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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# How to fit data"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"In lots of times, we need to fit our data with different lineshapes. We implenment the fitting function using lmfit package. Here is a link to the official document of lmfit\n",
"\n",
"https://lmfit.github.io/lmfit-py/\n",
"\n",
"Fortunately, one don't need to read and understand everything to do a fit, but just a few concepts and tools\n",
"\n",
"- Models. An object of Model() class in lmfit package is a slover for certain cureve. The lmfit package and we alread defined lots of models, and it is also possible and easy to define a new model for a new curve.\n",
"- Parameters. The fit is usually sensitive to the initial values and boundary conditions. Parameters() is a class, which hold all these information for a fit.\n",
"- Fit Reasult. In the lmfit package, the reulst of fit is also a class, but we implenment some functions to translate it into numbers.\n",
"\n",
"Let's start again with some examples."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Load some example data"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Import supporting packages"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"# Set the system path for importing packages\n",
"# This is just because I put all example scripts in another folder\n",
"# You DO NOT need to do this \n",
"# -------------- You do NOT need following part --------------\n",
"import sys\n",
"import os\n",
"sys.path.insert(0, os.path.abspath('..'))\n",
"# -------------- You do NOT need above part --------------\n",
"\n",
"import copy\n",
"import glob\n",
"from datetime import datetime\n",
"\n",
"# The package for data structure\n",
"import xarray as xr\n",
"import pandas as pd\n",
"import numpy as np\n",
"\n",
"# The packages for working with uncertainties\n",
"from uncertainties import ufloat\n",
"from uncertainties import unumpy as unp\n",
"from uncertainties import umath\n",
"\n",
"# The package for plotting\n",
"import matplotlib.pyplot as plt\n",
"plt.rcParams['font.size'] = 18 # Set the global font size\n",
"\n",
"# -------------- The modules written by us --------------\n",
"\n",
"# The packages for read data\n",
"from DataContainer.ReadData import read_hdf5_file, read_hdf5_global, read_hdf5_run_time, read_csv_file\n",
"\n",
"# The packages for data analysis\n",
"from Analyser.ImagingAnalyser import ImageAnalyser\n",
"from Analyser.FitAnalyser import FitAnalyser\n",
"from Analyser.FitAnalyser import ThomasFermi2dModel, DensityProfileBEC2dModel, Polylog22dModel\n",
"from Analyser.FFTAnalyser import fft, ifft, fft_nutou\n",
"from ToolFunction.ToolFunction import *\n",
"\n",
"# Add errorbar plot to xarray package\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"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Start a client for parallel computing"
]
},
{
"cell_type": "code",
"execution_count": 2,
"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",
" <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Client-4613caa9-20c7-11ee-8414-80e82ce2fa8e</p>\n",
" <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",
" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:8787/status\" target=\"_blank\">http://127.0.0.1:8787/status</a>\n",
" </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",
" <p style=\"color: #9D9D9D; margin-bottom: 0px;\">0611b212</p>\n",
" <table style=\"width: 100%; text-align: left;\">\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Dashboard:</strong> <a href=\"http://127.0.0.1:8787/status\" target=\"_blank\">http://127.0.0.1:8787/status</a>\n",
" </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",
" <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Scheduler-d40156cf-ceb8-45b9-8b27-2ddcdca85973</p>\n",
" <table style=\"width: 100%; text-align: left;\">\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Comm:</strong> tcp://127.0.0.1:65093\n",
" </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>Dashboard:</strong> <a href=\"http://127.0.0.1:8787/status\" target=\"_blank\">http://127.0.0.1:8787/status</a>\n",
" </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",
" <strong>Comm: </strong> tcp://127.0.0.1:65133\n",
" </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",
" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:65135/status\" target=\"_blank\">http://127.0.0.1:65135/status</a>\n",
" </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",
" <strong>Nanny: </strong> tcp://127.0.0.1:65096\n",
" </td>\n",
" <td style=\"text-align: left;\"></td>\n",
" </tr>\n",
" <tr>\n",
" <td colspan=\"2\" style=\"text-align: left;\">\n",
" <strong>Local directory: </strong> C:\\Users\\data\\AppData\\Local\\Temp\\dask-worker-space\\worker-q9qzw1g5\n",
" </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",
" <strong>Comm: </strong> tcp://127.0.0.1:65130\n",
" </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",
" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:65131/status\" target=\"_blank\">http://127.0.0.1:65131/status</a>\n",
" </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",
" <strong>Nanny: </strong> tcp://127.0.0.1:65097\n",
" </td>\n",
" <td style=\"text-align: left;\"></td>\n",
" </tr>\n",
" <tr>\n",
" <td colspan=\"2\" style=\"text-align: left;\">\n",
" <strong>Local directory: </strong> C:\\Users\\data\\AppData\\Local\\Temp\\dask-worker-space\\worker-yf6omtw_\n",
" </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",
" <strong>Comm: </strong> tcp://127.0.0.1:65122\n",
" </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",
" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:65125/status\" target=\"_blank\">http://127.0.0.1:65125/status</a>\n",
" </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",
" <strong>Nanny: </strong> tcp://127.0.0.1:65098\n",
" </td>\n",
" <td style=\"text-align: left;\"></td>\n",
" </tr>\n",
" <tr>\n",
" <td colspan=\"2\" style=\"text-align: left;\">\n",
" <strong>Local directory: </strong> C:\\Users\\data\\AppData\\Local\\Temp\\dask-worker-space\\worker-5nbwryjk\n",
" </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",
" <strong>Comm: </strong> tcp://127.0.0.1:65127\n",
" </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",
" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:65128/status\" target=\"_blank\">http://127.0.0.1:65128/status</a>\n",
" </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",
" <strong>Nanny: </strong> tcp://127.0.0.1:65099\n",
" </td>\n",
" <td style=\"text-align: left;\"></td>\n",
" </tr>\n",
" <tr>\n",
" <td colspan=\"2\" style=\"text-align: left;\">\n",
" <strong>Local directory: </strong> C:\\Users\\data\\AppData\\Local\\Temp\\dask-worker-space\\worker-hgtibcnt\n",
" </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",
" <strong>Comm: </strong> tcp://127.0.0.1:65111\n",
" </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",
" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:65123/status\" target=\"_blank\">http://127.0.0.1:65123/status</a>\n",
" </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",
" <strong>Nanny: </strong> tcp://127.0.0.1:65100\n",
" </td>\n",
" <td style=\"text-align: left;\"></td>\n",
" </tr>\n",
" <tr>\n",
" <td colspan=\"2\" style=\"text-align: left;\">\n",
" <strong>Local directory: </strong> C:\\Users\\data\\AppData\\Local\\Temp\\dask-worker-space\\worker-m3aoctgg\n",
" </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",
" <strong>Comm: </strong> tcp://127.0.0.1:65134\n",
" </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",
" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:65136/status\" target=\"_blank\">http://127.0.0.1:65136/status</a>\n",
" </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",
" <strong>Nanny: </strong> tcp://127.0.0.1:65101\n",
" </td>\n",
" <td style=\"text-align: left;\"></td>\n",
" </tr>\n",
" <tr>\n",
" <td colspan=\"2\" style=\"text-align: left;\">\n",
" <strong>Local directory: </strong> C:\\Users\\data\\AppData\\Local\\Temp\\dask-worker-space\\worker-c5mnml_p\n",
" </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": [
"<Client: 'tcp://127.0.0.1:65093' processes=6 threads=60, memory=55.88 GiB>"
]
},
"execution_count": 2,
"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"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Set the path for different cameras"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"groupList = [\n",
" \"images/MOT_3D_Camera/in_situ_absorption\",\n",
" \"images/ODT_1_Axis_Camera/in_situ_absorption\",\n",
" \"images/ODT_2_Axis_Camera/in_situ_absorption\",\n",
"]\n",
"\n",
"# give a short name to each path (or let's say each camera)\n",
"dskey = {\n",
" \"images/MOT_3D_Camera/in_situ_absorption\": \"camera_0\",\n",
" \"images/ODT_1_Axis_Camera/in_situ_absorption\": \"camera_1\",\n",
" \"images/ODT_2_Axis_Camera/in_situ_absorption\": \"camera_2\",\n",
"}"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Set global path for experiment"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"img_dir = '//DyLabNAS/Data/'\n",
"SequenceName = \"Evaporative_Cooling\" + \"/\"\n",
"folderPath = img_dir + SequenceName + '2023/04/17'# get_date()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Load shot 0058"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
"Dimensions: (runs: 5, truncation_value: 11, y: 1200, x: 1920)\n",
"Coordinates:\n",
" * runs (runs) float64 0.0 1.0 2.0 3.0 4.0\n",
" * truncation_value (truncation_value) float64 0.8 0.83 0.85 ... 0.97 0.99 1.0\n",
"Dimensions without coordinates: y, x\n",
"Data variables:\n",
" atoms (runs, truncation_value, y, x) uint16 dask.array&lt;chunksize=(5, 11, 1200, 1920), meta=np.ndarray&gt;\n",
" background (runs, truncation_value, y, x) uint16 dask.array&lt;chunksize=(5, 11, 1200, 1920), meta=np.ndarray&gt;\n",
" dark (runs, truncation_value, y, x) uint16 dask.array&lt;chunksize=(5, 11, 1200, 1920), meta=np.ndarray&gt;\n",
" shotNum (runs, truncation_value) &lt;U2 dask.array&lt;chunksize=(5, 11), meta=np.ndarray&gt;\n",
"Attributes: (12/100)\n",
" TOF_free: 0.02\n",
" abs_img_freq: 110.866\n",
" absorption_imaging_flag: True\n",
" backup_data: True\n",
" blink_off_time: nan\n",
" blink_on_time: nan\n",
" ... ...\n",
" z_offset: 0.195\n",
" z_offset_img: 0.195\n",
" truncation_value: [0.8 0.83 0.85 0.87 0.89 0.91 0.93 0....\n",
" runs: [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 1...\n",
" scanAxis: [&#x27;runs&#x27; &#x27;truncation_value&#x27;]\n",
" scanAxisLength: [55. 55.]</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-ec3b910b-3d18-4769-bdc2-827e72b00431' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ec3b910b-3d18-4769-bdc2-827e72b00431' 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'>runs</span>: 5</li><li><span class='xr-has-index'>truncation_value</span>: 11</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-239c173f-d00a-42d3-99e4-060709823c45' class='xr-section-summary-in' type='checkbox' checked><label for='section-239c173f-d00a-42d3-99e4-060709823c45' class='xr-section-summary' >Coordinates: <span>(2)</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'>runs</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.0 2.0 3.0 4.0</div><input id='attrs-64afd3ff-7f3e-44e0-8602-f7e2b00b7027' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-64afd3ff-7f3e-44e0-8602-f7e2b00b7027' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fb645573-4da5-439b-9c4d-b2d2327c525d' class='xr-var-data-in' type='checkbox'><label for='data-fb645573-4da5-439b-9c4d-b2d2327c525d' 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., 1., 2., 3., 4.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>truncation_value</span></div><div class='xr-var-dims'>(truncation_value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.8 0.83 0.85 ... 0.97 0.99 1.0</div><input id='attrs-3df46cb1-d92c-4f4f-bac6-cba0f15cce48' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3df46cb1-d92c-4f4f-bac6-cba0f15cce48' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2fbfc786-31bf-4345-b3e3-9e3aa3d3278b' class='xr-var-data-in' type='checkbox'><label for='data-2fbfc786-31bf-4345-b3e3-9e3aa3d3278b' 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([0.8 , 0.83, 0.85, 0.87, 0.89, 0.91, 0.93, 0.95, 0.97, 0.99, 1. ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9afbc3f3-bcfc-4c3b-a80e-937ef53cc96d' class='xr-section-summary-in' type='checkbox' checked><label for='section-9afbc3f3-bcfc-4c3b-a80e-937ef53cc96d' class='xr-section-summary' >Data variables: <span>(4)</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'>(runs, truncation_value, y, x)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(5, 11, 1200, 1920), meta=np.ndarray&gt;</div><input id='attrs-d7c86493-d59e-4a1d-9fa6-c474321decae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d7c86493-d59e-4a1d-9fa6-c474321decae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-324ff4f1-8047-4f58-aa26-6fca41d77010' class='xr-var-data-in' type='checkbox'><label for='data-324ff4f1-8047-
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"</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-c8b69ed0-eb12-4488-8098-399d805f04d3' class='xr-section-summary-in' type='checkbox' ><label for='section-c8b69ed0-eb12-4488-8098-399d805f04d3' class='xr-section-summary' >Indexes: <span>(2)</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>runs</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e9bb37c1-4cb1-42db-81d6-a8b9dd8c294f' class='xr-index-data-in' type='checkbox'/><label for='index-e9bb37c1-4cb1-42db-81d6-a8b9dd8c294f' 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([0.0, 1.0, 2.0, 3.0, 4.0], dtype=&#x27;float64&#x27;, name=&#x27;runs&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>truncation_value</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9aa607a4-9dd5-4d66-9612-376a3237271b' class='xr-index-data-in' type='checkbox'/><label for='index-9aa607a4-9dd5-4d66-9612-376a3237271b' 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([0.8, 0.83, 0.85, 0.87, 0.89, 0.91, 0.93, 0.95, 0.97, 0.99, 1.0], dtype=&#x27;float64&#x27;, name=&#x27;truncation_value&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5b2a6f36-619e-4ce3-9322-273f97d88c28' class='xr-section-summary-in' type='checkbox' ><label for='section-5b2a6f36-619e-4ce3-9322-273f97d88c28' class='xr-section-summary' >Attributes: <span>(100)</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>0.02</dd><dt><span>abs_img_freq :</span></dt><dd>110.866</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>nan</dd><dt><span>blink_on_time :</span></dt><dd>nan</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>0.002</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</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>0.195</dd><dt><span>compZ_final_current :</span></dt><dd>0.287</dd><dt><span>compZ_initial_current :</span></dt><dd>0</dd><dt><span>default_camera :</span></dt><dd>0</dd><dt><span>evap_1_final_pow_1 :</span></dt><dd>4.8</dd><dt><span>evap_1_final_pow_2 :</span></dt><dd>2.2</dd><dt><span>evap_1_final_pow_3 :</span></dt><dd>1.2</dd><dt><span>evap_1_final_pow_4 :</span></dt><dd>0.526</dd><dt><span>evap_1_ramp_duration_1 :</span></dt><dd>0.15</dd><dt><span>evap_1_ramp_duration_2 :</span></dt><dd>0.3</dd><dt><span>evap_1_ramp_duration_3 :</span></dt><dd>0.2</dd><dt><span>evap_1_ramp_duration_4 :</span></dt><dd>0.5</dd><dt><span>evap_1_start_pow_1 :</span></dt><dd>7</dd><dt><span>evap_1_start_pow_2 :</span></dt><dd>4.8</dd><dt><span>evap_1_start_pow_3 :</span></dt><dd>2.2</dd><dt><span>evap_1_start_pow_4 :</span></dt><dd>1.2</dd><dt><span>evap_2_final_pow_1 :</span></dt><dd>0.35</dd><dt><span>evap_2_ramp_duration_1 :</span></dt><dd>0.5</dd><dt><span>evap_2_start_pow_1 :</span></dt><dd>0.526</dd><dt><span>evap_3_arm_1_final_pow :</span></dt><dd>0.037</dd><dt><span>evap_3_arm_1_start_pow :</span></dt><dd>0.35</dd><dt><span>evap_3_ar
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"<xarray.Dataset>\n",
"Dimensions: (runs: 5, truncation_value: 11, y: 1200, x: 1920)\n",
"Coordinates:\n",
" * runs (runs) float64 0.0 1.0 2.0 3.0 4.0\n",
" * truncation_value (truncation_value) float64 0.8 0.83 0.85 ... 0.97 0.99 1.0\n",
"Dimensions without coordinates: y, x\n",
"Data variables:\n",
" atoms (runs, truncation_value, y, x) uint16 dask.array<chunksize=(5, 11, 1200, 1920), meta=np.ndarray>\n",
" background (runs, truncation_value, y, x) uint16 dask.array<chunksize=(5, 11, 1200, 1920), meta=np.ndarray>\n",
" dark (runs, truncation_value, y, x) uint16 dask.array<chunksize=(5, 11, 1200, 1920), meta=np.ndarray>\n",
" shotNum (runs, truncation_value) <U2 dask.array<chunksize=(5, 11), meta=np.ndarray>\n",
"Attributes: (12/100)\n",
" TOF_free: 0.02\n",
" abs_img_freq: 110.866\n",
" absorption_imaging_flag: True\n",
" backup_data: True\n",
" blink_off_time: nan\n",
" blink_on_time: nan\n",
" ... ...\n",
" z_offset: 0.195\n",
" z_offset_img: 0.195\n",
" truncation_value: [0.8 0.83 0.85 0.87 0.89 0.91 0.93 0....\n",
" runs: [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 1...\n",
" scanAxis: ['runs' 'truncation_value']\n",
" scanAxisLength: [55. 55.]"
