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{
"cells": [
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"# Import supporting package"
]
},
{
"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
"outputs": [],
"source": [
"import xarray as xr\n",
"import numpy as np\n",
"\n",
"from uncertainties import ufloat\n",
"from uncertainties import unumpy as unp\n",
"from uncertainties import umath\n",
"\n",
"import matplotlib.pyplot as plt\n",
"\n",
"from DataContainer.ReadData import read_hdf5_file\n",
"from Analyser.ImagingAnalyser import ImageAnalyser\n",
"from Analyser.FitAnalyser import FitAnalyser\n",
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"from Analyser.FitAnalyser import NewFitModel\n",
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"from ToolFunction.ToolFunction import *\n",
"\n",
"from ToolFunction.HomeMadeXarrayFunction import errorbar, dataarray_plot_errorbar\n",
"xr.plot.dataarray_plot.errorbar = errorbar\n",
"xr.plot.accessor.DataArrayPlotAccessor.errorbar = dataarray_plot_errorbar\n",
"\n",
"imageAnalyser = ImageAnalyser()"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## Start a client for parallel computing"
]
},
{
"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
" <div style=\"width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;\"> </div>\n",
" <div style=\"margin-left: 48px;\">\n",
" <h3 style=\"margin-bottom: 0px;\">Client</h3>\n",
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" <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Client-4c16e830-f491-11ed-afbc-80e82ce2fa8e</p>\n",
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" <table style=\"width: 100%; text-align: left;\">\n",
"\n",
" <tr>\n",
" \n",
" <td style=\"text-align: left;\"><strong>Connection method:</strong> Cluster object</td>\n",
" <td style=\"text-align: left;\"><strong>Cluster type:</strong> distributed.LocalCluster</td>\n",
" \n",
" </tr>\n",
"\n",
" \n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:8787/status\" target=\"_blank\">http://127.0.0.1:8787/status</a>\n",
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" </td>\n",
" <td style=\"text-align: left;\"></td>\n",
" </tr>\n",
" \n",
"\n",
" </table>\n",
"\n",
" \n",
"\n",
" \n",
" <details>\n",
" <summary style=\"margin-bottom: 20px;\"><h3 style=\"display: inline;\">Cluster Info</h3></summary>\n",
" <div class=\"jp-RenderedHTMLCommon jp-RenderedHTML jp-mod-trusted jp-OutputArea-output\">\n",
" <div style=\"width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;\">\n",
" </div>\n",
" <div style=\"margin-left: 48px;\">\n",
" <h3 style=\"margin-bottom: 0px; margin-top: 0px;\">LocalCluster</h3>\n",
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" <p style=\"color: #9D9D9D; margin-bottom: 0px;\">7792c6a6</p>\n",
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" <table style=\"width: 100%; text-align: left;\">\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Dashboard:</strong> <a href=\"http://127.0.0.1:8787/status\" target=\"_blank\">http://127.0.0.1:8787/status</a>\n",
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" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Workers:</strong> 6\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total threads:</strong> 60\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total memory:</strong> 55.88 GiB\n",
" </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <td style=\"text-align: left;\"><strong>Status:</strong> running</td>\n",
" <td style=\"text-align: left;\"><strong>Using processes:</strong> True</td>\n",
"</tr>\n",
"\n",
" \n",
" </table>\n",
"\n",
" <details>\n",
" <summary style=\"margin-bottom: 20px;\">\n",
" <h3 style=\"display: inline;\">Scheduler Info</h3>\n",
" </summary>\n",
"\n",
" <div style=\"\">\n",
" <div>\n",
" <div style=\"width: 24px; height: 24px; background-color: #FFF7E5; border: 3px solid #FF6132; border-radius: 5px; position: absolute;\"> </div>\n",
" <div style=\"margin-left: 48px;\">\n",
" <h3 style=\"margin-bottom: 0px;\">Scheduler</h3>\n",
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" <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Scheduler-728ebb44-86df-4773-92bb-8f5c392c0e07</p>\n",
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" <table style=\"width: 100%; text-align: left;\">\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Comm:</strong> tcp://127.0.0.1:51119\n",
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" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Workers:</strong> 6\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Dashboard:</strong> <a href=\"http://127.0.0.1:8787/status\" target=\"_blank\">http://127.0.0.1:8787/status</a>\n",
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" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total threads:</strong> 60\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Started:</strong> Just now\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total memory:</strong> 55.88 GiB\n",
" </td>\n",
" </tr>\n",
" </table>\n",
" </div>\n",
" </div>\n",
"\n",
" <details style=\"margin-left: 48px;\">\n",
" <summary style=\"margin-bottom: 20px;\">\n",
" <h3 style=\"display: inline;\">Workers</h3>\n",
" </summary>\n",
"\n",
" \n",
" <div style=\"margin-bottom: 20px;\">\n",
" <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
" <div style=\"margin-left: 48px;\">\n",
" <details>\n",
" <summary>\n",
" <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 0</h4>\n",
" </summary>\n",
" <table style=\"width: 100%; text-align: left;\">\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Comm: </strong> tcp://127.0.0.1:51152\n",
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" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total threads: </strong> 10\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:51154/status\" target=\"_blank\">http://127.0.0.1:51154/status</a>\n",
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" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Memory: </strong> 9.31 GiB\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Nanny: </strong> tcp://127.0.0.1:51122\n",
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" </td>\n",
" <td style=\"text-align: left;\"></td>\n",
" </tr>\n",
" <tr>\n",
" <td colspan=\"2\" style=\"text-align: left;\">\n",
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" <strong>Local directory: </strong> C:\\Users\\data\\AppData\\Local\\Temp\\dask-worker-space\\worker-h2e02ha_\n",
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" </td>\n",
" </tr>\n",
"\n",
" \n",
"\n",
" \n",
"\n",
" </table>\n",
" </details>\n",
" </div>\n",
" </div>\n",
" \n",
" <div style=\"margin-bottom: 20px;\">\n",
" <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
" <div style=\"margin-left: 48px;\">\n",
" <details>\n",
" <summary>\n",
" <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 1</h4>\n",
" </summary>\n",
" <table style=\"width: 100%; text-align: left;\">\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Comm: </strong> tcp://127.0.0.1:51146\n",
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" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total threads: </strong> 10\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:51147/status\" target=\"_blank\">http://127.0.0.1:51147/status</a>\n",
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" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Memory: </strong> 9.31 GiB\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Nanny: </strong> tcp://127.0.0.1:51123\n",
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" </td>\n",
" <td style=\"text-align: left;\"></td>\n",
" </tr>\n",
" <tr>\n",
" <td colspan=\"2\" style=\"text-align: left;\">\n",
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" <strong>Local directory: </strong> C:\\Users\\data\\AppData\\Local\\Temp\\dask-worker-space\\worker-qno9380b\n",
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" </td>\n",
" </tr>\n",
"\n",
" \n",
"\n",
" \n",
"\n",
" </table>\n",
" </details>\n",
" </div>\n",
" </div>\n",
" \n",
" <div style=\"margin-bottom: 20px;\">\n",
" <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
" <div style=\"margin-left: 48px;\">\n",
" <details>\n",
" <summary>\n",
" <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 2</h4>\n",
" </summary>\n",
" <table style=\"width: 100%; text-align: left;\">\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Comm: </strong> tcp://127.0.0.1:51158\n",
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" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total threads: </strong> 10\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:51159/status\" target=\"_blank\">http://127.0.0.1:51159/status</a>\n",
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" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Memory: </strong> 9.31 GiB\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Nanny: </strong> tcp://127.0.0.1:51124\n",
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" </td>\n",
" <td style=\"text-align: left;\"></td>\n",
" </tr>\n",
" <tr>\n",
" <td colspan=\"2\" style=\"text-align: left;\">\n",
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" <strong>Local directory: </strong> C:\\Users\\data\\AppData\\Local\\Temp\\dask-worker-space\\worker-g4faphle\n",
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" </td>\n",
" </tr>\n",
"\n",
" \n",
"\n",
" \n",
"\n",
" </table>\n",
" </details>\n",
" </div>\n",
" </div>\n",
" \n",
" <div style=\"margin-bottom: 20px;\">\n",
" <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
" <div style=\"margin-left: 48px;\">\n",
" <details>\n",
" <summary>\n",
" <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 3</h4>\n",
" </summary>\n",
" <table style=\"width: 100%; text-align: left;\">\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Comm: </strong> tcp://127.0.0.1:51149\n",
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" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total threads: </strong> 10\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:51150/status\" target=\"_blank\">http://127.0.0.1:51150/status</a>\n",
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" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Memory: </strong> 9.31 GiB\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Nanny: </strong> tcp://127.0.0.1:51125\n",
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" </td>\n",
" <td style=\"text-align: left;\"></td>\n",
" </tr>\n",
" <tr>\n",
" <td colspan=\"2\" style=\"text-align: left;\">\n",
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" <strong>Local directory: </strong> C:\\Users\\data\\AppData\\Local\\Temp\\dask-worker-space\\worker-wnk0crus\n",
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" </td>\n",
" </tr>\n",
"\n",
" \n",
"\n",
" \n",
"\n",
" </table>\n",
" </details>\n",
" </div>\n",
" </div>\n",
" \n",
" <div style=\"margin-bottom: 20px;\">\n",
" <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
" <div style=\"margin-left: 48px;\">\n",
" <details>\n",
" <summary>\n",
" <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 4</h4>\n",
" </summary>\n",
" <table style=\"width: 100%; text-align: left;\">\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Comm: </strong> tcp://127.0.0.1:51153\n",
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" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total threads: </strong> 10\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:51155/status\" target=\"_blank\">http://127.0.0.1:51155/status</a>\n",
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" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Memory: </strong> 9.31 GiB\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Nanny: </strong> tcp://127.0.0.1:51126\n",
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" </td>\n",
" <td style=\"text-align: left;\"></td>\n",
" </tr>\n",
" <tr>\n",
" <td colspan=\"2\" style=\"text-align: left;\">\n",
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" <strong>Local directory: </strong> C:\\Users\\data\\AppData\\Local\\Temp\\dask-worker-space\\worker-fmryn_7r\n",
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" </td>\n",
" </tr>\n",
"\n",
" \n",
"\n",
" \n",
"\n",
" </table>\n",
" </details>\n",
" </div>\n",
" </div>\n",
" \n",
" <div style=\"margin-bottom: 20px;\">\n",
" <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
" <div style=\"margin-left: 48px;\">\n",
" <details>\n",
" <summary>\n",
" <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 5</h4>\n",
" </summary>\n",
" <table style=\"width: 100%; text-align: left;\">\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Comm: </strong> tcp://127.0.0.1:51161\n",
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" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total threads: </strong> 10\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:51162/status\" target=\"_blank\">http://127.0.0.1:51162/status</a>\n",
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" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Memory: </strong> 9.31 GiB\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Nanny: </strong> tcp://127.0.0.1:51127\n",
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" </td>\n",
" <td style=\"text-align: left;\"></td>\n",
" </tr>\n",
" <tr>\n",
" <td colspan=\"2\" style=\"text-align: left;\">\n",
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" <strong>Local directory: </strong> C:\\Users\\data\\AppData\\Local\\Temp\\dask-worker-space\\worker-cv7o44ht\n",
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" </td>\n",
" </tr>\n",
"\n",
" \n",
"\n",
" \n",
"\n",
" </table>\n",
" </details>\n",
" </div>\n",
" </div>\n",
" \n",
"\n",
" </details>\n",
"</div>\n",
"\n",
" </details>\n",
" </div>\n",
"</div>\n",
" </details>\n",
" \n",
"\n",
" </div>\n",
"</div>"
],
"text/plain": [
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"<Client: 'tcp://127.0.0.1:51119' processes=6 threads=60, memory=55.88 GiB>"
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]
},
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"execution_count": 2,
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"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from dask.distributed import Client\n",
"client = Client(n_workers=6, threads_per_worker=10, processes=True, memory_limit='10GB')\n",
"client"
]
},
{
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"attachments": {},
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"cell_type": "markdown",
"metadata": {},
"source": [
"## Set global path for experiment"
]
},
{
"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
"outputs": [],
"source": [
"groupList = [\n",
" \"images/MOT_3D_Camera/in_situ_absorption\",\n",
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" \"images/ODT_1_Axis_Camera/in_situ_absorption\",\n",
" \"images/ODT_2_Axis_Camera/in_situ_absorption\",\n",
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"]\n",
"\n",
"dskey = {\n",
" \"images/MOT_3D_Camera/in_situ_absorption\": \"camera_1\",\n",
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" \"images/ODT_1_Axis_Camera/in_situ_absorption\": \"camera_2\",\n",
" \"images/ODT_2_Axis_Camera/in_situ_absorption\": \"camera_3\",\n",
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"}\n"
]
},
{
"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
"outputs": [],
"source": [
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"img_dir = '//DyLabNAS/Data/'\n",
"SequenceName = \"Repetition_scan\" + \"/\"\n",
"folderPath = img_dir + SequenceName + '2023/' + get_date()"
