analyseScript/20230509_Data_Analysis.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Import supporting package"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import xarray as xr\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import copy\n",
    "\n",
    "import xrft\n",
    "import finufft\n",
    "\n",
    "from uncertainties import ufloat\n",
    "from uncertainties import unumpy as unp\n",
    "from uncertainties import umath\n",
    "\n",
    "from datetime import datetime\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['font.size'] = 18\n",
    "\n",
    "from DataContainer.ReadData import read_hdf5_file, read_hdf5_global, read_hdf5_run_time\n",
    "from Analyser.ImagingAnalyser import ImageAnalyser\n",
    "from Analyser.FitAnalyser import FitAnalyser\n",
    "from ToolFunction.ToolFunction import *\n",
    "\n",
    "from ToolFunction.HomeMadeXarrayFunction import errorbar, dataarray_plot_errorbar\n",
    "xr.plot.dataarray_plot.errorbar = errorbar\n",
    "xr.plot.accessor.DataArrayPlotAccessor.errorbar = dataarray_plot_errorbar\n",
    "\n",
    "imageAnalyser = ImageAnalyser()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Start a client for parallel computing"
   ]
  },
  {
   "cell_type": "code",
   "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-784747fa-f619-11ed-8538-80e82ce2fa8e</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;\">8c306eb6</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> 24\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-a674fe0d-f3db-400a-9518-9f62a452c436</p>\n",
       "            <table style=\"width: 100%; text-align: left;\">\n",
       "                <tr>\n",
       "                    <td style=\"text-align: left;\">\n",
       "                        <strong>Comm:</strong> tcp://127.0.0.1:53300\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> 24\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://127.0.0.1:53340\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Total threads: </strong> 4\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:53342/status\" target=\"_blank\">http://127.0.0.1:53342/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://127.0.0.1:53303\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-6ewymjbd\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://127.0.0.1:53327\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Total threads: </strong> 4\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:53328/status\" target=\"_blank\">http://127.0.0.1:53328/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://127.0.0.1:53304\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-zx5fwp4m\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://127.0.0.1:53339\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Total threads: </strong> 4\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:53341/status\" target=\"_blank\">http://127.0.0.1:53341/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://127.0.0.1:53305\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-wvhmjerz\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://127.0.0.1:53331\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Total threads: </strong> 4\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:53334/status\" target=\"_blank\">http://127.0.0.1:53334/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://127.0.0.1:53306\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-tgsqxq_2\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://127.0.0.1:53336\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Total threads: </strong> 4\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:53337/status\" target=\"_blank\">http://127.0.0.1:53337/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://127.0.0.1:53307\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-l30tpttg\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://127.0.0.1:53330\n",
