From 82d1713442162063efb3b093fb5ea048cbdb185c Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Lo=C3=AFc=20Le=20Guyader?= <loic.le.guyader@xfel.eu>
Date: Tue, 31 Aug 2021 16:42:25 +0200
Subject: [PATCH] Boz issue26
---
...ysis part I parameters determination.ipynb | 147 +-
doc/BOZ analysis part II run processing.ipynb | 4386 ++++++++++++++++-
doc/howtos.rst | 41 +-
setup.py | 4 +-
src/toolbox_scs/routines/boz.py | 4 +-
5 files changed, 4289 insertions(+), 293 deletions(-)
diff --git a/doc/BOZ analysis part I parameters determination.ipynb b/doc/BOZ analysis part I parameters determination.ipynb
index 750b0d3..82f8741 100644
--- a/doc/BOZ analysis part I parameters determination.ipynb
+++ b/doc/BOZ analysis part I parameters determination.ipynb
@@ -13,126 +13,20 @@
"\n",
"import dask\n",
"print(f'dask: {dask.__version__}')\n",
- "import dask.array as da\n",
- "from dask.distributed import Client, progress\n",
- "from dask_jobqueue import SLURMCluster\n",
"\n",
- "import netCDF4\n",
- "import pickle"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
"from psutil import virtual_memory\n",
- "import gc\n",
- "# gc.collect() # run garbage collection to free possible memory\n",
"\n",
"mem = virtual_memory()\n",
- "print(f'Physical memory: {mem.total/1024/1024/1024:.0f} Gb') # total physical memory available"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "import logging\n",
- "logging.basicConfig(filename='example.log', level=logging.DEBUG)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "%load_ext autoreload\n",
+ "print(f'Physical memory: {mem.total/1024/1024/1024:.0f} Gb') # total physical memory available\n",
"\n",
- "%autoreload 2\n",
+ "import logging\n",
+ "logging.basicConfig(filename='example.log', level=logging.DEBUG)\n",
"\n",
"import toolbox_scs as tb\n",
"print(tb.__file__)\n",
"import toolbox_scs.routines.boz as boz"
]
},
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "%load_ext line_profiler\n",
- "%load_ext memory_profiler"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Slum cluster setup"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Change to *True* to allocate a slurm cluster and run the calculation on it instead of the current machine."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "if False:\n",
- " partition = 'exfel' # For users\n",
- " # partition = 'upex' # For users\n",
- "\n",
- " cluster = SLURMCluster(\n",
- " queue=partition,\n",
- " local_directory='/scratch', # Local disk space for workers to use\n",
- " \n",
- " # Resources per SLURM job (per node, the way SLURM is configured on Maxwell)\n",
- " # processes=16 runs 16 Dask workers in a job, so each worker has 1 core & 32 GB RAM.\n",
- " processes=8, cores=16, memory='512GB',\n",
- " walltime='9:00:00',\n",
- " #interface='ib0',\n",
- " #job_extra=[\"--reservation=upex_002619\"] # reserved partition\n",
- " )\n",
- "\n",
- " # dashboard link\n",
- " # print('https://max-jhub.desy.de/user/lleguy/proxy/8787/graph')\n",
- " \n",
- " # Submit 2 SLURM jobs, for 32 Dask workers\n",
- " cluster.scale(32)\n",
- " #cluster.adapt(minimum=0, maximum=32)\n",
- " \n",
- " client = Client(cluster)\n",
- " print(\"Created dask client:\", client)\n",
- " \n",
- " # Get a notbook widget showing the cluster state\n",
- " cluster"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "try:\n",
- " client.close()\n",
- " cluster.close()\n",
- "except:\n",
- " print('No client defined')"
- ]
- },
{
"cell_type": "markdown",
"metadata": {},
@@ -163,8 +57,20 @@
"metadata": {},
"outputs": [],
"source": [
- "params = boz.parameters(proposal=proposal, darkrun=darkrun, run=run, module=module, gain=gain)\n",
- "path = f'r{params.run}/'"
+ "params = boz.parameters(proposal=proposal, darkrun=darkrun, run=run, module=module, gain=gain)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from extra_data.read_machinery import find_proposal\n",
+ "\n",
+ "root = find_proposal(f'p{proposal:06d}')\n",
+ "path = root + '/usr/processed_runs/' + f'r{params.run}/'\n",
+ "print(path)"
]
},
{
@@ -306,7 +212,7 @@
"metadata": {},
"outputs": [],
"source": [
- "params.rois_th = 1\n",
+ "params.rois_th = 4\n",
"params.rois = boz.find_rois_from_params(params)"
]
},
@@ -460,6 +366,23 @@
"# Non-linearities correction extraction"
]
},
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "To speed up online analysis, we save the corrections with a dummy non-linearity correction. The saved file can be used for online analysis as soon as it appears."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "params.set_Fnl(np.arange(2**9))\n",
+ "params.save(path=path)"
+ ]
+ },
{
"cell_type": "code",
"execution_count": null,
diff --git a/doc/BOZ analysis part II run processing.ipynb b/doc/BOZ analysis part II run processing.ipynb
index c4a14ab..88b8de8 100644
--- a/doc/BOZ analysis part II run processing.ipynb
+++ b/doc/BOZ analysis part II run processing.ipynb
@@ -2,9 +2,18 @@
"cells": [
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 1,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "dask: 2.11.0\n",
+ "Physical memory: 754 Gb\n"
+ ]
+ }
+ ],
"source": [
"import numpy as np\n",
"%matplotlib notebook\n",
@@ -13,43 +22,32 @@
"\n",
"import dask\n",
"print(f'dask: {dask.__version__}')\n",
- "import dask.array as da\n",
- "from dask.distributed import Client, progress\n",
- "from dask_jobqueue import SLURMCluster\n",
"\n",
"import netCDF4\n",
- "import xarray as xr"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
+ "import xarray as xr\n",
+ "\n",
"from psutil import virtual_memory\n",
- "import gc\n",
- "# gc.collect() # run garbage collection to free possible memory\n",
"\n",
"mem = virtual_memory()\n",
- "print(f'Physical memory: {mem.total/1024/1024/1024:.0f} Gb') # total physical memory available"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
+ "print(f'Physical memory: {mem.total/1024/1024/1024:.0f} Gb') # total physical memory available\n",
+ "\n",
"import logging\n",
"logging.basicConfig(filename='example.log', level=logging.DEBUG)"
]
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 2,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "/home/lleguy/notebooks/ToolBox/src/toolbox_scs/__init__.py\n"
+ ]
+ }
+ ],
"source": [
"%load_ext autoreload\n",
"\n",
@@ -57,105 +55,187 @@
"\n",
"import toolbox_scs as tb\n",
"print(tb.__file__)\n",
- "import toolbox_scs.routines.boz as boz"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "%load_ext line_profiler\n",
- "%load_ext memory_profiler"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Slum cluster setup"
+ "import toolbox_scs.routines.boz as boz\n",
+ "\n",
+ "from extra_data.read_machinery import find_proposal"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "Change to *True* to allocate a slurm cluster and run the calculation on it instead of the current machine."
+ "# Loading analysis parameters"
]
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
- "if False:\n",
- " partition = 'exfel' # For users\n",
- " # partition = 'upex' # For users\n",
- "\n",
- " cluster = SLURMCluster(\n",
- " queue=partition,\n",
- " local_directory='/scratch', # Local disk space for workers to use\n",
- " \n",
- " # Resources per SLURM job (per node, the way SLURM is configured on Maxwell)\n",
- " # processes=16 runs 16 Dask workers in a job, so each worker has 1 core & 32 GB RAM.\n",
- " processes=8, cores=16, memory='512GB',\n",
- " walltime='24:00:00',\n",
- " #interface='ib0',\n",
- " #job_extra=[\"--reservation=upex_002619\"] # reserved partition\n",
- " )\n",
- "\n",
- " # dashboard link\n",
- " # print('https://max-jhub.desy.de/user/lleguy/proxy/8787/graph')\n",
- " \n",
- " # Submit 2 SLURM jobs, for 32 Dask workers\n",
- " cluster.scale(32)\n",
- " #cluster.adapt(minimum=0, maximum=32)\n",
- " \n",
- " client = Client(cluster)\n",
- " print(\"Created dask client:\", client)\n",
- " \n",
- " # Get a notbook widget showing the cluster state\n",
- " cluster"
+ "proposal = 2937\n",
+ "root = find_proposal(f'p{proposal:06d}')\n",
+ "path = root + '/usr/processed_runs/'"
]
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
- "try:\n",
- " client.close()\n",
- " cluster.close()\n",
- "except:\n",
- " print('No client defined')"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# Loading analysis parameters"
+ "params = boz.parameters.load(path + 'r614/parameters_p2937_d615_r614.json')"
]
},
{
"cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "params = boz.parameters.load('./parameters_p2712_d5_r6.json')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
+ "execution_count": 5,
"metadata": {
"scrolled": false
},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "proposal:2937 darkrun:615 run:614 module:15 gain:3 ph/bin\n",
+ "mean threshold:[15.974982271301599, 70.9749822713016] std threshold:[None, None]\n",
+ "mask:(#7) [[15, 437], [36, 477], [43, 506], [71, 451], [76, 302], [108, 185], [125, 296]]\n",
+ "rois threshold: 4\n",
+ "rois: {'b0': {'xl': 0, 'xh': 64, 'yl': 0, 'yh': 23}, 'b1': {'xl': 64, 'xh': 128, 'yl': 0, 'yh': 23}, 'b2': {'xl': 128, 'xh': 192, 'yl': 0, 'yh': 23}, 'b3': {'xl': 192, 'xh': 256, 'yl': 0, 'yh': 23}, 'b8': {'xl': 0, 'xh': 64, 'yl': 105, 'yh': 128}, 'b9': {'xl': 64, 'xh': 128, 'yl': 105, 'yh': 128}, 'b10': {'xl': 128, 'xh': 192, 'yl': 105, 'yh': 128}, 'b11': {'xl': 192, 'xh': 256, 'yl': 105, 'yh': 128}, 'n': {'xl': 12, 'xh': 89, 'yl': 23, 'yh': 105}, '0': {'xl': 89, 'xh': 167, 'yl': 23, 'yh': 105}, 'p': {'xl': 167, 'xh': 245, 'yl': 23, 'yh': 105}, 'sat': {'xl': 12, 'xh': 245, 'yl': 23, 'yh': 105}, '0X': {'xl': 12, 'xh': 64, 'yl': 23, 'yh': 64}, '1X1': {'xl': 64, 'xh': 89, 'yl': 23, 'yh': 64}, '1X2': {'xl': 89, 'xh': 128, 'yl': 23, 'yh': 64}, '2X1': {'xl': 128, 'xh': 167, 'yl': 23, 'yh': 64}, '2X2': {'xl': 167, 'xh': 192, 'yl': 23, 'yh': 64}, '3X': {'xl': 192, 'xh': 245, 'yl': 23, 'yh': 64}, '8X': {'xl': 12, 'xh': 64, 'yl': 64, 'yh': 105}, '9X1': {'xl': 64, 'xh': 89, 'yl': 64, 'yh': 105}, '9X2': {'xl': 89, 'xh': 128, 'yl': 64, 'yh': 105}, '10X1': {'xl': 128, 'xh': 167, 'yl': 64, 'yh': 105}, '10X2': {'xl': 167, 'xh': 192, 'yl': 64, 'yh': 105}, '11X': {'xl': 192, 'xh': 245, 'yl': 64, 'yh': 105}}\n",
+ "flat field: [-0.5594258486434432, 0.0014918759956336746, 1.0865116797604366, -0.4173933792722743]\n",
+ "dFnl: [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 -1.39492179e-01 -1.39492179e-01 -1.39492179e-01\n",
+ " -1.39492179e-01 -1.39492179e-01 -1.39492179e-01 -2.03635879e-01\n",
+ " -2.03635879e-01 -2.03635879e-01 -2.03635879e-01 -2.03635879e-01\n",
+ " -2.03635879e-01 1.91067813e-01 1.91067813e-01 1.91067813e-01\n",
+ " 1.91067813e-01 1.91067813e-01 1.91067813e-01 1.98444550e-01\n",
+ " 1.98444550e-01 1.98444550e-01 1.98444550e-01 1.98444550e-01\n",
+ " 1.98444550e-01 6.05373005e-01 6.05373005e-01 6.05373005e-01\n",
+ " 6.05373005e-01 6.05373005e-01 6.05373005e-01 3.27109078e-01\n",
+ " 3.27109078e-01 3.27109078e-01 3.27109078e-01 3.27109078e-01\n",
+ " 3.27109078e-01 1.22383397e-01 1.22383397e-01 1.22383397e-01\n",
+ " 1.22383397e-01 1.22383397e-01 1.22383397e-01 -2.13137092e-02\n",
+ " -2.13137092e-02 -2.13137092e-02 -2.13137092e-02 -2.13137092e-02\n",
+ " -7.59610481e-02 -7.59610481e-02 -7.59610481e-02 -7.59610481e-02\n",
+ " -7.59610481e-02 -7.59610481e-02 -1.53985644e-01 -1.53985644e-01\n",
+ " -1.53985644e-01 -1.53985644e-01 -1.53985644e-01 -1.53985644e-01\n",
+ " -2.10251513e-01 -2.10251513e-01 -2.10251513e-01 -2.10251513e-01\n",
+ " -2.10251513e-01 -2.10251513e-01 -3.41778014e-01 -3.41778014e-01\n",
+ " -3.41778014e-01 -3.41778014e-01 -3.41778014e-01 -3.41778014e-01\n",
+ " -3.33185220e-01 -3.33185220e-01 -3.33185220e-01 -3.33185220e-01\n",
+ " -3.33185220e-01 -3.33185220e-01 -2.75193204e-01 -2.75193204e-01\n",
+ " -2.75193204e-01 -2.75193204e-01 -2.75193204e-01 -2.75193204e-01\n",
+ " -3.36106486e-01 -3.36106486e-01 -3.36106486e-01 -3.36106486e-01\n",
+ " -3.36106486e-01 -3.59498908e-01 -3.59498908e-01 -3.59498908e-01\n",
+ " -3.59498908e-01 -3.59498908e-01 -3.59498908e-01 -4.89492981e-01\n",
+ " -4.89492981e-01 -4.89492981e-01 -4.89492981e-01 -4.89492981e-01\n",
+ " -4.89492981e-01 -5.00688300e-01 -5.00688300e-01 -5.00688300e-01\n",
+ " -5.00688300e-01 -5.00688300e-01 -5.00688300e-01 -5.27674265e-01\n",
+ " -5.27674265e-01 -5.27674265e-01 -5.27674265e-01 -5.27674265e-01\n",
+ " -5.27674265e-01 -3.86711554e-01 -3.86711554e-01 -3.86711554e-01\n",
+ " -3.86711554e-01 -3.86711554e-01 -3.86711554e-01 -3.44023249e-01\n",
+ " -3.44023249e-01 -3.44023249e-01 -3.44023249e-01 -3.44023249e-01\n",
+ " -3.44023249e-01 -2.22420449e-01 -2.22420449e-01 -2.22420449e-01\n",
+ " -2.22420449e-01 -2.22420449e-01 -9.77934794e-02 -9.77934794e-02\n",
+ " -9.77934794e-02 -9.77934794e-02 -9.77934794e-02 -9.77934794e-02\n",
+ " 1.76032659e-02 1.76032659e-02 1.76032659e-02 1.76032659e-02\n",
+ " 1.76032659e-02 1.76032659e-02 1.64466308e-01 1.64466308e-01\n",
+ " 1.64466308e-01 1.64466308e-01 1.64466308e-01 1.64466308e-01\n",
+ " 3.00781472e-01 3.00781472e-01 3.00781472e-01 3.00781472e-01\n",
+ " 3.00781472e-01 3.00781472e-01 3.51771494e-01 3.51771494e-01\n",
+ " 3.51771494e-01 3.51771494e-01 3.51771494e-01 3.51771494e-01\n",
+ " 3.41283938e-01 3.41283938e-01 3.41283938e-01 3.41283938e-01\n",
+ " 3.41283938e-01 3.41283938e-01 3.66648375e-01 3.66648375e-01\n",
+ " 3.66648375e-01 3.66648375e-01 3.66648375e-01 3.66648375e-01\n",
+ " 2.54320844e-01 2.54320844e-01 2.54320844e-01 2.54320844e-01\n",
+ " 2.54320844e-01 2.05588198e-01 2.05588198e-01 2.05588198e-01\n",
+ " 2.05588198e-01 2.05588198e-01 2.05588198e-01 1.63901858e-01\n",
+ " 1.63901858e-01 1.63901858e-01 1.63901858e-01 1.63901858e-01\n",
+ " 1.63901858e-01 9.16838860e-02 9.16838860e-02 9.16838860e-02\n",
+ " 9.16838860e-02 9.16838860e-02 9.16838860e-02 6.27706770e-02\n",
+ " 6.27706770e-02 6.27706770e-02 6.27706770e-02 6.27706770e-02\n",
+ " 6.27706770e-02 3.24587803e-02 3.24587803e-02 3.24587803e-02\n",
+ " 3.24587803e-02 3.24587803e-02 3.24587803e-02 2.16135883e-02\n",
+ " 2.16135883e-02 2.16135883e-02 2.16135883e-02 2.16135883e-02\n",
+ " 2.16135883e-02 1.10815639e-02 1.10815639e-02 1.10815639e-02\n",
+ " 1.10815639e-02 1.10815639e-02 6.28962090e-03 6.28962090e-03\n",
+ " 6.28962090e-03 6.28962090e-03 6.28962090e-03 6.28962090e-03\n",
+ " 2.63753757e-03 2.63753757e-03 2.63753757e-03 2.63753757e-03\n",
+ " 2.63753757e-03 2.63753757e-03 1.19182402e-03 1.19182402e-03\n",
+ " 1.19182402e-03 1.19182402e-03 1.19182402e-03 1.19182402e-03\n",
+ " 1.20079424e-04 1.20079424e-04 1.20079424e-04 1.20079424e-04\n",
+ " 1.20079424e-04 1.20079424e-04 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 -1.09490506e-03 -1.09490506e-03\n",
+ " -1.09490506e-03 -1.09490506e-03 -1.09490506e-03 -1.44358140e-04\n",
+ " -1.44358140e-04 -1.44358140e-04 -1.44358140e-04 -1.44358140e-04\n",
+ " -1.44358140e-04 8.29938751e-05 8.29938751e-05 8.29938751e-05\n",
+ " 8.29938751e-05 8.29938751e-05 8.29938751e-05 3.64660210e-04\n",
+ " 3.64660210e-04 3.64660210e-04 3.64660210e-04 3.64660210e-04\n",
+ " 3.64660210e-04 4.11052448e-04 4.11052448e-04 4.11052448e-04\n",
+ " 4.11052448e-04 4.11052448e-04 4.11052448e-04 2.97971008e-04\n",
+ " 2.97971008e-04 2.97971008e-04 2.97971008e-04 2.97971008e-04\n",
+ " 2.97971008e-04 3.20935561e-04 3.20935561e-04 3.20935561e-04\n",
+ " 3.20935561e-04 3.20935561e-04 3.20935561e-04 9.23245940e-05\n",
+ " 9.23245940e-05 9.23245940e-05 9.23245940e-05 9.23245940e-05\n",
+ " 1.60401167e-05 1.60401167e-05 1.60401167e-05 1.60401167e-05\n",
+ " 1.60401167e-05 1.60401167e-05 -6.81261911e-05 -6.81261911e-05\n",
+ " -6.81261911e-05 -6.81261911e-05 -6.81261911e-05 -6.81261911e-05\n",
+ " -6.38832428e-05 -6.38832428e-05 -6.38832428e-05 -6.38832428e-05\n",
+ " -6.38832428e-05 -6.38832428e-05 -6.29203175e-05 -6.29203175e-05\n",
+ " -6.29203175e-05 -6.29203175e-05 -6.29203175e-05 -6.29203175e-05\n",
+ " 7.18542688e-05 7.18542688e-05 7.18542688e-05 7.18542688e-05\n",
+ " 7.18542688e-05 7.18542688e-05 -4.19697282e-05 -4.19697282e-05\n",
+ " -4.19697282e-05 -4.19697282e-05 -4.19697282e-05 -4.19697282e-05\n",
+ " -8.58622520e-05 -8.58622520e-05 -8.58622520e-05 -8.58622520e-05\n",
+ " -8.58622520e-05 -8.58622520e-05 -1.15160075e-04 -1.15160075e-04\n",
+ " -1.15160075e-04 -1.15160075e-04 -1.15160075e-04 -5.18939116e-05\n",
+ " -5.18939116e-05 -5.18939116e-05 -5.18939116e-05 -5.18939116e-05\n",
+ " -5.18939116e-05 -6.25558991e-05 -6.25558991e-05 -6.25558991e-05\n",
+ " -6.25558991e-05 -6.25558991e-05 -6.25558991e-05 -3.33632570e-05\n",
+ " -3.33632570e-05 -3.33632570e-05 -3.33632570e-05 -3.33632570e-05\n",
+ " -3.33632570e-05 1.59375355e-06 1.59375355e-06 1.59375355e-06\n",
+ " 1.59375355e-06 1.59375355e-06 1.59375355e-06 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
+ " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00]\n",
+ "alpha:0.5, sat. level:511, max. iter.:25\n"
+ ]
+ }
+ ],
"source": [
"print(params)"
]
@@ -176,22 +256,811 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
- "proposalNB = 2712\n",
- "darkrunNB = 10\n",
+ "darkrunNB = 641\n",
"moduleNB = 15\n",
"\n",
- "arr_dark, tid_dark = boz.load_dssc_module(proposalNB, darkrunNB, moduleNB)"
+ "arr_dark, tid_dark = boz.load_dssc_module(proposal, darkrunNB, moduleNB)"
]
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 13,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "application/javascript": [
+ "/* Put everything inside the global mpl namespace */\n",
+ "window.mpl = {};\n",
+ "\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('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",
+ "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 = $('<div/>');\n",
+ " this._root_extra_style(this.root)\n",
+ " this.root.attr('style', 'display: inline-block');\n",
+ "\n",
+ " $(parent_element).append(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 (mpl.ratio != 1) {\n",
+ " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.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 = $(\n",
+ " '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
+ " 'ui-helper-clearfix\"/>');\n",
+ " var titletext = $(\n",
+ " '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
+ " 'text-align: center; padding: 3px;\"/>');\n",
+ " titlebar.append(titletext)\n",
+ " this.root.append(titlebar);\n",
+ " this.header = titletext[0];\n",
+ "}\n",
+ "\n",
+ "\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
+ "\n",
+ "}\n",
+ "\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
+ "\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._init_canvas = function() {\n",
+ " var fig = this;\n",
+ "\n",
+ " var canvas_div = $('<div/>');\n",
+ "\n",
+ " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
+ "\n",
+ " function canvas_keyboard_event(event) {\n",
+ " return fig.key_event(event, event['data']);\n",
+ " }\n",
+ "\n",
+ " canvas_div.keydown('key_press', canvas_keyboard_event);\n",
+ " canvas_div.keyup('key_release', canvas_keyboard_event);\n",
+ " this.canvas_div = canvas_div\n",
+ " this._canvas_extra_style(canvas_div)\n",
+ " this.root.append(canvas_div);\n",
+ "\n",
+ " var canvas = $('<canvas/>');\n",
+ " canvas.addClass('mpl-canvas');\n",
+ " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
+ "\n",
+ " this.canvas = canvas[0];\n",
+ " this.context = canvas[0].getContext(\"2d\");\n",
+ "\n",
+ " var backingStore = this.context.backingStorePixelRatio ||\n",
+ "\tthis.context.webkitBackingStorePixelRatio ||\n",
+ "\tthis.context.mozBackingStorePixelRatio ||\n",
+ "\tthis.context.msBackingStorePixelRatio ||\n",
+ "\tthis.context.oBackingStorePixelRatio ||\n",
+ "\tthis.context.backingStorePixelRatio || 1;\n",
+ "\n",
+ " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+ "\n",
+ " var rubberband = $('<canvas/>');\n",
+ " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
+ "\n",
+ " var pass_mouse_events = true;\n",
+ "\n",
+ " canvas_div.resizable({\n",
+ " start: function(event, ui) {\n",
+ " pass_mouse_events = false;\n",
+ " },\n",
+ " resize: function(event, ui) {\n",
+ " fig.request_resize(ui.size.width, ui.size.height);\n",
+ " },\n",
+ " stop: function(event, ui) {\n",
+ " pass_mouse_events = true;\n",
+ " fig.request_resize(ui.size.width, ui.size.height);\n",
+ " },\n",
+ " });\n",
+ "\n",
+ " function mouse_event_fn(event) {\n",
+ " if (pass_mouse_events)\n",
+ " return fig.mouse_event(event, event['data']);\n",
+ " }\n",
+ "\n",
+ " rubberband.mousedown('button_press', mouse_event_fn);\n",
+ " rubberband.mouseup('button_release', mouse_event_fn);\n",
+ " // Throttle sequential mouse events to 1 every 20ms.\n",
+ " rubberband.mousemove('motion_notify', mouse_event_fn);\n",
+ "\n",
+ " rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
+ " rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
+ "\n",
+ " canvas_div.on(\"wheel\", function (event) {\n",
+ " event = event.originalEvent;\n",
+ " event['data'] = 'scroll'\n",
+ " if (event.deltaY < 0) {\n",
+ " event.step = 1;\n",
+ " } else {\n",
+ " event.step = -1;\n",
+ " }\n",
+ " mouse_event_fn(event);\n",
+ " });\n",
+ "\n",
+ " canvas_div.append(canvas);\n",
+ " canvas_div.append(rubberband);\n",
+ "\n",
+ " this.rubberband = rubberband;\n",
+ " this.rubberband_canvas = rubberband[0];\n",
+ " this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
+ " this.rubberband_context.strokeStyle = \"#000000\";\n",
+ "\n",
+ " this._resize_canvas = function(width, height) {\n",
+ " // Keep the size of the canvas, canvas container, and rubber band\n",
+ " // canvas in synch.\n",
+ " canvas_div.css('width', width)\n",
+ " canvas_div.css('height', height)\n",
+ "\n",
+ " canvas.attr('width', width * mpl.ratio);\n",
+ " canvas.attr('height', height * mpl.ratio);\n",
+ " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
+ "\n",
+ " rubberband.attr('width', width);\n",
+ " rubberband.attr('height', height);\n",
+ " }\n",
+ "\n",
+ " // Set the figure to an initial 600x600px, this will subsequently be updated\n",
+ " // upon first draw.\n",
+ " this._resize_canvas(600, 600);\n",
+ "\n",
+ " // Disable right mouse context menu.\n",
+ " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\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 nav_element = $('<div/>');\n",
+ " nav_element.attr('style', 'width: 100%');\n",
+ " this.root.append(nav_element);\n",
+ "\n",
+ " // Define a callback function for later on.\n",
+ " function toolbar_event(event) {\n",
+ " return fig.toolbar_button_onclick(event['data']);\n",
+ " }\n",
+ " function toolbar_mouse_event(event) {\n",
+ " return fig.toolbar_button_onmouseover(event['data']);\n",
+ " }\n",
+ "\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",
+ " // put a spacer in here.\n",
+ " continue;\n",
+ " }\n",
+ " var button = $('<button/>');\n",
+ " button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
+ " 'ui-button-icon-only');\n",
+ " button.attr('role', 'button');\n",
+ " button.attr('aria-disabled', 'false');\n",
+ " button.click(method_name, toolbar_event);\n",
+ " button.mouseover(tooltip, toolbar_mouse_event);\n",
+ "\n",
+ " var icon_img = $('<span/>');\n",
+ " icon_img.addClass('ui-button-icon-primary ui-icon');\n",
+ " icon_img.addClass(image);\n",
+ " icon_img.addClass('ui-corner-all');\n",
+ "\n",
+ " var tooltip_span = $('<span/>');\n",
+ " tooltip_span.addClass('ui-button-text');\n",
+ " tooltip_span.html(tooltip);\n",
+ "\n",
+ " button.append(icon_img);\n",
+ " button.append(tooltip_span);\n",
+ "\n",
+ " nav_element.append(button);\n",
+ " }\n",
+ "\n",
+ " var fmt_picker_span = $('<span/>');\n",
+ "\n",
+ " var fmt_picker = $('<select/>');\n",
+ " fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
+ " fmt_picker_span.append(fmt_picker);\n",
+ " nav_element.append(fmt_picker_span);\n",
+ " this.format_dropdown = fmt_picker[0];\n",
+ "\n",
+ " for (var ind in mpl.extensions) {\n",
+ " var fmt = mpl.extensions[ind];\n",
+ " var option = $(\n",
+ " '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
+ " fmt_picker.append(option);\n",
+ " }\n",
+ "\n",
+ " // Add hover states to the ui-buttons\n",
+ " $( \".ui-button\" ).hover(\n",
+ " function() { $(this).addClass(\"ui-state-hover\");},\n",
+ " function() { $(this).removeClass(\"ui-state-hover\");}\n",
+ " );\n",
+ "\n",
+ " var status_bar = $('<span class=\"mpl-message\"/>');\n",
+ " nav_element.append(status_bar);\n",
+ " this.message = status_bar[0];\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",
+ "\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",
+ "\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]);\n",
+ " fig.send_message(\"refresh\", {});\n",
+ " };\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
+ " var x0 = msg['x0'] / mpl.ratio;\n",
+ " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
+ " var x1 = msg['x1'] / mpl.ratio;\n",
+ " var y1 = (fig.canvas.height - msg['y1']) / mpl.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, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\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",
+ " {\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.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",
+ " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+ " evt.data);\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ " else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\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(\"No handler for the '\" + msg_type + \"' message type: \", msg);\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(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\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",
+ " if (e.target)\n",
+ " targ = e.target;\n",
+ " else if (e.srcElement)\n",
+ " targ = e.srcElement;\n",
+ " if (targ.nodeType == 3) // defeat Safari bug\n",
+ " targ = targ.parentNode;\n",
+ "\n",
+ " // jQuery normalizes the pageX and pageY\n",
+ " // pageX,Y are the mouse positions relative to the document\n",
+ " // offset() returns the position of the element relative to the document\n",
+ " var x = e.pageX - $(targ).offset().left;\n",
+ " var y = e.pageY - $(targ).offset().top;\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",
+ " 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",
+ " {\n",
+ " this.canvas.focus();\n",
+ " this.canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " var x = canvas_pos.x * mpl.ratio;\n",
+ " var y = canvas_pos.y * mpl.ratio;\n",
+ "\n",
+ " this.send_message(name, {x: x, y: y, button: event.button,\n",
+ " step: event.step,\n",
+ " guiEvent: simpleKeys(event)});\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",
+ "\n",
+ " // Prevent repeat events\n",
+ " if (name == 'key_press')\n",
+ " {\n",
+ " if (event.which === this._key)\n",
+ " return;\n",
+ " else\n",
+ " this._key = event.which;\n",
+ " }\n",
+ " if (name == 'key_release')\n",
+ " this._key = null;\n",
+ "\n",
+ " var value = '';\n",
+ " if (event.ctrlKey && event.which != 17)\n",
+ " value += \"ctrl+\";\n",
+ " if (event.altKey && event.which != 18)\n",
+ " value += \"alt+\";\n",
+ " if (event.shiftKey && event.which != 16)\n",
+ " value += \"shift+\";\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,\n",
+ " 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",
+ "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\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"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\";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 = $(\"#\" + id);\n",
+ " var ws_proxy = comm_websocket_adapter(comm)\n",
+ "\n",
+ " function ondownload(figure, format) {\n",
+ " window.open(figure.imageObj.src);\n",
+ " }\n",
+ "\n",
+ " var fig = new mpl.figure(id, ws_proxy,\n",
+ " ondownload,\n",
+ " element.get(0));\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.get(0);\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",
+ "\n",
+ " var output_index = fig.cell_info[2]\n",
+ " var cell = fig.cell_info[0];\n",
+ "\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
+ " var width = fig.canvas.width/mpl.ratio\n",
+ " fig.root.unbind('remove')\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).html('<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/mpl.ratio\n",
+ " var dataURL = this.canvas.toDataURL();\n",
+ " this.cell_info[1]['text/html'] = '<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 () { fig.push_to_output() }, 1000);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function() {\n",
+ " var fig = this;\n",
+ "\n",
+ " var nav_element = $('<div/>');\n",