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},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"shotNum = \"0058\"\n",
"filePath = folderPath + \"/\" + shotNum + \"/*.h5\"\n",
"\n",
"dataSetDict = {\n",
" dskey[groupList[i]]: read_hdf5_file(filePath, groupList[i])\n",
" for i in [0] # range(len(groupList)) # uncommont to load data for all three cameras\n",
"}\n",
"dataSet = dataSetDict[\"camera_0\"]\n",
"\n",
"dataSet = swap_xy(dataSet)\n",
"\n",
"scanAxis = get_scanAxis(dataSet)\n",
"\n",
"dataSet = auto_rechunk(dataSet)\n",
"\n",
"dataSet"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Calculate the absorption imaging"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
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" -0.02529576, 0.00751452],\n",
" [ 0.12183205, 0.03190597, 0.01355683, ..., -0.02573907,\n",
" -0.05682966, -0.00446167],\n",
" [ 0.03475904, 0.0325796 , 0.07721636, ..., 0.02662891,\n",
" -0.05738408, 0.00751452]],\n",
"\n",
" [[ 0.05613155, -0.10849043, 0.05082337, ..., 0.09902547,\n",
" 0.01710835, 0.03692657],\n",
" [-0.08110418, -0.09280022, 0.01710835, ..., -0.04168176,\n",
" -0.15458948, 0.00483825],\n",
" [-0.07212279, -0.00743184, -0.05653069, ..., -0.18356235,\n",
" -0.01621516, -0.07006305],\n",
"...\n",
" [ 0.15678264, 0.09630046, 0.1255301 , ..., -0.00355249,\n",
" 0.01855798, -0.00499196],\n",
" [ 0.00774706, -0.07926432, 0.0260962 , ..., -0.01447608,\n",
" -0.03527032, 0.04126975],\n",
" [-0.01094507, -0.16745703, -0.0624572 , ..., 0.07159853,\n",
" 0.01769739, -0.06124581]],\n",
"\n",
" [[ 0.05950001, 0.0086876 , -0.02921711, ..., 0.04073558,\n",
" -0.00421581, -0.04723319],\n",
" [-0.0555091 , -0.11475768, -0.05360856, ..., -0.01551536,\n",
" 0.03087551, -0.00421581],\n",
" [ 0.03352452, -0.01663833, 0.01931469, ..., 0.01752418,\n",
" -0.02504989, 0.04815218],\n",
" ...,\n",
" [ 0.03087551, 0.05294261, -0.13050953, ..., -0.0277463 ,\n",
" -0.05020092, -0.04014782],\n",
" [ 0.03352452, -0.04422114, -0.06030527, ..., -0.06009626,\n",
" -0.03467501, 0.09642772],\n",
" [-0.04125708, 0.01447633, 0.07129175, ..., 0.06247557,\n",
" -0.05947848, -0.01538911]]]])\n",
"Coordinates:\n",
" * runs (runs) float64 0.0 1.0 2.0 3.0 4.0\n",
" * truncation_value (truncation_value) float64 0.8 0.83 0.85 ... 0.97 0.99 1.0\n",
"Dimensions without coordinates: y, x\n",
"Attributes:\n",
" IMAGE_SUBCLASS: IMAGE_GRAYSCALE\n",
" IMAGE_VERSION: 1.2\n",
" IMAGE_WHITE_IS_ZERO: 0\n",
" x_start: 810\n",
" x_end: 1110\n",
" y_end: 1025\n",
" y_start: 725\n",
" x_center: 960\n",
" y_center: 875\n",
" x_span: 300\n",
" y_span: 300</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'OD'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>runs</span>: 5</li><li><span class='xr-has-index'>truncation_value</span>: 11</li><li><span>y</span>: 300</li><li><span>x</span>: 300</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-769a2585-d324-4a83-b0ba-1f03e504aa21' class='xr-array-in' type='checkbox' checked><label for='section-769a2585-d324-4a83-b0ba-1f03e504aa21' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.1009 0.06965 0.05767 0.08365 ... -0.05714 0.06248 -0.05948 -0.01539</span></div><div class='xr-array-data'><pre>array([[[[ 0.10089884, 0.0696463 , 0.05767011, ..., 0.01963588,\n",
" -0.0650863 , -0.00446167],\n",
" [ 0.10342729, 0.04260584, 0.02118076, ..., 0.11194868,\n",
" 0.00723437, -0.0801735 ],\n",
" [ 0.00780842, 0.00827735, -0.02827232, ..., -0.02693453,\n",
" -0.00446167, 0.0622297 ],\n",
" ...,\n",
" [-0.1117072 , -0.0575715 , -0.03836323, ..., -0.05152918,\n",
" -0.02529576, 0.00751452],\n",
" [ 0.12183205, 0.03190597, 0.01355683, ..., -0.02573907,\n",
" -0.05682966, -0.00446167],\n",
" [ 0.03475904, 0.0325796 , 0.07721636, ..., 0.02662891,\n",
" -0.05738408, 0.00751452]],\n",
"\n",
" [[ 0.05613155, -0.10849043, 0.05082337, ..., 0.09902547,\n",
" 0.01710835, 0.03692657],\n",
" [-0.08110418, -0.09280022, 0.01710835, ..., -0.04168176,\n",
" -0.15458948, 0.00483825],\n",
" [-0.07212279, -0.00743184, -0.05653069, ..., -0.18356235,\n",
" -0.01621516, -0.07006305],\n",
"...\n",
" [ 0.15678264, 0.09630046, 0.1255301 , ..., -0.00355249,\n",
" 0.01855798, -0.00499196],\n",
" [ 0.00774706, -0.07926432, 0.0260962 , ..., -0.01447608,\n",
" -0.03527032, 0.04126975],\n",
" [-0.01094507, -0.16745703, -0.0624572 , ..., 0.07159853,\n",
" 0.01769739, -0.06124581]],\n",
"\n",
" [[ 0.05950001, 0.0086876 , -0.02921711, ..., 0.04073558,\n",
" -0.00421581, -0.04723319],\n",
" [-0.0555091 , -0.11475768, -0.05360856, ..., -0.01551536,\n",
" 0.03087551, -0.00421581],\n",
" [ 0.03352452, -0.01663833, 0.01931469, ..., 0.01752418,\n",
" -0.02504989, 0.04815218],\n",
" ...,\n",
" [ 0.03087551, 0.05294261, -0.13050953, ..., -0.0277463 ,\n",
" -0.05020092, -0.04014782],\n",
" [ 0.03352452, -0.04422114, -0.06030527, ..., -0.06009626,\n",
" -0.03467501, 0.09642772],\n",
" [-0.04125708, 0.01447633, 0.07129175, ..., 0.06247557,\n",
" -0.05947848, -0.01538911]]]])</pre></div></div></li><li class='xr-section-item'><input id='section-00514b98-0ee4-4240-a295-791fb1737634' class='xr-section-summary-in' type='checkbox' checked><label for='section-00514b98-0ee4-4240-a295-791fb1737634' class='xr-section-summary' >Coordinates: <span>(2)</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'>runs</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.0 2.0 3.0 4.0</div><input id='attrs-1d59f5dd-93eb-4929-a332-894155a2daa6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1d59f5dd-93eb-4929-a332-894155a2daa6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9abc84b6-c45b-4d56-b55d-5b41e13663cf' class='xr-var-data-in' type='checkbox'><label for='data-9abc84b6-c45b-4d56-b55d-5b41e13663cf' 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., 1., 2., 3., 4.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>truncation_value</span></div><div class='xr-var-dims'>(truncation_value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.8 0.83 0.85 ... 0.97 0.99 1.0</div><input id='attrs-16638bd4-b90b-46c6-bc5d-1867bf0f7774' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-16638bd4-b90b-46c6-bc5d-1867bf0f7774' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-448a77b4-362b-4007-8580-176dde198a73' class='xr-var-data-in' type='checkbox'><label for='data-448a77b4-362b-4007-8580-176dde198a73' 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([0.8 , 0.83, 0.85, 0.87, 0.89, 0.91, 0.93, 0.95, 0.97, 0.99, 1. ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ff9e9ae6-069c-4f99-b734-66f1a7d76276' class='xr-section-summary-in' type='checkbox' ><label for='section-ff9e9ae6-069c-4f99-b734-66f1a7d76276' class='xr-section-summary' >Indexes: <span>(2)</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>runs</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-baafe7cc-2943-4b22-84d0-c0999519176e' class='xr-index-data-in' type='checkbox'/><label for='index-baafe7cc-2943-4b22-84d0-c0999519176e' 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([0.0, 1.0, 2.0, 3.0, 4.0], dtype=&#x27;float64&#x27;, name=&#x27;runs&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>truncation_value</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e695e9d6-3555-4340-b899-24f2e3f56859' class='xr-index-data-in' type='checkbox'/><label for='index-e695e9d6-3555-4340-b899-24f2e3f56859' 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([0.8, 0.83, 0.85, 0.87, 0.89, 0.91, 0.93, 0.95, 0.97, 0.99, 1.0], dtype=&#x27;float64&#x27;, name=&#x27;truncation_value&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-bdb9df9e-cf6b-42e3-8c6c-098aeb0df406' class='xr-section-summary-in' type='checkbox' ><label for='section-bdb9df9e-cf6b-42e3-8c6c-098aeb0df406' class='xr-section-
],
"text/plain": [
"<xarray.DataArray 'OD' (runs: 5, truncation_value: 11, y: 300, x: 300)>\n",
"array([[[[ 0.10089884, 0.0696463 , 0.05767011, ..., 0.01963588,\n",
" -0.0650863 , -0.00446167],\n",
" [ 0.10342729, 0.04260584, 0.02118076, ..., 0.11194868,\n",
" 0.00723437, -0.0801735 ],\n",
" [ 0.00780842, 0.00827735, -0.02827232, ..., -0.02693453,\n",
" -0.00446167, 0.0622297 ],\n",
" ...,\n",
" [-0.1117072 , -0.0575715 , -0.03836323, ..., -0.05152918,\n",
" -0.02529576, 0.00751452],\n",
" [ 0.12183205, 0.03190597, 0.01355683, ..., -0.02573907,\n",
" -0.05682966, -0.00446167],\n",
" [ 0.03475904, 0.0325796 , 0.07721636, ..., 0.02662891,\n",
" -0.05738408, 0.00751452]],\n",
"\n",
" [[ 0.05613155, -0.10849043, 0.05082337, ..., 0.09902547,\n",
" 0.01710835, 0.03692657],\n",
" [-0.08110418, -0.09280022, 0.01710835, ..., -0.04168176,\n",
" -0.15458948, 0.00483825],\n",
" [-0.07212279, -0.00743184, -0.05653069, ..., -0.18356235,\n",
" -0.01621516, -0.07006305],\n",
"...\n",
" [ 0.15678264, 0.09630046, 0.1255301 , ..., -0.00355249,\n",
" 0.01855798, -0.00499196],\n",
" [ 0.00774706, -0.07926432, 0.0260962 , ..., -0.01447608,\n",
" -0.03527032, 0.04126975],\n",
" [-0.01094507, -0.16745703, -0.0624572 , ..., 0.07159853,\n",
" 0.01769739, -0.06124581]],\n",
"\n",
" [[ 0.05950001, 0.0086876 , -0.02921711, ..., 0.04073558,\n",
" -0.00421581, -0.04723319],\n",
" [-0.0555091 , -0.11475768, -0.05360856, ..., -0.01551536,\n",
" 0.03087551, -0.00421581],\n",
" [ 0.03352452, -0.01663833, 0.01931469, ..., 0.01752418,\n",
" -0.02504989, 0.04815218],\n",
" ...,\n",
" [ 0.03087551, 0.05294261, -0.13050953, ..., -0.0277463 ,\n",
" -0.05020092, -0.04014782],\n",
" [ 0.03352452, -0.04422114, -0.06030527, ..., -0.06009626,\n",
" -0.03467501, 0.09642772],\n",
" [-0.04125708, 0.01447633, 0.07129175, ..., 0.06247557,\n",
" -0.05947848, -0.01538911]]]])\n",
"Coordinates:\n",
" * runs (runs) float64 0.0 1.0 2.0 3.0 4.0\n",
" * truncation_value (truncation_value) float64 0.8 0.83 0.85 ... 0.97 0.99 1.0\n",
"Dimensions without coordinates: y, x\n",
"Attributes:\n",
" IMAGE_SUBCLASS: IMAGE_GRAYSCALE\n",
" IMAGE_VERSION: 1.2\n",
" IMAGE_WHITE_IS_ZERO: 0\n",
" x_start: 810\n",
" x_end: 1110\n",
" y_end: 1025\n",
" y_start: 725\n",
" x_center: 960\n",
" y_center: 875\n",
" x_span: 300\n",
" y_span: 300"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"imageAnalyser = ImageAnalyser()\n",
"\n",
"imageAnalyser.center = (960, 875)\n",
"imageAnalyser.span = (300, 300)\n",
"imageAnalyser.fraction = (0.1, 0.1)\n",
"\n",
"dataSet = imageAnalyser.get_absorption_images(dataSet)\n",
"\n",
"dataSet_cropOD = imageAnalyser.crop_image(dataSet.OD)\n",
"dataSet_cropOD = imageAnalyser.substract_offset(dataSet_cropOD).load()\n",
"dataSet_cropOD"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Plot the OD images"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
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"text/plain": [
"<Figure size 3400x1500 with 56 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# first get the scan axes\n",
"scanAxis = get_scanAxis(dataSet)\n",
"\n",
"# Name_of_varibale.plot.name_of_plot_type(col=scanAxis[0], row=scanAxis[1], **kwargs)\n",
"# The name of the plot type has the same name as it in the matplotlib package\n",
"# The **kwargs to adjust the plot also as same as the matplotlib package\n",
"dataSet_cropOD.plot.pcolormesh(col=scanAxis[0], row=scanAxis[1], cmap='jet', vmin=0, vmax=2)\n",
"\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let us first do a 2D-two-peak gaussian fit to find the center and waist of the cloud."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Creat an object of fit analyser "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The idea is to package all fitting related analysis funciton into a clasee, the 'FitAnalyser'. The advantage is that it record our last settings, i.e. the model of the fit, and thus we don't need to set it again.\n",
"\n",
"Therefore, first we need to create an object of the 'FitAnalyser' class."
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"from Analyser.FitAnalyser import TwoGaussian2dModel\n",
"\n",
"\n",
"# The fit model\n",
"# fitModel = DensityProfileBEC2dModel()\n",
"fitModel = TwoGaussian2dModel()\n",
"\n",
"fitAnalyser = FitAnalyser(fitModel, fitDim=2)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Here there is a complete list of implenmented fitting model\n",
"\n",
"```\n",
"lmfit_models = {'Constant': ConstantModel,\n",
" 'Complex Constant': ComplexConstantModel,\n",
" 'Linear': LinearModel,\n",
" 'Quadratic': QuadraticModel,\n",
" 'Polynomial': PolynomialModel,\n",
" 'Gaussian': GaussianModel,\n",
" 'Gaussian-2D': Gaussian2dModel,\n",
" 'Lorentzian': LorentzianModel,\n",
" 'Split-Lorentzian': SplitLorentzianModel,\n",
" 'Voigt': VoigtModel,\n",
" 'PseudoVoigt': PseudoVoigtModel,\n",
" 'Moffat': MoffatModel,\n",
" 'Pearson7': Pearson7Model,\n",
" 'StudentsT': StudentsTModel,\n",
" 'Breit-Wigner': BreitWignerModel,\n",
" 'Log-Normal': LognormalModel,\n",
" 'Damped Oscillator': DampedOscillatorModel,\n",
" 'Damped Harmonic Oscillator': DampedHarmonicOscillatorModel,\n",
" 'Exponential Gaussian': ExponentialGaussianModel,\n",
" 'Skewed Gaussian': SkewedGaussianModel,\n",
" 'Skewed Voigt': SkewedVoigtModel,\n",
" 'Thermal Distribution': ThermalDistributionModel,\n",
" 'Doniach': DoniachModel,\n",
" 'Power Law': PowerLawModel,\n",
" 'Exponential': ExponentialModel,\n",
" 'Step': StepModel,\n",
" 'Rectangle': RectangleModel,\n",
" 'Expression': ExpressionModel,\n",
" 'Gaussian With Offset':GaussianWithOffsetModel,\n",
" 'Lorentzian With Offset':LorentzianWithOffsetModel,\n",
" 'Expansion':ExpansionModel,\n",
" 'Damping Oscillation Model':DampingOscillationModel,\n",
" 'Two Gaussian-2D':TwoGaussian2dModel,\n",
" 'Thomas Fermi-2D': ThomasFermi2dModel,\n",
" 'Density Profile of BEC-2D': DensityProfileBEC2dModel,\n",
" 'Polylog2-2D': polylog2_2d, \n",
" }\n",
"```"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Set initial values and bondaries"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"There are two ways to set the parameters of a fit:\n",
"- Use the guession function of the model, which guess the initial values from the data\n",
"- Manually set the parameters"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Manually set the parameters "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"First we need to create an object of the parameters"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"params = fitAnalyser.fitModel.make_params()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Then we can use a function to generate a template."