       "                        </td>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Total threads: </strong> 4\n",
       "                        </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <td style=\"text-align: left;\">\n",
       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:53332/status\" target=\"_blank\">http://127.0.0.1:53332/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://127.0.0.1:53308\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-mfceqxqi\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://127.0.0.1:53300' processes=6 threads=24, 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=4, processes=True, memory_limit='10GB')\n",
    "client"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Set global path for experiment"
   ]
  },
  {
   "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",
    "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",
    "}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "img_dir = '//DyLabNAS/Data/'\n",
    "SequenceName = \"Evaporative_Cooling\" + \"/\"\n",
    "folderPath = img_dir + SequenceName + \"2023/05/09\" # get_date()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Check the stability of our BEC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The detected scaning axes and values are: \n",
      "\n",
      "{'runs': array([  0.,   1.,   2.,   3.,   4.,   5.,   6.,   7.,   8.,   9.,  10.,\n",
      "        11.,  12.,  13.,  14.,  15.,  16.,  17.,  18.,  19.,  20.,  21.,\n",
      "        22.,  23.,  24.,  25.,  26.,  27.,  28.,  29.,  30.,  31.,  32.,\n",
      "        33.,  34.,  35.,  36.,  37.,  38.,  39.,  40.,  41.,  42.,  43.,\n",
      "        44.,  45.,  46.,  47.,  48.,  49.,  50.,  51.,  52.,  53.,  54.,\n",
      "        55.,  56.,  57.,  58.,  59.,  60.,  61.,  62.,  63.,  64.,  65.,\n",
      "        66.,  67.,  68.,  69.,  70.,  71.,  72.,  73.,  74.,  75.,  76.,\n",
      "        77.,  78.,  79.,  80.,  81.,  82.,  83.,  84.,  85.,  86.,  87.,\n",
      "        88.,  89.,  90.,  91.,  92.,  93.,  94.,  95.,  96.,  97.,  98.,\n",
      "        99., 100., 101., 102., 103., 104., 105., 106., 107., 108., 109.,\n",
      "       110., 111., 112., 113., 114., 115., 116., 117., 118., 119., 120.,\n",
      "       121., 122., 123., 124., 125., 126., 127., 128., 129., 130., 131.,\n",
      "       132., 133., 134., 135., 136., 137., 138., 139., 140., 141., 142.,\n",
      "       143., 144., 145., 146., 147., 148., 149., 150., 151., 152., 153.,\n",
      "       154., 155., 156., 157., 158., 159., 160., 161., 162., 163., 164.,\n",
      "       165., 166., 167., 168., 169., 170., 171., 172., 173., 174., 175.,\n",
      "       176., 177., 178., 179., 180., 181., 182., 183., 184., 185., 186.,\n",
      "       187., 188., 189., 190., 191., 192., 193., 194., 195., 196., 197.,\n",
      "       198., 199., 200., 201., 202., 203., 204., 205., 206., 207., 208.,\n",
      "       209., 210., 211., 212., 213., 214., 215., 216., 217., 218., 219.,\n",
      "       220., 221., 222., 223., 224., 225., 226., 227., 228., 229., 230.,\n",
      "       231., 232., 233., 234., 235., 236., 237., 238., 239., 240., 241.,\n",
      "       242., 243., 244., 245., 246., 247., 248., 249., 250., 251., 252.,\n",
      "       253., 254., 255., 256., 257., 258., 259., 260., 261., 262., 263.,\n",
      "       264., 265., 266., 267., 268., 269., 270., 271., 272., 273., 274.,\n",
      "       275., 276., 277., 278., 279., 280., 281., 282., 283., 284., 285.,\n",
      "       286., 287., 288., 289., 290., 291., 292., 293., 294., 295., 296.,\n",
      "       297., 298., 299., 300., 301., 302., 303., 304., 305., 306., 307.,\n",
      "       308., 309., 310., 311., 312., 313., 314., 315., 316., 317., 318.,\n",
      "       319., 320., 321., 322., 323., 324., 325., 326., 327., 328., 329.,\n",
