From 6d1aa45d127f95d4bfe8e23f1ef832b2413b35d4 Mon Sep 17 00:00:00 2001 From: karnem <mikhail.karnevskiy@desy.de> Date: Fri, 30 Aug 2019 15:55:30 +0200 Subject: [PATCH 1/6] Add plotting constants of FCCD --- cal_tools/cal_tools/ana_tools.py | 14 + .../FastCCD/PlotFromCalDB_FastCCD_NBC.ipynb | 531 ++++++++++++++++++ xfel_calibrate/notebooks.py | 6 + 3 files changed, 551 insertions(+) create mode 100644 notebooks/FastCCD/PlotFromCalDB_FastCCD_NBC.ipynb diff --git a/cal_tools/cal_tools/ana_tools.py b/cal_tools/cal_tools/ana_tools.py index f58ace59b..dce75cf70 100644 --- a/cal_tools/cal_tools/ana_tools.py +++ b/cal_tools/cal_tools/ana_tools.py @@ -352,6 +352,20 @@ class HMType(Enum): INSET_AXIS = 2 +def get_range(data, scale): + """ + Get range, which includes most of the data points. + Range is calculated in units of median absolute deviations + + :param data: numpy.array of data points + :param scale: range in units of median absolute deviations + :return: + """ + med = np.nanmedian(data) + mad = np.nanmedian(np.abs(data.flatten() - med)) + return med - scale * mad, med + scale * mad + + def hm_combine(data, fname=None, htype=None, **kwargs): """ Plot heatmap for calibration report diff --git a/notebooks/FastCCD/PlotFromCalDB_FastCCD_NBC.ipynb b/notebooks/FastCCD/PlotFromCalDB_FastCCD_NBC.ipynb new file mode 100644 index 000000000..406e88e09 --- /dev/null +++ b/notebooks/FastCCD/PlotFromCalDB_FastCCD_NBC.ipynb @@ -0,0 +1,531 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Statistical analysis of calibration factors#\n", + "\n", + "Author: Mikhail Karnevskiy, Steffen Hauf, Version 0.1\n", + "\n", + "A description of the notebook." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "cluster_profile = \"noDB\" # The ipcluster profile to use\n", + "start_date = \"2019-01-30\" # date to start investigation interval from\n", + "end_date = \"2019-08-30\" # date to end investigation interval at, can be \"now\"\n", + "nconstants = 10 # Number of time stamps to plot. If not 0, overcome start_date.\n", + "dclass=\"CCD\" # Detector class\n", + "db_module = \"fastCCD1\" # detector entry in the DB to investigate\n", + "constants = [\"Noise\"]#, \"Offset\"] # constants to plot\n", + "\n", + "gain_setting = [0,1,2,8] # gain stages\n", + "bias_voltage = [79] # Bias voltage\n", + "temperature = [235]#, 216, 245] # Operation temperature\n", + "integration_time = [1, 50] # Integration time\n", + "pixels_x=[1934]\n", + "pixels_y=[960]\n", + "max_time = 15\n", + "parameter_names = ['bias_voltage', 'integration_time', 'temperature', \n", + " 'gain_setting', 'pixels_x', 'pixels_y'] # names of parameters\n", + "photon_energy = 9.2 # Photon energy of the beam\n", + "out_folder = \"/gpfs/exfel/data/scratch/karnem/test_FCCD5/\" # output folder\n", + "use_existing = \"\" # If not empty, constants stored in given folder will be used\n", + "cal_db_interface = \"tcp://max-exfl016:8015#8025\" # the database interface to use\n", + "cal_db_timeout = 180000 # timeout on caldb requests\",\n", + "plot_range = 3 # range for plotting in units of median absolute deviations" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "import copy\n", + "import datetime\n", + "import dateutil.parser\n", + "import numpy as np\n", + "from operator import itemgetter\n", + "import os\n", + "import sys\n", + "import warnings\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "import h5py\n", + "import matplotlib\n", + "%matplotlib inline\n", + "\n", + "from iCalibrationDB import Constants, Conditions, Detectors, ConstantMetaData\n", + "from cal_tools.tools import get_from_db, get_random_db_interface\n", + "from cal_tools.ana_tools import (save_dict_to_hdf5, load_data_from_hdf5, \n", + " combine_constants, HMType,\n", + " hm_combine, combine_lists, get_range)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Prepare variables\n", + "spShape = (967, 10) # Shape of superpixel\n", + "\n", + "parameters = [globals()[x] for x in parameter_names]\n", + "\n", + "constantsDark = {'Noise': 'BadPixelsDark',\n", + " 'Offset': 'BadPixelsDark'}\n", + "print('Bad pixels data: ', constantsDark)\n", + "\n", + "# Define parameters in order to perform loop over time stamps\n", + "start = datetime.datetime.now() if start_date.upper() == \"NOW\" else dateutil.parser.parse(\n", + " start_date)\n", + "end = datetime.datetime.now() if end_date.upper() == \"NOW\" else dateutil.parser.parse(\n", + " end_date)\n", + "\n", + "# Create output folder\n", + "os.makedirs(out_folder, exist_ok=True)\n", + "\n", + "# Get getector conditions\n", + "det = getattr(Detectors, db_module)\n", + "dconstants = getattr(Constants, dclass)(det.detector_type)\n", + "\n", + "print('CalDB Interface: {}'.format(cal_db_interface))\n", + "print('Start time at: ', start)\n", + "print('End time at: ', end)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "parameter_list = combine_lists(*parameters, names = parameter_names)\n", + "print(parameter_list)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": false + }, + "outputs": [], + "source": [ + "# Retrieve list of meta-data\n", + "constant_versions = []\n", + "constant_parameters = []\n", + "constantBP_versions = []\n", + "\n", + "# Loop over constants\n", + "for c, const in enumerate(constants):\n", + " \n", + " if use_existing != \"\":\n", + " break\n", + " \n", + " # Loop over parameters\n", + " for pars in parameter_list:\n", + " \n", + " if (const in [\"Offset\", \"Noise\", \"SlopesPC\"] or \"DARK\" in const.upper()):\n", + " dcond = Conditions.Dark\n", + " mcond = getattr(dcond, dclass)(**pars)\n", + " else:\n", + " dcond = Conditions.Illuminated\n", + " mcond = getattr(dcond, dclass)(**pars,\n", + " photon_energy=photon_energy)\n", + "\n", + " \n", + " \n", + " print('Request: ', const, 'with paramters:', pars)\n", + " # Request Constant versions for given parameters and module\n", + " data = get_from_db(det,\n", + " getattr(dconstants,\n", + " const)(),\n", + " copy.deepcopy(mcond), None,\n", + " cal_db_interface,\n", + " creation_time=start,\n", + " verbosity=0,\n", + " timeout=cal_db_timeout,\n", + " meta_only=True,\n", + " version_info=True)\n", + " \n", + " if not isinstance(data, list):\n", + " continue\n", + " \n", + " data = sorted(data, key=itemgetter('begin_at'))\n", + " print('Number of retrieved constants: {}'.format(len(data)) )\n", + " \n", + " if const in constantsDark:\n", + " # Request BP constant versions\n", + " dataBP = get_from_db(det,\n", + " getattr(dconstants, \n", + " constantsDark[const])(),\n", + " copy.deepcopy(mcond), None,\n", + " cal_db_interface,\n", + " creation_time=start,\n", + " verbosity=0,\n", + " timeout=cal_db_timeout,\n", + " meta_only=True,\n", + " version_info=True)\n", + " \n", + " if not isinstance(data, list) or not isinstance(dataBP, list):\n", + " continue\n", + " print('Number of retrieved darks: {}'.format(len(dataBP)) )\n", + " found_BPmatch = False\n", + " for d in data:\n", + " # Match proper BP constant version\n", + " # and get constant version within\n", + " # requested time range\n", + " if d is None:\n", + " print('Time or data is not found!')\n", + " continue\n", + "\n", + " dt = dateutil.parser.parse(d['begin_at'])\n", + "\n", + " if (dt.replace(tzinfo=None) > end or \n", + " (nconstants==0 and dt.replace(tzinfo=None) < start)):\n", + " continue\n", + " \n", + " if nconstants>0 and constant_parameters.count(pars)>nconstants-1:\n", + " break\n", + "\n", + " closest_BP = None\n", + " closest_BPtime = None\n", + "\n", + " for dBP in dataBP:\n", + " if dBP is None:\n", + " print(\"Bad pixels are not found!\")\n", + " continue\n", + "\n", + " dt = dateutil.parser.parse(d['begin_at'])\n", + " dBPt = dateutil.parser.parse(dBP['begin_at'])\n", + "\n", + " if dt == dBPt:\n", + " found_BPmatch = True\n", + " else:\n", + "\n", + " if np.abs(dBPt-dt).seconds < (max_time*60):\n", + " if closest_BP is None:\n", + " closest_BP = dBP\n", + " closest_BPtime = dBPt\n", + " else:\n", + " if np.abs(dBPt-dt) < np.abs(closest_BPtime-dt):\n", + " closest_BP = dBP\n", + " closest_BPtime = dBPt\n", + "\n", + " if dataBP.index(dBP) == len(dataBP)-1:\n", + " if closest_BP:\n", + " dBP = closest_BP\n", + " dBPt = closest_BPtime\n", + " found_BPmatch = True\n", + " else:\n", + " print('Bad pixels are not found!')