj, 0, 0);\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onunload = function () {\n",
+ " fig.ws.close();\n",
+ " };\n",
+ "\n",
+ " this.ws.onmessage = this._make_on_message_function(this);\n",
+ "\n",
+ " this.ondownload = ondownload;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_header = function () {\n",
+ " var titlebar = document.createElement('div');\n",
+ " titlebar.classList =\n",
+ " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
+ " var titletext = document.createElement('div');\n",
+ " titletext.classList = 'ui-dialog-title';\n",
+ " titletext.setAttribute(\n",
+ " 'style',\n",
+ " 'width: 100%; text-align: center; padding: 3px;'\n",
+ " );\n",
+ " titlebar.appendChild(titletext);\n",
+ " this.root.appendChild(titlebar);\n",
+ " this.header = titletext;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
+ "\n",
+ "mpl.figure.prototype._init_canvas = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var canvas_div = (this.canvas_div = document.createElement('div'));\n",
+ " canvas_div.setAttribute(\n",
+ " 'style',\n",
+ " 'border: 1px solid #ddd;' +\n",
+ " 'box-sizing: content-box;' +\n",
+ " 'clear: both;' +\n",
+ " 'min-height: 1px;' +\n",
+ " 'min-width: 1px;' +\n",
+ " 'outline: 0;' +\n",
+ " 'overflow: hidden;' +\n",
+ " 'position: relative;' +\n",
+ " 'resize: both;'\n",
+ " );\n",
+ "\n",
+ " function on_keyboard_event_closure(name) {\n",
+ " return function (event) {\n",
+ " return fig.key_event(event, name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " canvas_div.addEventListener(\n",
+ " 'keydown',\n",
+ " on_keyboard_event_closure('key_press')\n",
+ " );\n",
+ " canvas_div.addEventListener(\n",
+ " 'keyup',\n",
+ " on_keyboard_event_closure('key_release')\n",
+ " );\n",
+ "\n",
+ " this._canvas_extra_style(canvas_div);\n",
+ " this.root.appendChild(canvas_div);\n",
+ "\n",
+ " var canvas = (this.canvas = document.createElement('canvas'));\n",
+ " canvas.classList.add('mpl-canvas');\n",
+ " canvas.setAttribute('style', 'box-sizing: content-box;');\n",
+ "\n",
+ " this.context = canvas.getContext('2d');\n",
+ "\n",
+ " var backingStore =\n",
+ " this.context.backingStorePixelRatio ||\n",
+ " this.context.webkitBackingStorePixelRatio ||\n",
+ " this.context.mozBackingStorePixelRatio ||\n",
+ " this.context.msBackingStorePixelRatio ||\n",
+ " this.context.oBackingStorePixelRatio ||\n",
+ " this.context.backingStorePixelRatio ||\n",
+ " 1;\n",
+ "\n",
+ " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+ "\n",
+ " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
+ " 'canvas'\n",
+ " ));\n",
+ " rubberband_canvas.setAttribute(\n",
+ " 'style',\n",
+ " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
+ " );\n",
+ "\n",
+ " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
+ " if (this.ResizeObserver === undefined) {\n",
+ " if (window.ResizeObserver !== undefined) {\n",
+ " this.ResizeObserver = window.ResizeObserver;\n",
+ " } else {\n",
+ " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
+ " this.ResizeObserver = obs.ResizeObserver;\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
+ " var nentries = entries.length;\n",
+ " for (var i = 0; i < nentries; i++) {\n",
+ " var entry = entries[i];\n",
+ " var width, height;\n",
+ " if (entry.contentBoxSize) {\n",
+ " if (entry.contentBoxSize instanceof Array) {\n",
+ " // Chrome 84 implements new version of spec.\n",
+ " width = entry.contentBoxSize[0].inlineSize;\n",
+ " height = entry.contentBoxSize[0].blockSize;\n",
+ " } else {\n",
+ " // Firefox implements old version of spec.\n",
+ " width = entry.contentBoxSize.inlineSize;\n",
+ " height = entry.contentBoxSize.blockSize;\n",
+ " }\n",
+ " } else {\n",
+ " // Chrome <84 implements even older version of spec.\n",
+ " width = entry.contentRect.width;\n",
+ " height = entry.contentRect.height;\n",
+ " }\n",
+ "\n",
+ " // Keep the size of the canvas and rubber band canvas in sync with\n",
+ " // the canvas container.\n",
+ " if (entry.devicePixelContentBoxSize) {\n",
+ " // Chrome 84 implements new version of spec.\n",
+ " canvas.setAttribute(\n",
+ " 'width',\n",
+ " entry.devicePixelContentBoxSize[0].inlineSize\n",
+ " );\n",
+ " canvas.setAttribute(\n",
+ " 'height',\n",
+ " entry.devicePixelContentBoxSize[0].blockSize\n",
+ " );\n",
+ " } else {\n",
+ " canvas.setAttribute('width', width * fig.ratio);\n",
+ " canvas.setAttribute('height', height * fig.ratio);\n",
+ " }\n",
+ " canvas.setAttribute(\n",
+ " 'style',\n",
+ " 'width: ' + width + 'px; height: ' + height + 'px;'\n",
+ " );\n",
+ "\n",
+ " rubberband_canvas.setAttribute('width', width);\n",
+ " rubberband_canvas.setAttribute('height', height);\n",
+ "\n",
+ " // And update the size in Python. We ignore the initial 0/0 size\n",
+ " // that occurs as the element is placed into the DOM, which should\n",
+ " // otherwise not happen due to the minimum size styling.\n",
+ " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
+ " fig.request_resize(width, height);\n",
+ " }\n",
+ " }\n",
+ " });\n",
+ " this.resizeObserverInstance.observe(canvas_div);\n",
+ "\n",
+ " function on_mouse_event_closure(name) {\n",
+ " return function (event) {\n",
+ " return fig.mouse_event(event, name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mousedown',\n",
+ " on_mouse_event_closure('button_press')\n",
+ " );\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseup',\n",
+ " on_mouse_event_closure('button_release')\n",
+ " );\n",
+ " // Throttle sequential mouse events to 1 every 20ms.\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mousemove',\n",
+ " on_mouse_event_closure('motion_notify')\n",
+ " );\n",
+ "\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseenter',\n",
+ " on_mouse_event_closure('figure_enter')\n",
+ " );\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseleave',\n",
+ " on_mouse_event_closure('figure_leave')\n",
+ " );\n",
+ "\n",
+ " canvas_div.addEventListener('wheel', function (event) {\n",
+ " if (event.deltaY < 0) {\n",
+ " event.step = 1;\n",
+ " } else {\n",
+ " event.step = -1;\n",
+ " }\n",
+ " on_mouse_event_closure('scroll')(event);\n",
+ " });\n",
+ "\n",
+ " canvas_div.appendChild(canvas);\n",
+ " canvas_div.appendChild(rubberband_canvas);\n",
+ "\n",
+ " this.rubberband_context = rubberband_canvas.getContext('2d');\n",
+ " this.rubberband_context.strokeStyle = '#000000';\n",
+ "\n",
+ " this._resize_canvas = function (width, height, forward) {\n",
+ " if (forward) {\n",
+ " canvas_div.style.width = width + 'px';\n",
+ " canvas_div.style.height = height + 'px';\n",
+ " }\n",
+ " };\n",
+ "\n",
+ " // Disable right mouse context menu.\n",
+ " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ " });\n",
+ "\n",
+ " function set_focus() {\n",
+ " canvas.focus();\n",
+ " canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " window.setTimeout(set_focus, 100);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var toolbar = document.createElement('div');\n",
+ " toolbar.classList = 'mpl-toolbar';\n",
+ " this.root.appendChild(toolbar);\n",
+ "\n",
+ " function on_click_closure(name) {\n",
+ " return function (_event) {\n",
+ " return fig.toolbar_button_onclick(name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " function on_mouseover_closure(tooltip) {\n",
+ " return function (event) {\n",
+ " if (!event.currentTarget.disabled) {\n",
+ " return fig.toolbar_button_onmouseover(tooltip);\n",
+ " }\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " fig.buttons = {};\n",
+ " var buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'mpl-button-group';\n",
+ " for (var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " /* Instead of a spacer, we start a new button group. */\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ " buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'mpl-button-group';\n",
+ " continue;\n",
+ " }\n",
+ "\n",
+ " var button = (fig.buttons[name] = document.createElement('button'));\n",
+ " button.classList = 'mpl-widget';\n",
+ " button.setAttribute('role', 'button');\n",
+ " button.setAttribute('aria-disabled', 'false');\n",
+ " button.addEventListener('click', on_click_closure(method_name));\n",
+ " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+ "\n",
+ " var icon_img = document.createElement('img');\n",
+ " icon_img.src = '_images/' + image + '.png';\n",
+ " icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
+ " icon_img.alt = tooltip;\n",
+ " button.appendChild(icon_img);\n",
+ "\n",
+ " buttonGroup.appendChild(button);\n",
+ " }\n",
+ "\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ "\n",
+ " var fmt_picker = document.createElement('select');\n",
+ " fmt_picker.classList = 'mpl-widget';\n",
+ " toolbar.appendChild(fmt_picker);\n",
+ " this.format_dropdown = fmt_picker;\n",
+ "\n",
+ " for (var ind in mpl.extensions) {\n",
+ " var fmt = mpl.extensions[ind];\n",
+ " var option = document.createElement('option');\n",
+ " option.selected = fmt === mpl.default_extension;\n",
+ " option.innerHTML = fmt;\n",
+ " fmt_picker.appendChild(option);\n",
+ " }\n",
+ "\n",
+ " var status_bar = document.createElement('span');\n",
+ " status_bar.classList = 'mpl-message';\n",
+ " toolbar.appendChild(status_bar);\n",
+ " this.message = status_bar;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
+ " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+ " // which will in turn request a refresh of the image.\n",
+ " this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.send_message = function (type, properties) {\n",
+ " properties['type'] = type;\n",
+ " properties['figure_id'] = this.id;\n",
+ " this.ws.send(JSON.stringify(properties));\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.send_draw_message = function () {\n",
+ " if (!this.waiting) {\n",
+ " this.waiting = true;\n",
+ " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+ " var format_dropdown = fig.format_dropdown;\n",
+ " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+ " fig.ondownload(fig, format);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
+ " var size = msg['size'];\n",
+ " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
+ " fig._resize_canvas(size[0], size[1], msg['forward']);\n",
+ " fig.send_message('refresh', {});\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
+ " var x0 = msg['x0'] / fig.ratio;\n",
+ " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
+ " var x1 = msg['x1'] / fig.ratio;\n",
+ " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
+ " x0 = Math.floor(x0) + 0.5;\n",
+ " y0 = Math.floor(y0) + 0.5;\n",
+ " x1 = Math.floor(x1) + 0.5;\n",
+ " y1 = Math.floor(y1) + 0.5;\n",
+ " var min_x = Math.min(x0, x1);\n",
+ " var min_y = Math.min(y0, y1);\n",
+ " var width = Math.abs(x1 - x0);\n",
+ " var height = Math.abs(y1 - y0);\n",
+ "\n",
+ " fig.rubberband_context.clearRect(\n",
+ " 0,\n",
+ " 0,\n",
+ " fig.canvas.width / fig.ratio,\n",
+ " fig.canvas.height / fig.ratio\n",
+ " );\n",
+ "\n",
+ " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
+ " // Updates the figure title.\n",
+ " fig.header.textContent = msg['label'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
+ " var cursor = msg['cursor'];\n",
+ " switch (cursor) {\n",
+ " case 0:\n",
+ " cursor = 'pointer';\n",
+ " break;\n",
+ " case 1:\n",
+ " cursor = 'default';\n",
+ " break;\n",
+ " case 2:\n",
+ " cursor = 'crosshair';\n",
+ " break;\n",
+ " case 3:\n",
+ " cursor = 'move';\n",
+ " break;\n",
+ " }\n",
+ " fig.rubberband_canvas.style.cursor = cursor;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
+ " fig.message.textContent = msg['message'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
+ " // Request the server to send over a new figure.\n",
+ " fig.send_draw_message();\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
+ " fig.image_mode = msg['mode'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
+ " for (var key in msg) {\n",
+ " if (!(key in fig.buttons)) {\n",
+ " continue;\n",
+ " }\n",
+ " fig.buttons[key].disabled = !msg[key];\n",
+ " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
+ " if (msg['mode'] === 'PAN') {\n",
+ " fig.buttons['Pan'].classList.add('active');\n",
+ " fig.buttons['Zoom'].classList.remove('active');\n",
+ " } else if (msg['mode'] === 'ZOOM') {\n",
+ " fig.buttons['Pan'].classList.remove('active');\n",
+ " fig.buttons['Zoom'].classList.add('active');\n",
+ " } else {\n",
+ " fig.buttons['Pan'].classList.remove('active');\n",
+ " fig.buttons['Zoom'].classList.remove('active');\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function () {\n",
+ " // Called whenever the canvas gets updated.\n",
+ " this.send_message('ack', {});\n",
+ "};\n",
+ "\n",
+ "// A function to construct a web socket function for onmessage handling.\n",
+ "// Called in the figure constructor.\n",
+ "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
+ " return function socket_on_message(evt) {\n",
+ " if (evt.data instanceof Blob) {\n",
+ " /* FIXME: We get \"Resource interpreted as Image but\n",
+ " * transferred with MIME type text/plain:\" errors on\n",
+ " * Chrome. But how to set the MIME type? It doesn't seem\n",
+ " * to be part of the websocket stream */\n",
+ " evt.data.type = 'image/png';\n",
+ "\n",
+ " /* Free the memory for the previous frames */\n",
+ " if (fig.imageObj.src) {\n",
+ " (window.URL || window.webkitURL).revokeObjectURL(\n",
+ " fig.imageObj.src\n",
+ " );\n",
+ " }\n",
+ "\n",
+ " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+ " evt.data\n",
+ " );\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " } else if (\n",
+ " typeof evt.data === 'string' &&\n",
+ " evt.data.slice(0, 21) === 'data:image/png;base64'\n",
+ " ) {\n",
+ " fig.imageObj.src = evt.data;\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " var msg = JSON.parse(evt.data);\n",
+ " var msg_type = msg['type'];\n",
+ "\n",
+ " // Call the \"handle_{type}\" callback, which takes\n",
+ " // the figure and JSON message as its only arguments.\n",
+ " try {\n",
+ " var callback = fig['handle_' + msg_type];\n",
+ " } catch (e) {\n",
+ " console.log(\n",
+ " \"No handler for the '\" + msg_type + \"' message type: \",\n",
+ " msg\n",
+ " );\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " if (callback) {\n",
+ " try {\n",
+ " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+ " callback(fig, msg);\n",
+ " } catch (e) {\n",
+ " console.log(\n",
+ " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
+ " e,\n",
+ " e.stack,\n",
+ " msg\n",
+ " );\n",
+ " }\n",
+ " }\n",
+ " };\n",
+ "};\n",
+ "\n",
+ "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+ "mpl.findpos = function (e) {\n",
+ " //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+ " var targ;\n",
+ " if (!e) {\n",
+ " e = window.event;\n",
+ " }\n",
+ " if (e.target) {\n",
+ " targ = e.target;\n",
+ " } else if (e.srcElement) {\n",
+ " targ = e.srcElement;\n",
+ " }\n",
+ " if (targ.nodeType === 3) {\n",
+ " // defeat Safari bug\n",
+ " targ = targ.parentNode;\n",
+ " }\n",
+ "\n",
+ " // pageX,Y are the mouse positions relative to the document\n",
+ " var boundingRect = targ.getBoundingClientRect();\n",
+ " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
+ " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
+ "\n",
+ " return { x: x, y: y };\n",
+ "};\n",
+ "\n",
+ "/*\n",
+ " * return a copy of an object with only non-object keys\n",
+ " * we need this to avoid circular references\n",
+ " * http://stackoverflow.com/a/24161582/3208463\n",
+ " */\n",
+ "function simpleKeys(original) {\n",
+ " return Object.keys(original).reduce(function (obj, key) {\n",
+ " if (typeof original[key] !== 'object') {\n",
+ " obj[key] = original[key];\n",
+ " }\n",
+ " return obj;\n",
+ " }, {});\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.mouse_event = function (event, name) {\n",
+ " var canvas_pos = mpl.findpos(event);\n",
+ "\n",
+ " if (name === 'button_press') {\n",
+ " this.canvas.focus();\n",
+ " this.canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " var x = canvas_pos.x * this.ratio;\n",
+ " var y = canvas_pos.y * this.ratio;\n",
+ "\n",
+ " this.send_message(name, {\n",
+ " x: x,\n",
+ " y: y,\n",
+ " button: event.button,\n",
+ " step: event.step,\n",
+ " guiEvent: simpleKeys(event),\n",
+ " });\n",
+ "\n",
+ " /* This prevents the web browser from automatically changing to\n",
+ " * the text insertion cursor when the button is pressed. We want\n",
+ " * to control all of the cursor setting manually through the\n",
+ " * 'cursor' event from matplotlib */\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
+ " // Handle any extra behaviour associated with a key event\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.key_event = function (event, name) {\n",
+ " // Prevent repeat events\n",
+ " if (name === 'key_press') {\n",
+ " if (event.which === this._key) {\n",
+ " return;\n",
+ " } else {\n",
+ " this._key = event.which;\n",
+ " }\n",
+ " }\n",
+ " if (name === 'key_release') {\n",
+ " this._key = null;\n",
+ " }\n",
+ "\n",
+ " var value = '';\n",
+ " if (event.ctrlKey && event.which !== 17) {\n",
+ " value += 'ctrl+';\n",
+ " }\n",
+ " if (event.altKey && event.which !== 18) {\n",
+ " value += 'alt+';\n",
+ " }\n",
+ " if (event.shiftKey && event.which !== 16) {\n",
+ " value += 'shift+';\n",
+ " }\n",
+ "\n",
+ " value += 'k';\n",
+ " value += event.which.toString();\n",
+ "\n",
+ " this._key_event_extra(event, name);\n",
+ "\n",
+ " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
+ " return false;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
+ " if (name === 'download') {\n",
+ " this.handle_save(this, null);\n",
+ " } else {\n",
+ " this.send_message('toolbar_button', { name: name });\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
+ " this.message.textContent = tooltip;\n",
+ "};\n",
+ "\n",
+ "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
+ "// prettier-ignore\n",
+ "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
+ "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+ "\n",
+ "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
+ "\n",
+ "mpl.default_extension = \"png\";/* global mpl */\n",
+ "\n",
+ "var comm_websocket_adapter = function (comm) {\n",
+ " // Create a \"websocket\"-like object which calls the given IPython comm\n",
+ " // object with the appropriate methods. Currently this is a non binary\n",
+ " // socket, so there is still some room for performance tuning.\n",
+ " var ws = {};\n",
+ "\n",
+ " ws.close = function () {\n",
+ " comm.close();\n",
+ " };\n",
+ " ws.send = function (m) {\n",
+ " //console.log('sending', m);\n",
+ " comm.send(m);\n",
+ " };\n",
+ " // Register the callback with on_msg.\n",
+ " comm.on_msg(function (msg) {\n",
+ " //console.log('receiving', msg['content']['data'], msg);\n",
+ " // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
+ " ws.onmessage(msg['content']['data']);\n",
+ " });\n",
+ " return ws;\n",
+ "};\n",
+ "\n",
+ "mpl.mpl_figure_comm = function (comm, msg) {\n",
+ " // This is the function which gets called when the mpl process\n",
+ " // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+ "\n",
+ " var id = msg.content.data.id;\n",
+ " // Get hold of the div created by the display call when the Comm\n",
+ " // socket was opened in Python.\n",
+ " var element = document.getElementById(id);\n",
+ " var ws_proxy = comm_websocket_adapter(comm);\n",
+ "\n",
+ " function ondownload(figure, _format) {\n",
+ " window.open(figure.canvas.toDataURL());\n",
+ " }\n",
+ "\n",
+ " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
+ "\n",
+ " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+ " // web socket which is closed, not our websocket->open comm proxy.\n",
+ " ws_proxy.onopen();\n",
+ "\n",
+ " fig.parent_element = element;\n",
+ " fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+ " if (!fig.cell_info) {\n",
+ " console.error('Failed to find cell for figure', id, fig);\n",
+ " return;\n",
+ " }\n",
+ " fig.cell_info[0].output_area.element.on(\n",
+ " 'cleared',\n",
+ " { fig: fig },\n",
+ " fig._remove_fig_handler\n",
+ " );\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
+ " var width = fig.canvas.width / fig.ratio;\n",
+ " fig.cell_info[0].output_area.element.off(\n",
+ " 'cleared',\n",
+ " fig._remove_fig_handler\n",
+ " );\n",
+ " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
+ "\n",
+ " // Update the output cell to use the data from the current canvas.\n",
+ " fig.push_to_output();\n",
+ " var dataURL = fig.canvas.toDataURL();\n",
+ " // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+ " // the notebook keyboard shortcuts fail.\n",
+ " IPython.keyboard_manager.enable();\n",
+ " fig.parent_element.innerHTML =\n",
+ " '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ " fig.close_ws(fig, msg);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
+ " fig.send_message('closing', msg);\n",
+ " // fig.ws.close()\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
+ " // Turn the data on the canvas into data in the output cell.\n",
+ " var width = this.canvas.width / this.ratio;\n",
+ " var dataURL = this.canvas.toDataURL();\n",
+ " this.cell_info[1]['text/html'] =\n",
+ " '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function () {\n",
+ " // Tell IPython that the notebook contents must change.\n",
+ " IPython.notebook.set_dirty(true);\n",
+ " this.send_message('ack', {});\n",
+ " var fig = this;\n",
+ " // Wait a second, then push the new image to the DOM so\n",
+ " // that it is saved nicely (might be nice to debounce this).\n",
+ " setTimeout(function () {\n",
+ " fig.push_to_output();\n",
+ " }, 1000);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var toolbar = document.createElement('div');\n",
+ " toolbar.classList = 'btn-toolbar';\n",
+ " this.root.appendChild(toolbar);\n",
+ "\n",
+ " function on_click_closure(name) {\n",
+ " return function (_event) {\n",
+ " return fig.toolbar_button_onclick(name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " function on_mouseover_closure(tooltip) {\n",
+ " return function (event) {\n",
+ " if (!event.currentTarget.disabled) {\n",
+ " return fig.toolbar_button_onmouseover(tooltip);\n",
+ " }\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " fig.buttons = {};\n",
+ " var buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'btn-group';\n",
+ " var button;\n",
+ " for (var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " /* Instead of a spacer, we start a new button group. */\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ " buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'btn-group';\n",
+ " continue;\n",
+ " }\n",
+ "\n",
+ " button = fig.buttons[name] = document.createElement('button');\n",
+ " button.classList = 'btn btn-default';\n",
+ " button.href = '#';\n",
+ " button.title = name;\n",
+ " button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
+ " button.addEventListener('click', on_click_closure(method_name));\n",
+ " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+ " buttonGroup.appendChild(button);\n",
+ " }\n",
+ "\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ "\n",
+ " // Add the status bar.\n",
+ " var status_bar = document.createElement('span');\n",
+ " status_bar.classList = 'mpl-message pull-right';\n",
+ " toolbar.appendChild(status_bar);\n",
+ " this.message = status_bar;\n",
+ "\n",
+ " // Add the close button to the window.\n",
+ " var buttongrp = document.createElement('div');\n",
+ " buttongrp.classList = 'btn-group inline pull-right';\n",
+ " button = document.createElement('button');\n",
+ " button.classList = 'btn btn-mini btn-primary';\n",
+ " button.href = '#';\n",
+ " button.title = 'Stop Interaction';\n",
+ " button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
+ " button.addEventListener('click', function (_evt) {\n",
+ " fig.handle_close(fig, {});\n",
+ " });\n",
+ " button.addEventListener(\n",
+ " 'mouseover',\n",
+ " on_mouseover_closure('Stop Interaction')\n",
+ " );\n",
+ " buttongrp.appendChild(button);\n",
+ " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
+ " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
+ " var fig = event.data.fig;\n",
+ " if (event.target !== this) {\n",
+ " // Ignore bubbled events from children.\n",
+ " return;\n",
+ " }\n",
+ " fig.close_ws(fig, {});\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function (el) {\n",
+ " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
+ " // this is important to make the div 'focusable\n",
+ " el.setAttribute('tabindex', 0);\n",
+ " // reach out to IPython and tell the keyboard manager to turn it's self\n",
+ " // off when our div gets focus\n",
+ "\n",
+ " // location in version 3\n",
+ " if (IPython.notebook.keyboard_manager) {\n",
+ " IPython.notebook.keyboard_manager.register_events(el);\n",
+ " } else {\n",
+ " // location in version 2\n",
+ " IPython.keyboard_manager.register_events(el);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
+ " var manager = IPython.notebook.keyboard_manager;\n",
+ " if (!manager) {\n",
+ " manager = IPython.keyboard_manager;\n",
+ " }\n",
+ "\n",
+ " // Check for shift+enter\n",
+ " if (event.shiftKey && event.which === 13) {\n",
+ " this.canvas_div.blur();\n",
+ " // select the cell after this one\n",
+ " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
+ " IPython.notebook.select(index + 1);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+ " fig.ondownload(fig, null);\n",
+ "};\n",
+ "\n",
+ "mpl.find_output_cell = function (html_output) {\n",
+ " // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+ " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+ " // IPython event is triggered only after the cells have been serialised, which for\n",
+ " // our purposes (turning an active figure into a static one), is too late.\n",
+ " var cells = IPython.notebook.get_cells();\n",
+ " var ncells = cells.length;\n",
+ " for (var i = 0; i < ncells; i++) {\n",
+ " var cell = cells[i];\n",
+ " if (cell.cell_type === 'code') {\n",
+ " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
+ " var data = cell.output_area.outputs[j];\n",
+ " if (data.data) {\n",
+ " // IPython >= 3 moved mimebundle to data attribute of output\n",
+ " data = data.data;\n",
+ " }\n",
+ " if (data['text/html'] === html_output) {\n",
+ " return [cell, data, j];\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "// Register the function which deals with the matplotlib target/channel.\n",
+ "// The kernel may be null if the page has been refreshed.\n",
+ "if (IPython.notebook.kernel !== null) {\n",
+ " IPython.notebook.kernel.comm_manager.register_target(\n",
+ " 'matplotlib',\n",
+ " mpl.mpl_figure_comm\n",
+ " );\n",
+ "}\n"
+ ],
"text/plain": [
- "<Figure size 576x576 with 1 Axes>"
+ "<IPython.core.display.Javascript object>"
]
},
- "metadata": {
- "needs_background": "light"
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
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\" width=\"800\">"
+ ],
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ]
},
+ "metadata": {},
"output_type": "display_data"
}
],
@@ -325,7 +1284,7 @@
},
{
"cell_type": "code",
- "execution_count": 10,
+ "execution_count": 9,
"id": "88982b21",
"metadata": {},
"outputs": [],
@@ -344,60 +1303,1977 @@
},
{
"cell_type": "code",
- "execution_count": 11,
+ "execution_count": 10,
"id": "333581b5",
"metadata": {},
"outputs": [
{
"data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 1152x1152 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "fig, ax = plt.subplots(figsize=(16, 16), ncols=2)\n",
- "data.plot.scatter(x=\"pca1\", y=\"pca2\", alpha=0.3, ax=ax[0])\n",
- "data.plot.scatter(x=\"x1\", y=\"x2\", alpha=0.3, ax=ax[1])\n",
- "ax[0].set(xlabel=\"PCA component 1\", ylabel=r\"PCA component 2\", title=\"PCA representation\")\n",
- "ax[1].set(xlabel=\"$x_1$\", ylabel=r\"$x_2$\", title=\"Original data\")\n",
- "plt.show()"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "54e538c6",
- "metadata": {},
- "source": [
- "It is interesting to understand how many PCA components are necessary to explain the variance of the data. This is easily obtainable from the PCA object."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 12,
- "id": "fa5ebbce",
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 1 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
+ "application/javascript": [
+ "/* Put everything inside the global mpl namespace */\n",
+ "/* global mpl */\n",
+ "window.mpl = {};\n",
+ "\n",
+ "mpl.get_websocket_type = function () {\n",
+ " if (typeof WebSocket !== 'undefined') {\n",
+ " return WebSocket;\n",
+ " } else if (typeof MozWebSocket !== 'undefined') {\n",
+ " return MozWebSocket;\n",
+ " } else {\n",
+ " alert(\n",
+ " 'Your browser does not have WebSocket support. ' +\n",
+ " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+ " 'Firefox 4 and 5 are also supported but you ' +\n",
+ " 'have to enable WebSockets in about:config.'\n",
+ " );\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
+ " this.id = figure_id;\n",
+ "\n",
+ " this.ws = websocket;\n",
+ "\n",
+ " this.supports_binary = this.ws.binaryType !== undefined;\n",
+ "\n",
+ " if (!this.supports_binary) {\n",
+ " var warnings = document.getElementById('mpl-warnings');\n",
+ " if (warnings) {\n",
+ " warnings.style.display = 'block';\n",
+ " warnings.textContent =\n",
+ " 'This browser does not support binary websocket messages. ' +\n",
+ " 'Performance may be slow.';\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.imageObj = new Image();\n",
+ "\n",
+ " this.context = undefined;\n",
+ " this.message = undefined;\n",
+ " this.canvas = undefined;\n",
+ " this.rubberband_canvas = undefined;\n",
+ " this.rubberband_context = undefined;\n",
+ " this.format_dropdown = undefined;\n",
+ "\n",
+ " this.image_mode = 'full';\n",
+ "\n",
+ " this.root = document.createElement('div');\n",
+ " this.root.setAttribute('style', 'display: inline-block');\n",
+ " this._root_extra_style(this.root);\n",
+ "\n",
+ " parent_element.appendChild(this.root);\n",
+ "\n",
+ " this._init_header(this);\n",
+ " this._init_canvas(this);\n",
+ " this._init_toolbar(this);\n",
+ "\n",
+ " var fig = this;\n",
+ "\n",
+ " this.waiting = false;\n",
+ "\n",
+ " this.ws.onopen = function () {\n",
+ " fig.send_message('supports_binary', { value: fig.supports_binary });\n",
+ " fig.send_message('send_image_mode', {});\n",
+ " if (fig.ratio !== 1) {\n",
+ " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
+ " }\n",
+ " fig.send_message('refresh', {});\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onload = function () {\n",
+ " if (fig.image_mode === 'full') {\n",
+ " // Full images could contain transparency (where diff images\n",
+ " // almost always do), so we need to clear the canvas so that\n",
+ " // there is no ghosting.\n",
+ " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+ " }\n",
+ " fig.context.drawImage(fig.imageObj, 0, 0);\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onunload = function () {\n",
+ " fig.ws.close();\n",
+ " };\n",
+ "\n",
+ " this.ws.onmessage = this._make_on_message_function(this);\n",
+ "\n",
+ " this.ondownload = ondownload;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_header = function () {\n",
+ " var titlebar = document.createElement('div');\n",
+ " titlebar.classList =\n",
+ " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
+ " var titletext = document.createElement('div');\n",
+ " titletext.classList = 'ui-dialog-title';\n",
+ " titletext.setAttribute(\n",
+ " 'style',\n",
+ " 'width: 100%; text-align: center; padding: 3px;'\n",
+ " );\n",
+ " titlebar.appendChild(titletext);\n",
+ " this.root.appendChild(titlebar);\n",
+ " this.header = titletext;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
+ "\n",
+ "mpl.figure.prototype._init_canvas = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var canvas_div = (this.canvas_div = document.createElement('div'));\n",
+ " canvas_div.setAttribute(\n",
+ " 'style',\n",
+ " 'border: 1px solid #ddd;' +\n",
+ " 'box-sizing: content-box;' +\n",
+ " 'clear: both;' +\n",
+ " 'min-height: 1px;' +\n",
+ " 'min-width: 1px;' +\n",
+ " 'outline: 0;' +\n",
+ " 'overflow: hidden;' +\n",
+ " 'position: relative;' +\n",
+ " 'resize: both;'\n",
+ " );\n",
+ "\n",
+ " function on_keyboard_event_closure(name) {\n",
+ " return function (event) {\n",
+ " return fig.key_event(event, name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " canvas_div.addEventListener(\n",
+ " 'keydown',\n",
+ " on_keyboard_event_closure('key_press')\n",
+ " );\n",
+ " canvas_div.addEventListener(\n",
+ " 'keyup',\n",
+ " on_keyboard_event_closure('key_release')\n",
+ " );\n",
+ "\n",
+ " this._canvas_extra_style(canvas_div);\n",
+ " this.root.appendChild(canvas_div);\n",
+ "\n",
+ " var canvas = (this.canvas = document.createElement('canvas'));\n",
+ " canvas.classList.add('mpl-canvas');\n",
+ " canvas.setAttribute('style', 'box-sizing: content-box;');\n",
+ "\n",
+ " this.context = canvas.getContext('2d');\n",
+ "\n",
+ " var backingStore =\n",
+ " this.context.backingStorePixelRatio ||\n",
+ " this.context.webkitBackingStorePixelRatio ||\n",
+ " this.context.mozBackingStorePixelRatio ||\n",
+ " this.context.msBackingStorePixelRatio ||\n",
+ " this.context.oBackingStorePixelRatio ||\n",
+ " this.context.backingStorePixelRatio ||\n",
+ " 1;\n",
+ "\n",
+ " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+ "\n",
+ " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
+ " 'canvas'\n",
+ " ));\n",
+ " rubberband_canvas.setAttribute(\n",
+ " 'style',\n",
+ " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
+ " );\n",
+ "\n",
+ " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
+ " if (this.ResizeObserver === undefined) {\n",
+ " if (window.ResizeObserver !== undefined) {\n",
+ " this.ResizeObserver = window.ResizeObserver;\n",
+ " } else {\n",
+ " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
+ " this.ResizeObserver = obs.ResizeObserver;\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
+ " var nentries = entries.length;\n",
+ " for (var i = 0; i < nentries; i++) {\n",
+ " var entry = entries[i];\n",
+ " var width, height;\n",
+ " if (entry.contentBoxSize) {\n",
+ " if (entry.contentBoxSize instanceof Array) {\n",
+ " // Chrome 84 implements new version of spec.\n",
+ " width = entry.contentBoxSize[0].inlineSize;\n",
+ " height = entry.contentBoxSize[0].blockSize;\n",
+ " } else {\n",
+ " // Firefox implements old version of spec.\n",
+ " width = entry.contentBoxSize.inlineSize;\n",
+ " height = entry.contentBoxSize.blockSize;\n",
+ " }\n",
+ " } else {\n",
+ " // Chrome <84 implements even older version of spec.\n",
+ " width = entry.contentRect.width;\n",
+ " height = entry.contentRect.height;\n",
+ " }\n",
+ "\n",
+ " // Keep the size of the canvas and rubber band canvas in sync with\n",
+ " // the canvas container.\n",
+ " if (entry.devicePixelContentBoxSize) {\n",
+ " // Chrome 84 implements new version of spec.\n",
+ " canvas.setAttribute(\n",
+ " 'width',\n",
+ " entry.devicePixelContentBoxSize[0].inlineSize\n",
+ " );\n",
+ " canvas.setAttribute(\n",
+ " 'height',\n",
+ " entry.devicePixelContentBoxSize[0].blockSize\n",
+ " );\n",
+ " } else {\n",
+ " canvas.setAttribute('width', width * fig.ratio);\n",
+ " canvas.setAttribute('height', height * fig.ratio);\n",
+ " }\n",
+ " canvas.setAttribute(\n",
+ " 'style',\n",
+ " 'width: ' + width + 'px; height: ' + height + 'px;'\n",
+ " );\n",
+ "\n",
+ " rubberband_canvas.setAttribute('width', width);\n",
+ " rubberband_canvas.setAttribute('height', height);\n",
+ "\n",
+ " // And update the size in Python. We ignore the initial 0/0 size\n",
+ " // that occurs as the element is placed into the DOM, which should\n",
+ " // otherwise not happen due to the minimum size styling.\n",
+ " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
+ " fig.request_resize(width, height);\n",
+ " }\n",
+ " }\n",
+ " });\n",
+ " this.resizeObserverInstance.observe(canvas_div);\n",
+ "\n",
+ " function on_mouse_event_closure(name) {\n",
+ " return function (event) {\n",
+ " return fig.mouse_event(event, name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mousedown',\n",
+ " on_mouse_event_closure('button_press')\n",
+ " );\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseup',\n",
+ " on_mouse_event_closure('button_release')\n",
+ " );\n",
+ " // Throttle sequential mouse events to 1 every 20ms.\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mousemove',\n",
+ " on_mouse_event_closure('motion_notify')\n",
+ " );\n",
+ "\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseenter',\n",
+ " on_mouse_event_closure('figure_enter')\n",
+ " );\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseleave',\n",
+ " on_mouse_event_closure('figure_leave')\n",
+ " );\n",
+ "\n",
+ " canvas_div.addEventListener('wheel', function (event) {\n",
+ " if (event.deltaY < 0) {\n",
+ " event.step = 1;\n",
+ " } else {\n",
+ " event.step = -1;\n",
+ " }\n",
+ " on_mouse_event_closure('scroll')(event);\n",
+ " });\n",
+ "\n",
+ " canvas_div.appendChild(canvas);\n",
+ " canvas_div.appendChild(rubberband_canvas);\n",
+ "\n",
+ " this.rubberband_context = rubberband_canvas.getContext('2d');\n",
+ " this.rubberband_context.strokeStyle = '#000000';\n",
+ "\n",
+ " this._resize_canvas = function (width, height, forward) {\n",
+ " if (forward) {\n",
+ " canvas_div.style.width = width + 'px';\n",
+ " canvas_div.style.height = height + 'px';\n",
+ " }\n",
+ " };\n",
+ "\n",
+ " // Disable right mouse context menu.\n",
+ " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ " });\n",
+ "\n",
+ " function set_focus() {\n",
+ " canvas.focus();\n",
+ " canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " window.setTimeout(set_focus, 100);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var toolbar = document.createElement('div');\n",
+ " toolbar.classList = 'mpl-toolbar';\n",
+ " this.root.appendChild(toolbar);\n",
+ "\n",
+ " function on_click_closure(name) {\n",
+ " return function (_event) {\n",
+ " return fig.toolbar_button_onclick(name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " function on_mouseover_closure(tooltip) {\n",
+ " return function (event) {\n",
+ " if (!event.currentTarget.disabled) {\n",
+ " return fig.toolbar_button_onmouseover(tooltip);\n",
+ " }\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " fig.buttons = {};\n",
+ " var buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'mpl-button-group';\n",
+ " for (var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " /* Instead of a spacer, we start a new button group. */\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ " buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'mpl-button-group';\n",
+ " continue;\n",
+ " }\n",
+ "\n",
+ " var button = (fig.buttons[name] = document.createElement('button'));\n",
+ " button.classList = 'mpl-widget';\n",
+ " button.setAttribute('role', 'button');\n",
+ " button.setAttribute('aria-disabled', 'false');\n",
+ " button.addEventListener('click', on_click_closure(method_name));\n",
+ " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+ "\n",
+ " var icon_img = document.createElement('img');\n",
+ " icon_img.src = '_images/' + image + '.png';\n",
+ " icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
+ " icon_img.alt = tooltip;\n",
+ " button.appendChild(icon_img);\n",
+ "\n",
+ " buttonGroup.appendChild(button);\n",
+ " }\n",
+ "\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ "\n",
+ " var fmt_picker = document.createElement('select');\n",
+ " fmt_picker.classList = 'mpl-widget';\n",
+ " toolbar.appendChild(fmt_picker);\n",
+ " this.format_dropdown = fmt_picker;\n",
+ "\n",
+ " for (var ind in mpl.extensions) {\n",
+ " var fmt = mpl.extensions[ind];\n",
+ " var option = document.createElement('option');\n",
+ " option.selected = fmt === mpl.default_extension;\n",
+ " option.innerHTML = fmt;\n",
+ " fmt_picker.appendChild(option);\n",
+ " }\n",
+ "\n",
+ " var status_bar = document.createElement('span');\n",
+ " status_bar.classList = 'mpl-message';\n",
+ " toolbar.appendChild(status_bar);\n",
+ " this.message = status_bar;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
+ " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+ " // which will in turn request a refresh of the image.\n",
+ " this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.send_message = function (type, properties) {\n",
+ " properties['type'] = type;\n",
+ " properties['figure_id'] = this.id;\n",
+ " this.ws.send(JSON.stringify(properties));\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.send_draw_message = function () {\n",
+ " if (!this.waiting) {\n",
+ " this.waiting = true;\n",
+ " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+ " var format_dropdown = fig.format_dropdown;\n",
+ " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+ " fig.ondownload(fig, format);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
+ " var size = msg['size'];\n",
+ " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
+ " fig._resize_canvas(size[0], size[1], msg['forward']);\n",
+ " fig.send_message('refresh', {});\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
+ " var x0 = msg['x0'] / fig.ratio;\n",
+ " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
+ " var x1 = msg['x1'] / fig.ratio;\n",
+ " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
+ " x0 = Math.floor(x0) + 0.5;\n",
+ " y0 = Math.floor(y0) + 0.5;\n",
+ " x1 = Math.floor(x1) + 0.5;\n",
+ " y1 = Math.floor(y1) + 0.5;\n",
+ " var min_x = Math.min(x0, x1);\n",
+ " var min_y = Math.min(y0, y1);\n",
+ " var width = Math.abs(x1 - x0);\n",
+ " var height = Math.abs(y1 - y0);\n",
+ "\n",
+ " fig.rubberband_context.clearRect(\n",
+ " 0,\n",
+ " 0,\n",
+ " fig.canvas.width / fig.ratio,\n",
+ " fig.canvas.height / fig.ratio\n",
+ " );\n",
+ "\n",
+ " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
+ " // Updates the figure title.\n",
+ " fig.header.textContent = msg['label'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
+ " var cursor = msg['cursor'];\n",
+ " switch (cursor) {\n",
+ " case 0:\n",
+ " cursor = 'pointer';\n",
+ " break;\n",
+ " case 1:\n",
+ " cursor = 'default';\n",
+ " break;\n",
+ " case 2:\n",
+ " cursor = 'crosshair';\n",
+ " break;\n",
+ " case 3:\n",
+ " cursor = 'move';\n",
+ " break;\n",
+ " }\n",
+ " fig.rubberband_canvas.style.cursor = cursor;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
+ " fig.message.textContent = msg['message'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
+ " // Request the server to send over a new figure.\n",
+ " fig.send_draw_message();\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
+ " fig.image_mode = msg['mode'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
+ " for (var key in msg) {\n",
+ " if (!(key in fig.buttons)) {\n",
+ " continue;\n",
+ " }\n",
+ " fig.buttons[key].disabled = !msg[key];\n",
+ " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
+ " if (msg['mode'] === 'PAN') {\n",
+ " fig.buttons['Pan'].classList.add('active');\n",
+ " fig.buttons['Zoom'].classList.remove('active');\n",
+ " } else if (msg['mode'] === 'ZOOM') {\n",
+ " fig.buttons['Pan'].classList.remove('active');\n",
+ " fig.buttons['Zoom'].classList.add('active');\n",
+ " } else {\n",
+ " fig.buttons['Pan'].classList.remove('active');\n",
+ " fig.buttons['Zoom'].classList.remove('active');\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function () {\n",
+ " // Called whenever the canvas gets updated.\n",
+ " this.send_message('ack', {});\n",
+ "};\n",
+ "\n",
+ "// A function to construct a web socket function for onmessage handling.\n",
+ "// Called in the figure constructor.\n",
+ "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
+ " return function socket_on_message(evt) {\n",
+ " if (evt.data instanceof Blob) {\n",
+ " /* FIXME: We get \"Resource interpreted as Image but\n",
+ " * transferred with MIME type text/plain:\" errors on\n",
+ " * Chrome. But how to set the MIME type? It doesn't seem\n",
+ " * to be part of the websocket stream */\n",
+ " evt.data.type = 'image/png';\n",
+ "\n",
+ " /* Free the memory for the previous frames */\n",
+ " if (fig.imageObj.src) {\n",
+ " (window.URL || window.webkitURL).revokeObjectURL(\n",
+ " fig.imageObj.src\n",
+ " );\n",
+ " }\n",
+ "\n",
+ " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+ " evt.data\n",
+ " );\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " } else if (\n",
+ " typeof evt.data === 'string' &&\n",
+ " evt.data.slice(0, 21) === 'data:image/png;base64'\n",
+ " ) {\n",
+ " fig.imageObj.src = evt.data;\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " var msg = JSON.parse(evt.data);\n",
+ " var msg_type = msg['type'];\n",
+ "\n",
+ " // Call the \"handle_{type}\" callback, which takes\n",
+ " // the figure and JSON message as its only arguments.\n",
+ " try {\n",
+ " var callback = fig['handle_' + msg_type];\n",
+ " } catch (e) {\n",
+ " console.log(\n",
+ " \"No handler for the '\" + msg_type + \"' message type: \",\n",
+ " msg\n",
+ " );\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " if (callback) {\n",
+ " try {\n",
+ " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+ " callback(fig, msg);\n",
+ " } catch (e) {\n",
+ " console.log(\n",
+ " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
+ " e,\n",
+ " e.stack,\n",
+ " msg\n",
+ " );\n",
+ " }\n",
+ " }\n",
+ " };\n",
+ "};\n",
+ "\n",
+ "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+ "mpl.findpos = function (e) {\n",
+ " //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+ " var targ;\n",
+ " if (!e) {\n",
+ " e = window.event;\n",
+ " }\n",
+ " if (e.target) {\n",
+ " targ = e.target;\n",
+ " } else if (e.srcElement) {\n",
+ " targ = e.srcElement;\n",
+ " }\n",
+ " if (targ.nodeType === 3) {\n",
+ " // defeat Safari bug\n",
+ " targ = targ.parentNode;\n",
+ " }\n",
+ "\n",
+ " // pageX,Y are the mouse positions relative to the document\n",
+ " var boundingRect = targ.getBoundingClientRect();\n",
+ " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
+ " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
+ "\n",
+ " return { x: x, y: y };\n",
+ "};\n",
+ "\n",
+ "/*\n",
+ " * return a copy of an object with only non-object keys\n",
+ " * we need this to avoid circular references\n",
+ " * http://stackoverflow.com/a/24161582/3208463\n",
+ " */\n",
+ "function simpleKeys(original) {\n",
+ " return Object.keys(original).reduce(function (obj, key) {\n",
+ " if (typeof original[key] !== 'object') {\n",
+ " obj[key] = original[key];\n",
+ " }\n",
+ " return obj;\n",
+ " }, {});\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.mouse_event = function (event, name) {\n",
+ " var canvas_pos = mpl.findpos(event);\n",
+ "\n",
+ " if (name === 'button_press') {\n",
+ " this.canvas.focus();\n",
+ " this.canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " var x = canvas_pos.x * this.ratio;\n",
+ " var y = canvas_pos.y * this.ratio;\n",
+ "\n",
+ " this.send_message(name, {\n",
+ " x: x,\n",
+ " y: y,\n",
+ " button: event.button,\n",
+ " step: event.step,\n",
+ " guiEvent: simpleKeys(event),\n",
+ " });\n",
+ "\n",
+ " /* This prevents the web browser from automatically changing to\n",
+ " * the text insertion cursor when the button is pressed. We want\n",
+ " * to control all of the cursor setting manually through the\n",
+ " * 'cursor' event from matplotlib */\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
+ " // Handle any extra behaviour associated with a key event\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.key_event = function (event, name) {\n",
+ " // Prevent repeat events\n",
+ " if (name === 'key_press') {\n",
+ " if (event.which === this._key) {\n",
+ " return;\n",
+ " } else {\n",
+ " this._key = event.which;\n",
+ " }\n",
+ " }\n",
+ " if (name === 'key_release') {\n",
+ " this._key = null;\n",
+ " }\n",
+ "\n",
+ " var value = '';\n",
+ " if (event.ctrlKey && event.which !== 17) {\n",
+ " value += 'ctrl+';\n",
+ " }\n",
+ " if (event.altKey && event.which !== 18) {\n",
+ " value += 'alt+';\n",
+ " }\n",
+ " if (event.shiftKey && event.which !== 16) {\n",
+ " value += 'shift+';\n",
+ " }\n",
+ "\n",
+ " value += 'k';\n",
+ " value += event.which.toString();\n",
+ "\n",
+ " this._key_event_extra(event, name);\n",
+ "\n",
+ " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
+ " return false;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
+ " if (name === 'download') {\n",
+ " this.handle_save(this, null);\n",
+ " } else {\n",
+ " this.send_message('toolbar_button', { name: name });\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
+ " this.message.textContent = tooltip;\n",
+ "};\n",
+ "\n",
+ "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
+ "// prettier-ignore\n",
+ "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
+ "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+ "\n",
+ "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
+ "\n",
+ "mpl.default_extension = \"png\";/* global mpl */\n",
+ "\n",
+ "var comm_websocket_adapter = function (comm) {\n",
+ " // Create a \"websocket\"-like object which calls the given IPython comm\n",
+ " // object with the appropriate methods. Currently this is a non binary\n",
+ " // socket, so there is still some room for performance tuning.\n",
+ " var ws = {};\n",
+ "\n",
+ " ws.close = function () {\n",
+ " comm.close();\n",
+ " };\n",
+ " ws.send = function (m) {\n",
+ " //console.log('sending', m);\n",
+ " comm.send(m);\n",
+ " };\n",
+ " // Register the callback with on_msg.\n",
+ " comm.on_msg(function (msg) {\n",
+ " //console.log('receiving', msg['content']['data'], msg);\n",
+ " // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
+ " ws.onmessage(msg['content']['data']);\n",
+ " });\n",
+ " return ws;\n",
+ "};\n",
+ "\n",
+ "mpl.mpl_figure_comm = function (comm, msg) {\n",
+ " // This is the function which gets called when the mpl process\n",
+ " // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+ "\n",
+ " var id = msg.content.data.id;\n",
+ " // Get hold of the div created by the display call when the Comm\n",
+ " // socket was opened in Python.\n",
+ " var element = document.getElementById(id);\n",
+ " var ws_proxy = comm_websocket_adapter(comm);\n",
+ "\n",
+ " function ondownload(figure, _format) {\n",
+ " window.open(figure.canvas.toDataURL());\n",
+ " }\n",
+ "\n",
+ " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
+ "\n",
+ " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+ " // web socket which is closed, not our websocket->open comm proxy.\n",
+ " ws_proxy.onopen();\n",
+ "\n",
+ " fig.parent_element = element;\n",
+ " fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+ " if (!fig.cell_info) {\n",
+ " console.error('Failed to find cell for figure', id, fig);\n",
+ " return;\n",
+ " }\n",
+ " fig.cell_info[0].output_area.element.on(\n",
+ " 'cleared',\n",
+ " { fig: fig },\n",
+ " fig._remove_fig_handler\n",
+ " );\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
+ " var width = fig.canvas.width / fig.ratio;\n",
+ " fig.cell_info[0].output_area.element.off(\n",
+ " 'cleared',\n",
+ " fig._remove_fig_handler\n",
+ " );\n",
+ " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
+ "\n",
+ " // Update the output cell to use the data from the current canvas.\n",
+ " fig.push_to_output();\n",
+ " var dataURL = fig.canvas.toDataURL();\n",
+ " // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+ " // the notebook keyboard shortcuts fail.\n",
+ " IPython.keyboard_manager.enable();\n",
+ " fig.parent_element.innerHTML =\n",
+ " '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ " fig.close_ws(fig, msg);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
+ " fig.send_message('closing', msg);\n",
+ " // fig.ws.close()\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
+ " // Turn the data on the canvas into data in the output cell.\n",
+ " var width = this.canvas.width / this.ratio;\n",
+ " var dataURL = this.canvas.toDataURL();\n",
+ " this.cell_info[1]['text/html'] =\n",
+ " '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function () {\n",
+ " // Tell IPython that the notebook contents must change.\n",
+ " IPython.notebook.set_dirty(true);\n",
+ " this.send_message('ack', {});\n",
+ " var fig = this;\n",
+ " // Wait a second, then push the new image to the DOM so\n",
+ " // that it is saved nicely (might be nice to debounce this).\n",
+ " setTimeout(function () {\n",
+ " fig.push_to_output();\n",
+ " }, 1000);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var toolbar = document.createElement('div');\n",
+ " toolbar.classList = 'btn-toolbar';\n",
+ " this.root.appendChild(toolbar);\n",
+ "\n",
+ " function on_click_closure(name) {\n",
+ " return function (_event) {\n",
+ " return fig.toolbar_button_onclick(name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " function on_mouseover_closure(tooltip) {\n",
+ " return function (event) {\n",
+ " if (!event.currentTarget.disabled) {\n",
+ " return fig.toolbar_button_onmouseover(tooltip);\n",
+ " }\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " fig.buttons = {};\n",
+ " var buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'btn-group';\n",
+ " var button;\n",
+ " for (var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " /* Instead of a spacer, we start a new button group. */\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ " buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'btn-group';\n",
+ " continue;\n",
+ " }\n",
+ "\n",
+ " button = fig.buttons[name] = document.createElement('button');\n",
+ " button.classList = 'btn btn-default';\n",
+ " button.href = '#';\n",
+ " button.title = name;\n",
+ " button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
+ " button.addEventListener('click', on_click_closure(method_name));\n",
+ " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+ " buttonGroup.appendChild(button);\n",
+ " }\n",
+ "\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ "\n",
+ " // Add the status bar.\n",
+ " var status_bar = document.createElement('span');\n",
+ " status_bar.classList = 'mpl-message pull-right';\n",
+ " toolbar.appendChild(status_bar);\n",
+ " this.message = status_bar;\n",
+ "\n",
+ " // Add the close button to the window.\n",
+ " var buttongrp = document.createElement('div');\n",
+ " buttongrp.classList = 'btn-group inline pull-right';\n",
+ " button = document.createElement('button');\n",
+ " button.classList = 'btn btn-mini btn-primary';\n",
+ " button.href = '#';\n",
+ " button.title = 'Stop Interaction';\n",
+ " button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
+ " button.addEventListener('click', function (_evt) {\n",
+ " fig.handle_close(fig, {});\n",
+ " });\n",
+ " button.addEventListener(\n",
+ " 'mouseover',\n",
+ " on_mouseover_closure('Stop Interaction')\n",
+ " );\n",
+ " buttongrp.appendChild(button);\n",
+ " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
+ " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
+ " var fig = event.data.fig;\n",
+ " if (event.target !== this) {\n",
+ " // Ignore bubbled events from children.\n",
+ " return;\n",
+ " }\n",
+ " fig.close_ws(fig, {});\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function (el) {\n",
+ " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
+ " // this is important to make the div 'focusable\n",
+ " el.setAttribute('tabindex', 0);\n",
+ " // reach out to IPython and tell the keyboard manager to turn it's self\n",
+ " // off when our div gets focus\n",
+ "\n",
+ " // location in version 3\n",
+ " if (IPython.notebook.keyboard_manager) {\n",
+ " IPython.notebook.keyboard_manager.register_events(el);\n",
+ " } else {\n",
+ " // location in version 2\n",
+ " IPython.keyboard_manager.register_events(el);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
+ " var manager = IPython.notebook.keyboard_manager;\n",
+ " if (!manager) {\n",
+ " manager = IPython.keyboard_manager;\n",
+ " }\n",
+ "\n",
+ " // Check for shift+enter\n",
+ " if (event.shiftKey && event.which === 13) {\n",
+ " this.canvas_div.blur();\n",
+ " // select the cell after this one\n",
+ " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
+ " IPython.notebook.select(index + 1);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+ " fig.ondownload(fig, null);\n",
+ "};\n",
+ "\n",
+ "mpl.find_output_cell = function (html_output) {\n",
+ " // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+ " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+ " // IPython event is triggered only after the cells have been serialised, which for\n",
+ " // our purposes (turning an active figure into a static one), is too late.\n",
+ " var cells = IPython.notebook.get_cells();\n",
+ " var ncells = cells.length;\n",
+ " for (var i = 0; i < ncells; i++) {\n",
+ " var cell = cells[i];\n",
+ " if (cell.cell_type === 'code') {\n",
+ " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
+ " var data = cell.output_area.outputs[j];\n",
+ " if (data.data) {\n",
+ " // IPython >= 3 moved mimebundle to data attribute of output\n",
+ " data = data.data;\n",
+ " }\n",
+ " if (data['text/html'] === html_output) {\n",
+ " return [cell, data, j];\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "// Register the function which deals with the matplotlib target/channel.\n",
+ "// The kernel may be null if the page has been refreshed.\n",
+ "if (IPython.notebook.kernel !== null) {\n",
+ " IPython.notebook.kernel.comm_manager.register_target(\n",
+ " 'matplotlib',\n",
+ " mpl.mpl_figure_comm\n",
+ " );\n",
+ "}\n"
+ ],
+ "text/plain": [
+ "<IPython.core.display.Javascript object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
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SdsBAwaEfQ56R++zadMmdevWTddcc40yMjK0ceNGFRcX6+GHH24zRoQT0CP53M8995wcx9Htt9+u5cuXq7CwUMXFxfre976nIUOGtDyvvYB+9913q2vXrpo8ebJWrlypTZs2qbi4WN/85jc7dUE7AJ1DQAc84HYOemuBc53DvcDXZZdd1m4Y/fGPf9zu77sFvG3btslxHE2ePFnFxcUhH4Ft4ZGuoH/9619v87yRI0fqwgsvdH2vUCvXTU1Nys3N1bXXXivHcVruoxvJa3U2oL/xxhtyHEe5ublBP1+1alWnAnpHK+gzZ86UREAH4A8dXSSuoaHB9SJx+/fvb/P8eKyghxPQ77//fvXq1avNSnu0AT2SFfQRI0boO9/5TpvXuPzyy8MO6H379tXYsWPb/Hzw4MEEdMBDBHTAA+EG9HBus5aZmSlJqqqqkuM4uvHGG7V27do2j2uuuUY9evTQBx984Pp+7QW8YcOG6brrrgv7u7mdgz5lypSWn7kF9D/+8Y/q06dPWBe2a628vFyO4+ill16K+LXCDejTp08P2tYf8Oabb4acUAlcEO7UgD5+/Hg5jqPDhw93+H6BHRCtDzbvvPPOkOegE9ABmCxwm7Ubbrgh6HoZ0okV9sBt1jZu3Njy80gCemVlpRzHCTqFSYrsHPRwAvr48eN1xhlnBF2z5fDhwzrnnHOiCuiBcTycc9AvueQSXXvttUHPq6ioUNeuXYMC+j/+8Y+QbSFJX/ziF3XbbbcF/Wz58uVyHIeADniIgA54INyALknLli1Tnz59NHToUD377LPKyclRTk6OZsyYoREjRrRsGZ8wYYIcp+2FxAIC4fGFF15wfa/2At6aNWvUs2dPffe739XChQtbrvj65JNP6qabbmrz3c4++2zdcsstWrlypWbNmqX+/ftr8ODB+vDDD1ue6xbQP/nkE40YMUJnnXWWnnvuOa1atUpvv/22Zs2apR//+McqLCyUdOK+8b/+9a+Vlpam3NxcZWVl6aqrrlL37t1VWVkZ0WtJ4Qf0wAHdbbfdpvz8/JYdBB988IH69u2rb37zm8rMzNSyZcv0s5/9TMOGDWsT0APtlJKS0rI18ciRIyHfL3AV94EDB+rll1/W22+/rXvuuUddunTRHXfcEdbfj4AOwCTTp09X165dNXLkSKWlpWn9+vVKS0vTZZddpq5du2r69OlBz48koEsnruLerVs3TZ48WatWrQq6ivupt+LsTEDPycmR4zi66aab9M477yg9PV3/9m//1lLzIw3o0sk7rzz00EMtV3EfNGhQm6u4B64q/9hjjyknJ0d//vOfNXDgQJ133nlBAV06Maacf/75evvtt4N2jv3qV79Sz5499ac//Uk5OTl6+umn1a9fP5111lkEdMBDBHTAA5EEdOnEhcfuuOMOffWrX1XPnj3Vu3dvfe1rX9P48eNVV1eno0ePqn///kHnd7d27NgxnXXWWbrwwgtdn9NewJNOzM7/5Cc/Uf/+/dW9e3cNHDhQV199dcsW61O/2zvvvKObb75ZX/jCF9S7d29dd911qq6uDno9t4AunQjWjzzyiM4//3z16NFDZ555pi688ELdf//9LRfeWb58ub7//e9r8ODB6tGjh/r376/rrrtOGzZsiPi1pPADunRiVXvQoEHq2rVr0MFdfn6+LrvsMvXp00f9+vXTrbfeqnfffbdNQD9y5IhuvfVW9evXr+Vich3dB/2///u/9aUvfUndu3fX+eefr2eeecb1PuitEdABmKagoEA33XSTBgwYoNNOO039+/fXj370o5ZTlE4VaUAP3Ae9f//+LRdcLSgo0Jlnnhm0Qt2ZgC5Jc+bM0fnnn6+ePXvqK1/5iqZOnarZs2dHHdCPHDmiCRMmtPncrceFI0eO6IEHHtDgwYPVq1cvXXLJJcrKytKYMWPaBPTVq1cHXUwu8Doff/yxbrnlFvXv3199+vTRFVdcoQ0bNoT9WQHEBwEdQExFOvkAAEAiBE61WrBggdcfBQBcEdABxBQBHQDgtXfeeUePP/64li9frpycHD3//PPq37+/hg0b1uaibgBgEgI6gJgioAMAvFZYWKjLL79cffv21WmnnaaBAwdqzJgxIW9pCgAmIaADAAAAAGAAAjoAAAAAAAYgoAMAgE7529/+pl/84hf64he/qN69e+ub3/ymSkpKvP5YAAD4DgEdAABE7aOPPtKQIUM0duxYbdq0SXV1dVq9erVqamq8/mgAAPgOAd0yn332mRoaGnTgwAEdPHiQBw8ePHgk6HHgwAE1NDQE3bs+GUycOFFXXHFFp16DsYkHDx48vHkk69jkZwR0yzQ0NMhxHB48ePDg4dGjoaHB66Egpi644ALdd999uummm9SvXz9dfPHFevnll9v9naampqADxKqqKs//Ljx48OBh8yPZxiY/I6Bb5sCBAy2d0OsZOx48ePCw6RGYID1w4IDXQ0FM9ezZUz179tTkyZP17rvvaubMmerVq5fmzZvn+jspKSmuB4he/5148ODBw6ZHso5NfkZAt8zBgwflOI4OHjzo9UcBAKska/3t3r27LrvssqCf3X333Ro5cqTr77ReQQ8cICZb2wCA6ZJ1bPIzArpl6IQA4I1krb/nnHOObrnllqCf/fnPf9agQYPCfo1kbRsAMB311zwEdMvQCQHAG8laf3/+85+3uUjcfffd12ZVvT3J2jYAYDrqr3kI6JahEwKAN5K1/hYVFem0007TE088oerqai1YsEB9+vRRWlpa2K+RrG0DAKaj/pqHgG4ZOiEAeCOZ6++yZcv0jW98Qz179tTw4cM7vIp7a8ncNgBgMuqveQjolqETAoA3qL/uaBsA8Ab11zwEdMvQCQHAG9Rfd7QNAHiD+mseArpl6IQA4A3qrzvaBgC8Qf01DwHdMnRCAPAG9dcdbQMA3qD+moeAbhk6IQB4g/rrjrYBAG9Qf81DQLcMnRAAvEH9dUfbAIA3qL/mIaBbhk4IAN6g/rqjbQDAG9Rf8xDQLUMnBABvUH/d0TYA4A3qr3kI6JahEwKAN6i/7mgbAPAG9dc8BHTL0AkBwBvUX3e0DQB4g/prHgK6ZeiEAOAN6q872gYAvEH9NQ8B3TJ0QgDwBvXXHW0DAN6g/pqHgG4ZOiEAeIP66462AQBvUH/NQ0C3DJ0QALxB/XVH2wCAN6i/5iGgW4ZOCADeoP66o20AwBvUX/MQ0C1DJwQAb1B/3dE2AOAN6q95COiWoRMCgDeov+5oGwDwBvXXPAR0y9AJAcAb1F93tA0AeIP6ax4CumXohADgDeqvO9oGALxB/TUPAd0ydEIA8Ab11x1tAwDeoP6ah4BuGTohAHiD+uuOtgEAb1B/zUNAtwydEAC8Qf11R9sAgDeov+YhoFuGTggA3qD+uqNtAMAb1F/zENAtQycEAG9Qf93RNgDgDeqveQjolqETIp4OHWnW/sYmHTrS7PVHAYxD/XVH2wBIJn46HqL+moeAbhk6IeLh6LHPVFL/kdKLdmpOXq3Si3aqpP4jHT32mdcfDTAG9dcdbQMgGfjxeIj6ax4CumXohIiHkvqPNDO3RouKd2lFxR4tKt6lmbk1Kqn/yOuPBhiD+uuOtgGQDPx4PET9NQ8B3TJ0QsTaoSPNSi/aqUXFu7Tqvb0tj4yiXUov2umL7V1AIlB/3dE2APzOr8dD1F/zENAtQydErO1vbNKcvFqtqNgTNCCtqNijuRtrtb+xyeuPCBiB+uuOtgHgd349HqL+moeAbhk6IWLNrzPGQKJRf93RNgD8zq/HQ9Rf8xDQLUMnRDwEzrnKKDpxzlVGkfnnXAGJRv11R9sASAZ+PB6i/pqHgG4ZOiHi4dSrls7d6I+rlgKJRv11R9sASAZ+PB6i/pqHgO6RJ598Ut/61rd0xhlnqF+/fvrBD36gbdu2dfh7ubm5uuSSS9SzZ0+de+65Sk1Njeh96YSIJz/d9xNINOqvO9oGQDLx0/EQ9dc8BHSPXHvttZo7d64qKytVXl6u66+/Xuecc44++eQT19+pra1Vnz59dO+996qqqkqzZs1S9+7dtXjx4rDfl04IAN6g/rqjbQDAG9Rf8xDQDbFv3z45jqN169a5Puehhx7S8OHDg3522223aeTIkWG/D50QALxB/XVH2wCAN6i/5iGgG6K6ulqO42jLli2uz7nyyit1zz33BP0sMzNTp512mo4ePRrW+9AJAcAb1F93tA0AeIP6ax4CugGOHz+uG264QVdccUW7zxs2bJieeOKJoJ9t3LhRjuNoz549IX+nqalJBw8ebHk0NDTQCQHAAxwEuaNtAPiNn84zbw/11zwEdAPccccdGjJkiBoaGtp93rBhw/Tkk08G/SwvL0+O4+j9998P+TspKSlyHKfNg04IAInFQZA72gaAX5x6pfY5ef64Unt7qL/mIaB77K677tJZZ52l2traDp8bzRZ3VtABwAwcBLmjbQD4ReBe54uKT9zrfFGx+fc6bw/11zwEdI8cP35cd955pwYNGqTt27eH9TsPPfSQLrjggqCf3X777VwkDgB8gPrrjrYB4AeHjjQrvWinFhXv0qr39rY8Mop2Kb1opy+3u1N/zUNA98i4ceN05plnKjc3V++//37L4/Dhwy3PmTRpkm6++eaW/w7cZu3+++9XVVWVZs+ezW3WAMAnqL/uaBsAfrC/sUlz8mq1omJPUEBfUbFHczfWan9jk9cfMWLUX/MQ0D0S6rxwx3E0d+7clueMGTNGo0aNCvq93NxcjRgxQj169NDQoUOVmpoa0fvSCQHAG9Rfd7QNAD9gBR2JQEC3DJ0QALxB/XVH2wDwi8A56BlFJ85BzyjiHHTEFgHdMnRCAPAG9dcdbQPAL069ivvcjVzFHbFHQLcMnRAAvEH9dUfbAPAb7oOOeCGgW4ZOCADeoP66o20AwBvUX/MQ0C1DJwQAb1B/3dE2AOAN6q95COiWoRMCgDeov+5oGwDwBvXXPAR0y9AJAcAb1F93tA0AeIP6ax4CumXohGhPslzwBDAR9dcdbQMA3qD+moeAbhk6IUI59ZYhc/L8f8sQwETUX3e0DQB4g/prHgK6ZeiECKWk/iPNzK3RouJdWlGxR4uKd2lmbo1K6j/y+qMBSYP66462AQBvUH/NQ0C3DJ0QrR060qz0op1aVLxLq97b2/LIKNql9KKdbHcHYoT66462AeAV20/vo/6ah4BuGTohWtvf2KQ5ebVaUbEnKKCvqNijuRtrtb+xyeuPCCQF6q872gZAonF63wnUX/MQ0C1DJ0RrrKADiUH9dUfbAEg0Tu87gfprHgK6ZeiECCUwSGUUnRikMorsHKSAeKL+uqNtACQSixMnUX/NQ0C3DJ0QoZy6zWvuRnu3eQHxRP11R9sASCRO7zuJ+mseArpl6IRoj+0XSgHiifrrjrYBkEisoJ9E/TUPAd0ydEIgNCYnEG/UX3e0DYBE4/S+E6i/5iGgW4ZOCATjKq5IFOqvO9oGQKJxet8J1F/zENAtQycEgnEVVyQK9dcdbQMkJz/sTvPDZ4wn6q95COiWoRMCJ3EOGhKJ+uuOtgGSC7vT/IP6ax4CumXohMBJXMUViUT9dUfbAMmF3Wn+Qf01DwHdMnRC4CTTVtBt32aX7Ki/7mgbIHmYNraifdRf8xDQLUMnBIKZcBVXtgLagfrrjrYBkge70/yF+mseArpl6IRAMBOu4spWQDtQf93RNkDyYAXdX6i/5iGgW4ZOCITm1fZyDmTsQf11R9sAycWE3WkID/XXPAR0y9AJAbOwFdAe1F93tA2QXEzYnYbwUH/NQ0C3DJ0QMAsr6Pag/rqjbYDkxMVPzUf9NQ8B3TJ0QsA8bAW0A/XXHW0DAN6g/pqHgG4ZOiFgHrYC2oH66462AQBvUH/NQ0C3DJ0QMBdbAZMb9dcdbQMA3qD+moeAbhk6IQB4g/rrjrYBAG9Qf81DQLcMnRAwA6vl9qH+uqNtAMAb1F/zENAtQycEvHXq+eZz8jjf3CbUX3e0DQB4g/prHjdFE7UAACAASURBVAK6ZeiEgLcCV2xfVHziiu2Lirliuy2ov+5oGwDwBvXXPAR0y9AJAe9wz3O7UX/d0TYA/CgZTlej/pqHgG4ZOiHgnf2NTZqTV6sVFXuCAvqKij2au7FW+xubvP6IiCPqrzvaBoCfJNPpatRf8xDQLUMnBLzDCrrdqL/uaBsApmlvdTyZTlej/pqHgG4ZOiHgrcCgnlF0YlDPKPLvoI7IUH/d0TYATNHR6niyTbZTf81DQLcMnRDw1qkD/9yN/t4Wh8hQf93RNgC8dOpqeUer48l2uhr11zwEdMvQCQEzJMOFZRAZ6q872gaAF1qvls/Lr9O07Cqlb9rpujpu2gp6Z48nqL/mIaBbhk4IAN6g/rqjbQB4ofVq+ewNtbrl1SLNWL293dVxE05Xi9WF6qi/5iGgW4ZOCADeoP66o20AJFqolfDlFbs1PqNMD2SUaXn5btfVcRNOV4vVheqov+YhoFuGTggA3qD+uqNtACSa27nk03O269ZXizR7fW2Hq+Nena4Wy2321F/zENAtQycE/Ivz1v2N+uuOtgGQaG4hd2FhvaZlV2lefp2xF3ON5YXqqL/mIaBbhk4I+E+szjODt6i/7mgbAF5o71xykyfFWUFPbgR0y9AJAf+J1Xlm8Bb11x1tA8ALJpxLHq1YXaiO+mseArpl6ISAv5h2OxdEj/rrjrYB4CWTV8vdxGpygfprHgK6ZeiEgL/E8jwzeIv66462AYDocB/05ENAtwydEPAXVtCTB/XXHW0DAN6g/pqHgG4ZOiHgP7E6zwzeov66o20AwBvUX/MQ0C1DJwT8x88XscFJ1F93tA0AeIP6ax4CumXohIB/+fEiNjiJ+uuOtgEAb1B/zUNAtwydEAC8Qf11R9sAgDeov+YhoFuGTggA3qD+uqNtAMAb1F/zENAtQycEAG9Qf93RNgDgDeqveQjolqETAoA3qL/uaBsA8Ab11zwEdMvQCQHAG9Rfd7QNAHiD+mseArpl6IQA4A3qrzvaBgC8Qf01DwHdMnRCAPAG9dcdbQMA3qD+moeAbhk6IQB4g/rrjrYBAG9Qf81DQLcMnRAAvEH9dUfbAIA3qL/mIaBbhk4IAN6g/rqjbQAzHTrSrP2NTTp0pNnrj4I4of6ah4BuGTohAHiD+uuOtgHMcvTYZyqp/0jpRTs1J69W6UU7VVL/kY4e+8zrj4YYo/6ah4BuGTohAHiD+uuOtgHMUlL/kWbm1mhR8S6tqNijRcW7NDO3RiX1H3n90WKCnQEnUX/NQ0C3DJ0QALxB/XVH2wDmOHSkWelFO7WoeJdWvbe35ZFRtEvpRTt9HWrZGdAW9dc8BHTL0AkBwBvUX3e0DWCO/Y1NmpNXqxUVe4IC+oqKPZq7sVb7G5u8/ohRS/adAdGg/pqHgG4ZOiEAeIP66462AcyRrCvoyfq9Oov6ax4CumXohADgDeqvO9oGMEtgpTmj6MRKc0aRf1aa3c4vT+adAZ1B/TUPAd0ydEIA8Ab11x1tA5jl1HO15270x7naHZ1fzgp6aNRf8xDQLUMnBABvUH/d0TaAmfx0tfNwzi/3886AeKH+moeAbhk6IWzmpwMNJB/qrzvaBkBnhLs67sedAfFG/TUPAd0ydELYiNuqwATUX3e0DYDOiPT8cibsT6L+moeAbhk6IWzEbVVgAlvq75NPPinHcXTvvfeG/Tu2tA2A+OD88uhRf81DQLcMnRC2YdCGKWyov0VFRRo6dKguuugiAjqAhOL88uhQf81DQLcMnRC24bYqMEWy19/GxkYNGzZMq1at0qhRowjoABKK88ujQ/01DwHdMnRC2IYVdJgi2evvr371K913332S1GFAb2pq0sGDB1seDQ0NSd02ABLH5PPLTfxsyT42+REB3TJ0QtiIbW8wQTLX3/T0dH3jG9/Qp59+KqnjgJ6SkiLHcdo8krFtAMDki9Um89jkVwR0y9AJYSO2vcEEyVp/d+3apf79+6u8vLzlZ6ygA8BJJl+sNlnHJj8joFuGTgibmbi1DPZI1vq7dOlSOY6jbt26tTwcx1GXLl3UrVs3HTt2rMPXSNa2AQDTT7Wj/pqHgO6hdevWafTo0fryl78sx3G0dOnSdp+/du3akFsCt27dGvZ70gkBwBvJWn//8Y9/aMuWLUGPb33rW/rlL3+pLVu2hPUaydo2AGD6xWqpv+YhoHvorbfe0sMPP6wlS5ZEFND/+te/6v333295hLM6EUAnBABv2FR/uYo7AJzACjoiRUA3RCQB/eOPP476feiE6AjbwIH4sKn+EtABeMHUYxiTL1ZL/TUPAd0QkQT0oUOHauDAgbr66qu1Zs2adn+HC/EgXCZfYRSIh0QfyHEQ5I62AdAZph/DmHyxWuqveQjohggnoG/btk0vv/yySktLlZ+fr3HjxqlLly5at26d6+9wKxuEy+QrjAKx5NWBHAdB7mgbAJ3hl2MYE1f4qb/mIaAbIpyAHsro0aN1ww03uP47K+gIRzTnR5k4yADh8OpAjoMgd7QNgGiZfo636ai/5iGgGyLagP7HP/5Rw4cPD/v5dEKEEskVRk3fRga0x8sDOeqvO9oGQLRMv0q66ai/5iGgGyLagH7jjTfqqquuCvv5dEKEEklo8cs2MiAULw/kqL/uaBsA0WIFvXOov+YhoHuosbFRZWVlKisrk+M4ev7551VWVqadO3dKkiZNmqSbb7655fl/+tOftHTpUm3fvl2VlZWaNGmSHMfRkiVLwn5POiHchHOFUQZB+B0r6GaibQB0hslXSTcd9dc8BHQPBa7K3voxZswYSdKYMWM0atSoluc/9dRTOu+889SrVy/17dtXV1xxhVasWBHRe9IJ4SacK4yyjQzJwKsDOeqvO9oGQGeYfJV001F/zUNAtwydEB1p7+JvrKAjGXh1IEf9dUfbAIgFLmAbOeqveQjolqETorPYRoZkwX3QzUHbAIA3qL/mIaBbhk6IzmIbGRAd6q872gZAOBI1sWrTSjz11zwEdMvQCRErNg1eQCxQf93RNgDak6hbvNp4K1nqr3kI6JahEwKAN6i/7mgbAO1J1C1ebbyVLPXXPAR0y9AJAcAb1F93tA0Qe8my0y1RF6i19UK41F/zENAtQycEAG9Qf93RNkDs+H2bduuJhUTd4tXWW8lSf81DQLcMnRAAvEH9dUfbALHj123aoSYW8qr3q3Zfo+bl17GCHifUX/MQ0C1DJwQAb1B/3dE2QGz4OWSeOrHwZtluPb1yq8bNL9Hjyyo1LbtKjyzdrIWF9XG9xauNt5Kl/pqHgG4ZOiEAeIP66462AWLDr9u0W08spK6t0YSMcj2QUa7JSyo0b2OtHlm6WdOyq+J6i1cbbyVL/TUPAd0ydEIA8Ab11x1tA8SGX1fQT51YWF6+W49lbVHKG5WauqJKk5ZUaElpgzKKdmlefp12ffgJ90GPIeqveQjolqETAoA3qL/uaBsgdvy4TfvUiYUlJQ2auLhCU1dUKSWrUo9mbdHyit3G7wLwK+qveQjolqETAoA3qL/uaBsgdvy6TTswsTA/v16/y9ysBzLKNSGjTKm5Nb7YBeBX1F/zENAtQycE0B6btvUlGvXXHW0DxJ7f6vmpEwuPL6vU7fNL9FT2Vr1R9reE7QLwW5vFAvXXPAR0y9AJAYTi9/vm+gH11x1tAyDg0JFmvX/gsPKq9yVsF4DNYyD11zwEdMvQCQF/SdRsvl/vm+sn1F93tA2AUOMdY2D8UX/NQ0C3DJ0Q8IdEzub79aq/fkP9dUfbAPbyevXa9jGQ+mseArpl6ISAPyRyNt+v9831G+qvO9oGsJfXq9e2j4HUX/MQ0C1DJwTMl+jZfNtXDxKF+uuOtgHsZML4Y8Jn8BL11zwEdMvQCQHzeTGb78f75voN9dcdbQPYyZTVa5vHQOqveQjolqETAubzYjbfr/fN9RPqrzvaBrCTKavXbmPggcNHkv62a9Rf8xDQLUMn9E4i761p4308k41Xs/n8vxM/1F93tA1gl1PHmkSNd+GMb4HnHDh8xJrbrlF/zUNAtwydMPESeXVSr6+EithhRTv5UH/d0TaAHUIdpxTu+ECFOz6I23gXzbGR1xeuSyTqr3kI6JahEyZeIou8TQOKLVjRTh7UX3e0DZC8Qq2WhzpOidd4F+mxkSnb7hOF+mseArpl6ISJlcgib9uAAvgN9dcdbQMkn9Yr1/Py6zQtu0rpm3Ym7DglmmMjUy5clyjUX/MQ0C1DJ0ysRBZ52wYUwG+ov+5oGyD5tF65nr2hVre8WqQZq7cn7DglmmMj2xY8qL/mIaBbhk6YWKygAwig/rqjbYDkEuqYZHnFbo3PKNMDGWVaXr7b2BV0ya7brlF/zUNAtwydMPESWeRtGlAAv6H+uqNtgOTitnI9PWe7bn21SLPX1ybsOCWaYyObLtRK/TUPAd0ydMLES2SRt2lAAfyG+uuOtgFiy+sLjLqtXC8srNe07CrNy69L2HFKZ46NvG7HRKD+moeAbhk6oXe4DzpgN+qvO9oGiA2Tbrfa3sq1F8cpHBuFRv01DwHdMnRCAPAG9dcdbQPEhkm3W431rj4CdnxQf81DQLcMnRAAvEH9dUfbAJ1n6sViOxusTdoVkIyov+YhoFuGTggA3qD+uqNtgM4z+XarnQnpJu0KSEbUX/MQ0C1DJ0S02FoGdA711x1tA3SeiSvonV39NvE7JRvqr3kI6JahEyJSbC0DYoP66462AWIjEbdbjWTCvrOr3ybvCkgW1F/zENAtQydEpNhaBsQG9dcdbQPERjxvtxrphH1nV78PHWnWrg8PaV5+HSvocUT9NQ8B3TJ0QkSCrWVA7FB/3dE2QPsiPc0sHqelRTphH+3qd+uJgGnZVXpk6WYtLKyP264Am1F/zUNAtwydEJFgaxkQO9Rfd7QNEJopp5lFM2Ef7SR/64mA9E079cjSzZqWXRXzXQGg/pqIgG4ZOiEiwQo6EDvUX3e0DRCaKaeZRTthH+k58e0dd8zLr9OuDz/h2CPGqL/mIaBbhk6ISCXigjOADai/7mgboK14TZJHs/090s8SeI8Dh49EdE48O/cSj/prHgK6ZeiEiFQ8LzgD2IT66462AdqKdVjt7Hb5cCbs3d7jwOEjYU0KsHMv8ai/5iGgW4ZOiGjZdB90m74rEof66462AdqKdVjt7Hb5cCbsY7Elv/VEwPyCOj339jblVe+L6PsiPNRf8xDQLUMnBNyZcjEeJCfqrzvaBggtVqeZRRv2Q01Yu01ix2pCITAWLyis1x+WVWp8Rpkef7NSaYX1jMlxQP01DwHdMnRCwJ0pF+NBcqL+uqNtgNBidZpZpNvlo5mwjmZLfns71vKq9+u5t7cpraC+zZjMTrfYof6ah4BuGTph7DFIBEtEe8TjPTjvDfFG/XVH2wDt6+y4F+kYF82EdSTv0dEEgNtrLSzcqWnZVZqXX8dOtxih/pqHgG4ZOmHssB06WCLaI57vwZVjEW/UX3e0DRB/4W6X78yEdbjv0dEEgNuYPGP1dt0yr0izN9Sy0y1GqL/mIaBbhk4YO2yHDpaI9ojkPSJdbWAFHfFG/XVH2wDxF+52+c5MWIfzHuGMt6Ges7x8tyZklGlCRpmWV+xmnI4R6q95COiWoRPGBmEuWCLaI9z36MwqO/d8RzxRf93RNkDidDSBHYsxvb33CHcCoPWYPHt9rW59tUjTc7az0y2GqL/mIaBbhk4YG2yHDpaI9oh0QI9mJZ97viOeqL/uaBvALPGcsI5mwn3uxlrNy6/TtOwqLdxUz+JIDFF/zUNAtwydMDZYQQ9mygp6rD4HF/5DPFB/3dE2gFniPWEdyQTAqWMyO91ij/prHgK6ZeiEscMgESwR7dHRe7CzASaj/rqjbQAzxWvCOtoJAHa6xR711zwEdMvQCWPHb4NEvFeFE9EeHb0HOxtgMuqvO9oG8IbXO8aifX+vP3cyof6ah4BuGTph7Jk+SCT6dnBe3wednQ0wFfXXHW0DJJZNt4o1/TjNa9Rf8xDQLUMntI9tt4Pz284G2IP66462AWInnEBqw7GBTZMQnUH9NQ8B3TJ0QrvYvOWbGXOYhvrrjrYBOi/cQGrLsYENkxCxQP01DwHdMnRCu3DRNMAc1F93tA3QeeEGUhuODaKdhLBxcp/6ax4CumXohHaxZZYc8APqrzvaBuicSMb7Q0eaNS+/TnM21Gp5+e6kPDaIdBLC5u3w1F/zENAtQye0DxdNA8xA/XVH2wCdE24gDQTRadlVuvXVIk3IKNOM1du1sHBnUh0bRLpAYfN2eOqveQjolqET2sfri6bZuF0MCIX66462ATon3EAaCKILN9Vres52Tcgo0y3zijQtu0p51fv0/oHDSTNeh7tAYftuQ+qveQjolqET2ivRQdnm7WJAKNRfd7QN0HkdBdJQQXR5xW69vK5GU5a9d2LbexKN1+EuUNhwTn57qL/mIaBbhk6IRIl2uxgr7khW1F93tA3QeR0F0lBBdHnFbj31VpXGztmkORtqk3J7d0fHFaygU39NQ0C3DJ0QiRDNYBfJ7WH8FOD99nkRP9Rfd7QNEDtu486pY3P2lj1Kza3R5MzN+s8ZG/Sjl/L04qrtyt6yx9fhNNox1+br9VB/zUNAtwydEIkQzXaxjlbc/bZl3m+fF/FH/XVH2wCJERhrn8reqvvS39VdC0s1evp6/XZekSZklCt1bY0vt3d3dsz1+no9XqL+moeAbhk6IRIh0hX0cJ7vtyus+u3zIv6ov+5oG+CkeO68OnrsM+VV79P4jDLdk16qyZmbddtrxXps6RalZFXqsawtWl6+23cr6LEac23c9Ub9NQ8B3TJ0QiRKJNvFOlpx3/XhJ746P8z289kQGvXXHW0DJG7n1f7GJs3MrdHrm3ZqeflupebWaEJGmR5eslkPLCrX7PW1vppQZsztHOqveQjolqETIhEOHWnW+wcOK696f1jbxToaXHd9eMhXV1i1/YqwCI366462ARKz8+rQkWbt+vCQ5uXXtYy5gfPRx2eU6e6FpZqXX+er7d2MuZ1D/TUPAd0ydELEU6jZ/3Dvq9reirvJs+OhtsOZ/HnhHeqvO9oGtov3uNF6fJ6WXaVHlm7WwsL6ljF3Rs52ra7a67sxijG3c6i/5iGgW4ZOiHjqzOx/RxdoMe0Kqx1tRTTt88J71F93tA1sF+9V4Nbjc/qmnXpk6WZNy66K6qJo4Z6rnahzuhlzo0f9NQ8B3TJ0QsRLrGaw3QZz066wGjgYSCuoU/qmnUorqHO96rwJnxfeo/66o21gu3iuArf32vPy67Trw0/Cfv1wz5NP9J1MGHOjR/01DwHdMnTCyNl4Rc9oJOocMBP+HoeONGtBYb2eXrlVj2Zt0cTFFXo0a4ueyt6qBYX1bba7e/15/S5Z2pD66462AeK3ChzL8TncnXJe3ckkWcaLRKL+moeAbhk6Yfi4j3VkbDoHbH9jkx5fVqn70t/V79+o1NQVVfr