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"params.add(name=\"A_amplitude\", value= 1, max=np.inf, min=-np.inf, vary=True)\n",
"params.add(name=\"A_centerx\", value= 0, max=np.inf, min=-np.inf, vary=True)\n",
"params.add(name=\"A_centery\", value= 0, max=np.inf, min=-np.inf, vary=True)\n",
"params.add(name=\"A_sigmax\", expr=\"delta + B_sigmax\")\n",
"params.add(name=\"A_sigmay\", value= 1, max=np.inf, min=-np.inf, vary=True)\n",
"params.add(name=\"B_amplitude\", value= 1, max=np.inf, min=-np.inf, vary=True)\n",
"params.add(name=\"B_centerx\", value= 0, max=np.inf, min=-np.inf, vary=True)\n",
"params.add(name=\"B_centery\", value= 0, max=np.inf, min=-np.inf, vary=True)\n",
"params.add(name=\"B_sigmax\", value= 1, max=np.inf, min=-np.inf, vary=True)\n",
"params.add(name=\"B_sigmay\", value= 1, max=np.inf, min=-np.inf, vary=True)\n",
"params.add(name=\"delta\", value= -1, max= 0, min=-np.inf, vary=True)\n"
]
}
],
"source": [
"fitAnalyser.print_params_set_template()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Use the guess function"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"# The default name of x axis and y axis are 'x' and 'y', \n",
"# if not please use the argument 'x' and 'y' to specify the names or the values.\n",
"# The 'guess_kwargs' is the additional key words sent to guess() funcition in the model\n",
"params = fitAnalyser.guess(dataSet_cropOD, guess_kwargs=dict(pureBECThreshold=0.5), dask=\"parallelized\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Here the data are too large, we only show the parameters for the first shot"
]
},
{
"cell_type": "code",
"execution_count": 12,
"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><th> expression </th></tr><tr><td> A_amplitude </td><td> 1954.62481 </td><td> None </td><td> -inf </td><td> inf </td><td> True </td><td> </td></tr><tr><td> A_centerx </td><td> 144.000000 </td><td> None </td><td> -inf </td><td> inf </td><td> True </td><td> </td></tr><tr><td> A_centery </td><td> 136.000000 </td><td> None </td><td> -inf </td><td> inf </td><td> True </td><td> </td></tr><tr><td> A_sigmax </td><td> 48.8333333 </td><td> None </td><td> -inf </td><td> inf </td><td> False </td><td> delta + B_sigmax </td></tr><tr><td> A_sigmay </td><td> 49.8333333 </td><td> None </td><td> 0.00000000 </td><td> inf </td><td> True </td><td> </td></tr><tr><td> B_amplitude </td><td> 1954.62481 </td><td> None </td><td> -inf </td><td> inf </td><td> True </td><td> </td></tr><tr><td> B_centerx </td><td> 144.000000 </td><td> None </td><td> -inf </td><td> inf </td><td> True </td><td> </td></tr><tr><td> B_centery </td><td> 136.000000 </td><td> None </td><td> -inf </td><td> inf </td><td> True </td><td> </td></tr><tr><td> B_sigmax </td><td> 49.8333333 </td><td> None </td><td> 0.00000000 </td><td> inf </td><td> True </td><td> </td></tr><tr><td> B_sigmay </td><td> 49.8333333 </td><td> None </td><td> 0.00000000 </td><td> inf </td><td> True </td><td> </td></tr><tr><td> delta </td><td> -1.00000000 </td><td> -1 </td><td> -inf </td><td> 0.00000000 </td><td> True </td><td> </td></tr></table>"
],
"text/plain": [
"Parameters([('A_amplitude', <Parameter 'A_amplitude', value=1954.6248098806716, bounds=[-inf:inf]>), ('A_centerx', <Parameter 'A_centerx', value=144, bounds=[-inf:inf]>), ('A_centery', <Parameter 'A_centery', value=136, bounds=[-inf:inf]>), ('A_sigmax', <Parameter 'A_sigmax', value=48.833333333333336, bounds=[-inf:inf], expr='delta + B_sigmax'>), ('A_sigmay', <Parameter 'A_sigmay', value=49.833333333333336, bounds=[0.0:inf]>), ('B_amplitude', <Parameter 'B_amplitude', value=1954.6248098806716, bounds=[-inf:inf]>), ('B_centerx', <Parameter 'B_centerx', value=144, bounds=[-inf:inf]>), ('B_centery', <Parameter 'B_centery', value=136, bounds=[-inf:inf]>), ('B_sigmax', <Parameter 'B_sigmax', value=49.833333333333336, bounds=[0.0:inf]>), ('B_sigmay', <Parameter 'B_sigmay', value=49.833333333333336, bounds=[0.0:inf]>), ('delta', <Parameter 'delta', value=-1, bounds=[-inf:0]>)])"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"params[0, 0].item()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Do the fit"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"`As we discussed before, the parallel computing needs chunks. And now there is no chunk! In order to enable the parallel computing, we have to rechunk our data.`"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"dataSet_cropOD = dataSet_cropOD.chunk((1, 1, 300, 300))\n",
"params = params.chunk((1, 1))"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
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" display: inline;\n",
" margin-top: 0;\n",
" margin-bottom: 0;\n",
"}\n",
"\n",
".xr-obj-type,\n",
".xr-array-name {\n",
" margin-left: 2px;\n",
" margin-right: 10px;\n",
"}\n",
"\n",
".xr-obj-type {\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-sections {\n",
" padding-left: 0 !important;\n",
" display: grid;\n",
" grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
"}\n",
"\n",
".xr-section-item {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-section-item input {\n",
" display: none;\n",
"}\n",
"\n",
".xr-section-item input + label {\n",
" color: var(--xr-disabled-color);\n",
"}\n",
"\n",
".xr-section-item input:enabled + label {\n",
" cursor: pointer;\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-section-item input:enabled + label:hover {\n",
" color: var(--xr-font-color0);\n",
"}\n",
"\n",
".xr-section-summary {\n",
" grid-column: 1;\n",
" color: var(--xr-font-color2);\n",
" font-weight: 500;\n",
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"\n",
".xr-section-summary > span {\n",
" display: inline-block;\n",
" padding-left: 0.5em;\n",
"}\n",
"\n",
".xr-section-summary-in:disabled + label {\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-section-summary-in + label:before {\n",
" display: inline-block;\n",
" content: 'â–º';\n",
" font-size: 11px;\n",
" width: 15px;\n",
" text-align: center;\n",
"}\n",
"\n",
".xr-section-summary-in:disabled + label:before {\n",
" color: var(--xr-disabled-color);\n",
"}\n",
"\n",
".xr-section-summary-in:checked + label:before {\n",
" content: 'â–¼';\n",
"}\n",
"\n",
".xr-section-summary-in:checked + label > span {\n",
" display: none;\n",
"}\n",
"\n",
".xr-section-summary,\n",
".xr-section-inline-details {\n",
" padding-top: 4px;\n",
" padding-bottom: 4px;\n",
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"\n",
".xr-section-inline-details {\n",
" grid-column: 2 / -1;\n",
"}\n",
"\n",
".xr-section-details {\n",
" display: none;\n",
" grid-column: 1 / -1;\n",
" margin-bottom: 5px;\n",
"}\n",
"\n",
".xr-section-summary-in:checked ~ .xr-section-details {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-array-wrap {\n",
" grid-column: 1 / -1;\n",
" display: grid;\n",
" grid-template-columns: 20px auto;\n",
"}\n",
"\n",
".xr-array-wrap > label {\n",
" grid-column: 1;\n",
" vertical-align: top;\n",
"}\n",
"\n",
".xr-preview {\n",
" color: var(--xr-font-color3);\n",
"}\n",
"\n",
".xr-array-preview,\n",
".xr-array-data {\n",
" padding: 0 5px !important;\n",
" grid-column: 2;\n",
"}\n",
"\n",
".xr-array-data,\n",
".xr-array-in:checked ~ .xr-array-preview {\n",
" display: none;\n",
"}\n",
"\n",
".xr-array-in:checked ~ .xr-array-data,\n",
".xr-array-preview {\n",
" display: inline-block;\n",
"}\n",
"\n",
".xr-dim-list {\n",
" display: inline-block !important;\n",
" list-style: none;\n",
" padding: 0 !important;\n",
" margin: 0;\n",
"}\n",
"\n",
".xr-dim-list li {\n",
" display: inline-block;\n",
" padding: 0;\n",
" margin: 0;\n",
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"\n",
".xr-dim-list:before {\n",
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"\n",
".xr-dim-list:after {\n",
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"}\n",
"\n",
".xr-dim-list li:not(:last-child):after {\n",
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"\n",
".xr-has-index {\n",
" font-weight: bold;\n",
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"\n",
".xr-var-list,\n",
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"\n",
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".xr-var-item label,\n",
".xr-var-item > .xr-var-name span {\n",
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"\n",
".xr-var-list > li:nth-child(odd) > div,\n",
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"\n",
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;OD&#x27; (runs: 5, truncation_value: 11, y: 300, x: 300)&gt;\n",
"dask.array&lt;xarray-&lt;this-array&gt;, shape=(5, 11, 300, 300), dtype=float64, chunksize=(1, 1, 300, 300), chunktype=numpy.ndarray&gt;\n",
"Coordinates:\n",
" * runs (runs) float64 0.0 1.0 2.0 3.0 4.0\n",
" * truncation_value (truncation_value) float64 0.8 0.83 0.85 ... 0.97 0.99 1.0\n",
"Dimensions without coordinates: y, x\n",
"Attributes:\n",
" IMAGE_SUBCLASS: IMAGE_GRAYSCALE\n",
" IMAGE_VERSION: 1.2\n",
" IMAGE_WHITE_IS_ZERO: 0\n",
" x_start: 810\n",
" x_end: 1110\n",
" y_end: 1025\n",
" y_start: 725\n",
" x_center: 960\n",
" y_center: 875\n",
" x_span: 300\n",
" y_span: 300</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'OD'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>runs</span>: 5</li><li><span class='xr-has-index'>truncation_value</span>: 11</li><li><span>y</span>: 300</li><li><span>x</span>: 300</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-291ca7d0-87f5-4dd8-aef5-ecc5a349b4ef' class='xr-array-in' type='checkbox' checked><label for='section-291ca7d0-87f5-4dd8-aef5-ecc5a349b4ef' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(1, 1, 300, 300), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
" <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",
" <td> 37.77 MiB </td>\n",
" <td> 703.12 kiB </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (5, 11, 300, 300) </td>\n",
" <td> (1, 1, 300, 300) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 55 chunks in 1 graph layer </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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"</table></div></div></li><li class='xr-section-item'><input id='section-f6f3b643-7e78-4803-9f1b-f60ef46d8d10' class='xr-section-summary-in' type='checkbox' checked><label for='section-f6f3b643-7e78-4803-9f1b-f60ef46d8d10' class='xr-section-summary' >Coordinates: <span>(2)</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'>runs</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.0 2.0 3.0 4.0</div><input id='attrs-14181931-d3c2-4bc3-8211-984c273cc675' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-14181931-d3c2-4bc3-8211-984c273cc675' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3feeb2e8-328f-46e0-9dd3-650eddfcb27e' class='xr-var-data-in' type='checkbox'><label for='data-3feeb2e8-328f-46e0-9dd3-650eddfcb27e' 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., 1., 2., 3., 4.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>truncation_value</span></div><div class='xr-var-dims'>(truncation_value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.8 0.83 0.85 ... 0.97 0.99 1.0</div><input id='attrs-fe3babc1-16ca-4c63-b68b-3ff890152e1f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fe3babc1-16ca-4c63-b68b-3ff890152e1f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1869ef41-44a9-4b89-b448-e4f7ee483f84' class='xr-var-data-in' type='checkbox'><label for='data-1869ef41-44a9-4b89-b448-e4f7ee483f84' 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([0.8 , 0.83, 0.85, 0.87, 0.89, 0.91, 0.93, 0.95, 0.97, 0.99, 1. ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5cf00493-e9d4-4dab-a9d0-53758bcaa296' class='xr-section-summary-in' type='checkbox' ><label for='section-5cf00493-e9d4-4dab-a9d0-53758bcaa296' class='xr-section-summary' >Indexes: <span>(2)</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>runs</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-70f3513e-fb5d-4edc-9b09-70db787fb84e' class='xr-index-data-in' type='checkbox'/><label for='index-70f3513e-fb5d-4edc-9b09-70db787fb84e' 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([0.0, 1.0, 2.0, 3.0, 4.0], dtype=&#x27;float64&#x27;, name=&#x27;runs&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>truncation_value</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c52a0ed6-bde9-4a48-8921-0397b863e909' class='xr-index-data-in' type='checkbox'/><label for='index-c52a0ed6-bde9-4a48-8921-0397b863e909' 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([0.8, 0.83, 0.85, 0.87, 0.89, 0.91, 0.93, 0.95, 0.97, 0.99, 1.0], dtype=&#x27;float64&#x27;, name=&#x27;truncation_value&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f07bbf6a-132a-473e-bf91-769afd0eb1ae' class='xr-section-summary-in' type='checkbox' ><label for='section-f07bbf6a-132a-473e-bf91-769afd0eb1ae' class='xr-section-summary' >Attributes: <span>(11)</spa
],
"text/plain": [
"<xarray.DataArray 'OD' (runs: 5, truncation_value: 11, y: 300, x: 300)>\n",
"dask.array<xarray-<this-array>, shape=(5, 11, 300, 300), dtype=float64, chunksize=(1, 1, 300, 300), chunktype=numpy.ndarray>\n",
"Coordinates:\n",
" * runs (runs) float64 0.0 1.0 2.0 3.0 4.0\n",
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"Dimensions without coordinates: y, x\n",
"Attributes:\n",
" IMAGE_SUBCLASS: IMAGE_GRAYSCALE\n",
" IMAGE_VERSION: 1.2\n",
" IMAGE_WHITE_IS_ZERO: 0\n",
" x_start: 810\n",
" x_end: 1110\n",
" y_end: 1025\n",
" y_start: 725\n",
" x_center: 960\n",
" y_center: 875\n",
" x_span: 300\n",
" y_span: 300"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dataSet_cropOD"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"fitResult = fitAnalyser.fit(dataSet_cropOD, params).load()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Get the number from fit result"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Get the values"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
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" y_center: 875\n",
" x_span: 300\n",
" y_span: 300</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-326d57d6-4fd4-4088-84e6-cb6d0862cebe' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-326d57d6-4fd4-4088-84e6-cb6d0862cebe' 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'>runs</span>: 5</li><li><span class='xr-has-index'>truncation_value</span>: 11</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-18ad44f8-b528-44ed-8683-e14b00e3708a' class='xr-section-summary-in' type='checkbox' checked><label for='section-18ad44f8-b528-44ed-8683-e14b00e3708a' class='xr-section-summary' >Coordinates: <span>(2)</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'>runs</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.0 2.0 3.0 4.0</div><input id='attrs-3b1668f5-dc1c-4a2a-b9fe-1e0b75fd8c38' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3b1668f5-dc1c-4a2a-b9fe-1e0b75fd8c38' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7db15bc1-a649-4ab9-bfdf-5eccede7a488' class='xr-var-data-in' type='checkbox'><label for='data-7db15bc1-a649-4ab9-bfdf-5eccede7a488' 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., 1., 2., 3., 4.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>truncation_value</span></div><div class='xr-var-dims'>(truncation_value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.8 0.83 0.85 ... 0.97 0.99 1.0</div><input id='attrs-73c076a8-56ba-40af-96c1-dc4d9a4bac50' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-73c076a8-56ba-40af-96c1-dc4d9a4bac50' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3465e57a-93c4-4c81-8471-9c1223d82e0e' class='xr-var-data-in' type='checkbox'><label for='data-3465e57a-93c4-4c81-8471-9c1223d82e0e' 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([0.8 , 0.83, 0.85, 0.87, 0.89, 0.91, 0.93, 0.95, 0.97, 0.99, 1. ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6b41aa50-328b-44e4-b6be-086c3df4bcc7' class='xr-section-summary-in' type='checkbox' checked><label for='section-6b41aa50-328b-44e4-b6be-086c3df4bcc7' class='xr-section-summary' >Data variables: <span>(11)</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>A_amplitude</span></div><div class='xr-var-dims'>(runs, truncation_value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>87.87 73.76 61.26 ... 191.0 206.3</div><input id='attrs-990f193d-c826-47aa-aa82-337e72e4a0cd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-990f193d-c826-47aa-aa82-337e72e4a0cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f152a38b-ee3a-4944-9302-e2574ca401f9' class='xr-var-data-in' type='checkbox'><label for='data-f152a38b-ee3a-4944-9302-e2574ca401f9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:
" 89.85174968, 89.98098097, 109.52351131, 97.58957785,\n",