\n", + "\n", + " if found_BPmatch:\n", + " print(\"Found constant {}: begin at {}\".format(const, dt))\n", + " print(\"Found bad pixels at {}\".format(dBPt))\n", + " constantBP_versions.append(dBP)\n", + " constant_versions.append(d)\n", + " constant_parameters.append(copy.deepcopy(pars))\n", + " found_BPmatch = False\n", + " break\n", + " else:\n", + " constant_versions += data\n", + " constant_parameters += [copy.deepcopy(pars)]*len(data)\n", + "\n", + "# Remove dublications\n", + "constant_versions_tmp = []\n", + "constant_parameters_tmp = []\n", + "for i, x in enumerate(constant_versions):\n", + " if x not in constant_versions_tmp:\n", + " constant_versions_tmp.append(x)\n", + " constant_parameters_tmp.append(constant_parameters[i])\n", + " \n", + "constant_versions=constant_versions_tmp\n", + "constant_parameters=constant_parameters_tmp\n", + " \n", + "print('Number of stored constant versions is {}'.format(len(constant_versions)))\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def get_rebined(a, rebin):\n", + " return a[:,:,0].reshape(\n", + " int(a.shape[0] / rebin[0]),\n", + " rebin[0],\n", + " int(a.shape[1] / rebin[1]),\n", + " rebin[1])\n", + " \n", + "def modify_const(const, data, isBP = False):\n", + " return data\n", + "\n", + "ret_constants = {}\n", + "constand_data = ConstantMetaData()\n", + "constant_BP = ConstantMetaData()\n", + "for i, constant_version in enumerate(constant_versions):\n", + "\n", + " const = constant_version['data_set_name'].split('/')[-2]\n", + " qm = db_module\n", + " \n", + " print(\"constant: {}, module {}\".format(const,qm))\n", + " \n", + " constand_data.retrieve_from_version_info(constant_version)\n", + " \n", + " # Convert parameters to dict\n", + " dpar = {p.name: p.value for p in constand_data.detector_condition.parameters}\n", + " \n", + " const = \"{}_{}_{}_{}\".format(const, \n", + " constant_parameters[i]['gain_setting'],\n", + " constant_parameters[i]['temperature'],\n", + " constant_parameters[i]['integration_time'])\n", + " \n", + " if not const in ret_constants:\n", + " ret_constants[const] = {}\n", + " if not qm in ret_constants[const]:\n", + " ret_constants[const][qm] = []\n", + " \n", + " cdata = constand_data.calibration_constant.data\n", + " ctime = constand_data.calibration_constant_version.begin_at\n", + " \n", + " cdata = modify_const(const, cdata)\n", + " \n", + " if len(constantBP_versions)>0:\n", + " constant_BP.retrieve_from_version_info(constantBP_versions[i])\n", + " cdataBP = constant_BP.calibration_constant.data\n", + " cdataBP = modify_const(const, cdataBP, True)\n", + " \n", + " if cdataBP.shape != cdata.shape:\n", + " print('Wrong bad pixel shape! {}, expected {}'.format(cdataBP.shape, cdata.shape))\n", + " continue\n", + " \n", + " # Apply bad pixel mask\n", + " cdataABP = np.copy(cdata)\n", + " cdataABP[cdataBP > 0] = np.nan\n", + " \n", + " # Create superpixels for constants with BP applied\n", + " cdataABP = get_rebined(cdataABP, spShape)\n", + " toStoreBP = np.nanmean(cdataABP, axis=(1, 3))\n", + " toStoreBPStd = np.nanstd(cdataABP, axis=(1, 3))\n", + "\n", + " # Prepare number of bad pixels per superpixels\n", + " cdataBP = get_rebined(cdataBP, spShape)\n", + " cdataNBP = np.nansum(cdataBP > 0, axis=(1, 3))\n", + " else:\n", + " toStoreBP = 0\n", + " toStoreBPStd = 0\n", + " cdataNBP = 0\n", + "\n", + " # Create superpixels for constants without BP applied\n", + " cdata = get_rebined(cdata, spShape)\n", + " toStoreStd = np.nanstd(cdata, axis=(1, 3))\n", + " toStore = np.nanmean(cdata, axis=(1, 3))\n", + " \n", + " # Convert parameters to dict\n", + " dpar = {p.name: p.value for p in constand_data.detector_condition.parameters}\n", + " \n", + " print(\"Store values in dict\", const, qm, ctime)\n", + " ret_constants[const][qm].append({'ctime': ctime,\n", + " 'nBP': cdataNBP,\n", + " 'dataBP': toStoreBP,\n", + " 'dataBPStd': toStoreBPStd,\n", + " 'data': toStore,\n", + " 'dataStd': toStoreStd,\n", + " 'mdata': dpar}) \n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "if use_existing == \"\":\n", + " print('Save data to /CalDBAna_{}_{}.h5'.format(dclass, db_module))\n", + " save_dict_to_hdf5(ret_constants,\n", + " '{}/CalDBAna_{}_{}.h5'.format(out_folder, dclass, db_module))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "if use_existing == \"\":\n", + " fpath = '{}/CalDBAna_{}_*.h5'.format(out_folder, dclass)\n", + "else:\n", + " fpath = '{}/CalDBAna_{}_*.h5'.format(use_existing, dclass)\n", + "\n", + "print('Load data from {}'.format(fpath))\n", + "ret_constants = load_data_from_hdf5(fpath)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Parameters for plotting\n", + "\n", + "keys = {\n", + " 'Mean': ['data', '', 'Mean over pixels'],\n", + " 'std': ['dataStd', '', '$\\sigma$ over pixels'],\n", + " 'MeanBP': ['dataBP', 'Good pixels only', 'Mean over pixels'],\n", + " 'NBP': ['nBP', 'Fraction of BP', 'Fraction of BP'],\n", + " 'stdBP': ['dataBPStd', 'Good pixels only', '$\\sigma$ over pixels'],\n", + " 'stdASIC': ['', '', '$\\sigma$ over ASICs'],\n", + " 'stdCell': ['', '', '$\\sigma$ over Cells'],\n", + "}\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "print('Plot calibration constants')\n", + "\n", + "# loop over constat type\n", + "for const, modules in ret_constants.items():\n", + "\n", + " const, gain, temp, int_time = const.split(\"_\")\n", + " print('Const: {}'.format(const))\n", + "\n", + " # loop over modules\n", + " mod_data = {}\n", + " mod_data['stdASIC'] = []\n", + " mod_data['stdCell'] = []\n", + " mod_names = []\n", + " mod_times = []\n", + "\n", + " # Loop over modules\n", + " for mod, data in modules.items():\n", + " print(mod)\n", + "\n", + " ctimes = np.array(data[\"ctime\"])\n", + " ctimes_ticks = [x.strftime('%y-%m-%d') for x in ctimes]\n", + "\n", + " if (\"mdata\" in data):\n", + " cmdata = np.array(data[\"mdata\"])\n", + " for i, tick in enumerate(ctimes_ticks):\n", + " ctimes_ticks[i] = ctimes_ticks[i] + \\\n", + " ', V={:1.0f}'.format(cmdata[i]['Sensor Temperature']) + \\\n", + " ', T={:1.0f}'.format(\n", + " cmdata[i]['Integration Time'])\n", + "\n", + " sort_ind = np.argsort(ctimes_ticks)\n", + " ctimes_ticks = list(np.array(ctimes_ticks)[sort_ind])\n", + "\n", + " # Create sorted by data dataset\n", + " rdata = {}\n", + " for key, item in keys.items():\n", + " if item[0] in data:\n", + " rdata[key] = np.array(data[item[0]])[sort_ind]\n", + "\n", + " nTimes = rdata['Mean'].shape[0]\n", + " nPixels = rdata['Mean'].shape[1] * rdata['Mean'].shape[2]\n", + " nBins = nPixels\n", + "\n", + " # Avoid to low values\n", + " if const in [\"Noise\", \"Offset\", \"Noise-e\"]:\n", + " rdata['Mean'][rdata['Mean'] < 0.1] = np.nan\n", + " if 'MeanBP' in rdata:\n", + " rdata['MeanBP'][rdata['MeanBP'] < 0.1] = np.nan\n", + " \n", + " if 'NBP' in rdata:\n", + " rdata[\"NBP\"] = rdata[\"NBP\"] / spShape[0] / spShape[1] * 100\n", + "\n", + " # Reshape: ASICs over cells for plotting\n", + " pdata = {}\n", + " for key in rdata:\n", + " if len(rdata[key].shape)<3:\n", + " continue\n", + " pdata[key] = rdata[key][:, :, :].reshape(nTimes, nBins).swapaxes(0, 1)\n", + "\n", + " # Summary over ASICs\n", + " adata = {}\n", + " for key in rdata:\n", + " if len(rdata[key].shape)<3:\n", + " continue\n", + " adata[key] = np.nanmean(rdata[key], axis=(1, 2))\n", + "\n", + " # Summary information over modules\n", + " for key in pdata:\n", + " if key not in mod_data:\n", + " mod_data[key] = []\n", + " mod_data[key].append(np.nanmean(pdata[key], axis=0))\n", + "\n", + " mod_data['stdASIC'].append(np.nanstd(rdata['Mean'], axis=(1, 2)))\n", + "\n", + " mod_names.append(mod)\n", + " mod_times.append(ctimes_ticks)\n", + "\n", + " # Plotting\n", + " for key in pdata:\n", + " if len(pdata[key].shape)<2:\n", + " continue\n", + "\n", + " if key == 'NBP':\n", + " unit = '[%]'\n", + " else:\n", + " unit = '[ADU]'\n", + " if const == 'Noise-e':\n", + " unit = '[$e^-$]'\n", + "\n", + " title = '{}, module {}, gain {} {}'.format(\n", + " const, mod, gain, keys[key][1])\n", + " cb_label = '{}, {} {}'.format(const, keys[key][2], unit)\n", + "\n", + " vmin,vmax = get_range(pdata[key][::-1].flatten(), plot_range)\n", + " hm_combine(pdata[key][::-1], htype=HMType.mro,\n", + " x_label='Creation Time', y_label='ASIC ID',\n", + " x_ticklabels=ctimes_ticks,\n", + " x_ticks=np.arange(len(ctimes_ticks))+0.3,\n", + " title=title, cb_label=cb_label,\n", + " vmin=vmin, vmax=vmax,\n", + " fname='{}/{}_{}_g{}_t{}_t{}_ASIC_{}.png'.format(\n", + " out_folder, const, mod.replace('_', ''), gain, temp, int_time, key),\n", + " pad=[0.125, 0.125, 0.12, 0.185])\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.7" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/xfel_calibrate/notebooks.py b/xfel_calibrate/notebooks.py index 71da69695..fe9df1c8a 100644 --- a/xfel_calibrate/notebooks.py +++ b/xfel_calibrate/notebooks.py @@ -129,6 +129,12 @@ notebooks = { "use function": "balance_sequences", "cluster cores": 4}, }, + "STATS_FROM_DB": { + "notebook": "notebooks/FastCCD/PlotFromCalDB_FastCCD_NBC.ipynb", + "concurrency": {"parameter": None, + "default concurrency": None, + "cluster cores": 1}, + }, }, "JUNGFRAU": { "DARK": { -- GitLab From 273145be398dabfa495f6122f00194d52924b609 Mon Sep 17 00:00:00 2001 From: karnem <mikhail.karnevskiy@desy.de> Date: Mon, 2 Sep 2019 10:15:50 +0200 Subject: [PATCH 2/6] Cleanup code --- .../FastCCD/PlotFromCalDB_FastCCD_NBC.ipynb | 66 ++++++------------- 1 file changed, 20 insertions(+), 46 deletions(-) diff --git a/notebooks/FastCCD/PlotFromCalDB_FastCCD_NBC.ipynb b/notebooks/FastCCD/PlotFromCalDB_FastCCD_NBC.ipynb index 406e88e09..029a487d1 100644 --- a/notebooks/FastCCD/PlotFromCalDB_FastCCD_NBC.ipynb +++ b/notebooks/FastCCD/PlotFromCalDB_FastCCD_NBC.ipynb @@ -23,11 +23,11 @@ "nconstants = 10 # Number of time stamps to plot. If not 0, overcome start_date.