      "       330., 331., 332., 333., 334., 335., 336., 337., 338., 339., 340.,\n",
      "       341., 342., 343., 344., 345., 346., 347., 348., 349., 350., 351.,\n",
      "       352., 353., 354., 355., 356., 357., 358., 359., 360., 361., 362.,\n",
      "       363., 364., 365., 366., 367., 368., 369., 370., 371., 372., 373.,\n",
      "       374., 375., 376., 377., 378., 379., 380., 381., 382., 383., 384.,\n",
      "       385., 386., 387., 388., 389., 390., 391., 392., 393., 394., 395.,\n",
      "       396., 397., 398., 399., 400., 401., 402., 403., 404., 405., 406.,\n",
      "       407., 408., 409., 410., 411., 412., 413., 414., 415., 416., 417.,\n",
      "       418., 419., 420., 421., 422., 423., 424., 425., 426., 427., 428.,\n",
      "       429., 430., 431., 432., 433., 434., 435., 436., 437., 438., 439.,\n",
      "       440., 441., 442., 443., 444., 445., 446., 447., 448., 449., 450.,\n",
      "       451., 452., 453., 454., 455., 456., 457., 458., 459., 460., 461.,\n",
      "       462., 463., 464., 465., 466., 467., 468., 469., 470., 471., 472.,\n",
      "       473., 474., 475., 476., 477., 478., 479., 480., 481., 482., 483.,\n",
      "       484., 485., 486., 487., 488., 489., 490., 491., 492., 493., 494.,\n",
      "       495., 496., 497., 498., 499., 500., 501., 502., 503., 504., 505.,\n",
      "       506., 507., 508., 509., 510., 511., 512., 513., 514., 515., 516.,\n",
      "       517., 518., 519., 520., 521., 522., 523., 524., 525., 526., 527.,\n",
      "       528., 529., 530., 531., 532., 533., 534., 535., 536., 537., 538.,\n",
      "       539., 540., 541., 542., 543., 544., 545., 546., 547., 548., 549.])}\n"
     ]
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "shotNum = \"0007\"\n",
    "filePath = folderPath + \"/\" + shotNum + \"/*.h5\"\n",
    "\n",
    "dataSetOfGlobalDict = {\n",
    "    dskey[groupList[i]]: read_hdf5_global(filePath, groupList[i])\n",
    "    for i in [0]\n",
    "}\n",
    "\n",
    "dataSetDict = {\n",
    "    dskey[groupList[i]]: read_hdf5_file(filePath, groupList[i], datesetOfGlobal=dataSetOfGlobalDict[dskey[groupList[i]]])\n",
    "    for i in [0]\n",
    "}\n",
    "\n",
    "dataSet = dataSetDict[\"camera_0\"]\n",
    "\n",
    "print_scanAxis(dataSet)\n",
    "\n",
    "scanAxis = get_scanAxis(dataSet)\n",
    "\n",
    "dataSet = auto_rechunk(dataSet)\n",
    "dataSet = swap_xy(dataSet)\n",
    "\n",
    "dataSet = imageAnalyser.get_absorption_images(dataSet)\n",
    "\n",
    "imageAnalyser.center = (959, 876)\n",
    "imageAnalyser.span = (100, 100)\n",
    "imageAnalyser.fraction = (0.1, 0.1)\n",
    "\n",
    "dataSet_cropOD = imageAnalyser.crop_image(dataSet.OD)\n",
    "dataSet_cropOD = imageAnalyser.substract_offset(dataSet_cropOD).load()\n",
    "\n",
    "Ncount = imageAnalyser.get_Ncount(dataSet_cropOD).load()\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "Ncount.plot.errorbar(ax=ax, fmt='ob')\n",
    "\n",
    "plt.ylabel('NCount')\n",
    "plt.tight_layout()\n",
    "plt.grid(visible=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "dataSet_cropOD = auto_rechunk(dataSet_cropOD)\n",
    "\n",
    "fitAnalyser = FitAnalyser(\"Two Gaussian-2D\", fitDim=2)\n",
    "params = fitAnalyser.guess(dataSet_cropOD, dask=\"parallelized\")\n",
    "fitResult = fitAnalyser.fit(dataSet_cropOD, params, dask=\"parallelized\").load()\n",
    "\n",
    "fitValue = fitAnalyser.get_fit_value(fitResult)\n",
    "fitStd = fitAnalyser.get_fit_std(fitResult)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "BEC_Ncount_val = fitValue['A_amplitude']\n",
    "BEC_Ncount_std = fitStd['A_amplitude']\n",
    "\n",
    "thermal_Ncount_val = fitValue['B_amplitude']\n",
    "thermal_Ncount_std = fitStd['B_amplitude']\n",
    "\n",
    "BEC_width_x_val = fitValue['A_sigmax']\n",
    "BEC_width_x_std = fitStd['A_sigmax']\n",
    "BEC_width_y_val = fitValue['A_sigmay']\n",
    "BEC_width_y_std = fitStd['A_sigmay']\n",