+ " nav_element.attr('style', 'width: 100%');\n",
+ " this.root.append(nav_element);\n",
+ "\n",
+ " // Define a callback function for later on.\n",
+ " function toolbar_event(event) {\n",
+ " return fig.toolbar_button_onclick(event['data']);\n",
+ " }\n",
+ " function toolbar_mouse_event(event) {\n",
+ " return fig.toolbar_button_onmouseover(event['data']);\n",
+ " }\n",
+ "\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) { continue; };\n",
+ "\n",
+ " var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
+ " button.click(method_name, toolbar_event);\n",
+ " button.mouseover(tooltip, toolbar_mouse_event);\n",
+ " nav_element.append(button);\n",
+ " }\n",
+ "\n",
+ " // Add the status bar.\n",
+ " var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
+ " nav_element.append(status_bar);\n",
+ " this.message = status_bar[0];\n",
+ "\n",
+ " // Add the close button to the window.\n",
+ " var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
+ " var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
+ " button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
+ " button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
+ " buttongrp.append(button);\n",
+ " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
+ " titlebar.prepend(buttongrp);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function(el){\n",
+ " var fig = this\n",
+ " el.on(\"remove\", function(){\n",
+ "\tfig.close_ws(fig, {});\n",
+ " });\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function(el){\n",
+ " // this is important to make the div 'focusable\n",
+ " el.attr('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",
+ " }\n",
+ " else {\n",
+ " // location in version 2\n",
+ " IPython.keyboard_manager.register_events(el);\n",
+ " }\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",
+ " // 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",
+ "\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('matplotlib', mpl.mpl_figure_comm);\n",
+ "}\n"
+ ],
+ "text/plain": [
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+ ]
+ },
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+ "output_type": "display_data"
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\" width=\"700\">"
+ ],
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
"source": [
"f = boz.inspect_dark(arr_dark)"
]
@@ -212,30 +1081,820 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
- "runNB = 13"
+ "runNB = 646"
]
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"dark = boz.average_module(arr_dark).compute()\n",
- "arr, tid = boz.load_dssc_module(proposalNB, runNB, moduleNB)\n",
+ "arr, tid = boz.load_dssc_module(proposal, runNB, moduleNB)\n",
"data = boz.average_module(arr, dark=dark).compute()\n",
"dataM = data.mean(axis=0) # mean over pulseId"
]
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 14,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "application/javascript": [
+ "/* Put everything inside the global mpl namespace */\n",
+ "window.mpl = {};\n",
+ "\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('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",
+ "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 = $('<div/>');\n",
+ " this._root_extra_style(this.root)\n",
+ " this.root.attr('style', 'display: inline-block');\n",
+ "\n",
+ " $(parent_element).append(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 (mpl.ratio != 1) {\n",
+ " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.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 = $(\n",
+ " '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
+ " 'ui-helper-clearfix\"/>');\n",
+ " var titletext = $(\n",
+ " '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
+ " 'text-align: center; padding: 3px;\"/>');\n",
+ " titlebar.append(titletext)\n",
+ " this.root.append(titlebar);\n",
+ " this.header = titletext[0];\n",
+ "}\n",
+ "\n",
+ "\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
+ "\n",
+ "}\n",
+ "\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
+ "\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._init_canvas = function() {\n",
+ " var fig = this;\n",
+ "\n",
+ " var canvas_div = $('<div/>');\n",
+ "\n",
+ " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
+ "\n",
+ " function canvas_keyboard_event(event) {\n",
+ " return fig.key_event(event, event['data']);\n",
+ " }\n",
+ "\n",
+ " canvas_div.keydown('key_press', canvas_keyboard_event);\n",
+ " canvas_div.keyup('key_release', canvas_keyboard_event);\n",
+ " this.canvas_div = canvas_div\n",
+ " this._canvas_extra_style(canvas_div)\n",
+ " this.root.append(canvas_div);\n",
+ "\n",
+ " var canvas = $('<canvas/>');\n",
+ " canvas.addClass('mpl-canvas');\n",
+ " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
+ "\n",
+ " this.canvas = canvas[0];\n",
+ " this.context = canvas[0].getContext(\"2d\");\n",
+ "\n",
+ " var backingStore = this.context.backingStorePixelRatio ||\n",
+ "\tthis.context.webkitBackingStorePixelRatio ||\n",
+ "\tthis.context.mozBackingStorePixelRatio ||\n",
+ "\tthis.context.msBackingStorePixelRatio ||\n",
+ "\tthis.context.oBackingStorePixelRatio ||\n",
+ "\tthis.context.backingStorePixelRatio || 1;\n",
+ "\n",
+ " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+ "\n",
+ " var rubberband = $('<canvas/>');\n",
+ " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
+ "\n",
+ " var pass_mouse_events = true;\n",
+ "\n",
+ " canvas_div.resizable({\n",
+ " start: function(event, ui) {\n",
+ " pass_mouse_events = false;\n",
+ " },\n",
+ " resize: function(event, ui) {\n",
+ " fig.request_resize(ui.size.width, ui.size.height);\n",
+ " },\n",
+ " stop: function(event, ui) {\n",
+ " pass_mouse_events = true;\n",
+ " fig.request_resize(ui.size.width, ui.size.height);\n",
+ " },\n",
+ " });\n",
+ "\n",
+ " function mouse_event_fn(event) {\n",
+ " if (pass_mouse_events)\n",
+ " return fig.mouse_event(event, event['data']);\n",
+ " }\n",
+ "\n",
+ " rubberband.mousedown('button_press', mouse_event_fn);\n",
+ " rubberband.mouseup('button_release', mouse_event_fn);\n",
+ " // Throttle sequential mouse events to 1 every 20ms.\n",
+ " rubberband.mousemove('motion_notify', mouse_event_fn);\n",
+ "\n",
+ " rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
+ " rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
+ "\n",
+ " canvas_div.on(\"wheel\", function (event) {\n",
+ " event = event.originalEvent;\n",
+ " event['data'] = 'scroll'\n",
+ " if (event.deltaY < 0) {\n",
+ " event.step = 1;\n",
+ " } else {\n",
+ " event.step = -1;\n",
+ " }\n",
+ " mouse_event_fn(event);\n",
+ " });\n",
+ "\n",
+ " canvas_div.append(canvas);\n",
+ " canvas_div.append(rubberband);\n",
+ "\n",
+ " this.rubberband = rubberband;\n",
+ " this.rubberband_canvas = rubberband[0];\n",
+ " this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
+ " this.rubberband_context.strokeStyle = \"#000000\";\n",
+ "\n",
+ " this._resize_canvas = function(width, height) {\n",
+ " // Keep the size of the canvas, canvas container, and rubber band\n",
+ " // canvas in synch.\n",
+ " canvas_div.css('width', width)\n",
+ " canvas_div.css('height', height)\n",
+ "\n",
+ " canvas.attr('width', width * mpl.ratio);\n",
+ " canvas.attr('height', height * mpl.ratio);\n",
+ " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
+ "\n",
+ " rubberband.attr('width', width);\n",
+ " rubberband.attr('height', height);\n",
+ " }\n",
+ "\n",
+ " // Set the figure to an initial 600x600px, this will subsequently be updated\n",
+ " // upon first draw.\n",
+ " this._resize_canvas(600, 600);\n",
+ "\n",
+ " // Disable right mouse context menu.\n",
+ " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\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 nav_element = $('<div/>');\n",
+ " nav_element.attr('style', 'width: 100%');\n",
+ " this.root.append(nav_element);\n",
+ "\n",
+ " // Define a callback function for later on.\n",
+ " function toolbar_event(event) {\n",
+ " return fig.toolbar_button_onclick(event['data']);\n",
+ " }\n",
+ " function toolbar_mouse_event(event) {\n",
+ " return fig.toolbar_button_onmouseover(event['data']);\n",
+ " }\n",
+ "\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",
+ " // put a spacer in here.\n",
+ " continue;\n",
+ " }\n",
+ " var button = $('<button/>');\n",
+ " button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
+ " 'ui-button-icon-only');\n",
+ " button.attr('role', 'button');\n",
+ " button.attr('aria-disabled', 'false');\n",
+ " button.click(method_name, toolbar_event);\n",
+ " button.mouseover(tooltip, toolbar_mouse_event);\n",
+ "\n",
+ " var icon_img = $('<span/>');\n",
+ " icon_img.addClass('ui-button-icon-primary ui-icon');\n",
+ " icon_img.addClass(image);\n",
+ " icon_img.addClass('ui-corner-all');\n",
+ "\n",
+ " var tooltip_span = $('<span/>');\n",
+ " tooltip_span.addClass('ui-button-text');\n",
+ " tooltip_span.html(tooltip);\n",
+ "\n",
+ " button.append(icon_img);\n",
+ " button.append(tooltip_span);\n",
+ "\n",
+ " nav_element.append(button);\n",
+ " }\n",
+ "\n",
+ " var fmt_picker_span = $('<span/>');\n",
+ "\n",
+ " var fmt_picker = $('<select/>');\n",
+ " fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
+ " fmt_picker_span.append(fmt_picker);\n",
+ " nav_element.append(fmt_picker_span);\n",
+ " this.format_dropdown = fmt_picker[0];\n",
+ "\n",
+ " for (var ind in mpl.extensions) {\n",
+ " var fmt = mpl.extensions[ind];\n",
+ " var option = $(\n",
+ " '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
+ " fmt_picker.append(option);\n",
+ " }\n",
+ "\n",
+ " // Add hover states to the ui-buttons\n",
+ " $( \".ui-button\" ).hover(\n",
+ " function() { $(this).addClass(\"ui-state-hover\");},\n",
+ " function() { $(this).removeClass(\"ui-state-hover\");}\n",
+ " );\n",
+ "\n",
+ " var status_bar = $('<span class=\"mpl-message\"/>');\n",
+ " nav_element.append(status_bar);\n",
+ " this.message = status_bar[0];\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",
+ "\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",
+ "\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]);\n",
+ " fig.send_message(\"refresh\", {});\n",
+ " };\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
+ " var x0 = msg['x0'] / mpl.ratio;\n",
+ " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
+ " var x1 = msg['x1'] / mpl.ratio;\n",
+ " var y1 = (fig.canvas.height - msg['y1']) / mpl.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, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\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",
+ " {\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.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",
+ " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+ " evt.data);\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ " else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\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(\"No handler for the '\" + msg_type + \"' message type: \", msg);\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(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\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",
+ " if (e.target)\n",
+ " targ = e.target;\n",
+ " else if (e.srcElement)\n",
+ " targ = e.srcElement;\n",
+ " if (targ.nodeType == 3) // defeat Safari bug\n",
+ " targ = targ.parentNode;\n",
+ "\n",
+ " // jQuery normalizes the pageX and pageY\n",
+ " // pageX,Y are the mouse positions relative to the document\n",
+ " // offset() returns the position of the element relative to the document\n",
+ " var x = e.pageX - $(targ).offset().left;\n",
+ " var y = e.pageY - $(targ).offset().top;\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",
+ " 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",
+ " {\n",
+ " this.canvas.focus();\n",
+ " this.canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " var x = canvas_pos.x * mpl.ratio;\n",
+ " var y = canvas_pos.y * mpl.ratio;\n",
+ "\n",
+ " this.send_message(name, {x: x, y: y, button: event.button,\n",
+ " step: event.step,\n",
+ " guiEvent: simpleKeys(event)});\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",
+ "\n",
+ " // Prevent repeat events\n",
+ " if (name == 'key_press')\n",
+ " {\n",
+ " if (event.which === this._key)\n",
+ " return;\n",
+ " else\n",
+ " this._key = event.which;\n",
+ " }\n",
+ " if (name == 'key_release')\n",
+ " this._key = null;\n",
+ "\n",
+ " var value = '';\n",
+ " if (event.ctrlKey && event.which != 17)\n",
+ " value += \"ctrl+\";\n",
+ " if (event.altKey && event.which != 18)\n",
+ " value += \"alt+\";\n",
+ " if (event.shiftKey && event.which != 16)\n",
+ " value += \"shift+\";\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,\n",
+ " 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",
+ "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\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"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\";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 = $(\"#\" + id);\n",
+ " var ws_proxy = comm_websocket_adapter(comm)\n",
+ "\n",
+ " function ondownload(figure, format) {\n",
+ " window.open(figure.imageObj.src);\n",
+ " }\n",
+ "\n",
+ " var fig = new mpl.figure(id, ws_proxy,\n",
+ " ondownload,\n",
+ " element.get(0));\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.get(0);\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",
+ "\n",
+ " var output_index = fig.cell_info[2]\n",
+ " var cell = fig.cell_info[0];\n",
+ "\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
+ " var width = fig.canvas.width/mpl.ratio\n",
+ " fig.root.unbind('remove')\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).html('<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/mpl.ratio\n",
+ " var dataURL = this.canvas.toDataURL();\n",
+ " this.cell_info[1]['text/html'] = '<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 () { fig.push_to_output() }, 1000);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function() {\n",
+ " var fig = this;\n",
+ "\n",
+ " var nav_element = $('<div/>');\n",
+ " nav_element.attr('style', 'width: 100%');\n",
+ " this.root.append(nav_element);\n",
+ "\n",
+ " // Define a callback function for later on.\n",
+ " function toolbar_event(event) {\n",
+ " return fig.toolbar_button_onclick(event['data']);\n",
+ " }\n",
+ " function toolbar_mouse_event(event) {\n",
+ " return fig.toolbar_button_onmouseover(event['data']);\n",
+ " }\n",
+ "\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) { continue; };\n",
+ "\n",
+ " var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
+ " button.click(method_name, toolbar_event);\n",
+ " button.mouseover(tooltip, toolbar_mouse_event);\n",
+ " nav_element.append(button);\n",
+ " }\n",
+ "\n",
+ " // Add the status bar.\n",
+ " var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
+ " nav_element.append(status_bar);\n",
+ " this.message = status_bar[0];\n",
+ "\n",
+ " // Add the close button to the window.\n",
+ " var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
+ " var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
+ " button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
+ " button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
+ " buttongrp.append(button);\n",
+ " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
+ " titlebar.prepend(buttongrp);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function(el){\n",
+ " var fig = this\n",
+ " el.on(\"remove\", function(){\n",
+ "\tfig.close_ws(fig, {});\n",
+ " });\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function(el){\n",
+ " // this is important to make the div 'focusable\n",
+ " el.attr('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",
+ " }\n",
+ " else {\n",
+ " // location in version 2\n",
+ " IPython.keyboard_manager.register_events(el);\n",
+ " }\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",
+ " // 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",
+ "\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('matplotlib', mpl.mpl_figure_comm);\n",
+ "}\n"
+ ],
+ "text/plain": [
+ "<IPython.core.display.Javascript object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
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17e/Y/2a9muOpy+APmgTQP/qK+D77x/p9u3f/4kPfvdnNLxxA/OWr0fA8+FYUX0G80tOw3Pza3gy+eiAzSnlKBaVnUF65wd49cr/wy/ffad0/NtffTXigK6hYQBNzZXQ0YmHrq4CuroK6OlJjV+nr79RaT1t419Hjbqz8et1dOLZMfT0FEr78+v09TdCX38j207HoO38Magvv44/9qhR8Xdc+6hRfZ+LGq3T0+tbHjVqg9JnlX8/1FdPT4FRBjHQcAuA1hQ9GMwwgN2zdrB6xgrWz1jDaqH0arPIRmpLbGCz2AZWz1jBZpEN62v3rB0sFljAZpENLBdawvoZa5jPN4f5PKlZLLCA5UJLmMwxgeVCS1gttILNYhv85rnfwGaJDTuXxQILafkZK+kci6Vz2CyW+oyePxrm88yl7QutYD7fHFYLpeXR80fD6hkrWC60hOVCS5jPN4flQktYPG2B0fNHY/T80Wy9+TxzmM83h1mQGXtvFmSm1Gg/fp3JHBOlZeM5xjCabQSj2UYwnmMM83nmGD1NH6+M00K0tgZiNDURp62t9BqtoYENo0YhTltbqcVoaiJWS0upf6yWFqI1pOPIt8uPyfejxq+Tb+f3UbXMv1/f21T149ffrcmPr2pfVeteHgLUfxULBNCHbm+//TaWLFkCOzs7aGho4OjRo0rbf/nlF2RnZ8PW1hb6+voICgrCv/7rvyr1+frrr7Fq1SqYmJjAzMwM69atwzfffDOk62A3MT0dyM195Np/KVJxbmUMOp8JQ830VagKfAWVASuw9V/csPVf3FAZsAJVga+wtn3GKjQFhWD/ojD0PB+Jt1ZE4+raeHyZkILvN2cPeK7b6ekjDuhaWqOhp6eAkVEc9PVDYWgYxpqJSQRMTCJgbBzO3hsbh7P39EqNtlGT70t9zMwiYWYWBXPzaJiYRMDCIhbm5tEwN49m601NI2FiEgEzs0gYG4ezbbSdfzUzi8Lo0TFs+c4+kbL1kVyLgplZJExNI5XOzTfqx1+nuXk0LCxi2Xo9szBo+c2G0XRreId6I0gRhIDIAExfPx0zYmZgdvxszEmYgzkJcxCkCGLrZ8XOwrSoaZgaPhWB6wPhv84fM2NmYsq6KfAL84NnsCf81vrBb60fAiID4BPqA59QH0yPno7A9YGYvn465irmSi1hLgLXB2JW7CzMjp+NBZsWYMGmBZibMBezYmdJ2+JmwSfUBwGRAZgZMxP+6/wREBmAaVHTMC1qGmbFzkJAZACmhk9lbcq6KZiybgqmhk9FQGQA/Nf5wy/MT1oXMRV+YX7wCfWB+yp3eAZ7wjPYE+6r3OEd6g2/MD94h3pj8iuT4bbSjW33CvGCd6g33Fa6wWOVB1s/+ZXJ8FvrB/uZ5oh11MI6fS2E6usj3NgYYYaGWGtggDBDwzsavz5EXx9hhoYI1ddHiL4+QvT0sNbAgC2H6OsjVF8fa3R0WOPXrzUwkPbV01PaRscI7W20fY2ODjs2f0zaN3jUKKV18vfybau1tVmfVVpaWK2trdSoz2ptbazS0sIqLS3W/xVNTazW1mavtD2kF/KmAuiDsgcO9Ndffx2bN2/GkSNHVAK9pKQEZmZmOHbsGG7cuIGlS5di/Pjx+Pbbb1mfhQsXwsPDA++//z4uXLiAJ598Eq+88sqQruNRBvr3m7OVYF0V+Aoa5qzBsaXr0OLmi06PKfg0IgFfxKfg6+QMfJuZhV9ycu75fCMR6Jqa5tDWjoOhYRj09ZfD0HAFDAxehoHByzAyWgkjo5UwMHgZhoYrYGi4AkZGK1kfE5NVbB2tlzcDg+VsG388WjY3D4aZWTBMTVfD1HQ1zM2lZdrOL5ubr4GJySq2j5lZMExMVrFG6ywsQmFuHgxz8zVsHa2nc5mbr2Hbzc2De4+7RqkPv6+5ubS/peVaWFiEKi1bW6+DqfVaaE+dA11vczgscMCChAWYFjYN8+LmYUHCAjyjeAbz4+Zjftx8PB3/NBYkLEBQTBAWJCzAvLh5CIoNwuyo2Xg6/mnMiZ6DudFzMTNyJmZHzcbMyJmYGTkTMyJmYH7cfMyNnovZUbOl1/XSPktTlmJp8lK8mPEink1+Fi+kv4AXM17EixkvYlnmMjwd/zSejn8azyiewYKEBVioWIilKUuxOGkxFm1chKUpS7Fo4yIs2rgISzYtYW1x0mI8n/o8nk99HouTFmNp8lK8tPklLE1ZiudTn8ezyc/i2eRnsSRpCZ5RPMPa0/FPY9HGRXgu9TnpHImL2Oen8y9K7D1v4iKltipvFeavnYJEFwOsMdTBCkNDrLO2RrC5OUItLBBmZYUwKyuEWlhgraUla7Qt1MKCNdqHloPNzBBsZobVpqZKy6tMTNj2NebmWNO7Hy3TOddaWrL91vT2p/3pHOx4vf3YsXvbKhMTtm61qalSW2Viwl5XGhlhlYkJVhgaYoWhIVYaGbHXlUZGeNnAAC8bGLD3q0xM8LKBAeu/XF+fnWuNjg5itbQE0AdpD9XlLgf6L7/8AltbW5SXl7N1t27dgp6eHvbv3w8A+Oyzz6ChoYEPPviA9Tl58iQ0NTXxxz/+cdDnfhRd7v/91W3sOfNbLC4/w9zlu05/ii/+/H/45bvv8P0336AgKwsFWVn4/ptvhu28I9HlPmqUJXR1FTAxiVACrZHRSgZMAhyBk7bTNh68csDSfvJlAq4E3zWy1gdQWkeQJohSP4IrrbO2XgcrqzBYWYXBwiKUvfIA5qHM97WxCYeVVdgd8KbzW1mFKR3f2nodrK3XwdY2EkYWa6A1ZTZMAmwwI2IGlqYsxfy4+RIsk5cqwe4ZxTMMXgsVC/GM4hksTlqM+RvmM+jNiZ6D2VGzsSBhAeZGz8Xc6LmYFzcPT8c/jdlRszEneg4WJy3GgvgFCIoNwtPxT0tg3bQEz6c+j0WJi7A4abF0XAJpvDSImBc3TxpExAQxwM/fIA00FioWYnHSYgTFBiEoNohdH7X5G+ZjoWIhFioWYv4G6Zhzo+diTvQcLIhfgDnRczAneg4DOg1QZkbOxKyoWZgVNYst0+cMig3CgvgFWBC/AE/HP42gmCC4zhuLDY6jEGwwisGTABtsZsbgSLBebWqqBGy2rrevHJY8cPl1tJ6OR8dfwx2Dmqr3PMT5Y/W3L7+eoEyAXm1qypb593wfVbBfYWjI+tL21draiBYKfdA2ooD+7//+79DQ0MD169eV+s2cORMJCQkAgKamJpibmytt//HHH6GtrY0jR44M+tyPyk28/e0P6PrgC6xqvASH9L7EtQkZJ5B44Dp++Oln1ne4CsvccQ0jMClOQ8OUKXS50u3vPSlaE5NVDNIEYR7oBHhS3fyxlOG95g4lzAOfB7al5VpYWYWxV2q8WrayCmNwlkOY+lKT+kaw97QfAVy5X7jScW1sImBlFQZ7+ziY24ZDe+oc6PtawGmxE1bmrsSSpCVYkb2CKVxSvUuTl7L2XOpzTMUSJBcqFjJ4B8UGSeq7d4BAoKQBAR2PVPCSTUuYWieg82p9QcICdrylyUuxLHMZlmUuw5JNS/BC+gusL13zC+kv4OXsl7EsYxmWpkjq/PnU5/FixotYmrwUL2e/jOWbl+OF9BewZNMSdryFioXsWEs2LcG8uHl4LvU5LE1eioWKhViStASLEhdhWYbUn7wDixIXIawkDEFrfJHoYoBgg1F42cAA4TY2TCmvs7ZmapmU8zpra6yztmYqnRQ739ZwgJavX21qyo6/1tJSacCw1tJSGkjIBhG8gg/mXnmlT6p9lYmJUl9S+qtNTQf0HvCDA4I6LRPAScXzngHeCxBsbo4QPT3EaGoKoA/SRhTQL168CA0NDfzpT39S6rd8+XK8/PLLAICioiI89dRTdxzL2toadXV1/Z7ru+++w+3bt1n78ssvR+xN/P7Hn3Hqkz8jtv1DPLX5daUM9GV1F7Hv0h/w17/fCewHDfTh+k6H7m7XZDF0M7NIprQJznK4EoBVwZlgzK/rc23L3/epbjOzYCXAyhsBmVfT/Hoesra2kbCxiYCdXVTvtgiuhcPOLgp2dlHsvY1NOFPZVlZhbDsP/z54S/uPHRsDW9tI2NpGYsyYaNjZRcHBIR5GFmswauocmE//DYJigxBSGIKXNr+EFdkrGBCDC4IRXBCMFTkrsCpvFVblr8LyrOVYlrEML2e/jJW5KxksCfTLMpcxAD+b/CyWZS7DixkvSi7z5KVYlrEML21+iZ1jSdISPJf6HFbkrMDyrOVS2yy9vpjxIl7a/BJCi0OxKm8VVmSvQHBBMF7MeBHBBcF4afNLWFu8FiGFIVhXug7rStdhdcFqrC1eizWFa9j1hxSGILQ4FCuypc8RvCUYyzKXYXXBatbnxYwXEbxF+qw0cFiaspQNDJZlLpP2z1+FFzNexMrclViZuxJrCtdgXek6eC4aj/gJoxBirI8wKytE2NhgnbU1ouzsEGFjg3AbG/YabmPDwM4DnneTr+mFqCqg8+56anJ1zrvzycVPKl7u5udd/WFWVkoufGq0Dw99fsDAXPoc6Mk7QUAPNjNTUvB3wJxbFgp9aPbYAD03N1flH8BIuonffPcjGt7+PfwK31SCeFDFeex461/xxdf/GHD/Bw304fpO7zWGPmpUPMzMIhnEeSjz7mleMdN6AjnBuq9vnzvczCyYAZgHOA9LXk33ATcCtraRDNwEW1LGPLB5mNvZRWHMmGiMGRMNG5sIBl5+Hb8fDQCsrMJYH1pP57WxiYC9fazS/tTP2TkZlmMioT11Doz9reG5whMJtQlYvnk5QopCJHjmrEBMdQxiqmOwrnQdoiqiEFkeiZCiEARvkSC5InuFBPv8VZJyzViG4C3BDO4E56XJSxFRHoG1xWuxLHMZwkrCEF4ajpCiEAbg8LJwhJf2trJwrCtdx95HlEdgdcFqrClcg/CycAbw8NJwRJZHIqI8Ausr1mN9xXrEVMdgbfFathxeJh0vpCgEEeURiK+NR2hxKNYUrsHqgtUILQ5FaHEolmctx4qcFQgtDsXqgtVYmbtSAn/v56K+a4vXSt9TYQhCCkPwQvoLyGrLwqKIQCQ6GyDEWB+rTU0RPWYM1llbI9LWFpG2toiwsUGUnR17H2Vnx9o6a2slyEeoAD4Pd3lMfp21NdtOXgDyAPAxe9on3MaGrZN7D2ifCBubO87H95VDnh8kkMueH2DcEY/n1D55A1aZmLBzCYU+NBtRQL+fLveRrNC//eEnNL7z7/DofWzpuLTj8C18E1te+xQ3/+sWq9h2N3tcFLqGhgZ0da1hZLQJo0fHMBXNx5flcWiCeV98OVgJ+vJGCt3Sci0bIKhS2ARJUtrW1us4gIczIPfBW1rHq+WxY2MYkO3sohiA+XW0bG8fy7bz/Rwc4u84Fr+ejkPKfOzYGDg7J8PEKhSjAubCeo4Dlm9ejoTaBEnNFoUwSMbXxiO+Nh7RldEIL5UgG1IYgrXFa7G6YDVWF6zGqvxVCC8LZwo+uCBYUtibl2Nl7koG7cT6RIQWhyKkKARrCtcgojwCkeWRiKqIQnRlNKIqohC3PQ5x2+MQXhqO6MpoRJRHILw0HKHFoWz9+or1iK2JReS2SCTUJjBwb9ixARt2bEBCbQJiq2MRXxvP+sVWx7LtG3ZsYAOB9RXrEV0ZjejKaAQXBGN9xXrE18ZLA4zScLyc/TLWFq9FaHEooiujsWHHBqwrXYflm5ezwU58bTySGpLg+5wTEpx0EWqijyg7O8Q7OCB6zBhE2dkh3MYGkba2iBk7ljXaxjcCPwFXDnYesJG2tgzOdHzyAvAeAt4rIB80RHDnoVc6Fn9uHuR82EB+XXw4YLWpKQM/qXU+zi/PMZCDf42OjshyH4KNKKBTUty2bdvYutu3b6tMirt69Srrc+rUqXtPinuIN/Grb75D7dl/UyruMqf8HLqufIHvf/z57geQ2eMUQxdAF0AXQBdAF0BXtgcO9G+++QbXr1/H9evXoaGhgcrKSly/fh3/+Z//CUCatmZubo5XX30VH0R70IkAACAASURBVH/8MZ577jmV09a8vLxw+fJlvPvuu3Bycrr3aWsP4SZ+/ffvkXX0Jpwy++Lj/kVn0HXlC/z409BBTvY4AV1Dwwy6ugpIc6zXKMFbyvhWdrvzWeE87MmtzsNcnmGunFwWoQR0gqTcdc67tm1sIjB2bAzbzsOV3vNwtrePZWC2t4+DvX0cxo6NUWr29rEsNt7XNxb29nFwcIiHk1MiJkzYiPHjExjAx49PwPjxCbC3j8X48QmYODEVtuNiMSpgLoz9rRGwNgDZ7dlYU7gGmxo2IbI8Eom7EqGoU0BRp0BMdQwSahMQUx2D6MpoxG2Pw/qK9YiqiEJocSjCy8JZLJvi1aHFoQgrCUNYSRhWF6xG5LZIFtuOLI9E5DYJqAm1CVDsVCClMYWdL7oyGjHVMYitjkVURRRiqmOgqFNgfcV6KHYqoNipQNz2OKQ0piC5MRnRldFIbkxGcmMy4rbHIW1vGhuMxFbHQlGnQGxNLBJqExBfG4+47XHs+ARmgv+GHRuwvmI9g390ZTRia2KR1JCExPpEhBSFILwsHLE1sYitiUV4WTiKuovwyqZF2DTRCKEm+gi1sEC8gwMibW0Ra2+PKDs7RI8Zg1h7eyWgx4wdi1h7e7bMg51gHGZlxUAcPWYMoseMYe8JxBSn52P2dE5yvZP7nyAc3tufBgf0yocA+MFGBNef31ceFuDBz4cBWOIeN82OcgVYHN/MrO94hoYihj4Ee+BAP3funMobERoaCqCvsIyNjQ309PQQFBSE3/3ud0rH+Prrr/HKK6/A2NgYpqamCAsLu/fCMg/wJn7z3Y+oO/d7TO593vi4tONYuuMCDl39Et/+8NPdD3AXe5yArqNjBSOj5F6gByvFtilr3MYmnKlmUtbyLHNezfOJa7ROORktgnvfF4/mVTSpbvkyD2xeRdvbx8LBIR4ODvGwt49jqlp6H6sEaQIzAV16jWPHdnCIZ9CeMGEjez92bAwcHOIxYcJGTJiwEU5OiXBySoSbWwbMngiD7rQg/ObpJxFSGILM1kzEbY9DfG08MlszkdSQhOz2bGS3ZyOpIQmbGjYhtSkVGS0ZSKxPRHxtPBQ7FQyGG3ZsYJCmRiqcVPX6ivVI3ZMqQXanAht2bEBifSISdyUioTYBmS2ZUmvNRGpTKlIaUxicE2oTkLY3ja1L25uGzBap36aGTchoyUBGSwZyOnKQuicV6c3pyGjJQHJjMjbs2IDUPamsf2ZrJqIqotgghT5DbHUsIssjkd6cjsxW6Vqy92VjU8MmJDcmI6oiCuGl4UhqSGLXkLonFfn78zH95clIcNLFWlMDptDj7O1Zixk7FvEODqxF2dkhrhfmcrUePWaMUpw9eswYhFlZKQGf3vNeAP4935c/TkSvAicVTvAOl62na6Bz8TkA/D7kFeAHDqqS+GgQIo/3q8oLCLWwEAp9iCZKvz6Am/jDTz+j4e3fK8XIF1S9jYu//2pYz/M4AV2qTR4PC4tYJSDLM7z56WAEeVrHw53PGpcrcn5gwKtw3hUuh7atbSRT0aSwlWEdx0Btbx+HCRM2wtFRAQeHeDg6KpSUOYFYrrKdnBLh6Khg8KbjTZiwkQ0UCODjxyfA2TmZNUdHBSZPzmQK3Xy6HWZEzEBRdxHCy8IlSDWlIm1vGrL3ZSN7XzbyD+Qjuz2bgVOxU4FNDZsYbBU7FUhqSEJsdawSJGlbdGU0U+Ix1TFIrE9E6p5U5HTkMAjn7c9D8aFiFB8qRk5HDjt+ZmsmUvekIrE+ETkdOSjoKkD2vmzkdOQgqy0Lhd2FfQOBlkwUdRdhy8EtyN+fj+x92UhpTEFqU6oE8pZMFHQVKHkDkhqSGKCz92VLA5PySDYASGlMQXpzOhLrEyXvQJ0CaXvTpIFIfSKSGpJQc7IGK5OewaaJRlhnboS1lpZIcXFB9JgxSBg/HvEODuyVbwnjxyPW3h7xDg5QODoi3sFBSdHzIObfk8qnQQHfh9ZHjxmj5PaXH4d/lS/zCl++P0E9nPMIkCcgvDeRTpVqp2Pybn8e9gR3OleYoSHitLUF0AdpAuj3+SZ+9qfbmF95XilG3n31S/z08+AS3YZijwvQNTU1oa9vA2PjZDzxRMIdUOazzwnEPMxpO6/i+89cD1dyp48dG6MEdFLRvIucj1/z7m5eaROYJfd4Um9LZPB2dk7G+PEJcHJKYsB2dk6Gi0sKXFxS4OyczAYBBGk6NvUnkEuKPIm1iRNT4eSUCHf3zTC3DceogLmwneeIuO1xKDlSwqCW05GDzNZMbDm4BVsObkFhdyGKuosY4DNbMpHcmIykhiRJZfcq7PjaeAbsxHppXWpTKlL3pLLt6c3p7DyZLZkM6pktmcjtyEVuRy6y2rKQfyAfBV0F0rX0qvbC7kIUdhci/0A+8g/ks+vL7chFQVcBCroKUHasDCVHSpC/Px9F3UUo7C5EalMqSo6WoLC7EMmNycjfn4/ynnIUdReh9FgpSo+VSoOJw8Wsf05HjgT+nQokNyYjoyUD+fvzkduRi7z9eah9sxa1b9Yiuz0bJUdKEPiSGxRP6SHCwgTxDg5InTgRGydMuAPoGydMwMYJExjU+eW4XrjL3fPkoucbr8LJCxDb22LGjmXH4mP35N7nQwDRY8YwTwGdh+DLn18OdP46KDzAu+f5GDwfv5dXyVMVWgizshLT1oZoAuj38Sbe/K9bcM+TVLlXwWl0XfnivoCc7HEBOsXQ9fQUsLbewFzsfUVWIljSWd80rr453HwiG8XE5YMBfjvtz8/hJtc5D3TeZd6n2uOUVLS8EchdXdMZmCVVnQQHh3hMmpTGwOzikgI3twy4uWUwde7oqGDQJlDTfs7OyZg4MRXOzslwckpkgwFa5+ubj9+Mj4PutCCYzxiDudFzUfFaBSLKIyTF25qJjJaMPki+WoatR7aisLsQWw5uQd7+PGS3ZyN1T5/yTd2TCsVOSb2Syz2lMQWbGjYxJbypYRNSGlOQ1ZbFFHbe/jxktmai9Fgpth7Ziq1HtqKou4idf+uRrQy0W49sRfXJahR2F6Ls1TJUvFaBitcqUHKkBMWHJSCXHivF9lPbUXasDDVv1KDqRBXyD+Sj6kQVSo6WIKcjB5UnKlF9shrbT21ng4OtR7ZiW882lL1ahtJjpchqy0La3jQ2gCjqLkJuRy5yOnKQv186XtWJKih2KtBwvgGrU5dg0yQjhBjrI9zGBikuLoizt4fC0RFJTk5IdHJCwvjxSHJyQpKTEzZOmACFo6MS8EmxKxwdGZhVQVy+LpaDuVzlE8jlyp+OHSeL68sHEvzggMDPA5+/HtqXd/eT65530/OQJzc9zX+nc5JCNxNAH5QJoN+nm/iXv32LKUXSfPIXdr6rshDMcNvjAnQtLS3o6FjBzCwNNjYJzFVOAOfd7Hz8W76Or6LGQ50Uu/KAIFyFi/1ONU5tzJhopsD5eDjFr0mhE9BJaTs5JcHVNR1OTokM8E5OSZg8ORMuLilsPz4ZzsEhHi4uKXB33wwnpySMH58AN7cMbv9EJXXv7r4Zrq7p8PLKgbltOHSnzYPD4olIakhC9clq5O3PQ05HDgN3/v585O/PR8mREhR0FSD/gKRQs9slFZ/TkcNi2AT3hNoEptDJtZ66R+qT3pzO4tJbDm5ByZESbOvZhorjFSg9VoqyV8v62rEyFHYXovhwMYq6i1DxWgUqT1Si4rUKbD2ylUG5+mQ1yl4tQ9XrVah6vQoVr1Wg6vUq1J6WFHRRdxFq3qhBzRs1yO3IxY5TO1B/rp657lMaU5DSmILEXYkoPVaKyhOVqDxRibz9ecjtyEXpsVI2iOE9AwT0kiMl2HFqB2at8oTiKT2Emxtj44QJTKETyDdOmIAUFxck9sKdbwR3uVInQJKS5hU4D1Dqz+8fJ9snVqbiqS9BnxL46Jj88fj3dD3xDg4It7Fh56dr4iHNewN4BU+qfqB5+kKhD80E0O/TTSw8/inGpR3HvIrz+Nu3P9yXc8jtcQG65HY3h77+RtjYJIDqmSsXa+lzlfNJcQRygjRBvC87PVwpO10+1YxPSOOnkVGsm4BKiWi8a51c5E5OSUxdOzoq4OKSogRdJ6ckBuKJE1MxYcJGBnR5VjsNFmga2uTJmcyt7uaWgYkTU+HhkQUnpyRMmpSGSZPSmMt++vQS/Gb8BimGPmMMFsQvQMP5BqTuSUXJkRIJkCeqmEu77FgZig8Vo+RoCXO953bkMnd3dns2FHUK5B/Ih6JOwSCe05HD3NUE8/TmdGS1ZSG3I1dS1YeKUd5Tjm0925hCrzkpKWv+vFUnqlBxvAJlx8qwrWcbtvVsQ9WJKlSfrEZ5T7kE8NO1qD5Zjdo3a1FzsgY7z+xE9clq1JysQe3pWuQfyEf9uXrUvlmL9OZ0JNQmsGz2TQ2bkLgrEXn781BxvAJ1Z+pQ2F2I0mOlKOwuRHlPOfNSlBwtQcmREuYZOHDtAILTnkWKmwnCzAwRaWuLHC8vJDk5IdnZGWmTJiHZ2ZkBPrF3Pe+ST3RyUoI6xcAJzgRTgitBnvaPtbdnAwf+OLz6lw8Y5OeibTFjx7Jro2OS94C2KxwdEWVnh4Tx41kcn1fb1FQl7pFyJ3c7n3xHnzfc2FjE0IdgAuj34Sb+8/uf4F8kzS0/fuNPd99hmOxxAbqmpqaSQudrlFPj53rzZVSVXe99g4A+l3vf/jQokM8Fp1g6n9xG2eh8nJxi4hTfplg2734nZU4uct7t7uaWAQeHeEyenIlJk9LYOfsUf5zSNRDQKeHN2TmZuegnTUqDq2s6XF3TMXlyJlxd0+Hrmw+zJ8IwauocPPmcO7LaslBzsgbFh4sZNBm4jkqAJ5We25HLwJbZksmyvSkrnlzqWW1ZTAVntGSwODfF5ou6i1DUXYSSIyUo7ylH5YlKpnqrT1aj4ngFqk5UMaiWHitF9clq7Di1A7Vv1qLs1TLUnKxhipyU/fZT26XrPVqCXWd3YVvPNmw/tR25HblofKcRje80IrE+ETHVMUjdk8qmuyU3JkOxU4HUplRsP7Udu87uQnZ7NipPVLIBRfGhYnY95T3lKO8px96Le1F5ohL+L7hA8ZQuwkcbI23SJGS4uSFt0iSkuLiw12RnZ6ROnIjUiROR7OzMXO+8Uufj7XzCHK+uCaw8mAm+Sdxx6Nh83J6OSeGAWBnc6Vy0jXfjE8R51a5wdFTKhJeXt420tWXeAlLt9Er9+VACDQrW6OgIhT4EE0Af5pv4b3/5Bku2X8C4tOOYtvWtYZmONlh7nIDeF0OPl7nS+2DM1y/nE9l42PPKnJo8/q6quAuv1HnQ8olpFM+mhDaKpRPUCfbkVueB7uycDFfXdKbg3d03Kyn0vnMksez4CRM2wsMji8XdXV3T4eKSAg+PLKUY/eTJmXBzy0BgYAnGTkjAqIC5sJplj/kb5qP+XD2SGpJQ2F2IyhOVKDtWhobzDWg434CdZ3ZKMevjFSjsLmSx561HtrJktux92UhtSkX2vmwG+bz9eUhvTmeJdvn781lMuvRYqeTOP1qCyhOVDOqVJyqx49QOlB2TAF18qBiVJypReqxUipkfr0DNyRp2PSVHpP0pSa32dC2qXq9iMfIdp3Zg55md7HM1X2xG3v48KOqkTH2ampfbkcuS+/IP5GPX2V0sbl59shrFh4tR9boUh996ZCu2n9rOvofOq51YnbIESRMNEWZmiCg7O2R7eiJh/HikuLgwqGe4uSHZ2RnJzs4M8LwrnmCc7OwMhaMjU8Zy8KoCOalyAneSkxN7T33I/Z/s7MwGDXG9yl6u6OUZ+dTIE0CuepqCR3FxUtsEeVLlsZyK55PreFd7hI0NO0+EiYko/ToEE0Afxpv40Rf/B7feOebueafw3u//d9iOPRh7XICupaUFAwNbmJunw85uo1KGOrnM5dPLeHiTG51X7PKpaJQIpwrk5EK3t49jLnVyn1PRFj5ZjZQ6HyunNnFiKiZOTGVucHK7k5t9woSN8PbOxaRJaUrqn3fV0zqCt5NTIry8cpjbfdKkNEyenAl3981wd98MX998eHvnMoWuO20ennzOHenN6ag+Wc3i2FuPbFWKJ28/tR3berah/lw9Ko5XMMBtPbIVWw5uQfa+bBQfLpYy17lsdHLHk5Iv6CpA8aFidvyyV8sYyOvP1jOFXt5TjuqT1cxlXnZMUt41b/S50ater0Ltm7XYcWoHqk5UsWutP1eP