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]
},
{
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"attachments": {},
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"cell_type": "markdown",
"metadata": {},
"source": [
"# An example for one experimental run"
]
},
{
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"attachments": {},
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"cell_type": "markdown",
"metadata": {},
"source": [
"## Load the data"
]
},
{
"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
"outputs": [
{
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
Add new model for customized fit function
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"Dimensions: (sin_mod_freq: 37, y: 1200, x: 1920)\n",
The first working version
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"Coordinates:\n",
Add new model for customized fit function
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" * sin_mod_freq (sin_mod_freq) float64 65.0 66.0 67.0 ... 99.0 100.0 101.0\n",
Implentment new function
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"Dimensions without coordinates: y, x\n",
The first working version
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"Data variables:\n",
Add new model for customized fit function
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" atoms (sin_mod_freq, y, x) uint16 dask.array&lt;chunksize=(29, 1200, 1920), meta=np.ndarray&gt;\n",
" background (sin_mod_freq, y, x) uint16 dask.array&lt;chunksize=(29, 1200, 1920), meta=np.ndarray&gt;\n",
" dark (sin_mod_freq, y, x) uint16 dask.array&lt;chunksize=(29, 1200, 1920), meta=np.ndarray&gt;\n",
" shotNum (sin_mod_freq) int64 dask.array&lt;chunksize=(37,), meta=np.ndarray&gt;\n",
" OD (sin_mod_freq, y, x) float64 dask.array&lt;chunksize=(29, 1200, 1920), meta=np.ndarray&gt;\n",
Implentment new function
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"Attributes: (12/109)\n",
Add new model for customized fit function
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" TOF_free: 0.01\n",
The first working version
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" abs_img_freq: 110.858\n",
" absorption_imaging_flag: True\n",
" backup_data: True\n",
Implentment new function
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" blink_off_time: 0.001\n",
" blink_on_time: 0.001\n",
The first working version
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" ... ...\n",
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" y_offset_img: 0\n",
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" z_offset: 0.189\n",
" z_offset_img: 0.189\n",
Add new model for customized fit function
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" sin_mod_freq: [ 65. 66. 67. 68. 69. 70. 71. 7...\n",
" scanAxis: [&#x27;sin_mod_freq&#x27;]\n",
" scanAxisLength: [37.]</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-57a1413a-d91a-4579-a579-291f4098a77b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-57a1413a-d91a-4579-a579-291f4098a77b' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>sin_mod_freq</span>: 37</li><li><span>y</span>: 1200</li><li><span>x</span>: 1920</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-f606e9be-20fc-456c-a852-372817f27075' class='xr-section-summary-in' type='checkbox' checked><label for='section-f606e9be-20fc-456c-a852-372817f27075' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>sin_mod_freq</span></div><div class='xr-var-dims'>(sin_mod_freq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>65.0 66.0 67.0 ... 99.0 100.0 101.0</div><input id='attrs-c9ce61a7-e4b0-43e5-9d99-3611a91f34b4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c9ce61a7-e4b0-43e5-9d99-3611a91f34b4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-60adcb2a-fdcc-46fd-8a97-d82a3fde4554' class='xr-var-data-in' type='checkbox'><label for='data-60adcb2a-fdcc-46fd-8a97-d82a3fde4554' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 65., 66., 67., 68., 69., 70., 71., 72., 73., 74., 75., 76.,\n",
" 77., 78., 79., 80., 81., 82., 83., 84., 85., 86., 87., 88.,\n",
" 89., 90., 91., 92., 93., 94., 95., 96., 97., 98., 99., 100.,\n",
" 101.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1564266c-5361-4638-84a9-1cd32b72001e' class='xr-section-summary-in' type='checkbox' checked><label for='section-1564266c-5361-4638-84a9-1cd32b72001e' class='xr-section-summary' >Data variables: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>atoms</span></div><div class='xr-var-dims'>(sin_mod_freq, y, x)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(29, 1200, 1920), meta=np.ndarray&gt;</div><input id='attrs-7cb12d71-d598-477a-b402-53183d9bcd65' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7cb12d71-d598-477a-b402-53183d9bcd65' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8b0ee154-2d4d-497b-ab12-ed0e21df5eb1' class='xr-var-data-in' type='checkbox'><label for='data-8b0ee154-2d4d-497b-ab12-ed0e21df5eb1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>IMAGE_SUBCLASS :</span></dt><dd>IMAGE_GRAYSCALE</dd><dt><span>IMAGE_VERSION :</span></dt><dd>1.2</dd><dt><span>IMAGE_WHITE_IS_ZERO :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><table>\n",
The first working version
2023-05-07 23:41:31 +02:00
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <td> 162.60 MiB </td>\n",
" <td> 127.44 MiB </td>\n",
The first working version
2023-05-07 23:41:31 +02:00
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <td> (37, 1200, 1920) </td>\n",
" <td> (29, 1200, 1920) </td>\n",
The first working version
2023-05-07 23:41:31 +02:00
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <td colspan=\"2\"> 2 chunks in 113 graph layers </td>\n",
The first working version
2023-05-07 23:41:31 +02:00
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <td colspan=\"2\"> uint16 numpy.ndarray </td>\n",
The first working version
2023-05-07 23:41:31 +02:00
" </tr>\n",
" </tbody>\n",
" </table>\n",
" </td>\n",
" <td>\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <svg width=\"196\" height=\"141\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
The first working version
2023-05-07 23:41:31 +02:00
"\n",
" <!-- Horizontal lines -->\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <line x1=\"10\" y1=\"0\" x2=\"26\" y2=\"16\" style=\"stroke-width:2\" />\n",
" <line x1=\"10\" y1=\"75\" x2=\"26\" y2=\"91\" style=\"stroke-width:2\" />\n",
The first working version
2023-05-07 23:41:31 +02:00
"\n",
" <!-- Vertical lines -->\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"75\" style=\"stroke-width:2\" />\n",
" <line x1=\"23\" y1=\"13\" x2=\"23\" y2=\"88\" />\n",
" <line x1=\"26\" y1=\"16\" x2=\"26\" y2=\"91\" style=\"stroke-width:2\" />\n",
The first working version
2023-05-07 23:41:31 +02:00
"\n",
" <!-- Colored Rectangle -->\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <polygon points=\"10.0,0.0 26.954332251750458,16.954332251750458 26.954332251750458,91.95433225175046 10.0,75.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
The first working version
2023-05-07 23:41:31 +02:00
"\n",
" <!-- Horizontal lines -->\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <line x1=\"10\" y1=\"0\" x2=\"130\" y2=\"0\" style=\"stroke-width:2\" />\n",
" <line x1=\"23\" y1=\"13\" x2=\"143\" y2=\"13\" />\n",
" <line x1=\"26\" y1=\"16\" x2=\"146\" y2=\"16\" style=\"stroke-width:2\" />\n",
The first working version
2023-05-07 23:41:31 +02:00
"\n",
" <!-- Vertical lines -->\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <line x1=\"10\" y1=\"0\" x2=\"26\" y2=\"16\" style=\"stroke-width:2\" />\n",
" <line x1=\"130\" y1=\"0\" x2=\"146\" y2=\"16\" style=\"stroke-width:2\" />\n",
The first working version
2023-05-07 23:41:31 +02:00
"\n",
" <!-- Colored Rectangle -->\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <polygon points=\"10.0,0.0 130.0,0.0 146.95433225175046,16.954332251750458 26.954332251750458,16.954332251750458\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
The first working version
2023-05-07 23:41:31 +02:00
"\n",
" <!-- Horizontal lines -->\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <line x1=\"26\" y1=\"16\" x2=\"146\" y2=\"16\" style=\"stroke-width:2\" />\n",
" <line x1=\"26\" y1=\"91\" x2=\"146\" y2=\"91\" style=\"stroke-width:2\" />\n",
The first working version
2023-05-07 23:41:31 +02:00
"\n",
" <!-- Vertical lines -->\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <line x1=\"26\" y1=\"16\" x2=\"26\" y2=\"91\" style=\"stroke-width:2\" />\n",
" <line x1=\"146\" y1=\"16\" x2=\"146\" y2=\"91\" style=\"stroke-width:2\" />\n",
The first working version
2023-05-07 23:41:31 +02:00
"\n",
" <!-- Colored Rectangle -->\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <polygon points=\"26.954332251750458,16.954332251750458 146.95433225175046,16.954332251750458 146.95433225175046,91.95433225175046 26.954332251750458,91.95433225175046\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
The first working version
2023-05-07 23:41:31 +02:00
"\n",
" <!-- Text -->\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <text x=\"86.954332\" y=\"111.954332\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1920</text>\n",
" <text x=\"166.954332\" y=\"54.454332\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,166.954332,54.454332)\">1200</text>\n",
" <text x=\"8.477166\" y=\"103.477166\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,8.477166,103.477166)\">37</text>\n",
The first working version
2023-05-07 23:41:31 +02:00
"</svg>\n",
" </td>\n",
" </tr>\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>background</span></div><div class='xr-var-dims'>(sin_mod_freq, y, x)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(29, 1200, 1920), meta=np.ndarray&gt;</div><input id='attrs-05bc41c2-4d39-42f7-bc71-b743652763ab' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-05bc41c2-4d39-42f7-bc71-b743652763ab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fa6c6dd6-1f3f-4afa-b397-93a104b2ea0e' class='xr-var-data-in' type='checkbox'><label for='data-fa6c6dd6-1f3f-4afa-b397-93a104b2ea0e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>IMAGE_SUBCLASS :</span></dt><dd>IMAGE_GRAYSCALE</dd><dt><span>IMAGE_VERSION :</span></dt><dd>1.2</dd><dt><span>IMAGE_WHITE_IS_ZERO :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><table>\n",
The first working version
2023-05-07 23:41:31 +02:00
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <td> 162.60 MiB </td>\n",
" <td> 127.44 MiB </td>\n",
The first working version
2023-05-07 23:41:31 +02:00
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <td> (37, 1200, 1920) </td>\n",
" <td> (29, 1200, 1920) </td>\n",
The first working version
2023-05-07 23:41:31 +02:00
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <td colspan=\"2\"> 2 chunks in 113 graph layers </td>\n",
The first working version
2023-05-07 23:41:31 +02:00
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <td colspan=\"2\"> uint16 numpy.ndarray </td>\n",
The first working version
2023-05-07 23:41:31 +02:00
" </tr>\n",
" </tbody>\n",
" </table>\n",
" </td>\n",
" <td>\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <svg width=\"196\" height=\"141\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
The first working version
2023-05-07 23:41:31 +02:00
"\n",
" <!-- Horizontal lines -->\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <line x1=\"10\" y1=\"0\" x2=\"26\" y2=\"16\" style=\"stroke-width:2\" />\n",
" <line x1=\"10\" y1=\"75\" x2=\"26\" y2=\"91\" style=\"stroke-width:2\" />\n",
The first working version
2023-05-07 23:41:31 +02:00
"\n",
" <!-- Vertical lines -->\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"75\" style=\"stroke-width:2\" />\n",
" <line x1=\"23\" y1=\"13\" x2=\"23\" y2=\"88\" />\n",
" <line x1=\"26\" y1=\"16\" x2=\"26\" y2=\"91\" style=\"stroke-width:2\" />\n",
The first working version
2023-05-07 23:41:31 +02:00
"\n",
" <!-- Colored Rectangle -->\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <polygon points=\"10.0,0.0 26.954332251750458,16.954332251750458 26.954332251750458,91.95433225175046 10.0,75.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
The first working version
2023-05-07 23:41:31 +02:00
"\n",
" <!-- Horizontal lines -->\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <line x1=\"10\" y1=\"0\" x2=\"130\" y2=\"0\" style=\"stroke-width:2\" />\n",
" <line x1=\"23\" y1=\"13\" x2=\"143\" y2=\"13\" />\n",
" <line x1=\"26\" y1=\"16\" x2=\"146\" y2=\"16\" style=\"stroke-width:2\" />\n",
The first working version
2023-05-07 23:41:31 +02:00
"\n",
" <!-- Vertical lines -->\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <line x1=\"10\" y1=\"0\" x2=\"26\" y2=\"16\" style=\"stroke-width:2\" />\n",
" <line x1=\"130\" y1=\"0\" x2=\"146\" y2=\"16\" style=\"stroke-width:2\" />\n",
The first working version
2023-05-07 23:41:31 +02:00
"\n",
" <!-- Colored Rectangle -->\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <polygon points=\"10.0,0.0 130.0,0.0 146.95433225175046,16.954332251750458 26.954332251750458,16.954332251750458\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
The first working version
2023-05-07 23:41:31 +02:00
"\n",
" <!-- Horizontal lines -->\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <line x1=\"26\" y1=\"16\" x2=\"146\" y2=\"16\" style=\"stroke-width:2\" />\n",
" <line x1=\"26\" y1=\"91\" x2=\"146\" y2=\"91\" style=\"stroke-width:2\" />\n",
The first working version
2023-05-07 23:41:31 +02:00
"\n",
" <!-- Vertical lines -->\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <line x1=\"26\" y1=\"16\" x2=\"26\" y2=\"91\" style=\"stroke-width:2\" />\n",
" <line x1=\"146\" y1=\"16\" x2=\"146\" y2=\"91\" style=\"stroke-width:2\" />\n",
The first working version
2023-05-07 23:41:31 +02:00
"\n",
" <!-- Colored Rectangle -->\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <polygon points=\"26.954332251750458,16.954332251750458 146.95433225175046,16.954332251750458 146.95433225175046,91.95433225175046 26.954332251750458,91.95433225175046\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
The first working version
2023-05-07 23:41:31 +02:00
"\n",
" <!-- Text -->\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <text x=\"86.954332\" y=\"111.954332\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1920</text>\n",
" <text x=\"166.954332\" y=\"54.454332\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,166.954332,54.454332)\">1200</text>\n",
" <text x=\"8.477166\" y=\"103.477166\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,8.477166,103.477166)\">37</text>\n",
The first working version
2023-05-07 23:41:31 +02:00
"</svg>\n",
" </td>\n",
" </tr>\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dark</span></div><div class='xr-var-dims'>(sin_mod_freq, y, x)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(29, 1200, 1920), meta=np.ndarray&gt;</div><input id='attrs-c848c4a0-8a59-49d9-b765-3596b289862b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c848c4a0-8a59-49d9-b765-3596b289862b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-951db309-9e61-487e-93b7-bb8285e9001a' class='xr-var-data-in' type='checkbox'><label for='data-951db309-9e61-487e-93b7-bb8285e9001a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>IMAGE_SUBCLASS :</span></dt><dd>IMAGE_GRAYSCALE</dd><dt><span>IMAGE_VERSION :</span></dt><dd>1.2</dd><dt><span>IMAGE_WHITE_IS_ZERO :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><table>\n",
The first working version
2023-05-07 23:41:31 +02:00
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <td> 162.60 MiB </td>\n",
" <td> 127.44 MiB </td>\n",
The first working version