9Gyf++w/LKrkgTYwkWx+k/rqjbYD4rQK3Hp+Xl+/WkpIGzc+vj3iHWzjjvE3HA8mA+mseArpl6ITh4z7WkbPlHLD9jZ9qfEaZHlxUrmdWbmt5PJBRrvEZZdrf+KnXHzEpJFsfpP66o22Ak+KxClxS/5FeWlOtp7K36neZm3X3wlKNm1+itIL6sCcAwl2J56rq/kL9NQ8B3TJ0wvAw+xudRJwDZsL2tf2NTXr8zRMr5ilZlfrDm5V66P8qdFdaiR5nBT0mkrEPUn/d0TZA5CIZD48e+0xpBfW6dV6RbnutSA8uKtPTK7fqpTXVYU96xnsF3YTx3UbUX/MQ0C1DJwyPH2Z/wxnIvBrs4vG+Jm13PnSkWWmF9Zr6VpVue61YP07dqJtSN2rMnEI9seI9HTh8JOGfKdn4oQ9GivrrjrYBwtfeeOg2/h44fETTsqt0X3qp7kt/V5MzNyt1bY0WFu6MaNIz3J1ykeyo62h8J7jHF/XXPAR0y9AJw2Py6l04QdWkMBsrpm13Lqn/SI8s3az/mVesCRllmri4XHfML9EjSzf7dgu2SUzug9Gi/rqjbYDwhRoPX1pTrbSCetdxf3XVXt3yapEeztysqSuqlPJGpSZklGvG6u0RTXqGu1Mukh11buN74Y4Pku5YxkTUX/MQ0C1DJwyfqedThxNUTQuznWViWAusRkzIKNOkJSeu4p6aW6OFhZFddAfuTO2D0aL+uqNtkKxivfrrNh4+lb215Zzy1uP+oSPNmpdfpwkZZfr9G5Ut101JyarUhIwyzcuvi/jzxeo+6O2N79OyqzQjZ3vSHMuYivprHgK6ZeiE4TPxnprhBFUTw2xnebHduaODisBnyixt0JLSBi2v2O37LdimMbEPdgb11x1tg2QTr51socbD5RW7NXlJhe5JL9WSkoY24/6uDz/RnLxaTc/ZrgkZZUrJOnH3kYeXbNatrxYpp2pvjL51bL7Pqvf2KrO0QXcvLNXsDbUJOZaxeRs99dc8BHTL0AkjZ1LRDieoJuO5u4mcdAj3oCoZJ0JMZVIf7AzqrzvaBskmXjvZQo09S/4ZZn+XuVnLy3e3Gfd3fXhI6UU7tXBTvVJza/Ro1hZNWlKh8RllmpZd5el1U9xuAZe6tkZ3LSxVZmlDXI9lkvGUwEhRf81DQLcMndDfbF1BlxK33TmSg6pk24KN+KL+uqNtkExidd9xN63HnvkFdbp9fomeXrnVddw/9XcySxs0e8MOzcjZbsR4FeoWcL+dV6T70t/Vwk31cT2WSbZTAqNB/TUPAd1D69at0+jRo/XlL39ZjuNo6dKlHf5Obm6uLrnkEvXs2VPnnnuuUlNTI3pPOqH/hRMKkzE4JuoWbpFMbiTbFmzEF/XXHW2DZBLYyfZm2W6lrq3RY1lbNHFxhX6XuVmPL6vU+wcOd+r1Q409aQX1emlNteu4b/J4FbgF3O3zS3RPeqkmL6nQ0yu36ndLKvTI0s1xO5ZJ1gWNSFF/zUNA99Bbb72lhx9+WEuWLAkroNfW1qpPnz669957VVVVpVmzZql79+5avHhx2O9JJ/S/cAZZkwfizorndudoTw9Ili3YiC/qrzvaBskkEPyeXrlVEzLKlfLGiXO+H8go1+3zS5RXvS9m7xMYe8Id900crwLtlVZQF3RNl4WFOzUtu0rz8uviciyTjKcERoP6ax4CuiHCCegPPfSQhg8fHvSz2267TSNHjgz7feiEycPk+6D7VbLNpvP3Nwv11x1tg2STV71f4+aX6IGM8hO3NfvnFdOfyt4a1/Hk1LrvlzGgo6C868NDcfkeyTbmR4v6ax4CuiHCCehXXnml7rnnnqCfZWZm6rTTTtPRo0dD/k5TU5MOHjzY8mhoaKATJhG/DL5+kgynB3DRGzNxEOSOtkGyef/AYT2+rFKTl1QE3YrzjbK/xX111m9jgJdBORnG/M6i/pqHgG6IcAL6sGHD9MQTTwT9bOPGjXIcR3v27An5OykpKXIcp82DTuhvkQ6+BPnwJcPpAVz0xkwcBLmjbZBs3LZtJzJ0+mkM8CooJ8OY31nUX/MQ0A0RbkB/8skng36Wl5cnx3H0/vvvh/wdVtCTU7iDr99m0U3i10kNtuyZi4Mgd7QNklEsQmekY5HpY4Db9/E6KPt1zI8F6q95COiGiNcW99bohP4XyeDrx1l0dA4XvTEX9dcdbYNk1JnQGe0Eu6ljQLjfx+ag7BXqr3kI6IYI9yJxF1xwQdDPbr/9di4SZ5lwB1+3ID8/v16z1u/Q/sZPPf4miAfTV09sRv11R9sgmUUTOqOdYDd1DGDBwFzUX/MQ0D3U2NiosrIylZWVyXEcPf/88yorK9POnTslSZMmTdLNN9/c8vzAbdbuv/9+VVVVafbs2dxmzULhDr6tg3z2lj1KXVuj32Vu1m2vFeuV9TvY7p6kuOiNmai/7mgb4KT9jZ9q1vodSiuojypknzoGZJY2aPaGHZqRs92zMcDUSQOcQP01DwHdQ2vXrg15AbcxY8ZIksaMGaNRo0YF/U5ubq5GjBihHj16aOjQoUpNTY3oPemE/haYhc+r3tdhAGs9IKaurdGEjHI9kFGuyUsqlFZQR2hLUl6fy+cFP2yLpP66o22Ak7X7lfU7dNtrxfpd5malrq1R9pY9EW1TP3rsMxXu+EDTsqt098JS3bWgVNOyq1S44wNPxoFItt37oZYnG+qveQjolqET+lPrc7fSCuuVVlCvBYX17QawwCz6/Px6/S5zsx7IKNeEjDKl5tZ0evaaQdR8NvyN/HQhROqvO9oGODlmpxXUafKSCj24qFwTMsqVujbyMbuk/iNNX71dczbUKrO0wdMt5eGsoHemltsw1sUT9dc8BHTL0An9ye3crbzq/e0OSoEB76U11Ro7Z5MeXHQinEc6Gx/qNf0QiJD8/HReI/XXHW0D27XZ9ZZbowkZZXogo1wP/V+5UtdWt2xT7yiQmrilvKNTr6Kp5RyPxAb11zwEdMvQCf2nMwPtye1yNfqfecW6L700aLtcNIO1nwIRkpuJB6Htof66o21gu1DXjXlpTbV+O69I17+4Tr+dV6QnVryneRvrtKCwvt1AauKV3Ns79SraWs7xSGxQf81DQLcMndB/OjPQnjp4Tc/Zrjvml2jc/BLNWL096vux+ikQIbmZeBDaHuqvO9oGtgs1vqbmnphcv2tBqdI31evplVs1ds4mPb1ya7uB1MuxOpzV/V0fHtKuDz9xvahtOLWc45HYof6ah4BuGTqh/0Q7CLX+vewte5SaW6PxGWW6e2Gp5uXXKa96n94/cDjsgcxvgQjJzW8HaNRfd7QN0Pbq6+MzynRHWolS19ZoefluPZa1RQ9klOvRrC1aXrG73XqX6Lt5hLPd3O05Bw4fibiWczwSO9Rf8xDQLUMn9KdoBlq3wSuztEEvrv6rVmzeE/F5W+EGIi7YgkTx0y3lqL/uaBsgOMD+75pqm4iW+gAAIABJREFU3bWgVDNWb1f2lj1aUtKgiYsrNOXNSk1aUqElpQ3tBtJE380jnO3m7T0n0lrutwlak1F/zUNAtwyd0J+iGWjbG7ymZVdp+urtUZ231d4g6pcLtjCBkDz8dEs56q872gY46cQ28E80L7+uZQyPdAX91NeK93gXTlju6DkHDh+JuJb7aYLWZNRf8xDQLUMn9E4sBslIXyPU4DUjZ7umZVdFPevcXiAy/YItfplAQOT8MOlC/XVH2wBttR7Dn8o+cQ76U9lbExJIw62r4Ww3D3dLeiS13E8TtCaj/pqHgG4ZOmHieRkKQw1eq6v2atb6HZ0+b6v1IHrq7Pjy8t1aUtKg5eW7jdpuZvoEApIb9dcdbQO01XoMTyusV1pBvRYU1sc1kEZ63BKLFfRELl509veSDfXXPAR0y9AJE8+EUHjqIBSvQXJ/Y5Nmrd+hGau367GsLZq4uEKPZW3RjNXb9cqGHZ5fsIXz1eA16q872gZwF2pCPJ7BMprjlnC2m5uyJZ3ddMGov+YhoFuGTphYpobCeAySh440a1p2le5IK1HKG5WauqJKKW9Uatz8Ek3LrvI8AHPFV3iN+uuOtkGy8tsqbTTHLYeONOv9A4eVV72v3e3mpmxJN2HhxCTUX/MQ0C1DJ0wsU0NhPAbJloA+v0QpWf8M6FnmBPR4TJb47cAL3qL+uqNtkGz8ukobyXFLqO+YV72/w9u3ejl2mrpw4iXqr3kI6JahE7qLx4Bh+kAQy++8v7FJr2zYoek52/Vo1hZNWlKhR7O2aHpOdFvc4/H3iNXOAb8eeHnN9gkN6q872gbJxq+rtJEct7T3HU2t96YunHiJ+mseArpl6IRtxTtsmXLOVbwFXSSuYreWlDZoeUXkF4mL598jVjsH/Hrg5RUmNE6g/rqjbZBMTJ+c70g4xy1uF4ZdWFivadlVmpdfZ2S99/vfJh6ov+YhoFuGTthWvMOWKedcJUIsJiMSEX47M7PP4B45JjROoP66o22QDAJjy64PD/l6lTac4xa3C8NOXFKh38zdpDkbao2t97YsnISL+mseArpl6ITBEhm2TN3uFUudnYzwQ/hle1xk/PA3TRTqrzvaBn524PAR5VTtbVk1npdfp2nZVUrftNPXda+945bWF4ad8malJmSU6boX1mns7EItL99t7Pe2aeEkHNRf8xDQLUMnDEbYio9oJyP88PcgcEbGD3/TRKH+uqNtkAixnigPBL1p2VW69dUiPZBRphmrt2vexlo9kFGuiYsrjFqljeX3DwT0218r0bj5Jbr5lUL98H/z9O0nV+mm1I3KKmswvt7bsHASDuqveQjolqETBiNsmcUPf49DR5q1umqvZuRsN+rAy1R++JsmSrLW3yeffFLf+ta3dMYZZ6hfv376wQ9+oG3btkX0GsnaNjBDvK6DUVL/kWbkbNeEjDI9krlZj2Zt1pg5m3Tba8W6a2GJxswp1JTllXplw46w3jPWgTHwegcOH4n59w9cGHbi4nL96KU8/WTmRv1iVoGueyFX3/tTrp59e1vc6j3BOraov+YhoFuGTthWspyLlCwDlql/j1MP8Gat36Fp2VWall0V9oGXzUz9myZastbfa6+9VnPnzlVlZaXKy8t1/fXX65xzztEnn3wS9mska9vADPG4DkZg8nH2hlpNXFyhqSuqND6jTD96KU///ZcCPbZ0s+5JL9W0t6q0umpvu2NzrCcQWr/etOwqPbJ0s9I37Yzp95+XX6cJGWV6OHOz/vDmidur3j6/RKNfXK97FpYqs7QhpvWeC47GB/XXPAR0y9AJ2/L7uUjJNmCZ+vcIdYA3ffV25XRw4AVz/6aJZkv93bdvnxzH0bp168L+HVvaBokXr108gdN3Mksb9GjWFj2cuVlj52zSmNmb9MtXCvXQ/524aNr8/PoO3yfWEwinvl5maYMmZJTpjrQSpa6tiemq9uqqvbrl1SI9nLlZU1dUKSWrUve//q4mLa7Q3QtL9b9rqmNa77ngaHxQf81DQLcMndCdX1egk3XAMunvwTbt2DDpb+oFW+pvdXW1HMfRli1bwv4dW9oGiRev62CcOi6k5tbozgWl+nHqRv1yVoF+/pcC3bvwXaWurenwfWI9vrR+vSWlDZq4uEIPZ27WY1lbWi7eFovzwg8cPqJp2VV6IKNMk/55FffUtTVaWLhT8/LrtOvDT2K6rZ1xOD6ov+YhoFuGTphcGLASgwud+Y+JkwE21N/jx4/rhhtu0BVXXNHu85qamnTw4MGWR0NDQ9K3DbwRz3EyMEG+sLBez729VT98KU/ffyFXt71WrNS1NcresqfD94n1+NL69ZZX7NajWVv0SOZm3Zdeqv/N2a4lJbva/VyR1M+S+o80ffV2zV5fG/Mt7e19L8bh2LFhbPIbArpl6ITJhQErMZgI8Q+TT/mwof7ecccdGjJkiBoaGtp9XkpKihzHafNI5raBd+J1HYzWp+9MWfaeJmSU6dW8urDfJ94r6Kve26vpq/+q615cpyufytHoF9brhy/l6X9eK1Je9T7X7xNu/UzUKUyMw/Fjw9jkNwR0y9AJ4y+RK3cmDlgmrlzGAhc68weTT/lI9vp711136ayzzlJtbW2Hz2UFHYkU7xAZ6mrpkbxPrMeXvOp9eu7tbZpfcGKi4L70d3XZk6v03efW6qd/2agfvZSnH760Qa9trAv5OaKpn4kY+xmH4yPZxyY/IqBbhk4YP16t3MViwIrFwGryymUsmHahs2SdCOkMEyesTpWs9ff48eO68847NWjQIG3fvj2q10jWtoFZElU3I32fWI0vgddJK6zX429WanxGmSYvqdB/Tl+vX8zK1+/f2KI/LDtxtfUHMso1PqNM+xs/bfnMJtdPybxxOFlQf81DQLcMnTB+vFq568yAFctQbfLKZSx5HYyTfSKkM0w/5SNZ6++4ceN05plnKjc3V++//37L4/Dhw2G/RrK2DSCFP250dnxpPQ7P21inW1/dpFFP5+jHL+XpF7MKdM/Cd/VUdpWmvFmp2+cX6697/yEpPvUzXuOl1+NwsqH+moeAbhk6YXyYMPMczYAVq1Btwvd3+1zJNojbMhESDVP/PwxI1vob6lxyx3E0d+7csF8jWdsGdkvkhGqo+pe6tka/nrNJl/7xHX3n6Rz9v+dyddUzazVmdqHGv14WtxV0JpL9hfprHgK6ZeiE8WH6yl0osRyMTfv+yXpwYHoANYHJ5yhSf93RNvCr9iaCEzmh2ubq7eW79VjWFv12XpH+feoqjXxylb77XK7+33Nr9O9TV+s/Z2xQWkF9yM8bqn5GemV3JpL9g/prHgK6ZeiE8eHH4BRNqD50pFm7PvxEuz48FPSdTPv+yXpwYNpEiIlMPkeR+uuOtoHfdDQRnOhxsc39z0saNCGjTD9JzddPZubpl7Py9d3nc/WdZ3J0xdQc3f5accvqeajvFKifhTs+UOGOD8Ke8DbteAAdo/6ah4BumXh0wmTcRhwNk1fuQolkED167DMV7vhA07KrdNfCUt21oFTTsqtUuOODlkHalO9v0sFBrPuGSd/NdCbWJQ6C3NE2MEEsV4m9mFA9dRzOLG3QnWkl+v4L63Rv+rt6ZuU2/eHNSt2TXqr7M97VX9bVuH6GU9uh9fdMK6jXc29vU171/pC/y0Sy/1B/zUNAt0wsO2GybiOOlskrd27CDdUl9R/pkaWbdcf8Ej2SuVkPZ27WHWklemTp5pbnmvL9TTg4OLUtZubWaNb6Hcqr3h+TtjBlIgSR4yDIHW0DL0V6PBPOZKkXE6pt7su+vFI//Uu+JmS8q6krqpSSVakJGWV6KntrWJ/h1O+QvWWPUtfW6LGsLbp7YanGZ5Qpr3pfmzaK5nubOKFqE+qveQjolollJ0zWbcSd5aeBJpxQfehIs+bl12lCRpl+/0alnlm5Tc+s3NYy0M/Lr2s5GNnf2KT9jZ/GfNU4ktczYZW5pP4jvbSmWk+v3KrfZW7W3QtLNW5+idIK6jsd0k2ZCEHkOAhyR9vAS5Eez4Q7ERzuhGo8dlsF7sueVlCv2+eX6J70Uk1eUqEnllfqmZVblVe9r8PXOfV7pq6t0YSMcqW8Uakp/1yJf+7tbSHbKNzvzUKPGai/5iGgWyZWndCEEJSsvAj47b3n/sYmzcjZrgmLyjR1RVVLQJ+6okoPLCrXi6v/qtVVe2M+wHZm4PZylTnQN55eubXlYCZwz9nb55eEdVAU7vv4ZSIIJ3AQ5I62gVeiXfEN53c6mlBNREA9euwz5VXv01/WVevRrC0an1Gmx9+sVFphfYfvFfieaQX1eixri1L+OUmfklWpR7O2aH5BXcg2CncimYUeM1B/zUNAt0ysOqEJ24iTjakzyR2toE9ZXqkZOdtjPsB2ZuD2cpV5f2OTZubW6HeZm1sOZgITGvekl+qV9TsI1ZbiIMgdbQOvRHs8E8lEsNuEaiIDal71fj339jalFdRH9F4l9R/pube36e6FpZryZmXL2J+aW9NhG7U3kcxCjzmov+YhoFuGFXRzmTyTHDgHfdz8Ej285MQ56OPml2ji4gpNy66K+f8Hsfr/y6vdCLPW79DdC0uDdhykZFVq8pKKdi/Mg+TGQZA72gZeiXa86exEcLQr96HupNLZ92rv1LQTK/D7NT6jTPekl+rRrC1Kza1R9pY9nRrrE7XQw26zjlF/zUNAt0w8zkHnYlWdl4gJj84MUqdexf3uhaW6e+GJq7i/XblHr2zYEdYAG8n7+32HRl71fo2bX6IHMsqjujAPkhMHQe5oG3ipM8cz0Y6tkYxz4dxJJZr3erNstx5fVqlX1u/ocOdeXvU+Pff2Ns0vqIvJMV+8j3tM3ZVoIuqveQjolonXVdy5WFXnxDOQRjtIhTroaD17H84AG837+32HxtFjn7W5MM9T2Vv10ppqJrAsxkGQO9oGXvLieGZ/46eatX6H0grqOxznwrmTSnvcxtSnsrfq9vklSvtn6D51517rY4B4tFE8F3pM3pVoGuqveQjoluE+6GaKZyCNdJCKNFB3NMBGO0j6fYdG4MI8r6zfob+sq2ECCxwEtYO2gQkScTxz6hj7+LJKjZtfoqeyt+rNst0hx7lw76TSkdZj6vz8eo2bX6KnV24NOu5YWFivadlVmpdfF/IYIJZtFK+JEb9P8ica9dc8BHTL0AnNFY9AGs0g1ZlA33qA7cwgmSw7NJjAQgD11x1tA1ucOsa+UfY3Pb3yxCr248sqW8a5A4ePtIwbHd1JZcaa/8/eu0e1dV55/7HTptNJu6ZdmTVrOp01Tdu1epn3j3fe/H6Tt/NOf+3bdqZXt4nb5p7WztXG9wCOL9jGduIanLqJIQRjLjGWLCyMhLAhwo24SUISIKGrD6ALEibY1HIyJA44xM58f3+IcywJHelIOpKOdJ7PWl5tAB092vDs/ezLs7c7YZXd/OJNXJlbgN4TZGxqvdaHA+dd6LC+E2Gfq3rcePbkMJp0k1nLPPNtJ/P9mly2IfpXeBAHXWSQTShcMuGQJmuk0nGoYxlYPoxkNhzcTM2gJU45IRyif9khsiHkkmzpbDYbKzH60aD14fLcwrIKNr0niCa9j1MGPV5Z+u3nXcWVuQUEr99YtpZO+wyK5VaUyq1QWC5BYZlGp30m7zLPJIOeHET/Cg/ioIsMsgmFD58HhWSNFN9RZ9bDiCGAeq0Pwes30v6M6RB+eDne70W91ge9J5hyUIQ0pSHEg+hfdohsCLkg0zo72p4nsrE91GzMCjapMRBzkgp9B53tc5h81+JWxEVX7jXqfHj6zWHsUNixV+XEjrbQ/1b1uNGg8+VV5jnfr8llE6J/hQdx0EUG2YTiI9lZrXxHncPf/5x1BpXqMRRFlfPlyoE1B95DTa8HR7rHsFvpwGaZBUUSM6TGQEprIk1pCPEg+pcdIhtCLsiUzmZzmOcWFlltbLPBj2aDP+b3pKYA+if+smySCt3FPdbnqO5xJxyDGl2512zwY+sZC9afGsH+DhcOd1HY3xG6J1+hpvIq81wo1+SyAdG/woM46CKDbELxkayR4jvqHN0QZ/1SU5oO6ztpH4bSqTaggxFHusdQIrehfOkwUiq3Yb3EDL3nakrPIyV1BDaI/mWHyIaQbXLVnJXNxmqo2YQVbLHmoLN9jkadD5tOW6C0THMegxq8fgMVagobpGaUq1zMmNB8dNBpyJWzxBD9KzyIgy4yyCYUL1yNVKaizsHrN9Cg9UFq9Kd9GOKjLDF4/SMc7/dit9KB8rB7fYe7KGxpsaBB60tqTdlsSkMOHPkJ0b/sENkQsk2mdHYix39uYTGmjY2XXY9nI9k+h9Iyjc0yC5p0k5yfF7z+Eeq1Phy9MI7tZ20olVuxT+VEtSb/StwJ3CH6V3gQB11kkE1I4AqbE5iqc8jnYYiPssT5xZuo1/qwWWaJ6IxbrnJhl8KOugFvUmuiD2VSYwAK8zQ6bTO8Z9DJHff8huhfdohsCNkmUxl0rrYuli1NpYIt3ueoUFOo0rg5P29uYREVagqlS43itrfaUPX2BGSmKVIJVsAQ/Ss8iIMuMoS+CUlmULik6xzydRji81Cl9wRRJDGjVG5jSvlK5FZUqsdSyupLjaG5sptlFuxWOlCpHkNNr4e3O+jkjnt+I3T9m0uIbAi5QCjjTWlSrWBj+xwm37Wkr7jtaXdgA0szOkJhQvSv8CAOusgQ6iYkmUHhw4dzyMdhiM9MPO1Ur5eYsaXFgl0Ke8pOdXjDuV0KO7a0WLA+jYZz0ZA77vmPUPWvECCyIeSCTF3pStbWRScnkk1WJPocXJ5H2xjZUAC1/V7sVTmxU2FHsdyKCjWFuYXFJKVAyBeI/hUexEEXGULdhCQzKGz4cg75OAzx7ah+fOsT6D1X0aD1oW7Ay8uaOu0zUFimITH6eXOes3nHPZ8RchWOUPWvECCyIeQSvvUGV1vHd3Iinc8RbWNoO6a0TMe0MULWtYTkIPpXeBAHXWQIcROSzKDwycR89HQMe6bKEvk62GTCeSb7JD75UIUjRP0rFIhsCIVCuC1JZFfSTU6ka0uj18rFxuSDriUkB9G/woM46CJDiJuQZAaFj9Ccw2Qy8dmI8mdLPpkITBQK+VCFI0T9KxSIbAj5TrKOK1931VNxktleb/JdS2hj8kHXEpKD6F/hQRx0kSHETSg0548QGyE6h/Gc72xH+bMhn0zdl8x38kWHCFH/CgUiG0K+k6zjmk5ygu299J7gMpsYr1t89OsTNZXLF11LSA6if4UHcdBFhlA3oRCdP0Ik+eYcZjvKn035kLt/keRLFY5Q9a8QILIh5DOpOK6JXhO8foN11Gn069TOy6hUj6FYbkXdgBfNBj8uuC6jf+Ivy4LUXOats9mYfNG1hOQg+ld4EAddZAh1E+ab8ydmMu0c8vF8toOPxOhHg9aH4PUbPK54+XsT5zm75EtWR6j6VwgQ2RDymVQd11jJiZpeD6TGQEzHOnj9I1x6d37Ze9X2ebGtZRSbZBZUvEWhRG7Fb2sH8ehxA450j+GcdYYJUvdQswnXymbH8kXXEpKD6F/hQRx0kSH0TUicG2GTyd8PnyXp0YcltfMyavu92KWwY92pEdRrfXkTACJ7ghv5UIUjdP2bS4hsCPlMqo5rrOSE1BhATa+Hqf6SDQWwp92BCjWFJv0kmg1+VKgptAxNhbqt22awT+VEqdyG9ZIRbGsZRZnSgYdrB/GbGj22ykZR2+dl1tNs8KPZ4I+51tOmAPSeYFw7zJeuJbZNOBD9KzyIgy4yyCYkpEI27nPzWZIefViq7feiRG7F9lYbdisdkBoDgnPeoiGdcpMjH6pwiP5lh8iGkO+k47jSzmrw+o1ljn5tvxdFEjNK5VYoLdNoHbmEPe0O7Gl3QD58CWeGprBZZsGm0xasl4xgf4cLB8+78NgJIx4/YcSLZ+3Yp3Ki0zbDZMk11GzMtdK2MZ4dTlfXEtsmPIj+FR7EQRcZZBMSUiHT97kzUTZHr1li9GOXwo7trTaUyG0RmQQhl+SRTrmpIeSsDNG/7BDZEPIdPoKEsWaR71U5sUfpwM42OxTmabx9cRYyUwAVagrNBj/qBrwolltx4JwLL7bZcLiLwuEuCo/WGfB4nREHz7mY19J2b25hcdla9Z6rkJoCnO1wqrqW2DbhQfSv8CAOusggm5CQLNm4c5aJxjP0YalB68O6UyPYrXSgts8LtfNywmfn2skrxHt+uZapECD6lx0iG0KhkI6ui9b9Css0drTZUaZ0MFnwcPt16d0PEbz+EfSeq6jucaNYbsUepQPlKhfWNA1hbaMJpfJQ5ZjEsLxyLHyttB1WWqahME8vey8+GsAVom0rBIj+FR7EQRcZZBMSkiVZ5zmVw0kmjXbw+g3Ua32QGgMJny2U0ju+Axa5dI6FIlMhQPQvO0Q2BEKI8FJ5pWUaxXIrNkjNTPVXp30GjTofmg1+RqfTerZCTeHZk8MokVvx6p/H8YcuCuslZhw474qpe8Ntw9zCIirUFErlVuxoC5XF1/Z5ITNNCToYT0gfon+FB3HQRQbZhIRk4eo8p+uIZbLJF9dnC6X0jq+AhRCcY6HIVAgQ/csOkQ2BECK6VL5CTWFPuwMSgx9VS1nyZ04Oo0JNLdPncwuL6KFm0WzwR5SuX5lbSBiMlhoD2K10YIPEjDKFA2VKB4okZuxpdwj6OhshfYj+FR7EQRcZYtqEpKSWP7g4uOk6Ypls8sXl2UI7OPARsMi1cyw0meYaMenfZCGyIRAioc8w9H1xOjteKreiWuNGy9AUqnvc0FCzSd8Pj7YNUmMARRIzKt6iUNvvxV6VEzsVdhTLrahQU5hbWOTtc+XDxA2xQfSv8CAOusgQwyYUQtaw0Ejk4PLpiGUysBLv2UIrvUs3YCEE51hoMs01YtC/qUJkQ8gH+LBPqV4Dazb40aSbRKdthhkdWiy3YtNpC5oNfs72Ido2dNpmcFI/iSLJCHYp7Oi0z6DTPgOFZRpKyzTvujofJm6IDaJ/hQdx0EWGGDZhrrOGhQzbwSIb99QzjRAcWrZ1pSIrITjHQpVprhCD/k0VIhtCIvK9l0Y6z4jW5/To0D1KB0pbbWjSTXI+59DPOmedQW2fd2mGuhUPHzfgyXpDhL7OpK4W4jlArBD9KzyIgy4yCn0TZjKTm4/GJFtrztY99UxTSKV3QnGOC0mm6VLo+jcdiGwIbAjBbvAR+E/nGeH6nB69tr/DhXKVi+nuLh++hGaDHxOz7+PSu/OsOp5+1pHuMZTIbSjvcOFwF4Wnmobw4z/14+VOV0xdzdd5Ih/PUoUO0b/CgzjoIqPQNyEfWcPow4DUFIDUGMBpU0CQTmUsEh1oMmEgs3FPPdMUWumdEJzjQpNpOhS6/k0HIhsCG7m2G3wEO/l4Bi2HRp0PJa1WlCkdKJHbmPGhr/55HE/UG/Fc8wg2nbagQk3B5LsWU9fqPUEUScwolYfmpperXHjhjBWbZWZslFpQ3eNmdPX84s2kAySxzhjR55Jmgx8aapbX++2E1CD6V3gQB11kFPom5NMI0oeBI91jWNs0hCPdY4J0KmPBdqAx+a5lLBORzXvqqZBMUKJQIvxCco4LRabpUOj6Nx2IbAixyLXdAPgJ/POZPGg2+LFZZkGp3Mo457V9XjxaZ8CqY1rsaLOhTOnABil7B/Yrcws4cN6FXQo7dirs2NMe6tq+Q2HDsyeH8drbE9B7gsx7cg2QxEsO0M+RDQVQ1eNGSZxu9ITsQvSv8CAOusgQwyZMJ2sYq3lK6H6WDXtVTnTaZwR/hzbegaZCTaG6x53RTESie+pKyzQU5ml02maycif641ufQO8Jol7rw/F+rygzuMQ5FgZi0L+pQmRDiEWh9NJI9Izg9RtJBZB7qFlUadzMrPStLRb84pgWRVIzXukexyvd49itcGCj1Ix6rS9ml/fQaDU/FJZpVGlCDvP2Vht2Kx2QGgM43u+F3hNM6rOzOfN6z1XmOfT9+f0dLpQpHSiVW1GlcQs66VHoEP0rPIiDLjLEsAnTyRpGHwYU5mnsaLPjpXMu7FTYobBMC74LNduBRmmZxmaZBY26yZxkIuYWFlGhplAqt2JHmx37VE7U9nkhM01l7P0/vvUJMz5ms8yC3UoHjnSPoabXQw4DhKwjBv2bKkQ2hFgIIYMO8Dv2MvwZNb0eSI2BZRnnuYXFuA57+DmnuteN55tHsLZpCIc6KVS8NYZiuRW/bzDhgWodnjs1Ag01u+wMRK9HYvRjl8KO7a02pmSelnG91oe6AS+nAEm831XDUoBcaZlm7s+/0j2Ow10UdrbZ0aidFGzSQwwQ/Ss8iIMuMsS0CVMdZVKoGfRG7SQ2ySxQLgUZ+M5EcJm7uqfdgQ0SM8oUoXK6Igl7CR4f6D1XsV5ixvbWpXt2HS6UyG2oVI8J9veXCUgGXRiISf8mC5ENgY1C6aUxt7AIDTWLZoOfeYbUGEBNr4fJOLcMTWFPuwMVaorTNbT5xZu49O48GrS3s9LFciseO2HE43VGPFw7iK1nRlHdszxDTX+mBq0P606NYLfSwZTM02eDugEvGrQ+TgGSeNUOdQNe1Gt9aNRNYkebHYe7KLzSPc40ucvEODcCd4j+FR7EQRcZZBMmJvowUKkO3UGvVI/lTRfqWAeaKo0bFWqK90wElw67dNBANhRAbb8XOxV2bDszii2yUCObTDSJmV+8iQatD5tlFuYwQB8IdisdqBvwFvxhQAjdjwm3IfqXHSIbAhv53ksjVnO0HmoWl+cWlgXTa/u8KJKYUSK3QmmZ5nwNjQ6AP9c8jIdrDXj0+CB+XaPHmiYTapfOAmx2Pnj9Buq1PkiNgZhnA73nKqcASaJqB70niOoeN4qXxsOVq1xMxl7ISQ8xQPSv8CAOusggmzAx0YeB8C7uuT4ccIXtQGPyXeM9E8GlgUz03NVdSge2tYzixbM2HDjvwpW5BT4+dgS4rmQHAAAgAElEQVTB6x+hbsCLXQo7U05Hl9RtkJpx7O0JBK/f4P19hUSuux8TIiH6lx0iG0IihFAJlMoa2PSwhpqNyDjTFXtlSkfElTouzuvHtz6ByXcN+zqc+PmxAfymRo/1khHU9Hqgdl5OWCkXr0ohmQAJl+dUqCk8e3IYJXIrqjVuyExTxC7lGKJ/hQdx0EUG2YTcKcQ56HxnIrg2vglevxFz7mqp3Ib1EjP0nqt8fuyItYXe04pylQsvd17E2qYh/OKYFnvaHXkRbEkVodzdJNyG6F92iGwIQibVaqR4erjZ4Eezwc98j+55U6ZwRFypS65b/A280evB8X4vFJZLUFim0WmfSaj3uZwNuJyBuDxnbmERPVGl/oVqh/MFon+FB3HQRQbZhASAvrf2IS69O5+WoxbRmX3pIPD2xVl0WN/BwfMu1Gt9zGGmSTeJdadGIuaulsitGb0Pbg68h5peDyrVY9ilsOPJeiN+8qd+vCAfxTnrTEFnlIXQ/ZgQCdG/7BDZELIFn1nwRLYjkR7uoWaZjLPSMo0SuRUbJGbU9ntZg6qJ1m/yXcOedgeK5VaUtFpDJeXtDph81zIim1Sfk49Jj0KF6F/hQRx0kUE2ISE8wn28P9S4hZ53yoVwo0p3Zi9Z6sy+V+VEbb8XFW9RKJKYITUGmMPMK91j2HDazMxdpX+2w/pOxhzG8M/6eq8bG6QWHOq8yDTBKeSMMsmgCw+if9khsiFkGj6z4J32GTTqfGg2+BM6ofH08NzCYkTGuUJNYU+7AzJTIG6pebz10w56qdyK0lYbSpNw0AnihOhf4UEcdJFBNiGBziof6R7DbqUDm2UWxpmOd1CJdTiQGgPYrbBjg9SMMqUDe5QOPN88gkfqBnGkeyziQCIx+lEst6JJ54vItmfDYZxfvImJ2Q9wvJ/buJhCQQjdjwm3IfqXHSIbcZONbCofWXC18zJq+73Yq3KipNWKzTILeqJGmEV/lnA9rLRMo1HnW9ZVnX5NtMMe7oRzWf/t+eYByEwBtJgC6LQlLnEniBuif4UHcdBFBtmEhQnXw03kvezk7oJHHw7o+eKH36JQ2+fFPpUTO9vs2Ci14PF6A85GZQy67Jdx8LwLRy+MMw6jxOjH0QvjGbmDzvbZxZRRFlL3YwLRv/EgshEn2Zo0kY7+D39tbf/tcWZlylCWukrjjpvhnl+8CZPvGirUFDbLLNh0OjS9xOS7Fnd8WnQPHC7rvzK3gAPnQpNKdrTZsU/lRG2fF+esMwkD0eHvScrPxQXRv8KDOOgig2zCwiLZw03w+kc43u/FbqUD5VGdzbe0WNCg9cU0yLEOBwrzNDbLLNilsKPTPoNO2wwU5mm0DAVQJDWjSuNmsuT0QeK0KQC9J4jTpgAOng/Naz1wzgWpKZBxx3F+8SZ6qFlUadyiyyiTw5YwIPqXHSIbcZKtSRPp9uQwB95LOCKMHkcW67OYA++hSuNGk24yqfFpya5f77mK55qHUSQxY5fChjKlAyVyW9xeL+HniHqtDxVqChVqCg0637IzBbElhQnRv8KDOOgig2zCwiLZw8384k3Us8wG36Wws84Gj3U46LTNYLfSgS0tFmYcjNoZmhu/ptGEtU1DKJZbUdXjhswUiFiX3hPE0QvjEXfUM+Uohx8+GnTxDx/ZhBx0xAfRv+wQ2YiPbFY1pfteH9/6BBpqFptOW1DaamMy0/QIs7oBLxq0Pk7d2ulgtsQQ4JS9D5+Ewvb8S+/O4/LcAv7QReHBGh3+vaIH36/sxQOv6/FkvRFrmoagoWZjvkf4OaJa48YGqRkbJGZU9bgZ22zyXctKpQMhNxD9KzyIgy4yyCYsHFI9cOg9QRRJzEl1U2d7r0r1GNZLzJAY/eiyh5zztU1DOPwWhWqNG6VyK549OYwKNcUY82yXmscKYlT3uKGhZnPiHGerpJMgPIj+ZYfIRnxke9JEuj055hdvotngR5NuEp22yOqweq0PdQOxe5y83utBdY8b56wzzHWwHW127FY6cOC8C1fmFpa9F1vPl5peD7N+mSmAPe0OVKgpNOknsa/DiZ+82o9fVeuw+nU9/vOPvfh/X/oz/p+XuvHjP/Uz996j78uH31nfpQhV15WrXMyoN/nwJVSoKVRp3BmvdCDkBqJ/hQdx0EUG2YS5IRPZ0lQPNx/f+gRSYwDrJWZsaQmVqFeqx1DT64lrbGMdbmp6PZAaQ1mAugEviuVWHOkeY7qkd9pm0KidjOh0m81DmRDvnWerpJMgPIj+ZYfIRnxkWz/z0ZODzcnXe4IJ550n0/sllp0It7fhHd9bhqagtExjo2QE/+ewBquOabFBasFDtXr870Nv41/2X8C/V2iw6bR5WTf38DvrW1tG8dvaQWxtGcWhTgo7FXYoLNNQWkLX2Zp0k4KxowR+IfpXeBAHPcfU1NTg3nvvxWc+8xncd9990Gq1rD/b19eHO+64Y9m/sbExzu9HNmF2yWS2NJ3Dzce3PoHecxUNS1F/LuuKd7hJ1CW9bsCLidkPmOYz2TqUCW0WuBADBoTsQfQvO0Q24iQXkybSCZjHs4PxPksylWuJ7ETw+g1cevfDiLJ5hWUaW1tG8ZM/9eH/vtKLJ+uN+F5lD/5l/wX8r4MX8NNXB/Bimx1FEjMq1BTzfnrPVayXmLG91YaD51x4rM6IX9foUSQxMxn0Rp0Pm05boFy6ypZrO0rgH6J/hQdx0HPImTNn8OlPfxr19fWgKApbt27F3XffjampqZg/TzvoExMTuHLlCvPv1q1bnN+TbMLskulsKR8le8keVNheE+tQQd9JL5Zbcbz/diDA5LuWlUOZ0BxioQUMCNmF6F92iGzESb5OmohlB+N9litzCzhwPtTrZafCjr0qJ45p3JAa/ct6v3CxE9E/02mfwU6FHQ/VDuKnr/bhJ3/sw//Y+xb+x5638L8OduNX1Tq83HkRZYrQaNVL734YNdXFinKVC1tlFqw6psOqY1pm4kp1jxsVaippO0r6rOQPRP8KD+Kg55D7778f69evj/jat771LezcuTPmz9MO+n/913+l/J5kE2aPbDiHQjnc0IaY7mJLO970nfQj3WMRAYrwhjOZXreQZoELLWBAyC5E/7JDZCNuCsmZi/VZbt/1DmW9qzQT2KdyYrPMgmK5FXrP1YhO6c0GPxp1k8smodB2IpYtqe334tHjBvzgSC9+fLQX/3N/N/5lfzf+z+G38YuqARTLrShT0g76POPkd1jfYWa7v3jWhmdPDuGJeiOOaSY4B9XDPzPps5J/EP0rPIiDniMWFxdx5513QqlURnx9y5Yt+N73vhfzNbSDfu+99+Lv//7v8cMf/hC9vb1x3+ejjz7C+++/z/ybnp4mmzBL8JEtTWa+eS4ON9GGWGoKQGoM4LQpEPNOeqxDRqY/n1CCGDRCChgQsgs5BLFDZEModGjdX6kew7aWUZTKbdjWMooj3WOMDaDtVYWawjMnh1knoYQ/L7xp3IutVjxQo8WqY1r870N/xv0vv43VNXr8rsGIR+sMeP7UMFPiHu3kd9pnoLBMQ2L0L3WG/5CxuWx2dH7xJmszO9JnJX8g+ld4EAc9R8zMzOCOO+7A4OBgxNcPHTqEb3zjGzFfMz4+jhMnTsBiscBgMKCoqAgrVqzAwMAA6/uUl5fHvLdONmHmSfeOeD5EoNlK+PWeYNw76VwDFHzKQSgZGvozNRv8eL3Xg2aDX5C/WwL/kEMQO0Q2hEJmfvEmrswtQENdQbHcii0tFuxVOVHbHxrVFj1LvWVoinUSCk0sp7mHmsUbfR6cMvhxqNOFJ+uNeKzOiEePG/DA61qUyK0RTeKSDRhH29HwM4DSMo3j/V481zyMI91jpEosjyD6V3gQBz1H0A66wWCI+PrLL7+Mb37zm5yfs2rVKvzyl79k/T7JoOeWVLOl+dDpm0sjm3TLufNBDskS7qBX97iJgy4iyCGIHSIbcSGUgGmmiQ4y12t92NvuxGlTAJ32GSZrrbRMx5ylrjBfQtXbbtRrfZzueofbZbXzMmr7vNilsOP55mFskVkiSumj15dshRn9XrKhAFMiv61lFL+q1uG55hGorNMpBeYJ2YfoX+FBHPQckUqJeyxefvllfOtb3+L882QTZpdUjF++3FPmUsIfHqBQWqbRqJ1ElcbNycHOFzkkSyEGHQjcIPqXHSIbcZAv1WF8Ea3vpcZAqJP6WxTj1O5os6NYbsW+Dife6POgy36Zca73qZwolVuxWWaBhprlJKfoxIDEEMDRC+PQe4Ksr0klYEKfAap63CiRW7G/w4WD5114pHYQP3ttAH+8MF4wdrvQIfpXeBAHPYfcf//9KCoqivjat7/9bdYmcbH4zW9+gx/84Aecf55swtyQjPHLl07fXBzoj299ApPvGirUFDbLLNgks6BCTcHku5bwoJEvckiGQg06ELhB9C87RDbiQEwBSjZ9X6kewyN1g1jXPII9SgfKlA5skJqxo82Gl8670KibRJVmgpmZXqZwoERuRXUPt+B2tvqu0M3saOf8le5xvNI9jvUSM1Yd02KLLDSajfRZET5E/woP4qDnEHrMWmNjIyiKwrZt23D33XcjEAgAAHbu3Inf/e53zM+/+uqraG9vh9vthsvlws6dO3HHHXdAoVBwfk+yCTMLH2V7mXLiMlFSyKWE3xx4D9U9bjTqJqG0THM+kOWbM8tFvoUYdCBwh+hfdohsCp9M6PRslson+15s+v7syCU8UW/AxtMW7GyzY5/Kidd73PhDF4U1jSb8rsGE1TV6PN88gr3tIee8dsnOssmJrXN8pmWjoWbxzMlhlCkdzHz3F86MYmebHZtlFrze6yn4KolCgOhf4UEc9BxTU1ODr3zlK7jrrrtw3333RTR8W7NmDb7//e8z/11ZWYmvf/3r+Ku/+it88YtfxHe/+110dXUl9X5kE2YGvsv2+Oz0ncmSwkSR+nQPZPnQ8TwZ+eZb0IHAL0T/skNkU/jwGaDMZql8qu/Fpu8btZPYJLOgZSgAhXkanbYZ1PZ7sa1lFJtkZuxTOfFAlQ6/rNJivWSEaSQXS065vDIwv3gTk1c/wEudLpTKrUywobbPC5lpalkneLZniKEXgdAh+ld4EAddZIhlE2Zb6fNdtsdniVo2SgrZ5J3sgSz6OdkckZbq30yy8s2HoAMhM4hF/6YCkU3hw2eAMpul8um8Vyx9X6Vxo0JNRYw326tyYnurDftUTijMl7BL4cCm0xbsUjqYWeix5JSLKwPRQYEKNYUdbTacGPBxLmkXWy8CoUP0r/AgDrrIKPRNmAuln8msaLqBhlxnbLm+f6LfWyYDLun8zaQi31zPZScZi9xR6Po3HYhsxAEfAcps2rV034tN35t81xg5tAxNYbPMgm0to6jt8+Lti7Oo7Qtl1Le0WNAyNBVTTrmy79FBAdlQAHvaHahQUxGfcW5hkdXWiKkXQT5A9K/wIA66yCj0TZgLpS/ke8VCWBvXe+rhs1QbdZOcG+Lwtb5U/mbSkW+2HWWSscg9ha5/04HIRhzwEaDMpl3j673iVYfVDXhRLLfiSPcY1M7Q+6idl1GpHkOx3IrXe91o0PqWjUjLtBxi2ajg9Rto0PogNfqXBQVCJe3zmFtYTBhwJ1e9hAXRv8KDOOgio5A3Ya6UvpCNTabXxsXJ5HpPPXyWKj12pkJNYW5hMa01Jlp/OvIR8u8+GpKxyD2FrH/ThchGXKQToMynDDqX5wevfwS9J7gskF3T60GTLjQ7/Xi/d5ntjOcsp7O2WMFck+8aTL5rqNf6sO7UCHYp7MzdeLbxqmy2RgiJA0IkRP8KD+Kgi4xC3oS5VPpCvlecibWlko1NdE89fJbq4S4Ke5QOPHtyGD3UbMrrTAQffzOZ/N3zlWXPp0BCIVPI+jddiGwIyZBpmxuue/l8r/Dnhv//WIFsqTGAml7PMkfX5LvG/OyBcy6sl5hRqR5Dh/UdXuQQy8He0+7AnnYHpMYAdisd2N5qY7rLh9uS4PUbCW0NsUfCg+hf4UEcdJFRyJswl0o/1/eKs702PrOxbLNUy1UulMitaDb4BV39kIp8EznefJejk4yFMChk/ZsuRDaEeKTSQDSenmX7XrzscTo2NPy5DTofKtQUKtQU6rW+iOfR64rn6FaoKVRp3GgduYRz1hkc6R5DkcSMg+ddaduKWDax0z6DYrkVpXJrqON8nxclchtK5TbsUtghMfoZ+8/V1gg5qSFGiP4VHsRBFxmFvglzrfSF3IBLyNnYWLNUS+Q2VGvceVP9kGy5fzzHm+9ydJKxEAaFrn/TgciGEItUGojGew39vWaDH9U9bjQb/BHPi6d707Gh5sB7qO5xo1E3iaMXxrBBYsYGqRnVS452tH5nc3SVlmlsllnQpJuM+LrEEEC91ofg9RtpyTvW+yos0yhptaK01QaFeRpq52XU9nmxW+nAeskIGrS+iABDso1hhZbUECNE/woP4qCLjELfhETpZ55MZGPnFhZRoaZizlItpOoHLo53ppzpXAevCIWvf9OByIYQi1SClfFeY/Jdw552B0rl1tDc8dMW7Gizw+S7ljHdS9u3ErkVJXIrHq0zoEhqxt52B/apnOi0zSx7D3otUqMfCss0M2qtUefDptMWKC3TGWsMlyiDnigokIytEXJSQ0wQ/Ss8iIMuMsSyCYnSzxyZdCCrNG40aic5z1Llk0z/zXCVW7wASN2AFxOzHyxbIx/N+giZRyz6NxWIbAjRpGJr4r2m2eDHS52hO9tFEjN+32DCQ8cHseqYFlvPWOALXs/IVaAeahbPnhzGHmXIIX+odhCPHDdga8sodrbZoTBPL3uPj299AqkxgPUSMzbLLNilsKNSPYbX3p6ImKGeiWqoWA42fQedi9NNbE3+QfSv8BC1g76wsACdToeLFy8u+96NGzfQ3Nycg1VlFrIJs0chBwky3XiuEI0618qDWAfM8JE7dQO3u/nSDYz4aNZHyDxE/7JDZEOIJpVqrXiv+dOfJ/Bc8zDWNY/gsTojnn5zGOtOjeCR44P46WsDUFou8R58pnuslMqtKF9qgPpU0xAerzPi0ToDdikdMTPo5sB7qOn14Ej3GHYrHdjSYkGRxAypMRAxQz0T1VCxbHEq9/CJrckfiP4VHqJ10CcmJvCVr3wFK1aswMqVK/H9738fly9fZr4/OzuLlStX5nCFmYFswszD9Z5xtoxXJt4nk850oRr1ZLJB0QGQSvUY1jYN4Uj3WETJptQYIKPT8giif9khsiFEw3cG/Y1eD55rHsYjtYN4+s1hbJBasEFqwZqGIfyqWoeaPg/0nqu8Or90wKBa40aJ3IZylQtbW0bx4Ot6/Oy1flS8RS17j+jP0GmbgcI8DYkhgJbhqYg545kMZseyxYVqn8UO0b/CQ7QO+oMPPohVq1YhGAzC4/Hgl7/8Jb761a9iamoKAHHQCamT6M4c3x262ZhbWISGmkWzwZ+x9yHGOjm4Vh6E/43UDXhRLLfiSPcYM3P27YuzkBj9KJZbITUGSOO3PIHoX3aIbAixSKVai+01es9VlKuc+NlrA1jTYMK6UyN4umkYv67R47nmEdQNeHFlboFX55d2tluGplDb58U+lRMvnrVhTZMJaxpNeKPPE2O+Ofdqq3TtL7HhBIDoXyEiWgf97/7u7+BwOCK+tmHDBvzTP/0TfD4fcdAJKcEl4s93h+5oaOeuQk3hmZPDKJFbUdXjhmwokLXsKjH6sUm28mB+8SYmZj9A3YB32WGtZWgK606N4MzQFBmdlicQ/csOkQ0hFmw6c25hkdXGxNOz/RN/wSN1g3igRo+Hagfx8PFBrGkawuGui8uatPFlw8L7q7QMBdConUSVxg29JxjzPbIxdSNbiQJCfkD0r/AQrYP++c9/HhRFLfv6pk2b8I//+I/QarXEQSckTaLI96V3P8y44aUPA6VyK8qUDuzvCM0Tr13KKGQyu0qMPjeSOfyxHdZIBj3/IPqXHSIbQjxonRle3p3IxrCVaB/qvIifvTaAn/6pH7+p1WPbmVFUadwZCV5/fOsTmHzXUKGmUCQx47lTI3ip0wWT71pcu5jpqRuZThQQ8guif4WHaB30f/3Xf8WpU6difm/jxo34whe+QBz0PEMIWdtEke9L785npEts9Ps36Saxo82Ow10UXukeR7nKhb0qJ5SW6YxmVwvV6Of6b4vtsEbfQSej0/KDQta/6UJkQ+BCujaGbr52qOsiiuVWbJCOMM3Xkg0kc7EL4c3etrfZsK55BM81D7O+H/3MK3PzzBW1VErt460tGxl6Qn5B9K/wEK2D/oc//AE/+9nPWL9fVFSEFStWZHFF2aEQN6HQsrbxIt+ZNox0Bl9pmcY+lRPlHS680j2Ow10UdirsaNT5MmaAC9HoC+Vvi61kM7yLeyF2vi80ClH/8gWRDSER6dqYRM3XuNqoZBrBtgxP4Uj3GErkVuxf6uK+vdWGIokZek9w2TNPmwI4cN6FYrkVB8650KSfRA81i7mFRd7Wlkp3fEJhQ/Sv8BCtgy5WCnETCi1rm+iecSZL18IPILV9XqZrbJnCgWK5FdU9mSnjAwrT6Avtb4stK5LrDD+BG4Wof/mCyIaQiHRtDF82iqtdCF7/CHUDXuxS2LF/KVhOB8w3yyyo1/oixqod7/fiSPcYtrWMYnurDdtaRnGke4zV5sTS+1zWVojBdEJ6EP0rPIiDLjIKbRMK2dCwOU2ZnvdNG2iZaWpptIsVz54cRoWagt4TxJW5BZJB54AQPg9xvAuLQtO/fEJkQ0gE3xn0VHR6Ms+YX7yJBq0Pm2UW5roZfeVst9KBugEvo99bhqcgNfqxV+VknPlylQv7VM5lGX62LPncwiJrv5IGrQ/B6zeYtWX6jjshvyD6V3gQB11kFNomzOesbaacr+gAQLPBjwuuy+if+EvGS7ULyejz8beV6u9YKKX1BH4pNP3LJ0Q2BC6ka2PSfX2ydkHvuYr1EjO2t9pwuItCucqFErkNleoxxummn9kyNBXRO+ZwF4VSuRUNAz7GmQ//DNFZ8h5qNmJtaudl1PaHMvjrTo2gXutj7EimEwWE/ILoX+FBHHSRUWibUAhZTqES7hxyL8m7gYnZDyIi7clQSEY/nb+tdB1soZXWE/ih0PQvnxDZELiQro1J9/XJ2oWPb30CqTGAIokZm2UW7FY6UKkeQ02vh9HnsTLoFW+NYf0pMx6tM2CDxIJiuRV6z1XWLLl8+BKaDX40G/zM92r7vSiRW7G91YbdSgfTVDS63J1UaRGI/hUexEEXGYW4CQspa5sJY8nlQDG/eBNSYwDFcivWnRphxncluw56/cHrNwrC6Kf6t5WKgx0uOxJ0KkwKUf/yBZENIRnStZXpvD5Zu/DxrU+g9wRRrw1lwmMFBehnVqpDd9DXNg7h568N4KmmIWySmrH/nBNVGveyLHl0Bl9DzeJ4vxcSox+7FHZsb7WhRG7DsbfdKTXEI4gDon+Fh+gd9IGBAdy8uVxR3bx5EwMDAzlYUWYpxE0oxKxtssY/kyXNXErypMYA1jYNYXurDS+dc2F7qw1rm4YgNQZyvv5cksrfVioZlnDZNWh9OHDOhXPWmby7tkGITyHqX74gsiFkgkwEvVM9c8RbS3gX970qB1bX6PHYCQOeOzUcKpE/a0WJ3IqXOkOd3dnsCz0nvkHrw7pTI9jZZkeZ0oEypQM72uzYrXTgwHkXrswt8CYPQv5D9K/wEL2DvnLlSvzlL39Z9vVr166ROeh5BldDnMmSrlQd1UyWNCeezf4hipfK4OgmNq90j6NUbkOx3Mqp3L3QS7KT+ZtJ9o5itOykRj/WS8w40j1GMugFRiHr33QhsiHwSTaCxnycJaKfMb94ExOzH6C6ZwIVb1HY2jKK8qXxbGVKB55pHsbxPm/CDH7w+g3Ua3041HkxNM1l6RmlchuebR5Gl2OG2BICA9G/wkP0DvqKFStw9erVZV+fmJjA5z//+RysKLOIeRNmw2CnWtqc6ZLmeCV5E7MfYN2pEbx0LnIMzC6FHc+eHMbE7Adxn036AESSbJffWD9bqR5DkcQMiSGQkVF8hXD9IB8Rs/5NBJFN4ZFLXSP0oHG888j84k00G/wolVtRHjaerVwVmo/epPdB7wmi2eDH670eNBv8Mc8yek8QRRIzSuWhBnV7lU78rt6Ix+uMKJKYWV9HEB9E/woP0Troq1evxurVq7Fy5Ur8/Oc/Z/579erV+NWvfoV7770XP/nJT3K9TN4R8ybMtMFO1VHNRif6eCV5wes3mAx6pZpCsdyKtU1DeKBah9U1emio2bgGPJ876WcKrncU2WTXYX0HB8+7UK/18XZto1CvIeQTYta/iSCyKRxyrWvyIWic6DzSQ83i2ZPDKFM4wrq/W1HV40aDzoceahbNBj+qe9yo14b+e25hMeI9rswt4MB5F3Yp7HixzYZHjg/ix3/qx+oaPX5To8eBc66IZnUE8UL0r/AQrYO+du1arF27FitWrMAjjzzC/PfatWvx/PPP4w9/+AOCwWCul8k7Yt2E2TDYXBzVWBmFbB0m5hdv4tK787j07ofLnknfQV/bNISH3hjEb9/Q4+evDeAF+SiO93uh9wRZMyH5cBjKNlzvKCaSHZ/N9oSeURIDYtW/XCCyKRxyrWuEHjTmYjPnFhZRoaZQIrdip8KOvSonavu9kJkCqFBTqNK40TI0hWqNG6VyK549OYwKNRVhZ8K7w1e8ReGB13V4/IQRaxpNeLzOgK0toxHj3gjihehf4SFaB51m//79+PDDD3O9jKwh1k2YDYMdz+ieNgWg9wRZMwqZ7ETPJZsxv3gTTTofVtfosapqAI/WGVCmdKDD+g4q1WMolltZu89mev35DJcSz2zIjgRRhIFY9S8XiGwKAyHomkytgYs+T/Qz9B3z4/1eKC3TUJin0WmbiXkeMQfew9ELYzimcaNlKAD58CVU90jOxyMAACAASURBVLhRoabQOnIJtX1e5n55mcKBErkV1T3uCNthDryH6h43NkjN+O0beqxpGMJjdUYUy60oV4Wy6+Ez1gnihOhf4SF6B11siHUTZuvQwOZs0fNH2TIKmexEz30G+keo0rjRMOCDwrw0R7XPi20to9jSYkHL0BTra4XYSV9IcOnem0nZCT2jJBbEqn+5QGRTGAhF1/AZ+OQS5E70M+Hff6PPgzWNJqxpMmH7WSv2qZyo7fNCZppiziMf3/oEJt81VKgpbDptwWaZBRVqChdcl1Gv9UFpmcY+lRPlHS78oYvCvnYnSlutaNT5Is40H9/6BBpqFuslI/h1jR6P1xlQLLeiUk3hcBeFLS0WNGh9JEgrcoj+FR6id9BnZ2fx5JNP4ktf+hLuvPNOrFy5MuJfoSHmTZiNTGUsZ0vvuQqpKcC5aViiOeLJNN5Jp2FZp20G+1ROlMpt2KtyotM+kzCoEbx+AxOzH3Dq/F5oxPq9JHMXM5MNlYSQ1SKIW/8mgsimMBCKruEz8MklyJ3oZ8K/X61x47ETBvzk1X483zyCMqUDRRIz9rQ7Yv680jKNJt0kqjRu6D1XQ/ZEN4ntrTZslVlCV9NqDXi0zoCj3eNo0PkiAiF007kDHa5QV3jV7Y7u6yVm6D3LGyUTxAXRv8JD9A76T3/6U/zzP/8z3njjDbS3t0OlUkX8KzTEvAmzmeUNd7aSySjEc+hSabyT6sgv+fAlnBmawmaZBdtaRlHb72Veq7RM4/VeDy69e/tqSK6bAuWSeJ+dz7uY6Trw5BpC7hGz/k0EkU3hkIquyVSAkq3vSzJB7maDH426SSZIHR1w4NJLhP4+Hfjeqwo55Y/WGVDaakWx3IoKNYW5hcWEz9N7gqjSuLG20YQHX9fh8TojHq4dRJHEjCKJGRVqatlnMwfeQ02vB5XqMexWOrBZZkGRxAypMSAKO02ID9G/wkP0DvrnPvc5WK3WXC8ja5BNmP3RL8lkFOI5dFydvfDPl2w2I9zZrBvwolhuxZHuMaidl6F2XkZtf+hrm05bIka05LopUC5h++x0piPdTBJfwQ9yDSH3EP3LDpFN4ZCMrslmcDfZ9/r41ifooWaxSWZBSWuoWdsfL4xDZZ2OCHInCoRPzH7AfF9hnsaONjsOd4VKzEtbrTg56IfSMs35eVfmFqD3BLGmyYSfvRbqGbO1ZRR72x2sDnq0ba/Xhka1Ef1PAIj+FSKid9C//e1vY3R0NNfLyBpkEyYPHw49l4xCPGe62eBHs8Ef19ljO3yYfNdSzmboPVeZ11b1uFEkMWOD1IxqjTvMEQ0KoqQxF8T7nTVofTje7037LibfwQ8yBz13EP3LDpFN4ZFMk0w2/canvkpWl5oD76FK40bxmVE81zyMx+uM+FWVDuslZlSqxyA1BRIGwpsNfkxceZ+x33QGvbzDhXKVi7k+lkxGnpbJG30eVLxFYZfSwXR6p8ewsdkXov8JsSD6V3iI3kG/cOECfvzjH8Pv9+d6KVmBbELu8BnZ55JRiBc1r+51o7rHHdfZ03uu4uiFcUiN/ojDh8l3LeXMKb3uZoMfm2UWlMqtqO3zQu28zBwY6rU+1A2k74jmI/F+Z3SWIp3AhVDucxL4gehfdohs8pN0HL50Jp/w+V6xdGn4z5cpHVh1LFRK/uQJI1bX6PG7BhOkxgDz89FBeJkpgD3tDlSoKTTpJ1GhprCn3QGZKTQajS5Hr+pxxwyaswX16ZGnEWXz9hkoLNPLHH0CgStE/woP0TvoX/jCF3DXXXdh5cqV+NznPocvfvGLEf8KDbIJuZOJsu14h5lUM+inTQFoqFkUy63YLLMw81LVzsvLovJcDlKxfu7Su/Oo7nFDaZmO6Yg2pOmI5itc7gqmc+9bKB2RCfxA9C87RDb5BR8B7Hj67eB5F45eGOfN/iarS+mfV1qmmSZuTzUN4fETRjxUO4j9HS6cXsqgR8vjzcHbDnnL0FTIYR+67bA36HyoUFPM/0/UFf7NwUlITQFIjQGcNgUYeUuNAbz29gQadaGu7qSvCCFViP4VHqJ30E+ePBn3X6FBNiE3cpW5jFcKH2+E29EL49gss+Clcy7s73ChRG5F7VJ5NVdH7uNbn0DvCaJ+qTQ7/NCQ2BG9mpIjms3GQJki3u8s3XvfJINeWBD9yw6RTX7BRwCbTb9JjH4Uy62QGgO86b3w9+KScaZ/vkk3GXFn/MWzduxSOpg745fe/TDC1swv3sSldz9kDajXa32wX/ovBK/fSGquOm1jaXnLhgLYrbBj6xlLxBg2k+8auVdOSBqif4WH6B10sUE2ITdylbmM59DFG+EmNQaYe22vdI8zd9skRj+nA83Htz6B1BhAkcSMzTILdisdONI9hppez7KxL3w4olyzL8k62rnoJs/ls6cTMMhU93VyFzH7EP3LDpFN/sBn4DCWfjt6YRwHzrl4sb/hes7ku4Y97Q4Uy60oWeqcvqfdAZPvGuvaqjRulMitKFM6UK66HfyWmQKoUFNoNviX2ZpY5we18zKqNW5slllQ3eNOyjbFkndtvxdFEjNK5Va0DAWYMWxc7UI29D+xMfkD0b/CgzjoALxeL8rKyvDoo4/iL3/5CwBArVbD5XLleGX8QzYhN3KduUxUCh9rhFttnxclchvKVS68dM6FLS0WHL0wzslg6z1XsV5ixvZWGw53USjvcKFEbkOleixmE7p0HdHo7AtdBaD3BAGk7mjTz5UaAzgzFCoBzFbJX6YOI3x3XxfzSLxcQ/QvO0Q22SUdfcVnADte4Dkd+xtLz9VrvXjhzCi2tVhQ2mpDaQIHnX5GhZrCM83DKJZbUdXjZu6X72l3xKwgiOlQ94Uc6hK5FUrLdFIVB9Hy7rTPYK/KiT1KB3a22aEwT0fIJ3j9BuvvNhv6n9iY/IPoX+Ehege9v78fn/3sZ/Ef//EfuOuuu+Dz+QAAlZWV+M1vfpPj1fEP2YTcyeXc6GTui9MHAbUz5KTvUzmxWWZBsdwKvedqQqM4v3gTDVofNsssONxF4ZXucSYLv1vpQN2AN+LAla4jymXNdOd5ruWTdFlhk34SR7rHsE/lxI42O/apnBHddjNNJjMGfD1bzCPxuJKp3yPRv+wQ2WQHPpynTASwo/dcuvY3XM91WN/Boc6L+MUxLZ6oN0SMS+Oy5rmFRXTZZ1DT50F1jxtv9HrwUqcLLUNTrJ8/fP1KyzRK5FZskJhR2+9NWl7R8lZYQqPaypQO7FM50WkLzWfvsL6Dg+ddqNf6WH+32dD/xMbkH0T/Cg/RO+jf+c53cPToUQChmei0gz48PIx/+Id/yOXSMgLZhNzJxdzoVA5P0QcZiSEyG52I4PWPUDfgxfY2G15ss+PgeRcOng9l4TfLLKjX+nh1VGJm/TtuZ/0r3hpDhZridPgLl1d1jxuPnzDgdw0m7FU5mEqATVIzdirsuPTufFLrTMZJy5eMQa4rQ4ROpn+PRP+yQ2STHfhynjIdwE7H/kbrudp+LzaetuCBah2eOGFEmdLB2qclWu/T6zhtCmBvuxMbpJaQs700bpSeaBJdQRBhm3rd2CSzoKqH/efjfRb6DnqVxo1G7SRahgIoXlpDbd9th79SPYYiiRlSY4B1ZF06+p/rnXliY/IPon+Fh+gd9LvvvhuTk5MAIh10v9+Pz3zmM7lcWkYgmzB5ctFwLN7hKdYBgm7uVjfgTdqpmFtYRIWawu8bTfiPo334wSt9WFWlxYM1ejxSZ0D/+F94/Yy0AWe7N3+8z4NNpy0xO8ZHH2bC5dUyFMDqGj1+WaVFsdyKirfGUCy34tc1evyqSocGrZeTXLg4aWzZHqFnDEhX+Phk+vdI9C87RDaZh0/nia00/crcAq+2MhX7G67n6HLwMqUDv28w4eFaAw6cuz2DvFEXmkJyeW4hpt6nq7mOdI9hW8sotrfasOm0BWsbTcsc5FhyDFV3zbM2jWOTe7hdr+n14FDXRWxrGcXGpYZwW89YsFthh8wU6hIvMfqxXmLGke4x1vdIVf8nE7gkNiY/IfpXeIjeQf/yl7+MwcFBAJEOulKpxNe+9rVcLi0jkE0oXBIdnuYWFpcZSZPvGky+a2gZnmLGnXEpaw/HHHgPe9odeOT4IP7zaB9+cKQX/35Ygx+80ovnTw2z3s9LB3PgvYjO8+HNd5SWaWyWWdCkm4x7mFlW9meexjMnh/FgtQ6P1Rmw8bQZv64ZxOrX9XiqaQiNuklOzlY8Jy3WQUXvCeJ0mvclswXJbrCTDdkQ/csOkU3myYTzNL94E1fmFjjNLM9WsDt8L9Pl4Ie7KKyXmLG6Ro/dCgf2dzjxZL0RT705jAPnXBFj0ZSWaTTpJnH0wjgq1BSkRj/2qpzYHxZMXi8x47nmYWyVWdA8OAmJIX6/E9quSIx+tAxNQWL0s/58dNPWZ5uH8dgJA9afMuPohXE06ibx2tsTkBoDTICkQevDgXMunLOGyt07bTNQmKeZbvO03FPRcckELomNyU+I/hUeonfQt2/fju9+97u4cuUKPv/5z8Pj8UCv1+NrX/sa9u/fn+vl8Q7ZhMIl0eGph5pdZiTjNarhAm1Mmwcnse7UCB6vM+KxE0b89o1BPHtyCCf13LrAJwudHSiWW7GlZfns9go1hSqNO2755LLGObYZlCkdeL55BL+u0ePBmpCjXiQxY0+7I+5InWh5JJprHi7voxfGceA8Px2Hs0EueysImWxkfoj+ZYfIJvNkynlK5MDl4gpQuEO8S2HH9lYbXjgzytzbfqLeiFXHtDjUeRFnRy6hRG7FeomZ+f6ONjs2Ss14ot6A4/0ebGsZxcHzIQf9cBeF0lYrtp4Zxa+qtXjqzSFmLFw82yI1hkrT150aifvz4U1bD55z4bE6I35do0eRxIy9KmeELaMbwgWv30DL8BRahqaYvi472uwokVtRoaYwt7AYIReu+j+VvxliY/IPon+Fh+gd9I8//hiPP/44Vq5ciRUrVuDTn/40Vq5ciSeffBK3bt3K9fJ4h2xC4RLPEDYb/MtK5DrtMyiWW1EqtzJNYqINZ6KMBe2UtAxNYUebHQfPuXDgnAsHz7mws82OM0NTGXUy9Z6rOHphHBKjP8KQm3zXOHWMZ+uUu/7UCIokZuxoszGZeS7OVjwnrW7Ai3qtb/nMXkNg6bDlz4uMQS56K+QDJIOeW4hssgPfzhOXfZPs1RE+Mu3heu7geReKJGZUqsdwzjqDRp0PT705hENdFyOarq1rHgll2JWhHibb5VZ870gPHjk+iN/WDuLxOgOK5VbsbXdg/amlDPqZUZwy+CGNkxEHuE8YiW7aeuCcC082mLCmYQi/bzShtNUKhWWa9crXnnYHipYCDWUKBzYsBahjBUu46P9UApfExuQfRP8KD9E76DRerxdnz56FXC6H2+3O9XIyBtmEwoatDE5DzS4zkgrLNEparShttTFjVmjD2aDzQUPNcio5DN0HX17Ct0/lhMQQyKiTmciQJzqoRR82ZaYp7Gl34KXOUIM72jmnG/Okk0Fv0PpwfKmpUPRB5cB5F45eGM+rjAGZUbucTGd+iP5lh8gmO/DtPCVy4C69O8858JWJTHt0CX7McnD7DHYpHXikdpC5o/5K9zjWnzLj/x7pxc+PDeDpN4ewulqHVce0ePyEMXQHnWNX9mSCf3TT1l0KO/Z3uPCHLgprm4awptGEh2oHsf2sjbUajO4nUyK3YqfCzlSmyUzL7Xgqk2KSDVwSG5M/EP0rPIiDLjLIJhQmtCELXr8RswyOLl/jmkGvUFOo7nFzyljQTkmlOtQEp1Ruw7aWUVSqx3I+Vi6RgY8+bDYb/NBQs7g8twANNYvqnvhl8rFgc9L0nqusBxWpKcB8n2QM8pdMZ36I/mWHyCa78OU8JXLg6PGXXDKwmW7SGG5no9d89MI4fvbqAB6uNeDgORd2KxxYXaPHsyeH8czJIZTKrXjm5DBW1+jxUK0e606NcO7KnkwWmpbnke4xlMitKFe5sFVmwapjoeAAHQiOJRf6fZSWaSgs0+i0z/ByTYeUrBc+RP8KD9E76Ldu3UJDQwMee+wx/OhHP8IPfvCDiH+FBtmEwiI6Y0A3qmke9C8rg4tlJOk76OFfq9K4OY8pC1/DaVMAB8+7UCy34sB5F6SmQErzcfk49CWbSZlbWEQPNYtmgz9mA71knK14TlqigwrJGBQGZA569iGyyV/i6UWuGdhsNxczB95DdY8bjToflJZpnBycxCN1g1jbaMJOhR2lZ2145uQwdils2KtyQmG5BIV5Gi1DAfzpzxN4o9fD6TOxBQTifTZz4D3U9HpQqR7DLoUdm2RmPHLcgG0to2jQ+RJWxPEtQ1KyXvgQ/Ss8RO+gb9y4EXfffTcefvhhbN26Fdu2bYv4V2iQTSgswjMGSss0M1811uiW8C7utJGM5YT2ULNo0Pk43xkLP0SE/2+qI3e4ONSxHKDwryWbSYn386k6W7FeRw4qhHQg+pcdIpv8JZFe5JKBzeZ4ro9vfQKT7xoq1BQ2LY0tq1BTODXox2tvT6BR50PLUAAlciuebx7B0QvjTDaatsca6krM/imxpn00G0JX1V798wSnLHT468Ons8wtLCa0ZZnMdpMAdOFC9K/wEL2Dfs8996CrqyvXy8gaZBMKh2VjwpYa1dBdZOmy9egDSiLnlmsUnc/7flwd6ljvGR5koA8zFWoKsqEApyxALsa6kIMKIRWI/mWHyCb/YdOLXHqNcJ0VzofujQ6MN+kmUaVxRzQnbdD5sPWMBY/UDWKTzIxdCjsq1WOo0rghNQYgNQVw4Fyo4uzgeRdOh1Wc0c9vGZpCtcaNUrkVT785hG0to6hQU3Gz4NHyvPTuPC69+yHnz0u/f7PBjz/9eRxv9HqSHr1KEB9E/woP0TvoX/rSlzAxMZHrZWQNsgmFw7IxYfYZ7FU5sUfpwM42O9P4LRVHk0sUna/7fsHrN1Cv9UFqTOxQx3rP6FFxTbpJPHtyGFU9bkYuCkvkPNd4csxk5qVQEGKAQYhr4huif9khsil8ovc42xUvmSmQMCudakCZS0B3fvEmNNQsXnt7Ake6x7Bb6cCWFguKJGYc6ryImqXy9pC98uGl8y5oqCvLnl/b50WJ3IbyDhfKFA6UyK04emEMGmo2oZ5L9fPS1QEvnb+I55pD00wq1BRMvmvESSewQvSv8BC9g/7HP/4RGzZswH//93/neilZgWxC4RBzTFh/aExYidwKpWU65fI0LhmLdLPO9Hs0aH1Yd2oEu5UO1Pbd7pgeK/PPpdFdp20GJXIrXpCPokozgb1L81yLo+a5xpOjkMec5ZJczCPOxzVlCqJ/2SGyER/RAduWodAUjgo1xdr/I9WAMh0c4NK0LtqmdNpmoDBPo1E7yYzUVDsvo7bfi70qJzbLLCiWW6H3BHFlboFp1LZP5UR5x+3Z6TsV9lD5PAe7pPcEcfTCOKTGQFKflx61tkFixh6lA2VKBzZII0etEQjREP0rPETvoD/44IP4m7/5G3z1q1/FqlWrsHr16oh/hQbZhMJi+ZiwAOsBJRXYspJ8ZJ1vz3X1Y5fCju2tNpTIbcz9+WgHOdZ7so2Kq9a48dvaQaxpHEKJ3IodZ21xDxmkyyw3Mt0luVDWlCmI/mWHyEZcxAusNhv8EWXd6QRhY90HT3SFis0+nhmawrpTI2gZmkJtvxclciv2d7jw0jkXtrRYcPTCODPNo0k3iR1tdhzuopjRpXtVTtZKsPD16j1XUSy3YqPUjO1nbajSTEDtvMxpTGizwc+s65Xucea9S+RWNBv8gg1Yi6GCSsgQ/Ss8RO+gr127Nu6/QoNsQmHBlunm0gwmHdLNOke/nj6slMpt2K10QGIIxGgCtLwUnm1UXKN2Eg++rsWDr2uxukaPR+sMKFt6brxO9PncvC3TBxQhVhoIcU2ZhOhfdohsxEUyQeJY18HiXXsKJ961qnjTOGLppUbt5FITVw/2qpyME1yucmGfysnYJ70niCqNGyVyK8qUDsZBrl0KIsfTbebAe3ilewxP1Bvx+AkjHjo+iNU1epS1O9BhfSciyx9tL4LXP0J1jxslrVYmMEBn70tbbajudQvuypeYKqiEDNG/wkP0DrrYIJtQmOQiepxO1jn6wESX++1S2LFeMoJ6rY8xsuEG+MB5F4okZlSqx3DOOsM6Kq5EbsVvawexo82Gfe2hMr0SuQ3VGnfcA1k+RuGzdUAR4l19Ia4pkxS6/q2pqcG9996Lz3zmM7jvvvug1Wo5v7bQZUOIJJngHP2zsqEAU1Ye79pToveQmaZQoabQbPDjzcFQVl1DzUY8xxx4D1UaNxq1kzg7cgmV6jEUSczYKLXg6aYhPFFvwAGVc8n5DlWO0XrrytwCzIH3UKGm8EzzMIrlVlT1uCEzLQ9chxO8fgMNWh/2n3Pi1zV6PHHCiHWnRvD4CSNW1+jxcudFnDYFoPcEY9qLfMygi6mCSsgQ/Ss8iIO+xNWrV6HT6aDX63H16tVcLydjkE1IoOFyT53N2WU7+EiMfrzR68HElfeZ14Ub4A7rOzjSPYb1EjMOnHfFHBXXbPDjpfMXUSwfzZtDRjJEyzVbB5R0stWZCnyQDHrhcObMGXz6059GfX09KIrC1q1bcffdd2NqaorT6wtZNoTYhAeJlZZpNOp8qO5xs15j2tPuQFESd6sTBQAnr15HDzWLZoM/wtmdX7x5ewybzIIn6o145LgBh9+ioLRM41DnRfzimBZP1huwT+VEbZ8XKmvojnq4fZpbWIRm6fnxKrtoW1yv9eHZk8N4qHYQj9YZ8GidAU83DePZk8N4oFqPp94cQpNuMq69CJdTmSIkpyKJMO+gi03/Cxmif4WH6B30Dz/8EE899RTuvPNOrFixAitWrMCnPvUpPP3005ifn8/18niHbMLUycfsLBcSddZlO1TEuz9Pv07vCaJJ70OjbpKZI0s78g1aH4LXbyxbB93Ep6onVCJYrnLhcBeFMoUDz54cRg81m1X58EUsueo9QZw2BbJ2QEm2aiIb2X0x9Q8oZP17//33Y/369RFf+9a3voWdO3dyen0hy4YQm/B55JtlFmw6bWHtOD63sIgKNYVSuRU72+yMYywzTbHqykQOoN4TjOnsSo0B5ustQwFsOm3B86eGmf4qb1+cxaHOi3i6aQgn+n2oXipnX9s0hHKVc9lYs0Rnh9v9XAIollvxQLUOD9cOYk2TCU81DeHh2kE8fNyAnQobsy42exEtU3rGu8l3LeNX55JFbBVUQoboX+Ehegf9+eefx9e+9jW89dZbeP/99/H++++jq6sLX//615cdNgoBsgmTR2x3pLhmdOcWFpnsw5uDt0fktAxNMR15S1qteKLegJJWK/aqnKjtD3V5j2eAY5Uz7lQkLmcUOrHkevTCOA6cd2XtgJLsXf1sZPcLoX8AVwpV/y4uLuLOO++EUqmM+PqWLVvwve99j9MzClU2hPjQpeRNulDnczYdQztzSss0FOZppmdJIl3JFgCkm7ktqwIzBJhO7XQj0x1tdpQpHdincjLv22F9BwfPu7Cvw4mn3xzGkw1G/L7BhCKJGeslZkiNAU46LDqIUPX2BFbX6PGbGj1+12DCjjYbNkot2N/hwrG3J1ClcXOyF6EZ6h/i0rvzmFtYFOQZhmTQhQPRv8JD9A76Pffcg76+vmVf7+3txd/+7d9mf0EZhmzC5BHTHSkuBjNWV9wuxwya9JORI+P6vHiueRira/TY0WbD/o7kGuVwLX3MNqlUUrBeCYg6DHI5oPBRycHlGdk+PBVqhUo4hap/Z2ZmcMcdd2BwcDDi64cOHcI3vvGNmK/56KOPmKD4+++/j+np6YKUDYGdVO6hc9VHtD4Jd07DA4D0OLR4ndrphnR7VU7sUTqws83OTBuhu80fH/Bgo8SMB17X4aHaQfyuwYTfN5qwpskEDYdqr1j9XMqUDjz4ug6rqgawrWUU286MYt2pEextd6BYbsWR7jFmnCkXncznGYZvPS2mCiohU6i2KZ8RvYP+2c9+FhRFLfu6y+XCX//1X+dgRZmFbMLkEFuEl0vJGWsm+NztTHCnbQb7VE6UKR145uQQNp62oFzlQpkidMBI5Gxzyapm26FLp5IinlwPnHfh6IXxhAeUbFdykPJD/ilU/Us76AaDIeLrL7/8Mr75zW/GfE15eTnuuOOOZf8KTTaE20Tr7GR1DBdnjk1P0uXdwes3mP/lGjSt7feiSGJGidwKpWWaed8eahZ72514sFqHJ04Y8dzJEfy6Ro/vH+nFD17pxQapeVm5e7QcYp0x1M7LeLnzIjZIzdipsGG9xIwj3WNMD5e1TUOoVI9xcmiTGWcXj0zZHzFVUAmZQrVN+YzoHfQf/vCHeOihh3Djxu27sAsLC3jooYfwox/9KIcrywxkEyaH2JyURAEJ1kON0b90qAmNUFOYl8oCl5rUVGkmsE/lRGmrDZtlFmioWc7lf9FOeK6uHIQHJkJZ/UnOWf14cpWaAky5ZbwDSrYrOcQWnMoGhap/UylxJxl08RDPaU5Gx3Bx5tj0pMl3bdkapMYAano9yxx++g56eH+VnW127Otwom7Ay7zv5bkFbJBa8EC1DutOjeDROgN+8uoAfvRKH374Sh/WnRrG0QvjjI5mk4PJdy1m4EFDzaJB64sIFqidl1GpHkOx3BqxFjb7F+sMo3ZeRrXGjc0yC6p73JxsaKbtjxgqqIRModqmfEb0DrrT6cSXv/xl3HPPPfjhD3+IH/3oR7jnnnvw5S9/GS6XK9fL4x2yCZMjn5wUvgxcvCxFvIDFwbBMsNIyjRK5FRskZtT2e5msenSX23TWl80rB6mO+Ym17nizd5Ptmp/pv0O+yg/J4StEIevf+++/H0VFRRFf+/a3v02axBHi6uxUdAybPomnJyvUFKo07og11PR6IDUGljn884s3GUe6QedDhZpChZrCG30eNGh9hGdCHgAAIABJREFUTFY8eP0j7Gl34IHXdXjk+CB+fmwAP3l1AP95tB8/e60fL561QWL0MzraHHgP1T1uNEbdtw8PHnApw++yX0bdgBcTsx8k1KmxZFLbF1kRkMiG5tM5iJAaRP8KD9E76EAoY37ixAkUFxfjhRdeQH19PRYWFnK9rIxANmHyCP2OFN8Z5XhZiniGOnw+a3jTOJkpgC77ZUgMARy9MA69J5jyZ6XfX2r0Q2GZZjrD83FQiOdE0oEJurP8/o5QZ/k9Su6d5dMp5ctWJUe8jv6plB+KrcFiIgpZ/9Jj1hobG0FRFLZt24a7774bgUCA0+sLWTZiJpFzx3ZHPBUdwaYnlZZpbJZZ0KSbZK0MY3P4e6jZZY49bf/nF29CagrgBfkoflmlxf9X2YOfvjaAVa9p8eDrOlRpJhgd7QteR4WaQoncih1tdqZpqswUYGxXtP7lyzGO7ukSHTxP9EyxVRKKEaJ/hQdx0EUG2YTJI/Q7UpnKKLM5rFwzwfTBS2oK4MB5F4rlVhw478JpUyBl+V2ZW8CB8y7sUtgjDjkd1ndSPihwcSLnF2+i2eBnnPN0ZrPz2WSOrwxGIhmkmgEXU4NFLhS6/q2pqcFXvvIV3HXXXbjvvvswMDDA+bWFLhsxEEtPcHXu+Gp+GUtPNup82HTagpahQERgN5GDyUXvmgPvoabXg/IOJ1bX6LHqmBa/rtGjTOmA2nmZ+dm37DN49uQw9igdONxFMU1Tq3rcKXWhT0aHfnzrE+g9V9Gg9eFPfx7HJpkFVT3uiEZzXCarkAx64UL0r/AgDjqA8fFxbNy4kSlx37hxI8bGxnK9rIxANmHqCLFMNxeGM9mAhd5zFUcvjENq9KftpOk9QRRJzNjeaos45FSqx1L+vFycyPnFm1COTmNt0xDKlg5YIefchmpN/AMWV7jOyo11UEv3bzMTjjQ51C2H6F92iGzyl/CRm9EBvngTLOq1PgSv30j8BkkQS0++9vYEtp6xxM1ex4JLcCHcHu5VOfDUm8M41HkRHdZ3Ika6NRv8KJVbUR4V4C1OEODls4rpeL8XNb0evHT+ImRDgaT0stArCQnpQfSv8BC9g3727Fl86lOfwne+8x288MILeOGFF/Bv//Zv+NSnPoXW1tZcL493yCYsLPgqPUs1q5vNUV30s450j6FEbkO5KlRmXioPdbnVe65yfhbX9YWXX77R58GapfE5L561YZ/Kido+L2SmqbQcTq5l4LEOaibfNZh819IqIc+UI03KIpfz/7P35tFNnXf+P6QhW7N0pk3PTNvpNJmmbbpl6fw6M9/zbZaeflPSMk1JAs1aaEKKTdhim7Aas4RgyNAGO0YYL2AkLGRsYRtTmSJjW5a12JK1IoMWS7YxODZQF2KDA5n37w9ZiiTrSlfSvdKV7vM6xycnQtJ97qP7fJ7nsydD/k5MTODcuXPTXud6TRWyN6UfPplUKLNh0YEu5EkMKJbbIdb2Bylvgcpdo2EIO2S9yBbqsPmYlfGItHByUqT2YF2dCUtEOqyXmrFBaka2UIcNR81Rc90DZWOTaQh1+sGgvPLA914Ymwhb8NOXS14stwftXeulZrxZ1UWrHRuTUUwbjpqx4ag5JmWb65GEhMQg8pd78F5Bf+CBB5Cfnz/t9Y0bN+KBBx5IwYjYhSzCzCJR5YrtHGEmlTTfdzUahiBodWJjvQVrak1YJzVj8zErLozFXjdi4NI4ilvskOoHw46vxTYcdLjZ2dyL18s1KGiwBLXbCfW2x3KQitV7Hfj9THi+2VKkiQd9OmzL3yNHjuAb3/gGfvzjH+NHP/oRNBqN/98ee+wxVq7JFGRvSj98Rc9yJQZskJpR0OCNKhK0OoPWeeA+s/mYNahtGFtpLz456es8Itb2B+0buTQLfPpC2HfIerG2zoRl1XpkCXUQqT2U+yRVLnm8Y4gXKhlcrelHocyGKpU7ZmWbi5GEhMQh8pd78F5Bv/POO+FwOKa9brfbceedd6ZgROxCFmHmkUjoWTJapzDtQfd7M4xDqNMNQqiKHKYYDt+BsUrlRpawG0tFOuw++XlOnq9HbJXKPa0/LVWLm3iMHaH3VKcfwIFONyo6nFHviam5ZVORJmGRwbAtfx955BGMjHgjSbq7u/H9738fhw4dAgA8+uijrFyTKcjelF745EZFRx9W15qw/bjNH7a9sd5rwAw18I1evTatbRiVrGFKEQw1QDYZh1Ct8aCqsw+l7c6oBshPb34GkdqDbKEOy8V6rJOasbO5FyWnHDHJsdBCbRWKPhTJ6bXpjJdoxteBS+NE2SYAIPKXi/BeQX/22WdRWVk57fXKyko888wzKRgRu5BFSI90shLHG3qWLA8nk0oaU9/l84rsbO7FW1XdePbDdszZrcCaWhOqNf3+HrSxtLiJx9jhO0BJ9YNYLzXjpVIV5pYoMU/QibdFegxc+iTqZ5nwfLOlSJOwyGDYlr/f//73g/7/4sWLeOKJJ7B582biQScwSqDsyq+3+Itnbj9uw5paEyoUfdP2kVhzusPlsydSYFNmOe/3YC+r1iNHYvC3TIv2eZHa481Z13jQZByKeZ9MhSwkUUwEuhD5yz14r6ALBALcf//9ePvttyEUCiEUCvH222/jq1/9KgQCARoaGvx/mQBZhJFJ57ZQsR5eAg9LPm90k3GI8RxhJg8mTHxXaC57fr0ZK8Q9mFuixLMftmFrkxU6z2WMTUzSPtzEexDyfe6dwz2YU6TAq/vUWHSgCy/uUeKZP7WhsqMv6n0wcfhi+/CYTgYvNmFb/j711FMwmUxBr01OTuKll17CF77wBVauyRRkb0ovAuWPoM2JXIkBBfVWrJeavdXJw3iH6VZF9xk6pfpBVHT04cOTZ/39yuPZl33fuUPWi5XiHuRJjFgp7sHO5l5aRtQyhQvFcjs21luwutaEjfUWFMvtKO9wxbxPUslCtmQkiWIi0IHIX+7BewV95syZtP5uueWWVA+VEcgijEymt4UKPAT4erjubO4NOnjskPVCpPEwflBg8gCSyHeNXr2OvW1OrJvKmfRV1N1yzIrFB3XYc8rh/166h5tEvNly2wX8ercCL+5RYvFBHf6wvwsv71NjYYUWORJDxCrHTB++iCLNLmzJ3ytXrgAABgcHceHChbDvUSqVjF6TacjelH745E+1xoOiFjtyJAa8WdWFQpmNUoGO1o1C3NWPaq0HgjYn8qf2pQUVGvyutBMHOvtiqtPh628+NjEJpWMUORIDlov1/irugW3QIhlRC2U2LBHpUNDgLe5W0GBFtlCHQpmN9RaXiUKimAh0IPKXe/BeQecbZBFSk8nhYFSHgIOdbiys1CJPYsTWRivyJEYsrNRCpPawPqZoyiBbyuL45A2UKVxYVq335036cifX1pmC8hI/vfkZ5LZhfHjyLIpb7JSHm0SendNDY5gv6MSr+9R4rVyDhZVexXxzvQVZwm6cHb5C+VmuHb6Igh8ZtuTvI488QqmYpwtkb0o/QuVPlcoNuW04YtGzSDLLZ+gsmio8t6nBii2NVvxurwrPftiOXSfORJStvu8WaTzY3OhtYbb5mBWHNB7IbcPY0+qAWNvv74NOtxd6ocyGJUKdv/p6QT1zCnqynAJENhMiQeQv9yAKOs8gi5CaTG4LFe4QUCS34/3jNuxs7kV+vQVr6rz9YXfIenGIBQ+6j2geg2SkGfj6qedJjAE9zYP7qY9P3oBI7UGOxIBFB7rwtkiPyg4XY31ifQemgUufIEdiwDviHmxutOL9KaNBnsQY1YMe+l2pOnylc2pIMmFL/r755pv45je/id7e3qDXe3p68OyzzzJ6LbYge1P6wlSbzvHJG6hSuf3K+QfNZ7C50Yp5AhXmCzqxVmr2K9fh9mWfDN7Z7A1lX1XzeSh7cYsdhTJbkBG1yTiECkVfxD7ko1evo7zDhaIWe9A+WdRCP8Q9Ulh7pjoFCOkFkb/cgyjoALRaLXbs2IHc3Fx/L3TfX6ZBFiE16bRZxnIgorqvCkUfllbrIdUP+vu7NpmYz0EPJZrHgE2Pgm/exiYmIVJ7kDVVmXdtnQk7ZMGVeUVqDxZWarGqxhtdsKomcnQBXW92OGV2W9Np/L5Ck5JIBibI9NQQpmBT/m7atAlf/vKX0dHRgbNnz2LevHm45ZZb8Nvf/pbxa7EB2ZsIACC3DePNA11YLzVj+3Eb1tWZMbdEicVV3VhTZ0LdVEtMX6eNgUvjfoOqr5jbxnqLP31pvdSMd48YUdHhRKHMhiK5HdWa/qme5F7ja6SQ/MD9M3CfpHMuiGa4zGSnACG9IPKXe/BeQd+2bRtmzpyJ733ve3jyySfx1FNP+f+efvrpVA+PccgijEw4L2hxix1y2zAnFPR4PJVUhwCpfhDLqvWo6OiLubBZvN7aaEYQX89apo0k4eZN47qItrMfo1zhmtYybfTqNeRIDFhVY/SHwNP1akebn3DKbHGLHduaTiNHYkCWsBs5EgNEauaiGNj0sKeTYSvVsC1/33//fdxxxx2YNWsW5syZA71ez8p12IDsTQQAGJuYRKHMhjyJAWum6qKsl5qRdVCHHIkBUv0gqjUebDhqRqHM5pfnLbZhlHe4cFjbj9W1Jmxr8oa4v16uwdwSJd6Z8sqfsF5AocyGN6u6vMXsWuyo1noiGhTjrfURzXBJZCeBKxD5yz14r6B/9atfxf79+1M9jKRBFmFkAhW58g4XCmU2FMpsKFO4OBG2G4+nMtIhoFBmQ3GLndbBg4kw5mgeg7PDV1jxKESat3DK69nhK1h8sBtbG61BCvrWRmvUvPBIRDuQDVz6BGeHr9AKa6dDMkLPiReIPmzJ3/Pnz2PZsmW488478fjjj+Ouu+6CSCRi9BpsQ/Ymgg+d5zKK5HZUKPqmFPJ+v0K+v7MPhTIbNhw1Q6ztD0rZKpTZ/B70bKEOL5eq8Oo+NX5focFKcQ+yhTrIbRdQpXKjoqMvKBc9klIcT60Puso3qbJO4AJE/nIP3ivo//RP/wS73Z7qYSQNsgjpMT55Ay22YRTJ7ZwJ203E2k51CNC4LtI+eDARxsyEBz1Wb3A885aIBz0SyVZmkxF6TrxA9GFL/t5xxx149NFH0dTUBABobm7Gvffei8LCQkavwyZkbyL4oFKIxyYmMXDpE1Sp3BENzu81WfFccQde3KPEfIEKWUIdciVG7JD1olzhwt42Z1wyOJa9h66s51qhTwI/IfKXe/BeQd+xYwdWrFiR6mEkDbII6cG00sFEiHEiyl24arstAdV2qQr2BLZkY2o+onkM6BgTYvEGxztvvhx0JvPC45nHeJ+dZCrOxAtED7bkr1gsnvaaXq/HP//zPyM7O5vRa7EF2ZsIoYSTfZHkeXmHC3LbMErbnJgv6MT8vSp/Prug1YlGwxBK250oU7hYl4uxyt9UF/ok8Bsif7kH7xX0zz77DLNnz8aDDz6IOXPmYO7cuUF/mQZZhPRgytPJZIgxEwrX2MQk5LZhVKnclOMJN2Zffh8Tnt9oHgOqf9e4LsbkDQ7shRvPvAVWcWcyL5yuMpvos5NMbz3xAtEj2fLX7Xbj4YcfTsq1EoXsTQQq6BiLhSoPyhSuqd7n11CmcKGyow91ukE0GYeCZL7SMZoUgyIxXBLSBSJ/uQfvFfQlS5bg9ttvx+zZs7FgwQIsXLgw6C/TIIuQHkx5H5kOMU50w6czHqqWbKEtahL1OsTSBz2W3yOcYitSe1ByyhHXvI1evcZaXngkZTbRZycVoeeZ7gVK9P5SIX8vX04PZYDsTYRQqIyUPmOtUOXBIbUH7zWdRrZQh83HrNPeE07mx2tQjHX9E8MlIV0g8pd78F5Bv/vuu/15e3yALEL6JKoMs6EgJbLh0xkPUwXlmCYWb3A4xbbklAMitYdTB6VIhz2mDUTEg5MYTEXCEPlLDZkbQihURkqlY8Qf3TRf0Ilf71bgncM9kOoH/e+hU19lfPIGBi594m/VFo7xyRu4MDYBpWMk7vWf6YZLQvpD5C/34L2C/s1vfhO9vb0pu35JSQm+9a1v4fbbb8fjjz8OhUIR8f1tbW14/PHHcfvtt+OBBx6AQCCI6XpkEdInUes3myHG8Wz4dMZDJ78vFUouXYWVThG6cPPGhQNU4BjYSLHgimEiHWEqEobIX2rI3BACCSfLm4xDqFD0YWuTFcUtdlR2uJAjMeCdwz3IlRggaHPSLioazegW+O+bG63IEuqws7kXDYZzjBfb5ML+Q+A3RP5yD94r6JWVlZg/fz7Gx8eTfu3Dhw9j1qxZKCsrg81mw4oVK/DFL34R/f39Yd/f19eHu+66CytWrIDNZkNZWRlmzZqF2tpa2tckizB20qFIF1PjofueVBwm6HiDY1Vs6XhG2b7fcGNQOkYg0ng4VaSQbRIZY7r0eSfylxoyN4RAAmW5zHIeglYnNtZbsLJaj98UK7Cp0QpJt7fn+fbjNhTUW5Ffb0GTaYiWITOa0c337yK1B+ukZqyqMVIaAeIl0v6TDjKbkDkQ+cs9eK+gP/roo7jnnntw991344c//CEee+yxoD82+elPf4qsrKyg1773ve9hzZo1Yd//7rvv4nvf+17Qa4sXL8Z//ud/0r4mVxYhXzYfroUY0xkP18bsg443OFZlKtIhLRk9xCONQaT2cPJ3YJpE5jnd+rxzRf5yETI3hEACZbmg1YlciREFDVbkHjbgN0UdWHZIj91yOzbWW1DQYMX24zasqTOhTj9IqwAo3XafdbrBuI0A0YiWjsXmvkMgBELkL/fgvYK+adOmiH9sMTk5iS984QuQSqVBry9fvhxPPPFE2M/87Gc/w/Lly4Nek0qluPXWW/Hpp5+G/cz169fx97//3f83ODiY0kWYLKWHK3AtxJjOeLg05mjt38JB18AQ7ZCmdIyktIf4IY0HSscoJ34HNkkkfDzd+ryTQxA1ZG4Ioeg8l1EktyNXYsB6qRkF9VasqNYjS6hDnsSI/HoLiuRnkSsxIk9ixNo6E4Rqd1QZEM3odnb4iv/fm4xDcRkBokElV3bIepEl1EGkdrMm0wiEUIj85R68V9BTxdDQEGbMmIHOzs6g17dt24bvfOc7YT/z0EMPYdu2bUGvdXZ2YsaMGTh//nzYzxQUFGDGjBnT/lK1CJNxoOYiXIsYoDOeVI6ZKa9qJMU20iGttN2J8iT0yqXjneXas8MkiSi/6djnnRyCqCFzQwjl05ufocU2jKXVeuQdMSC/3gJBmxMftdixUtyD5WI9RGoPdsh6kS3UYUtAFfdIe0UsHvSTp4f9HvxYjADRCCf7m4xDWCc1Y7lYjzr9YMrT4gj8gchf7kEU9Cl0Oh2EQiFEIhF6enpYv55PQVepVEGvv/fee/jud78b9jMPPfQQ3n///aDXlEolZsyYgQsXLoT9DJc86FzLyeYDbCh3oe3P2Pj+FtswiuR2vyFHpPZg14kzUDpG4xon1b9TPY9lChdK251xhTVHq84e+G98XxOJhI+nY593cgiihsxN5hPPfjE+eQNVKjcqOvrQZPL2M5dZzmOHrBc5EgNK253+3uYXxiYY63AR+O+NhqGYjQB07itU9tfpBrGsWo+1dSb/vVLJtEw23BKSD5G/3IP3CvrHH3+Mp59+GjNnzsQ//MM/4Etf+hJmzpyJn//85xgZGWHtuskKcQ8llYswmQdqvhPNAx1P6PjYxCRabMOoUrlR3uFCocyGQpkNZQoXIwcW35irVG6vx0RiwEctDnzU4s0zXFatR47EAKVjhLEwb6pDmi+0PBbFOdKcR/o3rub8J4N08aAHXjPd+qCnC2RuMpdEU9siyelobdLojCmc0e3Tm59BbruA3SfPorjFHpcRINb7Eqo8yJ6qFk8l0/iWJkhIDkT+cg/eK+jz58/HT37yE9hsNv9rp0+fxr//+7/jpZdeYvXaP/3pT5GdnR302sMPPxyxSNzDDz8c9FpWVlbaFInju7cwmVClEgT2hvVt7hrXRWhcF6O2mymU2bDoQBfyJAasrjMh62A3loh0KJ7ydCeqVPrGXNHRh9wab87hwgotFlRoUdBgxdZGK5aL9dh14gxjymukQ1qsinPgnEv1g6js6EOR3A6d5zLtYnSZnGtORSIGinQzbpBDEDVkbjKXeFLbAo1h4WRktH2LLlTGal+f9UUHurBEpEdlRx/jZ5Rw9yVSe1ByyhHVs8+3NEECuxD5yz14r6Dfe++96Orqmva6VqvFfffdx+q1fW3WKioqYLPZsHLlSnzxi1+Ex+MBAKxZswavv/66//2+NmvvvPMObDYbKioq0q7NWrodqLlArF670avXUK5wQaR2TzOEFMpsKG6xB23uG46aseGoOWK7meIWb6GeDVIz1kvNmFuiRLZQh4J6KzbWW9BkHErI0BJovGkyDSG/3oL1UjNeLlXjlVJVUAVdodrNuEEn3BzHojj7xi/W9vvbAa2uNSFXYsDWJisqlX20erjzMWQxEQNFuhk3Ui1/uQyZm8wkVsM83dZjbCqqIrUHCyu1WFVjxNZGK1bVGLGwUguR2pPwd4cjmjEi8P6Jk4PABkT+cg/eK+h33303DAbDtNd7enpwzz33sH79kpIS/Ou//ituu+02PP7442hvb/f/24IFC/Dkk08Gvb+trQ2PPfYYbrvtNnzrW9+CQCCI6XqpXoTpdqCORCr6Y0eaK9/7yxQuLD7YjbV1JgjanJBZvCkFUr03v62io+/zojSmIeRIDMiTGNBkHJq24fuK5VR09PlbzWw5ZsU8QSd+X67BlkYr1tSaUKcbTChVITT9QdDmxNsiHV4oUeJ3e1V494jJ34M22SkRdH5n3/iL5XZ/O6Dtx21YLzXj9QoN1tSZSGpHFLjaB51JUi1/uQyZm8wk1tQ2Ooo3m4rq6NVryJEYsKrGiA+az/j/8iRG5EgMGL16Le7vjoVwMi3d0gTTRS4TiPzlIrxX0H/zm9/giSeewNDQkP+1c+fO4cknn8Rvf/vbFI6MHbiyCNNZcKe6P3a0EGuR2oN1UjNW1Rj9Su3J08OoUPRhabUe0oDqsHX6QeTWGJBXY0SdbnDahu9rNyPVDyK/3oJNU4rn6+UazBd4FedIHnS6v3PogUtmOY/dcjvmlijxXHEH1krNfmMDF70FvkJGeRIDChqs/kNdQb0VKwKqDROvB7/hivzlImRuMpNYlGm6701EUY22J50dvoLFB7uxtdEapKBvbbQiS9iNs8NXmJ2gGEgXDzrJk08/iPzlHrxX0AcGBvDYY49h1qxZePDBB/Fv//ZvmDVrFh5//HEMDg6meniMQxZh4nCx93Lo+8O1hSmS21EoswV9J10Pek33AARtTuRKDCiot+KPVd2Ys1uBt6q6UCy3T0tViGeDDpf+sKbOhFyJEcKpnrBcTolosQ1j0YEurK8z+0PycyUGFLXYseWYFbtOnPGG52v7GWnTQ0g/iPylhsxN5kI3tY2u4h2Pokp3T+KKB52KdEgTJHny6QeRv9yD9wq6j7/+9a8oKirC7t27cfLkyVQPhzXIIkyMZFmwY/UQhL5fZjkPQasT66RmZAm7Ua5wQee5DI3r4rTN3ZeDHq0oTbXGg6IWO3IkBryxvwsrDutRKLOhvGN6Ffd4NuhohYC4nhIxNjGJQpkNuRID1tSZ/D17qzUeVKncqOzoQ47EgMUHu5EjMUCk9nDG40FIDkT+UkPmJnOhm9oWy/6aSBHPaHuSLwc9T+LNQc+TJJaDzmTEINfTBNPFy08Ihshf7kEUdJ5BFmFiJCsHLFEPuu9PqPKgTOHyW/3jUYJDP1OlckNuG8bYxCRlBdxENuh4WsBxBV9BvYoOF6T6Qf+hUaT2+P97WNvv/3+mPQrpMk98hchfasjcZD505BNdxTvcvtQytS+Fuy6dPck3vtGr1/xV3LOE8RtU2Qz15qqsT7c8eYIXIn+5B+8V9GXLlmH37t3TXi8uLsaKFStSMCJ2IYswMZJpHY7XQ0Dn/fEowXQOBOOTN3B2+Ar2ThVzazIOoU43iCbjUNgwxcDv4+qBIxbCGUCUjhGINB6I1B7/XDD9zJCcv/SAyF9qyNwQgNg9xGMTk5Dbhr1RShSyL5rSeGFsIqz8vDA2jrPDV+IOa+djqDfxoKcnRP5yD94r6F/72teg0+mmva7X6/H1r389BSNil0xZhKlU5pKVAxbrQSWVoW+B1y5td2Ll4R68I+nBBqkZq2u9heR2yHoh0ngwNjEZdBg6NKW8ijSeqMolXSMB089GrN8Z+P4LYxPY3GjFuoC5ELQ60WgYmuZRiHfsfDwIpiOZIn/ZgMwNIRC6sjBQ9kn1g6jo6ENxiz2mqu9Kxwjj8pPPimo65MkTgiHyl3vwXkG//fbb4XA4pr3ucDhw++23p2BE7JLui5ALnsJkK8KJKIfJIlRBfOdwD37+wSksrNBOy+ELfe/O5l4srNRiZ3Mv5eGIzu/O5LPhm8NQY0I836l0jCBLqMOqGqO3eFyDFbkSI3bIev0HtUTGzueDYLqR7vKXTcjcEGLFJ/uqtR4I2pzIr7dgda0JORIDCmW2oHB3KqVR6RhlRX7yOdSb63nyhOkQ+cs9eK+g/+AHP0BxcfG014uKivDwww+nYETsku6LkEuewkwIyWaCUAWxyTSEDUfNWLhfi5dKVcirMSB/yoO+X+nNFQx8b369BatqjP52beEOR3R+dyaejVBFuVBmw4ajZoi1/XF9p29udjb3+ivgbz9uQ57EiGyhDkrHaMJj5/NBMN1Id/nLJmRuCLHik31FLXbkSgz+NqAbpGYsOtCFFtuw/71USuOFsQlW5CcxnJIzUjpB5C/34L2CXlFRgTvvvBMbN25EW1sb2trakJ+fj7vuugv79u1L9fAYJ50XIdnwuEmoglinH8TqWpPXc15jwIHOPjSZvDnoxafsKG6xh33vmlqTvxd74OGIzu/O1LMRGi6ZKzFgiUgHQaszru/0zU2D4Zzfw7OmzoRroFruAAAgAElEQVS1dSZsOWbFhbEJRorqkXWRHqSz/GUbMjeEaISrW1KlcvuVc19LNF+LyyqVO2xB1dDvYEt+klBvQrpA5C/34L2CDgB79uzB17/+dcycORMzZ87EAw88gKqqqlQPixXSeRESTyE3CedBp/KKV6ncMXvQ6fzuTDwboffhMx6sl5qDxhbrd1ap3Kjo8BopmkxDqNMPevuhx3B/0SAHwfQgneUv25C5IVARKQVIbhvGmwe6sF5q9qYQ1XtTiIrl9pTLTxLqTUgXiPzlHkRBD2BkZARXr15N9TBYJZ0XIfEUcpfQA84OmTevfIesd9qBJ5b3AvR+dyaejVBF2Wc82CA1B3n36X7n2MQkWmzD2NpkxZsHupAjMaCoxY5qjSfm+4sGOQimB+ksf9mGzA2BikgpQGMTkyiU2ZAnMWBNQBHOak1/0P4QKdSabflJQr0JXIfIX+5BFHSeke6LkHgKuUnoASewMnvogSeW9/qg87vH+2wE9r4NVZQFbU5kC3XIlRiC+ppH+k7f/RXKbFh0oAs5h3uwZqpw0aIDXSiU2eK6PzqQgyC3SXf5yyZkbgjhoGPA1Hkuo0huR4WiD1L9IIQqD3adOIO2sx9D6RhFmcKFvW3OqIo3F+QnF8ZA4B9E/nIPoqDzjHRfhMRTyG3GJ29g4NI4zg7/HQOXxjF69RrlYSOWPuh0fvdE2tL5wiZFag9KTjn8ivIBZR9yawzY2mSl/bzpPJdRPFW0aIPU7K/avvuk9wAZLi+SPNf8IN3lL5uQuUkPkt1VxBfZJNUPQqzxoFrjQZNxCFL9IIpP2TFwadwvP0UaDzYfsyJHYkBBgwXLq/X4XakKbx/SY53UjJ3NvSg55eCkQZ8LHWoI/IXIX+5BFHSekSmLMFX9sDOdRObs05ufQeO6iEKZDUur9Vh6SI9CmQ0a18WEDxmBXm6mfvdwYZMlpxx+b77voLf5mBWVShfktuGgtj1U1xZ39aOiow+ra03YftzmL1q0sd4CqX4wYl4keWYzm0yRv2xA5obbxKpAfnrzMygdIyhXuFDaHt17TcXYxCS2HT+NBZUavCjoxPN7lJgv6MTr5Rq8fUiPKpXb/71Kxwh2nTgDkdqNXc1nMGe3Av+9W4EV4p6w7S25ROh+JFK7sevEGSgdI6keGoEHEPnLPYiCzjP4sAiJJTp2Eu3DPXr1OpSOUWw4asYSoQ4bpGasl5qxRKTDhqPmuD0WbP2W0cIm5bYL/oNeLG3PAr09+fUWf2Xh7cdtWFNrQoWij5OHQ0Jy4IP8jRcyN9wmllaQn978DCK1B1lCHZZV67G2zhS391rnuYw/HuzGL//cht8JVPhNkQL/8d5J/KxQjtW1Rv84lI4Rv0xvMg5hVY0R8/Z2YkG5Bgsrtf4CcuukZpS2OzlVVDZwP5JZzvs7fiyr1iNHYoDSMUrOLwRWIfKXexAFnYKLFy/iz3/+c6qHwTh8WIRc6pWebOL1wMYzZ4HKc2m7E8vFeiys0GDjUQutdjdsjYsOkSqnF7fYsfvkWYjUnpiLtgUetARtTn/v8/VSM3IlBhTJ7RnxHBJPf3zwQf7GC5kb7hJrIUulYxTZQh1W1Rix/bgNmxq8+0Cs3mtfF4wcSQ+yRTq8Xq7BL3a14ukPTuHXRe1YU2tCk2kIkq4BlE/lmR83nUedbhB5EgN+X67BggoNXi/XYMsxb4/0ZdV6lClcnJJdgfuRb9/Y1GDF1kYrlov12HXiTEbsGwTuQuQv9yAKegD/+7//i+bmZsybNw+33XYbvvKVr6R6SIyT6YuQr5Xe4/E0RyqORmfOApVnsbYfi6u6MadIgRXVer+Cvv24DXk1RhSfssfksfDmsn8S1JKNyd8y3HMis3gryi8R6bHoQBfWSc0QtDohs5yPqe2Zb16qNR4UtdiRIzHgzarwxeESJdmKMolOSYxMl7+JQOaGu8TSCnJ88gbKFC4sq9b7U3x8xtq1dSZa3mufXBu49Im3nkeNAduP27DxqAW/K1XhD5VavLJPjaWH9DjQ6YZUP4jSdifKFC6/B31jvQXZQh2eL1HipVIVthyzIk9iRLZQB6VjlO0piwnffiRSu4Mir3ypUUKVJ6PPL4TUQ+Qv9yAKOgC32438/Hz8y7/8C2655Ra8/vrrOHnyJG7evJnqoTFOpi9CvvZKjzX8MFDJKle4sLnRikbDEO05C9f7fK3UjOdLlHilVI33A3KvY/GgB46tuMWOpYf0KJbb/Uoyk7+lb86EKg8Oa/vxXtNpLKzUYlvTaaytM2FVjRG5EiMErc6YDAOhBd+qVG5a+euxkCpFmc/RKUyQ6fI3EcjccJdYDN+jV69jb5sT66YKZAYaa5eL9SiP4L0OzVuvUrmx9ZgV70h6sKnBiveP27CwUov5e5X45Z/a8EKJEnk1BuRIDCiU2dB25mN/N4xiuR1ZB3X4XWkn3qrqwnKxHllCHURqT0Jyki2jqM5zGbtOnMGyaj22Nlr9/dwFrc6MP78QUg+Rv9yDtwr69evXUV1djZ///Oe44447MHfuXBw5cgS33norTp8+nerhsUamL0I+etBjvedwxWiyhDrsbO6lPWfhDCGCNideK1dj9oftyD1swHqpGdnC2HLQA8cm1Q8iV2LAEpHOryQz+VuOT96ASO3xergPdGFuiRLvHO5Bk2nIH2aYJzFindQMocoTsyLKpnc7FYoyH9cW02S6/E0EMjfchm4rSJ+c2Nnci1yJEQX13tDyPIkRWUIdZdEzqrz1dXUm/PFgN7KFOqytM2G+oBOPbj6BRwpkeHZ3GxZXdSNrap/RuC76DZflHS5sbbKioN6CD+VnUa5wQekYiUs5H5+8gQtjE1A6RlkzivqMEzkSA5aL9dhYb8Huk3ZIuvuJB53AOkT+cg/eKuhf/vKX8bOf/QylpaW4fPnzDYYo6OkP33qlxxp+GE7J2iHrRbZQB6HKQ2vOqELEC/9iw4JKDbKF3VhWHVsV93DfGU8fcrr4nhOR2o2ydhfeFumwUtwDQZvTX6hnbZ0JWcJulClcnAnlTpWizNfoFCbhg/yNFzI33CaWVpA6z2WUnHJgh6wX66RmLKvWIzuK95oqb/394za8f/w0th47jVfL1Ph/f2rF/91+ErM/bMeLAiXmliixXmpGtabfL//GJiYhtw2jSuXG3jZv6Hs8hdYC73nzMSuypwzZjYYh1HQPoEhuR4ttmFGZq3SMYqesF+81naY9dwRCohD5yz14q6B/6UtfwhNPPIF9+/YFPZBEQU8NTHob+dZTOtbww3BKVoPhHLYcs6JM4Yqp33c4Q4jSMYKBS59g4NJ4TL9nuLHVGwZR+BcbsoXdKD5lZ62Kuy9nMU9iRH69BU0mb7i/UO1GucKF0avXEroek9BVlAPXFBPri3jQE4er8pcLkLlJD+jIktACotEUZDp562cv/B0lrQ7sOnEGeTUGbGm0YnOjFevqzNNaWDIVYRRoxA1Me/qoxQ5BqzfKaml1cKu3RAmMJFguTqwCPoFAFyJ/uQdvFfRr165BJBLh6aefxp133onnn38eUqkUs2bNIgp6EmEzl5ZPlaaVjlEU/sUGQauD0tNMp/AanT7jPpg2hExrNdPqxMapVjPLxXocN5+n1YeczvjDhui3OrFS3IPlYj3E2n7ORl5EU5THJib9v0uZwoVCmQ2FMhvKO1wJ/0Z8i05hGq7JXy5B5iY66banxSKPqfLWl4i6sfvkWZy9cIVWC8t4i56GG7vve+r0g1hda8KWY1asrjXirQNdWFHdg/VSM/KOGFDR0ceYHAwsGFenH/Qbi4khlMAmRP5yD94q6IE4nU6sX78e3/jGNzBz5ky88sor+Otf/0qKxCUBUnQqMT69+Rk0rot4/7gNr5apMGe3AvMEndjcYPWHlocaQQplNmw46g0JZELJYvLQ6Hsedsh6sVLcgzyJESvFPdjZ3BtxjLEaeiJVcc+RGFDa7uR05EUkRTlwTRXL7Vgi0mGJUIeiFnvC64tv0SlMwzX5yyXI3FCT6d0TwuWtv3fsNBZWaPHr3QrkHzWjSuVGocwGsbY/YgtLplJxAr+n3nAOWcJuvFyqwnxBJ57c2YI39muRf9Tsj7iKx8gd7boklYiQLIj85R5EQQ/gs88+w1/+8he88MILuO222/CP//iPqR4S43BpEZKQ2cTReS5jw1Ezsg7q8MeD3XhRoMT/29WKeQKlP2ct1AhSrfVgw1EzCmU2zilZ3kI5o/5COfn1Fn9OeKTnIh5DD3WI/ijnvVRUivLYxKR/TfnC9gsavBWBQw+SiYa7c32OuAiX5C/XIHNDzfTCnh7sOnGGc+3CEiE0b/3VMhV++ac2vHO4Bw2Gc6jpHsCGo+Yp4zJ1C0umzhWB3yNoc2JBpQYv7FHi+RIlntzRgv/ercCCSg0Ebc5paWKJGFHIuYiQCoj85R5EQadgdHQUu3btSvUwGIdLi5DPlmKmcoKrVG7kSgzIFunwcqkab+zvwoIKDZ4vUWJRVRfktguUm32Vyh1znngyGL163dtip9MNsdaDJuNQxOci3gNNrN5gLiqloWMKXFN1Om9Y5vbjNm8YaJ0JdfpBXqwvrsIl+cs1yNyEJ1LqT47EEHdlcq4R2GJt14kzWCLSY1vT6aAWmwc6+7Cx3oKyqTZsJa0OHDcNTUt9YioVR+e5jOIpQ4C3YKgO/13UgV/8zyn89iMlsoTdqDecCyq0KlJ7Eo4GJKlEhGRD5C/34K2CfvnyZRQVFYV9GMfGxij/Ld3h0iLko6WYyVDF0avXUdxix0pxD35focEb+7uwRKTH4oM6vLJPjcUHu7D75FmUtjsTMoJEUkzZUFrHJiZRKLMhT2LA6loTNtZbIGh1BlXpDZ2HRAw90e4hncJLA9cUmx50QnxwSf5yDTI34QmUb97CZEYUNFixtdGK5WI9dp04wznFLdZ9IVDG7m1z4sOTZ5F/1IKGKeU3sKvGH6u6sU5qQkG9BXtaHWHlMVOpOJ/e/AzHzUN4q6obK8R6ZB3UYdEBLV7Zp8J/F3fg1TI1Dmk8EMbRqpTufHAtyo2QmRD5yz14q6Bv2bIFL774IuW/z5s3D9u2bUviiJID1xYh3yzFTObc+zzobx/SY56gE4sPdmOJSI8/7O/Cy6VqrKoxoLjFjnKFKy4jSCTFlE2l1Re2v0Sow/o6c9R+6mwbetKtTkLgmiqW25Et1CF7Kgc909cX1+Ga/OUSZG7C83nRMI/f4OarcJ5fb4FQ7WbM4JaowTXefSFcCH92gMLryzlfVWPEWwe68ceDXf66GiK1eyrcf3p/9UTux3cvVSo3soTdeKVUhdfKNcivNwfnx9ebUa5wYXOjFY2GIUajAbkYtUXITIj85R68VdAfeeQRyOVyyn+Xy+V49NFHkzii5MC1RZgqS3EqNj42FEmd5zLW1JowZ7cCvxOopsLbO7GwQoMdsl6Iu/qhdIzEZQSJpJiypbT65qha64GgzYn8egvW1JmQIzGgUGajrOLOhqHHW/V+PGLVey4enALXVHkHs1XcCYnBNfnLJcjcUKPzXMauE2ewrFqPrY3eiJhciQGCNicjKStMGVzj2Reo9sUdsl5kCXWo6HD6W5ytEPdg8cFuFDRYkX/UgixhN9ZO9Qr3hvvH3uuczr3sOnEGc4oUmLNbgRXiHv/8v9d0GmUKFwYufcK7aEBCZkHkL/fgrYJ+9913o7+/n/Lf+/v7cc899yRxRMmBq4swWQpzKsOV2ci591VxXynuwewP2/HcRwosOqDF+8dt/r6p8RhBIhkTqlRu1pTW0DlqMg2hTj8Y1OOWah6YMvQEfldxix1Lq/UoarEH5UIycShm+5lnug86IXG4Kn+5AJkbauItnkkXJgyu4faMJtMQKjpcqFK5KcdHtS82Goaw+ZgVH8rPYvHBbqyTmvE/zWewqsaI7cdtWCnuwa+LFFgu7sHGo2ZGw/1D70XS3Y83D3RhvqAT8wSdWCs1Q9DmRIPh3LTe63yJBiRkFkT+cg/eKuj33Xcf1Go15b+r1Wrcd999SRxRcuD7IkxluDKbodhjE5M4bh7CnlMOyhZhsShpkYwJxafsKG6xs1LcL9E5YkIRDXxGpPpB5EkMWCLU+av1JvqbpVNOO4FZ+C5/I0HmJjpKxwh2nTgDodrNaKRQLDKXSsYG7hm+nPH8egtyawxYVq1Hi204rIyLdv2BS5+gTOGCSO3x19VYW2vCrz9sx9MfnMIrpSq8XKrG4oPdOKBkJtx/mqF46rqra41YebgHYm3/tDkieeOEdIbIX+7BWwX9qaeewurVqyn//d1338VTTz2VxBElBz4vQi4UpWMrFJtpT2mqPOjjkzcgtw2jeCpfOtIcseEVDnffglYnsoU65EgMkOoHE/7N0i2nncAcfJa/0SBzEx02lEC6kV3RDIuhbclyJQZsavD2Kc8L6FMejmj7YmhdjRdKlPj/tv4VvynuwIJyLZ4vUWJBhRbFcrt/zInsD4nsAyRaiZCOEPnLPXiroNfW1uLWW29FcXExbt686X/95s2bKCoqwqxZs3DkyJEUjpAd+LwIudDWja1QbDY8sZEOTUwbGgLvpUwROW+azfsOfEaajEOo0w2ioecciuV2LKvW46NT4asG04ULRiJC6uCz/I0GmRv6MKkE0pVJVIZFpWPUP5bAtmQbpOapXG0jBK3OiDIu2r4Y+O97Wh14tVyNZ/7cihcFnXi9QoO3RXqsqTMhV2JApbIPSscI7f2Bai5D97hqTT82HDWjUGYjHnJCxkHkL/fgrYIOAOvWrcPMmTNx77334tFHH8Vjjz2Ge++9F7fccktE73o6w+dFyCXliOlQbCY8saFjinRoYtqTE+5eiuR2tNiGKQ9ObHigxydvQKTxYGdz71RIo7fN2w5ZLyqVfRi49AmjOfapMBIRUgef5W80yNykjmgG13B7p8xyHjtkvciRGPxpVRrXRZywnsfSQ3rk1Rj9LTJllvO0ZFy0fXF88gbODl9BabsTH8h68fI+FeYLOvHyPhXmCTrxokCJPacctPaHaIZeqj1ubGKSeMgJGQeRv9yD1wo6AGi1Wixfvhy/+tWv8Oyzz2LFihXQarWpHhZr8H0RZkohFyaNDXRCF9nsgx7LvTCVLxkJkdqDhZVa5EmM2NpoRZ7EiIWVWojUnrjvMdL4m0xD2NvqwJ5TDoxevRb395JDI/fhu/yNBJmb1BHN4BrOsChodWKluAfLxXqItf0BHvURVKncqOzoQ5NxiHFDuE+GFv7FhgWVGrxSqsIr+9R4oUSJFwVKbG600tof6Bp6iWwl8AEif7kH7xV0vsH3RRjuIKJ0jODC2ERabcBMemJTnRMdy70wlS9JxfjkDRzSeLCt6TTePWJEXo0B+VMe9EMaDyPPiG++qzUefHjyLBZUajD7wza8sk+FQpkNGtdF2pEIpOBcesF3+RsJMjfJJ1T5pFJGQw2LvqJpeRIj1krNEGv70WQa8ivCSsdoVI98Ikqv0jGCLKEOq2q8RtTVR7wt2DY1WLG0Wg+pfjDi/sClaDoCgQsQ+cs9eKugj4+PY8mSJfja176G+++/Hy+//DJGR0dTPSzWIYvQy/jkDVwYm4DSMZqWyg1TBwwuHFTY8KDHa3S4MDaBzcesWDuVz7jqiBFFcntQO51E8SnVhTIbXhQoMWe3An+s6sIqiQFvHtBida2RtnEk1cYVQmwQ+UsNmZvkEY9hLzD67LC2H28f0uO1cjWyhN1YXWtCfr0FRS12lHe4cGFsIqxH3pennuiee2FsApsbrVgnNWPNVBqSoNWJI90DWFatR0VHX8T9gSupRsQ7T+AKRP5yD94q6Hl5ebjrrrvw1ltvYdmyZfjKV76CF198MdXDYp1MXoSxbnbprtwwEa7PlYNKLPcST74kXaOD0jGK7CnPzPbjNmxqsCJXYsAOWW/QZxM9WI1P3kCZwoW3RTqsrTUhR2LAwkot5glUmFuixNYmK8YmJqN+R6qNK4TYyGT5myhkbpJHtL0vnHwLVOpL251YUKnBS6WdyK+3+GVltlCHQpmNUk4ytef6ZJ9I7UGdbtAfSi/pGkChzBa1C0iqZSeJfCJwDSJ/uQdvFfQHH3wQYrHY//9arRa33nprUEX3TCQTF2E8m120NmIDl8Y5r+AwUaiNyYNKIkprLPcST74kHaODby52NvciV2JEQb0V24/bkCcxIkuog9IxEvezFjovo1evo7jFjtwaA1ZU6/HyPjXe2N+FRQe68MIeJV6v0EBuG444Z1wxrhDok4nylynI3CSHSDL/kMYTNapsfPIGBi59gq1NViwR6fxysqB+uoJO97rxKMVUhlqN6yKtvSSV9WjS3TlAyDyI/OUevFXQZ82ahXPnzgW9dscdd2BgYCBFI0oO6bAIk+EJD6fcyCznUdTibadV3GJPG6t2ot7cRA8qTHoDYrkXuvmSdA+Cvmei0TAEQasTG+stWFNrwjqpGZuPWf1hm3SftUjzMj55A1UqN1ZU6/FKqVc5XyLS443KLrxcqsIKcQ+qVO6I85BqLxAhdtJB/qYKMjfJYeDSOIpb7GHztLccs2LXiTNR5dvo1esoU7hQLLf75eTGeguK5d4Q93DGQaYNimMTk2ixDaNK5Q6riEfbS5jsRBLrvkXkNoFrEPnLPXiroN9yyy0YGRkJeu3uu+9GX19fikaUHLi8CJn2hEfa7MJ9TtDmRLZQhzyJAVL9YNpatWNV2BM9qCTDG0D3nnzvUzpGaBkdAr83XCGkOt0ghCoPxF39GL16LaZnLdq86DyXkVtjwOwP2/HaPjUWVGjwfIkSCyo1KGqx0zq0ZkpXAr7AZfmbasjcsItPzlep3FharUeexOBvgXby9DCEajdyJAaI1J6YaoH45GSTcSjivsuUYvrpzc+gdIygXOFCabsTVSo35LbhqClBVNBp7Ub17/GcWUjkE4GLEPnLPXiroM+cORO/+tWvMHfuXP/frbfeimeeeSbotUyDy4uQKU843c0uULmR6geRIzFgiUgHQaszLa3aiXqy4/HEs+0NoHtPoe8TaTwQqT04pPGENTpQfa/GdZFS4Y3lWaMzL5/e/AxtZz7GgkoNnivuwDxBJ7KE3Sg55UC1xkNr/pjuR09gFy7L31RD5oZdAvfXohY7lgh1yBbqUCz35mvvOnEGmxuttPfSeIyDTERridQeZAl1WFatx9o6E3Y296LklINxoySdvSeeMwvxoBO4CJG/3IO3CvrChQtp/WUaXF2ETHrC6W52gRvwR6ccWHpIj2K53e9RiHQ44WL11VTktUUKl2TCG0D3nqjeJ7cN4+zwlWn9xaneHyl/MZZnLRZlXukYQeFfbNjb6oRUPxiXF5yLzyNhOlyVv1yAzA17hMoumeU8BG1O5EgMWFatR5XKDaVjBCKNh/ZeGo9xMFGDIt0inkyg81xGkdyOyo6+sBF1iZw9SOQTgWsQ+cs9eKug8xWuLkKmPOHxbHa+ojdVKnfUzZar1VeTbZWPFi6ZSJG50avX/P+lc0/hKvrKLOexQ9aLHIkBpe3OmBVtKoWX7rMWy+9BvOD8gavylwuQuWEPqv1Vqh/ER6ccGLj0CYD49tJ4I6/i+UyZwoVl1XpsP27DB81n8EHzGRTUe9tilrY7GTOkj01MolBmQ57EgNUBbdyqNf1++Z3ImYXIfALXIPKXexAFnWdwdREy5QlPZLOjczjhavXVZOS1BR52ooVLxlNk7pDGg83HrMiRGLC50Yq9bU5sPmZFg+FcxHsK7InrO0ytl5qxvLoHy8V6iLX9/t9J6RjF2eEr2NvmZPxgRdVSiO5hd/TqtbDefjZJtec91ddPNlyVv1yAzA170N1fuaw4jl69jr1tTqyTmlHQYPUr6NuP27BcrEe5wsWYIV1uG8abB7qwXmr2VqhvsCJXYkSx/PPaIEwYxfkm/wjchchf7kEUdJ7B5UXIhCc8kc0u2uGEy63ZfFXBKzv6/D1hmfKghx52qlRuFMpsqNZ6KMMl4ykyt7O5FyvFPVhVY8RKcQ+2NZ1GtlCHnc29EQ9ASscIsgLCHtdJzZhbosQfKrXIr7egyRTsUS9uOYsciQE7m3uD0hniPVhRHQZ9hoxoh91URGWwdU26a5CrkShsw2X5m2rI3LCLT84KVR4c1vZDqPJQ7q9cVBzptMH0kYgh3beX5koM2BRgCCio94bTB3bXIKHqhEyByF/uQRR0nsHlRZhK631oNe9whxOutmbzzVuhzIZFB7qQKzGgWG5HtaafkcNC6GGnsqMPiw50oajFHjFckg6fh6e7kV9v8R+ICuqt2FhvwXtNp/FWVRf2tjrC5mcHH9oM3s8dteC5og78trgDRXLvGAWtTqwUf+5R39nci4WVWuyQ9SYcyhntMBjtsJuKqAymrxmrws3VSBS24bL8TTVkbthlfPIGRGoPciQGLD7Y7a/YziUlPBo6z2WUnHJgh6wX66RmZAu78cZ+LSo7+mgZ0iNVmPfJaN8+X9Ri9+8p24/bsL7OjEUHutBiG/Z/jssRBwRCLBD5yz2Igs4z0mERJtN6H4tiwdXWbD5lp1rr8R8q3qzqQqHMlvBhIdw9NxmHkCsxIFdiQJMpMW+97zAk1vZjda3Jn1u4/bgN7x4x4v2m03i1TIW3qrqxrFqPQpkNGtdF/z35Pt9gOAdBmxP59Rbk1RgwX9CJ18rU/jZAG+styJMYw3rUQ3PUQ4nWzzyRMMdUVPRl45qxKNx8rmKcDvI3VZC5YRffGhWp3RBrvUZRJveqZOzbPlks0niQX2/GEpEe+UctOKTx+GVyLOle4WS7r1hetdbj31PW1JmQIzGgUGYL286NixEHBEIsEPnLPYiCzjPIIgyGrmLh24AD+2tzoTVbWAXaNISKDldQKF68UB12iuV2vFnVhYoOV0LpCL5CcOE86FkHdXiryhsRINZ6UNnRhyK5PegaofffZBpCnX4Q7zVZkSXUQah247C2HwWG8zcAACAASURBVMuq9Vgp7oGgzRl0YCttd+Ls8BVaFXdrur2/eUVHH4pb7DG3Xotlftnsicv0NWNVuPncB5jIX2rI3LAHm0axaEZuNpRXpWMEu06cgUjtnrZvx3KvVPu/SO0J2ucrOlx+mU8gZCJE/nIPoqDzDLIIP4dur+rAw0dgf+1YW7OxAdvKDtUcVWv6USizoUrljim0L9xhTqT2+MMWV4p7kCcxYukhPRZWaLBEqAtSqiMdsgLzAEtOOSBSe3uJF7fY8bZIj21Np2POOffdf6A3ZXXt596U82MTvPegx/oMEg86kb/hIHPDHmzuE3RaVtJR3Okq8nTkB53c8Ejfc0jjgdIxSkLXCbyByF/uQRR0nkEW4efQObRQHT6UjlHardnYhGllJ9whKdJhJ1bvSLj59CnThzQebJmq4r6mzoQlh3Qoaolu/KDKAxyfvAGlYxRlChc2HDUjS6jDDlkvGgznaHv8Q/MRNzV48xE3SD/PR0y0UFAqCg0xec14nkG+Flci8pcaMjfswZZRLNL3FspsKJLboyrugUZvOvUr6OzbdHLD6XwPCV0n8AUif7kHUdB5BlmEnxPt0EKnDzcXFA0mxhApTJGpQjh05tsX9j5waTxm4wdVm7Oa7gE0Goaws7kX2UIdthyz0r4HOhV9xyYmE5qfVBQaYvqasT6DfC2uROQvNWRu2IWNvSpSf/Vl1XpUdvRFVdx3Nvfi9XINNjVaaNVxicXYEEnB5nMkD4EQCpG/3IMo6DyDLMJgIh1amLLUsw0TY6CTix9vSKKPWMMsEzlQUh2+hCoPyhSumHqNT+uJWz+9J2488xFuzMn21jB1zXifQb55qIj8pYbMDbuwsVdRydmKDheWHtJDqh+MqLg39JzD4oPdeL5EiRcFnVgrNUPQ6kS1pj+iksyUsYELBnYCgQsQ+cs9iILOM8giDCbSoYUpS32yiHcMsXoS4u1hnch1Yj1QMplzOTYxiUKZDXkSA9bUmrCx3kLrEMlHuLAOuAyRv9SQuUkOTK/RcEpucYsdhTIbpeIu1npQpx9E4V9O4zfFHXitTI1X9qmxutboN35GKuDJlLGBCwZ2AoELEPnLPYiCzjPIIgxPtB7XmWxhj9ezHU8P63jmM9xvE+2QyXT4os5zGUVyOyoUfWH7sRMIdCDylxoyN+kJlZKrcV2cJus/PHkWKw7r/W065wk68evdCrxcqsLCSi22H7ch/6gZCyo1WF6tx962yC0wmTI2EMMige8Q+cs9iILOM8gijA0+WNhjjRRIRPFNdD5j8d4zaVzh2nNADpTpCZG/1JC5SW9CZVI4mSlSe7CuzoQlIh1yJQa8uEeJX+xqxdMfnEK2UIftx234Y1U3frGrFZsaLTEbgAkEQnwQ+cs9iILOM8gijI9MV4joKrNMhY7HO5+xeO/ZyrlM5XMQb3oBgRsQ+UsNmZvMxCczfUVXxdp+CFqdWFtnwjxBJ+aWKDG/tBOra43IqzFgbokSCyo1qDcMJhz5RCAQ6EHkL/cgCjrPIIuQEA66ymwqK9/Ge+14QuS5SiLpBYTUQ+QvNWRuMptQ426TcQj/03wGSw/psVysx0GVG7vldiys1KJYbg9rAB64NJ6WcptA4DpE/nIPoqDzDLIICdFaz0Q7AKUqL3/06nXsbXPisLYfTcahuLz36eyBJm2B0h8if6khc5PZhJNfMst57JD1IkdiQGm7E1UqNwplNoi1/UEyrlrTj0KZDVUqNyqVfahSuSG3DWNsYjLVt0UgZARE/nIPoqDzDLII+QtTymmq+nYrHSPIkRiwrFrvr6Qus5yPSUFNZw80k5XpqUjXyIJ0gchfasjcZD5Kxyh2nTgDocoTZNxVOkb9ciecAXjDUTM2HDWjWutBUYsduRID3jzQhUKZLW0MrAQClyHyl3sQBZ1nkEXIX3wHH5Hag8Nab8GeRJTTZCpzvrHvbO7FSnEP8iRGrBT3YIesN+He6OnigWZz/OkcWZBOEPlLDZmbzMUnXw5pPNh8zIociQGbj1kh0nimyZlQA7DPq16t9UDQ5kSuxIBNDVasl5qRJzGgSG5PCwMrgcBliPzlHkRB5xlkEfKT8ckbEGk82Nnci431Fqye6ue9Q9YLkcbDaeU0UDGVWc5D0OZEfr0Fy8V65EgMUDpGk94bPVWwlV6QzpEF6QSRv9SQueE+iRb3FKndEGv7UdHhwq4TZ6B0jES91sClT1Cp9La3zK+3YFODFR80n8H24zasqTWhQtGXFgZWAoHLEPnLPYiCzjPIIuQno1evY3OjFSvFPShosGL7cRsKGrz/v/mYldPKaTjFusk0BLG2H6Xtzpgqx6ezBx1grzJ9us9LukDkLzVkbpiD6eimWCJsQq89PnkDh6aMw/lTxuH8KePwIRrGYZ98qujow+paE7Yft+GD5jMoqLdiY70FUv1g0gysbEeNkRQjQqog8pd7EAWdZyS6CMkGkp6MXr2GHIkBq2qM+KD5jP8vT2JEjsSA0avXUj1ESphUIFNV4I5pmFyHTBlACNEhhyBqyNwkDlupKnQibKiufWFsApuPeY3Bm6aMw5umjMNbaBqHdZ7LKG6xI0diwAapGQX1VuRKjBC0OpNiSGQ7BYikGBFSDZG/3IMo6Dwj3kVINpD0ZvTqdf8hqaB+yoNeH9shKZUwpVinosAd16FKIVhWHVsKASE65BBEDZmbxGEjVYWugZTq2nLbBb9xePtxG7Y0evefWIzDPrldKLNh0YEu5EoMKJbbUa3pT4qBle0UIJJiREg1RP5yD6Kg84x4FyHZQLykawRBaJjhmrrYwgxTTSTFOp7fJF1/R7bwre8dMm8RvlU13iJ8O5vpF+EjRIccgqghc5MYbKWq0KndEena5QoX1tWZ8Hq5Bi+XqvDyPjVeLlXh9XINChosMRmHxyYm0WIbRpXKHbQPjE1MsibP2U4BIilGBC5A5C/3IAo6z4hnEZINJDMiCHxKmHCqUI9Q7U475StQsU7H3yTRHvRsEdjGbrk4/jZ2hMiQQxA1ZG4Sg60imHT2/4FLn6C4xQ6pfnDatUvbndhw1OxVzkvVeGWfGi+XqvHSXhW2HT8dl1zxycqxiUnW9wC2i4tmQvFSQvpD5C/3IAo6z4hnEZINJDMiCDItvDudfpNIxgSuGBpGr17H3jYnDmv70WQc4uU6ZxtyCKKGzE1isGlID00xEqo82HXiDNrOfAylYwR7TjmQLdIhV2KAoM1r2PNdu0rlxtZjp7FEqMO6OjM2HrVgXZ0Z2UIdCmU2RsaV6B4QzXBKPOiETIfIX+5BFHSeQTzosZNp98+EpzbVIeLx/iapGnekgyRXDA2Z9pxzEXIIoobMTeKwVQTTZ0QUBfQxL6i3YIlIj7klHVh8sAuLDmjx8j4VFh/UoajF7r92i20Y5R0uFLXYg9KrilrsKO9wserZp3tf0YyjbBcXzZTipYT0hchf7kEUdJ6RaA461QaSaoWNTUgEwedwydsby29CNW42cxd9RDpIVqncqFK5OaMUk4Miu5BDEDVkbhKH7SgppWMEu06cwYHOPuTWGPB/tsvxn++fxHPFCiw+2I3fl6uxoFKDZdV6VKncfhnrk39NpiHU6QfRZBpKSm58NOgaR6PNa6Lnn0yLbiOkH0T+cg+ioPMMJqq4B24g45M3OKGwsQnxLH5Ounp7Q8ct1vZjw1EzCmU21p/bSAfJj045UNxi54zxhxwU2YUcgqghc8McbBjMA2Vukfws/ruoA0/tPIVn/9yOX/65HfP3qpB1UIdVNQb86a9nMHBp3P/ZRA1/4e4n0X05ns+HjoNpg3UmOzoI3IbIX+5BFHSewXQfdK4obGxDPIveXuplChdEag8nDBVUv4nSMRL0jIY7iAlancgWenMmpfpBVp/bdPKgB46ZHBSZhxyCqCFzw218hkapfhDvHjHihRIlfrW7Hb/ercCzH7bj1TINfl+uwRJRN8oVriDZEa/hL5oCnMi+nEwPPIHAdYj85R5EQecZTC5CPnmW+exZ9N17ucKFxQe7sU5q9lf45pK395DGA5HaA5HGE3SYuzA2EXQQazIOYWO9BeulZqypM6FuqvIwm89tpIMkMf7wB3IIoobMDbfx7fcVHX3IqzHg9XINnt+jxM8/aMUv/9SOP1Rq8VyxEn/Yr4XSMUL5HXQNf+OTNyC3DaO4xU6pACeyL6fCA08gcBUif7kHUdB5BpOLkI+52Xz0LPoUSJHajbV1JqyqMSJXYoSg1cmJA4nvN1E6RsN6M5SO0aCDVJ1uEKtrTVhfZ0Z+vQVNpiHWn9tIB0k+G3/4BjkEUUPmhvvoPJdR3GJHjsSAPx7sxtwSJX75pzY895ECzxV3YM5uBSo7+sLKLqow9dDXfPKwSuXG0kP6sJXhQ/ebePflVHvgCQSuQOQv9yAKOs8gHnRCLIT+xoI2J3IlBuRJjFgnNUOo8nDC2xvtWVQ6RvwHMal+ELkSA5YIdRC0OZP63HK1DzohOZBDEDVkbriPT3kulNnwxv4uLKjUYNEBLbKE3fjD/q6wynm4MHWN6yI0rothQ9d9SnNlRx/yJAZskJr9SjrTCnAqPfAEApcg8pd7EAWdZzC9CEl4bvJhWpEL/b7A/w/1Esgs5yFoc2JtnQlZwm6UKVyc8PZG82ZcGJsIOogVymzYcNSMao0n7Z5bosinL+QQRA2ZG+ZgW0aMTUyixTaMKpUbpe1OlCtcUDpGwu4D4fK0Nxw1Y8NRc5hop5HPK75PpSIVNFhRUG/1RzsxqQD75mn06rWke+AJBC5B5C/3IAo6z2B6EZLw3OTBdMXY0O8Ll8OtdIzikMYzzUsgVLtRrnBh9Oo1hu8yPuh6M3wHsrGJybDPbTLarsULV1rcEeKHHIKoIXOTOMmWEdEMAeHkcpNpCDkSA/IkBjQZh4JkdbnChb1tTr+hVdDqRK7EiPVSM/KOGFDR4WK0r3ui80TOP4RMgchf7kEUdJ7B1iIkXj32YbpibOj37WzuxcJKLXY29wZ9v0jtSQsvQTzejHAKO1eVX1IxOP0hhyBqyNwkTqplROg5IFxkU51+ELk1BuTVGFGnGwyKdiptd6JM4fIr9DLL+Skl3RDUWz1Rucz0PJHzDyHdIfKXexAFnWeQRZieMJ3vFvp9TaYh5NdbsKrGiI31Fr9nQ9I1AJHG4w895LKXIBFvRqoPttEg+Y6ZAZG/1JC5SYxUyggqj/TYxGRMHnRf1FaoobVIbkeLbZj2PUSr9UFkKYEQDJG/3IMo6Cni8uXLeO2113Dvvffi3nvvxWuvvYa//e1vET+zYMECzJgxI+jvP/7jP2K6LlmE6QnTFWNDv69O761svrXRijW1Jr9nI/D708VLEOs4mTywsTVH6VAxOF2ej1RC5C81ZG4SI5UyIpyB06dUh1O4fTno4aKdEjG00gldTwdZSiAkGyJ/uQdR0FPE7Nmz8cMf/hAqlQoqlQo//OEPMWfOnIifWbBgAWbPno0LFy74/y5duhTTdckiTE9S6UHPZK/C+OQNnB2+gtJ2Z0IHNrZzP7ns9SG58fQh8pcaMjeJEa+MSNSwFnrdwLD0pdV6VCpd/tomPoU7sIo7lRIez7joREJxWZYSCKmCyF/uQRT0FGCz2TBjxgxoNBr/a2q1GjNmzMCZM2coP7dgwQI899xzCV2bLML0hemKsaHft0PmzUHfIeuN6/uT4UFl6hqBSuXeNidyJAbsbO7199qN9cCWjBB5rlYM5np6AJcg8pcaMjexEyoPY5ERTBnWQj3S0wu79fkrtNPpgx4vgYp3k2kIdfpByqrvXJWlBEKqIPKXexAFPQVUVFTgvvvum/b6fffdh8rKSsrPLViwAPfddx/uv/9+PPTQQ1i0aBE+/vjjmK5NFmH6wnTF2NDvC6ziHsv3J8ODyvQ1qArkxWOcSJZHhosVg4k3KjaI/KWGzA19qOTh+OQN2jKCKcNakGIcpjVanX4AFYo+VKncrMqD0avXUd7hQlGLHfn1FqyuNSG/3oKiFjvKO1xBkVBclKUEQioh8pd7EAU9BWzbtg0PPfTQtNcfeughvP/++5SfO3z4MJqammCxWNDY2IhHHnkEP/jBD3D9OnUI7vXr1/H3v//d/zc4OEgWYZqTzD7odEim95iJa4RTKmUWbwRBjsSA0nZnTAe2ZOc0cinXm+RzxgY5BFFD5oY+0eRhPO3PEjGs+cZToehDnsSA9XVmvHO4BzmSHiyr1mPpIT2WVeshtw2z2vKtUGbDEqEOmxqs2H7chk0NVmQLdSiU2SgLxiWy9xEImQKRv9yDKOgMUlBQMK2IW+hfd3c3tm3bhu985zvTPv/tb38b27dvp3298+fPY9asWairq4t5TGQREpggGR5Upq8RSaksbXfi7PCVmAvD8dWLzOd7jwdyCKKGzA09mFhzTBvWfB7pKpUby6r1WHG4B/MEnfhZYQt+VtiCJ3eewtyPlNh1ope1MHK/gi7SoaDeq6AX1EdW0EPHT+poEPgKkb/cgyjoDDI6Oore3t6If9euXYs7xD0c3/72t1FYWEj578SDTmCTZHhQmb4GG0oln3Ma+XzvsUIOQdSQuaEHE/KQLcPa+OQNyG3DWFihxX9s+yue/uAUnv2wHU/uOIWnPziFleIe1gx3o1evo0zhQrHcjo31FqypNWFjvQXF8ukh7qHoPJdRJLejsqMPUv0gqaNB4B1E/nIPoqCnAF+ROK1W639No9FELRIXysWLF3H77bejqqqK9mfIIuQW6R5Sl44edIB5pZLPOY18vvdYIfKXGjI39GBKHrJlWLswNo6XS1X4v9tb8Ms/t2FOkQLzBZ14oUSJF0uU+OiUPaoRIZ59MTQXvk43iCZj+CJxgYxNTKJQZkPeVG/2VTVGFJ08i2pNP4kCIvAGIn+5B1HQU8Ts2bPx4x//GGq1Gmq1Gj/60Y+mtVn77ne/C6lUCgC4evUqcnNzoVKp4Ha70draiv/6r//C17/+dVy5coX2dcki5AbRQurGJ29g4NI4Bi59wvkDQjI8qIHXkOoHUdHhQnGLnXMKdbobXBKBz/dOFyJ/qSFzQx8mZG6gDCxtd6JM4YLSMZqwDDw7fAVvHujCS6UqvFKqwnxBJ+YUKfDMn9rwX9vleLfWiLGJyahjiifU3DcvQrUbYm0/hGp31HmR24bxh/1dWFzVjd+XazBvbyfmliixptYU1fNOIGQKRP5yD6Kgp4hLly7h1VdfxT333IN77rkHr776Kv72t78FvWfGjBnYv38/AGBiYgLPPPMM7r//fsyaNQvf/OY3sWDBAgwMDMR0XbII2YeOokJV5MfXH7ZQZsPSQ3osrdajUGaDxnWRsx7JZHhQP735mX9efEWHmJgXolQSkkkmyl+324033ngD3/rWt3DHHXfgwQcfxMaNGzE5GV4JoyIT54YtmJK5n978DErHCMoVrpiLY1IxevUaciQGLKzU4te7Ffj5/7Ti17sVeHrnKfzX+3LkSnooFeZEi4GOT96ASO1BjsSAxQe7kSMxQKT2RCyWV6VyY2GlBi/sUeKN/V1YfLAbr+xTY85uBbY2WVOyN5B9iZBsiPzlHkRB5xlkEbIHXet/pBDFQpkNa+pMWCLSYb3UjA1SM5YIddhw1Mz5fDi2DxUkT5CQ7mSi/JXJZFi4cCFOnDgBl8uFhoYGfPWrX0Vubm5M35OJc8M2icpctjpwiNQevFqmxjO7WvGL/2nFUztP4f9sl+Otqi7K0PHQfdHXy1yodtMONffdj0jtwWFtP0RqT8T7Gb16HaXtTrxV1YUXSpR4o9KroC8o12L2h+3Y2GBJqpJMitURUgWRv9yDKOg8gyxC9qB72KEq8iPVDyJb2I23D+lR0GDFB81n8EHzGRTUW5EjMbDeR5ZtEjlMkmrhhEyAL/J3586deOCBB2L6DF/mhiuwKVPHJ29gb5sTvynqwJzdCrywR4nVR4xoMg1RFrPz7YsNhnMQtDn9vczX1pmw5ZgVF8Ymol6zSuVGZUcfmoxDtO5nfPIGyhUuLK3WY4W4BwsrtXi9XIOXSlV4q6obe1odSQ1xT0bLUgIhHET+cg+ioPMMsgjZIZbDDtV7KxR9eKuqCyvFPdh+3OZX0LcftyHviAEfnXJg4NInaRf6xoRXIF36badTaGI6jTVT4Iv8Xb9+PX7yk59EfA/pMJJamJSp4WSJV/l1okhuR51+IKrC7NsXdzb3IldiwKYGK7Y0WrHskB5vVXVB6RilvP6nNz+D3DaMpYf0yJMYsLHeAkGrEzLL+aj3o3SMIEuow6oaI7Y2WrG61ogV4h7skPUm1fhLjNCEVMKXvSmdIAo6zyCLkB1iPeyEK/JTJLdja5MVeRLDNA/6ysM92HrM6vUQpFnoGxNeAa4fXtIpNDGdxppp8EH+Op1O3HvvvSgrK4v4voKCAsyYMWPaXybPzf/f3r3HV1Xd+f8/SjEoKl4pSkexD2/ttNrbw9ZOR9uOFdrpaG1tq+1U/FWdAVvUGjtVrKRUrcGOHS9fCxaRYhCMEgQEI61cBOSWxAAJCZLEBEKAEqFBBBJu798fNDG3nZzLPmettdfr+Xicx0NDLvusZH32eq+19t42CaOm9lZLerqZXXehvjUsZ+eX6s5pJbrxmRW65smlGv7cSuUWVgTeXK64bpeeWrBR2fml+vXMdcqZXa7s/DUav6i61/dz4NBhTV1Rp5F5xRo1rUSjZ67TuMJKPb2wKqMr165MQiOafDg3uYaA7hk6YXokOtgJusnPypr39OtX1mlk3tFr0O8vOPrf//V8kX79yjrntr6FFaz3thzUgortevKNjVY+b9ulrYkuHWvUuFR/gwJ0+1dRUVGHr2loaND555+vW265pdfvH9UVdJd2pqR6N/jeakl357nWG6F2F+q3Ne3T2DnlunXKal371FL96JnlunP62xpdsE63TFmtNyq2dzmG9ueY8YurlZ1fqpxZ5bp/5jpl55fqyTd6f9rH0ZvlNWpiiDfLS5Ttk9CINpfOTb4goHuGTpg+yQx2WgdzjXv2q3FPs5r2tXS4W/moaSV68NX1+t289Zq+apNzJ+5UVwXaD/CeXVqj3MIK5RZW6NmlNdas/PY2sGr93drwe2IQaJZL9bexsVGVlZU9vvbv39/2+Q0NDbrwwgv1k5/8RIcPJ94nXWqb7ri4MyWVu8EnellXaw3sKdS3Xkd+1/S39auX17Rd6tXTfVjan2MKy7a2Xb9+z8ulGjWtRAsqtsf9OzA9uZKJR5YC3XG9/kYRAd0zNnRC0yfBdElmsBM0qGva19L2HPTNO/c6u/Ut1UDY3WDuqQUb9UbF9qT/fsL++wuahJhdukW/fbVcE5fUWDNgZxulWTbU33TYsmWLLrjgAt1www06dOhQUt/D9bZxeWdKMjUxmVoSz/lgQcV23frn1bq/YJ0emVehnFnlR1fCF2zs9vt29z3nrm3QpKU1zt1YNROPLAW643r9jSICumdMdkIXVxiS0Xmw09PgJ55BneurnsmuCoT9vtP19xd0nOMKKzUyr1hTV9RZM2B3/W/JdVEcBLVua//617+uLVu2aNu2bW2vRLjcNj72q2Teczyhvmlfi3ILK5SdX6p7C9bqgVllGr+4WtNW1gV+36itPEd1EQP2crn+RhUB3TMmO6HLKwzJ6C0QJjLAcXkAkuyqQNirven8++v8+8lbUasRecV69PVK6wbsLv8tuS6Kg6DJkycHXqOeCJfbxtedKYnWknjPea03fZu0tEYzS+p7/b6sPAOpcbn+RhUB3TOmOqGPKwy9BcJEBnVRGIAkuioQ5t9Muv/+Ov9+nl1So7FzyjWntMG6AXsU/pZcxSAomMtt4+P5TUqulsQT6pOtUaw8A8lxuf5GFQHdM6Y6oW8rDPEM2JIZ1Pk2AAkazC2rakyoHTL199f+pn+2D9gTuRQD4WAQFMz1tnF5Z0qqtSCRz08kfFOTgMxwvf5GEQHdM6ygZ0a8gdDlQV2q4hl8dR7MTV1Zp6kr6vTCyrqEriM38fdXXLdLT76xUZOWvBvXNk1TfLk3hA0YBAVzvW1c3JnSue8nW1+TQfgG7OF6/Y0iArpnbLgG3YcwGm8g7G5Qt6xqh7Y17YvswCWZQNg6mFtWtSPp68gz+fd34NDhtsfl/fwfj8vLLazQypr3rBuw+3ZvCJMYBAWLStu4FDw79/1HX6/Uzc+t0qOvV1ILAI9Epf5GCQHdM7bcxd2VFYZUJBII97Yc1LamfVpW1Rj5lcxkA2Gqq+CZ/Ptr/x5nltRr0tJ39dSCjdYNdH3b2WIag6BgUWobF0J6574/d02Dxswq0z35a/TArDLNXdtALQA8EaX6GxUEdM/Y0AldGLyEIdFA6MNKZiqBMKzryMP6+wv6Pi6FXt/uDWGaDfXXVlFoG5cuF+nc9wuK6/WrGWv14Jxy3VuwVgUl9XHVgnjrqS3nfVuOA7BJFOpv1BDQPUMnzLx4BgQuhbpUpBIIbWmj3gbhLoVeW9rUF9TfYFFoG5cmWVNdQY93MsKWSQtbjgOwURTqb9QQ0D1DJ7STS6EuFakGQhvuY9DbINy10GtDm/qC+hvM9bZxrd9LXfv+uMKj16CPK6zstRbEOxnR+fOmrqjTY/M3aFlVY6beZkLHC/jI9fobRQR0z9AJ7eTi4C5ZqQRC0/cx6LLqtLZBBSX1yltR2+H35FLozVSbsrWU+tsT19vGxUnWnp6S0VMtiPcxopt37tWU5bV6qWizCsu2avyiao2ZVaZR00p0d36pllXtyEjt9un8CiTD9fobRQR0z9AJ7WUq1IUdnHr7fmEEQlNhr3UQPrt0i8YvrtYDs8r0qxlrdV/BWv321XJta9onyfxEQjLS1aZsLf0Q9TeY623jcghM9DnoPU1GPLu0Rgsqtmv66k16asFG/XxaiZ5csFH/b8FGZeevUc7scj04p1x3TC/RY/M3ZGTS0sXJEyCTXK+/UURA9wyd0F6ZDnVhhyEfSgAAIABJREFUB6dEv5+LK6qtg/BHX69Udn6pfjO7XI/Mq9AvX1qjkXnFXbZtuvgew8bW0g9Rf4NFoW1c2jmTip4mI3ILK/TkGxvbnmBxT36p/mvKao3IK1bO7HL9/vUNyplVrgdmlXXZeWTieG2fPAEyIQr1N2oI6J6hE9qjfXgL+u90Cjs4uRbEkm3nZVU7NCKvWL98aY0emVehnFnlys5fo3GFlQz2OmFg3BH1N1gU2sbFnTPJ6m4y4qkFG5VbWNGhv49fVK2fTl6la55cqjGz1v2jXpZq/OLqjK5g+zJ5AiQjCvU3agjonqETmtd+EDdxSY1yCyuUW1ihZ5fWZGxAFxSc8pbXaeKSGjXu2R/K97MxiKW6c2Bb0z6NnVOu0TPX6d4ZazVmVpnGL6rWnNIGtkt2wtbSjqi/waLUNoluGXdRd5MRb1Rs18QlNR36e2HZVj02f4OueWqJ/vv5Yj0wq0zjF1ersGxrRs8PPk2eAImKUv2NCgK6Z+iE5rVfaX7qjY26fWqxbs8r1pMLNmZs1blzcGq9gc/omev0388X6dklNQkNXlwKYqmu9LdORkxdUaeC4nrNXdPz44h8ZsPEjU3hiPobLIpt49r9F5LpK513fwX19wfnliv3tQrlrag1uoJtUz0AbBHF+us6Arpn6IRmtR/AtD53Nmd2eds1eXPXNmQkvHQeSI1fVK3s/DW6J3+N7itYq6krapMKrTatoHc3EAvrONkuGT9TbWVjOKL+Boti29h82U/7+hhPX4k32Hbu73nLjz5WbfGGv7GCDVgqivXXdQR0z9AJzWq/0lxQXK9fzVirR+ZV6JF5Fbq3YK0KSuozturcOpDKW16n0TPX6Z78NW3XBrocWnsabIa10s92yfiZaisbwxH1N1jU2sbGSUup+/o4dUWdnl5Y1W1fSXSiq/Xzp66s09hXy3V3fqnGvlquF1bWqbhul5r2tbCCDVgmavU3CgjonqETmmXLCrr04UBq4pIa/ffzRbqvYG3btYEuh9aeglnYg2a2S8Yvk21lazii/gaLWtuk67KfVPtR5/o4dUWtRuQV69HXK7vtK8uqGpOa6FpWtUOPzd+gqf/Y0m7DBBmA7kWt/kYBAd0zdELz2q80P/XGRo3MK9bIf1yDnsqqc7IDt8Y9+/XskhpNXVHrfGiNJ5gV1+3Sk29s1KQl72pmST3b0yPI1nsiUH+DRa1twp4kCuOSje6OqaCkXqOmlWj0zHVt99No7SvPvFmtiUtqEn4Ptk6QAehe1OpvFBDQPUMnNK/9QOvZpanfxT2MgZst29NT1Vsw29a0Tytr3lNuYYV+Pq1Eo6aVKLewQitr3mN7eops2k1ga0Cg/gaLYtuEWVfDuGSju/o4d22D7itYqzuml6iguL5DX3l2SY0m/ONxaIlMdCU6QWZT7QB8FMX66zoCumfohPYI69nnYQzcbNmenupArbdgtqxqR1tbzSyp16Sl7+qpBRudm4iwiY03Y5PsnHSi/gaLYtuEVVfDmnAK+j7jCis1Mq9YecvrOvSVZVU7kvq58R6vrbUD8E0U66/rCOieoRNGS1SuqQ5zoBYUzJZVNVq5quo6G2/GJtkz6dQe9TdYlNsm1boa5iUb3dXHpxdWaeqKum77SrITXfF8na21A/BNlOuvqwjonqETRout19omKsyBWlAw29a0z0hbRXn7pq1byTsfoy3tT/0NRtt0b2/LQW3euVdTlteGsoK+rWlf22Rl5zDeXV9JdqKrt69zoXYAvqD+2oeA7hk6obvS+Vxvk9L1Hjq3V6bbyoftm1GZIMoU6m8w2qajzvUjt7BCv35lnaatrEv4ko3uatGyqh3a1rQvoXCfzERX0NdROwB7UH/tQ0D3DJ3QPb0FPRuvtU1EJgdqybRVsgNTH7ZvRmGCKJOov8Fom44614/pqzbp16+sU25hRcKXbNhYi6gdgD2ov/YhoHuGTuie3gZXtl1rm2igzeRALZG2SmUF3KfBp+sTRJlE/Q1G23yop/oxZXmtNu/8wMr6mihqB2AH6q99COieoRO6JZHBlelrbVMJtJkeqMXTVqmsOvm0fdO2CSKbUX+D0TYfCrN+2FyLqB2AHai/9