\n", "dclass=\"CCD\" # Detector class\n", "db_module = \"fastCCD1\" # detector entry in the DB to investigate\n", - "constants = [\"Noise\"]#, \"Offset\"] # constants to plot\n", + "constants = [\"Noise\", \"Offset\"] # constants to plot\n", "\n", "gain_setting = [0,1,2,8] # gain stages\n", "bias_voltage = [79] # Bias voltage\n", - "temperature = [235]#, 216, 245] # Operation temperature\n", + "temperature = [235, 216, 245] # Operation temperature\n", "integration_time = [1, 50] # Integration time\n", "pixels_x=[1934]\n", "pixels_y=[960]\n", @@ -35,7 +35,7 @@ "parameter_names = ['bias_voltage', 'integration_time', 'temperature', \n", " 'gain_setting', 'pixels_x', 'pixels_y'] # names of parameters\n", "photon_energy = 9.2 # Photon energy of the beam\n", - "out_folder = \"/gpfs/exfel/data/scratch/karnem/test_FCCD5/\" # output folder\n", + "out_folder = \"/gpfs/exfel/data/scratch/karnem/test_FCCD6/\" # output folder\n", "use_existing = \"\" # If not empty, constants stored in given folder will be used\n", "cal_db_interface = \"tcp://max-exfl016:8015#8025\" # the database interface to use\n", "cal_db_timeout = 180000 # timeout on caldb requests\",\n", @@ -60,15 +60,11 @@ "import warnings\n", "warnings.filterwarnings('ignore')\n", "\n", - "import h5py\n", - "import matplotlib\n", - "%matplotlib inline\n", - "\n", "from iCalibrationDB import Constants, Conditions, Detectors, ConstantMetaData\n", - "from cal_tools.tools import get_from_db, get_random_db_interface\n", + "from cal_tools.tools import get_from_db\n", "from cal_tools.ana_tools import (save_dict_to_hdf5, load_data_from_hdf5, \n", - " combine_constants, HMType,\n", - " hm_combine, combine_lists, get_range)" + " HMType, hm_combine,\n", + " combine_lists, get_range)" ] }, { @@ -246,15 +242,18 @@ "# Remove dublications\n", "constant_versions_tmp = []\n", "constant_parameters_tmp = []\n", + "constantBP_versions_tmp = []\n", "for i, x in enumerate(constant_versions):\n", " if x not in constant_versions_tmp:\n", " constant_versions_tmp.append(x)\n", " constant_parameters_tmp.append(constant_parameters[i])\n", - " \n", + " if i<len(constantBP_versions)-1:\n", + " constantBP_versions_tmp.append(constantBP_versions[i])\n", "constant_versions=constant_versions_tmp\n", + "constantBP_versions=constantBP_versions_tmp\n", "constant_parameters=constant_parameters_tmp\n", - " \n", - "print('Number of stored constant versions is {}'.format(len(constant_versions)))\n" + "\n", + "print('Number of stored constant versions is {}'.format(len(constant_versions)))" ] }, { @@ -274,7 +273,7 @@ " return data\n", "\n", "ret_constants = {}\n", - "constand_data = ConstantMetaData()\n", + "constant_data = ConstantMetaData()\n", "constant_BP = ConstantMetaData()\n", "for i, constant_version in enumerate(constant_versions):\n", "\n", @@ -283,10 +282,10 @@ " \n", " print(\"constant: {}, module {}\".format(const,qm))\n", " \n", - " constand_data.retrieve_from_version_info(constant_version)\n", + " constant_data.retrieve_from_version_info(constant_version)\n", " \n", " # Convert parameters to dict\n", - " dpar = {p.name: p.value for p in constand_data.detector_condition.parameters}\n", + " dpar = {p.name: p.value for p in constant_data.detector_condition.parameters}\n", " \n", " const = \"{}_{}_{}_{}\".format(const, \n", " constant_parameters[i]['gain_setting'],\n", @@ -298,8 +297,8 @@ " if not qm in ret_constants[const]:\n", " ret_constants[const][qm] = []\n", " \n", - " cdata = constand_data.calibration_constant.data\n", - " ctime = constand_data.calibration_constant_version.begin_at\n", + " cdata = constant_data.calibration_constant.data\n", + " ctime = constant_data.calibration_constant_version.begin_at\n", " \n", " cdata = modify_const(const, cdata)\n", " \n", @@ -335,7 +334,7 @@ " toStore = np.nanmean(cdata, axis=(1, 3))\n", " \n", " # Convert parameters to dict\n", - " dpar = {p.name: p.value for p in constand_data.detector_condition.parameters}\n", + " dpar = {p.name: p.value for p in constant_data.detector_condition.parameters}\n", " \n", " print(\"Store values in dict\", const, qm, ctime)\n", " ret_constants[const][qm].append({'ctime': ctime,\n", @@ -356,7 +355,7 @@ "outputs": [], "source": [ "if use_existing == \"\":\n", - " print('Save data to /CalDBAna_{}_{}.h5'.format(dclass, db_module))\n", + " print('Save data to {}/CalDBAna_{}_{}.h5'.format(out_folder, dclass, db_module))\n", " save_dict_to_hdf5(ret_constants,\n", " '{}/CalDBAna_{}_{}.h5'.format(out_folder, dclass, db_module))" ] @@ -409,13 +408,6 @@ " const, gain, temp, int_time = const.split(\"_\")\n", " print('Const: {}'.format(const))\n", "\n", - " # loop over modules\n", - " mod_data = {}\n", - " mod_data['stdASIC'] = []\n", - " mod_data['stdCell'] = []\n", - " mod_names = []\n", - " mod_times = []\n", - "\n", " # Loop over modules\n", " for mod, data in modules.items():\n", " print(mod)\n", @@ -444,7 +436,7 @@ " nPixels = rdata['Mean'].shape[1] * rdata['Mean'].shape[2]\n", " nBins = nPixels\n", "\n", - " # Avoid to low values\n", + " # Avoid too low values\n", " if const in [\"Noise\", \"Offset\", \"Noise-e\"]:\n", " rdata['Mean'][rdata['Mean'] < 0.1] = np.nan\n", " if 'MeanBP' in rdata:\n", @@ -460,24 +452,6 @@ " continue\n", " pdata[key] = rdata[key][:, :, :].reshape(nTimes, nBins).swapaxes(0, 1)\n", "\n", - " # Summary over ASICs\n", - " adata = {}\n", - " for key in rdata:\n", - " if len(rdata[key].shape)<3:\n", - " continue\n", - " adata[key] = np.nanmean(rdata[key], axis=(1, 2))\n", - "\n", - " # Summary information over modules\n", - " for key in pdata:\n", - " if key not in mod_data:\n", - " mod_data[key] = []\n", - " mod_data[key].append(np.nanmean(pdata[key], axis=0))\n", - "\n", - " mod_data['stdASIC'].append(np.nanstd(rdata['Mean'], axis=(1, 2)))\n", - "\n", - " mod_names.append(mod)\n", - " mod_times.append(ctimes_ticks)\n", - "\n", " # Plotting\n", " for key in pdata:\n", " if len(pdata[key].shape)<2:\n", -- GitLab From c8809a80f1451d49d054013ecdd789787e378a72 Mon Sep 17 00:00:00 2001 From: karnem <mikhail.karnevskiy@desy.de> Date: Mon, 2 Sep 2019 11:42:42 +0200 Subject: [PATCH 3/6] simplify code. Include nconstants. --- notebooks/AGIPD/PlotFromCalDB_AGIPD_NBC.ipynb | 91 +++++++------------ .../FastCCD/PlotFromCalDB_FastCCD_NBC.ipynb | 2 +- notebooks/LPD/PlotFromCalDB_LPD_NBC.ipynb | 74 ++++++--------- .../ePix/PlotFromCalDB_ePix100_NBC.ipynb | 70 ++++++-------- 4 files changed, 90 insertions(+), 147 deletions(-) diff --git a/notebooks/AGIPD/PlotFromCalDB_AGIPD_NBC.ipynb b/notebooks/AGIPD/PlotFromCalDB_AGIPD_NBC.ipynb index 545a9a475..e3efb528a 100644 --- a/notebooks/AGIPD/PlotFromCalDB_AGIPD_NBC.ipynb +++ b/notebooks/AGIPD/PlotFromCalDB_AGIPD_NBC.ipynb @@ -28,12 +28,14 @@ "cluster_profile = \"noDB\" # The ipcluster profile to use\n", "start_date = \"2019-01-01\" # Date to start investigation interval from\n", "end_date = \"2019-12-12\" # Date to end investigation interval at, can be \"now\"\n", + "nconstants = 20 # Number of time stamps to plot. If not 0, overcome start_date.\n", "constants = [\"Noise\", \"SlopesFF\", \"SlopesPC\", \"Offset\"] # Constants to plot\n", "modules = [1] # Modules, set to -1 for all, range allowed\n", "bias_voltages = [300, 500] # Bias voltage\n", - "mem_cells = [128, 176] # Number of used memory cells. Typically: 4,32,64,128,176.\n", + "mem_cells = [128, 176, 250] # Number of used memory cells. Typically: 4,32,64,128,176.\n", + "acquisition_rate = [None]\n", "photon_energy = 9.2 # Photon energy of the beam\n", - "out_folder = \"/gpfs/exfel/data/scratch/karnem/testAGIPD16_21/\" # Output folder, required\n", + "out_folder = \"/gpfs/exfel/data/scratch/karnem/testAGIPD16_25/\" # Output folder, required\n", "use_existing = \"\" # If not empty, constants stored in given folder will be used\n", "cal_db_timeout = 120000 # timeout on caldb requests\",\n", "adu_to_photon = 33.17 # ADU to photon conversion factor (8000 / 3.6 / 67.)\n", @@ -47,7 +49,8 @@ "range_gain = [0.8, 1.2, 0.8, 1.2] # plotting range for gain: high gain l, r, medium gain l, r \n", "range_noise_e = [85., 500., 85., 500.] # plotting range for noise in [e-]: high gain l, r, medium gain l, r \n", "range_slopesPC = [22.0, 27.0, -0.5, 1.5] # plotting range for slope PC: high gain l, r, medium gain l, r \n", - "range_slopesFF = [0.8, 1.2, 0.6, 1.2] # plotting range for slope FF: high gain l, r, medium gain l, r " + "range_slopesFF = [0.8, 1.2, 0.6, 1.2] # plotting range for slope FF: high gain l, r, medium gain l, r \n", + "plot_range = 3 # range for plotting in units of median absolute deviations" ] }, { @@ -67,13 +70,11 @@ "import warnings\n", "warnings.filterwarnings('ignore')\n", "\n", - "import h5py\n", - "\n", "from iCalibrationDB import Constants, Conditions, Detectors, ConstantMetaData\n", "from cal_tools.tools import get_from_db, get_random_db_interface\n", "from cal_tools.ana_tools import (save_dict_to_hdf5, load_data_from_hdf5, \n", " combine_constants, HMType,\n", - " hm_combine, combine_lists)" + " hm_combine, combine_lists, get_range)" ] }, { @@ -122,7 +123,8 @@ "metadata": {}, "outputs": [], "source": [ - "parameter_list = combine_lists(bias_voltages, modules, mem_cells, names = ['bias_voltage', 'module', 'mem_cells'])\n", + "parameter_list = combine_lists(bias_voltages, modules, mem_cells, acquisition_rate,\n", + " names = ['bias_voltage', 'module', 'mem_cells', 'acquisition_rate'])\n", "print(parameter_list)" ] }, @@ -152,13 +154,15 @@ " dcond = Conditions.Dark\n", " mcond = getattr(dcond, dclass)(\n", " memory_cells=pars['mem_cells'],\n", - " bias_voltage=pars['bias_voltage'])\n", + " bias_voltage=pars['bias_voltage'],\n", + " acquisition_rate=pars['acquisition_rate'])\n", " else:\n", " dcond = Conditions.Illuminated\n", " mcond = getattr(dcond, dclass)(\n", - " memory_cells=pars['mem_cells'],\n", - " bias_voltage=pars['bias_voltage'],\n", - " photon_energy=photon_energy)\n", + " memory_cells=pars['mem_cells'],\n", + " bias_voltage=pars['bias_voltage'],\n", + " acquisition_rate=pars['acquisition_rate'],\n", + " photon_energy=photon_energy)\n", "\n", " print('Request: ', const, 'with paramters:', pars)\n", " # Request Constant versions for given parameters and module\n", @@ -173,7 +177,6 @@ " meta_only=True,\n", " version_info=True)\n", "\n", - " print(data)\n", " # Request BP constant versions\n", " print('constantDark:', constantsDark[const], ) \n", " dataBP = get_from_db(getattr(det, pars['module']),\n", @@ -187,13 +190,12 @@ " meta_only=True,\n", " version_info=True)\n", " \n", - " print('BP!!!!!', dataBP)\n", - " \n", " if not isinstance(data, list) or not isinstance(dataBP, list):\n", " continue\n", " \n", " found_BPmatch = False\n", " for d in data:\n", + " print('Item: ', d)\n", " # Match proper BP constant version\n", " # and get constant version within\n", " # requested time range\n", @@ -203,7 +205,8 @@ "\n", " dt = dateutil.parser.parse(d['begin_at'])\n", "\n", - " if dt.replace(tzinfo=None) > end or dt.replace(tzinfo=None) < start:\n", + " if (dt.replace(tzinfo=None) > end or \n", + " (nconstants==0 and dt.replace(tzinfo=None) < start)):\n", " continue\n", " \n", " closest_BP = None\n", @@ -302,25 +305,31 @@ "ret_constants = {}\n", "constand_data = ConstantMetaData()\n", "constant_BP = ConstantMetaData()\n", - "for i, constant_version in enumerate(constant_versions):\n", + "# sort over begin_at\n", + "idxs, _ = zip(*sorted(enumerate(constant_versions), \n", + " key=lambda x: x[1]['begin_at'], reverse=True))\n", "\n", - " const = constant_version['data_set_name'].split('/')[-2]\n", + "for i in idxs:\n", + " const = constant_versions[i]['data_set_name'].split('/')[-2]\n", " qm = constant_parameters[i]['module']\n", " \n", - " constand_data.retrieve_from_version_info(constant_version)\n", + " if not const in ret_constants:\n", + " ret_constants[const] = {}\n", + " if not qm in ret_constants[const]:\n", + " ret_constants[const][qm] = []\n", + " \n", + " if nconstants>0 and len(ret_constants[const][qm])>=nconstants:\n", + " continue\n", + " \n", + " constand_data.retrieve_from_version_info(constant_versions[i])\n", " constant_BP.retrieve_from_version_info(constantBP_versions[i])\n", " \n", " cdata = constand_data.calibration_constant.data\n", " cdataBP = constant_BP.calibration_constant.data\n", " ctime = constand_data.calibration_constant_version.begin_at \n", - " \n", + " \n", " print(\"constant: {}, module {}, begin_at {}\".format(const, qm, ctime))\n", - " \n", - " if not const in ret_constants:\n", - " ret_constants[const] = {}\n", - " if not qm in ret_constants[const]:\n", - " ret_constants[const][qm] = []\n", - " \n", + "\n", " cdata = modify_const(const, cdata)\n", " cdataBP = modify_const(const, cdataBP, True)\n", "\n", @@ -540,20 +549,12 @@ " else:\n", " pass\n", "\n", - " # loop over modules\n", - " mod_data = {}\n", - " mod_data['stdASIC'] = []\n", - " mod_data['stdCell'] = []\n", - " mod_names = []\n", - " mod_times = []\n", - "\n", " # Loop over modules\n", " for mod, data in mods.items():\n", " if mod not in modules:\n", " continue\n", "\n", " print(mod)\n", - "\n", " ctimes = np.array(data[\"ctime\"])\n", " ctimes_ticks = [x.strftime('%y-%m-%d') for x in ctimes]\n", "\n", @@ -604,24 +605,9 @@ " for key in rdata:\n", " adata[key] = np.nanmean(rdata[key], axis=(1, 2)).swapaxes(0, 1)\n", "\n", - " # Summary information over modules\n", - " for key in pdata:\n", - " if key not in mod_data:\n", - " mod_data[key] = []\n", - " mod_data[key].append(np.nanmean(pdata[key], axis=0))\n", - "\n", - " mod_data['stdASIC'].append(np.nanstd(\n", - " np.nanmean(rdata['Mean'][:, :, :, :nMemToShow], axis=(1, 2)), axis=1))\n", - " mod_data['stdCell'].append(np.nanstd(\n", - " np.nanmean(rdata['Mean'][:, :, :, :nMemToShow], axis=3), axis=(1, 2)))\n", - "\n", - " mod_names.append(mod)\n", - " mod_times.append(ctimes_ticks)\n", - "\n", " # Plotting\n", " for key in pdata:\n", - " vmin = None\n", - " vmax = None\n", + " vmin,vmax = get_range(pdata[key][::-1], plot_range)\n", " if const in rangevals and key in ['Mean', 'MeanBP']:\n", " vmin = rangevals[const][gain][0]\n", " vmax = rangevals[const][gain][1]\n", @@ -658,13 +644,6 @@ " out_folder, const, mod, gain, key),\n", " vmin=vmin, vmax=vmax)" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { diff --git a/notebooks/FastCCD/PlotFromCalDB_FastCCD_NBC.ipynb b/notebooks/FastCCD/PlotFromCalDB_FastCCD_NBC.ipynb index 029a487d1..1bd8c1792 100644 --- a/notebooks/FastCCD/PlotFromCalDB_FastCCD_NBC.ipynb +++ b/notebooks/FastCCD/PlotFromCalDB_FastCCD_NBC.ipynb @@ -158,7 +158,7 @@ " if not isinstance(data, list):\n", " continue\n", " \n", - " data = sorted(data, key=itemgetter('begin_at'))\n", + " data = sorted(data, key=itemgetter('begin_at'), reverse=True)\n", " print('Number of retrieved constants: {}'.format(len(data)) )\n", " \n", " if const in constantsDark:\n", diff --git a/notebooks/LPD/PlotFromCalDB_LPD_NBC.ipynb b/notebooks/LPD/PlotFromCalDB_LPD_NBC.ipynb index 8ecc446be..b3f50de67 100644 --- a/notebooks/LPD/PlotFromCalDB_LPD_NBC.ipynb +++ b/notebooks/LPD/PlotFromCalDB_LPD_NBC.ipynb @@ -22,18 +22,17 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": true - }, + "metadata": {}, "outputs": [], "source": [ "cluster_profile = \"noDB\" # The ipcluster profile to use\n", "start_date = \"2018-01-30\" # Date to start investigation interval from\n", "end_date = \"2018-12-12\" # Date to end investigation interval at, can be \"now\"\n", - "constants = [\"Offset\", \"Noise\", \"SlopesFF\", \"SlopesCI\"] # constants to plot\n", + "nconstants = 10 # Number of time stamps to plot. If not 0, overcome start_date.\n", + "constants = [\"Offset\"]#, \"Noise\", \"SlopesFF\", \"SlopesCI\"] # constants to plot\n", "modules = [2] # Modules, set to -1 for all, range allowed\n", "bias_voltages = [250, 500] # Bias voltage\n", - "mem_cells = [1, 128, 256, 512] # Number of used memory cells. Typically: 4,32,64,128,176.\n", + "mem_cells = [128, 256, 512] # Number of used memory cells.\n", "photon_energy = 9.2 # Photon energy of the beam\n", "out_folder = \"/gpfs/exfel/data/scratch/karnem/testLPD_11/\" # Output folder, required\n", "use_existing = \"\" # If not empty, constants stored in given folder will be used\n", @@ -49,7 +48,8 @@ "range_gain = [20, 30, 20, 30] # plotting range for gain: high gain l, r, medium gain l, r \n", "range_noise_e = [100., 600., 100., 600.] # plotting range for noise in [e-]: high gain l, r, medium gain l, r \n", "range_slopesCI = [0.95, 1.05, 0.0, 0.5] # plotting range for slope CI: high gain l, r, medium gain l, r \n", - "range_slopesFF = [0.8, 1.2, 0.8, 1.2] # plotting range for slope FF: high gain l, r, medium gain l, r " + "range_slopesFF = [0.8, 1.2, 0.8, 1.2] # plotting range for slope FF: high gain l, r, medium gain l, r \n", + "plot_range = 3 # range for plotting in units of median absolute deviations" ] }, { @@ -69,13 +69,11 @@ "import warnings\n", "warnings.filterwarnings('ignore')\n", "\n", - "import h5py\n", - "\n", "from iCalibrationDB import Constants, Conditions, Detectors, ConstantMetaData\n", "from cal_tools.tools import get_from_db, get_random_db_interface\n", "from cal_tools.ana_tools import (save_dict_to_hdf5, load_data_from_hdf5, \n", " combine_constants, HMType,\n", - " hm_combine, combine_lists)" + " hm_combine, combine_lists, get_range)" ] }, { @@ -203,7 +201,8 @@ "\n", " dt = dateutil.parser.parse(d['begin_at'])\n", "\n", - " if dt.replace(tzinfo=None) > end or dt.replace(tzinfo=None) < start:\n", + " if (dt.replace(tzinfo=None) > end or \n", + " (nconstants==0 and dt.replace(tzinfo=None) < start)):\n", " continue\n", " \n", " closest_BP = None\n", @@ -293,12 +292,24 @@ "ret_constants = {}\n", "constand_data = ConstantMetaData()\n", "constant_BP = ConstantMetaData()\n", - "for i, constant_version in enumerate(constant_versions):\n", "\n", - " const = constant_version['data_set_name'].split('/')[-2]\n", + "# sort over begin_at\n", + "idxs, _ = zip(*sorted(enumerate(constant_versions), \n", + " key=lambda x: x[1]['begin_at'], reverse=True))\n", + "\n", + "for i in idxs:\n", + " const = constant_versions[i]['data_set_name'].split('/')[-2]\n", " qm = constant_parameters[i]['module']\n", " \n", - " constand_data.retrieve_from_version_info(constant_version)\n", + " if not const in ret_constants:\n", + " ret_constants[const] = {}\n", + " if not qm in ret_constants[const]:\n", + " ret_constants[const][qm] = []\n", + " \n", + " if nconstants>0 and len(ret_constants[const][qm])>=nconstants:\n", + " continue\n", + " \n", + " constand_data.retrieve_from_version_info(constant_versions[i])\n", " constant_BP.retrieve_from_version_info(constantBP_versions[i])\n", " \n", " cdata = constand_data.calibration_constant.data\n", @@ -306,12 +317,7 @@ " ctime = constand_data.calibration_constant_version.begin_at \n", " \n", " print(\"constant: {}, module {}, begin_at {}\".format(const, qm, ctime))\n", - " \n", - " if not const in ret_constants:\n", - " ret_constants[const] = {}\n", - " if not qm in ret_constants[const]:\n", - " ret_constants[const][qm] = []\n", - " \n", + "\n", " cdata = modify_const(const, cdata)\n", " cdataBP = modify_const(const, cdataBP)\n", "\n", @@ -481,9 +487,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": true - }, + "metadata": {}, "outputs": [], "source": [ "# Parameters for plotting\n", @@ -515,7 +519,7 @@ "cell_type": "code", "execution_count": null, "metadata": { - "scrolled": true + "scrolled": false }, "outputs": [], "source": [ @@ -533,13 +537,6 @@ " else:\n", " pass\n", "\n", - " # loop over modules\n", - " mod_data = {}\n", - " mod_data['stdASIC'] = []\n", - " mod_data['stdCell'] = []\n", - " mod_names = []\n", - " mod_times = []\n", - "\n", " # Loop over modules\n", " for mod, data in mods.items():\n", " \n", @@ -598,24 +595,9 @@ " for key in rdata:\n", " adata[key] = np.nanmean(rdata[key], axis=(1, 2)).swapaxes(0, 1)\n", "\n", - " # Summary information over modules\n", - " for key in pdata:\n", - " if key not in mod_data:\n", - " mod_data[key] = []\n", - " mod_data[key].append(np.nanmean(pdata[key], axis=0))\n", - "\n", - " mod_data['stdASIC'].append(np.nanstd(\n", - " np.nanmean(rdata['Mean'][:, :, :, :nMemToShow], axis=(1, 2)), axis=1))\n", - " mod_data['stdCell'].append(np.nanstd(\n", - " np.nanmean(rdata['Mean'][:, :, :, :nMemToShow], axis=3), axis=(1, 2)))\n", - "\n", - " mod_names.append(mod)\n", - " mod_times.append(ctimes_ticks)\n", - "\n", " # Plotting\n", " for key in pdata:\n", - " vmin = None\n", - " vmax = None\n", + " vmin,vmax = get_range(pdata[key][::-1].flatten(), plot_range)\n", " if const in rangevals and key in ['Mean', 'MeanBP']:\n", " vmin = rangevals[const][gain][0]\n", " vmax = rangevals[const][gain][1]\n", diff --git a/notebooks/ePix/PlotFromCalDB_ePix100_NBC.ipynb b/notebooks/ePix/PlotFromCalDB_ePix100_NBC.ipynb index 22aecccb9..e6163d8d4 100644 --- a/notebooks/ePix/PlotFromCalDB_ePix100_NBC.ipynb +++ b/notebooks/ePix/PlotFromCalDB_ePix100_NBC.ipynb @@ -24,6 +24,7 @@ "cluster_profile = \"noDB\" # The ipcluster profile to use\n", "start_date = \"2019-01-30\" # date to start investigation interval from\n", "end_date = \"2019-05-01\" # date to end investigation interval at, can be \"now\"\n", + "nconstants = 10 # Number of time stamps to plot. If not 0, overcome start_date.