2023-05-07 23:41:31 +02:00
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <td> (37, 1200, 1920) </td>\n",
" <td> (29, 1200, 1920) </td>\n",
The first working version
2023-05-07 23:41:31 +02:00
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <td colspan=\"2\"> 2 chunks in 113 graph layers </td>\n",
The first working version
2023-05-07 23:41:31 +02:00
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <td colspan=\"2\"> uint16 numpy.ndarray </td>\n",
The first working version
2023-05-07 23:41:31 +02:00
" </tr>\n",
" </tbody>\n",
" </table>\n",
" </td>\n",
" <td>\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <svg width=\"196\" height=\"141\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
regular backup
2023-05-08 17:48:53 +02:00
"\n",
" <!-- Horizontal lines -->\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <line x1=\"10\" y1=\"0\" x2=\"26\" y2=\"16\" style=\"stroke-width:2\" />\n",
" <line x1=\"10\" y1=\"75\" x2=\"26\" y2=\"91\" style=\"stroke-width:2\" />\n",
regular backup
2023-05-08 17:48:53 +02:00
"\n",
" <!-- Vertical lines -->\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"75\" style=\"stroke-width:2\" />\n",
" <line x1=\"23\" y1=\"13\" x2=\"23\" y2=\"88\" />\n",
" <line x1=\"26\" y1=\"16\" x2=\"26\" y2=\"91\" style=\"stroke-width:2\" />\n",
regular backup
2023-05-08 17:48:53 +02:00
"\n",
" <!-- Colored Rectangle -->\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <polygon points=\"10.0,0.0 26.954332251750458,16.954332251750458 26.954332251750458,91.95433225175046 10.0,75.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
The first working version
2023-05-07 23:41:31 +02:00
"\n",
" <!-- Horizontal lines -->\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <line x1=\"10\" y1=\"0\" x2=\"130\" y2=\"0\" style=\"stroke-width:2\" />\n",
" <line x1=\"23\" y1=\"13\" x2=\"143\" y2=\"13\" />\n",
" <line x1=\"26\" y1=\"16\" x2=\"146\" y2=\"16\" style=\"stroke-width:2\" />\n",
The first working version
2023-05-07 23:41:31 +02:00
"\n",
" <!-- Vertical lines -->\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <line x1=\"10\" y1=\"0\" x2=\"26\" y2=\"16\" style=\"stroke-width:2\" />\n",
" <line x1=\"130\" y1=\"0\" x2=\"146\" y2=\"16\" style=\"stroke-width:2\" />\n",
The first working version
2023-05-07 23:41:31 +02:00
"\n",
" <!-- Colored Rectangle -->\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <polygon points=\"10.0,0.0 130.0,0.0 146.95433225175046,16.954332251750458 26.954332251750458,16.954332251750458\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
The first working version
2023-05-07 23:41:31 +02:00
"\n",
" <!-- Horizontal lines -->\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <line x1=\"26\" y1=\"16\" x2=\"146\" y2=\"16\" style=\"stroke-width:2\" />\n",
" <line x1=\"26\" y1=\"91\" x2=\"146\" y2=\"91\" style=\"stroke-width:2\" />\n",
The first working version
2023-05-07 23:41:31 +02:00
"\n",
" <!-- Vertical lines -->\n",
Add new model for customized fit function
2023-05-17 11:03:34 +02:00
" <line x1=\"26\" y1=\"16\" x2=\"26\" y2=\"91\" style=\"stroke-width:2\" />\n",
" <line x1=\"146\" y1=\"16\" x2=\"146\" y2=\"91\" style=\"stroke-width:2\" />\n",
The first working version
2023-05-07 23:41:31 +02:00
"\n",
" <!-- Colored Rectangle -->\n",
Add new model for customized fit function
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"\n",
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" <text x=\"86.954332\" y=\"111.954332\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1920</text>\n",
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"</svg>\n",
" </td>\n",
" </tr>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>shotNum</span></div><div class='xr-var-dims'>(sin_mod_freq)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(37,), meta=np.ndarray&gt;</div><input id='attrs-b7b8c64f-3f56-40ba-a02a-082135ec4729' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b7b8c64f-3f56-40ba-a02a-082135ec4729' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fad5bc38-d913-4276-b188-b4cbfac0641f' class='xr-var-data-in' type='checkbox'><label for='data-fad5bc38-d913-4276-b188-b4cbfac0641f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
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" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
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" <td> 296 B </td>\n",
" <td> 296 B </td>\n",
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" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
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" <td> (37,) </td>\n",
" <td> (37,) </td>\n",
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" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 1 chunks in 1 graph layer </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
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" <td colspan=\"2\"> int64 numpy.ndarray </td>\n",
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" </tr>\n",
" </tbody>\n",
" </table>\n",
" </td>\n",
" <td>\n",
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" <svg width=\"170\" height=\"80\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
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" <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"30\" style=\"stroke-width:2\" />\n",
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"\n",
" <!-- Text -->\n",
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" <text x=\"60.000000\" y=\"50.769622\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >37</text>\n",
" <text x=\"140.000000\" y=\"15.384811\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,15.384811)\">1</text>\n",
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"</svg>\n",
" </td>\n",
" </tr>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>OD</span></div><div class='xr-var-dims'>(sin_mod_freq, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(29, 1200, 1920), meta=np.ndarray&gt;</div><input id='attrs-64421666-efde-4859-a275-b4f177273aba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-64421666-efde-4859-a275-b4f177273aba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e804bef4-59b4-4c5d-97d6-52fa58f39970' class='xr-var-data-in' type='checkbox'><label for='data-e804bef4-59b4-4c5d-97d6-52fa58f39970' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>IMAGE_SUBCLASS :</span></dt><dd>IMAGE_GRAYSCALE</dd><dt><span>IMAGE_VERSION :</span></dt><dd>1.2</dd><dt><span>IMAGE_WHITE_IS_ZERO :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><table>\n",
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" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
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" <td> 650.39 MiB </td>\n",
" <td> 509.77 MiB </td>\n",
The first working version
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" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
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" <td> (37, 1200, 1920) </td>\n",
" <td> (29, 1200, 1920) </td>\n",
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" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
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" <td colspan=\"2\"> 2 chunks in 349 graph layers </td>\n",
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" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
" </tr>\n",
" </tbody>\n",
" </table>\n",
" </td>\n",
" <td>\n",
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" <svg width=\"196\" height=\"141\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
The first working version
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The first working version
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"\n",
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" <line x1=\"10\" y1=\"0\" x2=\"26\" y2=\"16\" style=\"stroke-width:2\" />\n",
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The first working version
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The first working version
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The first working version
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"\n",
" <!-- Text -->\n",
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" <text x=\"86.954332\" y=\"111.954332\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1920</text>\n",
" <text x=\"166.954332\" y=\"54.454332\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,166.954332,54.454332)\">1200</text>\n",
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The first working version
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"</svg>\n",
" </td>\n",
" </tr>\n",
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"</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-99d3f0f7-2dc5-4e1b-a9a8-eb5e8eaf89a6' class='xr-section-summary-in' type='checkbox' ><label for='section-99d3f0f7-2dc5-4e1b-a9a8-eb5e8eaf89a6' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>sin_mod_freq</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-445382f2-44cb-458a-9fe1-0e4f1c21b11a' class='xr-index-data-in' type='checkbox'/><label for='index-445382f2-44cb-458a-9fe1-0e4f1c21b11a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([ 65.0, 66.0, 67.0, 68.0, 69.0, 70.0, 71.0, 72.0, 73.0,\n",
" 74.0, 75.0, 76.0, 77.0, 78.0, 79.0, 80.0, 81.0, 82.0,\n",
" 83.0, 84.0, 85.0, 86.0, 87.0, 88.0, 89.0, 90.0, 91.0,\n",
" 92.0, 93.0, 94.0, 95.0, 96.0, 97.0, 98.0, 99.0, 100.0,\n",
" 101.0],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;sin_mod_freq&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a2d0a646-a4ba-4c4a-b1ce-dedd8e84e93f' class='xr-section-summary-in' type='checkbox' ><label for='section-a2d0a646-a4ba-4c4a-b1ce-dedd8e84e93f' class='xr-section-summary' >Attributes: <span>(109)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>TOF_free :</span></dt><dd>0.01</dd><dt><span>abs_img_freq :</span></dt><dd>110.858</dd><dt><span>absorption_imaging_flag :</span></dt><dd>True</dd><dt><span>backup_data :</span></dt><dd>True</dd><dt><span>blink_off_time :</span></dt><dd>0.001</dd><dt><span>blink_on_time :</span></dt><dd>0.001</dd><dt><span>c_duration :</span></dt><dd>0.2</dd><dt><span>cmot_final_current :</span></dt><dd>0.65</dd><dt><span>cmot_hold :</span></dt><dd>0.06</dd><dt><span>cmot_initial_current :</span></dt><dd>0.18</dd><dt><span>compX_current :</span></dt><dd>0.005</dd><dt><span>compX_current_sg :</span></dt><dd>0</dd><dt><span>compX_final_current :</span></dt><dd>0.005</dd><dt><span>compX_initial_current :</span></dt><dd>0.005</dd><dt><span>compY_current :</span></dt><dd>0</dd><dt><span>compY_current_sg :</span></dt><dd>0</dd><dt><span>compY_final_current :</span></dt><dd>0.0</dd><dt><span>compY_initial_current :</span></dt><dd>0</dd><dt><span>compZ_current :</span></dt><dd>0</dd><dt><span>compZ_current_sg :</span></dt><dd>0.189</dd><dt><span>compZ_final_current :</span></dt><dd>0.271</dd><dt><span>compZ_initial_current :</span></dt><dd>0</dd><dt><span>default_camera :</span></dt><dd>0</dd><dt><span>evap_1_arm_1_final_pow :</span></dt><dd>0.35</dd><dt><span>evap_1_arm_1_mod_depth_final :</span></dt><dd>0</dd><dt><span>evap_1_arm_1_mod_depth_initial :</span></dt><dd>1.0</dd><dt><span>evap_1_arm_1_mod_ramp_duration :</span></dt><dd>1.15</dd><dt><span>evap_1_arm_1_pow_ramp_duration :</span></dt><dd>1.65</dd><dt><span>evap_1_arm_1_start_pow :</span></dt><dd>7</dd><dt><span>evap_1_arm_2_final_pow :</span></dt><dd>5</dd><dt><span>evap_1_arm_2_ramp_duration :</span></dt><dd>0.5</dd><dt><span>evap_1_arm_2_start_pow :</span></dt><dd>0</dd><dt><span>evap_1_mod_ramp_trunc_value :</span></dt><dd>1</dd><dt><span>evap_1_pow_ramp_trunc_value :</span></dt><dd>1.0</dd><dt><span>evap_1_rate_constant_1 :</span></dt><dd>0.525</dd><dt><span>evap_1_rate_constant_2 :</span></dt><dd>0.51</dd><dt><span>evap_2_arm_1_final_pow :</span></dt><dd>0.1</dd><dt><span>evap_2_arm_1_start_pow :</span></dt><dd>0.35</dd><dt><span>evap_2_arm_2_final_pow :</span></dt><dd>1.71</dd><dt><span>evap_2_arm_2_start_pow :</span></dt><dd>5</dd><dt><span>evap_2_ramp_duration :</span></dt><dd>0.5</dd><dt><span>evap_2_ramp_trunc_value :</span></dt><dd>1.0</dd><dt><span>evap_2_rate_constant_1 :</span></dt><dd>0.37</dd><dt><span>evap_2_rate_constant_2 :</span></dt><dd>0.71</dd><dt><span>evap_3_arm_1_final_pow :</span></dt><dd>0.1038</dd><dt><span>evap_3_arm_1_mod_depth_final :</span></dt><dd>0.43</dd><dt><span>evap_3_arm_1_mod_depth_initial :</span></dt><dd>0</dd><dt><span>evap_3_arm_1_start_pow :</span></dt><dd>0.1</dd><dt><span>evap_3_ramp_duration :</span></dt><dd>0.1</dd><dt><span>evap_3_ramp_trunc_value :</span></dt><dd>1.0</dd><dt><span>evap_3_rate_constant_1 :</span></dt><dd>-0.879</dd><dt><span>evap_3_rate_constant_2 :</span></dt><dd>-0.297</dd><dt><span>final_amp :</span></dt><dd>0.0001</dd><dt><span>final_freq :</span></dt><dd>104.0</dd><dt><span>final_pow_1 :</span></dt><dd>0.1038</dd><dt><span>final_pow_2 :</span></dt><dd>1.71</dd><dt><span>gradCoil_current :</span></dt><dd>0.18</dd><dt><span>gradCoil_current_sg :</span></dt><dd>0</dd><dt><span>imaging_method :</span></dt><dd>in_situ_absorption</dd><dt><span>imaging_pulse_duration :</span></dt><dd>2.5e-05</dd><dt><span>imaging_wavelength :</span></dt><dd>4.21291e-07</dd><dt><span>initial_amp :</span></dt><dd>0.62</dd><dt><span>initial_freq :</span></dt><dd>102.13</dd><dt><span>mod_depth_fin :</span></dt><dd>0.43</dd><dt><span>mod_depth_ini :</span></dt><dd>0</dd><d
" 79. 80. 81. 82. 83. 84. 85. 86. 87. 88. 89. 90. 91. 92.\n",
" 93. 94. 95. 96. 97. 98. 99. 100. 101.]</dd><dt><span>scanAxis :</span></dt><dd>[&#x27;sin_mod_freq&#x27;]</dd><dt><span>scanAxisLength :</span></dt><dd>[37.]</dd></dl></div></li></ul></div></div>"
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],
"text/plain": [
"<xarray.Dataset>\n",
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"Dimensions: (sin_mod_freq: 37, y: 1200, x: 1920)\n",
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"Coordinates:\n",
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" * sin_mod_freq (sin_mod_freq) float64 65.0 66.0 67.0 ... 99.0 100.0 101.0\n",
Implentment new function
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"Dimensions without coordinates: y, x\n",
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"Data variables:\n",
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" atoms (sin_mod_freq, y, x) uint16 dask.array<chunksize=(29, 1200, 1920), meta=np.ndarray>\n",
" background (sin_mod_freq, y, x) uint16 dask.array<chunksize=(29, 1200, 1920), meta=np.ndarray>\n",
" dark (sin_mod_freq, y, x) uint16 dask.array<chunksize=(29, 1200, 1920), meta=np.ndarray>\n",
" shotNum (sin_mod_freq) int64 dask.array<chunksize=(37,), meta=np.ndarray>\n",
" OD (sin_mod_freq, y, x) float64 dask.array<chunksize=(29, 1200, 1920), meta=np.ndarray>\n",
Implentment new function
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"Attributes: (12/109)\n",
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" TOF_free: 0.01\n",
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" abs_img_freq: 110.858\n",
" absorption_imaging_flag: True\n",
" backup_data: True\n",
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" blink_off_time: 0.001\n",
" blink_on_time: 0.001\n",
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" ... ...\n",
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" y_offset_img: 0\n",
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" z_offset: 0.189\n",
" z_offset_img: 0.189\n",
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" sin_mod_freq: [ 65. 66. 67. 68. 69. 70. 71. 7...\n",
" scanAxis: ['sin_mod_freq']\n",
" scanAxisLength: [37.]"