iGge4ZO6BabB1edpRJoDxw6rGVVjZq4pEbPvFnd7Q2FMjn5kOqqk82rVulieoLIBdTfYLTNh8KsH5mqRan0f2oHYBb11z4EdM/QCd1i02PUevraVI6z/SrKM29W69klNVpWtUMHDh1OeZt5su81jIkRtm+iM+pvMNqmozDrRzprkQ83wwSijvprHwK6Z+iE7gljcJXKICqer00l0Pa08p7MqnwYA8YwJkYysX2TlSe3UH+D0TYdJVo/eqoF6axFNt6ADkBiqL/2IaB7hk7onkQGV0GDtFQGUfF8bbKBtrebISXz7N+wBoxhrTqlI0SzauUm6m8w2qZ7vdWPRGpB2LXIx0t5gCii/tqHgO4ZOqG74l0h6TxIS2UQlcjXJhNoe1p5f2rhRj21YGNCq/JhDhhtvoERq1Zuov4Go22Sk2otMH0pEADzqL/2IaB7hk4YTT0N0lIZRG3e+YGeWrBRM0vqe/3aZAJt2Cvo6Rgw2raNnFUrd1F/g9E2iQvr3h8mLwUCYB711z4EdM/QCaOnt0FS4579CQ+iWgdvU5bX6ucvlCg7v1TjF1ersGxrr1+baKBtnVzIW16nF1dtUt7yui7XoMe7Ku/DgJFVK3dRf4PRNvFpX1/Tde+PRCSzc8q2SU/Ad9Rf+xDQPUMnjJ54BmmJDqLaD96eemOjbp9arJF5xXpywcbQ70a+t+Wgpq6o0x3TS/T/TV6lO6aXaOqKOu1tOZjUqnzU757uwyREVFF/g9E2PetuxXtZ1Q5NXVkX6r0/0nkpEPfOAOxE/bUPAd0zdMLoiWewleiN5tp/v8KyrRq/qFrZ+aUaNa1EU5bXhjqoWlnznn79yjrd+eLbGvVCie588W39+pV1WlnzXodjinfFxeZrx8MS9UmIqKL+BqNterasaocem79BU1fUdljxnrqiLtR7f6TzUiDunQHYifprHwK6Z+iE0RRvYItnEBU0eJtZUq+nFm7U5p17QzvuvS0HlVtYodvzivWb2eV6ZF6FfjO7XCPzipVbWJHSarDN2yhTPTYfJiGiiPobjLbp3oFDh7WsqlF3/2OC9IFZZW2XG+Wv3qwXVtZpWVVjaPf+SNcuHHb+APai/tqHgO4ZOmE0hRnYMjmQ2rzzA/18Wol+PXOdfv/6hrbX/QXrNGpaiTbv/CC0n2WDsLd42jwJga6ov8Fom+4V1+3SY/M3aNS0Ej04p1y/mV3edk+Q9iveyd77I1O7cLh3BmAv6q99COieoRNGW1iBLVODt8079+rnL5To/s4BfWZrQA9vtd4GbPH0G/U3GG3TVetk6dQVdRozq0w5s8v1+9c3KGdWuR6YVaa8FbVJT5pmehcOK+iAvai/9iGge4ZOiHhkavDWtsV9arFyZh3d4p4zK5wt7rZhgArqbzDapqv2q85H7wOyRjmzyvXgnHLdMb1Ej83fkPLkXiZ34XSe+M1bUavH5m/Qsqodaf/ZAIJRf+1DQPcMnRCJyMTgrfUmcdn5pbrnpTXKzi/tcpO4KGCLJ6i/wWibrtpP6rXerHPMrDKNmlaiu/NLtaxqh1P3nWid+H1hZZ1++2q57s4v1dg55Zq6so57aAAGUX/tQ0D3DJ0Qtmn/zPWnFm4M/S7xtmAFHdTfYLRN97qsOi+v+8eqc6PpQ0vasqrGf9yRvo5LfQALUH/tQ0D3DJ3QbVG+KViU31srHo/mN+pvMNqme1F7YgMTlYB9qL/2IaB7hk7oprDv/g0zojbYRmKov8Fom56lcwIzk5OjXOoD2If6ax8CumfohG5y4e7fPqyAhyUqg20khvobjLbJPBMTv66toFNP4QPqr30I6J6hE7rH9gENq/t24PdgP+pvMNom80xN/LpwqQ/1FD6h/tqHgO4ZOqF74t0SaGqm34XVfR/we7Af9TcYbZNZJid+XbjUh3oKn1B/7UNA9wyd0D29DaSa9rUYm+m3fXXfF/we3ED9DUbbZFZPE7/PvFmtd7a/n/a6kY5J5TC+J/UUvqH+2oeA7hk6oZt62hJocqafG/7Ygd+DG6i/wWibzOocQueubdBLRZv18Nz1uju/VBMWV1u5sh0kzC3p1FP4hvprHwK6Z+iE5iUzwx+0JbBpX4vRmX5WGuzA78EN1N9gtE3mFdft0tMLqzSusFL3FazVjyeu0NA/LNYv8t/WnNIGp7Z1hzlRTT2Fb6i/9iGge4ZOaE4YM/ydw70NM/0u3PDHB/we7Ef9DUbbZN6BQ4c1dUWdRuYV62dTi/WD8W/p5udW6Rcvlmr8ompnQmk6AjX1FD6h/tqHgO4ZOqE56diKbsNMvws3/PEBvwf7UX+DRa1tXHg8V+v5Y+qKOv35rXeVnV+qR+ZVKGdWucbMKtPcNQ09XpNuy3tMx0Q19RQ+iVr9jQICumfohGbEG6STGfCEMdMf1o11bBis+Y7fg72ov8Gi0jYuPZ6rfbCdu7ZBD8wq029ml+uReRW6d8Za5Rdt0rjCyi7XpO9tOWjVe0znRDX1FD6ISv2NEgK6Z+iEZvQ2w7+taV/SA55UZvpdGkwCrqP+BotK27j0eK7OwXb84mpl55fqnvw1Gj1znR6au143P7dKj75e2eG9TF1RZ917ZEs6kLyo1N8oIaB7hk5oRm8z/MuqGlMe8LTO9Dfu2R/3jL9Lg8l0YYUEmUL9DRaFtrHhkqOg4wqqce2D7ezSLRpXWKkRecV6YNY63Z1fqkdfr1Rh2YcTy3nL63R3fqmmrqg9evf3NQ0qKK5X3vI6o++RLelA8qJQf6OGgO4ZOqE5QTP8y6p2hDKoS3Q13NbBZKakY/dAJsI+Ewruov4Gi0Lb2HDTzvbiqXHdBdtlVTu0vqFJExZXd3kvL67apP9+vkhTV9Rp/KJqjZlVpl/NWKvRM9dp7Kvl2ta0L6PvsTPqI5C4KNTfqCGge4ZOaE7QDP+2pn2hDOoSXQ23bTCZaWHuHsjEpQJcjuA+6m+wKLSNbZOeidS4zsE26L20rqA/PLdc2flrlPOPa9bvyV+jEXnFWla1I6PvMR0I+fBNFOpv1BDQPUMnNC/egVAig7pkvodtg8lM2dtyUJt37tWU5bWhvfdMXCrA5Qjuo/4Gi0rb2HItdBj1Pei9PLf0XY3MK9Y9+Wva7vqenV+qcYWVTp87mASFr6JSf6OEgO4ZOqGdUh3UJbsabstgMhPaD76eWrBRP59WoicXbOxwfWUyuwcyMdHh62RK1FB/g0WlbXq6FjqTK7Nh7JAKei+bd36gsa+W676Ctbq3YK0emFWm8YurNbt0i9O7r5gEha+iUn+jhIDuGTqhnVK9wU2yAc6nG+u0H3zNLKnXPfmluj2vWOMXV6cUeMO8VCBoAO/75QhRQf0NFrW2ad+XTazMhjmpF7Tra+qKWhWU1Gvu2gbnJwyZBIXPolZ/o4CA7hk6od1SWWFJZTU86tfcdTf4Gr+oWiPzinV3fqlmltQnvXsgjIFdbwN4Bo/RQP0NZrpt0lkDTa3MpnOHVNR2XzEJCp+Zrr/oioDuGTphdPm0Gp6o7gZfhWVb9dQbGzVqWon+38KqlNor1cFqPAP4qA2Ik+H6RBL1N5iptkn36rbJybV0nhOidr5hEhQ+49xkHwK6Z+iE0ed6iJHCfw89Db6mLK/V5p0fpPSz4h2sdve+4h0YRm1AnIio3LyJ+hvMVNuke3U7rJXZVGpiOs8JUTjftGISFL7i3GQfArpn6ISwWTqDWCYGX0GD1Z7eV6ID+CgNiOMVlZs3UX+DmWgbF27wGJXJKRf4PAkKv3Fusg8B3TN0QtgsnUHM5OCrp/fVuGe/nl1So6kratla2Y0obT2l/gYz0TaZuu44lcnBqExOtXJhgtGFYwTCxLnJPgR0z9AJYat0BLGgLeWZHHwFva9pK+uUW1ihKctrNXZOuUbkFWtcYaVml25ha2U7Ubp5E/U3WFRX0KXkJwejNDnFTgDAXpyb7ENA9wydELYKM4jZNBgMel9PLtioW/+8Ws8tfVdzShv06OuVGplXrN++Ws7gtZ0ohRTqbzDT16Bn4rrjRCcHozQ5FbWdAECUcG6yDwHdM3RC2CrMIGbTYLC79zV3bYPuzi/VPfmlmrumoe3jecvrNHFJjRr37M/4cdosKjdvov4Gs+Eu7rZdd5xMTbRxe7YNk2w2tgtgC85N9iGge4ZOCJuFEcRsGAx21vl9TVpao1v+vFpPvbHR+ZWxTLA5RCWC+hvMdNvYGuDirYk27RrqzOROAJvbBbCF6fqLrgjonqETwmZhBDEbt4V2fl9Tltcqt7BC01dt+nBVfU2DJi05+m+2hQRb2Bqi4kX9DeZq26T7bzLemmjTrqHOTE6a2twugC1crb9RRkD3DJ0QLkj1mb/dDQbzVtTqWcPbx9u/r9aB47SVm/TUGxuVnV+qW/+8WrmFFazwRBT1N5hrbRPGymwida6nz7Vx11BnJi5TcaFdABu4Vn99QEA35KGHHtLll1+u448/XgMGDIjra44cOaKcnBydddZZ6tevn6688kqVl5cn9HPphPBB+8Hg7NItGldYqRF5xRo7x54bsLUO8HMLK3TLlNXKzi/Vkws2atqqOlZ4Ior6G8y1tkllZTbsbdc27hrqzMRlKi60C2AD1+qvDwjohowZM0Z/+MMfdPfdd8cd0HNzc3XSSSepoKBAZWVl+uEPf6izzjpL77//ftw/l06IKGtdZWra19I2GPztq+UamVesR1+v1JzSBqu2OO5tOagpy2s1aem7mru2gRWeiKP+BnOpbVJdmQ1727VLK8WZvEzFpXYBTHKp/vqCgG7Y5MmT4wroR44c0aBBg5Sbm9v2sebmZg0YMEATJkyI++fRCRFFQStSW5v2aeKSGk1dUWflAI0VHr9Qf4O51Dap9Nt0hcaoPOkgbLQL0DuX6q8vCOiGxRvQa2pqFIvF9Pbbb3f4+DXXXKObbrop7p9HJ0QUBa1ILajYbnUAZoXHL9TfYC61TSr9Nl2TclF50kHYaBegdy7VX18Q0A2LN6C/9dZbisViamho6PDx2267TVdffXXg1zU3N2v37t1tr/r6ejohIqWnwfKU5bWasry2x4G06TuDs8LjDwZBwVxrm2T7bbon5UzXM1vRLkAw1+qvDwjoIcrJyVEsFuvxVVRU1OFrEg3oW7du7fDxW2+9VUOHDk34mOiEiIreVqTeqNje7UB6Zc17Vjwf19YVHga04WMQFMy1tkml3zIpB8AmrtVfHxDQQ9TY2KjKysoeX/v3d3zEU7q3uLOCjqjrbUWq/Q3j2g+kV9a8Z9XzcW0JxGHfYRofYhAUzNW2Sabf2jopB8BPrtbfKCOgG5boTeLGjRvX9rGWlhZuEgcovhWp9gNprv0OFvYdprtjy2REplF/g/nYNr72AwB28bH+2o6AbsimTZtUWlqqsWPH6sQTT1RpaalKS0u1Z8+ets+56KKLNHPmzLb/z83N1YABAzRz5kyVlZXpxhtv5DFrgBJfkeLu6d1L98SF76vz1N9gtA0AmEH9tQ8B3ZDhw4d3e234okWL2j4nFotp8uTJbf9/5MgR5eTkaNCgQcrKytIVV1yhsrKyhH4unRAmpXvFKN7vzwp699I9cZGJ1XmbUX+D0TYAYAb11z4EdM/QCdGddAdnG1dOuVFTV+mcuGBShPrbE9oGAMyg/tqHgO4ZOiFa7W05qG1N+7Ssakfag7ONK6fcqKl76Zq44LIC6m9PaBsAMIP6ax8CumfohGgfTMfOKdeIvGI9+nqlZpdu6RCcw1pVt33llBs1dZSuiQvb/w4ygfobjLYJRo0CkE7UX/sQ0D1DJ0TrCunUFXUaPXOdfvnSGmXnl2r84mr9df12TVu5SbmFFZqyvDaUVXVWTt2UjlDg+2UF1N9gtE1XNl4aBCB6qL/2IaB7hk7ot/armAXF9frVjLV6ZF6FcmaV64FZZZq7tkFPvbFRt0xZrUlL3w1lOzorp2jl+2UF1N9gtE1XNl4aBCB6qL/2IaB7hk7ot/ar2XPXNGjMrDLlzC7XI/MqdG/BWk1bVafs/FJl55dq7tqG0MJ0WCunbPWMBl9/j9TfYLRNR0xsAsgU6q99COieoRP6rfOgb/yiamXnr9E9+Wt0X8FajV9cpVv/vFpPLtgY6nb0VFdO2eqJKKD+BqNtOuLSIACZQv21DwHdM3RCtF/NnlPaoHGFlRqZV6zfvlquKctrlVtYoWmr6tKyapPsyilbPREF1N9gtE1HrKADyBTqr30I6J6hE6K71exlVY3a1rRPe1sOWncjLwaqiArqbzDapivbajGAaKL+2oeA7hk6IVoFrWbbdiMvtnoiKqi/wWibrmyrxQCiifprHwK6Z+iEiJctN/JiBR1RQf0NRtsEs6UWA4gm6q99COieoRPCRWz1RBRQf4PRNgBgBvXXPgR0z9AJ4SK2eiIKqL/B0tE2JlaeWe0G4BrOTfYhoHuGTgiXMfiFy6i/wcJsGxOPZeRRkABcxbnJPgR0z9AJzSNkAn6i/gYLs21MPJaRR0ECcBXnJvsQ0D1DJzTH5hUWJg2A9KP+BgurbUzcVJIbWQJwGecm+xDQPUMnNMfGFRabJw2AqKH+BgurbUw8ljHsn8mEKYBM4txkHwK6Z+iEZqRjhSWMQZyNkwZAVFF/g7GCzoQpADM4N9mHgO4ZOqEZYa6whDWI6zyonLumQQXF9cpbXuf8tkxWoGAj6m+wdFyDnsnHMobxM5kwBWAC5yb7ENA9Qyc0I8xVnbAGca2TBnNKGzR+UbXGzCrTr2as1eiZ6zT21XJta9qX6Ns0jhUo2Iz6Gyxdd3HP1GMZU/2ZXMcOwBTOTfYhoHuGTmhOGCssYQ7iWr/Xo69XKjt/jXJml+uReRW6J3+NRuQVa1nVjmTeplGsQMFm1N9gvj8H3cS18wAgcW6yEQHdM3RCc8JY1Ql7ELesqlEj84p1T/4aPTKvQjmzypWdX6pxhZXOrdqEPXnBFnmEjfobzPe2YQUdgCm+118bEdA9Qyc0L5XwF/YgblvTPo19tVz3FazVvQVr9cCsMo1fXK3ZpVuMr9ok2k5hTF6wRR7pRP0NRtuYuXYeAKi/9iGge4ZO6L4wB3GtgX/qiloVlNRr7toG46s2yYbkMCYv2CKPdKL+BqNtzFw7nynsSgLsRf21DwHdM3RC94U9iLNt1SaVkJzKe2GLKdKN+huMtvlQlMIsu5IA+1F/7UNA9wydMDrCGsTZtGqTakhO5b1wk6YPRSkg2IT6G4y2iSZ2JQH2o/7ah4DuGTohgtgQysIKyUHvpaf3GOXnwseL1a70ov4Go22ih11JgBuov/YhoHuGTgibpWtAF2/wLK7bpacXVmlcYaVGz1ynUdNKNDKvWFNX1HkRUlntSi/qbzDaJnrYlQS4gfprHwK6Z+iEsF06romPN3geOHRYU1fUaURese6YXqL7Ctbq0dcr9fTCqsiHVFa70o/6G4y2iR5qCuAG6q99COieoRPCdmFfE5/IINHGu9pnCqtd6Uf9DUbbRJNtNyEF0BX11z4EdM/QCeGKsK6JTyR4+hxSWe1KP+pvMNommmy6CSmA7lF/7UNA9wydEC5LJrQns4Lua0hltSu9qL/Botw2NtyA0zTaALBXlOuvqwjonqETwkWp3l08keDpc0hltSu9qL/Botg2PBUBgAuiWH9dR0D3DJ0QLkr17uKJBE9CKqtd6UL9DRbFtuGpCABcEMX66zoCumfohH6JQtAKc9t5Iu0RhbaDXaJef5ubm3XppZcqFouptLQ0oa+NWtv4frkMAHdErf5GAQHdM3RCP0Rpa6XPN25DtES9/t5xxx365je/SUAXdQuAO6JWf6OAgO4ZOqEforS1kpUoREWU6+9rr72miy++WOvXryegi7oFwB1Rq79RQED3DJ0w+qI4MPT5xm2IjqjW3+3bt2vw4MEqKipSbW1tXAG9ublZu3fvbnvV19dHrm2oWwBcENVzk8sI6J6hE0ZfprdWZuJabW7chiiIYv09cuSIhg0bpgcffFCS4g7oOTk5isViXV5RapugutW0r4X7WwCwRhTPTa4joHuGThh9mVpBN3GdOzdug8tcqr9BAbr9q6ioSE888YS+/OUv69ChQ5LiD+g+rKC3aq1bTfta0lIzqYsAUuHSuckXBHTP0An9kImtlVG6zh3IBJfqb2NjoyorK3t87d+/X9dee62OPfZY9enTp+0Vi8XUp08f3XTTTXH/PJfaJllh18wo3QwUgDk+1F/XENA9Qyf0Q7q3hEfxOncg3aJYfzdt2qSysrK21/z58xWLxTRjxgzV19fH/X2i2DbtpaNmMkkKIAxRr78uIqB7hk7ol3RtfeQRQkDifKi/8W5x7yzqbRN2zWSSFEBYol5/XURA9wydEGFgcAgkzof6S0DvXtg1k0lSAGGJev11EQHdM3RChIVHCAGJof4G86FtwqyZTJICCIsP9dc1BHTP0An9ke47+/LoMyAx1N9gPrRN2DWTSVIAYfCh/rqGgO4ZOmH0ZfrOvjziJzr4XaYX9TeYT20TVj9jkhRAGHyqv64goHuGThh93NkXieJxTZlB/Q1G2ySPiTUAqaD+2oeA7hk6of1SGWxl4rpEBoPRw6ROZlB/g9E2AGAG9dc+BHTP0Al7ZyqAhrGKmc47+7LKGk3cbCpzqL/BUm0bJg4BIDmcm+xDQPcMnTCY6QAaxipmOsMWq6zRxOOaMof6GyzZtjFdtwHAdZyb7ENA9wydMJjJABpmsE7HnX1ZZY0ufreZQ/0NlmzbMHEYjF0FAOLBuck+BHTP0Am7ZzqkhLmKmY47+7LKGm08rikzqL/Bkmkb03XbVuwqAJAIzk32IaB7hk7YPdMBNB0DzTBXTxgIRxuPa8oM6m+wZNrcbP2AAAAgAElEQVTGdN22FbsKACSCc5N9COieoRN2z4YAavsqpu3Hh9SxJTa9qL/BWEEPB20CIFGcm+xDQPcMnTBYmAE0maBj+yqm7ccH2I76GyzVa9CZODyKXQUAEsW5yT4EdM/QCYOFEUDDuPbP9lVM248PsBX1N1gYd3Fn4pAVdACJ49xkHwK6Z+iEvUslgHLtH4Ag1N9gPAc9POwqAJAIzk32IaB7hk6YPqxcAOgJ9TcYbRMedhUASAT11z4EdM/QCdOHa/8A9IT6G4y2CR+7CgDEg/prHwK6Z+iE6cMKulsYvCLTqL/BaBsAMIP6ax8CumfohOnFtX/2C+NGfkAyqL/BbG8bJvQARJXt9ddHBHTPRLUT2jJ44to/+3EjP5gS1fobBlvbhgk9AFFna/31GQHdM1HrhLYOnmyZMEBHXIYAk6JWf8Nka9swoQcg6mytvz4joHsmap2QwRMSwY38YFLU6m+YbGwbJvQA+MDG+us7ArpnotQJGTwhUfzNwKQo1d+w2dg2TOgB8IGN9dd3BHTPRKkTMnhCMriRH0yJUv0Nm41tw4QeAB/YWH99R0D3TJQ6IYMnJIMb+cGUKNXfsNnaNkzoAYg6W+uvzwjonolaJ2TwhGRxIz9kWtTqb5hsbRsm9ABEna3112cEdM9ErRMyeALgiqjV3zDZ3jZM6AGIKtvrr48I6J6Jaidk8ATAdlGtv2GgbQDADOqvfQjonqETAoAZ1N9gtA0AmEH9tQ8B3TN0QgAwg/objLYBADOov/YhoHuGTgjfcPkDbEH9DUbbAIAZ1F/7ENA9QyeEL9rfQPC5Ze7cQJAJheii/gajbQDADOqvfQjonqETwhetj+B7qejoI/heKrL7EXyuTiggftTfYLQNAJhB/bUPAd0zdEL4YG/LQU1fvUkvFW3WX9dvb3vlr96s6as3Wbk67dqEAhJH/Q1G2wCAGdRf+xDQPUMnhA8a9zTruWXvat7arR0C+ry1WzX5rXfVuKfZ9CF24OKEAhJH/Q1G2wCAGdRf+xDQPUMnhA9cC7yuTSggOdTfYLQNAJhB/bUPAd2Qhx56SJdffrmOP/54DRgwIK6vGT58uGKxWIfXF7/4xYR+Lp0QvmjdMp6/+uiW8fzV9m4Zd21CAcmh/gajbQDADOqvfQjohowZM0Z/+MMfdPfddycU0IcNG6Zt27a1vXbu3JnQz6UTwhftb7o2+S37b7rm0oQCkkP9DUbbAIAZ1F/7ENANmzx5ckIB/dprr03p59EJ4RtXHlvm2oQCEkf9DUbbAIAZ1F/7ENANSzSgDxgwQGeeeaYuuOAC3Xrrrfrb3/6W0M+jEwJ2c2VCAYmj/gajbQDADOqvfQjohiUS0F988UXNnTtXZWVlmjNnji699FL98z//s5qbg28g1dzcrN27d7e96uvr6YQAYACDoGC0DQCYQf21DwE9RDk5OV1u4tb5VVRU1OFrEgnonW3dulV9+/ZVQUFBwsdEJwSAzGIQFIy2AQAzqL/2IaCHqLGxUZWVlT2+9u/f3+FrUgnoknT++ecrNzc38N9ZQQe6x1ZyZBqDoGC0DQCYQf21DwHdsFQC+nvvvaesrCxNmTIl7q+hE8J37W/G9twybsaGzKH+BqNtEsMEI4CwUH/tQ0A3ZNOmTSotLdXYsWN14oknqrS0VKWlpdqzZ0/b51x00UWaOXOmJGnPnj3Kzs7W8uXLVVtbq0WLFunyyy/X4MGD9f7778f9c+mE8F3r48xeKjr6OLOXiux6nBkD7+ii/gajbeLDBCOAsFF/7UNAN2T48OHdXhu+aNGits+JxWKaPHmyJGnfvn26+uqrdeaZZ6pv374655xzNHz4cG3evDmhn0snhI0yFUr3thzU9NWb9FLRZv11/fa2V/7qzZq+epPRUMzAO/qov8Fom/jYPsEIwD3UX/sQ0D1DJ4RNMh1KG/c067ll72re2q0dAvq8tVs1+a131bgn+IkI6cbAO/qov8Fom97ZPMEIwF3UX/sQ0D1DJ4RNMh1KbR3g2npcCBf1Nxht0zubJxgBuIv6ax8CumfohLCFqVDaOimQv/ropED+avMr1Qy8/UD9DUbb9I6JPADpQP21DwHdM3RC2MJUKG2/rX7yW3Zc683A2w/U32C0TXxsnGAE4Dbqr30I6J6hE8IWpkOpbXdLZ+AdfdTfYLRNfGycYATgNuqvfQjonqETwiaE0g8x8I4+6m+wqLdN2BOCtk0wAnBX1OuviwjonqETwiaE0q4YeEcX9TdYVNuGxycCsF1U66/LCOieoRPCRoRS+ID6GyyqbcPjEwHYLqr112UEdM/QCQHADOpvsCi2jen7bABAPKJYf11HQPcMnRBRwIo7XET9DRbFtuHxiQBcEMX66zoCumfohHAZ13PCZdTfYFFsG1bQAbggivXXdQR0z9AJ4TKu54TLqL/Boto2iTypgp1BAEyIav11GQHdM3RCuIrVKLiO+hssqm0Tz5Mq2BkEwKSo1l+XEdA9QyeEq7ieE66j/gaLetv0tDrOziAAJkW9/rqIgO4ZOiFc0zqwbdyznxV0OI36G8zXtmFnEADTfK2/NiOge4ZOCFd0t+1z6oo6Pb2wKq7rOQHbUH+D+do27AwCYJqv9ddmBHTP0Anhiu62fT69sEpTV9T1eD0nYCvqbzAf2qa7be6soAMwzYf66xoCumfohEhVJu403NugtXHPfu52DOdQf4NFuW16uwlcInd6B4CwRbn+uoqA7hk6IZKVyTsNs+0TUUT9DRbltuntJnDx3OkdANIlyvXXVQR0z9AJkaxM3mmYbZ+IIupvsKi2TSK1jOegAzAhqvXXZQR0z9AJkQwTgZltn4ga6m+wqLYNu4EA2C6q9ddlBHTP0AmRDBODTLZ9Imqov8Gi2jbsBgJgu6jWX5cR0D1DJ0QyTA4y2faJqKD+Bst022SyrrAbCIDNODfZh4DuGTohksUgE0gN9TdYptomkze77O5nshsIgG04N9mHgO4ZOiGSxSATSA31N1im2iaTN7vsjN1AAGzEuck+BHTP0AmRKgaZQHKov8FSbZt46hLXgwNAV5yb7ENA9wydEADMoP4GS7ZtEtmyzh3VAaArzk32IaB7hk4IAGZQf4Ml2zaJbFlnBR0AuuLcZB8CumfohABgBvU3WDJtk0zg5maXANAR5yb7ENA9QycEADOov8GSaZtktqxzs0sA6Ihzk30I6J6hEwKAGdTfYJlaQW//tdzsEgA4N9mIgO4ZOiEAmEH9DZbqNehsWQeA5HBusg8B3TN0QgAwg/obLIy7uLNlHQASx7nJPgR0z9AJAcAM6m+wTDwHHQDQFecm+xDQPUMnBAAzqL/BaBsAMIP6ax8CumfohABgBvU3GG0DAGZQf+1DQPcMnRAAzKD+BqNtAMAM6q99COieoRMCgBnU32C0DQCYQf21DwHdM3RCADCD+huMtgEAM6i/9iGge4ZOCABmUH+D0TYAYAb11z4EdM/QCQHADOpvMNoGAMyg/tqHgO4ZOiEAmEH9DUbbAIAZ1F/7ENA9QycEADOov8FoGwAwg/prHwK6Z+iEAGAG9TcYbQMAZlB/7UNA9wydEADMoP4Go20AwAzqr30I6J6hEwKAGdTfYLQNAJhB/bUPAd0zdEIAMIP6G4y2AQAzqL/2IaB7hk4IAGZQf4PRNgBgBvXXPgR0z9AJAcAM6m8w2gYAzKD+2oeA7hk6IQCYQf0NRtsAgBnUX/sQ0D1DJwQAM6i/wWgbADCD+msfArpn6IQAYAb1NxhtAwBmUH/tQ0D3DJ0QAMyg/gajbQDADOqvfQjonqETAoAZ1N9gtA0AmEH9tQ8B3TN0QgAwg/objLYBADOov/YhoHuGTggAZlB/g9E2AGAG9dc+BHTP0AkBwAzqbzDaBgDMoP7ah4DuGTohAJhB/Q1G2wCAGdRf+xDQPUMnBAAzqL/BaBsAMIP6ax8CumfohABgBvU3GG0DAGZQf+1DQPcMnRCI396Wg2rc06y9LQdNHwoigPobjLY5ipoDINOov/YhoHuGTgj07sChwyqu26XpqzfpuWXvavrqTSqu26UDhw6bPjQ4jPobzPe2oeYAMMX3+msjArpn6IRA74rrdmnC4mq9VLRZ89Zu1UtFmzVhcbWK63aZPjQ4jPobzPe2oeYAMMX3+msjArpn6IRAz/a2HNT01Zv0UtFm/XX99rZX/urNmr56E1tPkTTqbzCf24aaA8Akn+uvrQjonqETAj1r3NOs55a9q3lrt3YYLM9bu1WT33pXjXuaTR8iHEX9DeZz21BzAJjkc/21FQHdM3RCoGesZiFdqL/BfG4bag4Ak3yuv7YioHuGTgj0rvV60PzVR68HzV/N9aBIHfU3mO9tQ80BYIrv9ddGBHTP0AmB3rW/o/Lkt7ijMsJB/Q3me9tQcwCY4nv9tREB3TN0QiB+PJMYYYpy/Z07d64uu+wy9evXT6effrquu+66hL4+ym2TCGoOgEyj/tqHgO4ZOiEAmBHV+jtjxgydeuqpGj9+vN555x1t2LBBL7/8ckLfI6ptAwC2o/7ah4DuGTohAJgRxfp78OBBDR48WM8++2xK3yeKbQMALqD+2oeA7hk6IQCYEcX6u2rVKsViMT333HP6zGc+o0GDBmnYsGEqLy9P6PtEsW0AwAXUX/sQ0D1DJwQAM6JYf6dPn65YLKZzzjlHM2bMUHFxsW688Uadfvrp2rlzZ+DXNTc3a/fu3W2v+vr6yLUNALggiucm1xHQPUMnBAAzXKq/OTk5isViPb6Kior0wgsvKBaL6Zlnnmn72ubmZp1xxhmaMGFCwt/fhbYBgChx6dzkCwK6Z+iEAGCGS/W3sbFRlZWVPb7279+vhQsXKhaLaenSpR2+/rLLLtPo0aMDvz8r6ABgB5fOTb4goHuGTggAZkSx/u7evVtZWVkdbhJ34MABDRw4sMOqejzfJ2ptAwAuoP7ah4DuGTohAJgR1fp75513avDgwZo/f742bNigW265RQMHDtSuXbvi/h5RbRsAsB311z4EdM/QCQHAjKjW3wMHDig7O1sDBw7USSedpKuuuoq7uAOAI6i/9iGge4ZOCABmUH+D0TYAYAb11z4EdANqa2v105/+VEOGDFG/fv308Y9/XGPGjFFLS0uPX3fkyBHl5OTorLPOUr9+/XTllVeySgEAjqD+BqNtAMAM6q99COgGFBYW6uabb9b8+fNVU1Oj2bNna+DAgcrOzu7x63Jzc3XSSSepoKBAZWVl+uEPf6izzjpL77//ftw/m04IAGZQf4PRNgBgBvXXPgR0Szz66KM677zzAv/9yJEjGjRokHJzc9s+1tzcrAEDBvT4rNnO6IQAYAb1NxhtAwBmUH/tQ0C3xP3336/Pf/7zgf9eU1OjWCymt99+u8PHr7nmGt10001x/xw6IQCYQf0NRtsAgBnUX/sQ0C1QXV2tk08+WRMnTgz8nLfeekuxWEwNDQ0dPn7bbbfp6quvDvy65uZm7d69u+1VX19PJwQAAxgEBaNtAMAM6q99COghysnJUSwW6/FVVFTU4WsaGhp0/vnn65Zbbunxe7cG9K1bt3b4+K233qqhQ4cmfEx0QgDILAZBwWgbADCD+msfAnqIGhsbVVlZ2eNr//79bZ/f0NCgCy+8UD/5yU90+PDhHr93slvcWUEHADswCApG2wCAGdRf+xDQDdmyZYsuuOAC3XDDDTp06FCvn996k7hx48a1faylpYWbxAGAI6i/wWgbADCD+msfAroBrdvav/71r2vLli3atm1b26u9iy66SDNnzmz7/9zcXA0YMEAzZ85UWVmZbrzxRh6zBgCOoP4Go20AwAzqr30I6AZMnjw58Br19mKxmCZPntz2/0eOHFFOTo4GDRqkrKwsXXHFFSorK0voZ9MJAcAM6m8w2gYAzKD+2oeA7hk6IQCYQf0NRtsAgBnUX/sQ0D1DJwQAM6i/wWgbADCD+msfArpn6IQAYAb1NxhtAwBmUH/tQ0D3DJ0QAMyg/gajbQDADOqvfQjonqETAoAZ1N9gtA0AmEH9tQ8B3TN0QgAwg/objLYBADOov/YhoHuGTggAZlB/g9E2AGAG9dc+BHTP0AkBwAzqbzDaBgDMoP7ah4DuGTohAJhB/Q1G2wCAGdRf+xDQPdPU1KRYLKb6+nrt3r2bFy9evHhl6FVfX69YLKampibTpwLrcG7ixYsXLzMvzk32IaB7prUT8uLFixcvM6/6+nrTpwLrcG7ixYsXL7Mvzk32IKB75vDhw6qvr1dTU5OxGToXV0hcPXZXj5tj59ijeNxNTU2qr6/X4cOHTZ8KrGPq3OTC302mX7QJbUKb+NUmnJvsQ0BHxuze7e41Lq4eu6vHLXHsprh67K4eN8zi76Yr2qQr2qQr2qQr2gRhIaAjY1wuXK4eu6vHLXHsprh67K4eN8zi76Yr2qQr2qQr2qQr2gRhIaAjY1wuXK4eu6vHLXHsprh67K4eN8zi76Yr2qQr2qQr2qQr2gRhIaAjY5qbm5WTk6Pm5mbTh5IwV4/d1eOWOHZTXD12V48bZvF30xVt0hVt0hVt0hVtgrAQ0AEAAAAAsAABHQAAAAAACxDQAQAAAACwAAEdAAAAAAALENABAAAAALAAAR3GzJ07V5dddpn69eun008/Xdddd53pQ0pIc3OzLr30UsViMZWWlpo+nF7V1tbqpz/9qYYMGaJ+/frp4x//uMaMGaOWlhbTh9atp59+WkOGDFFWVpY+97nPacmSJaYPqUe/+93v9IUvfEEnnniizjzzTF177bXasGGD6cNKyu9+9zvFYjHdeeedpg8lLlu2bNGPf/xjnXbaaTr++ON16aWXqri42PRhwWGu1fd0ce28kS6unY/SKUrnunRw7fwJOxHQYcSMGTN06qmnavz48XrnnXe0YcMGvfzyy6YPKyF33HGHvvnNbzozgCssLNTNN9+s+fPnq6amRrNnz9bAgQOVnZ1t+tC6ePHFF9W3b19NnDhRFRUVuvPOO9W/f39t2rTJ9KEFGjp0qCZPnqzy8nKtWbNG//7v/65zzjlHH3zwgelDS8jq1as1ZMgQXXLJJU4MMHbt2qVzzz1XN998s1atWqXa2lq98cYbqq6uNn1ocJhr9T1dXDpvpIuL56N0isq5Lh1cO3/CXgR0ZNzBgwc1ePBgPfvss6YPJWmvvfaaLr74Yq1fv97pAdyjjz6q8847z/RhdHHZZZdpxIgRHT528cUX69577zV0RInbsWOHYrGY3nzzTdOHErc9e/boggsu0F//+lddeeWVTgwwfvWrX+krX/mK6cNAhESlvqeLreeNdInC+SidXDzXpYOL50/Yi4COjFu1apVisZiee+45feYzn9GgQYM0bNgwlZeXmz60uGzfvl2DBw9WUVGRamtrnR7A3X///fr85z9v+jA6aGlpUZ8+fTRz5swOH7/jjjt0xRVXGDqqxFVVVSkWi6msrMz0ocTtpptu0l133SVJzgwwPvGJT+iuu+7S9ddfrzPPPFOf+cxn9Kc//cn0YcFRUarv6WLjeSNdonI+SicXz3Xp4OL5E/YioCPjpk+frlgspnPOOUczZsxQcXGxbrzxRp1++unauXOn6cPr0ZEjRzRs2DA9+OCDkuT0AK66ulonn3yyJk6caPpQOmhoaFAsFtNbb73V4eMPP/ywLrzwQkNHlZgjR47oP/7jP5xa2Z0+fbo+9alPaf/+/ZLcGWBkZWUpKytL9913n95++21NmDBB/fr105QpU0wfGhwTpfqeLraeN9IlCuejdHLxXJcOrp4/YS8COkKTk5OjWCzW46uoqEgvvPCCYrGYnnnmmbavbW5u1hlnnKEJEyZYfexPPPGEvvzlL+vQoUOS7BjAxXvs7TU0NOj888/XLbfcYuiog7UOiJYvX97h4w899JAuuugiQ0eVmNtvv13nnnuu6uvrTR9KXDZv3qyBAwdqzZo1bR9zZYDRt29fXX755R0+NmrUKH3pS18ydESwjcv1PV2idt5Ilyicj9LJtXNdOrh8/oS9COgITWNjoyorK3t87d+/XwsXLlQsFtPSpUs7fP1ll12m0aNHW33s1157rY499lj16dOn7RWLxdSnTx/ddNNNVh97q4aGBl144YX6yU9+osOHDxs55p64vqXw5z//uT72sY/p3XffNX0ocXvllVfa/o7b/10fc8wx6tOnT1tgsdE555zTJTD88Y9/1Nlnn23oiGAbl+t7ukTtvJEurp+P0snFc106uHz+hL0I6Mi43bt3Kysrq8NN4g4cOKCBAwd2WFW30aZNm1RWVtb2mj9/vmKxmGbMmOHEDPKWLVt0wQUX6IYbbrD6pHHZZZdp5MiRHT72iU98wuqb8hw5ckQ/+9nPdPbZZ2vjxo2mDych77//foe/67KyMn3hC1/Qf/7nf1p/XeGNN97YZXvlXXfd1WVVHeiN6/U9XVw5b6SLi+ejdHL5XJcOLp8/YS8COoy48847NXjwYM2fP18bNmzQLbfcooEDB2rXrl2mDy0hLm2BbN2e+PWvf11btmzRtm3b2l62aX2szaRJk1RRUaG77rpL/fv3V11dnelDCzRy5EgNGDBAixcv7tC2+/btM31oSXFli97q1av1kY98RA8//LCqqqr0wgsv6IQTTtDUqVNNHxoc51J9TxeXzhvp4uL5KJ2idq5LB1fOn7AXAR1GHDhwQNnZ2Ro4cKBOOukkXXXVVc7cxb09lwZwkydPDrzW0EZPP/20zj33XB133HH63Oc+Z/0jXILadvLkyaYPLSkuDTBeffVVfepTn1JWVpYuvvhi7uKOULhU39PFtfNGurh2PkqnqJ3r0sGl8yfs5FeFBQAAAADAUgR0AAAAAAAsQEAHAAAAAMACBHQAAAAAACxAQAcAAAAAwAIEdAAAAAAALEBABwAAAADAAgR0AAAAAAAsQEAHAAAAAMACBHTAYcOHD1csFlMsFtNHPvIRnXfeecrOztYHH3zQ4fNmzJihK6+8UieffLL69++vT3/60xo7dqx27tzZ4fP27dunU045Raeeeqr27duXybcSWcOHD9e1117b6+e9+eab+va3v62zzjpLsVhMr7zySgaODgAAADYhoAMOGz58uIYNG6Zt27Zp8+bNeuGFF3T88cdrxIgRbZ8zevRo9enTR/fcc4/eeust1dbW6i9/+Yu++93v6vHHH+/w/fLy8vSVr3xF//Iv/6KpU6dm+u1EUrwB/bXXXtP999+vgoICAjoAWGratGnKysrSli1b2j52yy236NOf/rSampoMHhmAqCCgAw7rLvzdeuutGjRokCRp1apVisViXYJ4q7///e8d/v+rX/2qJkyYoPHjx+trX/taXMcwadIkffKTn9Rxxx2nQYMG6Wc/+1nbv23atEnXXHON+vfvr5NOOknf//73tX379rZ/z8nJ0aWXXqpJkybpn/7pn9S/f3+NGDFChw4d0rhx4/TRj35UZ555ph566KEOPzMWi+mPf/yjhg0bpn79+mnIkCF66aWXOnzOunXr9LWvfU39+vXTaaedpttuu0179uzp0na///3vNWjQIJ122mm6/fbbdeDAgbbPaWlp0S9/+UudffbZOuGEE3TZZZdp0aJFbf8+efJkDRgwQK+//rouvvhi9e/fX0OHDtXWrVvb3l/rDofWV/uvD0JABwA7HTlyRJdccknbue43v/mNPvaxj3UI7ACQCgI64LDuAvqoUaN0+umnS5LuuOMOnXjiiR1CZ5Dq6mplZWVp165d2rlzp7KyslRTU9Pj1/zxj39Uv3799Pjjj+udd97R6tWr9X//93+Sjg5iPvvZz+orX/mKiouLtXLlSn3uc5/TlVde2fb1OTk5OvHEE3X99ddr/fr1mjNnjo477jgNHTpUo0aN0oYNG/Tcc88pFotpxYoVbV8Xi8V0+umna+LEiXrnnXf061//Wn369FFFRYUkae/evTr77LP13e9+V2VlZVqwYIHOO+88DR8+vEPbnXzyyRoxYoQqKyv16quv6oQTTtCf/vSnts/50Y9+pC9/+ctasmSJqqur9fvf/15ZWVnauHGjpKMBvW/fvrrqqqtUVFSkkpISfeITn9CPfvQjSdKePXv0gx/8oG2Xw7Zt29TS0tLr74KADgD2evXVV5WVlaWHH35Yp556qsrLy9v+7Tvf+Y5OOeUUfe973zN4hABcRkAHHNY5oK9atUqnn366fvCDH0iSvvnNb+qSSy6J63uNHj1a3/nOd9r+/9prr9X999/f49ecffbZgZ/zl7/8RX369NHmzZvbPrZ+/XrFYjGtXr1a0tGAfsIJJ+j9999v+5yhQ4dqyJAhOnz4cNvHLrroIj3yyCNt/x+LxTps45ekL37xixo5cqQk6U9/+pNOPfXUDtfiz5s3T8cee2zbCv7w4cN17rnn6tChQ22f8/3vf18//OEPJR2dsDjmmGPU0NDQ4ef827/9m+677z5JRwN6LBZTdXV1278//fTT+uhHP9r2//FucW+PgA4AdvvsZz+r4447TosXL+7w8YULF2rOnDkEdABJI6ADDhs+fLj69Omj/v37KysrS8cee6yuu+46/e1vf5MkDRs2TJdeemmv3+fQoUMaPHiwZsyY0faxl19+WR/72Mc6BNj2/va3vykWi2nhwoXd/vsTTzyhIUOGdPn4KaecoilTpkg6GtA/+clPdvj3m266Sd/61rc6fOyKK67QL37xi7b/j8Vibd+j1V133aWvfvWrkqRf/OIXbf/dqqmpSbFYTG+++aako23X+efccccdbVv7X3rpJcViMfXv37/D6yMf+UjbBMjkyZN1wgkndPgeM2fO1DHHHNP2/wR0AIiW119/Xccff7z69OmjysrKLv++aNEiAjqApBHQAYcNHz5cV111laqqqlRXV9dlK3u8W9znzZunWCymPn36dHjFYjG99tpr3X7N+++/32NAf/zxx3Xeeed1+fiAAQP0/EzEw34AAAU3SURBVPPPS/rwGvTO76lzoL3yyit15513tv1/UEBvDdft/7tVa0BfsmRJ4M+5884727bgv/jii+rTp482bNigqqqqDq9t27ZJ+vAa9PZeeeUVxWIfllYCOgBER0lJiU466SQ9//zz+ta3vqXrr7++y+cQ0AGkgoAOOKy38Ldy5cq4bhL33e9+VzfccIPKyso6vH784x/3OMgYMmRIUlvci4qKJKUW0Fu3s7f60pe+lPAW954C+jvvvNMh0HcnnoB+22236dvf/nbg9+gOAR0A7FNbW6tBgwbp4YcfliQVFxfrmGOOUXFxcYfPI6ADSAUBHXBYPKuz//M//6M+ffrol7/8pZYvX666ujq98cYbuv766/X4449rx44d6tu3rwoLC7t87V/+8hf17dtXO3bs6PZ7//nPf1a/fv30xBNPaOPGjSopKdGTTz4p6cObxP3rv/6rSkpKtGrVKn3+85/vcpO4ZAP6GWecoUmTJumdd97RmDFjdOyxx2r9+vWSjt4k7qyzztL3vvc9lZWVaeHChfr4xz/e5SZxPQV0Sfrxj3+sIUOGqKCgQO+++65Wr16t3NxczZs3T1J8Af3hhx/WOeecow0bNqixsTFwN8OePXtUWlqq0tJSxWIx/eEPf1Bpaak2bdrU7ecDADJn586duvjii/Vf//VfHT5+zTXXaOjQoR0+RkAHkAoCOuCweLdP5+fn64orrtBJJ52k/v3765JLLtFvf/tb/f3vf9f//u//6pRTTuk2OB48eFCnnXaaHnvsscDvPWHCBF100UXq27evzjrrLI0aNart3+J9zFpv76m7gP7000/rG9/4hrKysnTuuedq+vTpHb4m3sestdc5oB84cEBjxozRkCFD1LdvXw0aNEjXXXed1q1bJym+gL5jxw594xvf0IknntjjY9YWLVrU5ZFssVisw6QCAMB+BHQAqSCgA3AOW8ABADa6+uqrdcYZZ+j444/X4MGD255aAgDxIqADcA4BHQAAAFFEQAfgHAI6AAAAooiADgAAAACABQjoAAAAAABYgIAOAAAAAIAFCOgAAAAAAFiAgA4AAAAAgAUI6AAAAAAAWICADgAAAACABQjoAAAAAABYgIAOAAAAAIAFCOgAAAAAAFiAgA4AAAAAgAUI6AAAAAAAWICADgAAAACABQjoAAAAAABYgIAOAAAAAIAFCOgAAAAAAFiAgA4AAAAAgAUI6AAAAAAAWICADgAAAACABQjoAAAAAABYgIAOAAAAAIAFCOgAAAAAAFiAgA4AAAAAgAUI6AAAAAAAWICADgAAAACABQjoAAAAAABYgIAOAAAAAIAFCOgAAAAAAFiAgA4AAAAAgAUI6AAAAAAAWICADgAAAACABQjoAAAAAABYgIAOAAAAAIAFCOgAAAAAAFiAgA4AAAAAgAUI6AAAAAAAWICADgAAAACABQjoAAAAAABYgIAOAAAAAIAFCOgAAAAAAFiAgA4AAAAAgAUI6AAAAAAAWICADgAAAACABQjoAAAAAABYgIAOAAAAAIAFCOgAAAAAAFiAgA4AAAAAgAUI6AAAAAAAWICADgAAAACABQjoAAAAAABYgIAOAAAAAIAFCOgAAAAAAFiAgA4AAAAAgAUI6AAAAAAAWICADgAAAACABQjoAAAAAABYgIAOAAAAAIAFCOgAAAAAAFiAgA4AAAAAgAUI6AAAAAAAWICADgAAAACABQjoAAAAAABYgIAOAAAAAIAFCOgAAAAAAFiAgA4AAAAAgAUI6AAAAAAAWICADgAAAACABf5/ISAf19tL1bMAAAAASUVORK5CYII=\" width=\"1000\">"
+ ],
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "fig, ax = plt.subplots(figsize=(10, 10), ncols=2)\n",
+ "data.plot.scatter(x=\"pca1\", y=\"pca2\", alpha=0.3, ax=ax[0])\n",
+ "data.plot.scatter(x=\"x1\", y=\"x2\", alpha=0.3, ax=ax[1])\n",
+ "ax[0].set(xlabel=\"PCA component 1\", ylabel=r\"PCA component 2\", title=\"PCA representation\")\n",
+ "ax[1].set(xlabel=\"$x_1$\", ylabel=r\"$x_2$\", title=\"Original data\")\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "54e538c6",
+ "metadata": {},
+ "source": [
+ "It is interesting to understand how many PCA components are necessary to explain the variance of the data. This is easily obtainable from the PCA object."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "id": "fa5ebbce",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "application/javascript": [
+ "/* Put everything inside the global mpl namespace */\n",
+ "/* global mpl */\n",
+ "window.mpl = {};\n",
+ "\n",
+ "mpl.get_websocket_type = function () {\n",
+ " if (typeof WebSocket !== 'undefined') {\n",
+ " return WebSocket;\n",
+ " } else if (typeof MozWebSocket !== 'undefined') {\n",
+ " return MozWebSocket;\n",
+ " } else {\n",
+ " alert(\n",
+ " 'Your browser does not have WebSocket support. ' +\n",
+ " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+ " 'Firefox 4 and 5 are also supported but you ' +\n",
+ " 'have to enable WebSockets in about:config.'\n",
+ " );\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
+ " this.id = figure_id;\n",
+ "\n",
+ " this.ws = websocket;\n",
+ "\n",
+ " this.supports_binary = this.ws.binaryType !== undefined;\n",
+ "\n",
+ " if (!this.supports_binary) {\n",
+ " var warnings = document.getElementById('mpl-warnings');\n",
+ " if (warnings) {\n",
+ " warnings.style.display = 'block';\n",
+ " warnings.textContent =\n",
+ " 'This browser does not support binary websocket messages. ' +\n",
+ " 'Performance may be slow.';\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.imageObj = new Image();\n",
+ "\n",
+ " this.context = undefined;\n",
+ " this.message = undefined;\n",
+ " this.canvas = undefined;\n",
+ " this.rubberband_canvas = undefined;\n",
+ " this.rubberband_context = undefined;\n",
+ " this.format_dropdown = undefined;\n",
+ "\n",
+ " this.image_mode = 'full';\n",
+ "\n",
+ " this.root = document.createElement('div');\n",
+ " this.root.setAttribute('style', 'display: inline-block');\n",
+ " this._root_extra_style(this.root);\n",
+ "\n",
+ " parent_element.appendChild(this.root);\n",
+ "\n",
+ " this._init_header(this);\n",
+ " this._init_canvas(this);\n",
+ " this._init_toolbar(this);\n",
+ "\n",
+ " var fig = this;\n",
+ "\n",
+ " this.waiting = false;\n",
+ "\n",
+ " this.ws.onopen = function () {\n",
+ " fig.send_message('supports_binary', { value: fig.supports_binary });\n",
+ " fig.send_message('send_image_mode', {});\n",
+ " if (fig.ratio !== 1) {\n",
+ " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
+ " }\n",
+ " fig.send_message('refresh', {});\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onload = function () {\n",
+ " if (fig.image_mode === 'full') {\n",
+ " // Full images could contain transparency (where diff images\n",
+ " // almost always do), so we need to clear the canvas so that\n",
+ " // there is no ghosting.\n",
+ " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+ " }\n",
+ " fig.context.drawImage(fig.imageObj, 0, 0);\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onunload = function () {\n",
+ " fig.ws.close();\n",
+ " };\n",
+ "\n",
+ " this.ws.onmessage = this._make_on_message_function(this);\n",
+ "\n",
+ " this.ondownload = ondownload;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_header = function () {\n",
+ " var titlebar = document.createElement('div');\n",
+ " titlebar.classList =\n",
+ " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
+ " var titletext = document.createElement('div');\n",
+ " titletext.classList = 'ui-dialog-title';\n",
+ " titletext.setAttribute(\n",
+ " 'style',\n",
+ " 'width: 100%; text-align: center; padding: 3px;'\n",
+ " );\n",
+ " titlebar.appendChild(titletext);\n",
+ " this.root.appendChild(titlebar);\n",
+ " this.header = titletext;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
+ "\n",
+ "mpl.figure.prototype._init_canvas = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var canvas_div = (this.canvas_div = document.createElement('div'));\n",
+ " canvas_div.setAttribute(\n",
+ " 'style',\n",
+ " 'border: 1px solid #ddd;' +\n",
+ " 'box-sizing: content-box;' +\n",
+ " 'clear: both;' +\n",
+ " 'min-height: 1px;' +\n",
+ " 'min-width: 1px;' +\n",
+ " 'outline: 0;' +\n",
+ " 'overflow: hidden;' +\n",
+ " 'position: relative;' +\n",
+ " 'resize: both;'\n",
+ " );\n",
+ "\n",
+ " function on_keyboard_event_closure(name) {\n",
+ " return function (event) {\n",
+ " return fig.key_event(event, name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " canvas_div.addEventListener(\n",
+ " 'keydown',\n",
+ " on_keyboard_event_closure('key_press')\n",
+ " );\n",
+ " canvas_div.addEventListener(\n",
+ " 'keyup',\n",
+ " on_keyboard_event_closure('key_release')\n",
+ " );\n",
+ "\n",
+ " this._canvas_extra_style(canvas_div);\n",
+ " this.root.appendChild(canvas_div);\n",
+ "\n",
+ " var canvas = (this.canvas = document.createElement('canvas'));\n",
+ " canvas.classList.add('mpl-canvas');\n",
+ " canvas.setAttribute('style', 'box-sizing: content-box;');\n",
+ "\n",
+ " this.context = canvas.getContext('2d');\n",
+ "\n",
+ " var backingStore =\n",
+ " this.context.backingStorePixelRatio ||\n",
+ " this.context.webkitBackingStorePixelRatio ||\n",
+ " this.context.mozBackingStorePixelRatio ||\n",
+ " this.context.msBackingStorePixelRatio ||\n",
+ " this.context.oBackingStorePixelRatio ||\n",
+ " this.context.backingStorePixelRatio ||\n",
+ " 1;\n",
+ "\n",
+ " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+ "\n",
+ " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
+ " 'canvas'\n",
+ " ));\n",
+ " rubberband_canvas.setAttribute(\n",
+ " 'style',\n",
+ " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
+ " );\n",
+ "\n",
+ " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
+ " if (this.ResizeObserver === undefined) {\n",
+ " if (window.ResizeObserver !== undefined) {\n",
+ " this.ResizeObserver = window.ResizeObserver;\n",
+ " } else {\n",
+ " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
+ " this.ResizeObserver = obs.ResizeObserver;\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
+ " var nentries = entries.length;\n",
+ " for (var i = 0; i < nentries; i++) {\n",
+ " var entry = entries[i];\n",
+ " var width, height;\n",
+ " if (entry.contentBoxSize) {\n",
+ " if (entry.contentBoxSize instanceof Array) {\n",
+ " // Chrome 84 implements new version of spec.\n",
+ " width = entry.contentBoxSize[0].inlineSize;\n",
+ " height = entry.contentBoxSize[0].blockSize;\n",
+ " } else {\n",
+ " // Firefox implements old version of spec.\n",
+ " width = entry.contentBoxSize.inlineSize;\n",
+ " height = entry.contentBoxSize.blockSize;\n",
+ " }\n",
+ " } else {\n",
+ " // Chrome <84 implements even older version of spec.\n",
+ " width = entry.contentRect.width;\n",
+ " height = entry.contentRect.height;\n",
+ " }\n",
+ "\n",
+ " // Keep the size of the canvas and rubber band canvas in sync with\n",
+ " // the canvas container.\n",
+ " if (entry.devicePixelContentBoxSize) {\n",
+ " // Chrome 84 implements new version of spec.\n",
+ " canvas.setAttribute(\n",
+ " 'width',\n",
+ " entry.devicePixelContentBoxSize[0].inlineSize\n",
+ " );\n",
+ " canvas.setAttribute(\n",
+ " 'height',\n",
+ " entry.devicePixelContentBoxSize[0].blockSize\n",
+ " );\n",
+ " } else {\n",
+ " canvas.setAttribute('width', width * fig.ratio);\n",
+ " canvas.setAttribute('height', height * fig.ratio);\n",
+ " }\n",
+ " canvas.setAttribute(\n",
+ " 'style',\n",
+ " 'width: ' + width + 'px; height: ' + height + 'px;'\n",
+ " );\n",
+ "\n",
+ " rubberband_canvas.setAttribute('width', width);\n",
+ " rubberband_canvas.setAttribute('height', height);\n",
+ "\n",
+ " // And update the size in Python. We ignore the initial 0/0 size\n",
+ " // that occurs as the element is placed into the DOM, which should\n",
+ " // otherwise not happen due to the minimum size styling.\n",
+ " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
+ " fig.request_resize(width, height);\n",
+ " }\n",
+ " }\n",
+ " });\n",
+ " this.resizeObserverInstance.observe(canvas_div);\n",
+ "\n",
+ " function on_mouse_event_closure(name) {\n",
+ " return function (event) {\n",
+ " return fig.mouse_event(event, name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mousedown',\n",
+ " on_mouse_event_closure('button_press')\n",
+ " );\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseup',\n",
+ " on_mouse_event_closure('button_release')\n",
+ " );\n",
+ " // Throttle sequential mouse events to 1 every 20ms.\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mousemove',\n",
+ " on_mouse_event_closure('motion_notify')\n",
+ " );\n",
+ "\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseenter',\n",
+ " on_mouse_event_closure('figure_enter')\n",
+ " );\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseleave',\n",
+ " on_mouse_event_closure('figure_leave')\n",
+ " );\n",
+ "\n",
+ " canvas_div.addEventListener('wheel', function (event) {\n",
+ " if (event.deltaY < 0) {\n",
+ " event.step = 1;\n",
+ " } else {\n",
+ " event.step = -1;\n",
+ " }\n",
+ " on_mouse_event_closure('scroll')(event);\n",
+ " });\n",
+ "\n",
+ " canvas_div.appendChild(canvas);\n",
+ " canvas_div.appendChild(rubberband_canvas);\n",
+ "\n",
+ " this.rubberband_context = rubberband_canvas.getContext('2d');\n",
+ " this.rubberband_context.strokeStyle = '#000000';\n",
+ "\n",
+ " this._resize_canvas = function (width, height, forward) {\n",
+ " if (forward) {\n",
+ " canvas_div.style.width = width + 'px';\n",
+ " canvas_div.style.height = height + 'px';\n",
+ " }\n",
+ " };\n",
+ "\n",
+ " // Disable right mouse context menu.\n",
+ " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ " });\n",
+ "\n",
+ " function set_focus() {\n",
+ " canvas.focus();\n",
+ " canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " window.setTimeout(set_focus, 100);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var toolbar = document.createElement('div');\n",
+ " toolbar.classList = 'mpl-toolbar';\n",
+ " this.root.appendChild(toolbar);\n",
+ "\n",
+ " function on_click_closure(name) {\n",
+ " return function (_event) {\n",
+ " return fig.toolbar_button_onclick(name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " function on_mouseover_closure(tooltip) {\n",
+ " return function (event) {\n",
+ " if (!event.currentTarget.disabled) {\n",
+ " return fig.toolbar_button_onmouseover(tooltip);\n",
+ " }\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " fig.buttons = {};\n",
+ " var buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'mpl-button-group';\n",
+ " for (var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " /* Instead of a spacer, we start a new button group. */\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ " buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'mpl-button-group';\n",
+ " continue;\n",
+ " }\n",
+ "\n",
+ " var button = (fig.buttons[name] = document.createElement('button'));\n",
+ " button.classList = 'mpl-widget';\n",
+ " button.setAttribute('role', 'button');\n",
+ " button.setAttribute('aria-disabled', 'false');\n",
+ " button.addEventListener('click', on_click_closure(method_name));\n",
+ " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+ "\n",
+ " var icon_img = document.createElement('img');\n",
+ " icon_img.src = '_images/' + image + '.png';\n",
+ " icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
+ " icon_img.alt = tooltip;\n",
+ " button.appendChild(icon_img);\n",
+ "\n",
+ " buttonGroup.appendChild(button);\n",
+ " }\n",
+ "\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ "\n",
+ " var fmt_picker = document.createElement('select');\n",
+ " fmt_picker.classList = 'mpl-widget';\n",
+ " toolbar.appendChild(fmt_picker);\n",
+ " this.format_dropdown = fmt_picker;\n",
+ "\n",
+ " for (var ind in mpl.extensions) {\n",
+ " var fmt = mpl.extensions[ind];\n",
+ " var option = document.createElement('option');\n",
+ " option.selected = fmt === mpl.default_extension;\n",
+ " option.innerHTML = fmt;\n",
+ " fmt_picker.appendChild(option);\n",
+ " }\n",
+ "\n",
+ " var status_bar = document.createElement('span');\n",
+ " status_bar.classList = 'mpl-message';\n",
+ " toolbar.appendChild(status_bar);\n",
+ " this.message = status_bar;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
+ " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+ " // which will in turn request a refresh of the image.\n",
+ " this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.send_message = function (type, properties) {\n",
+ " properties['type'] = type;\n",
+ " properties['figure_id'] = this.id;\n",
+ " this.ws.send(JSON.stringify(properties));\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.send_draw_message = function () {\n",
+ " if (!this.waiting) {\n",
+ " this.waiting = true;\n",
+ " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+ " var format_dropdown = fig.format_dropdown;\n",
+ " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+ " fig.ondownload(fig, format);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
+ " var size = msg['size'];\n",
+ " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
+ " fig._resize_canvas(size[0], size[1], msg['forward']);\n",
+ " fig.send_message('refresh', {});\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
+ " var x0 = msg['x0'] / fig.ratio;\n",
+ " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
+ " var x1 = msg['x1'] / fig.ratio;\n",
+ " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
+ " x0 = Math.floor(x0) + 0.5;\n",
+ " y0 = Math.floor(y0) + 0.5;\n",
+ " x1 = Math.floor(x1) + 0.5;\n",
+ " y1 = Math.floor(y1) + 0.5;\n",
+ " var min_x = Math.min(x0, x1);\n",
+ " var min_y = Math.min(y0, y1);\n",
+ " var width = Math.abs(x1 - x0);\n",
+ " var height = Math.abs(y1 - y0);\n",
+ "\n",
+ " fig.rubberband_context.clearRect(\n",
+ " 0,\n",
+ " 0,\n",
+ " fig.canvas.width / fig.ratio,\n",
+ " fig.canvas.height / fig.ratio\n",
+ " );\n",
+ "\n",
+ " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
+ " // Updates the figure title.\n",
+ " fig.header.textContent = msg['label'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
+ " var cursor = msg['cursor'];\n",
+ " switch (cursor) {\n",
+ " case 0:\n",
+ " cursor = 'pointer';\n",
+ " break;\n",
+ " case 1:\n",
+ " cursor = 'default';\n",
+ " break;\n",
+ " case 2:\n",
+ " cursor = 'crosshair';\n",
+ " break;\n",
+ " case 3:\n",
+ " cursor = 'move';\n",
+ " break;\n",
+ " }\n",
+ " fig.rubberband_canvas.style.cursor = cursor;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
+ " fig.message.textContent = msg['message'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
+ " // Request the server to send over a new figure.\n",
+ " fig.send_draw_message();\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
+ " fig.image_mode = msg['mode'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
+ " for (var key in msg) {\n",
+ " if (!(key in fig.buttons)) {\n",
+ " continue;\n",
+ " }\n",
+ " fig.buttons[key].disabled = !msg[key];\n",
+ " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
+ " if (msg['mode'] === 'PAN') {\n",
+ " fig.buttons['Pan'].classList.add('active');\n",
+ " fig.buttons['Zoom'].classList.remove('active');\n",
+ " } else if (msg['mode'] === 'ZOOM') {\n",
+ " fig.buttons['Pan'].classList.remove('active');\n",
+ " fig.buttons['Zoom'].classList.add('active');\n",
+ " } else {\n",
+ " fig.buttons['Pan'].classList.remove('active');\n",
+ " fig.buttons['Zoom'].classList.remove('active');\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function () {\n",
+ " // Called whenever the canvas gets updated.\n",
+ " this.send_message('ack', {});\n",
+ "};\n",
+ "\n",
+ "// A function to construct a web socket function for onmessage handling.\n",
+ "// Called in the figure constructor.\n",
+ "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
+ " return function socket_on_message(evt) {\n",
+ " if (evt.data instanceof Blob) {\n",
+ " /* FIXME: We get \"Resource interpreted as Image but\n",
+ " * transferred with MIME type text/plain:\" errors on\n",
+ " * Chrome. But how to set the MIME type? It doesn't seem\n",
+ " * to be part of the websocket stream */\n",
+ " evt.data.type = 'image/png';\n",
+ "\n",
+ " /* Free the memory for the previous frames */\n",
+ " if (fig.imageObj.src) {\n",
+ " (window.URL || window.webkitURL).revokeObjectURL(\n",
+ " fig.imageObj.src\n",
+ " );\n",
+ " }\n",
+ "\n",
+ " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+ " evt.data\n",
+ " );\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " } else if (\n",
+ " typeof evt.data === 'string' &&\n",
+ " evt.data.slice(0, 21) === 'data:image/png;base64'\n",
+ " ) {\n",
+ " fig.imageObj.src = evt.data;\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " var msg = JSON.parse(evt.data);\n",
+ " var msg_type = msg['type'];\n",
+ "\n",
+ " // Call the \"handle_{type}\" callback, which takes\n",
+ " // the figure and JSON message as its only arguments.\n",
+ " try {\n",
+ " var callback = fig['handle_' + msg_type];\n",
+ " } catch (e) {\n",
+ " console.log(\n",
+ " \"No handler for the '\" + msg_type + \"' message type: \",\n",
+ " msg\n",
+ " );\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " if (callback) {\n",
+ " try {\n",
+ " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+ " callback(fig, msg);\n",
+ " } catch (e) {\n",
+ " console.log(\n",
+ " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
+ " e,\n",
+ " e.stack,\n",
+ " msg\n",
+ " );\n",
+ " }\n",
+ " }\n",
+ " };\n",
+ "};\n",
+ "\n",
+ "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+ "mpl.findpos = function (e) {\n",
+ " //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+ " var targ;\n",
+ " if (!e) {\n",
+ " e = window.event;\n",
+ " }\n",
+ " if (e.target) {\n",
+ " targ = e.target;\n",
+ " } else if (e.srcElement) {\n",
+ " targ = e.srcElement;\n",
+ " }\n",
+ " if (targ.nodeType === 3) {\n",
+ " // defeat Safari bug\n",
+ " targ = targ.parentNode;\n",
+ " }\n",
+ "\n",
+ " // pageX,Y are the mouse positions relative to the document\n",
+ " var boundingRect = targ.getBoundingClientRect();\n",
+ " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
+ " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
+ "\n",
+ " return { x: x, y: y };\n",
+ "};\n",
+ "\n",
+ "/*\n",
+ " * return a copy of an object with only non-object keys\n",
+ " * we need this to avoid circular references\n",
+ " * http://stackoverflow.com/a/24161582/3208463\n",
+ " */\n",
+ "function simpleKeys(original) {\n",
+ " return Object.keys(original).reduce(function (obj, key) {\n",
+ " if (typeof original[key] !== 'object') {\n",
+ " obj[key] = original[key];\n",
+ " }\n",
+ " return obj;\n",
+ " }, {});\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.mouse_event = function (event, name) {\n",
+ " var canvas_pos = mpl.findpos(event);\n",
+ "\n",
+ " if (name === 'button_press') {\n",
+ " this.canvas.focus();\n",
+ " this.canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " var x = canvas_pos.x * this.ratio;\n",
+ " var y = canvas_pos.y * this.ratio;\n",
+ "\n",
+ " this.send_message(name, {\n",
+ " x: x,\n",
+ " y: y,\n",
+ " button: event.button,\n",
+ " step: event.step,\n",
+ " guiEvent: simpleKeys(event),\n",
+ " });\n",
+ "\n",
+ " /* This prevents the web browser from automatically changing to\n",
+ " * the text insertion cursor when the button is pressed. We want\n",
+ " * to control all of the cursor setting manually through the\n",
+ " * 'cursor' event from matplotlib */\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
+ " // Handle any extra behaviour associated with a key event\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.key_event = function (event, name) {\n",
+ " // Prevent repeat events\n",
+ " if (name === 'key_press') {\n",
+ " if (event.which === this._key) {\n",
+ " return;\n",
+ " } else {\n",
+ " this._key = event.which;\n",
+ " }\n",
+ " }\n",
+ " if (name === 'key_release') {\n",
+ " this._key = null;\n",
+ " }\n",
+ "\n",
+ " var value = '';\n",
+ " if (event.ctrlKey && event.which !== 17) {\n",
+ " value += 'ctrl+';\n",
+ " }\n",
+ " if (event.altKey && event.which !== 18) {\n",
+ " value += 'alt+';\n",
+ " }\n",
+ " if (event.shiftKey && event.which !== 16) {\n",
+ " value += 'shift+';\n",
+ " }\n",
+ "\n",
+ " value += 'k';\n",
+ " value += event.which.toString();\n",
+ "\n",
+ " this._key_event_extra(event, name);\n",
+ "\n",
+ " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
+ " return false;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
+ " if (name === 'download') {\n",
+ " this.handle_save(this, null);\n",
+ " } else {\n",
+ " this.send_message('toolbar_button', { name: name });\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
+ " this.message.textContent = tooltip;\n",
+ "};\n",
+ "\n",
+ "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
+ "// prettier-ignore\n",
+ "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
+ "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+ "\n",
+ "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
+ "\n",
+ "mpl.default_extension = \"png\";/* global mpl */\n",
+ "\n",
+ "var comm_websocket_adapter = function (comm) {\n",
+ " // Create a \"websocket\"-like object which calls the given IPython comm\n",
+ " // object with the appropriate methods. Currently this is a non binary\n",
+ " // socket, so there is still some room for performance tuning.\n",
+ " var ws = {};\n",
+ "\n",
+ " ws.close = function () {\n",
+ " comm.close();\n",
+ " };\n",
+ " ws.send = function (m) {\n",
+ " //console.log('sending', m);\n",
+ " comm.send(m);\n",
+ " };\n",
+ " // Register the callback with on_msg.\n",
+ " comm.on_msg(function (msg) {\n",
+ " //console.log('receiving', msg['content']['data'], msg);\n",
+ " // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
+ " ws.onmessage(msg['content']['data']);\n",
+ " });\n",
+ " return ws;\n",
+ "};\n",
+ "\n",
+ "mpl.mpl_figure_comm = function (comm, msg) {\n",
+ " // This is the function which gets called when the mpl process\n",
+ " // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+ "\n",
+ " var id = msg.content.data.id;\n",
+ " // Get hold of the div created by the display call when the Comm\n",
+ " // socket was opened in Python.\n",
+ " var element = document.getElementById(id);\n",
+ " var ws_proxy = comm_websocket_adapter(comm);\n",
+ "\n",
+ " function ondownload(figure, _format) {\n",
+ " window.open(figure.canvas.toDataURL());\n",
+ " }\n",
+ "\n",
+ " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
+ "\n",
+ " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+ " // web socket which is closed, not our websocket->open comm proxy.\n",
+ " ws_proxy.onopen();\n",
+ "\n",
+ " fig.parent_element = element;\n",
+ " fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+ " if (!fig.cell_info) {\n",
+ " console.error('Failed to find cell for figure', id, fig);\n",
+ " return;\n",
+ " }\n",
+ " fig.cell_info[0].output_area.element.on(\n",
+ " 'cleared',\n",
+ " { fig: fig },\n",
+ " fig._remove_fig_handler\n",
+ " );\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
+ " var width = fig.canvas.width / fig.ratio;\n",
+ " fig.cell_info[0].output_area.element.off(\n",
+ " 'cleared',\n",
+ " fig._remove_fig_handler\n",
+ " );\n",
+ " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
+ "\n",
+ " // Update the output cell to use the data from the current canvas.\n",
+ " fig.push_to_output();\n",
+ " var dataURL = fig.canvas.toDataURL();\n",
+ " // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+ " // the notebook keyboard shortcuts fail.\n",
+ " IPython.keyboard_manager.enable();\n",
+ " fig.parent_element.innerHTML =\n",
+ " '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ " fig.close_ws(fig, msg);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
+ " fig.send_message('closing', msg);\n",
+ " // fig.ws.close()\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
+ " // Turn the data on the canvas into data in the output cell.\n",
+ " var width = this.canvas.width / this.ratio;\n",
+ " var dataURL = this.canvas.toDataURL();\n",
+ " this.cell_info[1]['text/html'] =\n",
+ " '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function () {\n",
+ " // Tell IPython that the notebook contents must change.\n",
+ " IPython.notebook.set_dirty(true);\n",
+ " this.send_message('ack', {});\n",
+ " var fig = this;\n",
+ " // Wait a second, then push the new image to the DOM so\n",
+ " // that it is saved nicely (might be nice to debounce this).\n",
+ " setTimeout(function () {\n",
+ " fig.push_to_output();\n",
+ " }, 1000);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var toolbar = document.createElement('div');\n",
+ " toolbar.classList = 'btn-toolbar';\n",
+ " this.root.appendChild(toolbar);\n",
+ "\n",
+ " function on_click_closure(name) {\n",
+ " return function (_event) {\n",
+ " return fig.toolbar_button_onclick(name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " function on_mouseover_closure(tooltip) {\n",
+ " return function (event) {\n",
+ " if (!event.currentTarget.disabled) {\n",
+ " return fig.toolbar_button_onmouseover(tooltip);\n",
+ " }\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " fig.buttons = {};\n",
+ " var buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'btn-group';\n",
+ " var button;\n",
+ " for (var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " /* Instead of a spacer, we start a new button group. */\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ " buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'btn-group';\n",
+ " continue;\n",
+ " }\n",
+ "\n",
+ " button = fig.buttons[name] = document.createElement('button');\n",
+ " button.classList = 'btn btn-default';\n",
+ " button.href = '#';\n",
+ " button.title = name;\n",
+ " button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
+ " button.addEventListener('click', on_click_closure(method_name));\n",
+ " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+ " buttonGroup.appendChild(button);\n",
+ " }\n",
+ "\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ "\n",
+ " // Add the status bar.\n",
+ " var status_bar = document.createElement('span');\n",
+ " status_bar.classList = 'mpl-message pull-right';\n",
+ " toolbar.appendChild(status_bar);\n",
+ " this.message = status_bar;\n",
+ "\n",
+ " // Add the close button to the window.\n",
+ " var buttongrp = document.createElement('div');\n",
+ " buttongrp.classList = 'btn-group inline pull-right';\n",
+ " button = document.createElement('button');\n",
+ " button.classList = 'btn btn-mini btn-primary';\n",
+ " button.href = '#';\n",
+ " button.title = 'Stop Interaction';\n",
+ " button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
+ " button.addEventListener('click', function (_evt) {\n",
+ " fig.handle_close(fig, {});\n",
+ " });\n",
+ " button.addEventListener(\n",
+ " 'mouseover',\n",
+ " on_mouseover_closure('Stop Interaction')\n",
+ " );\n",
+ " buttongrp.appendChild(button);\n",
+ " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
+ " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
+ " var fig = event.data.fig;\n",
+ " if (event.target !== this) {\n",
+ " // Ignore bubbled events from children.\n",
+ " return;\n",
+ " }\n",
+ " fig.close_ws(fig, {});\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function (el) {\n",
+ " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
+ " // this is important to make the div 'focusable\n",
+ " el.setAttribute('tabindex', 0);\n",
+ " // reach out to IPython and tell the keyboard manager to turn it's self\n",
+ " // off when our div gets focus\n",
+ "\n",
+ " // location in version 3\n",
+ " if (IPython.notebook.keyboard_manager) {\n",
+ " IPython.notebook.keyboard_manager.register_events(el);\n",
+ " } else {\n",
+ " // location in version 2\n",
+ " IPython.keyboard_manager.register_events(el);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
+ " var manager = IPython.notebook.keyboard_manager;\n",
+ " if (!manager) {\n",
+ " manager = IPython.keyboard_manager;\n",
+ " }\n",
+ "\n",
+ " // Check for shift+enter\n",
+ " if (event.shiftKey && event.which === 13) {\n",
+ " this.canvas_div.blur();\n",
+ " // select the cell after this one\n",
+ " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
+ " IPython.notebook.select(index + 1);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+ " fig.ondownload(fig, null);\n",
+ "};\n",
+ "\n",
+ "mpl.find_output_cell = function (html_output) {\n",
+ " // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+ " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+ " // IPython event is triggered only after the cells have been serialised, which for\n",
+ " // our purposes (turning an active figure into a static one), is too late.\n",
+ " var cells = IPython.notebook.get_cells();\n",
+ " var ncells = cells.length;\n",
+ " for (var i = 0; i < ncells; i++) {\n",
+ " var cell = cells[i];\n",
+ " if (cell.cell_type === 'code') {\n",
+ " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
+ " var data = cell.output_area.outputs[j];\n",
+ " if (data.data) {\n",
+ " // IPython >= 3 moved mimebundle to data attribute of output\n",
+ " data = data.data;\n",
+ " }\n",
+ " if (data['text/html'] === html_output) {\n",
+ " return [cell, data, j];\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "// Register the function which deals with the matplotlib target/channel.\n",
+ "// The kernel may be null if the page has been refreshed.\n",
+ "if (IPython.notebook.kernel !== null) {\n",
+ " IPython.notebook.kernel.comm_manager.register_target(\n",
+ " 'matplotlib',\n",
+ " mpl.mpl_figure_comm\n",
+ " );\n",
+ "}\n"
+ ],
+ "text/plain": [
+ "<IPython.core.display.Javascript object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
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\" width=\"1000\">"
+ ],
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ]
+ },
+ "metadata": {},
"output_type": "display_data"
}
],
"source": [
+ "fig = plt.figure(figsize=(10,10))\n",
"plt.barh([\"PCA 1\", \"PCA 2\"], pca.explained_variance_)\n",
"plt.gca().set(xlabel=\"Variance\", ylabel=\"Component\", title=\"Explained variance\")\n",
"plt.show()"
@@ -436,8 +3312,7 @@
"source": [
"### Contact us at the EuXFEL Data Analysis group at any time if you need help analysing your data!\n",
"\n",
- "#### Danilo Ferreira de Lima: danilo.enoque.ferreira.de.lima@xfel.eu\n",
- "#### Arman Davtyan: arman.davtyan@xfel.eu"
+ "#### Data Analysis group: da@xfel.eu"
]
},
{
@@ -465,7 +3340,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.7.10"
+ "version": "3.6.13"
}
},
"nbformat": 4,
diff --git a/Supervised classification.ipynb b/Supervised classification.ipynb
index 1a10549..94a6db0 100644
--- a/Supervised classification.ipynb
+++ b/Supervised classification.ipynb
@@ -20,21 +20,44 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 1,
"id": "d0681795",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Requirement already satisfied: torchvision in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (0.11.2)\n",
+ "Requirement already satisfied: torch in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (1.10.1)\n",
+ "Requirement already satisfied: pandas in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (1.1.5)\n",
+ "Requirement already satisfied: numpy in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (1.19.2)\n",
+ "Requirement already satisfied: matplotlib in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (3.3.4)\n",
+ "Requirement already satisfied: pillow!=8.3.0,>=5.3.0 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from torchvision) (8.3.1)\n",
+ "Requirement already satisfied: typing_extensions in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from torch) (3.10.0.2)\n",
+ "Requirement already satisfied: dataclasses in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from torch) (0.8)\n",
+ "Requirement already satisfied: python-dateutil>=2.7.3 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from pandas) (2.8.2)\n",
+ "Requirement already satisfied: pytz>=2017.2 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from pandas) (2021.3)\n",
+ "Requirement already satisfied: kiwisolver>=1.0.1 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from matplotlib) (1.3.1)\n",
+ "Requirement already satisfied: cycler>=0.10 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from matplotlib) (0.11.0)\n",
+ "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.3 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from matplotlib) (3.0.4)\n",
+ "Requirement already satisfied: six>=1.5 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from python-dateutil>=2.7.3->pandas) (1.16.0)\n"
+ ]
+ }
+ ],
"source": [
"!pip install torchvision torch pandas numpy matplotlib"
]
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 2,
"id": "23feddde",
"metadata": {},
"outputs": [],
"source": [
+ "%matplotlib notebook\n",
+ "\n",
"# import standard PyTorch modules\n",
"import torch\n",
"import torch.nn as nn\n",
@@ -46,8 +69,7 @@
"\n",
"import pandas as pd\n",
"import numpy as np\n",
- "import matplotlib.pyplot as plt\n",
- "%matplotlib inline"
+ "import matplotlib.pyplot as plt"
]
},
{
@@ -62,7 +84,7 @@
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": 3,
"id": "30205402",
"metadata": {},
"outputs": [],
@@ -84,7 +106,7 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": 4,
"id": "cc0b0774",
"metadata": {},
"outputs": [
@@ -103,7 +125,7 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": 5,
"id": "6dccfac6",
"metadata": {},
"outputs": [
@@ -111,115 +133,115 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "{'data': tensor([[[ 1.5547e+00],\n",
- " [ 5.5951e-01],\n",
- " [-4.4580e-01],\n",
- " [-4.0911e-01],\n",
- " [-1.9626e+00],\n",
- " [-1.2957e+00],\n",
- " [ 1.0107e+00],\n",
- " [ 8.5706e-01],\n",
- " [ 8.2698e-02],\n",
- " [ 1.7445e+00]],\n",
+ "{'data': tensor([[[-2.2541e-01],\n",
+ " [-8.7492e-01],\n",
+ " [ 2.2757e-01],\n",
+ " [ 3.6083e-01],\n",
+ " [-1.0728e+00],\n",
+ " [-1.9445e+00],\n",
+ " [ 1.2723e+00],\n",
+ " [-4.6512e-01],\n",
+ " [ 7.8006e-01],\n",
+ " [-2.8025e+00]],\n",
"\n",
- " [[-1.1114e+00],\n",
- " [-1.5847e+00],\n",
- " [-2.0654e-01],\n",
- " [-1.0200e+00],\n",
- " [-1.6865e-01],\n",
- " [-1.2053e-01],\n",
- " [ 7.0255e-01],\n",
- " [-5.0251e-01],\n",
- " [ 1.0529e+00],\n",
- " [-2.9051e-01]],\n",
+ " [[ 2.5337e-01],\n",
+ " [-3.9780e-01],\n",
+ " [-1.5573e+00],\n",
+ " [-6.1211e-01],\n",
+ " [-1.7922e+00],\n",
+ " [ 1.4484e+00],\n",
+ " [-3.1899e-01],\n",
+ " [ 1.4920e-03],\n",
+ " [-1.3394e+00],\n",
+ " [ 2.9670e-01]],\n",
"\n",
- " [[-9.3932e-02],\n",
- " [ 2.6510e+00],\n",
- " [ 1.4673e+00],\n",
- " [-1.8302e+00],\n",
- " [-1.2404e-01],\n",
- " [ 3.8249e-01],\n",
- " [-5.5515e-02],\n",
- " [-1.3505e+00],\n",
- " [ 1.3203e-01],\n",
- " [ 9.6623e-02]],\n",
+ " [[-1.1016e-01],\n",
+ " [ 1.6733e+00],\n",
+ " [ 2.7996e-01],\n",
+ " [-3.7264e-01],\n",
+ " [-1.4377e+00],\n",
+ " [ 1.7887e+00],\n",
+ " [ 1.6038e-01],\n",
+ " [ 7.4539e-01],\n",
+ " [ 1.9320e+00],\n",
+ " [ 5.8520e-01]],\n",
"\n",
- " [[-7.8525e-01],\n",
- " [ 6.6473e-01],\n",
- " [ 4.6917e-01],\n",
- " [-1.2006e+00],\n",
- " [-7.7406e-01],\n",
- " [-1.3107e+00],\n",
- " [ 4.2693e-01],\n",
- " [-8.7382e-01],\n",
- " [-2.5915e-01],\n",
- " [ 1.5292e+00]],\n",
+ " [[ 1.8378e-03],\n",
+ " [ 7.1617e-01],\n",
+ " [ 1.9320e-01],\n",
+ " [-9.8246e-01],\n",
+ " [ 1.0930e+00],\n",
+ " [ 1.4183e+00],\n",
+ " [ 1.9863e-01],\n",
+ " [-1.1845e-01],\n",
+ " [ 1.3640e+00],\n",
+ " [ 8.7122e-01]],\n",
"\n",
- " [[-6.6223e-01],\n",
- " [-2.2870e-01],\n",
- " [-1.1778e-01],\n",
- " [ 1.1825e+00],\n",
- " [-1.1801e+00],\n",
- " [-2.1859e-01],\n",
- " [-1.6676e+00],\n",
- " [-1.0415e-01],\n",
- " [ 8.8033e-01],\n",
- " [-7.0019e-01]],\n",
+ " [[ 1.6613e+00],\n",
+ " [ 1.2155e-01],\n",
+ " [ 3.4827e-01],\n",
+ " [ 9.9064e-01],\n",
+ " [-9.4938e-01],\n",
+ " [ 4.7694e-01],\n",
+ " [ 5.2231e-01],\n",
+ " [ 5.8428e-01],\n",
+ " [ 4.5853e-02],\n",
+ " [-2.5305e+00]],\n",
"\n",
- " [[-1.9371e-01],\n",
- " [ 5.4381e-01],\n",
- " [-2.9687e-01],\n",
- " [ 6.8429e-01],\n",
- " [ 5.0528e-01],\n",
- " [-6.3122e-02],\n",
- " [ 2.4948e-02],\n",
- " [ 3.4935e-02],\n",
- " [-5.9903e-01],\n",
- " [ 2.9530e-01]],\n",
+ " [[-8.4262e-01],\n",
+ " [ 9.2893e-01],\n",
+ " [ 1.0124e+00],\n",
+ " [-1.6017e+00],\n",
+ " [-1.4961e-01],\n",
+ " [ 2.2560e+00],\n",
+ " [ 2.0985e-01],\n",
+ " [ 7.7839e-01],\n",
+ " [ 1.5581e+00],\n",
+ " [-2.3309e+00]],\n",
"\n",
- " [[-9.3742e-02],\n",
- " [ 5.5731e-01],\n",
- " [ 4.4727e-01],\n",
- " [-1.9633e+00],\n",
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- " [ 1.6627e-02],\n",
- " [ 2.7729e-01],\n",
- " [ 1.7569e-01],\n",
- " [ 1.2022e+00]],\n",
+ " [[ 1.5367e+00],\n",
+ " [-3.7147e-01],\n",
+ " [-2.3096e-01],\n",
+ " [ 1.1904e+00],\n",
+ " [ 1.9962e+00],\n",
+ " [-1.0334e-01],\n",
+ " [-6.0397e-01],\n",
+ " [ 1.0851e+00],\n",
+ " [-2.3377e-01],\n",
+ " [-7.0282e-01]],\n",
"\n",
- " [[ 2.4165e-02],\n",
- " [ 3.4443e-01],\n",
- " [-1.3817e+00],\n",
- " [-1.6941e+00],\n",
- " [ 5.7643e-01],\n",
- " [-3.3574e-01],\n",
- " [-8.5208e-04],\n",
- " [ 6.7266e-01],\n",
- " [ 2.4279e-01],\n",
- " [ 1.8059e+00]],\n",
+ " [[ 1.7610e+00],\n",
+ " [-1.3054e+00],\n",
+ " [ 1.6490e+00],\n",
+ " [-3.9569e-01],\n",
+ " [-1.5368e+00],\n",
+ " [-1.0189e+00],\n",
+ " [-1.9441e-02],\n",
+ " [ 9.1458e-01],\n",
+ " [ 1.2236e+00],\n",
+ " [ 8.6759e-01]],\n",
"\n",
- " [[ 1.5710e+00],\n",
- " [ 2.8216e+00],\n",
- " [-2.3268e-02],\n",
- " [-1.1153e+00],\n",
- " [-8.6641e-01],\n",
- " [ 5.0544e-01],\n",
- " [-3.7233e-02],\n",
- " [-2.8511e-01],\n",
- " [-2.3818e+00],\n",
- " [ 8.0363e-01]],\n",
+ " [[ 4.9696e-01],\n",
+ " [-1.0176e+00],\n",
+ " [ 2.7300e+00],\n",
+ " [-1.1193e+00],\n",
+ " [ 1.5149e+00],\n",
+ " [ 2.2174e+00],\n",
+ " [ 4.5604e-01],\n",
+ " [-1.0018e+00],\n",
+ " [ 6.1021e-01],\n",
+ " [-5.1552e-01]],\n",
"\n",
- " [[-2.4681e-01],\n",
- " [ 1.0006e+00],\n",
- " [ 1.9276e-01],\n",
- " [-7.3025e-01],\n",
- " [-1.0975e+00],\n",
- " [ 9.3319e-01],\n",
- " [-5.5379e-01],\n",
- " [-5.1401e-01],\n",
- " [-8.8545e-01],\n",
- " [ 4.6912e-01]]], dtype=torch.float64), 'label': tensor(7)}\n"
+ " [[ 2.3127e+00],\n",
+ " [-5.9054e-01],\n",
+ " [-1.1682e+00],\n",
+ " [-2.8864e-02],\n",
+ " [-1.8656e+00],\n",
+ " [-1.4874e+00],\n",
+ " [-1.7110e+00],\n",
+ " [ 8.5748e-01],\n",
+ " [-1.2645e+00],\n",
+ " [-3.9108e-01]]], dtype=torch.float64), 'label': tensor(3)}\n"
]
}
],
@@ -237,113 +259,10 @@
},
{
"cell_type": "code",
- "execution_count": 18,
+ "execution_count": 6,
"id": "e97239d5",
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Downloading http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz\n",
- "Downloading http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz to ./data/MNIST/MNIST/raw/train-images-idx3-ubyte.gz\n"
- ]
- },
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "81f14eed13584b959df99d123c11d53f",
- "version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
- " 0%| | 0/9912422 [00:00<?, ?it/s]"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Extracting ./data/MNIST/MNIST/raw/train-images-idx3-ubyte.gz to ./data/MNIST/MNIST/raw\n",
- "\n",
- "Downloading http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz\n",
- "Downloading http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz to ./data/MNIST/MNIST/raw/train-labels-idx1-ubyte.gz\n"
- ]
- },
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "35beff87bf47420fafba7e5a6301aaf9",
- "version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
- " 0%| | 0/28881 [00:00<?, ?it/s]"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Extracting ./data/MNIST/MNIST/raw/train-labels-idx1-ubyte.gz to ./data/MNIST/MNIST/raw\n",
- "\n",
- "Downloading http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz\n",
- "Downloading http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz to ./data/MNIST/MNIST/raw/t10k-images-idx3-ubyte.gz\n"
- ]
- },
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "7b5d6f41eef14f8a9ad29beae3acf62b",
- "version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
- " 0%| | 0/1648877 [00:00<?, ?it/s]"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Extracting ./data/MNIST/MNIST/raw/t10k-images-idx3-ubyte.gz to ./data/MNIST/MNIST/raw\n",
- "\n",
- "Downloading http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz\n",
- "Downloading http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz to ./data/MNIST/MNIST/raw/t10k-labels-idx1-ubyte.gz\n"
- ]
- },
- {
- "data": {
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "9e980b594b1942d68ab90d2255e2f42a",
- "version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
- " 0%| | 0/4542 [00:00<?, ?it/s]"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Extracting ./data/MNIST/MNIST/raw/t10k-labels-idx1-ubyte.gz to ./data/MNIST/MNIST/raw\n",
- "\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"# Use standard MNIST dataset\n",
"my_dataset = torchvision.datasets.MNIST(\n",
@@ -366,32 +285,990 @@
},
{
"cell_type": "code",
- "execution_count": 19,
+ "execution_count": 7,
"id": "067b8105",
"metadata": {},
"outputs": [
{
"data": {
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\n",
+ "application/javascript": [
+ "/* Put everything inside the global mpl namespace */\n",
+ "/* global mpl */\n",
+ "window.mpl = {};\n",
+ "\n",
+ "mpl.get_websocket_type = function () {\n",
+ " if (typeof WebSocket !== 'undefined') {\n",
+ " return WebSocket;\n",
+ " } else if (typeof MozWebSocket !== 'undefined') {\n",
+ " return MozWebSocket;\n",
+ " } else {\n",
+ " alert(\n",
+ " 'Your browser does not have WebSocket support. ' +\n",
+ " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+ " 'Firefox 4 and 5 are also supported but you ' +\n",
+ " 'have to enable WebSockets in about:config.'\n",
+ " );\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
+ " this.id = figure_id;\n",
+ "\n",
+ " this.ws = websocket;\n",
+ "\n",
+ " this.supports_binary = this.ws.binaryType !== undefined;\n",
+ "\n",
+ " if (!this.supports_binary) {\n",
+ " var warnings = document.getElementById('mpl-warnings');\n",
+ " if (warnings) {\n",
+ " warnings.style.display = 'block';\n",
+ " warnings.textContent =\n",
+ " 'This browser does not support binary websocket messages. ' +\n",
+ " 'Performance may be slow.';\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.imageObj = new Image();\n",
+ "\n",
+ " this.context = undefined;\n",
+ " this.message = undefined;\n",
+ " this.canvas = undefined;\n",
+ " this.rubberband_canvas = undefined;\n",
+ " this.rubberband_context = undefined;\n",
+ " this.format_dropdown = undefined;\n",
+ "\n",
+ " this.image_mode = 'full';\n",
+ "\n",
+ " this.root = document.createElement('div');\n",
+ " this.root.setAttribute('style', 'display: inline-block');\n",
+ " this._root_extra_style(this.root);\n",
+ "\n",
+ " parent_element.appendChild(this.root);\n",
+ "\n",
+ " this._init_header(this);\n",
+ " this._init_canvas(this);\n",
+ " this._init_toolbar(this);\n",
+ "\n",
+ " var fig = this;\n",
+ "\n",
+ " this.waiting = false;\n",
+ "\n",
+ " this.ws.onopen = function () {\n",
+ " fig.send_message('supports_binary', { value: fig.supports_binary });\n",
+ " fig.send_message('send_image_mode', {});\n",
+ " if (fig.ratio !== 1) {\n",
+ " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
+ " }\n",
+ " fig.send_message('refresh', {});\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onload = function () {\n",
+ " if (fig.image_mode === 'full') {\n",
+ " // Full images could contain transparency (where diff images\n",
+ " // almost always do), so we need to clear the canvas so that\n",
+ " // there is no ghosting.\n",
+ " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+ " }\n",
+ " fig.context.drawImage(fig.imageObj, 0, 0);\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onunload = function () {\n",
+ " fig.ws.close();\n",
+ " };\n",
+ "\n",
+ " this.ws.onmessage = this._make_on_message_function(this);\n",
+ "\n",
+ " this.ondownload = ondownload;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_header = function () {\n",
+ " var titlebar = document.createElement('div');\n",
+ " titlebar.classList =\n",
+ " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
+ " var titletext = document.createElement('div');\n",
+ " titletext.classList = 'ui-dialog-title';\n",
+ " titletext.setAttribute(\n",
+ " 'style',\n",
+ " 'width: 100%; text-align: center; padding: 3px;'\n",
+ " );\n",
+ " titlebar.appendChild(titletext);\n",
+ " this.root.appendChild(titlebar);\n",
+ " this.header = titletext;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
+ "\n",
+ "mpl.figure.prototype._init_canvas = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var canvas_div = (this.canvas_div = document.createElement('div'));\n",
+ " canvas_div.setAttribute(\n",
+ " 'style',\n",
+ " 'border: 1px solid #ddd;' +\n",
+ " 'box-sizing: content-box;' +\n",
+ " 'clear: both;' +\n",
+ " 'min-height: 1px;' +\n",
+ " 'min-width: 1px;' +\n",
+ " 'outline: 0;' +\n",
+ " 'overflow: hidden;' +\n",
+ " 'position: relative;' +\n",
+ " 'resize: both;'\n",
+ " );\n",
+ "\n",
+ " function on_keyboard_event_closure(name) {\n",
+ " return function (event) {\n",
+ " return fig.key_event(event, name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " canvas_div.addEventListener(\n",
+ " 'keydown',\n",
+ " on_keyboard_event_closure('key_press')\n",
+ " );\n",
+ " canvas_div.addEventListener(\n",
+ " 'keyup',\n",
+ " on_keyboard_event_closure('key_release')\n",
+ " );\n",
+ "\n",
+ " this._canvas_extra_style(canvas_div);\n",
+ " this.root.appendChild(canvas_div);\n",
+ "\n",
+ " var canvas = (this.canvas = document.createElement('canvas'));\n",
+ " canvas.classList.add('mpl-canvas');\n",
+ " canvas.setAttribute('style', 'box-sizing: content-box;');\n",
+ "\n",
+ " this.context = canvas.getContext('2d');\n",
+ "\n",
+ " var backingStore =\n",
+ " this.context.backingStorePixelRatio ||\n",
+ " this.context.webkitBackingStorePixelRatio ||\n",
+ " this.context.mozBackingStorePixelRatio ||\n",
+ " this.context.msBackingStorePixelRatio ||\n",
+ " this.context.oBackingStorePixelRatio ||\n",
+ " this.context.backingStorePixelRatio ||\n",
+ " 1;\n",
+ "\n",
+ " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+ "\n",
+ " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
+ " 'canvas'\n",
+ " ));\n",
+ " rubberband_canvas.setAttribute(\n",
+ " 'style',\n",
+ " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
+ " );\n",
+ "\n",
+ " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
+ " if (this.ResizeObserver === undefined) {\n",
+ " if (window.ResizeObserver !== undefined) {\n",
+ " this.ResizeObserver = window.ResizeObserver;\n",
+ " } else {\n",
+ " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
+ " this.ResizeObserver = obs.ResizeObserver;\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
+ " var nentries = entries.length;\n",
+ " for (var i = 0; i < nentries; i++) {\n",
+ " var entry = entries[i];\n",
+ " var width, height;\n",
+ " if (entry.contentBoxSize) {\n",
+ " if (entry.contentBoxSize instanceof Array) {\n",
+ " // Chrome 84 implements new version of spec.\n",
+ " width = entry.contentBoxSize[0].inlineSize;\n",
+ " height = entry.contentBoxSize[0].blockSize;\n",
+ " } else {\n",
+ " // Firefox implements old version of spec.\n",
+ " width = entry.contentBoxSize.inlineSize;\n",
+ " height = entry.contentBoxSize.blockSize;\n",
+ " }\n",
+ " } else {\n",
+ " // Chrome <84 implements even older version of spec.\n",
+ " width = entry.contentRect.width;\n",
+ " height = entry.contentRect.height;\n",
+ " }\n",
+ "\n",
+ " // Keep the size of the canvas and rubber band canvas in sync with\n",
+ " // the canvas container.\n",
+ " if (entry.devicePixelContentBoxSize) {\n",
+ " // Chrome 84 implements new version of spec.\n",
+ " canvas.setAttribute(\n",
+ " 'width',\n",
+ " entry.devicePixelContentBoxSize[0].inlineSize\n",
+ " );\n",
+ " canvas.setAttribute(\n",
+ " 'height',\n",
+ " entry.devicePixelContentBoxSize[0].blockSize\n",
+ " );\n",
+ " } else {\n",
+ " canvas.setAttribute('width', width * fig.ratio);\n",
+ " canvas.setAttribute('height', height * fig.ratio);\n",
+ " }\n",
+ " canvas.setAttribute(\n",
+ " 'style',\n",
+ " 'width: ' + width + 'px; height: ' + height + 'px;'\n",
+ " );\n",
+ "\n",
+ " rubberband_canvas.setAttribute('width', width);\n",
+ " rubberband_canvas.setAttribute('height', height);\n",
+ "\n",
+ " // And update the size in Python. We ignore the initial 0/0 size\n",
+ " // that occurs as the element is placed into the DOM, which should\n",
+ " // otherwise not happen due to the minimum size styling.\n",
+ " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
+ " fig.request_resize(width, height);\n",
+ " }\n",
+ " }\n",
+ " });\n",
+ " this.resizeObserverInstance.observe(canvas_div);\n",
+ "\n",
+ " function on_mouse_event_closure(name) {\n",
+ " return function (event) {\n",
+ " return fig.mouse_event(event, name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mousedown',\n",
+ " on_mouse_event_closure('button_press')\n",
+ " );\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseup',\n",