    "\n",
    "thermal_width_x_val = fitValue['B_sigmax']\n",
    "thermal_width_x_std = fitStd['B_sigmax']\n",
    "thermal_width_y_val = fitValue['B_sigmay']\n",
    "thermal_width_y_std = fitStd['B_sigmay']\n",
    "\n",
    "BEC_center_x_val = fitValue['A_centerx']\n",
    "BEC_center_x_std = fitStd['A_centerx']\n",
    "BEC_center_y_val = fitValue['A_centery']\n",
    "BEC_center_y_std = fitStd['A_centery']\n",
    "\n",
    "thermal_center_x_val = fitValue['B_centerx']\n",
    "thermal_center_x_std = fitStd['B_centerx']\n",
    "thermal_center_y_val = fitValue['B_centery']\n",
    "thermal_center_y_std = fitStd['B_centery']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAl4AAAG+CAYAAABCjQqZAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAAChJklEQVR4nO29eXwV1f3//5rchOyBLCiQhEWLbNr6qdZWCYjfQlAqHxTBolAFKyjtTw0IqEVZ/FQxKqitVisqagFBSYobCthCAa1WqEpFpSKLEDaBkH3P+f0xzs3cubOcM9u9N3k/H4/zSO7MnJkzZ86c855z3ovEGGMgCIIgCIIgPCcu0gUgCIIgCILoKJDgRRAEQRAE4RMkeBEEQRAEQfgECV4EQRAEQRA+QYIXQRAEQRCET5DgRRAEQRAE4RMkeBEEQRAEQfgECV4EQRAEQRA+ER/pAhDOaG1txeHDh5Geng5JkiJdHIIgCILocDDGUFVVhR49eiAuznxOiwSvGOfw4cPIz8+PdDEIgiAIosNz8OBB5OXlmR5DgleMk56eDkB+2BkZGa6dt6mpCRs2bEBhYSESEhJcOy9B8EDtj4gk1P4IUSorK5Gfnx8ck80gwSvGUZYXMzIyXBe8UlJSkJGRQR0P4TvU/ohIQu2PsAuPyg8p1xMEQRAEQfgECV4EQRAEQRA+QYIXQRAEQRCET5DgRRAEQRAE4RMkeBEEQRAEQfgECV4EQRAEQRA+QYIXQRAEQRCET5DgRRAEQRAE4RMkeBEEQRAEQfgECV4EQRAEQRA+QYIXQRAEQRCET5DgRRAEQRAE4RMkeBEEQRAEQfgECV4EEQFqagBJklNNTaRLQxAEQfgFCV4EQRAEQRA+QYIXQRAEQRCET5DgRRAEQRAE4RMkeBEEQRAEQfgECV4EEQFaWtr+37Il9DdBEATRfiHBiyB8prQUGDiw7feoUUDv3vJ2giAIon1DghdB+EhpKTBuHFBWFrq9rEzeTsIXQRBE+4YEL4LwiZYW4I47AMbC9ynbiopo2ZEgCKI9Q4IXQfjE1q3AoUPG+xkDDh6UjyMIgiDaJyR4EYRPHDni7nEEQRBE7EGCF0H4RPfu7h5HEARBxB4keBGETwwZAuTlyfEZ9ZAkID9fPo4gCIJon5DgRRA+EQgATzwh/68VvpTfjz8uH0cQBEG0T0jwIggfGTsWWLMG6NEjdHtenrx97NjIlIsgCILwh/hIF4AgOhpjxwLDhwOdO8u/160DCgtpposgCKIjQDNeBBEB1ELW0KEkdBEEQXQUSPAiCIIgCILwCRK8CIIgCIIgfIIEL4IgCIIgCJ8g5XqCiACpqfoxGwmCIIj2Dc14EQRBEARB+AQJXgRBEARBED5BghdBEARBEIRPkOBFEARBEAThEzEjeNXW1uKdd97B73//e4wdOxa9evWCJEmQJAkLFizgOsexY8dw5513ol+/fkhOTkZWVhaGDBmC5557DoxD0/mbb77BLbfcgj59+iApKQlnnHEGRo4ciZKSEq7r//vf/8akSZOQl5eHxMREdO/eHVdffTX+/ve/c+UnCIIgCCK2iRmrxn/9618YNWqU7fw7duzAyJEjcfLkSQBAWloaqqqqsG3bNmzbtg2vvfYa3njjDSQmJurmX7duHcaPH4/a2loAQEZGBk6ePIkNGzZgw4YNmDJlCp5//nlI2ujH3/Pcc89h+vTpaG5uBgB07twZx44dw9q1a7F27VrMnz+fW4AkCIKwoqYGSEuT/6+uli1pCYKIPDEz4wUAmZmZ+PnPf47Zs2fjlVdeQbdu3bjyVVRU4Morr8TJkyfRv39/fPzxx6iqqkJNTQ2efPJJJCQkYMOGDZgxY4Zu/n379uHaa69FbW0tBg8ejN27d6OiogIVFRWYN28eAGDZsmV45JFHdPP/85//xK233orm5mZcddVVOHjwIE6fPo3vvvsOt9xyCwBg4cKFePXVV23UCkEQBEEQMQOLEZqbm8O29erViwFg8+fPN8177733MgAsOTmZ7d27N2z/gw8+yACwQCDAdu/eHbZ/0qRJDADr1q0bKy8vD9s/bdo0BoBlZGSwU6dOhe0vKChgANh5553HGhsbw/aPHDmSAWC9evXSvU8zKioqGABWUVEhlM+KxsZGtnbtWt3yEoTXUPtzTnU1Y7K3OPl/gh9qf4QoImNxzMx4BRxEEX755ZcBABMmTECfPn3C9t92221IS0tDS0sLVqxYEbKvpqYmqMM1ffp0dOnSJSz/PffcAwCorKzE2rVrQ/bt3bsX27ZtAwDMmjULCQkJhvkPHDiALVu2iN0cQRCEDi0tbf9v2RL6O5aoqQEkSU41NZEuDUE4J2YEL7vs3r0b3377LQDgiiuu0D0mLS0NQ4YMAQBs2LAhZN+2bdtQV1dnmr93794YMGCAbv6NGzcG/7/88st18xcUFCA9PV03P0EQhCilpcDAgW2/R40CeveWtxMEEVnaveD1+eefB/8/99xzDY9T9n3xxReG+QcNGmSZf9euXbr5zzjjDJxxxhm6eQOBAPr376+bnyAIQoTSUmDcOKCsLHR7WZm8nYQvgogsMWPVaJfDhw8H/8/NzTU8TtlXWVmJ6upqpH1vDqTkz8zMREpKimV+9fXUv82urez/+OOPw/JraWhoQENDQ/B3ZWUlAKCpqQlNTU2meUVQzuXmOQmCF2p/9mhpAW6/Pf77OKChFtaMAZLEcMcdwKhRzXCgveErchNI+P7/JvjRJKj9EaKItJV2L3hVVVUF/zcTnNT7qqqqgoKXkt8sr3q/+npu5NeyaNEiLFy4MGz7hg0bLK9hB/VSKUH4DbU/Mf7zn2yUlRUY7mdMwqFDwKOPfoTzzjvpY8nsU1sbAHAlAGDJku04//zjvgmN1P4IXhRXUzy0e8GrvXHPPfdg5syZwd+VlZXIz89HYWEhMjIyXLtOU1MTNm7ciBEjRugaBBCEl1D7s0dlpb4fQS29ev0Mo0ZZO42ONH/9q4RZs9qkrP/7v4uRm8uwZEkLrr7au/JT+yNEUVafeGj3gpeitA7IEqmRcKKWVtV5lP+tpFllvzqvG/m1JCYm6jp5TUhI8KSD8Oq8BMEDtT8x8vN5j4tHtFdraSkwYQKgDSpy+LCECRPisWYNMHast2Wg9kfwItJO2r1yfY8ePYL/l2m1TVUo+zIyMoLLjOr85eXlpsKTkl99PfVvs2ub5ScIguBlyBAgL092vaCHJMnC2fdG3FFLSwtwxx3hQhfQtq2oKHZdZBAdm3YveKktGdUWilqUfQPVNtia/GYWh0p+reWjkv/48eP47rvvdPO2tLTgq6++0