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]
},
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"execution_count": 5,
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"metadata": {},
"output_type": "execute_result"
}
],
"source": [
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"shotNum = \"0065\"\n",
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"filePath = folderPath + \"/\" + shotNum + \"/*.h5\"\n",
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"filePath = \"//DyLabNAS/Data/Evaporative_Cooling/2023/05/12/0065/*.h5\"\n",
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"\n",
"dataSetDict = {\n",
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" dskey[groupList[i]]: read_hdf5_file(filePath, groupList[i])\n",
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" for i in [0] # range(len(groupList))\n",
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"}\n",
"\n",
"dataSet = dataSetDict[\"camera_1\"]\n",
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"dataSet = swap_xy(dataSet)\n",
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"\n",
"scanAxis = get_scanAxis(dataSet)\n",
"\n",
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"dataSet = auto_rechunk(dataSet)\n",
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"\n",
"dataSet = imageAnalyser.get_absorption_images(dataSet)\n",
"\n",
"dataSet"
]
},
{
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"attachments": {},
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"cell_type": "markdown",
"metadata": {},
"source": [
"## Calculate an plot OD images"
]
},
{
"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
"outputs": [
{
"data": {
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"image/png": "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"text/plain": [
Add new model for customized fit function
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"<Figure size 11200x300 with 38 Axes>"
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]
},
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"metadata": {},
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"output_type": "display_data"
}
],
"source": [
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"imageAnalyser.center = (959, 280)\n",
"imageAnalyser.span = (150, 200)\n",
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"imageAnalyser.fraction = (0.1, 0.1)\n",
"\n",
"dataSet_cropOD = imageAnalyser.crop_image(dataSet.OD)\n",
"dataSet_cropOD = imageAnalyser.substract_offset(dataSet_cropOD).load()\n",
"\n",
"dataSet_cropOD.plot.pcolormesh(cmap='jet', vmin=0, col=scanAxis[0], row=scanAxis[1])\n",
"plt.show()"
]
},
{
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"attachments": {},
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"cell_type": "markdown",
"metadata": {},
"source": [
"## Do a 2D two-peak gaussian fit to the OD images"
]
},
{
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"attachments": {},
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"cell_type": "markdown",
"metadata": {},
"source": [
"### Do the fit"
]
},
{
"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
Add new model for customized fit function
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"outputs": [],
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"source": [
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"fitAnalyser = FitAnalyser(\"Gaussian-2D\", fitDim=2)\n",
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"\n",
"params = fitAnalyser.guess(dataSet_cropOD, dask=\"parallelized\")\n",
"fitResult = fitAnalyser.fit(dataSet_cropOD, params).load()"
]
},
{
"cell_type": "code",
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"execution_count": 8,
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"metadata": {},
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"outputs": [
{
"data": {
"text/plain": [
"<xarray.plot.facetgrid.FacetGrid at 0x227b2a71d60>"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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"text/plain": [
"<Figure size 11200x300 with 38 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
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"source": [
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"fitCurve = fitAnalyser.eval(fitResult, x=np.arange(150), y=np.arange(200), dask=\"parallelized\").load()\n",
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"\n",
"fitCurve.plot.pcolormesh(cmap='jet', vmin=0, col=scanAxis[0], row=scanAxis[1])"
]
},
{
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"attachments": {},
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"cell_type": "markdown",
"metadata": {},
"source": [
"### Get the result of the fit"
]
},
{
"cell_type": "code",
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"execution_count": 9,
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"metadata": {},
Add new model for customized fit function
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"outputs": [
{
"data": {
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
"Dimensions: (sin_mod_freq: 37)\n",
"Coordinates:\n",
" * sin_mod_freq (sin_mod_freq) float64 65.0 66.0 67.0 ... 99.0 100.0 101.0\n",
"Data variables:\n",
" amplitude (sin_mod_freq) float64 1.808e+03 1.824e+03 ... 1.838e+03\n",
" centerx (sin_mod_freq) float64 73.1 74.3 72.99 ... 73.44 73.32 73.94\n",
" centery (sin_mod_freq) float64 102.0 101.4 102.1 ... 101.7 102.4 102.6\n",
" sigmax (sin_mod_freq) float64 13.57 13.13 13.86 ... 14.41 14.1 14.47\n",
" sigmay (sin_mod_freq) float64 14.06 13.93 14.49 ... 14.98 14.53 14.95\n",
" fwhmx (sin_mod_freq) float64 31.95 30.93 32.63 ... 33.94 33.21 34.08\n",
" fwhmy (sin_mod_freq) float64 33.12 32.8 34.11 ... 35.29 34.22 35.21\n",
" height (sin_mod_freq) float64 14.88 15.66 15.11 ... 12.13 12.67 13.34</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-b16ca569-424f-49fb-9624-e80ad59ef0ca' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b16ca569-424f-49fb-9624-e80ad59ef0ca' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>sin_mod_freq</span>: 37</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-9a359b01-9c2b-46af-a2a0-d462271c3b0c' class='xr-section-summary-in' type='checkbox' checked><label for='section-9a359b01-9c2b-46af-a2a0-d462271c3b0c' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>sin_mod_freq</span></div><div class='xr-var-dims'>(sin_mod_freq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>65.0 66.0 67.0 ... 99.0 100.0 101.0</div><input id='attrs-9a06a662-aff5-4a41-8e42-64faaaf903eb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9a06a662-aff5-4a41-8e42-64faaaf903eb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-048ed711-76a4-4a48-bb3b-94d3b8dd1c3c' class='xr-var-data-in' type='checkbox'><label for='data-048ed711-76a4-4a48-bb3b-94d3b8dd1c3c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 65., 66., 67., 68., 69., 70., 71., 72., 73., 74., 75., 76.,\n",
" 77., 78., 79., 80., 81., 82., 83., 84., 85., 86., 87., 88.,\n",
" 89., 90., 91., 92., 93., 94., 95., 96., 97., 98., 99., 100.,\n",
" 101.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1a5994d9-6c25-4135-bd3e-2811c25b3649' class='xr-section-summary-in' type='checkbox' checked><label for='section-1a5994d9-6c25-4135-bd3e-2811c25b3649' class='xr-section-summary' >Data variables: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>amplitude</span></div><div class='xr-var-dims'>(sin_mod_freq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.808e+03 1.824e+03 ... 1.838e+03</div><input id='attrs-69c255fd-e596-4d70-8fc6-4c2dc651ba8e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-69c255fd-e596-4d70-8fc6-4c2dc651ba8e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d0fb36f1-8b63-4112-a8fe-66496ff31713' class='xr-var-data-in' type='checkbox'><label for='data-d0fb36f1-8b63-4112-a8fe-66496ff31713' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1807.93528127, 1823.85154775, 1930.52699446, 2043.21337596,\n",
" 1755.28170587, 1928.90722727, 1643.95095489, 1283.65467467,\n",
" 808.72834012, 865.21929277, 1035.53685034, 1106.42181287,\n",
" 1412.38825624, 1371.48258955, 1196.81425677, 915.16240689,\n",
" 1146.63503079, 865.02846807, 1084.08216459, 967.18640745,\n",
" 1051.010351 , 1050.16006046, 1215.44969246, 1362.91431476,\n",
" 1217.75835749, 1272.49697584, 1481.75493508, 1464.34592017,\n",
" 1657.25602169, 1696.49246918, 1796.62378969, 1634.71899161,\n",
" 1840.97400511, 1842.53816907, 1668.38908365, 1652.79358228,\n",
" 1838.30544459])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>centerx</span></div><div class='xr-var-dims'>(sin_mod_freq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>73.1 74.3 72.99 ... 73.32 73.94</div><input id='attrs-03fafef3-da1e-4c90-987a-2c1d7dea1bc6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-03fafef3-da1e-4c90-987a-2c1d7dea1bc6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9032f8ec-9c8d-4dd2-8f3f-eeb362b81121' class='xr-var-data-in' type='checkbox'><label for='data-9032f8ec-9c8d-4dd2-8f3f-eeb362b81121' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([73.09504892, 74.2961648 , 72.99174212, 74.04348413, 73.22260606,\n",
" 74.18857612, 72.78553034, 74.97292592, 73.71314922, 72.01768796,\n",
" 74.64580353, 72.19659785, 75.62422128, 72.47608378, 74.504872 ,\n",
" 73.11416511, 73.66486606, 72.66877375, 73.70722415, 73.6648867 ,\n",
" 73.39905462, 73.7277819 , 73.47676618, 73.88127094, 73.05124233,\n",
" 73.61076109, 74.44622984, 73.64707412, 74.68086049, 73.38788184,\n",
" 73.8291442 , 73.54267863, 74.76275625, 73.73687047, 73.4383767 ,\n",
" 73.31801867, 73.93961529])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>centery</span></div><div class='xr-var-dims'>(sin_mod_freq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>102.0 101.4 102.1 ... 102.4 102.6</div><input id='attrs-5b07a723-b710-420d-828a-4721d4d2d180' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5b07a723-b710-420d-828a-4721d4d2d180' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0c45e941-4f12-4a94-a4a3-139718de7ce1' class='xr-var-data-in' type='checkbox'><label for='data-0c45e941-4f12-4a94-a4a3-139718de7ce1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([102.02065787, 101.40658166, 102.09392519, 102.25438654,\n",
" 102.2670119 , 102.52475183, 102.1406389 , 102.26768833,\n",
" 102.57357475, 102.05818657, 102.5193245 , 101.8701202 ,\n",
" 102.41939658, 103.10524973, 102.48141228, 102.63252011,\n",
" 102.48212386, 101.59476336, 102.20244382, 102.4378397 ,\n",
" 102.67450561, 102.67557878, 101.89233182, 102.33627655,\n",
" 102.70081039, 102.72444145, 101.89323699, 102.57296304,\n",
" 102.522762 , 102.08813975, 102.82408395, 101.05807313,\n",
" 103.08641643, 102.65939138, 101.65246632, 102.35511604,\n",
" 102.56255368])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sigmax</span></div><div class='xr-var-dims'>(sin_mod_freq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>13.57 13.13 13.86 ... 14.1 14.47</div><input id='attrs-c4082315-03e8-4c20-bee8-f95ca23f5ef5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c4082315-03e8-4c20-bee8-f95ca23f5ef5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-85ba9d5c-c018-4688-ab53-3ffec042e0fd' class='xr-var-data-in' type='checkbox'><label for='data-85ba9d5c-c018-4688-ab53-3ffec042e0fd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([13.5691735 , 13.13430177, 13.85572302, 13.75440855, 13.720683 ,\n",
" 14.52516874, 14.52583428, 14.89688471, 17.03144916, 16.75918137,\n",
" 17.01356513, 15.73297018, 15.20840342, 15.25850408, 15.49555383,\n",
" 16.05883375, 16.15979326, 16.05513176, 16.11833107, 16.37001508,\n",
" 15.87933474, 16.39350716, 15.96794591, 15.66836669, 16.01693447,\n",
" 15.29321879, 14.87997156, 15.21032252, 14.91656733, 14.57482083,\n",
" 15.40894035, 14.20511874, 14.40218836, 14.6416765 , 14.41249798,\n",
" 14.10096203, 14.4723655 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sigmay</span></div><div class='xr-var-dims'>(sin_mod_freq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>14.06 13.93 14.49 ... 14.53 14.95</div><input id='attrs-59d7f0fd-07a0-485d-a321-a7f1d2dc39bb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-59d7f0fd-07a0-485d-a321-a7f1d2dc39bb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1057992d-a9da-443d-8d9a-d0601bb47dcc' class='xr-var-data-in' type='checkbox'><label for='data-1057992d-a9da-443d-8d9a-d0601bb47dcc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([14.06347139, 13.9298189 , 14.4858854 , 14.39934646, 14.27531429,\n",
" 15.17673738, 14.82353887, 15.05124818, 16.953293 , 16.72497202,\n",
" 16.80107317, 15.8311623 , 15.41953837, 15.43527348, 15.61410368,\n",
" 15.90018414, 16.18510711, 15.94420795, 16.47725015, 16.45599857,\n",