+ " on_mouse_event_closure('button_release')\n",
+ " );\n",
+ " // Throttle sequential mouse events to 1 every 20ms.\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mousemove',\n",
+ " on_mouse_event_closure('motion_notify')\n",
+ " );\n",
+ "\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseenter',\n",
+ " on_mouse_event_closure('figure_enter')\n",
+ " );\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseleave',\n",
+ " on_mouse_event_closure('figure_leave')\n",
+ " );\n",
+ "\n",
+ " canvas_div.addEventListener('wheel', function (event) {\n",
+ " if (event.deltaY < 0) {\n",
+ " event.step = 1;\n",
+ " } else {\n",
+ " event.step = -1;\n",
+ " }\n",
+ " on_mouse_event_closure('scroll')(event);\n",
+ " });\n",
+ "\n",
+ " canvas_div.appendChild(canvas);\n",
+ " canvas_div.appendChild(rubberband_canvas);\n",
+ "\n",
+ " this.rubberband_context = rubberband_canvas.getContext('2d');\n",
+ " this.rubberband_context.strokeStyle = '#000000';\n",
+ "\n",
+ " this._resize_canvas = function (width, height, forward) {\n",
+ " if (forward) {\n",
+ " canvas_div.style.width = width + 'px';\n",
+ " canvas_div.style.height = height + 'px';\n",
+ " }\n",
+ " };\n",
+ "\n",
+ " // Disable right mouse context menu.\n",
+ " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ " });\n",
+ "\n",
+ " function set_focus() {\n",
+ " canvas.focus();\n",
+ " canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " window.setTimeout(set_focus, 100);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var toolbar = document.createElement('div');\n",
+ " toolbar.classList = 'mpl-toolbar';\n",
+ " this.root.appendChild(toolbar);\n",
+ "\n",
+ " function on_click_closure(name) {\n",
+ " return function (_event) {\n",
+ " return fig.toolbar_button_onclick(name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " function on_mouseover_closure(tooltip) {\n",
+ " return function (event) {\n",
+ " if (!event.currentTarget.disabled) {\n",
+ " return fig.toolbar_button_onmouseover(tooltip);\n",
+ " }\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " fig.buttons = {};\n",
+ " var buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'mpl-button-group';\n",
+ " for (var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " /* Instead of a spacer, we start a new button group. */\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ " buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'mpl-button-group';\n",
+ " continue;\n",
+ " }\n",
+ "\n",
+ " var button = (fig.buttons[name] = document.createElement('button'));\n",
+ " button.classList = 'mpl-widget';\n",
+ " button.setAttribute('role', 'button');\n",
+ " button.setAttribute('aria-disabled', 'false');\n",
+ " button.addEventListener('click', on_click_closure(method_name));\n",
+ " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+ "\n",
+ " var icon_img = document.createElement('img');\n",
+ " icon_img.src = '_images/' + image + '.png';\n",
+ " icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
+ " icon_img.alt = tooltip;\n",
+ " button.appendChild(icon_img);\n",
+ "\n",
+ " buttonGroup.appendChild(button);\n",
+ " }\n",
+ "\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ "\n",
+ " var fmt_picker = document.createElement('select');\n",
+ " fmt_picker.classList = 'mpl-widget';\n",
+ " toolbar.appendChild(fmt_picker);\n",
+ " this.format_dropdown = fmt_picker;\n",
+ "\n",
+ " for (var ind in mpl.extensions) {\n",
+ " var fmt = mpl.extensions[ind];\n",
+ " var option = document.createElement('option');\n",
+ " option.selected = fmt === mpl.default_extension;\n",
+ " option.innerHTML = fmt;\n",
+ " fmt_picker.appendChild(option);\n",
+ " }\n",
+ "\n",
+ " var status_bar = document.createElement('span');\n",
+ " status_bar.classList = 'mpl-message';\n",
+ " toolbar.appendChild(status_bar);\n",
+ " this.message = status_bar;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
+ " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+ " // which will in turn request a refresh of the image.\n",
+ " this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.send_message = function (type, properties) {\n",
+ " properties['type'] = type;\n",
+ " properties['figure_id'] = this.id;\n",
+ " this.ws.send(JSON.stringify(properties));\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.send_draw_message = function () {\n",
+ " if (!this.waiting) {\n",
+ " this.waiting = true;\n",
+ " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+ " var format_dropdown = fig.format_dropdown;\n",
+ " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+ " fig.ondownload(fig, format);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
+ " var size = msg['size'];\n",
+ " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
+ " fig._resize_canvas(size[0], size[1], msg['forward']);\n",
+ " fig.send_message('refresh', {});\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
+ " var x0 = msg['x0'] / fig.ratio;\n",
+ " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
+ " var x1 = msg['x1'] / fig.ratio;\n",
+ " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
+ " x0 = Math.floor(x0) + 0.5;\n",
+ " y0 = Math.floor(y0) + 0.5;\n",
+ " x1 = Math.floor(x1) + 0.5;\n",
+ " y1 = Math.floor(y1) + 0.5;\n",
+ " var min_x = Math.min(x0, x1);\n",
+ " var min_y = Math.min(y0, y1);\n",
+ " var width = Math.abs(x1 - x0);\n",
+ " var height = Math.abs(y1 - y0);\n",
+ "\n",
+ " fig.rubberband_context.clearRect(\n",
+ " 0,\n",
+ " 0,\n",
+ " fig.canvas.width / fig.ratio,\n",
+ " fig.canvas.height / fig.ratio\n",
+ " );\n",
+ "\n",
+ " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
+ " // Updates the figure title.\n",
+ " fig.header.textContent = msg['label'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
+ " var cursor = msg['cursor'];\n",
+ " switch (cursor) {\n",
+ " case 0:\n",
+ " cursor = 'pointer';\n",
+ " break;\n",
+ " case 1:\n",
+ " cursor = 'default';\n",
+ " break;\n",
+ " case 2:\n",
+ " cursor = 'crosshair';\n",
+ " break;\n",
+ " case 3:\n",
+ " cursor = 'move';\n",
+ " break;\n",
+ " }\n",
+ " fig.rubberband_canvas.style.cursor = cursor;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
+ " fig.message.textContent = msg['message'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
+ " // Request the server to send over a new figure.\n",
+ " fig.send_draw_message();\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
+ " fig.image_mode = msg['mode'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
+ " for (var key in msg) {\n",
+ " if (!(key in fig.buttons)) {\n",
+ " continue;\n",
+ " }\n",
+ " fig.buttons[key].disabled = !msg[key];\n",
+ " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
+ " if (msg['mode'] === 'PAN') {\n",
+ " fig.buttons['Pan'].classList.add('active');\n",
+ " fig.buttons['Zoom'].classList.remove('active');\n",
+ " } else if (msg['mode'] === 'ZOOM') {\n",
+ " fig.buttons['Pan'].classList.remove('active');\n",
+ " fig.buttons['Zoom'].classList.add('active');\n",
+ " } else {\n",
+ " fig.buttons['Pan'].classList.remove('active');\n",
+ " fig.buttons['Zoom'].classList.remove('active');\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function () {\n",
+ " // Called whenever the canvas gets updated.\n",
+ " this.send_message('ack', {});\n",
+ "};\n",
+ "\n",
+ "// A function to construct a web socket function for onmessage handling.\n",
+ "// Called in the figure constructor.\n",
+ "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
+ " return function socket_on_message(evt) {\n",
+ " if (evt.data instanceof Blob) {\n",
+ " /* FIXME: We get \"Resource interpreted as Image but\n",
+ " * transferred with MIME type text/plain:\" errors on\n",
+ " * Chrome. But how to set the MIME type? It doesn't seem\n",
+ " * to be part of the websocket stream */\n",
+ " evt.data.type = 'image/png';\n",
+ "\n",
+ " /* Free the memory for the previous frames */\n",
+ " if (fig.imageObj.src) {\n",
+ " (window.URL || window.webkitURL).revokeObjectURL(\n",
+ " fig.imageObj.src\n",
+ " );\n",
+ " }\n",
+ "\n",
+ " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+ " evt.data\n",
+ " );\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " } else if (\n",
+ " typeof evt.data === 'string' &&\n",
+ " evt.data.slice(0, 21) === 'data:image/png;base64'\n",
+ " ) {\n",
+ " fig.imageObj.src = evt.data;\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " var msg = JSON.parse(evt.data);\n",
+ " var msg_type = msg['type'];\n",
+ "\n",
+ " // Call the \"handle_{type}\" callback, which takes\n",
+ " // the figure and JSON message as its only arguments.\n",
+ " try {\n",
+ " var callback = fig['handle_' + msg_type];\n",
+ " } catch (e) {\n",
+ " console.log(\n",
+ " \"No handler for the '\" + msg_type + \"' message type: \",\n",
+ " msg\n",
+ " );\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " if (callback) {\n",
+ " try {\n",
+ " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+ " callback(fig, msg);\n",
+ " } catch (e) {\n",
+ " console.log(\n",
+ " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
+ " e,\n",
+ " e.stack,\n",
+ " msg\n",
+ " );\n",
+ " }\n",
+ " }\n",
+ " };\n",
+ "};\n",
+ "\n",
+ "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+ "mpl.findpos = function (e) {\n",
+ " //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+ " var targ;\n",
+ " if (!e) {\n",
+ " e = window.event;\n",
+ " }\n",
+ " if (e.target) {\n",
+ " targ = e.target;\n",
+ " } else if (e.srcElement) {\n",
+ " targ = e.srcElement;\n",
+ " }\n",
+ " if (targ.nodeType === 3) {\n",
+ " // defeat Safari bug\n",
+ " targ = targ.parentNode;\n",
+ " }\n",
+ "\n",
+ " // pageX,Y are the mouse positions relative to the document\n",
+ " var boundingRect = targ.getBoundingClientRect();\n",
+ " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
+ " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
+ "\n",
+ " return { x: x, y: y };\n",
+ "};\n",
+ "\n",
+ "/*\n",
+ " * return a copy of an object with only non-object keys\n",
+ " * we need this to avoid circular references\n",
+ " * http://stackoverflow.com/a/24161582/3208463\n",
+ " */\n",
+ "function simpleKeys(original) {\n",
+ " return Object.keys(original).reduce(function (obj, key) {\n",
+ " if (typeof original[key] !== 'object') {\n",
+ " obj[key] = original[key];\n",
+ " }\n",
+ " return obj;\n",
+ " }, {});\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.mouse_event = function (event, name) {\n",
+ " var canvas_pos = mpl.findpos(event);\n",
+ "\n",
+ " if (name === 'button_press') {\n",
+ " this.canvas.focus();\n",
+ " this.canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " var x = canvas_pos.x * this.ratio;\n",
+ " var y = canvas_pos.y * this.ratio;\n",
+ "\n",
+ " this.send_message(name, {\n",
+ " x: x,\n",
+ " y: y,\n",
+ " button: event.button,\n",
+ " step: event.step,\n",
+ " guiEvent: simpleKeys(event),\n",
+ " });\n",
+ "\n",
+ " /* This prevents the web browser from automatically changing to\n",
+ " * the text insertion cursor when the button is pressed. We want\n",
+ " * to control all of the cursor setting manually through the\n",
+ " * 'cursor' event from matplotlib */\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
+ " // Handle any extra behaviour associated with a key event\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.key_event = function (event, name) {\n",
+ " // Prevent repeat events\n",
+ " if (name === 'key_press') {\n",
+ " if (event.which === this._key) {\n",
+ " return;\n",
+ " } else {\n",
+ " this._key = event.which;\n",
+ " }\n",
+ " }\n",
+ " if (name === 'key_release') {\n",
+ " this._key = null;\n",
+ " }\n",
+ "\n",
+ " var value = '';\n",
+ " if (event.ctrlKey && event.which !== 17) {\n",
+ " value += 'ctrl+';\n",
+ " }\n",
+ " if (event.altKey && event.which !== 18) {\n",
+ " value += 'alt+';\n",
+ " }\n",
+ " if (event.shiftKey && event.which !== 16) {\n",
+ " value += 'shift+';\n",
+ " }\n",
+ "\n",
+ " value += 'k';\n",
+ " value += event.which.toString();\n",
+ "\n",
+ " this._key_event_extra(event, name);\n",
+ "\n",
+ " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
+ " return false;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
+ " if (name === 'download') {\n",
+ " this.handle_save(this, null);\n",
+ " } else {\n",
+ " this.send_message('toolbar_button', { name: name });\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
+ " this.message.textContent = tooltip;\n",
+ "};\n",
+ "\n",
+ "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
+ "// prettier-ignore\n",
+ "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
+ "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+ "\n",
+ "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
+ "\n",
+ "mpl.default_extension = \"png\";/* global mpl */\n",
+ "\n",
+ "var comm_websocket_adapter = function (comm) {\n",
+ " // Create a \"websocket\"-like object which calls the given IPython comm\n",
+ " // object with the appropriate methods. Currently this is a non binary\n",
+ " // socket, so there is still some room for performance tuning.\n",
+ " var ws = {};\n",
+ "\n",
+ " ws.close = function () {\n",
+ " comm.close();\n",
+ " };\n",
+ " ws.send = function (m) {\n",
+ " //console.log('sending', m);\n",
+ " comm.send(m);\n",
+ " };\n",
+ " // Register the callback with on_msg.\n",
+ " comm.on_msg(function (msg) {\n",
+ " //console.log('receiving', msg['content']['data'], msg);\n",
+ " // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
+ " ws.onmessage(msg['content']['data']);\n",
+ " });\n",
+ " return ws;\n",
+ "};\n",
+ "\n",
+ "mpl.mpl_figure_comm = function (comm, msg) {\n",
+ " // This is the function which gets called when the mpl process\n",
+ " // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+ "\n",
+ " var id = msg.content.data.id;\n",
+ " // Get hold of the div created by the display call when the Comm\n",
+ " // socket was opened in Python.\n",
+ " var element = document.getElementById(id);\n",
+ " var ws_proxy = comm_websocket_adapter(comm);\n",
+ "\n",
+ " function ondownload(figure, _format) {\n",
+ " window.open(figure.canvas.toDataURL());\n",
+ " }\n",
+ "\n",
+ " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
+ "\n",
+ " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+ " // web socket which is closed, not our websocket->open comm proxy.\n",
+ " ws_proxy.onopen();\n",
+ "\n",
+ " fig.parent_element = element;\n",
+ " fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+ " if (!fig.cell_info) {\n",
+ " console.error('Failed to find cell for figure', id, fig);\n",
+ " return;\n",
+ " }\n",
+ " fig.cell_info[0].output_area.element.on(\n",
+ " 'cleared',\n",
+ " { fig: fig },\n",
+ " fig._remove_fig_handler\n",
+ " );\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
+ " var width = fig.canvas.width / fig.ratio;\n",
+ " fig.cell_info[0].output_area.element.off(\n",
+ " 'cleared',\n",
+ " fig._remove_fig_handler\n",
+ " );\n",
+ " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
+ "\n",
+ " // Update the output cell to use the data from the current canvas.\n",
+ " fig.push_to_output();\n",
+ " var dataURL = fig.canvas.toDataURL();\n",
+ " // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+ " // the notebook keyboard shortcuts fail.\n",
+ " IPython.keyboard_manager.enable();\n",
+ " fig.parent_element.innerHTML =\n",
+ " '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ " fig.close_ws(fig, msg);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
+ " fig.send_message('closing', msg);\n",
+ " // fig.ws.close()\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
+ " // Turn the data on the canvas into data in the output cell.\n",
+ " var width = this.canvas.width / this.ratio;\n",
+ " var dataURL = this.canvas.toDataURL();\n",
+ " this.cell_info[1]['text/html'] =\n",
+ " '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function () {\n",
+ " // Tell IPython that the notebook contents must change.\n",
+ " IPython.notebook.set_dirty(true);\n",
+ " this.send_message('ack', {});\n",
+ " var fig = this;\n",
+ " // Wait a second, then push the new image to the DOM so\n",
+ " // that it is saved nicely (might be nice to debounce this).\n",
+ " setTimeout(function () {\n",
+ " fig.push_to_output();\n",
+ " }, 1000);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var toolbar = document.createElement('div');\n",
+ " toolbar.classList = 'btn-toolbar';\n",
+ " this.root.appendChild(toolbar);\n",
+ "\n",
+ " function on_click_closure(name) {\n",
+ " return function (_event) {\n",
+ " return fig.toolbar_button_onclick(name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " function on_mouseover_closure(tooltip) {\n",
+ " return function (event) {\n",
+ " if (!event.currentTarget.disabled) {\n",
+ " return fig.toolbar_button_onmouseover(tooltip);\n",
+ " }\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " fig.buttons = {};\n",
+ " var buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'btn-group';\n",
+ " var button;\n",
+ " for (var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " /* Instead of a spacer, we start a new button group. */\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ " buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'btn-group';\n",
+ " continue;\n",
+ " }\n",
+ "\n",
+ " button = fig.buttons[name] = document.createElement('button');\n",
+ " button.classList = 'btn btn-default';\n",
+ " button.href = '#';\n",
+ " button.title = name;\n",
+ " button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
+ " button.addEventListener('click', on_click_closure(method_name));\n",
+ " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+ " buttonGroup.appendChild(button);\n",
+ " }\n",
+ "\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ "\n",
+ " // Add the status bar.\n",
+ " var status_bar = document.createElement('span');\n",
+ " status_bar.classList = 'mpl-message pull-right';\n",
+ " toolbar.appendChild(status_bar);\n",
+ " this.message = status_bar;\n",
+ "\n",
+ " // Add the close button to the window.\n",
+ " var buttongrp = document.createElement('div');\n",
+ " buttongrp.classList = 'btn-group inline pull-right';\n",
+ " button = document.createElement('button');\n",
+ " button.classList = 'btn btn-mini btn-primary';\n",
+ " button.href = '#';\n",
+ " button.title = 'Stop Interaction';\n",
+ " button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
+ " button.addEventListener('click', function (_evt) {\n",
+ " fig.handle_close(fig, {});\n",
+ " });\n",
+ " button.addEventListener(\n",
+ " 'mouseover',\n",
+ " on_mouseover_closure('Stop Interaction')\n",
+ " );\n",
+ " buttongrp.appendChild(button);\n",
+ " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
+ " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
+ " var fig = event.data.fig;\n",
+ " if (event.target !== this) {\n",
+ " // Ignore bubbled events from children.\n",
+ " return;\n",
+ " }\n",
+ " fig.close_ws(fig, {});\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function (el) {\n",
+ " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
+ " // this is important to make the div 'focusable\n",
+ " el.setAttribute('tabindex', 0);\n",
+ " // reach out to IPython and tell the keyboard manager to turn it's self\n",
+ " // off when our div gets focus\n",
+ "\n",
+ " // location in version 3\n",
+ " if (IPython.notebook.keyboard_manager) {\n",
+ " IPython.notebook.keyboard_manager.register_events(el);\n",
+ " } else {\n",
+ " // location in version 2\n",
+ " IPython.keyboard_manager.register_events(el);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
+ " var manager = IPython.notebook.keyboard_manager;\n",
+ " if (!manager) {\n",
+ " manager = IPython.keyboard_manager;\n",
+ " }\n",
+ "\n",
+ " // Check for shift+enter\n",
+ " if (event.shiftKey && event.which === 13) {\n",
+ " this.canvas_div.blur();\n",
+ " // select the cell after this one\n",
+ " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
+ " IPython.notebook.select(index + 1);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+ " fig.ondownload(fig, null);\n",
+ "};\n",
+ "\n",
+ "mpl.find_output_cell = function (html_output) {\n",
+ " // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+ " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+ " // IPython event is triggered only after the cells have been serialised, which for\n",
+ " // our purposes (turning an active figure into a static one), is too late.\n",
+ " var cells = IPython.notebook.get_cells();\n",
+ " var ncells = cells.length;\n",
+ " for (var i = 0; i < ncells; i++) {\n",
+ " var cell = cells[i];\n",
+ " if (cell.cell_type === 'code') {\n",
+ " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
+ " var data = cell.output_area.outputs[j];\n",
+ " if (data.data) {\n",
+ " // IPython >= 3 moved mimebundle to data attribute of output\n",
+ " data = data.data;\n",
+ " }\n",
+ " if (data['text/html'] === html_output) {\n",
+ " return [cell, data, j];\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "// Register the function which deals with the matplotlib target/channel.\n",
+ "// The kernel may be null if the page has been refreshed.\n",
+ "if (IPython.notebook.kernel !== null) {\n",
+ " IPython.notebook.kernel.comm_manager.register_target(\n",
+ " 'matplotlib',\n",
+ " mpl.mpl_figure_comm\n",
+ " );\n",
+ "}\n"
+ ],
"text/plain": [
- "<Figure size 1440x1728 with 25 Axes>"
+ "<IPython.core.display.Javascript object>"
]
},
- "metadata": {
- "needs_background": "light"
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
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\" width=\"1000\">"
+ ],
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ]
},
+ "metadata": {},
"output_type": "display_data"
}
],
"source": [
- "fig, ax = plt.subplots(nrows=5, ncols=5, figsize=(20,24))\n",
+ "fig, ax = plt.subplots(nrows=5, ncols=5, figsize=(10,10))\n",
"for i in range(5):\n",
" for j in range(5):\n",
" idx = i*5+j\n",
" img = my_dataset[idx][0]\n",
" label = my_dataset[idx][1]\n",
" ax[i, j].imshow(img[0,...].detach().cpu().numpy())\n",
- " ax[i, j].set(title=f\"Image {idx}, true label {label}\")\n",
+ " ax[i, j].set(title=f\"Im. {idx}, true {label}\")\n",
" ax[i, j].set_xticklabels([])\n",
" ax[i, j].set_yticklabels([])\n",
"plt.subplots_adjust(hspace=0.2,wspace=0)\n",
@@ -412,7 +1289,7 @@
},
{
"cell_type": "code",
- "execution_count": 20,
+ "execution_count": 8,
"id": "d908ef86",
"metadata": {},
"outputs": [],
@@ -522,7 +1399,7 @@
},
{
"cell_type": "code",
- "execution_count": 21,
+ "execution_count": 9,
"id": "988e1979",
"metadata": {},
"outputs": [],
@@ -543,32 +1420,24 @@
},
{
"cell_type": "code",
- "execution_count": 22,
+ "execution_count": 10,
"id": "d15d655d",
"metadata": {},
"outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "/home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages/torch/nn/functional.py:718: UserWarning: Named tensors and all their associated APIs are an experimental feature and subject to change. Please do not use them for anything important until they are released as stable. (Triggered internally at /opt/conda/conda-bld/pytorch_1623448224956/work/c10/core/TensorImpl.h:1156.)\n",
- " return torch.max_pool2d(input, kernel_size, stride, padding, dilation, ceil_mode)\n"
- ]
- },
{
"name": "stdout",
"output_type": "stream",
"text": [
- "Epoch 0/10: average loss 0.36116\n",
- "Epoch 1/10: average loss 0.10886\n",
- "Epoch 2/10: average loss 0.07327\n",
- "Epoch 3/10: average loss 0.05648\n",
- "Epoch 4/10: average loss 0.04617\n",
- "Epoch 5/10: average loss 0.03912\n",
- "Epoch 6/10: average loss 0.03184\n",
- "Epoch 7/10: average loss 0.02736\n",
- "Epoch 8/10: average loss 0.02388\n",
- "Epoch 9/10: average loss 0.02053\n"
+ "Epoch 0/10: average loss 0.35421\n",
+ "Epoch 1/10: average loss 0.10931\n",
+ "Epoch 2/10: average loss 0.07470\n",
+ "Epoch 3/10: average loss 0.05767\n",
+ "Epoch 4/10: average loss 0.04682\n",
+ "Epoch 5/10: average loss 0.03882\n",
+ "Epoch 6/10: average loss 0.03285\n",
+ "Epoch 7/10: average loss 0.02714\n",
+ "Epoch 8/10: average loss 0.02437\n",
+ "Epoch 9/10: average loss 0.02176\n"
]
}
],
@@ -627,7 +1496,7 @@
},
{
"cell_type": "code",
- "execution_count": 23,
+ "execution_count": 11,
"id": "09646d29",
"metadata": {},
"outputs": [],
@@ -652,7 +1521,7 @@
},
{
"cell_type": "code",
- "execution_count": 26,
+ "execution_count": 12,
"id": "7a06a4c0",
"metadata": {
"scrolled": false
@@ -660,19 +1529,977 @@
"outputs": [
{
"data": {
- "image/png": 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\n",
+ "application/javascript": [
+ "/* Put everything inside the global mpl namespace */\n",
+ "/* global mpl */\n",
+ "window.mpl = {};\n",
+ "\n",
+ "mpl.get_websocket_type = function () {\n",
+ " if (typeof WebSocket !== 'undefined') {\n",
+ " return WebSocket;\n",
+ " } else if (typeof MozWebSocket !== 'undefined') {\n",
+ " return MozWebSocket;\n",
+ " } else {\n",
+ " alert(\n",
+ " 'Your browser does not have WebSocket support. ' +\n",
+ " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+ " 'Firefox 4 and 5 are also supported but you ' +\n",
+ " 'have to enable WebSockets in about:config.'\n",
+ " );\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
+ " this.id = figure_id;\n",
+ "\n",
+ " this.ws = websocket;\n",
+ "\n",
+ " this.supports_binary = this.ws.binaryType !== undefined;\n",
+ "\n",
+ " if (!this.supports_binary) {\n",
+ " var warnings = document.getElementById('mpl-warnings');\n",
+ " if (warnings) {\n",
+ " warnings.style.display = 'block';\n",
+ " warnings.textContent =\n",
+ " 'This browser does not support binary websocket messages. ' +\n",
+ " 'Performance may be slow.';\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.imageObj = new Image();\n",
+ "\n",
+ " this.context = undefined;\n",
+ " this.message = undefined;\n",
+ " this.canvas = undefined;\n",
+ " this.rubberband_canvas = undefined;\n",
+ " this.rubberband_context = undefined;\n",
+ " this.format_dropdown = undefined;\n",
+ "\n",
+ " this.image_mode = 'full';\n",
+ "\n",
+ " this.root = document.createElement('div');\n",
+ " this.root.setAttribute('style', 'display: inline-block');\n",
+ " this._root_extra_style(this.root);\n",
+ "\n",
+ " parent_element.appendChild(this.root);\n",
+ "\n",
+ " this._init_header(this);\n",
+ " this._init_canvas(this);\n",
+ " this._init_toolbar(this);\n",
+ "\n",
+ " var fig = this;\n",
+ "\n",
+ " this.waiting = false;\n",
+ "\n",
+ " this.ws.onopen = function () {\n",
+ " fig.send_message('supports_binary', { value: fig.supports_binary });\n",
+ " fig.send_message('send_image_mode', {});\n",
+ " if (fig.ratio !== 1) {\n",
+ " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
+ " }\n",
+ " fig.send_message('refresh', {});\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onload = function () {\n",
+ " if (fig.image_mode === 'full') {\n",
+ " // Full images could contain transparency (where diff images\n",
+ " // almost always do), so we need to clear the canvas so that\n",
+ " // there is no ghosting.\n",
+ " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+ " }\n",
+ " fig.context.drawImage(fig.imageObj, 0, 0);\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onunload = function () {\n",
+ " fig.ws.close();\n",
+ " };\n",
+ "\n",
+ " this.ws.onmessage = this._make_on_message_function(this);\n",
+ "\n",
+ " this.ondownload = ondownload;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_header = function () {\n",
+ " var titlebar = document.createElement('div');\n",
+ " titlebar.classList =\n",
+ " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
+ " var titletext = document.createElement('div');\n",
+ " titletext.classList = 'ui-dialog-title';\n",
+ " titletext.setAttribute(\n",
+ " 'style',\n",
+ " 'width: 100%; text-align: center; padding: 3px;'\n",
+ " );\n",
+ " titlebar.appendChild(titletext);\n",
+ " this.root.appendChild(titlebar);\n",
+ " this.header = titletext;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
+ "\n",
+ "mpl.figure.prototype._init_canvas = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var canvas_div = (this.canvas_div = document.createElement('div'));\n",
+ " canvas_div.setAttribute(\n",
+ " 'style',\n",
+ " 'border: 1px solid #ddd;' +\n",
+ " 'box-sizing: content-box;' +\n",
+ " 'clear: both;' +\n",
+ " 'min-height: 1px;' +\n",
+ " 'min-width: 1px;' +\n",
+ " 'outline: 0;' +\n",
+ " 'overflow: hidden;' +\n",
+ " 'position: relative;' +\n",
+ " 'resize: both;'\n",
+ " );\n",
+ "\n",
+ " function on_keyboard_event_closure(name) {\n",
+ " return function (event) {\n",
+ " return fig.key_event(event, name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " canvas_div.addEventListener(\n",
+ " 'keydown',\n",
+ " on_keyboard_event_closure('key_press')\n",
+ " );\n",
+ " canvas_div.addEventListener(\n",
+ " 'keyup',\n",
+ " on_keyboard_event_closure('key_release')\n",
+ " );\n",
+ "\n",
+ " this._canvas_extra_style(canvas_div);\n",
+ " this.root.appendChild(canvas_div);\n",
+ "\n",
+ " var canvas = (this.canvas = document.createElement('canvas'));\n",
+ " canvas.classList.add('mpl-canvas');\n",
+ " canvas.setAttribute('style', 'box-sizing: content-box;');\n",
+ "\n",
+ " this.context = canvas.getContext('2d');\n",
+ "\n",
+ " var backingStore =\n",
+ " this.context.backingStorePixelRatio ||\n",
+ " this.context.webkitBackingStorePixelRatio ||\n",
+ " this.context.mozBackingStorePixelRatio ||\n",
+ " this.context.msBackingStorePixelRatio ||\n",
+ " this.context.oBackingStorePixelRatio ||\n",
+ " this.context.backingStorePixelRatio ||\n",
+ " 1;\n",
+ "\n",
+ " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+ "\n",
+ " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
+ " 'canvas'\n",
+ " ));\n",
+ " rubberband_canvas.setAttribute(\n",
+ " 'style',\n",
+ " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
+ " );\n",
+ "\n",
+ " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
+ " if (this.ResizeObserver === undefined) {\n",
+ " if (window.ResizeObserver !== undefined) {\n",
+ " this.ResizeObserver = window.ResizeObserver;\n",
+ " } else {\n",
+ " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
+ " this.ResizeObserver = obs.ResizeObserver;\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
+ " var nentries = entries.length;\n",
+ " for (var i = 0; i < nentries; i++) {\n",
+ " var entry = entries[i];\n",
+ " var width, height;\n",
+ " if (entry.contentBoxSize) {\n",
+ " if (entry.contentBoxSize instanceof Array) {\n",
+ " // Chrome 84 implements new version of spec.\n",
+ " width = entry.contentBoxSize[0].inlineSize;\n",
+ " height = entry.contentBoxSize[0].blockSize;\n",
+ " } else {\n",
+ " // Firefox implements old version of spec.\n",
+ " width = entry.contentBoxSize.inlineSize;\n",
+ " height = entry.contentBoxSize.blockSize;\n",
+ " }\n",
+ " } else {\n",
+ " // Chrome <84 implements even older version of spec.\n",
+ " width = entry.contentRect.width;\n",
+ " height = entry.contentRect.height;\n",
+ " }\n",
+ "\n",
+ " // Keep the size of the canvas and rubber band canvas in sync with\n",
+ " // the canvas container.\n",
+ " if (entry.devicePixelContentBoxSize) {\n",
+ " // Chrome 84 implements new version of spec.\n",
+ " canvas.setAttribute(\n",
+ " 'width',\n",
+ " entry.devicePixelContentBoxSize[0].inlineSize\n",
+ " );\n",
+ " canvas.setAttribute(\n",
+ " 'height',\n",
+ " entry.devicePixelContentBoxSize[0].blockSize\n",
+ " );\n",
+ " } else {\n",
+ " canvas.setAttribute('width', width * fig.ratio);\n",
+ " canvas.setAttribute('height', height * fig.ratio);\n",
+ " }\n",
+ " canvas.setAttribute(\n",
+ " 'style',\n",
+ " 'width: ' + width + 'px; height: ' + height + 'px;'\n",
+ " );\n",
+ "\n",
+ " rubberband_canvas.setAttribute('width', width);\n",
+ " rubberband_canvas.setAttribute('height', height);\n",
+ "\n",
+ " // And update the size in Python. We ignore the initial 0/0 size\n",
+ " // that occurs as the element is placed into the DOM, which should\n",
+ " // otherwise not happen due to the minimum size styling.\n",
+ " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
+ " fig.request_resize(width, height);\n",
+ " }\n",
+ " }\n",
+ " });\n",
+ " this.resizeObserverInstance.observe(canvas_div);\n",
+ "\n",
+ " function on_mouse_event_closure(name) {\n",
+ " return function (event) {\n",
+ " return fig.mouse_event(event, name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mousedown',\n",
+ " on_mouse_event_closure('button_press')\n",
+ " );\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseup',\n",
+ " on_mouse_event_closure('button_release')\n",
+ " );\n",
+ " // Throttle sequential mouse events to 1 every 20ms.\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mousemove',\n",
+ " on_mouse_event_closure('motion_notify')\n",
+ " );\n",
+ "\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseenter',\n",
+ " on_mouse_event_closure('figure_enter')\n",
+ " );\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseleave',\n",
+ " on_mouse_event_closure('figure_leave')\n",
+ " );\n",
+ "\n",
+ " canvas_div.addEventListener('wheel', function (event) {\n",
+ " if (event.deltaY < 0) {\n",
+ " event.step = 1;\n",
+ " } else {\n",
+ " event.step = -1;\n",
+ " }\n",
+ " on_mouse_event_closure('scroll')(event);\n",
+ " });\n",
+ "\n",
+ " canvas_div.appendChild(canvas);\n",
+ " canvas_div.appendChild(rubberband_canvas);\n",
+ "\n",
+ " this.rubberband_context = rubberband_canvas.getContext('2d');\n",
+ " this.rubberband_context.strokeStyle = '#000000';\n",
+ "\n",
+ " this._resize_canvas = function (width, height, forward) {\n",
+ " if (forward) {\n",
+ " canvas_div.style.width = width + 'px';\n",
+ " canvas_div.style.height = height + 'px';\n",
+ " }\n",
+ " };\n",
+ "\n",
+ " // Disable right mouse context menu.\n",
+ " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ " });\n",
+ "\n",
+ " function set_focus() {\n",
+ " canvas.focus();\n",
+ " canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " window.setTimeout(set_focus, 100);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var toolbar = document.createElement('div');\n",
+ " toolbar.classList = 'mpl-toolbar';\n",
+ " this.root.appendChild(toolbar);\n",
+ "\n",
+ " function on_click_closure(name) {\n",
+ " return function (_event) {\n",
+ " return fig.toolbar_button_onclick(name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " function on_mouseover_closure(tooltip) {\n",
+ " return function (event) {\n",
+ " if (!event.currentTarget.disabled) {\n",
+ " return fig.toolbar_button_onmouseover(tooltip);\n",
+ " }\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " fig.buttons = {};\n",
+ " var buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'mpl-button-group';\n",
+ " for (var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " /* Instead of a spacer, we start a new button group. */\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ " buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'mpl-button-group';\n",
+ " continue;\n",
+ " }\n",
+ "\n",
+ " var button = (fig.buttons[name] = document.createElement('button'));\n",
+ " button.classList = 'mpl-widget';\n",
+ " button.setAttribute('role', 'button');\n",
+ " button.setAttribute('aria-disabled', 'false');\n",
+ " button.addEventListener('click', on_click_closure(method_name));\n",
+ " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+ "\n",
+ " var icon_img = document.createElement('img');\n",
+ " icon_img.src = '_images/' + image + '.png';\n",
+ " icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
+ " icon_img.alt = tooltip;\n",
+ " button.appendChild(icon_img);\n",
+ "\n",
+ " buttonGroup.appendChild(button);\n",
+ " }\n",
+ "\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ "\n",
+ " var fmt_picker = document.createElement('select');\n",
+ " fmt_picker.classList = 'mpl-widget';\n",
+ " toolbar.appendChild(fmt_picker);\n",
+ " this.format_dropdown = fmt_picker;\n",
+ "\n",
+ " for (var ind in mpl.extensions) {\n",
+ " var fmt = mpl.extensions[ind];\n",
+ " var option = document.createElement('option');\n",
+ " option.selected = fmt === mpl.default_extension;\n",
+ " option.innerHTML = fmt;\n",
+ " fmt_picker.appendChild(option);\n",
+ " }\n",
+ "\n",
+ " var status_bar = document.createElement('span');\n",
+ " status_bar.classList = 'mpl-message';\n",
+ " toolbar.appendChild(status_bar);\n",
+ " this.message = status_bar;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
+ " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+ " // which will in turn request a refresh of the image.\n",
+ " this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.send_message = function (type, properties) {\n",
+ " properties['type'] = type;\n",
+ " properties['figure_id'] = this.id;\n",
+ " this.ws.send(JSON.stringify(properties));\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.send_draw_message = function () {\n",
+ " if (!this.waiting) {\n",
+ " this.waiting = true;\n",
+ " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+ " var format_dropdown = fig.format_dropdown;\n",
+ " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+ " fig.ondownload(fig, format);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
+ " var size = msg['size'];\n",
+ " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
+ " fig._resize_canvas(size[0], size[1], msg['forward']);\n",
+ " fig.send_message('refresh', {});\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
+ " var x0 = msg['x0'] / fig.ratio;\n",
+ " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
+ " var x1 = msg['x1'] / fig.ratio;\n",
+ " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
+ " x0 = Math.floor(x0) + 0.5;\n",
+ " y0 = Math.floor(y0) + 0.5;\n",
+ " x1 = Math.floor(x1) + 0.5;\n",
+ " y1 = Math.floor(y1) + 0.5;\n",
+ " var min_x = Math.min(x0, x1);\n",
+ " var min_y = Math.min(y0, y1);\n",
+ " var width = Math.abs(x1 - x0);\n",
+ " var height = Math.abs(y1 - y0);\n",
+ "\n",
+ " fig.rubberband_context.clearRect(\n",
+ " 0,\n",
+ " 0,\n",
+ " fig.canvas.width / fig.ratio,\n",
+ " fig.canvas.height / fig.ratio\n",
+ " );\n",
+ "\n",
+ " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
+ " // Updates the figure title.\n",
+ " fig.header.textContent = msg['label'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
+ " var cursor = msg['cursor'];\n",
+ " switch (cursor) {\n",
+ " case 0:\n",
+ " cursor = 'pointer';\n",
+ " break;\n",
+ " case 1:\n",
+ " cursor = 'default';\n",
+ " break;\n",
+ " case 2:\n",
+ " cursor = 'crosshair';\n",
+ " break;\n",
+ " case 3:\n",
+ " cursor = 'move';\n",
+ " break;\n",
+ " }\n",
+ " fig.rubberband_canvas.style.cursor = cursor;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
+ " fig.message.textContent = msg['message'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
+ " // Request the server to send over a new figure.\n",
+ " fig.send_draw_message();\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
+ " fig.image_mode = msg['mode'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
+ " for (var key in msg) {\n",
+ " if (!(key in fig.buttons)) {\n",
+ " continue;\n",
+ " }\n",
+ " fig.buttons[key].disabled = !msg[key];\n",
+ " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
+ " if (msg['mode'] === 'PAN') {\n",
+ " fig.buttons['Pan'].classList.add('active');\n",
+ " fig.buttons['Zoom'].classList.remove('active');\n",
+ " } else if (msg['mode'] === 'ZOOM') {\n",
+ " fig.buttons['Pan'].classList.remove('active');\n",
+ " fig.buttons['Zoom'].classList.add('active');\n",
+ " } else {\n",
+ " fig.buttons['Pan'].classList.remove('active');\n",
+ " fig.buttons['Zoom'].classList.remove('active');\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function () {\n",
+ " // Called whenever the canvas gets updated.\n",
+ " this.send_message('ack', {});\n",
+ "};\n",
+ "\n",
+ "// A function to construct a web socket function for onmessage handling.\n",
+ "// Called in the figure constructor.\n",
+ "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
+ " return function socket_on_message(evt) {\n",
+ " if (evt.data instanceof Blob) {\n",
+ " /* FIXME: We get \"Resource interpreted as Image but\n",
+ " * transferred with MIME type text/plain:\" errors on\n",
+ " * Chrome. But how to set the MIME type? It doesn't seem\n",
+ " * to be part of the websocket stream */\n",
+ " evt.data.type = 'image/png';\n",
+ "\n",
+ " /* Free the memory for the previous frames */\n",
+ " if (fig.imageObj.src) {\n",
+ " (window.URL || window.webkitURL).revokeObjectURL(\n",
+ " fig.imageObj.src\n",
+ " );\n",
+ " }\n",
+ "\n",
+ " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+ " evt.data\n",
+ " );\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " } else if (\n",
+ " typeof evt.data === 'string' &&\n",
+ " evt.data.slice(0, 21) === 'data:image/png;base64'\n",
+ " ) {\n",
+ " fig.imageObj.src = evt.data;\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " var msg = JSON.parse(evt.data);\n",
+ " var msg_type = msg['type'];\n",
+ "\n",
+ " // Call the \"handle_{type}\" callback, which takes\n",
+ " // the figure and JSON message as its only arguments.\n",
+ " try {\n",
+ " var callback = fig['handle_' + msg_type];\n",
+ " } catch (e) {\n",
+ " console.log(\n",
+ " \"No handler for the '\" + msg_type + \"' message type: \",\n",
+ " msg\n",
+ " );\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " if (callback) {\n",
+ " try {\n",
+ " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+ " callback(fig, msg);\n",
+ " } catch (e) {\n",
+ " console.log(\n",
+ " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
+ " e,\n",
+ " e.stack,\n",
+ " msg\n",
+ " );\n",
+ " }\n",
+ " }\n",
+ " };\n",
+ "};\n",
+ "\n",
+ "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+ "mpl.findpos = function (e) {\n",
+ " //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+ " var targ;\n",
+ " if (!e) {\n",
+ " e = window.event;\n",
+ " }\n",
+ " if (e.target) {\n",
+ " targ = e.target;\n",
+ " } else if (e.srcElement) {\n",
+ " targ = e.srcElement;\n",
+ " }\n",
+ " if (targ.nodeType === 3) {\n",
+ " // defeat Safari bug\n",
+ " targ = targ.parentNode;\n",
+ " }\n",
+ "\n",
+ " // pageX,Y are the mouse positions relative to the document\n",
+ " var boundingRect = targ.getBoundingClientRect();\n",
+ " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
+ " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
+ "\n",
+ " return { x: x, y: y };\n",
+ "};\n",
+ "\n",
+ "/*\n",
+ " * return a copy of an object with only non-object keys\n",
+ " * we need this to avoid circular references\n",
+ " * http://stackoverflow.com/a/24161582/3208463\n",
+ " */\n",
+ "function simpleKeys(original) {\n",
+ " return Object.keys(original).reduce(function (obj, key) {\n",
+ " if (typeof original[key] !== 'object') {\n",
+ " obj[key] = original[key];\n",
+ " }\n",
+ " return obj;\n",
+ " }, {});\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.mouse_event = function (event, name) {\n",
+ " var canvas_pos = mpl.findpos(event);\n",
+ "\n",
+ " if (name === 'button_press') {\n",
+ " this.canvas.focus();\n",
+ " this.canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " var x = canvas_pos.x * this.ratio;\n",
+ " var y = canvas_pos.y * this.ratio;\n",
+ "\n",
+ " this.send_message(name, {\n",
+ " x: x,\n",
+ " y: y,\n",
+ " button: event.button,\n",
+ " step: event.step,\n",
+ " guiEvent: simpleKeys(event),\n",
+ " });\n",
+ "\n",
+ " /* This prevents the web browser from automatically changing to\n",
+ " * the text insertion cursor when the button is pressed. We want\n",
+ " * to control all of the cursor setting manually through the\n",
+ " * 'cursor' event from matplotlib */\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
+ " // Handle any extra behaviour associated with a key event\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.key_event = function (event, name) {\n",
+ " // Prevent repeat events\n",
+ " if (name === 'key_press') {\n",
+ " if (event.which === this._key) {\n",
+ " return;\n",
+ " } else {\n",
+ " this._key = event.which;\n",
+ " }\n",
+ " }\n",
+ " if (name === 'key_release') {\n",
+ " this._key = null;\n",
+ " }\n",
+ "\n",
+ " var value = '';\n",
+ " if (event.ctrlKey && event.which !== 17) {\n",
+ " value += 'ctrl+';\n",
+ " }\n",
+ " if (event.altKey && event.which !== 18) {\n",
+ " value += 'alt+';\n",
+ " }\n",
+ " if (event.shiftKey && event.which !== 16) {\n",
+ " value += 'shift+';\n",
+ " }\n",
+ "\n",
+ " value += 'k';\n",
+ " value += event.which.toString();\n",
+ "\n",
+ " this._key_event_extra(event, name);\n",
+ "\n",
+ " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
+ " return false;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
+ " if (name === 'download') {\n",
+ " this.handle_save(this, null);\n",
+ " } else {\n",
+ " this.send_message('toolbar_button', { name: name });\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
+ " this.message.textContent = tooltip;\n",
+ "};\n",
+ "\n",
+ "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
+ "// prettier-ignore\n",
+ "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
+ "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+ "\n",
+ "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
+ "\n",
+ "mpl.default_extension = \"png\";/* global mpl */\n",
+ "\n",
+ "var comm_websocket_adapter = function (comm) {\n",
+ " // Create a \"websocket\"-like object which calls the given IPython comm\n",
+ " // object with the appropriate methods. Currently this is a non binary\n",
+ " // socket, so there is still some room for performance tuning.\n",
+ " var ws = {};\n",
+ "\n",
+ " ws.close = function () {\n",
+ " comm.close();\n",
+ " };\n",
+ " ws.send = function (m) {\n",
+ " //console.log('sending', m);\n",
+ " comm.send(m);\n",
+ " };\n",
+ " // Register the callback with on_msg.\n",
+ " comm.on_msg(function (msg) {\n",
+ " //console.log('receiving', msg['content']['data'], msg);\n",
+ " // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
+ " ws.onmessage(msg['content']['data']);\n",
+ " });\n",
+ " return ws;\n",
+ "};\n",
+ "\n",
+ "mpl.mpl_figure_comm = function (comm, msg) {\n",
+ " // This is the function which gets called when the mpl process\n",
+ " // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+ "\n",
+ " var id = msg.content.data.id;\n",
+ " // Get hold of the div created by the display call when the Comm\n",
+ " // socket was opened in Python.\n",
+ " var element = document.getElementById(id);\n",
+ " var ws_proxy = comm_websocket_adapter(comm);\n",
+ "\n",
+ " function ondownload(figure, _format) {\n",
+ " window.open(figure.canvas.toDataURL());\n",
+ " }\n",
+ "\n",
+ " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
+ "\n",
+ " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+ " // web socket which is closed, not our websocket->open comm proxy.\n",
+ " ws_proxy.onopen();\n",
+ "\n",
+ " fig.parent_element = element;\n",
+ " fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+ " if (!fig.cell_info) {\n",
+ " console.error('Failed to find cell for figure', id, fig);\n",
+ " return;\n",
+ " }\n",
+ " fig.cell_info[0].output_area.element.on(\n",
+ " 'cleared',\n",
+ " { fig: fig },\n",
+ " fig._remove_fig_handler\n",
+ " );\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
+ " var width = fig.canvas.width / fig.ratio;\n",
+ " fig.cell_info[0].output_area.element.off(\n",
+ " 'cleared',\n",
+ " fig._remove_fig_handler\n",
+ " );\n",
+ " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
+ "\n",
+ " // Update the output cell to use the data from the current canvas.\n",
+ " fig.push_to_output();\n",
+ " var dataURL = fig.canvas.toDataURL();\n",
+ " // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+ " // the notebook keyboard shortcuts fail.\n",
+ " IPython.keyboard_manager.enable();\n",
+ " fig.parent_element.innerHTML =\n",
+ " '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ " fig.close_ws(fig, msg);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
+ " fig.send_message('closing', msg);\n",
+ " // fig.ws.close()\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
+ " // Turn the data on the canvas into data in the output cell.\n",
+ " var width = this.canvas.width / this.ratio;\n",
+ " var dataURL = this.canvas.toDataURL();\n",
+ " this.cell_info[1]['text/html'] =\n",
+ " '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function () {\n",
+ " // Tell IPython that the notebook contents must change.\n",
+ " IPython.notebook.set_dirty(true);\n",
+ " this.send_message('ack', {});\n",
+ " var fig = this;\n",
+ " // Wait a second, then push the new image to the DOM so\n",
+ " // that it is saved nicely (might be nice to debounce this).\n",
+ " setTimeout(function () {\n",
+ " fig.push_to_output();\n",
+ " }, 1000);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var toolbar = document.createElement('div');\n",
+ " toolbar.classList = 'btn-toolbar';\n",
+ " this.root.appendChild(toolbar);\n",
+ "\n",
+ " function on_click_closure(name) {\n",
+ " return function (_event) {\n",
+ " return fig.toolbar_button_onclick(name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " function on_mouseover_closure(tooltip) {\n",
+ " return function (event) {\n",
+ " if (!event.currentTarget.disabled) {\n",
+ " return fig.toolbar_button_onmouseover(tooltip);\n",
+ " }\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " fig.buttons = {};\n",
+ " var buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'btn-group';\n",
+ " var button;\n",
+ " for (var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " /* Instead of a spacer, we start a new button group. */\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ " buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'btn-group';\n",
+ " continue;\n",
+ " }\n",
+ "\n",
+ " button = fig.buttons[name] = document.createElement('button');\n",
+ " button.classList = 'btn btn-default';\n",
+ " button.href = '#';\n",
+ " button.title = name;\n",
+ " button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
+ " button.addEventListener('click', on_click_closure(method_name));\n",
+ " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+ " buttonGroup.appendChild(button);\n",
+ " }\n",
+ "\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ "\n",
+ " // Add the status bar.\n",
+ " var status_bar = document.createElement('span');\n",
+ " status_bar.classList = 'mpl-message pull-right';\n",
+ " toolbar.appendChild(status_bar);\n",
+ " this.message = status_bar;\n",
+ "\n",
+ " // Add the close button to the window.\n",
+ " var buttongrp = document.createElement('div');\n",
+ " buttongrp.classList = 'btn-group inline pull-right';\n",
+ " button = document.createElement('button');\n",
+ " button.classList = 'btn btn-mini btn-primary';\n",
+ " button.href = '#';\n",
+ " button.title = 'Stop Interaction';\n",
+ " button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
+ " button.addEventListener('click', function (_evt) {\n",
+ " fig.handle_close(fig, {});\n",
+ " });\n",
+ " button.addEventListener(\n",
+ " 'mouseover',\n",
+ " on_mouseover_closure('Stop Interaction')\n",
+ " );\n",
+ " buttongrp.appendChild(button);\n",
+ " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
+ " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
+ " var fig = event.data.fig;\n",
+ " if (event.target !== this) {\n",
+ " // Ignore bubbled events from children.\n",
+ " return;\n",
+ " }\n",
+ " fig.close_ws(fig, {});\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function (el) {\n",
+ " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
+ " // this is important to make the div 'focusable\n",
+ " el.setAttribute('tabindex', 0);\n",
+ " // reach out to IPython and tell the keyboard manager to turn it's self\n",
+ " // off when our div gets focus\n",
+ "\n",
+ " // location in version 3\n",
+ " if (IPython.notebook.keyboard_manager) {\n",
+ " IPython.notebook.keyboard_manager.register_events(el);\n",
+ " } else {\n",
+ " // location in version 2\n",
+ " IPython.keyboard_manager.register_events(el);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
+ " var manager = IPython.notebook.keyboard_manager;\n",
+ " if (!manager) {\n",
+ " manager = IPython.keyboard_manager;\n",
+ " }\n",
+ "\n",
+ " // Check for shift+enter\n",
+ " if (event.shiftKey && event.which === 13) {\n",
+ " this.canvas_div.blur();\n",
+ " // select the cell after this one\n",
+ " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
+ " IPython.notebook.select(index + 1);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+ " fig.ondownload(fig, null);\n",
+ "};\n",
+ "\n",
+ "mpl.find_output_cell = function (html_output) {\n",
+ " // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+ " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+ " // IPython event is triggered only after the cells have been serialised, which for\n",
+ " // our purposes (turning an active figure into a static one), is too late.\n",
+ " var cells = IPython.notebook.get_cells();\n",
+ " var ncells = cells.length;\n",
+ " for (var i = 0; i < ncells; i++) {\n",
+ " var cell = cells[i];\n",
+ " if (cell.cell_type === 'code') {\n",
+ " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
+ " var data = cell.output_area.outputs[j];\n",
+ " if (data.data) {\n",
+ " // IPython >= 3 moved mimebundle to data attribute of output\n",
+ " data = data.data;\n",
+ " }\n",
+ " if (data['text/html'] === html_output) {\n",
+ " return [cell, data, j];\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "// Register the function which deals with the matplotlib target/channel.\n",
+ "// The kernel may be null if the page has been refreshed.\n",
+ "if (IPython.notebook.kernel !== null) {\n",
+ " IPython.notebook.kernel.comm_manager.register_target(\n",
+ " 'matplotlib',\n",
+ " mpl.mpl_figure_comm\n",
+ " );\n",
+ "}\n"
+ ],
"text/plain": [
- "<Figure size 1440x1728 with 25 Axes>"
+ "<IPython.core.display.Javascript object>"
]
},
- "metadata": {
- "needs_background": "light"
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
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\" width=\"1000\">"
+ ],
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ]
},
+ "metadata": {},
"output_type": "display_data"
}
],
"source": [
- "fig, ax = plt.subplots(nrows=5, ncols=5, figsize=(20,24))\n",
+ "fig, ax = plt.subplots(nrows=5, ncols=5, figsize=(10,15))\n",
"for i in range(5):\n",
" for j in range(5):\n",
" idx = i*5+j\n",
@@ -682,7 +2509,7 @@
" probs = F.softmax(logits, dim=1) # apply softmax to normalize them\n",
" predicted = torch.argmax(probs[0, ...]) # index of the highest probability\n",
" ax[i, j].imshow(img[0,...].detach().cpu().numpy())\n",
- " ax[i, j].set(title=f\"Image {idx}, true label {label}, predicted: {predicted}\")\n",
+ " ax[i, j].set(title=f\"True {label}, pred. {predicted}\")\n",
" ax[i, j].set_xticklabels([])\n",
" ax[i, j].set_yticklabels([])\n",
"plt.subplots_adjust(hspace=0.2,wspace=0)\n",
@@ -699,7 +2526,7 @@
},
{
"cell_type": "code",
- "execution_count": 29,
+ "execution_count": 13,
"id": "b447df87",
"metadata": {},
"outputs": [],
@@ -717,7 +2544,7 @@
},
{
"cell_type": "code",
- "execution_count": 30,
+ "execution_count": 14,
"id": "d6df7b33",
"metadata": {},
"outputs": [],
@@ -735,20 +2562,978 @@
},
{
"cell_type": "code",
- "execution_count": 34,
+ "execution_count": 15,
"id": "93a5fe94",
"metadata": {},
"outputs": [
{
"data": {
- "image/png": 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tHaiqg5P06koCAFgvcwLZW6vqF5McWlU/kOSVSV632rIAANbHnEB2epLrkrwvyU8neWOSX15lUQAA62TOtyy/VFVnJXlXFocqr+xuhywBAA6QbQNZVT02ye8l+askleSYqvrp7v6fqy4OAGAdzLkw7G8n+f7uvipJqurYJG9IIpABABwAc84hu3ZvGJv8dZJrV1QPAMDa2XQPWVU9cXp4WVW9McnZWZxD9uQk796B2gAA1sJWhyx/ZMPjjyf5vunxdUnuubKKAADWzKaBrLufvpOFAACsqznfsjwmyTOT7NnYvrsft7qyAADWx5xvWb4mye9ncXX+L620GgCANTQnkP19d/+nlVcCALCm5gSy/1hVz0vy5iQ37h3Z3RevrCoAgDUyJ5B9S5KfSPKI/MMhy56GAQD4Cs0JZE9Icv/uvmnVxQAArKM5V+p/T5LDVlwHAMDamrOH7L5JPlBV786tzyFz2QsAgANgTiB73sqrAABYY9sGsu5+604UAgCwruZcqf9zWXyrMknulOSOSW7o7nussjAAgHUxZw/Z3TcOV9XjkzxkVQUBAKybOd+yvJXufk324xpkVXVQVV1SVa+fhu9VVW+pqg9Ov++5oe1zq+qqqrqyqh61v7UBAHw1mnPI8okbBu+Q5Pj8wyHMOZ6V5Iokew9xnp7kvO5+QVWdPg0/p6oemOTkJA9K8g1J/rSqHtDdt+zHsgAAvurM2UP2Ixt+HpXkc0lOmjPzqjoqyWOTvGTD6JOSnDU9PivJ4zeMf0V339jdH0pyVRwaBQDWwJxzyJ7+Fcz/PyT5t0k2nod23+6+Zpr3NVV1n2n8kUneuaHd1dM4AICvaZsGsqr6lS2m6+5+/lYzrqofTnJtd19UVQ+fUUstW86S+Z6a5NQkud/97jdjtgAAu9tWhyxvWPKTJM9I8pwZ835oksdV1YeTvCLJI6rqpUk+XlVHJMn0+9qp/dVJjt4w/VFJPrbvTLv7zO4+vruPP/zww2eUAQCwu20ayLr7t/f+JDkzyaFJnp5FuLr/djPu7ud291HdvSeLk/X/rLufkuTcJKdMzU5J8trp8blJTq6qQ6rqmCTHJbng9r0sAICvHlueQ1ZV90ry80l+PIsT8L+juz/1FS7zBUnOrqpnJPlIkicnSXdfVlVnJ7k8yc1JTvMNSwBgHWx1DtlvJnliFnvHvqW7r7+9C+nu85OcPz3+ZJITN2l3RpIzbu9yAAC+Gm11Dtm/yeJ6YL+c5GNV9dnp53NV9dmdKQ8A4GvfpnvIunu/r+IPAMD+E7oAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAZbWSCrqqOr6s+r6oqquqyqnjWNv1dVvaWqPjj9vueGaZ5bVVdV1ZVV9ahV1QYAsJuscg/ZzUn+TXd/c5ITkpxWVQ9McnqS87r7uCTnTcOZnjs5yYOSPDrJi6rqoBXWBwCwK6wskHX3Nd198fT4c0muSHJkkpOSnDU1OyvJ46fHJyV5RXff2N0fSnJVkoesqj4AgN1iR84hq6o9Sb49ybuS3Le7r0kWoS3JfaZmRyb56IbJrp7GAQB8TVt5IKuquyX54yT/qrs/u1XTJeN6yfxOraoLq+rC66677kCVCQAwzEoDWVXdMYsw9rLuftU0+uNVdcT0/BFJrp3GX53k6A2TH5XkY/vOs7vP7O7ju/v4ww8/fHXFAwDskFV+y7KS/H6SK7r7dzY8dW6SU6bHpyR57YbxJ1fVIVV1TJLjklywqvoAAHaLg1c474cm+Ykk76uqS6dxv5jkBUnOrqpnJPlIkicnSXdfVlVnJ7k8i29ontbdt6ywPgCAXWFlgay7/yLLzwtLkhM3meaMJGesqiYAgN3IlfoBAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABhPIAAAGE8gAAAYTyAAABjt4dAEAwFenPae/YXQJXzN23R6yqnp0VV1ZVVdV1emj6wEAWLVdtYesqg5K8v8m+YEkVyd5d1Wd292Xj6xrJ/4D+PALHrvyZQAAu9OuCmRJHpLkqu7+6ySpqlckOSnJ0EC2E+z23T87FWCFcWAVfOazr90WyI5M8tENw1cn+WeDamEX+1r6MPtaei3sn50I47av/eMfJEbZbYGslozrWzWoOjXJqdPg9VV15YpruneST6x4Gew//bL76JP9VC/ckcXol/2gT9ZXvXBH+uUbN3titwWyq5McvWH4qCQf29igu89McuZOFVRVF3b38Tu1PObRL7uPPtmd9Mvuo092p9H9stu+ZfnuJMdV1TFVdackJyc5d3BNAAArtav2kHX3zVX1L5P8SZKDkvxBd182uCwAgJXaVYEsSbr7jUneOLqODXbs8Cj7Rb/sPvpkd9Ivu48+2Z2G9kt19/atAABYmd12DhkAwNoRyCbb3bKpFv7T9Px7q+o7RtS5Tmb0yY9PffHeqnpHVX3riDrXzdzbm1XVg6vqlqp60k7Wt47m9ElVPbyqLq2qy6rqrTtd4zqa8Rn2dVX1uqp6z9QvTx9R5zqpqj+oqmur6v2bPD/sb71AllvdsumHkjwwyb+oqgfu0+yHkhw3/Zya5MU7WuSamdknH0ryfd39T5M8P87LWLmZ/bK33Quz+IIOKzSnT6rqsCQvSvK47n5QkifvdJ3rZuZ75bQkl3f3tyZ5eJLfnq4wwOr8UZJHb/H8sL/1AtnCl2/Z1N03Jdl7y6aNTkry33rhnUkOq6ojdrrQNbJtn3T3O7r7U9PgO7O4bh2rNee9kiTPTPLHSa7dyeLW1Jw++bEkr+rujyRJd+uX1ZvTL53k7lVVSe6W5O+S3LyzZa6X7n5bFut5M8P+1gtkC8tu2XTk7WjDgbO/6/sZSf7nSisimdEvVXVkkick+b0drGudzXmvPCDJPavq/Kq6qKqeumPVra85/fKfk3xzFhdAf1+SZ3X3l3amPDYx7G/9rrvsxSDb3rJpZhsOnNnru6q+P4tA9j0rrYhkXr/8hyTP6e5bFv/4s2Jz+uTgJN+Z5MQkhyb5y6p6Z3f/71UXt8bm9Mujklya5BFJjk3ylqp6e3d/dsW1sblhf+sFsoVtb9k0sw0Hzqz1XVX/NMlLkvxQd39yh2pbZ3P65fgkr5jC2L2TPKaqbu7u1+xIhetn7ufXJ7r7hiQ3VNXbknxrEoFsdeb0y9OTvKAX15+6qqo+lOSbklywMyWyxLC/9Q5ZLsy5ZdO5SZ46fQPjhCSf6e5rdrrQNbJtn1TV/ZK8KslP+E9/x2zbL919THfv6e49Sc5J8rPC2ErN+fx6bZKHVdXBVXWXJP8syRU7XOe6mdMvH8lir2Wq6r5J/nGSv97RKtnXsL/19pBl81s2VdXPTM//XhZ3D3hMkquSfD6L/2xYkZl98itJvj7Ji6a9MTe7Ye9qzewXdtCcPunuK6rqTUnem+RLSV7S3Uu/9s+BMfO98vwkf1RV78viUNlzuvsTw4peA1X18iy+0Xrvqro6yfOS3DEZ/7felfoBAAZzyBIAYDCBDABgMIEMAGAwgQwAYDCBDABgMIEMAGAwgQwAYDCBbE1V1S1VdWlVvb+qXjldvXvutHuqavZFJbdrX1XvmH5fv2TcYVX1s3OXtWya21Hvfi9zFfOYsYyDquqSqnr9Js/v1+ueprl++1YH1oFeV6t+Ddut95Gq6ler6tnT43ccoHnu+HvwK7Wq99/c11FVh1bVW6vqoP1pV1X/qKpeUVV/VVWXV9Ubq+oBW0x/flXt2eS5L28Lmzw/ax1V1Z2q6m1VdfCyYQ4cgWx9faG7v627/0mSm5L8zMYnp9tG7Mj20d3fvcW4w5Ls7wfr7ZnmQE6/5TwO4Lp9Vr42bn9zWL7y9b2Thq/3OdvQsvfV7XRYdv49+JU64Muvxe1A5r5vfzLJq7r7lrntpvm/Osn53X1sdz8wyS8mue/tLnprh2XGOurum5Kcl+SfLxvmwBHISJK3J/k/pv/+rqiqFyW5OMnRVfXz016091fVv9owzcFVdVZVvbeqztm7h62qXlNVF1XVZVV16nbtp2lus0djw7gXJDl22pv3m1X1/Kp61oZ2Z1TVz+0z+a2mmcYdVFX/darrzVV16Bb1Lpt+Y22bvcZNa1iybh+28T/tqnp2Vf3q9PgpVXXBNO1/WfZfdlUdleSxWdxYfSub9dOcZdym7ze8jtusy+n5f1dVH6iqt1TVy6fXddeqekNVvWea174f5LdZ31tsd/vW+NTptb2nqv77kudv01fL6plR4975bbveN9s+Nqt12fht1v2X35/T+F+qqiur6k+zuBfi3vlev890y7b/2/TXkpe077Y8p2/25z245bY4Y5tbNv2+Nf/bmj4nqup3q+rPpscnVtVL93edT8/dvxZ7Sh+85PX/eBb3D907jw/U8s+/L7dL8v1Jvrjx9mPdfWl3v32TdXwbW2wLsz7nNtt2k7xmqnWzYQ6E7vazhj9Jrp9+H5zFB8L/lWRPFve5O2F67juTvC/JXZPcLcllSb59atdJHjq1+4Mkz54e32v6fWiS92dxr8lN2+9Ty/VLxu1J8v4N4/ckuXh6fIckf5Xk6/d5bcumuTnJt03DZyd5yjb1vn+LdXebaZa0WVbDxnW77/PPTvKrSb45yeuS3HEa/6IkT10y/3Om/nl4ktdvUufS9b7VMjas9636frN1eXySS6f1cvckH5yW938m+a8b6vq6bdbV0mUveX0PSnJlknvv0y8bt6Nl/XuberarcT/X+7JlblbrbcZvs+6/vA3ts67ukuQeWdx/79kb18NmfbZZf221Le9H3+zbp5vVsO32vtm00+Ol0y9Z/glJXjk9fnuSC7K4f+Hzkvz03HW+d75ZhJ1L9ta0T713SvK3M96H+7b7uSS/u9nnzibb2vlJ9szYFmZ9zi1rNw0flOS6De1uNeznwPzYQ7a+Dq2qS5NcmOQjSX5/Gv833f3O6fH3JHl1d9/Q3dcneVWSh03PfbS7/9f0+KVT2yT5uap6T5J3ZvHf5HHbtN8v3f3hJJ+sqm9P8oNJLunuT86Y9EPdfen0+KIsPoy2qncrt2ea5NbrdjMnZvHB+u6pf05Mcv+NDarqh5Nc290XzVjmsvW+7TKydd9vti6/J8lru/sL3f25LP5QJos/Eo+sqhdW1cO6+zPb1LzVsjd6RJJzeroZc3f/3ZI2y/pqWT3b1rgf633ZMjerddn4rV7/vtvQw6a2n+/uzyY5d5OalvXZZv21lbl9M7eGOdviZtNmP6a/KMl3VtXdk9yY5C+zCKQPyyKg7c86PzyLf2KfsqGmje6d5NP7jFv2PlzWblO12It70bQdLrPVtjD3M2tpu14cer1pWn+3GebAcFLe+vpCd3/bxhFVlSQ3bBy1xfT73pW+q+rhSR6Z5Lu6+/NVdX6SO2/Wfv/KvZWXJHlakn+UxX+bc9y44fEtWQTSh2fzepe6PdNssHHd3pxbnzKwdx6V5Kzufu4W83loksdV1WOm6e5RVS/t7qcsabtsvc9ZxlZ9f5t1udU03f2/q+o7kzwmya9X1Zu7+9/fzmXv227T7Wizvtqsnhk1brvet9g+Nqt12fitXv8NS8bNeS8t67O563mj2zPNdjVsty1uNu3eem4zfe1zont3f7GqPpzk6UnekeS9WRwiPDaL8wF/cItl77vOP5Pko1lsD5ctaf+F3PYzYdn7cN92lyV50hZ1PCeLvYNbuc22MPcza0a7Q5L8/RbDfIXsIWMrb0vy+Kq6S1XdNckTsvhvMknuV1XfNT3+F0n+IotDP5+a3szflMVhgmzRfo7PZXE4ZaNXJ3l0kgcn+ZOZ0yyzWb1bTb/Va9yfGj6e5D5V9fVVdUiSvf/1npfkSVV1nySpqntV1TdunLC7n9vdR3X3niQnJ/mzTcJYsny9b7uMbN33m/mLJD9SVXeuqrtlca5Vquobkny+u1+a5LeSfMc+0+27ruYu+7wkP1pVX7/3dezz/NK+WlbPjBrnrvfNto/Nal02fn/W/duSPKEW39a7e5If2aTdMkv7a4mN/TO3trnvwTnb4u2Zftny35bFocK3TTX/TJJLu7v343Uliy9BPT7JU6vqx/Z9srs/lcX5chvDzG3eh0va/VmSQ6rqp/ZOVFUPrqrvq6pHJrk8i8+NzWy2Lcz9nNv0s23aPq/r7i8uG+bAEMjYVHdfnOSPsjjf4l1JXtLdl0xPX5HklKp6bxbnvbw4yZuyOIn8vUmen8Vu72zRfk4Nn0zyv2pxou1vTuNuSvLnSc7uJd9iWjbNJpbWu830W73G2TVMH2T/Pov1+vokH5jGX57kl5O8eVrGW5IcscVr2M5t1vucZWzT90t197uzOEzyniwO+VyYxd6Eb0lywXRI6ZeS/No+091qXc1ddndfluSMJG+dDrP8zj5NNuurZfVsWeN+2GybWlrrsvH7s+6ntv8ji3PB/jjbh+aN027WX/u2+3L/ZBEmtq1t7nvwK93eN5t+k+W/fZr3X3b3x7PYu/P2aT77tb139w1Z/BP1r6vqpCVN3pxbn5ax2effl9tNwfAJSX6gFpe9uCyL80o/lsXevBOS/FiSn6ol37DdYluY+zm31Wfb9yd54xbDHAC12Abgq8f0YXRxkid39wdH18M/qKq7dff1tfgW2duSnDr9oWAX0l+rUYtzXH++u39iOnz6+l5cYmjTdjPn+7Qkn+ju10/D5yd5Wi/OrV2ZqnpVkud295XLhjkwnEPGV5WqemAWe5ReLYztSmdOfXTnLM7t8cd9d9NfK9Ddl1TVn9c2F4bd2G7Z3v4l7f/ogBU5U1XdKclrNoSxWw1z4NhDBgBfhaY9Zq/p7k8PLoUDQCADABjMSf0AAIMJZAAAgwlkAACDCWQAAIMJZAAAgwlkAACDCWQAAIP9/xr1FN7hjdNnAAAAAElFTkSuQmCC\n",
+ "application/javascript": [
+ "/* Put everything inside the global mpl namespace */\n",
+ "/* global mpl */\n",
+ "window.mpl = {};\n",
+ "\n",
+ "mpl.get_websocket_type = function () {\n",
+ " if (typeof WebSocket !== 'undefined') {\n",
+ " return WebSocket;\n",
+ " } else if (typeof MozWebSocket !== 'undefined') {\n",
+ " return MozWebSocket;\n",
+ " } else {\n",
+ " alert(\n",
+ " 'Your browser does not have WebSocket support. ' +\n",
+ " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+ " 'Firefox 4 and 5 are also supported but you ' +\n",
+ " 'have to enable WebSockets in about:config.'\n",
+ " );\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
+ " this.id = figure_id;\n",
+ "\n",
+ " this.ws = websocket;\n",
+ "\n",
+ " this.supports_binary = this.ws.binaryType !== undefined;\n",
+ "\n",
+ " if (!this.supports_binary) {\n",
+ " var warnings = document.getElementById('mpl-warnings');\n",
+ " if (warnings) {\n",
+ " warnings.style.display = 'block';\n",
+ " warnings.textContent =\n",
+ " 'This browser does not support binary websocket messages. ' +\n",
+ " 'Performance may be slow.';\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.imageObj = new Image();\n",
+ "\n",
+ " this.context = undefined;\n",
+ " this.message = undefined;\n",
+ " this.canvas = undefined;\n",
+ " this.rubberband_canvas = undefined;\n",
+ " this.rubberband_context = undefined;\n",
+ " this.format_dropdown = undefined;\n",
+ "\n",
+ " this.image_mode = 'full';\n",
+ "\n",
+ " this.root = document.createElement('div');\n",
+ " this.root.setAttribute('style', 'display: inline-block');\n",
+ " this._root_extra_style(this.root);\n",
+ "\n",
+ " parent_element.appendChild(this.root);\n",
+ "\n",
+ " this._init_header(this);\n",
+ " this._init_canvas(this);\n",
+ " this._init_toolbar(this);\n",
+ "\n",
+ " var fig = this;\n",
+ "\n",
+ " this.waiting = false;\n",
+ "\n",
+ " this.ws.onopen = function () {\n",
+ " fig.send_message('supports_binary', { value: fig.supports_binary });\n",
+ " fig.send_message('send_image_mode', {});\n",
+ " if (fig.ratio !== 1) {\n",
+ " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
+ " }\n",
+ " fig.send_message('refresh', {});\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onload = function () {\n",
+ " if (fig.image_mode === 'full') {\n",
+ " // Full images could contain transparency (where diff images\n",
+ " // almost always do), so we need to clear the canvas so that\n",
+ " // there is no ghosting.\n",
+ " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+ " }\n",
+ " fig.context.drawImage(fig.imageObj, 0, 0);\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onunload = function () {\n",
+ " fig.ws.close();\n",
+ " };\n",
+ "\n",
+ " this.ws.onmessage = this._make_on_message_function(this);\n",
+ "\n",
+ " this.ondownload = ondownload;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_header = function () {\n",
+ " var titlebar = document.createElement('div');\n",
+ " titlebar.classList =\n",
+ " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
+ " var titletext = document.createElement('div');\n",
+ " titletext.classList = 'ui-dialog-title';\n",
+ " titletext.setAttribute(\n",
+ " 'style',\n",
+ " 'width: 100%; text-align: center; padding: 3px;'\n",
+ " );\n",
+ " titlebar.appendChild(titletext);\n",
+ " this.root.appendChild(titlebar);\n",
+ " this.header = titletext;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
+ "\n",
+ "mpl.figure.prototype._init_canvas = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var canvas_div = (this.canvas_div = document.createElement('div'));\n",
+ " canvas_div.setAttribute(\n",
+ " 'style',\n",
+ " 'border: 1px solid #ddd;' +\n",
+ " 'box-sizing: content-box;' +\n",
+ " 'clear: both;' +\n",
+ " 'min-height: 1px;' +\n",
+ " 'min-width: 1px;' +\n",
+ " 'outline: 0;' +\n",
+ " 'overflow: hidden;' +\n",
+ " 'position: relative;' +\n",
+ " 'resize: both;'\n",
+ " );\n",
+ "\n",
+ " function on_keyboard_event_closure(name) {\n",
+ " return function (event) {\n",
+ " return fig.key_event(event, name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " canvas_div.addEventListener(\n",
+ " 'keydown',\n",
+ " on_keyboard_event_closure('key_press')\n",
+ " );\n",
+ " canvas_div.addEventListener(\n",
+ " 'keyup',\n",
+ " on_keyboard_event_closure('key_release')\n",
+ " );\n",
+ "\n",
+ " this._canvas_extra_style(canvas_div);\n",
+ " this.root.appendChild(canvas_div);\n",
+ "\n",
+ " var canvas = (this.canvas = document.createElement('canvas'));\n",
+ " canvas.classList.add('mpl-canvas');\n",
+ " canvas.setAttribute('style', 'box-sizing: content-box;');\n",
+ "\n",
+ " this.context = canvas.getContext('2d');\n",
+ "\n",
+ " var backingStore =\n",
+ " this.context.backingStorePixelRatio ||\n",
+ " this.context.webkitBackingStorePixelRatio ||\n",
+ " this.context.mozBackingStorePixelRatio ||\n",
+ " this.context.msBackingStorePixelRatio ||\n",
+ " this.context.oBackingStorePixelRatio ||\n",
+ " this.context.backingStorePixelRatio ||\n",
+ " 1;\n",
+ "\n",
+ " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+ "\n",
+ " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
+ " 'canvas'\n",
+ " ));\n",
+ " rubberband_canvas.setAttribute(\n",
+ " 'style',\n",
+ " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
+ " );\n",
+ "\n",
+ " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
+ " if (this.ResizeObserver === undefined) {\n",
+ " if (window.ResizeObserver !== undefined) {\n",
+ " this.ResizeObserver = window.ResizeObserver;\n",
+ " } else {\n",
+ " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
+ " this.ResizeObserver = obs.ResizeObserver;\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
+ " var nentries = entries.length;\n",
+ " for (var i = 0; i < nentries; i++) {\n",
+ " var entry = entries[i];\n",
+ " var width, height;\n",
+ " if (entry.contentBoxSize) {\n",
+ " if (entry.contentBoxSize instanceof Array) {\n",
+ " // Chrome 84 implements new version of spec.\n",
+ " width = entry.contentBoxSize[0].inlineSize;\n",
+ " height = entry.contentBoxSize[0].blockSize;\n",
+ " } else {\n",
+ " // Firefox implements old version of spec.\n",
+ " width = entry.contentBoxSize.inlineSize;\n",
+ " height = entry.contentBoxSize.blockSize;\n",
+ " }\n",
+ " } else {\n",
+ " // Chrome <84 implements even older version of spec.\n",
+ " width = entry.contentRect.width;\n",
+ " height = entry.contentRect.height;\n",
+ " }\n",
+ "\n",
+ " // Keep the size of the canvas and rubber band canvas in sync with\n",
+ " // the canvas container.\n",
+ " if (entry.devicePixelContentBoxSize) {\n",
+ " // Chrome 84 implements new version of spec.\n",
+ " canvas.setAttribute(\n",
+ " 'width',\n",
+ " entry.devicePixelContentBoxSize[0].inlineSize\n",
+ " );\n",
+ " canvas.setAttribute(\n",
+ " 'height',\n",
+ " entry.devicePixelContentBoxSize[0].blockSize\n",
+ " );\n",
+ " } else {\n",
+ " canvas.setAttribute('width', width * fig.ratio);\n",
+ " canvas.setAttribute('height', height * fig.ratio);\n",
+ " }\n",
+ " canvas.setAttribute(\n",
+ " 'style',\n",
+ " 'width: ' + width + 'px; height: ' + height + 'px;'\n",
+ " );\n",
+ "\n",
+ " rubberband_canvas.setAttribute('width', width);\n",
+ " rubberband_canvas.setAttribute('height', height);\n",
+ "\n",
+ " // And update the size in Python. We ignore the initial 0/0 size\n",
+ " // that occurs as the element is placed into the DOM, which should\n",
+ " // otherwise not happen due to the minimum size styling.\n",
+ " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
+ " fig.request_resize(width, height);\n",
+ " }\n",
+ " }\n",
+ " });\n",
+ " this.resizeObserverInstance.observe(canvas_div);\n",
+ "\n",
+ " function on_mouse_event_closure(name) {\n",
+ " return function (event) {\n",
+ " return fig.mouse_event(event, name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mousedown',\n",
+ " on_mouse_event_closure('button_press')\n",
+ " );\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseup',\n",
+ " on_mouse_event_closure('button_release')\n",
+ " );\n",
+ " // Throttle sequential mouse events to 1 every 20ms.\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mousemove',\n",
+ " on_mouse_event_closure('motion_notify')\n",
+ " );\n",
+ "\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseenter',\n",
+ " on_mouse_event_closure('figure_enter')\n",
+ " );\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseleave',\n",
+ " on_mouse_event_closure('figure_leave')\n",
+ " );\n",
+ "\n",
+ " canvas_div.addEventListener('wheel', function (event) {\n",
+ " if (event.deltaY < 0) {\n",
+ " event.step = 1;\n",
+ " } else {\n",
+ " event.step = -1;\n",
+ " }\n",
+ " on_mouse_event_closure('scroll')(event);\n",
+ " });\n",
+ "\n",
+ " canvas_div.appendChild(canvas);\n",
+ " canvas_div.appendChild(rubberband_canvas);\n",
+ "\n",
+ " this.rubberband_context = rubberband_canvas.getContext('2d');\n",
+ " this.rubberband_context.strokeStyle = '#000000';\n",