" 532.18950818, 171.64670067, 214.73142279],\n",
" [148.41500588, 145.61502822, 94.92340958, 72.21905613,\n",
" 84.25138954, 100.46822242, 110.93503999, 78.36838557,\n",
" 94.33703708, 119.67472955, 228.32795235],\n",
" [115.21345578, 84.28198786, 55.72623183, 70.13868353,\n",
" 82.6401066 , 98.79937296, 102.53213546, 69.81928149,\n",
" 72.26478134, 158.97720012, 215.26178293],\n",
" [109.83077758, 46.15486001, 96.68708012, 70.7767806 ,\n",
" 87.10001164, 103.46997629, 95.1466356 , 94.06124781,\n",
" 485.13172534, 152.33301794, 288.72901879],\n",
" [104.31036272, 68.66710998, 61.12873582, 85.32616375,\n",
" 74.21429557, 87.74512331, 102.5255358 , 85.7467111 ,\n",
" 274.83792979, 190.99452403, 206.32857438]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>A_centerx</span></div><div class='xr-var-dims'>(runs, truncation_value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>147.4 151.4 151.0 ... 151.7 152.8</div><input id='attrs-23a6d70e-0d88-407f-b747-0f0104276510' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-23a6d70e-0d88-407f-b747-0f0104276510' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d95f66c7-0f1f-41f5-989e-3ff7435f9843' class='xr-var-data-in' type='checkbox'><label for='data-d95f66c7-0f1f-41f5-989e-3ff7435f9843' 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([[147.35658257, 151.44869095, 151.03280367, 149.72531953,\n",
" 151.21663764, 150.79959828, 149.22566816, 149.73136708,\n",
" 152.01462232, 152.02274818, 152.97453588],\n",
" [151.75284936, 154.79722431, 151.44589412, 150.38113633,\n",
" 150.20223384, 151.1905475 , 152.34142813, 150.9735046 ,\n",
" 152.99632453, 152.23926255, 150.49176424],\n",
" [148.08751505, 151.51478581, 151.9317039 , 151.3149808 ,\n",
" 149.70399115, 149.89951133, 152.13218017, 151.93027834,\n",
" 150.00888743, 149.64321357, 149.95105012],\n",
" [152.09296219, 150.13056962, 151.87197238, 150.03042241,\n",
" 151.42003475, 151.07674413, 150.53424524, 151.3627544 ,\n",
" 151.27411477, 151.4765571 , 151.82911296],\n",
" [154.27478854, 151.63087441, 151.20635115, 150.81624618,\n",
" 150.73325793, 148.60106674, 150.35065807, 150.98962516,\n",
" 152.79891129, 151.74830745, 152.81634249]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>A_centery</span></div><div class='xr-var-dims'>(runs, truncation_value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>151.3 147.2 148.7 ... 151.3 150.4</div><input id='attrs-53db6cdd-c0cb-4cf0-bd23-dad9c7c02f87' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-53db6cdd-c0cb-4cf0-bd23-dad9c7c02f87' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-61ee8a00-be5d-4d64-a269-7105e7d041da' class='xr-var-data-in' type='checkbox'><label for='data-61ee8a00-be5d-4d64-a269-7105e7d041da' 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([[151.28394589, 147.24150186, 148.72611409, 148.71669935,\n",
" 148.86331633, 150.16395069, 152.87180325, 143.01228827,\n",
" 157.30707731, 156.69107701, 149.8008272 ],\n",
" [150.23531282, 148.20649663, 149.39950182, 151.05181871,\n",
" 150.68922629, 150.92349357, 148.74791296, 155.70451963,\n",
" 169.96642044, 144.61915795, 152.33532947],\n",
" [153.67521382, 149.06280853, 150.10019083, 150.01999179,\n",
" 149.73239595, 149.35429893, 149.11430827, 154.15372705,\n",
" 163.35622755, 144.74355021, 145.41704076],\n",
" [148.77391618, 148.84134191, 149.30281946, 148.17720047,\n",
" 150.10029747, 151.30430775, 149.08990239, 150.85013866,\n",
" 151.38360691, 148.76234516, 151.38588399],\n",
" [148.80726575, 148.31953846, 148.60253328, 147.8027244 ,\n",
" 147.1907308 , 149.18648509, 150.49834047, 151.80537805,\n",
" 140.14296659, 151.29080636, 150.43594967]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>A_sigmax</span></div><div class='xr-var-dims'>(runs, truncation_value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>15.86 9.018 4.671 ... 3.781 3.964</div><input id='attrs-58bf5689-d4da-40fc-b4eb-d01bf6bb7d3d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-58bf5689-d4da-40fc-b4eb-d01bf6bb7d3d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-42ed4679-bba6-4dcd-967b-57e0e19a318a' class='xr-var-data-in' type='checkbox'><label for='data-42ed4679-bba6-4dcd-967b-57e0e19a318a' 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([[15.86033684, 9.0184675 , 4.67142174, 4.44462332, 4.14528732,\n",
" 3.82312735, 4.32416442, 4.50668022, 22.21245866, 4.02875393,\n",
" 3.90390035],\n",
" [16.65366702, 15.08437968, 7.79824126, 4.31443398, 4.02082315,\n",
" 3.92133528, 4.01732547, 3.77607115, 11.70680121, 4.02025535,\n",
" 3.77276103],\n",
" [14.05379459, 9.51781911, 5.25329603, 4.22650208, 4.39356879,\n",
" 4.3519179 , 4.31736887, 3.89746383, 10.84196056, 4.05900851,\n",
" 4.25002353],\n",
" [15.45723413, 6.69385599, 7.61202754, 4.50399055, 4.20628858,\n",
" 3.93307359, 3.94888466, 4.25195559, 22.37312866, 3.72031909,\n",
" 4.69954113],\n",
" [13.6617594 , 7.78926053, 4.48376347, 5.16074758, 3.99757519,\n",
" 3.78708533, 4.04323162, 4.1008123 , 19.82471029, 3.78116519,\n",
" 3.96389527]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>A_sigmay</span></div><div class='xr-var-dims'>(runs, truncation_value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>19.13 13.12 10.79 ... 10.36 10.61</div><input id='attrs-010f1f10-2e72-4748-b086-e14abddc8f5d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-010f1f10-2e72-4748-b086-e14abddc8f5d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69e5ed23-9038-4e92-a0a9-4c7e8871e97d' class='xr-var-data-in' type='checkbox'><label for='data-69e5ed23-9038-4e92-a0a9-4c7e8871e97d' 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([[19.12600649, 13.11979427, 10.79097925, 10.35446929, 11.4544053 ,\n",
" 10.75293975, 10.39075295, 9.29855065, 22.61916547, 9.46062774,\n",
" 9.61893074],\n",
" [18.37413835, 14.93642054, 12.9723271 , 11.47917761, 10.43588992,\n",
" 10.79180886, 10.863663 , 9.27068049, 10.97909164, 8.41824973,\n",
" 10.37416908],\n",
" [19.22624209, 13.21012726, 11.54148464, 11.28129907, 10.53017304,\n",
" 10.63218736, 9.91655465, 9.38706098, 10.34983933, 9.7173262 ,\n",
" 10.23441355],\n",
" [18.91397396, 12.38230482, 12.60057 , 10.42910762, 10.89766943,\n",
" 10.98100296, 9.54922648, 9.96676745, 21.96858327, 10.68052954,\n",
" 10.76544928],\n",
" [17.44929619, 10.16640595, 10.99961809, 11.14857526, 9.9112425 ,\n",
" 10.54292534, 10.61162461, 9.71627544, 14.77240984, 10.35969562,\n",
" 10.60766696]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>B_amplitude</span></div><div class='xr-var-dims'>(runs, truncation_value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.783e+03 1.583e+03 ... 171.9 159.9</div><input id='attrs-6c8ec77f-ff0d-4efd-83a2-44fa98e25840' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6c8ec77f-ff0d-4efd-83a2-44fa98e25840' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-11d92c8e-8fd1-42c6-87e5-d30ebf822cae' class='xr-var-data-in' type='checkbox'><label for='data-11d92c8e-8fd1-42c6-87e5-d30ebf822cae' 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([[ 1783.45054701, 1583.36795539, 1294.14272468,\n",
" 1085.9674567 , 980.30332582, 710.70254556,\n",
" 589.94319664, 473.6037191 , -1554.95748481,\n",
" 223.91672763, 153.3267524 ],\n",
" [ 1755.57473769, 1618.71259176, 1455.21148963,\n",
" 1097.03528314, 917.68371146, 730.49784306,\n",
" 583.15954472, 495.27277533, 369.51462502,\n",
" 307.67637387, 132.00866082],\n",
" [ 1824.94480896, 1560.58162411, 1354.93718336,\n",
" 1097.36556181, 933.96058739, 730.30586937,\n",
" 585.52364835, 461.52620908, 387.56015693,\n",
" 246.47749078, 130.88129224],\n",
" [ 1884.05160993, 1587.47647175, 1353.99558341,\n",
" 1030.3350402 , 892.00561639, 615.6802281 ,\n",
" 575.53953248, 520.77898298, -12794.63770211,\n",
" 247.63518228, -512.41114085],\n",
" [ 1787.52744747, 1413.59773834, 1283.83218285,\n",
" 1131.89914361, 932.44739769, 739.28845463,\n",
" 576.17585769, 518.67050619, 187.26884654,\n",
" 171.93192999, 159.92341651]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>B_centerx</span></div><div class='xr-var-dims'>(runs, truncation_value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>149.8 152.0 150.8 ... 154.2 154.1</div><input id='attrs-d856f3c4-4cce-4b5c-88ef-62a29fc8f70c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d856f3c4-4cce-4b5c-88ef-62a29fc8f70c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b0dcc064-977c-4b15-b012-f909fa4485e9' class='xr-var-data-in' type='checkbox'><label for='data-b0dcc064-977c-4b15-b012-f909fa4485e9' 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([[ 149.77259545, 152.02155216, 150.82226953, 150.17856412,\n",
" 151.49869445, 151.00882072, 150.00017539, 151.2056335 ,\n",
" 425.4471671 , 155.07081348, 155.37875268],\n",
" [ 152.18376687, 151.4144676 , 151.87836658, 150.54995899,\n",
" 150.23221437, 152.14621363, 152.72951398, 151.07172615,\n",
" 150.89663936, 153.94104155, 152.35166839],\n",
" [ 150.22539645, 151.82546419, 151.8155642 , 150.92405452,\n",
" 149.98395125, 150.44869725, 152.2557924 , 150.71412855,\n",
" 153.24001471, 150.92939804, 152.08822726],\n",
" [ 151.88129055, 149.75770493, 151.57847363, 150.21954836,\n",
" 151.41093996, 150.73394379, 151.18173904, 151.31132354,\n",
" 1794.40094581, 152.91301882, -123.18365955],\n",
" [ 152.47370924, 151.44312867, 151.13645269, 151.59289508,\n",
" 151.67957652, 149.82793657, 149.77567429, 151.21747559,\n",
" 151.16624065, 154.17608173, 154.05517934]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>B_centery</span></div><div class='xr-var-dims'>(runs, truncation_value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>147.5 148.1 150.0 ... 149.7 150.4</div><input id='attrs-3b74dbfd-9f7f-4b4f-93c0-3f5168047ecb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3b74dbfd-9f7f-4b4f-93c0-3f5168047ecb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-887378aa-357a-4f5c-9d46-a851d1c9cdfd' class='xr-var-data-in' type='checkbox'><label for='data-887378aa-357a-4f5c-9d46-a851d1c9cdfd' 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([[147.45295195, 148.09746651, 150.0255 , 149.14691129,\n",
" 148.98258537, 150.22718776, 153.16129424, 152.81932317,\n",
" 72.24418704, 154.52991041, 149.17022831],\n",
" [149.47572526, 149.34656247, 149.83533472, 150.93254944,\n",
" 151.01030524, 151.51733988, 147.4931119 , 151.6147346 ,\n",
" 153.7661836 , 146.32505819, 150.50395509],\n",
" [150.41254937, 150.71499149, 151.63638785, 151.25714745,\n",
" 150.4626488 , 151.46493096, 151.75523375, 149.02192961,\n",
" 154.16333799, 145.82390071, 146.81309327],\n",
" [148.08358746, 148.574133 , 150.01635145, 149.58154983,\n",
" 151.26380613, 148.55592561, 152.23705055, 144.97313415,\n",
" 299.42496082, 151.15903259, 200.07482412],\n",
" [149.28876671, 148.64087187, 148.86311139, 148.44094162,\n",
" 147.56308142, 151.31740191, 147.95630349, 155.4460084 ,\n",
" 166.00908446, 149.67457383, 150.43124107]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>B_sigmax</span></div><div class='xr-var-dims'>(runs, truncation_value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>32.53 31.39 27.64 ... 16.65 15.85</div><input id='attrs-39e03964-5cdd-49c7-a591-c74278b9ec52' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-39e03964-5cdd-49c7-a591-c74278b9ec52' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d912a8f0-a9b3-47a1-80b0-3949b8a6b2cb' class='xr-var-data-in' type='checkbox'><label for='data-d912a8f0-a9b3-47a1-80b0-3949b8a6b2cb' 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([[ 32.5349708 , 31.39433096, 27.64328817, 26.22763531,\n",
" 25.30006205, 22.90070236, 23.22010131, 21.56317923,\n",
" 51.04673134, 17.58633398, 17.49492739],\n",
" [ 33.27712833, 31.13507291, 29.13042227, 25.96001938,\n",
" 24.96531387, 23.51968294, 22.63545942, 20.88798559,\n",
" 23.14105763, 18.77307842, 15.69149838],\n",
" [ 32.41647008, 30.06301091, 27.95029662, 25.78889949,\n",
" 25.32669046, 23.73947481, 22.21131961, 19.08019799,\n",
" 20.76525779, 17.90936397, 17.59006204],\n",
" [ 33.65336072, 29.67929946, 29.7644638 , 25.82239234,\n",
" 24.71819699, 23.03948697, 22.25809162, 22.09705834,\n",
" 1103.61563922, 17.76208096, 69.21926428],\n",
" [ 33.29573618, 29.07307007, 27.83726355, 26.94999028,\n",
" 25.42299204, 24.04340187, 23.02812015, 21.43220187,\n",
" 22.93573535, 16.64979817, 15.85282615]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>B_sigmay</span></div><div class='xr-var-dims'>(runs, truncation_value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>33.29 32.43 28.47 ... 16.34 13.79</div><input id='attrs-270f3dde-5cf3-44c6-a696-f22eade70b6d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-270f3dde-5cf3-44c6-a696-f22eade70b6d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eaba2a47-35ef-4d66-96fa-cd7ab987f518' class='xr-var-data-in' type='checkbox'><label for='data-eaba2a47-35ef-4d66-96fa-cd7ab987f518' 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([[ 33.29334334, 32.43099741, 28.47278332, 27.18103378,\n",
" 25.71431976, 24.27199694, 22.77078579, 20.37040614,\n",
" 25.22140544, 15.74705493, 14.21177517],\n",
" [ 34.99745369, 33.20946815, 30.58125742, 26.52760872,\n",
" 25.11661825, 23.70894422, 22.08155913, 21.77847574,\n",
" 21.59150892, 17.9765663 , 12.89178954],\n",
" [ 33.77124313, 31.3243406 , 29.13665369, 26.74559133,\n",
" 25.652014 , 23.57574991, 22.42657894, 20.55697484,\n",
" 19.96887556, 16.99616651, 13.87336776],\n",
" [ 34.67043472, 31.21760361, 30.83496859, 26.86661064,\n",
" 25.70634067, 23.05941925, 22.88232236, 21.20419837,\n",
" 309.01438251, 16.70070999, 51.108073 ],\n",
" [ 34.22146326, 30.3244038 , 28.76138498, 28.27677548,\n",
" 26.24162491, 24.57777006, 22.9522538 , 22.40814737,\n",
" 16.89351118, 16.34461527, 13.78927636]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>delta</span></div><div class='xr-var-dims'>(runs, truncation_value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-16.67 -22.38 ... -12.87 -11.89</div><input id='attrs-d79a72ed-c4c4-4763-953f-c907adad5ffa' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d79a72ed-c4c4-4763-953f-c907adad5ffa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3ef98c7b-3a35-4e7f-b916-6c5cf55b497a' class='xr-var-data-in' type='checkbox'><label for='data-3ef98c7b-3a35-4e7f-b916-6c5cf55b497a' 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([[ -16.67463396, -22.37586347, -22.97186643, -21.78301199,\n",
" -21.15477472, -19.07757501, -18.89593689, -17.05649901,\n",
" -28.83427268, -13.55758005, -13.59102704],\n",
" [ -16.62346131, -16.05069323, -21.33218101, -21.6455854 ,\n",
" -20.94449072, -19.59834765, -18.61813395, -17.11191444,\n",
" -11.43425642, -14.75282307, -11.91873735],\n",
" [ -18.36267549, -20.5451918 , -22.69700059, -21.5623974 ,\n",
" -20.93312167, -19.38755691, -17.89395074, -15.18273416,\n",
" -9.92329723, -13.85035547, -13.34003851],\n",
" [ -18.19612659, -22.98544347, -22.15243626, -21.31840179,\n",
" -20.51190841, -19.10641338, -18.30920696, -17.84510275,\n",
" -1081.24251056, -14.04176187, -64.51972315],\n",
" [ -19.63397678, -21.28380955, -23.35350008, -21.7892427 ,\n",
" -21.42541685, -20.25631654, -18.98488854, -17.33138957,\n",
" -3.11102506, -12.86863298, -11.88893088]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7fc03b3c-8287-44ea-96b1-d992a59022b0' class='xr-section-summary-in' type='checkbox' ><label for='section-7fc03b3c-8287-44ea-96b1-d992a59022b0' class='xr-section-summary' >Indexes: <span>(2)</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>runs</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4fafec04-6a2a-4095-8a5d-49abd894c9fa' class='xr-index-data-in' type='checkbox'/><label for='index-4fafec04-6a2a-4095-8a5d-49abd894c9fa' 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([0.0, 1.0, 2.0, 3.0, 4.0], dtype=&#x27;float64&#x27;, name=&#x27;runs&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>truncation_value</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-bcaf87d0-4d94-4a14-8092-4fceadd4a21c' class='xr-index-data-in' type='checkbox'/><label for='index-bcaf87d0-4d94-4a14-8092-4fceadd4a21c' 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([0.8, 0.83, 0.85, 0.87, 0.89, 0.91, 0.93, 0.95, 0.97, 0.99, 1.0], dtype=&#x27;float64&#x27;, name=&#x27;truncation_value&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-604afbdd-f2bf-4cab-9f07-94ba43d9e904' class='xr-section-summary-in' type='checkbox' ><label for='section-604afbdd-f2bf-4cab-9f07-94ba43d9e904' class='xr-section-summary' >Attributes: <span>(11)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><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><dt><span>x_start :</span></dt><dd>810</dd><dt><span>x_end :</span></dt><dd>1110</dd><dt><span>y_end :</span></dt><dd>1025</dd><dt><span>y_start :</span></dt><dd>725</dd><dt><span>x_center :</span></dt><dd>960</dd><dt><span>y_center :</span></dt><dd>875</dd><dt><span>x_span :</span></dt><dd>300</dd><dt><span>y_span :</span></dt><dd>300</dd></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (runs: 5, truncation_value: 11)\n",
"Coordinates:\n",
" * runs (runs) float64 0.0 1.0 2.0 3.0 4.0\n",
" * truncation_value (truncation_value) float64 0.8 0.83 0.85 ... 0.97 0.99 1.0\n",
"Data variables:\n",
" A_amplitude (runs, truncation_value) float64 87.87 73.76 ... 206.3\n",
" A_centerx (runs, truncation_value) float64 147.4 151.4 ... 152.8\n",
" A_centery (runs, truncation_value) float64 151.3 147.2 ... 150.4\n",
" A_sigmax (runs, truncation_value) float64 15.86 9.018 ... 3.964\n",
" A_sigmay (runs, truncation_value) float64 19.13 13.12 ... 10.61\n",
" B_amplitude (runs, truncation_value) float64 1.783e+03 ... 159.9\n",
" B_centerx (runs, truncation_value) float64 149.8 152.0 ... 154.1\n",
" B_centery (runs, truncation_value) float64 147.5 148.1 ... 150.4\n",
" B_sigmax (runs, truncation_value) float64 32.53 31.39 ... 15.85\n",
" B_sigmay (runs, truncation_value) float64 33.29 32.43 ... 13.79\n",
" delta (runs, truncation_value) float64 -16.67 -22.38 ... -11.89\n",
"Attributes:\n",
" IMAGE_SUBCLASS: IMAGE_GRAYSCALE\n",
" IMAGE_VERSION: 1.2\n",
" IMAGE_WHITE_IS_ZERO: 0\n",
" x_start: 810\n",
" x_end: 1110\n",
" y_end: 1025\n",
" y_start: 725\n",
" x_center: 960\n",
" y_center: 875\n",
" x_span: 300\n",
" y_span: 300"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"val = fitAnalyser.get_fit_value(fitResult)\n",
"val"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Get the standard deviation"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
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" 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: (runs: 5, truncation_value: 11)\n",
"Coordinates:\n",
" * runs (runs) float64 0.0 1.0 2.0 3.0 4.0\n",
" * truncation_value (truncation_value) float64 0.8 0.83 0.85 ... 0.97 0.99 1.0\n",
"Data variables:\n",
" A_amplitude (runs, truncation_value) float64 41.35 8.536 ... 4.752\n",
" A_centerx (runs, truncation_value) float64 1.373 0.4656 ... 0.0426\n",
" A_centery (runs, truncation_value) float64 1.829 0.7057 ... 0.1419\n",
" A_sigmax (runs, truncation_value) float64 2.502 0.6067 ... 0.05853\n",
" A_sigmay (runs, truncation_value) float64 2.561 0.8023 ... 0.139\n",
" B_amplitude (runs, truncation_value) float64 38.55 11.89 ... 6.328\n",
" B_centerx (runs, truncation_value) float64 0.271 0.2215 ... 0.5065\n",
" B_centery (runs, truncation_value) float64 0.3084 0.239 ... 0.5433\n",
" B_sigmax (runs, truncation_value) float64 0.473 0.2884 ... 0.6838\n",
" B_sigmay (runs, truncation_value) float64 0.4067 0.2715 ... 0.5322\n",
" delta (runs, truncation_value) float64 2.199 0.5443 ... 0.6551\n",
"Attributes:\n",
" IMAGE_SUBCLASS: IMAGE_GRAYSCALE\n",
" IMAGE_VERSION: 1.2\n",
" IMAGE_WHITE_IS_ZERO: 0\n",
" x_start: 810\n",
" x_end: 1110\n",
" y_end: 1025\n",
" y_start: 725\n",
" x_center: 960\n",
" y_center: 875\n",
" x_span: 300\n",
" y_span: 300</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-a6596bf9-f8e5-4501-8fcb-251b50168f39' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a6596bf9-f8e5-4501-8fcb-251b50168f39' 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'>runs</span>: 5</li><li><span class='xr-has-index'>truncation_value</span>: 11</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-f25e1ec7-d75b-4b65-afd2-21dbac9d7d2c' class='xr-section-summary-in' type='checkbox' checked><label for='section-f25e1ec7-d75b-4b65-afd2-21dbac9d7d2c' class='xr-section-summary' >Coordinates: <span>(2)</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'>runs</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.0 2.0 3.0 4.0</div><input id='attrs-7b5c83e0-0bb5-4ee2-97b1-6a275a0a9b60' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7b5c83e0-0bb5-4ee2-97b1-6a275a0a9b60' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-50b6be17-25f7-4f7c-b6bb-4c67df7aaf61' class='xr-var-data-in' type='checkbox'><label for='data-50b6be17-25f7-4f7c-b6bb-4c67df7aaf61' 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., 1., 2., 3., 4.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>truncation_value</span></div><div class='xr-var-dims'>(truncation_value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.8 0.83 0.85 ... 0.97 0.99 1.0</div><input id='attrs-ef3349d2-feb7-464a-b4c0-726fb8daaf5c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ef3349d2-feb7-464a-b4c0-726fb8daaf5c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-193f6082-2f8e-45ec-8fff-e1ccbdbae348' class='xr-var-data-in' type='checkbox'><label for='data-193f6082-2f8e-45ec-8fff-e1ccbdbae348' 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([0.8 , 0.83, 0.85, 0.87, 0.89, 0.91, 0.93, 0.95, 0.97, 0.99, 1. ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4397190e-0c2b-458f-9c4e-813c31d39edd' class='xr-section-summary-in' type='checkbox' checked><label for='section-4397190e-0c2b-458f-9c4e-813c31d39edd' class='xr-section-summary' >Data variables: <span>(11)</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>A_amplitude</span></div><div class='xr-var-dims'>(runs, truncation_value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>41.35 8.536 3.549 ... 4.165 4.752</div><input id='attrs-6dc8d5f5-9946-4cc7-9afb-90d8a484c8e3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6dc8d5f5-9946-4cc7-9afb-90d8a484c8e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-96fa7a28-66c8-47d1-8d06-863caca87ef9' class='xr-var-data-in' type='checkbox'><label for='data-96fa7a28-66c8-47d1-8d06-863caca87ef9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:
" 3.23781731, 3.63912115, 3.55016032, 7.24158601, 4.00295491,\n",
" 3.93889204],\n",
" [39.09039398, 24.2472226 , 7.31704996, 3.60212261, 3.21228769,\n",
" 3.39514472, 3.5072124 , 3.16249809, 15.15014763, 3.5416771 ,\n",
" 4.24968854],\n",
" [30.03008996, 9.94253914, 4.24707555, 3.52201376, 3.51626384,\n",
" 3.65879701, 3.67011253, 3.4681694 , 17.90365434, 4.15399748,\n",
" 4.55700578],\n",
" [34.44351574, 5.62730163, 6.8327929 , 3.47510006, 3.54695392,\n",
" 3.52943849, 3.19843539, 3.6674288 , 9.46190948, 3.8137756 ,\n",
" 2.31426625],\n",
" [23.36180289, 5.92033204, 3.42391579, 4.16076828, 3.03207606,\n",
" 3.04692971, 3.40342961, 3.48868316, 78.00226286, 4.1649254 ,\n",
" 4.75175596]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>A_centerx</span></div><div class='xr-var-dims'>(runs, truncation_value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.373 0.4656 ... 0.04294 0.0426</div><input id='attrs-1a0909c4-01c4-40f8-ac2d-c3acecfb91f0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1a0909c4-01c4-40f8-ac2d-c3acecfb91f0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-829f4350-a4f6-40d7-a718-a26182362fe1' class='xr-var-data-in' type='checkbox'><label for='data-829f4350-a4f6-40d7-a718-a26182362fe1' 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([[1.37275271, 0.46564767, 0.1783507 , 0.11981298, 0.10298813,\n",
" 0.08899595, 0.0870227 , 0.09711865, 0.30224711, 0.04919934,\n",
" 0.03767388],\n",
" [0.83459062, 0.63964249, 0.28050157, 0.13988076, 0.10183172,\n",
" 0.08559291, 0.07848608, 0.0956075 , 0.53288645, 0.06586354,\n",
" 0.03460433],\n",
" [0.80957124, 0.44954895, 0.24654689, 0.13935714, 0.1195584 ,\n",
" 0.09885554, 0.09180816, 0.1125341 , 0.70066171, 0.05450696,\n",
" 0.04395562],\n",
" [0.97982363, 0.44603965, 0.2650354 , 0.14280239, 0.11040201,\n",
" 0.08525171, 0.08422187, 0.09946159, 0.33900844, 0.05097848,\n",
" 0.03763179],\n",
" [0.78888259, 0.34901146, 0.16877679, 0.15361024, 0.1114052 ,\n",
" 0.08812014, 0.08422454, 0.10064893, 0.51415449, 0.04294127,\n",
" 0.04259848]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>A_centery</span></div><div class='xr-var-dims'>(runs, truncation_value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.829 0.7057 ... 0.1367 0.1419</div><input id='attrs-02730faa-e60d-4e34-ae1f-a8bfaf64647b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-02730faa-e60d-4e34-ae1f-a8bfaf64647b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fc19d08a-237a-4ce2-9e2f-76a48aff7c6a' class='xr-var-data-in' type='checkbox'><label for='data-fc19d08a-237a-4ce2-9e2f-76a48aff7c6a' 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([[1.82931682, 0.70570221, 0.42876793, 0.29065492, 0.30153625,\n",
" 0.26494553, 0.22368237, 0.22421098, 0.30777979, 0.13240613,\n",
" 0.10918892],\n",
" [0.94431847, 0.6077866 , 0.49261836, 0.3936542 , 0.27748013,\n",
" 0.25035213, 0.22946576, 0.24985908, 0.62978456, 0.14881484,\n",
" 0.11940909],\n",
" [1.2445461 , 0.65460182, 0.56542821, 0.39119808, 0.30168532,\n",
" 0.25821964, 0.22503312, 0.29482473, 0.79728417, 0.14782686,\n",
" 0.12960455],\n",
" [1.28849429, 0.86237911, 0.46076192, 0.34495895, 0.30172961,\n",
" 0.2559253 , 0.21511481, 0.25545875, 0.3329528 , 0.17058156,\n",
" 0.08620531],\n",
" [1.07567013, 0.46326371, 0.43025492, 0.3469241 , 0.28673676,\n",
" 0.25872847, 0.23708082, 0.254787 , 2.59960234, 0.13666223,\n",
" 0.14190089]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>A_sigmax</span></div><div class='xr-var-dims'>(runs, truncation_value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.502 0.6067 ... 0.05553 0.05853</div><input id='attrs-96df74d4-33e3-4200-a8e9-9a85e3678353' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-96df74d4-33e3-4200-a8e9-9a85e3678353' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-98856a02-bc11-4fea-a71c-5965b61d9915' class='xr-var-data-in' type='checkbox'><label for='data-98856a02-bc11-4fea-a71c-5965b61d9915' 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([[2.50210815, 0.60673241, 0.20515777, 0.13801476, 0.11995417,\n",
" 0.10400531, 0.1043108 , 0.11584281, 0.3022487 , 0.06311102,\n",
" 0.04876893],\n",
" [1.44371672, 0.90920954, 0.36405611, 0.16292322, 0.11745137,\n",
" 0.10021903, 0.09383077, 0.11241069, 0.73901507, 0.08152476,\n",
" 0.04645569],\n",
" [1.41176589, 0.60765676, 0.29087273, 0.16149254, 0.13956056,\n",
" 0.11779449, 0.11045638, 0.13623811, 0.94231078, 0.07058897,\n",
" 0.05895437],\n",
" [1.73929057, 0.54681615, 0.33653577, 0.16561969, 0.12882168,\n",
" 0.10061599, 0.09861943, 0.11933154, 0.36220156, 0.06483756,\n",
" 0.03764181],\n",
" [1.26746526, 0.42348683, 0.19301044, 0.18167604, 0.12668019,\n",
" 0.10143472, 0.09968958, 0.12014094, 0.68257015, 0.05553422,\n",
" 0.05853344]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>A_sigmay</span></div><div class='xr-var-dims'>(runs, truncation_value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.561 0.8023 0.444 ... 0.1329 0.139</div><input id='attrs-4250fed9-1f49-4fdb-84a6-0d91c8e12fc5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4250fed9-1f49-4fdb-84a6-0d91c8e12fc5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e91d17be-51db-4196-84f8-40dc3a9f5fb1' class='xr-var-data-in' type='checkbox'><label for='data-e91d17be-51db-4196-84f8-40dc3a9f5fb1' 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([[2.56072913, 0.80234429, 0.44396565, 0.30092615, 0.30512136,\n",
" 0.26858688, 0.22733819, 0.21966024, 0.30778103, 0.12884175,\n",
" 0.10648424],\n",
" [1.51795074, 0.94715391, 0.54081991, 0.40013487, 0.28305137,\n",
" 0.25275274, 0.22965698, 0.25413912, 0.72668546, 0.15198206,\n",
" 0.11545866],\n",
" [1.55052073, 0.76507566, 0.5883192 , 0.39853779, 0.30978006,\n",
" 0.26208035, 0.23001055, 0.29685328, 0.96653882, 0.1461634 ,\n",
" 0.12554477],\n",
" [1.81945195, 0.92222802, 0.50365298, 0.35711069, 0.30797541,\n",
" 0.25612964, 0.21997048, 0.25373163, 0.35554785, 0.16478862,\n",
" 0.0862227 ],\n",
" [1.39250289, 0.52895344, 0.44345531, 0.36205789, 0.29537217,\n",
" 0.26203786, 0.23873928, 0.26001589, 0.98330524, 0.13292493,\n",
" 0.13899744]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>B_amplitude</span></div><div class='xr-var-dims'>(runs, truncation_value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>38.55 11.89 9.327 ... 6.462 6.328</div><input id='attrs-00e3ff8e-1415-46bf-8275-b5f0dba87fe5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-00e3ff8e-1415-46bf-8275-b5f0dba87fe5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ba5ea9c6-e32f-42a0-97d5-9f91044e7538' class='xr-var-data-in' type='checkbox'><label for='data-ba5ea9c6-e32f-42a0-97d5-9f91044e7538' 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([[3.85547497e+01, 1.18924107e+01, 9.32697398e+00, 8.78389686e+00,\n",
" 8.42996656e+00, 7.85105927e+00, 7.77063271e+00, 7.19874879e+00,\n",
" 9.18369699e+04, 6.30520086e+00, 6.10434083e+00],\n",
" [3.59788621e+01, 2.27132673e+01, 1.07460296e+01, 8.89038556e+00,\n",
" 8.36260017e+00, 8.13665269e+00, 7.58775085e+00, 7.30684128e+00,\n",
" 1.68050976e+01, 6.46784323e+00, 5.88043739e+00],\n",
" [2.82088774e+01, 1.22000097e+01, 9.69713959e+00, 8.92292396e+00,\n",
" 8.55493699e+00, 8.01386612e+00, 7.64219203e+00, 6.86518652e+00,\n",
" 1.80541029e+01, 6.53151700e+00, 6.37560014e+00],\n",
" [3.18504614e+01, 1.04987920e+01, 1.08501487e+01, 8.71677797e+00,\n",
" 8.65750292e+00, 8.09273140e+00, 7.58877301e+00, 7.60357840e+00,\n",
" 9.23104837e+05, 6.32816270e+00, 1.35243844e+04],\n",
" [2.21892519e+01, 1.03713054e+01, 9.34310101e+00, 9.36686554e+00,\n",
" 8.55244243e+00, 7.97942115e+00, 7.69694096e+00, 7.49530133e+00,\n",
" 7.76742958e+01, 6.46160396e+00, 6.32769171e+00]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>B_centerx</span></div><div class='xr-var-dims'>(runs, truncation_value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.271 0.2215 ... 0.5714 0.5065</div><input id='attrs-57f275b5-58ba-41d1-918b-002fdd64da47' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-57f275b5-58ba-41d1-918b-002fdd64da47' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4758dcc9-384e-435b-8675-9935a5cfaee2' class='xr-var-data-in' type='checkbox'><label for='data-4758dcc9-384e-435b-8675-9935a5cfaee2' 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([[2.70963487e-01, 2.21482694e-01, 1.97551706e-01, 2.10345493e-01,\n",
" 2.13343499e-01, 2.48068244e-01, 2.97636503e-01, 3.11270572e-01,\n",
" 1.91778052e+03, 4.62258307e-01, 6.26441819e-01],\n",
" [2.73736145e-01, 2.62818740e-01, 2.02847052e-01, 2.06761948e-01,\n",
" 2.24441605e-01, 2.56558188e-01, 2.84708375e-01, 3.01622502e-01,\n",
" 5.33484685e-01, 3.81303887e-01, 5.81213557e-01],\n",
" [2.43361048e-01, 2.10054101e-01, 1.97335113e-01, 2.06620014e-01,\n",
" 2.28723156e-01, 2.53872776e-01, 2.82010009e-01, 2.73807119e-01,\n",
" 5.01162595e-01, 4.34167477e-01, 7.26200639e-01],\n",
" [2.49039159e-01, 1.91941903e-01, 2.28909262e-01, 2.16181397e-01,\n",
" 2.35932668e-01, 2.94326841e-01, 2.88449947e-01, 3.10046973e-01,\n",
" 7.83183242e+04, 4.11836960e-01, 1.39815877e+03],\n",
" [2.48682834e-01, 2.10943978e-01, 2.00946864e-01, 2.20160710e-01,\n",
" 2.31651585e-01, 2.55919052e-01, 2.99458615e-01, 3.02040797e-01,\n",
" 9.82489672e-01, 5.71430324e-01, 5.06473515e-01]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>B_centery</span></div><div class='xr-var-dims'>(runs, truncation_value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.3084 0.239 ... 0.6315 0.5433</div><input id='attrs-0f9d49e0-5f4a-4429-9ab6-cfcd393a2300' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0f9d49e0-5f4a-4429-9ab6-cfcd393a2300' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-574510ea-6f75-438d-846c-0ece7513453c' class='xr-var-data-in' type='checkbox'><label for='data-574510ea-6f75-438d-846c-0ece7513453c' 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([[3.08352266e-01, 2.38991239e-01, 2.11583536e-01, 2.26634616e-01,\n",
" 2.29758880e-01, 2.78595826e-01, 3.11620423e-01, 3.39820106e-01,\n",
" 1.23305969e+01, 4.55185737e-01, 5.83677190e-01],\n",
" [2.94859097e-01, 2.61430846e-01, 2.25117977e-01, 2.23076358e-01,\n",
" 2.36954007e-01, 2.74767600e-01, 3.00276342e-01, 3.36156583e-01,\n",
" 1.08640672e+00, 3.91089347e-01, 5.80818196e-01],\n",
" [2.83553239e-01, 2.29947553e-01, 2.15510698e-01, 2.25512279e-01,\n",
" 2.43243871e-01, 2.69345389e-01, 3.04743583e-01, 3.22618143e-01,\n",
" 7.67363009e-01, 4.63745121e-01, 6.83170270e-01],\n",
" [2.76093188e-01, 2.11508744e-01, 2.49325976e-01, 2.34703962e-01,\n",
" 2.58717490e-01, 3.17069589e-01, 3.13967255e-01, 3.28295246e-01,\n",
" 6.07132323e+02, 4.46745744e-01, 2.44319652e+01],\n",
" [2.69790854e-01, 2.24207207e-01, 2.15787586e-01, 2.41485901e-01,\n",
" 2.47844655e-01, 2.75432228e-01, 3.20075584e-01, 3.38286591e-01,\n",