" 16.23727608, 16.38777376, 16.00877073, 15.87241749, 16.18279681,\n",
" 15.3962658 , 15.10517002, 15.38423864, 14.97613875, 14.91383042,\n",
" 15.4906641 , 14.79252339, 15.06554254, 14.96508184, 14.98475356,\n",
" 14.53172023, 14.95164104])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fwhmx</span></div><div class='xr-var-dims'>(sin_mod_freq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>31.95 30.93 32.63 ... 33.21 34.08</div><input id='attrs-20b8310d-5bfa-4b1e-b5a8-f32aede111be' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-20b8310d-5bfa-4b1e-b5a8-f32aede111be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e62025aa-b49e-4657-8e52-5f13f9b847c2' class='xr-var-data-in' type='checkbox'><label for='data-e62025aa-b49e-4657-8e52-5f13f9b847c2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([31.95296115, 30.9289165 , 32.62773368, 32.38915634, 32.30973875,\n",
" 34.20415786, 34.20572508, 35.07948204, 40.10599712, 39.46485547,\n",
" 40.06388344, 37.04831283, 35.81305255, 35.93103059, 36.48924008,\n",
" 37.8156629 , 38.05340437, 37.80694536, 37.95576838, 38.5484389 ,\n",
" 37.39297502, 38.60375853, 37.60163839, 36.89618325, 37.71699762,\n",
" 36.01277746, 35.03965462, 35.81757167, 35.12583107, 34.32107959,\n",
" 36.28528092, 33.45049772, 33.91456118, 34.47851266, 33.9388385 ,\n",
" 33.2052274 , 34.07981572])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fwhmy</span></div><div class='xr-var-dims'>(sin_mod_freq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>33.12 32.8 34.11 ... 34.22 35.21</div><input id='attrs-b0154a41-1124-41f7-a6d6-38eddd2d0057' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b0154a41-1124-41f7-a6d6-38eddd2d0057' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7fe05271-c015-41c8-b7b7-dbb0e5098425' class='xr-var-data-in' type='checkbox'><label for='data-7fe05271-c015-41c8-b7b7-dbb0e5098425' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([33.11694369, 32.80221615, 34.11165266, 33.90786903, 33.6157956 ,\n",
" 35.73848472, 34.90676581, 35.44298023, 39.92195342, 39.38429861,\n",
" 39.56350313, 37.27953762, 36.31023736, 36.34729069, 36.76840363,\n",
" 37.44207162, 38.11301392, 37.54573976, 38.80095819, 38.75091454,\n",
" 38.23586246, 38.59025741, 37.69777349, 37.37668616, 38.10757359,\n",
" 36.25543463, 35.56995646, 36.22711283, 35.26611106, 35.11938614,\n",
" 36.47772564, 34.83372993, 35.47664087, 35.24007403, 35.28639738,\n",
" 34.21958544, 35.20842336])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>height</span></div><div class='xr-var-dims'>(sin_mod_freq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>14.88 15.66 15.11 ... 12.67 13.34</div><input id='attrs-8641450c-34bf-41c7-a7e3-4abc77174512' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8641450c-34bf-41c7-a7e3-4abc77174512' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ccbdc5eb-958a-45be-a9dc-a9a565b530bd' class='xr-var-data-in' type='checkbox'><label for='data-ccbdc5eb-958a-45be-a9dc-a9a565b530bd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([14.88184648, 15.65874295, 15.10850561, 16.20499463, 14.07684364,\n",
" 13.74458414, 11.99266617, 8.99290702, 4.39963716, 4.84872846,\n",
" 5.69053471, 6.97777687, 9.46060633, 9.14710957, 7.77002581,\n",
" 5.62991562, 6.88642302, 5.30803094, 6.41176006, 5.6397095 ,\n",
" 6.40296878, 6.14021435, 7.46878263, 8.60838372, 7.37985805,\n",
" 8.48911324, 10.35543944, 9.82990047, 11.65307999, 12.25968695,\n",
" 11.82317737, 12.22013053, 13.327671 , 13.20889413, 12.13468046,\n",
" 12.66988626, 13.34471058])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-99363739-3a85-453a-a7fd-55b609c1de7c' class='xr-section-summary-in' type='checkbox' ><label for='section-99363739-3a85-453a-a7fd-55b609c1de7c' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>sin_mod_freq</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ed47bed7-852a-4fb0-95ef-eb2ec3b29863' class='xr-index-data-in' type='checkbox'/><label for='index-ed47bed7-852a-4fb0-95ef-eb2ec3b29863' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([ 65.0, 66.0, 67.0, 68.0, 69.0, 70.0, 71.0, 72.0, 73.0,\n",
" 74.0, 75.0, 76.0, 77.0, 78.0, 79.0, 80.0, 81.0, 82.0,\n",
" 83.0, 84.0, 85.0, 86.0, 87.0, 88.0, 89.0, 90.0, 91.0,\n",
" 92.0, 93.0, 94.0, 95.0, 96.0, 97.0, 98.0, 99.0, 100.0,\n",
" 101.0],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;sin_mod_freq&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4f9e0301-7ad5-4e4d-a1ea-0c8b7f72e5fe' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-4f9e0301-7ad5-4e4d-a1ea-0c8b7f72e5fe' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (sin_mod_freq: 37)\n",
"Coordinates:\n",
" * sin_mod_freq (sin_mod_freq) float64 65.0 66.0 67.0 ... 99.0 100.0 101.0\n",
"Data variables:\n",
" amplitude (sin_mod_freq) float64 1.808e+03 1.824e+03 ... 1.838e+03\n",
" centerx (sin_mod_freq) float64 73.1 74.3 72.99 ... 73.44 73.32 73.94\n",
" centery (sin_mod_freq) float64 102.0 101.4 102.1 ... 101.7 102.4 102.6\n",
" sigmax (sin_mod_freq) float64 13.57 13.13 13.86 ... 14.41 14.1 14.47\n",
" sigmay (sin_mod_freq) float64 14.06 13.93 14.49 ... 14.98 14.53 14.95\n",
" fwhmx (sin_mod_freq) float64 31.95 30.93 32.63 ... 33.94 33.21 34.08\n",
" fwhmy (sin_mod_freq) float64 33.12 32.8 34.11 ... 35.29 34.22 35.21\n",
" height (sin_mod_freq) float64 14.88 15.66 15.11 ... 12.13 12.67 13.34"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"fitAnalyser.get_fit_value(fitResult)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
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"}\n",
"\n",
".xr-var-dtype {\n",
" grid-column: 3;\n",
" text-align: right;\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-var-preview {\n",
" grid-column: 4;\n",
"}\n",
"\n",
".xr-index-preview {\n",
" grid-column: 2 / 5;\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-var-name,\n",
".xr-var-dims,\n",
".xr-var-dtype,\n",
".xr-preview,\n",
".xr-attrs dt {\n",
" white-space: nowrap;\n",
" overflow: hidden;\n",
" text-overflow: ellipsis;\n",
" padding-right: 10px;\n",
"}\n",
"\n",
".xr-var-name:hover,\n",
".xr-var-dims:hover,\n",
".xr-var-dtype:hover,\n",
".xr-attrs dt:hover {\n",
" overflow: visible;\n",
" width: auto;\n",
" z-index: 1;\n",
"}\n",
"\n",
".xr-var-attrs,\n",
".xr-var-data,\n",
".xr-index-data {\n",
" display: none;\n",
" background-color: var(--xr-background-color) !important;\n",
" padding-bottom: 5px !important;\n",
"}\n",
"\n",
".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
".xr-var-data-in:checked ~ .xr-var-data,\n",
".xr-index-data-in:checked ~ .xr-index-data {\n",
" display: block;\n",
"}\n",
"\n",
".xr-var-data > table {\n",
" float: right;\n",
"}\n",
"\n",
".xr-var-name span,\n",
".xr-var-data,\n",
".xr-index-name div,\n",
".xr-index-data,\n",
".xr-attrs {\n",
" padding-left: 25px !important;\n",
"}\n",
"\n",
".xr-attrs,\n",
".xr-var-attrs,\n",
".xr-var-data,\n",
".xr-index-data {\n",
" grid-column: 1 / -1;\n",
"}\n",
"\n",
"dl.xr-attrs {\n",
" padding: 0;\n",
" margin: 0;\n",
" display: grid;\n",
" grid-template-columns: 125px auto;\n",
"}\n",
"\n",
".xr-attrs dt,\n",
".xr-attrs dd {\n",
" padding: 0;\n",
" margin: 0;\n",
" float: left;\n",
" padding-right: 10px;\n",
" width: auto;\n",
"}\n",
"\n",
".xr-attrs dt {\n",
" font-weight: normal;\n",
" grid-column: 1;\n",
"}\n",
"\n",
".xr-attrs dt:hover span {\n",
" display: inline-block;\n",
" background: var(--xr-background-color);\n",
" padding-right: 10px;\n",
"}\n",
"\n",
".xr-attrs dd {\n",
" grid-column: 2;\n",
" white-space: pre-wrap;\n",
" word-break: break-all;\n",
"}\n",
"\n",
".xr-icon-database,\n",
".xr-icon-file-text2,\n",
".xr-no-icon {\n",
" display: inline-block;\n",
" vertical-align: middle;\n",
" width: 1em;\n",
" height: 1.5em !important;\n",
" stroke-width: 0;\n",
" stroke: currentColor;\n",
" fill: currentColor;\n",
"}\n",
"</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
"Dimensions: (sin_mod_freq: 37)\n",
"Coordinates:\n",
" * sin_mod_freq (sin_mod_freq) float64 65.0 66.0 67.0 ... 99.0 100.0 101.0\n",
"Data variables:\n",
" amplitude (sin_mod_freq) float64 4.983 4.902 5.145 ... 5.149 4.996 5.165\n",
" centerx (sin_mod_freq) float64 0.0374 0.0353 ... 0.04263 0.04066\n",
" centery (sin_mod_freq) float64 0.03876 0.03744 ... 0.04393 0.04201\n",
" sigmax (sin_mod_freq) float64 0.0374 0.0353 ... 0.04263 0.04066\n",
" sigmay (sin_mod_freq) float64 0.03876 0.03744 ... 0.04393 0.04201\n",
" fwhmx (sin_mod_freq) float64 0.08806 0.08313 ... 0.1004 0.09574\n",
" fwhmy (sin_mod_freq) float64 0.09127 0.08816 ... 0.1034 0.09892\n",
" height (sin_mod_freq) float64 0.04101 0.04209 ... 0.0383 0.03749</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-cac0d698-2d75-429b-a3ca-38fed65cef65' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-cac0d698-2d75-429b-a3ca-38fed65cef65' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>sin_mod_freq</span>: 37</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-3aa534af-2aca-4001-b652-f387349711a3' class='xr-section-summary-in' type='checkbox' checked><label for='section-3aa534af-2aca-4001-b652-f387349711a3' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>sin_mod_freq</span></div><div class='xr-var-dims'>(sin_mod_freq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>65.0 66.0 67.0 ... 99.0 100.0 101.0</div><input id='attrs-c779c951-7e15-4018-b465-7a0d30285dd5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c779c951-7e15-4018-b465-7a0d30285dd5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-01389afa-a2e5-403c-a4a3-288ae7dd7796' class='xr-var-data-in' type='checkbox'><label for='data-01389afa-a2e5-403c-a4a3-288ae7dd7796' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 65., 66., 67., 68., 69., 70., 71., 72., 73., 74., 75., 76.,\n",
" 77., 78., 79., 80., 81., 82., 83., 84., 85., 86., 87., 88.,\n",
" 89., 90., 91., 92., 93., 94., 95., 96., 97., 98., 99., 100.,\n",
" 101.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-28d2b246-837b-4cdc-adb9-47eebb2a0260' class='xr-section-summary-in' type='checkbox' checked><label for='section-28d2b246-837b-4cdc-adb9-47eebb2a0260' class='xr-section-summary' >Data variables: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>amplitude</span></div><div class='xr-var-dims'>(sin_mod_freq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.983 4.902 5.145 ... 4.996 5.165</div><input id='attrs-7ddaa2ed-a5f4-46c4-bc75-c6847fc26932' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7ddaa2ed-a5f4-46c4-bc75-c6847fc26932' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4653bac4-f020-46db-9bee-ce5793b9b6b4' class='xr-var-data-in' type='checkbox'><label for='data-4653bac4-f020-46db-9bee-ce5793b9b6b4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([4.98266213, 4.9018281 , 5.14479386, 5.14442997, 4.86529692,\n",
" 5.34609263, 5.1097508 , 5.1617247 , 5.69705651, 5.89572879,\n",
" 5.78177404, 5.53785205, 5.20287401, 5.39181656, 5.36781952,\n",
" 5.39325699, 5.68167692, 5.51096182, 5.51376788, 5.56567199,\n",
" 5.45334662, 5.54583049, 5.4727448 , 5.38871563, 5.54963612,\n",
" 5.21836749, 5.14053489, 5.34020993, 5.26880024, 5.13042965,\n",
" 5.3829478 , 5.07450941, 5.17017526, 5.1489505 , 5.14911231,\n",
" 4.99648472, 5.16450928])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>centerx</span></div><div class='xr-var-dims'>(sin_mod_freq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0374 0.0353 ... 0.04263 0.04066</div><input id='attrs-edaebb91-c2f7-4e6e-b1b4-68706f5d6200' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-edaebb91-c2f7-4e6e-b1b4-68706f5d6200' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cf3be500-3116-4804-ab11-6c5a45d1e5a2' class='xr-var-data-in' type='checkbox'><label for='data-cf3be500-3116-4804-ab11-6c5a45d1e5a2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0.03739685, 0.03530027, 0.03692505, 0.03463122, 0.03803077,\n",
" 0.04025705, 0.04514956, 0.05990229, 0.11997833, 0.11419663,\n",
" 0.09499302, 0.07874793, 0.05602331, 0.05998719, 0.06949439,\n",
" 0.09463008, 0.08007261, 0.10228334, 0.08198005, 0.09420169,\n",
" 0.08239179, 0.08656959, 0.0718938 , 0.06194711, 0.07299034,\n",
" 0.06271671, 0.05162148, 0.05546782, 0.04742076, 0.04407622,\n",
" 0.04616704, 0.04409588, 0.04044664, 0.04091482, 0.04448065,\n",
" 0.04262786, 0.04065761])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>centery</span></div><div class='xr-var-dims'>(sin_mod_freq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.03876 0.03744 ... 0.04393 0.04201</div><input id='attrs-b342a352-1401-491f-8bbc-908cfb145283' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b342a352-1401-491f-8bbc-908cfb145283' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-35a1e03d-229b-48b8-9a7a-37f649774ce6' class='xr-var-data-in' type='checkbox'><label for='data-35a1e03d-229b-48b8-9a7a-37f649774ce6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0.03875935, 0.03743946, 0.03860445, 0.03625476, 0.03956924,\n",