\n", "dclass=\"ePix100\" # Detector class\n", "db_module = \"ePix100_M15\" # detector entry in the DB to investigate\n", "constants = [\"Noise\", \"Offset\"] # constants to plot\n", @@ -35,10 +36,11 @@ "photon_energy = 9.2 # Photon energy of the beam\n", "out_folder = \"/gpfs/exfel/data/scratch/karnem/test_ePix/\" # output folder\n", "use_existing = \"\" # If not empty, constants stored in given folder will be used\n", - "cal_db_interface = \"tcp://max-exfl016:8016\" # the database interface to use\n", + "cal_db_interface = \"tcp://max-exfl016:8015#8025\" # the database interface to use\n", "cal_db_timeout = 180000 # timeout on caldb requests\",\n", - "range_offset = [1000., 2200] # plotting range for offset: high gain l, r, medium gain l, r \n", - "range_noise = [1.5, 3.3] # plotting range for noise: high gain l, r, medium gain l, r " + "range_offset = [1000., 2200] # plotting range for offset\n", + "range_noise = [1.5, 3.3] # plotting range for noise\n", + "plot_range = 3 # range for plotting in units of median absolute deviations" ] }, { @@ -58,13 +60,11 @@ "import warnings\n", "warnings.filterwarnings('ignore')\n", "\n", - "import h5py\n", - "\n", "from iCalibrationDB import Constants, Conditions, Detectors, ConstantMetaData\n", "from cal_tools.tools import get_from_db, get_random_db_interface\n", "from cal_tools.ana_tools import (save_dict_to_hdf5, load_data_from_hdf5, \n", - " combine_constants, HMType,\n", - " hm_combine, combine_lists)" + " HMType, hm_combine, \n", + " combine_lists, get_range)" ] }, { @@ -170,8 +170,6 @@ " meta_only=True,\n", " version_info=True)\n", " \n", - " print(dataBP)\n", - " \n", " if not isinstance(data, list) or not isinstance(dataBP, list):\n", " continue\n", " \n", @@ -186,7 +184,8 @@ "\n", " dt = dateutil.parser.parse(d['begin_at'])\n", "\n", - " if dt.replace(tzinfo=None) > end or dt.replace(tzinfo=None) < start:\n", + " if (dt.replace(tzinfo=None) > end or \n", + " (nconstants==0 and dt.replace(tzinfo=None) < start)):\n", " continue\n", "\n", " closest_BP = None\n", @@ -236,12 +235,15 @@ "# Remove dublications\n", "constant_versions_tmp = []\n", "constant_parameters_tmp = []\n", + "constantBP_versions_tmp = []\n", "for i, x in enumerate(constant_versions):\n", " if x not in constant_versions_tmp:\n", " constant_versions_tmp.append(x)\n", " constant_parameters_tmp.append(constant_parameters[i])\n", - " \n", + " if i<len(constantBP_versions)-1:\n", + " constantBP_versions_tmp.append(constantBP_versions[i])\n", "constant_versions=constant_versions_tmp\n", + "constantBP_versions=constantBP_versions_tmp\n", "constant_parameters=constant_parameters_tmp\n", "\n", "print('Number of stored constant versions is {}'.format(len(constant_versions)))\n" @@ -266,19 +268,25 @@ "ret_constants = {}\n", "constand_data = ConstantMetaData()\n", "constant_BP = ConstantMetaData()\n", - "for i, constant_version in enumerate(constant_versions):\n", "\n", - " const = constant_version['data_set_name'].split('/')[-2]\n", + "# sort over begin_at\n", + "idxs, _ = zip(*sorted(enumerate(constant_versions), \n", + " key=lambda x: x[1]['begin_at'], reverse=True))\n", + "\n", + "for i in idxs:\n", + " const = constant_versions[i]['data_set_name'].split('/')[-2]\n", " qm = db_module\n", " \n", - " print(\"constant: {}, module {}\".format(const,qm))\n", - " \n", - " constand_data.retrieve_from_version_info(constant_version)\n", - " \n", " if not const in ret_constants:\n", " ret_constants[const] = {}\n", " if not qm in ret_constants[const]:\n", " ret_constants[const][qm] = []\n", + " \n", + " if nconstants>0 and len(ret_constants[const][qm])>=nconstants:\n", + " continue\n", + " \n", + " print(\"constant: {}, module {}\".format(const,qm))\n", + " constand_data.retrieve_from_version_info(constant_versions[i])\n", " \n", " cdata = constand_data.calibration_constant.data\n", " ctime = constand_data.calibration_constant_version.begin_at\n", @@ -374,13 +382,6 @@ "\n", " print('Const: {}'.format(const))\n", "\n", - " # loop over modules\n", - " mod_data = {}\n", - " mod_data['stdASIC'] = []\n", - " mod_data['stdCell'] = []\n", - " mod_names = []\n", - " mod_times = []\n", - "\n", " # Loop over modules\n", " for mod, data in modules.items():\n", " print(mod)\n", @@ -422,32 +423,13 @@ " continue\n", " pdata[key] = rdata[key][:, :, :].reshape(nTimes, nBins).swapaxes(0, 1)\n", "\n", - " # Summary over ASICs\n", - " adata = {}\n", - " for key in rdata:\n", - " if key not in ['Mean', 'std']:\n", - " continue\n", - " adata[key] = np.nanmean(rdata[key], axis=(1, 2))\n", - "\n", - " # Summary information over modules\n", - " for key in pdata:\n", - " if key not in mod_data:\n", - " mod_data[key] = []\n", - " mod_data[key].append(np.nanmean(pdata[key], axis=0))\n", - "\n", - " mod_data['stdASIC'].append(np.nanstd(rdata['Mean'], axis=(1, 2)))\n", - "\n", - " mod_names.append(mod)\n", - " mod_times.append(ctimes_ticks)\n", - "\n", " # Plotting\n", " for key in pdata:\n", " \n", " if key not in ['Mean', 'std']:\n", " continue\n", " \n", - " vmin = None\n", - " vmax = None\n", + " vmin,vmax = get_range(pdata[key][::-1].flatten(), plot_range)\n", " if const in rangevals and key in ['Mean', 'MeanBP']:\n", " vmin = rangevals[const][0][0]\n", " vmax = rangevals[const][0][1]\n", -- GitLab From aec5abf416731d6ee0db1ba6774b5a5b29567479 Mon Sep 17 00:00:00 2001 From: karnem <mikhail.karnevskiy@desy.de> Date: Mon, 2 Sep 2019 11:59:38 +0200 Subject: [PATCH 4/6] simplify code. Include nconstants. --- notebooks/LPD/PlotFromCalDB_LPD_NBC.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/notebooks/LPD/PlotFromCalDB_LPD_NBC.ipynb b/notebooks/LPD/PlotFromCalDB_LPD_NBC.ipynb index b3f50de67..a9471e229 100644 --- a/notebooks/LPD/PlotFromCalDB_LPD_NBC.ipynb +++ b/notebooks/LPD/PlotFromCalDB_LPD_NBC.ipynb @@ -29,7 +29,7 @@ "start_date = \"2018-01-30\" # Date to start investigation interval from\n", "end_date = \"2018-12-12\" # Date to end investigation interval at, can be \"now\"\n", "nconstants = 10 # Number of time stamps to plot. If not 0, overcome start_date.\n", - "constants = [\"Offset\"]#, \"Noise\", \"SlopesFF\", \"SlopesCI\"] # constants to plot\n", + "constants = [\"Offset\", \"Noise\", \"SlopesFF\", \"SlopesCI\"] # constants to plot\n", "modules = [2] # Modules, set to -1 for all, range allowed\n", "bias_voltages = [250, 500] # Bias voltage\n", "mem_cells = [128, 256, 512] # Number of used memory cells.\n", -- GitLab From 50fe51c62ff349c11798c003eab25060791e6285 Mon Sep 17 00:00:00 2001 From: karnem <mikhail.karnevskiy@desy.de> Date: Wed, 4 Sep 2019 19:34:53 +0200 Subject: [PATCH 5/6] Use spShape for plotting --- cal_tools/cal_tools/ana_tools.py | 3 +-- notebooks/AGIPD/PlotFromCalDB_AGIPD_NBC.ipynb | 10 +++++----- notebooks/FastCCD/PlotFromCalDB_FastCCD_NBC.ipynb | 3 ++- notebooks/LPD/PlotFromCalDB_LPD_NBC.ipynb | 9 +++------ 4 files changed, 11 insertions(+), 14 deletions(-) diff --git a/cal_tools/cal_tools/ana_tools.py b/cal_tools/cal_tools/ana_tools.py index dce75cf70..83ee3a30f 100644 --- a/cal_tools/cal_tools/ana_tools.py +++ b/cal_tools/cal_tools/ana_tools.py @@ -354,8 +354,7 @@ class HMType(Enum): def get_range(data, scale): """ - Get range, which includes most of the data points. - Range is calculated in units of median absolute deviations + Return a range calculated by median absolute deviations :param data: numpy.array of data points :param scale: range in units of median absolute deviations diff --git a/notebooks/AGIPD/PlotFromCalDB_AGIPD_NBC.ipynb b/notebooks/AGIPD/PlotFromCalDB_AGIPD_NBC.ipynb index e3efb528a..09e8c0160 100644 --- a/notebooks/AGIPD/PlotFromCalDB_AGIPD_NBC.ipynb +++ b/notebooks/AGIPD/PlotFromCalDB_AGIPD_NBC.ipynb @@ -32,10 +32,10 @@ "constants = [\"Noise\", \"SlopesFF\", \"SlopesPC\", \"Offset\"] # Constants to plot\n", "modules = [1] # Modules, set to -1 for all, range allowed\n", "bias_voltages = [300, 500] # Bias voltage\n", - "mem_cells = [128, 176, 250] # Number of used memory cells. Typically: 4,32,64,128,176.\n", - "acquisition_rate = [None]\n", + "mem_cells = [128, 176, 202, 250] # Number of used memory cells. Typically: 4,32,64,128,176.\n", + "acquisition_rate = [None, 1.1, 2.2, 4.5]\n", "photon_energy = 9.2 # Photon energy of the beam\n", - "out_folder = \"/gpfs/exfel/data/scratch/karnem/testAGIPD16_25/\" # Output folder, required\n", + "out_folder = \"/gpfs/exfel/data/scratch/karnem/test_AGIPD/\" # Output folder, required\n", "use_existing = \"\" # If not empty, constants stored in given folder will be used\n", "cal_db_timeout = 120000 # timeout on caldb requests\",\n", "adu_to_photon = 33.17 # ADU to photon conversion factor (8000 / 3.6 / 67.)