s1PEATBSyAAPPGE/L9W+FJ+P/44ol6xfutW4NAh4/2MAQcPyscRRKzR7gWvfv36oWfPngCAd999V/eYmpoabP3+DS4sLAzZV1BQgOTkZNP8Bw4cwJdffqmbf8SIEcH/jfK///77QaV6bX6CIAgRxo4F1qwBtJPneXnwZXnODY4ccfc4gogm2r3gBQA33HADAGDVqlXYv39/2P6nnnoK1dXVCAQCmDhxYsi+1NRUXHPNNQCAp59+GhUVFWH5i4uLAcj6WVdddVXIvrPOOgsFBbKV0eLFi3VNTh966CEAQK9evTB06FCxmyMIgtAwdiygdkm4bh2wb19sCF0A0L27u8cRRDQRU4JXeXk5Tpw4EUytra0AZMV09fbq6uqQfLNmzUK3bt1QW1uLX/ziF9ixYwcAoLGxEU8//TTuu+8+AMC0adNwzjnnhF33/vvvR2pqKo4cOYLRo0fj66+/BiDPlN1///145plnAAD33nsvMjMzw/I//PDDCAQC+OyzzzBhwoSgPtepU6fwm9/8Bu+8807IcQRBEE5RdyVDh0b/8qIap7pqFGaIiGp8iB3pGkpQbKt04403huXdvn07y87ODh6Tnp7OEhISgr8LCwtZfX294bXffvttlpKSEjy+c+fOLBAIBH9PnjyZtba2GuZfunQpi4+PDx7fpUsXJklS8LdVoG8joiFINgXjjW2i8flRkGLnRONzFaGkhDFJkpNyH0DbtpIS47xO7729tL9YbwOxRLsMku2
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<xarray.DataArray ()>\n",
      "array(853.42940839)\n"
     ]
    }
   ],
   "source": [
    "total_Ncount_val = BEC_Ncount_val + thermal_Ncount_val\n",
    "total_Ncount_std = BEC_Ncount_std + thermal_Ncount_std\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "total_Ncount_val.plot.errorbar(ax=ax, yerr=total_Ncount_std, fmt='ob')\n",
    "# plt.ylim([0, 1100])\n",
    "plt.ylabel('Ncount from fit')\n",
    "plt.tight_layout()\n",
    "plt.grid(visible=1)\n",
    "plt.show()\n",
    "\n",
    "print(total_Ncount_val.mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "BEC_Ncount_val.plot.errorbar(ax=ax, yerr=BEC_Ncount_std, fmt='ob')\n",
    "plt.ylim([0, 750])\n",
    "plt.ylabel('Ncount of BEC part')\n",
    "plt.tight_layout()\n",
    "plt.grid(visible=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAl4AAAG+CAYAAABCjQqZAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAACHd0lEQVR4nO3dd5wU9f0/8Nfs9Qp3B1LuaBqkCLGTqKBYAEGJBkssqIiCD0xURIoIAkdUpCmWYAEFiRjaESIIUvzBV0iiAU0sYFDhQDqhXeX65/fHOsvs3vSZnd09Xs/HYx4cu9P3MzPv+VRJCCFARERERGHni/QOEBEREZ0tGHgREREReYSBFxEREZFHGHgREREReYSBFxEREZFHGHgREREReYSBFxEREZFHGHgREREReYSBFxEREZFHGHgREREReSRmAq/58+dDkiTDacOGDZrrOHLkCJ566il06NABKSkpyM7ORo8ePTB37lyYGTlp165deOSRR9CuXTskJyfjnHPOQZ8+fVBQUODmoRIREVEDFR/pHbDK5/OhadOmmt8nJSWpfv7FF1+gT58+OH78OAAgPT0dJSUl2LJlC7Zs2YKlS5fiww8/1Fx+9erVuOOOO1BeXg4AyMzMxPHjx7Fu3TqsW7cODz74IN555x1IkuTwCImIiKihipkcL1mrVq1w+PBhzalHjx71likqKsLNN9+M48ePo2PHjti6dStKSkpQVlaG119/HQkJCVi3bh2efPJJ1W0WFhbizjvvRHl5Oa666irs3LkTRUVFKCoqwoQJEwAA8+bNw/Tp08N67ERERBTbYi7wsmPGjBk4fPgwUlJSsHr1alx22WUAgMTERPz+979Hfn4+AODtt9/G999/X2/5CRMmoKysDM2bN8eqVatw/vnnA/DnmuXn52Po0KEAgOeffx4nT5706KiIiIgo1pwVgdeCBQsAAHfddRfatWtX7/vHHnsM6enpqK2txcKFC4O+KysrC9ThGjZsGBo3blxv+bFjxwIAiouLsWLFCnd3noiIiBqMBh947dy5Ez/99BMAoG/fvqrzpKenB4oo161bF/Tdli1bcPr0ad3l27Zti06dOqkuT0RERCSLucDrf//7Hy699FKkp6cjJSUF5557LgYOHIhNmzapzv/tt98G/u7SpYvmeuXvduzYobn8BRdcYLj89u3bDY+BiIiIzk4xF3iVl5fjyy+/RGJiIurq6lBYWIiFCxfi2muvxeDBg1FTUxM0/8GDBwN/5+bmaq5X/q64uBilpaX1ls/KykJqaqrh8srtERERESnFTHcSLVu2xMSJEzFgwAB06NABSUlJqK2txeeff46JEydiw4YNmDdvHtLS0vDaa68FlispKQn8rRc4Kb8rKSlBenp60PJ6yyq/V25PTWVlJSorKwP/r6urw4kTJ5CTk8OuKIiIiGKQEAIlJSVo2bIlfD79PK2YCbx69+6N3r17B30WFxeHK6+8EmvXrsWAAQPwt7/9DbNnz8bjjz+O9u3bR2hP9U2ZMiXQipKIiIgajn379iEvL093npgJvPT4fD7MmDEDf/vb31BXV4eVK1dixIgRAICMjIzAfOXl5cjMzFRdh9wxaugy8t/K7/WWVy6rZuzYsYF9A/x9jLVu3RqFhYWGy1pVXV2NjRs34tprr0VCQoKr6yayg2mSog3TJLmhpKQE7dq1M/UcbxCBFwD84he/QJMmTXDs2DHs3r078HnLli0Dfx84cEAz8Dpw4AAAf4/0cjGjcvmTJ0+ivLxcs8hRXl65PTVJSUmqveNnZ2dr7ptd1dXVSE1NRU5ODm8oFBWYJinaME2SG+S0Y6bKUMxVrrdK2ZJR2UIxlPxd586dNZfXa7EoL6/X8pGIiIjObg0m8Nq1axeOHTsGAEGdpHbo0AGtW7cGAHz88ceqy5aVlWHz5s0AUK8eWffu3ZGSkqK7/N69e/Hdd9+pLk9EREQki4nASwhh+P2oUaMA+Ot73XzzzUHf33///QCARYsWYc+ePfWW/9Of/oTS0lLExcXh3nvvDfouLS0Nt912GwDgjTfeQFFRUb3lp06dCsBfv+vWW281dUxERER09omJwGvv3r3o1q0b3nrrLezevTsQiNXV1eGzzz5D37598de//hUA8Mgjj6BDhw5By48cORLNmzdHeXk5brrpJnzxxRcAgKqqKrzxxht49tlnAQBDhw4NjMOoNHnyZKSlpeHQoUPo378/fvjhBwD+nLLJkyfjzTffBACMHz8eWVlZ4TkJREREFPNipnL91q1bsXXrVgD+CuoZGRkoKSkJ6hPrwQcfxKuvvlpv2UaNGmHVqlXo06cPduzYgcsuuwwZGRmoqKhAdXU1AH8R4csvv6y67Xbt2mHJkiW44447sHnzZpx//vlo1KgRSktLUVtbCwAYNGhQINeNiIiISE1M5Hg1a9YMr732Gu655x507twZmZmZOHXqFBISEtCxY0cMHjwYW7Zswbvvvov4ePVY8tJLL8X27dvx5JNPon379qiurkZaWhq6d++OOXPmYM2aNaqtDWX9+vXD119/jSFDhqBt27Y4ffo0GjdujF69emHZsmWYN28eO0AlIiIiXZIwqkBFYVVcXIxGjRqhqKgoLN1JrF69Gv369WMzaYoKTJMUbZgmyQ1WnuUxkeNFRERE1BAw8CIiIiLyCAMvIiIiIo8w8CIiIiLyCAMvIiIiIo8w8CIiIiLyCAMvIiIiIo8w8CIiIiLyCAMvIiIiIo8w8CIiIiLyCAMvIiIiIo8w8CIiIiLyCAMvIiIiIo8w8CIiIiLyCAMvIiIiIo8w8CIiIiLyCAMvIiIiIo8w8CIiIiLyCAMvIiIiIo8w8CIiIiLyCAMvIiIiIo8w8CIiIiLyCAMvIiIiIo8w8CIiIiLyiO3Aa/DgwRgxYoTp+UePHo2HHnrI7uaIiIiIYp7twGv+/PlYtGiR6fmXLl2K+fPn290cERERUczzrKhRCOHVpoiIiIiikmeB17Fjx5CamurV5oiIiIiiTtgDr6KiIsycORPl5eU499xzw705ioTiYkCS/NOaNUBtbaT3iIiIKCqZDrzy8/MRFxcXmADgyJEjQZ+pTdnZ2Rg9ejQkScLtt98etgOhCFm+HOjc+cz/+/UD2rb1f05ERERBLOV4CSECkyRJQf/XmxISEjB48GA8/fTT4ToOioTly4HbbwcOHAj+/MAB/+cMvoiIiILEm51x0KBB6NmzJwB/AHbdddchOzsbBQUFmsv4fD5kZmbi/PPPR0pKiuOdpShSWws88QSg1mhCCH+x4/DhwC23AD/nkBIREZ3tTAdebdq0QZs2bQL/b926NZo1a4ZrrrkmLDtGUW7zZmD/fu3vhQD27fPP93PATkREdLYzHXiFys/PhyRJOHLkCJo1a+bmPlEsOHTI3fmIiIjOArYDrwcffBDx8fE4deqUi7tDMaNFC3fnIyIiOgvY7k4iOzsbmZmZ7JvrbNWjB5CX56/LpUaSgFat/PMRERERAAeBV8eOHVFUVITS0lI394diRVwc8Mor/r9Dgy/5/7NmsWI9ERGRgu3Aa9CgQaitrcXcuXPd3B+KJQMGAMuWAS1bBn+el+f/fMCAyOwXERFRlLJdx+vhhx/GunXrMGbMGCQmJmLo0KGIj7e9OopVAwYAN9wANGrk///q1UDv3szpIiIiUmE7Uho8eDDS0tKQlJSExx57DBMmTMDll1+Oc845J9CzfShJkvDOO+/Y3lmKUpmZ6v15ERERURDbgdf8+fMDvdcDwIkTJ7B27VrVeeX5GHgRERHR2cx24HX//fdD0mrRRhSriotZbEpERGHjKMeLqEFZvhx4/PEz/+/Xz99Q4JVX2FCAiIhcYbtVI1GDwgG/iYjIAwy8iIwG/Ab8A37X1nq6W0RE1PAw8CKyMuC3lrIyf8exkuT/m4iISIXjjrcOHz6Md999F1u2bMH+/ftRVlYWaOkYSpIk7Nq1y+kmidzlxoDfytywTz+tXymflfaJiAgOA6+//vWveOCBBwyDLfk7toIkQ5EIUJwO+G1UKZ+V9on08cWEziK2ixp37NiBe+65B6WlpejXrx9mz54NAGj
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "thermal_Ncount_val.plot.errorbar(ax=ax, yerr=thermal_Ncount_std, fmt='or')\n",
    "plt.ylim([0, 500])\n",
    "plt.ylabel('Ncount of thermal part')\n",
    "plt.tight_layout()\n",
    "plt.grid(visible=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "BEC_width_x_val.plot.errorbar(ax=ax, yerr=BEC_width_x_std, fmt='ob')\n",
    "\n",
    "plt.ylabel('X-axis Width of BEC part')\n",
    "plt.tight_layout()\n",
    "plt.grid(visible=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "BEC_width_y_val.plot.errorbar(ax=ax, yerr=BEC_width_y_std, fmt='ob')\n",
    "\n",
    "plt.ylabel('Y-axis Width of BEC part')\n",
    "plt.tight_layout()\n",
    "plt.grid(visible=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "thermal_width_x_val.plot.errorbar(ax=ax, yerr=thermal_width_x_std, fmt='or')\n",
    "\n",
    "plt.ylabel('X-axis width of thermal part')\n",
    "plt.tight_layout()\n",
    "plt.grid(visible=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "thermal_width_y_val.plot.errorbar(ax=ax, yerr=thermal_width_y_std, fmt='or')\n",
    "\n",
    "plt.ylabel('Y-axis width of thermal part')\n",
    "plt.tight_layout()\n",
    "plt.grid(visible=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "BEC_center_x_val.plot.errorbar(ax=ax, yerr=BEC_center_x_std, fmt='ob')\n",
    "\n",
    "plt.ylabel('X-axis center of BEC part')\n",
    "plt.tight_layout()\n",
    "plt.grid(visible=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "BEC_center_y_val.plot.errorbar(ax=ax, yerr=BEC_center_y_std, fmt='ob')\n",
    "\n",
    "plt.ylabel('Y-axis center of BEC part')\n",
    "plt.tight_layout()\n",
    "plt.grid(visible=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "thermal_center_x_val.plot.errorbar(ax=ax, yerr=thermal_center_x_std, fmt='or')\n",
    "\n",
    "plt.ylabel('X-axis center of thermal part')\n",
    "plt.tight_layout()\n",