" 0.04206379, 0.04607504, 0.06052306, 0.11942617, 0.11397052,\n",
" 0.09380765, 0.07923845, 0.05680222, 0.06068179, 0.07003664,\n",
" 0.09371249, 0.08020002, 0.10157981, 0.08380485, 0.09469552,\n",
" 0.08425091, 0.0865484 , 0.07208946, 0.06275968, 0.0737563 ,\n",
" 0.06314083, 0.05240361, 0.05610598, 0.04761736, 0.04510225,\n",
" 0.04641279, 0.04591886, 0.0423105 , 0.041822 , 0.04624768,\n",
" 0.0439303 , 0.04200607])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sigmax</span></div><div class='xr-var-dims'>(sin_mod_freq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0374 0.0353 ... 0.04263 0.04066</div><input id='attrs-245f2957-a1a4-4bb5-9893-82537a88f854' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-245f2957-a1a4-4bb5-9893-82537a88f854' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b3c4913c-19eb-4b31-9982-cd5891c41a2e' class='xr-var-data-in' type='checkbox'><label for='data-b3c4913c-19eb-4b31-9982-cd5891c41a2e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0.03739685, 0.03530027, 0.03692505, 0.03463121, 0.03803077,\n",
" 0.04025705, 0.04514956, 0.05990229, 0.11997834, 0.11419664,\n",
" 0.09499305, 0.07874792, 0.05602331, 0.05998719, 0.06949441,\n",
" 0.09463009, 0.08007261, 0.10228335, 0.08198006, 0.0942017 ,\n",
" 0.08239179, 0.08656961, 0.07189379, 0.06194711, 0.07299033,\n",
" 0.06271671, 0.05162148, 0.05546782, 0.04742077, 0.04407622,\n",
" 0.04616705, 0.04409588, 0.04044664, 0.04091483, 0.04448065,\n",
" 0.04262786, 0.04065762])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sigmay</span></div><div class='xr-var-dims'>(sin_mod_freq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.03876 0.03744 ... 0.04393 0.04201</div><input id='attrs-0135726a-76be-466d-adfc-7f50a7def6ab' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0135726a-76be-466d-adfc-7f50a7def6ab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dc92b54c-8286-4461-820b-ed418497e09d' class='xr-var-data-in' type='checkbox'><label for='data-dc92b54c-8286-4461-820b-ed418497e09d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0.03875935, 0.03743946, 0.03860444, 0.03625475, 0.03956923,\n",
" 0.04206379, 0.04607504, 0.06052306, 0.11942617, 0.11397049,\n",
" 0.09380766, 0.07923845, 0.05680221, 0.06068179, 0.07003661,\n",
" 0.09371244, 0.08020001, 0.10157981, 0.08380486, 0.09469553,\n",
" 0.0842509 , 0.08654838, 0.07208941, 0.06275966, 0.07375626,\n",
" 0.06314083, 0.05240361, 0.05610597, 0.04761734, 0.04510226,\n",
" 0.04641279, 0.04591886, 0.04231049, 0.04182199, 0.04624768,\n",
" 0.0439303 , 0.04200607])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fwhmx</span></div><div class='xr-var-dims'>(sin_mod_freq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.08806 0.08313 ... 0.1004 0.09574</div><input id='attrs-c7d25169-f854-4556-9ce2-f3d0bdb6e468' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c7d25169-f854-4556-9ce2-f3d0bdb6e468' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-657a67a5-bc4d-4c91-a9ee-34ccf6935ff1' class='xr-var-data-in' type='checkbox'><label for='data-657a67a5-bc4d-4c91-a9ee-34ccf6935ff1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0.08806284, 0.08312579, 0.08695185, 0.08155028, 0.08955563,\n",
" 0.0947981 , 0.10631909, 0.1410591 , 0.28252741, 0.26891253,\n",
" 0.22369154, 0.18543718, 0.13192482, 0.14125904, 0.16364682,\n",
" 0.22283683, 0.18855659, 0.24085888, 0.19304828, 0.22182804,\n",
" 0.19401783, 0.20385584, 0.16929693, 0.1458743 , 0.1718791 ,\n",
" 0.14768657, 0.1215593 , 0.13061673, 0.11166738, 0.10379157,\n",
" 0.10871508, 0.10383785, 0.09524457, 0.09634705, 0.10474393,\n",
" 0.10038094, 0.09574137])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fwhmy</span></div><div class='xr-var-dims'>(sin_mod_freq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.09127 0.08816 ... 0.1034 0.09892</div><input id='attrs-08f2b605-675f-4040-a823-c543e1969070' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-08f2b605-675f-4040-a823-c543e1969070' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bed4eb15-4f5c-4fd8-beec-61a5e3282dfd' class='xr-var-data-in' type='checkbox'><label for='data-bed4eb15-4f5c-4fd8-beec-61a5e3282dfd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0.09127129, 0.08816319, 0.09090652, 0.08537342, 0.09317842,\n",
" 0.09905265, 0.10849844, 0.1425209 , 0.28122714, 0.26838 ,\n",
" 0.22090016, 0.18659229, 0.13375899, 0.1428947 , 0.16492362,\n",
" 0.22067594, 0.18885659, 0.23920217, 0.19734535, 0.22299093,\n",
" 0.1983957 , 0.20380585, 0.16975759, 0.1477877 , 0.17368273,\n",
" 0.14868529, 0.12340107, 0.13211945, 0.11213027, 0.1062077 ,\n",
" 0.10929377, 0.10813065, 0.0996336 , 0.09848326, 0.10890495,\n",
" 0.10344794, 0.09891673])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>height</span></div><div class='xr-var-dims'>(sin_mod_freq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.04101 0.04209 ... 0.0383 0.03749</div><input id='attrs-4009f69a-78a7-40af-bdc0-a8ef70793600' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4009f69a-78a7-40af-bdc0-a8ef70793600' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cf180fb6-5d4a-432d-9ac1-d5de65f346ce' class='xr-var-data-in' type='checkbox'><label for='data-cf180fb6-5d4a-432d-9ac1-d5de65f346ce' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0.0410147 , 0.04208569, 0.04026369, 0.04080119, 0.03901854,\n",
" 0.03809403, 0.03727596, 0.03616165, 0.03099311, 0.03304012,\n",
" 0.03177254, 0.03492552, 0.03485046, 0.03596079, 0.03484961,\n",
" 0.03317852, 0.034123 , 0.0338167 , 0.03261096, 0.0324537 ,\n",
" 0.03322293, 0.03242648, 0.03363007, 0.03403604, 0.03363285,\n",
" 0.03481384, 0.03592531, 0.03584817, 0.03704872, 0.03707528,\n",
" 0.03542401, 0.03793384, 0.0374294 , 0.03691256, 0.03745109,\n",
" 0.03830176, 0.03749056])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d8dcef1b-1ff1-49e4-810f-2dd69ffd339a' class='xr-section-summary-in' type='checkbox' ><label for='section-d8dcef1b-1ff1-49e4-810f-2dd69ffd339a' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>sin_mod_freq</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-99628903-ae7a-49a8-99ac-e32bb8623e5e' class='xr-index-data-in' type='checkbox'/><label for='index-99628903-ae7a-49a8-99ac-e32bb8623e5e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([ 65.0, 66.0, 67.0, 68.0, 69.0, 70.0, 71.0, 72.0, 73.0,\n",
" 74.0, 75.0, 76.0, 77.0, 78.0, 79.0, 80.0, 81.0, 82.0,\n",
" 83.0, 84.0, 85.0, 86.0, 87.0, 88.0, 89.0, 90.0, 91.0,\n",
" 92.0, 93.0, 94.0, 95.0, 96.0, 97.0, 98.0, 99.0, 100.0,\n",
" 101.0],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;sin_mod_freq&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a547d877-6292-4f5e-ad89-da4c7791d161' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a547d877-6292-4f5e-ad89-da4c7791d161' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (sin_mod_freq: 37)\n",
"Coordinates:\n",
" * sin_mod_freq (sin_mod_freq) float64 65.0 66.0 67.0 ... 99.0 100.0 101.0\n",
"Data variables:\n",
" amplitude (sin_mod_freq) float64 4.983 4.902 5.145 ... 5.149 4.996 5.165\n",
" centerx (sin_mod_freq) float64 0.0374 0.0353 ... 0.04263 0.04066\n",
" centery (sin_mod_freq) float64 0.03876 0.03744 ... 0.04393 0.04201\n",
" sigmax (sin_mod_freq) float64 0.0374 0.0353 ... 0.04263 0.04066\n",
" sigmay (sin_mod_freq) float64 0.03876 0.03744 ... 0.04393 0.04201\n",
" fwhmx (sin_mod_freq) float64 0.08806 0.08313 ... 0.1004 0.09574\n",
" fwhmy (sin_mod_freq) float64 0.09127 0.08816 ... 0.1034 0.09892\n",
" height (sin_mod_freq) float64 0.04101 0.04209 ... 0.0383 0.03749"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"fitAnalyser.get_fit_std(fitResult)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
"Dimensions: (sin_mod_freq: 37)\n",
"Coordinates:\n",
" * sin_mod_freq (sin_mod_freq) float64 65.0 66.0 67.0 ... 99.0 100.0 101.0\n",
"Data variables:\n",
" amplitude (sin_mod_freq) object 1808+/-5 1824+/-5 ... 1653+/-5 1838+/-5\n",
" centerx (sin_mod_freq) object 73.10+/-0.04 ... 73.94+/-0.04\n",
" centery (sin_mod_freq) object 102.02+/-0.04 ... 102.56+/-0.04\n",
" sigmax (sin_mod_freq) object 13.57+/-0.04 ... 14.47+/-0.04\n",
" sigmay (sin_mod_freq) object 14.06+/-0.04 ... 14.95+/-0.04\n",
" fwhmx (sin_mod_freq) object 31.95+/-0.09 ... 34.08+/-0.10\n",
" fwhmy (sin_mod_freq) object 33.12+/-0.09 ... 35.21+/-0.10\n",
" height (sin_mod_freq) object 14.88+/-0.04 ... 13.34+/-0.04</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-894eab8a-1d40-490e-9d18-b1a9f5661d7a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-894eab8a-1d40-490e-9d18-b1a9f5661d7a' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>sin_mod_freq</span>: 37</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-75eed7c9-9609-436b-9846-fc2e24428fec' class='xr-section-summary-in' type='checkbox' checked><label for='section-75eed7c9-9609-436b-9846-fc2e24428fec' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>sin_mod_freq</span></div><div class='xr-var-dims'>(sin_mod_freq)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>65.0 66.0 67.0 ... 99.0 100.0 101.0</div><input id='attrs-526a431f-cd92-4d25-98c4-8ac284c61f09' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-526a431f-cd92-4d25-98c4-8ac284c61f09' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aa2ea4c3-100b-45cb-8885-f630d69fccae' class='xr-var-data-in' type='checkbox'><label for='data-aa2ea4c3-100b-45cb-8885-f630d69fccae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 65., 66., 67., 68., 69., 70., 71., 72., 73., 74., 75., 76.,\n",
" 77., 78., 79., 80., 81., 82., 83., 84., 85., 86., 87., 88.,\n",
" 89., 90., 91., 92., 93., 94., 95., 96., 97., 98., 99., 100.,\n",
" 101.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3a99ee18-0de9-4a3f-8b2e-245b35953be0' class='xr-section-summary-in' type='checkbox' checked><label for='section-3a99ee18-0de9-4a3f-8b2e-245b35953be0' class='xr-section-summary' >Data variables: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>amplitude</span></div><div class='xr-var-dims'>(sin_mod_freq)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1808+/-5 1824+/-5 ... 1838+/-5</div><input id='attrs-2a987756-cc4a-4c30-b277-e841b6962784' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2a987756-cc4a-4c30-b277-e841b6962784' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e15651d-8b95-4ca8-a4a1-045c659483f7' class='xr-var-data-in' type='checkbox'><label for='data-5e15651d-8b95-4ca8-a4a1-045c659483f7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1807.9352812714108+/-4.982662132541037,\n",
" 1823.85154775407+/-4.901828102937968,\n",
" 1930.526994462659+/-5.144793857378006,\n",
" 2043.2133759591493+/-5.144429970325212,\n",
" 1755.2817058652079+/-4.86529691834173,\n",
" 1928.9072272722694+/-5.346092633667021,\n",
" 1643.9509548864705+/-5.109750803337729,\n",
" 1283.654674671457+/-5.1617246974732485,\n",
" 808.7283401228694+/-5.697056508272371,\n",
" 865.2192927733671+/-5.895728785034902,\n",
" 1035.536850335498+/-5.781774039739138,\n",
" 1106.4218128703744+/-5.537852048784642,\n",
" 1412.3882562391304+/-5.202874010094001,\n",
" 1371.4825895492959+/-5.391816564009922,\n",
" 1196.8142567708005+/-5.3678195236863235,\n",
" 915.1624068883597+/-5.393256988391256,\n",
" 1146.6350307865969+/-5.681676915033084,\n",
" 865.0284680658392+/-5.510961821839697,\n",
" 1084.0821645931596+/-5.513767876755912,\n",
" 967.1864074466855+/-5.565671987567326,\n",
" 1051.0103509981298+/-5.453346618750489,\n",
" 1050.160060457267+/-5.545830491165124,\n",
" 1215.4496924647362+/-5.472744803940935,\n",
" 1362.914314763412+/-5.38871563145762,\n",
" 1217.758357490078+/-5.549636118273387,\n",
" 1272.4969758358966+/-5.218367489271,\n",
" 1481.7549350788274+/-5.140534890135545,\n",
" 1464.345920167834+/-5.340209925672025,\n",
" 1657.2560216925572+/-5.26880023524984,\n",
" 1696.4924691819663+/-5.130429652113225,\n",
" 1796.623789689513+/-5.382947804916028,\n",
" 1634.7189916108157+/-5.074509405013973,\n",
" 1840.9740051070407+/-5.170175257574056,\n",
" 1842.538169066767+/-5.148950503187781,\n",
" 1668.3890836530013+/-5.14911231440146,\n",
" 1652.7935822839536+/-4.996484716004756,\n",
" 1838.3054445911898+/-5.1645092842102125], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>centerx</span></div><div class='xr-var-dims'>(sin_mod_freq)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>73.10+/-0.04 ... 73.94+/-0.04</div><input id='attrs-f3770277-1a3d-4dee-84fe-b2696572e392' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f3770277-1a3d-4dee-84fe-b2696572e392' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e03cc860-b1fd-4a21-8e53-082884c1c3d1' class='xr-var-data-in' type='checkbox'><label for='data-e03cc860-b1fd-4a21-8e53-082884c1c3d1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([73.09504891981685+/-0.037396850843899786,\n",