+ "\n",
+ " this._resize_canvas = function (width, height, forward) {\n",
+ " if (forward) {\n",
+ " canvas_div.style.width = width + 'px';\n",
+ " canvas_div.style.height = height + 'px';\n",
+ " }\n",
+ " };\n",
+ "\n",
+ " // Disable right mouse context menu.\n",
+ " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ " });\n",
+ "\n",
+ " function set_focus() {\n",
+ " canvas.focus();\n",
+ " canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " window.setTimeout(set_focus, 100);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var toolbar = document.createElement('div');\n",
+ " toolbar.classList = 'mpl-toolbar';\n",
+ " this.root.appendChild(toolbar);\n",
+ "\n",
+ " function on_click_closure(name) {\n",
+ " return function (_event) {\n",
+ " return fig.toolbar_button_onclick(name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " function on_mouseover_closure(tooltip) {\n",
+ " return function (event) {\n",
+ " if (!event.currentTarget.disabled) {\n",
+ " return fig.toolbar_button_onmouseover(tooltip);\n",
+ " }\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " fig.buttons = {};\n",
+ " var buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'mpl-button-group';\n",
+ " for (var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " /* Instead of a spacer, we start a new button group. */\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ " buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'mpl-button-group';\n",
+ " continue;\n",
+ " }\n",
+ "\n",
+ " var button = (fig.buttons[name] = document.createElement('button'));\n",
+ " button.classList = 'mpl-widget';\n",
+ " button.setAttribute('role', 'button');\n",
+ " button.setAttribute('aria-disabled', 'false');\n",
+ " button.addEventListener('click', on_click_closure(method_name));\n",
+ " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+ "\n",
+ " var icon_img = document.createElement('img');\n",
+ " icon_img.src = '_images/' + image + '.png';\n",
+ " icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
+ " icon_img.alt = tooltip;\n",
+ " button.appendChild(icon_img);\n",
+ "\n",
+ " buttonGroup.appendChild(button);\n",
+ " }\n",
+ "\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ "\n",
+ " var fmt_picker = document.createElement('select');\n",
+ " fmt_picker.classList = 'mpl-widget';\n",
+ " toolbar.appendChild(fmt_picker);\n",
+ " this.format_dropdown = fmt_picker;\n",
+ "\n",
+ " for (var ind in mpl.extensions) {\n",
+ " var fmt = mpl.extensions[ind];\n",
+ " var option = document.createElement('option');\n",
+ " option.selected = fmt === mpl.default_extension;\n",
+ " option.innerHTML = fmt;\n",
+ " fmt_picker.appendChild(option);\n",
+ " }\n",
+ "\n",
+ " var status_bar = document.createElement('span');\n",
+ " status_bar.classList = 'mpl-message';\n",
+ " toolbar.appendChild(status_bar);\n",
+ " this.message = status_bar;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
+ " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+ " // which will in turn request a refresh of the image.\n",
+ " this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.send_message = function (type, properties) {\n",
+ " properties['type'] = type;\n",
+ " properties['figure_id'] = this.id;\n",
+ " this.ws.send(JSON.stringify(properties));\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.send_draw_message = function () {\n",
+ " if (!this.waiting) {\n",
+ " this.waiting = true;\n",
+ " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+ " var format_dropdown = fig.format_dropdown;\n",
+ " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+ " fig.ondownload(fig, format);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
+ " var size = msg['size'];\n",
+ " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
+ " fig._resize_canvas(size[0], size[1], msg['forward']);\n",
+ " fig.send_message('refresh', {});\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
+ " var x0 = msg['x0'] / fig.ratio;\n",
+ " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
+ " var x1 = msg['x1'] / fig.ratio;\n",
+ " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
+ " x0 = Math.floor(x0) + 0.5;\n",
+ " y0 = Math.floor(y0) + 0.5;\n",
+ " x1 = Math.floor(x1) + 0.5;\n",
+ " y1 = Math.floor(y1) + 0.5;\n",
+ " var min_x = Math.min(x0, x1);\n",
+ " var min_y = Math.min(y0, y1);\n",
+ " var width = Math.abs(x1 - x0);\n",
+ " var height = Math.abs(y1 - y0);\n",
+ "\n",
+ " fig.rubberband_context.clearRect(\n",
+ " 0,\n",
+ " 0,\n",
+ " fig.canvas.width / fig.ratio,\n",
+ " fig.canvas.height / fig.ratio\n",
+ " );\n",
+ "\n",
+ " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
+ " // Updates the figure title.\n",
+ " fig.header.textContent = msg['label'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
+ " var cursor = msg['cursor'];\n",
+ " switch (cursor) {\n",
+ " case 0:\n",
+ " cursor = 'pointer';\n",
+ " break;\n",
+ " case 1:\n",
+ " cursor = 'default';\n",
+ " break;\n",
+ " case 2:\n",
+ " cursor = 'crosshair';\n",
+ " break;\n",
+ " case 3:\n",
+ " cursor = 'move';\n",
+ " break;\n",
+ " }\n",
+ " fig.rubberband_canvas.style.cursor = cursor;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
+ " fig.message.textContent = msg['message'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
+ " // Request the server to send over a new figure.\n",
+ " fig.send_draw_message();\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
+ " fig.image_mode = msg['mode'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
+ " for (var key in msg) {\n",
+ " if (!(key in fig.buttons)) {\n",
+ " continue;\n",
+ " }\n",
+ " fig.buttons[key].disabled = !msg[key];\n",
+ " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
+ " if (msg['mode'] === 'PAN') {\n",
+ " fig.buttons['Pan'].classList.add('active');\n",
+ " fig.buttons['Zoom'].classList.remove('active');\n",
+ " } else if (msg['mode'] === 'ZOOM') {\n",
+ " fig.buttons['Pan'].classList.remove('active');\n",
+ " fig.buttons['Zoom'].classList.add('active');\n",
+ " } else {\n",
+ " fig.buttons['Pan'].classList.remove('active');\n",
+ " fig.buttons['Zoom'].classList.remove('active');\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function () {\n",
+ " // Called whenever the canvas gets updated.\n",
+ " this.send_message('ack', {});\n",
+ "};\n",
+ "\n",
+ "// A function to construct a web socket function for onmessage handling.\n",
+ "// Called in the figure constructor.\n",
+ "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
+ " return function socket_on_message(evt) {\n",
+ " if (evt.data instanceof Blob) {\n",
+ " /* FIXME: We get \"Resource interpreted as Image but\n",
+ " * transferred with MIME type text/plain:\" errors on\n",
+ " * Chrome. But how to set the MIME type? It doesn't seem\n",
+ " * to be part of the websocket stream */\n",
+ " evt.data.type = 'image/png';\n",
+ "\n",
+ " /* Free the memory for the previous frames */\n",
+ " if (fig.imageObj.src) {\n",
+ " (window.URL || window.webkitURL).revokeObjectURL(\n",
+ " fig.imageObj.src\n",
+ " );\n",
+ " }\n",
+ "\n",
+ " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+ " evt.data\n",
+ " );\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " } else if (\n",
+ " typeof evt.data === 'string' &&\n",
+ " evt.data.slice(0, 21) === 'data:image/png;base64'\n",
+ " ) {\n",
+ " fig.imageObj.src = evt.data;\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " var msg = JSON.parse(evt.data);\n",
+ " var msg_type = msg['type'];\n",
+ "\n",
+ " // Call the \"handle_{type}\" callback, which takes\n",
+ " // the figure and JSON message as its only arguments.\n",
+ " try {\n",
+ " var callback = fig['handle_' + msg_type];\n",
+ " } catch (e) {\n",
+ " console.log(\n",
+ " \"No handler for the '\" + msg_type + \"' message type: \",\n",
+ " msg\n",
+ " );\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " if (callback) {\n",
+ " try {\n",
+ " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+ " callback(fig, msg);\n",
+ " } catch (e) {\n",
+ " console.log(\n",
+ " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
+ " e,\n",
+ " e.stack,\n",
+ " msg\n",
+ " );\n",
+ " }\n",
+ " }\n",
+ " };\n",
+ "};\n",
+ "\n",
+ "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+ "mpl.findpos = function (e) {\n",
+ " //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+ " var targ;\n",
+ " if (!e) {\n",
+ " e = window.event;\n",
+ " }\n",
+ " if (e.target) {\n",
+ " targ = e.target;\n",
+ " } else if (e.srcElement) {\n",
+ " targ = e.srcElement;\n",
+ " }\n",
+ " if (targ.nodeType === 3) {\n",
+ " // defeat Safari bug\n",
+ " targ = targ.parentNode;\n",
+ " }\n",
+ "\n",
+ " // pageX,Y are the mouse positions relative to the document\n",
+ " var boundingRect = targ.getBoundingClientRect();\n",
+ " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
+ " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
+ "\n",
+ " return { x: x, y: y };\n",
+ "};\n",
+ "\n",
+ "/*\n",
+ " * return a copy of an object with only non-object keys\n",
+ " * we need this to avoid circular references\n",
+ " * http://stackoverflow.com/a/24161582/3208463\n",
+ " */\n",
+ "function simpleKeys(original) {\n",
+ " return Object.keys(original).reduce(function (obj, key) {\n",
+ " if (typeof original[key] !== 'object') {\n",
+ " obj[key] = original[key];\n",
+ " }\n",
+ " return obj;\n",
+ " }, {});\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.mouse_event = function (event, name) {\n",
+ " var canvas_pos = mpl.findpos(event);\n",
+ "\n",
+ " if (name === 'button_press') {\n",
+ " this.canvas.focus();\n",
+ " this.canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " var x = canvas_pos.x * this.ratio;\n",
+ " var y = canvas_pos.y * this.ratio;\n",
+ "\n",
+ " this.send_message(name, {\n",
+ " x: x,\n",
+ " y: y,\n",
+ " button: event.button,\n",
+ " step: event.step,\n",
+ " guiEvent: simpleKeys(event),\n",
+ " });\n",
+ "\n",
+ " /* This prevents the web browser from automatically changing to\n",
+ " * the text insertion cursor when the button is pressed. We want\n",
+ " * to control all of the cursor setting manually through the\n",
+ " * 'cursor' event from matplotlib */\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
+ " // Handle any extra behaviour associated with a key event\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.key_event = function (event, name) {\n",
+ " // Prevent repeat events\n",
+ " if (name === 'key_press') {\n",
+ " if (event.which === this._key) {\n",
+ " return;\n",
+ " } else {\n",
+ " this._key = event.which;\n",
+ " }\n",
+ " }\n",
+ " if (name === 'key_release') {\n",
+ " this._key = null;\n",
+ " }\n",
+ "\n",
+ " var value = '';\n",
+ " if (event.ctrlKey && event.which !== 17) {\n",
+ " value += 'ctrl+';\n",
+ " }\n",
+ " if (event.altKey && event.which !== 18) {\n",
+ " value += 'alt+';\n",
+ " }\n",
+ " if (event.shiftKey && event.which !== 16) {\n",
+ " value += 'shift+';\n",
+ " }\n",
+ "\n",
+ " value += 'k';\n",
+ " value += event.which.toString();\n",
+ "\n",
+ " this._key_event_extra(event, name);\n",
+ "\n",
+ " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
+ " return false;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
+ " if (name === 'download') {\n",
+ " this.handle_save(this, null);\n",
+ " } else {\n",
+ " this.send_message('toolbar_button', { name: name });\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
+ " this.message.textContent = tooltip;\n",
+ "};\n",
+ "\n",
+ "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
+ "// prettier-ignore\n",
+ "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
+ "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+ "\n",
+ "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
+ "\n",
+ "mpl.default_extension = \"png\";/* global mpl */\n",
+ "\n",
+ "var comm_websocket_adapter = function (comm) {\n",
+ " // Create a \"websocket\"-like object which calls the given IPython comm\n",
+ " // object with the appropriate methods. Currently this is a non binary\n",
+ " // socket, so there is still some room for performance tuning.\n",
+ " var ws = {};\n",
+ "\n",
+ " ws.close = function () {\n",
+ " comm.close();\n",
+ " };\n",
+ " ws.send = function (m) {\n",
+ " //console.log('sending', m);\n",
+ " comm.send(m);\n",
+ " };\n",
+ " // Register the callback with on_msg.\n",
+ " comm.on_msg(function (msg) {\n",
+ " //console.log('receiving', msg['content']['data'], msg);\n",
+ " // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
+ " ws.onmessage(msg['content']['data']);\n",
+ " });\n",
+ " return ws;\n",
+ "};\n",
+ "\n",
+ "mpl.mpl_figure_comm = function (comm, msg) {\n",
+ " // This is the function which gets called when the mpl process\n",
+ " // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+ "\n",
+ " var id = msg.content.data.id;\n",
+ " // Get hold of the div created by the display call when the Comm\n",
+ " // socket was opened in Python.\n",
+ " var element = document.getElementById(id);\n",
+ " var ws_proxy = comm_websocket_adapter(comm);\n",
+ "\n",
+ " function ondownload(figure, _format) {\n",
+ " window.open(figure.canvas.toDataURL());\n",
+ " }\n",
+ "\n",
+ " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
+ "\n",
+ " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+ " // web socket which is closed, not our websocket->open comm proxy.\n",
+ " ws_proxy.onopen();\n",
+ "\n",
+ " fig.parent_element = element;\n",
+ " fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+ " if (!fig.cell_info) {\n",
+ " console.error('Failed to find cell for figure', id, fig);\n",
+ " return;\n",
+ " }\n",
+ " fig.cell_info[0].output_area.element.on(\n",
+ " 'cleared',\n",
+ " { fig: fig },\n",
+ " fig._remove_fig_handler\n",
+ " );\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
+ " var width = fig.canvas.width / fig.ratio;\n",
+ " fig.cell_info[0].output_area.element.off(\n",
+ " 'cleared',\n",
+ " fig._remove_fig_handler\n",
+ " );\n",
+ " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
+ "\n",
+ " // Update the output cell to use the data from the current canvas.\n",
+ " fig.push_to_output();\n",
+ " var dataURL = fig.canvas.toDataURL();\n",
+ " // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+ " // the notebook keyboard shortcuts fail.\n",
+ " IPython.keyboard_manager.enable();\n",
+ " fig.parent_element.innerHTML =\n",
+ " '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ " fig.close_ws(fig, msg);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
+ " fig.send_message('closing', msg);\n",
+ " // fig.ws.close()\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
+ " // Turn the data on the canvas into data in the output cell.\n",
+ " var width = this.canvas.width / this.ratio;\n",
+ " var dataURL = this.canvas.toDataURL();\n",
+ " this.cell_info[1]['text/html'] =\n",
+ " '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function () {\n",
+ " // Tell IPython that the notebook contents must change.\n",
+ " IPython.notebook.set_dirty(true);\n",
+ " this.send_message('ack', {});\n",
+ " var fig = this;\n",
+ " // Wait a second, then push the new image to the DOM so\n",
+ " // that it is saved nicely (might be nice to debounce this).\n",
+ " setTimeout(function () {\n",
+ " fig.push_to_output();\n",
+ " }, 1000);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var toolbar = document.createElement('div');\n",
+ " toolbar.classList = 'btn-toolbar';\n",
+ " this.root.appendChild(toolbar);\n",
+ "\n",
+ " function on_click_closure(name) {\n",
+ " return function (_event) {\n",
+ " return fig.toolbar_button_onclick(name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " function on_mouseover_closure(tooltip) {\n",
+ " return function (event) {\n",
+ " if (!event.currentTarget.disabled) {\n",
+ " return fig.toolbar_button_onmouseover(tooltip);\n",
+ " }\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " fig.buttons = {};\n",
+ " var buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'btn-group';\n",
+ " var button;\n",
+ " for (var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " /* Instead of a spacer, we start a new button group. */\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ " buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'btn-group';\n",
+ " continue;\n",
+ " }\n",
+ "\n",
+ " button = fig.buttons[name] = document.createElement('button');\n",
+ " button.classList = 'btn btn-default';\n",
+ " button.href = '#';\n",
+ " button.title = name;\n",
+ " button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
+ " button.addEventListener('click', on_click_closure(method_name));\n",
+ " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+ " buttonGroup.appendChild(button);\n",
+ " }\n",
+ "\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ "\n",
+ " // Add the status bar.\n",
+ " var status_bar = document.createElement('span');\n",
+ " status_bar.classList = 'mpl-message pull-right';\n",
+ " toolbar.appendChild(status_bar);\n",
+ " this.message = status_bar;\n",
+ "\n",
+ " // Add the close button to the window.\n",
+ " var buttongrp = document.createElement('div');\n",
+ " buttongrp.classList = 'btn-group inline pull-right';\n",
+ " button = document.createElement('button');\n",
+ " button.classList = 'btn btn-mini btn-primary';\n",
+ " button.href = '#';\n",
+ " button.title = 'Stop Interaction';\n",
+ " button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
+ " button.addEventListener('click', function (_evt) {\n",
+ " fig.handle_close(fig, {});\n",
+ " });\n",
+ " button.addEventListener(\n",
+ " 'mouseover',\n",
+ " on_mouseover_closure('Stop Interaction')\n",
+ " );\n",
+ " buttongrp.appendChild(button);\n",
+ " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
+ " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
+ " var fig = event.data.fig;\n",
+ " if (event.target !== this) {\n",
+ " // Ignore bubbled events from children.\n",
+ " return;\n",
+ " }\n",
+ " fig.close_ws(fig, {});\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function (el) {\n",
+ " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
+ " // this is important to make the div 'focusable\n",
+ " el.setAttribute('tabindex', 0);\n",
+ " // reach out to IPython and tell the keyboard manager to turn it's self\n",
+ " // off when our div gets focus\n",
+ "\n",
+ " // location in version 3\n",
+ " if (IPython.notebook.keyboard_manager) {\n",
+ " IPython.notebook.keyboard_manager.register_events(el);\n",
+ " } else {\n",
+ " // location in version 2\n",
+ " IPython.keyboard_manager.register_events(el);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
+ " var manager = IPython.notebook.keyboard_manager;\n",
+ " if (!manager) {\n",
+ " manager = IPython.keyboard_manager;\n",
+ " }\n",
+ "\n",
+ " // Check for shift+enter\n",
+ " if (event.shiftKey && event.which === 13) {\n",
+ " this.canvas_div.blur();\n",
+ " // select the cell after this one\n",
+ " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
+ " IPython.notebook.select(index + 1);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+ " fig.ondownload(fig, null);\n",
+ "};\n",
+ "\n",
+ "mpl.find_output_cell = function (html_output) {\n",
+ " // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+ " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+ " // IPython event is triggered only after the cells have been serialised, which for\n",
+ " // our purposes (turning an active figure into a static one), is too late.\n",
+ " var cells = IPython.notebook.get_cells();\n",
+ " var ncells = cells.length;\n",
+ " for (var i = 0; i < ncells; i++) {\n",
+ " var cell = cells[i];\n",
+ " if (cell.cell_type === 'code') {\n",
+ " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
+ " var data = cell.output_area.outputs[j];\n",
+ " if (data.data) {\n",
+ " // IPython >= 3 moved mimebundle to data attribute of output\n",
+ " data = data.data;\n",
+ " }\n",
+ " if (data['text/html'] === html_output) {\n",
+ " return [cell, data, j];\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "// Register the function which deals with the matplotlib target/channel.\n",
+ "// The kernel may be null if the page has been refreshed.\n",
+ "if (IPython.notebook.kernel !== null) {\n",
+ " IPython.notebook.kernel.comm_manager.register_target(\n",
+ " 'matplotlib',\n",
+ " mpl.mpl_figure_comm\n",
+ " );\n",
+ "}\n"
+ ],
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+ "metadata": {},
+ "output_type": "display_data"
+ },
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+ "data": {
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\" width=\"1000\">"
+ ],
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ]
},
+ "metadata": {},
"output_type": "display_data"
}
],
@@ -768,8 +3553,7 @@
"source": [
"### Contact us at the EuXFEL Data Analysis group at any time if you need help analysing your data!\n",
"\n",
- "#### Danilo Ferreira de Lima: danilo.enoque.ferreira.de.lima@xfel.eu\n",
- "#### Arman Davtyan: arman.davtyan@xfel.eu"
+ "#### Data Analysis group: da@xfel.eu"
]
},
{
@@ -797,7 +3581,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.7.10"
+ "version": "3.6.13"
}
},
"nbformat": 4,
diff --git a/Supervised regression.ipynb b/Supervised regression.ipynb
index e14ea8b..89ffc2f 100644
--- a/Supervised regression.ipynb
+++ b/Supervised regression.ipynb
@@ -14,7 +14,7 @@
},
{
"cell_type": "code",
- "execution_count": 23,
+ "execution_count": 1,
"id": "d0681795",
"metadata": {},
"outputs": [
@@ -22,91 +22,31 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "Requirement already satisfied: torchvision in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (0.10.0)\n",
- "Requirement already satisfied: torch in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (1.9.0)\n",
- "Requirement already satisfied: pandas in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (1.3.0)\n",
- "Requirement already satisfied: numpy in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (1.19.2)\n",
- "Requirement already satisfied: matplotlib in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (3.4.2)\n",
- "Requirement already satisfied: ipympl in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (0.8.2)\n",
- "Collecting torchbnn\n",
- " Downloading torchbnn-1.2-py3-none-any.whl (12 kB)\n",
- "Requirement already satisfied: pillow>=5.3.0 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from torchvision) (8.3.1)\n",
- "Requirement already satisfied: typing_extensions in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from torch) (3.10.0.0)\n",
- "Requirement already satisfied: python-dateutil>=2.7.3 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from pandas) (2.8.2)\n",
- "Requirement already satisfied: pytz>=2017.3 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from pandas) (2021.1)\n",
- "Requirement already satisfied: six>=1.5 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from python-dateutil>=2.7.3->pandas) (1.16.0)\n",
- "Requirement already satisfied: pyparsing>=2.2.1 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from matplotlib) (2.4.7)\n",
- "Requirement already satisfied: kiwisolver>=1.0.1 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from matplotlib) (1.3.1)\n",
- "Requirement already satisfied: cycler>=0.10 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from matplotlib) (0.10.0)\n",
- "Requirement already satisfied: ipywidgets>=7.6.0 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from ipympl) (7.6.3)\n",
- "Requirement already satisfied: ipykernel>=4.7 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from ipympl) (5.5.5)\n",
- "Requirement already satisfied: tornado>=4.2 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from ipykernel>=4.7->ipympl) (6.1)\n",
- "Requirement already satisfied: jupyter-client in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from ipykernel>=4.7->ipympl) (6.1.12)\n",
- "Requirement already satisfied: ipython>=5.0.0 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from ipykernel>=4.7->ipympl) (7.25.0)\n",
- "Requirement already satisfied: traitlets>=4.1.0 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from ipykernel>=4.7->ipympl) (5.0.5)\n",
- "Requirement already satisfied: prompt-toolkit!=3.0.0,!=3.0.1,<3.1.0,>=2.0.0 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from ipython>=5.0.0->ipykernel>=4.7->ipympl) (3.0.19)\n",
- "Requirement already satisfied: pickleshare in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from ipython>=5.0.0->ipykernel>=4.7->ipympl) (0.7.5)\n",
- "Requirement already satisfied: decorator in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from ipython>=5.0.0->ipykernel>=4.7->ipympl) (5.0.9)\n",
- "Requirement already satisfied: jedi>=0.16 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from ipython>=5.0.0->ipykernel>=4.7->ipympl) (0.18.0)\n",
- "Requirement already satisfied: pygments in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from ipython>=5.0.0->ipykernel>=4.7->ipympl) (2.9.0)\n",
- "Requirement already satisfied: backcall in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from ipython>=5.0.0->ipykernel>=4.7->ipympl) (0.2.0)\n",
- "Requirement already satisfied: setuptools>=18.5 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from ipython>=5.0.0->ipykernel>=4.7->ipympl) (49.6.0.post20210108)\n",
- "Requirement already satisfied: matplotlib-inline in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from ipython>=5.0.0->ipykernel>=4.7->ipympl) (0.1.2)\n",
- "Requirement already satisfied: pexpect>4.3 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from ipython>=5.0.0->ipykernel>=4.7->ipympl) (4.8.0)\n",
- "Requirement already satisfied: widgetsnbextension~=3.5.0 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from ipywidgets>=7.6.0->ipympl) (3.5.1)\n",
- "Requirement already satisfied: jupyterlab-widgets>=1.0.0 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from ipywidgets>=7.6.0->ipympl) (1.0.0)\n",
- "Requirement already satisfied: nbformat>=4.2.0 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from ipywidgets>=7.6.0->ipympl) (5.1.3)\n",
- "Requirement already satisfied: parso<0.9.0,>=0.8.0 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from jedi>=0.16->ipython>=5.0.0->ipykernel>=4.7->ipympl) (0.8.2)\n",
- "Requirement already satisfied: jupyter-core in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from nbformat>=4.2.0->ipywidgets>=7.6.0->ipympl) (4.7.1)\n",
- "Requirement already satisfied: jsonschema!=2.5.0,>=2.4 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from nbformat>=4.2.0->ipywidgets>=7.6.0->ipympl) (3.2.0)\n",
- "Requirement already satisfied: ipython-genutils in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from nbformat>=4.2.0->ipywidgets>=7.6.0->ipympl) (0.2.0)\n",
- "Requirement already satisfied: pyrsistent>=0.14.0 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from jsonschema!=2.5.0,>=2.4->nbformat>=4.2.0->ipywidgets>=7.6.0->ipympl) (0.17.3)\n",
- "Requirement already satisfied: importlib-metadata in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from jsonschema!=2.5.0,>=2.4->nbformat>=4.2.0->ipywidgets>=7.6.0->ipympl) (1.7.0)\n",
- "Requirement already satisfied: attrs>=17.4.0 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from jsonschema!=2.5.0,>=2.4->nbformat>=4.2.0->ipywidgets>=7.6.0->ipympl) (21.2.0)\n",
- "Requirement already satisfied: ptyprocess>=0.5 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from pexpect>4.3->ipython>=5.0.0->ipykernel>=4.7->ipympl) (0.7.0)\n",
- "Requirement already satisfied: wcwidth in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from prompt-toolkit!=3.0.0,!=3.0.1,<3.1.0,>=2.0.0->ipython>=5.0.0->ipykernel>=4.7->ipympl) (0.2.5)\n",
- "Requirement already satisfied: notebook>=4.4.1 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from widgetsnbextension~=3.5.0->ipywidgets>=7.6.0->ipympl) (6.4.0)\n",
- "Requirement already satisfied: nbconvert in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.6.0->ipympl) (6.1.0)\n",
- "Requirement already satisfied: prometheus-client in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.6.0->ipympl) (0.11.0)\n",
- "Requirement already satisfied: jinja2 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.6.0->ipympl) (3.0.1)\n",
- "Requirement already satisfied: Send2Trash>=1.5.0 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.6.0->ipympl) (1.7.1)\n",
- "Requirement already satisfied: argon2-cffi in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.6.0->ipympl) (20.1.0)\n",
- "Requirement already satisfied: pyzmq>=17 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.6.0->ipympl) (22.1.0)\n",
- "Requirement already satisfied: terminado>=0.8.3 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.6.0->ipympl) (0.10.1)\n",
- "Requirement already satisfied: cffi>=1.0.0 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from argon2-cffi->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.6.0->ipympl) (1.14.6)\n",
- "Requirement already satisfied: pycparser in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from cffi>=1.0.0->argon2-cffi->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.6.0->ipympl) (2.20)\n",
- "Requirement already satisfied: zipp>=0.5 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from importlib-metadata->jsonschema!=2.5.0,>=2.4->nbformat>=4.2.0->ipywidgets>=7.6.0->ipympl) (3.5.0)\n",
- "Requirement already satisfied: MarkupSafe>=2.0 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from jinja2->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.6.0->ipympl) (2.0.1)\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Requirement already satisfied: entrypoints>=0.2.2 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.6.0->ipympl) (0.3)\n",
- "Requirement already satisfied: pandocfilters>=1.4.1 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.6.0->ipympl) (1.4.2)\n",
- "Requirement already satisfied: mistune<2,>=0.8.1 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.6.0->ipympl) (0.8.4)\n",
- "Requirement already satisfied: jupyterlab-pygments in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.6.0->ipympl) (0.1.2)\n",
- "Requirement already satisfied: bleach in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.6.0->ipympl) (3.3.1)\n",
- "Requirement already satisfied: defusedxml in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.6.0->ipympl) (0.7.1)\n",
- "Requirement already satisfied: nbclient<0.6.0,>=0.5.0 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.6.0->ipympl) (0.5.3)\n",
- "Requirement already satisfied: testpath in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.6.0->ipympl) (0.5.0)\n",
- "Requirement already satisfied: async-generator in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from nbclient<0.6.0,>=0.5.0->nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.6.0->ipympl) (1.10)\n",
- "Requirement already satisfied: nest-asyncio in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from nbclient<0.6.0,>=0.5.0->nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.6.0->ipympl) (1.5.1)\n",
- "Requirement already satisfied: packaging in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from bleach->nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.6.0->ipympl) (21.0)\n",
- "Requirement already satisfied: webencodings in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from bleach->nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.6.0->ipympl) (0.5.1)\n",
- "Installing collected packages: torchbnn\n",
- "Successfully installed torchbnn-1.2\n"
+ "Requirement already satisfied: torchvision in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (0.11.2)\r\n",
+ "Requirement already satisfied: torch in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (1.10.1)\r\n",
+ "Requirement already satisfied: pandas in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (1.1.5)\r\n",
+ "Requirement already satisfied: numpy in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (1.19.2)\r\n",
+ "Requirement already satisfied: matplotlib in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (3.3.4)\r\n",
+ "Requirement already satisfied: torchbnn in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (1.2)\r\n",
+ "Requirement already satisfied: pillow!=8.3.0,>=5.3.0 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from torchvision) (8.3.1)\r\n",
+ "Requirement already satisfied: typing_extensions in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from torch) (3.10.0.2)\r\n",
+ "Requirement already satisfied: dataclasses in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from torch) (0.8)\r\n",
+ "Requirement already satisfied: python-dateutil>=2.7.3 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from pandas) (2.8.2)\r\n",
+ "Requirement already satisfied: pytz>=2017.2 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from pandas) (2021.3)\r\n",
+ "Requirement already satisfied: kiwisolver>=1.0.1 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from matplotlib) (1.3.1)\r\n",
+ "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.3 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from matplotlib) (3.0.4)\r\n",
+ "Requirement already satisfied: cycler>=0.10 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from matplotlib) (0.11.0)\r\n",
+ "Requirement already satisfied: six>=1.5 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from python-dateutil>=2.7.3->pandas) (1.16.0)\r\n"
]
}
],
"source": [
- "!pip install torchvision torch pandas numpy matplotlib ipympl torchbnn"
+ "!pip install torchvision torch pandas numpy matplotlib torchbnn"
]
},
{
"cell_type": "code",
- "execution_count": 1,
+ "execution_count": 2,
"id": "23feddde",
"metadata": {},
"outputs": [],
@@ -156,7 +96,7 @@
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": 3,
"id": "5d457cd8",
"metadata": {},
"outputs": [],
@@ -181,7 +121,7 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": 4,
"id": "30205402",
"metadata": {},
"outputs": [],
@@ -199,7 +139,7 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": 5,
"id": "cc0b0774",
"metadata": {},
"outputs": [
@@ -218,7 +158,7 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 6,
"id": "6dccfac6",
"metadata": {},
"outputs": [
@@ -226,7 +166,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "{'data': array([-0.5583114], dtype=float32), 'target': array([-11.577045], dtype=float32)}\n"
+ "{'data': array([1.1675025], dtype=float32), 'target': array([12.259927], dtype=float32)}\n"
]
}
],
@@ -244,7 +184,7 @@
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": 7,
"id": "067b8105",
"metadata": {},
"outputs": [
@@ -498,10 +438,6 @@
" 'mouseup',\n",
" on_mouse_event_closure('button_release')\n",
" );\n",
- " rubberband_canvas.addEventListener(\n",
- " 'dblclick',\n",
- " on_mouse_event_closure('dblclick')\n",
- " );\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband_canvas.addEventListener(\n",
" 'mousemove',\n",
@@ -759,14 +695,11 @@
"mpl.figure.prototype._make_on_message_function = function (fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
- " var img = evt.data;\n",
- " if (img.type !== 'image/png') {\n",
- " /* FIXME: We get \"Resource interpreted as Image but\n",
- " * transferred with MIME type text/plain:\" errors on\n",
- " * Chrome. But how to set the MIME type? It doesn't seem\n",
- " * to be part of the websocket stream */\n",
- " img.type = 'image/png';\n",
- " }\n",
+ " /* FIXME: We get \"Resource interpreted as Image but\n",
+ " * transferred with MIME type text/plain:\" errors on\n",
+ " * Chrome. But how to set the MIME type? It doesn't seem\n",
+ " * to be part of the websocket stream */\n",
+ " evt.data.type = 'image/png';\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
@@ -776,7 +709,7 @@
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
- " img\n",
+ " evt.data\n",
" );\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
@@ -895,10 +828,10 @@
"mpl.figure.prototype.key_event = function (event, name) {\n",
" // Prevent repeat events\n",
" if (name === 'key_press') {\n",
- " if (event.key === this._key) {\n",
+ " if (event.which === this._key) {\n",
" return;\n",
" } else {\n",
- " this._key = event.key;\n",
+ " this._key = event.which;\n",
" }\n",
" }\n",
" if (name === 'key_release') {\n",
@@ -906,17 +839,18 @@
" }\n",
"\n",
" var value = '';\n",
- " if (event.ctrlKey && event.key !== 'Control') {\n",
+ " if (event.ctrlKey && event.which !== 17) {\n",
" value += 'ctrl+';\n",
" }\n",
- " else if (event.altKey && event.key !== 'Alt') {\n",
+ " if (event.altKey && event.which !== 18) {\n",
" value += 'alt+';\n",
" }\n",
- " else if (event.shiftKey && event.key !== 'Shift') {\n",
+ " if (event.shiftKey && event.which !== 16) {\n",
" value += 'shift+';\n",
" }\n",
"\n",
- " value += 'k' + event.key;\n",
+ " value += 'k';\n",
+ " value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
@@ -941,7 +875,7 @@
"var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
- "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
+ "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";/* global mpl */\n",
"\n",
@@ -951,19 +885,6 @@
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
- " ws.binaryType = comm.kernel.ws.binaryType;\n",
- " ws.readyState = comm.kernel.ws.readyState;\n",
- " function updateReadyState(_event) {\n",
- " if (comm.kernel.ws) {\n",
- " ws.readyState = comm.kernel.ws.readyState;\n",
- " } else {\n",
- " ws.readyState = 3; // Closed state.\n",
- " }\n",
- " }\n",
- " comm.kernel.ws.addEventListener('open', updateReadyState);\n",
- " comm.kernel.ws.addEventListener('close', updateReadyState);\n",
- " comm.kernel.ws.addEventListener('error', updateReadyState);\n",
- "\n",
" ws.close = function () {\n",
" comm.close();\n",
" };\n",
@@ -974,14 +895,8 @@
" // Register the callback with on_msg.\n",
" comm.on_msg(function (msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
- " var data = msg['content']['data'];\n",
- " if (data['blob'] !== undefined) {\n",
- " data = {\n",
- " data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
- " };\n",
- " }\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
- " ws.onmessage(data);\n",
+ " ws.onmessage(msg['content']['data']);\n",
" });\n",
" return ws;\n",
"};\n",
@@ -1234,7 +1149,7 @@
{
"data": {
"text/html": [
- "<img 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\" 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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
@@ -1265,7 +1180,7 @@
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 8,
"id": "d908ef86",
"metadata": {},
"outputs": [],
@@ -1315,7 +1230,7 @@
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": 9,
"id": "988e1979",
"metadata": {},
"outputs": [],
@@ -1336,7 +1251,7 @@
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": 10,
"id": "d15d655d",
"metadata": {},
"outputs": [
@@ -1344,106 +1259,106 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "Epoch 0/100: average loss 378.81588\n",
- "Epoch 1/100: average loss 275.14966\n",
- "Epoch 2/100: average loss 209.67680\n",
- "Epoch 3/100: average loss 177.45487\n",
- "Epoch 4/100: average loss 161.36641\n",
- "Epoch 5/100: average loss 151.22071\n",
- "Epoch 6/100: average loss 143.62892\n",
- "Epoch 7/100: average loss 137.58497\n",
- "Epoch 8/100: average loss 132.61164\n",
- "Epoch 9/100: average loss 128.38996\n",
- "Epoch 10/100: average loss 124.72414\n",
- "Epoch 11/100: average loss 121.49631\n",
- "Epoch 12/100: average loss 118.62273\n",
- "Epoch 13/100: average loss 116.04727\n",
- "Epoch 14/100: average loss 113.73365\n",
- "Epoch 15/100: average loss 111.67534\n",
- "Epoch 16/100: average loss 109.85956\n",
- "Epoch 17/100: average loss 108.26555\n",
- "Epoch 18/100: average loss 106.88248\n",
- "Epoch 19/100: average loss 105.69173\n",
- "Epoch 20/100: average loss 104.67635\n",
- "Epoch 21/100: average loss 103.80502\n",
- "Epoch 22/100: average loss 103.06343\n",
- "Epoch 23/100: average loss 102.43223\n",
- "Epoch 24/100: average loss 101.89756\n",
- "Epoch 25/100: average loss 101.43507\n",
- "Epoch 26/100: average loss 101.03641\n",
- "Epoch 27/100: average loss 100.68191\n",
- "Epoch 28/100: average loss 100.35821\n",
- "Epoch 29/100: average loss 100.06578\n",
- "Epoch 30/100: average loss 99.79758\n",
- "Epoch 31/100: average loss 99.54630\n",
- "Epoch 32/100: average loss 99.31432\n",
- "Epoch 33/100: average loss 99.08812\n",
- "Epoch 34/100: average loss 98.87219\n",
- "Epoch 35/100: average loss 98.67368\n",
- "Epoch 36/100: average loss 98.48651\n",
- "Epoch 37/100: average loss 98.31420\n",
- "Epoch 38/100: average loss 98.15310\n",
- "Epoch 39/100: average loss 97.99930\n",
- "Epoch 40/100: average loss 97.85031\n",
- "Epoch 41/100: average loss 97.71002\n",
- "Epoch 42/100: average loss 97.57293\n",
- "Epoch 43/100: average loss 97.44047\n",
- "Epoch 44/100: average loss 97.31417\n",
- "Epoch 45/100: average loss 97.18990\n",
- "Epoch 46/100: average loss 97.07419\n",
- "Epoch 47/100: average loss 96.96548\n",
- "Epoch 48/100: average loss 96.86184\n",
- "Epoch 49/100: average loss 96.76805\n",
- "Epoch 50/100: average loss 96.67791\n",
- "Epoch 51/100: average loss 96.59360\n",
- "Epoch 52/100: average loss 96.51472\n",
- "Epoch 53/100: average loss 96.43937\n",
- "Epoch 54/100: average loss 96.36539\n",
- "Epoch 55/100: average loss 96.29459\n",
- "Epoch 56/100: average loss 96.22356\n",
- "Epoch 57/100: average loss 96.15634\n",
- "Epoch 58/100: average loss 96.08934\n",
- "Epoch 59/100: average loss 96.02401\n",
- "Epoch 60/100: average loss 95.96307\n",
- "Epoch 61/100: average loss 95.90349\n",
- "Epoch 62/100: average loss 95.84973\n",
- "Epoch 63/100: average loss 95.79636\n",
- "Epoch 64/100: average loss 95.74215\n",
- "Epoch 65/100: average loss 95.69529\n",
- "Epoch 66/100: average loss 95.64951\n",
- "Epoch 67/100: average loss 95.60449\n",
- "Epoch 68/100: average loss 95.56373\n",
- "Epoch 69/100: average loss 95.52165\n",
- "Epoch 70/100: average loss 95.48233\n",
- "Epoch 71/100: average loss 95.44179\n",
- "Epoch 72/100: average loss 95.39826\n",
- "Epoch 73/100: average loss 95.35763\n",
- "Epoch 74/100: average loss 95.31944\n",
- "Epoch 75/100: average loss 95.27754\n",
- "Epoch 76/100: average loss 95.23919\n",
- "Epoch 77/100: average loss 95.20086\n",
- "Epoch 78/100: average loss 95.16258\n",
- "Epoch 79/100: average loss 95.12233\n",
- "Epoch 80/100: average loss 95.08201\n",
- "Epoch 81/100: average loss 95.04595\n",
- "Epoch 82/100: average loss 95.01281\n",
- "Epoch 83/100: average loss 94.97996\n",
- "Epoch 84/100: average loss 94.94827\n",
- "Epoch 85/100: average loss 94.91624\n",
- "Epoch 86/100: average loss 94.88639\n",
- "Epoch 87/100: average loss 94.85546\n",
- "Epoch 88/100: average loss 94.82733\n",
- "Epoch 89/100: average loss 94.79647\n",
- "Epoch 90/100: average loss 94.77049\n",
- "Epoch 91/100: average loss 94.74167\n",
- "Epoch 92/100: average loss 94.71930\n",
- "Epoch 93/100: average loss 94.69341\n",
- "Epoch 94/100: average loss 94.66904\n",
- "Epoch 95/100: average loss 94.64581\n",
- "Epoch 96/100: average loss 94.61936\n",
- "Epoch 97/100: average loss 94.59652\n",
- "Epoch 98/100: average loss 94.57301\n",
- "Epoch 99/100: average loss 94.55085\n"
+ "Epoch 0/100: average loss 463.27606\n",
+ "Epoch 1/100: average loss 323.28888\n",
+ "Epoch 2/100: average loss 234.26296\n",
+ "Epoch 3/100: average loss 194.53857\n",
+ "Epoch 4/100: average loss 177.44959\n",
+ "Epoch 5/100: average loss 167.27537\n",
+ "Epoch 6/100: average loss 159.72572\n",
+ "Epoch 7/100: average loss 153.60603\n",
+ "Epoch 8/100: average loss 148.43027\n",
+ "Epoch 9/100: average loss 143.90963\n",
+ "Epoch 10/100: average loss 139.86888\n",
+ "Epoch 11/100: average loss 136.22562\n",
+ "Epoch 12/100: average loss 132.94330\n",
+ "Epoch 13/100: average loss 130.02063\n",
+ "Epoch 14/100: average loss 127.45114\n",
+ "Epoch 15/100: average loss 125.22582\n",
+ "Epoch 16/100: average loss 123.31896\n",
+ "Epoch 17/100: average loss 121.69351\n",
+ "Epoch 18/100: average loss 120.31040\n",
+ "Epoch 19/100: average loss 119.12970\n",
+ "Epoch 20/100: average loss 118.11008\n",
+ "Epoch 21/100: average loss 117.21726\n",
+ "Epoch 22/100: average loss 116.42635\n",
+ "Epoch 23/100: average loss 115.71731\n",
+ "Epoch 24/100: average loss 115.06646\n",
+ "Epoch 25/100: average loss 114.46563\n",
+ "Epoch 26/100: average loss 113.90477\n",
+ "Epoch 27/100: average loss 113.37237\n",
+ "Epoch 28/100: average loss 112.87031\n",
+ "Epoch 29/100: average loss 112.39047\n",
+ "Epoch 30/100: average loss 111.93409\n",
+ "Epoch 31/100: average loss 111.49390\n",
+ "Epoch 32/100: average loss 111.06857\n",
+ "Epoch 33/100: average loss 110.65716\n",
+ "Epoch 34/100: average loss 110.25265\n",
+ "Epoch 35/100: average loss 109.86220\n",
+ "Epoch 36/100: average loss 109.48867\n",
+ "Epoch 37/100: average loss 109.12127\n",
+ "Epoch 38/100: average loss 108.76681\n",
+ "Epoch 39/100: average loss 108.42491\n",
+ "Epoch 40/100: average loss 108.09927\n",
+ "Epoch 41/100: average loss 107.78307\n",
+ "Epoch 42/100: average loss 107.47245\n",
+ "Epoch 43/100: average loss 107.17395\n",
+ "Epoch 44/100: average loss 106.88436\n",
+ "Epoch 45/100: average loss 106.60057\n",
+ "Epoch 46/100: average loss 106.32841\n",
+ "Epoch 47/100: average loss 106.06270\n",
+ "Epoch 48/100: average loss 105.80896\n",
+ "Epoch 49/100: average loss 105.56264\n",
+ "Epoch 50/100: average loss 105.32331\n",
+ "Epoch 51/100: average loss 105.09678\n",
+ "Epoch 52/100: average loss 104.87590\n",
+ "Epoch 53/100: average loss 104.66059\n",
+ "Epoch 54/100: average loss 104.45863\n",
+ "Epoch 55/100: average loss 104.25898\n",
+ "Epoch 56/100: average loss 104.06311\n",
+ "Epoch 57/100: average loss 103.87301\n",
+ "Epoch 58/100: average loss 103.69415\n",
+ "Epoch 59/100: average loss 103.52273\n",
+ "Epoch 60/100: average loss 103.35392\n",
+ "Epoch 61/100: average loss 103.19550\n",
+ "Epoch 62/100: average loss 103.04080\n",
+ "Epoch 63/100: average loss 102.88722\n",
+ "Epoch 64/100: average loss 102.73497\n",
+ "Epoch 65/100: average loss 102.58267\n",
+ "Epoch 66/100: average loss 102.43699\n",
+ "Epoch 67/100: average loss 102.30370\n",
+ "Epoch 68/100: average loss 102.17610\n",
+ "Epoch 69/100: average loss 102.05236\n",
+ "Epoch 70/100: average loss 101.93588\n",
+ "Epoch 71/100: average loss 101.82917\n",
+ "Epoch 72/100: average loss 101.72810\n",
+ "Epoch 73/100: average loss 101.63402\n",
+ "Epoch 74/100: average loss 101.54512\n",
+ "Epoch 75/100: average loss 101.45931\n",
+ "Epoch 76/100: average loss 101.37704\n",
+ "Epoch 77/100: average loss 101.29983\n",
+ "Epoch 78/100: average loss 101.22755\n",
+ "Epoch 79/100: average loss 101.16446\n",
+ "Epoch 80/100: average loss 101.09839\n",
+ "Epoch 81/100: average loss 101.03817\n",
+ "Epoch 82/100: average loss 100.97671\n",
+ "Epoch 83/100: average loss 100.91873\n",
+ "Epoch 84/100: average loss 100.86162\n",
+ "Epoch 85/100: average loss 100.80946\n",
+ "Epoch 86/100: average loss 100.75977\n",
+ "Epoch 87/100: average loss 100.71061\n",
+ "Epoch 88/100: average loss 100.66631\n",
+ "Epoch 89/100: average loss 100.62580\n",
+ "Epoch 90/100: average loss 100.58395\n",
+ "Epoch 91/100: average loss 100.54316\n",
+ "Epoch 92/100: average loss 100.50635\n",
+ "Epoch 93/100: average loss 100.47235\n",
+ "Epoch 94/100: average loss 100.43290\n",
+ "Epoch 95/100: average loss 100.39308\n",
+ "Epoch 96/100: average loss 100.35649\n",
+ "Epoch 97/100: average loss 100.32257\n",
+ "Epoch 98/100: average loss 100.28716\n",
+ "Epoch 99/100: average loss 100.25479\n"
]
}
],
@@ -1493,7 +1408,7 @@
},
{
"cell_type": "code",
- "execution_count": 10,
+ "execution_count": 11,
"id": "09646d29",
"metadata": {},
"outputs": [],
@@ -1511,7 +1426,7 @@
},
{
"cell_type": "code",
- "execution_count": 11,
+ "execution_count": 12,
"id": "7a06a4c0",
"metadata": {
"scrolled": false
@@ -1523,7 +1438,7 @@
},
{
"cell_type": "code",
- "execution_count": 12,
+ "execution_count": 13,
"id": "bab0ce43",
"metadata": {},
"outputs": [
@@ -1777,10 +1692,6 @@
" 'mouseup',\n",
" on_mouse_event_closure('button_release')\n",
" );\n",
- " rubberband_canvas.addEventListener(\n",
- " 'dblclick',\n",
- " on_mouse_event_closure('dblclick')\n",
- " );\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband_canvas.addEventListener(\n",
" 'mousemove',\n",
@@ -2038,14 +1949,11 @@
"mpl.figure.prototype._make_on_message_function = function (fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
- " var img = evt.data;\n",
- " if (img.type !== 'image/png') {\n",
- " /* FIXME: We get \"Resource interpreted as Image but\n",
- " * transferred with MIME type text/plain:\" errors on\n",
- " * Chrome. But how to set the MIME type? It doesn't seem\n",
- " * to be part of the websocket stream */\n",
- " img.type = 'image/png';\n",
- " }\n",
+ " /* FIXME: We get \"Resource interpreted as Image but\n",
+ " * transferred with MIME type text/plain:\" errors on\n",
+ " * Chrome. But how to set the MIME type? It doesn't seem\n",
+ " * to be part of the websocket stream */\n",
+ " evt.data.type = 'image/png';\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
@@ -2055,7 +1963,7 @@
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
- " img\n",
+ " evt.data\n",
" );\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
@@ -2174,10 +2082,10 @@
"mpl.figure.prototype.key_event = function (event, name) {\n",
" // Prevent repeat events\n",
" if (name === 'key_press') {\n",
- " if (event.key === this._key) {\n",
+ " if (event.which === this._key) {\n",
" return;\n",
" } else {\n",
- " this._key = event.key;\n",
+ " this._key = event.which;\n",
" }\n",
" }\n",
" if (name === 'key_release') {\n",
@@ -2185,17 +2093,18 @@
" }\n",
"\n",
" var value = '';\n",
- " if (event.ctrlKey && event.key !== 'Control') {\n",
+ " if (event.ctrlKey && event.which !== 17) {\n",
" value += 'ctrl+';\n",
" }\n",
- " else if (event.altKey && event.key !== 'Alt') {\n",
+ " if (event.altKey && event.which !== 18) {\n",
" value += 'alt+';\n",
" }\n",
- " else if (event.shiftKey && event.key !== 'Shift') {\n",
+ " if (event.shiftKey && event.which !== 16) {\n",
" value += 'shift+';\n",
" }\n",
"\n",
- " value += 'k' + event.key;\n",
+ " value += 'k';\n",
+ " value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
@@ -2220,7 +2129,7 @@
"var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
- "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
+ "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";/* global mpl */\n",
"\n",
@@ -2230,19 +2139,6 @@
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
- " ws.binaryType = comm.kernel.ws.binaryType;\n",
- " ws.readyState = comm.kernel.ws.readyState;\n",
- " function updateReadyState(_event) {\n",
- " if (comm.kernel.ws) {\n",
- " ws.readyState = comm.kernel.ws.readyState;\n",
- " } else {\n",
- " ws.readyState = 3; // Closed state.\n",
- " }\n",
- " }\n",
- " comm.kernel.ws.addEventListener('open', updateReadyState);\n",
- " comm.kernel.ws.addEventListener('close', updateReadyState);\n",
- " comm.kernel.ws.addEventListener('error', updateReadyState);\n",
- "\n",
" ws.close = function () {\n",
" comm.close();\n",
" };\n",
@@ -2253,14 +2149,8 @@
" // Register the callback with on_msg.\n",
" comm.on_msg(function (msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
- " var data = msg['content']['data'];\n",
- " if (data['blob'] !== undefined) {\n",
- " data = {\n",
- " data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
- " };\n",
- " }\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
- " ws.onmessage(data);\n",
+ " ws.onmessage(msg['content']['data']);\n",
" });\n",
" return ws;\n",
"};\n",
@@ -2513,7 +2403,7 @@
{
"data": {
"text/html": [
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\" 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RrN/U6ZMQXX10ZEqQ0NDyMvLw5o1a4TOYakDpWESOiGEEKKCJTuBpAEKQAcLwHvuuQfTpk3D7t27AQBvvfUWzjzzTDz77LMAgJ6eHrhcLrS3t8f83DXXXIObbrpJ6ByWO5DFk9AJIYSQXIQC0MECMBKJYOXKlTjmmGNw/PHH45hjjkFVVVX037ds2QKXy4X+/v6Yn1uyZAmuvPJK3WMODQ3h4MGDUevt7c15ByKEEEJisEHyggLQwQJw7dq1mDp1KtauXYvt27fjySefxKRJk/Cb3/wGwFEBODAQW6uwePFiXHXVVbrHDAQCcLlc48wODmTXND0hhBAboVu+dH7WlS9RADpYAE6dOhUPP/xwzGt33303Zs6cCcDYErBdM4B2LtQlhBCSHaRMJOxY/2mzYvY3MFIAOlgATpo0Cb/4xS9iXquqqsKMGTMAHG0CWb16dfTfh4eHs6cJxCTsvmE3IYSQzJMykRAOjc/8ZfEIMzvEb6txrAC8+eabcfbZZ0fHwNTW1uL000/Hz372s+h7qqurkZeXh9raWgSDQVx//fXZMQbGJJywYTchhJDMIpRIeGezrTYxyPb4nQ4cKwAPHTqEH//4xzjnnHMwceJEnHvuuSgpKcHw8HD0Pdog6ClTpmDChAm45JJLEAwGhc+R7Q6ksl0PawYJIYSkSiSc66nH8lU1CDf81FbbmGZ7/E4HjhWA6SDbHcjoht2sGSSEEHti9sN7skTCUq8f/f4CMeHHDGDWQQGoQLY7kJEMIGsGCSHEnljx8J4okbDU60fY70bYLyr+WAOYbVAAKpDtDiS6YffwSBhb9+5HbXsf5lW0sGaQEEJshlUP73qJhEJPPfr9BXLij13AWQcFoAJ2cKBUG3ZXNe5IWt8hWjNICCEkM1jZ8KeXSFjkvVdu2TcLtzG1Q/y2GgpABeziQImWBaoadyTMDsrUDBJCCMkcKg1/IsQnEu70FosJv8b/5E4gWQwFoAJ2cqD4wuDhkbB05o8ZQEIIyT6MNvzJMDaRIJwBzJKGDz3sFL+tggJQAVs5UNzejFu7/yot/FgDSAgh2YfVGUCN0MgIutoa8Gb9IxiumoaITRo+9LBV/LYICkAFbONAOnszHr5nBpZ6/VLij13AhBCSfYg2/Ck9vOvt8WuThg89bBO/LYQCUAFbOFCCvRkjgTyE/W5hEcg5gIQQkr2kavhTun8n3OPXHg0fetgiflsMBaACWe9AKfZmDAfc6PcXotBTr/vEeFHFRtRu6+VOIIQQYgMsGeIvssfv6nOBzueztuFDj6yP32mAAlCBrHcgwb0ZF3nv5XIvIYQ4ANO38bTZHr+iZH38TgMUgApkvQNtf1HoD7f07gCXewkhhIxHMI5kyx6/omR9/E4DFIAKZL0DCT65hXpeM/eJkRBCiDNgBtCxUAAqkPUOFK3dSFS8m/2t+oQQQtJI3MgwjAw7Mo5kffxOAxSACtjCgaLdW/F/vPZo1SeEEKdjet2eUfRGvTxwPtDic1wcsUX8thgKQAVs40C6f9T2aNUnhBAnY2bnrpKQ/DRZED/cOaKJvBafo+KIbeK3hVAAKmArB4pP649N1yf7N0IIIZagze4zY/C+kpD8tFwo0c4eEW2Zd2TYMbHCVvHbIigAFXCEAyVK+dv0qY4QQuyAtnuHGVtvJhKSmtW07k5+HIc2eiTDEfFbEQpABWzvQAmnu9ujriNr6mYIIUQSs/bvHR4JY15FS8rjzK9MnA0Md74gJADDnS9Y8VVkBNvHbxOgAFTA1g4kMt09izu7LJl4TwghaaKuo09IAN7XvCvhw21TcADzKjZK7emud4/samsQEoBdbQ1Wfy1pw9bx2yQoABWwtQOJpvx7/pDpKx2HmXUzhBCSCUQzgIkeblMt+8osK9e170O/vwBhf4LMn39029C69n3p/Iosxdbx2yQoABWwtQOJTnevPierloLNrJshhJBMod3LRERc/MNtqvug7LLy1r37sdTrR9jvHicCtdeWev0pl6PthK3jt0lQACpgawcSzQBqFlyX6SsGYF7dDCGEZBotiycqArWHW5nsoZ7VdfTFXIcmKG/z+tHvL4i59/f7C3Gb1++4B2tbx2+ToABUwNYOlHKXEB1rLsn0VQvXzcTf4AghJBvRq2dO9XAreh+UeUDWxOi5nnos8t6LO73FWOS9F+d66h1ZWmPr+G0SFIAK2N6BEnYBJ7EWX0YvmRlAQojTCIUjuK95p/DDrdEMYKoSmVxqrrN9/DYBCkAFHOFAO9YD1dPEBWDZZ0eHgWaIVHUzrAEkhNgRmYdbmfrBsfdGkUxerozXckT8VoQCUAHHONDeV+WygFsfzujlJqqbYRcwIcSuyD7cJrsPTvM0oKg8djagUzN5RnFM/FaAAlABxzhQOITD1echkmAEwDhr/M9MX3FOLVUQQqwh27Jdsg+3ye6D2fbZsg3HxG8FKAAVcIoDhcIReO5eJS4A1y3Jin0geYMjhBglWx8iZa8r5X2Qe73r4pT4rQIFoAJOcSCt9mS5tySpCIzfKDzCPYMJITYk24fJh8IRbN79AX78bDv+9Rdt+I9n27F59wfyD7nc6z0hTonfKlAAKuAUBxo7UuCR4usQ8bvHCcGIf7wADAfciNhgz2BCCNGwwzD5qsYdKFg5/tpmlTaJi9Pgywke5u2x17vVOCV+q0ABqIBTHCi+++yR4hsQ8ueNE4CJtgg6fM8MLisQQmxBto+SqmrckfLaUorArpeBstOSlPJk917v6cAp8VsFCkAFnOJAet1n0z11KC++HU2+bwjVBYZeuSfTH4MQQlKSzcPkh0fCKNTJ/MXb/MrWxBnKHevFJzq8szm9HzCLcEr8VoECUAEnOVCi7rM7vcVCN5JIwJ3zSwqEkOwnmzOAj2/uEZ7rp3t90R2eBAXg9hfT/hmzBSfFb6NQACrgNAfS6z67texBcQGY40sKhJDsJ5uHyZfWBYUFoG6G8pUquZmuzAA6Jn4bgQJQASc6UPxIgbZdf0G/vwBh0RExOXxDIYTYg2wdJq+UAWwWW6052g2c2w/sTozfsjhaAPb19eHGG2/EpEmTcNJJJ6GoqAh/+tOfov8eiUQQCASQn5+PiRMnYuHChejq6hI+fi44kDYjUFgA/v7unL6pEELsQTbOATRcA9hcIif+WLKTE/E7FY4VgB999BGmTZuGW265Ba+//jreffddbNq0CXv37o2+p7q6GqeeeirWrVuHYDCIRYsWIT8/H4cOHRI6R644UFNwAA8U/7vEkyXnTBFCsp9sHCYv3QXclWjcSwIr++zoiJgcJ1fidzIcKwA9Hg++9rWvJfz3SCSCKVOmoLq6Ovra0NAQ8vLysGbNGqFz5JIDNW3vxV8ChYKZwNg5U9l4kyWEkGwl0RzAC+LnAIZDQHWhnADsovgDcit+J8KxAnDWrFm466678L3vfQ9nnHEG5s6di0cffTT67z09PXC5XGhvb4/5uWuuuQY33XST0DlyzYFCXXWIBPJGhz8L1pg0be/NumUWQgjJdoZHwnj0tR4s+e0b+PFanZ1AwiGgdpmc+Hu1OvEJc4xci996OFYATpgwARMmTIDX60V7ezvWrFmDiRMn4re//S0AYMuWLXC5XOjv74/5uSVLluDKK6/UPebQ0BAOHjwYtd7e3txzIL2thZLY+pIrdbvssmG7JUIIsSU71gOVZ8mJv+pC1mePgQLQwQLwhBNOwFe+8pWY1+68804sWLAAwFEBODAQK0IWL16Mq666SveYgUAALpdrnOWcA4VDwKa7hW46Eb8bjxTfkFWjFgghRA9blKvIDHrm0m9CKAAdLADPOecc3HrrrTGv/eIXv8BZZ50FwNgSMDOAY3hns7AADPndmO6py5phq4QQEk82dgWPIxwCqqfJi7/m4kxfedZBAehgAXj99dePawK56667ollBrQlk9erV0X8fHh5mE8inpHwSlpw4/7ZvVtZst0QIIWPR5gJmfbnKq9UGxF9Jpq86K3Fy/BbFsQLwjTfewPHHH4/Kykrs2bMHzzzzDE4++WQ8/fTT0fdUV1cjLy8PtbW1CAaDuP766zkGBhJPwjvWj+4AIpgJbCm5lBlAQkhWoe0MkmjkStaUq4RDQPU5cuLvlarMXnMW49T4LYNjBSAA/O53v8Ps2bMxYcIEnH/++TFdwMDRQdBTpkzBhAkTcMkllyAYDAof34kOJPIkPDY7uGvND4RvRhG/G3d4i7PrpkoIyWnSsTewds+s3daLxzf3oLZdssYwHAK2Piwl/iKrz2XTRxKcGL9lcbQAtBqnOZDIk/Dc8hbMr2yNvjbdUye+S8inIvB2788wzdOAmtbdFICEkIxS19FnfO9dAfRWVKRqDHesB+6fKXWPjfjd8N5dMe6BPWsbWzKA0+K3ESgAFXCaA4k+Ccfb+pIr5Z5M/W60++ZmZ5E1ISSnsDIDmGhFJf7BOuE90EDHrzZ5QTtvUXlLdje2ZAinxW8jUAAq4DQHEn0SjrdCTz2G/JOkn1BbSi7NviJrQkhOoa18JBNqRspVUq2opKwxNNDxG/K7sezTMptk5+M913nx2wgUgAo4zYGMZgCneRqw3FuCiMRSsCYEZ3hqWQ9ICMkoqTJ1VY07pI8pez8dl2Hs3iT9UL3MWyp0Lt5znRe/jUABqIDTHEjkSTiZNZdcKi0Ct/tmKy2xEEKIGVQ17jC2TJsA2RWVmBrDrpeBitOF76P9/kIs9fql79m5fM91Wvw2AgWgAk50IO1J2KgIbJEUgWOfWjkTkBCSCawYBWM4A9jik3qIfqnkWyj01Bu6X+fyPdeJ8VsWCkAFnOpAieYAFpW3CAnDO7zFUiLwoP9zKPTUR2+Asl1r7HIjhKhgRSOIoRrA4Drppo/rvNWGxB8zgM6M3zJQACrgZAfSE1Uy2cGHisXnAyLgRkvZt6LnkNmOycztmygkCclNrBoFI9UFHHwZCORJrZ586D/LUPaPNYDOjt+iUAAqkIsOpCe4LqrYOO4GU+ipxxH/aeI3s4Ab7U2/ltqOycztm2yxDyghxBJkMoCyD4pCcwCNjHsJuGPq/gpXxh5bG/8Sf49kF/AouRi/46EAVCBXHSj+Bjg8EtZtHlnmLZVaCv4wMDXh02z8E6uZNTu22QeUEGIJqRrgtPtJY2e/oQfFpDuBhEPAPZJbvAXcuL/436PXMK+iBb/79H4cv2rDB1t9cjV+j4UCUAE60FGaggO6N85Hiq+TEoHlxbcnXdLQalbMqtmxzT6ghBBLSVTior1W1bjDmgfFF26RFn+D/rNj7pPJroGlLfowflMAKkEHOkooHBk3cV6zupIrpG5u/f6ChCMNtBocs2p20rEPKCHEHiTKmDV2Jl7GjX9Q1BNcCUWYZNNHJJB43h8fVuVg/KYAVIIOdJRkQqrQU49D/jOFb3Jh/6jpiUCzM4BW7wNKCLEXemJN9H5T07p7nFAsKm/R3Y6tvenXQJl4nbTW+PFI8Q18WDUBxm8KQCXoQEdJJaRu8/qi0+qNdLglqgFMVbOT6mmYGUBCSCqMbpOZ+H7oR1hyaP5wxRTc5vXxYdUkGL8pAJWgAx1FREg9UnyD9E4h9xf/e8ouYJUuN7OEJCHEuahsk6m3ItLvL5ASgKF1S/Gr17r5sGoijN8UgErQgY4iuo3cMm8p9vvPFr7xHfKfia+t2hAVc/HLM0a78sZihpAkhDgX1W0yx9oi771SD8GH/J/DV1bp11fzYdU4jN8UgErQgWIRHRR9rqce5cW3i9e9rC4EdqxPWqCt2uXGcQmEkGSobpOp2Z3eYuEymIjfLbTsy4dVeRi/KQCVoAONR09IxQ8oXVC1CU3be4HqaRLdb3m4TacpxMwbH8clEEKSkWyos+jyr+jDr0jDh2ZF5S2oae3mPUsCxm8KQCXoQProDYpu2zOI1U078eO17bi3aSfa9gwi9Mo9EgJwdDyM3oxALn0QQtLF8EgY83R2P0ol/O4v/hE+8p8lVvPnz8Nyb4m0wOSqhTiM3xSAStCBxGgKDujOCOTzlEsAACAASURBVJxXtgFDlXIT8MdOv483o8XPzPwRQkSRbQhZ6vXjQ39+wgfbsf+tjcASWfblUrAajN8UgErQgUZJJqAS7RAy9uYYfxNMZonmA07zGBt/wNo/QogMMiNhlnr9COsIvUTW7y9MeH+TEYFcEUkN4zcFoBJ0oOQCKhSOYH5la8oblufuVaONHoJ1MYmWgrUMoGhGj3sAE0JkEc0A3t/UhSOV5wiLv1TbYMoax8Ekh/GbAlCJXHegRAJKs4c27ha/We0aAFafK5wJXF9ype4Tb1NwAPMrYwXp/MrxGT3uAUwIMYLw7NDnbpIqb7nTW2ya+DO6IpJL5Hr8BigAlchlB0oloLQbodTNasd68aYQvxvNJZdGz9MUHEi53Dx2luDjm3v4FE0IMUSq2aE9z/wfKfGHgBuv//5l3dWUqsYdhjqPee9KTi7Hbw0KQAVy2YHMnIwfc7N6tVpKBP42cH10uVmv0WSszS1vSbmpO5+iCSGpCIUjqGntRlHZ+D1+mzr/LL3HLx6YBYRDCctXxr7etmcQ8ytbuXuRIrkcvzUoABXIZQcyc2/MmJtVOATcP1O4biYScAPNJWjbM2iqIOVTNCFED72656KyFtS07h69j7X9l3T2DzvWS18Ddy9SI5fjt4blAvDIkSN47733sGvXLnz44YdWny6t5LIDmZkBHHez2rFeqjMYATfqnv65qcKPT9GEkHhSNY6NLv3mSdy78oDgy4avhRMMjJPL8VvDEgH48ccfY82aNVi4cCFOOukkHHvssVE755xzsHjxYrzxxhtWnDqt5LIDidQAprK55S2Jb1YvL5MSgJ+UTTGtg45P0YQ4B7PmfKa65z1SfAMiAfGRLwi4gS5j4s/sz5aL5HL81jBdAD744IOYPHkyLr74YpSXl6OpqQnbt2/Hnj178Prrr+NXv/oVbrnlFuTl5eGqq65Cd3e32ZeQNnLdgVI1XcTbvPIW3Nu0E/c17xrdCSTZzWpkWHoZ5TpvtSkCkE/RhDgDM7NkyVY9pnvqEPLnIeIXL10Jdb5EAZdBcj1+AxYIwO9973vYvn17yvcNDQ3h5z//OR577DGzLyFt0IGAxs6BcXv9JjOpmrpmsU3TNesIXKws/m549I/YvPsD3ogJsTmycz5TibFkdc8y+/tG/G6sKb4eNa27uYSbQRi/La4BPHTokJWHzzh0oFEaO/uFBZZMV20oHMGB//9S8a7ggBvNJZclPHdReYvwaJqisiTL04SQrEZ2zqdIplAvA1joqcci7734g++fhO5RYb8bjxTfwPKTLIDx22IBWFRUhPfff9/KU2QUOtBRalrFhj6LZgC1G3Khpx6H/acLC8BIwI3bvd44MdccnROo1zmXzHgjJsR+iDapbd27XzhTGD8AeqnXj35/gdQqRUXxbSmviQ1o6YHx22IBeOutt+Kcc87Bzp07Y15vb2/Ht771LStPnRboQEcZ3fbNnJ014m/Iy7yl0aUT0afsZXFT9bWbuN6TfvJMYDNvxITYDNExVaub3pa6b2n3pkT3pEQNIBG/GyP+0zDdUyd87+EIKmth/E7DGJiysjJMnjwZ//M//4Pdu3fj+9//Po499lhce+21Vp/acuhAsZgxmyrR0s0jxTcIC0DthqsttcTfxEPhCH76fIfwjbhtz6DVXx0hxEQsG1QPoL3p1wgFxAc9a0LxkeIb5HdHIpbB+J2mQdBVVVWYOHEiTjjhBFx99dXYtm1bOk5rOXSg8ah23SW7cT9f8m3pm+4yb+m4m7hs9/J9zbus/MoIIYKIds2m2q9X1qJiTGK7Ss1G/KdFH0YXVG1CTWs3M4BZAOO3xQJwYGAAd955J0466SRcdNFFOPnkk/H0009becq0QgfSR2W0QbKlG23UgszNd9A/NTofsK6jz9D8wvuad6a+cEIcTqZHlsg+XBqp+U0qxsIhoFqi5u/JaxHa8jC27hqI+c5SiVPWAKYHxm+LBeDEiRMxd+5cNDQ0AACam5vhdrtRXV1t5WnHUVVVBZfLhR//+MfR1yKRCAKBAPLz8zFx4kQsXLgQXV1dUselA5lPqqWbR4qvk6oHRMCNB4pvid7EjSwNtXVzCZjkNpnedUJ2pEuy65a1qBh7pUou+/fO5pSfR7RcJtPi24kwflssANeuXTvutW3btiE/Px/Lly+38tRR3njjDRQUFGDOnDkxArC6uhqnnnoq1q1bh2AwiEWLFiE/P19qdA0dyHxElm6aSy6Trgd8svwmhMIR6T2Mi8pbpG+2vFkTJ2FUfJmF7EgXvZ+/r3mXYQFY1bhjdMcOGfH3wCwgHEp6LxAV1ZkW306F8TtNNYDxvPvuu5g1a5bl5/n4448xY8YMtLa2YuHChVEBGIlEMGXKlJhM5NDQEPLy8rBmzRrh49OBrCHZ07H2/+/wehEWnbrv/3TyfrAWj2/ukbr5y95kebMmTkJVfJmBzEgX1WPomefuVdJ7k2PHeqF7QaqHxUyLbyfD+J0hAQgAH330keXnuOmmm3DXXXcBQIwA7OnpgcvlQnt7e8z7r7nmGtx0003Cx6cDWYfezXNOWTN++vxbKFvfhXkVLVjmLZZaDj4cOF1qv+CiZHsVJ7hm3qyJkzBDfKkimrVP1jU7PBLGvIoWafFX6KnHh/58OQG4wWPKvSAbxLeTYfy2QADu27dP6v19fda0uq9duxazZ8/GJ598AiBWAG7ZsgUulwv9/f0xP7NkyRJceeWVCY85NDSEgwcPRq23tzfnHchKQuEIalp3o6hM/8Y9r2Ij2n6xTOrmXF9yuXQQaOzkzZrkJmaIL1VURahKHeBDxTdJd/2Gel4z5V6QDeLbyVAAWiAAzzzzTCxevBivv/56wvccOHAAjz76KC688EL893//t9mXgPfeew9nnnkm3nrrrehregJwYCA2sC9evBhXXXVVwuMGAgG4XK5xlssOZAaJlkESPUXH30wHHv1XqXrANcXXy2UBVjagsbM/6WfgzZo4kWzwa5WuWZF7SCJrLrlUqtZYq/3b2v1XU76zbBDfToYC0AIBuGTJEvzkJz/BZz/7WZx55pn453/+ZyxevBgrVqzAjTfeiHnz5uHEE0/EV7/6VWzYsMHs0wMAXn75ZbhcLhx33HFRc7lcOOaYY3Dcccdh7969hpaAmQE0n0R1Mo2dYk/tBZ4G3H73g1I36fj5gKKWbNmGN2viRDI9skR7OCyv74qeL/78iZZUjYx8Oir+FsqLv09r/8y6F2SD+HYyFIAWCMATTjgBf/nLX3D48GGceuqpuPXWW3Httdfiqquuwo033oj7778fwWDQ7NPGcOjQIQSDwRj70pe+hB/84AcIBoPRJpDVq1dHf2Z4eJhNIGkmWZ2MzM260FOPkYp8qRv1Qf/npOoBNWGaKNDxZk2cihk7/Bg9b7yAK1w5/m+yKTigu4pgtPHjl8X/Ji3+IlVnjw6Jhnn3gkyLb6fD+G2BACwoKEBTUxMA4JhjjsFf//pXs09hiLFLwMDoGJi8vDzU1tYiGAzi+uuv5xiYNBEKR9DWPZiwts+I/SRQJt2pt95APWCimzZv1sTJpLu7PdXSbUV9V1To6V3bvIoWlK0PSv99rym+XnrE1EH/mdi6K7az16x7QabEdy7A+G2BAHz44Ydxwgkn4Ctf+QqOPfZYPPjgg3jjjTdw+PBhs08lRbwA1AZBT5kyBRMmTMAll1winZmkA8ljxmDWpDdvyaXglpJLpc6RbNmGN2viZNI131KmoUqlxi/etKkCMg+RYb8bS73+cfcFM+8FHC1lDYzfFo2B6erqQmVlJY455hhMnz4dxx13HI4//nicf/75WLRoEe655x7L6v/SCR1IDjNv1okCw9PlN0qLQJmmkFTLNrxZE6KG6BJqW/egaQ+Ty7ylwnNFx4q/27y+hPcFM+8FHC5vPozfFs8BnD59OgYHB3H48GH87//+L9asWYNly5ZhwYIF+MxnPmPlqdMCHUgclYJsWXv9kWVST/JhvxszPLUpxaXoss3wSBiPb+5BaV0Qj2/uwfBIOA3fMCHOQLSJ4r7mnabcL5Z6/fI1f3437vAWC+1CQuGWnTB+Z3AQdCRi/z8EOpAYoXBEegcO7cba2NkvLRzva96J9SVXSN3QP/F/Fku9/oTXIrps09g5gHkVG3M6A8iglztY8bsWzQCqbO+mWaGnHh/5z5Ku+2suuZSlHTaH8TuDAtAJ0IFSY6TmL/7GqgWZ1U1iT/xt3YP4amULDvk/J3VTD/vd+N3aR3QLyscWnSeiqnFH0usSOYbd4RJ47mDV71q0iaJtz6CyAHyw+GbpzF9zyUL6tQNg/KYAVIIOlByjNX+Jbqwy3XVNwQEs85bKPdkH3IiUn47QyEh09phoNq+xs9/Q57Njtkx2cDczJc7D6t+1SBNFKBwxtL2bZo8U3yCd+ftl8b9hmqcBF1VsZGmHzWH8pgBUgg6UGCM1f0VlLWjbM5hUBMl01zUFB/CbgNxNHgE38PzNUgFONhBpx6hq3JFwCHa2ikKjg7s5Bsc5WLXtYfyDhV75R/wDmMyD11i7zeuT2kccATfWl1wRcwzO9LQ3jN8UgErQgRIjM4RVNmsgs/QUCkewp+bb0pnAr63akPSa51e2RgOc0YGzoja/chNqWrszLgjNGNzNoGl/rBh6nuzBoq17EPc178R9zbt0HxBTlV7EW6GnHgf9Z0g9FB72f3bc4Hju6mNvGL8pAJWgAyVGtJMvmXjTQ8sS1Lb34fHNPajd1iskikK//pbUDb/Pd07K665p7Zb+rGZYJmqPzOriZtDMflKVJZi97WGqUpGi8tjsup7/P9Ai3hByo7dCbkUg4MYDxbfwYcZhMH5TACpBB0qMaJbg8c09whktpaLzkWGg7DSpep+PfJ9Lef1NwQHLM4DxlomaOrM+I4NmdpPsb0wThqLdtyK/ayMPFvH+3xQcwPxKsWM0l1wmXfd3yH/muOxfgaeBNYA2h/GbAlAJOlBizN4aLVGtT6KOYd3sRXOJdMffO77pSQPKgqpNGB4Jp23GodHvTxXVLCdrALOfVEv88Zk4M37XRh8sxo6JEi1B2PNf3xlt9JK4B2g7fegdT1sBIPaE8ZsCUAk6UHJkGjaSCbfGzoFxm8DrBwOBDOHT/yYtAld4VyYNLFv37rd8l5Nk504HsjWdqX7fJLswa4lf9nddu61X6XwizVcFngb8x5NthsSfttOHnhWVt/CBxsYwflMAKkEHSo3Ism2y9zQFB8wPSI9eLiUCh/2njVsCGmtarVNTcEAoS2KmUExXTZ1oRlekc5OYj+o4IbOW+GV/17ID4o3YDE8t9vumSDWBRfxuLPeWpDw2SxrsC+M3BaASdCAxkgUns5adUgmusUtSTdt7MewXrwdMVAQeHwRC4YhQLdL8ylZUNe7QzY7KWjoDkGhG146zDe2MGQOZVZf472veaeh3XdtubQOVbM2fJgB/HfiB0PHZ1GRfGL8pAJWgA6mRzv2BNbGknfN2r1d6v+Bl3uKkwlJ4E/s9gwCM7ZKS6Nzpgjt9ZBei8ypTiXLVDKBRIaRSA3hR3JD2ROJPSgBWnAkEX8aKZ/4kfE8h9oTxmwJQCTqQGununtWCn/bfe3xfkK4H/GXxopgA29jZHw2sot2RY4OlyPDbVME93TDDlx2IDmQWqY1NtcRvlRAKhSO4oDT5zM1En037XHrXPMNTKy3+IgE3tnb9WWi4NJua7A/jNwWgEnQgNdI9P+/eT4fJav9d6KlHSHZ5yO9Gc8llWFC1SXcnDzOC5ViBVdO6G/MrW5MGb5KbqDxAJdo5x2hZQmOnMX8cFYBN0ucrKm+J1gjrXe8rvn+S+rtGwI3XfV8avS8kaTgb+/3xb9DeMH5TACpBB1LDjAxg4coG/K6jz3D2QnZLKK2T8E8Nj0ufz6wtsph1IIA1o3n0lvhF6nCNZsNUloC1DHxNazfmlB29xpmel6Qf7Ib8k5I2esUbR8DYH8ZvCkAl6EBqiHSWFpW3JM1KaJkHleyF7KbwCLjxj8BkqYBxNHDsTouAo2h0PlYN547PQM8tbzZ0HBFURWx8ts5Q00eKcS96pu1ApPf3xb89e8D4TQGoBB1IHZHOUtHGA5kdAeJtubcEYcnAUVdypaFzWb2Ey0aN3EC1bk+zRA0csrMtS+uC0oLHzDpgI00fo3W9/yZ9rnlxDShjx1bxb88eMH5TACpBBzIHkZum6FN1W/eg4QDyQPG/S2cOlnlLpc9jZROHaFcocQbJHqBE/VEvc6fSoS+7t7cZItZQ04ffjQ7fHFPEZ7Lr599edsL4TQGoBB3IPMxaNlFZUir01OND/xSpIDLoP9vQUrBKF2Gi70q0K9QJS1JOWGYz6zMkeoDSOsqNbMdodoNJqutXnYkZ9F0o/fDW4/uCKeLP6r93Yg2M3xSAStCBsg/VJaWlXj/CkpkEo0vB0zzydVPJsqWin93us8uydZlNRtCZ/RkSnVtmO8axpHvv50Tfh1YDnOxcLSULpev+3vRdlPIzxNcXimw75/S/PSfB+E0BqAQdKPswY7j0Uq8fQ/7PStYRXWfoXPc174rJ4CUTEKmWd8vru4TOaefdC7J1iVtG0KX7MxgRm1Y0mOj599jX2roH0bZnMObfU2UHjYi/g/7PJc3aH+0wHoi5XjN2LbHz357TYPymAFSCDpSdyBav69l0Tx3+IS0Cv2foXIlmCo4N0iLLu6l2RtALynYiW5e4ZQRdpj5DsocLvX8bHgkLzcMTFTyJxsvEj5iZV7Fx3ExBvZ8t8DTgl8XXGer4ja/bjf+cicSxGaLYrn97ToTxmwJQCTpQ9pJsm7W5OoFHz6RnBPrdaPfNVQ4SegJCNPjMq0i8ZGb3OqRsXOKWFXTZ9hkSZQdrWrtN8eGte/cbeiD70ROvxwjVxs6BmM5b7W9TVvytKb4+4Tkr6ruSLt2rNKzY/W/PiTB+UwAqQQfKbrTMRu22Xjy+uQe17bFLT76Xt6e8ccvMCNTEotHl4GSBQ3T5qaK+y1DNlx0QrUsTWWYzqwFDVtCZ+RlUSZa5NMtvh0fCSiUZWnZ87DUVeurxD/8kafGX7O+ywNOA+ZWt45agE31nybqunfi350QYvykAlaAD2Zvabb1CQej5km9LBZuw343pnjrTROA0T4OQWNWERrY2SSRDRJCZlT0z8/uRFXTZkgE0o1ZWRPBYsd/3Dd5Vpoq/RJashjOR/9jxby9XYfymAFSCDmRvRGcGTvfUIeTPk1pyavt0X9F0WfwSk53GpIgGTZGdY1Its5ndgCEr6Mz4DGagKsy062zsTP67M3u/79u9Xhzx50mKv+8b/oyJfEK2ppJkH4zfFIBK0IHsTdse8aHRstvFRfxu3O71pk382XWJSVaQGR1rAljTgGFE0Kl8BtFrSiVAzBjzMrZBKdH5alp3m+bn7b450nV/b/guVv6crN1zJozfFIBK0IHsjUwQXFC1CT1P3ym99PRI8Q2WC8D5la22FH9GBZnRZTarll+NCDrVpcJkc/9EjquSASxc2YDGzn6ha5xf2WqKj7/r+4K0+Bv25xka0m6GT5Dsh/GbAlAJOpC9EQ2Cj2/uObq0+vB8KQFodLs4OQGYuRojleUuFUFm5LxWNmAYEXRGv7tE54pvlkgmRFW3YBMRRGbV/73l+6J09j3id2O5t8S0v7G6jj4u7ToMxm8KQCXoQPbGyPLd1rd7pTMR//BPSpqJKCpvwbUPtxkOTplaAlbNYqW7I9ZqwZkOgWC0c1dmKdqs34kZ9X8dBpZ9I343mksuM038TfM0oKa1m80dDoPxmwJQCTqQ/RFZvhsb2Fc37YzuPiATmAZ858Qc/wvFjTivZINpASrdtUpmNFMYFWShcARtewZxX/Mu3Ne8E23dgyk/dygcwebdH+ACf5P0d5iubdtEfk61czf+u2wKDmB+pfwx05EB3FhyibT4C/vdeKT4OmFR+5Pn2zG/MvlDYKLt6Oxce0sYvwEKQCXoQM5AdqzDNE8DenwzpJelOnxFpgk+lcCcCFFhYlYzhdEGCr0h3kXlLQkDcaKfEQnmZncNq4hJM5ZU4zN3jZ39mFveLPzzqX630dmb7X149LUenO+Te8jRHoqaDWzxhoAbN3oro8eaHUj9ueZXtqKxM/lsv2S+wyYR+8L4TQGoBB3IOeiJn1Q7GGzxfUl6aWqFd6WlAtDocqmMMDFzKTVR8NVs7O4MTcGBlOfUE3Ai15ps7IxZwd+omNS+s9K6oLJ/jP2dVDXuMHSMZEJbNUP56Gt70ff8TxCRFH4Rvxsf+vNjSi2WPfWm8HeSeEcUsS5mNonYD8ZvCkAl6EDORWS5bbqnDmED9UlLvX7lQJ7I2vYMSn9WWWFitHYvWfNC/Ovx+7POr9yEorLU2/fNr2yNmYUosrw5r7wFh4dD4x4AzOwaNrPj2YjFH7+xU0wYx1tReUvSHTKUrnFlAw5//DEQEJ/zl+zv6r7mXVJ+qvcQmE07txBzYfx2sACsqqrCl770JXzmM5/BGWecge9+97vYtWtXzHsikQgCgQDy8/MxceJELFy4EF1dXcLnoAM5F9Hgv6b4euml4EP+yaaNp4i3tm45AWhEmIh+N/c170qZTdVEZmNnP7bu3Y/y+i7l70ATZDJLpvMqYsXlgqpNqBC8FpHgb0RMmiGqxn7PY+f2jd1X1+j3O9aHjNQRxttSrx+HAlOkxV/Y78ZtXl/MsYrKW/DQRrHsXbK/mWzZuYWYD+O3gwXgVVddhSeeeAJdXV1466238O1vfxvnnHMO/v73v0ffU11djVNPPRXr1q1DMBjEokWLkJ+fj0OHDgmdgw7kXGQ6GF/3XSwdtN70zTMlsBsRIxqhcASPb+6RDnCyI0TmlLXgQn/ieiyz9o2N/w5UulBlhJdI8JfNJJm5VVtRWWx9pGotYbyPmTHseZm3VLqxKtWYpVR1n5olG6OULTu3EPNh/HawAIzngw8+gMvlwmuvvQZgNPs3ZcoUVFdXR98zNDSEvLw8rFmzRuiYdKDswewRHDJBstBTj4/9p0sHrx7fF0wJ8GNNNAMou7So1zxg9rWLilGR49R19JlyvMKVicWgzPZ7spkkM/fQjS8LUB3PEp+lVL2+271eQw0fQ/48U8opUtVgWr1zC8kMjN85JAD37NkDl8uFYDAIAOjp6YHL5UJ7e3vM+6655hrcdNNNQsekA2UHVmzALpLlKiprxgWlo2NFlnr9huaVveErMnU5+KGNu1J+NiNLi/FB34wlv3gzo8nBrCVTUdN8LJUPymaSREXaLJ/8WBuj4lJP8KpmKVsMjHqJ+Ecz6Gb+3aTK5FlxjyGZhfE7RwRgJBLBd77zHXzta1+LvrZlyxa4XC7098duabRkyRJceeWVuscZGhrCwYMHo9bb25vzDpRpzB7ToXdsUVGhLWPJZjIO+yelzGSINEBo70uW/ZQN2vGB0YyMTyIzKwOYTtNGBYn4YCp/auyUX6atad0tnZ0yItz0jqeapewxsL1bxO/Gq4FvmFIrqmfJlvO5E4izoADMEQF4++23Y9q0aejt7Y2+pgnAgYHYG+TixYtx1VVX6R4nEAjA5XKNs1x2oExi9pgOPWSXSrXlLNnl4HCC7uCZvg2oad2Ntj2DpgQxmaAdH/RD4YhwXZWsuBhbA5gsS3ahv1l3tly6M3/aOb+8aiPmSsyJS+ZPMhnDaZ4GXFSxEcMjYUPZqVRZYC2znex4RpeSZ3lewMe+yfLiL+BG3/M/kerQljV28+YOFIA5IABXrFiBqVOn4p133ol53cgSMDOA2UW6OvSiw2239Qp1TzaXXGYoszHsd2Om5yXdYzZ29mNWaeLlvrFWXt8Vc91GxlroBX0ZESorpESzZGPtQn8Tlj31Jh59ba8l12WmjfXBRPWTshnDsb8jI9kpPeE4r2IjHtq4G7XbevH45h7Utic+nhER9q5vuqEsOQJuYPNDMX+TqR4WtB08zG7oIc6AAtDBAjASieCOO+7AWWedhe7ubt1/nzJlClavXh19bXh4mE0gNiJb95Kd5mnAo8XfNxToRvcxvXTc8YrKmpN20sab3mw9mcG255U04ifPt6N2W29UAIjOVZMxrUN1rICpae0WqjHUgntgvXrtoNU2VpSnylrPr2xF255Bqe+iprXbUKY79nvfjfmVreN8ZuxDwNj3t+0ZHPf+RDbdU4cjPrnMeHz2DyPD4643mV8k28lH72fYzZtbMH47WAAuX74ceXl5+MMf/oD3338/aocPH46+p7q6Gnl5eaitrUUwGMT111/PMTA2It0zumSXvIzsZaqJQCu2jRPZ2iqRLajahOWCOyvIWNueQd0gPb+yFTWtu1Hb3jduRl+8xQ+NzlZrCg4Yypp9MdCMmQJbqs2vbDVc8ypSx6j3exLxpccMPgxpfwsRvxt9T9+he/4Cnd99/LaAmmjU6gbZzUsAxm/AwQJQr1bP5XLhiSeeiL5HGwQ9ZcoUTJgwAZdcckm0S1gEOlBmSfeMLiPB20ihuxb4fln8PUuESCbq5fSsqKwFjZ39SYWHGTPm9I6t1e2l87soKmvBvU07LT2HESEjkpXUllNlfKnQU48PfVOML/l++nfwse90VNR3Cf+uUo10YTcvARi/AQcLwHRAB8o8qeqkxu4lq4rRHRRaSr6mIAKvS5tASbc9tHF3auEh2P0sI5BklwftZEYeesxoqIjPxN3p9SgJP83/3/dNxTRPA2YHxMsfUn0H7OYlAOM3QAGoBB0oO9AL5PHLgmY95RsdP2Fk3pkWBB+zKBOYUaGysgGbd32Q9vPq1bS1dQ+aLjQzbTJlD6qDoePtfd/Zylm/Id9puNDzXNq+A5J7MH5TACpBB8oe4ut8xgkOjzl1Pm3dxjthW0ouNSwCB3yft2z/4EzZfc1iy6FFZfrLj6J2UcXGmGaWcb9Ti7qbM2kyjU8qPj3WvvvQJgwpNHocrX+dk/bvgOQejN8U5oaOxQAAIABJREFUgErQgbILq+cCmrEDxq+Kv2c4QI4E8vDikw9nXFyYZcue+pPQ+2pau5XPlSgb1BQccFz2b5qnAfc174oK3lRLnmYI4DXFi5SXfEN+N273ek37DpgBJMlg/KYAVIIOlF3IdAXL1gGJbJ+m/fuKZ5ILG8ONIZ/+7582/EZqJEw2m14X51ibV9GCMhPGvOhlg4xsiWc3KypvGdepW1TWgprW3RgeCWPr3v1KW/AVeuqxxzfDlCVfszLcHOlCRGD8pgBUgg6UXYjWMlXUd0l1AopunVVU1hw9RlXjjqTjSTp8XzQeNO8+C6GRETy0cRdmlaYeD0Ibnw0yYx/bRGaXsTSpxHcqW+4tQciURo+zzPtMHo50IWIwflMAKkEHyi5UuhmTBQ6Z4ybbGzbeNpZ8XXrbOM0O3zM9q7NXVmwZZ/T3qpcNsmorMc0u9DtbmButZ40Xf2aPOtJ7kGPXL9GD8ZsCUAk6UHYhMhcwWXYmkViQ6ZIsKmuWqhM0sm2cthz8oW9K1jaGVDXuMGXpVsWSiXqzO1/NvOZMX0Mym+6pw07fLOUl30O+MzDdU2fqtV3ob8bm3R/E/P1y7h9JBOM3BaASdKDsI9FcQJX9QK3OFs3w1GK7waAa8ruxwvuTjAuDeFtQtQmPvtaT8WvQAn18FihbO38vqtiIZRbsuGKGPVb8fYQVs35hvxuPFX8/Lb93kd1NSO7C+E0BqAQdKDtJ9NQvOsMvvmHAynqxsfaOb7rhMTEf+07Pumzg0t+mX8g8tHHXuKU+3S3MypzRRJMOm+l5CZ/4TjOh0SNPKOt3QWkT7nhmm+GOe5EtD9koQhi/KQCVoANlL3p1Pyp7BzcFB9ISbP/imxrt9jWSDTRzjIYdLX55Lxc6fa0yMzp8NfH3V9/Z0ufX9oOuqO/C7ECTJZ+Ro2JyF8ZvCkAl6ED2QnXv4MbO9IiJvb9ZrhRs231zMy4eMmVjl/fSlbl1mhV66vFg8Q+Vl3s1f+zwzcF5xY2Gf59NwQEMj4QNbcOYyjgsOndh/KYAVIIOZD+S1QiK1AU9tHGX5QF46979QMczhgNuxO/GxpKvZ1xIZMo0IW/WDhe5YtM9dXih5FumCD8tI73cu9KU32UoHEm577cRYwYwd2H8pgBUgg5kT1Q6A0PhCC4oTb4cNbe8BY2d/YZrmKJZiYfmKGVedvpmmt5paSf7j2e3Zfwa7GKPFf+r8lLvWN/7yOQOdU2o6f3tGjHWABLGbwpAJehA9kVkNpjee0LhSMoZd0XlLdH31rTulg5ONa27j17E6i8oB+Mu3wWY4anNuMigZZcVeupxg3cVhhX37433t40ll5h+rWOXakPhCNr2DCbdwq/AM/p3qJLtJ86G8ZsCUAk6kHNJlCUU3Zf28c09UeHY2NkvlbWYX9kaK0gb/z9TAnNLycKMiw6a+TazRH7o9DJvMYb9eaaIPs3+7p+EZd5iSz5josasVAKPcwBJIhi/KQCVoAM5k2Tzw4wErwVVm9DYOYCte/dj2VPJ9wnWC3ihcARbdw3gSNnphjuENRHY7/t81o2LoRm3C0qbcHg4JCQCZ3hq8WTJd3G4dJKpGb+I340Him+xxK9SLdWKCDzuBEL0YPymAFSCDuQ8rOgcHZuREN2BQlvyig9wh33qwTvkd+OFkn/O6fpAJ1myrPToMu896C/9vGmiL96Xlnr9hq891c48Iku1FHjECIzfFIBK0IGch1W7fsh2pm7duz9hJrLdd6EpwTzid2O7bzbrA21ucxLUwt3h9eCIBaJP8509vhmGs37Ln3oT9zXvwubdH6CtexAV9V2YVxH7ObhUS6yE8ZsCUAk6kPOQ2SPWyJJw257BpLMIp3lGsyL1byWvG7zDW4wRk2q4In433vDN5dKwA+yLnmfxZ980hEvNa+zQy/qZOXBcE3pGG7MIMQLjNwWgEnQg5yGaAaxp3W1oqbiuo8+03SkKPfV4wzcvWodlRmC/w+vJuIihyfvBDd5VOOLLs0z0af5RU/xD0x8URJd62dBBzITxmwJQCTqQ85DZLSQUjuC+5p1SwU5r7mjs7DdtoG27b66pRf3Dvjx80fNsxoUNLblN99ThJRMHNyfzifqSyy3PEKdq9kjUmMWRLsQIjN8UgErQgZyJzG4hMjWDYwOc6DgZUbvd60XIRCEwKgTdmOV5IeNChxZrMzy1CPpmWZrt03xgi+/LaW0WipmB+SmpGrM41JkYgfGbAlAJOpBzEV1uSpUxHBuktDqntu5BzEqxm4gRK/TUo993jqnCIOJ347DvsxkRgoUrG7DsqTczLriywaZ76nBP8a0YtrC2b+zv/KBvcsa6xOP/xkQfsritG5GB8ZsCUAk6kLMRLThPtUfp3PKWhENprbBZnhdwyHe66UJwyHcaLvQ8l3ExlEuWrmyf9jse9E3J+O84PpsnOzqJEBEYvykAlaADEQ09cVdU1oKa1t0xG9nLBELVLOEvixeZLhwynR3KBZvhqcVvS67FxyYObM62pd5UNjabxwwgsQLGbwpAJehAZCyJMoZGh0sv+uVW5UA63VOHnb4LLBGCn5Sehrd952c8Y+QEm+l5CS2+r6VliXfs73Cn73wl4XdeSaMl30f83r+ijVmEiML4TQGoBB2IiKAyXFrb0D5R4Csq1x8CHG8zPLU44DvTEnER8bsxVJqHiuLbsiqLlO02ujXbtaZuzSbyuxouzcOTJd/N6gHg2gOU9kBV09ot3JhFiAiM3xSAStCBiAgyw6Xjg9vcTwVessBXUd8lfMyWkkstFRsRvxubfP+ERd57OVhaxwo99bjZW4qhNGb6tN/LgG9q1nd1a9m8xs7xg9CLylvGPfBwDiAxCuM3BaASdCAigur2cnpDp8fWF8oef4anFk+VfBcjFouQkN+Nd33n4kZvRc6LwRmeWvzBt8DymX16wm+L7+KMZ2bnVSTOZI+1Ak8Dqhp3JJz5p/09cCcQogrjNwWgEnQgIkIoHMH8ylbDwbOuow+hcAQ1rd0oKhufAdGyJUYGSz9a/P20ZKLCfjf+5jsDRZ6nMy7G0mVaXd+RDGT7hkvzUFn8o4wLv7E+mso/R9+XvFOe9X7ELBi/KQCVoAMRUWpadxsOoPc174zWQCV6z4pn/hQNkLLHn+6pM31sTDJxEip1o8W3EDM9L2VcnJhto9nVa9Iu+rTv9l3fuVn3vWpLtFWNO5K+r7FzgB2/JG0wflMAKkEHIqIYrQOUMb0aKRnbWHJJ2jNV4VI3/l46GRt9X8s64SJi0z11WFV8G3aUzkQoQ6LvSKkblcWLsyLbF281rd0ARrPgyXxTy+zVbusVOm6ymX+i8ztJbsP4TQGoBB2IiKJaByhqBZ8G3bqOPjy+uUf650czWNfiUGl6MoLxYuZw6STcXbwkK8VMrOi7FQcy8B2N/a76s7ypY35l65itD8Uy4KI+mygDKLqDDyGM3xSAStCBiChGZwHK2tgaKdFt6pIJnUO+yRkROaOZrdOwt3QGbspwE8mFnuewyzcTw6XujGT54r+Xl0quyGqBrPmhJrpC4ci42tVEVtveZ3jmX6Jh6xwVQ/Rg/KYAVIIORGRoCg6kLQC37RnE1r37Uf7piJhkIlD7t/NKNiQUQAd9Z2Rc+IRLRy1U6sY+3zR80fOsqSJv56ciLxxnmfzc2mc/XHoa/t3rs0U3dXzGTSb7vXXv/oRbKyYTcqkesNg8QuJh/KYAxM9//nMUFBRgwoQJuOiii7B582bhn6UDEVkaO/tRuNL6IHyBP3YbuWTnvNDfLHTM0S3K/t+MZ8H0RKEmDP9Rmoe/l56GoVJ3NGMXLnVjZMz/H/v+UJaIvHgL+934W+npWVvbp9lFFRvx0pvv4fHNPaht16+5E61/LVjZgOGRMAD5pVw2jxBZGL9zXAA+99xzOOGEE/DYY4/h7bffxo9//GOccsop2Ldvn9DP04GIERo705cJjLflT72JB1p2RQdMG7Uiz9MI+bJPONnZIn43Dpaejucf/D/wvfgmZvr0M7LZZCLLqjId8GMFmkwzh6jITNY8QnILxu8cF4Bf/vKXsWzZspjXzj//fKxcuVLo5+lAxCh6GQ472hc9z+LPvmlZkxW0m2l7Kj9VcjVmeGqjy5Rt3YMZ/92mslUNO4T8XOaYRgUaM4BEFsbvHBaAw8PDOO6441BbWxvz+n/8x3/gkksuEToGHYioMDbDYaRjN9tMWyL+uDQzjSN2srDfjRd1mjkaOwfQFBwQbpqwwkSbhlLV1BlpfDIq0FI1PLEGkMTD+J3DArC/vx8ulwtbtmyJeb2yshLnnXee7s8MDQ3h4MGDUevt7c15ByLmoNqxm202w1OLJ0u+m5GByNloWr1in28qfuj1J2zmSDXwOx22oGoTalq7lQWbTPOHGQLNSPMIyV0oACkAsXXr1pjXV61ahZkzZ+r+TCAQgMvlGme57EDEPBIFMLvbLM8LeMM3LyfFYMTvxn7fFFzoeU7ou7qgtMnS30Uie3xzT0ytnRk1dTLDz80SaJwDSEShAMxhAWhkCZgZQGI1TqkNTGROzwxqmb59pQVYleUdvJrw0su8mVFTJ3qMiyo2mirQuBMIEYECMIcFIDDaBLJ8+fKY12bNmsUmEJJRxgawmtbdmF/ZmjKIF3galLaBy4SNZgbnjs7es7EY1ETfLt8M4Uxftlj8wGbN79r2DGJ+ZWvSbLRoDWCyY8yraImOfiEknTB+57gA1MbA/OpXv8Lbb7+Nu+66C6eccgr+/Oc/C/08HYikg8bOfsyrSCzutCWuxs7+jAsKo1boqcci7724y/ufeN93VtZmByP+0ZmCB0vPwL7Sc7Gq+Nasz/IlFH8rG1DVONrJq5d5TvVAof1sMliXR7IVxu8cF4DA6CDoadOm4cQTT8RFF12E1157Tfhn6UDEahJtb6VZTevuaBYmXfsNp8NG9yS+Bn8rPQNHtOHNaRKF8QOmR0pHhzI/U/IdzPDUKn2uwpUNmOVrzPj3O9b+/YnX9QViip8TFXCsyyPZCOM3BaASdCBiJbLbW8kU3WejJdqKLiqePPW4wbsKm30XHxWFJuwEMvY9f/IVYZbnBUs/50zfBlzoz0yzh5km07nLujySbTB+UwAqQQciViJbiG/3DGCBpwHXPvw/Gb8OmpxxuDKxI4zfFIBK0IGIlciO4rD7LMECj/i+xLTsMb1RMMz4kWyH8ZsCUAk6ELESI6M4nDpLkJa9Fp8BZM0fsQOM3xSAStCBiJUY3d6qKTig28E5q3TDuAzbgqpNKK/vyriIiL1O+9fH5YLp+V+ipiV2/ZJsg/GbAlAJOhCxGiNjNJqCAwkD9jTPaOfw2KW5tu5By0TCgxt3o3Cl3M/UtO7OuLihxZqI/8k2LRGSSRi/KQCVoAORdCCzpGYkCLftsUYAFqxsQGNnPxo79QVpImvs7EdTcADzK527I0omrEBSiGtWVN4y7neh539m7B5CSLpg/KYAVIIORKxGK6avbe/D45t7ULutN2lRvZEgbPX4mMbOfqllZk2ghsIRtO0ZRFGZvXY4yZRpWbr45f+ishbUtO7G8EgYW/fux02/+l/pY7d1D6Zs6jBj/2BC0gXjNwWgEnQgYiVGiumNBGGrx8cUrmzAQxvllnUf39yDuo5R0ZtpYWUX03wjVQeukd+3iGhTzQCyc5ikE8ZvCkAl6EDEKowW0xsJwqFwJOlWc2ZZOvYq/uFjf8Rcm+2JbIbdtbYdbXsGo1m+ZCIqVZmAnt3XvCulKDPatKT5OzuHSTph/KYAVIIORKxApZjeaBBOxz7CuSjM0m3xDTeJRFSqLQYTWSpRZrRpiZ3DJN0wflMAKkEHIlagupRmJAgDQFXjDssFyk+e68i4SMolSyW8ZLOyIqLM6qYlQsyA8ZsCUAk6ELECM4rpjS6pNXYOYF7FRssEyZLfvpFxUZRrFi+itFo7o/MfRUSZaD0fO4dJpmD8pgBUgg5ErMCsoGi0qD4Ujkg1X1zAwc22sLbuQd0HA6Nmhihj5zDJFIzfFIBK0IGIFRip41PtoIz/+eGRcMp9hQs8o929oXAEjZ393H4uy83sHVbMEGXMAJJMwfhNAagEHYhYhUwdn2oHZaKfr2rckXRf4cbO/phjpKPLl5Y9ZoYoU+kcJkQFxm8KQCXoQMRKRISdagdlqm7QqsYdhq+B5kwzW5QZbVoiRAXGbwpAJehAxGqSLe2qdlCKzIMrKm9JOlvOyEw5mn3NKlHGOYAk3TB+UwAqQQcimUS1fkr052tau5WvgZY+gWbGMQo8YtlfM+FOICSdMH5TACpBByKZRLWDUvTni8pbEgZjq/cRponbT57vMGXY9liRlyoDTcFG7ArjNwWgEnQgkknSlQE06xh2tsKVDbjl1687ejeTivouYSHHJVtidxi/KQCVoAORTKLaQRkKR1BUJiZoEmURU11DKrOqeeS6NVtNP6a2LJqsM9oOFt+tLSvcuHUbcQKM3xSAStCBSKZR7aCsad0tJBqSjfxIdA2J7MurWtEUHEBjZz/mVViTUSvwWDOgem55Cxo7+8dlv+wwAmdeRQuaggNKS7fcuo04BcZvCkAl6EAkG1BZjguFI0nFi2hAbwoOCA8aLqntNHVHinRbTevucSKqrXsw49eVymrbObiZEA3GbwpAJehAJFtQyeqYtaR342N/FBIH/89Dr9l7CbVsfFOMHcbhtO0ZlPIpPbh1G3EKjN8UgErQgYhTMKOo3/fydiFxcL5vQ8ZE0ExfoynH0ctwmTUQW+YYc8tbMKesWei98ytblevzmAEkToHxmwJQCToQcRKqYz0OD4dME2pfDDSjdlsv7mvemTGxmMwSZbhUl7bnlrdgfmVrzGuFK2PfM6+iBRX1XcL1m2OFpWqTBrduI06B8ZsCUAk6ECGxLP7tG0lFyNX/vVlYsGzduz9rx8wky3BpQrp2W69wVnSste0ZjBHi2k4stdt68fjmHtS296Ftz+A4oSgqAlUFGrduI06A8ZsCUAk6ECHjSSQCF//2DSlBV9fRpzxmxmyTFVAV9V3S59DLLprdNKO6RMs5gMTuMH5TACpBByJEn8PDIfhe3o4fPP6/8L28HYeHQwBGs2Oio180kSI7ZkbVihLU1MlmuJqCA6aIM7NqC1OJTFm4EwixM4zfFIBK0IEIkaexsz+lQInPsqXKgM2raMGyp/5kijiqad2tnOEy0hWsl120qruYTRok12H8pgBUgg5EcgErMj1VjTuSCiE9oTX2Otq6B9G2ZzDmmoZHwuMaJlSyY6k+d7J/l61dTJRdNLsGkk0ahIzC+E0BqAQdiDgdK2u9GjsHMK9io2nHNkssiWTHUn0vovPyUn1u2eMYEZmE5CKM3xSAStCBiJMxe89XvYyZmdlFM8SS3pBnI99LTWu30Pnua96V9HMbEbULqjahqnEHmzQISQLjNwWgEnQg4lTM3vM1HV2jZmQAa1p3Jz2H6Pfy5VWpR7TMr2xN+f2Jzt1r6x4cJ6LZpEFIYhi/KQCVoAMRp2Lmjg9mZxITodowMbc8dfbPzJq8Fc/8Sehzce4eIebD+O1AAfjuu+/iRz/6EQoKCjBx4kSce+658Pv9GB4ejnnfvn37cPXVV+Pkk0/G5MmTceedd457TyroQOnB5XLh5ZdfzvRl5BRm7flqdiYxFUZHr0wTFFJm1uSJLDeP/Vxc0iXEPBi/HSgAm5qacMstt6ClpQU9PT1Yv349zjzzTPz0pz+NvicUCmH27Nm47LLL0N7ejtbWVpx11llYsWKF1Lmc5kAulyup3XzzzYaPPW3aNDz00EOGr0tGAAYCARQVFRk6FxnFrAxgJvaOld0ibZon9dKv7OcRNZnPzSVdQszDafHbCI4TgHrce++9KCwsjP73hg0bcOyxx6K/vz/62tq1azFhwgQpZ0iHA6Xzpv/+++9HraamBm63O+a1AwcOGD42BaC9MGvPV7Myido1ifwthMIRzK8UXwqWyUCK7Ewyt7wFcwL6w6SNfG5CiPlQAOaIACwpKcHFF18c/e/S0lLMmTMn5j0fffQRXC4XXnnlFeHjWu1AmVz2eeKJJ5CXlxfzWn19PS666CJMmDABhYWFKCsrw8jISPTfA4EAPv/5z+PEE09Efn4+7rzzTgDAwoULx2UTE9Hd3Y2vf/3rmDBhAmbNmoWNGzeOE4A/+9nPMGPGDJx00kkoLCyEz+fDkSNHotcdf64nnngCAPDAAw9g9uzZOPnkkzF16lQsX74cH3/8sVlfmeMwo/bMrAyg3t9CUVkLalq7dcWbyO4hRmvoRJaZ73hmW9ozn4QQcSgAc0AA7t27F263G4899lj0tSVLluCKK64Y994TTzwRzz77bMJjDQ0N4eDBg1Hr7e21zIHSVTifiHgB2NzcDLfbjd/85jfo6enBxo0bUVBQgLKyMgDAiy++CLfbjQ0bNmDfvn14/fXX8eijjwIAPvzwQ0ydOhUVFRXRbKIe4XAYs2fPxqWXXoqOjg689tprmDdv3jgBePfdd2PLli149913UV9fj8997nNYvXo1AODw4cP46U9/igsvvDB6rsOHDwMAHnroIbzyyit455138Pvf/x4zZ87E8uXLLfn+nIJZO2KoZBJTbYVWVN6iez2pdg8x+jAVCkdQVJ54OzvtMyXaUk4mg0oIsQYKQBsJwEAgkLJG7c0334z5mf7+fnzhC1/ArbfeGvP6kiVLcOWVV447xwknnIC1a9dKX4PZDpTuwnk94gXg17/+dVRVVcW856mnnkJ+fj6A0ezaeeedF83ExSOyBNzS0oLjjjsOvb290deamppSLgHfe++9MRle0SXgF154AZMnT075vlxHtQxBJZMo09mbcveQPYO641JkEc1qJqpFZPcuIZmHAtBGAnBwcBA7d+5Map988kn0/f39/TjvvPPwwx/+EOFwOOZYRpeA05UBzEThfDzxAvDkk0/GxIkTccopp0Rt4sSJcLlc+Mc//oH33nsPn//85zF16lQsXrwYtbW1McvDIgKwpqYmplYTAA4cODBOAL744ov4p3/6J3zuc5/DKaecggkTJuCMM86I/nsiAfjKK6/g8ssvx1lnnYXPfOYz0ev/+9//Lv39EDmMZhJlmi7SlVGTqWtk9y4h2QkFoI0EoAx9fX2YMWMGrrvuOoRCoXH/rjWBDAwcvQk/99xzWdMEYmbhvFHiBeDEiROxevVq7NmzZ5xpAvvw4cNYv3497rzzTkyZMgVf+cpXohlBEQH40EMPjROA2nesCcA//vGPOO6447Bq1Sq8+eab6O7uRkVFRcy16gnAP//5z5g4cSLuuusu/PGPf8Tu3bvxq1/9Ci6XC3/729+Mf1FEGCOZRNmxK23dg5Y3Tck+oLF7l5DsgwLQgQJQW/b9xje+gb6+vpguVg1tDMw3v/lNtLe3Y9OmTZg6dWrWjIHJxgzgV7/6VfzoRz8S/vldu3bB5XJh27ZtAIAZM2bg/vvvT/oz2hLw2O7s5ubmGAF4//3349xzz435uVtvvTXmWisrKzF79uyY97z00ks4/vjjY7LBd999NwVgliM7dqWoLLY2z4psm1kd0oSQzEEB6EABqNcFqtd5um/fPnz729/GSSedhEmTJmHFihUYGhqSOpdVDpQNAUavCeT4449HIBBAV1cX3n77bTz33HMoKSmJvv/xxx9HMBhET08PSkpKcNJJJ2H//lGResUVV+Caa65BX18fBgcHdc8ZDodxwQUX4Jvf/CbeeustbN68GRdffHGMAKyrq8Pxxx+PtWvXYu/evfiv//ovTJo0KeZan3nmGZxyyino6OjA4OAghoaG0NHRAZfLhZqaGvT09ODJJ5/E2WefTQGY5aju7mFVvR135yDE3lAAOlAAphMrHSjTAUZvDExzczO++tWv/t/27j62xvv/4/il1R5nvZmqNqi27lVi2iGlmxCLpLbFRCYzsamwLcxok2Zsk6jvqIlvbPaHDXUfd4u772I3jC3Gz6Ta0VG02rVo+2OE1M2om/b1++O7np+DcpzrHNc5zvORfCKu9pzz9slHP69e1+f6XLLb7YqMjFRqaqrjTt9t27apX79+ioyMVFhYmPr376/du3c7XnvgwAH16tVLNpvtodvAlJaWasCAAQoNDVW3bt3uOwMoSR9++KGio6MVHh6uUaNG6YsvvnCqta6uTq+//rpatmzptA3M559/rrZt28putys9PV1r1qwhAPqBR90F7EoI9MYvTKzvA/wXAZAAaMrTvA8g4Et+PPq/D916xaolE6zvA/wTAZAAaMrT9iQQwJfdqW/Qwl2l963zu/fvTbV/7yjh/w8ASQRAiQBoCgMIePLu/aXof8ouuHwWkDPoACTmb4kAaAoDCLCeK8/n5SYNAHdj/iYAmsIAAnyDK8/+ZZsWAI2YvwmApjCAAM/wxFrXRz3790nuownAtzF/EwBNYQAB5nnibvfGALn19yplbjjkUgD05pN0APg25m8CoCkMIMCcpvb4e5y1eo975o8zgACYvwmApjCAAPc96ikfrqzVc2eTaNYAAmD+JgCawgAC3Gf2mdfuPCaOu4ABSMzfEgHQFAaQOTk5OUpOTnb8PSMjQ8OHD3/idVRWVsowDB0+fPiJf3Yg+8/halNr9VwNkOwDCOBezN8EQFOe1gGUkZEhwzBkGIaaN2+ujh07Kjs7W9euXfPo59wbAGtra11+Lq8nQxsB0BpmzwC6GiD/vaOEJ+kAcPK0zt+PgwBowhMZQPV3pIq90pFN//2z/o73PusfGRkZGjp0qM6ePaszZ85o3bp1stvtmjhx4n3fe+vWLbc/594A+DgIgP7vURs4P2qtntkACSBwEQAJgKZ4fQAd+1ZakCTlRP5/W5D03+Ne9KBLse+8847atGnjCG3Lly9Xx44d1axZMzU0NKi2tlbvvvuuYmJiFBERocGDB6uoqMjpPT777DPFxsYqPDxc48eP1/Tp0x96Cbi+vl42VABHAAANC0lEQVTz5s1T586dFRoaqvj4eM2ZM0eSHGcoG9ugQYMcr1uxYoWSkpJks9nUvXt3LVq0yKmO/Px8paSkyGazqU+fPtq6dSsB8Am6e8+/hbtOPnADZ1fW6pkNkAACFwGQAGiKVwfQsW+lnGedw19O5D/HnvVqCHxQAJwyZYqio6OVk5OjsLAwpaen69ChQ/rjjz/U0NCgF198UcOGDVNBQYFOnjyp7OxsRUdH6+LFi5Kkb775RqGhocrLy1NJSYlmzJihiIiIhwbAadOmKSoqSqtWrVJ5ebn27dunvLw8SdLBgwdlGIZ2796ts2fPOj5n6dKlatu2rbZs2aKKigpt2bJFrVq10qpVqyRJ165dU0xMjEaNGqXi4mJt375dnTp1IgA+IQ/asiX5XzuV/K+dbq3Va+oJIO7c7OGJzagB+AcCIAHQFK8NoPo795/5uzcELujhtcvB9wax/Px8RUdH64033lBOTo5CQkJ0/vx5x9d//vlnRUZGqq6uzul9OnfurCVLlkiS0tLS7ruE3K9fvyYD4JUrV2Sz2RyB715NXbaNj4/X+vXrnY7Nnj1baWlpkqQlS5aoVatW+vvvvx1f//rrrwmAT8DD9vxLnP6dFu4qdSt8eWIjaU+8BwD/QQAkAJritQFUsfch4e+uVrHXs5/7j4yMDAUHByssLEw2m01BQUEaMWKE/vrrL+Xk5KhLly5O3z9//nwFBQUpLCzMqQUFBWnatGmSpJYtW2r16tVOr8vKymoyAObn58swDFVUVDywxgcFwPPnz8swDNntdqc6bDabYmNjHZ85ePBgp/cqKioiAHqZJ/b8e9T7u3v2zhObUQPwLwRAAqApXhtARza5FgCPbPLs5/4jIyNDQ4YMUVlZmU6dOuV0o8eDbtyYN2+e4uLiVFZWdl+7cOGCpMcPgEeOHHnsAHju3DkZhqG1a9feV0fj+2RmZhIALeCrN2x4O5gC8E0EQAKgKU/zGcCm9uN7UAD86aefFBwcrMrKyibfMy0tTZMmTXI61r9//yYD4I0bN2S325u8BFxTUyPDMFRYWOh0PC4uTp9++mmTdTReAr5+/brj2OLFiwmAXmZ2zz9v8dVgCsC7CIAEQFO8vwbwQTeBPPk1gHd7UABsaGjQgAEDlJycrB07dqiyslL79+/XjBkzVFBQIEnauHGjbDabli9frtLSUs2cOfORN4HMmjVLUVFRWr16tcrLy3XgwAEtW7ZMknT79m3Z7XbNmTNH586dU21trSQpLy9PdrtdCxcuVGlpqY4cOaIVK1ZowYIFkqSrV6+qdevWGj16tI4dO6bvv/9eXbp0IQB6ma8GLV8NpgC8iwBIADTlydwFfG8ItOYu4EZN7d135coVTZkyRe3atVNISIji4+M1ZswYnTlzxvE9ubm5at26tcLDw5WRkaFp06Y9chuYOXPmKDExUSEhIUpISNDcuXMdX8/Ly1N8fLyCgoKctoFZt26dUlJSFBoaqqioKA0cOFBbt251fP3AgQNKTk5WaGioUlJStGXLFgKgl/nqli2+GkwBeBcBkABoijX7APbw+j6AgDd4cssWT/HVYArAuwiABEBTntYngQDe4ovbrfhiMAXgXQRAAqApDCDg8fnihsu+GEwBeA/zNwHQFAYQ8PTwxWAKwDuYvwmApjCAAADwP8zfBEBTGEAAAPgf5m8CoCkMIAAA/A/zNwHQFAYQAAD+h/mbAGgKAwgAAP/D/E0ANIUBBACA/2H+JgCawgACAMD/MH8TAE1hAAEA4H+YvwmApjCAAADwP8zfBEBTGEAAAPgf5m8CoCm1tbUyDENVVVW6fPkyjUaj0Wg0P2hVVVUyDEO1tbVWRwnLEABNaBxANBqNRqPR/K9VVVVZHSUsQwA0ob6+XlVVVaqtrXWEQc4Guv+bGH1H39F3/tHoO/rO3/uucd6ur6+3OkpYhgDoIZcvs57AXfSd++g799F37qPv3EffuY++8ywCoIcwMN1H37mPvnMffec++s599J376DvPIgB6CAPTffSd++g799F37qPv3EffuY++8ywCoIfU1dUpJydHdXV1Vpfid+g799F37qPv3EffuY++cx9951kEQAAAgABDAAQAAAgwBEAAAIAAQwAEAAAIMARAAACAAEMA9JLvvvtOqampatGihaKjozVixAirS/IrdXV1Sk5OlmEYOnz4sNXl+LzKykqNHz9eHTp0UIsWLdSpUyfNnDlTN2/etLo0n7Ro0SJ16NBBNptNvXv31t69e60uyS/MnTtXffv2VXh4uGJiYjR8+HCVlJRYXZbfmTt3rgzDUGZmptWl+I3q6mqNGTNGrVq1kt1uV3JysgoLC60uy68RAL1g8+bNioqK0tdff63S0lKVlJRo06ZNVpflV6ZOnaqXX36ZAOiiH3/8UePGjdPOnTv1559/6ttvv1VsbKyys7OtLs3nbNy4USEhIcrLy9Px48eVmZmpsLAwnT592urSfF56erpWrlyp4uJiFRUV6dVXX1VCQoKuXbtmdWl+4+DBg+rQoYN69epFAHTRpUuXlJiYqHHjxik/P1+VlZXavXu3ysvLrS7NrxEAPez27duKi4vTsmXLrC7Fb/3www9KSkrSsWPHCIAmzJ8/Xx07drS6DJ+TmpqqiRMnOh1LSkrSRx99ZFFF/uv8+fMyDEO//vqr1aX4hatXr6pr167atWuXBg0aRAB00fTp0zVgwACry3jqEAA9LD8/X4ZhaMWKFUpJSVGbNm00dOhQFRcXW12aXzh37pzi4uJUUFCgyspKAqAJM2bMUJ8+fawuw6fcvHlTwcHB2rp1q9PxqVOnauDAgRZV5b/KyspkGIaOHj1qdSl+YezYscrKypIkAuBj6NGjh7KysjRy5EjFxMQoJSVFS5cutbosv0cA9LANGzbIMAwlJCRo8+bNKiws1OjRoxUdHa2LFy9aXZ5Pa2ho0NChQzV79mxJIgCaUF5ersjISOXl5Vldik+pqamRYRjav3+/0/Hc3Fx169bNoqr8U0NDg4YNG8aZGRdt2LBBPXv21I0bNyQRAB+HzWaTzWbTxx9/rEOHDmnx4sVq0aKFVq9ebXVpfo0A6KKcnBwZhvHQVlBQoHXr1skwDC1ZssTx2rq6OrVu3VqLFy+28F9gHVf77ssvv9QLL7ygO3fuSCIASq733d1qamrUpUsXTZgwwaKqfVdjAPztt9+cjs+ZM0fdu3e3qCr/9P777ysxMVFVVVVWl+Lzzpw5o9jYWBUVFTmOEQBdFxISorS0NKdjU6ZMUf/+/S2q6OlAAHTRhQsXdOLEiYe2Gzdu6JdffpFhGNq3b5/T61NTU/XJJ59YVL21XO274cOHKygoSMHBwY5mGIaCg4M1duxYq/8ZlnC17xrV1NSoW7duevvtt1VfX29h5b6JS8Ce8cEHH6h9+/aqqKiwuhS/sG3bNsfPsrt/tjVr1kzBwcGOX3rxYAkJCff9QvvVV1+pXbt2FlX0dCAAetjly5dls9mcbgK5deuWYmNjnc4K4n6nT5/W0aNHHW3nzp0yDEObN2/mLIMLqqur1bVrV7355ptMKA+RmpqqSZMmOR3r0aMHN4G4oKGhQZMnT1a7du108uRJq8vxG1euXHH62Xb06FH17dtXb731FusnXTB69Oj7lhpkZWXdd1YQj4cA6AWZmZmKi4vTzp07VVJSogkTJig2NlaXLl2yujS/wiVg1zVe9n3ppZdUXV2ts2fPOhqcNW4Ds3z5ch0/flxZWVkKCwvTqVOnrC7N502aNEnPPvus9uzZ4zTGrl+/bnVpfodLwK47ePCgmjdvrtzcXJWVlWndunV65plntHbtWqtL82sEQC+4deuWsrOzFRsbq4iICA0ZMoS7gN1AAHTdypUrm1wjiPstWrRIiYmJCg0NVe/evdnGxEVNjbGVK1daXZrfIQA+nu3bt6tnz56y2WxKSkriLmAPYHYAAAAIMARAAACAAEMABAAACDAEQAAAgABDAAQAAAgwBEAAAIAAQwAEAAAIMARAAACAAEMABAAACDAEQAAAgABDAAQAAAgwBEAAuMv69etls9lUXV3tODZhwgQ999xzqq2ttbAyAPAcAiAA3KWhoUG9evXS5MmTJUmzZs1S+/btnQIhAPg7AiAA3GP79u2y2WzKzc1VVFSUiouLrS4JADyKAAgAD/D8888rNDRUe/bssboUAPA4AiAA3GPHjh2y2+0KDg7WiRMnrC4HADyOAAgAd/n9998VERGhNWvW6JVXXtHIkSOtLgkAPI4ACAD/qKysVJs2bZSbmytJKiwsVLNmzVRYWGhxZQDgWQRAAJB08eJFJSUl6b333nM6/tprryk9Pd2iqgDAOwiAAAAAAYYACAAAEGAIgAAAAAGGAAgAABBgCIAAAAABhgAIAAAQYAiAAAAAAYYACAAAEGAIgAAAAAGGAAgAABBgCIAAAAABhgAIAAAQYAiAAAAAAeb/AFnu+4rxkehPAAAAAElFTkSuQmCC\" 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"text/plain": [
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@@ -2583,7 +2473,7 @@
},
{
"cell_type": "code",
- "execution_count": 13,
+ "execution_count": 14,
"id": "f8d501ff",
"metadata": {},
"outputs": [],
@@ -2647,7 +2537,7 @@
},
{
"cell_type": "code",
- "execution_count": 14,
+ "execution_count": 15,
"id": "7b9beb21",
"metadata": {},
"outputs": [],
@@ -2680,7 +2570,7 @@
},
{
"cell_type": "code",
- "execution_count": 15,
+ "execution_count": 16,
"id": "fbea6b0c",
"metadata": {},
"outputs": [],
@@ -2690,546 +2580,546 @@
},
{
"cell_type": "code",
- "execution_count": 16,
+ "execution_count": 17,
"id": "b92ed4b0",
"metadata": {
- "scrolled": false
+ "scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "Epoch 0/500 total: 58.60563, -LL: 29.30297, prior: 0.49401, aleatoric unc.: 1.70738\n",
- "Epoch 1/500 total: 29.89883, -LL: 22.77377, prior: 0.51578, aleatoric unc.: 1.74675\n",
- "Epoch 2/500 total: 24.01581, -LL: 19.56905, prior: 0.54058, aleatoric unc.: 1.78531\n",
- "Epoch 3/500 total: 20.88541, -LL: 15.23512, prior: 0.56686, aleatoric unc.: 1.82458\n",
- "Epoch 4/500 total: 18.42086, -LL: 12.56114, prior: 0.59138, aleatoric unc.: 1.86375\n",
- "Epoch 5/500 total: 16.78540, -LL: 11.47957, prior: 0.61184, aleatoric unc.: 1.90320\n",
- "Epoch 6/500 total: 15.74639, -LL: 10.39981, prior: 0.63168, aleatoric unc.: 1.94387\n",
- "Epoch 7/500 total: 15.23265, -LL: 10.92122, prior: 0.64618, aleatoric unc.: 1.98676\n",
- "Epoch 8/500 total: 14.43628, -LL: 14.04801, prior: 0.65764, aleatoric unc.: 2.03084\n",
- "Epoch 9/500 total: 13.75567, -LL: 9.28419, prior: 0.66495, aleatoric unc.: 2.07617\n",
- "Epoch 10/500 total: 13.46332, -LL: 9.24567, prior: 0.67066, aleatoric unc.: 2.12401\n",
- "Epoch 11/500 total: 12.68328, -LL: 8.02405, prior: 0.68236, aleatoric unc.: 2.17244\n",
- "Epoch 12/500 total: 12.16965, -LL: 10.14399, prior: 0.69100, aleatoric unc.: 2.22149\n",
- "Epoch 13/500 total: 11.89046, -LL: 10.02692, prior: 0.69707, aleatoric unc.: 2.27265\n",
- "Epoch 14/500 total: 11.31826, -LL: 8.22698, prior: 0.70348, aleatoric unc.: 2.32503\n",
- "Epoch 15/500 total: 11.15097, -LL: 8.46218, prior: 0.70463, aleatoric unc.: 2.37917\n",
- "Epoch 16/500 total: 10.78811, -LL: 6.91465, prior: 0.70900, aleatoric unc.: 2.43505\n",
- "Epoch 17/500 total: 10.27545, -LL: 7.55249, prior: 0.70822, aleatoric unc.: 2.49083\n",
- "Epoch 18/500 total: 9.88403, -LL: 7.78374, prior: 0.70896, aleatoric unc.: 2.54750\n",
- "Epoch 19/500 total: 9.49734, -LL: 6.96424, prior: 0.71104, aleatoric unc.: 2.60481\n",
- "Epoch 20/500 total: 9.18567, -LL: 6.83609, prior: 0.71782, aleatoric unc.: 2.66279\n",
- "Epoch 21/500 total: 8.77549, -LL: 6.85847, prior: 0.72051, aleatoric unc.: 2.72092\n",
- "Epoch 22/500 total: 8.64839, -LL: 6.52611, prior: 0.71736, aleatoric unc.: 2.78174\n",
- "Epoch 23/500 total: 8.43415, -LL: 7.78695, prior: 0.71795, aleatoric unc.: 2.84376\n",
- "Epoch 24/500 total: 8.17714, -LL: 6.13595, prior: 0.72104, aleatoric unc.: 2.90688\n",
- "Epoch 25/500 total: 7.70156, -LL: 6.61542, prior: 0.72217, aleatoric unc.: 2.96854\n",
- "Epoch 26/500 total: 7.61942, -LL: 6.63054, prior: 0.72667, aleatoric unc.: 3.03244\n",
- "Epoch 27/500 total: 7.42529, -LL: 5.76781, prior: 0.72993, aleatoric unc.: 3.09773\n",
- "Epoch 28/500 total: 7.29471, -LL: 6.51807, prior: 0.72927, aleatoric unc.: 3.16509\n",
- "Epoch 29/500 total: 7.12159, -LL: 5.48303, prior: 0.73176, aleatoric unc.: 3.23374\n",
- "Epoch 30/500 total: 6.79870, -LL: 6.10557, prior: 0.73237, aleatoric unc.: 3.30124\n",
- "Epoch 31/500 total: 6.60342, -LL: 5.65072, prior: 0.73511, aleatoric unc.: 3.36955\n",
- "Epoch 32/500 total: 6.63333, -LL: 6.37231, prior: 0.73616, aleatoric unc.: 3.44177\n",
- "Epoch 33/500 total: 6.25342, -LL: 5.67089, prior: 0.73999, aleatoric unc.: 3.51138\n",
- "Epoch 34/500 total: 6.25324, -LL: 5.80523, prior: 0.74006, aleatoric unc.: 3.58479\n",
- "Epoch 35/500 total: 6.06724, -LL: 4.63822, prior: 0.73928, aleatoric unc.: 3.65814\n",
- "Epoch 36/500 total: 5.97354, -LL: 4.87066, prior: 0.73962, aleatoric unc.: 3.73306\n",
- "Epoch 37/500 total: 5.75250, -LL: 5.21252, prior: 0.74361, aleatoric unc.: 3.80782\n",
- "Epoch 38/500 total: 5.70047, -LL: 4.60235, prior: 0.74538, aleatoric unc.: 3.88453\n",
- "Epoch 39/500 total: 5.65181, -LL: 5.21456, prior: 0.74527, aleatoric unc.: 3.96423\n",
- "Epoch 40/500 total: 5.43323, -LL: 4.63033, prior: 0.74861, aleatoric unc.: 4.04155\n",
- "Epoch 41/500 total: 5.28977, -LL: 5.04850, prior: 0.74891, aleatoric unc.: 4.11915\n",
- "Epoch 42/500 total: 5.24329, -LL: 5.24680, prior: 0.74535, aleatoric unc.: 4.19924\n",
- "Epoch 43/500 total: 5.17848, -LL: 4.70368, prior: 0.75037, aleatoric unc.: 4.28055\n",
- "Epoch 44/500 total: 5.16991, -LL: 4.86729, prior: 0.74977, aleatoric unc.: 4.36667\n",
- "Epoch 45/500 total: 5.00426, -LL: 4.76213, prior: 0.74627, aleatoric unc.: 4.45042\n",
- "Epoch 46/500 total: 4.96309, -LL: 4.31775, prior: 0.75200, aleatoric unc.: 4.53622\n",
- "Epoch 47/500 total: 4.89156, -LL: 4.62450, prior: 0.75400, aleatoric unc.: 4.62413\n",
- "Epoch 48/500 total: 4.77733, -LL: 4.33423, prior: 0.75599, aleatoric unc.: 4.71083\n",
- "Epoch 49/500 total: 4.70859, -LL: 4.23383, prior: 0.75542, aleatoric unc.: 4.79768\n",
- "Epoch 50/500 total: 4.61107, -LL: 4.23617, prior: 0.75896, aleatoric unc.: 4.88461\n",
- "Epoch 51/500 total: 4.53410, -LL: 4.05732, prior: 0.76156, aleatoric unc.: 4.97112\n",
- "Epoch 52/500 total: 4.53218, -LL: 4.03225, prior: 0.76646, aleatoric unc.: 5.06118\n",
- "Epoch 53/500 total: 4.47935, -LL: 4.09978, prior: 0.76704, aleatoric unc.: 5.15256\n",
- "Epoch 54/500 total: 4.39028, -LL: 3.94386, prior: 0.76755, aleatoric unc.: 5.24289\n",
- "Epoch 55/500 total: 4.38337, -LL: 4.36773, prior: 0.76699, aleatoric unc.: 5.33596\n",
- "Epoch 56/500 total: 4.35281, -LL: 4.11247, prior: 0.77196, aleatoric unc.: 5.43080\n",
- "Epoch 57/500 total: 4.29956, -LL: 3.87602, prior: 0.77093, aleatoric unc.: 5.52630\n",
- "Epoch 58/500 total: 4.23197, -LL: 4.01298, prior: 0.77028, aleatoric unc.: 5.62054\n",
- "Epoch 59/500 total: 4.24475, -LL: 3.99289, prior: 0.77126, aleatoric unc.: 5.71866\n",
- "Epoch 60/500 total: 4.16691, -LL: 3.89405, prior: 0.77055, aleatoric unc.: 5.81574\n",
- "Epoch 61/500 total: 4.16522, -LL: 3.96328, prior: 0.76699, aleatoric unc.: 5.91432\n",
- "Epoch 62/500 total: 4.11586, -LL: 3.69259, prior: 0.76921, aleatoric unc.: 6.01400\n",
- "Epoch 63/500 total: 4.07180, -LL: 3.89622, prior: 0.77077, aleatoric unc.: 6.11181\n",
- "Epoch 64/500 total: 4.07462, -LL: 3.86786, prior: 0.77294, aleatoric unc.: 6.21290\n",
- "Epoch 65/500 total: 4.01141, -LL: 3.77488, prior: 0.77207, aleatoric unc.: 6.31128\n",
- "Epoch 66/500 total: 3.99999, -LL: 3.65617, prior: 0.77586, aleatoric unc.: 6.41138\n",
- "Epoch 67/500 total: 4.02086, -LL: 3.71232, prior: 0.77457, aleatoric unc.: 6.51647\n",
- "Epoch 68/500 total: 3.96727, -LL: 3.82445, prior: 0.77131, aleatoric unc.: 6.61852\n",
- "Epoch 69/500 total: 3.91331, -LL: 3.59059, prior: 0.77492, aleatoric unc.: 6.71576\n",
- "Epoch 70/500 total: 3.92368, -LL: 3.87038, prior: 0.77663, aleatoric unc.: 6.81692\n",
- "Epoch 71/500 total: 3.91091, -LL: 3.71611, prior: 0.77434, aleatoric unc.: 6.91915\n",
- "Epoch 72/500 total: 3.90254, -LL: 3.84058, prior: 0.77568, aleatoric unc.: 7.02362\n",
- "Epoch 73/500 total: 3.86610, -LL: 3.79804, prior: 0.77613, aleatoric unc.: 7.12259\n",
- "Epoch 74/500 total: 3.86877, -LL: 3.67038, prior: 0.77967, aleatoric unc.: 7.22509\n",
- "Epoch 75/500 total: 3.83692, -LL: 3.71282, prior: 0.78043, aleatoric unc.: 7.32391\n",
- "Epoch 76/500 total: 3.84445, -LL: 3.81955, prior: 0.77407, aleatoric unc.: 7.42552\n",
- "Epoch 77/500 total: 3.82880, -LL: 3.67313, prior: 0.77377, aleatoric unc.: 7.52656\n",
- "Epoch 78/500 total: 3.81437, -LL: 3.66513, prior: 0.77432, aleatoric unc.: 7.62591\n",
- "Epoch 79/500 total: 3.78821, -LL: 3.75625, prior: 0.77875, aleatoric unc.: 7.71907\n",
- "Epoch 80/500 total: 3.83347, -LL: 3.61354, prior: 0.77968, aleatoric unc.: 7.82734\n",
- "Epoch 81/500 total: 3.78359, -LL: 3.59515, prior: 0.77631, aleatoric unc.: 7.92300\n",
- "Epoch 82/500 total: 3.78367, -LL: 3.67180, prior: 0.77953, aleatoric unc.: 8.01834\n",
- "Epoch 83/500 total: 3.75569, -LL: 3.61895, prior: 0.78101, aleatoric unc.: 8.10435\n",
- "Epoch 84/500 total: 3.76833, -LL: 3.55765, prior: 0.78393, aleatoric unc.: 8.19697\n",
- "Epoch 85/500 total: 3.76053, -LL: 3.68451, prior: 0.78236, aleatoric unc.: 8.28731\n",
- "Epoch 86/500 total: 3.76217, -LL: 3.74953, prior: 0.78270, aleatoric unc.: 8.37660\n",
- "Epoch 87/500 total: 3.73655, -LL: 3.64136, prior: 0.77914, aleatoric unc.: 8.45761\n",
- "Epoch 88/500 total: 3.75396, -LL: 3.62085, prior: 0.77929, aleatoric unc.: 8.54510\n",
- "Epoch 89/500 total: 3.74527, -LL: 3.68434, prior: 0.77997, aleatoric unc.: 8.62806\n",
- "Epoch 90/500 total: 3.75304, -LL: 3.66249, prior: 0.77914, aleatoric unc.: 8.71503\n",
- "Epoch 91/500 total: 3.72325, -LL: 3.60384, prior: 0.77980, aleatoric unc.: 8.78583\n",
- "Epoch 92/500 total: 3.74192, -LL: 3.59396, prior: 0.78044, aleatoric unc.: 8.86492\n",
- "Epoch 93/500 total: 3.71866, -LL: 3.61358, prior: 0.78299, aleatoric unc.: 8.93002\n",
- "Epoch 94/500 total: 3.72444, -LL: 3.58171, prior: 0.78235, aleatoric unc.: 8.99536\n",
- "Epoch 95/500 total: 3.72439, -LL: 3.60700, prior: 0.77858, aleatoric unc.: 9.05974\n",
- "Epoch 96/500 total: 3.73727, -LL: 3.67353, prior: 0.77897, aleatoric unc.: 9.13145\n",
- "Epoch 97/500 total: 3.73587, -LL: 3.65088, prior: 0.78041, aleatoric unc.: 9.19960\n"
+ "Epoch 0/500 total: 70.25152, -LL: 21.77500, prior: 0.53135, aleatoric unc.: 1.70893\n",
+ "Epoch 1/500 total: 31.65050, -LL: 21.02528, prior: 0.55477, aleatoric unc.: 1.74608\n",
+ "Epoch 2/500 total: 26.59239, -LL: 20.43588, prior: 0.57386, aleatoric unc.: 1.78440\n",
+ "Epoch 3/500 total: 22.83483, -LL: 21.70591, prior: 0.60339, aleatoric unc.: 1.82282\n",
+ "Epoch 4/500 total: 19.29930, -LL: 18.81559, prior: 0.63071, aleatoric unc.: 1.85982\n",
+ "Epoch 5/500 total: 18.39163, -LL: 19.47896, prior: 0.65367, aleatoric unc.: 1.89902\n",
+ "Epoch 6/500 total: 17.13096, -LL: 18.68217, prior: 0.67211, aleatoric unc.: 1.93924\n",
+ "Epoch 7/500 total: 16.97922, -LL: 17.90156, prior: 0.68758, aleatoric unc.: 1.98306\n",
+ "Epoch 8/500 total: 15.76646, -LL: 17.70547, prior: 0.70069, aleatoric unc.: 2.02726\n",
+ "Epoch 9/500 total: 15.40406, -LL: 17.11720, prior: 0.71126, aleatoric unc.: 2.07418\n",
+ "Epoch 10/500 total: 14.64107, -LL: 15.48578, prior: 0.71729, aleatoric unc.: 2.12184\n",
+ "Epoch 11/500 total: 14.02109, -LL: 15.42325, prior: 0.73019, aleatoric unc.: 2.17055\n",
+ "Epoch 12/500 total: 13.05929, -LL: 15.26133, prior: 0.74044, aleatoric unc.: 2.21917\n",
+ "Epoch 13/500 total: 12.94440, -LL: 13.63645, prior: 0.74257, aleatoric unc.: 2.27045\n",
+ "Epoch 14/500 total: 12.05735, -LL: 13.53255, prior: 0.74883, aleatoric unc.: 2.32131\n",
+ "Epoch 15/500 total: 11.57835, -LL: 13.11155, prior: 0.75640, aleatoric unc.: 2.37314\n",
+ "Epoch 16/500 total: 11.51349, -LL: 12.47247, prior: 0.75862, aleatoric unc.: 2.42737\n",
+ "Epoch 17/500 total: 10.95014, -LL: 12.53422, prior: 0.76783, aleatoric unc.: 2.48286\n",
+ "Epoch 18/500 total: 10.52485, -LL: 11.63550, prior: 0.76954, aleatoric unc.: 2.53843\n",
+ "Epoch 19/500 total: 10.20493, -LL: 11.15514, prior: 0.77366, aleatoric unc.: 2.59592\n",
+ "Epoch 20/500 total: 9.83085, -LL: 11.33587, prior: 0.77800, aleatoric unc.: 2.65377\n",
+ "Epoch 21/500 total: 9.43129, -LL: 10.59203, prior: 0.77934, aleatoric unc.: 2.71191\n",
+ "Epoch 22/500 total: 9.31535, -LL: 10.35122, prior: 0.78458, aleatoric unc.: 2.77312\n",
+ "Epoch 23/500 total: 8.99058, -LL: 9.78121, prior: 0.79155, aleatoric unc.: 2.83501\n",
+ "Epoch 24/500 total: 8.60071, -LL: 9.62699, prior: 0.79597, aleatoric unc.: 2.89697\n",
+ "Epoch 25/500 total: 8.18161, -LL: 9.25629, prior: 0.79841, aleatoric unc.: 2.95814\n",
+ "Epoch 26/500 total: 8.11976, -LL: 8.75236, prior: 0.79969, aleatoric unc.: 3.02171\n",
+ "Epoch 27/500 total: 7.69320, -LL: 8.54075, prior: 0.80662, aleatoric unc.: 3.08531\n",
+ "Epoch 28/500 total: 7.71203, -LL: 8.61242, prior: 0.80597, aleatoric unc.: 3.15187\n",
+ "Epoch 29/500 total: 7.33146, -LL: 8.37583, prior: 0.81074, aleatoric unc.: 3.21746\n",
+ "Epoch 30/500 total: 7.12741, -LL: 8.09264, prior: 0.81912, aleatoric unc.: 3.28449\n",
+ "Epoch 31/500 total: 6.82985, -LL: 7.96702, prior: 0.81739, aleatoric unc.: 3.35038\n",
+ "Epoch 32/500 total: 6.85332, -LL: 7.81610, prior: 0.82108, aleatoric unc.: 3.42018\n",
+ "Epoch 33/500 total: 6.48937, -LL: 7.29156, prior: 0.82439, aleatoric unc.: 3.48776\n",
+ "Epoch 34/500 total: 6.40705, -LL: 7.11866, prior: 0.82284, aleatoric unc.: 3.55825\n",
+ "Epoch 35/500 total: 6.28291, -LL: 7.16727, prior: 0.82726, aleatoric unc.: 3.62942\n",
+ "Epoch 36/500 total: 6.11709, -LL: 6.96031, prior: 0.83276, aleatoric unc.: 3.70237\n",
+ "Epoch 37/500 total: 6.02628, -LL: 7.04397, prior: 0.83415, aleatoric unc.: 3.77627\n",
+ "Epoch 38/500 total: 5.90711, -LL: 6.62934, prior: 0.83468, aleatoric unc.: 3.85172\n",
+ "Epoch 39/500 total: 5.77246, -LL: 6.40979, prior: 0.83356, aleatoric unc.: 3.92818\n",
+ "Epoch 40/500 total: 5.66154, -LL: 6.18940, prior: 0.83742, aleatoric unc.: 4.00555\n",
+ "Epoch 41/500 total: 5.59375, -LL: 6.11153, prior: 0.83922, aleatoric unc.: 4.08529\n",
+ "Epoch 42/500 total: 5.45022, -LL: 5.96574, prior: 0.84189, aleatoric unc.: 4.16530\n",
+ "Epoch 43/500 total: 5.34939, -LL: 5.82496, prior: 0.84235, aleatoric unc.: 4.24656\n",
+ "Epoch 44/500 total: 5.23652, -LL: 5.72203, prior: 0.84446, aleatoric unc.: 4.32835\n",
+ "Epoch 45/500 total: 5.14614, -LL: 5.59121, prior: 0.84935, aleatoric unc.: 4.41080\n",
+ "Epoch 46/500 total: 5.13085, -LL: 5.71749, prior: 0.85116, aleatoric unc.: 4.49678\n",
+ "Epoch 47/500 total: 5.01557, -LL: 5.53531, prior: 0.85169, aleatoric unc.: 4.58240\n",
+ "Epoch 48/500 total: 4.92441, -LL: 5.33155, prior: 0.85473, aleatoric unc.: 4.66906\n",
+ "Epoch 49/500 total: 4.84676, -LL: 5.42828, prior: 0.85388, aleatoric unc.: 4.75578\n",
+ "Epoch 50/500 total: 4.76905, -LL: 5.08875, prior: 0.85773, aleatoric unc.: 4.84416\n",
+ "Epoch 51/500 total: 4.72422, -LL: 5.05217, prior: 0.85497, aleatoric unc.: 4.93447\n",
+ "Epoch 52/500 total: 4.75352, -LL: 5.01116, prior: 0.85224, aleatoric unc.: 5.02964\n",
+ "Epoch 53/500 total: 4.58029, -LL: 4.88449, prior: 0.85596, aleatoric unc.: 5.12190\n",
+ "Epoch 54/500 total: 4.61482, -LL: 5.01953, prior: 0.85656, aleatoric unc.: 5.21822\n",
+ "Epoch 55/500 total: 4.51711, -LL: 4.77787, prior: 0.85969, aleatoric unc.: 5.31415\n",
+ "Epoch 56/500 total: 4.42652, -LL: 4.81638, prior: 0.85566, aleatoric unc.: 5.40780\n",
+ "Epoch 57/500 total: 4.39081, -LL: 4.59852, prior: 0.85573, aleatoric unc.: 5.50328\n",
+ "Epoch 58/500 total: 4.35142, -LL: 4.62409, prior: 0.85882, aleatoric unc.: 5.59930\n",
+ "Epoch 59/500 total: 4.37183, -LL: 4.65835, prior: 0.85917, aleatoric unc.: 5.70237\n",
+ "Epoch 60/500 total: 4.24384, -LL: 4.54369, prior: 0.86191, aleatoric unc.: 5.79825\n",
+ "Epoch 61/500 total: 4.23949, -LL: 4.55674, prior: 0.86728, aleatoric unc.: 5.89776\n",
+ "Epoch 62/500 total: 4.18089, -LL: 4.47382, prior: 0.86757, aleatoric unc.: 5.99668\n",
+ "Epoch 63/500 total: 4.14600, -LL: 4.36870, prior: 0.86710, aleatoric unc.: 6.09457\n",
+ "Epoch 64/500 total: 4.13551, -LL: 4.45779, prior: 0.86734, aleatoric unc.: 6.19636\n",
+ "Epoch 65/500 total: 4.08151, -LL: 4.42791, prior: 0.86745, aleatoric unc.: 6.29525\n",
+ "Epoch 66/500 total: 4.06487, -LL: 4.28903, prior: 0.87429, aleatoric unc.: 6.39733\n",
+ "Epoch 67/500 total: 4.03409, -LL: 4.24191, prior: 0.87228, aleatoric unc.: 6.49832\n",
+ "Epoch 68/500 total: 4.06712, -LL: 4.18360, prior: 0.87340, aleatoric unc.: 6.60592\n",
+ "Epoch 69/500 total: 4.06883, -LL: 4.27839, prior: 0.87231, aleatoric unc.: 6.72010\n",
+ "Epoch 70/500 total: 3.98950, -LL: 4.26492, prior: 0.87387, aleatoric unc.: 6.82558\n",
+ "Epoch 71/500 total: 3.99313, -LL: 4.22671, prior: 0.87400, aleatoric unc.: 6.93427\n",
+ "Epoch 72/500 total: 3.93554, -LL: 4.08919, prior: 0.87938, aleatoric unc.: 7.03637\n",
+ "Epoch 73/500 total: 3.88887, -LL: 4.16175, prior: 0.87978, aleatoric unc.: 7.13473\n",
+ "Epoch 74/500 total: 3.89049, -LL: 4.06035, prior: 0.87818, aleatoric unc.: 7.23365\n",
+ "Epoch 75/500 total: 3.90688, -LL: 4.08672, prior: 0.87830, aleatoric unc.: 7.33916\n",
+ "Epoch 76/500 total: 3.87086, -LL: 4.00104, prior: 0.87457, aleatoric unc.: 7.44130\n",
+ "Epoch 77/500 total: 3.87557, -LL: 4.00404, prior: 0.87575, aleatoric unc.: 7.54601\n",
+ "Epoch 78/500 total: 3.87118, -LL: 4.01505, prior: 0.87283, aleatoric unc.: 7.65226\n",
+ "Epoch 79/500 total: 3.87023, -LL: 3.98401, prior: 0.87265, aleatoric unc.: 7.76025\n",
+ "Epoch 80/500 total: 3.83903, -LL: 3.96228, prior: 0.87321, aleatoric unc.: 7.86185\n",
+ "Epoch 81/500 total: 3.83727, -LL: 3.96250, prior: 0.87293, aleatoric unc.: 7.96465\n",
+ "Epoch 82/500 total: 3.81156, -LL: 3.92226, prior: 0.87132, aleatoric unc.: 8.06236\n",
+ "Epoch 83/500 total: 3.82978, -LL: 3.97800, prior: 0.87215, aleatoric unc.: 8.16535\n",
+ "Epoch 84/500 total: 3.80776, -LL: 3.93948, prior: 0.87251, aleatoric unc.: 8.26426\n",
+ "Epoch 85/500 total: 3.80882, -LL: 3.93136, prior: 0.87188, aleatoric unc.: 8.36425\n",
+ "Epoch 86/500 total: 3.79106, -LL: 3.94773, prior: 0.87398, aleatoric unc.: 8.45723\n",
+ "Epoch 87/500 total: 3.76971, -LL: 3.92687, prior: 0.86911, aleatoric unc.: 8.54351\n",
+ "Epoch 88/500 total: 3.78953, -LL: 3.94034, prior: 0.87490, aleatoric unc.: 8.63500\n",
+ "Epoch 89/500 total: 3.78685, -LL: 3.89338, prior: 0.87492, aleatoric unc.: 8.72990\n",
+ "Epoch 90/500 total: 3.78132, -LL: 3.93788, prior: 0.87580, aleatoric unc.: 8.81905\n",
+ "Epoch 91/500 total: 3.77357, -LL: 3.89067, prior: 0.87284, aleatoric unc.: 8.90431\n",
+ "Epoch 92/500 total: 3.76655, -LL: 3.88172, prior: 0.87427, aleatoric unc.: 8.98560\n",
+ "Epoch 93/500 total: 3.77686, -LL: 3.95055, prior: 0.87286, aleatoric unc.: 9.07076\n",
+ "Epoch 94/500 total: 3.77278, -LL: 3.87056, prior: 0.87418, aleatoric unc.: 9.15368\n",
+ "Epoch 95/500 total: 3.77267, -LL: 3.88493, prior: 0.87691, aleatoric unc.: 9.23351\n",
+ "Epoch 96/500 total: 3.76005, -LL: 3.87830, prior: 0.87744, aleatoric unc.: 9.30644\n",
+ "Epoch 97/500 total: 3.75343, -LL: 3.86725, prior: 0.87701, aleatoric unc.: 9.37226\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
- "Epoch 98/500 total: 3.72790, -LL: 3.58224, prior: 0.78028, aleatoric unc.: 9.25964\n",
- "Epoch 99/500 total: 3.71771, -LL: 3.66020, prior: 0.77745, aleatoric unc.: 9.31000\n",
- "Epoch 100/500 total: 3.72549, -LL: 3.62102, prior: 0.77761, aleatoric unc.: 9.36518\n",
- "Epoch 101/500 total: 3.71956, -LL: 3.57595, prior: 0.77925, aleatoric unc.: 9.41201\n",
- "Epoch 102/500 total: 3.72677, -LL: 3.57028, prior: 0.77652, aleatoric unc.: 9.46463\n",
- "Epoch 103/500 total: 3.72387, -LL: 3.65744, prior: 0.77754, aleatoric unc.: 9.50802\n",
- "Epoch 104/500 total: 3.71402, -LL: 3.60348, prior: 0.77234, aleatoric unc.: 9.54170\n",
- "Epoch 105/500 total: 3.72198, -LL: 3.63285, prior: 0.77360, aleatoric unc.: 9.58104\n",
- "Epoch 106/500 total: 3.71737, -LL: 3.64993, prior: 0.77597, aleatoric unc.: 9.61322\n",
- "Epoch 107/500 total: 3.71005, -LL: 3.56981, prior: 0.77387, aleatoric unc.: 9.63459\n",
- "Epoch 108/500 total: 3.71906, -LL: 3.58226, prior: 0.77644, aleatoric unc.: 9.66549\n",
- "Epoch 109/500 total: 3.72139, -LL: 3.63789, prior: 0.77184, aleatoric unc.: 9.69481\n",
- "Epoch 110/500 total: 3.70912, -LL: 3.60181, prior: 0.77226, aleatoric unc.: 9.71032\n",
- "Epoch 111/500 total: 3.71838, -LL: 3.63031, prior: 0.77578, aleatoric unc.: 9.73120\n",
- "Epoch 112/500 total: 3.71506, -LL: 3.61052, prior: 0.77374, aleatoric unc.: 9.74926\n",
- "Epoch 113/500 total: 3.71562, -LL: 3.72471, prior: 0.77285, aleatoric unc.: 9.76058\n",
- "Epoch 114/500 total: 3.71990, -LL: 3.74557, prior: 0.76846, aleatoric unc.: 9.78141\n",
- "Epoch 115/500 total: 3.72581, -LL: 3.67777, prior: 0.76765, aleatoric unc.: 9.80824\n",
- "Epoch 116/500 total: 3.72395, -LL: 3.66619, prior: 0.76687, aleatoric unc.: 9.82927\n",
- "Epoch 117/500 total: 3.72196, -LL: 3.67000, prior: 0.76839, aleatoric unc.: 9.84076\n",
- "Epoch 118/500 total: 3.70945, -LL: 3.61228, prior: 0.76902, aleatoric unc.: 9.84046\n",
- "Epoch 119/500 total: 3.71781, -LL: 3.57591, prior: 0.77380, aleatoric unc.: 9.84767\n",
- "Epoch 120/500 total: 3.70874, -LL: 3.66554, prior: 0.77551, aleatoric unc.: 9.83665\n",
- "Epoch 121/500 total: 3.72752, -LL: 3.65136, prior: 0.77845, aleatoric unc.: 9.86153\n",
- "Epoch 122/500 total: 3.73040, -LL: 3.62794, prior: 0.77837, aleatoric unc.: 9.88645\n",
- "Epoch 123/500 total: 3.71462, -LL: 3.68275, prior: 0.78350, aleatoric unc.: 9.88238\n",
- "Epoch 124/500 total: 3.71511, -LL: 3.59032, prior: 0.78381, aleatoric unc.: 9.87697\n",
- "Epoch 125/500 total: 3.72409, -LL: 3.58439, prior: 0.78439, aleatoric unc.: 9.89114\n",
- "Epoch 126/500 total: 3.71711, -LL: 3.66987, prior: 0.78606, aleatoric unc.: 9.88819\n",
- "Epoch 127/500 total: 3.71188, -LL: 3.63467, prior: 0.78302, aleatoric unc.: 9.87889\n",
- "Epoch 128/500 total: 3.72376, -LL: 3.58284, prior: 0.78485, aleatoric unc.: 9.88960\n",
- "Epoch 129/500 total: 3.71365, -LL: 3.66670, prior: 0.78087, aleatoric unc.: 9.88381\n",
- "Epoch 130/500 total: 3.72456, -LL: 3.66885, prior: 0.78370, aleatoric unc.: 9.89316\n",
- "Epoch 131/500 total: 3.71323, -LL: 3.62470, prior: 0.78227, aleatoric unc.: 9.88930\n",
- "Epoch 132/500 total: 3.71856, -LL: 3.66937, prior: 0.78154, aleatoric unc.: 9.88618\n",
- "Epoch 133/500 total: 3.71670, -LL: 3.64594, prior: 0.77825, aleatoric unc.: 9.88424\n",
- "Epoch 134/500 total: 3.72210, -LL: 3.60950, prior: 0.77902, aleatoric unc.: 9.89171\n",
- "Epoch 135/500 total: 3.71507, -LL: 3.59651, prior: 0.77877, aleatoric unc.: 9.88918\n",
- "Epoch 136/500 total: 3.71900, -LL: 3.65212, prior: 0.78622, aleatoric unc.: 9.89051\n",
- "Epoch 137/500 total: 3.71307, -LL: 3.61388, prior: 0.78563, aleatoric unc.: 9.88130\n",
- "Epoch 138/500 total: 3.71602, -LL: 3.60536, prior: 0.78637, aleatoric unc.: 9.88007\n",
- "Epoch 139/500 total: 3.72967, -LL: 3.64175, prior: 0.78606, aleatoric unc.: 9.89858\n",
- "Epoch 140/500 total: 3.71805, -LL: 3.57543, prior: 0.78286, aleatoric unc.: 9.90221\n",
- "Epoch 141/500 total: 3.71457, -LL: 3.60350, prior: 0.78505, aleatoric unc.: 9.89543\n",
- "Epoch 142/500 total: 3.71818, -LL: 3.66506, prior: 0.79071, aleatoric unc.: 9.89198\n",
- "Epoch 143/500 total: 3.70745, -LL: 3.66879, prior: 0.79167, aleatoric unc.: 9.87098\n",
- "Epoch 144/500 total: 3.71752, -LL: 3.59973, prior: 0.79228, aleatoric unc.: 9.87335\n",
- "Epoch 145/500 total: 3.71323, -LL: 3.68346, prior: 0.78821, aleatoric unc.: 9.86594\n",
- "Epoch 146/500 total: 3.69810, -LL: 3.62257, prior: 0.79184, aleatoric unc.: 9.83553\n",
- "Epoch 147/500 total: 3.70289, -LL: 3.60558, prior: 0.79325, aleatoric unc.: 9.81485\n",
- "Epoch 148/500 total: 3.71252, -LL: 3.67221, prior: 0.79652, aleatoric unc.: 9.81311\n",
- "Epoch 149/500 total: 3.73219, -LL: 3.57769, prior: 0.79471, aleatoric unc.: 9.85562\n",
- "Epoch 150/500 total: 3.72208, -LL: 3.67267, prior: 0.78948, aleatoric unc.: 9.87345\n",
- "Epoch 151/500 total: 3.71389, -LL: 3.65466, prior: 0.79006, aleatoric unc.: 9.87153\n",
- "Epoch 152/500 total: 3.72419, -LL: 3.67915, prior: 0.79090, aleatoric unc.: 9.87917\n",
- "Epoch 153/500 total: 3.71665, -LL: 3.62692, prior: 0.79997, aleatoric unc.: 9.88276\n",
- "Epoch 154/500 total: 3.72019, -LL: 3.58589, prior: 0.79751, aleatoric unc.: 9.88690\n",
- "Epoch 155/500 total: 3.71445, -LL: 3.61408, prior: 0.80268, aleatoric unc.: 9.88311\n",
- "Epoch 156/500 total: 3.70221, -LL: 3.68263, prior: 0.80404, aleatoric unc.: 9.85331\n",
- "Epoch 157/500 total: 3.70698, -LL: 3.70702, prior: 0.80339, aleatoric unc.: 9.83723\n",
- "Epoch 158/500 total: 3.72310, -LL: 3.59278, prior: 0.80445, aleatoric unc.: 9.85699\n",
- "Epoch 159/500 total: 3.71378, -LL: 3.73156, prior: 0.80416, aleatoric unc.: 9.85512\n",
- "Epoch 160/500 total: 3.70706, -LL: 3.63655, prior: 0.80595, aleatoric unc.: 9.84014\n",
- "Epoch 161/500 total: 3.71271, -LL: 3.57877, prior: 0.80410, aleatoric unc.: 9.84335\n",
- "Epoch 162/500 total: 3.71768, -LL: 3.63120, prior: 0.80659, aleatoric unc.: 9.85032\n",
- "Epoch 163/500 total: 3.71903, -LL: 3.65138, prior: 0.80638, aleatoric unc.: 9.85763\n",
- "Epoch 164/500 total: 3.71713, -LL: 3.64704, prior: 0.80705, aleatoric unc.: 9.86186\n",
- "Epoch 165/500 total: 3.71419, -LL: 3.64462, prior: 0.80874, aleatoric unc.: 9.86155\n",
- "Epoch 166/500 total: 3.70272, -LL: 3.60857, prior: 0.80695, aleatoric unc.: 9.83837\n",
- "Epoch 167/500 total: 3.71688, -LL: 3.60935, prior: 0.81090, aleatoric unc.: 9.84529\n",
- "Epoch 168/500 total: 3.70292, -LL: 3.60577, prior: 0.80637, aleatoric unc.: 9.82553\n",
- "Epoch 169/500 total: 3.71970, -LL: 3.63841, prior: 0.80866, aleatoric unc.: 9.83715\n",
- "Epoch 170/500 total: 3.71758, -LL: 3.67275, prior: 0.81033, aleatoric unc.: 9.84604\n",
- "Epoch 171/500 total: 3.72500, -LL: 3.59006, prior: 0.81392, aleatoric unc.: 9.86759\n",
- "Epoch 172/500 total: 3.70126, -LL: 3.64450, prior: 0.81116, aleatoric unc.: 9.84247\n",
- "Epoch 173/500 total: 3.72101, -LL: 3.64824, prior: 0.81156, aleatoric unc.: 9.84976\n",
- "Epoch 174/500 total: 3.71152, -LL: 3.69934, prior: 0.81262, aleatoric unc.: 9.84919\n",
- "Epoch 175/500 total: 3.71467, -LL: 3.68428, prior: 0.81517, aleatoric unc.: 9.85176\n",
- "Epoch 176/500 total: 3.70291, -LL: 3.63773, prior: 0.81583, aleatoric unc.: 9.83082\n",
- "Epoch 177/500 total: 3.70896, -LL: 3.66547, prior: 0.81045, aleatoric unc.: 9.82290\n",
- "Epoch 178/500 total: 3.71117, -LL: 3.68764, prior: 0.81337, aleatoric unc.: 9.82000\n",
- "Epoch 179/500 total: 3.70928, -LL: 3.61341, prior: 0.81607, aleatoric unc.: 9.81955\n",
- "Epoch 180/500 total: 3.70466, -LL: 3.65554, prior: 0.81575, aleatoric unc.: 9.80751\n",
- "Epoch 181/500 total: 3.70420, -LL: 3.64272, prior: 0.81693, aleatoric unc.: 9.79344\n",
- "Epoch 182/500 total: 3.71046, -LL: 3.64984, prior: 0.81584, aleatoric unc.: 9.79500\n",
- "Epoch 183/500 total: 3.71474, -LL: 3.66882, prior: 0.81325, aleatoric unc.: 9.80760\n",
- "Epoch 184/500 total: 3.71527, -LL: 3.61031, prior: 0.81348, aleatoric unc.: 9.82014\n",
- "Epoch 185/500 total: 3.70042, -LL: 3.66272, prior: 0.81257, aleatoric unc.: 9.80154\n",
- "Epoch 186/500 total: 3.71282, -LL: 3.61934, prior: 0.81781, aleatoric unc.: 9.80770\n",
- "Epoch 187/500 total: 3.71327, -LL: 3.67081, prior: 0.81615, aleatoric unc.: 9.81168\n",
- "Epoch 188/500 total: 3.70315, -LL: 3.66320, prior: 0.81042, aleatoric unc.: 9.80011\n",
- "Epoch 189/500 total: 3.69962, -LL: 3.63048, prior: 0.81293, aleatoric unc.: 9.78159\n",
- "Epoch 190/500 total: 3.71830, -LL: 3.68563, prior: 0.81299, aleatoric unc.: 9.80476\n",
- "Epoch 191/500 total: 3.71706, -LL: 3.64913, prior: 0.81458, aleatoric unc.: 9.81613\n",
- "Epoch 192/500 total: 3.70988, -LL: 3.62455, prior: 0.81865, aleatoric unc.: 9.81723\n",
- "Epoch 193/500 total: 3.70870, -LL: 3.63595, prior: 0.81586, aleatoric unc.: 9.81325\n",
- "Epoch 194/500 total: 3.71062, -LL: 3.63609, prior: 0.81832, aleatoric unc.: 9.81209\n"
+ "Epoch 98/500 total: 3.75489, -LL: 3.86650, prior: 0.87387, aleatoric unc.: 9.43639\n",
+ "Epoch 99/500 total: 3.75204, -LL: 3.88775, prior: 0.87541, aleatoric unc.: 9.49778\n",
+ "Epoch 100/500 total: 3.74928, -LL: 3.88524, prior: 0.87766, aleatoric unc.: 9.55119\n",
+ "Epoch 101/500 total: 3.75035, -LL: 3.89834, prior: 0.87757, aleatoric unc.: 9.60368\n",
+ "Epoch 102/500 total: 3.75176, -LL: 3.84637, prior: 0.87619, aleatoric unc.: 9.65913\n",
+ "Epoch 103/500 total: 3.74618, -LL: 3.85358, prior: 0.87332, aleatoric unc.: 9.70444\n",
+ "Epoch 104/500 total: 3.75131, -LL: 3.82844, prior: 0.87389, aleatoric unc.: 9.75208\n",
+ "Epoch 105/500 total: 3.75830, -LL: 3.85860, prior: 0.87168, aleatoric unc.: 9.80331\n",
+ "Epoch 106/500 total: 3.74013, -LL: 3.82363, prior: 0.87422, aleatoric unc.: 9.83733\n",
+ "Epoch 107/500 total: 3.75714, -LL: 3.87234, prior: 0.87499, aleatoric unc.: 9.88155\n",
+ "Epoch 108/500 total: 3.76437, -LL: 3.84260, prior: 0.87272, aleatoric unc.: 9.93000\n",
+ "Epoch 109/500 total: 3.75821, -LL: 3.83804, prior: 0.86936, aleatoric unc.: 9.97239\n",
+ "Epoch 110/500 total: 3.74620, -LL: 3.83302, prior: 0.87047, aleatoric unc.: 9.99439\n",
+ "Epoch 111/500 total: 3.74528, -LL: 3.82421, prior: 0.87420, aleatoric unc.: 10.01774\n",
+ "Epoch 112/500 total: 3.74257, -LL: 3.86775, prior: 0.87206, aleatoric unc.: 10.02876\n",
+ "Epoch 113/500 total: 3.74466, -LL: 3.84895, prior: 0.87320, aleatoric unc.: 10.04690\n",
+ "Epoch 114/500 total: 3.74745, -LL: 3.85205, prior: 0.87074, aleatoric unc.: 10.06460\n",
+ "Epoch 115/500 total: 3.73718, -LL: 3.84279, prior: 0.87076, aleatoric unc.: 10.06521\n",
+ "Epoch 116/500 total: 3.75617, -LL: 3.86068, prior: 0.86986, aleatoric unc.: 10.09347\n",
+ "Epoch 117/500 total: 3.74887, -LL: 3.85102, prior: 0.87165, aleatoric unc.: 10.10835\n",
+ "Epoch 118/500 total: 3.75465, -LL: 3.83214, prior: 0.87595, aleatoric unc.: 10.12994\n",
+ "Epoch 119/500 total: 3.74453, -LL: 3.83483, prior: 0.87396, aleatoric unc.: 10.13305\n",
+ "Epoch 120/500 total: 3.75249, -LL: 3.85369, prior: 0.87303, aleatoric unc.: 10.14400\n",
+ "Epoch 121/500 total: 3.74372, -LL: 3.82296, prior: 0.87450, aleatoric unc.: 10.14816\n",
+ "Epoch 122/500 total: 3.73883, -LL: 3.81294, prior: 0.87580, aleatoric unc.: 10.13818\n",
+ "Epoch 123/500 total: 3.76165, -LL: 3.83089, prior: 0.86827, aleatoric unc.: 10.16922\n",
+ "Epoch 124/500 total: 3.73840, -LL: 3.82414, prior: 0.87176, aleatoric unc.: 10.15764\n",
+ "Epoch 125/500 total: 3.74571, -LL: 3.84270, prior: 0.87256, aleatoric unc.: 10.15516\n",
+ "Epoch 126/500 total: 3.75008, -LL: 3.83471, prior: 0.87215, aleatoric unc.: 10.16320\n",
+ "Epoch 127/500 total: 3.74074, -LL: 3.82977, prior: 0.87414, aleatoric unc.: 10.15534\n",
+ "Epoch 128/500 total: 3.74676, -LL: 3.83996, prior: 0.87442, aleatoric unc.: 10.15799\n",
+ "Epoch 129/500 total: 3.75401, -LL: 3.83700, prior: 0.87262, aleatoric unc.: 10.17440\n",
+ "Epoch 130/500 total: 3.74349, -LL: 3.82789, prior: 0.87716, aleatoric unc.: 10.17104\n",
+ "Epoch 131/500 total: 3.74931, -LL: 3.82503, prior: 0.87422, aleatoric unc.: 10.17491\n",
+ "Epoch 132/500 total: 3.75705, -LL: 3.83076, prior: 0.87151, aleatoric unc.: 10.19173\n",
+ "Epoch 133/500 total: 3.74695, -LL: 3.85002, prior: 0.87422, aleatoric unc.: 10.18815\n",
+ "Epoch 134/500 total: 3.73636, -LL: 3.83064, prior: 0.88023, aleatoric unc.: 10.16924\n",
+ "Epoch 135/500 total: 3.75153, -LL: 3.86666, prior: 0.87499, aleatoric unc.: 10.17578\n",
+ "Epoch 136/500 total: 3.73906, -LL: 3.82249, prior: 0.87708, aleatoric unc.: 10.16144\n",
+ "Epoch 137/500 total: 3.74281, -LL: 3.84614, prior: 0.87192, aleatoric unc.: 10.15285\n",
+ "Epoch 138/500 total: 3.73507, -LL: 3.82791, prior: 0.87696, aleatoric unc.: 10.13826\n",
+ "Epoch 139/500 total: 3.74250, -LL: 3.82145, prior: 0.87161, aleatoric unc.: 10.13395\n",
+ "Epoch 140/500 total: 3.74895, -LL: 3.85658, prior: 0.87233, aleatoric unc.: 10.14499\n",
+ "Epoch 141/500 total: 3.74945, -LL: 3.83508, prior: 0.87410, aleatoric unc.: 10.16039\n",
+ "Epoch 142/500 total: 3.74703, -LL: 3.84708, prior: 0.87038, aleatoric unc.: 10.16293\n",
+ "Epoch 143/500 total: 3.74602, -LL: 3.85310, prior: 0.86954, aleatoric unc.: 10.16378\n",
+ "Epoch 144/500 total: 3.73776, -LL: 3.85131, prior: 0.87608, aleatoric unc.: 10.14276\n",
+ "Epoch 145/500 total: 3.74502, -LL: 3.86227, prior: 0.87469, aleatoric unc.: 10.14487\n",
+ "Epoch 146/500 total: 3.75178, -LL: 3.83493, prior: 0.87348, aleatoric unc.: 10.16400\n",
+ "Epoch 147/500 total: 3.73801, -LL: 3.84173, prior: 0.87025, aleatoric unc.: 10.15082\n",
+ "Epoch 148/500 total: 3.74166, -LL: 3.82734, prior: 0.86839, aleatoric unc.: 10.14235\n",
+ "Epoch 149/500 total: 3.75373, -LL: 3.82091, prior: 0.87186, aleatoric unc.: 10.16233\n",
+ "Epoch 150/500 total: 3.74526, -LL: 3.83084, prior: 0.87280, aleatoric unc.: 10.16059\n",
+ "Epoch 151/500 total: 3.73425, -LL: 3.85029, prior: 0.87720, aleatoric unc.: 10.13720\n",
+ "Epoch 152/500 total: 3.75034, -LL: 3.81246, prior: 0.87624, aleatoric unc.: 10.15177\n",
+ "Epoch 153/500 total: 3.74241, -LL: 3.84087, prior: 0.87682, aleatoric unc.: 10.14831\n",
+ "Epoch 154/500 total: 3.74580, -LL: 3.83439, prior: 0.87499, aleatoric unc.: 10.15077\n",
+ "Epoch 155/500 total: 3.74812, -LL: 3.82937, prior: 0.87166, aleatoric unc.: 10.16117\n",
+ "Epoch 156/500 total: 3.74080, -LL: 3.84487, prior: 0.87110, aleatoric unc.: 10.15156\n",
+ "Epoch 157/500 total: 3.74060, -LL: 3.83325, prior: 0.86850, aleatoric unc.: 10.14273\n",
+ "Epoch 158/500 total: 3.74610, -LL: 3.82031, prior: 0.86979, aleatoric unc.: 10.14972\n",
+ "Epoch 159/500 total: 3.74913, -LL: 3.83025, prior: 0.86887, aleatoric unc.: 10.15754\n",
+ "Epoch 160/500 total: 3.74738, -LL: 3.84690, prior: 0.87071, aleatoric unc.: 10.16020\n",
+ "Epoch 161/500 total: 3.74441, -LL: 3.83083, prior: 0.87562, aleatoric unc.: 10.16298\n",
+ "Epoch 162/500 total: 3.74127, -LL: 3.83037, prior: 0.86911, aleatoric unc.: 10.15245\n",
+ "Epoch 163/500 total: 3.73776, -LL: 3.85702, prior: 0.87000, aleatoric unc.: 10.13875\n",
+ "Epoch 164/500 total: 3.74046, -LL: 3.83894, prior: 0.87265, aleatoric unc.: 10.12902\n",
+ "Epoch 165/500 total: 3.74645, -LL: 3.85668, prior: 0.86959, aleatoric unc.: 10.14033\n",
+ "Epoch 166/500 total: 3.74859, -LL: 3.81528, prior: 0.87264, aleatoric unc.: 10.15082\n",
+ "Epoch 167/500 total: 3.73561, -LL: 3.81875, prior: 0.86975, aleatoric unc.: 10.13387\n",
+ "Epoch 168/500 total: 3.74583, -LL: 3.81903, prior: 0.87138, aleatoric unc.: 10.14144\n",
+ "Epoch 169/500 total: 3.74097, -LL: 3.82545, prior: 0.87102, aleatoric unc.: 10.13799\n",
+ "Epoch 170/500 total: 3.73085, -LL: 3.82076, prior: 0.86865, aleatoric unc.: 10.11129\n",
+ "Epoch 171/500 total: 3.73720, -LL: 3.83468, prior: 0.87468, aleatoric unc.: 10.10508\n",
+ "Epoch 172/500 total: 3.73434, -LL: 3.84906, prior: 0.87264, aleatoric unc.: 10.09243\n",
+ "Epoch 173/500 total: 3.73799, -LL: 3.84463, prior: 0.87365, aleatoric unc.: 10.08736\n",
+ "Epoch 174/500 total: 3.73862, -LL: 3.85773, prior: 0.87482, aleatoric unc.: 10.09258\n",
+ "Epoch 175/500 total: 3.73140, -LL: 3.84049, prior: 0.87401, aleatoric unc.: 10.07639\n",
+ "Epoch 176/500 total: 3.74932, -LL: 3.84273, prior: 0.87495, aleatoric unc.: 10.10247\n",
+ "Epoch 177/500 total: 3.74212, -LL: 3.84727, prior: 0.87307, aleatoric unc.: 10.10432\n",
+ "Epoch 178/500 total: 3.74354, -LL: 3.84564, prior: 0.86907, aleatoric unc.: 10.11403\n",
+ "Epoch 179/500 total: 3.73614, -LL: 3.83136, prior: 0.86890, aleatoric unc.: 10.10359\n",
+ "Epoch 180/500 total: 3.73570, -LL: 3.83556, prior: 0.86727, aleatoric unc.: 10.09912\n",
+ "Epoch 181/500 total: 3.73227, -LL: 3.82470, prior: 0.86786, aleatoric unc.: 10.08085\n",
+ "Epoch 182/500 total: 3.73792, -LL: 3.82237, prior: 0.87092, aleatoric unc.: 10.08044\n",
+ "Epoch 183/500 total: 3.73197, -LL: 3.84259, prior: 0.86857, aleatoric unc.: 10.07049\n",
+ "Epoch 184/500 total: 3.74259, -LL: 3.82540, prior: 0.86568, aleatoric unc.: 10.08699\n",
+ "Epoch 185/500 total: 3.73696, -LL: 3.85460, prior: 0.86807, aleatoric unc.: 10.08008\n",
+ "Epoch 186/500 total: 3.74458, -LL: 3.83057, prior: 0.86602, aleatoric unc.: 10.09612\n",
+ "Epoch 187/500 total: 3.73795, -LL: 3.86993, prior: 0.86651, aleatoric unc.: 10.09590\n",
+ "Epoch 188/500 total: 3.73716, -LL: 3.84042, prior: 0.86435, aleatoric unc.: 10.09067\n",
+ "Epoch 189/500 total: 3.74265, -LL: 3.80450, prior: 0.86052, aleatoric unc.: 10.09959\n",
+ "Epoch 190/500 total: 3.74872, -LL: 3.83485, prior: 0.86200, aleatoric unc.: 10.12078\n",
+ "Epoch 191/500 total: 3.74471, -LL: 3.86692, prior: 0.86335, aleatoric unc.: 10.12616\n",
+ "Epoch 192/500 total: 3.73707, -LL: 3.85219, prior: 0.86578, aleatoric unc.: 10.11676\n",
+ "Epoch 193/500 total: 3.74931, -LL: 3.81395, prior: 0.86345, aleatoric unc.: 10.13512\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
- "Epoch 195/500 total: 3.72410, -LL: 3.62442, prior: 0.81648, aleatoric unc.: 9.83962\n",
- "Epoch 196/500 total: 3.71915, -LL: 3.66803, prior: 0.81624, aleatoric unc.: 9.84151\n",
- "Epoch 197/500 total: 3.71432, -LL: 3.64483, prior: 0.81001, aleatoric unc.: 9.85190\n",
- "Epoch 198/500 total: 3.71493, -LL: 3.59165, prior: 0.81170, aleatoric unc.: 9.85324\n",
- "Epoch 199/500 total: 3.70331, -LL: 3.60793, prior: 0.80896, aleatoric unc.: 9.83340\n",
- "Epoch 200/500 total: 3.70812, -LL: 3.59062, prior: 0.81499, aleatoric unc.: 9.82334\n",
- "Epoch 201/500 total: 3.71478, -LL: 3.62452, prior: 0.81519, aleatoric unc.: 9.82977\n",
- "Epoch 202/500 total: 3.71517, -LL: 3.56803, prior: 0.81508, aleatoric unc.: 9.83826\n",
- "Epoch 203/500 total: 3.69960, -LL: 3.63084, prior: 0.81742, aleatoric unc.: 9.81023\n",
- "Epoch 204/500 total: 3.70639, -LL: 3.66974, prior: 0.81871, aleatoric unc.: 9.80200\n",
- "Epoch 205/500 total: 3.70826, -LL: 3.62572, prior: 0.81504, aleatoric unc.: 9.79858\n",
- "Epoch 206/500 total: 3.71623, -LL: 3.64392, prior: 0.81659, aleatoric unc.: 9.81016\n",
- "Epoch 207/500 total: 3.71774, -LL: 3.65070, prior: 0.81498, aleatoric unc.: 9.82834\n",
- "Epoch 208/500 total: 3.69666, -LL: 3.65249, prior: 0.81455, aleatoric unc.: 9.79752\n",
- "Epoch 209/500 total: 3.70594, -LL: 3.67450, prior: 0.81606, aleatoric unc.: 9.79126\n",
- "Epoch 210/500 total: 3.69925, -LL: 3.68792, prior: 0.81400, aleatoric unc.: 9.77435\n",
- "Epoch 211/500 total: 3.70082, -LL: 3.60530, prior: 0.81230, aleatoric unc.: 9.76606\n",
- "Epoch 212/500 total: 3.71195, -LL: 3.64706, prior: 0.81609, aleatoric unc.: 9.77611\n",
- "Epoch 213/500 total: 3.70414, -LL: 3.64134, prior: 0.81544, aleatoric unc.: 9.77201\n",
- "Epoch 214/500 total: 3.71389, -LL: 3.63395, prior: 0.81622, aleatoric unc.: 9.78563\n",
- "Epoch 215/500 total: 3.71683, -LL: 3.66099, prior: 0.81664, aleatoric unc.: 9.80171\n",
- "Epoch 216/500 total: 3.72204, -LL: 3.66836, prior: 0.81515, aleatoric unc.: 9.82727\n",
- "Epoch 217/500 total: 3.70703, -LL: 3.63465, prior: 0.81890, aleatoric unc.: 9.82033\n",
- "Epoch 218/500 total: 3.70247, -LL: 3.71451, prior: 0.81721, aleatoric unc.: 9.80064\n",
- "Epoch 219/500 total: 3.71433, -LL: 3.63672, prior: 0.82165, aleatoric unc.: 9.80686\n",
- "Epoch 220/500 total: 3.70779, -LL: 3.61201, prior: 0.82151, aleatoric unc.: 9.80850\n",
- "Epoch 221/500 total: 3.72726, -LL: 3.65804, prior: 0.82183, aleatoric unc.: 9.83772\n",
- "Epoch 222/500 total: 3.71228, -LL: 3.65686, prior: 0.81864, aleatoric unc.: 9.84025\n",
- "Epoch 223/500 total: 3.72339, -LL: 3.64982, prior: 0.82202, aleatoric unc.: 9.85690\n",
- "Epoch 224/500 total: 3.70915, -LL: 3.63755, prior: 0.81988, aleatoric unc.: 9.85046\n",
- "Epoch 225/500 total: 3.70552, -LL: 3.63990, prior: 0.82102, aleatoric unc.: 9.82943\n",
- "Epoch 226/500 total: 3.70323, -LL: 3.64443, prior: 0.82060, aleatoric unc.: 9.81781\n",
- "Epoch 227/500 total: 3.70019, -LL: 3.65555, prior: 0.82249, aleatoric unc.: 9.79478\n",
- "Epoch 228/500 total: 3.71216, -LL: 3.69579, prior: 0.82333, aleatoric unc.: 9.79841\n",
- "Epoch 229/500 total: 3.71140, -LL: 3.62137, prior: 0.82447, aleatoric unc.: 9.80692\n",
- "Epoch 230/500 total: 3.70575, -LL: 3.64446, prior: 0.82529, aleatoric unc.: 9.79880\n",
- "Epoch 231/500 total: 3.71456, -LL: 3.75829, prior: 0.82439, aleatoric unc.: 9.80728\n",
- "Epoch 232/500 total: 3.70966, -LL: 3.63882, prior: 0.82492, aleatoric unc.: 9.80583\n",
- "Epoch 233/500 total: 3.71351, -LL: 3.61270, prior: 0.82613, aleatoric unc.: 9.81784\n",
- "Epoch 234/500 total: 3.70172, -LL: 3.62794, prior: 0.81822, aleatoric unc.: 9.79805\n",
- "Epoch 235/500 total: 3.71109, -LL: 3.64488, prior: 0.82053, aleatoric unc.: 9.80066\n",
- "Epoch 236/500 total: 3.70431, -LL: 3.62616, prior: 0.82161, aleatoric unc.: 9.78883\n",
- "Epoch 237/500 total: 3.70279, -LL: 3.68337, prior: 0.82063, aleatoric unc.: 9.77969\n",
- "Epoch 238/500 total: 3.71613, -LL: 3.67027, prior: 0.82166, aleatoric unc.: 9.79706\n",
- "Epoch 239/500 total: 3.70064, -LL: 3.66745, prior: 0.82222, aleatoric unc.: 9.78118\n",
- "Epoch 240/500 total: 3.70537, -LL: 3.60819, prior: 0.82710, aleatoric unc.: 9.77992\n",
- "Epoch 241/500 total: 3.71476, -LL: 3.61006, prior: 0.82356, aleatoric unc.: 9.79421\n",
- "Epoch 242/500 total: 3.71145, -LL: 3.64876, prior: 0.82434, aleatoric unc.: 9.79779\n",
- "Epoch 243/500 total: 3.70802, -LL: 3.58574, prior: 0.82809, aleatoric unc.: 9.79796\n",
- "Epoch 244/500 total: 3.70571, -LL: 3.65710, prior: 0.82588, aleatoric unc.: 9.79101\n",
- "Epoch 245/500 total: 3.70188, -LL: 3.62964, prior: 0.82486, aleatoric unc.: 9.77658\n",
- "Epoch 246/500 total: 3.72030, -LL: 3.63991, prior: 0.82122, aleatoric unc.: 9.80154\n",
- "Epoch 247/500 total: 3.71523, -LL: 3.61676, prior: 0.82447, aleatoric unc.: 9.81099\n",
- "Epoch 248/500 total: 3.71168, -LL: 3.59765, prior: 0.82207, aleatoric unc.: 9.81821\n",
- "Epoch 249/500 total: 3.71399, -LL: 3.63747, prior: 0.82239, aleatoric unc.: 9.82253\n",
- "Epoch 250/500 total: 3.70465, -LL: 3.64624, prior: 0.82184, aleatoric unc.: 9.81008\n",
- "Epoch 251/500 total: 3.69921, -LL: 3.60426, prior: 0.82150, aleatoric unc.: 9.78902\n",
- "Epoch 252/500 total: 3.71118, -LL: 3.67592, prior: 0.82288, aleatoric unc.: 9.79504\n",
- "Epoch 253/500 total: 3.70237, -LL: 3.62898, prior: 0.82680, aleatoric unc.: 9.78291\n",
- "Epoch 254/500 total: 3.70794, -LL: 3.64745, prior: 0.82541, aleatoric unc.: 9.78084\n",
- "Epoch 255/500 total: 3.70302, -LL: 3.62780, prior: 0.82535, aleatoric unc.: 9.77530\n",
- "Epoch 256/500 total: 3.71729, -LL: 3.63795, prior: 0.82601, aleatoric unc.: 9.79276\n",
- "Epoch 257/500 total: 3.70993, -LL: 3.63274, prior: 0.82741, aleatoric unc.: 9.79693\n",
- "Epoch 258/500 total: 3.71243, -LL: 3.65305, prior: 0.82601, aleatoric unc.: 9.80389\n",
- "Epoch 259/500 total: 3.70296, -LL: 3.64940, prior: 0.82313, aleatoric unc.: 9.79133\n",
- "Epoch 260/500 total: 3.71093, -LL: 3.59715, prior: 0.82558, aleatoric unc.: 9.79233\n",
- "Epoch 261/500 total: 3.71045, -LL: 3.63395, prior: 0.82771, aleatoric unc.: 9.79831\n",
- "Epoch 262/500 total: 3.69963, -LL: 3.67210, prior: 0.82712, aleatoric unc.: 9.77961\n",
- "Epoch 263/500 total: 3.71113, -LL: 3.65016, prior: 0.82726, aleatoric unc.: 9.78695\n",
- "Epoch 264/500 total: 3.70665, -LL: 3.60633, prior: 0.83064, aleatoric unc.: 9.78443\n",
- "Epoch 265/500 total: 3.71054, -LL: 3.65116, prior: 0.83137, aleatoric unc.: 9.79059\n",
- "Epoch 266/500 total: 3.69886, -LL: 3.60721, prior: 0.83100, aleatoric unc.: 9.77077\n",
- "Epoch 267/500 total: 3.70686, -LL: 3.65023, prior: 0.83398, aleatoric unc.: 9.77222\n",
- "Epoch 268/500 total: 3.69995, -LL: 3.71522, prior: 0.83159, aleatoric unc.: 9.75908\n",
- "Epoch 269/500 total: 3.70539, -LL: 3.64799, prior: 0.83221, aleatoric unc.: 9.75858\n",
- "Epoch 270/500 total: 3.70420, -LL: 3.63578, prior: 0.83041, aleatoric unc.: 9.75445\n",
- "Epoch 271/500 total: 3.70999, -LL: 3.68182, prior: 0.82908, aleatoric unc.: 9.76730\n",
- "Epoch 272/500 total: 3.70793, -LL: 3.63381, prior: 0.83376, aleatoric unc.: 9.76915\n",
- "Epoch 273/500 total: 3.70842, -LL: 3.64926, prior: 0.83353, aleatoric unc.: 9.77610\n",
- "Epoch 274/500 total: 3.70973, -LL: 3.62482, prior: 0.83395, aleatoric unc.: 9.77950\n",
- "Epoch 275/500 total: 3.71090, -LL: 3.60236, prior: 0.83533, aleatoric unc.: 9.78900\n",
- "Epoch 276/500 total: 3.70221, -LL: 3.67710, prior: 0.83294, aleatoric unc.: 9.77734\n",
- "Epoch 277/500 total: 3.70494, -LL: 3.64316, prior: 0.83875, aleatoric unc.: 9.77393\n",
- "Epoch 278/500 total: 3.71155, -LL: 3.61530, prior: 0.83769, aleatoric unc.: 9.78493\n",
- "Epoch 279/500 total: 3.72149, -LL: 3.63981, prior: 0.83667, aleatoric unc.: 9.81001\n",
- "Epoch 280/500 total: 3.70467, -LL: 3.62610, prior: 0.83533, aleatoric unc.: 9.80246\n",
- "Epoch 281/500 total: 3.70502, -LL: 3.66885, prior: 0.83573, aleatoric unc.: 9.79123\n",
- "Epoch 282/500 total: 3.70405, -LL: 3.63700, prior: 0.83748, aleatoric unc.: 9.78283\n",
- "Epoch 283/500 total: 3.70889, -LL: 3.63902, prior: 0.83531, aleatoric unc.: 9.78254\n",
- "Epoch 284/500 total: 3.71741, -LL: 3.60456, prior: 0.83570, aleatoric unc.: 9.80172\n",
- "Epoch 285/500 total: 3.71138, -LL: 3.68161, prior: 0.83478, aleatoric unc.: 9.80546\n",
- "Epoch 286/500 total: 3.70675, -LL: 3.59507, prior: 0.83560, aleatoric unc.: 9.80310\n",
- "Epoch 287/500 total: 3.70698, -LL: 3.61376, prior: 0.83594, aleatoric unc.: 9.79633\n",
- "Epoch 288/500 total: 3.70635, -LL: 3.60290, prior: 0.83656, aleatoric unc.: 9.78862\n",
- "Epoch 289/500 total: 3.71560, -LL: 3.64837, prior: 0.83419, aleatoric unc.: 9.80237\n",
- "Epoch 290/500 total: 3.70476, -LL: 3.65473, prior: 0.83240, aleatoric unc.: 9.79643\n",
- "Epoch 291/500 total: 3.70503, -LL: 3.67415, prior: 0.83116, aleatoric unc.: 9.78742\n"
+ "Epoch 194/500 total: 3.74560, -LL: 3.82039, prior: 0.87088, aleatoric unc.: 10.13949\n",
+ "Epoch 195/500 total: 3.74263, -LL: 3.82117, prior: 0.87204, aleatoric unc.: 10.13703\n",
+ "Epoch 196/500 total: 3.73787, -LL: 3.82781, prior: 0.87220, aleatoric unc.: 10.12694\n",
+ "Epoch 197/500 total: 3.73958, -LL: 3.82228, prior: 0.87277, aleatoric unc.: 10.12465\n",
+ "Epoch 198/500 total: 3.73709, -LL: 3.86563, prior: 0.87002, aleatoric unc.: 10.10822\n",
+ "Epoch 199/500 total: 3.73462, -LL: 3.81377, prior: 0.87348, aleatoric unc.: 10.10007\n",
+ "Epoch 200/500 total: 3.74196, -LL: 3.83315, prior: 0.87177, aleatoric unc.: 10.10149\n",
+ "Epoch 201/500 total: 3.74295, -LL: 3.82900, prior: 0.86735, aleatoric unc.: 10.11109\n",
+ "Epoch 202/500 total: 3.74102, -LL: 3.84751, prior: 0.87283, aleatoric unc.: 10.11312\n",
+ "Epoch 203/500 total: 3.73415, -LL: 3.82106, prior: 0.87166, aleatoric unc.: 10.09795\n",
+ "Epoch 204/500 total: 3.74028, -LL: 3.80506, prior: 0.86942, aleatoric unc.: 10.10092\n",
+ "Epoch 205/500 total: 3.74091, -LL: 3.87411, prior: 0.87070, aleatoric unc.: 10.10217\n",
+ "Epoch 206/500 total: 3.73768, -LL: 3.83774, prior: 0.86826, aleatoric unc.: 10.09931\n",
+ "Epoch 207/500 total: 3.73887, -LL: 3.80833, prior: 0.87087, aleatoric unc.: 10.09679\n",
+ "Epoch 208/500 total: 3.74039, -LL: 3.84832, prior: 0.87311, aleatoric unc.: 10.10020\n",
+ "Epoch 209/500 total: 3.72806, -LL: 3.84503, prior: 0.87395, aleatoric unc.: 10.07768\n",
+ "Epoch 210/500 total: 3.73440, -LL: 3.82243, prior: 0.87101, aleatoric unc.: 10.07020\n",
+ "Epoch 211/500 total: 3.73633, -LL: 3.81108, prior: 0.86629, aleatoric unc.: 10.06764\n",
+ "Epoch 212/500 total: 3.73923, -LL: 3.83664, prior: 0.86599, aleatoric unc.: 10.07389\n",
+ "Epoch 213/500 total: 3.73807, -LL: 3.84422, prior: 0.86756, aleatoric unc.: 10.07313\n",
+ "Epoch 214/500 total: 3.73945, -LL: 3.83458, prior: 0.86490, aleatoric unc.: 10.08496\n",
+ "Epoch 215/500 total: 3.74090, -LL: 3.82905, prior: 0.86707, aleatoric unc.: 10.09087\n",
+ "Epoch 216/500 total: 3.73818, -LL: 3.84171, prior: 0.86245, aleatoric unc.: 10.09037\n",
+ "Epoch 217/500 total: 3.74622, -LL: 3.84954, prior: 0.86237, aleatoric unc.: 10.10379\n",
+ "Epoch 218/500 total: 3.74220, -LL: 3.82079, prior: 0.86418, aleatoric unc.: 10.11133\n",
+ "Epoch 219/500 total: 3.74040, -LL: 3.85974, prior: 0.86777, aleatoric unc.: 10.11192\n",
+ "Epoch 220/500 total: 3.73723, -LL: 3.84683, prior: 0.86470, aleatoric unc.: 10.10319\n",
+ "Epoch 221/500 total: 3.73823, -LL: 3.85080, prior: 0.86649, aleatoric unc.: 10.10033\n",
+ "Epoch 222/500 total: 3.74458, -LL: 3.85009, prior: 0.86799, aleatoric unc.: 10.11421\n",
+ "Epoch 223/500 total: 3.72804, -LL: 3.82770, prior: 0.86696, aleatoric unc.: 10.08886\n",
+ "Epoch 224/500 total: 3.73275, -LL: 3.85922, prior: 0.86889, aleatoric unc.: 10.07470\n",
+ "Epoch 225/500 total: 3.73947, -LL: 3.85123, prior: 0.86994, aleatoric unc.: 10.07797\n",
+ "Epoch 226/500 total: 3.73466, -LL: 3.83908, prior: 0.86836, aleatoric unc.: 10.07260\n",
+ "Epoch 227/500 total: 3.74633, -LL: 3.85449, prior: 0.87059, aleatoric unc.: 10.09478\n",
+ "Epoch 228/500 total: 3.73569, -LL: 3.82477, prior: 0.87201, aleatoric unc.: 10.08870\n",
+ "Epoch 229/500 total: 3.73087, -LL: 3.84901, prior: 0.86998, aleatoric unc.: 10.07468\n",
+ "Epoch 230/500 total: 3.73849, -LL: 3.85777, prior: 0.86937, aleatoric unc.: 10.07428\n",
+ "Epoch 231/500 total: 3.73356, -LL: 3.85047, prior: 0.86571, aleatoric unc.: 10.06948\n",
+ "Epoch 232/500 total: 3.74225, -LL: 3.82129, prior: 0.86677, aleatoric unc.: 10.08225\n",
+ "Epoch 233/500 total: 3.73858, -LL: 3.83511, prior: 0.87041, aleatoric unc.: 10.08435\n",
+ "Epoch 234/500 total: 3.73545, -LL: 3.84898, prior: 0.87459, aleatoric unc.: 10.07925\n",
+ "Epoch 235/500 total: 3.74321, -LL: 3.87172, prior: 0.88229, aleatoric unc.: 10.08612\n",
+ "Epoch 236/500 total: 3.73258, -LL: 3.83945, prior: 0.88139, aleatoric unc.: 10.07778\n",
+ "Epoch 237/500 total: 3.73088, -LL: 3.85592, prior: 0.88219, aleatoric unc.: 10.06729\n",
+ "Epoch 238/500 total: 3.72690, -LL: 3.84330, prior: 0.88206, aleatoric unc.: 10.04798\n",
+ "Epoch 239/500 total: 3.72471, -LL: 3.81567, prior: 0.87896, aleatoric unc.: 10.02770\n",
+ "Epoch 240/500 total: 3.73120, -LL: 3.84921, prior: 0.87845, aleatoric unc.: 10.02429\n",
+ "Epoch 241/500 total: 3.73744, -LL: 3.84474, prior: 0.87716, aleatoric unc.: 10.02944\n",
+ "Epoch 242/500 total: 3.73518, -LL: 3.85295, prior: 0.87562, aleatoric unc.: 10.04032\n",
+ "Epoch 243/500 total: 3.73957, -LL: 3.83003, prior: 0.87569, aleatoric unc.: 10.05301\n",
+ "Epoch 244/500 total: 3.72330, -LL: 3.79862, prior: 0.87359, aleatoric unc.: 10.03373\n",
+ "Epoch 245/500 total: 3.73717, -LL: 3.84251, prior: 0.87580, aleatoric unc.: 10.03952\n",
+ "Epoch 246/500 total: 3.73337, -LL: 3.84113, prior: 0.87794, aleatoric unc.: 10.03982\n",
+ "Epoch 247/500 total: 3.73732, -LL: 3.82673, prior: 0.87200, aleatoric unc.: 10.04777\n",
+ "Epoch 248/500 total: 3.73092, -LL: 3.84884, prior: 0.87618, aleatoric unc.: 10.03941\n",
+ "Epoch 249/500 total: 3.73682, -LL: 3.83811, prior: 0.87866, aleatoric unc.: 10.04432\n",
+ "Epoch 250/500 total: 3.73329, -LL: 3.84938, prior: 0.87504, aleatoric unc.: 10.04439\n",
+ "Epoch 251/500 total: 3.72405, -LL: 3.83273, prior: 0.87539, aleatoric unc.: 10.02378\n",
+ "Epoch 252/500 total: 3.73673, -LL: 3.83746, prior: 0.87136, aleatoric unc.: 10.03440\n",
+ "Epoch 253/500 total: 3.73512, -LL: 3.85179, prior: 0.87069, aleatoric unc.: 10.03872\n",
+ "Epoch 254/500 total: 3.74583, -LL: 3.86775, prior: 0.87206, aleatoric unc.: 10.06437\n",
+ "Epoch 255/500 total: 3.73648, -LL: 3.82828, prior: 0.87207, aleatoric unc.: 10.07062\n",
+ "Epoch 256/500 total: 3.74652, -LL: 3.86064, prior: 0.87944, aleatoric unc.: 10.08661\n",
+ "Epoch 257/500 total: 3.74674, -LL: 3.83243, prior: 0.87490, aleatoric unc.: 10.10284\n",
+ "Epoch 258/500 total: 3.73108, -LL: 3.80533, prior: 0.88290, aleatoric unc.: 10.08756\n",
+ "Epoch 259/500 total: 3.73936, -LL: 3.82145, prior: 0.88110, aleatoric unc.: 10.08701\n",
+ "Epoch 260/500 total: 3.74065, -LL: 3.84406, prior: 0.88456, aleatoric unc.: 10.09371\n",
+ "Epoch 261/500 total: 3.72781, -LL: 3.85403, prior: 0.88144, aleatoric unc.: 10.07256\n",
+ "Epoch 262/500 total: 3.73517, -LL: 3.84944, prior: 0.88410, aleatoric unc.: 10.06823\n",
+ "Epoch 263/500 total: 3.72663, -LL: 3.82933, prior: 0.88237, aleatoric unc.: 10.04667\n",
+ "Epoch 264/500 total: 3.73305, -LL: 3.84147, prior: 0.87848, aleatoric unc.: 10.04373\n",
+ "Epoch 265/500 total: 3.74472, -LL: 3.86220, prior: 0.87989, aleatoric unc.: 10.06395\n",
+ "Epoch 266/500 total: 3.74537, -LL: 3.81982, prior: 0.87981, aleatoric unc.: 10.08481\n",
+ "Epoch 267/500 total: 3.73193, -LL: 3.81571, prior: 0.87682, aleatoric unc.: 10.07143\n",
+ "Epoch 268/500 total: 3.73677, -LL: 3.84343, prior: 0.87995, aleatoric unc.: 10.07501\n",
+ "Epoch 269/500 total: 3.73038, -LL: 3.83264, prior: 0.88027, aleatoric unc.: 10.05903\n",
+ "Epoch 270/500 total: 3.73205, -LL: 3.81584, prior: 0.87711, aleatoric unc.: 10.05225\n",
+ "Epoch 271/500 total: 3.72595, -LL: 3.82210, prior: 0.88014, aleatoric unc.: 10.03504\n",
+ "Epoch 272/500 total: 3.73350, -LL: 3.82732, prior: 0.87685, aleatoric unc.: 10.03423\n",
+ "Epoch 273/500 total: 3.73925, -LL: 3.81784, prior: 0.87958, aleatoric unc.: 10.04436\n",
+ "Epoch 274/500 total: 3.73767, -LL: 3.79338, prior: 0.88357, aleatoric unc.: 10.05611\n",
+ "Epoch 275/500 total: 3.74194, -LL: 3.84523, prior: 0.88517, aleatoric unc.: 10.06982\n",
+ "Epoch 276/500 total: 3.74030, -LL: 3.83185, prior: 0.88759, aleatoric unc.: 10.07730\n",
+ "Epoch 277/500 total: 3.73708, -LL: 3.83321, prior: 0.88411, aleatoric unc.: 10.07823\n",
+ "Epoch 278/500 total: 3.73453, -LL: 3.82810, prior: 0.88412, aleatoric unc.: 10.07381\n",
+ "Epoch 279/500 total: 3.72974, -LL: 3.84434, prior: 0.88644, aleatoric unc.: 10.05808\n",
+ "Epoch 280/500 total: 3.73375, -LL: 3.84109, prior: 0.88328, aleatoric unc.: 10.05523\n",
+ "Epoch 281/500 total: 3.73087, -LL: 3.82218, prior: 0.88493, aleatoric unc.: 10.04799\n",
+ "Epoch 282/500 total: 3.73445, -LL: 3.84461, prior: 0.88107, aleatoric unc.: 10.04239\n",
+ "Epoch 283/500 total: 3.74024, -LL: 3.85273, prior: 0.87883, aleatoric unc.: 10.05470\n",
+ "Epoch 284/500 total: 3.73575, -LL: 3.84200, prior: 0.88010, aleatoric unc.: 10.05948\n",
+ "Epoch 285/500 total: 3.73147, -LL: 3.84219, prior: 0.87924, aleatoric unc.: 10.05173\n",
+ "Epoch 286/500 total: 3.72579, -LL: 3.83094, prior: 0.87940, aleatoric unc.: 10.03240\n",
+ "Epoch 287/500 total: 3.72818, -LL: 3.82885, prior: 0.87679, aleatoric unc.: 10.02026\n",
+ "Epoch 288/500 total: 3.73522, -LL: 3.83685, prior: 0.87990, aleatoric unc.: 10.02844\n",
+ "Epoch 289/500 total: 3.74124, -LL: 3.85903, prior: 0.88043, aleatoric unc.: 10.04685\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
- "Epoch 292/500 total: 3.69757, -LL: 3.58311, prior: 0.82735, aleatoric unc.: 9.77046\n",
- "Epoch 293/500 total: 3.70371, -LL: 3.64588, prior: 0.82783, aleatoric unc.: 9.76296\n",
- "Epoch 294/500 total: 3.70312, -LL: 3.62281, prior: 0.83122, aleatoric unc.: 9.76033\n",
- "Epoch 295/500 total: 3.70929, -LL: 3.64419, prior: 0.83021, aleatoric unc.: 9.76300\n",
- "Epoch 296/500 total: 3.70208, -LL: 3.64338, prior: 0.83049, aleatoric unc.: 9.76104\n",
- "Epoch 297/500 total: 3.70218, -LL: 3.61723, prior: 0.83026, aleatoric unc.: 9.75453\n",
- "Epoch 298/500 total: 3.70252, -LL: 3.64148, prior: 0.83147, aleatoric unc.: 9.74977\n",
- "Epoch 299/500 total: 3.70108, -LL: 3.68672, prior: 0.83107, aleatoric unc.: 9.74179\n",
- "Epoch 300/500 total: 3.70634, -LL: 3.67040, prior: 0.82994, aleatoric unc.: 9.75107\n",
- "Epoch 301/500 total: 3.69355, -LL: 3.60485, prior: 0.82971, aleatoric unc.: 9.73195\n",
- "Epoch 302/500 total: 3.70322, -LL: 3.63580, prior: 0.83051, aleatoric unc.: 9.73157\n",
- "Epoch 303/500 total: 3.70026, -LL: 3.70596, prior: 0.82929, aleatoric unc.: 9.72599\n",
- "Epoch 304/500 total: 3.70397, -LL: 3.65822, prior: 0.83103, aleatoric unc.: 9.72934\n",
- "Epoch 305/500 total: 3.70864, -LL: 3.56731, prior: 0.83211, aleatoric unc.: 9.74369\n",
- "Epoch 306/500 total: 3.70876, -LL: 3.59099, prior: 0.83176, aleatoric unc.: 9.75274\n",
- "Epoch 307/500 total: 3.70129, -LL: 3.63883, prior: 0.82881, aleatoric unc.: 9.74951\n",
- "Epoch 308/500 total: 3.70983, -LL: 3.63237, prior: 0.82886, aleatoric unc.: 9.75686\n",
- "Epoch 309/500 total: 3.70741, -LL: 3.60030, prior: 0.83055, aleatoric unc.: 9.76448\n",
- "Epoch 310/500 total: 3.70709, -LL: 3.59931, prior: 0.83434, aleatoric unc.: 9.76765\n",
- "Epoch 311/500 total: 3.69747, -LL: 3.63639, prior: 0.83337, aleatoric unc.: 9.74833\n",
- "Epoch 312/500 total: 3.71152, -LL: 3.62594, prior: 0.83660, aleatoric unc.: 9.76304\n",
- "Epoch 313/500 total: 3.70416, -LL: 3.64673, prior: 0.83517, aleatoric unc.: 9.76183\n",
- "Epoch 314/500 total: 3.69919, -LL: 3.58278, prior: 0.83536, aleatoric unc.: 9.75043\n",
- "Epoch 315/500 total: 3.70675, -LL: 3.60159, prior: 0.83583, aleatoric unc.: 9.75515\n",
- "Epoch 316/500 total: 3.70445, -LL: 3.64417, prior: 0.83832, aleatoric unc.: 9.75135\n",
- "Epoch 317/500 total: 3.70155, -LL: 3.64957, prior: 0.83247, aleatoric unc.: 9.74824\n",
- "Epoch 318/500 total: 3.70251, -LL: 3.61336, prior: 0.83256, aleatoric unc.: 9.74411\n",
- "Epoch 319/500 total: 3.70864, -LL: 3.61781, prior: 0.83391, aleatoric unc.: 9.75591\n",
- "Epoch 320/500 total: 3.69483, -LL: 3.62589, prior: 0.83023, aleatoric unc.: 9.73673\n",
- "Epoch 321/500 total: 3.70477, -LL: 3.65918, prior: 0.83147, aleatoric unc.: 9.73801\n",
- "Epoch 322/500 total: 3.71006, -LL: 3.68025, prior: 0.83056, aleatoric unc.: 9.75054\n",
- "Epoch 323/500 total: 3.70612, -LL: 3.63204, prior: 0.82882, aleatoric unc.: 9.75776\n",
- "Epoch 324/500 total: 3.70220, -LL: 3.63502, prior: 0.82885, aleatoric unc.: 9.75287\n",
- "Epoch 325/500 total: 3.70991, -LL: 3.67634, prior: 0.82949, aleatoric unc.: 9.75935\n",
- "Epoch 326/500 total: 3.70031, -LL: 3.67920, prior: 0.83210, aleatoric unc.: 9.74968\n",
- "Epoch 327/500 total: 3.71157, -LL: 3.65393, prior: 0.83033, aleatoric unc.: 9.76567\n",
- "Epoch 328/500 total: 3.70492, -LL: 3.64040, prior: 0.82936, aleatoric unc.: 9.76520\n",
- "Epoch 329/500 total: 3.70176, -LL: 3.60859, prior: 0.83023, aleatoric unc.: 9.75874\n",
- "Epoch 330/500 total: 3.70091, -LL: 3.61544, prior: 0.83437, aleatoric unc.: 9.74670\n",
- "Epoch 331/500 total: 3.70303, -LL: 3.65750, prior: 0.83323, aleatoric unc.: 9.74530\n",
- "Epoch 332/500 total: 3.70879, -LL: 3.59750, prior: 0.82948, aleatoric unc.: 9.75656\n",
- "Epoch 333/500 total: 3.70656, -LL: 3.65474, prior: 0.82868, aleatoric unc.: 9.76092\n",
- "Epoch 334/500 total: 3.69965, -LL: 3.63443, prior: 0.83218, aleatoric unc.: 9.74758\n",
- "Epoch 335/500 total: 3.70277, -LL: 3.63288, prior: 0.83110, aleatoric unc.: 9.74762\n",
- "Epoch 336/500 total: 3.70189, -LL: 3.66539, prior: 0.83201, aleatoric unc.: 9.74239\n",
- "Epoch 337/500 total: 3.69537, -LL: 3.65592, prior: 0.82954, aleatoric unc.: 9.72731\n",
- "Epoch 338/500 total: 3.69802, -LL: 3.60642, prior: 0.82822, aleatoric unc.: 9.72182\n",