    "plt.grid(visible=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAl4AAAG+CAYAAABCjQqZAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAAC6CklEQVR4nO2deXgVRdaHf32TEAghERLWBAVHR8Rd1BEBRUVUxGGMOiLihvsyDsrmDArizIgoIO4LKCqgICbIgPlkcUAERUHHcd8j+xaWhCSEbPX9cembvn27uququ++W8z5PP7npraqrq6tPnzqLxhhjIAiCIAiCIHwnEOsKEARBEARBNBVI8CIIgiAIgogSJHgRBEEQBEFECRK8CIIgCIIgogQJXgRBEARBEFGCBC+CIAiCIIgoQYIXQRAEQRBElCDBiyAIgiAIIkqkxroCiU5DQwO2bt2KVq1aQdO0WFeHIAiCIIgowxjD/v370alTJwQC9jotErxcsnXrVnTu3DnW1SAIgiAIIsZs2rQJ+fn5tvuQ4OWSVq1aAQg2dlZWlqfnrq2txdKlS9G/f3+kpaV5em6C8BLqq0SiQH2V8IPy8nJ07tw5JBPYQYKXS/TpxaysLF8Er4yMDGRlZdEAQcQ11FeJRIH6KuEnIiZHZFxPEARBEAQRJZQFr2HDhuG+++4T3n/06NG46aabVIsjCIIgCIJIeJQFr1dffRVz584V3n/+/Pl49dVXVYsjCIIgCIJIeKI21cgYi1ZRBEEQBEEQcUnUBK/S0lJkZGREqziCIAiCIIi4w3evxrKyMsyYMQNVVVU44YQT/C6OIAiCIAgibhEWvCZMmICHH344bN2OHTuQkpIidLymabjiiivkakcQBEEQBJFESGm8jHZamqYJ2201a9YM1157Le6//3652hEEQRAEQSQRwoLXDTfcgL59+wIICmDnnXce2rRpg8LCQu4xgUAAWVlZ+P3vf48WLVq4rixBEARBEEQiIyx4HXHEETjiiCNC/x9++OFo3749zjnnHF8qRhAEQRAEkWwoG9dPmDABmqZhx44daN++vZd1IgiCIAiCSEqUBa8bb7wRqamp2Ldvn4fVIQiCIAiCSF6UBa82bdoAAMXmIgiCIAiCEEQ5gGq3bt1QVlaGiooKL+tDELGlshLQtOBSWRnr2hAEQRBJhrLgdcMNN6C+vh4zZszwsj4EQRAEQRBJi/JU480334ylS5dizJgxaNasGW699VakpvoeCJ8gCIIgCCJhUZaUhg0bhpYtWyI9PR1/+ctfMG7cOJx++ulo164dN5q9pml4+eWXlStL+ERlJZCZGfxdUQG0bBnb+hAEQRBEkqIseL366qth0ev37NmDJUuWWO6r70eCF0EQBEEQTRllweu6666Dpmle1oUgCIIgCCKpcaXxIgiCIAiCIMRR9mokmjAUcoEgCIIglCDBiyAIgiAIIkqQ4EUA9fWNv1etCv+/qUFtQRAEQfiI68Bb27dvxyuvvILVq1dj8+bNqKysDHk6mtE0Db/88ovbIgkvKSoC7rmn8f8BA4D8fODJJ4GCgtjVKxZQWxAEQRA+40rwWrBgAa6//npHYUvfRl6QcUZREXDFFYD53m3ZElz/9ttNR+CgtghCMd0IgiB8RXmq8dtvv8WQIUNQUVGBAQMG4LnnngMAZGdnY8aMGfjnP/+Jvn37gjGG3NxcPPPMM3jllVc8qzjhkvp64K9/jRQ0gMZ1w4dbT7Ul23Scm7YgCIIgCAmUBa8nnngCBw8exNChQ7Fo0SLcfvvtAIAWLVpg2LBh+Pvf/47//Oc/ePfdd1FVVYXXXnsNQ4YM8azihEs+/BDYvJm/nTFg06bgfkaKioDu3Rv/HzAA6NIluD5RUW0LgiAIgpBEWfBauXIlNE3D3/72N9v9Lr74YkyZMgXr1q3DtGnTVIsjvGbbNvn99Om4LVvC99Gn4xJV+FJpC4IgCIJQQFnw2rJlC1JTU3HssceG1mmahoMHD0bse+211yIlJQVz585VLY7wmo4d5fZL5uk42bYgCIIgCEWUBa9mzZohIyMjbF1mZibKyspQV1cXtj4jIwOtWrUij0Y/UA1m2qdP0GOP5/CgaUDnzsH9gOSejpNtC4IgCIJQRFnw6tSpE8rLy3HgwIHQui5duoAxhv/9739h++7duxf79u1DTU2Nek0Jb0lJCYZJACIFDv3/adOC+wHJPR0n2xYEQRAEoYiy4KVPMf7000+hdb169QJjDJMnTw7b94EHHgAAHHPMMarFEX5QUBAMk9CpU/j6/PzI8AnRno6LdloimbZIZpLNY5UgCCLOUBa8LrnkEjDGUFhYGFp3++23IxAI4K233sLxxx+Pa665BieeeCJeeOEFaJqGYcOGeVJpwkMKCoBvv238v7gYKCmJFDSawnScaFskK8nosUoQBBFnKAtel156Ka6//nqkpjbGYD3xxBMxbdo0BAIBfPvtt3jzzTfx9ddfgzGGwYMH4y9/+YsnlSY8xjiFdvbZ1lNqTWU6TqQtkpFk9VglCIKIM5Qj17dt2xYzZ86MWH/33XejX79+ePvtt7Fp0yZkZ2fjoosuwnnnneeqokQcoE/H3XNP+As6Pz8odDUVzVCy4eSxqmlBj9VBg5qOIEoQBOETrnM1WtGtW7eQXReRZBQUAP36AdnZwf+Li4H+/emFLEs8peaR8Vjt2zdq1SIIgkhGlKcaiSZMU52OS1aS2WOVIAgizvBM4/XNN99g/fr12LlzJwCgXbt2OO2003Dcccd5VQRhhdkLLVm0T8l6XfFIogSQjSctIUEQhCKuBa/Fixfjb3/7G741eoMZ6N69O/71r3/hj3/8o9uiCDNFRUF7K50BA4L2Vk8+mdj2Vsl6XfGK7rG6ZYu1nZemBbcnsscqQRBEnOBqqvHhhx/GoEGD8M0334AxhpSUFLRr1w7t2rVDSkoKGGP45ptvcNlll+Ghhx7yqMoEAG+90Fq2DL5wGYu9FoG866JPU/FYJQiCiAOUBa/33nsPDz30EBhjOPvss7F06VJUVFRg27Zt2LZtGyoqKrB06VL07dsXjDH84x//wJIlS7yse9Ml1nkT/RLUYn1dQHwJodGEAsgSBEFEBWXBa+rUqQCAK6+8EitWrEC/fv3QrFmz0PZmzZqhX79+eP/993HllVeCMRY6hnBJouZNdIpGn6jXpUI8Rohv6gFkCYIgooCy4LV+/XpomoapU6dC40UzB6BpGqZMmQIAWLdunWpxhJFk9UJL1usyE88R4sljlSAIwleUBa+amhocdthhyMvLc9w3Pz8frVu3Rm1trWpxhJFE8UKTJVmvywjZsBEEQTRplAWvI488EhUVFaipqXHc9+DBg6ioqMCRRx6pWhxhJFnzJibrdenEgw0bQRAEEVOUBa8hQ4agtrYWr7/+uuO+s2bNQm1tLYYMGaJaHGHEzgtNJxG90JLdu64p2bARBEEQligLXiNGjEDv3r1xzz334LXXXuPu9/rrr+Oee+5Bnz59MGLECNXiCDM8LzQAmD07Pg2iRQzKk9m7rqnYsBEEQRBclAOoTpw4EWeffTa++uorDBs2DOPHj0ffvn2Rl5cHTdOwefNmfPDBB9i4cSOys7PRp08fPPLII5bnGjdunPIFNGnMeRN1Bg2KTX3skAmKmqz5IJuCDZufUDYDgiCSAI0xK4MTZwKBQMibUT+F2buRt95MfQLbtJSXlyM7OxtlZWXIysry9Ny1tbUoLi7GgAEDkJaWZr2TMY2KTrylU9ENys1dTe8XVpqsZEwPU18f9F50ihBfUpJwAoVQX3WDLrgbnRIomwGhgO99lWiSyMgCyhqvs88+21GgIghHg3JNCxqUDxqUcMKGNLoN2xVXBK/b2CbJYMPmFzzBXfcETfQpaIIgmhTKgtfKlSs9rAaRtMgYlPftG7VqxQzdhs1KezNtGgkQZkhwJwgiyXCVqzGavPrqq9A0zXFZvny58Dlvv/320HFdunTxr/LRJjPTOjJ8LFAxKLeaPlXBKVJ+rKAI8eKQJyhBEEmGssYrVgQCAbRt25a7PT09Xeg8K1euxEsvveRVteKPeLGbI4N
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "thermal_center_y_val.plot.errorbar(ax=ax, yerr=thermal_center_y_std, fmt='or')\n",
    "\n",