" 74.29616480490488+/-0.03530026573901377,\n",
" 72.99174212405437+/-0.03692505314668794,\n",
" 74.04348412960547+/-0.034631221056806515,\n",
" 73.22260606208776+/-0.03803077217333051,\n",
" 74.18857612462642+/-0.040257049047883846,\n",
" 72.78553034213337+/-0.045149557482025246,\n",
" 74.97292592232597+/-0.059902294648404804,\n",
" 73.71314922193328+/-0.119978325212914,\n",
" 72.0176879617503+/-0.11419662774435227,\n",
" 74.645803526158+/-0.09499302238504567,\n",
" 72.19659785409318+/-0.07874792616944704,\n",
" 75.62422127845886+/-0.05602331222095948,\n",
" 72.47608378462917+/-0.059987190631156734,\n",
" 74.50487200177812+/-0.06949439442737751,\n",
" 73.11416510596015+/-0.0946300766642044,\n",
" 73.66486606016898+/-0.08007260777748927,\n",
" 72.66877374594371+/-0.10228334033784599,\n",
" 73.70722414562073+/-0.08198005354710461,\n",
" 73.66488669941407+/-0.09420169292548253,\n",
" 73.39905461616789+/-0.08239179358343209,\n",
" 73.72778190423742+/-0.08656959204498607,\n",
" 73.47676617581749+/-0.07189379747074462,\n",
" 73.88127093983336+/-0.06194710936103844,\n",
" 73.0512423338802+/-0.07299033561438083,\n",
" 73.6107610907786+/-0.06271671074663257,\n",
" 74.44622984418639+/-0.051621482668948705,\n",
" 73.64707412048958+/-0.05546781600340132,\n",
" 74.68086049145623+/-0.047420757491135564,\n",
" 73.38788183970141+/-0.04407621891829975,\n",
" 73.82914420096141+/-0.046167044698070384,\n",
" 73.54267863233993+/-0.04409587546638506,\n",
" 74.76275624723894+/-0.040446642439489214,\n",
" 73.73687047199249+/-0.040914824588434165,\n",
" 73.43837670134414+/-0.044480653109287005,\n",
" 73.3180186748058+/-0.04262786101060659,\n",
" 73.93961529084122+/-0.040657614876137206], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>centery</span></div><div class='xr-var-dims'>(sin_mod_freq)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>102.02+/-0.04 ... 102.56+/-0.04</div><input id='attrs-cfd8b0e2-ff01-42fa-8403-91d56337b634' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cfd8b0e2-ff01-42fa-8403-91d56337b634' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d9b5868d-34d3-4629-9350-c6a8639362a5' class='xr-var-data-in' type='checkbox'><label for='data-d9b5868d-34d3-4629-9350-c6a8639362a5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([102.02065787176446+/-0.03875935360837667,\n",
" 101.40658165721067+/-0.03743946020656038,\n",
" 102.09392518616498+/-0.03860444799056684,\n",
" 102.25438654459214+/-0.03625475884751028,\n",
" 102.26701189852484+/-0.03956923706689795,\n",
" 102.52475183023932+/-0.04206379046160063,\n",
" 102.14063890468991+/-0.0460750429618416,\n",
" 102.26768833058534+/-0.060523064815414335,\n",
" 102.5735747504943+/-0.11942617427669155,\n",
" 102.05818657219392+/-0.11397052419701628,\n",
" 102.5193245010779+/-0.09380765446436551,\n",
" 101.87012020466427+/-0.07923845352943534,\n",
" 102.41939658216964+/-0.05680221613230117,\n",
" 103.10524972566515+/-0.06068179055019741,\n",
" 102.4814122838628+/-0.07003663597202123,\n",
" 102.63252011125154+/-0.09371248895718273,\n",
" 102.48212386105973+/-0.08020001687348137,\n",
" 101.59476336364582+/-0.1015798123137109,\n",
" 102.20244381944985+/-0.08380485227387936,\n",
" 102.4378396998888+/-0.09469552494709083,\n",
" 102.67450561086073+/-0.08425091006234325,\n",
" 102.67557877513744+/-0.08654839745122632,\n",
" 101.89233182320508+/-0.07208946326502778,\n",
" 102.33627655123132+/-0.06275967796778213,\n",
" 102.70081039416783+/-0.07375630011442043,\n",
" 102.7244414546981+/-0.06314083331824284,\n",
" 101.89323698659102+/-0.052403614967216794,\n",
" 102.57296303925237+/-0.05610597615550597,\n",
" 102.52276200109449+/-0.04761735525006581,\n",
" 102.08813974615472+/-0.04510225443317714,\n",
" 102.82408394967328+/-0.046412793659455796,\n",
" 101.05807313058507+/-0.045918857127639,\n",
" 103.08641642886512+/-0.042310495379330945,\n",
" 102.6593913839422+/-0.04182200020917299,\n",
" 101.65246632370746+/-0.0462476794898511,\n",
" 102.35511603648571+/-0.04393029668411993,\n",
" 102.5625536770304+/-0.04200607251326068], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sigmax</span></div><div class='xr-var-dims'>(sin_mod_freq)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>13.57+/-0.04 ... 14.47+/-0.04</div><input id='attrs-7663d28b-58d3-4ae4-a972-19b12b1a2a5e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7663d28b-58d3-4ae4-a972-19b12b1a2a5e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d4a70ea5-7c12-40f5-a5af-e548f2085907' class='xr-var-data-in' type='checkbox'><label for='data-d4a70ea5-7c12-40f5-a5af-e548f2085907' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([13.569173504306505+/-0.037396847719753434,\n",
" 13.134301774185666+/-0.03530027285274352,\n",
" 13.855723020904408+/-0.03692505024051494,\n",
" 13.754408548681447+/-0.03463121423827747,\n",
" 13.720683001901005+/-0.038030773532425094,\n",
" 14.525168743389449+/-0.04025704866808143,\n",
" 14.52583428240102+/-0.045149559773349474,\n",
" 14.896884706502126+/-0.05990228662109335,\n",
" 17.031449164894067+/-0.1199783449482783,\n",
" 16.75918136855712+/-0.11419663801157412,\n",
" 17.013565131091937+/-0.09499305022154365,\n",
" 15.73297017703764+/-0.07874791947403095,\n",
" 15.208403424002462+/-0.0560233138860654,\n",
" 15.258504084506772+/-0.059987191057218246,\n",
" 15.49555383265196+/-0.06949440692627573,\n",
" 16.058833752809814+/-0.09463009164895014,\n",
" 16.159793263725494+/-0.0800726116032752,\n",
" 16.055131756553152+/-0.10228335001836295,\n",
" 16.118331072975888+/-0.08198005759381842,\n",
" 16.37001507653549+/-0.09420169847030081,\n",
" 15.879334736731362+/-0.08239178884498273,\n",
" 16.393507159672822+/-0.08656960554653291,\n",
" 15.967945912624543+/-0.0718937870158822,\n",
" 15.668366688899447+/-0.061947111672037015,\n",
" 16.01693446766972+/-0.07299033293205849,\n",
" 15.293218786379907+/-0.0627167141051018,\n",
" 14.879971557306325+/-0.05162148291168589,\n",
" 15.210322518525086+/-0.05546782021883629,\n",
" 14.916567325930995+/-0.04742077261807891,\n",
" 14.574820830628099+/-0.044076224367750716,\n",
" 15.408940353714637+/-0.0461670464784016,\n",
" 14.205118741915296+/-0.0440958758861363,\n",
" 14.402188355497445+/-0.04044664378364179,\n",
" 14.641676503917477+/-0.04091482684494756,\n",
" 14.41249798382422+/-0.044480653723043946,\n",
" 14.100962028338062+/-0.042627863260911864,\n",
" 14.47236549602896+/-0.04065761651283394], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sigmay</span></div><div class='xr-var-dims'>(sin_mod_freq)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>14.06+/-0.04 ... 14.95+/-0.04</div><input id='attrs-82f8ad49-1507-4f9e-8e07-f61178f9a6e0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-82f8ad49-1507-4f9e-8e07-f61178f9a6e0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-677b782a-a725-49d5-8e7e-1e8ed61cfbd3' class='xr-var-data-in' type='checkbox'><label for='data-677b782a-a725-49d5-8e7e-1e8ed61cfbd3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([14.063471385960062+/-0.03875934950576456,\n",
" 13.92981890299772+/-0.03743946227379337,\n",
" 14.485885399190085+/-0.03860444499360111,\n",
" 14.399346457572326+/-0.03625475338394724,\n",
" 14.275314291868877+/-0.03956923347243963,\n",
" 15.176737382879598+/-0.04206378707447388,\n",
" 14.823538872250287+/-0.04607504431597218,\n",
" 15.051248175031947+/-0.06052305590582919,\n",
" 16.9532929975256+/-0.11942617283874755,\n",
" 16.72497202040855+/-0.11397049487790552,\n",
" 16.801073174049286+/-0.09380766202844636,\n",
" 15.83116230365194+/-0.07923845106501783,\n",
" 15.419538374924894+/-0.056802213235449886,\n",
" 15.435273475864271+/-0.06068179152951895,\n",
" 15.614103679244732+/-0.0700366129354111,\n",
" 15.900184139453355+/-0.09371244367659479,\n",
" 16.185107108451028+/-0.08020001047877354,\n",
" 15.9442079491525+/-0.10157980905019252,\n",
" 16.477250147560312+/-0.08380485616759545,\n",
" 16.45599856565011+/-0.09469553033981885,\n",
" 16.237276079141967+/-0.084250898004433,\n",
" 16.38777376057195+/-0.08654837771011424,\n",
" 16.0087707286694+/-0.07208941153302233,\n",
" 15.872417492933067+/-0.06275965962921957,\n",
" 16.182796812452068+/-0.07375626395556516,\n",
" 15.396265799674268+/-0.06314083177839307,\n",
" 15.105170017602152+/-0.05240361084159723,\n",
" 15.384238636239676+/-0.05610596667110579,\n",
" 14.976138754479786+/-0.04761734373220863,\n",
" 14.913830417363938+/-0.04510225676060777,\n",
" 15.490664101660112+/-0.046412792906928194,\n",
" 14.792523390463542+/-0.04591885911254156,\n",
" 15.065542535217219+/-0.04231049398766332,\n",
" 14.965081843205327+/-0.0418219896043396,\n",
" 14.984753560181455+/-0.046247676858111875,\n",
" 14.531720234531237+/-0.04393029804015326,\n",
" 14.951641041563711+/-0.04200606644357985], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fwhmx</span></div><div class='xr-var-dims'>(sin_mod_freq)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>31.95+/-0.09 ... 34.08+/-0.10</div><input id='attrs-c2135620-156f-4e3a-bde0-643ba68708f1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c2135620-156f-4e3a-bde0-643ba68708f1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7ce561d6-0cfd-48c5-a6c2-f9e13de42420' class='xr-var-data-in' type='checkbox'><label for='data-7ce561d6-0cfd-48c5-a6c2-f9e13de42420' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([31.952961151411046+/-0.08806284477053719,\n",
" 30.92891650388789+/-0.08312578838586394,\n",
" 32.627733684086124+/-0.08695184623419695,\n",
" 32.38915633860605+/-0.08155027591999983,\n",
" 32.309738746536524+/-0.0895556258232886,\n",
" 34.20415786030834+/-0.0947981032585882,\n",
" 34.20572508488357+/-0.10631908594054404,\n",
" 35.07948204456534+/-0.14105910271774877,\n",
" 40.10599712247585+/-0.28252740767067386,\n",
" 39.46485547030568+/-0.2689125268648788,\n",
" 40.063883441997916+/-0.2236915350867087,\n",
" 37.04831283229178+/-0.1854371760870019,\n",
" 35.81305255090948+/-0.1319248203859211,\n",
" 35.93103058827824+/-0.141259036944913,\n",
" 36.48924007620549+/-0.16364681973665232,\n",
" 37.81566289779161+/-0.22283683219921452,\n",
" 38.05340437328607+/-0.1885565870471219,\n",
" 37.806945362966495+/-0.24085887956054602,\n",
" 37.95576837726508+/-0.1930482790680572,\n",
" 38.54843890252731+/-0.2218280429296777,\n",
" 37.392975024749745+/-0.19401783255653662,\n",
" 38.60375852974076+/-0.20385583876433666,\n",
" 37.60163839396653+/-0.1692969282681454,\n",
" 36.8961832463542+/-0.14587429753119055,\n",
" 37.716997623158015+/-0.17187909579637145,\n",
" 36.012777462543134+/-0.1476865731369782,\n",
" 35.03965462257608+/-0.12155930076884316,\n",
" 35.817571673073246+/-0.13061673228716467,\n",
" 35.125831070448825+/-0.11166738395681468,\n",
" 34.32107958837966+/-0.10379157437592229,\n",
" 36.285280923734305+/-0.10871508444574295,\n",
" 33.45049771583698+/-0.10383785017922341,\n",
" 33.9145611832925+/-0.09524456529321775,\n",
" 34.478512664954955+/-0.09634705216148866,\n",
" 33.93883850226895+/-0.1047439329372441,\n",
" 33.20522740357104+/-0.10038094487778118,\n",
" 34.07981571735892+/-0.09574136893029611], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fwhmy</span></div><div class='xr-var-dims'>(sin_mod_freq)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>33.12+/-0.09 ... 35.21+/-0.10</div><input id='attrs-363cf11f-77ba-457f-ab97-7aaf74db0d43' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-363cf11f-77ba-457f-ab97-7aaf74db0d43' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ff4b7c6a-02f8-4352-bd02-dc12bf61d215' class='xr-var-data-in' type='checkbox'><label for='data-ff4b7c6a-02f8-4352-bd02-dc12bf61d215' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([33.116943689086476+/-0.09127129115155849,\n",
" 32.80221614915709+/-0.08816319493395755,\n",
" 34.111652655720796+/-0.09090651904514575,\n",
" 33.907869025220464+/-0.08537341855330385,\n",
" 33.615795600778675+/-0.09317842239760347,\n",
" 35.73848472395254+/-0.09905264745430267,\n",
" 34.906765807152425+/-0.1084984362622371,\n",
" 35.442980227528736+/-0.14252090179848284,\n",
" 39.92195341643324+/-0.28122714048812875,\n",
" 39.384298613098466+/-0.26838000203170054,\n",
" 39.56350313171474+/-0.22090015944414187,\n",
" 37.279537615885666+/-0.18659228964664437,\n",
" 36.31023735604064+/-0.13375898708306416,\n",
" 36.347290686434704+/-0.14289469659641718,\n",
" 36.76840362595908+/-0.16492361644268516,\n",
" 37.44207161526755+/-0.22067593697796228,\n",
" 38.11301392112265+/-0.18885658898111282,\n",
" 37.54573976282329+/-0.2392021652334097,\n",
" 38.80095819247798+/-0.1973453512180256,\n",
" 38.75091454236419+/-0.22299092756298497,\n",
" 38.23586245668509+/-0.19839569982989957,\n",
" 38.59025740687004+/-0.203805850795976,\n",
" 37.69777348728528+/-0.16975758792789278,\n",