- "Epoch 339/500 total: 3.71005, -LL: 3.67063, prior: 0.82849, aleatoric unc.: 9.73660\n",
- "Epoch 340/500 total: 3.70104, -LL: 3.60019, prior: 0.83237, aleatoric unc.: 9.73406\n",
- "Epoch 341/500 total: 3.70567, -LL: 3.62259, prior: 0.83000, aleatoric unc.: 9.74208\n",
- "Epoch 342/500 total: 3.70195, -LL: 3.65865, prior: 0.82917, aleatoric unc.: 9.73657\n",
- "Epoch 343/500 total: 3.70123, -LL: 3.62708, prior: 0.83080, aleatoric unc.: 9.73533\n",
- "Epoch 344/500 total: 3.70437, -LL: 3.61342, prior: 0.82911, aleatoric unc.: 9.73596\n",
- "Epoch 345/500 total: 3.70366, -LL: 3.60328, prior: 0.83045, aleatoric unc.: 9.74204\n",
- "Epoch 346/500 total: 3.70356, -LL: 3.62689, prior: 0.83147, aleatoric unc.: 9.73873\n",
- "Epoch 347/500 total: 3.69629, -LL: 3.64269, prior: 0.82647, aleatoric unc.: 9.72898\n",
- "Epoch 348/500 total: 3.69996, -LL: 3.65626, prior: 0.82871, aleatoric unc.: 9.72221\n",
- "Epoch 349/500 total: 3.70417, -LL: 3.63705, prior: 0.82662, aleatoric unc.: 9.72849\n",
- "Epoch 350/500 total: 3.70177, -LL: 3.65497, prior: 0.82323, aleatoric unc.: 9.72953\n",
- "Epoch 351/500 total: 3.70254, -LL: 3.67832, prior: 0.82772, aleatoric unc.: 9.73065\n",
- "Epoch 352/500 total: 3.70162, -LL: 3.63990, prior: 0.83119, aleatoric unc.: 9.72532\n",
- "Epoch 353/500 total: 3.70578, -LL: 3.60402, prior: 0.83188, aleatoric unc.: 9.73709\n",
- "Epoch 354/500 total: 3.70272, -LL: 3.62950, prior: 0.82930, aleatoric unc.: 9.73685\n",
- "Epoch 355/500 total: 3.70043, -LL: 3.62746, prior: 0.82995, aleatoric unc.: 9.73355\n",
- "Epoch 356/500 total: 3.69946, -LL: 3.61545, prior: 0.83072, aleatoric unc.: 9.72545\n",
- "Epoch 357/500 total: 3.70071, -LL: 3.67021, prior: 0.83015, aleatoric unc.: 9.72398\n",
- "Epoch 358/500 total: 3.70548, -LL: 3.63582, prior: 0.82771, aleatoric unc.: 9.73216\n",
- "Epoch 359/500 total: 3.69811, -LL: 3.60202, prior: 0.82758, aleatoric unc.: 9.72475\n",
- "Epoch 360/500 total: 3.69686, -LL: 3.64973, prior: 0.82581, aleatoric unc.: 9.71591\n",
- "Epoch 361/500 total: 3.70717, -LL: 3.65881, prior: 0.82941, aleatoric unc.: 9.72619\n",
- "Epoch 362/500 total: 3.70385, -LL: 3.65302, prior: 0.82832, aleatoric unc.: 9.73025\n",
- "Epoch 363/500 total: 3.70743, -LL: 3.64934, prior: 0.82749, aleatoric unc.: 9.74160\n",
- "Epoch 364/500 total: 3.70326, -LL: 3.58934, prior: 0.82753, aleatoric unc.: 9.74316\n",
- "Epoch 365/500 total: 3.70402, -LL: 3.62665, prior: 0.82742, aleatoric unc.: 9.74414\n",
- "Epoch 366/500 total: 3.70585, -LL: 3.68176, prior: 0.82632, aleatoric unc.: 9.74891\n",
- "Epoch 367/500 total: 3.70568, -LL: 3.62934, prior: 0.82647, aleatoric unc.: 9.75294\n",
- "Epoch 368/500 total: 3.69735, -LL: 3.63394, prior: 0.82584, aleatoric unc.: 9.73833\n",
- "Epoch 369/500 total: 3.70665, -LL: 3.60627, prior: 0.82508, aleatoric unc.: 9.74506\n",
- "Epoch 370/500 total: 3.70283, -LL: 3.64191, prior: 0.82496, aleatoric unc.: 9.74463\n",
- "Epoch 371/500 total: 3.69990, -LL: 3.63656, prior: 0.82942, aleatoric unc.: 9.73714\n",
- "Epoch 372/500 total: 3.70170, -LL: 3.65815, prior: 0.82560, aleatoric unc.: 9.73377\n",
- "Epoch 373/500 total: 3.70135, -LL: 3.66173, prior: 0.82487, aleatoric unc.: 9.73149\n",
- "Epoch 374/500 total: 3.70539, -LL: 3.60903, prior: 0.82451, aleatoric unc.: 9.74010\n",
- "Epoch 375/500 total: 3.69980, -LL: 3.63325, prior: 0.82713, aleatoric unc.: 9.73296\n",
- "Epoch 376/500 total: 3.69921, -LL: 3.60023, prior: 0.82868, aleatoric unc.: 9.72724\n",
- "Epoch 377/500 total: 3.69869, -LL: 3.66106, prior: 0.82731, aleatoric unc.: 9.72021\n",
- "Epoch 378/500 total: 3.69702, -LL: 3.62505, prior: 0.82719, aleatoric unc.: 9.71488\n",
- "Epoch 379/500 total: 3.69819, -LL: 3.60678, prior: 0.82717, aleatoric unc.: 9.71085\n",
- "Epoch 380/500 total: 3.69677, -LL: 3.62688, prior: 0.82746, aleatoric unc.: 9.70245\n",
- "Epoch 381/500 total: 3.70501, -LL: 3.60229, prior: 0.82751, aleatoric unc.: 9.71364\n",
- "Epoch 382/500 total: 3.69922, -LL: 3.57855, prior: 0.83100, aleatoric unc.: 9.71044\n",
- "Epoch 383/500 total: 3.69865, -LL: 3.63590, prior: 0.82836, aleatoric unc.: 9.70802\n",
- "Epoch 384/500 total: 3.70344, -LL: 3.59795, prior: 0.82755, aleatoric unc.: 9.71421\n",
- "Epoch 385/500 total: 3.70533, -LL: 3.64661, prior: 0.82573, aleatoric unc.: 9.72334\n",
- "Epoch 386/500 total: 3.70198, -LL: 3.61014, prior: 0.82611, aleatoric unc.: 9.72450\n",
- "Epoch 387/500 total: 3.70406, -LL: 3.64215, prior: 0.82555, aleatoric unc.: 9.73054\n",
- "Epoch 388/500 total: 3.70490, -LL: 3.63847, prior: 0.82456, aleatoric unc.: 9.73703\n"
+ "Epoch 290/500 total: 3.73078, -LL: 3.82290, prior: 0.88317, aleatoric unc.: 10.03864\n",
+ "Epoch 291/500 total: 3.73531, -LL: 3.84319, prior: 0.88349, aleatoric unc.: 10.04144\n",
+ "Epoch 292/500 total: 3.73754, -LL: 3.81090, prior: 0.87882, aleatoric unc.: 10.05152\n",
+ "Epoch 293/500 total: 3.73974, -LL: 3.84554, prior: 0.87938, aleatoric unc.: 10.05891\n",
+ "Epoch 294/500 total: 3.73681, -LL: 3.83876, prior: 0.88027, aleatoric unc.: 10.06562\n",
+ "Epoch 295/500 total: 3.73704, -LL: 3.83492, prior: 0.87828, aleatoric unc.: 10.06698\n",
+ "Epoch 296/500 total: 3.73231, -LL: 3.82193, prior: 0.87644, aleatoric unc.: 10.05933\n",
+ "Epoch 297/500 total: 3.72739, -LL: 3.79936, prior: 0.87980, aleatoric unc.: 10.04408\n",
+ "Epoch 298/500 total: 3.73196, -LL: 3.83840, prior: 0.88188, aleatoric unc.: 10.03749\n",
+ "Epoch 299/500 total: 3.73376, -LL: 3.84997, prior: 0.88427, aleatoric unc.: 10.03885\n",
+ "Epoch 300/500 total: 3.73323, -LL: 3.80997, prior: 0.88066, aleatoric unc.: 10.03964\n",
+ "Epoch 301/500 total: 3.72601, -LL: 3.83434, prior: 0.88612, aleatoric unc.: 10.02257\n",
+ "Epoch 302/500 total: 3.73202, -LL: 3.81852, prior: 0.88779, aleatoric unc.: 10.02244\n",
+ "Epoch 303/500 total: 3.73000, -LL: 3.83370, prior: 0.88513, aleatoric unc.: 10.01924\n",
+ "Epoch 304/500 total: 3.72759, -LL: 3.82018, prior: 0.88922, aleatoric unc.: 10.01199\n",
+ "Epoch 305/500 total: 3.73553, -LL: 3.83870, prior: 0.88858, aleatoric unc.: 10.01710\n",
+ "Epoch 306/500 total: 3.73251, -LL: 3.82719, prior: 0.88847, aleatoric unc.: 10.02079\n",
+ "Epoch 307/500 total: 3.73815, -LL: 3.82262, prior: 0.88536, aleatoric unc.: 10.03512\n",
+ "Epoch 308/500 total: 3.73279, -LL: 3.82678, prior: 0.88497, aleatoric unc.: 10.03456\n",
+ "Epoch 309/500 total: 3.73932, -LL: 3.84826, prior: 0.88323, aleatoric unc.: 10.04989\n",
+ "Epoch 310/500 total: 3.73145, -LL: 3.83595, prior: 0.88123, aleatoric unc.: 10.04353\n",
+ "Epoch 311/500 total: 3.73321, -LL: 3.83717, prior: 0.88390, aleatoric unc.: 10.04142\n",
+ "Epoch 312/500 total: 3.72959, -LL: 3.83596, prior: 0.88110, aleatoric unc.: 10.03537\n",
+ "Epoch 313/500 total: 3.73188, -LL: 3.84000, prior: 0.88260, aleatoric unc.: 10.03028\n",
+ "Epoch 314/500 total: 3.74220, -LL: 3.81744, prior: 0.88203, aleatoric unc.: 10.05165\n",
+ "Epoch 315/500 total: 3.73042, -LL: 3.82799, prior: 0.88232, aleatoric unc.: 10.04013\n",
+ "Epoch 316/500 total: 3.72984, -LL: 3.85550, prior: 0.88176, aleatoric unc.: 10.03514\n",
+ "Epoch 317/500 total: 3.73183, -LL: 3.81656, prior: 0.87717, aleatoric unc.: 10.03121\n",
+ "Epoch 318/500 total: 3.73261, -LL: 3.85981, prior: 0.87807, aleatoric unc.: 10.03441\n",
+ "Epoch 319/500 total: 3.73095, -LL: 3.82401, prior: 0.87428, aleatoric unc.: 10.02800\n",
+ "Epoch 320/500 total: 3.73588, -LL: 3.82786, prior: 0.87595, aleatoric unc.: 10.03349\n",
+ "Epoch 321/500 total: 3.73572, -LL: 3.84833, prior: 0.87874, aleatoric unc.: 10.04079\n",
+ "Epoch 322/500 total: 3.73743, -LL: 3.83180, prior: 0.88097, aleatoric unc.: 10.04579\n",
+ "Epoch 323/500 total: 3.73886, -LL: 3.86098, prior: 0.88275, aleatoric unc.: 10.05595\n",
+ "Epoch 324/500 total: 3.73219, -LL: 3.82601, prior: 0.88648, aleatoric unc.: 10.05257\n",
+ "Epoch 325/500 total: 3.73201, -LL: 3.82155, prior: 0.88320, aleatoric unc.: 10.04786\n",
+ "Epoch 326/500 total: 3.73172, -LL: 3.81521, prior: 0.88657, aleatoric unc.: 10.04028\n",
+ "Epoch 327/500 total: 3.73528, -LL: 3.80903, prior: 0.88422, aleatoric unc.: 10.04721\n",
+ "Epoch 328/500 total: 3.72830, -LL: 3.84799, prior: 0.88342, aleatoric unc.: 10.03386\n",
+ "Epoch 329/500 total: 3.72787, -LL: 3.82583, prior: 0.87974, aleatoric unc.: 10.02465\n",
+ "Epoch 330/500 total: 3.73035, -LL: 3.84009, prior: 0.87974, aleatoric unc.: 10.01949\n",
+ "Epoch 331/500 total: 3.72952, -LL: 3.83119, prior: 0.88266, aleatoric unc.: 10.01468\n",
+ "Epoch 332/500 total: 3.73463, -LL: 3.83972, prior: 0.88579, aleatoric unc.: 10.02100\n",
+ "Epoch 333/500 total: 3.73573, -LL: 3.85132, prior: 0.88518, aleatoric unc.: 10.03044\n",
+ "Epoch 334/500 total: 3.73782, -LL: 3.83100, prior: 0.88682, aleatoric unc.: 10.03967\n",
+ "Epoch 335/500 total: 3.73350, -LL: 3.84184, prior: 0.88841, aleatoric unc.: 10.03893\n",
+ "Epoch 336/500 total: 3.73208, -LL: 3.83762, prior: 0.89050, aleatoric unc.: 10.03780\n",
+ "Epoch 337/500 total: 3.73019, -LL: 3.83957, prior: 0.89159, aleatoric unc.: 10.02703\n",
+ "Epoch 338/500 total: 3.73397, -LL: 3.84011, prior: 0.89324, aleatoric unc.: 10.03091\n",
+ "Epoch 339/500 total: 3.73350, -LL: 3.82932, prior: 0.89086, aleatoric unc.: 10.03356\n",
+ "Epoch 340/500 total: 3.72820, -LL: 3.82996, prior: 0.89210, aleatoric unc.: 10.02680\n",
+ "Epoch 341/500 total: 3.73196, -LL: 3.81454, prior: 0.89177, aleatoric unc.: 10.02168\n",
+ "Epoch 342/500 total: 3.73540, -LL: 3.82618, prior: 0.89100, aleatoric unc.: 10.02984\n",
+ "Epoch 343/500 total: 3.73078, -LL: 3.85091, prior: 0.89221, aleatoric unc.: 10.02542\n",
+ "Epoch 344/500 total: 3.73540, -LL: 3.83629, prior: 0.89025, aleatoric unc.: 10.03324\n",
+ "Epoch 345/500 total: 3.73057, -LL: 3.85112, prior: 0.89017, aleatoric unc.: 10.02916\n",
+ "Epoch 346/500 total: 3.73014, -LL: 3.83488, prior: 0.89049, aleatoric unc.: 10.02050\n",
+ "Epoch 347/500 total: 3.73608, -LL: 3.84264, prior: 0.89203, aleatoric unc.: 10.03130\n",
+ "Epoch 348/500 total: 3.73567, -LL: 3.84484, prior: 0.89498, aleatoric unc.: 10.03739\n",
+ "Epoch 349/500 total: 3.72357, -LL: 3.82079, prior: 0.89434, aleatoric unc.: 10.02024\n",
+ "Epoch 350/500 total: 3.73541, -LL: 3.84696, prior: 0.89677, aleatoric unc.: 10.02459\n",
+ "Epoch 351/500 total: 3.73969, -LL: 3.82401, prior: 0.89731, aleatoric unc.: 10.04085\n",
+ "Epoch 352/500 total: 3.73720, -LL: 3.82906, prior: 0.89721, aleatoric unc.: 10.04858\n",
+ "Epoch 353/500 total: 3.73829, -LL: 3.83458, prior: 0.89393, aleatoric unc.: 10.05570\n",
+ "Epoch 354/500 total: 3.73489, -LL: 3.81912, prior: 0.89696, aleatoric unc.: 10.05356\n",
+ "Epoch 355/500 total: 3.73196, -LL: 3.82104, prior: 0.89589, aleatoric unc.: 10.04821\n",
+ "Epoch 356/500 total: 3.72923, -LL: 3.83192, prior: 0.89528, aleatoric unc.: 10.04053\n",
+ "Epoch 357/500 total: 3.73127, -LL: 3.84338, prior: 0.89679, aleatoric unc.: 10.03265\n",
+ "Epoch 358/500 total: 3.72917, -LL: 3.86333, prior: 0.89251, aleatoric unc.: 10.02645\n",
+ "Epoch 359/500 total: 3.73414, -LL: 3.84732, prior: 0.89364, aleatoric unc.: 10.02898\n",
+ "Epoch 360/500 total: 3.73101, -LL: 3.83801, prior: 0.89542, aleatoric unc.: 10.02329\n",
+ "Epoch 361/500 total: 3.73287, -LL: 3.83443, prior: 0.89314, aleatoric unc.: 10.02719\n",
+ "Epoch 362/500 total: 3.73435, -LL: 3.86091, prior: 0.89526, aleatoric unc.: 10.02911\n",
+ "Epoch 363/500 total: 3.73365, -LL: 3.82555, prior: 0.89690, aleatoric unc.: 10.03178\n",
+ "Epoch 364/500 total: 3.72439, -LL: 3.86389, prior: 0.89553, aleatoric unc.: 10.01470\n",
+ "Epoch 365/500 total: 3.72976, -LL: 3.83215, prior: 0.89460, aleatoric unc.: 10.01259\n",
+ "Epoch 366/500 total: 3.73202, -LL: 3.85007, prior: 0.89171, aleatoric unc.: 10.01205\n",
+ "Epoch 367/500 total: 3.73954, -LL: 3.83204, prior: 0.89550, aleatoric unc.: 10.03099\n",
+ "Epoch 368/500 total: 3.72965, -LL: 3.82549, prior: 0.89351, aleatoric unc.: 10.02582\n",
+ "Epoch 369/500 total: 3.73506, -LL: 3.82564, prior: 0.89420, aleatoric unc.: 10.02934\n",
+ "Epoch 370/500 total: 3.72704, -LL: 3.83145, prior: 0.89169, aleatoric unc.: 10.02203\n",
+ "Epoch 371/500 total: 3.73389, -LL: 3.81709, prior: 0.89459, aleatoric unc.: 10.02458\n",
+ "Epoch 372/500 total: 3.73686, -LL: 3.81059, prior: 0.89624, aleatoric unc.: 10.03357\n",
+ "Epoch 373/500 total: 3.73560, -LL: 3.82662, prior: 0.89119, aleatoric unc.: 10.03854\n",
+ "Epoch 374/500 total: 3.73360, -LL: 3.84537, prior: 0.89562, aleatoric unc.: 10.03877\n",
+ "Epoch 375/500 total: 3.73328, -LL: 3.82317, prior: 0.89219, aleatoric unc.: 10.03795\n",
+ "Epoch 376/500 total: 3.73026, -LL: 3.83765, prior: 0.88902, aleatoric unc.: 10.02962\n",
+ "Epoch 377/500 total: 3.73204, -LL: 3.83662, prior: 0.89147, aleatoric unc.: 10.02926\n",
+ "Epoch 378/500 total: 3.73036, -LL: 3.82936, prior: 0.89292, aleatoric unc.: 10.02385\n",
+ "Epoch 379/500 total: 3.72926, -LL: 3.82606, prior: 0.89050, aleatoric unc.: 10.02054\n",
+ "Epoch 380/500 total: 3.73048, -LL: 3.82632, prior: 0.89072, aleatoric unc.: 10.01658\n",
+ "Epoch 381/500 total: 3.72972, -LL: 3.83331, prior: 0.89171, aleatoric unc.: 10.01003\n",
+ "Epoch 382/500 total: 3.73252, -LL: 3.84965, prior: 0.88848, aleatoric unc.: 10.01669\n",
+ "Epoch 383/500 total: 3.72503, -LL: 3.85571, prior: 0.88730, aleatoric unc.: 10.00144\n",
+ "Epoch 384/500 total: 3.72739, -LL: 3.85552, prior: 0.88597, aleatoric unc.: 9.99612\n",
+ "Epoch 385/500 total: 3.73108, -LL: 3.83535, prior: 0.88979, aleatoric unc.: 9.99871\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
- "Epoch 389/500 total: 3.69739, -LL: 3.60615, prior: 0.82374, aleatoric unc.: 9.72495\n",
- "Epoch 390/500 total: 3.70646, -LL: 3.59768, prior: 0.82653, aleatoric unc.: 9.73402\n",
- "Epoch 391/500 total: 3.69914, -LL: 3.65293, prior: 0.82449, aleatoric unc.: 9.72576\n",
- "Epoch 392/500 total: 3.70214, -LL: 3.62112, prior: 0.82444, aleatoric unc.: 9.72820\n",
- "Epoch 393/500 total: 3.70022, -LL: 3.57499, prior: 0.82906, aleatoric unc.: 9.72694\n",
- "Epoch 394/500 total: 3.69050, -LL: 3.60771, prior: 0.82554, aleatoric unc.: 9.70561\n",
- "Epoch 395/500 total: 3.69285, -LL: 3.68116, prior: 0.82755, aleatoric unc.: 9.69149\n",
- "Epoch 396/500 total: 3.70537, -LL: 3.61828, prior: 0.82465, aleatoric unc.: 9.70394\n",
- "Epoch 397/500 total: 3.69655, -LL: 3.61455, prior: 0.82317, aleatoric unc.: 9.70052\n",
- "Epoch 398/500 total: 3.70530, -LL: 3.62109, prior: 0.82612, aleatoric unc.: 9.71183\n",
- "Epoch 399/500 total: 3.70086, -LL: 3.61040, prior: 0.82481, aleatoric unc.: 9.71438\n",
- "Epoch 400/500 total: 3.70211, -LL: 3.64791, prior: 0.82474, aleatoric unc.: 9.71751\n",
- "Epoch 401/500 total: 3.70449, -LL: 3.66220, prior: 0.82469, aleatoric unc.: 9.72471\n",
- "Epoch 402/500 total: 3.69559, -LL: 3.68538, prior: 0.82521, aleatoric unc.: 9.71284\n",
- "Epoch 403/500 total: 3.70262, -LL: 3.61727, prior: 0.82641, aleatoric unc.: 9.71845\n",
- "Epoch 404/500 total: 3.70541, -LL: 3.65800, prior: 0.82866, aleatoric unc.: 9.72628\n",
- "Epoch 405/500 total: 3.70215, -LL: 3.66135, prior: 0.82954, aleatoric unc.: 9.72948\n",
- "Epoch 406/500 total: 3.69729, -LL: 3.64724, prior: 0.82800, aleatoric unc.: 9.72026\n",
- "Epoch 407/500 total: 3.69719, -LL: 3.63176, prior: 0.82775, aleatoric unc.: 9.71121\n",
- "Epoch 408/500 total: 3.70596, -LL: 3.66872, prior: 0.82940, aleatoric unc.: 9.72126\n",
- "Epoch 409/500 total: 3.70204, -LL: 3.63414, prior: 0.83020, aleatoric unc.: 9.72397\n",
- "Epoch 410/500 total: 3.70021, -LL: 3.64946, prior: 0.83012, aleatoric unc.: 9.72245\n",
- "Epoch 411/500 total: 3.69402, -LL: 3.61718, prior: 0.82774, aleatoric unc.: 9.70823\n",
- "Epoch 412/500 total: 3.70567, -LL: 3.61743, prior: 0.82851, aleatoric unc.: 9.71849\n",
- "Epoch 413/500 total: 3.70361, -LL: 3.64554, prior: 0.82617, aleatoric unc.: 9.72331\n",
- "Epoch 414/500 total: 3.69468, -LL: 3.60278, prior: 0.82620, aleatoric unc.: 9.71184\n",
- "Epoch 415/500 total: 3.70510, -LL: 3.64241, prior: 0.82747, aleatoric unc.: 9.72071\n",
- "Epoch 416/500 total: 3.70178, -LL: 3.59014, prior: 0.83144, aleatoric unc.: 9.72354\n",
- "Epoch 417/500 total: 3.69967, -LL: 3.63795, prior: 0.83206, aleatoric unc.: 9.71923\n",
- "Epoch 418/500 total: 3.69828, -LL: 3.60308, prior: 0.82796, aleatoric unc.: 9.71243\n",
- "Epoch 419/500 total: 3.70307, -LL: 3.66544, prior: 0.82524, aleatoric unc.: 9.71768\n",
- "Epoch 420/500 total: 3.70183, -LL: 3.61180, prior: 0.82254, aleatoric unc.: 9.72192\n",
- "Epoch 421/500 total: 3.69221, -LL: 3.63945, prior: 0.82239, aleatoric unc.: 9.70423\n",
- "Epoch 422/500 total: 3.69980, -LL: 3.61604, prior: 0.82302, aleatoric unc.: 9.70583\n",
- "Epoch 423/500 total: 3.69928, -LL: 3.63499, prior: 0.81947, aleatoric unc.: 9.70428\n",
- "Epoch 424/500 total: 3.70064, -LL: 3.64438, prior: 0.82250, aleatoric unc.: 9.70499\n",
- "Epoch 425/500 total: 3.69506, -LL: 3.61971, prior: 0.82166, aleatoric unc.: 9.69757\n",
- "Epoch 426/500 total: 3.70398, -LL: 3.62597, prior: 0.82278, aleatoric unc.: 9.70802\n",
- "Epoch 427/500 total: 3.70216, -LL: 3.65498, prior: 0.81911, aleatoric unc.: 9.71137\n",
- "Epoch 428/500 total: 3.70190, -LL: 3.64064, prior: 0.81833, aleatoric unc.: 9.71579\n",
- "Epoch 429/500 total: 3.70573, -LL: 3.66083, prior: 0.81893, aleatoric unc.: 9.72434\n",
- "Epoch 430/500 total: 3.69885, -LL: 3.65177, prior: 0.82123, aleatoric unc.: 9.72031\n",
- "Epoch 431/500 total: 3.70198, -LL: 3.67658, prior: 0.81868, aleatoric unc.: 9.72134\n",
- "Epoch 432/500 total: 3.70692, -LL: 3.63311, prior: 0.81943, aleatoric unc.: 9.73138\n",
- "Epoch 433/500 total: 3.70009, -LL: 3.59875, prior: 0.81951, aleatoric unc.: 9.72938\n",
- "Epoch 434/500 total: 3.69864, -LL: 3.63859, prior: 0.82302, aleatoric unc.: 9.72290\n",
- "Epoch 435/500 total: 3.69655, -LL: 3.66607, prior: 0.82137, aleatoric unc.: 9.71333\n",
- "Epoch 436/500 total: 3.69973, -LL: 3.65163, prior: 0.81886, aleatoric unc.: 9.71366\n",
- "Epoch 437/500 total: 3.69769, -LL: 3.68498, prior: 0.81805, aleatoric unc.: 9.70730\n",
- "Epoch 438/500 total: 3.69672, -LL: 3.64131, prior: 0.81733, aleatoric unc.: 9.70155\n",
- "Epoch 439/500 total: 3.69554, -LL: 3.62049, prior: 0.82319, aleatoric unc.: 9.69490\n",
- "Epoch 440/500 total: 3.69749, -LL: 3.62081, prior: 0.82234, aleatoric unc.: 9.69433\n",
- "Epoch 441/500 total: 3.70329, -LL: 3.59532, prior: 0.82169, aleatoric unc.: 9.70249\n",
- "Epoch 442/500 total: 3.69808, -LL: 3.62759, prior: 0.82254, aleatoric unc.: 9.70274\n",
- "Epoch 443/500 total: 3.70494, -LL: 3.65422, prior: 0.82270, aleatoric unc.: 9.71221\n",
- "Epoch 444/500 total: 3.69976, -LL: 3.65673, prior: 0.82426, aleatoric unc.: 9.71188\n",
- "Epoch 445/500 total: 3.70325, -LL: 3.64046, prior: 0.82422, aleatoric unc.: 9.71596\n",
- "Epoch 446/500 total: 3.70594, -LL: 3.65127, prior: 0.82255, aleatoric unc.: 9.72795\n",
- "Epoch 447/500 total: 3.70256, -LL: 3.65205, prior: 0.82299, aleatoric unc.: 9.72941\n",
- "Epoch 448/500 total: 3.70255, -LL: 3.66160, prior: 0.82127, aleatoric unc.: 9.73019\n",
- "Epoch 449/500 total: 3.70477, -LL: 3.65332, prior: 0.82186, aleatoric unc.: 9.73749\n",
- "Epoch 450/500 total: 3.69821, -LL: 3.62343, prior: 0.82277, aleatoric unc.: 9.72872\n",
- "Epoch 451/500 total: 3.69862, -LL: 3.61988, prior: 0.81971, aleatoric unc.: 9.72094\n",
- "Epoch 452/500 total: 3.69956, -LL: 3.64692, prior: 0.82058, aleatoric unc.: 9.71754\n",
- "Epoch 453/500 total: 3.68746, -LL: 3.61281, prior: 0.81960, aleatoric unc.: 9.69424\n",
- "Epoch 454/500 total: 3.69136, -LL: 3.61534, prior: 0.82130, aleatoric unc.: 9.67839\n",
- "Epoch 455/500 total: 3.70947, -LL: 3.63629, prior: 0.82276, aleatoric unc.: 9.70095\n",
- "Epoch 456/500 total: 3.70455, -LL: 3.62145, prior: 0.82456, aleatoric unc.: 9.71287\n",
- "Epoch 457/500 total: 3.69434, -LL: 3.64094, prior: 0.82408, aleatoric unc.: 9.70524\n",
- "Epoch 458/500 total: 3.69588, -LL: 3.62607, prior: 0.82356, aleatoric unc.: 9.69614\n",
- "Epoch 459/500 total: 3.69965, -LL: 3.67129, prior: 0.82353, aleatoric unc.: 9.69692\n",
- "Epoch 460/500 total: 3.69278, -LL: 3.64340, prior: 0.82238, aleatoric unc.: 9.68522\n",
- "Epoch 461/500 total: 3.69769, -LL: 3.66663, prior: 0.82365, aleatoric unc.: 9.68477\n",
- "Epoch 462/500 total: 3.70174, -LL: 3.64461, prior: 0.82374, aleatoric unc.: 9.69469\n",
- "Epoch 463/500 total: 3.69422, -LL: 3.62371, prior: 0.82634, aleatoric unc.: 9.68775\n",
- "Epoch 464/500 total: 3.70086, -LL: 3.65318, prior: 0.82430, aleatoric unc.: 9.69298\n",
- "Epoch 465/500 total: 3.69787, -LL: 3.66150, prior: 0.81959, aleatoric unc.: 9.69327\n",
- "Epoch 466/500 total: 3.69348, -LL: 3.64051, prior: 0.81754, aleatoric unc.: 9.68517\n",
- "Epoch 467/500 total: 3.70298, -LL: 3.65390, prior: 0.81789, aleatoric unc.: 9.69441\n",
- "Epoch 468/500 total: 3.69817, -LL: 3.65901, prior: 0.81541, aleatoric unc.: 9.69768\n",
- "Epoch 469/500 total: 3.69301, -LL: 3.63411, prior: 0.81612, aleatoric unc.: 9.68669\n",
- "Epoch 470/500 total: 3.70037, -LL: 3.61972, prior: 0.81542, aleatoric unc.: 9.69086\n",
- "Epoch 471/500 total: 3.70139, -LL: 3.60899, prior: 0.81560, aleatoric unc.: 9.69815\n",
- "Epoch 472/500 total: 3.70118, -LL: 3.68662, prior: 0.81407, aleatoric unc.: 9.70126\n",
- "Epoch 473/500 total: 3.70042, -LL: 3.64964, prior: 0.81481, aleatoric unc.: 9.70599\n",
- "Epoch 474/500 total: 3.70516, -LL: 3.62561, prior: 0.81684, aleatoric unc.: 9.71484\n",
- "Epoch 475/500 total: 3.69569, -LL: 3.62760, prior: 0.81538, aleatoric unc.: 9.70852\n",
- "Epoch 476/500 total: 3.69344, -LL: 3.63575, prior: 0.81317, aleatoric unc.: 9.69601\n",
- "Epoch 477/500 total: 3.69725, -LL: 3.66014, prior: 0.81203, aleatoric unc.: 9.69300\n",
- "Epoch 478/500 total: 3.70594, -LL: 3.65619, prior: 0.81437, aleatoric unc.: 9.70621\n",
- "Epoch 479/500 total: 3.69992, -LL: 3.61516, prior: 0.81284, aleatoric unc.: 9.70868\n",
- "Epoch 480/500 total: 3.69582, -LL: 3.64135, prior: 0.81684, aleatoric unc.: 9.70021\n",
- "Epoch 481/500 total: 3.69739, -LL: 3.60619, prior: 0.81517, aleatoric unc.: 9.70025\n",
- "Epoch 482/500 total: 3.70488, -LL: 3.63401, prior: 0.81520, aleatoric unc.: 9.70766\n",
- "Epoch 483/500 total: 3.69736, -LL: 3.61727, prior: 0.81478, aleatoric unc.: 9.70594\n",
- "Epoch 484/500 total: 3.70235, -LL: 3.63803, prior: 0.81578, aleatoric unc.: 9.71074\n",
- "Epoch 485/500 total: 3.70031, -LL: 3.64106, prior: 0.81726, aleatoric unc.: 9.71344\n"
+ "Epoch 386/500 total: 3.73416, -LL: 3.81177, prior: 0.88866, aleatoric unc.: 10.00876\n",
+ "Epoch 387/500 total: 3.72839, -LL: 3.81913, prior: 0.88887, aleatoric unc.: 10.00420\n",
+ "Epoch 388/500 total: 3.72809, -LL: 3.85305, prior: 0.88874, aleatoric unc.: 10.00104\n",
+ "Epoch 389/500 total: 3.72773, -LL: 3.82120, prior: 0.88876, aleatoric unc.: 9.99688\n",
+ "Epoch 390/500 total: 3.73334, -LL: 3.82726, prior: 0.88548, aleatoric unc.: 10.00346\n",
+ "Epoch 391/500 total: 3.73490, -LL: 3.82492, prior: 0.88685, aleatoric unc.: 10.01549\n",
+ "Epoch 392/500 total: 3.72916, -LL: 3.84311, prior: 0.88795, aleatoric unc.: 10.00856\n",
+ "Epoch 393/500 total: 3.73429, -LL: 3.82947, prior: 0.88792, aleatoric unc.: 10.01743\n",
+ "Epoch 394/500 total: 3.73181, -LL: 3.81629, prior: 0.88642, aleatoric unc.: 10.01939\n",
+ "Epoch 395/500 total: 3.72808, -LL: 3.83636, prior: 0.88873, aleatoric unc.: 10.01162\n",
+ "Epoch 396/500 total: 3.72751, -LL: 3.82526, prior: 0.88703, aleatoric unc.: 10.00507\n",
+ "Epoch 397/500 total: 3.73501, -LL: 3.82711, prior: 0.88789, aleatoric unc.: 10.01148\n",
+ "Epoch 398/500 total: 3.72396, -LL: 3.82852, prior: 0.88770, aleatoric unc.: 9.99962\n",
+ "Epoch 399/500 total: 3.72896, -LL: 3.83363, prior: 0.88469, aleatoric unc.: 9.99559\n",
+ "Epoch 400/500 total: 3.73358, -LL: 3.84655, prior: 0.88321, aleatoric unc.: 10.00445\n",
+ "Epoch 401/500 total: 3.73450, -LL: 3.84568, prior: 0.88243, aleatoric unc.: 10.01549\n",
+ "Epoch 402/500 total: 3.73173, -LL: 3.82600, prior: 0.88310, aleatoric unc.: 10.01693\n",
+ "Epoch 403/500 total: 3.73635, -LL: 3.83453, prior: 0.88487, aleatoric unc.: 10.02586\n",
+ "Epoch 404/500 total: 3.72528, -LL: 3.83294, prior: 0.88362, aleatoric unc.: 10.01279\n",
+ "Epoch 405/500 total: 3.72882, -LL: 3.80771, prior: 0.88225, aleatoric unc.: 10.00938\n",
+ "Epoch 406/500 total: 3.73199, -LL: 3.86916, prior: 0.87739, aleatoric unc.: 10.00910\n",
+ "Epoch 407/500 total: 3.72269, -LL: 3.82055, prior: 0.87675, aleatoric unc.: 9.99726\n",
+ "Epoch 408/500 total: 3.72756, -LL: 3.81504, prior: 0.87524, aleatoric unc.: 9.99008\n",
+ "Epoch 409/500 total: 3.72625, -LL: 3.84240, prior: 0.87482, aleatoric unc.: 9.98890\n",
+ "Epoch 410/500 total: 3.73310, -LL: 3.82112, prior: 0.87371, aleatoric unc.: 9.99657\n",
+ "Epoch 411/500 total: 3.73343, -LL: 3.81922, prior: 0.87862, aleatoric unc.: 10.00432\n",
+ "Epoch 412/500 total: 3.72648, -LL: 3.83221, prior: 0.87685, aleatoric unc.: 9.99893\n",
+ "Epoch 413/500 total: 3.73209, -LL: 3.83570, prior: 0.88170, aleatoric unc.: 10.00689\n",
+ "Epoch 414/500 total: 3.73212, -LL: 3.84502, prior: 0.88266, aleatoric unc.: 10.00734\n",
+ "Epoch 415/500 total: 3.73225, -LL: 3.82004, prior: 0.88298, aleatoric unc.: 10.01361\n",
+ "Epoch 416/500 total: 3.73441, -LL: 3.82674, prior: 0.87963, aleatoric unc.: 10.02181\n",
+ "Epoch 417/500 total: 3.72539, -LL: 3.81829, prior: 0.88259, aleatoric unc.: 10.00947\n",
+ "Epoch 418/500 total: 3.73125, -LL: 3.82794, prior: 0.88510, aleatoric unc.: 10.00791\n",
+ "Epoch 419/500 total: 3.72788, -LL: 3.83194, prior: 0.88230, aleatoric unc.: 10.00315\n",
+ "Epoch 420/500 total: 3.73432, -LL: 3.83581, prior: 0.88245, aleatoric unc.: 10.01237\n",
+ "Epoch 421/500 total: 3.72825, -LL: 3.83660, prior: 0.87966, aleatoric unc.: 10.00960\n",
+ "Epoch 422/500 total: 3.73042, -LL: 3.83286, prior: 0.88341, aleatoric unc.: 10.00669\n",
+ "Epoch 423/500 total: 3.72403, -LL: 3.82759, prior: 0.88128, aleatoric unc.: 9.99594\n",
+ "Epoch 424/500 total: 3.72736, -LL: 3.83538, prior: 0.87860, aleatoric unc.: 9.98931\n",
+ "Epoch 425/500 total: 3.73519, -LL: 3.83184, prior: 0.87881, aleatoric unc.: 10.00450\n",
+ "Epoch 426/500 total: 3.72966, -LL: 3.82760, prior: 0.88036, aleatoric unc.: 10.00496\n",
+ "Epoch 427/500 total: 3.73070, -LL: 3.81873, prior: 0.87821, aleatoric unc.: 10.00390\n",
+ "Epoch 428/500 total: 3.73247, -LL: 3.82698, prior: 0.87670, aleatoric unc.: 10.00907\n",
+ "Epoch 429/500 total: 3.73084, -LL: 3.84893, prior: 0.87818, aleatoric unc.: 10.00802\n",
+ "Epoch 430/500 total: 3.72784, -LL: 3.83185, prior: 0.87821, aleatoric unc.: 10.00394\n",
+ "Epoch 431/500 total: 3.72422, -LL: 3.81806, prior: 0.87927, aleatoric unc.: 9.99349\n",
+ "Epoch 432/500 total: 3.73010, -LL: 3.83658, prior: 0.87893, aleatoric unc.: 9.99328\n",
+ "Epoch 433/500 total: 3.73329, -LL: 3.82127, prior: 0.87941, aleatoric unc.: 10.00461\n",
+ "Epoch 434/500 total: 3.72406, -LL: 3.83071, prior: 0.87800, aleatoric unc.: 9.99093\n",
+ "Epoch 435/500 total: 3.73008, -LL: 3.83305, prior: 0.87833, aleatoric unc.: 9.99316\n",
+ "Epoch 436/500 total: 3.72957, -LL: 3.82030, prior: 0.88042, aleatoric unc.: 9.99453\n",
+ "Epoch 437/500 total: 3.72984, -LL: 3.83393, prior: 0.87976, aleatoric unc.: 9.99500\n",
+ "Epoch 438/500 total: 3.72609, -LL: 3.82555, prior: 0.87855, aleatoric unc.: 9.98869\n",
+ "Epoch 439/500 total: 3.73091, -LL: 3.82861, prior: 0.87551, aleatoric unc.: 9.99418\n",
+ "Epoch 440/500 total: 3.73153, -LL: 3.83980, prior: 0.87521, aleatoric unc.: 9.99892\n",
+ "Epoch 441/500 total: 3.72319, -LL: 3.83642, prior: 0.87585, aleatoric unc.: 9.98656\n",
+ "Epoch 442/500 total: 3.72476, -LL: 3.81737, prior: 0.87802, aleatoric unc.: 9.97697\n",
+ "Epoch 443/500 total: 3.73107, -LL: 3.82724, prior: 0.87879, aleatoric unc.: 9.98574\n",
+ "Epoch 444/500 total: 3.72469, -LL: 3.82348, prior: 0.87504, aleatoric unc.: 9.97848\n",
+ "Epoch 445/500 total: 3.72959, -LL: 3.83049, prior: 0.87477, aleatoric unc.: 9.98287\n",
+ "Epoch 446/500 total: 3.72359, -LL: 3.81934, prior: 0.87120, aleatoric unc.: 9.97612\n",
+ "Epoch 447/500 total: 3.73261, -LL: 3.83914, prior: 0.87673, aleatoric unc.: 9.98519\n",
+ "Epoch 448/500 total: 3.72847, -LL: 3.83839, prior: 0.87406, aleatoric unc.: 9.98692\n",
+ "Epoch 449/500 total: 3.72623, -LL: 3.82678, prior: 0.87109, aleatoric unc.: 9.98354\n",
+ "Epoch 450/500 total: 3.72840, -LL: 3.82360, prior: 0.87192, aleatoric unc.: 9.98230\n",
+ "Epoch 451/500 total: 3.73242, -LL: 3.83121, prior: 0.87329, aleatoric unc.: 9.99246\n",
+ "Epoch 452/500 total: 3.72609, -LL: 3.84144, prior: 0.87455, aleatoric unc.: 9.98621\n",
+ "Epoch 453/500 total: 3.72770, -LL: 3.83764, prior: 0.87255, aleatoric unc.: 9.98583\n",
+ "Epoch 454/500 total: 3.72808, -LL: 3.84712, prior: 0.87781, aleatoric unc.: 9.98613\n",
+ "Epoch 455/500 total: 3.73070, -LL: 3.82634, prior: 0.87533, aleatoric unc.: 9.98968\n",
+ "Epoch 456/500 total: 3.73363, -LL: 3.82287, prior: 0.87563, aleatoric unc.: 10.00168\n",
+ "Epoch 457/500 total: 3.72727, -LL: 3.81423, prior: 0.87800, aleatoric unc.: 9.99531\n",
+ "Epoch 458/500 total: 3.73414, -LL: 3.82865, prior: 0.87807, aleatoric unc.: 10.00688\n",
+ "Epoch 459/500 total: 3.72611, -LL: 3.83435, prior: 0.87671, aleatoric unc.: 9.99795\n",
+ "Epoch 460/500 total: 3.73275, -LL: 3.83322, prior: 0.87540, aleatoric unc.: 10.00565\n",
+ "Epoch 461/500 total: 3.72783, -LL: 3.82594, prior: 0.87547, aleatoric unc.: 9.99865\n",
+ "Epoch 462/500 total: 3.73166, -LL: 3.81160, prior: 0.87461, aleatoric unc.: 10.00305\n",
+ "Epoch 463/500 total: 3.72671, -LL: 3.81470, prior: 0.87593, aleatoric unc.: 9.99850\n",
+ "Epoch 464/500 total: 3.72499, -LL: 3.81690, prior: 0.87581, aleatoric unc.: 9.98839\n",
+ "Epoch 465/500 total: 3.73228, -LL: 3.82494, prior: 0.87802, aleatoric unc.: 9.99579\n",
+ "Epoch 466/500 total: 3.72764, -LL: 3.83893, prior: 0.87525, aleatoric unc.: 9.99090\n",
+ "Epoch 467/500 total: 3.72456, -LL: 3.81647, prior: 0.87726, aleatoric unc.: 9.98477\n",
+ "Epoch 468/500 total: 3.72660, -LL: 3.84040, prior: 0.87775, aleatoric unc.: 9.97989\n",
+ "Epoch 469/500 total: 3.73049, -LL: 3.82220, prior: 0.87773, aleatoric unc.: 9.98726\n",
+ "Epoch 470/500 total: 3.72854, -LL: 3.86049, prior: 0.87588, aleatoric unc.: 9.98729\n",
+ "Epoch 471/500 total: 3.73255, -LL: 3.82695, prior: 0.87574, aleatoric unc.: 9.99501\n",
+ "Epoch 472/500 total: 3.72359, -LL: 3.82691, prior: 0.88025, aleatoric unc.: 9.98528\n",
+ "Epoch 473/500 total: 3.73089, -LL: 3.82909, prior: 0.87920, aleatoric unc.: 9.99031\n",
+ "Epoch 474/500 total: 3.73378, -LL: 3.83185, prior: 0.87792, aleatoric unc.: 10.00215\n",
+ "Epoch 475/500 total: 3.73113, -LL: 3.84989, prior: 0.88087, aleatoric unc.: 10.00428\n",
+ "Epoch 476/500 total: 3.72500, -LL: 3.81862, prior: 0.87891, aleatoric unc.: 9.99466\n",
+ "Epoch 477/500 total: 3.72598, -LL: 3.82432, prior: 0.87830, aleatoric unc.: 9.98845\n",
+ "Epoch 478/500 total: 3.72689, -LL: 3.81920, prior: 0.87943, aleatoric unc.: 9.98351\n",
+ "Epoch 479/500 total: 3.72763, -LL: 3.85005, prior: 0.87979, aleatoric unc.: 9.98261\n",
+ "Epoch 480/500 total: 3.72894, -LL: 3.82676, prior: 0.88107, aleatoric unc.: 9.98493\n",
+ "Epoch 481/500 total: 3.72996, -LL: 3.82628, prior: 0.88181, aleatoric unc.: 9.98893\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
- "Epoch 486/500 total: 3.70281, -LL: 3.65334, prior: 0.81765, aleatoric unc.: 9.71675\n",
- "Epoch 487/500 total: 3.69665, -LL: 3.62427, prior: 0.81798, aleatoric unc.: 9.71068\n",
- "Epoch 488/500 total: 3.69354, -LL: 3.60938, prior: 0.81778, aleatoric unc.: 9.69865\n",
- "Epoch 489/500 total: 3.69664, -LL: 3.66371, prior: 0.81562, aleatoric unc.: 9.69401\n",
- "Epoch 490/500 total: 3.70017, -LL: 3.61261, prior: 0.81859, aleatoric unc.: 9.69709\n",
- "Epoch 491/500 total: 3.70181, -LL: 3.64116, prior: 0.81858, aleatoric unc.: 9.70037\n",
- "Epoch 492/500 total: 3.69507, -LL: 3.62122, prior: 0.81482, aleatoric unc.: 9.69759\n",
- "Epoch 493/500 total: 3.69890, -LL: 3.65301, prior: 0.81908, aleatoric unc.: 9.69581\n",
- "Epoch 494/500 total: 3.70058, -LL: 3.65166, prior: 0.81909, aleatoric unc.: 9.69850\n",
- "Epoch 495/500 total: 3.69788, -LL: 3.62267, prior: 0.81817, aleatoric unc.: 9.70015\n",
- "Epoch 496/500 total: 3.69267, -LL: 3.64171, prior: 0.81855, aleatoric unc.: 9.68762\n",
- "Epoch 497/500 total: 3.70465, -LL: 3.66362, prior: 0.81682, aleatoric unc.: 9.70045\n",
- "Epoch 498/500 total: 3.70106, -LL: 3.66015, prior: 0.81733, aleatoric unc.: 9.70227\n",
- "Epoch 499/500 total: 3.69741, -LL: 3.64281, prior: 0.81737, aleatoric unc.: 9.70153\n"
+ "Epoch 482/500 total: 3.72968, -LL: 3.83054, prior: 0.88382, aleatoric unc.: 9.99294\n",
+ "Epoch 483/500 total: 3.72980, -LL: 3.82583, prior: 0.88426, aleatoric unc.: 9.99362\n",
+ "Epoch 484/500 total: 3.73002, -LL: 3.82194, prior: 0.88617, aleatoric unc.: 9.99726\n",
+ "Epoch 485/500 total: 3.72822, -LL: 3.84083, prior: 0.88546, aleatoric unc.: 9.99438\n",
+ "Epoch 486/500 total: 3.72565, -LL: 3.81954, prior: 0.88737, aleatoric unc.: 9.98701\n",
+ "Epoch 487/500 total: 3.72438, -LL: 3.83046, prior: 0.88298, aleatoric unc.: 9.97804\n",
+ "Epoch 488/500 total: 3.73051, -LL: 3.84720, prior: 0.88185, aleatoric unc.: 9.98359\n",
+ "Epoch 489/500 total: 3.73112, -LL: 3.83173, prior: 0.88252, aleatoric unc.: 9.99134\n",
+ "Epoch 490/500 total: 3.72454, -LL: 3.83466, prior: 0.88286, aleatoric unc.: 9.98333\n",
+ "Epoch 491/500 total: 3.72815, -LL: 3.83819, prior: 0.88356, aleatoric unc.: 9.98163\n",
+ "Epoch 492/500 total: 3.72773, -LL: 3.80841, prior: 0.88449, aleatoric unc.: 9.98276\n",
+ "Epoch 493/500 total: 3.72504, -LL: 3.82441, prior: 0.88649, aleatoric unc.: 9.97645\n",
+ "Epoch 494/500 total: 3.73343, -LL: 3.82006, prior: 0.88583, aleatoric unc.: 9.98840\n",
+ "Epoch 495/500 total: 3.72690, -LL: 3.81129, prior: 0.88969, aleatoric unc.: 9.98657\n",
+ "Epoch 496/500 total: 3.72634, -LL: 3.83957, prior: 0.88817, aleatoric unc.: 9.98136\n",
+ "Epoch 497/500 total: 3.72504, -LL: 3.81558, prior: 0.88621, aleatoric unc.: 9.97691\n",
+ "Epoch 498/500 total: 3.72726, -LL: 3.83550, prior: 0.88450, aleatoric unc.: 9.97391\n",
+ "Epoch 499/500 total: 3.72785, -LL: 3.83303, prior: 0.88575, aleatoric unc.: 9.97703\n"
]
}
],
@@ -3286,7 +3176,7 @@
},
{
"cell_type": "code",
- "execution_count": 17,
+ "execution_count": 18,
"id": "a3d244e2",
"metadata": {},
"outputs": [],
@@ -3310,7 +3200,7 @@
},
{
"cell_type": "code",
- "execution_count": 18,
+ "execution_count": 19,
"id": "4a56960d",
"metadata": {},
"outputs": [],
@@ -3332,7 +3222,7 @@
},
{
"cell_type": "code",
- "execution_count": 19,
+ "execution_count": 20,
"id": "4d01c41f",
"metadata": {},
"outputs": [
@@ -3340,7 +3230,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "Average epistemic uncertainty: 0.83653456\n"
+ "Average epistemic uncertainty: 0.7480032\n"
]
}
],
@@ -3350,7 +3240,7 @@
},
{
"cell_type": "code",
- "execution_count": 20,
+ "execution_count": 21,
"id": "67d456a1",
"metadata": {},
"outputs": [
@@ -3358,7 +3248,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "Aleatoric uncertainty: 9.7015295\n"
+ "Aleatoric uncertainty: 9.977034\n"
]
}
],
@@ -3380,7 +3270,7 @@
},
{
"cell_type": "code",
- "execution_count": 21,
+ "execution_count": 22,
"id": "8b9142e8",
"metadata": {
"scrolled": false
@@ -3636,10 +3526,6 @@
" 'mouseup',\n",
" on_mouse_event_closure('button_release')\n",
" );\n",
- " rubberband_canvas.addEventListener(\n",
- " 'dblclick',\n",
- " on_mouse_event_closure('dblclick')\n",
- " );\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband_canvas.addEventListener(\n",
" 'mousemove',\n",
@@ -3897,14 +3783,11 @@
"mpl.figure.prototype._make_on_message_function = function (fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
- " var img = evt.data;\n",
- " if (img.type !== 'image/png') {\n",
- " /* FIXME: We get \"Resource interpreted as Image but\n",
- " * transferred with MIME type text/plain:\" errors on\n",
- " * Chrome. But how to set the MIME type? It doesn't seem\n",
- " * to be part of the websocket stream */\n",
- " img.type = 'image/png';\n",
- " }\n",
+ " /* FIXME: We get \"Resource interpreted as Image but\n",
+ " * transferred with MIME type text/plain:\" errors on\n",
+ " * Chrome. But how to set the MIME type? It doesn't seem\n",
+ " * to be part of the websocket stream */\n",
+ " evt.data.type = 'image/png';\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
@@ -3914,7 +3797,7 @@
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
- " img\n",
+ " evt.data\n",
" );\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
@@ -4033,10 +3916,10 @@
"mpl.figure.prototype.key_event = function (event, name) {\n",
" // Prevent repeat events\n",
" if (name === 'key_press') {\n",
- " if (event.key === this._key) {\n",
+ " if (event.which === this._key) {\n",
" return;\n",
" } else {\n",
- " this._key = event.key;\n",
+ " this._key = event.which;\n",
" }\n",
" }\n",
" if (name === 'key_release') {\n",
@@ -4044,17 +3927,18 @@
" }\n",
"\n",
" var value = '';\n",
- " if (event.ctrlKey && event.key !== 'Control') {\n",
+ " if (event.ctrlKey && event.which !== 17) {\n",
" value += 'ctrl+';\n",
" }\n",
- " else if (event.altKey && event.key !== 'Alt') {\n",
+ " if (event.altKey && event.which !== 18) {\n",
" value += 'alt+';\n",
" }\n",
- " else if (event.shiftKey && event.key !== 'Shift') {\n",
+ " if (event.shiftKey && event.which !== 16) {\n",
" value += 'shift+';\n",
" }\n",
"\n",
- " value += 'k' + event.key;\n",
+ " value += 'k';\n",
+ " value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
@@ -4079,7 +3963,7 @@
"var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
- "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
+ "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";/* global mpl */\n",
"\n",
@@ -4089,19 +3973,6 @@
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
- " ws.binaryType = comm.kernel.ws.binaryType;\n",
- " ws.readyState = comm.kernel.ws.readyState;\n",
- " function updateReadyState(_event) {\n",
- " if (comm.kernel.ws) {\n",
- " ws.readyState = comm.kernel.ws.readyState;\n",
- " } else {\n",
- " ws.readyState = 3; // Closed state.\n",
- " }\n",
- " }\n",
- " comm.kernel.ws.addEventListener('open', updateReadyState);\n",
- " comm.kernel.ws.addEventListener('close', updateReadyState);\n",
- " comm.kernel.ws.addEventListener('error', updateReadyState);\n",
- "\n",
" ws.close = function () {\n",
" comm.close();\n",
" };\n",
@@ -4112,14 +3983,8 @@
" // Register the callback with on_msg.\n",
" comm.on_msg(function (msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
- " var data = msg['content']['data'];\n",
- " if (data['blob'] !== undefined) {\n",
- " data = {\n",
- " data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
- " };\n",
- " }\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
- " ws.onmessage(data);\n",
+ " ws.onmessage(msg['content']['data']);\n",
" });\n",
" return ws;\n",
"};\n",
@@ -4372,7 +4237,7 @@
{
"data": {
"text/html": [
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\" 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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
@@ -4401,8 +4266,7 @@
"source": [
"### Contact us at the EuXFEL Data Analysis group at any time if you need help analysing your data!\n",
"\n",
- "#### Danilo Ferreira de Lima: danilo.enoque.ferreira.de.lima@xfel.eu\n",
- "#### Arman Davtyan: arman.davtyan@xfel.eu"
+ "#### Data Analysis group: da@xfel.eu"
]
},
{
@@ -4430,7 +4294,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.7.10"
+ "version": "3.6.13"
}
},
"nbformat": 4,
diff --git a/Support Vector Machines.ipynb b/Support Vector Machines.ipynb
index abce0ee..40ad473 100644
--- a/Support Vector Machines.ipynb
+++ b/Support Vector Machines.ipynb
@@ -69,7 +69,7 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": 1,
"id": "44ca341e",
"metadata": {},
"outputs": [
@@ -77,20 +77,20 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "Requirement already satisfied: numpy in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (1.19.2)\n",
- "Requirement already satisfied: scikit-learn in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (0.24.2)\n",
- "Requirement already satisfied: pandas in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (1.3.0)\n",
- "Requirement already satisfied: matplotlib in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (3.4.2)\n",
- "Requirement already satisfied: joblib>=0.11 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from scikit-learn) (1.0.1)\n",
- "Requirement already satisfied: scipy>=0.19.1 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from scikit-learn) (1.6.2)\n",
- "Requirement already satisfied: threadpoolctl>=2.0.0 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from scikit-learn) (2.2.0)\n",
- "Requirement already satisfied: python-dateutil>=2.7.3 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from pandas) (2.8.2)\n",
- "Requirement already satisfied: pytz>=2017.3 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from pandas) (2021.1)\n",
- "Requirement already satisfied: six>=1.5 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from python-dateutil>=2.7.3->pandas) (1.16.0)\n",
- "Requirement already satisfied: kiwisolver>=1.0.1 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from matplotlib) (1.3.1)\n",
- "Requirement already satisfied: pillow>=6.2.0 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from matplotlib) (8.3.1)\n",
- "Requirement already satisfied: pyparsing>=2.2.1 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from matplotlib) (2.4.7)\n",
- "Requirement already satisfied: cycler>=0.10 in /home/danilo/miniconda3/envs/mlmkl/lib/python3.7/site-packages (from matplotlib) (0.10.0)\n"
+ "Requirement already satisfied: numpy in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (1.19.2)\n",
+ "Requirement already satisfied: scikit-learn in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (0.24.2)\n",
+ "Requirement already satisfied: pandas in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (1.1.5)\n",
+ "Requirement already satisfied: matplotlib in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (3.3.4)\n",
+ "Requirement already satisfied: joblib>=0.11 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from scikit-learn) (1.0.1)\n",
+ "Requirement already satisfied: threadpoolctl>=2.0.0 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from scikit-learn) (2.2.0)\n",
+ "Requirement already satisfied: scipy>=0.19.1 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from scikit-learn) (1.5.2)\n",
+ "Requirement already satisfied: python-dateutil>=2.7.3 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from pandas) (2.8.2)\n",
+ "Requirement already satisfied: pytz>=2017.2 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from pandas) (2021.3)\n",
+ "Requirement already satisfied: cycler>=0.10 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from matplotlib) (0.11.0)\n",
+ "Requirement already satisfied: kiwisolver>=1.0.1 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from matplotlib) (1.3.1)\n",
+ "Requirement already satisfied: pillow>=6.2.0 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from matplotlib) (8.3.1)\n",
+ "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.3 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from matplotlib) (3.0.4)\n",
+ "Requirement already satisfied: six>=1.5 in /home/daniloefl/miniconda3/envs/mltut/lib/python3.6/site-packages (from python-dateutil>=2.7.3->pandas) (1.16.0)\n"
]
}
],
@@ -100,13 +100,14 @@
},
{
"cell_type": "code",
- "execution_count": 1,
+ "execution_count": 2,
"id": "300cf8d3",
"metadata": {},
"outputs": [],
"source": [
+ "%matplotlib notebook\n",
+ "\n",
"import matplotlib.pyplot as plt\n",
- "%matplotlib inline\n",
"\n",
"import pandas as pd\n",
"import numpy as np\n",
@@ -123,7 +124,7 @@
},
{
"cell_type": "code",
- "execution_count": 25,
+ "execution_count": 3,
"id": "4959a292",
"metadata": {},
"outputs": [],
@@ -140,7 +141,7 @@
},
{
"cell_type": "code",
- "execution_count": 26,
+ "execution_count": 4,
"id": "82929490",
"metadata": {},
"outputs": [],
@@ -159,7 +160,7 @@
},
{
"cell_type": "code",
- "execution_count": 27,
+ "execution_count": 5,
"id": "024fb65a",
"metadata": {},
"outputs": [
@@ -192,32 +193,32 @@
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
- " <td>0.993649</td>\n",
- " <td>1.630545</td>\n",
+ " <td>1.985442</td>\n",
+ " <td>0.987135</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
- " <td>1.907532</td>\n",
- " <td>1.870662</td>\n",
+ " <td>1.128882</td>\n",
+ " <td>1.217191</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
- " <td>2.121213</td>\n",
- " <td>1.848977</td>\n",
+ " <td>2.941344</td>\n",
+ " <td>1.856144</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
- " <td>1.504255</td>\n",
- " <td>2.807217</td>\n",
+ " <td>1.956792</td>\n",
+ " <td>1.893925</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
- " <td>1.780940</td>\n",
- " <td>0.967064</td>\n",
+ " <td>2.596261</td>\n",
+ " <td>1.949837</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
@@ -228,32 +229,32 @@
" </tr>\n",
" <tr>\n",
" <th>1995</th>\n",
- " <td>-0.318836</td>\n",
- " <td>1.025854</td>\n",
+ " <td>-0.031483</td>\n",
+ " <td>1.113162</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1996</th>\n",
- " <td>0.711106</td>\n",
- " <td>1.369357</td>\n",
+ " <td>-0.904133</td>\n",
+ " <td>0.969933</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1997</th>\n",
- " <td>-0.827128</td>\n",
- " <td>0.722899</td>\n",
+ " <td>-0.837312</td>\n",
+ " <td>0.674358</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1998</th>\n",
- " <td>-1.047059</td>\n",
- " <td>1.136644</td>\n",
+ " <td>0.096271</td>\n",
+ " <td>0.977671</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1999</th>\n",
- " <td>-1.204980</td>\n",
- " <td>0.570485</td>\n",
+ " <td>-0.842105</td>\n",
+ " <td>1.131658</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" </tbody>\n",
@@ -263,22 +264,22 @@
],
"text/plain": [
" x y source\n",
- "0 0.993649 1.630545 0.0\n",
- "1 1.907532 1.870662 0.0\n",
- "2 2.121213 1.848977 0.0\n",
- "3 1.504255 2.807217 0.0\n",
- "4 1.780940 0.967064 0.0\n",
+ "0 1.985442 0.987135 0.0\n",
+ "1 1.128882 1.217191 0.0\n",
+ "2 2.941344 1.856144 0.0\n",
+ "3 1.956792 1.893925 0.0\n",
+ "4 2.596261 1.949837 0.0\n",
"... ... ... ...\n",
- "1995 -0.318836 1.025854 1.0\n",
- "1996 0.711106 1.369357 1.0\n",
- "1997 -0.827128 0.722899 1.0\n",
- "1998 -1.047059 1.136644 1.0\n",
- "1999 -1.204980 0.570485 1.0\n",
+ "1995 -0.031483 1.113162 1.0\n",
+ "1996 -0.904133 0.969933 1.0\n",
+ "1997 -0.837312 0.674358 1.0\n",
+ "1998 0.096271 0.977671 1.0\n",
+ "1999 -0.842105 1.131658 1.0\n",
"\n",
"[2000 rows x 3 columns]"
]
},
- "execution_count": 27,
+ "execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
@@ -297,20 +298,978 @@
},
{
"cell_type": "code",
- "execution_count": 28,
+ "execution_count": 6,
"id": "e63b38c5",
"metadata": {},
"outputs": [
{
"data": {
- "image/png": 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\n",
+ "application/javascript": [
+ "/* Put everything inside the global mpl namespace */\n",
+ "/* global mpl */\n",
+ "window.mpl = {};\n",
+ "\n",
+ "mpl.get_websocket_type = function () {\n",
+ " if (typeof WebSocket !== 'undefined') {\n",
+ " return WebSocket;\n",
+ " } else if (typeof MozWebSocket !== 'undefined') {\n",
+ " return MozWebSocket;\n",
+ " } else {\n",
+ " alert(\n",
+ " 'Your browser does not have WebSocket support. ' +\n",
+ " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+ " 'Firefox 4 and 5 are also supported but you ' +\n",
+ " 'have to enable WebSockets in about:config.'\n",
+ " );\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
+ " this.id = figure_id;\n",
+ "\n",
+ " this.ws = websocket;\n",
+ "\n",
+ " this.supports_binary = this.ws.binaryType !== undefined;\n",
+ "\n",
+ " if (!this.supports_binary) {\n",
+ " var warnings = document.getElementById('mpl-warnings');\n",
+ " if (warnings) {\n",
+ " warnings.style.display = 'block';\n",
+ " warnings.textContent =\n",
+ " 'This browser does not support binary websocket messages. ' +\n",
+ " 'Performance may be slow.';\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.imageObj = new Image();\n",
+ "\n",
+ " this.context = undefined;\n",
+ " this.message = undefined;\n",
+ " this.canvas = undefined;\n",
+ " this.rubberband_canvas = undefined;\n",
+ " this.rubberband_context = undefined;\n",
+ " this.format_dropdown = undefined;\n",
+ "\n",
+ " this.image_mode = 'full';\n",
+ "\n",
+ " this.root = document.createElement('div');\n",
+ " this.root.setAttribute('style', 'display: inline-block');\n",
+ " this._root_extra_style(this.root);\n",
+ "\n",
+ " parent_element.appendChild(this.root);\n",
+ "\n",
+ " this._init_header(this);\n",
+ " this._init_canvas(this);\n",
+ " this._init_toolbar(this);\n",
+ "\n",
+ " var fig = this;\n",
+ "\n",
+ " this.waiting = false;\n",
+ "\n",
+ " this.ws.onopen = function () {\n",
+ " fig.send_message('supports_binary', { value: fig.supports_binary });\n",
+ " fig.send_message('send_image_mode', {});\n",
+ " if (fig.ratio !== 1) {\n",
+ " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
+ " }\n",
+ " fig.send_message('refresh', {});\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onload = function () {\n",
+ " if (fig.image_mode === 'full') {\n",
+ " // Full images could contain transparency (where diff images\n",
+ " // almost always do), so we need to clear the canvas so that\n",
+ " // there is no ghosting.\n",
+ " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+ " }\n",
+ " fig.context.drawImage(fig.imageObj, 0, 0);\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onunload = function () {\n",
+ " fig.ws.close();\n",
+ " };\n",
+ "\n",
+ " this.ws.onmessage = this._make_on_message_function(this);\n",
+ "\n",
+ " this.ondownload = ondownload;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_header = function () {\n",
+ " var titlebar = document.createElement('div');\n",
+ " titlebar.classList =\n",
+ " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
+ " var titletext = document.createElement('div');\n",
+ " titletext.classList = 'ui-dialog-title';\n",
+ " titletext.setAttribute(\n",
+ " 'style',\n",
+ " 'width: 100%; text-align: center; padding: 3px;'\n",
+ " );\n",
+ " titlebar.appendChild(titletext);\n",
+ " this.root.appendChild(titlebar);\n",
+ " this.header = titletext;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
+ "\n",
+ "mpl.figure.prototype._init_canvas = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var canvas_div = (this.canvas_div = document.createElement('div'));\n",
+ " canvas_div.setAttribute(\n",
+ " 'style',\n",
+ " 'border: 1px solid #ddd;' +\n",
+ " 'box-sizing: content-box;' +\n",
+ " 'clear: both;' +\n",
+ " 'min-height: 1px;' +\n",
+ " 'min-width: 1px;' +\n",
+ " 'outline: 0;' +\n",
+ " 'overflow: hidden;' +\n",
+ " 'position: relative;' +\n",
+ " 'resize: both;'\n",
+ " );\n",
+ "\n",
+ " function on_keyboard_event_closure(name) {\n",
+ " return function (event) {\n",
+ " return fig.key_event(event, name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " canvas_div.addEventListener(\n",
+ " 'keydown',\n",
+ " on_keyboard_event_closure('key_press')\n",
+ " );\n",
+ " canvas_div.addEventListener(\n",
+ " 'keyup',\n",
+ " on_keyboard_event_closure('key_release')\n",
+ " );\n",
+ "\n",
+ " this._canvas_extra_style(canvas_div);\n",
+ " this.root.appendChild(canvas_div);\n",
+ "\n",
+ " var canvas = (this.canvas = document.createElement('canvas'));\n",
+ " canvas.classList.add('mpl-canvas');\n",
+ " canvas.setAttribute('style', 'box-sizing: content-box;');\n",
+ "\n",
+ " this.context = canvas.getContext('2d');\n",
+ "\n",
+ " var backingStore =\n",
+ " this.context.backingStorePixelRatio ||\n",
+ " this.context.webkitBackingStorePixelRatio ||\n",
+ " this.context.mozBackingStorePixelRatio ||\n",
+ " this.context.msBackingStorePixelRatio ||\n",
+ " this.context.oBackingStorePixelRatio ||\n",
+ " this.context.backingStorePixelRatio ||\n",
+ " 1;\n",
+ "\n",
+ " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+ "\n",
+ " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
+ " 'canvas'\n",
+ " ));\n",
+ " rubberband_canvas.setAttribute(\n",
+ " 'style',\n",
+ " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
+ " );\n",
+ "\n",
+ " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
+ " if (this.ResizeObserver === undefined) {\n",
+ " if (window.ResizeObserver !== undefined) {\n",
+ " this.ResizeObserver = window.ResizeObserver;\n",
+ " } else {\n",
+ " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
+ " this.ResizeObserver = obs.ResizeObserver;\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
+ " var nentries = entries.length;\n",
+ " for (var i = 0; i < nentries; i++) {\n",
+ " var entry = entries[i];\n",
+ " var width, height;\n",
+ " if (entry.contentBoxSize) {\n",
+ " if (entry.contentBoxSize instanceof Array) {\n",
+ " // Chrome 84 implements new version of spec.\n",
+ " width = entry.contentBoxSize[0].inlineSize;\n",
+ " height = entry.contentBoxSize[0].blockSize;\n",
+ " } else {\n",
+ " // Firefox implements old version of spec.\n",
+ " width = entry.contentBoxSize.inlineSize;\n",
+ " height = entry.contentBoxSize.blockSize;\n",
+ " }\n",
+ " } else {\n",
+ " // Chrome <84 implements even older version of spec.\n",
+ " width = entry.contentRect.width;\n",
+ " height = entry.contentRect.height;\n",
+ " }\n",
+ "\n",
+ " // Keep the size of the canvas and rubber band canvas in sync with\n",
+ " // the canvas container.\n",
+ " if (entry.devicePixelContentBoxSize) {\n",
+ " // Chrome 84 implements new version of spec.\n",
+ " canvas.setAttribute(\n",
+ " 'width',\n",
+ " entry.devicePixelContentBoxSize[0].inlineSize\n",
+ " );\n",
+ " canvas.setAttribute(\n",
+ " 'height',\n",
+ " entry.devicePixelContentBoxSize[0].blockSize\n",
+ " );\n",
+ " } else {\n",
+ " canvas.setAttribute('width', width * fig.ratio);\n",
+ " canvas.setAttribute('height', height * fig.ratio);\n",
+ " }\n",
+ " canvas.setAttribute(\n",
+ " 'style',\n",
+ " 'width: ' + width + 'px; height: ' + height + 'px;'\n",
+ " );\n",
+ "\n",
+ " rubberband_canvas.setAttribute('width', width);\n",
+ " rubberband_canvas.setAttribute('height', height);\n",
+ "\n",
+ " // And update the size in Python. We ignore the initial 0/0 size\n",
+ " // that occurs as the element is placed into the DOM, which should\n",
+ " // otherwise not happen due to the minimum size styling.\n",
+ " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
+ " fig.request_resize(width, height);\n",
+ " }\n",
+ " }\n",
+ " });\n",
+ " this.resizeObserverInstance.observe(canvas_div);\n",
+ "\n",
+ " function on_mouse_event_closure(name) {\n",
+ " return function (event) {\n",
+ " return fig.mouse_event(event, name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mousedown',\n",
+ " on_mouse_event_closure('button_press')\n",
+ " );\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseup',\n",
+ " on_mouse_event_closure('button_release')\n",
+ " );\n",
+ " // Throttle sequential mouse events to 1 every 20ms.\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mousemove',\n",
+ " on_mouse_event_closure('motion_notify')\n",
+ " );\n",
+ "\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseenter',\n",
+ " on_mouse_event_closure('figure_enter')\n",
+ " );\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseleave',\n",
+ " on_mouse_event_closure('figure_leave')\n",
+ " );\n",
+ "\n",
+ " canvas_div.addEventListener('wheel', function (event) {\n",
+ " if (event.deltaY < 0) {\n",
+ " event.step = 1;\n",
+ " } else {\n",
+ " event.step = -1;\n",
+ " }\n",
+ " on_mouse_event_closure('scroll')(event);\n",
+ " });\n",
+ "\n",
+ " canvas_div.appendChild(canvas);\n",
+ " canvas_div.appendChild(rubberband_canvas);\n",
+ "\n",
+ " this.rubberband_context = rubberband_canvas.getContext('2d');\n",
+ " this.rubberband_context.strokeStyle = '#000000';\n",
+ "\n",
+ " this._resize_canvas = function (width, height, forward) {\n",
+ " if (forward) {\n",
+ " canvas_div.style.width = width + 'px';\n",
+ " canvas_div.style.height = height + 'px';\n",
+ " }\n",
+ " };\n",
+ "\n",
+ " // Disable right mouse context menu.\n",
+ " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ " });\n",
+ "\n",
+ " function set_focus() {\n",
+ " canvas.focus();\n",
+ " canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " window.setTimeout(set_focus, 100);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var toolbar = document.createElement('div');\n",
+ " toolbar.classList = 'mpl-toolbar';\n",
+ " this.root.appendChild(toolbar);\n",
+ "\n",
+ " function on_click_closure(name) {\n",
+ " return function (_event) {\n",
+ " return fig.toolbar_button_onclick(name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " function on_mouseover_closure(tooltip) {\n",
+ " return function (event) {\n",
+ " if (!event.currentTarget.disabled) {\n",
+ " return fig.toolbar_button_onmouseover(tooltip);\n",
+ " }\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " fig.buttons = {};\n",
+ " var buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'mpl-button-group';\n",
+ " for (var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " /* Instead of a spacer, we start a new button group. */\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ " buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'mpl-button-group';\n",
+ " continue;\n",
+ " }\n",
+ "\n",
+ " var button = (fig.buttons[name] = document.createElement('button'));\n",
+ " button.classList = 'mpl-widget';\n",
+ " button.setAttribute('role', 'button');\n",
+ " button.setAttribute('aria-disabled', 'false');\n",
+ " button.addEventListener('click', on_click_closure(method_name));\n",
+ " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+ "\n",
+ " var icon_img = document.createElement('img');\n",
+ " icon_img.src = '_images/' + image + '.png';\n",
+ " icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
+ " icon_img.alt = tooltip;\n",
+ " button.appendChild(icon_img);\n",
+ "\n",
+ " buttonGroup.appendChild(button);\n",
+ " }\n",
+ "\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ "\n",
+ " var fmt_picker = document.createElement('select');\n",
+ " fmt_picker.classList = 'mpl-widget';\n",
+ " toolbar.appendChild(fmt_picker);\n",
+ " this.format_dropdown = fmt_picker;\n",
+ "\n",
+ " for (var ind in mpl.extensions) {\n",
+ " var fmt = mpl.extensions[ind];\n",
+ " var option = document.createElement('option');\n",
+ " option.selected = fmt === mpl.default_extension;\n",
+ " option.innerHTML = fmt;\n",
+ " fmt_picker.appendChild(option);\n",
+ " }\n",
+ "\n",
+ " var status_bar = document.createElement('span');\n",
+ " status_bar.classList = 'mpl-message';\n",
+ " toolbar.appendChild(status_bar);\n",
+ " this.message = status_bar;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
+ " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+ " // which will in turn request a refresh of the image.\n",
+ " this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.send_message = function (type, properties) {\n",
+ " properties['type'] = type;\n",
+ " properties['figure_id'] = this.id;\n",
+ " this.ws.send(JSON.stringify(properties));\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.send_draw_message = function () {\n",
+ " if (!this.waiting) {\n",
+ " this.waiting = true;\n",
+ " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+ " var format_dropdown = fig.format_dropdown;\n",
+ " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+ " fig.ondownload(fig, format);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
+ " var size = msg['size'];\n",
+ " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
+ " fig._resize_canvas(size[0], size[1], msg['forward']);\n",
+ " fig.send_message('refresh', {});\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
+ " var x0 = msg['x0'] / fig.ratio;\n",
+ " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
+ " var x1 = msg['x1'] / fig.ratio;\n",
+ " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
+ " x0 = Math.floor(x0) + 0.5;\n",
+ " y0 = Math.floor(y0) + 0.5;\n",
+ " x1 = Math.floor(x1) + 0.5;\n",
+ " y1 = Math.floor(y1) + 0.5;\n",
+ " var min_x = Math.min(x0, x1);\n",
+ " var min_y = Math.min(y0, y1);\n",
+ " var width = Math.abs(x1 - x0);\n",
+ " var height = Math.abs(y1 - y0);\n",
+ "\n",
+ " fig.rubberband_context.clearRect(\n",
+ " 0,\n",
+ " 0,\n",
+ " fig.canvas.width / fig.ratio,\n",
+ " fig.canvas.height / fig.ratio\n",
+ " );\n",
+ "\n",
+ " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
+ " // Updates the figure title.\n",
+ " fig.header.textContent = msg['label'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
+ " var cursor = msg['cursor'];\n",
+ " switch (cursor) {\n",
+ " case 0:\n",
+ " cursor = 'pointer';\n",
+ " break;\n",
+ " case 1:\n",
+ " cursor = 'default';\n",
+ " break;\n",
+ " case 2:\n",
+ " cursor = 'crosshair';\n",
+ " break;\n",
+ " case 3:\n",
+ " cursor = 'move';\n",
+ " break;\n",
+ " }\n",
+ " fig.rubberband_canvas.style.cursor = cursor;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
+ " fig.message.textContent = msg['message'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
+ " // Request the server to send over a new figure.\n",
+ " fig.send_draw_message();\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
+ " fig.image_mode = msg['mode'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
+ " for (var key in msg) {\n",
+ " if (!(key in fig.buttons)) {\n",
+ " continue;\n",
+ " }\n",
+ " fig.buttons[key].disabled = !msg[key];\n",
+ " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
+ " if (msg['mode'] === 'PAN') {\n",
+ " fig.buttons['Pan'].classList.add('active');\n",
+ " fig.buttons['Zoom'].classList.remove('active');\n",
+ " } else if (msg['mode'] === 'ZOOM') {\n",
+ " fig.buttons['Pan'].classList.remove('active');\n",
+ " fig.buttons['Zoom'].classList.add('active');\n",
+ " } else {\n",
+ " fig.buttons['Pan'].classList.remove('active');\n",
+ " fig.buttons['Zoom'].classList.remove('active');\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function () {\n",
+ " // Called whenever the canvas gets updated.\n",
+ " this.send_message('ack', {});\n",
+ "};\n",
+ "\n",
+ "// A function to construct a web socket function for onmessage handling.\n",
+ "// Called in the figure constructor.\n",
+ "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
+ " return function socket_on_message(evt) {\n",
+ " if (evt.data instanceof Blob) {\n",
+ " /* FIXME: We get \"Resource interpreted as Image but\n",
+ " * transferred with MIME type text/plain:\" errors on\n",
+ " * Chrome. But how to set the MIME type? It doesn't seem\n",
+ " * to be part of the websocket stream */\n",
+ " evt.data.type = 'image/png';\n",
+ "\n",
+ " /* Free the memory for the previous frames */\n",
+ " if (fig.imageObj.src) {\n",
+ " (window.URL || window.webkitURL).revokeObjectURL(\n",
+ " fig.imageObj.src\n",
+ " );\n",
+ " }\n",
+ "\n",
+ " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+ " evt.data\n",
+ " );\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " } else if (\n",
+ " typeof evt.data === 'string' &&\n",
+ " evt.data.slice(0, 21) === 'data:image/png;base64'\n",
+ " ) {\n",
+ " fig.imageObj.src = evt.data;\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " var msg = JSON.parse(evt.data);\n",
+ " var msg_type = msg['type'];\n",
+ "\n",
+ " // Call the \"handle_{type}\" callback, which takes\n",
+ " // the figure and JSON message as its only arguments.\n",
+ " try {\n",
+ " var callback = fig['handle_' + msg_type];\n",
+ " } catch (e) {\n",
+ " console.log(\n",
+ " \"No handler for the '\" + msg_type + \"' message type: \",\n",
+ " msg\n",
+ " );\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " if (callback) {\n",
+ " try {\n",
+ " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+ " callback(fig, msg);\n",
+ " } catch (e) {\n",
+ " console.log(\n",
+ " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
+ " e,\n",
+ " e.stack,\n",
+ " msg\n",
+ " );\n",
+ " }\n",
+ " }\n",
+ " };\n",
+ "};\n",
+ "\n",
+ "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+ "mpl.findpos = function (e) {\n",
+ " //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+ " var targ;\n",
+ " if (!e) {\n",
+ " e = window.event;\n",
+ " }\n",
+ " if (e.target) {\n",
+ " targ = e.target;\n",
+ " } else if (e.srcElement) {\n",
+ " targ = e.srcElement;\n",
+ " }\n",
+ " if (targ.nodeType === 3) {\n",
+ " // defeat Safari bug\n",
+ " targ = targ.parentNode;\n",
+ " }\n",
+ "\n",
+ " // pageX,Y are the mouse positions relative to the document\n",
+ " var boundingRect = targ.getBoundingClientRect();\n",
+ " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
+ " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
+ "\n",
+ " return { x: x, y: y };\n",
+ "};\n",
+ "\n",
+ "/*\n",
+ " * return a copy of an object with only non-object keys\n",
+ " * we need this to avoid circular references\n",
+ " * http://stackoverflow.com/a/24161582/3208463\n",
+ " */\n",
+ "function simpleKeys(original) {\n",
+ " return Object.keys(original).reduce(function (obj, key) {\n",
+ " if (typeof original[key] !== 'object') {\n",
+ " obj[key] = original[key];\n",
+ " }\n",
+ " return obj;\n",
+ " }, {});\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.mouse_event = function (event, name) {\n",
+ " var canvas_pos = mpl.findpos(event);\n",
+ "\n",
+ " if (name === 'button_press') {\n",
+ " this.canvas.focus();\n",
+ " this.canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " var x = canvas_pos.x * this.ratio;\n",
+ " var y = canvas_pos.y * this.ratio;\n",
+ "\n",
+ " this.send_message(name, {\n",
+ " x: x,\n",
+ " y: y,\n",
+ " button: event.button,\n",
+ " step: event.step,\n",
+ " guiEvent: simpleKeys(event),\n",
+ " });\n",
+ "\n",
+ " /* This prevents the web browser from automatically changing to\n",
+ " * the text insertion cursor when the button is pressed. We want\n",
+ " * to control all of the cursor setting manually through the\n",
+ " * 'cursor' event from matplotlib */\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
+ " // Handle any extra behaviour associated with a key event\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.key_event = function (event, name) {\n",
+ " // Prevent repeat events\n",
+ " if (name === 'key_press') {\n",
+ " if (event.which === this._key) {\n",
+ " return;\n",
+ " } else {\n",
+ " this._key = event.which;\n",
+ " }\n",
+ " }\n",
+ " if (name === 'key_release') {\n",
+ " this._key = null;\n",
+ " }\n",
+ "\n",
+ " var value = '';\n",
+ " if (event.ctrlKey && event.which !== 17) {\n",
+ " value += 'ctrl+';\n",
+ " }\n",
+ " if (event.altKey && event.which !== 18) {\n",
+ " value += 'alt+';\n",
+ " }\n",
+ " if (event.shiftKey && event.which !== 16) {\n",
+ " value += 'shift+';\n",
+ " }\n",
+ "\n",
+ " value += 'k';\n",
+ " value += event.which.toString();\n",
+ "\n",
+ " this._key_event_extra(event, name);\n",
+ "\n",
+ " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
+ " return false;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
+ " if (name === 'download') {\n",
+ " this.handle_save(this, null);\n",
+ " } else {\n",
+ " this.send_message('toolbar_button', { name: name });\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
+ " this.message.textContent = tooltip;\n",
+ "};\n",
+ "\n",
+ "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
+ "// prettier-ignore\n",
+ "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
+ "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+ "\n",
+ "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
+ "\n",
+ "mpl.default_extension = \"png\";/* global mpl */\n",
+ "\n",
+ "var comm_websocket_adapter = function (comm) {\n",
+ " // Create a \"websocket\"-like object which calls the given IPython comm\n",
+ " // object with the appropriate methods. Currently this is a non binary\n",
+ " // socket, so there is still some room for performance tuning.\n",
+ " var ws = {};\n",
+ "\n",
+ " ws.close = function () {\n",
+ " comm.close();\n",
+ " };\n",
+ " ws.send = function (m) {\n",
+ " //console.log('sending', m);\n",
+ " comm.send(m);\n",
+ " };\n",
+ " // Register the callback with on_msg.\n",
+ " comm.on_msg(function (msg) {\n",
+ " //console.log('receiving', msg['content']['data'], msg);\n",
+ " // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
+ " ws.onmessage(msg['content']['data']);\n",
+ " });\n",
+ " return ws;\n",
+ "};\n",
+ "\n",
+ "mpl.mpl_figure_comm = function (comm, msg) {\n",
+ " // This is the function which gets called when the mpl process\n",
+ " // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+ "\n",
+ " var id = msg.content.data.id;\n",
+ " // Get hold of the div created by the display call when the Comm\n",
+ " // socket was opened in Python.\n",
+ " var element = document.getElementById(id);\n",
+ " var ws_proxy = comm_websocket_adapter(comm);\n",
+ "\n",
+ " function ondownload(figure, _format) {\n",
+ " window.open(figure.canvas.toDataURL());\n",
+ " }\n",
+ "\n",
+ " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
+ "\n",
+ " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+ " // web socket which is closed, not our websocket->open comm proxy.\n",
+ " ws_proxy.onopen();\n",
+ "\n",
+ " fig.parent_element = element;\n",
+ " fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+ " if (!fig.cell_info) {\n",
+ " console.error('Failed to find cell for figure', id, fig);\n",
+ " return;\n",
+ " }\n",
+ " fig.cell_info[0].output_area.element.on(\n",
+ " 'cleared',\n",
+ " { fig: fig },\n",
+ " fig._remove_fig_handler\n",
+ " );\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
+ " var width = fig.canvas.width / fig.ratio;\n",
+ " fig.cell_info[0].output_area.element.off(\n",
+ " 'cleared',\n",
+ " fig._remove_fig_handler\n",
+ " );\n",
+ " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
+ "\n",
+ " // Update the output cell to use the data from the current canvas.\n",
+ " fig.push_to_output();\n",
+ " var dataURL = fig.canvas.toDataURL();\n",
+ " // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+ " // the notebook keyboard shortcuts fail.\n",
+ " IPython.keyboard_manager.enable();\n",
+ " fig.parent_element.innerHTML =\n",
+ " '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ " fig.close_ws(fig, msg);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
+ " fig.send_message('closing', msg);\n",
+ " // fig.ws.close()\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
+ " // Turn the data on the canvas into data in the output cell.\n",
+ " var width = this.canvas.width / this.ratio;\n",
+ " var dataURL = this.canvas.toDataURL();\n",
+ " this.cell_info[1]['text/html'] =\n",
+ " '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function () {\n",
+ " // Tell IPython that the notebook contents must change.\n",
+ " IPython.notebook.set_dirty(true);\n",
+ " this.send_message('ack', {});\n",
+ " var fig = this;\n",
+ " // Wait a second, then push the new image to the DOM so\n",
+ " // that it is saved nicely (might be nice to debounce this).\n",
+ " setTimeout(function () {\n",
+ " fig.push_to_output();\n",
+ " }, 1000);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var toolbar = document.createElement('div');\n",
+ " toolbar.classList = 'btn-toolbar';\n",