+rNS23lmJ+rO1GH3+d3I25+H1kutqDtTx7Lsczty2bUWdheybPuq16uw6+wuZLRkoOF8A0qOlqD2dC229WxjHgJS+3su7EHV61WY+uJEKJ7SQ6SFKXOzb3Z3R7qrK5KcnJA6cSIy3NyQOXkyMidPRrqrK+tHoCcok0omd3ecvT1zpVMf3h3Og5j6kurnYcz3TXZ2Zn14gPPnIC/AxgkTGLz5TPxkZ2fE2dsz1zpl1MuBTrF8fpobnxFPLvh4Bweh0O/RBNCH6SZ+8B9fM5i/WHcRf7717d13GmZ7XIBOCp1i6PLpZuSCVi4E06e8Cdiq1DtfjpV/CAoPdr4IDIGc3OkEe4I6Abo/FU5KnI9vT5yYylzjlJFOUOe9AJRUZ28fywA/ZcoWtg+pdR7q5G53c8vAtGlbWQx99MyxeCH9Bew6uws5HTksPrznwh40X2xG88VmbOvZhpqTNdjWs425ycllXny4GLkduVJsvT1bUuC9yXT5B/LZ3G9y1285uIVlqFedkBLZyo6VofbNWuw8sxM7z+xE/dl67D6/G7WnayVXfC9gm99rRsP5Buw6u4v13X5qO3af380gvuvsLtS+WYs9F/Zg9/ndaDjfgI6rHag6UYX6c/XouNqBkqMlUNQpkNWWxea+Fx8uljL16xSoOF6B1kutqHq9ig1kat6oQXlPOXae2cni9bWna1F6rBQHbxxESMbzSHE1Qbi5MaLs7JDj5QWFoyPSJk1CkpPTHS73FBcXbHZ3Z+v5V1LnBOGk3vg675rnVTlly/PbE2WZ9NSfd+3z8FaVcS8fQPBegFhukEHKm8DMw5pgr3B0VKo+x099o4EAn7EfbmwsgD4EE0Afhpt47vO/wDlLKuP60q6L+Oa7H4fhCodujwPQpUenakFX1/oOha6q/jm53unJZPJMdVXueD5OzpdXJYjyUCWgUxIbVWmj7HUCOk0pI9hSxrmTUxJcXFIYePl4Or13d98MD48suLllMFc9P9+czu/tncsGAQRzT89s1ry9c+HtnQs/vwL4+xdi2rStMLdZB91pQXjyeQ9ktmai/qwErZKjJdh7cS8Of3IYTRea0HShicXQq05IWeQlR0vuUPSU4Ja3P4+1gq4CFHYXMmVObvKakzXMtV73Vh2qXq/CzjM7meptfLsRDecbsPv8bkkR9ya7bT+1HXVn6lD3Vh0DNsGfgN5wvgH1Z+uxrWcbGt9uRNWJKuy7sg/Fh4vR+E4jmi40ofhQMRLrE1k1uYyWDDYvvrC7EHsu7EHD+QZsPbIVu8/vRuWJSrRfaUfj242oOVmDHad2oPm9ZjS/14y2y21oON/Qm+Wui0gLU6bOCdjprq7InDwZ2Z6ezAVPCXN8S3FxYQCnuDepcLm6JuXOx8gJ6PzUOL4RtGkaXaKKGD5BXOHoyK4r0cmJxdUpgS/Kzg5JveqerzQnT44L73Wjx9rbI8LGBgnjxytNm+MHAfEODiyuLhT60EwA/VfexNc//hOezDyBcWnHEbr3Mv75/YOLmcvtcQB6n9t9NFPovHtcXledf+AJn+jGV3WTPyxF/qCUvoS3WKaGCe585bU+tZ7E1knx7CQGcoI0udrJ3e7klAQ3twy4u2/G5MmZ8PDIgotLCry8cliZVn//Qnh4ZLFtfQVkpH09PbN7s9wT4edXgMmTM+Hpmc2OO2XKFkyZsoX1mz27Ag7OidCdFgTrOQ5Ylb8KnVc7UXyomAGx9VIrg2TViSrsPr+bQZWS0GpO1rAsc0oWy2rLYu7v/AP5qHitgrm0+eQ23q2+49QO6bzn6lF/rh6Nbzdi55mdTG3Xn61H88Vmpt6bLjQxpVx/th51b9WxVnOyBk0XmtjnaLnUgsa3JZCX95Sj+WIzGt9pRMnREmS1ZWFTwyY27W7LwS2oOVmDvRf3ovGdRmw9shX156TPv+PUDilWf7oWu87uYtdafbIah28eRlTeCkmhjzZGzNixKAkMhMLREZmTJyNt0iQU+vuzZQI+JcelTpzIXPC8SidwU8ybHwwQ7PnseZouRzF5PhmPbxS3J1jzsXs+UY/6kyrnFT7F9WmZ3Ox8HJ2WKYmPL1ZDWfryynU0aAk3NkaslpaYhz5IE0C/x5v488+/oPGdf8f4dKkCXFzHh/f0hLThtMcF6FpaWtDXt4GFRSZ+85tEJVe5/MEnvOqmPg4O8Xesk7vjVT3NjIrE8PXSqfoaudRJlROEKY7Nq3JKSuObq2s6PDyyGODd3DIYvAn8BHpKcnN338z6+frmw8+vAJMmpcHDIwuentnw8cljzcsrhyn1qVOL4Oubj+nTS2BuGw796fMx+RV/VJ6olOLLb9Wh5VILgx/N825+r5nFrKtOVKGouwiVJypRd6aOJcoVdReh5GgJKwJT2F2IkiOSkqfpbiVHS7D91HbUnq7F9lPbmaLeeWYn8wY0XWhC3Vt1aDjfgLq36ph7vfm9Zuy5sEcaZJyrR+M7jah7qw5NF5rYe2oUP6dYN+1XeaISey/uRdv7bSwWzw82ak/XovHtRuw+vxtF3UXMhV9/rp4NaOh69lzYgz0X9qD9Sjt2nd2FoBBfKJ7SQ8wTo5Hn44MtU6YgbdIk5Hh5sWlrqRMnItvTE9meniyenuHmxkBNkE3iVDa5w/l56xRvp740551gTR4BfkDAH5dAzr/Kk+V45U/nJ0We6OTEwEzXqOoJcvzUO3n5WN7Fzk/HI8iH6OkJhT4EE0C/h5v41TffIXTvZVbONfngR/e1AtxgTQBdAF0AXQBdAP3+/L49CiaAPsSb+Okfb8Nni1QB7qnNr6Pt0h/wyy8PH+bA4wN0KY4+GgYGiXjiiQRYWq5VeoIZX3edz1DnIU5xcXlN9jsfSRrH6rFT9Te+Rrq8OAyf+MbDno+lE8AJygRqquDm7r4ZEyemKgGboE5xcH//Qnh55TCQe3nlsP2nTNnC3nt55cDPr4BltVPz8clDUFA1HJyToBc4H9azx2F51nJ0Xu1E9r5s7Dq7C7vP71bKcqepXzVv1DAgl/eUo+RoCXaf383mi+cfyGfz2YsPFytVdas8UYmmC01sKtmOUzsk9/m7TZJL/N0m7LuyD/uu7FNymVM8u+lCE5rebULzRQnsFA9vON+Atvfb0P5BO9o/aEfrpVbsu7IP7R+0o/liM3ttfq8Z9WfrUXasDI3vSNBufq8ZnR92ovPDTtS9VYfa07VovdSKXWd39bne325kLnu6nuaLzSwprvJEJXo+78H6/JUsKS7ewQFbp01D2qRJyPLwQK63N4M3ZbnTVLbMyZOROnEiEnvBnOXhcUciHZ+RzmevJ/b2oQEDX8SGjs0PFngXP7nuedc6X/BGPoCQn5tP2uNd83xZWr7iXX8PguFbpK0tG0REmpqKwjJDMAH0IdzE//3mO8woPYtxacfxdOXb+PzPf7uPVzh0e1yArqGhAX19G5ibp2Ps2KQ7njHOJ7rxUOfj4gRzuaqXl3bly7by1d5oDjk/n5wS3EiRU+yczzAnmPNzwklRu7tvZirawyMLXl45mDw5Ez4+eUyVE9BpgODmlsHi4rQPNR+fPCWYk1r39y9EYGAJpk8vheWYSOhOmwfXl31ZbJkyxxvfkZK/dp/fzRLOtvVsQ+2bEsBq3qhh8eSG8w3Yfmo7So+VskxwvsZ61etVDOKU3MZi271Q3ntxL/Ze3IvWS61ovdSKxrcbGYBbL7Wi4XwD9l7ci7ozdWi73Ibd53czuLddbkPnh53out6Frutd6L7Rjc6rnTh88zC6rneh88NOqc/VTnR91IWmd5uYR6D2zVqWyd91vYvF52vfrMXu87ux78o+tFxqQeulVjRdaEL7B+0sJk+Dj67rXWi/0o6gNb7Y6KyPmCdGI8fLC9mensjy8ECGmxtLjtvs7o4sDw9keXgwkGe4uSnFzym2njB+/B0FaPg4eCKntuWNYvI8wKnx8XO+0QAixcVFKTZPSXrUj5Lq5PPSScXLK9LxNeEJ7FRohi8ZS8ehLPcQfX2h0IdgAuiDvInffPcjFlS9jXFpxxFY8hZu/ePBlHMdij0uQNfU1MSoUZYwMEjE2LFJbHoZr6x5Bc4/RIUHtqrGDwD46WF8VnufW11ZfVNym/zBKKS2CcCknL28cjBpUpqSO5xPjHNzy2D9KKmNBgbkWqdpbzQg8PbOhadnNgM5qXk/vwKWFOfvXwgfnzzMm1eDf3lSISn0OQ54afNL6P64G4XdhZJifqcRdWfqWGGZpgtN2HFqBxrfkZLVGt9ulMB+UqqRXvtmLSpeq0Dt6VqUHStj88kpCa7qhFRbvf6c5AqvP1fPQNr0bhNaLrWg4XwDU9mkrNveb0PrpVbsPr8bey/ulTLLe5Pami82Y/+1/ej6qAutl1oZ0Luud7H1HVc70HShib3vvtGN7hvd7DOWHClhg4iakzVSFvsbNWi91Ir2K+1ou9yG5vease/KPmnw8H4bmt6Vjsey3N9vQ8/nPYjOfwUpriaIsDBBzNixKPT3R7KzM7I9PZHr7c1c7ZT9zsM9deJEliyX7urKVDopd7krPtnZWWkQwKtzHt6k0Ok9D2aCPa/Q+ex7UvF8/Xne1S9/uEySk9MdLneav8670/l59vyggNzydM4oMzOh0IdgAuiDvIkHP/gC49KOY3LuG/j9/3xzn6/u3uxxATop9NGjMzBuXOodypp3pasCNb9NrtT5+uz0MBW5OufVOP84U5pLztdSnzQpjbnOaTtf5IVgYdMNbwAAIABJREFUTWra1zcfXl45DMw0FY1c6xRzpwx2J6ckTJmyhbndPTyy4OdXwADu7Z2LqVOL4O9fiICAYgQEFGP69BJMm7YVgYElMHsiDPrT58NjdQAqT1Si+0Y3Gs43sBg6QbP5YjMDe/PFZqXMc8pyr3mjBnVn6lhNdlbk5Ww9izvXnJTAX39OUsF7LuxhUGy91IqOqx2sNV1oQvuVdnR+2ImmdyVlTEq87XIbc6mTGm+60Oeub/+gHZ1XO5UGBgdvHETH1Q6mxNs/aEft6Vp03+jGkU+P4MinR1B6rBTtH7Sj8Z2+KXN1b9UxVU7X2XKpRRog9A4eej7vQdvlNsxe7cUUOsXQsz09ke/ry4BOypzaZnd3tkwuclLWNN0tqTdbPVEGY94tT3CmY5Lyz3BzY/sT7OXz4Wk9X+AmSYX6p7nwfOyenwJHdeVpWhrNPSdwU9EbOcTp4S6x9vZIdnYWMfR7NAH0Qd7Esjd+i3Fpx5F++MZ9vrJ7t8cJ6Jqa5jAy2gR7+xQlOJMaV5UcR250moImf2Ka/BnmfK10Uud8Mhw/bY1X7BTvJoBTQhsVjKHCLqTGaZ45ud7JRe7tncsUurd3Ljw8sjB1ahGmTi1ix3J2TmbT2Xx88phrnX8llU4KPTCwBD4+eViwoBb2ThuhOy0IYxc+hVV5q3D0s6OoP1uPfVf2SS7md5uYy73uTB2bO151QpozTgVe6s5Isee6M3V9LvmTNeyBKPXnJHc9gZ2mqDW+04iuj7rQ+E4jg3Db5Tap9SrhzqudaH5PUvFN7zYxNU3zvwnkRz49wtQ3ud8P3zyMro+6mNucBg97LuxB/bl6HLh2AHsu7MHBGwdx8MZB1L1Vh/3X9rN4ftMFyaW/9+JetF9pR8fVDrReasWBawfYPgdvHETThSb0fN6D8OyXkOJmgmhrc8Q7OKBsxgymwHO8vBjkaV2Wh4eSWz7Lw4PBnFQ6Lae7uiopbVLylBBH+1H9eBocZHl4KLnXsz09lWLsNGjg+/ADBD72Tsl7vHKnBDn+ka/Jzs4M6DzEY1WAnYe9wtGRJdklOTmJaWtDNAH0QdzEW//4AdNL3xJAHyFA19bWhrHxGJibp6tU6PyTyJQfoBJ3h1qnZR78/HPNlR+2ksRgzld/I5CTWidoU4zc0zObreMBT0qdFLinZzYDMQGe+ri6pitlrVO83Ns7l7nap04tYhntpPZJnfMKPSCgGLNmbUNgYAksx0RCf/p8+ITOxLaebei63sUgRiqVB2jrpVYG5T0X9jClXnu6tk+p975SnXOqLkcu9+2ntrOiMI3vNLKBA0tco/ZeM4P13ot70XKpBe1X2tH8XjNaLrWw2HXThSY0vye53kndt15qZYqekuTaLrdJUL/YzD5T941utFxqYQl6+6/tR/PFZuahoPg8hQE6r3Yquflpfc/nPdhzYQ8CX3LDRmd9bLCzQp6PD4oDApDv64sCPz8GdN7lTkVmsjw8sNndXUkpk1qmhDf+gS68m5zfJ93Vle2b6+3NQC2PlxPECcwEdvk5yK1PfcmTQGEA3gVPiXIUD5fXhCeIkxqnsrYUV1c4OrJSsjQYEIVlhmYC6He5iW988mf4Fr7J3O2f/Wnk3vTHAehS2VcN6OhYKSl0Pk7OP4lM/mSyvqekxbK663J3vfJxYu94cpqTUyLLWKfGF4yhWDllrNN6L68cuLqms0pupKo9PLJYZrqnZ7aSIqf3fH+CNiW++fjksWlqU6ZsQUBAMVPnU6ZswdSpRQgIKEZgYAkCA0uYK54Uul7gfNjNn4B1pevQ83kPqk5UsWQ1gmrThSYcvHFQinf3ArTlUgvqz0lTuqpel2LldWfqUHWiiin22tNSKdeK1yrYVC8qykJx+bbLbei63oW299tw4NoBdF7tROfVTuy7sg8dVzvQdlmKoe+9uBcHrh1A2/tt2H9tPw7eOIj91/ZL+3/UhQPXDjDAtl9pZy58gjsNEui85JI/eOMg2q9I+7R/0M6S8Aj8BPCWSy3out6l7OrvzY5vfLsRPZ/3ICpvBdLczRBpYQqFoyPKZ85kLvccLy/k+/oy9zs1Xp1ne3oyYMoT21InTsRmd/d+Y+U8eHO9vZkrP8PNTUlRE8xpwJDu6sqOK0+gS3FxYW57haOjkrueKtqRC55/5ju54ZO4BDk+4Y1UObnj+Qp0sfb2bFAiFPrQTAB9gJv44X/+FQ69hWPmbjuHT/546wFe4dDtcQG6pqYm9PVtYGm5GQ4OaSxznS/JyrvPeTDb2UVh/PgEpsJ58PNqXv6+b6qasiLna7AT1N3cMphSpwemUNU3ykanhDVv71wGYH//QuZyJ5BTfJz6krInJU/bCO7Tp5fC37+QQZxe/fwKmDqfOrUIs2dXYMaMMiWFXn+2HoduHmKZ5p1XO1F/TspEpyzv9ivt6LrepTTfu+F8AypPVGLX2V2oeK0Cey7sQd1bdUoPdWk434Adp3ag5o0aNu2L3Oxd17ukxLOLzTh44yBzuROgD1w7gPYr7Uru8c6rnXj1t6/i4I2DOHDtgORq/7gbh24ewqGbhyR3+yeHsf/afuy/tp+57Zvfa0bn1U4cvHFQyob/uJtlwVNrvtgsDRwuSwMHgveBawdYfzoPxex7Pu9B04UmBIX4ItHFABvsrJDr7Y1Cf38U+Pkh39cXW6ZMQZ6PDwr8/FA0dSqKpk5lyp2S5uSxdVLdBFGCMw9bXqGnuLgg29MTOV5eyJw8GTleXkrqPd3Vle2T5eGhlFVPkOfVOe++5+fR868EYnK/k+uclvknuRG4eXc7/yQ4mgJHMXSh0IdmAugD3MSQJql4TPS+qw/0Maj3ao8D0KnxCr2/IjD8M8v7npAWqwR6uQue1DwpdSoiQy53AjtlspObnX9P7nY3tww4OiqY2nZySmLAphg6r8gpdk7AJ0gHBBQrxcipkfqm/Ump8zFzvm77jBllmDGjjKl0moeuP30+xi5wQnhpOA5/chjlPeVMmZKbmcW2e9UxTeHadXYX2i63MeVd9XoV6s/Ws3KsVABmx6kdTM2TOt97cS/LGm+73IaOqx1KiWb8FLTWS604dPMQ2i5L2eTHfnsMze81o+sjCdzU9+hnR3H0s6Po+kiCLsGewEyvNBCg4xOgG99pZB6DfVf2SX0+kjLmqf+x3x5D941udp6uj7rQfLH5jiz3RCcnbJs1Cxlubsj39UVxQAC2TJmCXG9vptSLAwKQ5+ODfF9fpXg674KnZDmKp8sT2fjHshLESaFnuLkhz8eHKXEe2lR0hlf8fFIcHY/2IyXPT4WTz5FXODqyxDlVU9zkdelVKfs4e3um7unxqea9njkB9IFNAL2fm/gfX/0d49KOwyH9OP7wv39/wFd3b/a4AJ1X6HwMnZ+aJlfaNP1MuS57nFLVOBoM8M83p0Q4ym6nGDofB6cpZpTRzk9bI8A7OSUxsPNzxQnMfFZ6QECx0rxxWqZseD7Zzc+vgLnaKXZO7yluPnNmOYM6gT0oqJpluesFzofv2lloudTCVDFNFaO4Obmv91/bj84PO7H34l42B5yKvFSeqETLpRZUn6xmLvZdZ3exuepUlIYqtlFCW+fVTnTf6Max3x7D4ZuHWWIbqejDNw/j8M3D6LzaiSOfHkHP5z1MLbdfaWdA5rPVaXoaZbO3XW5D+5V2Bubuj7tx+OZhKeOdi4WT4mau/N7pb51XO5naP3zzMAM9n+Xe+HYj5gR7Q/GUHuJsLVHo788gvmXKFAbxAj8/lEyfzhpBnWLqFF8ngPIKnHedk3InlzhBmhQ/qXyCOT+NLdvTk2W+0zK5+knN03Q3/gEzBHE+fs8rc74ADf8wGf5pbfxT4viHz1DMPW3SJBZDX62tjfVCoQ/aBND7uYmlJ3/LHrjyqNjjBHRJoSfDwSENNjYRTFWTslblRpeeVx4ni6PH3TEAUDUQoAeyEMz5p6RRohs9MY3WU6ycXsmlzs9Dp0Q4co37+xcytU1wpu2ktkl9+/sXsuls1GiAQLH06dOlAjIUP5cKykgKffHielYpznaeI8JKwnD0s6MoPVbKFHnze80Mdl3Xu7D34l6WGEYu6b0X97I56l0fdaHkqPRENv555KTgydVed6aOxahpCtrhTyRwU+Y4qV9Kajv62VG0XW7D3ot7sefCHqa8D1w7gMOfHMaRT48w+NOxuj+WXPFdH/W61XuLzRz77TH0fN7DwE9eiK6Puthgput6F5vq1v5BO7o/7mZu/u6Pu5WUffN7zSyGvmmiESIsTJDs7IzymTOR5eGBQn9/FPr7I9fbWwJ6YCBKAgOZSs/39VWaq57j5cWgSoAlMPNAJwVNSp6mq5FCz/HyYkDm4/C0Lz8tjRLw5CVpae48HZ+vSpc2aRKrKEeApuPxKpyK4lAf/gEvfEEaeqIbeQsiTU0Ro6kpYuiDNAH0fm4iuds73v/PB3xl926PC9A1NDSgp/cErKyyYW+f0q8q73OzyxPkYtk23i3PA10+VU3+LHNS4/Ser8tO1d8oMY7c6TRNjSBOKpsy1GkOujx27udXwLbzQCfIk2qnKW0UJ++DeimmTy9l20mhz5q1DaPtIqA/fT68Q6ezTHOq3Lbvyj5WXY0azcEm2NefrUfdmTpWj53mbte8UcOmrVWeqETdW3XsEadNF6Qyr5RkR4lwXR91KZ2LsstJLVOcnMDdcbUDh24ewuGbh5kqJ8VMip2OQW7zo58dRc/nPTj62VEGfDo+Nfqc3Te62Tx4OubRz47iwLUDSrF6fh76zFc8WJZ7SWCgEshLAgOR5+ODoqlT2fo8Hx+UBAaiaOpUBnU+A56PlcvnrJP6JuVO23iXPQGdd5uT8s/z8WHwpSI2dO5cb28Gc1pH1e54tU+FauSPWZU/xpWUO//IVj4LntzuCkdHpLu6iiz3ezQBdBU38ZdffoFXwWmMSzuOq3/4+iFc3b3Z4wR0La3RMDLaBAeH9DuKwchVOc0plxR6LOd+74O2HPTyCnFSnfa+CnGU8MYrdH5eOV8Vjn8WOcGez1anym38VDSCMcGcd68TvMmlTqAnBU+g9/MrQGBgiZJSnz69FLNnV2Dq1CIsWrQL4ycmQ3faPNgEjUd4aTh6Pu/BzjM7WaY4JYk1X2xmoKWCM1TbnCqo1Z+Tisy0XGphZVmpGhsVoCGwE9QJ3IduHkLH1Q6WfHbg2gGmqCme3XW9iw0Auj/uVsqIp5g5qfrDnxzGoZuH0H5FKghD/Xs+75GA/ulRBv2DNw5Kir43ia7zw06WjEcJewdvHETP5z04/Emf6u/+uJvtR1PXYgtXI8XVBOvMjZDo5ITymTOZmz3f1xdFU6diy5QpTKGXBAZiy5QpKPDzQ4GfH7I9PVmiHFWRI6VMYOULxPCZ7byLnmLy6a6uDMo5Xl4svk6udVpPCpy8AHxyHrn05VPjaDDB13gntzyViiVlzkOdj7PzcXUe9OSFCDc2FjH0IZgAuoqb+NU337H4+Xc/jvxkODIBdAF0AXQBdAH0+/P79iiYALqKm/jRF/+HcWnH4V905iFc2b3b4wR0I6PfwMYml2W5K0NdOcOdn8rGJ8RR9jvF1vm+fDKcvX0cm4NOyW7kTqd56K6u6QzW/Dx0Aj8lrE2enKmU5c5XhSNgk7uc1vv65ivNH6d15LqnKWm8u33atK2YOrUIgYFSmVeC+fTppZg5sxxPP72DTVujpDhyM1NMvOVSS9+87t5s931X9rHHiHZc7WCPN6WqbzTHmwrTEMx3n9/NHm9KgwBKtGu/IsHw0M1DDODk4u682okD1w6wKWcEbKoKR/33X9vPAE3JcMxl3pt0131DAvDRT48yMNP8dWrMbc9lz3dc7WDXcejmIRZDZ7H0j7vR83kPWi+1YuYrHlA8pYcNdlYM3sUBAazRe5q2Rn34aW253t7scavkaqe4dr6vr1K9d971TjF4AneOl9cdlehoYEADAD4zno+3q4rZU+EZPhOeSs9SLJ6vN0+ApiI0/MNk+Pi5fM76Znd35nIPHjVKuNyHYALoKm5iXs8nGJd2HMF73n8IV3bv9jgBfdQoy96kuPQ7pq3xsXBS4hMmbGTqnCDNK3F+eho9GpUy2uXPOieQu7ikMEVOVeD4aWuk3OlZ55QE5+OTpzQPnU9iI8XOT0uj/qTCKSOeEucoNs6/nzZtK0uyI4hTmzOnElOmbMHSpY1wnJTCCssk7kpEz+c9TEG3XGphKpmKsNAUs86rnawQS+M7jexBK/xzyKkgDV+dre6tOulJajQH/aO+LHJeYRNQ+Qe10ECBYtoHbxxE2/ttbD9+yhvNXafjEIxJoVOmOmXP0370MBbKaKfjUFydBg00dY2S8Gg63fr8lUieZIRoa3OkTZqE7fPns0S3kunTsXXaNBQHBLAYOs1FLw4IYDCmIjQUE+fj2fwDXgjOPKj5p7iR6qYSsqS4CdZ8mVhS4vz0NQI7wZ5gTol6VFiGYM3Pj5dnvhOw6cEvpNxpLjrNS6d1dIxIU1NRWGYIJoCu4iYGlkhlXs989t8P4cru3R4noBsY2PY+PnUTg7e8Hru9fSxT2nzmO+9Klzc51PkkOL5Wu6pEOJq+5uaWwYBPICfo01Q1cp3zRV8I4gEBxWz6GrnjCeY0CPDyysGMGWXMzc5XhKMHr/RltUtAnzVrG2bN2oY5cyqxcOFOzJ1bBaux66E7bR6mrJuN2tO1TPm2XW7DrrO70P1xt1KSGl+9rfliM7o/7mZlUnee2Yn6s/UM9HVn6lg2e9v7bQzITe82SXO332tm8O38sJPNEafyrZSZTqVf6SlrBGpyi9MUNCUXfK9qP/yJBGzKameegN7z0eCA9qPHrR777THmCaBCNjTPnbwHVHCm+0Y3lxTnyZLitk6bhpLp01ExezZT5iWBgQzgpNhzvLxQ4OfHXO+UlEaA5xUzZcCT+qZSsvyjWqnELLndt0yZwiDMA5kKyvCg///sfWlYVGe2NYMyKAgqBIgIqCECgqg4ACLiFNOJnc7QGTpJJ0bFAeOAEVAEcUBkEBBFRQFRREUQQRrjEGOMxjjEmBhj9N6b+/XXndtfZ+juxO6b7vSQXt+PU+tl16GKgDFR4bzP8z5Vdc6pU6fq8LDetffaa5PxM5S/cMAAM7tXlr3p684J7vqOcIsEM2e4XdrEStCn+n3Z4MGI9/ZGvLe3IYpr5zAAXXcTr/3+BvxTNHe4z//8zW26upsbnQnQmUP380uCt3e8GUi3tH5t7mvO48jSzWvT56ryNJk7Z5kan9P2lUp25splmJ0gL7utMZfOmnEax8hadAIyQ+lS1U7QZkiez8nG5WNMTI4CdubPydDj4vIRFZWFn/2sDAEDF8EheiI8xwXg+VXPo+ZyDbac2IK6D7XysdI3SxULLX+rHPve26fq0ivPVWoh9LfKlVkMu7JtObFFMfTSU6UoPlZs5o2+99JeZSFbfalala9J5bhUqbPz2s6zO1V4ncc0XGtQznAE5vqr9aqevPZyLeqv1itAZx07Q+b8XJ6ToX7m12lCI8vpGq41oP5qPQ5eO4iD1w4qt7g5q59FUqgrpvd0wYL+/ZEfF4c1kZHIjolRoXWpfmcNOlXuzKUT1GWonDlyAvqKiIgWNedLBg3CyuHD1WvJ+KVTHEPtBGqG2uV55CJA2sSuiIgwY/TSBlb2U18UaK5wl61ZWdJGYCfwczs/c4arKxLs7AxAb+MwAF13E9MbrsA/pQlzqi7epiu7+dFZAN3Ozg5OTl5wd18CL6/58PaOx4ABCxUI+/jMxIABC+HrO8fU/rQZqPno5zcXPj4zzfLlst6cLH3gwMXqMSQkBQMGLDQDdQL4kCHpCAtLVbl0Nl2RDm4EdL3jm2TmFLGRndMQhiF27mOO3NLr0aOzlSMc8+gxMdnKKW7ixCI89NAWVbbmOForW8s9mIuy02XYeXYnGq83qhA6WSiZ9+6Lu5WX+95Le1H+Vjm2ntyK4mPFKD1Viu1ntmPz8c0ofVMTzhUfK0bRkSJsO7kNey7uaTaouahZrdJOVjm7CdEZj9v3/j5l7Vr3YZ2WDri4R5Wxcb/shV53pU6J3ySYMwTPOva6K80WsTSzIYsn0O+9tFexe0YxeL0U21WcqcDYZ4dgwf2OmO3pjrTwcKwcPhzrxo5FwbhxCsBzYmIUcGdFRWHViBFm5W0ETClmY7idYCwBWfZVJ1sn2JPp60VuMmzOz5GlbulDhiijGv1CQPq+sx5egrU0oNHn1HkMy9zoDCcBXpatMYduhNzbNgxAFzfx22//rcLtr129u8LtQOcBdBsbGzg4eKJ791dw772J8PB4CX36zFZKdIriZN5cAr7Mr+vD8RTTNfu2JypWTxBnHl32Q6dD3NChy83C8DSRIeOmsE3vFifd3ZgnJxOXdeh0e5MLAwn0Ws48WzB1DchjYnIUoLPT2pQpWxEwMBGOozXr12k501D3YR1W7F2BPe9qYeqSN0q0vPm5SuW6RtMV2r/SLIaq95I3SjQ1+xua7Wvxa8VKNLfn4h7VjpUMmqY1bLZC1ksg5j4lejMBuwLz95rBnvl3ecy+9/eZATod5bifAjdlB2sSyvGz6F5Xc7kGdVfqFMjLc1LYN3vVL5Ac1gMze7th4YAByI6JQUpICNZGRyMvNharR45ETkyMmcp9RUSEqkmXinjWoktxm1SgMzdOsxqpjCfDZ0hegjrPw0ea0DBkr2frUmQnlfQEcimgk73a9d3dpOGMVMYzb06WPr9fP7V4MIxl2jcMQDfdxN/+8Ws8VfI2/FOaELjsVXz993/e5its/+gsgG5vbw8nJy94eKTBx2ehySkuAQMGLFTMnGBOgDcPvWtKdze351uUuRG8BwxYqBg7y9ToEkdHOH1f86FDl6swOxXveiMZhs7JvqluZwkamTpz6zI3zvA6gVqeh2DOR76HAK4H9MmTixETkwN3r2lwHN3cnIVObMwll58uV6BH4Vr1pWrsurAL5afLlSK+9FSpAvay02VaS1XT3Hh0I7af2a6OrfuwToXJ97y7R4EnXemk9Stz1QR7htvrPqxTofR97+3DwWsHzULkNIGhAl2y8z0X92jGMh/WqYWDmdLdZDdLZbtyrRM2tCyLk+C+68IuxDwVhoUDnZDg1QtrIiORFh6ONZGRyIuNRU5MDNZERqJw/HhlB5s7ZowKuTPfvXL4cMWwZQc2ycDJvpcPHYrFAwcqdTz3M+wujyOgk+mTieunXognIwDST54hdcngJXiTdevFc/owPcvXKIqT1q9GDr19wwB0002cVnEB/ilNCEo7jLp3P7nNV3dzo7MAup2dnbJ+9fdPhofHS6ojWmBgomLaAwcuVuF2bidI9++/QC0A9O5wzeVqCcrDncxcOsOxD/mwYRmqPWpISAqGDElXoE6hnBS1ydw4S9MkOJPNk7UTxJkjl2H2mJhsBeTcL8PsZOhSFMcc+k9/us3M+nXBpgXYf2U/svZnKVa7+fhm5QDXeL1R5aRrP6jVWp+e04RyrDmvPFephG+sX2eonfvY2KT+o3ozv3aCM/PgBFuGxGsv1yqr1oPXDjbXlH9Ur4BVlpHRUU4COhcSB64eUFEIRgH42cyPq9C8YOl0l5PnZChe5tBnebgjKSgIuWPGICUkBGsiI1XYPXv0aOXjLkvbCMoEe4IzAXVNZCSWhoaaCebItFePHKkWBKtGjDALtXORQECnbzwXAJLRU1SnD8NLBs86dLJwhtkpmNP3X0+0oG6XdeoMu88LCFAMnYsGNmcxAL1twwB0000sOv6f8E9pQvTa1++KzmqWRmcAdFtbW9jb28PFpQ96914GX99FZsp21ptrYJ7QItQugZ2PNJ6RwjgCfmDgIvVeWYsuWThrzyUrDwpKQkTEClWDzp7mDJXL/uYMwUtw14fhmVuX6nWWpFEcx3x7s5FMthkzlwydOXQP31lwHvMARkwdq5nDnNDKz+o/qseBqwdQdrpMNTxhqJ2NStjIheK3za9vVoYypW+WqoVA2ekybDu5DRVvazn5A1cPYNeFXZr3u+l8dR/WqXIyWbbGcjOydgKwqiU3KczrP6o3KyOjIp3NXGRoXArk6q/Wo+Fag3kduklBT1Zee7lW5f31rL/hWoO6pupL1Yj9xRAkDnTGy/d6KpDOjonBurFjlclMwbhxCrSzY2KwIiJChdsJ5FSo0w6WU5af8Tnr19OHDFHnoYKeEQKG3Tkl6+d7COiy5E3awUqTGwK4rEuXDWQkE5dsnOF25tSpcJcla8sGD1btU4069PYNA9BNN/Hrv/8TI9e8Bv+UJjS89z+3+epubnQGQCeok6Hfe28ifHxmmnVIaw6jJ5iF0PVhdRmGl3XoXATIOnSG3hmKJ6hT7EYQp2lMeHiaao3KHugRESsQFpaqwFvfUU22PB09OttMLCeBW9/rnOH5MWNyVQ6d7J2snOVq48YVIDY2DzEx2fjZz8rgF7gQTjGTcO8D92FazjRUvVOFtQfWYt/7Whi74kwF6q/WN7NnU89w9gtnGJ3qdRrLlL6phd7LTpeh8nwlSk5orVO5CNh2chu2ntyKqnc0Jzd2TSOIE8jrPqxTIFz/Ub26lvqP6lWZGUPntZdrVd26yqFfNmfTKmxuMpjhIoARA1nSRoOZvZf2KnAnE+cCRAJ74/VGTE//ucqhJwYGInv0aCwbPBhro6NROH48MkeNQo6pw1pWVBTyYmPNVPBk0wRXMmSpZJcAK3PbDLGnhoWpXDzBXm82w/dzESHbt8qQvmy7SjEd8+YLBwxo0SCGRjJp4eFmane9WxzBXHZfk6DOz3ypWzcD0NsxDEA33cSPP/8LQjOOwD+lCSeuf3abr+7mRmcB9K5du8LFpQ88PNIREJAilOvN9q16oxiCM61grdWhSyZPQxmCOM/BSdEb8+cDBy42U7OzXC0kJEUBt95MhoYxQ4akKyW73mxmxIhViI3NM2u00lySlmOWW2cOPS53ye9GAAAgAElEQVQu3ySGy1bh9ri4fDWnTNmq5dC9p8MpZhLCfjFK5b+p/K54u0IxcQI4G5nQNY690ZlT33l2J8rf0sxk6BRXeqpU2clWnq/ExqMbNZHcm6Wq7I0LB6rIzdqgmjqbHbx2UOXbCag1l2sUE2e5Wv1V7bWl0DiFdA3XGtRj7Qe16n0EfZlPl21ZuRBQUQER4i87XaZy6C/7eKga8+yYGAXifM5WqmyfSlvYNZGRKpzOkDnBnbl1CsYIwhLol4aGKqDPGDYMmaNGYfnQoSpcvzQ0VIXkpRKe7J7hdulUR3CV5jJk4dxPgxra0LLOnSF0fW267LImJxm6VLkbIfe2DwPQb9zA13//J6LXaur2n248jX99++/bfXk3NToLoGug7gFX12Tcd1+asHNNUHlvfetTGsXIOnT5XD+1nLymcjcPwSealaxJT3YC+qBBS8xqz2XZGkvZZMidKnWayAwZkq6U7bGxeQq8Zf6cuXOWpjE0L0PucXH5CvQJ7KxDj43NUyp3h+iJCJgSgnnF89B4vRHlp8vNaq9VGPv9fc1KcAF6lecrFZBTGFd1oUqVrVW8XaHYePnpcsXO2aOcfcj3XNyjgLL+o3oVJaDIjddRc7lGgTFD5Myh01tdAq+cNZdrcPDaQY2dm4BYnkfm5Xnemss1aLjWoPL2+jC+nM8lT0HSIFfM9nTH0tBQFE6YgOyYGOTFxipWnh8XhxwTsOfFxiomTTBnSVvGsGGqhpzsWbZBlYI3Wba2asQItRAg22cYn4uClcOHm9nASkW8XuUuQ/5k4lS0k7FLQCcrl3XuZO4S2GlMQ6MZqtwX9O/fIoduqNzbNgxAv3EDpaf+W+XP//CXu8tMRo7OAOhauL0revToC0/PdPj7Jyt2zn7oZOcaw05s4ctOwJcMnqDNHDvBnO+XgjiWqkmHOArkGFYnYNN3nbasUt0um7CwoQrNZugUFx29FmPG5JqZxkRHr0VsbJ5ZXl0ydPY/J6hHR6/FuHEFKoceG5uHRx4pRWxsHnr6zIDzmMmYuOARFYKuuVyDXRd2qTwyw9gUscnysB1nd6DyXKUCZWn1yvD8tpPbsOPsDuy/sl+Vuu2+uNtsYUAnNjqz1VyuUUybCwsCLcVyBGxeD0PvBF4uEDj5uuFagzpWD9AEcCrfGXZvvN5odjxz71xkNF5vRMXbFYj++SAsHOiEBX7e2DBpEtZGRytzmayoKOSOGaMec8eMUfXndJBjLTofCchUpcv+5ARgaQmrrz+nSQ3Po8+j81gZlpdtWFdERKjQP8P+zJ9Lkxmq32XjGJljJ1CTtS8SefO5fn6qDzpL1mZ4eWGGl5eRQ2/nMAD9xg0sPfAB/FOakHvk2u2+rO81DEA3AN0AdAPQDUD/Yf6/3Q3DAPQbN5Bz+Br8U5qwovHD231Z32t0FkC3t7eHg4MnXF2TcN99aWYNWeSkyxsbrQwYsNAs1G6tOQtBPSgoSZ2DoM5tgYGLVD06u6bJnHpo6FIMHLhYgTqFc1Su0zwmKipLgT1z6MOHrzQziZE2rwRl1qyzC5tUv8tcO/PoeutXiuICBibCKWYS+j8SivRd6SoXvP3MdjM3NdZ/052NoXfm0stPl6PyvObXvuXEFhWG33l2J7ad3IZNxzepcrSSN0qw68IulYvnZHifIffqS9Wo/6i+2epVhMRZokaQZ86c76Utqz4kXvdhndlnEODlQoALBpa9yfI3Gc6X/vCcL6U9jqRBWtla+pAhKJ48WZWSZY8erUxl8uPikB8Xp5zjKIqjqYxUrsvSMlnGRkU8RWiy0xpBeEVEBFaPHIllgwerkL8UxhHQGdpnDp2iOksheDrMJQUFtbCmlY1fZPmaVLQv6N/fTAzHHDuBXnZfm+7igrn29gagt3EYgH7jBna+/Wv4pzThhfLzt/uyvtfoDIBuY2OjytbYPlU6vEnlOgGcYjjzDmwJSujW7OeeoABdlqhRGEdlO7cTqJk3J8BzO0vVaC7D0jLZ13zkyNWqTp0e72Taw4ZlKPAmIycoSwHciBGrEBOTY2Yfy2PZ/5xsnfMnP9mM2Ng89O4zE04xkxA7ZzLKT5crJTuZ895Le5utWE3iMNmLnI+sN2cuvPi1YqVy33F2B7af2a4J6s5pynjWppPpSzYt8+IEXSrM6z7Ucvl1V+oUoKq68SvN+XM6wlli6PveM8+Vy1w769xZe06PeC4emKtn3l2ev/J8JcY9PwwLBzoh0f9eFIwbp0CcinYCOGd2TIzG0E3HZI4ahbXR0QrQV48caQbULClj7bkEfKlkp/2rdKBjeRxZN5k5Xy8fOtRsIUHVvOzgRoX74oEDlbo+JSTELMcu260yny5r0qloZ2MXCfZk6NO9vDDdYOjtHgag37iBs//9B/inNCE298TtvqzvNToLoNvZ2aFLl95wdU1G//5L4eMz06zBCkVyUhCnD7Hr26hKhs7FAZXuWnOWRDODGbrHscacYM5QO/uV6/3bIyJWKJ/3sLBUFWqXJWpk6FwA0AimubY8W7nBRUauMQPzmJhs0zbtOJapSWOZCRPWIzp6LR55pFQx9H4/HYSU7SlovN6I4mPFqm1q/dV6FTpnKJx2qmThey7u0ZqnmERvpW+WqpK27We2Y997+7T2qiYnuKoLWstVtlRlK1WCNxcQDG0TcBXIvr9PHUvxmp4pKyW6ThgnVfHqvKJ+ff+V/dh1YZdaULCeXXrCc6Ehy+jI7meueBpJg1wxs7cbkoKCUDRxIrKiolTb1LXR0cgePRpro6NVOJ790Vm3Lpm6ZMwEYalyly5wywYPNrOAXRERgVUjRigjGYriZEhe7+Eue7LL1qwM+ROkKYJbERGhxHDs5GbNWIaWsKw7l0xdusgR6BcFBuKlbt0MlXs7xh0H6BkZGS1u0sCBA9X+v/3tb0hISECvXr3QvXt3PP744/j00/b7rsub+NZ/fQH/lCZMKjh5K7/Kjz46C6B37doVrq6+8PFZiYCAFJMxTIKYc82AWyrZLdWbS193ve87mTnz6fRxpwNcSEiKMpkhsDPMHhaWqvLiNI0h6DPkzhw73d2io9di6NDlVr3ZGXJnnbq0gJXd1RhqJ8Onsp3A/vDDJRgzJhc9fWag+9gHEffyT1QzFCrPK89Vqjpslq+xZ7hsp8oe4syfl50uU81bdpzdgcrzldh2cht2nt2pnftCleYqd17rrV5zuQa7L+42Y8DMZbMJCqMD0pWNeXCG0ZkGYLMUAr6+bE0fKlfnMLF/mUdXDWGuNIfqydC5QGB+v/J8JcY/H4HEgc6Y7+ul2qYyb54j1O50issePVr1RGcdOufyoUPNcukEaYa2uV2awciOaGTnnCyLo4KeFrFp4eFKWU8jG5lPlwsIfQvVjGHDzIxlOGV/dNagE6zZNpVALsvaWNuuZ+iGyr1t444E9EGDBuH3v/+9ml988YXaP3v2bPTt2xevv/46Ll68iMjISERHR7f7c+RNPGMC9Kis4/j3v+/OkjWg8wA6jWVcXZMREJDSog86xXESnFl2Zqmrmh7Q2Zil2VxGK1VjZzWWpYWFparwu7R5DQtLNQu562vTae0qm67QJCYmJlstAqSVa3T0WowfX6jEb2PG5ComzhD8qFGZCsDpCMd69LFj12H8+EKMH1+ISZM2IC4uH488Uoq+9y2A4+hJ6PuT+7F893I0Xm9E0ZEiFQ6vPFdp5nNec7kGe97VbFzZq5y16OWnta5rFW9XaO5xJjtYdnCjFawseSNbZiifoKqarJgc4mgXy+3MebM2neF4WYcu8+Z6AFcAL5zmKPqjQQ2/b/WlasXQeQzPKSMIiqGHagw9fcgQbJg0SXOLM4Xe10ZHY93YsWYhd1mLztx15qhRZvXiDKtThCZtXMmoyebJ8hnCJyOXoM1FA89P8JfhexrJMJxOe9hFphI05tJlWJ4gnhQUpARybMKiF8PR6pXAzmO4b15AAKY6Oxsh93aMOxLQw8PDLe776quv0LVrV9TW1qpt165dg42NDc6ePduuz5E38auv/6F6oP/pf28dEP7YozMAuq2trWqf6uWVgf79U1V3NSl0k0p2yc71zF3/WubVqZQnSyeQE9SDg5PNmrMQvFmfzpB8eHiaAu5RozIRHJysVO70bqfwjd7tFMzJHHpsbJ5SyXN/TEyzGE6y/OjotYiLy8eECYUK2OkUN3bsOkyZshXR0Wvhds9LcBw9CVHx45UIjv3Jaz/QWqYSfNmgpfJ8pWpRSla+7/19KD1Vim0ntylRHU1ltp7ciupL1ag4U4Gy02VmLVJZD7774m6lgpf5bHqo641jGq41KCGddIzjewnoBHxL4riD1w4q8R0XDcyX01Bm76W9yuCm7sM6dV4uQGT9esmJEqVyn9/XC4XjxyPHlCNnqF1NwdAzR41S7JmsnKFzguzqkSPNwFV2TJMgTRCXtecyfM9z6l8zbE9DGX1rVuksx/pzWsMSzKXPuwy5k52z1pzsnPXnFMoR7JcNHoxpnp6Y5umJ5+ztDYbejnFHAnq3bt3g4+ODfv364dlnn8VvfvMbAMDrr78OGxsbfPnll2bv8fPzQ0FBQbs+R97E9377JfxTmjBk5VGDoVsYdxKgE9Q1lbvG0JlDJ1PXRG4tm7JYc4WTIXZpTKOF2RcpUZ1Utmt59UVK1T548DIMHLgYERErFMAT0BlaHzIkHaGhSzF06HIEBycjODhZ5cLZYIWgL7unNbP3HAXeY8euU+BPtziWt9FJjs8phCOgT5q0AbGxeXj44RL4DpgPh+iJ8J0cqIxlKs5UqHap+ln3YZ1irwy5k4lXvK3Zv1ac0cLtFW9XqNB7yQlTDt0Unqc6nuFs5uRl6RnFaxSkyWYqBGWCPduuShU8hXP1H9W3aNJiCfgPXjuozsVmMPVX65VuYP+V/Th47WBzQxcLufvnkqfgleDumOXhjuTgYGx56CGzHHpWVJQZsEvDGYKxZNKrRoxQjDlz1CizsjWGyylqSx8yBGsiI9XigSH5zFGjFPBzkonz3DwPVeqy8xqfy1x9UlCQUr4zpy7tXmU/dCmMS9SF3gn4BHQCPX3fX3B0xGwbG7jb2hqA3oZxxwH6q6++ipqaGly+fBlHjhxBVFQU/Pz88Oc//xm7d++Gg4NDi/eMGDECycnJrZ73m2++wY0bN9T85JNP1E3MbLoK/5QmvFRx4Yf6Wj/K+LEBvbXftD2jvYBub28PZ2dveHllwNf3FdWQRc+yZRtUS0Auvd2loE6WuQUGLkJQUJIC9pCQFNX/nOVpBPCwsFSVX+e+oUOXIzJyjRLKkZlTTCfbo7LMTIbOycKjorJUG9SYmByL3diYH5flaRMmFKracwJ7TEwOHnmkFJGRa+DuPR3OYyZj1LQ4VJ6rVABWeb5SqdylEp0lZNWXqrH9zHbsPLsT289sx8ajG1FyogTbTm5D1YUqJYjjMeWny7VQvckdjo8sg2NLVYa8GQpnXp/hbsnCZUtX1qUrpzgB4JbK1ySgE8D5XdkBTvrBM5fPvLm+H3rj9UaUv1WOmKfCVHOWvNhYrBs7VjFxWaZGUZzMpzN8zhB5Wni4GdsmuJMxM0zP96yIiFBlaQR3sn7m5CV4c8GQMWwYsqKilNUsw+0M/cuoAJm6tIWlUxxfM+zOXD+7sTGXLn3dF+ly6PMCArA0NBQveXjgJQ8Po31qO8cdB+j68eWXX6JHjx4oKyv7XoBuSWxnY2ODz/7wJwxYegj+KU0oPfXfP9TX+FHGjw3o1n7TH4Ohd+nSG927L7YoiiOAS7BmDl02apHtUxliZ6mbLHmTwM7QO/uhcw4blmFm+RoenmZWwhYenqbK0gjEI0euRnh4mgL9yMg1JtDOVqp1Sz3OWYM+YUKhOhe3E9DHjMlV+fO4uHyMH1+oAH3ixCKMGZOLhx8uQd/7FsAheiL8HgrCgs0L0HCtQeW6K86Ye7mzdEy2MmUIniVsuy7sUt3VCJKlb5ai8pwmmqt4u0Kxey4gKDareqdKAbPaflWrQ+drCebcT5EalfFk3ZbqxPVT7/dOIxsuMqSwjvXqljziOZ9NehivBHfHzN5uWBoaiqKJE7E2OlqZx+THxZmF3/NiY5UwjtavZNdseiL91SVjJruWOXQq3wnkDMWzTSs7sMnuazKXzsYu3M8oAN+TFRWlcunShpYAnj5kiGLi+n7oBG0K5biNDJ42sAT7RFMdeoKdnRFyb+O44wEdAIYPH44lS5Z8r5C7NTb51Vdf4emtb8M/pQnPbG1fHv5OG52Bodva2sLW1lbl0C3Vofv6zlGhdrJugncz2CeYqdy5GJBNXCRLl+F3ht0HD16mVO50iGM4XorkZF06c+rstibbpVKhLtXqBHru5/sI4BERKxATk2PmIqcvV4uLyzdj97GxeXj00XKMHp0Nd69pcIrRcuhk4DWXa1DxtiZe23F2h5kCfNeFXUqgxhxyxZkKFSqvulCFzcc3o/RUKXZd2IVdF3YpQRybv+y5uEc5y/HzZA6bLUnVdlMNPF3b2PlNKuBZM05At8SgZXmZtRD8vve08zM6oaIUps/Tg79szlJ+uhyjfx6q5dB9vVT9eX5cnALqVSNGKJc4OsVJcGfIneyZ/c8JsDJfTXAm8BK8Cc5Swc7SNSrlZS90uSCQ5jUsVZMCvFUjRmDJoEEq3C4bsFAMx9A7hW10ipPiN5asUeVOpj7H1xdp4eGI9/ZGvLe3wdDbOe54QP/LX/6Cnj17oqioSIni9u/fr/Zfv34dNjbfTxT36y/+F/4pTei/9BCu/u7uvamdJYduY2ODLl16w8VlMQIClqgcusyDk7VT2KYPt/v4zDRru6oHfubQ6TRHUGffc6ls1092X6OpDEvTRoxYpZg6gZkNWci+o6PXmjFxitxkv/Po6LWqpn3YsAyL7VTHjl2ncu0UyDXXoRcqYZzG0Ccg4OFgJJcno/F6o9YJzVQbXnO5Rlm/Vl2oUnl0gtyed/dogM0a83eqUPJGieq8xn1ssbrz7E7seVcDdHZpo/Mc895k6LR/pTiOuXZpMFP1TpVWdnalTrFnnk8PvnSAo9DOkgKepWpk6HUf1llcHFhj/9PSn8Ci4G6Yc09PpISEYMOkSWa58Rb5dFG6RoEcBWvsYy7ZNEPesnZc2rZKxp05ahRWjxyJtdHRSvmu77dOkCags2ELFw/SmW7Z4MFYExmpmDivYdWIEXjW1dUsV75s8GAF3tzGcLwUwelz6nwPc+8zXF2RYGdnAHobxx0H6K+88gpOnjyJX//61zhz5gwmTpwIDw8PfP755wC0sjU/Pz+cOHECFy9eRFRUFKKiotr9Ofqb+IttZ1XpmtFtzXzcaYBub28PV1dflUPXl61ZsoHV7GETWpS3yfI12TpVAjnFdQy5h4SkKGc4htyHDEk3M5eh1eugQUsUIx86dLli5GTeFMyx/EyG2nkclewytM4ZGbkGERErFHunQl6yfRrJsIZ97Nh1ePTRckRFZakcevTMicqCtfZyLXae3YndF3ebublVXahSrJmit60nt2LbyW3Y/PpmbDmxBcWvFWPH2R3YenKrmjvP7tR6npt6n5Ohs6vbvveau7hVXahSLJtmM2TcVOCrdqcfNYfmGXKXjJnhcmnbyjy8BHg631Vfqlb18HVX6lRYX7J5aRnL2vPK85VovN6I0lOlGPVYkGLouWPGqDI16ePOEHzmqFGKwcuyNQIl89lky7RwlSBPME8LD1c15suHDlUmNRTBMfwuP4Me7DwPzWeoqie4c7HAfQy/cz/z5LKWXNq5EqSpbidzlwYyZOkJfn5IDQszvNxvctxxgP7000/Dx8cHDg4O6NOnD55++ml8/PHHaj+NZXr27Ilu3brhsccew+9///t2f47+Jp76z8/hn9KEsIwj+NYAdLNxpwG6jY0NHB3vgZtbCvr3T4WX1wz4+MxUefA+fWabKdfpCCeBn6VuGpOfq0rb2NxFNmshsBPQORleZ4idKvbw8DTVoEW2TGUOnUYwsv0p8+cEeLJtycoZWudksxfWsUuGToc5lqyRmU+YUKhy6myf6hQzCQEPByO9SvNyL36tGFtPbsX+K/tR+mapMk9hCVvt5VqUny5H0eEibD25FcXHirH5+GblBrflxBZsO7kNuQ25yG3IRcWZCmw/s11zk7tQpTVuMYE6FxBcKOx5d48C0boP61B9qVr5qZN5s3yNgEuglU1jWoTbTUCuIgACmKWynouHA1cPNNeoX61vYVDD7fptz6f8FEmhrphzT0+khYdj04MPYm10NFYOH47C8ePN+qMzJL9u7FglWiOwSjYu3dtkHbps0sI6c4Ixw+zMqUunOII4w+4Mw0umL0vZyOyZ42fJ3NLQUFXCxoYs3JYcHNyiTaoUxbEXOh/n+vkp1TtZPZ3i5trbGzn0No47DtB/rKG/iRf/75/gn9KE8JVH8eXXd2ctugHoBqAbgG4AugHoP8z/t7thGIBuuon/+Ne3iMo6Dv+UJjy66a27MuzeWQDdzs4OLi594OOzEl5ezf7rsg69T5/ZZmYysiObBHWCuL6Ujd3WqHKXzVoI4CEhKaoMLTw8Te0bOnQ5Bg9ehuDgZFXONnTocuUWR+U61epsrsJcOcPlw4evVI5wBHYZaqdojsDO0reoqCxMmFCoQvxRUVmqBn3cuALExeVj8uRixMRkw917usn69SHsv7JfNU3Zc3EPyk6XqbpzhsvrrtRhz7t7UPG2ZhJD45itJ7ei6HCREsRtPbkVhYcKUXioEDvP7tTsYE3K+crzlVro3ZRLZzh9z7t7zMLaNI6pvVyr2qtKkxgCt742XebFlQjOlAunmI9mMczHM8xP0R3D81JIx/dKa9rdF3erMH3pqVLEPBWGRcHdsNDPBxsfeMAsrL4iIkKF3bOFS1zmqFFmynN9G1Spapeqc74moLP0bOXw4UqNztC+bMQiW6ayflxfdy7bpnIhoK9FXzJoEFLDwsxC7wRziuBYV86cOIGduXOG3xmSn+vnh6WhoZjp44OZPj6GKK6dwwB0cRPp6e6f0oS//eNft/Hqbm50FkC3tbVVDN3PL8kkimvJwC3VnpORE9hlTp2COpa6sS96c9e1RAQHJ2PQoCWqH7qsRyeYsx0qWTqPYYc1dlcjCMvcOMGd28nAuY/GMtLjPSJihWL+rFsfP74QAwYsNFPAs2ELle9TpmyF74D5cB7zAPo/Eoo1tWtQf7UeBYcKlAMcxW90hmMJ2b73NHV76ZulKH+rXJnHcBLEy06XmW3j3POuVuZW/la58o03a4byUT0q3q5Qyve6D+uw8+xOdR01l2uUEl6K1vSALsG+4VqDKktjqRzz8owKsClN5flK7L64W4kCG683IrM2Uy1WDl47qExtmI9vvN6IJ+ZPRMpgN8z2dMfqkSNROGGCAnUK1OSkaxwZsKwPZ46bjFqWsMm6cNnXnADMvDnz6rINKg1qmEdfMmiQWVe31SNHKu94+Vl0kePigtawZOusO2cZ2yLBtGVpGpXv8wICMLtPH5VPl/XpRtnazQ0D0MVN/M0fvlaAvqz+A/z5b/+4jVfY/tEZAF3zce8KF5c+8PRMh4/PQqVatwTc0jRGquH79JmtjmGJm94KlqF3CuNYgy7D7UFBScrnnTXloaFLFRtnk5bQ0KWIiFiB8PA0RESsUIBO8JeMnUBPRk5VPEGdHvB8TWEczxkTk4OQkBSMG1eARx4pxeDBy8xar0ZFZeEnP9mMkSNXw+2el9B97IMYN3+KKlPbf2U/St4oUcy88pxWM77z7E7se3+fErlRFFd2ugybX9+MwkOF2Py6xtArz1ei+Fgxio8VY9vJbag4U4HdF3drfdNN59pxdodiucrm1RRWr7lcY1ZPrgxjTO5wVMDXXq4192YXojiCOUPjstMaFwZk6dKKlmY18tx5jXnqM4qOFKmFBF3yGq83IvdgLqKeCEFikDMWBfgiJyYGq0aMUE1a6BKXFRWlxGpk6DRxIYNmjTfZMNkzAZQNWAjAsre5DMOTUdOvnVPax0rhGx3gZFtVXisXFPyclJAQxczp3a7vssZ69KSgIBVKTwoKUkA+188Pc/38VPidYC+tXw1Ab/swAF13EytNvdH9U5owbNUxNLz3P7fpCts/OgOgE9Rp/erruwje3vHw9o5XteQMr/v6zlFATwAnK+fkNtl2VTOeSVAmNDSZYdtUtk4NC0tVuXbmz2WLVRrQsISN9eoSfCMj16j2qlLZTsCmAY0Mz3Pqc+lk6yyHGzx4GcaMyUV4eBoGDFiIKVO2YsqUrZg0aYMCdW//BDiOnoT7fjYYqTtT0Xi9UbHqvZf2qnw3W6TSRGbT8U0oOVGiAfibpSh5owSbjm9SYfeKMxWKmZPFl50u0wxm3tJK2KgqZy6dtrGsSWefc9ahcxuBm9awltqaMrdO9kzLVi4UuJ217TIKwVRA5blKtdjYfmY7Ks5UqChAwaECs9w5UwFPzJ+IV4K742UfDywfOhQbJk1SAKqc4Uz16AR06fQmFedsS8owOJXv0rKV3uksHyOIy6YusoxNv2iQ9eecS0NDzXqk0wWO+Xuq6tlhjaH21LAw1bRFMnTmyQnu8wICMMfXF/MCArBy+HAs6N8fL/bqpQCdxy/o3x8vOjlhrr29EXJv4zAA3cJNfP3apxi37g0F7HvP/+Y2XGH7R2cBdDs7Ozg7e8PDIw0+PgtVSRpry8nEJVgT3CWYE8Q10VyCAnFZ005R3cCBixVbJ6DLWnQ2a5FGNPR7pxguMHCRWe/zkSNXm/VKHzp0uSpPI+uWAM/wu6xf5/sjIlYgOnotRo5crfLvERErEBi4CMOGZSA2Ns/Mbvbhh0swfPhKxdDHJjyIXRd2YevJrah6R7Nu3Xx8M6ouVKk2qCVvlGg16m+Wqpx50ZEiFB8rRu7BXJScKEHxMU1Qt/7wepS+WaqB/YkSrf+5idGXny7Hvvf3qaYtVe9UoUAbvDwAACAASURBVPYDrVROhs8rz1WqSAA7tjFvTgFc4/VG7Lm4xwzYZe6cgraayzUqfUCWTwtb2Zyl6p0q5Su/5909qt1q4auF2PfePpSfLsfi0sUK2PkdG683IqchB0On9Fc59IJx47BqxAgF5Ay5y7amMrRuKYS9eOBA1cVM3zBFgq4MxdPtjS1PuWiQ72fenAsBviaArxw+vAV7Z4ieiw9eb2pYmFlNOUvYmEOX/uwMr8d7e6v68+fd3JQRzRxfXyQHB+OX7u74pbs7fmFrazRnaccwAN3KTfzHv77F4pr34Z/ShIjVx37kq7u50ZkA3c6uJ1xcFsPPLwkeHi/B2zu+BfsmW6eaXc/QGXLXv0f2VJdMvV+/+QgKSkK/fvMVC2d+fMiQdAQGJiohHvcHBiYiJCRFhc2Dg5MRGblGecAPH76yhXMcwZvgTBGcbLvKFqtcLAwevAwjR65Wi4MRI1YhNjYPw4ZlKH94Aj+Z/eTJxYqhB0wJQWJJImov16Lw1UJsPr5ZgTebrNCTnW1SS94oQdGRIhQdLkLBoQIUHytWnu4bj27E+sPrNWA/VYp1jetQdrpMa69qMpjZcmIL9r2nsV+600nR256Le7Dh6AZtEWAKbW85sUWx79oPahVrrr5UrULpdIyTYXh2UVNheeHPvvfSXhWF4KRLXMXbFSh/q1yp8fN/lY+qC5qQr/DVQpWOYJ79sbnjsSi4G2Z7umPJoEHKJY5CNYIjleNk5WTLZORUjBOAl4aGqs5mDGnzNYFYMmoCMm1g2UQlKShIhcgpYOPCguI2Waeu77bGGnleD1m6bLyiV6pT2U51O+fsPn0Q7+2N6V5emN+vH2Z4eSnAZyj+BScnA9DbMQxAb+Um/u7LvyqWfuiD//cjXt3Njc4A6La2trC3t4eTkxc8PdPh5TVfMW/p/sZtBGw9cDc7xJmbzRDU9d3YWMLWHHrXjGbY65x59oCAeSI0n6iMaGJicsyANzw8TQG5FNHJEDoZtwy9My8/ZEi6Amg60TFvP2LEKkRHr8WQIemq9erw4StVP/SYmBxMmrQBw4ZloIfni3Ae8wCi4scrQ5jSN0tV+Hvn2Z2ouqC5xJWfLlclaVS2bzmxBUWHNZZe/lY5Nh3fhMJDhVh7YC02H9+Mzcc3I78pX4E8FwLbz2xXkYC6D+uw7eQ2BcpkzeWny7Hx6EaUnirFhqMbUPG2FsZnTnzfe/tUfp3NVCSIH7h6QOXZWYLWcK1B2cnSU57Mf9/7+9Q2pgDoOb//yn7surBLCehK3tBEftJYJv9X+Rg6pT8W3O+I+X29kB0To8rG6Ba3IiLCzAFOLzpjHpu5bIIs3ddkL3Sau0jPd4L54oEDlWscw/f6SfAl6JP1k+Xzs+V7uOiQvu3Sj51snKF2htEphpOGMjN9fDDH1xfz+/XDTB8fxHt7Y4aXF5YMGqSas7B9qhFyb9swAP07bmJSrcbS71/2Kj678bcf6epubnQGQOek9eu99ybC03OaWbhdPy0x89ZC8fre6lIcJ1m3n99cFXIPCkpqcTzFdSEhKUrURmbO+vUhQ9JVPp2hdObWybYjI9coNk52zpw7Gb7sp65vuxodvRYRESvU4mPChEKTg1whPPvO0tqnPng/ErckovpSNbIPZCvHt/ymfNXXXIbdN7++WXOIO74Zm45vwoajG1ByogRbTmxB/q/yUXCoQM2NRzei8NVClJzQGD2btZS+WaotFEwMeNPxTYptV1+qVguCjUc3quhAyRtaRzcCd8XbzQydpWksRaN7XN2VOtX6lPXley/tReU5bdFS/