" 6.71779625e+00, 6.31471809e-01, 5.43326115e-01]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>B_sigmax</span></div><div class='xr-var-dims'>(runs, truncation_value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.473 0.2884 ... 0.7047 0.6838</div><input id='attrs-4c39759a-f00a-47b8-8dc9-d19fc6ec0139' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4c39759a-f00a-47b8-8dc9-d19fc6ec0139' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3b39996c-8e62-4876-bc9c-9ba59c0bdd98' class='xr-var-data-in' type='checkbox'><label for='data-3b39996c-8e62-4876-bc9c-9ba59c0bdd98' 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([[4.72961568e-01, 2.88359766e-01, 2.27229296e-01, 2.42215079e-01,\n",
" 2.48449854e-01, 2.89873557e-01, 3.56157343e-01, 3.66590098e-01,\n",
" 3.43237077e+02, 5.55688418e-01, 7.77098961e-01],\n",
" [4.72836818e-01, 3.56274668e-01, 2.63130939e-01, 2.40808876e-01,\n",
" 2.58867524e-01, 2.99745634e-01, 3.40219856e-01, 3.54574654e-01,\n",
" 6.44011924e-01, 4.64897840e-01, 7.51901115e-01],\n",
" [4.12335168e-01, 2.83845657e-01, 2.32807499e-01, 2.39371729e-01,\n",
" 2.66947023e-01, 3.02268542e-01, 3.39268203e-01, 3.29131343e-01,\n",
" 6.07439127e-01, 5.55776865e-01, 9.37292179e-01],\n",
" [4.41951448e-01, 2.35249230e-01, 2.90604150e-01, 2.50706366e-01,\n",
" 2.75295969e-01, 3.47257460e-01, 3.37367075e-01, 3.71741725e-01,\n",
" 2.69804862e+04, 5.16673630e-01, 3.20122419e+02],\n",
" [3.93476889e-01, 2.55939168e-01, 2.29798024e-01, 2.60081186e-01,\n",
" 2.63023818e-01, 2.93690407e-01, 3.54131295e-01, 3.60443580e-01,\n",
" 1.12155031e+00, 7.04655972e-01, 6.83791670e-01]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>B_sigmay</span></div><div class='xr-var-dims'>(runs, truncation_value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.4067 0.2715 ... 0.6158 0.5322</div><input id='attrs-795a356d-261c-4e98-aee1-9fcdebeb9d52' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-795a356d-261c-4e98-aee1-9fcdebeb9d52' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-24175d95-b505-4d53-bff5-0ea1101f7b96' class='xr-var-data-in' type='checkbox'><label for='data-24175d95-b505-4d53-bff5-0ea1101f7b96' 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([[4.06654450e-01, 2.71488919e-01, 2.18931978e-01, 2.34625483e-01,\n",
" 2.32487747e-01, 2.82422649e-01, 3.16705370e-01, 3.15533315e-01,\n",
" 1.23535011e+01, 4.44479398e-01, 5.69567405e-01],\n",
" [4.72599301e-01, 4.04978433e-01, 2.47100938e-01, 2.26748682e-01,\n",
" 2.41703515e-01, 2.77383757e-01, 3.00506162e-01, 3.39041762e-01,\n",
" 5.58268252e-01, 3.98515560e-01, 5.65437909e-01],\n",
" [3.44167875e-01, 2.67614933e-01, 2.24000411e-01, 2.29653027e-01,\n",
" 2.49724904e-01, 2.72998922e-01, 3.10390936e-01, 3.19999626e-01,\n",
" 5.23098024e-01, 4.58721975e-01, 6.64432727e-01],\n",
" [3.89120074e-01, 2.26177573e-01, 2.72411609e-01, 2.42751524e-01,\n",
" 2.63961482e-01, 3.17092545e-01, 3.19526663e-01, 3.22432108e-01,\n",
" 6.41302765e+02, 4.34104378e-01, 2.54645912e+01],\n",
" [3.49071224e-01, 2.55966778e-01, 2.22404061e-01, 2.51968387e-01,\n",
" 2.55294572e-01, 2.78662011e-01, 3.21893786e-01, 3.42829829e-01,\n",
" 2.75018760e+00, 6.15842516e-01, 5.32203246e-01]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>delta</span></div><div class='xr-var-dims'>(runs, truncation_value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.199 0.5443 ... 0.6814 0.6551</div><input id='attrs-815f8ea7-5316-41e8-ab84-5a66dacdbf91' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-815f8ea7-5316-41e8-ab84-5a66dacdbf91' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a2e3aca5-5439-4f6c-b6f3-7dcc27eaef7e' class='xr-var-data-in' type='checkbox'><label for='data-a2e3aca5-5439-4f6c-b6f3-7dcc27eaef7e' 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([[2.19915120e+00, 5.44321962e-01, 2.53704498e-01, 2.37772412e-01,\n",
" 2.36780072e-01, 2.72624706e-01, 3.31966151e-01, 3.44197602e-01,\n",
" 3.43236051e+02, 5.31153332e-01, 7.56071907e-01],\n",
" [1.19235308e+00, 7.99923763e-01, 3.41253990e-01, 2.41269565e-01,\n",
" 2.47448686e-01, 2.81594732e-01, 3.17631991e-01, 3.33061626e-01,\n",
" 8.17174586e-01, 4.38516002e-01, 7.29889334e-01],\n",
" [1.17376058e+00, 5.34482837e-01, 3.03101058e-01, 2.40851273e-01,\n",
" 2.56323446e-01, 2.81746545e-01, 3.15202324e-01, 3.05237139e-01,\n",
" 9.00085649e-01, 5.27200762e-01, 9.09559446e-01],\n",
" [1.47627490e+00, 5.04673958e-01, 3.39169843e-01, 2.51461332e-01,\n",
" 2.61723353e-01, 3.25540430e-01, 3.17785108e-01, 3.46009011e-01,\n",
" 2.69805636e+04, 4.91442571e-01, 3.20121518e+02],\n",
" [1.07111596e+00, 4.08835659e-01, 2.50446161e-01, 2.60160608e-01,\n",
" 2.55434849e-01, 2.78448303e-01, 3.31963581e-01, 3.36081959e-01,\n",
" 1.20207122e+00, 6.81354888e-01, 6.55114890e-01]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3a8f43fd-6342-4d5b-be29-56366bf0b591' class='xr-section-summary-in' type='checkbox' ><label for='section-3a8f43fd-6342-4d5b-be29-56366bf0b591' class='xr-section-summary' >Indexes: <span>(2)</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>runs</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-02be0481-08d5-41ac-a360-df3eb494ddaf' class='xr-index-data-in' type='checkbox'/><label for='index-02be0481-08d5-41ac-a360-df3eb494ddaf' 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([0.0, 1.0, 2.0, 3.0, 4.0], dtype=&#x27;float64&#x27;, name=&#x27;runs&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>truncation_value</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4766b51f-7fa1-4f2a-90a6-d8eff4691206' class='xr-index-data-in' type='checkbox'/><label for='index-4766b51f-7fa1-4f2a-90a6-d8eff4691206' 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([0.8, 0.83, 0.85, 0.87, 0.89, 0.91, 0.93, 0.95, 0.97, 0.99, 1.0], dtype=&#x27;float64&#x27;, name=&#x27;truncation_value&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-44775fcc-d91a-43ec-9eb4-125b72978c3c' class='xr-section-summary-in' type='checkbox' ><label for='section-44775fcc-d91a-43ec-9eb4-125b72978c3c' class='xr-section-summary' >Attributes: <span>(11)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><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><dt><span>x_start :</span></dt><dd>810</dd><dt><span>x_end :</span></dt><dd>1110</dd><dt><span>y_end :</span></dt><dd>1025</dd><dt><span>y_start :</span></dt><dd>725</dd><dt><span>x_center :</span></dt><dd>960</dd><dt><span>y_center :</span></dt><dd>875</dd><dt><span>x_span :</span></dt><dd>300</dd><dt><span>y_span :</span></dt><dd>300</dd></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (runs: 5, truncation_value: 11)\n",
"Coordinates:\n",
" * runs (runs) float64 0.0 1.0 2.0 3.0 4.0\n",
" * truncation_value (truncation_value) float64 0.8 0.83 0.85 ... 0.97 0.99 1.0\n",
"Data variables:\n",
" A_amplitude (runs, truncation_value) float64 41.35 8.536 ... 4.752\n",
" A_centerx (runs, truncation_value) float64 1.373 0.4656 ... 0.0426\n",
" A_centery (runs, truncation_value) float64 1.829 0.7057 ... 0.1419\n",
" A_sigmax (runs, truncation_value) float64 2.502 0.6067 ... 0.05853\n",
" A_sigmay (runs, truncation_value) float64 2.561 0.8023 ... 0.139\n",
" B_amplitude (runs, truncation_value) float64 38.55 11.89 ... 6.328\n",
" B_centerx (runs, truncation_value) float64 0.271 0.2215 ... 0.5065\n",
" B_centery (runs, truncation_value) float64 0.3084 0.239 ... 0.5433\n",
" B_sigmax (runs, truncation_value) float64 0.473 0.2884 ... 0.6838\n",
" B_sigmay (runs, truncation_value) float64 0.4067 0.2715 ... 0.5322\n",
" delta (runs, truncation_value) float64 2.199 0.5443 ... 0.6551\n",
"Attributes:\n",
" IMAGE_SUBCLASS: IMAGE_GRAYSCALE\n",
" IMAGE_VERSION: 1.2\n",
" IMAGE_WHITE_IS_ZERO: 0\n",
" x_start: 810\n",
" x_end: 1110\n",
" y_end: 1025\n",
" y_start: 725\n",
" x_center: 960\n",
" y_center: 875\n",
" x_span: 300\n",
" y_span: 300"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"std = fitAnalyser.get_fit_std(fitResult)\n",
"std"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Work with uncertainties"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Sometimes we will do some other calculation based on the fit result. It is always a little bit tricky to calculate the error propagation. Fortunately, there is a package provide a solution to deal with it, please have a look of the following link.\n",
"\n",
"https://pythonhosted.org/uncertainties/\n",
"\n",
"We can also read the fit results as a format combining the value and standard deviation, which is used in the above package. Such a format allows us to do the basic calculation with auto-calculated error propagation."
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
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" --xr-background-color: var(--jp-layout-color0, white);\n",
" --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
" --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
"}\n",
"\n",
"html[theme=dark],\n",
"body[data-theme=dark],\n",
"body.vscode-dark {\n",
" --xr-font-color0: rgba(255, 255, 255, 1);\n",
" --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
" --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
" --xr-border-color: #1F1F1F;\n",
" --xr-disabled-color: #515151;\n",
" --xr-background-color: #111111;\n",
" --xr-background-color-row-even: #111111;\n",
" --xr-background-color-row-odd: #313131;\n",
"}\n",
"\n",
".xr-wrap {\n",
" display: block !important;\n",
" min-width: 300px;\n",
" max-width: 700px;\n",
"}\n",
"\n",
".xr-text-repr-fallback {\n",
" /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
" display: none;\n",
"}\n",
"\n",
".xr-header {\n",
" padding-top: 6px;\n",
" padding-bottom: 6px;\n",
" margin-bottom: 4px;\n",
" border-bottom: solid 1px var(--xr-border-color);\n",
"}\n",
"\n",
".xr-header > div,\n",
".xr-header > ul {\n",
" display: inline;\n",
" margin-top: 0;\n",
" margin-bottom: 0;\n",
"}\n",
"\n",
".xr-obj-type,\n",
".xr-array-name {\n",
" margin-left: 2px;\n",
" margin-right: 10px;\n",
"}\n",
"\n",
".xr-obj-type {\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-sections {\n",
" padding-left: 0 !important;\n",
" display: grid;\n",
" grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
"}\n",
"\n",
".xr-section-item {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-section-item input {\n",
" display: none;\n",
"}\n",
"\n",
".xr-section-item input + label {\n",
" color: var(--xr-disabled-color);\n",
"}\n",
"\n",
".xr-section-item input:enabled + label {\n",
" cursor: pointer;\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-section-item input:enabled + label:hover {\n",
" color: var(--xr-font-color0);\n",
"}\n",
"\n",
".xr-section-summary {\n",
" grid-column: 1;\n",
" color: var(--xr-font-color2);\n",
" font-weight: 500;\n",
"}\n",
"\n",
".xr-section-summary > span {\n",
" display: inline-block;\n",
" padding-left: 0.5em;\n",
"}\n",
"\n",
".xr-section-summary-in:disabled + label {\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
".xr-section-summary-in + label:before {\n",
" display: inline-block;\n",
" content: 'â–º';\n",
" font-size: 11px;\n",
" width: 15px;\n",
" text-align: center;\n",
"}\n",
"\n",
".xr-section-summary-in:disabled + label:before {\n",
" color: var(--xr-disabled-color);\n",
"}\n",
"\n",
".xr-section-summary-in:checked + label:before {\n",
" content: 'â–¼';\n",
"}\n",
"\n",
".xr-section-summary-in:checked + label > span {\n",
" display: none;\n",
"}\n",
"\n",
".xr-section-summary,\n",
".xr-section-inline-details {\n",
" padding-top: 4px;\n",
" padding-bottom: 4px;\n",
"}\n",
"\n",
".xr-section-inline-details {\n",
" grid-column: 2 / -1;\n",
"}\n",
"\n",
".xr-section-details {\n",
" display: none;\n",
" grid-column: 1 / -1;\n",
" margin-bottom: 5px;\n",
"}\n",
"\n",
".xr-section-summary-in:checked ~ .xr-section-details {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-array-wrap {\n",
" grid-column: 1 / -1;\n",
" display: grid;\n",
" grid-template-columns: 20px auto;\n",
"}\n",
"\n",
".xr-array-wrap > label {\n",
" grid-column: 1;\n",
" vertical-align: top;\n",
"}\n",
"\n",
".xr-preview {\n",
" color: var(--xr-font-color3);\n",
"}\n",
"\n",
".xr-array-preview,\n",
".xr-array-data {\n",
" padding: 0 5px !important;\n",
" grid-column: 2;\n",
"}\n",
"\n",
".xr-array-data,\n",
".xr-array-in:checked ~ .xr-array-preview {\n",
" display: none;\n",
"}\n",
"\n",
".xr-array-in:checked ~ .xr-array-data,\n",
".xr-array-preview {\n",
" display: inline-block;\n",
"}\n",
"\n",
".xr-dim-list {\n",
" display: inline-block !important;\n",
" list-style: none;\n",
" padding: 0 !important;\n",
" margin: 0;\n",
"}\n",
"\n",
".xr-dim-list li {\n",
" display: inline-block;\n",
" padding: 0;\n",
" margin: 0;\n",
"}\n",
"\n",
".xr-dim-list:before {\n",
" content: '(';\n",
"}\n",
"\n",
".xr-dim-list:after {\n",
" content: ')';\n",
"}\n",
"\n",
".xr-dim-list li:not(:last-child):after {\n",
" content: ',';\n",
" padding-right: 5px;\n",
"}\n",
"\n",
".xr-has-index {\n",
" font-weight: bold;\n",
"}\n",
"\n",
".xr-var-list,\n",
".xr-var-item {\n",
" display: contents;\n",
"}\n",
"\n",
".xr-var-item > div,\n",
".xr-var-item label,\n",
".xr-var-item > .xr-var-name span {\n",
" background-color: var(--xr-background-color-row-even);\n",
" margin-bottom: 0;\n",
"}\n",
"\n",
".xr-var-item > .xr-var-name:hover span {\n",
" padding-right: 5px;\n",
"}\n",
"\n",
".xr-var-list > li:nth-child(odd) > div,\n",
".xr-var-list > li:nth-child(odd) > label,\n",
".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
" background-color: var(--xr-background-color-row-odd);\n",
"}\n",
"\n",
".xr-var-name {\n",
" grid-column: 1;\n",
"}\n",
"\n",
".xr-var-dims {\n",
" grid-column: 2;\n",
"}\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: (runs: 5, truncation_value: 11)\n",
"Coordinates:\n",
" * runs (runs) float64 0.0 1.0 2.0 3.0 4.0\n",
" * truncation_value (truncation_value) float64 0.8 0.83 0.85 ... 0.97 0.99 1.0\n",
"Data variables:\n",
" A_amplitude (runs, truncation_value) object (9+/-4)e+01 ... 206+/-5\n",
" A_centerx (runs, truncation_value) object 147.4+/-1.4 ... 152.82+...\n",
" A_centery (runs, truncation_value) object 151.3+/-1.8 ... 150.44+...\n",
" A_sigmax (runs, truncation_value) object 15.9+/-2.5 ... 3.96+/-0.06\n",
" A_sigmay (runs, truncation_value) object 19.1+/-2.6 ... 10.61+/-...\n",
" B_amplitude (runs, truncation_value) object (1.78+/-0.04)e+03 ... 1...\n",
" B_centerx (runs, truncation_value) object 149.77+/-0.27 ... 154.1...\n",
" B_centery (runs, truncation_value) object 147.45+/-0.31 ... 150.4...\n",
" B_sigmax (runs, truncation_value) object 32.5+/-0.5 ... 15.9+/-0.7\n",
" B_sigmay (runs, truncation_value) object 33.3+/-0.4 ... 13.8+/-0.5\n",
" delta (runs, truncation_value) object -16.7+/-2.2 ... -11.9+/...\n",
"Attributes:\n",
" IMAGE_SUBCLASS: IMAGE_GRAYSCALE\n",
" IMAGE_VERSION: 1.2\n",
" IMAGE_WHITE_IS_ZERO: 0\n",
" x_start: 810\n",
" x_end: 1110\n",
" y_end: 1025\n",
" y_start: 725\n",
" x_center: 960\n",
" y_center: 875\n",
" x_span: 300\n",
" y_span: 300</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-4344dd9f-2c32-4782-972b-615de4b21a48' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-4344dd9f-2c32-4782-972b-615de4b21a48' 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'>runs</span>: 5</li><li><span class='xr-has-index'>truncation_value</span>: 11</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-5843a6d4-c2c8-40a5-bd42-74b0414d3d9d' class='xr-section-summary-in' type='checkbox' checked><label for='section-5843a6d4-c2c8-40a5-bd42-74b0414d3d9d' class='xr-section-summary' >Coordinates: <span>(2)</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'>runs</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.0 2.0 3.0 4.0</div><input id='attrs-08016d88-eee0-43ce-8e14-fd80748ebacf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-08016d88-eee0-43ce-8e14-fd80748ebacf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e4f1c10f-2f72-4950-8614-86842c904efe' class='xr-var-data-in' type='checkbox'><label for='data-e4f1c10f-2f72-4950-8614-86842c904efe' 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., 1., 2., 3., 4.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>truncation_value</span></div><div class='xr-var-dims'>(truncation_value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.8 0.83 0.85 ... 0.97 0.99 1.0</div><input id='attrs-857cbbe0-a4b4-442e-a2f1-35a5ffc4f275' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-857cbbe0-a4b4-442e-a2f1-35a5ffc4f275' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ec4b3cf9-9b40-4588-9c45-ddc4d5c30a0d' class='xr-var-data-in' type='checkbox'><label for='data-ec4b3cf9-9b40-4588-9c45-ddc4d5c30a0d' 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([0.8 , 0.83, 0.85, 0.87, 0.89, 0.91, 0.93, 0.95, 0.97, 0.99, 1. ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b0f445e3-e28a-4d74-89a6-a4839a11e398' class='xr-section-summary-in' type='checkbox' checked><label for='section-b0f445e3-e28a-4d74-89a6-a4839a11e398' class='xr-section-summary' >Data variables: <span>(11)</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>A_amplitude</span></div><div class='xr-var-dims'>(runs, truncation_value)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>(9+/-4)e+01 74+/-9 ... 206+/-5</div><input id='attrs-40e7dd60-3c37-448c-bd1b-316d9402b3ca' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-40e7dd60-3c37-448c-bd1b-316d9402b3ca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0a38ab3c-af99-463d-9545-f7d571dd2ef7' class='xr-var-data-in' type='checkbox'><label for='data-0a38ab3c-af99-463d-9545-f7d571dd2ef7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href