+ " this.root.appendChild(toolbar);\n",
+ "\n",
+ " function on_click_closure(name) {\n",
+ " return function (_event) {\n",
+ " return fig.toolbar_button_onclick(name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " function on_mouseover_closure(tooltip) {\n",
+ " return function (event) {\n",
+ " if (!event.currentTarget.disabled) {\n",
+ " return fig.toolbar_button_onmouseover(tooltip);\n",
+ " }\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " fig.buttons = {};\n",
+ " var buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'btn-group';\n",
+ " var button;\n",
+ " for (var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " /* Instead of a spacer, we start a new button group. */\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ " buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'btn-group';\n",
+ " continue;\n",
+ " }\n",
+ "\n",
+ " button = fig.buttons[name] = document.createElement('button');\n",
+ " button.classList = 'btn btn-default';\n",
+ " button.href = '#';\n",
+ " button.title = name;\n",
+ " button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
+ " button.addEventListener('click', on_click_closure(method_name));\n",
+ " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+ " buttonGroup.appendChild(button);\n",
+ " }\n",
+ "\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ "\n",
+ " // Add the status bar.\n",
+ " var status_bar = document.createElement('span');\n",
+ " status_bar.classList = 'mpl-message pull-right';\n",
+ " toolbar.appendChild(status_bar);\n",
+ " this.message = status_bar;\n",
+ "\n",
+ " // Add the close button to the window.\n",
+ " var buttongrp = document.createElement('div');\n",
+ " buttongrp.classList = 'btn-group inline pull-right';\n",
+ " button = document.createElement('button');\n",
+ " button.classList = 'btn btn-mini btn-primary';\n",
+ " button.href = '#';\n",
+ " button.title = 'Stop Interaction';\n",
+ " button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
+ " button.addEventListener('click', function (_evt) {\n",
+ " fig.handle_close(fig, {});\n",
+ " });\n",
+ " button.addEventListener(\n",
+ " 'mouseover',\n",
+ " on_mouseover_closure('Stop Interaction')\n",
+ " );\n",
+ " buttongrp.appendChild(button);\n",
+ " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
+ " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
+ " var fig = event.data.fig;\n",
+ " if (event.target !== this) {\n",
+ " // Ignore bubbled events from children.\n",
+ " return;\n",
+ " }\n",
+ " fig.close_ws(fig, {});\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function (el) {\n",
+ " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
+ " // this is important to make the div 'focusable\n",
+ " el.setAttribute('tabindex', 0);\n",
+ " // reach out to IPython and tell the keyboard manager to turn it's self\n",
+ " // off when our div gets focus\n",
+ "\n",
+ " // location in version 3\n",
+ " if (IPython.notebook.keyboard_manager) {\n",
+ " IPython.notebook.keyboard_manager.register_events(el);\n",
+ " } else {\n",
+ " // location in version 2\n",
+ " IPython.keyboard_manager.register_events(el);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
+ " var manager = IPython.notebook.keyboard_manager;\n",
+ " if (!manager) {\n",
+ " manager = IPython.keyboard_manager;\n",
+ " }\n",
+ "\n",
+ " // Check for shift+enter\n",
+ " if (event.shiftKey && event.which === 13) {\n",
+ " this.canvas_div.blur();\n",
+ " // select the cell after this one\n",
+ " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
+ " IPython.notebook.select(index + 1);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+ " fig.ondownload(fig, null);\n",
+ "};\n",
+ "\n",
+ "mpl.find_output_cell = function (html_output) {\n",
+ " // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+ " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+ " // IPython event is triggered only after the cells have been serialised, which for\n",
+ " // our purposes (turning an active figure into a static one), is too late.\n",
+ " var cells = IPython.notebook.get_cells();\n",
+ " var ncells = cells.length;\n",
+ " for (var i = 0; i < ncells; i++) {\n",
+ " var cell = cells[i];\n",
+ " if (cell.cell_type === 'code') {\n",
+ " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
+ " var data = cell.output_area.outputs[j];\n",
+ " if (data.data) {\n",
+ " // IPython >= 3 moved mimebundle to data attribute of output\n",
+ " data = data.data;\n",
+ " }\n",
+ " if (data['text/html'] === html_output) {\n",
+ " return [cell, data, j];\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "// Register the function which deals with the matplotlib target/channel.\n",
+ "// The kernel may be null if the page has been refreshed.\n",
+ "if (IPython.notebook.kernel !== null) {\n",
+ " IPython.notebook.kernel.comm_manager.register_target(\n",
+ " 'matplotlib',\n",
+ " mpl.mpl_figure_comm\n",
+ " );\n",
+ "}\n"
+ ],
"text/plain": [
- "<Figure size 576x576 with 2 Axes>"
+ "<IPython.core.display.Javascript object>"
]
},
- "metadata": {
- "needs_background": "light"
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
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\" width=\"800\">"
+ ],
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ]
},
+ "metadata": {},
"output_type": "display_data"
}
],
@@ -333,7 +1292,7 @@
},
{
"cell_type": "code",
- "execution_count": 35,
+ "execution_count": 7,
"id": "0837b3ff",
"metadata": {},
"outputs": [],
@@ -343,7 +1302,7 @@
},
{
"cell_type": "code",
- "execution_count": 36,
+ "execution_count": 8,
"id": "8798f857",
"metadata": {},
"outputs": [
@@ -353,7 +1312,7 @@
"SVC(kernel='linear')"
]
},
- "execution_count": 36,
+ "execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
@@ -372,139 +1331,101 @@
},
{
"cell_type": "code",
- "execution_count": 37,
+ "execution_count": 9,
"id": "fb5796e5",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "array([[ 1.09066717, 1.14168402],\n",
- " [ 0.82332406, 1.36527456],\n",
- " [ 0.81776713, 1.37941045],\n",
- " [ 2.14372476, -1.62753273],\n",
- " [ 1.90384852, 0.05469226],\n",
- " [-0.11368861, 0.789209 ],\n",
- " [ 0.82616617, 1.11588989],\n",
- " [ 2.28846317, -1.99513747],\n",
- " [ 1.57613484, 0.16334826],\n",
- " [ 0.39242418, 2.29848453],\n",
- " [ 1.77477496, 0.28227371],\n",
- " [ 1.29584153, 1.06915897],\n",
- " [ 0.43253476, 2.14776942],\n",
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+ " [ 0.40255384, 1.01645976],\n",
+ " [ 0.72794211, 1.44631683],\n",
+ " [ 0.74914917, 0.90509902],\n",
+ " [ 0.55048689, 0.80809041],\n",
+ " [ 0.33953792, 1.01802976],\n",
+ " [ 0.86791963, 1.10610129],\n",
+ " [ 0.43545804, 0.94008493],\n",
+ " [ 0.37769854, 1.06156196],\n",
+ " [ 0.26890853, 1.09087437],\n",
+ " [ 0.47686887, 0.7498173 ],\n",
+ " [ 0.45791321, 1.14821281],\n",
+ " [ 0.42977444, 1.1675954 ],\n",
+ " [ 0.92787593, 1.35712678],\n",
+ " [ 1.13271067, 0.84080793],\n",
+ " [ 0.6319547 , 1.20117136],\n",
+ " [ 0.74754794, 0.89002571]])"
]
},
- "execution_count": 37,
+ "execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
@@ -527,94 +1448,992 @@
},
{
"cell_type": "code",
- "execution_count": 38,
+ "execution_count": 10,
"id": "cc8fc1f1",
"metadata": {},
"outputs": [
{
"data": {
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\n",
- "text/plain": [
- "<Figure size 432x288 with 1 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "plt.scatter(data.loc[:, \"x\"], data.loc[:, \"y\"], c=data.loc[:, \"source\"], s=30, cmap=plt.cm.Paired)\n",
- "\n",
- "# plot the decision function\n",
- "ax = plt.gca()\n",
- "xlim = ax.get_xlim()\n",
- "ylim = ax.get_ylim()\n",
- "\n",
- "# create grid to evaluate model\n",
- "xx = np.linspace(xlim[0], xlim[1], 30)\n",
- "yy = np.linspace(ylim[0], ylim[1], 30)\n",
- "YY, XX = np.meshgrid(yy, xx)\n",
- "xy = np.vstack([XX.ravel(), YY.ravel()]).T\n",
- "Z = clf.decision_function(xy).reshape(XX.shape)\n",
- "\n",
- "# plot decision boundary and margins\n",
- "ax.contour(\n",
- " XX, YY, Z, colors=\"k\", levels=[-1, 0, 1], alpha=0.5, linestyles=[\"--\", \"-\", \"--\"]\n",
- ")\n",
- "# plot support vectors\n",
- "ax.scatter(\n",
- " clf.support_vectors_[:, 0],\n",
- " clf.support_vectors_[:, 1],\n",
- " s=100,\n",
- " linewidth=1,\n",
- " facecolors=\"none\",\n",
- " edgecolors=\"k\",\n",
- ")\n",
- "plt.show()"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "0ee97208",
- "metadata": {},
- "source": [
- "Try the same using another kernel to see how the decision boundary changes:"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 39,
- "id": "d98ececa",
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
- "text/plain": [
- "<Figure size 432x288 with 1 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "clf = svm.SVC(kernel=\"rbf\")\n",
- "clf.fit(data.loc[:, [\"x\", \"y\"]], data.loc[:, \"source\"])\n",
- "\n",
- "plt.scatter(data.loc[:, \"x\"], data.loc[:, \"y\"], c=data.loc[:, \"source\"], s=30, cmap=plt.cm.Paired)\n",
- "\n",
- "# plot the decision function\n",
- "ax = plt.gca()\n",
- "xlim = ax.get_xlim()\n",
- "ylim = ax.get_ylim()\n",
- "\n",
- "# create grid to evaluate model\n",
- "xx = np.linspace(xlim[0], xlim[1], 30)\n",
+ "application/javascript": [
+ "/* Put everything inside the global mpl namespace */\n",
+ "/* global mpl */\n",
+ "window.mpl = {};\n",
+ "\n",
+ "mpl.get_websocket_type = function () {\n",
+ " if (typeof WebSocket !== 'undefined') {\n",
+ " return WebSocket;\n",
+ " } else if (typeof MozWebSocket !== 'undefined') {\n",
+ " return MozWebSocket;\n",
+ " } else {\n",
+ " alert(\n",
+ " 'Your browser does not have WebSocket support. ' +\n",
+ " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+ " 'Firefox 4 and 5 are also supported but you ' +\n",
+ " 'have to enable WebSockets in about:config.'\n",
+ " );\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
+ " this.id = figure_id;\n",
+ "\n",
+ " this.ws = websocket;\n",
+ "\n",
+ " this.supports_binary = this.ws.binaryType !== undefined;\n",
+ "\n",
+ " if (!this.supports_binary) {\n",
+ " var warnings = document.getElementById('mpl-warnings');\n",
+ " if (warnings) {\n",
+ " warnings.style.display = 'block';\n",
+ " warnings.textContent =\n",
+ " 'This browser does not support binary websocket messages. ' +\n",
+ " 'Performance may be slow.';\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.imageObj = new Image();\n",
+ "\n",
+ " this.context = undefined;\n",
+ " this.message = undefined;\n",
+ " this.canvas = undefined;\n",
+ " this.rubberband_canvas = undefined;\n",
+ " this.rubberband_context = undefined;\n",
+ " this.format_dropdown = undefined;\n",
+ "\n",
+ " this.image_mode = 'full';\n",
+ "\n",
+ " this.root = document.createElement('div');\n",
+ " this.root.setAttribute('style', 'display: inline-block');\n",
+ " this._root_extra_style(this.root);\n",
+ "\n",
+ " parent_element.appendChild(this.root);\n",
+ "\n",
+ " this._init_header(this);\n",
+ " this._init_canvas(this);\n",
+ " this._init_toolbar(this);\n",
+ "\n",
+ " var fig = this;\n",
+ "\n",
+ " this.waiting = false;\n",
+ "\n",
+ " this.ws.onopen = function () {\n",
+ " fig.send_message('supports_binary', { value: fig.supports_binary });\n",
+ " fig.send_message('send_image_mode', {});\n",
+ " if (fig.ratio !== 1) {\n",
+ " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
+ " }\n",
+ " fig.send_message('refresh', {});\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onload = function () {\n",
+ " if (fig.image_mode === 'full') {\n",
+ " // Full images could contain transparency (where diff images\n",
+ " // almost always do), so we need to clear the canvas so that\n",
+ " // there is no ghosting.\n",
+ " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+ " }\n",
+ " fig.context.drawImage(fig.imageObj, 0, 0);\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onunload = function () {\n",
+ " fig.ws.close();\n",
+ " };\n",
+ "\n",
+ " this.ws.onmessage = this._make_on_message_function(this);\n",
+ "\n",
+ " this.ondownload = ondownload;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_header = function () {\n",
+ " var titlebar = document.createElement('div');\n",
+ " titlebar.classList =\n",
+ " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
+ " var titletext = document.createElement('div');\n",
+ " titletext.classList = 'ui-dialog-title';\n",
+ " titletext.setAttribute(\n",
+ " 'style',\n",
+ " 'width: 100%; text-align: center; padding: 3px;'\n",
+ " );\n",
+ " titlebar.appendChild(titletext);\n",
+ " this.root.appendChild(titlebar);\n",
+ " this.header = titletext;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
+ "\n",
+ "mpl.figure.prototype._init_canvas = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var canvas_div = (this.canvas_div = document.createElement('div'));\n",
+ " canvas_div.setAttribute(\n",
+ " 'style',\n",
+ " 'border: 1px solid #ddd;' +\n",
+ " 'box-sizing: content-box;' +\n",
+ " 'clear: both;' +\n",
+ " 'min-height: 1px;' +\n",
+ " 'min-width: 1px;' +\n",
+ " 'outline: 0;' +\n",
+ " 'overflow: hidden;' +\n",
+ " 'position: relative;' +\n",
+ " 'resize: both;'\n",
+ " );\n",
+ "\n",
+ " function on_keyboard_event_closure(name) {\n",
+ " return function (event) {\n",
+ " return fig.key_event(event, name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " canvas_div.addEventListener(\n",
+ " 'keydown',\n",
+ " on_keyboard_event_closure('key_press')\n",
+ " );\n",
+ " canvas_div.addEventListener(\n",
+ " 'keyup',\n",
+ " on_keyboard_event_closure('key_release')\n",
+ " );\n",
+ "\n",
+ " this._canvas_extra_style(canvas_div);\n",
+ " this.root.appendChild(canvas_div);\n",
+ "\n",
+ " var canvas = (this.canvas = document.createElement('canvas'));\n",
+ " canvas.classList.add('mpl-canvas');\n",
+ " canvas.setAttribute('style', 'box-sizing: content-box;');\n",
+ "\n",
+ " this.context = canvas.getContext('2d');\n",
+ "\n",
+ " var backingStore =\n",
+ " this.context.backingStorePixelRatio ||\n",
+ " this.context.webkitBackingStorePixelRatio ||\n",
+ " this.context.mozBackingStorePixelRatio ||\n",
+ " this.context.msBackingStorePixelRatio ||\n",
+ " this.context.oBackingStorePixelRatio ||\n",
+ " this.context.backingStorePixelRatio ||\n",
+ " 1;\n",
+ "\n",
+ " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+ "\n",
+ " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
+ " 'canvas'\n",
+ " ));\n",
+ " rubberband_canvas.setAttribute(\n",
+ " 'style',\n",
+ " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
+ " );\n",
+ "\n",
+ " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
+ " if (this.ResizeObserver === undefined) {\n",
+ " if (window.ResizeObserver !== undefined) {\n",
+ " this.ResizeObserver = window.ResizeObserver;\n",
+ " } else {\n",
+ " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
+ " this.ResizeObserver = obs.ResizeObserver;\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
+ " var nentries = entries.length;\n",
+ " for (var i = 0; i < nentries; i++) {\n",
+ " var entry = entries[i];\n",
+ " var width, height;\n",
+ " if (entry.contentBoxSize) {\n",
+ " if (entry.contentBoxSize instanceof Array) {\n",
+ " // Chrome 84 implements new version of spec.\n",
+ " width = entry.contentBoxSize[0].inlineSize;\n",
+ " height = entry.contentBoxSize[0].blockSize;\n",
+ " } else {\n",
+ " // Firefox implements old version of spec.\n",
+ " width = entry.contentBoxSize.inlineSize;\n",
+ " height = entry.contentBoxSize.blockSize;\n",
+ " }\n",
+ " } else {\n",
+ " // Chrome <84 implements even older version of spec.\n",
+ " width = entry.contentRect.width;\n",
+ " height = entry.contentRect.height;\n",
+ " }\n",
+ "\n",
+ " // Keep the size of the canvas and rubber band canvas in sync with\n",
+ " // the canvas container.\n",
+ " if (entry.devicePixelContentBoxSize) {\n",
+ " // Chrome 84 implements new version of spec.\n",
+ " canvas.setAttribute(\n",
+ " 'width',\n",
+ " entry.devicePixelContentBoxSize[0].inlineSize\n",
+ " );\n",
+ " canvas.setAttribute(\n",
+ " 'height',\n",
+ " entry.devicePixelContentBoxSize[0].blockSize\n",
+ " );\n",
+ " } else {\n",
+ " canvas.setAttribute('width', width * fig.ratio);\n",
+ " canvas.setAttribute('height', height * fig.ratio);\n",
+ " }\n",
+ " canvas.setAttribute(\n",
+ " 'style',\n",
+ " 'width: ' + width + 'px; height: ' + height + 'px;'\n",
+ " );\n",
+ "\n",
+ " rubberband_canvas.setAttribute('width', width);\n",
+ " rubberband_canvas.setAttribute('height', height);\n",
+ "\n",
+ " // And update the size in Python. We ignore the initial 0/0 size\n",
+ " // that occurs as the element is placed into the DOM, which should\n",
+ " // otherwise not happen due to the minimum size styling.\n",
+ " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
+ " fig.request_resize(width, height);\n",
+ " }\n",
+ " }\n",
+ " });\n",
+ " this.resizeObserverInstance.observe(canvas_div);\n",
+ "\n",
+ " function on_mouse_event_closure(name) {\n",
+ " return function (event) {\n",
+ " return fig.mouse_event(event, name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mousedown',\n",
+ " on_mouse_event_closure('button_press')\n",
+ " );\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseup',\n",
+ " on_mouse_event_closure('button_release')\n",
+ " );\n",
+ " // Throttle sequential mouse events to 1 every 20ms.\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mousemove',\n",
+ " on_mouse_event_closure('motion_notify')\n",
+ " );\n",
+ "\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseenter',\n",
+ " on_mouse_event_closure('figure_enter')\n",
+ " );\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseleave',\n",
+ " on_mouse_event_closure('figure_leave')\n",
+ " );\n",
+ "\n",
+ " canvas_div.addEventListener('wheel', function (event) {\n",
+ " if (event.deltaY < 0) {\n",
+ " event.step = 1;\n",
+ " } else {\n",
+ " event.step = -1;\n",
+ " }\n",
+ " on_mouse_event_closure('scroll')(event);\n",
+ " });\n",
+ "\n",
+ " canvas_div.appendChild(canvas);\n",
+ " canvas_div.appendChild(rubberband_canvas);\n",
+ "\n",
+ " this.rubberband_context = rubberband_canvas.getContext('2d');\n",
+ " this.rubberband_context.strokeStyle = '#000000';\n",
+ "\n",
+ " this._resize_canvas = function (width, height, forward) {\n",
+ " if (forward) {\n",
+ " canvas_div.style.width = width + 'px';\n",
+ " canvas_div.style.height = height + 'px';\n",
+ " }\n",
+ " };\n",
+ "\n",
+ " // Disable right mouse context menu.\n",
+ " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ " });\n",
+ "\n",
+ " function set_focus() {\n",
+ " canvas.focus();\n",
+ " canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " window.setTimeout(set_focus, 100);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var toolbar = document.createElement('div');\n",
+ " toolbar.classList = 'mpl-toolbar';\n",
+ " this.root.appendChild(toolbar);\n",
+ "\n",
+ " function on_click_closure(name) {\n",
+ " return function (_event) {\n",
+ " return fig.toolbar_button_onclick(name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " function on_mouseover_closure(tooltip) {\n",
+ " return function (event) {\n",
+ " if (!event.currentTarget.disabled) {\n",
+ " return fig.toolbar_button_onmouseover(tooltip);\n",
+ " }\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " fig.buttons = {};\n",
+ " var buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'mpl-button-group';\n",
+ " for (var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " /* Instead of a spacer, we start a new button group. */\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ " buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'mpl-button-group';\n",
+ " continue;\n",
+ " }\n",
+ "\n",
+ " var button = (fig.buttons[name] = document.createElement('button'));\n",
+ " button.classList = 'mpl-widget';\n",
+ " button.setAttribute('role', 'button');\n",
+ " button.setAttribute('aria-disabled', 'false');\n",
+ " button.addEventListener('click', on_click_closure(method_name));\n",
+ " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+ "\n",
+ " var icon_img = document.createElement('img');\n",
+ " icon_img.src = '_images/' + image + '.png';\n",
+ " icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
+ " icon_img.alt = tooltip;\n",
+ " button.appendChild(icon_img);\n",
+ "\n",
+ " buttonGroup.appendChild(button);\n",
+ " }\n",
+ "\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ "\n",
+ " var fmt_picker = document.createElement('select');\n",
+ " fmt_picker.classList = 'mpl-widget';\n",
+ " toolbar.appendChild(fmt_picker);\n",
+ " this.format_dropdown = fmt_picker;\n",
+ "\n",
+ " for (var ind in mpl.extensions) {\n",
+ " var fmt = mpl.extensions[ind];\n",
+ " var option = document.createElement('option');\n",
+ " option.selected = fmt === mpl.default_extension;\n",
+ " option.innerHTML = fmt;\n",
+ " fmt_picker.appendChild(option);\n",
+ " }\n",
+ "\n",
+ " var status_bar = document.createElement('span');\n",
+ " status_bar.classList = 'mpl-message';\n",
+ " toolbar.appendChild(status_bar);\n",
+ " this.message = status_bar;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
+ " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+ " // which will in turn request a refresh of the image.\n",
+ " this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.send_message = function (type, properties) {\n",
+ " properties['type'] = type;\n",
+ " properties['figure_id'] = this.id;\n",
+ " this.ws.send(JSON.stringify(properties));\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.send_draw_message = function () {\n",
+ " if (!this.waiting) {\n",
+ " this.waiting = true;\n",
+ " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+ " var format_dropdown = fig.format_dropdown;\n",
+ " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+ " fig.ondownload(fig, format);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
+ " var size = msg['size'];\n",
+ " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
+ " fig._resize_canvas(size[0], size[1], msg['forward']);\n",
+ " fig.send_message('refresh', {});\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
+ " var x0 = msg['x0'] / fig.ratio;\n",
+ " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
+ " var x1 = msg['x1'] / fig.ratio;\n",
+ " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
+ " x0 = Math.floor(x0) + 0.5;\n",
+ " y0 = Math.floor(y0) + 0.5;\n",
+ " x1 = Math.floor(x1) + 0.5;\n",
+ " y1 = Math.floor(y1) + 0.5;\n",
+ " var min_x = Math.min(x0, x1);\n",
+ " var min_y = Math.min(y0, y1);\n",
+ " var width = Math.abs(x1 - x0);\n",
+ " var height = Math.abs(y1 - y0);\n",
+ "\n",
+ " fig.rubberband_context.clearRect(\n",
+ " 0,\n",
+ " 0,\n",
+ " fig.canvas.width / fig.ratio,\n",
+ " fig.canvas.height / fig.ratio\n",
+ " );\n",
+ "\n",
+ " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
+ " // Updates the figure title.\n",
+ " fig.header.textContent = msg['label'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
+ " var cursor = msg['cursor'];\n",
+ " switch (cursor) {\n",
+ " case 0:\n",
+ " cursor = 'pointer';\n",
+ " break;\n",
+ " case 1:\n",
+ " cursor = 'default';\n",
+ " break;\n",
+ " case 2:\n",
+ " cursor = 'crosshair';\n",
+ " break;\n",
+ " case 3:\n",
+ " cursor = 'move';\n",
+ " break;\n",
+ " }\n",
+ " fig.rubberband_canvas.style.cursor = cursor;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
+ " fig.message.textContent = msg['message'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
+ " // Request the server to send over a new figure.\n",
+ " fig.send_draw_message();\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
+ " fig.image_mode = msg['mode'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
+ " for (var key in msg) {\n",
+ " if (!(key in fig.buttons)) {\n",
+ " continue;\n",
+ " }\n",
+ " fig.buttons[key].disabled = !msg[key];\n",
+ " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
+ " if (msg['mode'] === 'PAN') {\n",
+ " fig.buttons['Pan'].classList.add('active');\n",
+ " fig.buttons['Zoom'].classList.remove('active');\n",
+ " } else if (msg['mode'] === 'ZOOM') {\n",
+ " fig.buttons['Pan'].classList.remove('active');\n",
+ " fig.buttons['Zoom'].classList.add('active');\n",
+ " } else {\n",
+ " fig.buttons['Pan'].classList.remove('active');\n",
+ " fig.buttons['Zoom'].classList.remove('active');\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function () {\n",
+ " // Called whenever the canvas gets updated.\n",
+ " this.send_message('ack', {});\n",
+ "};\n",
+ "\n",
+ "// A function to construct a web socket function for onmessage handling.\n",
+ "// Called in the figure constructor.\n",
+ "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
+ " return function socket_on_message(evt) {\n",
+ " if (evt.data instanceof Blob) {\n",
+ " /* FIXME: We get \"Resource interpreted as Image but\n",
+ " * transferred with MIME type text/plain:\" errors on\n",
+ " * Chrome. But how to set the MIME type? It doesn't seem\n",
+ " * to be part of the websocket stream */\n",
+ " evt.data.type = 'image/png';\n",
+ "\n",
+ " /* Free the memory for the previous frames */\n",
+ " if (fig.imageObj.src) {\n",
+ " (window.URL || window.webkitURL).revokeObjectURL(\n",
+ " fig.imageObj.src\n",
+ " );\n",
+ " }\n",
+ "\n",
+ " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+ " evt.data\n",
+ " );\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " } else if (\n",
+ " typeof evt.data === 'string' &&\n",
+ " evt.data.slice(0, 21) === 'data:image/png;base64'\n",
+ " ) {\n",
+ " fig.imageObj.src = evt.data;\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " var msg = JSON.parse(evt.data);\n",
+ " var msg_type = msg['type'];\n",
+ "\n",
+ " // Call the \"handle_{type}\" callback, which takes\n",
+ " // the figure and JSON message as its only arguments.\n",
+ " try {\n",
+ " var callback = fig['handle_' + msg_type];\n",
+ " } catch (e) {\n",
+ " console.log(\n",
+ " \"No handler for the '\" + msg_type + \"' message type: \",\n",
+ " msg\n",
+ " );\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " if (callback) {\n",
+ " try {\n",
+ " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+ " callback(fig, msg);\n",
+ " } catch (e) {\n",
+ " console.log(\n",
+ " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
+ " e,\n",
+ " e.stack,\n",
+ " msg\n",
+ " );\n",
+ " }\n",
+ " }\n",
+ " };\n",
+ "};\n",
+ "\n",
+ "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+ "mpl.findpos = function (e) {\n",
+ " //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+ " var targ;\n",
+ " if (!e) {\n",
+ " e = window.event;\n",
+ " }\n",
+ " if (e.target) {\n",
+ " targ = e.target;\n",
+ " } else if (e.srcElement) {\n",
+ " targ = e.srcElement;\n",
+ " }\n",
+ " if (targ.nodeType === 3) {\n",
+ " // defeat Safari bug\n",
+ " targ = targ.parentNode;\n",
+ " }\n",
+ "\n",
+ " // pageX,Y are the mouse positions relative to the document\n",
+ " var boundingRect = targ.getBoundingClientRect();\n",
+ " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
+ " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
+ "\n",
+ " return { x: x, y: y };\n",
+ "};\n",
+ "\n",
+ "/*\n",
+ " * return a copy of an object with only non-object keys\n",
+ " * we need this to avoid circular references\n",
+ " * http://stackoverflow.com/a/24161582/3208463\n",
+ " */\n",
+ "function simpleKeys(original) {\n",
+ " return Object.keys(original).reduce(function (obj, key) {\n",
+ " if (typeof original[key] !== 'object') {\n",
+ " obj[key] = original[key];\n",
+ " }\n",
+ " return obj;\n",
+ " }, {});\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.mouse_event = function (event, name) {\n",
+ " var canvas_pos = mpl.findpos(event);\n",
+ "\n",
+ " if (name === 'button_press') {\n",
+ " this.canvas.focus();\n",
+ " this.canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " var x = canvas_pos.x * this.ratio;\n",
+ " var y = canvas_pos.y * this.ratio;\n",
+ "\n",
+ " this.send_message(name, {\n",
+ " x: x,\n",
+ " y: y,\n",
+ " button: event.button,\n",
+ " step: event.step,\n",
+ " guiEvent: simpleKeys(event),\n",
+ " });\n",
+ "\n",
+ " /* This prevents the web browser from automatically changing to\n",
+ " * the text insertion cursor when the button is pressed. We want\n",
+ " * to control all of the cursor setting manually through the\n",
+ " * 'cursor' event from matplotlib */\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
+ " // Handle any extra behaviour associated with a key event\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.key_event = function (event, name) {\n",
+ " // Prevent repeat events\n",
+ " if (name === 'key_press') {\n",
+ " if (event.which === this._key) {\n",
+ " return;\n",
+ " } else {\n",
+ " this._key = event.which;\n",
+ " }\n",
+ " }\n",
+ " if (name === 'key_release') {\n",
+ " this._key = null;\n",
+ " }\n",
+ "\n",
+ " var value = '';\n",
+ " if (event.ctrlKey && event.which !== 17) {\n",
+ " value += 'ctrl+';\n",
+ " }\n",
+ " if (event.altKey && event.which !== 18) {\n",
+ " value += 'alt+';\n",
+ " }\n",
+ " if (event.shiftKey && event.which !== 16) {\n",
+ " value += 'shift+';\n",
+ " }\n",
+ "\n",
+ " value += 'k';\n",
+ " value += event.which.toString();\n",
+ "\n",
+ " this._key_event_extra(event, name);\n",
+ "\n",
+ " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
+ " return false;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
+ " if (name === 'download') {\n",
+ " this.handle_save(this, null);\n",
+ " } else {\n",
+ " this.send_message('toolbar_button', { name: name });\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
+ " this.message.textContent = tooltip;\n",
+ "};\n",
+ "\n",
+ "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
+ "// prettier-ignore\n",
+ "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
+ "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+ "\n",
+ "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
+ "\n",
+ "mpl.default_extension = \"png\";/* global mpl */\n",
+ "\n",
+ "var comm_websocket_adapter = function (comm) {\n",
+ " // Create a \"websocket\"-like object which calls the given IPython comm\n",
+ " // object with the appropriate methods. Currently this is a non binary\n",
+ " // socket, so there is still some room for performance tuning.\n",
+ " var ws = {};\n",
+ "\n",
+ " ws.close = function () {\n",
+ " comm.close();\n",
+ " };\n",
+ " ws.send = function (m) {\n",
+ " //console.log('sending', m);\n",
+ " comm.send(m);\n",
+ " };\n",
+ " // Register the callback with on_msg.\n",
+ " comm.on_msg(function (msg) {\n",
+ " //console.log('receiving', msg['content']['data'], msg);\n",
+ " // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
+ " ws.onmessage(msg['content']['data']);\n",
+ " });\n",
+ " return ws;\n",
+ "};\n",
+ "\n",
+ "mpl.mpl_figure_comm = function (comm, msg) {\n",
+ " // This is the function which gets called when the mpl process\n",
+ " // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+ "\n",
+ " var id = msg.content.data.id;\n",
+ " // Get hold of the div created by the display call when the Comm\n",
+ " // socket was opened in Python.\n",
+ " var element = document.getElementById(id);\n",
+ " var ws_proxy = comm_websocket_adapter(comm);\n",
+ "\n",
+ " function ondownload(figure, _format) {\n",
+ " window.open(figure.canvas.toDataURL());\n",
+ " }\n",
+ "\n",
+ " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
+ "\n",
+ " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+ " // web socket which is closed, not our websocket->open comm proxy.\n",
+ " ws_proxy.onopen();\n",
+ "\n",
+ " fig.parent_element = element;\n",
+ " fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+ " if (!fig.cell_info) {\n",
+ " console.error('Failed to find cell for figure', id, fig);\n",
+ " return;\n",
+ " }\n",
+ " fig.cell_info[0].output_area.element.on(\n",
+ " 'cleared',\n",
+ " { fig: fig },\n",
+ " fig._remove_fig_handler\n",
+ " );\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
+ " var width = fig.canvas.width / fig.ratio;\n",
+ " fig.cell_info[0].output_area.element.off(\n",
+ " 'cleared',\n",
+ " fig._remove_fig_handler\n",
+ " );\n",
+ " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
+ "\n",
+ " // Update the output cell to use the data from the current canvas.\n",
+ " fig.push_to_output();\n",
+ " var dataURL = fig.canvas.toDataURL();\n",
+ " // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+ " // the notebook keyboard shortcuts fail.\n",
+ " IPython.keyboard_manager.enable();\n",
+ " fig.parent_element.innerHTML =\n",
+ " '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ " fig.close_ws(fig, msg);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
+ " fig.send_message('closing', msg);\n",
+ " // fig.ws.close()\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
+ " // Turn the data on the canvas into data in the output cell.\n",
+ " var width = this.canvas.width / this.ratio;\n",
+ " var dataURL = this.canvas.toDataURL();\n",
+ " this.cell_info[1]['text/html'] =\n",
+ " '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function () {\n",
+ " // Tell IPython that the notebook contents must change.\n",
+ " IPython.notebook.set_dirty(true);\n",
+ " this.send_message('ack', {});\n",
+ " var fig = this;\n",
+ " // Wait a second, then push the new image to the DOM so\n",
+ " // that it is saved nicely (might be nice to debounce this).\n",
+ " setTimeout(function () {\n",
+ " fig.push_to_output();\n",
+ " }, 1000);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var toolbar = document.createElement('div');\n",
+ " toolbar.classList = 'btn-toolbar';\n",
+ " this.root.appendChild(toolbar);\n",
+ "\n",
+ " function on_click_closure(name) {\n",
+ " return function (_event) {\n",
+ " return fig.toolbar_button_onclick(name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " function on_mouseover_closure(tooltip) {\n",
+ " return function (event) {\n",
+ " if (!event.currentTarget.disabled) {\n",
+ " return fig.toolbar_button_onmouseover(tooltip);\n",
+ " }\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " fig.buttons = {};\n",
+ " var buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'btn-group';\n",
+ " var button;\n",
+ " for (var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " /* Instead of a spacer, we start a new button group. */\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ " buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'btn-group';\n",
+ " continue;\n",
+ " }\n",
+ "\n",
+ " button = fig.buttons[name] = document.createElement('button');\n",
+ " button.classList = 'btn btn-default';\n",
+ " button.href = '#';\n",
+ " button.title = name;\n",
+ " button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
+ " button.addEventListener('click', on_click_closure(method_name));\n",
+ " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+ " buttonGroup.appendChild(button);\n",
+ " }\n",
+ "\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ "\n",
+ " // Add the status bar.\n",
+ " var status_bar = document.createElement('span');\n",
+ " status_bar.classList = 'mpl-message pull-right';\n",
+ " toolbar.appendChild(status_bar);\n",
+ " this.message = status_bar;\n",
+ "\n",
+ " // Add the close button to the window.\n",
+ " var buttongrp = document.createElement('div');\n",
+ " buttongrp.classList = 'btn-group inline pull-right';\n",
+ " button = document.createElement('button');\n",
+ " button.classList = 'btn btn-mini btn-primary';\n",
+ " button.href = '#';\n",
+ " button.title = 'Stop Interaction';\n",
+ " button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
+ " button.addEventListener('click', function (_evt) {\n",
+ " fig.handle_close(fig, {});\n",
+ " });\n",
+ " button.addEventListener(\n",
+ " 'mouseover',\n",
+ " on_mouseover_closure('Stop Interaction')\n",
+ " );\n",
+ " buttongrp.appendChild(button);\n",
+ " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
+ " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
+ " var fig = event.data.fig;\n",
+ " if (event.target !== this) {\n",
+ " // Ignore bubbled events from children.\n",
+ " return;\n",
+ " }\n",
+ " fig.close_ws(fig, {});\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function (el) {\n",
+ " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
+ " // this is important to make the div 'focusable\n",
+ " el.setAttribute('tabindex', 0);\n",
+ " // reach out to IPython and tell the keyboard manager to turn it's self\n",
+ " // off when our div gets focus\n",
+ "\n",
+ " // location in version 3\n",
+ " if (IPython.notebook.keyboard_manager) {\n",
+ " IPython.notebook.keyboard_manager.register_events(el);\n",
+ " } else {\n",
+ " // location in version 2\n",
+ " IPython.keyboard_manager.register_events(el);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
+ " var manager = IPython.notebook.keyboard_manager;\n",
+ " if (!manager) {\n",
+ " manager = IPython.keyboard_manager;\n",
+ " }\n",
+ "\n",
+ " // Check for shift+enter\n",
+ " if (event.shiftKey && event.which === 13) {\n",
+ " this.canvas_div.blur();\n",
+ " // select the cell after this one\n",
+ " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
+ " IPython.notebook.select(index + 1);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+ " fig.ondownload(fig, null);\n",
+ "};\n",
+ "\n",
+ "mpl.find_output_cell = function (html_output) {\n",
+ " // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+ " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+ " // IPython event is triggered only after the cells have been serialised, which for\n",
+ " // our purposes (turning an active figure into a static one), is too late.\n",
+ " var cells = IPython.notebook.get_cells();\n",
+ " var ncells = cells.length;\n",
+ " for (var i = 0; i < ncells; i++) {\n",
+ " var cell = cells[i];\n",
+ " if (cell.cell_type === 'code') {\n",
+ " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
+ " var data = cell.output_area.outputs[j];\n",
+ " if (data.data) {\n",
+ " // IPython >= 3 moved mimebundle to data attribute of output\n",
+ " data = data.data;\n",
+ " }\n",
+ " if (data['text/html'] === html_output) {\n",
+ " return [cell, data, j];\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "// Register the function which deals with the matplotlib target/channel.\n",
+ "// The kernel may be null if the page has been refreshed.\n",
+ "if (IPython.notebook.kernel !== null) {\n",
+ " IPython.notebook.kernel.comm_manager.register_target(\n",
+ " 'matplotlib',\n",
+ " mpl.mpl_figure_comm\n",
+ " );\n",
+ "}\n"
+ ],
+ "text/plain": [
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+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
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\" width=\"800\">"
+ ],
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "fig, ax = plt.subplots(figsize=(8, 8))\n",
+ "plt.scatter(data.loc[:, \"x\"], data.loc[:, \"y\"], c=data.loc[:, \"source\"], s=30, cmap=plt.cm.Paired)\n",
+ "\n",
+ "# plot the decision function\n",
+ "ax = plt.gca()\n",
+ "xlim = ax.get_xlim()\n",
+ "ylim = ax.get_ylim()\n",
+ "\n",
+ "# create grid to evaluate model\n",
+ "xx = np.linspace(xlim[0], xlim[1], 30)\n",
"yy = np.linspace(ylim[0], ylim[1], 30)\n",
"YY, XX = np.meshgrid(yy, xx)\n",
"xy = np.vstack([XX.ravel(), YY.ravel()]).T\n",
@@ -636,6 +2455,1026 @@
"plt.show()"
]
},
+ {
+ "cell_type": "markdown",
+ "id": "0ee97208",
+ "metadata": {},
+ "source": [
+ "Try the same using another kernel to see how the decision boundary changes:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "id": "d98ececa",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "application/javascript": [
+ "/* Put everything inside the global mpl namespace */\n",
+ "/* global mpl */\n",
+ "window.mpl = {};\n",
+ "\n",
+ "mpl.get_websocket_type = function () {\n",
+ " if (typeof WebSocket !== 'undefined') {\n",
+ " return WebSocket;\n",
+ " } else if (typeof MozWebSocket !== 'undefined') {\n",
+ " return MozWebSocket;\n",
+ " } else {\n",
+ " alert(\n",
+ " 'Your browser does not have WebSocket support. ' +\n",
+ " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+ " 'Firefox 4 and 5 are also supported but you ' +\n",
+ " 'have to enable WebSockets in about:config.'\n",
+ " );\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
+ " this.id = figure_id;\n",
+ "\n",
+ " this.ws = websocket;\n",
+ "\n",
+ " this.supports_binary = this.ws.binaryType !== undefined;\n",
+ "\n",
+ " if (!this.supports_binary) {\n",
+ " var warnings = document.getElementById('mpl-warnings');\n",
+ " if (warnings) {\n",
+ " warnings.style.display = 'block';\n",
+ " warnings.textContent =\n",
+ " 'This browser does not support binary websocket messages. ' +\n",
+ " 'Performance may be slow.';\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.imageObj = new Image();\n",
+ "\n",
+ " this.context = undefined;\n",
+ " this.message = undefined;\n",
+ " this.canvas = undefined;\n",
+ " this.rubberband_canvas = undefined;\n",
+ " this.rubberband_context = undefined;\n",
+ " this.format_dropdown = undefined;\n",
+ "\n",
+ " this.image_mode = 'full';\n",
+ "\n",
+ " this.root = document.createElement('div');\n",
+ " this.root.setAttribute('style', 'display: inline-block');\n",
+ " this._root_extra_style(this.root);\n",
+ "\n",
+ " parent_element.appendChild(this.root);\n",
+ "\n",
+ " this._init_header(this);\n",
+ " this._init_canvas(this);\n",
+ " this._init_toolbar(this);\n",
+ "\n",
+ " var fig = this;\n",
+ "\n",
+ " this.waiting = false;\n",
+ "\n",
+ " this.ws.onopen = function () {\n",
+ " fig.send_message('supports_binary', { value: fig.supports_binary });\n",
+ " fig.send_message('send_image_mode', {});\n",
+ " if (fig.ratio !== 1) {\n",
+ " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
+ " }\n",
+ " fig.send_message('refresh', {});\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onload = function () {\n",
+ " if (fig.image_mode === 'full') {\n",
+ " // Full images could contain transparency (where diff images\n",
+ " // almost always do), so we need to clear the canvas so that\n",
+ " // there is no ghosting.\n",
+ " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+ " }\n",
+ " fig.context.drawImage(fig.imageObj, 0, 0);\n",
+ " };\n",
+ "\n",
+ " this.imageObj.onunload = function () {\n",
+ " fig.ws.close();\n",
+ " };\n",
+ "\n",
+ " this.ws.onmessage = this._make_on_message_function(this);\n",
+ "\n",
+ " this.ondownload = ondownload;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_header = function () {\n",
+ " var titlebar = document.createElement('div');\n",
+ " titlebar.classList =\n",
+ " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
+ " var titletext = document.createElement('div');\n",
+ " titletext.classList = 'ui-dialog-title';\n",
+ " titletext.setAttribute(\n",
+ " 'style',\n",
+ " 'width: 100%; text-align: center; padding: 3px;'\n",
+ " );\n",
+ " titlebar.appendChild(titletext);\n",
+ " this.root.appendChild(titlebar);\n",
+ " this.header = titletext;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
+ "\n",
+ "mpl.figure.prototype._init_canvas = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var canvas_div = (this.canvas_div = document.createElement('div'));\n",
+ " canvas_div.setAttribute(\n",
+ " 'style',\n",
+ " 'border: 1px solid #ddd;' +\n",
+ " 'box-sizing: content-box;' +\n",
+ " 'clear: both;' +\n",
+ " 'min-height: 1px;' +\n",
+ " 'min-width: 1px;' +\n",
+ " 'outline: 0;' +\n",
+ " 'overflow: hidden;' +\n",
+ " 'position: relative;' +\n",
+ " 'resize: both;'\n",
+ " );\n",
+ "\n",
+ " function on_keyboard_event_closure(name) {\n",
+ " return function (event) {\n",
+ " return fig.key_event(event, name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " canvas_div.addEventListener(\n",
+ " 'keydown',\n",
+ " on_keyboard_event_closure('key_press')\n",
+ " );\n",
+ " canvas_div.addEventListener(\n",
+ " 'keyup',\n",
+ " on_keyboard_event_closure('key_release')\n",
+ " );\n",
+ "\n",
+ " this._canvas_extra_style(canvas_div);\n",
+ " this.root.appendChild(canvas_div);\n",
+ "\n",
+ " var canvas = (this.canvas = document.createElement('canvas'));\n",
+ " canvas.classList.add('mpl-canvas');\n",
+ " canvas.setAttribute('style', 'box-sizing: content-box;');\n",
+ "\n",
+ " this.context = canvas.getContext('2d');\n",
+ "\n",
+ " var backingStore =\n",
+ " this.context.backingStorePixelRatio ||\n",
+ " this.context.webkitBackingStorePixelRatio ||\n",
+ " this.context.mozBackingStorePixelRatio ||\n",
+ " this.context.msBackingStorePixelRatio ||\n",
+ " this.context.oBackingStorePixelRatio ||\n",
+ " this.context.backingStorePixelRatio ||\n",
+ " 1;\n",
+ "\n",
+ " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+ "\n",
+ " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
+ " 'canvas'\n",
+ " ));\n",
+ " rubberband_canvas.setAttribute(\n",
+ " 'style',\n",
+ " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
+ " );\n",
+ "\n",
+ " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
+ " if (this.ResizeObserver === undefined) {\n",
+ " if (window.ResizeObserver !== undefined) {\n",
+ " this.ResizeObserver = window.ResizeObserver;\n",
+ " } else {\n",
+ " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
+ " this.ResizeObserver = obs.ResizeObserver;\n",
+ " }\n",
+ " }\n",
+ "\n",
+ " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
+ " var nentries = entries.length;\n",
+ " for (var i = 0; i < nentries; i++) {\n",
+ " var entry = entries[i];\n",
+ " var width, height;\n",
+ " if (entry.contentBoxSize) {\n",
+ " if (entry.contentBoxSize instanceof Array) {\n",
+ " // Chrome 84 implements new version of spec.\n",
+ " width = entry.contentBoxSize[0].inlineSize;\n",
+ " height = entry.contentBoxSize[0].blockSize;\n",
+ " } else {\n",
+ " // Firefox implements old version of spec.\n",
+ " width = entry.contentBoxSize.inlineSize;\n",
+ " height = entry.contentBoxSize.blockSize;\n",
+ " }\n",
+ " } else {\n",
+ " // Chrome <84 implements even older version of spec.\n",
+ " width = entry.contentRect.width;\n",
+ " height = entry.contentRect.height;\n",
+ " }\n",
+ "\n",
+ " // Keep the size of the canvas and rubber band canvas in sync with\n",
+ " // the canvas container.\n",
+ " if (entry.devicePixelContentBoxSize) {\n",
+ " // Chrome 84 implements new version of spec.\n",
+ " canvas.setAttribute(\n",
+ " 'width',\n",
+ " entry.devicePixelContentBoxSize[0].inlineSize\n",
+ " );\n",
+ " canvas.setAttribute(\n",
+ " 'height',\n",
+ " entry.devicePixelContentBoxSize[0].blockSize\n",
+ " );\n",
+ " } else {\n",
+ " canvas.setAttribute('width', width * fig.ratio);\n",
+ " canvas.setAttribute('height', height * fig.ratio);\n",
+ " }\n",
+ " canvas.setAttribute(\n",
+ " 'style',\n",
+ " 'width: ' + width + 'px; height: ' + height + 'px;'\n",
+ " );\n",
+ "\n",
+ " rubberband_canvas.setAttribute('width', width);\n",
+ " rubberband_canvas.setAttribute('height', height);\n",
+ "\n",
+ " // And update the size in Python. We ignore the initial 0/0 size\n",
+ " // that occurs as the element is placed into the DOM, which should\n",
+ " // otherwise not happen due to the minimum size styling.\n",
+ " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
+ " fig.request_resize(width, height);\n",
+ " }\n",
+ " }\n",
+ " });\n",
+ " this.resizeObserverInstance.observe(canvas_div);\n",
+ "\n",
+ " function on_mouse_event_closure(name) {\n",
+ " return function (event) {\n",
+ " return fig.mouse_event(event, name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mousedown',\n",
+ " on_mouse_event_closure('button_press')\n",
+ " );\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseup',\n",
+ " on_mouse_event_closure('button_release')\n",
+ " );\n",
+ " // Throttle sequential mouse events to 1 every 20ms.\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mousemove',\n",
+ " on_mouse_event_closure('motion_notify')\n",
+ " );\n",
+ "\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseenter',\n",
+ " on_mouse_event_closure('figure_enter')\n",
+ " );\n",
+ " rubberband_canvas.addEventListener(\n",
+ " 'mouseleave',\n",
+ " on_mouse_event_closure('figure_leave')\n",
+ " );\n",
+ "\n",
+ " canvas_div.addEventListener('wheel', function (event) {\n",
+ " if (event.deltaY < 0) {\n",
+ " event.step = 1;\n",
+ " } else {\n",
+ " event.step = -1;\n",
+ " }\n",
+ " on_mouse_event_closure('scroll')(event);\n",
+ " });\n",
+ "\n",
+ " canvas_div.appendChild(canvas);\n",
+ " canvas_div.appendChild(rubberband_canvas);\n",
+ "\n",
+ " this.rubberband_context = rubberband_canvas.getContext('2d');\n",
+ " this.rubberband_context.strokeStyle = '#000000';\n",
+ "\n",
+ " this._resize_canvas = function (width, height, forward) {\n",
+ " if (forward) {\n",
+ " canvas_div.style.width = width + 'px';\n",
+ " canvas_div.style.height = height + 'px';\n",
+ " }\n",
+ " };\n",
+ "\n",
+ " // Disable right mouse context menu.\n",
+ " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ " });\n",
+ "\n",
+ " function set_focus() {\n",
+ " canvas.focus();\n",
+ " canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " window.setTimeout(set_focus, 100);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var toolbar = document.createElement('div');\n",
+ " toolbar.classList = 'mpl-toolbar';\n",
+ " this.root.appendChild(toolbar);\n",
+ "\n",
+ " function on_click_closure(name) {\n",
+ " return function (_event) {\n",
+ " return fig.toolbar_button_onclick(name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " function on_mouseover_closure(tooltip) {\n",
+ " return function (event) {\n",
+ " if (!event.currentTarget.disabled) {\n",
+ " return fig.toolbar_button_onmouseover(tooltip);\n",
+ " }\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " fig.buttons = {};\n",
+ " var buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'mpl-button-group';\n",
+ " for (var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " /* Instead of a spacer, we start a new button group. */\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ " buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'mpl-button-group';\n",
+ " continue;\n",
+ " }\n",
+ "\n",
+ " var button = (fig.buttons[name] = document.createElement('button'));\n",
+ " button.classList = 'mpl-widget';\n",
+ " button.setAttribute('role', 'button');\n",
+ " button.setAttribute('aria-disabled', 'false');\n",
+ " button.addEventListener('click', on_click_closure(method_name));\n",
+ " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+ "\n",
+ " var icon_img = document.createElement('img');\n",
+ " icon_img.src = '_images/' + image + '.png';\n",
+ " icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
+ " icon_img.alt = tooltip;\n",
+ " button.appendChild(icon_img);\n",
+ "\n",
+ " buttonGroup.appendChild(button);\n",
+ " }\n",
+ "\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ "\n",
+ " var fmt_picker = document.createElement('select');\n",
+ " fmt_picker.classList = 'mpl-widget';\n",
+ " toolbar.appendChild(fmt_picker);\n",
+ " this.format_dropdown = fmt_picker;\n",
+ "\n",
+ " for (var ind in mpl.extensions) {\n",
+ " var fmt = mpl.extensions[ind];\n",
+ " var option = document.createElement('option');\n",
+ " option.selected = fmt === mpl.default_extension;\n",
+ " option.innerHTML = fmt;\n",
+ " fmt_picker.appendChild(option);\n",
+ " }\n",
+ "\n",
+ " var status_bar = document.createElement('span');\n",
+ " status_bar.classList = 'mpl-message';\n",
+ " toolbar.appendChild(status_bar);\n",
+ " this.message = status_bar;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
+ " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+ " // which will in turn request a refresh of the image.\n",
+ " this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.send_message = function (type, properties) {\n",
+ " properties['type'] = type;\n",
+ " properties['figure_id'] = this.id;\n",
+ " this.ws.send(JSON.stringify(properties));\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.send_draw_message = function () {\n",
+ " if (!this.waiting) {\n",
+ " this.waiting = true;\n",
+ " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+ " var format_dropdown = fig.format_dropdown;\n",
+ " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+ " fig.ondownload(fig, format);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
+ " var size = msg['size'];\n",
+ " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
+ " fig._resize_canvas(size[0], size[1], msg['forward']);\n",
+ " fig.send_message('refresh', {});\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
+ " var x0 = msg['x0'] / fig.ratio;\n",
+ " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
+ " var x1 = msg['x1'] / fig.ratio;\n",
+ " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
+ " x0 = Math.floor(x0) + 0.5;\n",
+ " y0 = Math.floor(y0) + 0.5;\n",
+ " x1 = Math.floor(x1) + 0.5;\n",
+ " y1 = Math.floor(y1) + 0.5;\n",
+ " var min_x = Math.min(x0, x1);\n",
+ " var min_y = Math.min(y0, y1);\n",
+ " var width = Math.abs(x1 - x0);\n",
+ " var height = Math.abs(y1 - y0);\n",
+ "\n",
+ " fig.rubberband_context.clearRect(\n",
+ " 0,\n",
+ " 0,\n",
+ " fig.canvas.width / fig.ratio,\n",
+ " fig.canvas.height / fig.ratio\n",
+ " );\n",
+ "\n",
+ " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
+ " // Updates the figure title.\n",
+ " fig.header.textContent = msg['label'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
+ " var cursor = msg['cursor'];\n",
+ " switch (cursor) {\n",
+ " case 0:\n",
+ " cursor = 'pointer';\n",
+ " break;\n",
+ " case 1:\n",
+ " cursor = 'default';\n",
+ " break;\n",
+ " case 2:\n",
+ " cursor = 'crosshair';\n",
+ " break;\n",
+ " case 3:\n",
+ " cursor = 'move';\n",
+ " break;\n",
+ " }\n",
+ " fig.rubberband_canvas.style.cursor = cursor;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
+ " fig.message.textContent = msg['message'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
+ " // Request the server to send over a new figure.\n",
+ " fig.send_draw_message();\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
+ " fig.image_mode = msg['mode'];\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
+ " for (var key in msg) {\n",
+ " if (!(key in fig.buttons)) {\n",
+ " continue;\n",
+ " }\n",
+ " fig.buttons[key].disabled = !msg[key];\n",
+ " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
+ " if (msg['mode'] === 'PAN') {\n",
+ " fig.buttons['Pan'].classList.add('active');\n",
+ " fig.buttons['Zoom'].classList.remove('active');\n",
+ " } else if (msg['mode'] === 'ZOOM') {\n",
+ " fig.buttons['Pan'].classList.remove('active');\n",
+ " fig.buttons['Zoom'].classList.add('active');\n",
+ " } else {\n",
+ " fig.buttons['Pan'].classList.remove('active');\n",
+ " fig.buttons['Zoom'].classList.remove('active');\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function () {\n",
+ " // Called whenever the canvas gets updated.\n",
+ " this.send_message('ack', {});\n",
+ "};\n",
+ "\n",
+ "// A function to construct a web socket function for onmessage handling.\n",
+ "// Called in the figure constructor.\n",
+ "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
+ " return function socket_on_message(evt) {\n",
+ " if (evt.data instanceof Blob) {\n",
+ " /* FIXME: We get \"Resource interpreted as Image but\n",
+ " * transferred with MIME type text/plain:\" errors on\n",
+ " * Chrome. But how to set the MIME type? It doesn't seem\n",
+ " * to be part of the websocket stream */\n",
+ " evt.data.type = 'image/png';\n",
+ "\n",
+ " /* Free the memory for the previous frames */\n",
+ " if (fig.imageObj.src) {\n",
+ " (window.URL || window.webkitURL).revokeObjectURL(\n",
+ " fig.imageObj.src\n",
+ " );\n",
+ " }\n",
+ "\n",
+ " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+ " evt.data\n",
+ " );\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " } else if (\n",
+ " typeof evt.data === 'string' &&\n",
+ " evt.data.slice(0, 21) === 'data:image/png;base64'\n",
+ " ) {\n",
+ " fig.imageObj.src = evt.data;\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " var msg = JSON.parse(evt.data);\n",
+ " var msg_type = msg['type'];\n",
+ "\n",
+ " // Call the \"handle_{type}\" callback, which takes\n",
+ " // the figure and JSON message as its only arguments.\n",
+ " try {\n",
+ " var callback = fig['handle_' + msg_type];\n",
+ " } catch (e) {\n",
+ " console.log(\n",
+ " \"No handler for the '\" + msg_type + \"' message type: \",\n",
+ " msg\n",
+ " );\n",
+ " return;\n",
+ " }\n",
+ "\n",
+ " if (callback) {\n",
+ " try {\n",
+ " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+ " callback(fig, msg);\n",
+ " } catch (e) {\n",
+ " console.log(\n",
+ " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
+ " e,\n",
+ " e.stack,\n",
+ " msg\n",
+ " );\n",
+ " }\n",
+ " }\n",
+ " };\n",
+ "};\n",
+ "\n",
+ "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+ "mpl.findpos = function (e) {\n",
+ " //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+ " var targ;\n",
+ " if (!e) {\n",
+ " e = window.event;\n",
+ " }\n",
+ " if (e.target) {\n",
+ " targ = e.target;\n",
+ " } else if (e.srcElement) {\n",
+ " targ = e.srcElement;\n",
+ " }\n",
+ " if (targ.nodeType === 3) {\n",
+ " // defeat Safari bug\n",
+ " targ = targ.parentNode;\n",
+ " }\n",
+ "\n",
+ " // pageX,Y are the mouse positions relative to the document\n",
+ " var boundingRect = targ.getBoundingClientRect();\n",
+ " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
+ " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
+ "\n",
+ " return { x: x, y: y };\n",
+ "};\n",
+ "\n",
+ "/*\n",
+ " * return a copy of an object with only non-object keys\n",
+ " * we need this to avoid circular references\n",
+ " * http://stackoverflow.com/a/24161582/3208463\n",
+ " */\n",
+ "function simpleKeys(original) {\n",
+ " return Object.keys(original).reduce(function (obj, key) {\n",
+ " if (typeof original[key] !== 'object') {\n",
+ " obj[key] = original[key];\n",
+ " }\n",
+ " return obj;\n",
+ " }, {});\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.mouse_event = function (event, name) {\n",
+ " var canvas_pos = mpl.findpos(event);\n",
+ "\n",
+ " if (name === 'button_press') {\n",
+ " this.canvas.focus();\n",
+ " this.canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " var x = canvas_pos.x * this.ratio;\n",
+ " var y = canvas_pos.y * this.ratio;\n",
+ "\n",
+ " this.send_message(name, {\n",
+ " x: x,\n",
+ " y: y,\n",
+ " button: event.button,\n",
+ " step: event.step,\n",
+ " guiEvent: simpleKeys(event),\n",
+ " });\n",
+ "\n",
+ " /* This prevents the web browser from automatically changing to\n",
+ " * the text insertion cursor when the button is pressed. We want\n",
+ " * to control all of the cursor setting manually through the\n",
+ " * 'cursor' event from matplotlib */\n",
+ " event.preventDefault();\n",
+ " return false;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
+ " // Handle any extra behaviour associated with a key event\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.key_event = function (event, name) {\n",
+ " // Prevent repeat events\n",
+ " if (name === 'key_press') {\n",
+ " if (event.which === this._key) {\n",
+ " return;\n",
+ " } else {\n",
+ " this._key = event.which;\n",
+ " }\n",
+ " }\n",
+ " if (name === 'key_release') {\n",
+ " this._key = null;\n",
+ " }\n",
+ "\n",
+ " var value = '';\n",
+ " if (event.ctrlKey && event.which !== 17) {\n",
+ " value += 'ctrl+';\n",
+ " }\n",
+ " if (event.altKey && event.which !== 18) {\n",
+ " value += 'alt+';\n",
+ " }\n",
+ " if (event.shiftKey && event.which !== 16) {\n",
+ " value += 'shift+';\n",
+ " }\n",
+ "\n",
+ " value += 'k';\n",
+ " value += event.which.toString();\n",
+ "\n",
+ " this._key_event_extra(event, name);\n",
+ "\n",
+ " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
+ " return false;\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
+ " if (name === 'download') {\n",
+ " this.handle_save(this, null);\n",
+ " } else {\n",
+ " this.send_message('toolbar_button', { name: name });\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
+ " this.message.textContent = tooltip;\n",
+ "};\n",
+ "\n",
+ "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
+ "// prettier-ignore\n",
+ "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
+ "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+ "\n",
+ "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
+ "\n",
+ "mpl.default_extension = \"png\";/* global mpl */\n",
+ "\n",
+ "var comm_websocket_adapter = function (comm) {\n",
+ " // Create a \"websocket\"-like object which calls the given IPython comm\n",
+ " // object with the appropriate methods. Currently this is a non binary\n",
+ " // socket, so there is still some room for performance tuning.\n",
+ " var ws = {};\n",
+ "\n",
+ " ws.close = function () {\n",
+ " comm.close();\n",
+ " };\n",
+ " ws.send = function (m) {\n",
+ " //console.log('sending', m);\n",
+ " comm.send(m);\n",
+ " };\n",
+ " // Register the callback with on_msg.\n",
+ " comm.on_msg(function (msg) {\n",
+ " //console.log('receiving', msg['content']['data'], msg);\n",
+ " // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
+ " ws.onmessage(msg['content']['data']);\n",
+ " });\n",
+ " return ws;\n",
+ "};\n",
+ "\n",
+ "mpl.mpl_figure_comm = function (comm, msg) {\n",
+ " // This is the function which gets called when the mpl process\n",
+ " // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+ "\n",
+ " var id = msg.content.data.id;\n",
+ " // Get hold of the div created by the display call when the Comm\n",
+ " // socket was opened in Python.\n",
+ " var element = document.getElementById(id);\n",
+ " var ws_proxy = comm_websocket_adapter(comm);\n",
+ "\n",
+ " function ondownload(figure, _format) {\n",
+ " window.open(figure.canvas.toDataURL());\n",
+ " }\n",
+ "\n",
+ " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
+ "\n",
+ " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+ " // web socket which is closed, not our websocket->open comm proxy.\n",
+ " ws_proxy.onopen();\n",
+ "\n",
+ " fig.parent_element = element;\n",
+ " fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+ " if (!fig.cell_info) {\n",
+ " console.error('Failed to find cell for figure', id, fig);\n",
+ " return;\n",
+ " }\n",
+ " fig.cell_info[0].output_area.element.on(\n",
+ " 'cleared',\n",
+ " { fig: fig },\n",
+ " fig._remove_fig_handler\n",
+ " );\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
+ " var width = fig.canvas.width / fig.ratio;\n",
+ " fig.cell_info[0].output_area.element.off(\n",
+ " 'cleared',\n",
+ " fig._remove_fig_handler\n",
+ " );\n",
+ " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
+ "\n",
+ " // Update the output cell to use the data from the current canvas.\n",
+ " fig.push_to_output();\n",
+ " var dataURL = fig.canvas.toDataURL();\n",
+ " // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+ " // the notebook keyboard shortcuts fail.\n",
+ " IPython.keyboard_manager.enable();\n",
+ " fig.parent_element.innerHTML =\n",
+ " '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ " fig.close_ws(fig, msg);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
+ " fig.send_message('closing', msg);\n",
+ " // fig.ws.close()\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
+ " // Turn the data on the canvas into data in the output cell.\n",
+ " var width = this.canvas.width / this.ratio;\n",
+ " var dataURL = this.canvas.toDataURL();\n",
+ " this.cell_info[1]['text/html'] =\n",
+ " '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.updated_canvas_event = function () {\n",
+ " // Tell IPython that the notebook contents must change.\n",
+ " IPython.notebook.set_dirty(true);\n",
+ " this.send_message('ack', {});\n",
+ " var fig = this;\n",
+ " // Wait a second, then push the new image to the DOM so\n",
+ " // that it is saved nicely (might be nice to debounce this).\n",
+ " setTimeout(function () {\n",
+ " fig.push_to_output();\n",
+ " }, 1000);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function () {\n",
+ " var fig = this;\n",
+ "\n",
+ " var toolbar = document.createElement('div');\n",
+ " toolbar.classList = 'btn-toolbar';\n",
+ " this.root.appendChild(toolbar);\n",
+ "\n",
+ " function on_click_closure(name) {\n",
+ " return function (_event) {\n",
+ " return fig.toolbar_button_onclick(name);\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " function on_mouseover_closure(tooltip) {\n",
+ " return function (event) {\n",
+ " if (!event.currentTarget.disabled) {\n",
+ " return fig.toolbar_button_onmouseover(tooltip);\n",
+ " }\n",
+ " };\n",
+ " }\n",
+ "\n",
+ " fig.buttons = {};\n",
+ " var buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'btn-group';\n",
+ " var button;\n",
+ " for (var toolbar_ind in mpl.toolbar_items) {\n",
+ " var name = mpl.toolbar_items[toolbar_ind][0];\n",
+ " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+ " var image = mpl.toolbar_items[toolbar_ind][2];\n",
+ " var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+ "\n",
+ " if (!name) {\n",
+ " /* Instead of a spacer, we start a new button group. */\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ " buttonGroup = document.createElement('div');\n",
+ " buttonGroup.classList = 'btn-group';\n",
+ " continue;\n",
+ " }\n",
+ "\n",
+ " button = fig.buttons[name] = document.createElement('button');\n",
+ " button.classList = 'btn btn-default';\n",
+ " button.href = '#';\n",
+ " button.title = name;\n",
+ " button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
+ " button.addEventListener('click', on_click_closure(method_name));\n",
+ " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
+ " buttonGroup.appendChild(button);\n",
+ " }\n",
+ "\n",
+ " if (buttonGroup.hasChildNodes()) {\n",
+ " toolbar.appendChild(buttonGroup);\n",
+ " }\n",
+ "\n",
+ " // Add the status bar.\n",
+ " var status_bar = document.createElement('span');\n",
+ " status_bar.classList = 'mpl-message pull-right';\n",
+ " toolbar.appendChild(status_bar);\n",
+ " this.message = status_bar;\n",
+ "\n",
+ " // Add the close button to the window.\n",
+ " var buttongrp = document.createElement('div');\n",
+ " buttongrp.classList = 'btn-group inline pull-right';\n",
+ " button = document.createElement('button');\n",
+ " button.classList = 'btn btn-mini btn-primary';\n",
+ " button.href = '#';\n",
+ " button.title = 'Stop Interaction';\n",
+ " button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
+ " button.addEventListener('click', function (_evt) {\n",
+ " fig.handle_close(fig, {});\n",
+ " });\n",
+ " button.addEventListener(\n",
+ " 'mouseover',\n",
+ " on_mouseover_closure('Stop Interaction')\n",
+ " );\n",
+ " buttongrp.appendChild(button);\n",
+ " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
+ " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
+ " var fig = event.data.fig;\n",
+ " if (event.target !== this) {\n",
+ " // Ignore bubbled events from children.\n",
+ " return;\n",
+ " }\n",
+ " fig.close_ws(fig, {});\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function (el) {\n",
+ " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
+ " // this is important to make the div 'focusable\n",
+ " el.setAttribute('tabindex', 0);\n",
+ " // reach out to IPython and tell the keyboard manager to turn it's self\n",
+ " // off when our div gets focus\n",
+ "\n",
+ " // location in version 3\n",
+ " if (IPython.notebook.keyboard_manager) {\n",
+ " IPython.notebook.keyboard_manager.register_events(el);\n",
+ " } else {\n",
+ " // location in version 2\n",
+ " IPython.keyboard_manager.register_events(el);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
+ " var manager = IPython.notebook.keyboard_manager;\n",
+ " if (!manager) {\n",
+ " manager = IPython.keyboard_manager;\n",
+ " }\n",
+ "\n",
+ " // Check for shift+enter\n",
+ " if (event.shiftKey && event.which === 13) {\n",
+ " this.canvas_div.blur();\n",
+ " // select the cell after this one\n",
+ " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
+ " IPython.notebook.select(index + 1);\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
+ " fig.ondownload(fig, null);\n",
+ "};\n",
+ "\n",
+ "mpl.find_output_cell = function (html_output) {\n",
+ " // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+ " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+ " // IPython event is triggered only after the cells have been serialised, which for\n",
+ " // our purposes (turning an active figure into a static one), is too late.\n",
+ " var cells = IPython.notebook.get_cells();\n",
+ " var ncells = cells.length;\n",
+ " for (var i = 0; i < ncells; i++) {\n",
+ " var cell = cells[i];\n",
+ " if (cell.cell_type === 'code') {\n",
+ " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
+ " var data = cell.output_area.outputs[j];\n",
+ " if (data.data) {\n",
+ " // IPython >= 3 moved mimebundle to data attribute of output\n",
+ " data = data.data;\n",
+ " }\n",
+ " if (data['text/html'] === html_output) {\n",
+ " return [cell, data, j];\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ " }\n",
+ "};\n",
+ "\n",
+ "// Register the function which deals with the matplotlib target/channel.\n",
+ "// The kernel may be null if the page has been refreshed.\n",
+ "if (IPython.notebook.kernel !== null) {\n",
+ " IPython.notebook.kernel.comm_manager.register_target(\n",
+ " 'matplotlib',\n",
+ " mpl.mpl_figure_comm\n",
+ " );\n",
+ "}\n"
+ ],
+ "text/plain": [
+ "<IPython.core.display.Javascript object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
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\" width=\"800\">"
+ ],
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "clf_kernel = svm.SVC(kernel=\"rbf\")\n",
+ "clf_kernel.fit(data.loc[:, [\"x\", \"y\"]], data.loc[:, \"source\"])\n",
+ "\n",
+ "fig, ax = plt.subplots(figsize=(8, 8))\n",
+ "plt.scatter(data.loc[:, \"x\"], data.loc[:, \"y\"], c=data.loc[:, \"source\"], s=30, cmap=plt.cm.Paired)\n",
+ "\n",
+ "# plot the decision function\n",
+ "ax = plt.gca()\n",
+ "xlim = ax.get_xlim()\n",
+ "ylim = ax.get_ylim()\n",
+ "\n",
+ "# create grid to evaluate model\n",
+ "xx = np.linspace(xlim[0], xlim[1], 30)\n",
+ "yy = np.linspace(ylim[0], ylim[1], 30)\n",
+ "YY, XX = np.meshgrid(yy, xx)\n",
+ "xy = np.vstack([XX.ravel(), YY.ravel()]).T\n",
+ "Z = clf_kernel.decision_function(xy).reshape(XX.shape)\n",
+ "\n",
+ "# plot decision boundary and margins\n",
+ "ax.contour(\n",
+ " XX, YY, Z, colors=\"k\", levels=[-1, 0, 1], alpha=0.5, linestyles=[\"--\", \"-\", \"--\"]\n",
+ ")\n",
+ "# plot support vectors\n",
+ "ax.scatter(\n",
+ " clf_kernel.support_vectors_[:, 0],\n",
+ " clf_kernel.support_vectors_[:, 1],\n",
+ " s=100,\n",
+ " linewidth=1,\n",
+ " facecolors=\"none\",\n",
+ " edgecolors=\"k\",\n",
+ ")\n",
+ "plt.show()"
+ ]
+ },
{
"cell_type": "markdown",
"id": "df35963b",
@@ -643,8 +3482,7 @@
"source": [
"### Contact us at the EuXFEL Data Analysis group at any time if you need help analysing your data!\n",
"\n",
- "#### Danilo Ferreira de Lima: danilo.enoque.ferreira.de.lima@xfel.eu\n",
- "#### Arman Davtyan: arman.davtyan@xfel.eu"
+ "#### Data Analysis group: da@xfel.eu"
]
},
{
@@ -672,7 +3510,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.7.10"
+ "version": "3.6.13"
}
},
"nbformat": 4,
diff --git a/user_meeting_ml_intro_jan_2022.pdf b/user_meeting_ml_intro_jan_2022.pdf
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