\n", @@ -591,8 +591,8 @@ " rdata['MeanBP'][rdata['MeanBP'] < 0.1] = np.nan\n", "\n", " if 'NBP' in rdata:\n", - " rdata[\"NBP\"][rdata[\"NBP\"] == 4096] = np.nan\n", - " rdata[\"NBP\"] = rdata[\"NBP\"] / (64 * 64) * 100\n", + " rdata[\"NBP\"][rdata[\"NBP\"] == (spShape[0] * spShape[1])] = np.nan\n", + " rdata[\"NBP\"] = rdata[\"NBP\"] / (spShape[0] * spShape[1]) * 100\n", "\n", " # Reshape: ASICs over cells for plotting\n", " pdata = {}\n", diff --git a/notebooks/FastCCD/PlotFromCalDB_FastCCD_NBC.ipynb b/notebooks/FastCCD/PlotFromCalDB_FastCCD_NBC.ipynb index 1bd8c1792..b0b88ecd6 100644 --- a/notebooks/FastCCD/PlotFromCalDB_FastCCD_NBC.ipynb +++ b/notebooks/FastCCD/PlotFromCalDB_FastCCD_NBC.ipynb @@ -35,7 +35,7 @@ "parameter_names = ['bias_voltage', 'integration_time', 'temperature', \n", " 'gain_setting', 'pixels_x', 'pixels_y'] # names of parameters\n", "photon_energy = 9.2 # Photon energy of the beam\n", - "out_folder = \"/gpfs/exfel/data/scratch/karnem/test_FCCD6/\" # output folder\n", + "out_folder = \"/gpfs/exfel/data/scratch/karnem/test_FCCD/\" # output folder\n", "use_existing = \"\" # If not empty, constants stored in given folder will be used\n", "cal_db_interface = \"tcp://max-exfl016:8015#8025\" # the database interface to use\n", "cal_db_timeout = 180000 # timeout on caldb requests\",\n", @@ -443,6 +443,7 @@ " rdata['MeanBP'][rdata['MeanBP'] < 0.1] = np.nan\n", " \n", " if 'NBP' in rdata:\n", + " rdata[\"NBP\"][rdata[\"NBP\"] == (spShape[0] * spShape[1])] = np.nan\n", " rdata[\"NBP\"] = rdata[\"NBP\"] / spShape[0] / spShape[1] * 100\n", "\n", " # Reshape: ASICs over cells for plotting\n", diff --git a/notebooks/LPD/PlotFromCalDB_LPD_NBC.ipynb b/notebooks/LPD/PlotFromCalDB_LPD_NBC.ipynb index a9471e229..d30fc84ba 100644 --- a/notebooks/LPD/PlotFromCalDB_LPD_NBC.ipynb +++ b/notebooks/LPD/PlotFromCalDB_LPD_NBC.ipynb @@ -34,7 +34,7 @@ "bias_voltages = [250, 500] # Bias voltage\n", "mem_cells = [128, 256, 512] # Number of used memory cells.\n", "photon_energy = 9.2 # Photon energy of the beam\n", - "out_folder = \"/gpfs/exfel/data/scratch/karnem/testLPD_11/\" # Output folder, required\n", + "out_folder = \"/gpfs/exfel/data/scratch/karnem/test_LPD/\" # Output folder, required\n", "use_existing = \"\" # If not empty, constants stored in given folder will be used\n", "cal_db_timeout = 180000 # timeout on caldb requests\",\n", "adu_to_photon = 33.17 # ADU to photon conversion factor (8000 / 3.6 / 67.)\n", @@ -171,7 +171,6 @@ " meta_only=True,\n", " version_info=True)\n", "\n", - " print(data)\n", " # Request BP constant versions\n", " print('constantDark:', constantsDark[const], ) \n", " dataBP = get_from_db(getattr(det, pars['module']),\n", @@ -185,8 +184,6 @@ " meta_only=True,\n", " version_info=True)\n", " \n", - " print('BP!!!!!', dataBP)\n", - " \n", " if not isinstance(data, list) or not isinstance(dataBP, list):\n", " continue\n", " \n", @@ -581,8 +578,8 @@ " rdata['MeanBP'][rdata['MeanBP'] < 0.1] = np.nan\n", "\n", " if 'NBP' in rdata:\n", - " rdata[\"NBP\"][rdata[\"NBP\"] == 4096] = np.nan\n", - " rdata[\"NBP\"] = rdata[\"NBP\"] / (64 * 64) * 100\n", + " rdata[\"NBP\"][rdata[\"NBP\"] == (spShape[0] * spShape[1])] = np.nan\n", + " rdata[\"NBP\"] = rdata[\"NBP\"] / (spShape[0] * spShape[1]) * 100\n", "\n", " # Reshape: ASICs over cells for plotting\n", " pdata = {}\n", -- GitLab From 48439e07954d77d83fa6bc1a593f24f71787a03c Mon Sep 17 00:00:00 2001 From: karnem <mikhail.karnevskiy@desy.de> Date: Thu, 5 Sep 2019 10:55:42 +0200 Subject: [PATCH 6/6] Convert NBP to float --- notebooks/AGIPD/PlotFromCalDB_AGIPD_NBC.ipynb | 121 ++++++++++++++++-- .../FastCCD/PlotFromCalDB_FastCCD_NBC.ipynb | 1 + notebooks/LPD/PlotFromCalDB_LPD_NBC.ipynb | 1 + 3 files changed, 114 insertions(+), 9 deletions(-) diff --git a/notebooks/AGIPD/PlotFromCalDB_AGIPD_NBC.ipynb b/notebooks/AGIPD/PlotFromCalDB_AGIPD_NBC.ipynb index 09e8c0160..7f4b500b3 100644 --- a/notebooks/AGIPD/PlotFromCalDB_AGIPD_NBC.ipynb +++ b/notebooks/AGIPD/PlotFromCalDB_AGIPD_NBC.ipynb @@ -21,7 +21,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -33,7 +33,7 @@ "modules = [1] # Modules, set to -1 for all, range allowed\n", "bias_voltages = [300, 500] # Bias voltage\n", "mem_cells = [128, 176, 202, 250] # Number of used memory cells. Typically: 4,32,64,128,176.\n", - "acquisition_rate = [None, 1.1, 2.2, 4.5]\n", + "acquisition_rate = [0.0, 1.1, 2.2, 4.5]\n", "photon_energy = 9.2 # Photon energy of the beam\n", "out_folder = \"/gpfs/exfel/data/scratch/karnem/test_AGIPD/\" # Output folder, required\n", "use_existing = \"\" # If not empty, constants stored in given folder will be used\n", @@ -55,7 +55,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": { "scrolled": true }, @@ -79,9 +79,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Bad pixels data: {'SlopesFF': 'BadPixelsFF', 'SlopesPC': 'BadPixelsPC', 'Noise': 'BadPixelsDark', 'Offset': 'BadPixelsDark'}\n", + "CalDB Interface: tcp://max-exfl016:8015#8025\n", + "Start time at: 2019-01-01 00:00:00\n", + "End time at: 2019-12-12 00:00:00\n", + "Modules: ['Q1M2']\n" + ] + } + ], "source": [ "# Prepare variables\n", "nMem = max(mem_cells) # Number of mem Cells to store\n", @@ -92,6 +104,8 @@ " \n", "modules = [\"Q{}M{}\".format(x // 4 + 1, x % 4 + 1) for x in modules]\n", "\n", + "acquisition_rate[acquisition_rate==0] = None\n", + "\n", "constantsDark = {\"SlopesFF\": 'BadPixelsFF',\n", " 'SlopesPC': 'BadPixelsPC',\n", " 'Noise': 'BadPixelsDark',\n", @@ -119,9 +133,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[{'bias_voltage': 300, 'module': 'Q1M2', 'mem_cells': 128, 'acquisition_rate': None}, {'bias_voltage': 300, 'module': 'Q1M2', 'mem_cells': 128, 'acquisition_rate': 1.1}, {'bias_voltage': 300, 'module': 'Q1M2', 'mem_cells': 128, 'acquisition_rate': 2.2}, {'bias_voltage': 300, 'module': 'Q1M2', 'mem_cells': 128, 'acquisition_rate': 4.5}, {'bias_voltage': 300, 'module': 'Q1M2', 'mem_cells': 176, 'acquisition_rate': None}, {'bias_voltage': 300, 'module': 'Q1M2', 'mem_cells': 176, 'acquisition_rate': 1.1}, {'bias_voltage': 300, 'module': 'Q1M2', 'mem_cells': 176, 'acquisition_rate': 2.2}, {'bias_voltage': 300, 'module': 'Q1M2', 'mem_cells': 176, 'acquisition_rate': 4.5}, {'bias_voltage': 300, 'module': 'Q1M2', 'mem_cells': 202, 'acquisition_rate': None}, {'bias_voltage': 300, 'module': 'Q1M2', 'mem_cells': 202, 'acquisition_rate': 1.1}, {'bias_voltage': 300, 'module': 'Q1M2', 'mem_cells': 202, 'acquisition_rate': 2.2}, {'bias_voltage': 300, 'module': 'Q1M2', 'mem_cells': 202, 'acquisition_rate': 4.5}, {'bias_voltage': 300, 'module': 'Q1M2', 'mem_cells': 250, 'acquisition_rate': None}, {'bias_voltage': 300, 'module': 'Q1M2', 'mem_cells': 250, 'acquisition_rate': 1.1}, {'bias_voltage': 300, 'module': 'Q1M2', 'mem_cells': 250, 'acquisition_rate': 2.2}, {'bias_voltage': 300, 'module': 'Q1M2', 'mem_cells': 250, 'acquisition_rate': 4.5}, {'bias_voltage': 500, 'module': 'Q1M2', 'mem_cells': 128, 'acquisition_rate': None}, {'bias_voltage': 500, 'module': 'Q1M2', 'mem_cells': 128, 'acquisition_rate': 1.1}, {'bias_voltage': 500, 'module': 'Q1M2', 'mem_cells': 128, 'acquisition_rate': 2.2}, {'bias_voltage': 500, 'module': 'Q1M2', 'mem_cells': 128, 'acquisition_rate': 4.5}, {'bias_voltage': 500, 'module': 'Q1M2', 'mem_cells': 176, 'acquisition_rate': None}, {'bias_voltage': 500, 'module': 'Q1M2', 'mem_cells': 176, 'acquisition_rate': 1.1}, {'bias_voltage': 500, 'module': 'Q1M2', 'mem_cells': 176, 'acquisition_rate': 2.2}, {'bias_voltage': 500, 'module': 'Q1M2', 'mem_cells': 176, 'acquisition_rate': 4.5}, {'bias_voltage': 500, 'module': 'Q1M2', 'mem_cells': 202, 'acquisition_rate': None}, {'bias_voltage': 500, 'module': 'Q1M2', 'mem_cells': 202, 'acquisition_rate': 1.1}, {'bias_voltage': 500, 'module': 'Q1M2', 'mem_cells': 202, 'acquisition_rate': 2.2}, {'bias_voltage': 500, 'module': 'Q1M2', 'mem_cells': 202, 'acquisition_rate': 4.5}, {'bias_voltage': 500, 'module': 'Q1M2', 'mem_cells': 250, 'acquisition_rate': None}, {'bias_voltage': 500, 'module': 'Q1M2', 'mem_cells': 250, 'acquisition_rate': 1.1}, {'bias_voltage': 500, 'module': 'Q1M2', 'mem_cells': 250, 'acquisition_rate': 2.2}, {'bias_voltage': 500, 'module': 'Q1M2', 'mem_cells': 250, 'acquisition_rate': 4.5}]\n" + ] + } + ], "source": [ "parameter_list = combine_lists(bias_voltages, modules, mem_cells, acquisition_rate,\n", " names = ['bias_voltage', 'module', 'mem_cells', 'acquisition_rate'])\n", @@ -130,11 +152,91 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": { "scrolled": false }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Request: Noise with paramters: {'bias_voltage': 300, 'module': 'Q1M2', 'mem_cells': 128, 'acquisition_rate': None}\n", + "constantDark: BadPixelsDark\n", + "Item: {'id': 6990, 'name': '20190220_072419_sIdx=0', 'file_name': 'cal.1550647458.8201447.h5', 'path_to_file': 'xfel/cal/agipd-type/agipd_siv1_agipdv11_m315/', 'data_set_name': '/AGIPD_SIV1_AGIPDV11_M315/Noise/0', 'flg_deployed': True, 'flg_good_quality': True, 'begin_validity_at': '2019-02-19T15:54:20.000+01:00', 'end_validity_at': None, 'begin_at': '2019-02-19T15:54:20.000+01:00', 'start_idx': 0, 'end_idx': 0, 'raw_data_location': '', 'description': '', 'calibration_constant': {'id': 913, 'name': 'AGIPD-Type_Noise_AGIPD DefJAwEUE0Km+', 'flg_auto_approve': True, 'flg_available': True, 'description': 'Per-pixel (per-memory cell) noise', 'device_type_id': 2, 'calibration_id': 2, 'condition_id': 271}, 'physical_device': {'id': 58, 'name': 'AGIPD_SIV1_AGIPDV11_M315', 'device_type_id': 2, 'flg_available': True, 'parent_id': None, 'description': ''}}\n", + "Found constant Noise: begin at 2019-02-19 15:54:20+01:00\n", + "Found bad pixels at 2019-02-19 15:54:20+01:00\n", + "Item: {'id': 5471, 'name': '20181027_075853_sIdx=0', 'file_name': 'cal.1540627132.6379695.h5', 'path_to_file': 'xfel/cal/agipd-type/agipd_siv1_agipdv11_m315/', 'data_set_name': '/AGIPD_SIV1_AGIPDV11_M315/Noise/0', 'flg_deployed': True, 'flg_good_quality': True, 'begin_validity_at': '2018-10-27T09:20:58.000+02:00', 'end_validity_at': None, 'begin_at': '2018-10-27T09:20:58.000+02:00', 'start_idx': 0, 'end_idx': 0, 'raw_data_location': '', 'description': '', 'calibration_constant': {'id': 