" 37.376686160708644+/-0.14778770143297712,\n",
" 38.10757358989838+/-0.17368272620675895,\n",
" 36.25543463038896+/-0.14868529398512134,\n",
" 35.5699564608499+/-0.12340107033315005,\n",
" 36.227112825389916+/-0.13211945310424864,\n",
" 35.26611106182409+/-0.11213027360168085,\n",
" 35.11938614341695+/-0.10620769570342516,\n",
" 36.47772563987127+/-0.1092937725914777,\n",
" 34.83372993033136+/-0.10813064723685459,\n",
" 35.476640872780216+/-0.09963359697042247,\n",
" 35.24007402601677+/-0.09848325792813946,\n",
" 35.28639737858649+/-0.10890495392557194,\n",
" 34.21958544267885+/-0.1034479443584277,\n",
" 35.20842335749506+/-0.09891672543489384], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>height</span></div><div class='xr-var-dims'>(sin_mod_freq)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>14.88+/-0.04 ... 13.34+/-0.04</div><input id='attrs-6b324caf-a714-4940-a708-b92cff6cd27b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6b324caf-a714-4940-a708-b92cff6cd27b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0e1736f0-0664-4889-b7c1-38b92c922538' class='xr-var-data-in' type='checkbox'><label for='data-0e1736f0-0664-4889-b7c1-38b92c922538' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([14.881846478060568+/-0.041014704762308826,\n",
" 15.658742950611938+/-0.042085694249360636,\n",
" 15.108505608926777+/-0.04026369173013211,\n",
" 16.20499462577937+/-0.04080119447282727,\n",
" 14.076843644603082+/-0.039018536369990066,\n",
" 13.744584142449428+/-0.03809403255423364,\n",
" 11.992666166551302+/-0.03727596482711554,\n",
" 8.992907016926464+/-0.03616164998427754,\n",
" 4.399637159573817+/-0.030993112478954518,\n",
" 4.848728463464351+/-0.03304011995039604,\n",
" 5.6905347073889+/-0.03177254087973001,\n",
" 6.977776873662123+/-0.03492551695714294,\n",
" 9.460606325912064+/-0.03485045828423297,\n",
" 9.147109574214229+/-0.03596078758676632,\n",
" 7.770025814451326+/-0.03484960630107405,\n",
" 5.629915615179705+/-0.033178524466074305,\n",
" 6.886423021088101+/-0.03412300033140615,\n",
" 5.308030944838632+/-0.033816697887333255,\n",
" 6.411760063346376+/-0.03261095773984154,\n",
" 5.639709495924107+/-0.03245369643956646,\n",
" 6.4029687784061835+/-0.03322292587191607,\n",
" 6.1402143523385275+/-0.032426478891914495,\n",
" 7.468782629050527+/-0.033630066224154355,\n",
" 8.608383720549918+/-0.03403604052924044,\n",
" 7.379858052582905+/-0.03363284835404896,\n",
" 8.489113238037195+/-0.03481384338756646,\n",
" 10.355439436142177+/-0.03592530946183675,\n",
" 9.82990046573795+/-0.035848168513840845,\n",
" 11.653079988430191+/-0.037048723369731924,\n",
" 12.259686948733842+/-0.037075284989632376,\n",
" 11.823177366506883+/-0.03542400772571197,\n",
" 12.22013052536784+/-0.03793383964644581,\n",
" 13.327671000983392+/-0.037429404726160076,\n",
" 13.208894130472325+/-0.03691256379755125,\n",
" 12.134680462715613+/-0.037451088980787674,\n",
" 12.669886259561324+/-0.03830175577793736,\n",
" 13.344710576348463+/-0.037490560189562455], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-682be448-12a2-43b9-a797-b8ad652f47ba' class='xr-section-summary-in' type='checkbox' ><label for='section-682be448-12a2-43b9-a797-b8ad652f47ba' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>sin_mod_freq</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d7996c9e-128b-4f85-8d09-a8e68dbedc5f' class='xr-index-data-in' type='checkbox'/><label for='index-d7996c9e-128b-4f85-8d09-a8e68dbedc5f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([ 65.0, 66.0, 67.0, 68.0, 69.0, 70.0, 71.0, 72.0, 73.0,\n",
" 74.0, 75.0, 76.0, 77.0, 78.0, 79.0, 80.0, 81.0, 82.0,\n",
" 83.0, 84.0, 85.0, 86.0, 87.0, 88.0, 89.0, 90.0, 91.0,\n",
" 92.0, 93.0, 94.0, 95.0, 96.0, 97.0, 98.0, 99.0, 100.0,\n",
" 101.0],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;sin_mod_freq&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-bb48d7ea-1be3-45d2-a640-d1bd666f23a0' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-bb48d7ea-1be3-45d2-a640-d1bd666f23a0' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (sin_mod_freq: 37)\n",
"Coordinates:\n",
" * sin_mod_freq (sin_mod_freq) float64 65.0 66.0 67.0 ... 99.0 100.0 101.0\n",
"Data variables:\n",
" amplitude (sin_mod_freq) object 1808+/-5 1824+/-5 ... 1653+/-5 1838+/-5\n",
" centerx (sin_mod_freq) object 73.10+/-0.04 ... 73.94+/-0.04\n",
" centery (sin_mod_freq) object 102.02+/-0.04 ... 102.56+/-0.04\n",
" sigmax (sin_mod_freq) object 13.57+/-0.04 ... 14.47+/-0.04\n",
" sigmay (sin_mod_freq) object 14.06+/-0.04 ... 14.95+/-0.04\n",
" fwhmx (sin_mod_freq) object 31.95+/-0.09 ... 34.08+/-0.10\n",
" fwhmy (sin_mod_freq) object 33.12+/-0.09 ... 35.21+/-0.10\n",
" height (sin_mod_freq) object 14.88+/-0.04 ... 13.34+/-0.04"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"fitAnalyser.get_fit_full_result(fitResult)"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## Get the Ncount"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"### Calculate the mean and standard deviation"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"Ncount = imageAnalyser.get_Ncount(dataSet_cropOD)\n",
"\n",
"Ncount.load()\n",
"Ncount_mean = calculate_mean(Ncount)\n",
"Ncount_std = calculate_std(Ncount)\n",
"Ncount_mean.plot.errorbar(yerr=Ncount_std)\n",
"plt.show()"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"### Do a 1D fit"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<table><tr><th> name </th><th> value </th><th> initial value </th><th> min </th><th> max </th><th> vary </th></tr><tr><td> amplitude </td><td> 1.00000000 </td><td> None </td><td> -inf </td><td> inf </td><td> True </td></tr><tr><td> center </td><td> 0.00000000 </td><td> None </td><td> -inf </td><td> inf </td><td> True </td></tr><tr><td> sigma </td><td> 1.00000000 </td><td> None </td><td> -inf </td><td> inf </td><td> True </td></tr></table>"
],
"text/plain": [
"Parameters([('amplitude', <Parameter 'amplitude', value=1.0, bounds=[-inf:inf]>), ('center', <Parameter 'center', value=0.0, bounds=[-inf:inf]>), ('sigma', <Parameter 'sigma', value=1.0, bounds=[-inf:inf]>)])"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"def gaussian(x, amplitude=1.0, center=0.0, sigma=1.0):\n",
" \"\"\"Return a 1-dimensional Gaussian function.\n",
"\n",
" gaussian(x, amplitude, center, sigma) =\n",
" (amplitude/(s2pi*sigma)) * exp(-(1.0*x-center)**2 / (2*sigma**2))\n",
"\n",
" \"\"\"\n",
" return ((amplitude/(max(1e-10, np.sqrt(2*np.pi)*sigma)))\n",
" * np.exp(-(1.0*x-center)**2 / max(1e-10, (2*sigma**2))))\n",
"\n",
"fitModel = NewFitModel(gaussian)\n",
"\n",
"fitModel.make_params()"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fitAnalyser = FitAnalyser(fitModel, fitDim=1)\n",
"\n",
"params = fitAnalyser.guess(Ncount_mean, x=\"sin_mod_freq\", dask=\"parallelized\")\n",
"fitResult = fitAnalyser.fit(Ncount_mean, params, x=\"sin_mod_freq\").load()\n",
"\n",
"plot_x = np.linspace(Ncount_mean[\"sin_mod_freq\"].min(), Ncount_mean[\"sin_mod_freq\"].max(), 100)\n",
"\n",
"fitCurve = fitAnalyser.eval(fitResult, x=plot_x, dask=\"parallelized\").load()\n",
"\n",
"fig = plt.figure()\n",
"ax = fig.gca()\n",
"\n",
"Ncount_mean.plot.errorbar(ax=ax, yerr=Ncount_std)\n",
"fitCurve.plot.errorbar(ax=ax, fmt='--g')\n",
"\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"ename": "ValueError",
"evalue": "Line plots are for 1- or 2-dimensional DataArrays. Passed DataArray has 3 dimensions",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mValueError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32mf:\\Jianshun\\analyseScript\\Example.ipynb Cell 27\u001b[0m in \u001b[0;36m6\n\u001b[0;32m <a href='vscode-notebook-cell:/f%3A/Jianshun/analyseScript/Example.ipynb#X34sZmlsZQ%3D%3D?line=3'>4</a>\u001b[0m fig \u001b[39m=\u001b[39m plt\u001b[39m.\u001b[39mfigure()\n\u001b[0;32m <a href='vscode-notebook-cell:/f%3A/Jianshun/analyseScript/Example.ipynb#X34sZmlsZQ%3D%3D?line=4'>5</a>\u001b[0m ax \u001b[39m=\u001b[39m fig\u001b[39m.\u001b[39mgca()\n\u001b[1;32m----> <a href='vscode-notebook-cell:/f%3A/Jianshun/analyseScript/Example.ipynb#X34sZmlsZQ%3D%3D?line=5'>6</a>\u001b[0m plot_dataSe\u001b[39m.\u001b[39;49msel(plot\u001b[39m=\u001b[39;49m[\u001b[39m0\u001b[39;49m, \u001b[39m1\u001b[39;49m])\u001b[39m.\u001b[39;49mplot\u001b[39m.\u001b[39;49merrorbar(ax\u001b[39m=\u001b[39;49max, hue\u001b[39m=\u001b[39;49m\u001b[39m'\u001b[39;49m\u001b[39mplot\u001b[39;49m\u001b[39m'\u001b[39;49m, x\u001b[39m=\u001b[39;49m\u001b[39m'\u001b[39;49m\u001b[39mfinal_amp\u001b[39;49m\u001b[39m'\u001b[39;49m, fmt\u001b[39m=\u001b[39;49m[\u001b[39m'\u001b[39;49m\u001b[39mob\u001b[39;49m\u001b[39m'\u001b[39;49m, \u001b[39m'\u001b[39;49m\u001b[39m-g\u001b[39;49m\u001b[39m'\u001b[39;49m])\n\u001b[0;32m <a href='vscode-notebook-cell:/f%3A/Jianshun/analyseScript/Example.ipynb#X34sZmlsZQ%3D%3D?line=6'>7</a>\u001b[0m plt\u001b[39m.\u001b[39mshow()\n",
"File \u001b[1;32mf:\\Jianshun\\analyseScript\\ToolFunction\\HomeMadeXarrayFunction.py:274\u001b[0m, in \u001b[0;36mdataarray_plot_errorbar\u001b[1;34m(DataArrayPlotAccessor, *args, **kwargs)\u001b[0m\n\u001b[0;32m 273\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mdataarray_plot_errorbar\u001b[39m(DataArrayPlotAccessor, \u001b[39m*\u001b[39margs, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs) \u001b[39m-\u001b[39m\u001b[39m>\u001b[39m \u001b[39mlist\u001b[39m[Line3D] \u001b[39m|\u001b[39m FacetGrid[DataArray]:\n\u001b[1;32m--> 274\u001b[0m \u001b[39mreturn\u001b[39;00m errorbar(DataArrayPlotAccessor\u001b[39m.\u001b[39m_da, \u001b[39m*\u001b[39margs, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs)\n",
"File \u001b[1;32mf:\\Jianshun\\analyseScript\\ToolFunction\\HomeMadeXarrayFunction.py:185\u001b[0m, in \u001b[0;36merrorbar\u001b[1;34m(darray, xerr, yerr, row, col, figsize, aspect, size, ax, hue, x, y, xincrease, yincrease, xscale, yscale, xticks, yticks, xlim, ylim, add_legend, _labels, *args, **kwargs)\u001b[0m\n\u001b[0;32m 183\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mTypeError\u001b[39;00m(\u001b[39m\"\u001b[39m\u001b[39mNo numeric data to plot.\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[0;32m 184\u001b[0m \u001b[39mif\u001b[39;00m ndims \u001b[39m>\u001b[39m \u001b[39m2\u001b[39m:\n\u001b[1;32m--> 185\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mValueError\u001b[39;00m(\n\u001b[0;32m 186\u001b[0m \u001b[39m\"\u001b[39m\u001b[39mLine plots are for 1- or 2-dimensional DataArrays. \u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m 187\u001b[0m \u001b[39m\"\u001b[39m\u001b[39mPassed DataArray has \u001b[39m\u001b[39m{ndims}\u001b[39;00m\u001b[39m \u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m 188\u001b[0m \u001b[39m\"\u001b[39m\u001b[39mdimensions\u001b[39m\u001b[39m\"\u001b[39m\u001b[39m.\u001b[39mformat(ndims\u001b[39m=\u001b[39mndims)\n\u001b[0;32m 189\u001b[0m )\n\u001b[0;32m 191\u001b[0m \u001b[39m# The allargs dict passed to _easy_facetgrid above contains args\u001b[39;00m\n\u001b[0;32m 192\u001b[0m \u001b[39mif\u001b[39;00m args \u001b[39m==\u001b[39m ():\n",
"\u001b[1;31mValueError\u001b[0m: Line plots are for 1- or 2-dimensional DataArrays. Passed DataArray has 3 dimensions"
]
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
Implentment new function
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"source": [
"fitCurve = fitCurve.rename(dict(x='final_amp'))\n",
"plot_dataSe = xr.combine_nested([Ncount_mean, fitCurve], ['plot'])\n",
"\n",
"fig = plt.figure()\n",
"ax = fig.gca()\n",
"plot_dataSe.sel(plot=[0, 1]).plot.errorbar(ax=ax, hue='plot', x='final_amp', fmt=['ob', '-g'])\n",
"plt.show()\n"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"# Select data and remove bad shot"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
The first working version
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"source": [
regular backup
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"plot_dataSe.where( (Ncount_mean[scanAxis[0]]<2e-4) & (Ncount_mean[scanAxis[0]]>1e-4) )"
The first working version
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]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
fix bugs (can not use xarray.sutck with dask)
2023-05-15 17:05:16 +02:00
"display_name": "Python 3",
The first working version
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"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",
regular backup
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"version": "3.9.13"
The first working version
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},
fix bugs (can not use xarray.sutck with dask)
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"orig_nbformat": 4
The first working version
2023-05-07 23:41:31 +02:00
},
"nbformat": 4,
"nbformat_minor": 2
}
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