" 73.76056456492633+/-8.535927522067164,\n",
" 61.257178931708154+/-3.548925202189388,\n",
" 82.02977417551669+/-3.3663082751567805,\n",
" 89.85174968215657+/-3.4158821755431874,\n",
" 89.98098096512223+/-3.23781730660918,\n",
" 109.52351131461167+/-3.6391211539802413,\n",
" 97.58957784582442+/-3.5501603222143956,\n",
" 532.1895081768257+/-7.241586013893313,\n",
" 171.6467006741975+/-4.002954910436906,\n",
" 214.73142279127188+/-3.938892040945838],\n",
" [148.41500588322282+/-39.09039397852023,\n",
" 145.6150282175172+/-24.24722259598128,\n",
" 94.92340957918049+/-7.317049959454216,\n",
" 72.2190561335944+/-3.602122607106354,\n",
" 84.25138954461792+/-3.212287686069062,\n",
" 100.46822241664755+/-3.3951447205932093,\n",
" 110.93503998583688+/-3.507212402944828,\n",
" 78.36838557204585+/-3.162498086748741,\n",
" 94.33703707558132+/-15.15014763423152,\n",
"...\n",
" 96.68708012170059+/-6.832792897384724,\n",
" 70.77678060058007+/-3.475100062592538,\n",
" 87.10001164030419+/-3.5469539243783808,\n",
" 103.46997628689134+/-3.5294384853516183,\n",
" 95.1466356044004+/-3.1984353903335845,\n",
" 94.06124781232714+/-3.667428798184913,\n",
" 485.1317253372093+/-9.461909478029698,\n",
" 152.33301794466743+/-3.8137756002898264,\n",
" 288.72901879236593+/-2.314266246252939],\n",
" [104.31036272198831+/-23.361802886643076,\n",
" 68.66710998399797+/-5.920332039818534,\n",
" 61.12873582156941+/-3.423915790119221,\n",
" 85.32616375119623+/-4.160768278472826,\n",
" 74.21429556583232+/-3.0320760617498426,\n",
" 87.74512330543023+/-3.0469297136967626,\n",
" 102.52553580448769+/-3.4034296132718564,\n",
" 85.74671110287964+/-3.488683162453253,\n",
" 274.83792979180555+/-78.00226286239986,\n",
" 190.9945240324237+/-4.164925399776236,\n",
" 206.32857438484933+/-4.751755957006824]], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>A_centerx</span></div><div class='xr-var-dims'>(runs, truncation_value)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>147.4+/-1.4 ... 152.82+/-0.04</div><input id='attrs-74e8238b-baf2-45b4-a5d4-fb3ef4b27dc7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-74e8238b-baf2-45b4-a5d4-fb3ef4b27dc7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e20630c5-4fcd-4076-a55e-1756d99e647f' class='xr-var-data-in' type='checkbox'><label for='data-e20630c5-4fcd-4076-a55e-1756d99e647f' 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([[147.35658257446002+/-1.3727527054893753,\n",
" 151.44869095052894+/-0.46564767393578377,\n",
" 151.03280367252364+/-0.1783507013649013,\n",
" 149.7253195308006+/-0.11981297817175503,\n",
" 151.21663764283258+/-0.10298812814823738,\n",
" 150.79959828326716+/-0.0889959478195437,\n",
" 149.2256681578159+/-0.08702270426730412,\n",
" 149.7313670843037+/-0.09711865256312112,\n",
" 152.01462231664286+/-0.3022471120886092,\n",
" 152.02274818241068+/-0.04919933765157741,\n",
" 152.97453587929408+/-0.03767387506666367],\n",
" [151.75284936211438+/-0.8345906186483887,\n",
" 154.79722431154462+/-0.6396424877756492,\n",
" 151.44589411579776+/-0.28050157348926474,\n",
" 150.38113633168228+/-0.13988075734953734,\n",
" 150.2022338375022+/-0.10183172113123262,\n",
" 151.19054749940534+/-0.08559290605354591,\n",
" 152.34142813146076+/-0.07848608231447052,\n",
" 150.97350460226963+/-0.09560750185351725,\n",
" 152.99632453327143+/-0.5328864545667023,\n",
"...\n",
" 151.87197238230672+/-0.2650354017933109,\n",
" 150.03042241372953+/-0.14280239154843152,\n",
" 151.42003475333627+/-0.11040200813326806,\n",
" 151.07674412829488+/-0.08525170503495666,\n",
" 150.5342452365423+/-0.08422186783334362,\n",
" 151.3627544004239+/-0.09946159371013555,\n",
" 151.2741147718366+/-0.33900843850129,\n",
" 151.47655710177486+/-0.05097848104685737,\n",
" 151.82911295821808+/-0.0376317887719723],\n",
" [154.2747885416835+/-0.7888825946165041,\n",
" 151.6308744083375+/-0.3490114633756347,\n",
" 151.20635115439393+/-0.16877678965988724,\n",
" 150.81624618296868+/-0.1536102364155593,\n",
" 150.73325793391044+/-0.1114052016597937,\n",
" 148.60106673995304+/-0.0881201390010303,\n",
" 150.35065806595094+/-0.08422454423638877,\n",
" 150.9896251643052+/-0.10064893067132687,\n",
" 152.7989112936687+/-0.514154485578547,\n",
" 151.74830745233456+/-0.042941267689209,\n",
" 152.81634248533373+/-0.04259848135736634]], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>A_centery</span></div><div class='xr-var-dims'>(runs, truncation_value)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>151.3+/-1.8 ... 150.44+/-0.14</div><input id='attrs-1e64b272-050b-49de-ba36-dc2e32c68f53' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1e64b272-050b-49de-ba36-dc2e32c68f53' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b17c331-ee8d-4448-a550-f7d523747cbb' class='xr-var-data-in' type='checkbox'><label for='data-9b17c331-ee8d-4448-a550-f7d523747cbb' 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([[151.2839458880331+/-1.829316824826828,\n",
" 147.24150185539412+/-0.7057022055683831,\n",
" 148.72611408598524+/-0.4287679333158799,\n",
" 148.71669934795293+/-0.2906549150884485,\n",
" 148.86331632657718+/-0.3015362509148028,\n",
" 150.16395069449482+/-0.26494553118252956,\n",
" 152.87180324947852+/-0.22368236905733271,\n",
" 143.01228826995762+/-0.22421097705528029,\n",
" 157.30707731491353+/-0.30777979465210936,\n",
" 156.69107701383817+/-0.13240613124440306,\n",
" 149.80082720386957+/-0.10918892136983431],\n",
" [150.2353128160028+/-0.9443184698534371,\n",
" 148.20649663059598+/-0.6077866042533147,\n",
" 149.39950181507152+/-0.49261835893511763,\n",
" 151.05181870977842+/-0.3936541988812647,\n",
" 150.6892262907698+/-0.27748013289873646,\n",
" 150.92349357189585+/-0.25035212776538496,\n",
" 148.74791296331952+/-0.22946575835233796,\n",
" 155.7045196294939+/-0.249859078062335,\n",
" 169.9664204384583+/-0.6297845568899584,\n",
"...\n",
" 149.30281946475702+/-0.46076191899923064,\n",
" 148.1772004682875+/-0.34495894989135467,\n",
" 150.10029746821937+/-0.3017296102983003,\n",
" 151.3043077505104+/-0.2559252968471558,\n",
" 149.08990239453158+/-0.215114811025664,\n",
" 150.8501386570686+/-0.2554587494591535,\n",
" 151.3836069099311+/-0.33295279971308983,\n",
" 148.76234516326355+/-0.17058155609199388,\n",
" 151.38588399417014+/-0.08620530926662816],\n",
" [148.80726574592722+/-1.0756701266594844,\n",
" 148.31953845670276+/-0.46326371332000216,\n",
" 148.60253327910877+/-0.4302549246697413,\n",
" 147.80272439794774+/-0.34692409930889195,\n",
" 147.19073079699558+/-0.28673675578233065,\n",
" 149.1864850926175+/-0.2587284706312692,\n",
" 150.498340471091+/-0.23708082117490248,\n",
" 151.8053780485012+/-0.2547870001155802,\n",
" 140.14296659241558+/-2.5996023423082417,\n",
" 151.29080636002382+/-0.13666223487686108,\n",
" 150.43594967254194+/-0.14190089144102574]], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>A_sigmax</span></div><div class='xr-var-dims'>(runs, truncation_value)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>15.9+/-2.5 ... 3.96+/-0.06</div><input id='attrs-bc193415-d6ab-41c6-a8a2-ef3305a27ddf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bc193415-d6ab-41c6-a8a2-ef3305a27ddf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b33860b-96f0-44d1-b593-dfe2e7c001e9' class='xr-var-data-in' type='checkbox'><label for='data-7b33860b-96f0-44d1-b593-dfe2e7c001e9' 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([[15.860336835731808+/-2.5021081546034893,\n",
" 9.018467496192105+/-0.606732407563129,\n",
" 4.671421736925886+/-0.20515777361639356,\n",
" 4.444623316201177+/-0.13801476004470056,\n",
" 4.145287320373015+/-0.1199541728852385,\n",
" 3.8231273472551983+/-0.10400530613636956,\n",
" 4.3241644194841875+/-0.10431080227895158,\n",
" 4.506680224739807+/-0.11584280883254539,\n",
" 22.212458660785703+/-0.30224870174417107,\n",
" 4.0287539334186135+/-0.06311101542301505,\n",
" 3.9039003515907726+/-0.04876892597551594],\n",
" [16.653667019295312+/-1.4437167238759603,\n",
" 15.084379675398349+/-0.9092095384366196,\n",
" 7.7982412554339255+/-0.3640561142872948,\n",
" 4.314433981664749+/-0.1629232234084342,\n",
" 4.020823153078126+/-0.11745136965738474,\n",
" 3.9213352831433568+/-0.10021902891354785,\n",
" 4.017325472614189+/-0.09383076587235913,\n",
" 3.776071153651131+/-0.1124106923238107,\n",
" 11.70680121384749+/-0.7390150721343427,\n",
"...\n",
" 7.612027541518859+/-0.33653577135445556,\n",
" 4.5039905455406455+/-0.1656196856578219,\n",
" 4.2062885767719+/-0.12882167808361056,\n",
" 3.9330735877390737+/-0.10061599254862207,\n",
" 3.9488846592325046+/-0.09861942576151124,\n",
" 4.251955586666529+/-0.11933153818889743,\n",
" 22.373128656916833+/-0.3622015556659721,\n",
" 3.720319094626557+/-0.06483756288852549,\n",
" 4.699541128694051+/-0.037641814669170104],\n",
" [13.661759397609686+/-1.2674652565314353,\n",
" 7.789260527342016+/-0.4234868285408567,\n",
" 4.483763473600636+/-0.19301044345619955,\n",
" 5.160747578953156+/-0.18167604331615717,\n",
" 3.9975751871867793+/-0.12668018803960593,\n",
" 3.787085333696158+/-0.10143472217957544,\n",
" 4.043231617488043+/-0.09968957711142692,\n",
" 4.100812298258319+/-0.12014094196012937,\n",
" 19.824710290576512+/-0.6825701511655348,\n",
" 3.7811651866446265+/-0.05553421500376992,\n",
" 3.963895272850106+/-0.05853343916600622]], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>A_sigmay</span></div><div class='xr-var-dims'>(runs, truncation_value)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>19.1+/-2.6 ... 10.61+/-0.14</div><input id='attrs-0b8d67f5-4d74-4663-bf80-a4c45d64c356' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0b8d67f5-4d74-4663-bf80-a4c45d64c356' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dce98f8e-10de-4022-9703-f5fe33b3b30c' class='xr-var-data-in' type='checkbox'><label for='data-dce98f8e-10de-4022-9703-f5fe33b3b30c' 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([[19.126006486369683+/-2.5607291299158637,\n",
" 13.119794267117575+/-0.8023442905278281,\n",
" 10.79097924824702+/-0.4439656474092933,\n",
" 10.354469293064817+/-0.30092614792472977,\n",
" 11.454405296800097+/-0.3051213556570911,\n",
" 10.752939752477435+/-0.26858687782067064,\n",
" 10.390752947106503+/-0.22733818612185655,\n",
" 9.298550649701577+/-0.2196602389094534,\n",
" 22.619165465336945+/-0.3077810340161551,\n",
" 9.460627742638442+/-0.1288417515253295,\n",
" 9.6189307408148+/-0.10648424134429936],\n",
" [18.374138350020697+/-1.517950737084869,\n",
" 14.936420540217329+/-0.9471539050808155,\n",
" 12.972327097886307+/-0.5408199120650325,\n",
" 11.47917760686184+/-0.4001348715733418,\n",
" 10.435889924376486+/-0.28305136725573543,\n",
" 10.791808861647066+/-0.25275273588514435,\n",
" 10.863662998552966+/-0.22965697771003002,\n",
" 9.270680493013959+/-0.2541391247466058,\n",
" 10.979091638792877+/-0.7266854575756488,\n",
"...\n",
" 12.600570000896163+/-0.5036529791730312,\n",
" 10.429107618337827+/-0.3571106868420577,\n",
" 10.897669432195974+/-0.30797540682504954,\n",
" 10.981002964990902+/-0.2561296351087414,\n",
" 9.549226478110224+/-0.21997047640261871,\n",
" 9.966767446151533+/-0.25373163492629236,\n",
" 21.968583265840405+/-0.3555478533974791,\n",
" 10.68052953879806+/-0.16478861899855546,\n",
" 10.765449283022289+/-0.08622270074293793],\n",
" [17.44929619108874+/-1.3925028858428408,\n",
" 10.166405949335147+/-0.528953438850541,\n",
" 10.999618091486422+/-0.443455312003405,\n",
" 11.148575256656544+/-0.36205788812693357,\n",
" 9.91124249592798+/-0.2953721655725335,\n",
" 10.542925339671095+/-0.2620378579986912,\n",
" 10.611624609563744+/-0.23873927602698705,\n",
" 9.716275435636975+/-0.2600158872682979,\n",
" 14.77240983837925+/-0.9833052433004487,\n",
" 10.359695621100855+/-0.1329249314196161,\n",
" 10.607666958514722+/-0.13899744396105262]], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>B_amplitude</span></div><div class='xr-var-dims'>(runs, truncation_value)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>(1.78+/-0.04)e+03 ... 160+/-6</div><input id='attrs-23e0e7cf-49de-4aa6-b03c-dc0302213f97' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-23e0e7cf-49de-4aa6-b03c-dc0302213f97' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3d11d29a-567b-40df-a432-d165a4068abc' class='xr-var-data-in' type='checkbox'><label for='data-3d11d29a-567b-40df-a432-d165a4068abc' 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([[1783.4505470093975+/-38.55474973769937,\n",
" 1583.367955386121+/-11.892410719723728,\n",
" 1294.1427246760277+/-9.326973981614957,\n",
" 1085.9674567041911+/-8.783896864768144,\n",
" 980.3033258172821+/-8.429966556153339,\n",
" 710.702545557956+/-7.851059274540122,\n",
" 589.9431966374505+/-7.770632709507968,\n",
" 473.6037191028235+/-7.198748788486686,\n",
" -1554.9574848078128+/-91836.96989438758,\n",
" 223.9167276316795+/-6.305200864349702,\n",
" 153.32675239662007+/-6.104340830252059],\n",
" [1755.5747376929044+/-35.97886207410223,\n",
" 1618.712591762719+/-22.713267269709537,\n",
" 1455.2114896338119+/-10.746029604517,\n",
" 1097.0352831402772+/-8.890385556296682,\n",
" 917.6837114638918+/-8.362600170019222,\n",
" 730.4978430623682+/-8.136652692366296,\n",
" 583.1595447189275+/-7.587750849207557,\n",
" 495.27277533409085+/-7.306841284510048,\n",
" 369.5146250235052+/-16.805097603928182,\n",
"...\n",
" 1353.9955834116154+/-10.850148732917633,\n",
" 1030.3350401966509+/-8.716777971851396,\n",
" 892.0056163932509+/-8.657502915041901,\n",
" 615.6802280993078+/-8.092731400749054,\n",
" 575.5395324819432+/-7.5887730085928355,\n",
" 520.7789829789416+/-7.603578399475881,\n",
" -12794.637702111053+/-923104.8373638523,\n",
" 247.6351822842168+/-6.328162695401922,\n",
" -512.4111408505026+/-13524.384447726974],\n",
" [1787.5274474744454+/-22.189251882576485,\n",
" 1413.597738337935+/-10.371305429807931,\n",
" 1283.832182854877+/-9.343101011967025,\n",
" 1131.8991436071396+/-9.366865538228117,\n",
" 932.4473976857394+/-8.552442430499893,\n",
" 739.288454628114+/-7.979421151379551,\n",
" 576.1758576932972+/-7.696940957083554,\n",
" 518.6705061896287+/-7.495301326668071,\n",
" 187.26884653862214+/-77.67429575991974,\n",
" 171.93192998540695+/-6.4616039587037255,\n",
" 159.92341651165464+/-6.327691705966064]], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>B_centerx</span></div><div class='xr-var-dims'>(runs, truncation_value)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>149.77+/-0.27 ... 154.1+/-0.5</div><input id='attrs-411b2026-35e3-4664-bc7e-f0e347337729' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-411b2026-35e3-4664-bc7e-f0e347337729' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-009586f2-5a6f-4364-a6c0-f7667b858d2c' class='xr-var-data-in' type='checkbox'><label for='data-009586f2-5a6f-4364-a6c0-f7667b858d2c' 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([[149.77259545393022+/-0.27096348676646426,\n",
" 152.02155216390227+/-0.22148269407960736,\n",
" 150.8222695321032+/-0.19755170611071138,\n",
" 150.17856412475348+/-0.21034549276886044,\n",
" 151.4986944484829+/-0.21334349930537377,\n",
" 151.00882072021355+/-0.24806824373703065,\n",
" 150.00017539111465+/-0.2976365030176029,\n",
" 151.20563350417447+/-0.311270572264415,\n",
" 425.4471671031649+/-1917.7805245346653,\n",
" 155.07081347632086+/-0.46225830704668547,\n",
" 155.3787526785979+/-0.6264418193400905],\n",
" [152.18376687383596+/-0.27373614491648834,\n",
" 151.414467596611+/-0.26281873956518004,\n",
" 151.87836658004133+/-0.20284705179516455,\n",
" 150.5499589871522+/-0.20676194813000695,\n",
" 150.2322143691497+/-0.2244416046644352,\n",
" 152.14621363068946+/-0.2565581879939017,\n",
" 152.7295139777507+/-0.2847083747967142,\n",
" 151.07172615399887+/-0.30162250219933945,\n",
" 150.89663936186258+/-0.5334846846113871,\n",
"...\n",