la5WrSwexzL9CrOaNEJsvbK85VouNagleGZPrvxeiOq3tEc7n46OxavBHdHfK8eSAkJQe6YMar1KRXsehtWgujK4cORGhZm5tku673JiAn4sutZ+pAhSA4ONuuTnhgYqBTuDIUvCgxUOW6ec/HAger6koKClL0rWTpz6EwDcJtUtcvzL+jfX4XTKXaTrJzlaXP9/DDH1xcL+vdX29lxjZM5dIOht20YgP4dN/Ff3/4bj256C/4pTVhz6KMf6epubnQWQGcduoeHxtC9vGbA2zteAThfE6B9fGaq/fqwPAFftk+VIXeWwMmWqmTgwcHJCqCplJeiOHrIBwUlqdD4wIGLMXz4SrWfJWcSoMPCUpW/O9k7Q+bMg/P4oUOXq8UCc+56QB89Ohvh4WnKoGbo0OWYPLkY4eFp6OH5IpxiJiFyxniUny5X4fbtZ7aj+JgG6sWvFSuzGQLqpuObUPxaMdY1rsOGoxu00PuRIuQ25GLj0Y3Y/Ppm5B7MRe7BXBQfK9YEcm+UqNp1qujzm/JRfaka6w+v10riPqrHxqMbsfHoRpWXrzxXqaIChYcKVViebVVZI77v/X2qsYv0c6d6nvsYYq++VK01lzH1aWfb1/K3ylVTFoI+mTrtcAsPFaLmcg22nNiCLSe2oPF6I9bUrkHEI/dhfqADErx6IS82VuW2c8eMMVOPUxSn755GkGS4mwyYwCnBlQxe9jAnqDP3vnrkSMWWWU4mlegLBwxAaliYAnQpcqNYTn9NeoYv2TmFb3rL1wX9+yPBzw8JJgMZWX8+LyAA0zw9kRgYiHhvbywKDMTU3r0xtXdvPN+lC2YZDL3NwwD0NtzEE9c+g39KE4LSDuObf9659emdBdC10jUPuLgsho/PQnh6ToOX13QF6Prwu5fXDHh5zWixnQxdD/DNzV3mtmDqBOmBAxfDz2+u6rY2aNASsy5tFMRRBR8enobIyDUICkpS5W169Tv7pDMMT8ZNIR1BW06G2EeNyjQzrZG17cybU1wXF5eP2Ng8jB9fCC//OXCInoi+P7kfi7YuQuW5SuT/Kh+5DbkoPVWKjUc3qvKzrSe3YsPRDdhwdAOKjxVj/eH1KDhUgNyGXBS+WohNxzchvykfK/euRNHhIuUUV3SkCOsPr1cKeJ5ry4ktKD1Vqsxsil8rVgYze97doxYKjA6UnipF4aFCFB8rVrXmW09uNStRYwic9etsv0pwZ+MXetSrsLqYVPbvurBLGd9UnNG6zymDHFM3OubcD147iPqr9fjprFgkBjmr9qk5JkEae5sTwKXQjKBJhTiV67KfuARyAir3k02TrXMRkRQUpDzZZX6b75UgzDw/GTwjAPJzGdrXt00lqCeKkLsMsTPMTjCX+xcOGIC5fn6Y3acPEkyMXTL4FxwdMcfW1gD0Ng4D0NtwE//9739j0PIj8E9pwvNl5/Cfn/75R7jC9o/OAOi2traws7ND9+73KoZOVm6JoUtWLsGeIXeyd0uCOoI4S9mk7Ssd5NicJTg4Gf36zVfheobdmUMfNixDGdCEhi5VCwGGwYcMSVdiNgK1VMAT1AnkfA+Plfl1huW1pi+aAx3r0/n64YdLEBaWih6eU+E85gFEx09Q6nQ2Wtl0fBM2Hd+kQt9lp8s0sDex7sJXtbrzDUc3YMuJLSh5owQFhwqUQxwZesGhAmw+vhl5jXkofq0YBYcKUHa6DFUXqrDp+CZUnqtUHd7qP6pX5jMM2fPzN7+uhferLmgCtPLT5So3vu99rcGLavUqXOXo7sYuazWXa1D7Qa1S79NEZvfF3eqzuYCoOFOBXRd2oeJMhXKHY6kbt1OYl16VjrAH/VRzFjZcYdczdlGj7Sp7njM3TnCUKnfWdycHB6u2pARxgrsUyC0eOFDl0Cm+I9hyErAZ3k4NC1OiODL7pKAglauX4X8ydLJ8ae/KKZ3fmEPnpMUrt5O1M+w+x9fXjKE/Z29vMPR2DAPQ23gTsw59pARy96Uewoe/++oHvsL2j84A6JYYuofHSwqY5bTEzCW4W8qvS8CnaE62ViXjJlPnay3svkgtALhgCAxMVN3YaEgTEbFCqeNpREOlPO1aCewEcoroyOwpsKPtLH3juQiQuXmG2snY4+LyEROjtVbt3SceDtET4Ds5EAlFCdh+ZjsyazNVyHz94fUqBL7p+Cbl215wqEDlyvMa81B4qBDZB7KR05CDdY3rNOZuAnSeh0ydde5bTmxB6ZulKD5WjOpL1cjan6VK2Go/qEXpm6XIachBZm0mVu5diZyGHA3QTV3Y9lzUWrfuvbRXPUpb1r2X9qLuwzqV/957aa+mjH+7QgE16+K3n9mO7We2KxOcnWd3mtfZnyhRYfmqC1Uakzedp+JMBRquNWDfe/sweWokEoOcVQ59TWSkAkNZJy5tWNOHDFG15JINM3RO5p4UFKSeS1AlQ2dpW1JQEDKGDVPMmyYwsoRMGr4kBwcrA5r5/fphyaBBmN+vn1m0gAsHhvUlM5chdsnI5/j6Yo6vrzKO0QP4TB8fM6AnyC8cMEAd96JJ5W4AetuGAejtuIlXf3cDwzNfg39KExbXvI9///vO8nvvTIDu7OyN3r2XwdNzngm8p5sxdAngGrBPN8unc+pD9LJHOhu1NIN6ggJ1lrGxeQu926lsp3iOTVvY2IUhdukiN3TockRGrlFNXci+R4xYZdbwhS5zkqET3HmMZPIE9BEjVrWwl6XK3e2el1QOvex0GTJrM5stXN8oUeF2MvK8xjxVb174aiHym7Tw/LrGdciuz0b2gWzkHsxFTkOOmpm1mSg4VICiI1p524ajG1B6qlTl3Xec3YGdZ3ei+FixZjRDVf1b5Sg+Voyiw0XIrM3EusZ1GkhfqdPK2EztV4uPFaumLQRuMnQK5Gov12Lf+/vUZ7G+naY3BHSmANhMhp/Dsjka4XBSMNh4vRGLSxdj8EMBWHC/A+b39VIe7bJpCsvM9L7qtFWVOWuCLZkvmbgsP2NOnOF2eQ6y9NSwMBXanivy2Av69zfLuS/o3x8Zw4Ypds7FBKcEdkslaawzlyI4hs9ZY55gugYpiuM1kaEv6N8fz/XooU2DobdrGIDezpv42tVPFVOfuv083vqvL+4YYO9MgG5r647u3V8xy6Fzytc+PjPh4fESPDxeMjtGArheQCeBXzJ4AjvV6yxjY0kbw+sUxgUFJSEkJEU9MjxPBzlaxEqDmqFDlyMkJAXh4WnKZU6K4TilTzyPGzx4GUJCUhTAE/yplGcofuTI1Rg9OhvjxhWYcugT4DNpAF7e+DJ2nt2JjN0ZyD6QrRj15tc3q9D6puObkNOQo+XNDxWi8NVC5DTkIPtANtY1rkNuQy4yazOR/6t8ZOzO0M5VrzH3vMY8rD+8HmsPrFXAvun4Jq2PuqnsTQ+ezGmXnChB5flKBeIVZypQfKwYVe9oynR6wjOnXXmuEnsv7VVK9dJTpYrJbz+zXZ239FSpMsrZenKrMsHZenKryvfTrpbgzVp8mXdnZOGnszSV+ywPdyQFBSErKkrVh6eFhyuDFzJn6bjG8LasGSeQ6gVoiwIDzfLZBF/m0hl+lzl7htDJzmnDygjBosBAtUBICw9Houkz+D5+vjSP0XdTY35cit+YG+fz+f36KQbO7WTrEtjn+PriBScnI4fejmEA+k3cxMq3f41+S5oUsE8ufBMXfv3HH+Aq2zcMQDcA3QB0A9ANQP9h/r/dDcMA9Ju8iR9//hcsb7iC4PTDCthfqXkfv/3j17f4Sts+OgOgUxTn4tJHhdw1kJ4hALv5uQbkMxSwc7sUzTHXzvfpy9xoOMPwu+yhzpC7zLMT3JlTZ449LCy1RR/1kJAUBcRstyod6KiEJ0gT+Ank8n2hoUuVxzxz8SyXCw1daiaae+CBjRg4cDG69/olnMc8gFHT4rDp+Casa1yHwkOFWF2zGiv3rkTW/iyzmvKCQwUoOaGVrq09sBbZB7KxfPdy5B7MRdb+LKzatwqZtZnqMbM2Exm7M5C6IxWZtZlYXbMaBYcKsKZ2DdYfXo/cg7nIPpCN/KZ8DaRfK1ZK+s3HN6uyseJjxSh9sxSbj2sLi33v7cOed/dg68mtyvyGwrySNzRQpmf8jrM7NBGeKUTO/uwlJzT/+W0ntymdQPFrxSg8VIiiI0UofLVQU/S/Vqyazmw6vknZ4hYcKtDsbw8XoeFaAxZsWoDQB/piwf0OeNnHQ4E5ndbYN1y2P5UhbArWCNASODkJmKz1XjhgAFJCQhT4MlfOWnRZcsb8PPPtMg/PxQM/m4sK+dlsd8rFQHJwsLoWOsMxD84wOgF6po8PZvfpY6Zml8DNfTO8vLBwwAC82KsXXuzVyzCWaecwAP173sQvv/47UvZfVqA+YOkhJNdexvXf//hK+M4A6JxduvRG9+6Lcc8989Gr14uKhetB28trhtk2T89pisFbfj7DrK5dAr9k62yt2q/ffAXaZPHSmIb16/37LzDzetcr5oODkxEenqbYO0GeuXkCNRk+gZyd3gjyNLlhu1bm5WlMM3LkatV3fdSoTLjd8xK6RI6D7+RAzC+ej83HN2Nl9UqkVaYha38W8pvysWrfKqzatwpratdgZbUmTis5UYLCQ4VYumMpchpysKZ2DZLLkpFelY6lO5YifVc6Fm1dhEVbFyFjdwbSq9KRtT8LK/eu1EC8PhsFhwq0vHt9tsqVl58ux7rGdVjXuA5ZdVlYe2At8hrzkNOQg+JjxUpFv+n4JlRfqlZitdJTmnCt8FUtarDt5DYlvqMTHC1kS97QNAKsrd98fLOqJ990fJNS8hPQqbDnoqL8rXKzBUfluUpUX6rGzrM7Me75YVhwvwNm9nZDalgYsqKizJzXyHZZtkYA1wMoBXJkvwTv+f36mSnKKUij+xqNXbg4WDZ4sAJZS4sEnjMlJMQsb86ceKLuWLJwvpZ5dDJy5sUlWPNRAjt7nif4+WGmjw9meHkpZs9jXnB0NAC9HcMA9Ft0Ey/95k94vuycAnb/lCY8s/UsNr/xMc58/AX+8s0/b8nntDY6C6Db29vD0fEeuLsvQa9eCWZgTkZOgPb0nAYPj5fQq9eLZtt6956qgF5up3jO2zsenp7TlOBOhuT1bVaphpfe8OyrTgtYKuP15W/SJjY8PM0M7MngyerZzU2/EODrkJAUFYoPC0tVYX6Wt1FIN3jwMsTEZCMwMBGuHi/CcfQkhD8biewD2UjZnoKs/VnIa8zDqn2rkNOQg6y6LAWuK/euRMbuDOQ05GDF3hXIrM3E8t3LkVyWjNQdqUguT0ZyeTIWbF6ApTuWYumOpVhZvRIp21O0c9dlIXVnKtbUrkH2gWysrlmtass3HN2gAfn+LGTtz8LqmtXIrM3Emto1WFO7RnnFbzmxRfm603ym9FSpVk5nMsEpOlyE8rfKUXCoQNnTUrVOtf76w+ux7eQ2tWDIachBflM+chpylGCv4FCBYueZtZlqYVF2ugwlb5SoxUft5VpMy5mG4PH3YuFAJ7zs46Gc12QjFDJkWWNOZjwvIMCsBIzKcFmzze16li4ZM0vaCNCy37gUrvF9CwcMaNG/fPHAgeoYCeiJ4nOkqp3ntMS65XPavUqAj/f2Vq9nmHzdn+neHc90745n7ewMUVw7hgHot/gmXvy/f8ScqotmOXY5nys9hz/85Ztb+pkcnQXQydCdnRPRu/dcuLs/j169XoS7+/PqOSdBns/l9t69p6JXrxfVI7d7ek5TCwAyfMnYLZW/Nde2Jyg7Warig4KSlBUsgVgq4amAJwizf3pQUJJZNzceN3DgYrPnnDS3CQxcpMCc6vgRI1aZNZKhcY271zQ4RE+A14R+eG7Vc8g+kI3UnalYUrEEqTtSkVaZhuW7l2P57uXIrM3Eir0rsLpmNeYVz0N6VTqSSpOQulM7bl7xPCzYvACJWxKRuCURr2x9Ba9sfQVLdyxFcnkyFpcuRsr2FLyy9RUs370cS3csReKWRKxrXIeiw0XIa8xTYfnVNatVmD6tMg1LKpZg5d6VSn1Phlx0uEhFDDYc3aDy/WwOw+Pzm/LNFPtmZXUNuchrzENeY576rsz9UyOQezAXqTtTlW5gw9ENyP9VvkoPFB4qRP6v8jHhheFYcL8jpru7YF5AgFmtOFXp0hAmKShIATZLwCz5n5O5ygYneuMWKtlZjsZSMnlO2bpUsvZEwe65j+Vj8tjEwMAW/csTTJ/JHudk3gRxPZjLMDyZeby3t9qW4Oen6tDJ0A3r17YNA9B/oJv4yZ++xpyqixZBPa3+Cv74v3/HP//17S39zM4A6JogTitb69lzKdzdZ5sBsgTx3r2nqrw42biezfM4/TYfn5lmHvF+fgmKqQcEzLPoF8/6cznJzFni1vx8kTKn4eugoCSzHHxQUJICbrJ8vo+hfNnilYsHno/nCAxcpFIEnMOHr0SfPrPh5PYsukSNx5Dno5FWmYb4vHgkFCVg7oa5mJo1FdNypmF2wWzMLpiNWfmzkLI9BXPWz8HcDXMxZ/0cvJD5AqbnTMcLmS8gPi8ez616Ds+ueBbTc7VtL2S+gOdWPYf4dfGIz4vHnPVzMGf9HKRsT0H8unjMyp+FldUrMWf9HMzMn4mXN76MecXztMXBpgWYXTAbc9bPwYy8GUgqTVKAn1yejNyGXKypXYOM3RkK+FdWr8TK6pXIa8zDmto1KqqwdMdSJdZjfn/pjqXI2J2hLTjKkpFclowFmxYgrTINaZVp6ju/vPFlrK5ZjfRd6VjXuA45DTlI35WuaQN2piJ1Zyp2X9yNJ5c9ifvjvDA/0AFz7umJpKAgzO/XT7FbfZhathlNFPlnsmgCJEu9Zvfpo0rAuJ+5ahnyZlhcb+AyV3ceMnwybebAyc6lLztD9Ty37HHOzyBYz/H1Rby3t5oE95k+PphuAm+CuX5O8/TE7D59VNka26caDL1twwD0H/AmTtlw2iKgyxmacQQxOa/j4Q2n8FzpOSTsfhepBz5A7pFr2Prmx9hz/jdofP93OHHtM1z49R/x0f+7gd/+8Wv86X//jn/oFgSdAdAlQ3dyWgh399no1u1puLo+ix49nkOPHs/BzU1j6q6uz8LV9Vn1ukeP5+Du/kvB6H9p9pqTDJ0LBRmaJ9jLmnea10j3ueaFAPutz1VGMz4+MxWr9vObq3qtDxiwUB0jw+7NoL6oBSuX28nMmX8PD08zy7/rXemiorLg7j0d9pHj4DkuANNypqHwUKECz6TSJCwuXYwVe1dgxd4VSKtMU2HwpTuWqrz4koolSC5LxtIdS7GkYgkStyRiXvE8FWZP35WO1J2pWmjexNRX7VuF9F3pSKtMUyw3+0A2svZnqTA2DWqW716OlXtXYu2Btdh4dCPK3ypXpjaV5ytRcKhA86E/VKhEcVTQFx4q1IR8pm0qD2+qoaeaP/tAtporq1ciqy4L6VXpKDqi2dVm1mai6EgR8n+Vj/ymfFVbTzEdDXLGPDMYC+53wIxerkgODsaywYPN2LIMcUsFuwRQfQibYCkBXu+JzpajZNLS2EVf/822pTwfWbdsnCJz4fy8ueJR1o7L0Lmc0zw9Mc3TEy95eGCGl5fqoMZtfD7dywtTe/c2e01R3C+7djVC7u0YBqD/gDfx7Y//gKis4wjLOIJHN72Fh4pOIXrt6wg12cjeinn/slcRsfoYYnNP4MH81xHy8DQM/dkMzN11HqkHPkDWqx9hw/H/xPa3/g9q3vktzvzXF/jkT1/jX9+2vXb+TgR0O7uesLefC3v759Cly2Nm08HhCfW8a9fHzV7LY7hPTrmta9fH4eT0JJydn1SPzs5PqUcnpyfRrdvT6NbtaTg7P4nu3Z+Bs/NT6N79GXTr9jS6d38GPXo8h+7dn0H37s+oBQa3awsMbeHh7v5LuLlpi47m9MEv1cLDze35FrN5//Nq0dK8UHleLUioA5ARCD+/BLi7/xJ23Z6E/ahx6D3WDxPnTkT0S9GImxmHuJlxmJAwARPnTkRsfCxi42MxfvZ4TJo7CZPnT0bcrDjExsdi4tyJGDNjDMbOHItJL09C3Kw4TJw7EQ8ueBBTFk3BlEVTMOnlSXgo8SFt2ytT8MjiR/DE0icwed5kPJn2JF7MehGPLXlMzZ8v+zl+vuzneCbjGTyR+gQeX/o4HlvyGJ5OfxrTc6ZjVv4sxOfFY3rOdLyU/RKm5UzDrPxZmJk/E9NzpmN6znQkFCVgdsFsTMuZhnnF85BYkoj5xfPx8saXEb8uHjPzZ2rH505X0YP4vHjM3TAXs/JnYWrWVMzdMBfJZcnqXItLFyM+Lx7JZclYXbMaaZVpKuKw+fhmPLL4EQSM7omX+3fBLA93pISEtABehrEJinoGTYW4zDszD60v6WLofK7uMxYFBqpj9aF7eX4uIhIDAzHH11exfB5P9i0tXSXrl4p2eU2WmPd0Ly8zps4pWXyCnx/ivb0xLyAAz7q6atPIobdrGID++efAN9/86PMfX/8Vf/jDDXz8yR/w7n/8Hicu/wb1Zz/GjhPXUNR0Bav2X8KiynOYVfoWnt14Ej/LP46JWUcQmdGE0CUHEfhKfYt538IaeEY9Bc+op3DfwhqLx3CGJB/EA9lHMWPraazafwk7TlzDqSuf4B9f/7XFtd74/PM7DtBtbHrAxmYWbGymwsbmGdjYPC3mM+LxGQv7nzJ7bWv7C9O2p1qcx9b2F2ryXLa2v4Cd3bOmbc3H2tk9a7afx9jbP6fOwe329s/B3v65Fq8tTUv79du6dv2l2WfJ7fI5Z5cuz8PJ6QXYOD0Hm+FjYB/hCpdIF3jGecIl0gVuo93Qa2wv9IrtBbfRbnAb7YaesT3RM7YnPOM80WtsL/W6V2wv3DP+HnjGecJ9jDt6j+2NXmN7wTPOE55xnvCa4KX2e4330uYEL/hM8oHXBC/4PugLn0k+Labvg77wnaxNr/Fe8J3si4CfBqD/I/3R/2f90f+R/rjv0fvg95Af+j/SHwFTArTtpn3BTwYj8LFA3Pfofbj/8ftx36P3of/P+iPo50Hwf9hfnSvgpwFqDnxiIO579D7c9+h9CJgSgPsfv1+d+/7H70fwk8EY/OxgBD8ZjJCnQjDk+SEY8vwQjJg6AoOfHQyfyG5I6GeHGU5d8KKTE2a4umK6iwumOjur5y91uXQ0fAAAIABJREFU62Y2p7u4tNiufz3V2bnF++S++B491Hmmu7hghqur2fvkPnl+HivfN93Fxex8M1xd1Zzu4oLZ7u6Id3PDDFdXxLu5qe+nv25L34vXJa+Hn8djeM7pLi6YZmdnhNzbMQxAnzoVmDnzrpv/io/HN9Om4y8vTsOfnp+Kz3/xIj75+XM4HhyGo0GhuPrwU/jg4afx7uQncW7SEzg9/nG8HvsoGiOnYO+QB7E73PI8OGoKPn7sWXwbH68+68bUqXcgoDuZAHgWbGxmmx6tzdm655aOl9utnU9/zGwL57O0Xb9Nf7y1a2yetrZzWj2meX/ztLNLMNtnaztHTbW9y3TYDIqCzfCu6BrdFV2iuqBLZBfteaT23D7SHvaR9mqb42hHbV+Udhxnl6gusB+lHecQ7WA2nWKc4DjaEV2ju8JxtCMcYxzhFOMEpxgnOI9xhkO0AxxjHOE42hHOY5zhPMZZe81p2t59bHe4jHOB2wQ39br72O7qPTynfjsnt3G/vAbnMc7oHte8n9fsONoR3eO6q/d0H9sdruNczba5jnPVjhthh6d8bZDQxQ4vd+mCufb2SLCzw1x7ezUT7OzUlNvlsfKYOba2SLDTzmfpPdxv6ZHP9dPaOeQ+buNrfp85trYtvpf+cy19L/l9ZtvYtHg/zz/XVHs+28YGs2xs8JSNDZwMQG/TMAD9LgV0iyA/fTreGTYM7wwbhn9Nn271uG/j4/GXF6fh90+/gP989Flc+smTeHPcY9g//CEF7O9OfvIOB3SCeo87bLqZpn6btddted7aeS1vs7V1V9v43NbW3eJzmy6OsHGygY2TDbq4dIFdNzvYdbNDF5cusHGyga2zLWydbc32dXXtii4uXdSjXTc7OPRwUO/r6tpVTYceDuji0gUOPRzg0MNBbee2rq5d4ejmaPbc0c1RnYfvc3JzUo8uvV3g0tsF3Xt1h6ObI5zdneHk5qSms7szXHq7qO0OPRzMjnF0c1Tv5Wc79HCAo5uj2Tn4+d17dVev+X4+8jmv36mLDdxtbeFua4veXbrAzcb8NZ/rp5uNjdov38PZw8YGPe3s4Gajqb75vIfpWPm8h+mYHqbpZmX20B0jz6M/Vl5nD9059OeUx/O6rV3Xd11fW8HcAHQD0G9byP2HmH//85+xatkyrFq2DH//85/b/f6v//y/KH71Q1NIvgGfffHVHRxyN6atrW2r21gRYO21PJ4OfHZ2duq5jY2N2mZnZwd7e3vY29vDwcFBve7atSvs7e3NjuHzrl27omvXrnB0dFSPDg4Oajvfy/M4ODiY7bezs4ODg4Paz/c7OzvDxcUFTk5OcHBwgKOjI5ycnNC1a1d069YN3bp1g5OTk9nn8r3cxs/iNv1n83s6ODioc8tr4HXJ30R+d60jYFf1W9rb26vfmt+H35HHy3tgaXI/j7V2b/Xb5f7v+pux9nfV1r+/9v7tfp9zWJrfCwsMQL97R0e6iRy3SuX+UNEp+Kc0oeG9/wFwZ4rijHlr/qHq/7nqgcXGxsbicwleBBlukyBmb2+vAJGAKffJ1xLEJWhKgCWoOjk5oVu3bi3AWQIz3yNB3M7OzuLCQgIsn/Pz+T5rx3Mfv5MlINaDsf53lPv1AK4HcXmO2/03eKfNmxkdCQsMQO8AN5HjVgF6Uu378E9pQvGJ/wJgAPqdNK2xLGvHtufcBAg9cBCorIGKpYWAnAR0yUz1gK6PAliaBFlHR0f06NFDPZfsWx7L13IxoWfg+sUJn+vB2tHR0Ww7j5PXpwdha2BuCaitgfbN3vvOOm9mdCQsMAC9A9xEjlsF6GsOfQT/lCZkNl0FYAD6nTQNQDcA/Xb/Dd7J82ZGR8ICA9A7wE3kuFWAXnDsP+Cf0oTUAx8AMAC9o87WAIIAI4/Tv9aDkj7kLEPXMoQtAZ0LBQmIetCXIXlONzc39OjRo0WeXg/YMlSvz3VbOrdeF2DpOvTfT78o0YM6fzP5u1oCfXmM/h5YW2zd7r+hO23ezOhIWGAAege4iRy3CtDzTYC+rN4A9Ns5b1as1N7zW2LdlhijjU1LsLGW67WWc5Ygb4mV69+n30Ym3rdvXzg7O5sBtiVRmx6Q9Tl7/SJEL1izFCXQ5/wtfQdLgN4aG5e/qbUFlKUF1e3+G73T5s2MjoQFBqB3gJvIcasBPa3+CgAD0DvytLRIsMYCLQGMnpVaCtXrgdXSc2usVw+gFL317NkTHh4eZgI3CeiWQux6xi2361m4pWiDjCTIiAInz8fj9JEHS7+ppbC7pfsgX9/uv5k7ed7M6EhYYAB6B7iJHLca0NMbDEC/nfPH/ufdGiuU19Maw5TTkvK8NcC2BKLyNcPqzs7O8PT0VGVrMpyvB2v9o7VjrDFt/fXoj7GkHbCWSpC/rf63au23bsu9MaY2b2Z0JCwwAL0D3EQOg6Eb82amNfFVayHgtoTeCWz6/LalHLkEcGs5eVm25urqChcXF7OSNH1I31L+25rYTkYTrIXP9aF7S9dqicFbE7x91z55L6wtpm73386dNm9mdCQsMAC9A9xEjlsG6EevG4B+B81b8Y/7u87xXaF1CeJ6hmkN0GUtuaUQuF4xboklS4DkOZydneHh4YFu3bpZDLdbWjhYWkjoX+vz5NZC8dau1RLjZqjemtZAf1/aIoQzwNz6vJnRkbDAAPQOcBM5bhWgZxlla51iWmPmrW3Xs8rWcuj60Lu13HZrU4KmDN97e3ujb9++LYxkWgNzSwxaH0aX+/Sfr48a6K/VUmShtd9MD+6WnlsCfwPUrc+bGR0JCwxA7wA3keNWAXrGwQ/hn9KEvCPXARiA3hGmJQbO59aYnyUAsRQitgZWMvxtiQW3NSQuGbqDgwNcXV0RGhoKNzc3M3tXeUxbQF2K7Swx7dby+a0tPFpj45a2tRZWb+1eGIDect7M6EhYYAB6B7iJHLca0HOPXANgAHpHndYYX2shX2sAZY1xWgqpW2K/ZLj6mm5LgO7o6AhfX1/07du3hTd7ayp3/We2JsiT+y2xeGvfi9st/WaWjrXGyvn7639zS/fLmM3zZkZHwgID0DvATeS4VYCe2XQV/ilNyDr0EQAD0O+22ZZ/9npwkM+tscHWQsDfFT5uLSctw9StgT+ZuLOzM/r06aNy6HoglxEBa77wepC2lmP/rvw+f8/WgN5SasIasOtB3QDu9s2bGR0JCwxA7wA3keNWAXr24WvwT2nCykYjh96RZ2vgzW36460BlLV9fK3PMeuBzxKQy2Pt7Mxz8X379sWAAQPMup9ZK5GzFubXM3BrYX9LixH9NbeFgcvfiL+ptfC7vCffFaI3ZvO8mdGRsMAA9A5wEzludcg9+7ARcr8T5s38427PeyzlcPXAo99uDbitTUtAaEmIJs8n90sG3rNnTzzxxBO45557zPzc9bnw9ojwLO1vbaGhXwhY+76WfpfWIh76qIelkPv3+bvo6PNmRkfCAgPQO8BN5LhVgL6w+j34pzSh5OTHAAxA76hTL7qyBCj6fZaAvC25dGth6NZYuh50JQOPiopCXFxci17mrane9QDemhhPv7+1dEFrKYPWwu+WAPu7GLnB0FufNzM6EhYYgN4BbiLHrQL0tPor8E9pQsbBDwEYgN5RpwHoBqB3tHkzoyNhwV0N6MXFxfD394ejoyNGjhyJ8+fPt/m9HekmctwqQK98+9fwT2lC/M53ABiAfjfN9oba5XNLed7vApTWgEp/DAGQ+2VY2tLCQP9agrI1hzhrZjLWANwS6FoKzVsC9tYEfNamte/J39raIkreLwPQrc+bGR0JC+5aQK+uroaDgwO2b9+Oq1evIj4+Hu7u7vjss8/a9P6OdBM5bhWg7zQB+uxdFwEYgH43ztb+2VsCirayQEuArgd2G5uWvu7WWHxbwVCf59Yr1y2xcH33NWtM3VJUQH6mNZZuDdwle9cvYqwteCwtjuR+a7//7f47u9PmzYyOhAV3LaCPHDkSc+fOVa+//fZb3HvvvVi7dm2b3t+RbiLHrQL0irf+D/xTmpCw+10ABqDfydPSP3U9o2vLOb4r/G6NnbfG1i2xUWus1hqYS3DUA7Ml/3Z9yF0fPrckfLMmlrNkRGMpTaB/LdMJln4b+ZtaC7vb2LSugG/P/e1M82ZGR8KCuxLQ//73v8Pe3h719fVm21944QU88sgjFt/zzTff4MaNG2p+8sknHeYmctwqQC87rQH6vD2XAFj/g79Vv+nt/ifQWacl9s3H1gDdGljrwU4eYw0ErZ3HEsOnol2CeWte7pKl6wFaz771TF7Pvi05xVli9K0tXr4rEqIHbGtgbzB06/NmhgHot3n87ne/g42NDd5++22z7UlJSRg5cqTF92RkZFj8A+gIN5HjVgH6tjf/G/4pTVhY/R4A63/wt+o3vd3/BO7EebPs+mY/yxKA6/fpwdfGxhx09ADdFtBvDRQZspag2pojnKVadH3YXQK4NZC39Lq1HLw1tm7pu+u3WQvDW2L2BqB/97yZYQD6bR43A+gGQ2/7eP+3X6Lk5Md4/dqnAH54hm4MYxjDGLdrGIB+m8fNhNz1oyPdRI5bBej68UPn0I1hDGMY43aNjvR/664EdEATxb388svq9bfffos+ffoYojgD0I1hDGMYo82jI/3fumsBvbq6Go6OjtixYwc++ugjzJw5E+7u7vj000/b9P6OdBM5DEA3hjGMYYz2jY70f+uuBXQA2LhxI/z8/ODg4ICRI0fi3LlzbX5vR7qJHAagG8MYxjBG+0ZH+r91VwP69xlfffUVbGxs8Mknn5gJu+7m+cUXX2DJkiVYsmQJvvjii1t2Xordvvrqq073mxrTmMbs2LOt/9/uhtFpAZ030Zhtn5988onxmxrTmMbskPO7/r/dDaPTAvq3336LTz75BF999dWPugq8W9irvN6vvvoKn3zyCb799tsf5De9236bzvqdjO91903je333bOv/t7thdFpA/7HHjRt3V57mx7zeu+23acvoiN8JML7X3TaM79W5hgHoP9K42/4ADUD/fqMjfifA+F532zC+V+caBqD/SONu+wM0AP37jY74nQDje91tw/henWsYgP4jjW+++QYZGRn45ptvbveltGnczPXebA79888/x5IlS/D555/f9tzcrZod8TsZ3+vum8b3+u5p5NCNYQwLw1C5G9OYxrxbp6FyN4YxxPhR6tC/+AI3lizR5i2ste+U8/PPcWPqVG12MAZ3W+Znn+HG5Mna/Oyz2389d/v89FPcGDJEm59++oN9jlGHbgxj4NZ0W8s9cg0vbj+PF8rP45fl5zF1+3lM3/EOZlVeRELVu5i35xISq9/DKzXvI+Pgh9j15n/gf5csAzIygFvohtcpxzffADNnavMuSQXd0eNvfwOmTNHm3/52u6/m7h9//SsQEYF/Dh2Gna9/hDWHPsKife8jYfe7mFV5EdN3XMC0ipbz/d9+2a6PuXGj4+TjDUA3xk2PW9EP/dnSs/BPaWrzvG9xPYpjn8NniSkGoH/fYQD6rR0GoN/a8de/4i//v707DWvqzPs4nk6v6rTTUdvCU21nTBWT1qW1VUHRulXFdXRsx1q7jONYHJdeY210gitTd4tLF6fWutbREa1NtA2LhEVkF2QVkH0JyGYgIUDYkt/zAkgJYOXoDYeT/j/Xdb+QbPctId/k5JxkxEjcGiCB9JMfOv0Y0fK1z51FQScEbF6hB90uwcXofHwfo8H3MRpciM7H/6LycCYiF6fDcnA8JBvfBmfhP0EZ2OuTijmf+ePQhCU4NWMpagw1Xbi6XwEKOlsUdKbM1dVI/+OLSOg/BH/a54cdPyXj66BMnArNxpmIXJyPysOFG/ntRmEFt8cFCjohHeiOP4zycgO+feMDHJqwBD9G53TZ7fwqUNDZoqAzdSOlAAn9hyCp/xBoy7ru/W0KOiEd6JY/jLo6BL2zCocmLIH7xdiuu51fAwo6WxR0puRnI5HQfwg0g4c1vZ/eRSjohHSgu4KevvITHJqwBHM9/Lvudn4NKOhsUdCZ+rOHGgn9h0A37BUKeidR0AkzLX8YZWVlqKur65phMEC/wQ0HnRdjyCcXUVpR1XW3ZeujshKFi97DjRlvwVCu438+Qh96PUxz5sA0Zw7q9Hr+5yPgUWOsxQjZRSQ86wDjK6+iTtd198+ysjIKOiFttQTdzc0N7u7uXTK2b9mCoMmTcWjwSNg5v40PVsu67LZsfXy6aRNOPuuAk8864O2/fcT7fIQ+dmzejNtSKW5LJFj38QZs27aN9zkJdazdsBHPjluEuCefRsGAAdixaVOX3ZabmxsFnZC2ujPoJ4aNhp3z25i4eCW20gPnA41Vaz6xBH3eu6t4n4/Qx47Nm5E42AH+dn/A/zm/jb+4fsz7nIQ6Plgtw7PjFiGxzzMopKB3GgWdMNNdm9wbt2xB5sp1cFh3EQPXK/HCBiWWnQjHteRClFQYUFtby/smQyEMd88onH3FBWdfccHmcxG8z0fwQ69HwsgJUA8eA8nHF7DB8yb/cxLo+NIvBZK1nsh94SWYRo2iTe6dREEnzHTXTnFwd0fDlq0Ysl7Z4QdLOGz0whSPIHz4XTTePx6JP/8nFIuOhGPivkC88u+rmPX5dYzd5Y8Xt3hjqkcQXA4G4439QZjiEQTX76JxwC8NJ0KykaDh9olTQuOy9yrOjZyFcyNnYfnREL6nI3xGI2JengC1gyOkMgWWfBvB94x6rLoGE8qr6pCvrUZyoR5R2VokF+qRd7cauup6rD0fC+knP6BYOgIYPZp2iuskCjphpjuDDnd3rDoZDrFchTE71ZBfSsCo7X6cPnWuM2PC3gDM/fI61l+MR3BaKRpN5q5bWzcym8142e2KJeiz9vnxPSXhMxoRMczZEvTxewL4nhEvahsaka+thk/SHez1ScVGRSJ2eaXA7YdELD0ZheHbfDv1tyf95AdUjhhJQeeAgk6Y6e6gF5TocOx6FiqN9ZaTaxsaUVBRg9CMMpwOy8HZyFz4JBVBlXAH4Zl3kVyoR2BqCRI1OuSUVSEsswxhGWWIzLqL8My7OOiXhs3KRCw/HQ3JJu92DzJjd/lj9bmb+F9UHkr0wj00yVDbAIlMaQn6y25XYDbbxpMV3hiNCHlpnCXoL7ipUNvQyPesulSlsR5R2VqcDM2G7GI8Zh4KhsNGr04/YX5piw/G7FRjikcQXna3Dv2H3wTDPHo0BZ0DCjphpruDjrqu/Sz3u4ZaRGbdxdVbRdiiTGr3gCOWqzD78+vY3fylER9+F42PPeOwRZmEz3xTcS4yD5ry6i6d44PKKjVAIlPi/KtNQZfIlLhroGPRH4rRiECJkyXoYrkKGSUG5jdTXdcAQ20DgKYnsPpWT2g7o67BhPTiShRU1KCq+XpaVNU2oK6h6XvBNeXVSNTooKuuR0OjCcV6I27kaPGlfzr+ciQMo3fce4uYdLM3pu4PwiZFIg74pWGnKhlf+Kfju/AcJBX8fJ2tmc1mNDSasMsrBW99HYaCO9qmmFPQO42CTpixtaC3ZaxvxPX0Unzhn44Fh0Pxgtv9X4G84KbCOs84hGaUIbPUgJhcrdUWBb5EZN2FRKbEj2PnQeE4FxKZkvO3VBFrxsoqqB0coXZwxBs7fSCWq+Cfwu2LQlpoyqvxv6g8LDt1A0u+jYDzbn+M2+2P8XsCLPuJzDh4zXI/m/xZID65EI9NikScCs3GrUIdrqeX4nZRJfTGenz6YzLmfxWC+V+F4NVPr1rdR9/YH4T1F+Px/vFIDHJTYehWH0zcF9jufnyv+7jzbn8sPx2Ng35puHqrCAUVNWy29jR/2xoFvfMo6IQZWw96W2WGWihjCyC/lIA93qk4G5mLo8GZOOCXhm2Xk7DoSHiHD4CSTd6Y4hGEjz3jcDosBzfzyh/o9htN5navcjrrSnwhJDIl/CYuwNXXF0AiU0KVcOeBros0KSmpgNrBEf4OjvjoRBjEchWOh2R36rJFOiMUsRps+D4er+8LYLofyOAONoEP3erT4VtKbSPe+lX4ILemeK84E43zUXlIKtBx3jrACQWdMwo6YebXFvTOiM+vwCcX4jF+TwCGb/PFmJ3qDh88530ZgnlfhuC17X6YfuAalnwbgbXnY7FTlYxvrjV9w9TWy0l46+swDNvqg5e2+Fjeqxy7yx+yi/E4G5mLqGwtYvPK77vz3rHrWZDIlAh5400ET10IiUyJ/0bkdtP/im3KyC2F2sER16RjcfDHBIjlKqw5dxOXYjS4nl6KmrpGxOdXIK24EnUNJmSXVeGAXxqmegR1GOEFh0NxODADilgNwjLKEJ2jRVS2FtqqOiQV6PBjfCGK9UboqusRkFqMz9Xp+Mw3Fe8fj8SwrT4YvyfAEvOpHkFQxhbAP6UYUdlayxPB8qo6+CUXY//V2zgVmo3MUgNS7uhxI0eLksqmfUSq6xpQUmns/h1CKeicUdAJMxT0+zObzci7W42Q9DJs/ykZy0/fwJBNnd+JqLNj/J4ALDgcis/V6YjJ1SIuv8JqU/9urxRIZErEzFyE0GlvQiJT4tj1LB7/Z4Qv+nYh1A6OCBs6DrFpd+776rf1vwe5NT2p2+WVgsDUEst75A9LW1WHOzpGm8C7GwWdMwo6YYaC/mCK9UYoYwvww00Nkgv1CM0ogzK2AN8GZ2GXVwrWecZh5X9jsNsrBZfjCpBWXIm8u9Uo0hmhrapDcFopPHxv4/3jkZi4LxAj7nFY0Ah3Xxz0S4Ouph7rPOMgkSmR/Kd3EDnjLUhkSnwVkM73f4Wg+cfmQu3giKgR42Guqenw8Kzh23wtm7qlm72x4HAoLscVQFfD/34VPQ4FnTMKOmGGgt4zVNU2IDC1BBdu5OO9Y5GYsDfA6hj90TuaDhOSyJTIWvgeomcugkSmxGe+qXxPXdAuhaZD7eCI2JGvA0YjPlenQyxXYYpHEEwmM0ora2Gsb4ShtmkTtiBfNXcnCjpnFHTCDAW95zKZzPBKvIOp+39+v1YiU+LO4g8QO/ttSGRKbP8pme9pCtpJdQrUDo5IGjURMBphrG/E8ZBsFOmE+3kFvKKgc0ZBJ8xQ0Hu+qtoGrDobYwm67oNlSJy7GBKZEhsViXxPT9AO/ZQAtYMjbo+ZTN+HzgIFnTMKOmGGgi4MZrMZZyJy8YUqCWZXVyT/6R1IZEqsuxDH99QE7d8XYqB2cETm2CkUdBYo6JxR0AkzFHSBqa0FVqxA2oIlkMiUWHU2hu8ZCdrHpyOgdnBE3vg3KOgsUNA5o6ATZijoAtMc9MyF70IiU2LZqRt8z0jQlh0JhtrBEXcmTqegs0BB54yCTpihoAtMc9Bz3noPEpkS7xylr/t8GIu/CITawRElkynoTFDQOaOgE2Yo6ALTHHTNog8gkSnx5/+E8j0jQVt4wB9qB0eUTZlBQWeBgs4ZBZ0wQ0EXmOag31ncFPSZh4L5npGgzd3nB7WDI7RTXSjoLFDQOaOgE2Yo6ALTHPTSJUshkSkxxSOI7xkJ2ozdV6F2cET5GzMp6CxQ0DmjoBNmKOgC0xx07Xt/g0SmxNhd/nzPSNCmbPeB2sERumkUdCYo6JxR0AkzFHSBaQ667oNlkMiUGPnpVb5nJGjj3b2gdnBE5fRZFHQWKOicUdAJMxR0gWkOumHp3yGRKSHd7M33jARtzOafoHZwRNUMCjoTFHTOKOiEGQq6wDQH3bhsOSQyJcRyFUzd/Z3XNuQVtytQOziiZuZsCjoLFHTOKOiEGQq6wDQHvX75h5ag19Q18j0rwXppgxJqB0fUzppDQWeBgs4ZBZ0wQ0EXmOagm1xdLUHXVtH/6YNoNJkhlSmgdnBE3WwKOhMUdM4o6IQZCrrANAcdK1ZgmPwKxHIVCiu67oHTltXUNVqC3jBnLgWdBQo6ZxR0wgwFXWBaBX3U5h8hlquQWWrge1aCpKuutwTdNJeCzgQFnTMKOmGGgi4wrYI+4VMviOUq3CrU8T0rQSqpNFqCbp43j4LOAgWdMwo6YYaCLjCtgj5tty/EchVicrV8z0qQNOXVkMoUCBjiBFDQ2aCgc0ZBJw+strYWer3eMjQaDQVdSFoFfZ6HGmK5CqEZZXzPSpCySg2QyhQIkoyloLNCQeeMgk4emLu7O0QiUbtBQReIVkF/81AgxHIV1MnFfM9KkFKL9JDKFAiWUtCZoaBzRkEnD4xeoQtcq6C/d/gaxHIVfkoo5HtWgpSo0UEqUyDkpXEUdFYo6JxR0Akz9B66wLQK+vKjIRDLVbgYnc/3rAQpJlcLqUyBsKEUdGYo6JxR0AkzFHSBaRX0j06GQyxX4UxELt+zEqSwzDJIZQqED3OmoLNCQeeMgk6YoaALTKugr/9vFMRyFY4GZ/I9K0EKul0CqUyByOHjKeisUNA5o6ATZijoAtMq6O4Xb0IsV+GgXxrfsxKkq7eKIJUpcGMEBZ0ZCjpnFHTCDAVdYFoF/cCPCRDLVXC/covvWQnSTwmFkMoUiHl5AgWdFQo6ZxR0wgwFXWBaBf1bv2SI5SqsuxDH96wE6YebGkhlCsS+QkFnhoLOGQWdMENBF5hWQfcMSYdYrsLy09F8z0qQzkflQSpTIH7k6xR0VijonFHQCTMUdIFpFXTv6ByI5Sos+iac71kJ0nfhOZDKFEh4dSIFnRUKOmcUdMIMBV1gWgU95JYGYrkKMw8FM7nqRpMZ1XUNMJvNTK6vpzt2PQtSmQJJoyjozFDQOaOgE2Yo6ALTKuiJmcUQy1Vw3u2PRtODRThRo8M6zzi4HAzGkE1N39424+A1XIzOR0ZJJePJ9yyHAzMglSmQPGoSBZ0VCjpnFHTCDAVdYFoFPadAC7FcBbFchUFuKpwJz+n01YRmlGH+VyGWy3c0BrmpcOx6FkwP+GShpzukToNUpkDqGAo6MxR0zijohBkKusC0CrpWW9kuwvdTU9eIbZeTLOcfvNEL6zzjEJhagnxtNYr1Ruz92xwWAAAN6ElEQVRUJcPlYLDlPAsOh+KOrusenPmyzycVUpkCtx0nU9BZoaBzRkEnzFDQBaZV0Oura9oFXVNefc+LFlbUYNbn1y3n3axMRJmhtsPzms1mnA7LwfBtTd+5PmFvAOLzK7pqVbzY8VMypDIF0p2mUNBZoaBzRkEnzFDQBaZV0FFbi6FbfayCfiYiF5mlBuiN9VYXi8uvwJidTd+fPnqHH4LTSjt1c5ryakz+LNCyCX63VwpqGxq7YmXdbuvlJEhlCmSOpaAzQ0HnjIJOmKGgC0yboI/d5W8VdMlmb4jlKkzxCIK2qg6+t4rw7x9vQdr885mHgn/xVXxHtFV1+Of5WMttrD0faxN7wssvJUAqUyB73FQKOisUdM4o6IQZCrrAtAn6VI8gS2hf3xfwizu5LTt1A4bahge+aZ+kOxi8sWlP+O847IDXU63zjINUpkCuMwWdGQo6ZxR0wgwFXWDaBN1pl9oS7IZGE9TJxbgcVwDJpqZX5GN2qiG/lIAzEbkPfGhba8euZ0EsV8FhoxeuxBd2eJ1VtQ34KiAda8/Hct4awFV0jhYH/NJwNDgT6cWVnLYcrD53E1KZAvnj36Cgs0JB54yCTpihoAtMm6APa/Ueemv52mpklFQyiXhrZrMZq87GWG5zwt4AqJOLAQAJmgrs80nF6B0/P8l4bbsfwjLKmM6hRd7dary4xdtqK8S0A9dwOiwH8ksJSNTofvHyH34XDalMgYIJ0yjorFDQOaOgE2Yo6ALTJuhcDlljpaauEft8UjHy06sQy1UYutUHfsnFcGjeHC+WqzBxX6Blj/pBbipmUTebzTgTnoOZh34+rG7ENl8sPRll2SrRMqSbvbHLKwV3dDXwSSrCrULrwP/1RBSkMgUKJ06noLNCQeeMgk6YoaALTA8IegtjfSPe/DrMag5T9wfhwo181DWYYKxvxIoz0RDLVXjvWCST27wQnW91ey9t8UF2WRUAQG+sxxZlUrs9/1u2Ygze6IVD6jTcNdSi0WTGO0cjIJUpUDSJgs4MBZ0zCjphhoIuMG2C7pdcjBHbfOGTVMTLdJIKdJaPjHXapYa2yvr3m6+txgtuTWHNKDHgQnQ+Zn9+HYfUaTCbzUgq0OF6eimq7rOzXk1dI7LLqjCi+bj4XV4piMktR762/Xv0ZrMZjSYzfJKKMKn5kLu2Y+r+IMz7MgRSmQIlk2dQ0FmhoHNGQSfMUNAFpk3QAfD+0az52mpEZWvbxbzF8tM3IJarMH6P9V74o3f43fe9drPZjKPBmZa968VyFd78OqzT+wbklFXh/eOROHY9C5fjCuC8++fD/F5wU0EqU6BsCgWdGQo6ZxR0wgwFXWA6CHpPF5tXbhXyV/591erfLa+6X3BTYenJKOzxTkVFddP95ERIttV5x+8JQEnlg4fXbDZbfYa9VKaAdqoLBZ0VCjpnFHTCDAVdYAQYdABY2/zBNH85EgaTyYz04kpcjitAenEljPWNcPshwSrckz4LxH8jci17se/zSYVPUhGK9Q8f3U2KRKugV7vMpqCzQkHnjIJOmKGgC4xAg15prMex61m/+Oo6JrccB/zSMG639affLT4azvST6U6F/vyq33mbF8zz5lHQWaGgc0ZBJ8xQ0AVGoEHnorz5o2aHbPLC6rM3UcLgVXlrIelllqCvPh7aFHMKOhsUdM4o6IQZCrrA/AqC3oL1h+K0KNYbLUE/4nuLgs4SBZ0zCjphhoIuML+ioHcVs9lsCXpIUj4FnSUKOmcUdMIMBV1gKOhMBKeV4kx4TlPEKejsUNA5o6ATZijoAkNBZ4uCzhYFnTMKOmFGp9NBJBJBo9FAr9d3zSgrg97NrWmUlXXd7fwaRmkp9H/7W9MoLeV/PkIfJSXQz5zZNEpK+J+P0EdxMfSvvto0iou77HY0Gg1EIhF0ul/+Ah4hoKATZlr+MGjQoEFDaEOj0fD9EPrQKOiEGZPJBI1GA51Ox/nZcZe+qudh0LqENWhdwhos16XT6aDRaGAymfh+CH1oFHTCK73edt6/ao3WJSy0LmGx1XU9LAo64ZWt/mHSuoSF1iUstrquh0VBJ7yy1T9MWpew0LqExVbX9bAo6IRXtbW1cHd3R62NHTZF6xIWWpew2Oq6HhYFnRBCCLEBFHRCCCHEBlDQCSGEEBtAQSeEEEJsAAWdEEIIsQEUdMKrw4cPQywWo3fv3nByckJUVBTfU+LE3d293UdIvvjii5bTjUYjVq9ejaeffhq/+93v8Oabb6K4uJjHGXcsODgY8+bNw4ABAyASiaBUKq1ON5vN2Lp1K/r374/f/va3mDZtGtLT063Oo9Vq8e677+L3v/89+vbti7///e8wGAzduQwr91vT0qVL2/3uZs6caXWenrYmANi9ezfGjBmDJ598Evb29liwYAFu375tdZ7O3O/y8vIwZ84cPP7447C3t8f69evR0NDQnUux0pl1TZ48ud3v7B//+IfVeXrauroTBZ3wxtPTE7169cLJkyeRnJwMV1dX9OvXDyUlJXxPrdPc3d0xfPhwFBUVWUZZWZnl9JUrV+KPf/wjAgICEBMTg3HjxmH8+PE8zrhj3t7e2Lx5MxQKRYfx27t3L/r27YvLly8jISEB8+fPx6BBg2Bs9a1is2bNwsiRIxEZGYmQkBAMGTIES5Ys6e6lWNxvTUuXLsWsWbOsfnfl5eVW5+lpawKAmTNn4tSpU7h16xbi4+MxZ84cDBw4EFVVVZbz3O9+19jYiBEjRmD69OmIi4uDt7c37OzssHHjRj6WBKBz65o8eTJcXV2tfmetj0XvievqThR0whsnJyesWbPG8m+TyYTnnnsOe/bs4XFW3Li7u2PkyJEdnqbT6fDYY4/h+++/t/wsNTUVIpEIERER3TVFztrGz2w2o3///vDw8LD8TKfToXfv3jh//jwAICUlBSKRCNHR0Zbz+Pj44JFHHkFhYWH3Tf4e7hX0BQsW3PMyPX1NLUpLSyESiRAcHAygc/c7b29v/OY3v7F61X7kyBH06dMHdT3ka4nbrgtoCvratWvveRkhrKsrUdAJL+rq6vDoo4+2e5D961//ivnz5/M0K+7c3d3xxBNPYMCAARg0aBDeffdd5OXlAQACAgIgEolQUVFhdZmBAwfi4MGDfEy3U9rGLysrCyKRCHFxcVbnmzRpEv75z38CAE6cOIF+/fpZnd7Q0IBHH30UCoWi6yd9H/cKet++fWFvbw+pVIqVK1fi7t27ltN7+ppaZGRkQCQSISkpCUDn7ndbt25t90Q0OzsbIpEIsbGx3TPx+2i7LqAp6HZ2dnjmmWcwfPhwuLm5obq62nK6ENbVlSjohBeFhYUQiUQIDw+3+vmGDRvg5OTE06y48/b2xsWLF5GQkABfX184Oztj4MCBqKysxLlz59CrV692l3F0dMS//vUvHmbbOW3jFxYWBpFIhDt37lidb9GiRXj77bcBALt27YJUKm13Xfb29vj666+7dsKd0FHQz58/jytXriAxMRFKpRJDhw6Fo6MjGhsbAfT8NQFNW7Xmzp2LCRMmWH7Wmfudq6srXFxcrE6vrq6GSCSCt7d31066EzpaFwAcPXoUvr6+SExMxNmzZ/H8889j4cKFltN7+rq6GgWd8MJWgt5WRUUF+vTpg+PHj1PQ0XPi11HQ22rZEuHv7w+g568JaHqvXCwWW32Xty0EvaN1daRla0RmZiaAnr+urkZBJ7ywlU3uHRkzZgzc3Nxok3sP2jzdmaADgJ2dHb755hsAPX9Na9aswR/+8AdkZ2db/Vzom9zvta6OVFVVQSQSwdfXF0DPXld3oKAT3jg5OeGjjz6y/NtkMuH5558X1E5xbRkMBjz11FP44osvLDsnXbp0yXL67du3BbtT3P79+y0/0+v1He4UFxMTYznP1atXe8wOZJ0JukajwSOPPIIrV64A6LlrMpvNWLNmDZ577rl2hw4C6NT9rmXnsdZHlBw9ehR9+vTh7QtP7reujoSGhkIkEiEhIQFAz1xXd6KgE954enqid+/eOH36NFJSUrBixQr069evRx6nfS8ymQzXrl1DTk4OwsLCMH36dNjZ2aG0tBRA06bDgQMHIjAwEDExMXB2doazszPPs27PYDAgLi4OcXFxEIlEOHjwIOLi4iw7+O3duxf9+vWzvOe8YMGCDg9be+211xAVFYXQ0FBIJBJeD/H6pTUZDAasX78eERERyMnJgb+/P0aNGgWJRGL1wN/T1gQAq1atQt++fXHt2jWrw7dqamos57nf/a7l8C4XFxfEx8fD19cX9vb2vB7edb91ZWZmYvv27YiJiUFOTg6uXLmCwYMHY9KkSZbr6Inr6k4UdMKrr776CgMHDkSvXr3g5OSEyMhIvqfEyeLFizFgwAD06tULzz//PBYvXmx5Pw/4+QM+nnrqKTzxxBNYuHAhioqKeJxxx4KCgtp9YIdIJMLSpUsB/PzBMs8++yx69+6NadOmIS0tzeo6tFotlixZgieffBJ9+vTBsmXLeP0Qll9aU01NDVxcXGBvb4/HHnsMYrEYrq6u7Z5M9rQ1AehwTSKRCKdOnbKcpzP3u9zcXMyePRuPP/447OzsIJPJeP0AlvutKz8/H5MmTcLTTz+N3r17Y8iQIdiwYUO770TvaevqThR0QgghxAZQ0AkhhBAbQEEnhBBCbAAFnRBCCLEBFHRCCCHEBlDQCSGEEBtAQSeEEEJsAAWdEEIIsQEUdEIIIcQGUNAJIYQQG0BBJ4QQQmwABZ0QQgixAf8PKr8UxFeJd4MAAAAASUVORK5CYII=\" width=\"500\">"
+ ],
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
"source": [
"f = boz.inspect_rois(dataM, params.rois, params.rois_th)"
]
@@ -249,19 +1908,809 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
- "rois_th = 35\n",
+ "rois_th = 1\n",
"rois = boz.find_rois(dataM, rois_th)"
]
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 16,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "application/javascript": [
+ "/* Put everything inside the global mpl namespace */\n",
+ "window.mpl = {};\n",
+ "\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('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",
+ "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 = $('<div/>');\n",
+ " this._root_extra_style(this.root)\n",
+ " this.root.attr('style', 'display: inline-block');\n",
+ "\n",
+ " $(parent_element).append(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 (mpl.ratio != 1) {\n",
+ " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.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 = $(\n",
+ " '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
+ " 'ui-helper-clearfix\"/>');\n",
+ " var titletext = $(\n",
+ " '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
+ " 'text-align: center; padding: 3px;\"/>');\n",
+ " titlebar.append(titletext)\n",
+ " this.root.append(titlebar);\n",
+ " this.header = titletext[0];\n",
+ "}\n",
+ "\n",
+ "\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
+ "\n",
+ "}\n",
+ "\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
+ "\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._init_canvas = function() {\n",
+ " var fig = this;\n",
+ "\n",
+ " var canvas_div = $('<div/>');\n",
+ "\n",
+ " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
+ "\n",
+ " function canvas_keyboard_event(event) {\n",
+ " return fig.key_event(event, event['data']);\n",
+ " }\n",
+ "\n",
+ " canvas_div.keydown('key_press', canvas_keyboard_event);\n",
+ " canvas_div.keyup('key_release', canvas_keyboard_event);\n",
+ " this.canvas_div = canvas_div\n",
+ " this._canvas_extra_style(canvas_div)\n",
+ " this.root.append(canvas_div);\n",
+ "\n",
+ " var canvas = $('<canvas/>');\n",
+ " canvas.addClass('mpl-canvas');\n",
+ " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
+ "\n",
+ " this.canvas = canvas[0];\n",
+ " this.context = canvas[0].getContext(\"2d\");\n",
+ "\n",
+ " var backingStore = this.context.backingStorePixelRatio ||\n",
+ "\tthis.context.webkitBackingStorePixelRatio ||\n",
+ "\tthis.context.mozBackingStorePixelRatio ||\n",
+ "\tthis.context.msBackingStorePixelRatio ||\n",
+ "\tthis.context.oBackingStorePixelRatio ||\n",
+ "\tthis.context.backingStorePixelRatio || 1;\n",
+ "\n",
+ " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+ "\n",
+ " var rubberband = $('<canvas/>');\n",
+ " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
+ "\n",
+ " var pass_mouse_events = true;\n",
+ "\n",
+ " canvas_div.resizable({\n",
+ " start: function(event, ui) {\n",
+ " pass_mouse_events = false;\n",
+ " },\n",
+ " resize: function(event, ui) {\n",
+ " fig.request_resize(ui.size.width, ui.size.height);\n",
+ " },\n",
+ " stop: function(event, ui) {\n",
+ " pass_mouse_events = true;\n",
+ " fig.request_resize(ui.size.width, ui.size.height);\n",
+ " },\n",
+ " });\n",
+ "\n",
+ " function mouse_event_fn(event) {\n",
+ " if (pass_mouse_events)\n",
+ " return fig.mouse_event(event, event['data']);\n",
+ " }\n",
+ "\n",
+ " rubberband.mousedown('button_press', mouse_event_fn);\n",
+ " rubberband.mouseup('button_release', mouse_event_fn);\n",