913, 'name': 'AGIPD-Type_Noise_AGIPD DefJAwEUE0Km+', 'flg_auto_approve': True, 'flg_available': True, 'description': 'Per-pixel (per-memory cell) noise', 'device_type_id': 2, 'calibration_id': 2, 'condition_id': 271}, 'physical_device': {'id': 58, 'name': 'AGIPD_SIV1_AGIPDV11_M315', 'device_type_id': 2, 'flg_available': True, 'parent_id': None, 'description': ''}}\n", + "Found constant Noise: begin at 2018-10-27 09:20:58+02:00\n", + "Found bad pixels at 2018-10-27 09:20:58+02:00\n", + "Item: {'id': 6791, 'name': '20181213_160158_sIdx=0', 'file_name': 'cal.1544716917.4122818.h5', 'path_to_file': 'xfel/cal/agipd-type/agipd_siv1_agipdv11_m315/', 'data_set_name': '/AGIPD_SIV1_AGIPDV11_M315/Noise/0', 'flg_deployed': True, 'flg_good_quality': True, 'begin_validity_at': '2018-10-22T22:24:16.000+02:00', 'end_validity_at': None, 'begin_at': '2018-10-22T22:24:16.000+02:00', 'start_idx': 0, 'end_idx': 0, 'raw_data_location': '', 'description': '', 'calibration_constant': {'id': 913, 'name': 'AGIPD-Type_Noise_AGIPD DefJAwEUE0Km+', 'flg_auto_approve': True, 'flg_available': True, 'description': 'Per-pixel (per-memory cell) noise', 'device_type_id': 2, 'calibration_id': 2, 'condition_id': 271}, 'physical_device': {'id': 58, 'name': 'AGIPD_SIV1_AGIPDV11_M315', 'device_type_id': 2, 'flg_available': True, 'parent_id': None, 'description': ''}}\n", + "Found constant Noise: begin at 2018-10-22 22:24:16+02:00\n", + "Found bad pixels at 2018-10-22 22:24:16+02:00\n", + "Item: {'id': 6834, 'name': '20190207_135120_sIdx=0', 'file_name': 'cal.1549547479.2884257.h5', 'path_to_file': 'xfel/cal/agipd-type/agipd_siv1_agipdv11_m315/', 'data_set_name': '/AGIPD_SIV1_AGIPDV11_M315/Noise/0', 'flg_deployed': True, 'flg_good_quality': True, 'begin_validity_at': '2018-10-21T20:55:02.000+02:00', 'end_validity_at': None, 'begin_at': '2018-10-21T20:55:02.000+02:00', 'start_idx': 0, 'end_idx': 0, 'raw_data_location': '', 'description': '', 'calibration_constant': {'id': 913, 'name': 'AGIPD-Type_Noise_AGIPD DefJAwEUE0Km+', 'flg_auto_approve': True, 'flg_available': True, 'description': 'Per-pixel (per-memory cell) noise', 'device_type_id': 2, 'calibration_id': 2, 'condition_id': 271}, 'physical_device': {'id': 58, 'name': 'AGIPD_SIV1_AGIPDV11_M315', 'device_type_id': 2, 'flg_available': True, 'parent_id': None, 'description': ''}}\n", + "Found constant Noise: begin at 2018-10-21 20:55:02+02:00\n", + "Found bad pixels at 2018-10-21 20:55:02+02:00\n", + "Item: {'id': 4670, 'name': '20180923_021047_sIdx=0', 'file_name': 'cal.1537668646.6458402.h5', 'path_to_file': 'xfel/cal/agipd-type/agipd_siv1_agipdv11_m315/', 'data_set_name': '/AGIPD_SIV1_AGIPDV11_M315/Noise/0', 'flg_deployed': True, 'flg_good_quality': True, 'begin_validity_at': '2018-09-23T04:10:45.000+02:00', 'end_validity_at': None, 'begin_at': '2018-09-23T04:10:45.000+02:00', 'start_idx': 0, 'end_idx': 0, 'raw_data_location': '', 'description': '', 'calibration_constant': {'id': 913, 'name': 'AGIPD-Type_Noise_AGIPD DefJAwEUE0Km+', 'flg_auto_approve': True, 'flg_available': True, 'description': 'Per-pixel (per-memory cell) noise', 'device_type_id': 2, 'calibration_id': 2, 'condition_id': 271}, 'physical_device': {'id': 58, 'name': 'AGIPD_SIV1_AGIPDV11_M315', 'device_type_id': 2, 'flg_available': True, 'parent_id': None, 'description': ''}}\n", + "Found constant Noise: begin at 2018-09-23 04:10:45+02:00\n", + "Found bad pixels at 2018-09-23 04:10:50+02:00\n", + "Item: {'id': 4546, 'name': '20180923_000251_sIdx=0', 'file_name': 'cal.1537660970.398414.h5', 'path_to_file': 'xfel/cal/agipd-type/agipd_siv1_agipdv11_m315/', 'data_set_name': '/AGIPD_SIV1_AGIPDV11_M315/Noise/0', 'flg_deployed': True, 'flg_good_quality': True, 'begin_validity_at': '2018-09-23T02:02:49.000+02:00', 'end_validity_at': None, 'begin_at': '2018-09-23T02:02:49.000+02:00', 'start_idx': 0, 'end_idx': 0, 'raw_data_location': '', 'description': '', 'calibration_constant': {'id': 913, 'name': 'AGIPD-Type_Noise_AGIPD DefJAwEUE0Km+', 'flg_auto_approve': True, 'flg_available': True, 'description': 'Per-pixel (per-memory cell) noise', 'device_type_id': 2, 'calibration_id': 2, 'condition_id': 271}, 'physical_device': {'id': 58, 'name': 'AGIPD_SIV1_AGIPDV11_M315', 'device_type_id': 2, 'flg_available': True, 'parent_id': None, 'description': ''}}\n", + "Found constant Noise: begin at 2018-09-23 02:02:49+02:00\n", + "Found bad pixels at 2018-09-23 02:02:57+02:00\n", + "Item: {'id': 4482, 'name': '20180922_235703_sIdx=0', 'file_name': 'cal.1537660622.794079.h5', 'path_to_file': 'xfel/cal/agipd-type/agipd_siv1_agipdv11_m315/', 'data_set_name': '/AGIPD_SIV1_AGIPDV11_M315/Noise/0', 'flg_deployed': True, 'flg_good_quality': True, 'begin_validity_at': '2018-09-23T01:57:01.000+02:00', 'end_validity_at': None, 'begin_at': '2018-09-23T01:57:01.000+02:00', 'start_idx': 0, 'end_idx': 0, 'raw_data_location': '', 'description': '', 'calibration_constant': {'id': 913, 'name': 'AGIPD-Type_Noise_AGIPD DefJAwEUE0Km+', 'flg_auto_approve': True, 'flg_available': True, 'description': 'Per-pixel (per-memory cell) noise', 'device_type_id': 2, 'calibration_id': 2, 'condition_id': 271}, 'physical_device': {'id': 58, 'name': 'AGIPD_SIV1_AGIPDV11_M315', 'device_type_id': 2, 'flg_available': True, 'parent_id': None, 'description': ''}}\n", + "Found constant Noise: begin at 2018-09-23 01:57:01+02:00\n", + "Found bad pixels at 2018-09-23 01:57:06+02:00\n", + "Item: {'id': 5269, 'name': '20181025_061038_sIdx=0', 'file_name': 'cal.1540447837.275528.h5', 'path_to_file': 'xfel/cal/agipd-type/agipd_siv1_agipdv11_m315/', 'data_set_name': '/AGIPD_SIV1_AGIPDV11_M315/Noise/0', 'flg_deployed': True, 'flg_good_quality': True, 'begin_validity_at': '2018-09-02T16:25:41.000+02:00', 'end_validity_at': None, 'begin_at': '2018-09-02T16:25:41.000+02:00', 'start_idx': 0, 'end_idx': 0, 'raw_data_location': '', 'description': '', 'calibration_constant': {'id': 913, 'name': 'AGIPD-Type_Noise_AGIPD DefJAwEUE0Km+', 'flg_auto_approve': True, 'flg_available': True, 'description': 'Per-pixel (per-memory cell) noise', 'device_type_id': 2, 'calibration_id': 2, 'condition_id': 271}, 'physical_device': {'id': 58, 'name': 'AGIPD_SIV1_AGIPDV11_M315', 'device_type_id': 2, 'flg_available': True, 'parent_id': None, 'description': ''}}\n", + "Found constant Noise: begin at 2018-09-02 16:25:41+02:00\n", + "Found bad pixels at 2018-09-02 16:25:41+02:00\n", + "Item: {'id': 3431, 'name': '20180901_173920_sIdx=0', 'file_name': 'cal.1535823559.5818477.h5', 'path_to_file': 'xfel/cal/agipd-type/agipd_siv1_agipdv11_m315/', 'data_set_name': '/AGIPD_SIV1_AGIPDV11_M315/Noise/0', 'flg_deployed': True, 'flg_good_quality': True, 'begin_validity_at': '2018-09-01T19:39:13.000+02:00', 'end_validity_at': None, 'begin_at': '2018-09-01T19:39:13.000+02:00', 'start_idx': 0, 'end_idx': 0, 'raw_data_location': '', 'description': '', 'calibration_constant': {'id': 913, 'name': 'AGIPD-Type_Noise_AGIPD DefJAwEUE0Km+', 'flg_auto_approve': True, 'flg_available': True, 'description': 'Per-pixel (per-memory cell) noise', 'device_type_id': 2, 'calibration_id': 2, 'condition_id': 271}, 'physical_device': {'id': 58, 'name': 'AGIPD_SIV1_AGIPDV11_M315', 'device_type_id': 2, 'flg_available': True, 'parent_id': None, 'description': ''}}\n", + "Found constant Noise: begin at 2018-09-01 19:39:13+02:00\n", + "Found bad pixels at 2018-09-01 19:39:29+02:00\n", + "Item: {'id': 3229, 'name': '20180830_164924_sIdx=0', 'file_name': 'cal.1535647763.2838182.h5', 'path_to_file': 'xfel/cal/agipd-type/agipd_siv1_agipdv11_m315/', 'data_set_name': '/AGIPD_SIV1_AGIPDV11_M315/Noise/0', 'flg_deployed': True, 'flg_good_quality': True, 'begin_validity_at': '2018-08-30T18:49:21.000+02:00', 'end_validity_at': None, 'begin_at': '2018-08-30T18:49:21.000+02:00', 'start_idx': 0, 'end_idx': 0, 'raw_data_location': '', 'description': '', 'calibration_constant': {'id': 913, 'name': 'AGIPD-Type_Noise_AGIPD DefJAwEUE0Km+', 'flg_auto_approve': True, 'flg_available': True, 'description': 'Per-pixel (per-memory cell) noise', 'device_type_id': 2, 'calibration_id': 2, 'condition_id': 271}, 'physical_device': {'id': 58, 'name': 'AGIPD_SIV1_AGIPDV11_M315', 'device_type_id': 2, 'flg_available': True, 'parent_id': None, 'description': ''}}\n", + "Found constant Noise: begin at 2018-08-30 18:49:21+02:00\n", + "Found bad pixels at 2018-08-30 18:49:26+02:00\n", + "Item: {'id': 6413, 'name': '20181210_082033_sIdx=0', 'file_name': 'cal.1544430032.7715538.h5', 'path_to_file': 'xfel/cal/agipd-type/agipd_siv1_agipdv11_m315/', 'data_set_name': '/AGIPD_SIV1_AGIPDV11_M315/Noise/0', 'flg_deployed': True, 'flg_good_quality': True, 'begin_validity_at': '2018-01-29T17:10:23.000+01:00', 'end_validity_at': None, 'begin_at': '2018-01-29T17:10:23.000+01:00', 'start_idx': 0, 'end_idx': 0, 'raw_data_location': '', 'description': '', 'calibration_constant': {'id': 913, 'name': 'AGIPD-Type_Noise_AGIPD DefJAwEUE0Km+', 'flg_auto_approve': True, 'flg_available': True, 'description': 'Per-pixel (per-memory cell) noise', 'device_type_id': 2, 'calibration_id': 2, 'condition_id': 271}, 'physical_device': {'id': 58, 'name': 'AGIPD_SIV1_AGIPDV11_M315', 'device_type_id': 2, 'flg_available': True, 'parent_id': None, 'description': ''}}\n", + "Found constant Noise: begin at 2018-01-29 17:10:23+01:00\n", + "Found bad pixels at 2018-01-29 17:10:23+01:00\n", + "Item: {'id': 6348, 'name': '20181210_081739_sIdx=0', 'file_name': 'cal.1544429858.2109814.h5', 'path_to_file': 'xfel/cal/agipd-type/agipd_siv1_agipdv11_m315/', 'data_set_name': '/AGIPD_SIV1_AGIPDV11_M315/Noise/0', 'flg_deployed': True, 'flg_good_quality': True, 'begin_validity_at': '2017-12-04T20:15:40.000+01:00', 'end_validity_at': None, 'begin_at': '2017-12-04T20:15:40.000+01:00', 'start_idx': 0, 'end_idx': 0, 'raw_data_location': '', 'description': '', 'calibration_constant': {'id': 913, 'name': 'AGIPD-Type_Noise_AGIPD DefJAwEUE0Km+', 'flg_auto_approve': True, 'flg_available': True, 'description': 'Per-pixel (per-memory cell) noise', 'device_type_id': 2, 'calibration_id': 2, 'condition_id': 271}, 'physical_device': {'id': 58, 'name': 'AGIPD_SIV1_AGIPDV11_M315', 'device_type_id': 2, 'flg_available': True, 'parent_id': None, 'description': ''}}\n", + "Bad pixels are not found!