" 151.57847362564357+/-0.22890926244357485,\n",
" 150.2195483641291+/-0.21618139659893149,\n",
" 151.4109399624761+/-0.235932668005744,\n",
" 150.73394378755532+/-0.29432684086616645,\n",
" 151.18173903724954+/-0.2884499465467387,\n",
" 151.31132354357783+/-0.31004697264860187,\n",
" 1794.4009458057362+/-78318.32418180678,\n",
" 152.9130188171137+/-0.41183695977305995,\n",
" -123.18365954603638+/-1398.15877037124],\n",
" [152.47370923950172+/-0.2486828343301986,\n",
" 151.44312867338033+/-0.2109439779557269,\n",
" 151.13645268574652+/-0.20094686366985717,\n",
" 151.59289508417712+/-0.2201607104828267,\n",
" 151.67957651879482+/-0.23165158459947108,\n",
" 149.82793656812112+/-0.25591905182754016,\n",
" 149.77567428775137+/-0.2994586149660122,\n",
" 151.2174755930937+/-0.3020407969189618,\n",
" 151.16624064977492+/-0.9824896717820301,\n",
" 154.17608172674252+/-0.5714303239307091,\n",
" 154.05517933635204+/-0.5064735148698376]], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>B_centery</span></div><div class='xr-var-dims'>(runs, truncation_value)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>147.45+/-0.31 ... 150.4+/-0.5</div><input id='attrs-187f4cc8-d75c-4867-8c4c-8861cb5c299a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-187f4cc8-d75c-4867-8c4c-8861cb5c299a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a08c4711-ccb1-4870-8b4d-22b9740e6c7e' class='xr-var-data-in' type='checkbox'><label for='data-a08c4711-ccb1-4870-8b4d-22b9740e6c7e' 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([[147.45295194989208+/-0.3083522659603334,\n",
" 148.0974665141219+/-0.23899123902231514,\n",
" 150.0254999984521+/-0.2115835357552914,\n",
" 149.1469112936274+/-0.2266346164778228,\n",
" 148.98258536603274+/-0.22975888030022823,\n",
" 150.22718775974442+/-0.2785958264264556,\n",
" 153.16129423629363+/-0.3116204227058065,\n",
" 152.81932316502167+/-0.33982010636279714,\n",
" 72.24418703843509+/-12.330596902301377,\n",
" 154.5299104123529+/-0.45518573723845307,\n",
" 149.1702283127959+/-0.5836771903943897],\n",
" [149.47572525757352+/-0.29485909692154016,\n",
" 149.34656246875323+/-0.26143084641374137,\n",
" 149.83533472058832+/-0.22511797664478206,\n",
" 150.93254944051256+/-0.22307635764982814,\n",
" 151.0103052434597+/-0.23695400685424034,\n",
" 151.51733987577816+/-0.27476760011999973,\n",
" 147.49311189893734+/-0.3002763416325275,\n",
" 151.61473460452595+/-0.33615658279736677,\n",
" 153.7661835957186+/-1.0864067205456087,\n",
"...\n",
" 150.01635145341498+/-0.24932597628425426,\n",
" 149.5815498283574+/-0.23470396165839805,\n",
" 151.26380613376625+/-0.2587174898144533,\n",
" 148.55592561413462+/-0.3170695888085809,\n",
" 152.23705055274704+/-0.3139672552811612,\n",
" 144.97313414989264+/-0.3282952463322462,\n",
" 299.4249608202302+/-607.1323233790305,\n",
" 151.1590325930633+/-0.44674574397002587,\n",
" 200.0748241237876+/-24.431965173791674],\n",
" [149.28876670902272+/-0.26979085358778726,\n",
" 148.6408718726947+/-0.22420720694200333,\n",
" 148.86311139139536+/-0.21578758550038865,\n",
" 148.44094162412216+/-0.2414859011353413,\n",
" 147.56308141548737+/-0.24784465508352876,\n",
" 151.31740191299292+/-0.2754322281706898,\n",
" 147.95630348736913+/-0.32007558373254436,\n",
" 155.44600839693098+/-0.3382865907816203,\n",
" 166.00908445801264+/-6.717796250609652,\n",
" 149.67457383448772+/-0.6314718091955727,\n",
" 150.43124106556053+/-0.5433261146137754]], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>B_sigmax</span></div><div class='xr-var-dims'>(runs, truncation_value)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>32.5+/-0.5 ... 15.9+/-0.7</div><input id='attrs-a27368e1-efad-46e4-82f8-4240ec8eb04a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a27368e1-efad-46e4-82f8-4240ec8eb04a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-84a9331b-c99d-46b6-b38b-51c626fcf1a8' class='xr-var-data-in' type='checkbox'><label for='data-84a9331b-c99d-46b6-b38b-51c626fcf1a8' 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([[32.53497079822689+/-0.4729615678127935,\n",
" 31.39433096134706+/-0.2883597660897553,\n",
" 27.643288171180245+/-0.22722929612378928,\n",
" 26.227635309821252+/-0.242215079373659,\n",
" 25.30006204520641+/-0.24844985350259502,\n",
" 22.900702355023153+/-0.2898735566478717,\n",
" 23.220101308005322+/-0.35615734285732503,\n",
" 21.563179231474496+/-0.3665900983003838,\n",
" 51.04673134380755+/-343.2370769196211,\n",
" 17.58633398430754+/-0.5556884176691106,\n",
" 17.494927389164523+/-0.7770989611534336],\n",
" [33.27712832852207+/-0.4728368175211743,\n",
" 31.1350729081485+/-0.3562746682075235,\n",
" 29.13042226831489+/-0.26313093900657836,\n",
" 25.960019384669543+/-0.24080887611530888,\n",
" 24.965313874296477+/-0.2588675239478265,\n",
" 23.519682936958166+/-0.2997456340724818,\n",
" 22.63545942144049+/-0.34021985632083396,\n",
" 20.887985590808885+/-0.3545746537691722,\n",
" 23.14105763123112+/-0.6440119243670632,\n",
"...\n",
" 29.76446379821113+/-0.29060414998946255,\n",
" 25.822392335045908+/-0.2507063659517471,\n",
" 24.71819699048615+/-0.27529596902284525,\n",
" 23.039486967672275+/-0.3472574601189607,\n",
" 22.25809162293119+/-0.3373670754724408,\n",
" 22.097058341555595+/-0.3717417248274327,\n",
" 1103.6156392167222+/-26980.486228359703,\n",
" 17.762080960812995+/-0.5166736295628915,\n",
" 69.21926427808638+/-320.1224187246483],\n",
" [33.295736175881146+/-0.39347688902135264,\n",
" 29.073070074031243+/-0.2559391676376474,\n",
" 27.83726355324668+/-0.22979802433386118,\n",
" 26.949990282352264+/-0.260081186416113,\n",
" 25.422992040483493+/-0.26302381795665986,\n",
" 24.04340187222614+/-0.29369040655816425,\n",
" 23.02812015411594+/-0.35413129538040744,\n",
" 21.432201872199876+/-0.36044358023889495,\n",
" 22.935735350744352+/-1.1215503060249485,\n",
" 16.64979816710927+/-0.704655972276601,\n",
" 15.852826148500313+/-0.6837916703649396]], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>B_sigmay</span></div><div class='xr-var-dims'>(runs, truncation_value)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>33.3+/-0.4 ... 13.8+/-0.5</div><input id='attrs-0b901c2f-be2e-458b-8d8a-42d6a9944406' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0b901c2f-be2e-458b-8d8a-42d6a9944406' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-91d41d7e-0e7c-4332-8f23-627196079fef' class='xr-var-data-in' type='checkbox'><label for='data-91d41d7e-0e7c-4332-8f23-627196079fef' 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([[33.293343342278405+/-0.4066544500984663,\n",
" 32.43099740937326+/-0.27148891867125463,\n",
" 28.472783323021986+/-0.21893197835361336,\n",
" 27.18103377926991+/-0.23462548292930036,\n",
" 25.71431975647876+/-0.23248774717835208,\n",
" 24.27199693874956+/-0.2824226488025367,\n",
" 22.770785790863183+/-0.3167053704909412,\n",
" 20.370406137999066+/-0.3155333149640038,\n",
" 25.221405440199703+/-12.353501050690598,\n",
" 15.747054930603152+/-0.4444793981872891,\n",
" 14.211775169728398+/-0.5695674047029192],\n",
" [34.99745368882624+/-0.47259930062476757,\n",
" 33.209468150285915+/-0.4049784334626913,\n",
" 30.581257424467506+/-0.24710093842031955,\n",
" 26.52760871514206+/-0.22674868214473995,\n",
" 25.116618253458665+/-0.2417035148301304,\n",
" 23.708944223278383+/-0.277383756606172,\n",
" 22.081559134612146+/-0.30050616164939203,\n",
" 21.77847573557396+/-0.3390417619506489,\n",
" 21.59150892237305+/-0.5582682518179167,\n",
"...\n",
" 30.834968586600677+/-0.27241160921173674,\n",
" 26.866610640622174+/-0.24275152442848408,\n",
" 25.70634067075639+/-0.2639614815472633,\n",
" 23.059419248253157+/-0.31709254460316105,\n",
" 22.882322357909604+/-0.319526663295368,\n",
" 21.204198371102226+/-0.3224321076860436,\n",
" 309.0143825127214+/-641.3027645024034,\n",
" 16.700709993228845+/-0.43410437753408676,\n",
" 51.10807299975128+/-25.46459121666361],\n",
" [34.22146325864612+/-0.34907122443873395,\n",
" 30.3244037985267+/-0.2559667779101596,\n",
" 28.76138497555883+/-0.22240406118282088,\n",
" 28.27677548228437+/-0.2519683873228171,\n",
" 26.241624910802816+/-0.2552945715815403,\n",
" 24.57777005543095+/-0.27866201116092393,\n",
" 22.952253804126208+/-0.32189378595400997,\n",
" 22.40814737132149+/-0.3428298294377704,\n",
" 16.893511181682335+/-2.7501875962284204,\n",
" 16.344615274167303+/-0.6158425160306178,\n",
" 13.789276360488932+/-0.5322032462465591]], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>delta</span></div><div class='xr-var-dims'>(runs, truncation_value)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>-16.7+/-2.2 ... -11.9+/-0.7</div><input id='attrs-f4f33e84-e51f-46b7-ae74-5bf33cdb13c1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f4f33e84-e51f-46b7-ae74-5bf33cdb13c1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-47885b13-3680-4b71-85b2-f557b30c924b' class='xr-var-data-in' type='checkbox'><label for='data-47885b13-3680-4b71-85b2-f557b30c924b' 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([[-16.67463396249508+/-2.1991511965119726,\n",
" -22.375863465154954+/-0.5443219620873246,\n",
" -22.97186643425436+/-0.253704497852298,\n",
" -21.783011993620075+/-0.23777241238485272,\n",
" -21.154774724833395+/-0.2367800720748362,\n",
" -19.077575007767955+/-0.2726247057851301,\n",
" -18.895936888521135+/-0.33196615114467765,\n",
" -17.05649900673469+/-0.3441976023691042,\n",
" -28.834272683021847+/-343.23605093560667,\n",
" -13.557580050888927+/-0.5311533324080612,\n",
" -13.59102703757375+/-0.7560719065618806],\n",
" [-16.623461309226755+/-1.1923530766421955,\n",
" -16.050693232750152+/-0.7999237628946209,\n",
" -21.332181012880966+/-0.3412539896993802,\n",
" -21.645585403004795+/-0.2412695647296705,\n",
" -20.94449072121835+/-0.2474486857025613,\n",
" -19.59834765381481+/-0.2815947324480169,\n",
" -18.6181339488263+/-0.3176319907249022,\n",
" -17.111914437157754+/-0.3330616258719197,\n",
" -11.434256417383631+/-0.8171745860770954,\n",
"...\n",
" -22.15243625669227+/-0.33916984349231327,\n",
" -21.318401789505263+/-0.2514613323155388,\n",
" -20.51190841371425+/-0.2617233529837117,\n",
" -19.1064133799332+/-0.325540430315436,\n",
" -18.309206963698685+/-0.3177851075106094,\n",
" -17.845102754889066+/-0.34600901125013195,\n",
" -1081.2425105598054+/-26980.56364577257,\n",
" -14.041761866186437+/-0.49144257071260145,\n",
" -64.51972314939233+/-320.12151826282064],\n",
" [-19.63397677827146+/-1.071115963987468,\n",
" -21.283809546689227+/-0.4088356591455356,\n",
" -23.353500079646043+/-0.25044616060384367,\n",
" -21.789242703399108+/-0.26016060780255845,\n",
" -21.425416853296714+/-0.255434849197033,\n",
" -20.256316538529983+/-0.278448302682127,\n",
" -18.984888536627896+/-0.3319635812417402,\n",
" -17.331389573941557+/-0.33608195940298935,\n",
" -3.11102506016784+/-1.2020712150918103,\n",
" -12.868632980464644+/-0.6813548880630336,\n",
" -11.888930875650207+/-0.6551148896497988]], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-be5b2e50-2790-4eab-b8d3-f0697bfcbf1c' class='xr-section-summary-in' type='checkbox' ><label for='section-be5b2e50-2790-4eab-b8d3-f0697bfcbf1c' class='xr-section-summary' >Indexes: <span>(2)</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>runs</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-6ba3fd40-ecb3-48eb-bf81-8f6490ad8288' class='xr-index-data-in' type='checkbox'/><label for='index-6ba3fd40-ecb3-48eb-bf81-8f6490ad8288' 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([0.0, 1.0, 2.0, 3.0, 4.0], dtype=&#x27;float64&#x27;, name=&#x27;runs&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>truncation_value</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-bba0aba8-2789-4ccd-a177-ff1b18b2ed1b' class='xr-index-data-in' type='checkbox'/><label for='index-bba0aba8-2789-4ccd-a177-ff1b18b2ed1b' 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([0.8, 0.83, 0.85, 0.87, 0.89, 0.91, 0.93, 0.95, 0.97, 0.99, 1.0], dtype=&#x27;float64&#x27;, name=&#x27;truncation_value&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-047e1c12-7ebc-4393-a5ed-cf1a1c0c1a9d' class='xr-section-summary-in' type='checkbox' ><label for='section-047e1c12-7ebc-4393-a5ed-cf1a1c0c1a9d' class='xr-section-summary' >Attributes: <span>(11)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><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><dt><span>x_start :</span></dt><dd>810</dd><dt><span>x_end :</span></dt><dd>1110</dd><dt><span>y_end :</span></dt><dd>1025</dd><dt><span>y_start :</span></dt><dd>725</dd><dt><span>x_center :</span></dt><dd>960</dd><dt><span>y_center :</span></dt><dd>875</dd><dt><span>x_span :</span></dt><dd>300</dd><dt><span>y_span :</span></dt><dd>300</dd></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (runs: 5, truncation_value: 11)\n",
"Coordinates:\n",
" * runs (runs) float64 0.0 1.0 2.0 3.0 4.0\n",
" * truncation_value (truncation_value) float64 0.8 0.83 0.85 ... 0.97 0.99 1.0\n",
"Data variables:\n",
" A_amplitude (runs, truncation_value) object (9+/-4)e+01 ... 206+/-5\n",
" A_centerx (runs, truncation_value) object 147.4+/-1.4 ... 152.82+...\n",
" A_centery (runs, truncation_value) object 151.3+/-1.8 ... 150.44+...\n",
" A_sigmax (runs, truncation_value) object 15.9+/-2.5 ... 3.96+/-0.06\n",
" A_sigmay (runs, truncation_value) object 19.1+/-2.6 ... 10.61+/-...\n",
" B_amplitude (runs, truncation_value) object (1.78+/-0.04)e+03 ... 1...\n",
" B_centerx (runs, truncation_value) object 149.77+/-0.27 ... 154.1...\n",
" B_centery (runs, truncation_value) object 147.45+/-0.31 ... 150.4...\n",
" B_sigmax (runs, truncation_value) object 32.5+/-0.5 ... 15.9+/-0.7\n",
" B_sigmay (runs, truncation_value) object 33.3+/-0.4 ... 13.8+/-0.5\n",
" delta (runs, truncation_value) object -16.7+/-2.2 ... -11.9+/...\n",
"Attributes:\n",
" IMAGE_SUBCLASS: IMAGE_GRAYSCALE\n",
" IMAGE_VERSION: 1.2\n",
" IMAGE_WHITE_IS_ZERO: 0\n",
" x_start: 810\n",
" x_end: 1110\n",
" y_end: 1025\n",
" y_start: 725\n",
" x_center: 960\n",
" y_center: 875\n",
" x_span: 300\n",
" y_span: 300"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"uval = fitAnalyser.get_fit_full_result(fitResult)\n",
"uval"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Plot the fit curve"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"In the most of cases, we need not only to know the fit result, but also plot the fit curve. Here we also provide a function to calculate the fit curve."
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 3400x1500 with 56 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fitCurve = fitAnalyser.eval(fitResult, x=np.arange(300), y=np.arange(300), dask=\"parallelized\").load()\n",
"\n",
"fitCurve.plot.pcolormesh(cmap='jet', vmin=0, col=scanAxis[0], row=scanAxis[1])\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Sometimes, the fit model contains two parts, i.e. the BEC part and the thermal part. People only want to plot one part of the result. In the following, there is an example for that."
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"f:\\Jianshun\\analyseScript\\Analyser\\FitAnalyser.py:86: RuntimeWarning: invalid value encountered in power\n",
" res = (1- ((x-centerx)/(sigmax))**2 - ((y-centery)/(sigmay))**2)**(3 / 2)\n"
]
},
{
"data": {
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"text/plain": [
"<Figure size 3400x1500 with 56 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Create a fit model for the BEC part with prefix string \n",
"# making the name of parameters as same as its in the fit reuslts.\n",
"fitModel = ThomasFermi2dModel(prefix='A_')\n",
"\n",
"fitAnalyser_BEC = FitAnalyser(fitModel, fitDim=2)\n",
"fitCurve = fitAnalyser_BEC.eval(fitResult, x=np.arange(300), y=np.arange(300), dask=\"parallelized\").load()\n",
"\n",
"fitCurve.plot.pcolormesh(cmap='jet', vmin=0, col=scanAxis[0], row=scanAxis[1])\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Creat a customized fit model"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"params.add(name=\"a\", value=-inf, max=np.inf, min=-np.inf, vary=True)\n",
"params.add(name=\"b\", value=-inf, max=np.inf, min=-np.inf, vary=True)\n"
]
}
],
"source": [
"from Analyser.FitAnalyser import NewFitModel\n",
"\n",
"\n",
"def customized_function(x, a, b):\n",
" return x * a + b\n",
"\n",
"customized_fitModel = NewFitModel(customized_function)\n",
"\n",
"customized_fitAnalyser = FitAnalyser(customized_fitModel, fitDim=1)\n",
"\n",
"customized_fitAnalyser.print_params_set_template()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "base",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.12"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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