+ " // Throttle sequential mouse events to 1 every 20ms.\n",
+ " rubberband.mousemove('motion_notify', mouse_event_fn);\n",
+ "\n",
+ " rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
+ " rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
+ "\n",
+ " canvas_div.on(\"wheel\", function (event) {\n",
+ " event = event.originalEvent;\n",
+ " event['data'] = 'scroll'\n",
+ " if (event.deltaY < 0) {\n",
+ " event.step = 1;\n",
+ " } else {\n",
+ " event.step = -1;\n",
+ " }\n",
+ " mouse_event_fn(event);\n",
+ " });\n",
+ "\n",
+ " canvas_div.append(canvas);\n",
+ " canvas_div.append(rubberband);\n",
+ "\n",
+ " this.rubberband = rubberband;\n",
+ " this.rubberband_canvas = rubberband[0];\n",
+ " this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
+ " this.rubberband_context.strokeStyle = \"#000000\";\n",
+ "\n",
+ " this._resize_canvas = function(width, height) {\n",
+ " // Keep the size of the canvas, canvas container, and rubber band\n",
+ " // canvas in synch.\n",
+ " canvas_div.css('width', width)\n",
+ " canvas_div.css('height', height)\n",
+ "\n",
+ " canvas.attr('width', width * mpl.ratio);\n",
+ " canvas.attr('height', height * mpl.ratio);\n",
+ " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
+ "\n",
+ " rubberband.attr('width', width);\n",
+ " rubberband.attr('height', height);\n",
+ " }\n",
+ "\n",
+ " // Set the figure to an initial 600x600px, this will subsequently be updated\n",
+ " // upon first draw.\n",
+ " this._resize_canvas(600, 600);\n",
+ "\n",
+ " // Disable right mouse context menu.\n",
+ " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\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 nav_element = $('<div/>');\n",
+ " nav_element.attr('style', 'width: 100%');\n",
+ " this.root.append(nav_element);\n",
+ "\n",
+ " // Define a callback function for later on.\n",
+ " function toolbar_event(event) {\n",
+ " return fig.toolbar_button_onclick(event['data']);\n",
+ " }\n",
+ " function toolbar_mouse_event(event) {\n",
+ " return fig.toolbar_button_onmouseover(event['data']);\n",
+ " }\n",
+ "\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",
+ " // put a spacer in here.\n",
+ " continue;\n",
+ " }\n",
+ " var button = $('<button/>');\n",
+ " button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
+ " 'ui-button-icon-only');\n",
+ " button.attr('role', 'button');\n",
+ " button.attr('aria-disabled', 'false');\n",
+ " button.click(method_name, toolbar_event);\n",
+ " button.mouseover(tooltip, toolbar_mouse_event);\n",
+ "\n",
+ " var icon_img = $('<span/>');\n",
+ " icon_img.addClass('ui-button-icon-primary ui-icon');\n",
+ " icon_img.addClass(image);\n",
+ " icon_img.addClass('ui-corner-all');\n",
+ "\n",
+ " var tooltip_span = $('<span/>');\n",
+ " tooltip_span.addClass('ui-button-text');\n",
+ " tooltip_span.html(tooltip);\n",
+ "\n",
+ " button.append(icon_img);\n",
+ " button.append(tooltip_span);\n",
+ "\n",
+ " nav_element.append(button);\n",
+ " }\n",
+ "\n",
+ " var fmt_picker_span = $('<span/>');\n",
+ "\n",
+ " var fmt_picker = $('<select/>');\n",
+ " fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
+ " fmt_picker_span.append(fmt_picker);\n",
+ " nav_element.append(fmt_picker_span);\n",
+ " this.format_dropdown = fmt_picker[0];\n",
+ "\n",
+ " for (var ind in mpl.extensions) {\n",
+ " var fmt = mpl.extensions[ind];\n",
+ " var option = $(\n",
+ " '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
+ " fmt_picker.append(option);\n",
+ " }\n",
+ "\n",
+ " // Add hover states to the ui-buttons\n",
+ " $( \".ui-button\" ).hover(\n",
+ " function() { $(this).addClass(\"ui-state-hover\");},\n",
+ " function() { $(this).removeClass(\"ui-state-hover\");}\n",
+ " );\n",
+ "\n",
+ " var status_bar = $('<span class=\"mpl-message\"/>');\n",
+ " nav_element.append(status_bar);\n",
+ " this.message = status_bar[0];\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",
+ "\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",
+ "\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]);\n",
+ " fig.send_message(\"refresh\", {});\n",
+ " };\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
+ " var x0 = msg['x0'] / mpl.ratio;\n",
+ " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
+ " var x1 = msg['x1'] / mpl.ratio;\n",
+ " var y1 = (fig.canvas.height - msg['y1']) / mpl.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, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\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",
+ " {\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.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",
+ " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+ " evt.data);\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ " else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\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(\"No handler for the '\" + msg_type + \"' message type: \", msg);\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(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\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",
+ " if (e.target)\n",
+ " targ = e.target;\n",
+ " else if (e.srcElement)\n",
+ " targ = e.srcElement;\n",
+ " if (targ.nodeType == 3) // defeat Safari bug\n",
+ " targ = targ.parentNode;\n",
+ "\n",
+ " // jQuery normalizes the pageX and pageY\n",
+ " // pageX,Y are the mouse positions relative to the document\n",
+ " // offset() returns the position of the element relative to the document\n",
+ " var x = e.pageX - $(targ).offset().left;\n",
+ " var y = e.pageY - $(targ).offset().top;\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",
+ " 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",
+ " {\n",
+ " this.canvas.focus();\n",
+ " this.canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " var x = canvas_pos.x * mpl.ratio;\n",
+ " var y = canvas_pos.y * mpl.ratio;\n",
+ "\n",
+ " this.send_message(name, {x: x, y: y, button: event.button,\n",
+ " step: event.step,\n",
+ " guiEvent: simpleKeys(event)});\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",
+ "\n",
+ " // Prevent repeat events\n",
+ " if (name == 'key_press')\n",
+ " {\n",
+ " if (event.which === this._key)\n",
+ " return;\n",
+ " else\n",
+ " this._key = event.which;\n",
+ " }\n",
+ " if (name == 'key_release')\n",
+ " this._key = null;\n",
+ "\n",
+ " var value = '';\n",
+ " if (event.ctrlKey && event.which != 17)\n",
+ " value += \"ctrl+\";\n",
+ " if (event.altKey && event.which != 18)\n",
+ " value += \"alt+\";\n",
+ " if (event.shiftKey && event.which != 16)\n",
+ " value += \"shift+\";\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,\n",
+ " 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",
+ "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\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"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\";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 = $(\"#\" + id);\n",
+ " var ws_proxy = comm_websocket_adapter(comm)\n",
+ "\n",
+ " function ondownload(figure, format) {\n",
+ " window.open(figure.imageObj.src);\n",
+ " }\n",
+ "\n",
+ " var fig = new mpl.figure(id, ws_proxy,\n",
+ " ondownload,\n",
+ " element.get(0));\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.get(0);\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",
+ "\n",
+ " var output_index = fig.cell_info[2]\n",
+ " var cell = fig.cell_info[0];\n",
+ "\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
+ " var width = fig.canvas.width/mpl.ratio\n",
+ " fig.root.unbind('remove')\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).html('<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/mpl.ratio\n",
+ " var dataURL = this.canvas.toDataURL();\n",
+ " this.cell_info[1]['text/html'] = '<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 () { fig.push_to_output() }, 1000);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function() {\n",
+ " var fig = this;\n",
+ "\n",
+ " var nav_element = $('<div/>');\n",
+ " nav_element.attr('style', 'width: 100%');\n",
+ " this.root.append(nav_element);\n",
+ "\n",
+ " // Define a callback function for later on.\n",
+ " function toolbar_event(event) {\n",
+ " return fig.toolbar_button_onclick(event['data']);\n",
+ " }\n",
+ " function toolbar_mouse_event(event) {\n",
+ " return fig.toolbar_button_onmouseover(event['data']);\n",
+ " }\n",
+ "\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) { continue; };\n",
+ "\n",
+ " var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
+ " button.click(method_name, toolbar_event);\n",
+ " button.mouseover(tooltip, toolbar_mouse_event);\n",
+ " nav_element.append(button);\n",
+ " }\n",
+ "\n",
+ " // Add the status bar.\n",
+ " var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
+ " nav_element.append(status_bar);\n",
+ " this.message = status_bar[0];\n",
+ "\n",
+ " // Add the close button to the window.\n",
+ " var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
+ " var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
+ " button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
+ " button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
+ " buttongrp.append(button);\n",
+ " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
+ " titlebar.prepend(buttongrp);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function(el){\n",
+ " var fig = this\n",
+ " el.on(\"remove\", function(){\n",
+ "\tfig.close_ws(fig, {});\n",
+ " });\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function(el){\n",
+ " // this is important to make the div 'focusable\n",
+ " el.attr('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",
+ " }\n",
+ " else {\n",
+ " // location in version 2\n",
+ " IPython.keyboard_manager.register_events(el);\n",
+ " }\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",
+ " // 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",
+ "\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('matplotlib', mpl.mpl_figure_comm);\n",
+ "}\n"
+ ],
+ "text/plain": [
+ "<IPython.core.display.Javascript object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "text/html": [
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DvSm6kEnUAe6U3WhHaAN7QBt6XsKkJp2gDZ0AnSg6asJA08NLLXRwAYtDURpDK5Fa2oiSkMDG3reb1DRR75uA9dUrdsgWyc/Tn99+zvWg7QHOd7SIUD9fkwAXQ1MnYD+Q2YWfqdIwYdr4nFheQxOLlqPQ8+vQ/PcMOyavhKVQa8M3KYuQ5W9O/ZO9sanEfH4KTtb6fjDE+gm0NSMhq5uJPT1V0NffzUMDMJgYBAGXd1VbJ2h4RoYGKxm62kb/zqYRsc2MAhT2l86du+5DA3X9Dku7UN9DQx6+0rHVD4O7dfftfOt9zp6P7eOTqjK/r3nCeu5rtXQGR0GDZ9p0PIeBSM/I9jMt4HlbEtYhljiidlPwDLEEtZzrGE9xxpPPvMkrOdaw3K2tM5mntTXZp4NLGZawHqONSxmWcAyxBJm080wdvpYjJ0+FhYzLWAxywImQSawmGWBJ2Y/Aeu51rB91hZPPvMkO5fFTGlfy9lSs54rncN6rrV0zBnSMS1nS/3NppvhidlPSMszzGA52xIWs6RzmU03g8UsC4ybMQ5mM8xgNsOMrR87fSzMppvBdJope28abNrbppmy/UynmbJmEmTCtpsEmcA40BhjAsdgTOAYGAcaY+z0sTDyNcJYDy1ssNXAGl0NrNTWxiuamux1uYYGQnV0sFJbW6m9oqmJFVpaSv1XaGlhmYYGXtHU7LNdfszlXD9q/Dr5dn4fVcv0flkPUJfK1tPyUg0NLOO2LZO98st0PGqq9pWvC+uBurEA+qDskQP97bffxoIFC2BtbQ0NDQ0cO3ZMaftPP/2ErKwsWFlZwcDAACEhIfjP//xPpT7ffPMNVqxYgTFjxsDExATr1q3D3bt3h3QdI93l/sF//BH5R25gUdV5TEo5jqeSjg3YJqe9ihkFr+Pl6vOI3vcesg99iIazn+HK53/AX/78f8jPzER+Zia+v3u3z7mGo8tdS2ss9PUVGD06HIaGSzFq1HLWjI1Xwth4JcaMWcHejxmzgr2nV2q0jZp8X+pjahoKU9NVMDMLg7HxSpibr4WZWRjMzMLYehOTUBgbr4SpaSjGjFnBttF2/tXUdBXGjVvDlvv2CZWtD+XaKpiahsLEJFTp3Hyjfvx1mpmFwdx8LVtvYLICWr4zMTrgCfit8sN8xXxMi5iGmetnYlbULMzdOBfPxD2DZ+KewXzFfLY+JDoE0yOnI3hdMGasn4GgtUGYHTUbU9dOReCaQPis8EFgWCACwwIxLWIa/Ff7w3+1P2ZumIkZ62dg5vqZmBc/T2px8zBj/QyERIdg7sa5WLB5ARZsXoB5cfMQEh0ibYsJgf9qf0yLmIbZUbMRtDYI0yKmYXrkdEyPnI6Q6BBMi5iG4HXBrE1dOxVT105F8LpgTIuYhqC1QQhcEyitCw9G4JpA+K/2h+dyT/is8IHPCh94LveE3yo/BK4JhN8qP3gs84D7Und4r/CGzwof+Ib6wm+VH9yXusNruRe8V3jDe4U3PJZ5IDAsEOZB5hjnpoNoO02sHm2AFWPGYPmoUVhmZITlo0b1afz6JYaGWD5qFJYaGmKJoSGWGBhgmZERW15iaIilhoZYrKfHGr9+mZGRtK+BgdI2OsbSnkbbF+vpsWPzx6R9F+nqKq2Tv5dve0lHh/V5UVsbL+noKDXq85KODl7U1saL2tqs/wtaWnhJR4e90valAuhDskcO9FOnTmHLli04evSoSqAXFxfDxMQEx48fx82bN7Fw4UJMnDgR3377Leszf/58uLu74/3338fFixfx1FNP4ZVXXhnSdYzkm3j3ux8wIfWEUvMpeBORLR+g6NRnaHjnNzh+43d479d/xq/+dBe3//FPluCmyuTT1uQ2HJPiNDVNoa0dCyOjtTAwWAIjo2UwNFyqBHdDw6UwMloGI6NlGDVqOeszZswKto7Wy5uh4RK2jT8eLRNMafBgahrK4M8PBKS+q9iAgGDLDyBoHQ9xHszKA4VVbDsNGuSDCTnUzczCMG7cGgZ0WrawWAdjizXQDpgFPS9T2M2zw7z4eZi6dirmxM7BvPh5eFbxLObGzsXcWAns8+IlyM6Ln4c5sXMQEhOCmetn4pm4ZzArahZmR83G9MjpmLl+JoPttIhpmBs7F7OjZmPm+pnS6wZpn4XJC7EwaSEWpS/CL5N+iZfSXsKi9EVYlL4IizMWs8HEs4pnMS9+HuYr5mNh8kI8n/g8ntv0HBYmL8Rzm57Dc5ueYwOBBZsX4PnE5/Fiyot4MeVFPJ/4PBYmLcTLW17GwuSFeDHlRfwy6Zf4ZdIvsSBxAZ5VPMvaM3HP4LlNz+GFlBekcyQ8xz4/nf+5hJ7zJjyn1FbkrsD0yOmYMNUUMfZaCBtjgHUWFgg1NUWYmRnWmptjrbk5wszMsGbcONZoW5iZGWu0Dy2Hmpgg1MQEK42NlZZXjBnDtq8yNcWqnv1omc65Ztw4tt+qnv60P52DHa+nHzt2T1sxZgxbt9LYWKmtGDOGvS4fNQorxozBMiMjNmDhBy40sKD3K8aMYQOSZUZGWGJgwM61SlcXMVpaAuiDtMfqcpcD/aeffoKVlRXKysrYutu3b0NfXx8HDhwAAHz22WfQ0NDABx98wPqcPn0ampqa+P3vfz/oc4/Em/g/d77Fnrd/g3mVbzOQ7zr/K3z5zd8HBPa9bCQCXUdnHPT0FBgzJqKPQidgEuB4dU5q28QktI8C5wFL+8mXeZXOK2tSzARQubImiFI/XjGbmq6ChcU6mJuvZWqaV9W0Lw9lvq+lZXiP6laGN53f3Hyt0vEtLNbBwmIdrKwiMcpsFbT8ZmJMoCWmRUzDwuSFmBs7V4Jl0kIl2D2reJbBa75iPp5VPIvnE5/H3I1zGfRmRc1i6nt21GzMjpqNObFz8EzcM0zdP5/4vKS+Y0LwTNwzElg3L8CLKS/iuYTn8Hzi89JxCaQ9Sn1O7BxpEBEdwgBPHoT5ivl4PvF5hMSEICQmhF0ftbkb52K+Yj7mK+Zj7kbpmLOjZmNW1CzMi5uHWVGzMCtqFgM6DVCmR07HjPUzMGP9DLZMnzMkJgTz4iQPwzNxzyAkOgR2z9jB0tMAMRO1ED52tBJgQ01MGBwJ1iuNjZWAzdb19JXDkgcuv47W0/Ho+Ku4Y1BT9Z6HOH+s/vbl1xOUCdArjY2VvBD0nu+jCvbLjIxYX9q+UlsbUUKhD9qGFdB/85vfQENDAzdu3FDqN336dMTHxwMAGhsbYWpqqrT9hx9+gLa2No4ePTroc4+Um3jn23+i84MvsaLhMuzSehW5Q/pJJBy8gX/+68cHPsdIBLqGhjFT6HKl2997UrS8W50gzAOdd7HzMCf3di+8V/VRwjzweWCPG7cG5uZr2Ss1Xi2bm69lcJZDmPpSk/pGsPe0HwFcuV+40nEtLSNgbr4WtraxMLUKh3bALBj4mMHxeUcsz1mOBYkLsCxrGVO4pHoXJi1k7YWUF5iKJUjOV8xn8A6JCZHUd88AgUBJAwI6HqngBZsXMLVOQOfV+rz4eex4C5MWYnHGYizOWIwFmxfgpbSXWF+65pfSXsLSrKVYnL4YC5Mldf5iyotYlL4IC5MWYmnWUizZsgQvpb2EBZsXsOPNV8xnx1qweQHmxM7BCykvYGHSQsxXzMeCxAV4LuE5LE6X+pN34LmE57C2eC2C1wVLCn2iFlaPNkC4pSVTyussLJhaJuW8zsIC6ywsmEonxc63VRyg5etXGhuz468ZN05pwLBm3DhpICEbRPAKPpR75ZU+qfYVY8Yo9SWlv9LYeEDvAT84IKjLww+k4nnPAO8FCDU1xWp9fURragqgD9KGFdAvXboEDQ0N/OEPf1Dqt2TJEixduhQAUFhYiKeffrrPsSwsLFBbW9vvub777jvcuXOHta+++mrY3sTvf/gRZz75I2LaPsTTW04pudYX117C/su/xV/+1he8932++wT6z/WdDt3drsli6CYmkUxp8zFmeQy6PzgTjPl1va5t+fte1W1iEqoEWHkjIPNqml/PQ9bKKhKWlhGwtl7fsy2Ca+Gwtl4Pa+v17L2lZThT2ebma9l2Hv698Jb2t7GJhpVVJKysIjF+fBSsrdfDzi4Oo8xWQSdgFkyDn0RITAhWF6zGy1texrKsZQyIofmhCM0PxbLsZViRuwIr8lZgSeYSLE5fjKVZS7E8ZzmDJYF+ccZiBuBfJv0SizMWY1H6IsllnrQQi9MX4+UtL7NzLEhcgBdSXsCy7GVYkrlEaluk10Xpi/DylpcRVhSGFbkrsCxrGULzQ7EofRFC80Px8paXsaZoDVYXrMa6knVYV7IOK/NXYk3RGqwqWMWuf3XBaoQVhWFZlvQ5QreGYnHGYqzMX8n6LEpfhNCt0melgcPC5IVsYLA4Y7G0f94KLEpfhOU5y7E8ZzlWFazCupJ1cPqlE6y8DBFrr43oJ8YiwtIS6ywssN7aGhGWlgi3tGSv4ZaWDOw84Hk3+aoeiKoCOu+upyZX57w7n1z8pOLlbn7e1b/W3FzJhU+N9uGhzw8YmEufAz15JwjooSYmSgq+D8y5ZaHQh2b/NkDPyclR+QcwnG7i3e9+QP3bv4ZvwZtKEA8pv4Cdb/0nvvzm7w/lvPcL9J/rO73fGLqOThxMTCIZxHko8+5pXjHTegI5wbq3b6873MQklAGYBzgPS15N9wI3AlZWkQzcBFtSxjyweZhbW6/H+PFRGD8+CpaWEQy8/Dp+PxoAmJuvZX1oPZ3X0jICtrYxSvtTPyenJIwbHwntgFkY7W8Bj2UeiK+Jx5ItS7C6cLUEz+xliK6KRnRVNNaVrMP68vWILIvE6sLVCN0qQXJZ1jIJ9nkrJOWavhihW0MZ3AnOC5MWIqIsAmuK1mBxxmKsLV6L8JJwrC5czQAcXhqO8JKeVhqOdSXr2PuIsgiszF+JVQWrEF4azgAeXhKOyLJIRJRFYEP5Bmwo34DoqmisKVrDlsNLpeOtLlyNiLIIxNXEIawoDKsKVmFl/kqEFYUhrCgMSzKXYFn2MoQVhWFl/kosz1kugb/nc1HfNUVrpO+pYDVWF6zGS2kvIbM1EyExIbCdaopYe22Em45G1PjxWGdhgUgrK0RaWSHC0hLrra3Z+/XW1qyts7BQgnyECuDzcJfH5NdZWLDt5AUgDwAfs6d9wi0t2Tq594D2ibC07HM+vq8c8vwggVz2/ACjTzyeU/vkDVgxZgw7l1DoQ7NhBfSH6XIfzgr923/+Cw3v/AbuPY8tpSS3ra99ilu/u/1A8fHB2EhT6BoaGtDTs8CoUZsxdmw0U9F8fFkehyaY98aXQ5WgL2+k0CkLXa68SSkTJElpW1is4wAezoDcC29pHa+WbWyiGZCtrdczAPPraNnWNoZt5/vZ2cX1ORa/no5DytzGJhpOTkkYYx4GncDZsJhlhyVbliC+Jl5Ss4WrGSTjauIQVxOHqIoohJdIkF1dsBpritZgZf5KrMxfiRV5KxBeGs4UfGh+qKSwtyzB8pzlDNoJdQkIKwrD6sLVWFWwChFlEYgsi8T68vWIqojC+vL1iN0Ri9gdsQgvCUdURRQiyiIQXhKOsKIwtn5D+QbEVMcgcnsk4mviGbg37tyIjTs3Ir4mHjFVMYiriWP9Yqpi2PaNOzeygcCG8g2IqohCVEUUQvNDsaF8A+Jq4qQBRkk4lmYtxZqiNQgrCkNURRQ27tyIdSXrsGTLEjbYiauJQ2J9IlwWueBJ71HYaK+DjU9aIM7ODlHjx2O9tTXCLS0RaWWFaBsb1mgb3wj8BFw52HnARlpZMTjT8ckLQIOCdRYWSl4B+aAhgjsPvdKx+HPzIOfDBvLr4sMBK42NGfhJrfNxfnmOgRz8q3R1RZb7EGxYAZ2S4rZv387W3blzR2VS3LVr11ifM2fOjMikuK/vfoeac79CQNFZBvJZZefRefVLfP/Dg8fGB2sjMYYugC6ALoAugC6ArmyPHOh3797FjRs3cOPGDWhoaKCiogI3btzAf//3fwOQpq2Zmpri1Vdfxccff4wXXnhB5ZwVVkEAACAASURBVLQ1T09PXLlyBe+++y4cHR1H1LS1b/72PTKP3YJjRm983L/wLDqvfokffoYkt6HaSAS6hoYJ9PQUMDOL6TPXmuZZ95cVzsOe3OryedryQUBvclmEEtAJknLXOe/atrSMgI1NNNvOw5Xe83C2tY1hYLa1jYWtbSxsbKKVmq1tDIuN9/aNga1tLOzs4uDomAAHh02YODGeAXzixHhMnBgPW9sYTJwYD2fnFFhNiIFO4GyM9rdA4JpAZLVlYVXBKmyu34zIskgk7E6AolYBRa0C0VXRiK+JR3RVNKIqohC7IxYbyjdgffl6hBWFIbw0nMWyKV4dVhSGtcVrsbZ4LVbmr0Tk9kgW244si0Tkdgmo8TXxUOxSILkhmZ0vqiIK0VXRiKmKwfry9YiuioaiVoEN5Rug2KWAYpcCsTtikdyQjKSGJERVRCGpIQlJDUmI3RGL1H2pbDASUxUDRa0CMdUxiK+JR1xNHGJ3xLLjE5gJ/ht3bsSG8g0M/lEVUYipjkFifSIS6hKwunA1wkvDEVMdg5jqGISXhqOwqxAvb3kZDtPNsdFeBxvMTRFnZ4dIKyvE2NpivbU1osaPR4ytrRLQo21sEGNry5Z5sBOM15qbMxBHjR+PqPHj2XsCMcXp+Zg9nZNc7+T+JwiH9/SnwQG98iEAfrARwfXn95WHBXjw82EAlrjHTbOjXAEWxzcx6T2ekZGIoQ/BHjnQz58/r/JGhIWFAegtLGNpaQl9fX2EhITgP/7jP5SO8c033+CVV17B6NGjYWxsjLVr195/YZlHeBPvfvcDas//GlN6njc+IfUEFu68iMPXvsK3//zXI7sOuY1EoOvqmmPUqKQeoIcqxbYpa9zSMpypZlLW8ixzXs3ziWu0TjkZLYJ73xuP5lU0qW75Mg9sXkXb2sbAzi4OdnZxsLWNZapaeh+jBGkCMwFdeo1lx7azi2PQdnDYxN7b2ETDzi4ODg6b4OCwCY6OCXB0TICrazpMnlgLvakhePKZp7C6YDUyWjIQuyMWcTVxyGjJQGJ9IrLaspDVloXE+kRsrt+MlMYUpDenI6EuAXE1cVDsUjAYbty5kUGaGqlwUtUbyjcgZW+KBNldCmzcuREJdQlI2J2A+Jp4ZDRnSK0lAymNKUhuSGZwjq+JR+q+VLYudV8qMpqlfpvrNyO9OR3pzenIbs9Gyt4UpDWlIb05HUkNSdi4cyNS9qaw/hktGVhfvp4NUugzxFTFILIsEmlNachoka4la38WNtdvRlJDEtaXr0d4STgS6xPZNaTsTUHegTx4r/DGeN/RiHPQQdx4SaHH2tqyFm1jgzg7O9bWW1sjtgfmcrUeNX68Upw9avx4rDU3VwI+vee9APx7vi9/nIgeBU4qnOAdLltP10Dn4nMA+H3IK8APHFQl8dEgRB7vV5UXEGZmJhT6EE2Ufn0EN/Gf//oR9W//WilGPq/ybVz69dcP/dyDsZEIdC2tsdDRiYOZWYwSkOUZ3vx0MII8rePhzmeNyxU5PzDgVTjvCpdD28oqkqloUtjKsI5loLa1jYWDwybY2ytgZxcHe3uFkjInEMtVtqNjAuztFQzedDwHh01soEAAnzgxHk5OSazZ2yswZUoGU+imwdaYFjENhV2FCC8NlyDVmILUfanI2p+FrP1ZyDuYh6y2LAZOxS4FNtdvZrBV7FIgsT4RMVUxSpCkbVEVUUyJR1dFI6EuASl7U5Ddns0gnHsgF0WHi1B0uAjZ7dns+BktGUjZm4KEugRkt2cjvzMfWfuzkN2ejczWTBR0FfQOBJozUNhViK2HtiLvQB6y9mchuSEZKY0pEsibM5Dfma/kDUisT2SAztqfJQ1MyiLZACC5IRlpTWlIqEuQvAO1CqTuS5UGInUJSKxPRPXpaizOWAz7aeMQ76iHKAtTJE+ahKjx4xE/cSLi7OzYK9/iJ05EjK0t4uzsoLC3R5ydnZKi50HMvyeVT4MCvg+tjxo/XsntLz8O/ypf5hW+fH+CejjnESBPQHhPIp0q1U7H5N3+POwJ7nSutUZGiNXWFkAfpAmgP+Sb+Nkf7mBuxQWlGHnXta/wrx8fbqLbUGykAV1TUxMGBpYYPToJTzwR3wfKfPY5gZiHOW3nVXz/mevhSu50G5toJaCTiuZd5Hz8mnd380qbwCy5xxN7WgKDt5NTEiZOjIejYyIDtpNTEiZNSsakSclwckpigwCCNB2b+hPIJUWeyJqzcwocHRPg5rYFplbh0AmcDas59ojdEYvio8UMatnt2choycDWQ1ux9dBWFHQVoLCrkAE+ozkDSQ1JSKxPlFR2j8KOq4ljwE6ok9alNKYgZW8K257WlMbOk9GcwaCe0ZyBnPYc5LTnILM1E3kH85DfmS9dS49qL+gqQEFXAfIO5iHvYB67vpz2HOR35iO/Mx+lx0tRfLQYeQfyUNhViIKuAqQ0pqD4WDEKugqQ1JCEvAN5KOsuQ2FXIUqOl6DkeIk0mDhSxPpnt2dL4N+lQFJDEtKb05F3IA857TnIPZCLmjdrUPNmDbLaslB8tBhey73wC39jKJ7Wx2Y7G6Q4O2OTg0MfoG9ycMAmBwcGdX45tgfucvc8uej5xqtw8gLE9LRoGxt2LD52T+59PgQQNX488xTQeQi+/PnlQOevg8IDvHuej8Hz8Xt5lTxVoYW15uZi2toQTQD9Id7EW7+7DbdcSZV75r+BzqtfDiuQk400oFMMXV9fAQuLjczF3ltkJYIlnfVO4+qdw80nslFMXD4Y4LfT/vwcbnKd80DnXea9qj1WSUXLG4HcxSWNgVlS1Ymws4vD5MmpDMyTJiXD1TUdrq7pTJ3b2ysYtAnUtJ+TUxKcnVPg5JQER8cENhigdT4+eXhyYiz0pobAdNp4zI6ajfLXyhFRFiEp3pYMpDen90Ly1VJsO7oNBV0F2HpoK3IP5CKrLQspe3uVb8reFCh2SeqVXO7JDcnYXL+ZKeHN9ZuR3JCMzNZMprBzD+QioyUDJcdLsO3oNmw7ug2FXYXs/NuObmOg3XZ0G6pOV6GgqwClr5ai/LVylL9WjuKjxSg6IgG55HgJdpzZgdLjpah+vRqVJyuRdzAPlScrUXysGNnt2ag4WYGq01XYcWYHGxxsO7oN27u3o/TVUpQcL0FmayZS96WyAURhVyFy2nOQ3Z6NvAPS8SpPVkKxS4H6C/VYlr0MT023QKy9NmKtxiF50iTE2tpCYW+PREdHJDg6In7iRCQ6OiLR0RGbHBygsLdXAj4pdoW9PQOzKojL18VwMJerfAK5XPnTsWNlcX35QIIfHBD4eeDz10P78u5+ct3zbnoe8uSmp/nvdE5S6CYC6IMyAfSHdBP/9Ndv4VcozSd/ade7P2shmJ/bRhrQtbS0oKtrDhOTVFhaxjNXOQGcd7Pz8W/5Or6KGg91UuzKA4JwFS72vmqc2vjxUUyB8/Fwil+TQiegk9J2dEyEi0saHB0TGOAdHRMxZUoGJk1KZvvxyXB2dnGYNCkZbm5b4OiYiIkT4+Hqms7tn6Ck7t3ctsDFJQ2entkwtQqH3tQ5sHveGYn1iag6XYXcA7nIbs9m4M47kIe8A3koPlqM/M585B2UFGpWm6Tis9uzWQyb4B5fE88UOrnWU/ZKfdKa0lhceuuhrSg+Wozt3dtRfqIcJcdLUPpqaW87XoqCrgIUHSlCYVchyl8rR8XJCpS/Vo5tR7cxKFedrkLpq6WoPFWJylOVKH+tHJWnKlHzhqSgC7sKUf16Napfr0ZOew52ntmJuvN1zHWf3JCM5IZkJOxOQMnxElScrEDFyQrkHshFTnsOSo6XsEEM7xkgoBcfLcbOMzsREBaAX/gbI95RDykOE5hCJ5BvcnBA8qRJSOiBO98I7nKlToAkJc0rcB6g1J/fP1a2T4xMxVNfgj4l8NEx+ePx7+l64uzsEG5pyc5P18RDmvcG8AqeVP1A8/SFQh+aCaA/pJtYcOJTTEg9gTnlF/DXb//5UM7xc9lIA7rkdjeFgcEmWFrGg+qZKxdr6XWV80lxBHKCNEG8Nzs9XCk7XT7VjE9I46eRUaybgEqJaLxrnVzkjo6JTF3b2yswaVKyEnQdHRMZiJ2dU+DgsIkBXZ7VToMFmoY2ZUoGc6u7uqbD2TkF7u6ZcHRMxOTJqZg8OZW57IODi/HkxI1SDH3aeMyLm4f6C/VI2ZuC4qPFEiBPVjKXdunxUhQdLkLxsWLmes9pz2Hu7qy2LChqFcg7mAdFrYJBPLs9m7mrCeZpTWnIbM1ETnuOpKoPF6Gsuwzbu7czhV59WlLW/HkrT1ai/EQ5So+XYnv3dmzv3o7Kk5WoOl2Fsu4yCeBv1KDqdBVq3qxB9elq7Dq7C1Wnq1B9uho1b9Qg72Ae6s7XoebNGqQ1pSG+Jp5ls2+u34yE3QnIPZCL8hPlqD1bi4KuApQcL0FBVwHKusuYl6L4WDGKjxYzz8DB6wexPGc5nGZZIc5BBxutzZHt6YlER0ckOTkhdfJkJDk5McAn9KznXfIJjo5KUKcYOMGZYEpwJcjT/jG2tmzgwB+HV//yAYP8XLQt2saGXRsdk7wHtF1hb4/11taInziRxfF5tU1NVeIeKXdyt/PJd/R5w0ePFjH0IZgA+kO4if/4/l/wL5Tmlp+4+Yd77/CYbaQBXVNTU0mh8zXKqfFzvfkyqsqu995BQK/LvXd/GhTI54JTLJ1PbqNsdD5OTjFxim9TLJt3v5MyJxc573Z3dU2HnV0cpkzJwOTJqeycvYo/VukaCOiU8ObklMRc9JMnp8LFJQ0uLmmYMiUDLi5p8PHJg8kTa6ETMAtPveCGzNZMVJ+uRtGRIgZNBq5jEuBJpee05zCwZTRnsGxvyoonl3pmayZTwenN6SzOTbH5wq5CFHYVovhoMcq6y1BxsoKp3qrTVSg/UY7Kk5UMqiXHS1B1ugo7z+xEzZs1KH21FNWnq5kiJ2W/48wO6XqPFWP3ud3Y3r0dO87sQE57DhreaUDDOw1IqEtAdFU0UvamsOluSQ1JUOxSIKUxBTvO7MDuc7uR1ZaFipMVbEBRdLiIXU9ZdxnKusuw79I+VJysgNsSN9j4joHiaT1kOj+FdFdXpE6ejORJk9hrkpMTUpydkeLsjCQnJ+Z655U6H2/nE+Z4dU1g5cFM8E3kjkPH5uP2dEwKB8TI4E7nom28G58gzqt2hb29Uia8vLxtpJUV8xaQaqdX6s+HEmhQsEpXVyj0IZgA+s98E3/1p7tYsOMiJqSewNRtbz3W6WiDtZEI9N4YepzMld4LY75+OZ/IxsOeV+bU5PF3VcVdeKXOg5ZPTKN4NiW0USydoE6wJ7c6D3QnpyS4uKQxBe/mtkVJofeeI5Flxzs4bIK7eyaLu7u4pGHSpGS4u2cqxeinTMmAq2s6goKKYeMQD53A2TCfYYu5G+ei7nwdEusTUdBVgIqTFSg9Xor6C/Wov1CPXWd3STHrE+Uo6CpgsedtR7exZLas/VlIaUxB1v4sBvncA7lIa0pjiXZ5B/JYTLrkeInkzj9WjIqTFQzqFScrsPPMTpQelwBddLgIFScrUHK8RIqZnyhH9elqdj3FR6X9KUmt5o0aVJ6qZDHynWd2YtfZXexzNV1qQu6BXChqpUx9mpqX057DkvvyDuZh97ndLG5edboKRUeKUHlKisNvO7oNO87sYN9Dx7UOLMtaBvvgcWzaWpaHB+InTkTypEkM6umurkhyckKSkxMDPO+KJxgnOTlBYW/PlLEcvKpATqqcwJ3o6MjeUx9y/yc5ObFBQ2yPspcrenlGPjXyBJCrnqbgUVyc1DZBnlR5DKfi+eQ63tUeYWnJzhMxZowo/ToEE0D/GW/iR1/+H1x75pi75Z7Be7/+88927IdpIw3oWlpaMDS0gqlpGqytNyllqJPLXD69jIc3udF5xS6fikaJcKpATi50W9tY5lIn9zkVbeGT1Uip87Fyas7OKXB2TmFucHK7k5vdwWETvLxyMHlyqpL65131tI7g7eiYAE/PbOZ2nzw5FVOmZMDNbQvc3LbAxycPXl45TKHrTZ2Dp15wQ1pTGqpOV7E49raj25TiyTvO7MD27u2oO1+H8hPlDHDbjm7D1kNbkbU/C0VHiqTMdS4bndzxpOTzO/NRdLiIHb/01VIG8rpzdUyhl3WXoep0FXOZlx6XlHf1671u9MpTlah5swY7z+xE5clKdq115+tQd05qu87uQu3ZWuy5sAe5B3LRcrkFtWdrWZZ9TnsOu9aCrgKWbV95qhK7z+1GenM66i/Uo/hYMWreqMH27u3MQ0Bqf+/Fvag8VQn3pe74hZ+U5Z7uZI/UyZOxxc0NaS4uSHR0RIqzM9JdXZExZQoypkxBmosLc8cT6AnKpJLJ3R1ra8tc6dSHd4fzIKa+pPp5GPN9k5ycWB8e4Pw5yAuwycGBwZvPxE9yckKsrS1zrVNGvRzoFMvnp7nxGfHkgo+zsxMK/T5NAP1nuokf/Nc3DOaLai/hj7e/vfdOw8RGGtBJoVMMXT7djFzQyoVgepU3AVuVeufLsfIPQeHBzheBIZCTO51gT1AnQPenwkmJ8/FtZ+cU5hqnjHSCOu8FoKQ6W9sYBng/v61sH1LrPNTJ3e7qmo6pU7exGPrY6TZ4Ke0l7D63G9nt2Sw+vPfiXjRdakLTpSZs796O6tPV2N69nbnJyWVedKQIOe05Umy9LUtS4D3JdHkH89jcb3LXbz20lWWoV56UEtlKj5ei5s0a7Dq7C7vO7kLduTrsubAHNW/USK74HsA2vdeE+gv12H1uN+u748wO7Lmwh0F897ndqHmzBnsv7sWeC3tQf6Ee7dfaUXmyEnXn69B+rR3Fx4qhqFUgszWTzX0vOlIkZerXKlB+ohwtl1tQeaqSDWSqX69GWXcZdp3dxeL1NW/UoOR4CQ7dPISV+Svx9ExLxDvqIW68BbI9PaGwl8Ce6OjYx+WePGkStri5sfX8K6lzgnBiT3ydd83zqpyy5fntCbJMeurPu/Z5eKvKuJcPIHgvQAw3yCDlTWDmYU2wV9jbK1Wf46e+0UCAz9gPHz1aAH0IJoD+M9zE81/8CU6ZUhnXl3dfwt3vfvgZrvDR2UgCuvToVC3o6Vn0Ueiq6p+T652eTCbPVFfljufj5Hx5VYIoD1UCOiWxUZU2yl4noNOUMoItZZw7OiZi0qRkBl4+nk7v3dy2wN09E66u6cxVz883p/N7eeWwQQDB3MMjizUvrxx4eeXA1zcf/v4FmDp1G0wt10FvagieetEdGS0ZqDsnQav4WDH2XdqHI58cQePFRjRebGQx9MqTUhZ58bHiPoqeEtxyD+Sylt+Zj4KuAqbMyU1efbqaudZr36pF5alK7Dq7i6nehrcbUH+hHnsu7JEUcU+y244zO1B7tha1b9UyYBP8Cej1F+pRd64O27u3o+HtBlSerMT+q/tRdKQIDe80oPFiI4oOFyGhLoFVk0tvTmfz4gu6CrD34l7UX6jHtqPbsOfCHlScrEDb1TY0vN2A6tPV2HlmJ5rea0LTe01ovdKK+gv1CAgL6Imh6yPT+SlscXNjwE5zcUHGlCnI8vBgLnhKmONb8qRJDOAU9yYVLlfXpNz5GDkBnZ8axzeCNk2jS1ARwyeIK+zt2XUlODqyuDol8K23tkZij7rnK83Jk+PCe9zoMba2iLC0RPzEiUrT5vhBQJydHYurC4U+NBNAf8CbeOrjP+CpjJOYkHoCYfuu4B/fD/+YudxGEtB73e5jmULn3ePyuur8A0/4RDe+qpv8YSnyB6X0JrzFMDVMcOcrr/Wq9US2TopnJzKQE6TJ1U7udkfHRLi6psPNbQumTMmAu3smJk1KhqdnNivT6u9fAHf3TLatt4CMtK+HR1ZPlnsCfH3zMWVKBjw8sthx/fy2ws9vK+s3c2Y57JwSoDc1BBaz7LAibwU6rnWg6HARA2LL5RYGycqTldhzYQ+DKiWhVZ+uZlnmlCyW2ZrJ3N95B/NQ/lo5c2nzyW28W33nmZ3Sec/Xoe58HRrebsCus7uY2q47V4emS01MvTdebGRKue5cHWrfqmWt+nQ1Gi82ss/RfLkZDW9LIC/rLkPTpSY0vNOA4mPFyGzNxOb6zWza3dZDW1F9uhr7Lu1DwzsN2HZ0G+rOS59/55mdUqz+jRrsPrebXWvV6SocuXUE4aXheHqmJRRP60Fha4XioCAo7O2RMWUKUidPRoG/P1smdzwlx6U4OzMXPK/SCdwU8+YHAwR7Pnt+k4MDU/8Jjo5KyXh8o7g9wZqP3fOJetSfVDmv8CmuT8vkZufj6LRMSXx8sRrK0pdXrqNBS/jo0YjR0hLz0AdpAuj3eRN//PEnNLzzG0xMkyrAxbZ/+EifkPZz2kgDupaWFgwMLGFmloEnn0xQcpXLH3zCq27qY2cX12ed3B2v6mlmVCSGr5dO1dfIpU6qnCBMcWxelVNSGt9cXNLg7p7JAO/qms7gTeAn0FOSm5vbFtbPxycPvr75mDw5Fe7umfDwyIK3dy5rnp7ZTKkHBBTCxycPwcHFMLUKh0HwXEx5xR8VJyuk+PJbtWi+3MzgR/O8m95rYjHrypOVKOwqRMXJCtSerWWJcoVdhSg+VsyKwBR0FaD4qKTkabpb8bFi7DizAzVv1GDHmR1MUe86u4t5AxovNqL2rVrUX6hH7Vu1zL3e9F4T9l7cKw0yzteh4Z0G1L5Vi8aLjew9NYqfU6yb9qs4WYF9l/ah9f1WFovnBxs1b9Sg4e0G7LmwB4VdhcyFX3e+jg1o6Hr2XtyLvRf3ou1qG3af243g8GD8ws8YCZMMUeA5BVv9/JA6eTKyPT3ZtLUUZ2dkeXggy8ODxdPTXV0ZqAmyiZzKJnc4P2+d4u3Ul+a8E6zJI8APCPjjEsj5V3myHK/86fykyBMcHRmY6RpVPUGOn3onLx/Lu9j56XgE+dX6+kKhD8EE0O/jJn599zuE7bvCyrkmHfpoWFaAG6wJoAugC6ALoAugC6CPWLvfm/jp7+/Ae6tUAe7pLafQevm3+OmnkQtzYOQBXYqjj4WhYQKeeCIe48atUXqCGV93nc9Q5yFOcXF5Tfa+jySNZfXYqfobXyNdXhyGT3zjYc/H0gngBGUCNVVwc3PbAmfnFCVgE9QpDu7vXwBPz2wGck/PbLa/n99W9t7TMxu+vvksq52at3cuQkKqYOeUCP2gubCYOQFLMpeg41oHsvZnYfe53dhzYY9SljtN/ap+vZoBuay7DMXHirHnwh42XzzvYB6bz150pEipqlvFyQo0XmxkU8l2ntkpuc/fbZRc4u82Yv/V/dh/db+Sy5zi2Y0XG9H4biOaLklgp3h4/YV6tL7firYP2tD2QRtaLrdg/9X9aPugDU2Xmthr03tNqDtXh9LjpWh4R4J203tN6PiwAx0fdqD2rVrUvFGDlsst2H1ud6/r/e0G5rKn62m61MSS4ipOVqD7i25ElEWwpLjNdjbYNnUqUidPRqa7O3K8vBi8KcudprJlTJmCFGdnJPSAOdPdvU8iHZ+RzmevJ/T0oQEDX8SGjs0PFngXP7nuedc6X/BGPoCQn5tP2uNd83xZWr7iXX8PguFbpJUVG0REGhuLwjJDMAH0IdzEP9/9DtNKzmFC6gk8U/E2vvjjXx/iFT46G2lA19DQgIGBJUxN02Bjk9jnGeN8ohsPdT4uTjCXq3p5aVe+bCtf7Y3mkPPzySnBjRQ5xc75DHOCOT8nnBS1m9sWpqLd3TPh6ZmNKVMy4O2dy1Q5AZ0GCK6u6SwuTvtQ8/bOVYI5qXV//wIEBRUjOLgE48ZHQm/qHLgs9WGxZcocb3hHSv7ac2EPSzjb3r0dNW9KAKt+vZrFk+sv1GPHmR0oOV7CMsH5GuuVpyoZxCm5jcW2e6C879I+7Lu0Dy2XW9ByuQUNbzcwALdcbkH9hXrsu7QPtWdr0XqlFXsu7GFwb73Sio4PO9B5oxOdNzrRdbMLHdc6cOTWEXTe6ETHhx1Sn2sd6PyoE43vNjKPQM2bNSyTv/NGJ4vP17xZgz0X9mD/1f1ovtyMlsstaLzYiLYP2lhMngYfnTc60Xa1DcHrgmEbYIKESYbI93BBlocHMt3dke7qypLjtri5IdPdHZnu7gzk6a6uSvFziq3HT5zYpwANHwdP4NS2vFFMngc4NT5+zjcaQCRPmqQUm6ckPepHSXXyeemk4uUV6fia8AR2KjTDl4yl41CW+2oDA6HQh2AC6IO8iXe/+wHzKt/GhNQTCCp+C7f/PrzLuQ7FRhrQNTU1oaMzDoaGCbCxSWTTy3hlzStw/iEqPLBVNX4AwE8P47Pae93qyuqbktvkD0YhtU0AJuXs6ZmNyZNTldzhfGKcq2s660dJbTQwINc6TXujAYGXVw48PLIYyEnN+/rms6Q4f/8CeHvnYs6cavziKYWk0GfZ4eUtL6Pr4y4UdBVIivmdBtSerWWFZRovNmLnmZ1oeEdKVmt4u0EC+2mpRnrNmzUof60cNW/UoPR4KZtPTklwlSel2up15yVXeN35OgbSxncb0Xy5GfUX6pnKJmXd+n4rWi63YM+FPdh3aZ+UWd6T1NZ0qQkHrh9A50edaLncwoDeeaOTrW+/1o7Gi43sfdfNLnTd7GKfsfhoMRtEVJ+ulrLYX69Gy+UWtF1tQ+uVVjS914T9V/dLg4f3W9H4rnQ8luX+fiu6v+hGZFlkT1KcPhS2Vijw90eSkxOyPDyQ4+XFXO2U/c7DPcXZmSXLpbm4MJVOyl3uik9yclIaBPDqnIc3KXR6z4OZYM8rdD77nlQ8X3+ed/XLHy6T6OjYx+VO89d5dzo/z54fFJBbns653sREKPQhmAD6IG/ioQ++xITUE5iS8zp+/b93H/LVPVobaUAnhT52bDomTEjpo6x5V7oqUPPb5Eqdr89OD1ORq3NejfOPM6W55Hwt9cmTU5nrnLbzRV4I1qSmfXzy4OmZ49RNvQAAIABJREFUzcBMU9HItU4xd8pgd3RMhJ/fVuZ2d3fPhK9vPgO4l1cOAgIK4e9fgMDAIgQGFiE4uBhTp25DUFAxTJ5YC4PguXBfGYiKkxXoutmF+gv1LIZO0Gy61MTA3nSpSSnznLLcq1+vRu3ZWlaTnRV5OVfH4s7VpyXw152XVPDei3sZFFsut6D9WjtrjRcb0Xa1DR0fdqDxXUkZkxJvvdLKXOqkxhsv9rrr2z5oQ8e1DqWBwaGbh9B+rZ0p8bYP2lDzRg26bnbh6KdHcfTToyg5XoK2D9rQ8E7vlLnat2qZKqfrbL7cLA0QegYP3V90o/VKKwLXBDKFTjH0LA8P5Pn4MKCTMqe2xc2NLZOLnJQ1TXdL7MlWT5DBmHfLE5zpmKT8011d2f4Ee/l8eFrPF7hJVKH+aS48H7vnp8BRXXmalkZzzwncVPRGDnF6uEuMrS2SnJxEDP0+TQB9kDex9PXPMSH1BNKO3HzIV/bobSQCXVPTFKNGbYatbbISnEmNq0qOIzc6TUGTPzFN/gxzvlY6qXM+GY6ftsYrdop3E8ApoY0KxlBhF1LjNM+cXO/kIvfyymEK3csrB+7umQgIKERAQCE7lpNTEpvO5u2dy1zr/CupdFLoQUHF8PbOxbx5NbB13AS9qSGwmf80VuSuwLHPjqHuXB32X90vuZjfbWQu99qztWzueOVJac44FXipPSvFnmvP1va65E9Xswei1J2X3PUEdpqi1vBOAzo/6kTDOw0Mwq1XWqXWo4Q7rnWg6T1JxTe+28jUNM3/JpAf/fQoU9/kfj9y6wg6P+pkbnMaPOy9uBd15+tw8PpB7L24F4duHsKhm4dQ+1YtDlw/wOL5jRcll/6+S/vQdrUN7dfa0XK5BQevH2T7HLp5CI0XG9H9RTfWFK2B0ywrJDgZYrOdDUqnTWMKPNvTE7ne3tjq58fWZbq7K7nlM93dGcxJpdNymouLktImJU8JcbQf1Y+nwUGmu7uSez3Lw0Mpxk6DBr4PP0DgY++UvMcrd0qQ4x/5muTkxIDOQzxGBdh52Cvs7VmSXaKjo5i2NkQTQB/ETbz9938iuOQtAfRhAnRtbW2MHj0epqZpKhU6/yQy5QeoxPZR67TMg59/rrnyw1YSGcz56m8EclLrBG2KkXt4ZLF1POBJqZMC9/DIYiAmwFMfF5c0pax1ipd7eeUwV3tAQCHLaCe1T+qcV+iBgUWYMWM7goKKMW58JAyC58I7bDq2d29H541OBjFSqTxAWy63MCjvvbiXKfWaN2p6lXrPK9U5p+py5HLfcWYHKwrT8E4DGziwxDVq7zUxWO+7tA/Nl5vRdrUNTe81oflyM4tdN15sRNN7kuud1H3L5Ram6ClJrvVKqwT1S03sM3Xd7ELz5WaWoHfg+gE0XWpiHgqKz1MYoONah5Kbn9Z3f9GNvRf3wmu5F2wDTLDZeRQKPKegKDAQeT4+yPf1ZUDnXe5UZCbT3R1b3NyUlDKpZUp44x/owrvJ+X3SXFzYvjleXgzU8ng5QZzATGCXn4Pc+tSXPAkUBuBd8JQoR/FweU14gjipcSprS3F1hb09KyVLgwFRWGZoJoB+j5v4+id/hE/Bm8zd/tkfRv5Nl9tIArpU9lUDurrmSgqdj5PzTyKTP5ms9ylpMazuutxdr3ycmD5PTnN0TGAZ69T4gjEUK6eMdVrv6ZkNF5c0VsmNVLW7eybLTPfwyFJS5PSe70/QpsQ3b+9cNk3Nz28rAgOLmDr389uKgIBCBAYWISioGEFBxcwVTwpdP2gurOc6YF3JOnR/0Y3Kk5UsWY2g2nixEYduHpLi3T0Abb7cjLrz0pSuylNSrLz2bC0qT1YyxV7zhlTKtfy1cjbVi4qyUFy+9UorOm90ovX9Vhy8fhAd1zrQca0D+6/uR/u1drRekWLo+y7tw8HrB9H6fisOXD+AQzcP4cD1A9L+H3Xi4PWDDLBtV9uYC5/gToMEOi+55A/dPIS2q9I+bR+0sSQ8Aj8BvPlyMzpvdCq7+nuy4xvebkD3F90ILw2HyxwbKJ7WR7K9LcqmT2cu92xPT+T5+DD3OzVenWd5eDBgyhPbUpydscXNrd9YOQ/eHC8v5spPd3VVUtQEcxowpLm4sOPKE+iSJ01ibnuFvb2Su54q2pELnn/mO7nhE7kEOT7hjVQ5ueP5CnQxtrZsUCIU+tBMAH2Am/jhf/8Fdj2FY2ZvP49Pfn/7EV7ho7ORBnRNTU0YGFhi3LgtsLNLZZnrfElW3n3Og9naej0mToxnKpwHP6/m5e97p6opK3K+BjtB3dU1nSl1emAKVX2jbHRKWPPyymEA9vcvYC53AjnFx6kvKXtS8rSN4B4cXAJ//wIGcXr19c1n6jwgoBAzZ5Zj2rRSJYVed64Oh28dZpnmHdc6UHdeykSnLO+2q23ovNGpNN+7/kI9Kk5WYPe53Sh/rRx7L+5F7Vu1Sg91qb9Qj51ndqL69Wo27Yvc7J03OqXEs0tNOHTzEHO5E6APXj+ItqttSu7xjmsdePXzV3Ho5iEcvH5QcrV/3IXDtw7j8K3Dkrv9kyM4cP0ADlw/wNz2Te81oeNaBw7dPCRlw3/cxbLgqTVdapIGDlekgQPB++D1g6w/nYdi9t1fdKPxYiOCw4MxYaopNjuPQr6HCwr8/ZHv64s8Hx9s9fNDrrc38n19URgQgMKAAKbcKWlOHlsn1U0QJTjzsOUVevKkScjy8EC2pycypkxBtqenknpPc3Fh+2S6uytl1RPkeXXOu+/5efT8K4GY3O/kOqdl/kluBG7e3c4/CY6mwFEMXSj0oZkA+gA3cXWjVDwmav+1EfEY1Pu1kQR0arxC768IDP/M8t4npMUogV7ugic1T0qdisiQy53ATpns5Gbn35O73dU1Hfb2Cqa2HR0TGbAphs4rcoqdE/AJ0oGBRUoxcmqkvml/Uup8zJyv2z5tWimmTStlKp3moRsEz4XNPEeEl4TjyCdHUNZdxpQpuZlZbLtHHdMUrt3ndqP1SitT3pWnKlF3ro6VY6UCMDvP7GRqntT5vkv7WNZ465VWtF9rV0o046egtVxuweFbh9F6RcomP/75cTS914TOjyRwU99jnx3Dsc+OofMjCboEewIzvdJAgI5PgG54p4F5DPZf3S/1+UjKmKf+xz8/jq6bXew8nR91oulSU58s99Sn7LB9xgyku7oiz8cHRYGB2OrnhxwvL6bUiwIDkevtjTwfH6V4Ou+Cp2Q5iqfLE9n4x7ISxEmhp7u6ItfbmylxHtpUdIZX/HxSHB2P9iMlz0+Fk8+RV9jbs8Q5VVPc5HXpVSn7WFtbpu7p8ammPZ45AfSBTQC9n5v4X1//DRNST8Au7QR+++e/PeKre7Q20oDOK3Q+hs5PTZMrbZp+plyXPVapahwNBvjnm1MiHGW3Uwydj4PTFDPKaOenrRHgHR0TGdj5ueIEZj4rPTCwSGneOC1TNjyf7Obrm89c7RQ7p/cUN58+vYxBncAeElLFstz1g+bCZ80MNF9uZqqYpopR3Jzc1weuH0DHhx3Yd2kfmwNORV4qTlag+XIzqk5XMRf77nO72Vx1KkpDFdsooa3jWge6bnbh+OfHceTWEZbYRir6yK0jOHLrCDqudeDop0fR/UU3U8ttV9sYkPlsdZqeRtnsrVda0Xa1jYG56+MuHLl1RMp452LhpLiZK79n+lvHtQ6m9o/cOsJAz2e5N7zdgKlrp+IXfsZIdDZCsa8Hg/hWPz8G8XxfXxQHB7NGUKeYOsXXCaC8Audd56TcySVOkCbFTyqfYM5PY8vy8GCZ77RMrn5S8zTdjX/ADEGcj9/zypwvQMM/TIZ/Whv/lDj+4TMUc0+dPJnF0Fdqa2ODUOiDNgH0fm5iyenP2QNX1N1GItAlhZ4EO7tUWFpGMFVNylqVG116XnmsLI4e22cAoGogQA9kIZjzT0mjRDd6Yhqtp1g5vZJLnZ+HTolw5Br39y9gapvgTNtJbZP69vcvYNPZqNEAgWLpwcFSARmKn0sFZSSF/vzzdaxSnNUce6wtXotjnx1DyfESpsib3mtisOu80Yl9l/axxDBySe+7tI/NUe/8qBPFx6QnsvHPIycFT6722rO1LEZNU9COfCKBmzLHSf1SUtuxz46h9Uor9l3ah70X9zLlffD6QRz55AiOfnqUwZ+O1fWx5Irv/KjHrd5TbOb458fR/UU3Az95ITo/6mSDmc4bnWyqW9sHbej6uIu5+bs+7lJS9k3vSQo9vCQcDtPNpeehPz0RZdOnI9PdHQX+/ijw90eOl5cE9KAgFAcFMZWe5+OjNFc929OTQZUAS2DmgU4KmpQ8TVcjhZ7t6cmAzMfhaV9+Whol4MlL0tLceTo+X5UudfJkVlGOAE3H41U4FcWhPvwDXviCNPREN/IWRBobI1pTU8TQB2kC6P3cRHK3t7//34/4yh69jTSga2hoQF//CZibZ8HWNrlfVd7rZpcnyMWwbbxbnge6fKqa/FnmpMbpPV+Xnaq/UWIcudNpmhpBnFQ2ZajTHHR57NzXN59t54FOkCfVTlPaKE7eC/USBAeXsO2k0GfM2I6x1hEwCJ4Lr7BglmlOldv2X93PqqtRoznYBPu6c3WoPVvL6rHT3O3q16vZtLWKkxWofauWPeK08aJU5pWS7CgRrvOjTqVzUXY5qWWKkxO426+14/Ctwzhy6whT5aSYSbHTMchtfuyzY+j+ohvHPjvGgE/Hp0afs+tmF5sHT8c89tkxHLx+UClWz89D91vlx7LcywK8lUBeHBSEXG9vFAYEsPW53t4oDgpCYUAAgzqfAc/HyuVz1kl9k3KnbbzLnoDOu81J+ed6ezP4UhEbOneOlxeDOa2jane82qdCNfLHrMof40rKnX9kK58FT253hb090lxcRJb7fZoAuoqb+NNPP8Ez/w1MSD2Ba7/95jFc3aO1kQh0La2xGDVqM+zs0voUg5GrcppTLin0GM793gttOejlFeKkOu29FeIo4Y1X6Py8cr4qHP8scoI9n61Oldv4qWgEY4I5714neJNLnUBPCp5A7+ubj6CgYiWlHhxcgpkzyxEQUIjnntuNic5J0Js6B5YhExFeEo7uL7qx6+wulilOSWJNl5oYaKngDNU2pwpqdeelIjPNl5tZWVaqxkYFaAjsBHUC9+Fbh9F+rZ0lnx28fpApaopnd97oZAOAro+7lDLiKWZOqv7IJ0dw+NZhtF2VCsJQ/+4vuiWgf3qMQf/QzUOSou9Jouv4sIMl41HC3qGbh9D9RTeOfNKr+rs+7mL70dS1qIooVss99Sk7lE2fztzseT4+KAwIwFY/P6bQi4OCsNXPD/m+vsj39UWWhwdLlKMqcqSUCax8gRg+s5130VNMPs3FhUE529OTxdfJtU7rSYGTF4BPziOXvnxqHA0m+Brv5JanUrGkzHmo83F2Pq7Og568EOGjR4sY+hBMAF3FTfz67ncsfv7dD+qbDEcmgC6ALoAugC6ALoA+Ym2gm/jRl/+HCakn4F949jFc2aO3kQj0UaOehKVlDstyV4a6coY7P5WNT4ij7HeKrfN9+WQ4W9tYNgedkt3InU7z0F1c0his+XnoBH5KWJsyJUMpy52vCkfAJnc5rffxyVOaP07ryHVPU9J4d/vUqdsQEFCIoCCpzCvBPDi4BNOnl+GZZ3ayaWuUFEduZoqJN19u7p3X3ZPtvv/qfvYY0fZr7ezxplT1jeZ4U2EagvmeC3vY401pEECJdm1XJRgevnWYAZxc3B3XOnDw+kE25YyATVXhqP+B6wcYoCkZjrnMe5Luum5KAD726TEGZpq/To257bns+fZr7ew6Dt86zGLoLJb+cRe6v+hGy+UW+K3ywy/8jLHZeRSKfT2x1c8PRYGBrNF7mrZGgOenteV4ebHHrZKrneLaeT4+SvXeedc7xeAJ3Nmenn0q0dHAgAYAfGY8H29XFbOnwjN8JjyVnqVYPF9vngBNRWj4h8nw8XP5nPUtbm7M5R6qoyNc7kMwAXQVNzG3+xNMSD2B0L3vP4Yre/Q2EoGuozOuJykurc+0NT4WTkrcwWETU+cEaV6J89PT6NGolNEuf9Y5gXzSpGSmyKkKHD9tjZQ7PeuckuC8vXOV5qHzSWyk2PlpadSfVDhlxFPiHMXG+fdTp25jSXYEcWqzZlXAz28rFi5sgP3kZFZYJmF3Arq/6GYKuvlyM1PJVISFpph1XOtghVga3mlgD1rhn0NOBWn46my1b9VKT1KjOegf9WaR8wqbgMo/qIUGChTTPnTzEFrfb2X78VPeaO46HYdgTAqdMtUpe572o4exUEY7HYfi6jRooKlrlIRH0+kiyiLw1AwLJDgZItP5KeyYO5cluhUHB2Pb1KkoCgxkMXSai14UGMhgTEVoKCbOx7P5B7wQnHlQ809xI9VNJWRJcROs+TKxpMT56WsEdoI9wZwS9aiwDMGanx8vz3wnYNODX0i501x0mpdO6+gYkcbGorDMEEwAXcVNDCqWyrye/ex/HsOVPXobiUA3NLTqeXzqZgZveT12W9sYprT5zHfelS5vcqjzSXB8rXZViXA0fc3VNZ0Bn0BO0KepauQ654u+EMQDA4vY9DVyxxPMaRDg6ZmNadNKmZudrwhHD17pzWqXgD5jxnbMmLEds2ZVYP78XZg9uxLmNhugN3UO/NbNRM0bNUz5tl5pxe5zu9H1cZdSkhpfva3pUhO6Pu5iZVJ3nd2FunN1DPS1Z2tZNnvr+60MyI3vNkpzt99rYvDt+LCDzRGn8q2UmU6lX+kpawRqcovTFDQlF3yPaj/yiQRsympnnoCe89HggPajx60e//w48wRQIRua507eAyo403WziyXF+a/2V0qKKw4ORvnMmUyZFwcFMYCTYs/29ES+ry9zvVNSGgGeV8yUAU/qm0rJktucrxlPbvetfn4MwjyQqaAMD3pS/OTK3+TgoFTulaa9yeedE9zlT4RL5JQ5udv5MrE89Cn7fYubGyKtrBBpZSWS4oZoAuiym/j5H+9gQqpUHe5///rdY7q6R2sjEegUQ7e1TYaVVaQSpP8/e18eVtV5bs+gDAKCA0EiAoKEwQEVRUBEnGqaWJu2N02apIlRMYpxwCgogogiMgiIoqKIKKIiiCDFOMQYo3GMMTHG4d6b++ttc3uboW1i29wmbe36/bHP+njP5hyCmqiQ/T3P95xz9t5nn33O5mF9633Xu96W1q/Nfc15HFm6eW36bFWeJnPnLFPjc9q+UsnOXLkMsxPkZbc15tJZM07jGFmLTkBmKF2q2gnaDMnzOdm4fIyNzVXAzvw5GXp8fAGio7Px4x9vhX/wAjjEjIfnGH88t+I51Fyuwabjm1D3gVY+VvZmmWKh5W+VY++7e1VdeuW5Si2E/la5MothV7ZNxzcphl52sgwlR0vMvNH3XNqjLGSrL1Wr8jWpHJcqdXZe23F2hwqv85iG6w3KGY7AXH+1XtWT116uRf3VegXorGNnyJyfy3My1M/8Ok1oZDldw/UG1F+tx4HrB3Dg+gHlFvdSwUsIHtML8x5xwKIAXxTEx2NVVBRyYmNVaD1n5EjF0FmDTpU7c+kEdRkqZ46cgL48IqJFzfni/v2ROWyYei0Zv3SKY6idQM1QuzyPXARIm9jlERFmjF7awMp+6guCzBXusjUrS9oI7AR+budnTndzQ6KdnQHobRwGoOtuYnrDFfilNGFW1cX7dGX3frQ3QLezs4OTkxc8PBbDy2suevVKQGDgfAXC3t4zEBg4Hz4+s0ztT5uBmo++vrPh7T3DLF8u683J0oODF6rHsLAUBAbONwN1AvjgwekYODBV5dLZdEU6uBHQ9Y5vkplTxEZ2TkMYhti5jzlyS69HjsxRjnDMo8fG5iinuPHji/HYY5tU2ZrjSK1sLe9AHrae2oodZ3eg8UajCqGThZJ577q4S3m577m0B+VvlWPzic0oOVqCspNl2HZ6GzYe24iyNzXhXMnREhQfLsaWE1uw++LuZoOai5rVKu1klbObEJ3xuL3v7VXWrnUf1GnpgIu7VRkb98te6HVX6pT4TYI5Q/CsY6+70mwRSzMbsngC/Z5LexS7ZxSD10uxXcXpCkS9EIU+kV2RFOKM5YNCkTlsGNaMHo3CMWMUgOfGxirgzo6Oxorhw83K2wiYUszGcDvBWAKy7KtOtk6wJ9PXi9xk2JyfI0vd0gcPVkY1+oWA9H1nPbwEa2lAo8+p8xiWudEZTgK8LFtjDt0IubdtGIAubuKtW/9S4fbXrn4/wu1A+wN0GxsbODh4wsXlFTz8cBJ69nwRvXvPVEp0iuJk3lwCvsyv68PxFNM1+7YnKVZPEGceXfZDp0PckCHLzMLwNJEh46awTe8WJ93dmCcnE5d16HR7kwsDCfRazjxHMHUNyGNjcxWgs9PapEmb4R+cBMeRmvXr1NypqPugDsv3LMfud7QwdekbpVre/Fylcl2j6QrtX2kWQ9V76Rulmpr9Dc32teS1EiWa231xt2rHSgZN0xo2WyHrJRBznxK9mYBdgfm7zWDP/Ls8Zu97e80AnY5y3E+Bm7KDNQnl+Fl0r6u5XIO6K3UK5OU5KexLWJOA0HEPY36wE5ID/ZATG4uUsDCsjolBflwcVkZGIjc21kzlvjwiQtWkS0U8a9GluE0q0Jkbp1mNVMaT4TMkL0Gd5+EjTWgYstezdSmyk0p6ArkU0Mle7frubtJwRirjmTcnS5/bt69aPBjGMrc3DEA33cTf/vFL/Lz0DPxSmhC09FV8+fU/7vMV3rvR3gDd3t4eTk5e6NkzDd7e801OcYkIDJyvmDnBnABvHnrXlO7u7s+1KHMjeAcGzleMnWVqdImjI5y+r/mQIctUmJ2Kd72RDEPnZN9Ut7MEjUyduXWZG2d4nUAtz0Mw5yPfQwDXA/rEiSWIjc2Fh9dUOI5sbs5CJzbmkstPlSvQo3Ct+lI1dl7YifJT5UoRX3ayTAH71lNbtZaqprn+yHpsO71NHVv3QZ0Kk+9+Z7cCT7rSSetX5qoJ9gy3131Qp0Lpe9/diwPXD5iFyGkCQwW6ZOe7L+7WjGU+qFMLBzOlu8lulsp25VonbGhZFifBfeeFnRj2zDD4RrubrF81IF4VFYX8uDjkxsZiVVQUisaOVXaweaNGqZA7892Zw4Yphi07sEkGTva9bMgQLAwOVup47mfYXR5HQCfTJxPXT70QT0YApJ88Q+qSwUvwJuvWi+f0YXqWr1EUJ61fjRz67Q0D0E03cWrFBfilNCEk7RDq3vnoPl/dvR3tDdDt7OyU9aufXzJ69nxRdUQLCkpSTDs4eKEKt3M7QTogYJ5aAOjd4ZrL1RKVhzuZuXSGYx/yoUMzVHvUsLAUDB6crkCdQjkpapO5cZamSXAmmydrJ4gzRy7D7LGxOQrIuV+G2cnQpSiOOfQf/WiLmfXrvA3zsO/KPmTvy1asduOxjcoBrvFGo8pJ175fq7U+PacJ5VhzXnmuUgnfWL/OUDv3sbFJ/bV6M792gjPz4ARbhsRrL9cqq9YD1w8015Rfq1fAKsvI6CgnAZ0Lif1X96soBKMA/Gzmx1VoXrB0usvJczIU33ijETMKZiB4TC/MD3ZCakgA8kaNQkpYGFZFRamwe87IkcrHnWVrzKVnDB2qwJ7gTEBdFRWFJQMGmAnmyLRXRkaqBcGK4cPNQu1cJBDQ6RvPBYBk9BTV6cPwksGzDp0snGF2Cub0/deTLKjbZZ06w+5z/P0VQ+eigc1ZDEBv2zAA3XQTi4/9B/xSmhCz+vUO3VnN0mhPgG5rawt7e3u4uvZGjx5L4eOzwEzZznpzDcwTW4TaJbDzkcYzUhhHwA8KWqDeK2vRJQtn7blk5SEhixARsVzVoLOnOUPlsr85Q/AS3PVheObWpXqdJWkUxzHf3mwkk2PGzCVDZw69p89LcB71AwyfMlozhzmulZ/VX6vH/qv7sfXUVtXwhKF2NiphIxeK3za+vlEZypS9WaYWAltPbcWWE1tQcUbLye+/uh87L+zUvN9N56v7oE6Vk8myNZabkbUTgFUtuUlhXn+t3qyMjIp0NnORoXEpkKu/Wo+G6w3mdegmBT1Zee3lWpX317P+husN6pqqL1VrKvcYD7wS5oK8EVrIOyc2FmtGj1YmM4VjxijQzomNxfKICBVuJ5BToU47WE5ZfsbnrF9PHzxYnYcKekYIGHbnlKyf7yGgy5I3aQcrTW4I4LIuXTaQkUxcsnGG25lTp8JdlqwtHTRItU816tBvbxiAbrqJX379D0Sueg1+KU1oePd/7vPV3dvRngCdoE6G/vDDSfD2nmHWIa05jJ5oFkLXh9VlGF7WoXMRIOvQGXpnKJ6gTrEbQZymMeHhaao1KnugR0Qsx8CBqQq89R3VZMvTkSNzzMRyErj1vc4Znh81Kk/l0MneycpZrjZmTCHi4vIRG5uDH/94K3yD5sMpdgIe/kE/TM2diqq3q7B6/2rsfU8LY1ecrkD91fpm9mzqGc5+4QyjU71OY5myN7XQ+9ZTW1F5vhKlx7XWqVwEbDmxBZtPbEbV25qTG7umEcQJ5HUf1CkQrr9Wr66l/lq9KjNj6Lz2cq2qW1c59MvmbFqFzU0GM1wEMGIgS9poMLPn0h4F7mTiXIBIYG+80Ygp2VMQOlbLoaf080fOyJFYOmgQVsfEoGjsWGSNGIFcU4e17Oho5MfFmangyaYJrmTIUskuAVbmthliTx04UOXiCfZ6sxm+n4sI2b5VhvRl21WK6Zg3nx8Y2KJBDI1k0sLDzdTuerc4grnsviZBnZ/5YpcuBqDfxjAA3XQTP/z0LxiQcRh+KU04fuOT+3x193a0N0Dv3LkzXF17o2fPdPj7pwjlerN9q94ohuBMK1hrdeiSydNQhiDOc3BS9Mb8eXDwQjM1O8vVwsJSFHDrzWRoGDN4cLpSsuvNZoYPX4G4uHyzRivNJWm5Zrl15tDj4wvOUqehAAAgAElEQVRMYrgcFW6Pjy9Qc9KkzVoOvdc0OMVOwMBfjFD5byq/K85UKCZOAGcjE7rGsTc6c+o7zu5A+VuamQyd4spOlik72crzlVh/ZL0mknuzTJW9ceFAFblZG1RTZ7MD1w+ofDsBteZyjWLiLFerv6q9thQap5Cu4XqDeqx9v1a9j6Av8+myLSsXAioqIEL8W09tVTn0V0JdkB2hAW5ObKwCcT5nK1W2T6Ut7KqoKBVOZ8ic4M7cOgVjBGEJ9EsGDFBAnzF0KLJGjMCyIUNUuH7JgAEqJC+V8GT3DLdLpzqCqzSXIQvnfhrU0IaWde4Moetr02WXNTnJ0KXK3Qi5t30YgH7zJr78+h+IWa2p23+0/hT+eetf9/vy7ulob4CugXpPuLklo1+/NGHnmqjy3vrWpzSKkXXo8rl+ajl5TeVuHoJPMitZk57sBPT+/Reb1Z7LsjWWssmQO1XqNJEZPDhdKdvj4vIVeMv8OXPnLE1jaF6G3OPjCxToE9hZhx4Xl69U7g4x4+E/KQxzSuag8UYjyk+Vm9VeqzD2e3ubleAC9CrPVyogpzCu6kKVKlurOFOh2Hj5qXLFztmjnH3Id1/crYCy/lq9ihJQ5MbrqLlco8CYIXLm0OmtLoFXzprLNThw/YDGzk1ALM8j8/I8b83lGjRcb1B5e30YX86nlj2FR+K9kBTijGX9H0HRuHHIiY1FflycYuUF8fHINQF7flycYtIEc5a0ZQwdqmrIyZ5lG1QpeJNlayuGD1cLAbJ9hvG5KMgcNszMBlYq4vUqdxnyJxOnop2MXQI6Wbmscydzl8BOYxoazVDlPi8goEUO3VC5t20YgH7zJspO/pfKn//hL98PMxk52hOga+H2zujatQ88PdPh55es2Dn7oZOdaww7qYUvOwFfMniCNnPsBHO+XwriWKomHeIokGNYnYBN33Xaskp1u2zCwoYqNJuhU1xMzGqMGpVnZhoTE7MacXH5Znl1ydDZ/5ygHhOzGmPGFKocelxcPiZPLkNcXD66eU+H86iJGD9vsgpB11yuwc4LO1UemWFsithkedj2s9tRea5SgbK0emV4fsuJLdh+djv2XdmnSt12XdxltjCgExud2Wou1yimzYUFgZZiOQI2r4ehdwIvFwicfN1wvUEdqwdoAjiV7wy7N95oNDueuXcuMhpvNKLiTAWGPD0EvtHuWDTADSVjRmF1TIwyl8mOjkbeqFHqMW/UKFV/Tgc51qLzkYBMVbrsT04Alpaw+vpzmtTwPPo8Oo+VYXnZhnV5RIQK/TPsz/y5NJmh+l02jpE5dgI1WfsCkTef7eur+qCzZG26lxeme3kZOfTbHAag37yJJfvfh19KE/IOX7/fl3VfhgHoBqAbgG4AugHoBqC32yFvYu6h6/BLacLyxg/u92Xdl9HeAN3e3h4ODp5wc1uEfv3SzBqyyEmXNzZaCQycbxZqt9achaAeErJInYOgzm1BQQtUPTq7psmc+oABSxAcvFCBOoVzVK7TPCY6OluBPXPow4ZlmpnESJtXgjJr1tmFTarfZa6deXS99StFcf7BSXCKnYCAyQOQvjNd5YK3nd5m5qbG+m+6szH0zlx6+alyVJ7X/No3Hd+kwvA7zu7AlhNbsOHYBlWOVvpGKXZe2Kly8ZwM7zPkXn2pGvXX6putXkVInCVqBHnmzPle2rLqQ+J1H9SZfQYBXi4EuGBg2Zssf5PhfOkPz/n8qufxSLwX5gc7ITM8DCUTJ6pSspyRI5WpTEF8PAri45VzHEVxNJWRynVZWibL2KiIpwhNdlojCC+PiMDKyEgsHTRIhfylMI6AztA+c+gU1VkKwdNhblFISAtrWtn4RZavSUX7vIAAMzEcc+wEetl9bZqrK2bb2xuA3sZhAPrNm9hx5tfwS2nC8+Xn7/dl3ZfRngDdxsZGla2xfap0eJPKdQI4xXDmHdgSldCt2c89UQG6LFGjMI7Kdm4nUDNvToDndpaq0VyGpWWyr3lk5EpVp06PdzLtoUMzFHiTkROUpQBu+PAViI3NNbOP5bHsf062zvnDH25EXFw+evSeAafYCYibNRHlp8qVkp3Mec+lPc1WrCZxmOxFzkfWmzMXXvJaiVK5bz+7HdtOb9MEdec0ZTxr08n0JZuWeXGCLhXmdR9oufy6K3UKUFXd+JXm/Dkd4Swx9L3vmufKZa6dde6sPadHPBcPzNUz7y7PX3m+EjEvxsA3yh3JA7tibVy0AnEq2gngnDmxsRpDNx2TNWIEVsfEKEBfGRlpBtQsKWPtuQR8qWSn/at0oGN5HFk3mTlfLxsyxGwhQdW87OBGhfvC4GClrk8JCzPLsct2q8yny5p0KtrZ2EWCPRn6NC8vTDMY+m0PA9Bv3sTZ//oD/FKaEJd3/H5f1n0Z7Q3Q7ezs0KlTD7i5JSMgYAm8vWeYNVihSE4K4vQhdn0bVcnQuTig0l1rzpJkZjBD9zjWmBPMGWpnv3K9f3tExHLl8z5wYKoKtcsSNTJ0LgBoBNNcW56j3OCiolaZgXlsbI5pm3Ycy9Skscy4cWsRE7MakyeXKYbe90f9kbItBY03GlFytES1Ta2/Wq9C5wyF006VLHz3xd1a8xST6K3szTJV0rbt9DbsfXev1l7V5ARXdUFrucqWqmylSvDmAoKhbQKuAtn39qpjKV7TM2WlRNcJ46QqXp1X1K/vu7IPOy/sVAsK1rNLT3guNGQZHdn9tNxpiqGnhgSgePx4ZEdHq7apq2NikDNyJFbHxKhwPPuj01xGMnXJmAnCUuUuXeCWDhpkZgG7PCICK4YPV0YyFMXJkLzew132ZJetWRnyJ0hTBLc8IkKJ4djJzZqxDC1hWXcumbp0kSPQLwgKwotduhgq99sYDxygZ2RktLhJwcHBav/f/vY3JCYmonv37nBxccFPf/pTfPzx7fuuy5v41n9+Br+UJkwoPPFtfpV2M9oboHfu3Blubj7w9s6Ev3+KyRgmUczZZsAtleyW6s2lr7ve953MnPl0+rjTAS4sLEWZzBDYGWYfODBV5cVpGkPQZ8idOXa6u8XErMaQIcuserMz5M46dWkBK7urMdROhk9lO4H98cdLMWpUHrp5T4fL6EcR//IPVTMUKs8rz1WqOmyWr7FnuGynyh7izJ9vPbVVNW/ZfnY7Ks9XYsuJLdhxdod27gtVmqvcea23es3lGuy6uMuMATOXzSYojA5IVzbmwRlGZxqAzVII+PqyNX2oXJ3DxP5lHl01hLnSHKonQ+cCgfn9yvOVGPniSPjGeGBRfzcUxUUpe1cyc7J0OsXljBypeqKzDp1z2ZAhZrl0gjRD29wuzWBkRzSyc06WxVFBT4vYtPBwpaynkY3Mp8sFhL6FasbQoWbGMpyyPzpr0AnWbJtKIJdlbaxt1zN0Q+XetvFAAnr//v3x+9//Xs3PPvtM7Z85cyb69OmD119/HRcvXkRUVBRiYmJu+3PkTTxtAvTo7GP417++XyVrQPsDdBrLuLklw98/pUUfdIrjJDiz7MxSVzU9oLMxS7O5jFaqxs5qLEsbODBVhd+lzevAgalmIXd9bTqtXWXTFZrExMbmqEWAtHKNiVmNsWOLlPht1Kg8xcQZgh8xIksBOB3hWI8+evQajB1bhLFjizBhwjrExxdg8uQy9Ok3D44jJ6DPDx/Bsl3L0HijEcWHi1U4vPJcpZnPec3lGux+R7NxZa9y1qKXn9K6rlWcqdDc40x2sOzgRitYWfJGtsxQPkFVNVkxOcTRLpbbmfNmbTrD8bIOXebN9QCuAF44zVH0R4Maft/qS9WKofMYnlNGEBpvNGJa3jRl/ZoZHoZ1EyZobnGm0PvqmBisGT3aLOQua9GZu84aMcKsXpxhdYrQpI0rGTXZPFk+Q/hk5BK0uWjg+Qn+MnxPIxmG02kPu8BUgsZcugzLE8QXhYQogRybsOjFcLR6JbDzGO6b4++PKc7ORsj9NsYDCejh4eEW933xxRfo3Lkzamtr1bbr16/DxsYGZ8+eva3PkTfxiy//rnqg/+mvLQGto4/2BOi2traqfaqXVwYCAlJVdzUpdJNKdsnO9cxd/1rm1amUJ0snkBPUQ0OTzZqzELxZn86QfHh4mgLuESOyEBqarFTu9G6n8I3e7RTMyRx6XFy+Uslzf2xssxhOsvyYmNWIjy/AuHFFCtjpFDd69BpMmrQZMTGr4f7Qi3AcOQHRCWOVCI79yWvf11qmEnzZoKXyfKVqUUpWvve9vSg7WYYtJ7YoUR1NZTaf2IzqS9WoOF2Brae2mrVIZT34rou7lApe5rPpoa43jmm43qCEdNIxju8loBPwLYnjDlw/oMR3XDQwX05DmT2X9iiDm7oP6tR5uQCR9eulx0ubVe793VA8Oga5phw5Q+1qCoaeNWKEYs9k5QydE2RXRkaagavsmCZBmiAua89l+J7n1L9m2J6GMvrWrNJZjvXntIYlmEufdxlyJztnrTnZOevPKZQj2C8dNAhTPT0x1dMTz9rbGwz9NsYDCehdunSBt7c3+vbti2eeeQa/+c1vAACvv/46bGxs8Pnnn5u9x9fXF4WFhbf1OfImvvvbz+GX0oTBmUcMhv6AAzpBXVO5awydOXQydU3k1rIpizVXOBlil8Y0Wph9gRLVSWW7lldfoFTtgwYtRXDwQkRELFcAT0BnaH3w4HQMGLAEQ4YsQ2hoMkJDk1UunA1WCPqye1oze89V4D169BoF/nSLY3kbneT4nEI4AvqECesQF5ePxx8vhU/gXDjEjIfPxCBlLFNxukK1S9XPug/qFHtlyJ1MvOKMZv9acVoLt1ecqVCh99Ljphy6KTxPdTzD2czJy9IzitcoSJPNVAjKBHu2XZUqeArn6q/Vt2jSYgn4D1w/oM7FZjD1V+uVbmDflX04cP1Ac0MXC7n7p5Y9hcC4npgf7IS0kH7Y9NhjZjn07OhoM2CXhjMEY8mkVwwfrhhz1ogRZmVrDJdT1JY+eDBWRUWpxQND8lkjRijg5yQT57l5HqrUZec1Ppe5+kUhIUr5zpy6tHuV/dClMC5JF3on4BPQCfT0fX/e0REzbWzgYWtrAHobxgMH6K+++ipqampw+fJlHD58GNHR0fD19cWf//xn7Nq1Cw4ODi3eM3z4cCQnJ7d63q+++go3b95U86OPPlI3MavpKvxSmvBixYXv6ms90ONOAb213/R2xu0Cur29PZyde8HLKwM+Pq+ohix6li3boFoCcuntLgV1sswtKGgBQkIWKWAPC0tR/c9ZnkYAHzgwVeXXuW/IkGWIilqlhHJk5hTTyfaoLDOToXOy8OjobNUGNTY212I3NubHZXnauHFFqvacwB4bm4vJk8sQFbUKHr2mwXnURIyYGo/Kc5UKwCrPVyqVu1Sis4Ss+lI1tp3ehh1nd2Db6W1Yf2Q9So+XYsuJLai6UKUEcTym/FS5Fqo3ucPxkWVwbKnKkDdD4czrM9wtWbhs6cq6dOUUJwDcUvmaBHQCOL8rO8BJP3jm8pk31/dDb7zRiPK3yjXrV1NzlsLYSKwZPVoxcVmmRlGczKczfM4QeVp4uBnbJriTMTNMz/csj4hQZWkEd7J+5uQleHPBkDF0KLKjo5XVLMPtDP3LqACZurSFpVMcXzPszlw/u7Exly593Rfocuhz/P2xZMAAvNizJ17s2dNon3qb44EDdP34/PPP0bVrV2zduvWuAN2S2M7Gxgaf/OFPCFxyEH4pTSg7+V/f1dd4oMedArq13/ReMPROnXrAxWWhRVEcAVyCNXPoslGLbJ/KEDtL3WTJmwR2ht7ZD51z6NAMM8vX8PA0sxK28PA0VZZGII6MXInw8DQF+lFRq0ygnaNU65Z6nLMGfdy4InUubiegjxqVp/Ln8fEFGDu2SAH6+PHFGDUqD48/Xoo+/ebBIWY8fB8LwbyN89BwvUHluitOm3u5s3RMtjJlCJ4lbDsv7FTd1QiSZW+WofKcJpqrOFOh2D0XEBSbVb1dpYBZbb+q1aHztQRz7qdIjcp4sm5LdeL6qfd7p5ENFxlSWMd6dUse8Zw/T/+5YujL+j+C4vHjsTomRpnHFMTHm4Xf8+PilDCO1q9k12x6Iv3VJWMmu5Y5dCrfCeQMxbNNKzuwye5rMpfOxi7czygA35MdHa1y6dKGlgCePniwYuL6fugEbQrluI0MnjawBPskUx16op2dEXJv43jgAR0Ahg0bhsWLF99VyN0am/ziiy/w1OYz8EtpwtObby8P31FGe2Lotra2sLW1VTl0S3XoPj6zVKidrJvg3Qz2iWYqdy4GZBMXydJl+J1h90GDliqVOx3iGI6XIjlZl86cOrutyXapVKhLtTqBnvv5PgJ4RMRyxMbmmrnI6cvV4uMLzNh9XFw+nniiHCNH5sDDayqcYrUcOhl4zeUaVJzRxGvbz243U4DvvLBTCdSYQ644XaFC5VUXqrDx2EaUnSzDzgs7sfPCTiWIY/OX3Rd3K2c5fp7MYbMlqdpuqoGnaxs7v0kFPGvGCeiWGLQsL7MWgt/7rnZ+RidUlML0eXrwl81Zyk+VY+jTQ+EbpeXQ18QMU97tBOoVw4crlzg6xUlwZ8id7Jn9zwmwMl9NcCbwErwJzlLBztI1KuVlL3S5IJDmNSxVkwK8FcOHY3H//ircLhuwUAzH0DuFbXSKk+I3lqxR5U6mPsvHB2nh4Ujo1QsJvXoZDP02xwMP6H/5y1/QrVs3FBcXK1Hcvn371P4bN27AxubuRHG//uyv8EtpQsCSg7j6u/Z/U293tLccuo2NDTp16gFX14Xw91+scugyD07WTmGbPtzu7T3DrO2qHviZQ6fTHEGdfc+lsl0/2X2NpjIsTRs+fIVi6gRmNmQh+46JWW3GxClyk/3OY2JWq5r2oUMzLLZTHT16jcq1UyDXXIdepIRxGkMfB//HQ5FcnozGG41aJzRTbXjN5Rpl/Vp1oUrl0Qlyu9/ZrQE2a8zfrkLpG6Wq8xr3scXqjrM7sPsdDdDZpY3Oc8x7k6HT/pXiOObapcFM1dtVWtnZlTrFnnk+PfjSAY5CO0sKeJaqkaHXfVBncXFgjf2/kP0C/Ed2Q1KIM9JC+2HdhAlmufEW+XRRukaBHAVr7GMu2TRD3rJ2XNq2SsadNWIEVkZGYnVMjFK+6/utE6QJ6GzYwsWDdKZbOmgQVkVFKSbOa1gxfDiecXMzy5UvHTRIgTe3MRwvRXD6nDrfw9z7dDc3JNrZGYDexvHAAforr7yCEydO4Ne//jVOnz6N8ePHo2fPnvj0008BaGVrvr6+OH78OC5evIjo6GhER0ff9ufob+IvtpxVpWtGtzXz8aABur29PdzcfFQOXV+2ZskGVrOHTWxR3ibL12TrVAnkFNcx5B4WlqKc4RhyHzw43cxchlav/fsvVox8yJBlipGTeVMwx/IzGWrncVSyy9A6Z1TUKkRELFfsnQp5yfZpJMMa9tGj1+CJJ8oRHZ2tcugxM8YrC9bay7XYcXYHdl3cZebmVnWhSrFmit42n9iMLSe2YOPrG7Hp+CaUvFaC7We3Y/OJzWruOLtD63lu6n1Ohs6ubnvfbe7iVnWhSrFsms2QcVOBr9qdXmsOzTPkLhkzw+XStpV5eAnwdL6rvlSt6uHrrtSpsL5k89IylrXnlecr0XijEWUnyzDoyUFK5V4QM1yVqUkfd4bgs0aMUAxelq0RKJnPJlumhasEeYJ5Wni4qjFfNmSIMqmhCI7hd/kZ9GDneWg+Q1U9wZ2LBe5j+J37mSeXteTSzpUgTXU7mbs0kCFLT/T1RerAgYaX+x2OBw7Qn3rqKXh7e8PBwQG9e/fGU089hQ8//FDtp7FMt27d0KVLF/zkJz/B73//+9v+HP1NPPkfn8IvpQkDMw7jlgHoZuNBA3QbGxs4Oj4Ed/cUBASkwstrOry9Z6g8eO/eM82U63SEk8DPUjeNyc9WpW1s7iKbtRDYCeicDK8zxE4Ve3h4mmrQIlumModOIxjZ/pT5cwI82bZk5Qytc7LZC+vYJUOnwxxL1sjMx40rUjl1tk91ip0A/8dDkV6lebmXvFaCzSc2Y9+VfSh7s0yZp7CErfZyLcpPlaP4UDE2n9iMkqMl2Hhso3KD23R8E7ac2IK8hjzkNeSh4nQFtp3eprnJXajSGreYQJ0LCC4Udr+zW4Fo3Qd1qL5UrfzUybxZvkbAJdDKpjEtwu0mIFcRAAHMUlnPxcP+q/uba9Sv1rcwqOF2/banM55G8JheSApxxvJBodjw6KNYHRODzGHDUDR2rFl/dFrCrhk9WonWCKySjUv3NlmHLpu0sM6cYMwwO3Pq0imOIM6wO8PwkunLUjYye+b4WTK3ZMAAVcLGhizclhwa2qJNqhTFsRc6H2f7+irVO1k9neJm29sbOfQ2jgcO0O/V0N/Ei//9J/ilNCE88wg+//L7VYtuALoB6AagG4BuALoB6O126G/i3/95C9HZx+CX0oQnNrz1vQq7tzdAt7Ozg6trb3h7Z8LLq9l/Xdah9+4908xMRnZkk6BOENeXsrHbGlXuslkLATwsLEWVoYWHp6l9Q4Ysw6BBSxEamqzK2YYMWabc4qhcp1qdzVWYK2e4fNiwTOUIR2CXoXaK5gjsLH2Ljs7GuHFFKsQfHZ2tatDHjClEfHwBJk4sQWxsDjx6TTNZvz6GfVf2qaYpuy/uxtZTW1XdOcPldVfqsPud3ag4o5nE0Dhm84nNKD5UrARxm09sRtHBIhQdLMKOszs0O1iTcr7yfKUWejfl0hlO3/3ObrOwNo1jai/Xqvaq0iSGwK2vTZd5cSWCM+XCKeajWQzz8QzzU3TH8LwU0vG90pp218VdKkxfdrIMw54ZhoDYHkge2BUbxsaZhdWXR0SosHuOcInLGjHCTHmub4MqVe1Sdc7XBHSWnmUOG6bU6Azty0YssmUq68f1deeybSoXAvpa9MX9+yN14ECz0DvBnCI41pUzJ05gZ+6c4XeG5Gf7+mLJgAGY4e2NGd7ehijuNocB6OIm0tPdL6UJf/v7P+/j1d3b0d4A3dbWVjF0X99FJlFcSwZuqfacjJzALnPqFNSx1I190Zu7riUhNDQZ/fsvVv3QZT06wZztUMnSeQw7rLG7GkFY5sYJ7txOBs59NJaRHu8REcsV82fd+tixRQgMnG+mgGfDFirfJ03aDJ/AuXAe9QMETB6AVbWrUH+1HoUHC5UDHMVvdIZjCdnedzV1e9mbZSh/q1yZx3ASxLee2mq2jXP3O1qZW/lb5co33qwZyrV6VJypUMr3ug/qsOPsDnUdNZdrlBJeitb0gC7BvuF6gypLY6kc8/KMCrApTeX5Suy6uEuJAhtvNCKrNkstVg5cP6BMbZiPb7zRiMmLJmPAD/ogKcQZ2RHhKBo3ToE6BWpy0jWODFjWhzPHTUYtS9hkXbjsa04AZt6ceXXZBpUGNcyjL+7f36yr28rISOUdLz+LLnJcXNAalmyddecsY1sgmLYsTaPyfY6/P2b27q3y6bI+3Shbu7NhALq4ib/5w5cK0JfWv48//+3v9/EK791oT4Cu+bh3hqtrb3h6psPbe75SrVsCbmkaI9XwvXvPVMewxE1vBcvQO4VxrEGX4faQkEXK55015QMGLFFsnE1aBgxYgoiI5QgPT0NExHIF6AR/ydgJ9GTkVMUT1OkBz9cUxvGcsbG5CAtLwZgxhZg8uQyDBi01a70aHZ2NH/5wIyIjV8L9oRfhMvpRjJk7SZWp7buyD6VvlCpmXnlOqxnfcXYH9r63V4ncKIrbemorNr6+EUUHi7DxdY2hV56vRMnREpQcLcGWE1tQcboCuy7u0vqmm861/ex2xXKVzasprF5zucasnlwZxpjc4aiAr71ca+7NLkRxBHOGxmWnNS4MyNKlFS3NauS58xvz1WcUHy5WCwm65DXeaETegTwMfmow/EZ6IGWQO9bEaMBaEB+vbFlzRo5EdnS0EquRodPEhQyaNd5kw2TPBFA2YCEAy97mMgxPRk2/dk5pHyuFb3SAk21Vea1cUPBzUsLCFDOnd7u+yxrr0ReFhKhQ+qKQEAXks319MdvXV4XfCfbS+tUA9LYPA9B1N7HS1BvdL6UJQ1ccRcO7/3OfrvDejfYE6AR1Wr/6+CxAr14J6NUrQdWSM7zu4zNLAT0BnKyck9tk21XNeCZRmdDQZIZtU9k6deDAVJVrZ/5ctlilAQ1L2FivLsE3KmqVaq8qle0EbBrQyPA8pz6XTrbOcrhBg5Zi1Kg8hIenITBwPiZN2oxJkzZjwoR1CtR7+SXCceQE9PvxIKTuSEXjjUbFqvdc2qPy3WyRShOZDcc2oPR4qQbgb5ah9I1SbDi2QYXdK05XKGZOFr/11FbNYOYtrYSNqnLm0mkby5p09jlnHTq3EbhpDWuprSlz62TPtGzlQoHbWdsuoxBMBVSeq1SLjW2nt6HidIWKAhQeLDTLnTMVMHnRZATG9cQroS5YMbg/1k2YoABUOcOZ6tEJ6NLpTSrO2ZaUYXAq36VlK73TWT5GEJdNXWQZm37RIOvPOZcMGGDWI50ucMzfU1XPDmsMtacOHKiatkiGzjw5wX2Ovz9m+fhgjr8/MocNw7yAALzQvbsCdB4/LyAALzg5Yba9vRFyb+MwAN3CTXz9+scYs+YNBex7zv/mPlzhvRvtDdDt7Ozg7NwLPXumwdt7vipJY205mbgEa4K7BHOCuCaaS1QgLmvaKaoLDl6o2DoBXdais1mLNKKh3zvFcEFBC8x6n0dGrjTrlT5kyDJVnkbWLQGe4XdZv873R0QsR0zMakRGrlT594iI5QgKWoChQzMQF5dvZjf7+OOlGDYsUzH00YmPYueFndh8YjOq3tasWzce24iqC1WqDWrpG6VajfqbZSpnXny4GCVHS5B3IA+lx0tRclQT1K09tBZlb5ZpYH+8VOt/bmL05afKsfe9vappS9XbVah9XyuVk+HzynOVKsY+wIQAACAASURBVBLAjm3Mm1MA13ijEbsv7jYDdpk7p6Ct5nKNSh+Q5dPCVjZnqXq7SvnK735nt2q3WvRqEfa+uxflp8qxsGyhAnZ+x8YbjchtyEXIj0PgP7Ibkgd2xdo4jYkTyBlyl21NZWjdUgh7YXCw6mKmb5giQVeG4un2xpanXDTI9zNvzoUAXxPAM4cNa8HeGaLn4oPXmzpwoFlNOUvYmEOX/uwMryf06qXqz59zd1dGNLN8fJAcGopfenjglx4e+IWtrdGc5TaGAehWbuLf/3kLC2veg19KEyJWHr3HV3dvR3sEdDu7bnB1XQhf30Xo2fNF9OqV0IJ9k61Tza5n6Ay5698je6pLpt6371yEhCxC375zFQtnfnzw4HQEBSUpIR73BwUlISwsRYXNQ0OTERW1SnnADxuW2cI5juBNcKYITrZdZYtVLhYGDVqKyMiVanEwfPgKxMXlY+jQDOUPT+Ans584sUQxdP9JYUgqTULt5VoUvVqEjcc2KvBmkxV6srNNaukbpSg+XIziQ8UoPFiIkqMlytN9/ZH1WHtorQbsJ8uwpnENtp7aqrVXNRnMbDq+CXvf1dgv3emk6G33xd1Yd2SdtggwhbY3Hd+k2Hft+7WKNVdfqlahdDrGyTA8u6ipsLzwZ99zaY+KQnDSJa7iTAXK3ypXavyCXxWg6oIm5Ct6tUilI5hnn7RgEgJieyApxBnL+j+iXOIoVCM4UjlOVk62TEZOxTgBeMmAAaqzGUPafE0gloyagEwbWDZRWRQSokLkFLBxYUFxm6xT13dbY408r4csXTZe0SvVqWynup1zZu/eSOjVC9O8vDC3b19M9/JSgM9Q/PNOTgag38YwAL2Vm/i7z/9PsfSD7//vPby6ezvaE6Db2trC3t4eTk5e8PRMh5fXXMW8pfsbtxGw9cDd7BBnbjZDUNd3Y2MJW3PoXTOaYa9z5tn9/eeI0HySMqKJjc01A97w8DQF5FJEJ0PoZNwy9M68/ODB6Qqg6UTHvP3w4SsQE7Magwenq9arw4Zlqn7osbG5mDBhHYYOzUBXzxfgPOoHiE4Yqwxhyt4sU+HvHWd3oOqC5hJXfqpclaRR2b7p+CYUH9JYevlb5dhwbAOKDhZh9f7V2HhsIzYe24iCpgIF8lwIbDu9TUUC6j6ow5YTWxQokzWXnyrH+iPrUXayDOuOrEPFGS2Mz5z43nf3qvw6m6lIEN9/db/Ks7MEreF6g7KTpac8mf/e9/aqbUwB0HN+35V92HlhpxLQlb6hifyksUzBrwoQ8uMQ9BnRFYv6uyE/urlsjG5xyyMizBzg9KIz5rGZyybI0n1N9kKnuYv0fCeYLwwOVq5xDN/rJ8GXoE/WT5bPz5bv4aJD+rZLP3aycYbaGUanGE4ayszw9sYsHx/M7dsXM7y9kdCrF6Z7eWFx//6qOQvbpxoh97YNA9C/4SYuqtVY+iNLX8UnN/92j67u3o72BOictH59+OEkeHpONQu366clZt5aKF7fW12K4yTr9vWdrULuISGLWhxPcV1YWIoStZGZs3598OB0lU9nKJ25dbLtqKhVio2TnTPnToYv+6nr267GxKxGRMRytfgYN67I5CBXBM8+L2ntUx99BEmbklB9qRo5+3OU41tBU4Hqay7D7htf36g5xB3biA3HNmDdkXUoPV6KTcc3oeBXBSg8WKjm+iPrUfRqEUqPa4yezVrK3izTFgomBrzh2AbFtqsvVasFwfoj61V0oPQNraMbgbviTDNDZ2kaS9HoHld3pU61PmV9+Z5Le1B5Tlu0lL9VrhYt7B7HMr2K01p0gqy98nwlGq43aGV4ps9uvNGIqrc1h7uJcyciMK4n5j3iiLTQfsgbNUq1PqWCXW/DShDNHDYMqQMHmnm2y3pvMmICvux6lj54MJJDQ836pCcFBSmFO0PhC4KCVI6b51wYHKyub1FIiLJ3JUtnDp1pAG6TqnZ5/nkBASqcTrGbZOUsT5vt64tZPj6YFxCgtrPjGidz6AZDb9swAP0bbuI/b/0LT2x4C34pTVh18No9urp7O9oboLMOvWdPjaF7eU1Hr14JCsD5mgDt7T1D7deH5Qn4sn2qDLmzBE62VCUDDw1NVgBNpbwUxdFDPiRkkQqNBwcvxLBhmWo/S84kQA8cmKr83cneGTJnHpzHDxmyTC0WmHPXA/rIkTkID09TBjVDhizDxIklCA9PQ1fPF+AUOwFR08ei/FS5CrdvO70NJUc1UC95rUSZzRBQNxzbgJLXSrCmcQ3WHVmnhd4PFyOvIQ/rj6zHxtc3Iu9AHvIO5KHkaIkmkHujVNWuU0Vf0FSA6kvVWHtorVYSd60e64+sx/oj61VevvJcpYoKFB0sUmF5tlVljfje9/aqxi7Sz53qee5jiL36UrXWXMbUp51tX8vfKldNWQj6ZOq0wy06WISayzXYdHwTNh3fhMYbjVhVuwphPwlD7+GuWBDaBYWxkSq3nTdqlJl6nKI4ffc0giTD3WTABE4JrmTwsoc5QZ2595WRkYots5xMKtHnBwYideBABehS5EaxnP6a9AxfsnMK3/SWr/MCApDo64tEk4GMrD+f4++PqZ6eSAoKQkKvXlgQFIQpPXpgSo8eeK5TJ7xkMPQ2DwPQ23ATj1//BH4pTQhJO4Sv/tHx6tPbG6BrpWs94eq6EN7e8+HpORVeXtMUoOvD715e0+HlNb3FdjJ0PcA3N3eZ3YKpE6SDgxfC13e26rbWv/9isy5tFMRRBR8enoaoqFUICVmkytv06nf2SWcYnoybQjqCtpwMsY8YkWVmWiNr25k3p7guPr4AcXH5GDu2CF5+s+AQMx59fvgIFmxegMpzlSj4VQHyGvJQdrIM64+sV+Vnm09sxroj67DuyDqUHC3B2kNrUXiwEHkNeSh6tQgbjm1AQVMBMvdkovhQsXKKKz5cjLWH1ioFPM+16fgmlJ0sU2Y2Ja+VKIOZ3e/sVgsFRgfKTpah6GARSo6WqFrzzSc2m5WoMQTO+nW2XyW4s/ELPepVWF1MKvt3XtipjG8qTmvd55RBjqkbHXPuB64fQP3VekycMxF+MR6qfWquSZDG3uYEcCk0I2hSIU7luuwnLoGcgMr9ZNNk61xELAoJUZ7sMr/N90oQZp6fDJ4RAPm5DO3r26YS1JNEyF2G2BlmJ5jL/fMDAzHb1xcze/dGoomxSwb/vKMjZtnaGoDexmEAehtu4r/+9S/0X3YYfilNeG7rOfzHx3++B1d470Z7AnRbW1vY2dnBxeVhxdDJyi0xdMnKJdgz5E72bklQRxBnKZu0faWDHJuzhIYmo2/fuSpcz7A7c+hDh2YoA5oBA5aohQDD4IMHpysxG4FaKuAJ6gRyvofHyvw6w/Ja0xfNgY716Xz9+OOlGDgwFV09p8B51A8QkzBOqdPZaGXDsQ3YcGyDCn1vPbVVA3sT6y56Vas7X3dkHTYd34TSN0pReLBQOcSRoRceLMTGYxuR35iPktdKUHiwEFtPbUXVhSpsOLYBlecqVYe3+mv1ynyGIXt+/sbXtfB+1QVNgFZ+qlzlxve+pzV4Ua1ehasc3d3YZa3mcg1q369V6n2ayOy6uEt9NhcQFacrsPPCTlScrlDucCx143YK89Kr0hH4WKBqzpIbqTU0YdczdlGj7Sp7njM3TnCUKnfWdyeHhqq2pARxgrsUyC0MDlY5dIrvCLacBGyGt1MHDlSiODL7RSEhKlcvw/9k6GT50t6VUzq/MYfOSYtXbidrZ9h9lo+PGUN/1t7eYOi3MQxAb+NNzD54TQnk+qUexAe/++I7vsJ7N9oToFti6D17vqiAWU5LzFyCu6X8ugR8iuZka1UybjJ1vtbC7gvUAoALhqCgJNWNjYY0ERHLlTqeRjRUytOulcBOIKeIjsyeAjvaztI3nosAmZtnqJ2MPT6+ALGxWmvVHr0T4BAzDj4Tg5BYnIhtp7chqzZLhczXHlqrQuAbjm1Qvu2FBwtVrjy/MR9FB4uQsz8HuQ25WNO4RmPuJkDnecjUWee+6fgmlL1ZhpKjJai+VI3sfdmqhK32/VqUvVmG3IZcZNVmIXNPJnIbcjVAN3Vh231Ra92659Ie9ShtWfdc2oO6D+pU/nvPpT2aMv5MhQJq1sVvO70N205vUyY4O87uMK+zP16qwvJVF6o0Jm86T8XpCjRcb8Ded/cifkY8/GI8VA59VVSUAkNZJy5tWNMHD1a15JINM3RO5r4oJEQ9l6BKhs7StkUhIcgYOlQxb5rAyBIyafiSHBqqDGjm9u2Lxf37Y27fvmbRAi4cGNaXzFyG2CUjn+Xjg1k+Pso4Rg/gM7y9zYCeID8/MFAd94JJ5W4AetuGAei3cROv/u4mhmW9Br+UJiyseQ//+lfH8Htvj4Du7NwLPXoshafnHBN4TzNj6BLANWCfZpZP59SH6GWPdDZqaQb1RAXqLGNj8xZ6t1PZTvEcm7awsQtD7NJFbsiQZYiKWqWaupB9Dx++wqzhC13mJEMnuPMYyeQJ6MOHr2hhL0uVu/tDL6oc+tZTW5FVm9Vs4fpGqQq3k5HnN+arevOiV4tQ0KSF59c0rkFOfQ5y9ucg70Aechty1cyqzULhwUIUH9bK29YdWYeyk2Uq77797HbsOLsDJUdLNKMZqurfKkfJ0RIUHypGVm0W1jSu0UD6Sp1WxmZqv1pytEQ1bSFwk6FTIFd7uRZ739urPov17TS9IaAzBcBmMvwcls3RCIeTgsHGG41YWLYQQZOC4DPcDYv6uyFn+GDltEaDF5aZ6X3Vaasqc9YEWzJfMnFZfsacOMPt8hxk6akDB6rQ9myRx54XEGCWc58XEICMoUMVO+diglMCu6WSNNaZSxEcw+esMU80XYMUxfGayNDnBQTg2a5dtWkw9NsaBqDf5k187erHiqlP2XYeb/3nZ+0e2NsjoNvaesDF5RWzHDqnfO3tPQM9e76Inj1fNDtGArheQCeBXzJ4AjvV6yxjY0kbw+sUxoWELEJYWIp6ZHieDnK0iJUGNUOGLENYWArCw9OUy5wUw3FKn3geN2jQUoSFpSiAJ/hTKc9QfGTkSowcmYMxYwpNOfRx8J4QiJfXv4wdZ3cgY1cGcvbnKEa98fWNKrS+4dgG5Dbkannzg0UoerUIuQ25yNmfgzWNa5DXkIes2iwU/KoAGbsytHPVa8w9vzEfaw+txer9qxWwbzi2Qeujbip704Mnc9qlx0tReb5SgXjF6QqUHC1B1duaMp2e8MxpV56rxJ5Le5RSvexkmWLy205vU+ctO1mmjHI2n9isTHA2n9is8v20qyV4sxZf5t0ZWZg4ZyICRvXA/GAnpIYEIDs6WtWHp4WHK4MXMmfpuMbwtqwZJ5DqBWgLgoLM8tkEX+bSGX6XOXuG0MnOacPKCMGCoCC1QEgLD0eS6TP4Pn6+NI/Rd1NjflyK35gb5/O5ffsqBs7tZOsS2Gf5+OB5Jycjh34bwwD0O7iJlWd+jb6LmxSwTyx6Exd+/cfv4CrvzTAA3QB0A9ANQDcA3QD0djvu9iZ++OlfsKzhCkLTDylgf6XmPfz2j19+y1f63Y/2BOgUxbm69lYhdw2kpwvAbn6uAfl0BezcLkVzzLXzffoyNxrOMPwue6gz5C7z7AR35tSZYx84MLVFH/WwsBQFxGy3Kh3oqIQnSBP4CeTyfQMGLFEe88zFs1xuwIAlZqK5H/xgPYKDF8Kl+y/hPOoHGDE1HhuObcCaxjUoOliElTUrkbknE9n7ss1qygsPFqL0uFa6tnr/auTsz8GyXcuQdyAP2fuysWLvCmTVZqnHrNosZOzKQOr2VGTVZmFlzUoUHizEqtpVWHtoLfIO5CFnfw4Kmgo0kH6tRCnpNx7bqMrGSo6WoOzNMmw8pi0s9r67F7vf2Y3NJzYr8xsK80rf0ECZnvHbz27XRHimEDn7s5ce1/znt5zYonQCJa+VoOhgEYoPF6Po1SJN0f9aiWo6s+HYBmWLW3iwULO/PVSMhusNmLdhHvo+2hc+w93wSqgLciObVewUvhFsOWUIm4I1ArQETk4CJmu95wcGIiUsTIEvc+WsRZclZ8zPM98u8/BcPPCzuaiQn812p1wMJIeGqmuhMxzz4AyjE6BneHtjZu/eZmp2CdzcN93LC/MDA/FC9+54oXt3w1jmNocB6Hd5Ez//8muk7LusQD1wyUEk117Gjd+3HyV8ewJ0zk6desDFZSEeemguund/QbFwPWh7eU032+bpOVUxeMvPp5vVtUvgl2ydrVX79p2rQJssXhrTsH49IGCemde7XjEfGpqM8PA0xd4J8szNE6jJ8Ank7PRGkKfJDdu1Mi9PY5rIyJWq7/qIEVlwf+hFdIoaA5+JQZhbMhcbj21EZnUm0irTkL0vGwVNBVixdwVW7F2BVbWrkFmtidNKj5ei6GARlmxfgtyGXKyqXYXkrclIr0rHku1LkL4zHQs2L8CCzQuQsSsD6VXpyN6Xjcw9mRqI1+eg8GChlnevz1G58vJT5VjTuAZrGtcguy4bq/evRn5jPnIbclFytESp6Dcc24DqS9VKrFZ2UhOuFb2qRQ22nNiixHd0gqOFbOkbmkaAtfUbj21U9eQbjm1QSn4COhX2XFSUv1VutuCoPFeJ6kvV2HF2B2JejIHPcDetbG1AMLKjo82c18h2WbZGANcDKAVyZL8E77l9+5opyilIo/sajV24OFg6aJACWUuLBJ4zJSzMLG/OnHiS7liycL6WeXQycubFJVjzUQI7e54n+vpihrc3pnt5KWbPY553dDQA/TaGAejf0k289Js/4bmt5xSw+6U04enNZ7HxjQ9x+sPP8Jev/vGtfM53MdoboNvb28PR8SF4eCxG9+6JZmBORk6A9vScip49X0T37i+YbevRY4oCermd4rlevRLg6TlVCe5kSF7fZpVqeOkNz77qtIClMl5f/iZtYsPD08zAngyerJ7d3PQLAb4OC0tRofiBA1NVmJ/lbRTSDRq0FLGxOQgKSoJbzxfgOHICwp+JQs7+HKRsS0H2vmzkN+Zjxd4VyG3IRXZdtgLXzD2ZyNiVgdyGXCzfsxxZtVlYtmsZkrcmI3V7KpLLk5Fcnox5G+dhyfYlWLJ9CTKrM5GyLUU7d102UnekYlXtKuTsz8HKmpWqtnzdkXUakO/LRva+bKysWYms2iysql2FVbWrlFf8puOblK87zWfKTpZp5XQmE5ziQ8Uof6schQcLlT0tVetU6689tBZbTmxRC4bchlwUNBUgtyFXCfYKDxYqdp5Vm6UWFltPbUXpG6Vq8VF7uRZTc6fCd7wvfKPc8UqoC7KGDFThazZCIUOWNeZkxnP8/c1KwKgMlzXb3K5n6ZIxs6SNAC37jUvhGt83PzCwRf/yhcHB6hgJ6Enic6Sqnee0xLrlc9q9SoBP6NVLvZ5u8nV/2sUFT7u44Bk7O0MUdxvDAPRv+SZe/O8/YlbVRbMcu5zPlp3DH/7y1bf6mXc72hugk6E7OyehR4/Z8PB4Dt27vwAPj+fUc06CPJ/L7T16TEH37i+oR2739JyqFgBk+JKxWyp/a65tT1R2slTFh4QsUlawBGKphKcCniDM/ukhIYvMurnxuODghWbPOWluExS0QIE51fHDh68wayRD4xoPr6lwiBkHr3F98eyKZ5GzPwepO1KxuGIxUrenIq0yDct2LcOyXcuQVZuF5XuWY2XNSswpmYP0qnQsKluE1B3acXNK5mDexnlI2pSEpE1JeGXzK3hl8ytYsn0JksuTsbBsIVK2peCVza9g2a5lWLJ9CZI2JWFN4xoUHypGfmO+CsuvrFmpwvRplWlYXLEYmXsylfqeDLn4ULGKGKw7