\n", + "Item: {'id': 6590, 'name': '20181210_092654_sIdx=0', 'file_name': 'cal.1544434013.2191806.h5', 'path_to_file': 'xfel/cal/agipd-type/agipd_siv1_agipdv11_m315/', 'data_set_name': '/AGIPD_SIV1_AGIPDV11_M315/Noise/0', 'flg_deployed': True, 'flg_good_quality': True, 'begin_validity_at': '2017-10-10T19:00:34.000+02:00', 'end_validity_at': None, 'begin_at': '2017-10-10T19:00:34.000+02:00', 'start_idx': 0, 'end_idx': 0, 'raw_data_location': '', 'description': '', 'calibration_constant': {'id': 913, 'name': 'AGIPD-Type_Noise_AGIPD DefJAwEUE0Km+', 'flg_auto_approve': True, 'flg_available': True, 'description': 'Per-pixel (per-memory cell) noise', 'device_type_id': 2, 'calibration_id': 2, 'condition_id': 271}, 'physical_device': {'id': 58, 'name': 'AGIPD_SIV1_AGIPDV11_M315', 'device_type_id': 2, 'flg_available': True, 'parent_id': None, 'description': ''}}\n", + "Found constant Noise: begin at 2017-10-10 19:00:34+02:00\n", + "Found bad pixels at 2017-10-10 19:00:34+02:00\n", + "Item: {'id': 6509, 'name': '20181210_085802_sIdx=0', 'file_name': 'cal.1544432281.1941464.h5', 'path_to_file': 'xfel/cal/agipd-type/agipd_siv1_agipdv11_m315/', 'data_set_name': '/AGIPD_SIV1_AGIPDV11_M315/Noise/0', 'flg_deployed': True, 'flg_good_quality': True, 'begin_validity_at': '2017-09-19T15:10:49.000+02:00', 'end_validity_at': None, 'begin_at': '2017-09-19T15:10:49.000+02:00', 'start_idx': 0, 'end_idx': 0, 'raw_data_location': '', 'description': '', 'calibration_constant': {'id': 913, 'name': 'AGIPD-Type_Noise_AGIPD DefJAwEUE0Km+', 'flg_auto_approve': True, 'flg_available': True, 'description': 'Per-pixel (per-memory cell) noise', 'device_type_id': 2, 'calibration_id': 2, 'condition_id': 271}, 'physical_device': {'id': 58, 'name': 'AGIPD_SIV1_AGIPDV11_M315', 'device_type_id': 2, 'flg_available': True, 'parent_id': None, 'description': ''}}\n", + "Found constant Noise: begin at 2017-09-19 15:10:49+02:00\n", + "Found bad pixels at 2017-09-19 15:10:49+02:00\n", + "Item: {'id': 6543, 'name': '20181210_085904_sIdx=0', 'file_name': 'cal.1544432342.903418.h5', 'path_to_file': 'xfel/cal/agipd-type/agipd_siv1_agipdv11_m315/', 'data_set_name': '/AGIPD_SIV1_AGIPDV11_M315/Noise/0', 'flg_deployed': True, 'flg_good_quality': True, 'begin_validity_at': '2017-09-15T23:33:29.000+02:00', 'end_validity_at': None, 'begin_at': '2017-09-15T23:33:29.000+02:00', 'start_idx': 0, 'end_idx': 0, 'raw_data_location': '', 'description': '', 'calibration_constant': {'id': 913, 'name': 'AGIPD-Type_Noise_AGIPD DefJAwEUE0Km+', 'flg_auto_approve': True, 'flg_available': True, 'description': 'Per-pixel (per-memory cell) noise', 'device_type_id': 2, 'calibration_id': 2, 'condition_id': 271}, 'physical_device': {'id': 58, 'name': 'AGIPD_SIV1_AGIPDV11_M315', 'device_type_id': 2, 'flg_available': True, 'parent_id': None, 'description': ''}}\n", + "Found constant Noise: begin at 2017-09-15 23:33:29+02:00\n", + "Found bad pixels at 2017-09-15 23:33:29+02:00\n", + "Request: Noise with paramters: {'bias_voltage': 300, 'module': 'Q1M2', 'mem_cells': 128, 'acquisition_rate': 1.1}\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "constantDark: BadPixelsDark\n", + "Request: Noise with paramters: {'bias_voltage': 300, 'module': 'Q1M2', 'mem_cells': 128, 'acquisition_rate': 2.2}\n" + ] + }, + { + "ename": "KeyboardInterrupt", + "evalue": "", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m<ipython-input-5-a602d73b9ab9>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 38\u001b[0m \u001b[0mtimeout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcal_db_timeout\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 39\u001b[0m \u001b[0mmeta_only\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 40\u001b[0;31m version_info=True)\n\u001b[0m\u001b[1;32m 41\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 42\u001b[0m \u001b[0;31m# Request BP constant versions\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/gpfs/exfel/data/scratch/karnem/calibration3/pycalibration/cal_tools/cal_tools/tools.py\u001b[0m in \u001b[0;36mget_from_db\u001b[0;34m(device, constant, condition, empty_constant, cal_db_interface, creation_time, verbosity, timeout, ntries, meta_only, version_info)\u001b[0m\n\u001b[1;32m 512\u001b[0m r = metadata.retrieve(this_interface, timeout=timeout,\n\u001b[1;32m 513\u001b[0m \u001b[0mwhen\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mwhen\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmeta_only\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmeta_only\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 514\u001b[0;31m version_info=version_info)\n\u001b[0m\u001b[1;32m 515\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mversion_info\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 516\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mr\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/.local/lib/python3.6/site-packages/iCalibrationDB/meta_data.py\u001b[0m in \u001b[0;36mretrieve\u001b[0;34m(self, receiver, when, silent, timeout, meta_only, version_info)\u001b[0m\n\u001b[1;32m 285\u001b[0m \u001b[0msock\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconnect\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreceiver\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 286\u001b[0m \u001b[0msock\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msend_pyobj\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 287\u001b[0;31m \u001b[0mresp\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msock\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrecv_pyobj\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 288\u001b[0m \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 289\u001b[0m \u001b[0;32mdel\u001b[0m \u001b[0msock\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/software/anaconda3/5.2/lib/python3.6/site-packages/zmq/sugar/socket.py\u001b[0m in \u001b[0;36mrecv_pyobj\u001b[0;34m(self, flags)\u001b[0m\n\u001b[1;32m 620\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0many\u001b[0m \u001b[0mof\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mreasons\u001b[0m \u001b[0;34m:\u001b[0m\u001b[0mfunc\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;31m`\u001b[0m\u001b[0;34m~\u001b[0m\u001b[0mSocket\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrecv\u001b[0m\u001b[0;31m`\u001b[0m \u001b[0mmight\u001b[0m \u001b[0mfail\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 621\u001b[0m \"\"\"\n\u001b[0;32m--> 622\u001b[0;31m \u001b[0mmsg\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrecv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mflags\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 623\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_deserialize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmsg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpickle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloads\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 624\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32mzmq/backend/cython/socket.pyx\u001b[0m in \u001b[0;36mzmq.backend.cython.socket.Socket.recv\u001b[0;34m()\u001b[0m\n", + "\u001b[0;32mzmq/backend/cython/socket.pyx\u001b[0m in \u001b[0;36mzmq.backend.cython.socket.Socket.recv\u001b[0;34m()\u001b[0m\n", + "\u001b[0;32mzmq/backend/cython/socket.pyx\u001b[0m in \u001b[0;36mzmq.backend.cython.socket._recv_copy\u001b[0;34m()\u001b[0m\n", + "\u001b[0;32m/software/anaconda3/5.2/lib/python3.6/site-packages/zmq/backend/cython/checkrc.pxd\u001b[0m in \u001b[0;36mzmq.backend.cython.checkrc._check_rc\u001b[0;34m()\u001b[0m\n", + "\u001b[0;31mKeyboardInterrupt\u001b[0m: " + ] + } + ], "source": [ "# Retrieve list of meta-data\n", "constant_versions = []\n", @@ -591,6 +693,7 @@ " rdata['MeanBP'][rdata['MeanBP'] < 0.1] = np.nan\n", "\n", " if 'NBP' in rdata:\n", + " rdata['NBP'] = rdata['NBP'].astype(float)\n", " rdata[\"NBP\"][rdata[\"NBP\"] == (spShape[0] * spShape[1])] = np.nan\n", " rdata[\"NBP\"] = rdata[\"NBP\"] / (spShape[0] * spShape[1]) * 100\n", "\n", diff --git a/notebooks/FastCCD/PlotFromCalDB_FastCCD_NBC.ipynb b/notebooks/FastCCD/PlotFromCalDB_FastCCD_NBC.ipynb index b0b88ecd6..e2b9a436f 100644 --- a/notebooks/FastCCD/PlotFromCalDB_FastCCD_NBC.ipynb +++ b/notebooks/FastCCD/PlotFromCalDB_FastCCD_NBC.ipynb @@ -443,6 +443,7 @@ " rdata['MeanBP'][rdata['MeanBP'] < 0.1] = np.nan\n", " \n", " if 'NBP' in rdata:\n", + " rdata['NBP'] = rdata['NBP'].astype(float)\n", " rdata[\"NBP\"][rdata[\"NBP\"] == (spShape[0] * spShape[1])] = np.nan\n", " rdata[\"NBP\"] = rdata[\"NBP\"] / spShape[0] / spShape[1] * 100\n", "\n", diff --git a/notebooks/LPD/PlotFromCalDB_LPD_NBC.ipynb b/notebooks/LPD/PlotFromCalDB_LPD_NBC.ipynb index d30fc84ba..d6eba9461 100644 --- a/notebooks/LPD/PlotFromCalDB_LPD_NBC.ipynb +++ b/notebooks/LPD/PlotFromCalDB_LPD_NBC.ipynb @@ -578,6 +578,7 @@ " rdata['MeanBP'][rdata['MeanBP'] < 0.1] = np.nan\n", "\n", " if 'NBP' in rdata:\n", + " rdata['NBP'] = rdata['NBP'].astype(float)\n", " rdata[\"NBP\"][rdata[\"NBP\"] == (spShape[0] * spShape[1])] = np.nan\n", " rdata[\"NBP\"] = rdata[\"NBP\"] / (spShape[0] * spShape[1]) * 100\n", "\n", -- GitLab