sk7l+9kchscXNBWYKfbNyuoa8pDfmI/8xnz1XZn7p0Yg70AeUnekKt3AuiPrUPCrApUeKDpYhIJfFSB2Wiz6RHbF3CAHLPD3MasVpypdGsIsCglRgM0SMEv+52SussGJ3riFSnaWo7GUTJ5Tti6VrD1JsHvuY/mYPDYpKKhF//JE02eyxzmZN0FcD+YyDE9mntCrl9qW6Our6tDJ0A3r17YNA9C/o5v40Z++xKyqixZBPa3+Cv7416/xj3/e+k4++3ZHewJ0TRCnla1167YEHh4zzQBZgniPHlNUXpxsXM/meZx+m7f3DDOPeF/fRMXU/f3nWPSLZ/25nGTmLHFrfr5AmdPwdUjIIrMcfEjIIgXcZPl8H0P5ssUrFw88H88RFLRApQg4hw3LRO/eM+Hk/gw6RY/F4OdikFaZhoT8BCQWJ2L2utmYkj0FU3OnYmbhTMwsnImXCl5CyrYUzFo7C7PXzcastbPwfNbzmJY7Dc9nPY+E/AQ8u+JZPLP8GUzL07Y9n/U8nl3xLBLWJCAhPwGz1s7CrLWzkLItBQlrEvBSwUvIrM7ErLWzMKNgBl5e/zLmlMzRFgcb5mFm4UzMWjsL0/OnY1HZIgX4yeXJyGvIw6raVcjYlaGAP7M6E5nVmchvzMeq2lUqqrBk+xIl1mN+f8n2JcjYlaEtOLYmI3lrMuZtmIe0yjSkVaap7/zy+pexsmYl0nemY03jGuQ25CJ9Z7qmDdiRitQdqdh1cReeXPokeo/pjYcjXJAU4ozUEA30yG71YWrZZjRJ5J/JogmQLPWa2bu3KgHjfuaqZcibYXG9gcts3XnI8Mm0mQMnO5e+7AzV89yyxzk/g2A9y8cHCb16qUlwn+HtjWkm8CaY6+dUT0/M7N1bla2xfarB0Ns2DED/Dm/ipHWnLAK6nAMyDiM293U8vu4kni07h8Rd7yB1//vIO3wdm9/8ELvP/waN7/0Ox69/ggu//iOu/e9N/PaPX+JPf/0af/+WFgTtCdAlQ3dymg8Pj5no0uUpuLk9g65dn0XXrs/C3V1j6m5uz8DN7Rn1umvXZ+Hh8UvB6H9p9pqTDJ0LBRmaJ9jLmnea10j3ueaFAPutz1ZGM97eMxSr9vWdrXqtBwbOV8fIsHszqC9owcrldjJz5t/Dw9PM8u96V7ro6Gx49JoG+6gx8Bzjj6m5U1F0sEiB56KyRVhYthDL9yzH8j3LkVaZpsLgS7YvUXnxxRWLkbw1GUu2L8HiisVI2pSEOSVzVJg9fWc6UnekaqF5E1NfsXcF0nemI60yTbHcnP05yN6XrcLYNKhZtmsZMvdkYvX+1Vh/ZD3K3ypXpjaV5ytReLBQ86E/WKREcVTQFx0s0oR8pm0qD2+qoaeaP2d/jpqZ1ZnIrstGelU6ig9rdrVZtVkoPlyMgl8VoKCpQNXWU0xHg5zhzw2Hz3A3zVgmpB+WDhpkxpZliFsq2CWA6kPYBEsJ8HpPdLYcJZOWxi76+m+2LeX5yLpl4xSZC+fnzRaPsnZchs7lnOrpiamennixZ09M9/JSHdS4jc+neXlhSo8eZq8pivtl585GyP02hgHo3+FNPPPhHxCdfQwDMw7jiQ1v4bHik4hZ/ToGmGxkv435yNJXEbHyKOLyjuOx4pP4eekZTNt+AXP3XELq/veR/eo1rDv2H9j21v9Dzdu/xen//Awf/elL/PNWc+18ewR0O7tusLefDXv7Z9Gp00/MpoPDz9Tzzp1/avZaHsN9csptnTv/FE5OT8LZ+Un16Oz8c/Xo5PQkunR5Cl26PAVn5yfh4vI0nJ1/DheXp9Gly1NwcXkaXbs+CxeXp+Hi8rRaYHC7tsDQFh4eHr+Eu7u26GhOH/xSLTzc3Z9rMZv3P6cWLc0LlefUgoQ6ABmB8PVNhIfHL2HX5UnYjxiDHqN9MX72eMS8GIP4GfGInxGPcYnjMH72eMQlxCEuIQ5jZ47FhNkTMHHuRMS/FI+4hDiMnz0eo6aPwugZozHh5QmIfyke42ePx6PzHsWkBZMwacEkTHh5Ah5Lekzb9sokTF44GT9b8jNMnDMRT6Y9iReyX8BPFv9EzX9b+m/4t6X/hqcznsbPUn+Gny75KX6y+Cd4Kv0pTMudhpcKXkJCfgKm5U7DizkvYmruVLxU8BJmFMzAtNxpmJY7DYnFiZhZOBNTc6diTskcJJUmYW7JXLy8/mUkrEnAjIIZ2vF501T0ICE/AbPXzcZLBS9hSvYUzF43G8lbk9W5FpYtREJ+ApK3JmNlzUqkVaapiMPGYxsxeeFkeMZ6wmuIE+YHOyEttF8L4GUYm6CoZ9BUiMu8M/PQ+pIuhs5n6z5jQVCQOlYfupfn5yIiKSgIs3x8FMvn8WTf0tJVsn6paJfXZIl5T/PyMmPqnJLFJ/r6IqFXL8zx98czbm7aNHLotzUMQP/0U+Crr+75/PuX/4c//OEmPvzoD3jn33+P45d/g/qzH2L78esobrqCFfsuYUHlObxU9haeWX8CPy44hvHZhxGV0YQBiw8g6JX6u5phyQfwg5wjmL75FDL2nMdPn0/E9Fnz8dfPv2hxrTc//fSBA3Qbm66wsXkJNjZTYGPzNGxsnhLzafH4tIX9Pzd7bWv7C9O2n7c4j63tL9TkuWxtfwE7u2dM25qPtbN7xmw/j7G3f1adg9vt7Z+Fvf2zLV5bmpb267d17vxLs8+S2+Vzzk6dnoOT0/OwcXoWNsNGwT7CDa5RrvCM94RrlCvcR7qj++ju6B7XHe4j3eE+0h3d4rqhW1w3eMZ7ovvo7up197jueGjsQ/CM94THKA/0GN0D3Ud3h2e8JzzjPeE1zkvt9xrrpc1xXvCe4A2vcV7wedQH3hO8W0yfR33gM1GbXmO94DPRB/4/8kfA5AAE/DgAAZMD0O+JfvB9zBcBkwPgP8lf227aF/pkKIJ+EoR+T/TDIz99BP2e6IeAHwcg5N9C4Pe4nzqX/4/81Qz+WTD6PdEP/Z7oB/9J/njkp4+ocz/y00cQ+mQoBj0zCKFPhiLs52EY/NxgDH5uMIZPGY5BzwyCa5QregzuhMS+dpjh4oTpbm6Y5uqKKc7O6vmLXbqYzWmuri22619PcXZu8T65L6FrV3We6Mvd2wAAIABJREFUaa6umO7mZvY+uU+en8fK901zdTU733Q3NzWnubpipocHEtzdMd3NDQnu7ur76a/b0vfidcnr4efxGJ5zmqsrptrZGSH32xgGoE+ZAsyY0e7mPxMS8NXUafjLC1Pxp+em4NNfvIDf/fyX+O+fPYv/fOIZXPvR03j/8afwzsQncW7Cz3Bq7E/xetwTaIyahD2DH8Wu8OZZNegH2OYViG1egWgY/hg+/MkzuJWQoD7r5pQpDyCgO5kA+CXY2Mw0PVqbM3XPLR0vt1s7n/6YmRbOZ2m7fpv+eGvX2DxtbWe1ekzz/uZpZ5dots/WdpaaanunabDpHw2bYZ3ROaYzOkV3QqeoTtrzKO25fZQ97KPs1TbHkY7avmjtOM5O0Z1gP0I7ziHGwWw6xTrBcaQjOsd0huNIRzjGOsIp1glOsU5wHuUMhxgHOMY6wnGkI5xHOcN5lLP2mtO03WW0C1zHuMJ9nLt67TLaRb2H59Rv5+Q27pfX4DzKGS7xzft5zY4jHeES76Le4zLaBW5j3My2uY1xg+NIR9iPsIdThA2e9rXBbAd7zLa3R6KdHWbb26uZaGenptwuj5XHzLK1RaKdHV7u1Mnie7jf0iOf66e1c8h93MbXL3fqpLbrv5f+cy19L/l9ZtrYtHg/zz/bVHs+08YGL9nY4Oc2NnAyAL1NwwD0dgrodzNvJSTgLy9Mxe+feh7/8cQzuDjxZ6jzD0Gldz9UDfoBdoU/incmPvmAAzpBvesDNt1NU7/N2uu2PG/tvJa32dp6qG18bmvrYfG5TSdH2DjZwMbJBp1cO8Guix3sutihk2sn2DjZwNbZFrbOtmb7Ort1RifXTurRrosdHLo6qPd1duuspkNXB3Ry7QSHrg5w6OqgtnNbZ7fOcHR3NHvu6O6ozsP3Obk7qUfXHq5w7eEKl+4ucHR3hLOHM5zcndR09nCGaw9Xtd2hq4PZMY7ujuq9/GyHrg5wdHc0Owc/36W7i3rN9/ORz3n9Nk42cO5sAw9bW/To1AnuNtpzvuZz/XS3sVH75Xs4u9rYoJudHdxtNNU3n3c1HSufdzUd09U03a3Mrrpj5Hn0x8rr7Ko7h/6c8nhet7Xr+qbrayuYG4BuAPp9C7k/SPPrP/8ZK5YuRfriJSg+cMkUkm/AJ5998QCH3I1pa2vb6jZWBFh7LY+nA5+dnZ16bmNjo7bZ2dnB3t4e9vb2cHBwUK87d+4Me3t7s2P4vHPnzujcuTMcHR3Vo4ODg9rO9/I8Dg4OZvvt7Ozg4OCg9vP9zs7OcHV1hZOTExwcHODo6AgnJyd07twZXbp0QZcuXeDk5GT2uXwvt/GzuE3/2fyeDg4O6tzyGnhd8jeR313rCNhZ/Zb29vbqt+b34Xfk8fIeWJrcz2Ot3Vv9drn/m/5mrP1dtfXv73b/du/mHJbmXWGBAejtd3Skm3i3Qy+Ke6z4JPxSmtDw7v8AeDBFccb8dv6h6v+56oHFxsbG4nMJXgQZbpMgZm9vrwCRgCn3ydcSxCVoSoAlqDo5OaFLly4twFkCM98jQdzOzs7iwkICLJ/z8/k+a8dzH7+TJSDWg7H+d5T79QCuB3F5jvv9N/igzTsZHQkLDEDvADfxboce0BfVvge/lCaUHP9PAAagP0jTGsuyduztnJsAoQcOApU1ULG0EJCTgC6ZqR7Q9VEAS5Mg6+joiK5du6rnkn3LY/laLib0DFy/OOFzPVg7Ojqabedx8vr0IGwNzC0BtTXQvtN7/32ddzI6EhYYgN4BbuLdDj2grzp4DX4pTchqugrAAPQHaRqAbgD6/f4bfJDnnYyOhAUGoHeAm3i3Qw/ohUf/HX4pTUjd/z4AA9A76mwNIAgw8jj9az0o6UPOMnQtQ9gS0LlQkICoB30Zkud0d3dH165dW+Tp9YAtQ/X6XLelc+t1AZauQ//99IsSPajzN5O/qyXQl8fo74G1xdb9/ht60OadjI6EBQagd4CbeLdDD+gFJkBfWm8A+v2cdypWut3zW2LdlhijjU1LsLGW67WWc5Ygb4mV69+n30Ym3qdPHzg7O5sBtiVRmx6Q9Tl7/SJEL1izFCXQ5/wtfQdLgN4aG5e/qbUFlKUF1f3+G33Q5p2MjoQFBqB3gJt4t8MaoKfVXwFgAHpHnpYWCdZYoCWA0bNSS6F6PbBaem6N9eoBlKK3bt26oWfPnmYCNwnolkLsesYtt+tZuKVog4wkyIgCJ8/H4/SRB0u/qaWwu6X7IF/f77+ZB3neyehIWGAAege4iXc7rAF6eoMB6Pdz3ut/3q2xQnk9rTFMOS0pz1sDbEsgKl8zrO7s7AxPT09VtibD+Xqw1j9aO8Ya09Zfj/4YS9oBa6kE+dvqf6vWfuu23BtjavNORkfCAgPQO8BNvNthMPTv97QmvmotBNyW0DuBTZ/ftpQjlwBuLScvy9bc3Nzg6upqVpKmD+lbyn9bE9vJaIK18Lk+dG/pWi0xeGuCt2/aJ++FtcXU/f7bedDmnYyOhAUGoHeAm3i3owWgH7lhAPoDNL+Nf9zfdI5vCq1LENczTGuALmvJLYXA9YpxSyxZAiTP4ezsjJ49e6JLly4Ww+2WFg6WFhL61/o8ubVQvLVrtcS4Gaq3pjXQ35e2COEMMLc+72R0JCwwAL0D3MS7HXpAzzbK1r4X0xozb227nlW2lkPXh96t5bZbmxI0Zfi+V69e6NOnTwsjmdbA3BKD1ofR5T795+ujBvprtRRZaO0304O7peeWwN8AdevzTkZHwgID0DvATbzboQf0jAMfwC+lCfmHbwAwAL0jTEsMnM+tMT9LAGIpRGwNrGT42xILbmtIXDJ0BwcHuLm5YcCAAXB3dzezd5XHtAXUpdjOEtNuLZ/f2sKjNTZuaVtrYfXW7oUB6C3nnYyOhAUGoHeAm3i3wxqg5x2+DsAA9I46rTG+1kK+1gDKGuO0FFK3xH7JcPU13ZYA3dHRET4+PujTp08Lb/bWVO76z2xNkCf3W2Lx1r4Xt1v6zSwda42V8/fX/+aW7pcxm+edjI6EBQagd4CbeLdDD+hZTVfhl9KE7IPXABiA3t5mW/7Z68FBPrfGBlsLAX9T+Li1nLQMU7cG/mTizs7O6N27t8qh64FcRgSs+cLrQdpajv2b8vv8PVsDekupCWvArgd1A7hvb97J6EhYYAB6B7iJdzv0gJ5z6Dr8UpqQ2Wjk0DvybA28uU1/vDWAsraPr/U5Zj3wWQJyeaydnXkuvk+fPggMDDTrfmatRM5amF/PwK2F/S0tRvTX3BYGLn8j/qbWwu/ynnxTiN6YzfNORkfCAgPQO8BNvNthLeSec8gIuT8I807+cd/OeyzlcPXAo99uDbitTUtAaEmIJs8n90sG3q1bN/zsZz/DQw89ZObnrs+F344Iz9L+1hYa+oWAte9r6XdpLeKhj3pYCrnfzd9FR593MjoSFhiA3gFu4t0OPaDPr34XfilNKD3xIQAD0Dvq1IuuLAGKfp8lIG9LLt1aGLo1lq4HXcnAo6OjER8f36KXeWuqdz2AtybG0+9vLV3QWsqgtfC7JcD+JkZuMPTW552MjoQFBqB3gJt4t0MP6Gn1V+CX0oSMAx8AMAC9o04D0A1A72jzTkZHwoJ2DeglJSXw8/ODo6MjIiMjcf78+Ta/tyPdxLsdekCvPPNr+KU0IWHH2wAMQG9P83ZD7fK5pTzvNwFKa0ClP4YAyP0yLG1pYaB/LUHZmkOcNTMZawBuCXQtheYtAXtrAj5r09r35G9tbREl75cB6NbnnYyOhAXtFtCrq6vh4OCAbdu24erVq0hISICHhwc++eSTNr2/I93Eux16QN9hAvSZOy8CMAC9Pc7W/tlbAoq2skBLgK4Hdhublr7u1lh8W8FQn+fWK9ctsXB99zVrTN1SVEB+pjWWbg3cJXvXL2KsLXgsLY7kfmu///3+O3vQ5p2MjoQF7RbQIyMjMXv2bPX61q1bePjhh7F69eo2vb8j3cS7HXpAr3jr/8EvpQmJu94BYAD6gzwt/VPXM7q2nOObwu/W2HlrbN0SG7XGaq2BuQRHPTBb8m/Xh9z14XNLwjdrYjlLRjSW0gT61zKdYOm3kb+ptbC7jU3rCvjbub/fp3knoyNhQbsE9K+//hr29vaor6832/78889j8uTJFt/z1Vdf4ebNm2p+9NFHHeYm3u3QA/rWUxqgz9l9CYD1P/hv6ze93/8Evq/TEvvmY2uAbg2s9WAnj7EGgtbOY4nhU9Euwbw1L3fJ0vUArWffeiavZ9+WnOIsMfrWFi/fFAnRA7Y1sDcYuvV5J8MA9Ps8fve738HGxgZnzpwx275o0SJERkZafE9GRobFP4COcBPvdugBfcub/wW/lCbMr34XgPU/+G/rN73f/wQexHmn7PpOP8sSgOv36cHXxsYcdPQA3RbQbw0UGbKWoNqaI5ylWnR92F0CuDWQt/S6tRy8NbZu6bvrt1kLw1ti9gagf/O8k2EA+n0edwLoBkO3PvSA/t5vP0fpiQ/x+vWPAXz3DN0YxjCGMe7XMAD9Po87CbnrR0e6iXc79ICuH991Dt0YxjCGMe7X6Ej/t9oloAOaKO7ll19Wr2/duoXevXsborg7GAagG8MYxvi+jo70f6vdAnp1dTUcHR2xfft2XLt2DTNmzICHhwc+/vjjNr2/I93Eux0GoBvDGMb4vo6O9H+r3QI6AKxfvx6+vr5wcHBAZGQkzp071+b3dqSbeLfDAHRjGMMY39fRkf5vtWtAv5vxxRdfwMbGBh999JGZsOv7OD/77DMsXrwYixcvxmeffdZiP8VuX3zxhfGbGtOYxuxQs63/39rD+N4COm+iMds+P/roI+M3NaYxjdkh5zf9f2sP43sL6Ldu3cJHH32EL7744p6uAtsLe5XX+8UXX+Cjjz7CrVu3vpPftL39Nt/X72R8r/Y3je/1zbOt/9/aw/jeAvq9Hjdvtq88zb283vb227RldMTvBBjfq70N43t9v4YB6PdotLc/QAPQ7250xO8EGN+rvQ3je32/hgHo92i0tz9AA9DvbnTE7wQY36u9DeN7fb+GAej3aHz11VfIyMjAV199db8vpU3jTq73TnPon376KRYvXoxPP/30vufmvq3ZEb+T8b3a3zS+1zdPI4duDGNYGIbK3ZjGNGZ7nYbK3RjGEOOe1KF/9hluLl6sTQs188a8jfnpp7g5ZYo2OxiDu2/zk09wc+JEbX7yyf2/nvY8P/4YNwcP1ubHH39nn2PUoRvDGPh2uq3lHb6OF7adx/Pl5/HL8vOYsu08pm1/Gy9VXkRi1TuYs/sSkqrfxSs17yHjwAfY+ea/46+LlwIZGYAFVztj3Mb46itgxgxttpNU0AM//vY3YNIkbf7tb/f7atr3+L//AyIi8I8hQ7Hj9WtYdfAaFux9D4m73sFLlRcxbfsFTK1oOd/77ee39TE3b3acfLwB6Ma442GtH/pnn32Gr7/+uk3zqU0n4buwvs0zMKkGJbFP43/nLsTXf/lLmz/HmBbmn/+Mf06bhn9Om4av//zn+389HWHevIlbjz2GW489hq9v3rz/19Oe5xdf4M/9B+ED734Imlfd5v8Rhy////buNLypMu/jeBwvYVwGkKHXgIxElsRBGFGEIjCyCFKWDhUUGUTtIBRRfEQImEKBjuxYFhUGRZBtYIoMJKDpvtG9paXpQlu6L+le0qb7mvyeF2lD0xbpgbs9PfH/ua7zgma77zbkm5ycJZfT45SWllLQCbnXJ3RHR0fTseHvt9iv3Yi3HT7HEof1WOKwHm87fI7Fqz7HmyvXwe7Ddfj7is9g+8/PMN/+/zBr+Vo8P/t97H12LA6PGIdtm7d0+XFo6bjscHJC1PjxiBo/HjucnHgfjyUsO52ccFsqxW2pFDvpd/pQy47NmxHf74+IeXIgXpj9HmYu+wTz7f8Pdis+w5sr1+GtVZ/j7U6WDXJurwuOjo4UdELaa111xSXoXJfNX2zGgedexN5nx2L5qnW8vuAIfaGgs18o6OyWjz9Zj5gnB0L91EBs2SjvtsehoBPSidagc1nlznmpqoLfOx/h0OSl2PrfSP5XCwp5oVXu7Bda5c5s2XQmGHF/Gonc4aPRoNN12+PQKndCOtEjG5c0NCB1zQYcnroMC1x8u+9xfgtoozj2aKM4Zt508UHc4FHQvfCicQO5bkIbxRHSiZ4KerWjEw5PXQbJJiV0NY3d91iWrr4ehUs/QLTNEjRUd98L5m8KBZ2JZr0Bf/1CibjBo1A/7mUKehdR0AkzPRV0ODvjzBv2GLVRCZ/Eou57LAunr63DhXFzcWHcXLgGpfI9HMtQVwf9ggWonjMXhm6MkKXLvlMN6YYriB88CoZXXqGgdxEFnTDTk0H3fWcNRm1UwkkZj2a9ofsez4LdTCkwBf1btwS+h2MRkjKKEfbCZPiMnIjLIfQm6UH5JBZBuuEKUp59HqCgdxkFnTDTk0HPXLsRozYqIZarMNxRhVVnoxCaVorymgYYDBT4rth5JcYU9O2XovkejkX47FQYfEZOhM/IidjqGsX3cATrWEA6pBuuIGf4aAo6BxR0wkxPBr1p6zZT0NsvIze7YYZLAFadjcJ7JyPw5r9DsOS7MLy23x8v/ssLc78OwqTdvnh+qztmugRgzqFAvH4gADNcAuBwNgoHvVPwY3Am4jTcjjglNHP2eZmCvvJ4MN/DsQjLjwSYgv7Bv6/zPZxeq6FJj7LqBuRqa5CYX4HITC0S8yuQc6cGuppGrHONgXTDFRRJx1LQOaCgE2Z6MuhwdsbHp8IglqswYZcP5JfjMH6Hd6eBf5hl6j4/LPg2CBsvxSIwpcRiVu8bDAb81fGaKehz93vzPSSLYPuVtynoM3Z48D0cXtQ3NSNXWwOPhALs80jGZkU8drslwfFKPOxPRWLMds8u/d+TbriCyrHjKOgcUNAJMz0d9LxiHU4EZaCy7u6W7vVNzcgrr0VIWinOhGbhfEQ2PBIKoYorQFj6HSTmV8A/uRjxGh2ySqsRml6K0LRSRGTcQVj6HRzyToGTMh4rz0RBssW9w4vMpN2++OTCTfw3MgfFFcLdirmqvgkSmdIU9L86XqOvKhiY9qW7KejSjQrUNzXzPaRuVVnXiMhMLU6FZEJ2KRY2hwMxcrNbl98w/2WrBybs8sEMlwD81dk89Ku+DzRuEEdB7zIKOmGmp4OOhu49OcudqnpEZNyB161CbFUmdHjBEctVmPd1EPa0nDRi1dkofH5Rja3KBHzlmYwLETnQlNV06xgfVEZJFSQyJVxfMgZdIlPiThXti/6wXnS8djfoMgXSiquYP0ZNQxOq6psAGN/AVtRx23WzoUmP1KJK5JXXorrlflpV1zehocl4XnBNWQ3iNTroahrR1KxHUUUdbmRp8a1vKt7+LhSv7Lz3GjGpkztmHgjAFkU8DnqnYJcqEd/4puJsWBYS8u7eZ1sGgwFNzXrsdkvCW8dCkVegNcacgt5lFHTCjKUFvb26xmYEpZbgG99U2B0NwXOO9/8E8pyjCusvqhGSVor0kipEZ2vN1ijwJTzjDiQyJX6eZAvFxAWQyJScz1JFzNU1NkMqU8Bn5ESEjH4VUpkCvkkPtlulpqwG/43MwYrTN7Dsh3BM3uOLV/f4YspeP9N2Im8cum56nk3/yh8bforFFkU8Todk4la+DkGpJbhdWImKukZ8+XMiFh4JxsIjwXjpSy+z5+jrBwKw8VIs3jsZgeGOKoze5oHX9vt3eB7f6zk+eY8vVp6JwiHvFHjdKkReeS2btT0tZ1ujoHcdBZ0wY+lBb6+0qh7KmDzIL8dhr3syzkdk43hgOg56p2D71QQs+S6s0xdAyRZ3zHAJwOcX1TgTmoWbOWUP9PjNekOHTzlddS02HxKZEt6v2cHrb3aQyJRQxRU80H0Ro+KKOmPER05E3EuvQSpT4GRwZpduW6irgyJGg03/i8Xf9vsx3Q5kRCerwEdv8+j0K6X2EW/7KXy4ozHeq89FwTUyBwl5Os5rBzihoHNGQSfM/NaC3hWxueXY8FMspuz1w5jtnpiwy6fTF0/bb4Nh+20wXt7hjdkHr2PZD+FY5xqDXapEfH89HadDMrHtagLeOhaKF7Z54C9bPUzfVU7a7QvZpVicj8hGZKYWMTll991470RQBiQyJYJfX4zAmYsgkSnxn/DsHvqtWKbUokpIZQpcl05C+qQZkMoUWHvhJi5HaxCUWoLahmbE5pYjpagSDU16ZJZW46B3Cma6BHQaYbujITjqnwZFjAahaaWIytIiMlMLbXUDEvJ0+Dk2H0UVddDVNMIvuQhf+6TiK89kvHcyAi9s88CUvX6mmM90CYAyJg++SUWIzNSa3giWVTfAO7EIB7xu43RIJtJLqpBUUIEbWVoUVxq3EalpaEJxZV3PbxBKQeeMgk6YoaDfn8FgQM6dGgSnlmLHL4lYeeYGRm3p+kZEXV2m7PWD3dEQfO2TiuhsLdS55War+ve4JUEiUyLaZglCZi2GRKbEiaAMHn8zwncjSwupTIHQ0a9CN8sGUpniVz/9tv33cEfjm7rdbknwTy42fUf+sLTVDSjQMVoF3tMo6JxR0AkzFPQHU1RRB2VMHq7c1CAxvwIhaaVQxuThh8AM7HZLwvqLaqz5TzT2uCXhqjoPKUWVyLlTg0JdHbTVDQhMKYGL5228dzICr+33x9h77BY01tkTh7xToKttxPqLakhkSiT+/R+IeOMtSGRKHPGjI5s9DO/EIkhlCkSOnQKDrS1e3vJzh7/BmO2eplXdUid32B0NwVV1HnS1/G9X0etQ0DmjoBNmKOi9Q3V9E/yTi/HTjVwsPxGBqfv8zPbRf2WncTchiUyJjEXLEWWzBBKZEl95JvM9dEG7FJULqUyBmHF/A2xtccQtAWK5CjNcAqDXG1BSWY+6xmZU1RtXYQvyU3NPoqBzRkEnzFDQey+93gC3+ALMPHD3+1qJTImCpe8jZt47kMiU2PFLIt/DFLQTQRmQyhRIGP8aYGuLuspqnAzORKFOuMcr4BUFnTMKOmGGgt77Vdc34ePz0aag695fgfgFSyGRKbFZEc/38ATtgNdtSGUK3J4wnU6fygIFnTMKOmGGgi4MBoMB58Kz8Y0qAQYHByT+/R+QyJRY/5Oa76EJ2lZlAqQyBdInzaCgs0BB54yCTpihoAtMfT2wejVS7JZBIlPi4/N0xrWH8el/YyCVKZAz5XUKOgsUdM4o6IQZCrrAtAQ9fdG7kMiUWHH6Bt8jErT3TkZAKlOg4LXZFHQWKOicUdAJMxR0gWkJetZbyyGRKfGP4+F8j0jQFh8LhVSmQPF0CjoTFHTOKOiEGQq6wLQEXbPkfUhkSrz57xC+RyRott8GQypToHTGGxR0FijonFHQCTMUdIFpCXrBUmPQbQ4H8j0iQZtzKBBSmQLamXMo6CxQ0DmjoBNmKOgC0xL0kmX2kMiUmOESwPeIBG2GSwCkMgXKXrehoLNAQeeMgk6YoaALTEvQtcv/CYlMiUm7ffkekaBN2esHqUwB3SwKOhMUdM4o6IQZCrrAtARd9/4KSGRKjPvSi+8RCdqEXT6QyhSonD2Xgs4CBZ0zCjphhoIuMC1Br7L/EBKZElInd75HJGgv/ssLUpkC1W9Q0JmgoHNGQSfMUNAFpiXodStWQiJTQixXQd/T57y2IH/Z6gGpTIFam3kUdBYo6JxR0AkzFHSBaQl648pVpqDXNjTzPSrBGrHZDVKZAvVz51PQWaCgc0ZBJ8xQ0AWmJeh6BwdT0LXV9Dt9EM16g/Ec5zIFGuZR0JmgoHNGQSfMUNAFpiXoWL0aL8ivQSxXIb+8+144LVltQ7Mp6E3zF1DQWaCgc0ZBJ8xQ0AWmTdDHO/0MsVyF9JIqvkclSLqaRlPQ9Qso6ExQ0DmjoBNmKOgC0yboU790g1iuwq18Hd+jEqTiyjpT0A22thR0FijonFHQCTMUdIFpE/RZezwhlqsQna3le1SCpCmrgViuwhj5VWPMKegPj4LOGQWdPLD6+npUVFSYFo1GQ0EXkjZBt3XxgViuQkhaKd+jEqSMkiqI5SqM3/IzBZ0VCjpnFHTywJydnSESiTosFHSBaBP0xYf9IZar4JNYxPeoBCm5sAJiuQqvblNR0FmhoHNGQScPjD6hC1yboC8/eh1iuQq/xOXzPSpBitfoIJarMO1Ldwo6KxR0zijohBn6Dl1g2gR95fFgiOUqXIrK5XtUghSdrYVYrsLs3Z4UdFYo6JxR0AkzFHSBaRP0T0+FQSxX4Vx4Nt+jEqTQ9FKI5SrM2+dFQWeFgs4ZBZ0wQ0EXmDZB3/ifSIjlKhwPTOd7VIIUcLsYYrkKdgd8KOisUNA5o6ATZijoAtMm6M6XbkIsV+GQdwrfoxIkr1uFEMtVWPK1HwWdFQo6ZxR0wgwFXWDaBP3gz3EQy1VwvnaL71EJ0i9x+RDLVVh+JICCzgoFnTMKOmGGgi4wbYL+g3cixHIV1v+k5ntUgnTlpgZiuQorvgukoLNCQeeMgk6YoaALTJugXwxOhViuwsozUXyPSpBcI3Mglqvw0Q/BFHRWKOicUdAJMxR0gWkTdPeoLON3wN+H8T0qQTobZvz9ffpjKAWdFQo6ZxR0wgwFXWDaBD34lnGVsc3hQCZ33aw3oKahCQaDgcn99XYngjIglquw4Ww4BZ0VCjpnFHTCDAVdYNoEPT69CGK5CpP3+KJZ/2ARjtfosP6iGnMOBWLUFuPZ2944dB2XonKRVlzJePC9y1H/NIjlKjiej6Sgs0JB54yCTpihoAtMm6Bn5RmPdCaWqzDcUYVzYVldvpuQtFIsPBJsun1ny3BHFU4EZUD/gG8WervDPikQy1XYfjGKgs4KBZ0zCjphhoIuMG2CrtVWdojw/dQ2NGP71QTT9UdsdsP6i2r4JxcjV1uDooo67FIlYs6hQNN17I6GoEDXfS/OfNnvkQyxXIWdl2/vqerXAAANuUlEQVRS0FmhoHNGQSfMUNAFpk3QG2tqOwRdU1Zzz5vml9di7tdBpus6KeNRWlXf6XUNBgPOhGZhzHbjOden7vNDbG55d82KFzt/Me72t/+qmoLOCgWdMwo6YYaCLjBtgo76eoze5mEW9HPh2UgvqUJFXaPZzdS55Ziwy3j+9Fd2eiMwpaRLD6cpq8H0r/xNq+D3uCWhvqm5O2bW47a1rKn4+pc4CjorFHTOKOiEGQq6wLQL+qTdvmZBlzi5QyxXYYZLALTVDfC8VYh//XwL0paf2xwO/NVP8Z3RVjfgM9cY02Osc42xiC3h5ZeNR9o75pFAQWeFgs4ZBZ0wQ0EXmHZBn+kSYArt3/b7/epGbitO30BVfdMDP7RHQgFGbDZuCX+WwwZ4vdX6i2qI5Sqc9E6koLNCQeeMgk6YoaALTLugW+/2MQW7qVkPn8QiXFXnQbLF+Il8wi4fyC/H4Vx49gPv2tZW677bIze74Vpsfqf3WV3fhCN+qVjnGsN5bQBXUVlaHPROwfHAdKQWVXJac/DJBePJbc75JVPQWaGgc0ZBJ8xQ0AWmXdBfaPMdelu52hqkFVcyiXhbBoMBH5+PNj3m1H1+8EksAgDEacqx3yMZr+y8+ybj5R3eCE0rZTqGVjl3avD8VneztRCzDl7HmdAsyC/HIV6j+9XbrzobBbFcBdfAFAo6KxR0zijohBkKusC0CzqXXdZYqW1oxn6PZIz70gtiuQqjt3nAO7EII1tWx4vlKry239+0Rf1wRxWzqBsMBpwLy4LN4bu71Y3d7gn7U5GmtRKti9TJHbvdklCgq4VHQiFu5ZsH/oMfjeeTvxKaRkFnhYLOGQWdMENBF5heEPRWdY3NWHws1GwMMw8E4KcbuWho0qOusRmrzxk/BS8/EcHkMX+KyjV7vL9s9UBmaTUAoKKuEVuVCR22/G9dizFisxsO+6TgTlU9mvUG/ON4OMRyFX6JzKCgs0JB54yCTpihoAtMu6B7JxZh7HZPeCQU8jKchDyd6ZCx1rt9oK02//vmamvwnKMxrGnFVfgpKhfzvg7CYZ8UGAwGJOTpEJRagur7bKxX29CMzNJqjG3ZL363WxKis8uQq+34Hb3BYECz3gCPhEJMa9nlrv0y80AAbL81HinPKzqLgs4KBZ0zCjphhoIuMO2CDoD3Q7PmamsQmantEPNWK8/cgFiuwpS95lvhv7LT+77ftRsMBhwPTDdtXS+Wq7D4WGiXtw3IKq3GeycjcCIoA1fVeZi85+5ufq1vNK7H5lDQWaGgc0ZBJ8xQ0AWmk6D3djE5ZWYhf/FfXmb/bv3U/ZyjCvanIrHXPRnlNcbnyY/BmWbXnbLXD8WVDx5dg8HQ4Rj2IQkaCjorFHTOKOiEGQq6wAgw6ACwruXANG9/Fwq93oDUokpcVechtagSdY3NcLwSZxbZaV/54z/h2aat2Pd7JMMjoRBFFQ8f3C2KeLPHys67Q0FnhYLOGQWdMENBFxiBBr2yrhEngjJ+9dN1dHYZDnqn4NU95ke/W3o8jOmR6U6H3P3U/8pOHxhqaynorFDQOaOgE2Yo6AIj0KBzUdZyqNlRW9zwyfmbKGbwqbyt4NRSU9BXn4syRpyCzgYFnTMKOmGGgi4wv4Ggt2J9UJxWRRV1pqAf9U+joLNEQeeMgk6YoaALzG8o6N3FYDCYgh6UWkJBZ4mCzhkFnTBDQRcYCjoTgSklONd6ghkKOjsUdM4o6IQZCrrAUNDZo6CzQ0HnjIJOmNHpdBCJRNBoNKioqOiepbQUFY6OxqW0tPse57ewlJSg4p//NC4lJfyPxxKW4mJU2NgYl+Ji/scj5KWoCBUvvWRcioq67XE0Gg1EIhF0ul8/AY8QUNAJM63/MWihhRZahLZoNBq+X0IfGgWdMKPX66HRaKDT6Ti/O+7WT/U8LDQvYS00L2EtLOel0+mg0Wig1+v5fgl9aBR0wquKCsv5/qotmpew0LyExVLn9bAo6IRXlvofk+YlLDQvYbHUeT0sCjrhlaX+x6R5CQvNS1gsdV4Pi4JOeFVfXw9nZ2fUW9huUzQvYaF5CYulzuthUdAJIYQQC0BBJ4QQQiwABZ0QQgixABR0QgghxAJQ0AkhhBALQEEnvDp69CjEYjH69u0La2trREZG8j0kTpydnTscQvL55583XV5XV4dPPvkEAwcOxJNPPonFixejqKiIxxF3LjAwELa2thgyZAhEIhGUSqXZ5QaDAdu2bcPgwYPx+9//HrNmzUJqaqrZdbRaLd5991384Q9/QP/+/fHhhx+iqqqqJ6dh5n5zsre37/C3s7GxMbtOb5sTAOzZswcTJkzAU089BSsrK9jZ2eH27dtm1+nK8y4nJwfz58/H448/DisrK2zcuBFNTU09ORUzXZnX9OnTO/zNPvroI7Pr9LZ59SQKOuHNxYsX0adPH5w6dQqJiYlwcHDAgAEDUFxczPfQuszZ2RljxoxBYWGhaSktLTVdvmbNGjz77LPw8/NDdHQ0Xn31VUyZMoXHEXfO3d0dTk5OUCgUncZv37596N+/P65evYq4uDgsXLgQw4cPR12bM4rNnTsX48aNQ0REBIKDgzFq1CgsW7asp6dicr852dvbY+7cuWZ/u7KyMrPr9LY5AYCNjQ1Onz6NW7duITY2FvPnz8ewYcNQXV1tus79nnfNzc0YO3YsZs+eDbVaDXd3dwwaNAibN2/mY0oAujav6dOnw8HBwexv1nZf9N44r55EQSe8sba2xtq1a03/1uv1eOaZZ7B3714eR8WNs7Mzxo0b1+llOp0Ojz32GP73v/+ZfpacnAyRSITw8PCeGiJn7eNnMBgwePBguLi4mH6m0+nQt29fuLq6AgCSkpIgEokQFRVluo6HhwceeeQR5Ofn99zg7+FeQbezs7vnbXr7nFqVlJRAJBIhMDAQQNeed+7u7vjd735n9qn9u+++Q79+/dDQS05L3H5egDHo69atu+dthDCv7kRBJ7xoaGjAo48+2uFF9oMPPsDChQt5GhV3zs7OeOKJJzBkyBAMHz4c7777LnJycgAAfn5+EIlEKC8vN7vNsGHDcOjQIT6G2yXt45eRkQGRSAS1Wm12vWnTpuGzzz4DAPz4448YMGCA2eVNTU149NFHoVAoun/Q93GvoPfv3x9WVlaQSqVYs2YN7ty5Y7q8t8+pVVpaGkQiERISEgB07Xm3bdu2Dm9EMzMzIRKJEBMT0zMDv4/28wKMQR80aBD++Mc/YsyYMXB0dERNTY3pciHMqztR0Akv8vPzIRKJEBYWZvbzTZs2wdramqdRcefu7o5Lly4hLi4Onp6emDx5MoYNG4bKykpcuHABffr06XCbiRMn4osvvuBhtF3TPn6hoaEQiUQoKCgwu96SJUvwzjvvAAB2794NqVTa4b6srKxw7Nix7h1wF3QWdFdXV1y7dg3x8fFQKpUYPXo0Jk6ciObmZgC9f06Aca3WggULMHXqVNPPuvK8c3BwwJw5c8wur6mpgUgkgru7e/cOugs6mxcAHD9+HJ6enoiPj8f58+cxdOhQLFq0yHR5b59Xd6OgE15YStDbKy8vR79+/XDy5EkKOnpP/DoLenutayJ8fX0B9P45AcbvysVisdm5vC0h6J3NqzOtayPS09MB9P55dTcKOuGFpaxy78yECRPg6OhIq9x70erprgQdAAYNGoTvv/8eQO+f09q1a/HnP/8ZmZmZZj8X+ir3e82rM9XV1RCJRPD09ATQu+fVEyjohDfW1tb49NNPTf/W6/UYOnSooDaKa6+qqgpPP/00vvnmG9PGSZcvXzZdfvv2bcFuFHfgwAHTzyoqKjrdKC46Otp0HS8vr16zAVlXgq7RaPDII4/g2rVrAHrvnAwGA9auXYtnnnmmw66DALr0vGvdeKztHiXHjx9Hv379eDvhyf3m1ZmQkBCIRCLExcUB6J3z6kkUdMKbixcvom/fvjhz5gySkpKwevVqDBgwoFfup30vMpkM169fR1ZWFkJDQzF79mwMGjQIJSUlAIyrDocNGwZ/f39ER0dj8uTJmDx5Ms+j7qiqqgpqtRpqtRoikQiHDh2CWq02beC3b98+DBgwwPSds52dXae7rb388suIjIxESEgIJBIJr7t4/dqcqqqqsHHjRoSHhyMrKwu+vr4YP348JBKJ2Qt/b5sTAHz88cfo378/rl+/brb7Vm1trek693vete7eNWfOHMTGxsLT0xNWVla87t51v3mlp6djx44diI6ORlZWFq5du4YRI0Zg2rRppvvojfPqSRR0wqsjR45g2LBh6NOnD6ytrREREcH3kDhZunQphgwZgj59+mDo0KFYunSp6fs84O4BPp5++mk88cQTWLRoEQoLC3kccecCAgI6HLBDJBLB3t4ewN0Dy/zpT39C3759MWvWLKSkpJjdh1arxbJly/DUU0+hX79+WLFiBa8HYfm1OdXW1mLOnDmwsrLCY489BrFYDAcHhw5vJnvbnAB0OieRSITTp0+brtOV5112djbmzZuHxx9/HIMGDYJMJuP1ACz3m1dubi6mTZuGgQMHom/fvhg1ahQ2bdrU4ZzovW1ePYmCTgghhFgACjohhBBiASjohBBCiAWgoBNCCCEWgIJOCCGEWAAKOiGEEGIBKOiEEEKIBaCgE0IIIRaAgk4IIYRYAAo6IYQQYgEo6IQQQogFoKATQgghFuD/AXdGIXMBggxiAAAAAElFTkSuQmCC\" width=\"500\">"
+ ],
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
"source": [
"f = boz.inspect_rois(dataM, rois, rois_th)"
]
@@ -289,7 +2738,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
@@ -298,9 +2747,799 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 18,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "application/javascript": [
+ "/* Put everything inside the global mpl namespace */\n",
+ "window.mpl = {};\n",
+ "\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('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",
+ "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 = $('<div/>');\n",
+ " this._root_extra_style(this.root)\n",
+ " this.root.attr('style', 'display: inline-block');\n",
+ "\n",
+ " $(parent_element).append(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 (mpl.ratio != 1) {\n",
+ " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.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 = $(\n",
+ " '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
+ " 'ui-helper-clearfix\"/>');\n",
+ " var titletext = $(\n",
+ " '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
+ " 'text-align: center; padding: 3px;\"/>');\n",
+ " titlebar.append(titletext)\n",
+ " this.root.append(titlebar);\n",
+ " this.header = titletext[0];\n",
+ "}\n",
+ "\n",
+ "\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
+ "\n",
+ "}\n",
+ "\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
+ "\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._init_canvas = function() {\n",
+ " var fig = this;\n",
+ "\n",
+ " var canvas_div = $('<div/>');\n",
+ "\n",
+ " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
+ "\n",
+ " function canvas_keyboard_event(event) {\n",
+ " return fig.key_event(event, event['data']);\n",
+ " }\n",
+ "\n",
+ " canvas_div.keydown('key_press', canvas_keyboard_event);\n",
+ " canvas_div.keyup('key_release', canvas_keyboard_event);\n",
+ " this.canvas_div = canvas_div\n",
+ " this._canvas_extra_style(canvas_div)\n",
+ " this.root.append(canvas_div);\n",
+ "\n",
+ " var canvas = $('<canvas/>');\n",
+ " canvas.addClass('mpl-canvas');\n",
+ " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
+ "\n",
+ " this.canvas = canvas[0];\n",
+ " this.context = canvas[0].getContext(\"2d\");\n",
+ "\n",
+ " var backingStore = this.context.backingStorePixelRatio ||\n",
+ "\tthis.context.webkitBackingStorePixelRatio ||\n",
+ "\tthis.context.mozBackingStorePixelRatio ||\n",
+ "\tthis.context.msBackingStorePixelRatio ||\n",
+ "\tthis.context.oBackingStorePixelRatio ||\n",
+ "\tthis.context.backingStorePixelRatio || 1;\n",
+ "\n",
+ " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+ "\n",
+ " var rubberband = $('<canvas/>');\n",
+ " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
+ "\n",
+ " var pass_mouse_events = true;\n",
+ "\n",
+ " canvas_div.resizable({\n",
+ " start: function(event, ui) {\n",
+ " pass_mouse_events = false;\n",
+ " },\n",
+ " resize: function(event, ui) {\n",
+ " fig.request_resize(ui.size.width, ui.size.height);\n",
+ " },\n",
+ " stop: function(event, ui) {\n",
+ " pass_mouse_events = true;\n",
+ " fig.request_resize(ui.size.width, ui.size.height);\n",
+ " },\n",
+ " });\n",
+ "\n",
+ " function mouse_event_fn(event) {\n",
+ " if (pass_mouse_events)\n",
+ " return fig.mouse_event(event, event['data']);\n",
+ " }\n",
+ "\n",
+ " rubberband.mousedown('button_press', mouse_event_fn);\n",
+ " rubberband.mouseup('button_release', mouse_event_fn);\n",
+ " // Throttle sequential mouse events to 1 every 20ms.\n",
+ " rubberband.mousemove('motion_notify', mouse_event_fn);\n",
+ "\n",
+ " rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
+ " rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
+ "\n",
+ " canvas_div.on(\"wheel\", function (event) {\n",
+ " event = event.originalEvent;\n",
+ " event['data'] = 'scroll'\n",
+ " if (event.deltaY < 0) {\n",
+ " event.step = 1;\n",
+ " } else {\n",
+ " event.step = -1;\n",
+ " }\n",
+ " mouse_event_fn(event);\n",
+ " });\n",
+ "\n",
+ " canvas_div.append(canvas);\n",
+ " canvas_div.append(rubberband);\n",
+ "\n",
+ " this.rubberband = rubberband;\n",
+ " this.rubberband_canvas = rubberband[0];\n",
+ " this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
+ " this.rubberband_context.strokeStyle = \"#000000\";\n",
+ "\n",
+ " this._resize_canvas = function(width, height) {\n",
+ " // Keep the size of the canvas, canvas container, and rubber band\n",
+ " // canvas in synch.\n",
+ " canvas_div.css('width', width)\n",
+ " canvas_div.css('height', height)\n",
+ "\n",
+ " canvas.attr('width', width * mpl.ratio);\n",
+ " canvas.attr('height', height * mpl.ratio);\n",
+ " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
+ "\n",
+ " rubberband.attr('width', width);\n",
+ " rubberband.attr('height', height);\n",
+ " }\n",
+ "\n",
+ " // Set the figure to an initial 600x600px, this will subsequently be updated\n",
+ " // upon first draw.\n",
+ " this._resize_canvas(600, 600);\n",
+ "\n",
+ " // Disable right mouse context menu.\n",
+ " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\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 nav_element = $('<div/>');\n",
+ " nav_element.attr('style', 'width: 100%');\n",
+ " this.root.append(nav_element);\n",
+ "\n",
+ " // Define a callback function for later on.\n",
+ " function toolbar_event(event) {\n",
+ " return fig.toolbar_button_onclick(event['data']);\n",
+ " }\n",
+ " function toolbar_mouse_event(event) {\n",
+ " return fig.toolbar_button_onmouseover(event['data']);\n",
+ " }\n",
+ "\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",
+ " // put a spacer in here.\n",
+ " continue;\n",
+ " }\n",
+ " var button = $('<button/>');\n",
+ " button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
+ " 'ui-button-icon-only');\n",
+ " button.attr('role', 'button');\n",
+ " button.attr('aria-disabled', 'false');\n",
+ " button.click(method_name, toolbar_event);\n",
+ " button.mouseover(tooltip, toolbar_mouse_event);\n",
+ "\n",
+ " var icon_img = $('<span/>');\n",
+ " icon_img.addClass('ui-button-icon-primary ui-icon');\n",
+ " icon_img.addClass(image);\n",
+ " icon_img.addClass('ui-corner-all');\n",
+ "\n",
+ " var tooltip_span = $('<span/>');\n",
+ " tooltip_span.addClass('ui-button-text');\n",
+ " tooltip_span.html(tooltip);\n",
+ "\n",
+ " button.append(icon_img);\n",
+ " button.append(tooltip_span);\n",
+ "\n",
+ " nav_element.append(button);\n",
+ " }\n",
+ "\n",
+ " var fmt_picker_span = $('<span/>');\n",
+ "\n",
+ " var fmt_picker = $('<select/>');\n",
+ " fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
+ " fmt_picker_span.append(fmt_picker);\n",
+ " nav_element.append(fmt_picker_span);\n",
+ " this.format_dropdown = fmt_picker[0];\n",
+ "\n",
+ " for (var ind in mpl.extensions) {\n",
+ " var fmt = mpl.extensions[ind];\n",
+ " var option = $(\n",
+ " '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
+ " fmt_picker.append(option);\n",
+ " }\n",
+ "\n",
+ " // Add hover states to the ui-buttons\n",
+ " $( \".ui-button\" ).hover(\n",
+ " function() { $(this).addClass(\"ui-state-hover\");},\n",
+ " function() { $(this).removeClass(\"ui-state-hover\");}\n",
+ " );\n",
+ "\n",
+ " var status_bar = $('<span class=\"mpl-message\"/>');\n",
+ " nav_element.append(status_bar);\n",
+ " this.message = status_bar[0];\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",
+ "\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",
+ "\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]);\n",
+ " fig.send_message(\"refresh\", {});\n",
+ " };\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
+ " var x0 = msg['x0'] / mpl.ratio;\n",
+ " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
+ " var x1 = msg['x1'] / mpl.ratio;\n",
+ " var y1 = (fig.canvas.height - msg['y1']) / mpl.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, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\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",
+ " {\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.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",
+ " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+ " evt.data);\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ " else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\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(\"No handler for the '\" + msg_type + \"' message type: \", msg);\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(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\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",
+ " if (e.target)\n",
+ " targ = e.target;\n",
+ " else if (e.srcElement)\n",
+ " targ = e.srcElement;\n",
+ " if (targ.nodeType == 3) // defeat Safari bug\n",
+ " targ = targ.parentNode;\n",
+ "\n",
+ " // jQuery normalizes the pageX and pageY\n",
+ " // pageX,Y are the mouse positions relative to the document\n",
+ " // offset() returns the position of the element relative to the document\n",
+ " var x = e.pageX - $(targ).offset().left;\n",
+ " var y = e.pageY - $(targ).offset().top;\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",
+ " 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",
+ " {\n",
+ " this.canvas.focus();\n",
+ " this.canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " var x = canvas_pos.x * mpl.ratio;\n",
+ " var y = canvas_pos.y * mpl.ratio;\n",
+ "\n",
+ " this.send_message(name, {x: x, y: y, button: event.button,\n",
+ " step: event.step,\n",
+ " guiEvent: simpleKeys(event)});\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",
+ "\n",
+ " // Prevent repeat events\n",
+ " if (name == 'key_press')\n",
+ " {\n",
+ " if (event.which === this._key)\n",
+ " return;\n",
+ " else\n",
+ " this._key = event.which;\n",
+ " }\n",
+ " if (name == 'key_release')\n",
+ " this._key = null;\n",
+ "\n",
+ " var value = '';\n",
+ " if (event.ctrlKey && event.which != 17)\n",
+ " value += \"ctrl+\";\n",
+ " if (event.altKey && event.which != 18)\n",
+ " value += \"alt+\";\n",
+ " if (event.shiftKey && event.which != 16)\n",
+ " value += \"shift+\";\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,\n",
+ " 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",
+ "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\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"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\";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 = $(\"#\" + id);\n",
+ " var ws_proxy = comm_websocket_adapter(comm)\n",
+ "\n",
+ " function ondownload(figure, format) {\n",
+ " window.open(figure.imageObj.src);\n",
+ " }\n",
+ "\n",
+ " var fig = new mpl.figure(id, ws_proxy,\n",
+ " ondownload,\n",
+ " element.get(0));\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.get(0);\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",
+ "\n",
+ " var output_index = fig.cell_info[2]\n",
+ " var cell = fig.cell_info[0];\n",
+ "\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
+ " var width = fig.canvas.width/mpl.ratio\n",
+ " fig.root.unbind('remove')\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).html('<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/mpl.ratio\n",
+ " var dataURL = this.canvas.toDataURL();\n",
+ " this.cell_info[1]['text/html'] = '<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 () { fig.push_to_output() }, 1000);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function() {\n",
+ " var fig = this;\n",
+ "\n",
+ " var nav_element = $('<div/>');\n",
+ " nav_element.attr('style', 'width: 100%');\n",
+ " this.root.append(nav_element);\n",
+ "\n",
+ " // Define a callback function for later on.\n",
+ " function toolbar_event(event) {\n",
+ " return fig.toolbar_button_onclick(event['data']);\n",
+ " }\n",
+ " function toolbar_mouse_event(event) {\n",
+ " return fig.toolbar_button_onmouseover(event['data']);\n",
+ " }\n",
+ "\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) { continue; };\n",
+ "\n",
+ " var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
+ " button.click(method_name, toolbar_event);\n",
+ " button.mouseover(tooltip, toolbar_mouse_event);\n",
+ " nav_element.append(button);\n",
+ " }\n",
+ "\n",
+ " // Add the status bar.\n",
+ " var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
+ " nav_element.append(status_bar);\n",
+ " this.message = status_bar[0];\n",
+ "\n",
+ " // Add the close button to the window.\n",
+ " var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
+ " var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
+ " button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
+ " button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
+ " buttongrp.append(button);\n",
+ " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
+ " titlebar.prepend(buttongrp);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function(el){\n",
+ " var fig = this\n",
+ " el.on(\"remove\", function(){\n",
+ "\tfig.close_ws(fig, {});\n",
+ " });\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function(el){\n",
+ " // this is important to make the div 'focusable\n",
+ " el.attr('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",
+ " }\n",
+ " else {\n",
+ " // location in version 2\n",
+ " IPython.keyboard_manager.register_events(el);\n",
+ " }\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",
+ " // 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",
+ "\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('matplotlib', mpl.mpl_figure_comm);\n",
+ "}\n"
+ ],
+ "text/plain": [
+ "<IPython.core.display.Javascript object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "text/html": [
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\" width=\"600\">"
+ ],
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
"source": [
"f = boz.inspect_plane_fitting(dataM/ff, rois)"
]
@@ -321,32 +3560,45 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 68,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "darkrunNB = 671\n",
+ "\n",
+ "runNB = 690\n",
+ "xaxis = 'delay_mm'\n",
+ "\n",
+ "#runNB = 686\n",
+ "#xaxis = 'nrj'"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 69,
"metadata": {},
"outputs": [],
"source": [
"# load data\n",
- "arr, tid = boz.load_dssc_module(proposalNB, runNB, moduleNB)\n",
- "arr_dark, tid_dark = boz.load_dssc_module(proposalNB, darkrunNB, moduleNB)\n",
+ "arr, tid = boz.load_dssc_module(proposal, runNB, moduleNB)\n",
+ "arr_dark, tid_dark = boz.load_dssc_module(proposal, darkrunNB, moduleNB)\n",
"\n",
"# make sure to rechunk the arrays\n",
"arr = arr.rechunk((100,-1,-1,-1))\n",
"arr_dark = arr_dark.rechunk((100,-1,-1,-1))\n",
"\n",
"#no correction\n",
- "data = boz.process(np.arange(2**9), arr_dark, arr, tid, rois, params.get_mask(),\n",
- " np.ones_like(ff), params.sat_level)\n",
+ "#data = boz.process(np.arange(2**9), arr_dark, arr, tid, rois, params.get_mask(),\n",
+ "# np.ones_like(ff), params.sat_level)\n",
"#with flat field correction\n",
- "data_ff = boz.process(np.arange(2**9), arr_dark, arr, tid, rois, params.get_mask(),\n",
- " ff, params.sat_level)\n",
+ "#data = boz.process(np.arange(2**9), arr_dark, arr, tid, rois, params.get_mask(),\n",
+ "# ff, params.sat_level)\n",
"# with flat field and non linear correction\n",
- "data_ff_nl = boz.process(params.get_Fnl(), arr_dark, arr, tid, rois, params.get_mask(),\n",
+ "data = boz.process(params.get_Fnl(), arr_dark, arr, tid, rois, params.get_mask(),\n",
" ff, params.sat_level)\n",
"\n",
"# drop saturated shots\n",
- "d = data.where(data['sat_sat'] == False, drop=True)\n",
- "d_ff = data_ff.where(data_ff['sat_sat'] == False, drop=True)\n",
- "d_ff_nl = data_ff_nl.where(data_ff_nl['sat_sat'] == False, drop=True)"
+ "d = data.where(data['sat_sat'] == False, drop=True)"
]
},
{
@@ -358,78 +3610,880 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 70,
"metadata": {},
"outputs": [],
"source": [
- "run, data = tb.load(proposalNB, runNB, ['nrj'])"
+ "run, data = tb.load(proposal, runNB, ['PP800_DelayLine', 'nrj', 'BAM1932M'])"
]
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 71,
"metadata": {},
"outputs": [],
"source": [
- "r = xr.merge([data, d], join='inner')\n",
- "r_ff = xr.merge([data, d_ff], join='inner')\n",
- "r_ff_nl = xr.merge([data, d_ff_nl], join='inner')"
+ "r = xr.merge([data, d], join='inner')"
]
},
{
"cell_type": "code",
- "execution_count": null,
- "metadata": {
- "scrolled": false
- },
+ "execution_count": 104,
+ "metadata": {},
"outputs": [],
"source": [
- "res = tb.xas(r_ff_nl, 0.1, Iokey = '0', Itkey = 'n', nrjkey = 'nrj', plot=True)"
+ "bam = r['BAM1932M'] - r['BAM1932M'].mean()\n",
+ "bam['sa3_pId'] = np.arange(20)\n",
+ "bam = bam.rename(sa3_pId = 'pulseId')\n",
+ "\n",
+ "r['delay_ps'] = tb.misc.laser_utils.positionToDelay(r['PP800_DelayLine'], invert=True) + bam\n",
+ "r['delay_mm'] = r['delay_ps']*0.15"
]
},
{
- "cell_type": "markdown",
- "metadata": {},
+ "cell_type": "code",
+ "execution_count": 105,
+ "metadata": {
+ "scrolled": false
+ },
+ "outputs": [],
"source": [
- "# Comparison spectra between the different correction"
+ "if xaxis == 'delay_mm':\n",
+ " bin_width = 0.05*0.15 #0.15mm is 1ps\n",
+ "else:\n",
+ " bin_width = 0.1\n",
+ "\n",
+ "dXAS = tb.xas(r, bin_width, Iokey = 'p', Itkey = 'n', nrjkey = xaxis, plot=False)\n",
+ "XASp = tb.xas(r, bin_width, Iokey = '0', Itkey = 'p', nrjkey = xaxis, plot=False)\n",
+ "XASn = tb.xas(r, bin_width, Iokey = '0', Itkey = 'n', nrjkey = xaxis, plot=False)"
]
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 106,
"metadata": {},
"outputs": [],
"source": [
- "res = tb.xas(r, 0.1, Iokey = '0', Itkey = 'n', nrjkey = 'nrj', plot=False)\n",
- "res_ff = tb.xas(r_ff, 0.1, Iokey = '0', Itkey = 'n', nrjkey = 'nrj', plot=False)\n",
- "res_ff_nl = tb.xas(r_ff_nl, 0.1, Iokey = '0', Itkey = 'n', nrjkey = 'nrj', plot=False)"
+ "ph = r['nrj'].mean().values\n",
+ "t0 = 50.45\n",
+ "t = t0 + r['delay_ps'].mean().values"
]
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 107,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "application/javascript": [
+ "/* Put everything inside the global mpl namespace */\n",
+ "window.mpl = {};\n",
+ "\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('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",
+ "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 = $('<div/>');\n",
+ " this._root_extra_style(this.root)\n",
+ " this.root.attr('style', 'display: inline-block');\n",
+ "\n",
+ " $(parent_element).append(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 (mpl.ratio != 1) {\n",
+ " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.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 = $(\n",
+ " '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
+ " 'ui-helper-clearfix\"/>');\n",
+ " var titletext = $(\n",
+ " '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
+ " 'text-align: center; padding: 3px;\"/>');\n",
+ " titlebar.append(titletext)\n",
+ " this.root.append(titlebar);\n",
+ " this.header = titletext[0];\n",
+ "}\n",
+ "\n",
+ "\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
+ "\n",
+ "}\n",
+ "\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
+ "\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._init_canvas = function() {\n",
+ " var fig = this;\n",
+ "\n",
+ " var canvas_div = $('<div/>');\n",
+ "\n",
+ " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
+ "\n",
+ " function canvas_keyboard_event(event) {\n",
+ " return fig.key_event(event, event['data']);\n",
+ " }\n",
+ "\n",
+ " canvas_div.keydown('key_press', canvas_keyboard_event);\n",
+ " canvas_div.keyup('key_release', canvas_keyboard_event);\n",
+ " this.canvas_div = canvas_div\n",
+ " this._canvas_extra_style(canvas_div)\n",
+ " this.root.append(canvas_div);\n",
+ "\n",
+ " var canvas = $('<canvas/>');\n",
+ " canvas.addClass('mpl-canvas');\n",
+ " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
+ "\n",
+ " this.canvas = canvas[0];\n",
+ " this.context = canvas[0].getContext(\"2d\");\n",
+ "\n",
+ " var backingStore = this.context.backingStorePixelRatio ||\n",
+ "\tthis.context.webkitBackingStorePixelRatio ||\n",
+ "\tthis.context.mozBackingStorePixelRatio ||\n",
+ "\tthis.context.msBackingStorePixelRatio ||\n",
+ "\tthis.context.oBackingStorePixelRatio ||\n",
+ "\tthis.context.backingStorePixelRatio || 1;\n",
+ "\n",
+ " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+ "\n",
+ " var rubberband = $('<canvas/>');\n",
+ " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
+ "\n",
+ " var pass_mouse_events = true;\n",
+ "\n",
+ " canvas_div.resizable({\n",
+ " start: function(event, ui) {\n",
+ " pass_mouse_events = false;\n",
+ " },\n",
+ " resize: function(event, ui) {\n",
+ " fig.request_resize(ui.size.width, ui.size.height);\n",
+ " },\n",
+ " stop: function(event, ui) {\n",
+ " pass_mouse_events = true;\n",
+ " fig.request_resize(ui.size.width, ui.size.height);\n",
+ " },\n",
+ " });\n",
+ "\n",
+ " function mouse_event_fn(event) {\n",
+ " if (pass_mouse_events)\n",
+ " return fig.mouse_event(event, event['data']);\n",
+ " }\n",
+ "\n",
+ " rubberband.mousedown('button_press', mouse_event_fn);\n",
+ " rubberband.mouseup('button_release', mouse_event_fn);\n",
+ " // Throttle sequential mouse events to 1 every 20ms.\n",
+ " rubberband.mousemove('motion_notify', mouse_event_fn);\n",
+ "\n",
+ " rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
+ " rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
+ "\n",
+ " canvas_div.on(\"wheel\", function (event) {\n",
+ " event = event.originalEvent;\n",
+ " event['data'] = 'scroll'\n",
+ " if (event.deltaY < 0) {\n",
+ " event.step = 1;\n",
+ " } else {\n",
+ " event.step = -1;\n",
+ " }\n",
+ " mouse_event_fn(event);\n",
+ " });\n",
+ "\n",
+ " canvas_div.append(canvas);\n",
+ " canvas_div.append(rubberband);\n",
+ "\n",
+ " this.rubberband = rubberband;\n",
+ " this.rubberband_canvas = rubberband[0];\n",
+ " this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
+ " this.rubberband_context.strokeStyle = \"#000000\";\n",
+ "\n",
+ " this._resize_canvas = function(width, height) {\n",
+ " // Keep the size of the canvas, canvas container, and rubber band\n",
+ " // canvas in synch.\n",
+ " canvas_div.css('width', width)\n",
+ " canvas_div.css('height', height)\n",
+ "\n",
+ " canvas.attr('width', width * mpl.ratio);\n",
+ " canvas.attr('height', height * mpl.ratio);\n",
+ " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
+ "\n",
+ " rubberband.attr('width', width);\n",
+ " rubberband.attr('height', height);\n",
+ " }\n",
+ "\n",
+ " // Set the figure to an initial 600x600px, this will subsequently be updated\n",
+ " // upon first draw.\n",
+ " this._resize_canvas(600, 600);\n",
+ "\n",
+ " // Disable right mouse context menu.\n",
+ " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\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 nav_element = $('<div/>');\n",
+ " nav_element.attr('style', 'width: 100%');\n",
+ " this.root.append(nav_element);\n",
+ "\n",
+ " // Define a callback function for later on.\n",
+ " function toolbar_event(event) {\n",
+ " return fig.toolbar_button_onclick(event['data']);\n",
+ " }\n",
+ " function toolbar_mouse_event(event) {\n",
+ " return fig.toolbar_button_onmouseover(event['data']);\n",
+ " }\n",
+ "\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",
+ " // put a spacer in here.\n",
+ " continue;\n",
+ " }\n",
+ " var button = $('<button/>');\n",
+ " button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
+ " 'ui-button-icon-only');\n",
+ " button.attr('role', 'button');\n",
+ " button.attr('aria-disabled', 'false');\n",
+ " button.click(method_name, toolbar_event);\n",
+ " button.mouseover(tooltip, toolbar_mouse_event);\n",
+ "\n",
+ " var icon_img = $('<span/>');\n",
+ " icon_img.addClass('ui-button-icon-primary ui-icon');\n",
+ " icon_img.addClass(image);\n",
+ " icon_img.addClass('ui-corner-all');\n",
+ "\n",
+ " var tooltip_span = $('<span/>');\n",
+ " tooltip_span.addClass('ui-button-text');\n",
+ " tooltip_span.html(tooltip);\n",
+ "\n",
+ " button.append(icon_img);\n",
+ " button.append(tooltip_span);\n",
+ "\n",
+ " nav_element.append(button);\n",
+ " }\n",
+ "\n",
+ " var fmt_picker_span = $('<span/>');\n",
+ "\n",
+ " var fmt_picker = $('<select/>');\n",
+ " fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
+ " fmt_picker_span.append(fmt_picker);\n",
+ " nav_element.append(fmt_picker_span);\n",
+ " this.format_dropdown = fmt_picker[0];\n",
+ "\n",
+ " for (var ind in mpl.extensions) {\n",
+ " var fmt = mpl.extensions[ind];\n",
+ " var option = $(\n",
+ " '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
+ " fmt_picker.append(option);\n",
+ " }\n",
+ "\n",
+ " // Add hover states to the ui-buttons\n",
+ " $( \".ui-button\" ).hover(\n",
+ " function() { $(this).addClass(\"ui-state-hover\");},\n",
+ " function() { $(this).removeClass(\"ui-state-hover\");}\n",
+ " );\n",
+ "\n",
+ " var status_bar = $('<span class=\"mpl-message\"/>');\n",
+ " nav_element.append(status_bar);\n",
+ " this.message = status_bar[0];\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",
+ "\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",
+ "\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]);\n",
+ " fig.send_message(\"refresh\", {});\n",
+ " };\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
+ " var x0 = msg['x0'] / mpl.ratio;\n",
+ " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
+ " var x1 = msg['x1'] / mpl.ratio;\n",
+ " var y1 = (fig.canvas.height - msg['y1']) / mpl.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, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\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",
+ " {\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.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",
+ " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+ " evt.data);\n",
+ " fig.updated_canvas_event();\n",
+ " fig.waiting = false;\n",
+ " return;\n",
+ " }\n",
+ " else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\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(\"No handler for the '\" + msg_type + \"' message type: \", msg);\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(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\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",
+ " if (e.target)\n",
+ " targ = e.target;\n",
+ " else if (e.srcElement)\n",
+ " targ = e.srcElement;\n",
+ " if (targ.nodeType == 3) // defeat Safari bug\n",
+ " targ = targ.parentNode;\n",
+ "\n",
+ " // jQuery normalizes the pageX and pageY\n",
+ " // pageX,Y are the mouse positions relative to the document\n",
+ " // offset() returns the position of the element relative to the document\n",
+ " var x = e.pageX - $(targ).offset().left;\n",
+ " var y = e.pageY - $(targ).offset().top;\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",
+ " 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",
+ " {\n",
+ " this.canvas.focus();\n",
+ " this.canvas_div.focus();\n",
+ " }\n",
+ "\n",
+ " var x = canvas_pos.x * mpl.ratio;\n",
+ " var y = canvas_pos.y * mpl.ratio;\n",
+ "\n",
+ " this.send_message(name, {x: x, y: y, button: event.button,\n",
+ " step: event.step,\n",
+ " guiEvent: simpleKeys(event)});\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",
+ "\n",
+ " // Prevent repeat events\n",
+ " if (name == 'key_press')\n",
+ " {\n",
+ " if (event.which === this._key)\n",
+ " return;\n",
+ " else\n",
+ " this._key = event.which;\n",
+ " }\n",
+ " if (name == 'key_release')\n",
+ " this._key = null;\n",
+ "\n",
+ " var value = '';\n",
+ " if (event.ctrlKey && event.which != 17)\n",
+ " value += \"ctrl+\";\n",
+ " if (event.altKey && event.which != 18)\n",
+ " value += \"alt+\";\n",
+ " if (event.shiftKey && event.which != 16)\n",
+ " value += \"shift+\";\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,\n",
+ " 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",
+ "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\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"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\";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 = $(\"#\" + id);\n",
+ " var ws_proxy = comm_websocket_adapter(comm)\n",
+ "\n",
+ " function ondownload(figure, format) {\n",
+ " window.open(figure.imageObj.src);\n",
+ " }\n",
+ "\n",
+ " var fig = new mpl.figure(id, ws_proxy,\n",
+ " ondownload,\n",
+ " element.get(0));\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.get(0);\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",
+ "\n",
+ " var output_index = fig.cell_info[2]\n",
+ " var cell = fig.cell_info[0];\n",
+ "\n",
+ "};\n",
+ "\n",
+ "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
+ " var width = fig.canvas.width/mpl.ratio\n",
+ " fig.root.unbind('remove')\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).html('<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/mpl.ratio\n",
+ " var dataURL = this.canvas.toDataURL();\n",
+ " this.cell_info[1]['text/html'] = '<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 () { fig.push_to_output() }, 1000);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._init_toolbar = function() {\n",
+ " var fig = this;\n",
+ "\n",
+ " var nav_element = $('<div/>');\n",
+ " nav_element.attr('style', 'width: 100%');\n",
+ " this.root.append(nav_element);\n",
+ "\n",
+ " // Define a callback function for later on.\n",
+ " function toolbar_event(event) {\n",
+ " return fig.toolbar_button_onclick(event['data']);\n",
+ " }\n",
+ " function toolbar_mouse_event(event) {\n",
+ " return fig.toolbar_button_onmouseover(event['data']);\n",
+ " }\n",
+ "\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) { continue; };\n",
+ "\n",
+ " var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
+ " button.click(method_name, toolbar_event);\n",
+ " button.mouseover(tooltip, toolbar_mouse_event);\n",
+ " nav_element.append(button);\n",
+ " }\n",
+ "\n",
+ " // Add the status bar.\n",
+ " var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
+ " nav_element.append(status_bar);\n",
+ " this.message = status_bar[0];\n",
+ "\n",
+ " // Add the close button to the window.\n",
+ " var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
+ " var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
+ " button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
+ " button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
+ " buttongrp.append(button);\n",
+ " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
+ " titlebar.prepend(buttongrp);\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._root_extra_style = function(el){\n",
+ " var fig = this\n",
+ " el.on(\"remove\", function(){\n",
+ "\tfig.close_ws(fig, {});\n",
+ " });\n",
+ "}\n",
+ "\n",
+ "mpl.figure.prototype._canvas_extra_style = function(el){\n",
+ " // this is important to make the div 'focusable\n",
+ " el.attr('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",
+ " }\n",
+ " else {\n",
+ " // location in version 2\n",
+ " IPython.keyboard_manager.register_events(el);\n",
+ " }\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",
+ " // 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",
+ "\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('matplotlib', mpl.mpl_figure_comm);\n",
+ "}\n"
+ ],
+ "text/plain": [
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+ "output_type": "display_data"
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\" width=\"640\">"
+ ],
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
"source": [
"f = plt.figure()\n",
"ax = f.gca()\n",
- "ax.errorbar(res['nrj'], res['muA'] - res['muA'][0], res['sterrA'], label='raw')\n",
- "ax.errorbar(res_ff['nrj'], res_ff['muA'] - res_ff['muA'][0], res_ff['sterrA'], label='ff')\n",
- "ax.errorbar(res_ff_nl['nrj'], res_ff_nl['muA'] - res_ff_nl['muA'][0], res_ff_nl['sterrA'], label='ff+nl')\n",
- "ax.set_xlabel('Energy (eV)')\n",
- "ax.set_ylabel('XAS')\n",
- "ax.set_xlim([695, 740])\n",
- "ax.legend(loc=2)\n",
- "\n",
- "from mpl_toolkits.axes_grid1.inset_locator import inset_axes, mark_inset\n",
- "\n",
- "axins = inset_axes(ax, width='40%', height='30%', loc=1)\n",
- "axins.errorbar(res['nrj'], res['muA'] - res['muA'][0], res['sterrA'], label='raw')\n",
- "axins.errorbar(res_ff['nrj'], res_ff['muA'] - res_ff['muA'][0], res_ff['sterrA'], label='ff')\n",
- "axins.errorbar(res_ff_nl['nrj'], res_ff_nl['muA'] - res_ff_nl['muA'][0], res_ff_nl['sterrA'], label='ff+nl')\n",
- "axins.set_xlim([695, 698])\n",
- "axins.set_ylim([-0.005, 0.005])\n",
- "mark_inset(ax, axins, loc1=2, loc2=4, fc=\"none\", ec=\"0.5\")"
+ "ax.errorbar(dXAS['nrj'], dXAS['muA'] - dXAS['muA'][0], dXAS['sterrA'], c='C3')\n",
+ "ax.set_ylabel('dXAS')\n",
+ "ax.set_title(f'p: {proposal} run: {runNB} dark: {darkrunNB}')\n",
+ "if xaxis == 'delay_mm':\n",
+ " ax.set_xlabel('delay (mm)')\n",
+ " ax.axvline(-t0*0.15, c='k', alpha=0.5, ls='--')\n",
+ " ax.text(0.02, 0.85, f'E = {ph:.1f} eV', transform=ax.transAxes)\n",
+ " secax = ax.secondary_xaxis('top', functions=(lambda x: x/0.15 + t0, lambda x: (x - t0)*0.15))\n",
+ " secax.set_xlabel('delay (ps)')\n",
+ "if xaxis == 'nrj':\n",
+ " ax.set_xlabel('Energy (eV)')\n",
+ " ax.text(0.02, 0.85, f't = {t:.1f} ps', transform=ax.transAxes)\n",
+ " ax2 = ax.twinx()\n",
+ " ax2.errorbar(XASp['nrj'], XASp['muA'] - XASp['muA'][0], XASp['sterrA'], label='p')\n",
+ " ax2.errorbar(XASn['nrj'], XASn['muA'] - XASn['muA'][0], XASn['sterrA'], label='n')\n",
+ " ax2.set_ylabel('XAS')\n",
+ " ax.legend(loc=2)"
]
},
{
diff --git a/doc/howtos.rst b/doc/howtos.rst
index 716e45b..59df406 100644
--- a/doc/howtos.rst
+++ b/doc/howtos.rst
@@ -41,14 +41,33 @@ routines
BOZ: Beam-Splitting Off-axis Zone plate analysis
++++++++++++++++++++++++++++++++++++++++++++++++
-The BOZ analysis consists of 2 notebooks and a script. The first notebook is used to determine
-all the correction. The input are a dark run and a run with X-ray on empty sample or at the pre-edge.
-The result is a JSON file that contains the flat field and non-linearity correction. The determination
-of the non-linearity correction can take some 2 to 8 hours depending on the number of pulses in the
-train. For this reason it is possible to use a script 'scripts/boz_parameters_job.sh' in the toolbox to
-launch the first notebook via slurm. It requires 'papermill' to be installed.
-
-The second notebook then use the JSON file to load all needed correction and process an run with a
-corresponding dark run to bin data and compute a spectrum or a time resolved XAS scan.
-* :doc:`BOZ analysis part I parameters determination <BOZ analysis part I parameters determination>`.
-* :doc:`BOZ analysis part II run processing <BOZ analysis part II run processing>`.
+The BOZ analysis consists of 2 notebooks and a script. The first notebook
+:doc:`BOZ analysis part I parameters determination <BOZ analysis part I parameters determination>`
+is used to determine all the necessary correction, that is the flat field
+correction from the zone plate optics and the non-linearity correction from the
+DSSC gain. The inputs are a dark run and a run with X-rays on three broken or
+empty membranes. For the latter, an alternative is to use pre-edge data on an
+actual sample. The result is a JSON file that contains the flat field and
+non-linearity correction as well as the parameters used for their determination
+such that this can be reproduced and investigated in case of issues. The
+determination of the flat field correction is rather quick, few minutes and is
+the most important correction for the change in XAS computed from the 1st and
+1st order. For quick correction of the online preview one can bypass the
+non-linearity calculation by taking the JSON file as soon as it appears.
+The determination of the non-linearity correction is a lot longer and can take
+some 2 to 8 hours depending on the number of pulses in the
+train. For this reason it is possible to use a script
+``scripts/boz_parameters_job.sh`` in the toolbox to launch the first notebook
+via slurm:
+
+``sbatch ./boz_parameters_job.sh 615 614 3``
+
+where 615 is the dark run number, 614 is the run on 3 broken membranes and 3 is
+the DSSC gain in photon per bin. The proposal run number is defined inside the
+script file.
+
+The second notebook
+:doc:`BOZ analysis part II run processing <BOZ analysis part II run processing>`
+then use the JSON file to load all needed corrections and
+process an run with a corresponding dark run to bin data and compute a
+spectrum or a time resolved XAS scan
diff --git a/setup.py b/setup.py
index fc1c33f..202ee0d 100644
--- a/setup.py
+++ b/setup.py
@@ -2,7 +2,7 @@ from setuptools import setup, find_packages
with open('README.rst') as f:
readme = f.read()
-
+
with open('VERSION') as f:
_version = f.read()
_version = _version.strip("\n")
@@ -12,7 +12,7 @@ basic_analysis_reqs = ['numpy', 'scipy',] # and is readily available in Karabo
advanced_analysis_reqs = [
'pandas', 'imageio', 'xarray>=0.13.0', 'h5py', 'h5netcdf',]
interactive_reqs = ['ipykernel', 'matplotlib', 'tqdm',]
-maxwell_reqs = ['joblib', 'extra_data', 'euxfel_bunch_pattern>=0.6']
+maxwell_reqs = ['joblib', 'papermill', 'extra_data', 'euxfel_bunch_pattern>=0.6']
setup(name='toolbox_scs',
diff --git a/src/toolbox_scs/routines/boz.py b/src/toolbox_scs/routines/boz.py
index 9c281c8..398dc70 100644
--- a/src/toolbox_scs/routines/boz.py
+++ b/src/toolbox_scs/routines/boz.py
@@ -577,7 +577,7 @@ def inspect_histogram(proposalNB, runNB, moduleNB,
def load_dssc_module(proposalNB, runNB, moduleNB=15,
- subset=slice(None), drop_intra_darks=True, persist=True):
+ subset=slice(None), drop_intra_darks=True, persist=False):
"""Load single module dssc data as dask array.
Inputs
@@ -587,7 +587,7 @@ def load_dssc_module(proposalNB, runNB, moduleNB=15,
moduleNB: default 15, module number
subset: default slice(None), subset of trains to load
drop_intra_darks: boolean, default True, remove intra darks from the data
- persist: load all data in memory
+ persist: default False, load all data persistently in memory
Returns
-------
--
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