    "plt.ylabel('Y-axis center of thermal part')\n",
    "plt.tight_layout()\n",
    "plt.grid(visible=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAl4AAAG+CAYAAABCjQqZAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAACUDElEQVR4nO2deXwV1d3/P3OTkJCEhBD2JBpsXUCgUpVqEQRFFCqPNaBiXR/Xp/oTcQGsWIVaN0QebKt1qwIVEDARRYMSKSh1e8TagmDVakBJUGRLIAGynd8f17mZO3eWc84sd+bm+3695pXcWc/MnDnnc77ne75HYYwxEARBEARBEJ4TSXYCCIIgCIIgOgokvAiCIAiCIHyChBdBEARBEIRPkPAiCIIgCILwCRJeBEEQBEEQPkHCiyAIgiAIwidIeBEEQRAEQfgECS+CIAiCIAifSE92AlKdtrY21NbWokuXLlAUJdnJIQiCIAjCZRhj2L9/P/r27YtIxNqmRcLLY2pra1FSUpLsZBAEQRAE4THffPMNiouLLfch4eUxXbp0ARB9GXl5ea6eu7m5GatXr8aYMWOQkZHh6rkJwimUP4kgQ/mTcJP6+nqUlJTE6nwrSHh5jNq9mJeX54nwys7ORl5eHhUcROCg/EkEGcqfhBfwuBSRcz1BEARBEIRPkPAiCIIgCILwCRJeBEEQBEEQPkHCiyAIgiAIwidIeBEEQRAEQfgECS+CIAiCIAifIOFFEARBEAThEyS8CIIgCIIgfIKEF0EQBEEQhE+Q8CIIgiAIgvAJEl4EQRAEQRA+QcKLIAiCIAjCJ0h4EQRBEARB+AQJL4IgCIIIGA0NgKJEl4aGZKeGcBMSXgRBEARBED5BwosgCIIgCMInSHgRBEEQRMBobW3//+23438T4YaEF0EQBEEEiIoKYMCA9t/jxgGlpdH1RPgh4UUQBEEQAaGiApg4EaipiV9fUxNdT+Ir/JDwIgiCIIgA0NoK3HwzwFjiNnXdlCnU7Rh2SHgRBEEQgaUjhVVYvx7Yvt18O2PAN99E9yPCCwkvgiAIgggAO3a4ux8RTEh4EQRBEEQA6NPH3f2IYELCiyAIgggsHSmswvDhQHFxtFvVCEUBSkqi+xHhhYQXQRAEEUg6WliFtDTg0Uej/+vFl/p73rzofkR4IeFFEARBBI6OGlahrAx48UWgb9/49cXF0fVlZclJF+EeJLwIgiCIQNHRwyqUlQFbtrT/rqwEqqtJdKUKJLwIgiCIQEFhFeK7E0eMoO7FVCI92QkgCIIgCC0UVgHIyTG2+BHhhyxeBEEQRKCgsApEKkPCiyAIgggUFFaBSGVIeBEEQRCBgsIqEKkMCS+CIAgicFBYBSJVIed6giAIIpCUlQGjRwP5+dHflZXAmDFk6SLCDVm8CIIgiMBCYRWc0dAQ7Z5VlOj/RPIhixdBEAQRWCisApFqkMWLIAiCIAjCJ0h4EQRBEESKop1W6e23U3eapTBBwosgCMJnyO+GMMPNvFFRAQwY0P573DigtDR1JxgPCyS8CIIgCCLFqKgAJk4Eamri19fURNeT+EoeJLwIgiB8hrp/CC9pbQVuvtl4UIK6bsoUynfJgoQXQRCEj1D3D2GFG6J8/Xpg+3bz7YwB33wT3c9PqIs9CgkvgiAIn6DuH8IKt0T5jh3u7ke4CwkvgiAIH6DuH8IKN0V5nz7u7ucW1MUehYQXQRCEDwS1+4dIPm6L8uHDo3Na6icYV1EUoKQkup9fUBd7OyS8CIIgfIC6fwgz3BblaWnAo49G/9eLL/X3vHn+Tb9EXezxkPAiCILwgaB2/xDJxwtRXlYGvPgi0Ldv/Pri4uj6sjL+czmButgTIeFFEAThA0Hs/iGCgVeivKwM2LKl/XdlJVBd7Z/oAqiL3QgSXgRBED4QtO4fIjh4Kcq1+WnECP/zF3WxJ0LCiyAIwieC0v1DBItUFuXUxZ4ICS+CIAgfCUL3DxE8vBLlOTnR7jzGov/7DXWxJ0LCiyAIwmeS3f2TTCh6uTmpKMpT2ZonS7pbJzp06BD27t2L5uZmy/2OOOIIty5JEAQRSlQrBEHoSUVRrlrzJk+ODylRXBwVXWEWljI4El6NjY2YPXs2lixZgv/85z+2+yuKgpaWFieXJAiCIIiUJVVFeVkZMHo0kJ8f/V1ZCYwZkxrCUhRp4bVv3z6MGDECmzdvBuPMJbz7EQRBEKmJftqYjlr5dkRS0Zong7SP17333otPPvkE6enpuPXWW/HWW2/hiy++QHV1teXilP3792PmzJkYNGgQcnNzkZ+fj5NPPhmPPPIImpqahM+3detWKIrCvfz3f/+343sgCILoiNC0MR2bZDv6BwVpi9eKFSugKArmzZuHX//6126myZRt27Zh5MiR2Lp1KwAgOzsbhw8fxoYNG7BhwwYsWrQIa9asQUFBAfc509LS0KtXL8t9Dh06hLq6OgDAySefLJ1+giCIjoo6bYy+40OdNobCaRAdBWmLV01NDSKRiG8WoNbWVowfPx5bt25Fnz59UFVVhYaGBjQ2NuKFF15Aly5d8PHHH+OSSy4ROm9JSQm+/fZby+Wyyy4DAHTu3Bm/+tWvvLg9giCSgOwIOxqZJwZNG5N6OPkGOvr3Iy28unXrhi5duiArK8vN9Jgyf/58bNq0CQBQXl6O0aNHAwAikQguuugiPPnkkwCAVatWYc2aNa5d99ChQ1i0aBEAYMKECejatatr5yYIIjjk5vJXBHo/JRIM1tC0MQTRjrTwOu2001BXV4ca/XTjHrFgwQIAwKhRo3DqqacmbJ80aRL69esHAFi4cKFr162oqMDevXsBANdcc41r5yUIIpyQn5I4NG1M6kGND3mkhdf06dORnp6Oe++91830GNLY2Ih33nkHADB27FjDfRRFwTnnnAMAWL16tWvX/stf/gIAOProo3H66ae7dl6CIJzjd5eF6qekb2+qfkokvoyhaWOcE6TuOaeNj44u2qSF14knnoj58+djwYIFuPrqq/HVV1+5ma44Pv30U7S1tQEABg4caLqfuu3bb7/Fnj17HF/3q6++wtq1awEAV199tePzEURHoqEB+OUvz0OnThmeVRS8BbhZpSVS4JOfkjw0bUzq4LTxQRZjB6MajzrqKADRUYHz58/H/PnzY35fZiiKgi+//FL4WrW1tbH/i4qKTPfTbqutrUW3bt2Er6Xl2WefBWMM6enpuOKKK7iOOXz4MA4fPhz7XV9fDwBobm62jeovino+t89LEG4QzZcZsf/dzqYvvaTgllvSAERr83HjgKIihrlzW3H++fHqKHrt+LToj1e5775W3H13W0KMobfeUrB9u3mRqfoprV3bgtNPp5iFeh55RMGkSWlQFICx9meuKNFnNWdOK9raGH5oY3tO2MrPQ4cANQ+vXduC0aOZ73GwWluByZPTf2hoxH83jEXf5c03A+PGtRim7aWXonlAf3xNDcPEicALLyR+u2FBJB9JCy81pIOW3bt3Y/fu3abHKGbNHRv2798f+z87O9t0P+027TEytLa2Yv78+QCAX/ziF+jduzfXcQ888ABmzZqVsH716tWWaXdCVVWVJ+clCCccOpQG4FwAwBtvvIGsLPdMQe+91wcPPZQY2qWmBrjoojRMn/4hTj213WFIn5aPP+5peDwAPPBAGv70pxbccMO/4s7x9ttFAE6yTduqVf9EQ4M/vq9hIjMTmDatD55+ehD27OkcW19YeBBXX/0JMjN3oLLS/3SFofx8773oc1OF1/jx6SgsPIhrrtkUl0e9ZtOmQtTUnGa6nTEF27cDc+Z8gEGD4rVAaytwww1jwFhiYycqxBluvLEJ6elVoQys2tjYyL2vtPB67rnnZA8NBa+//nps4ICIU/1vfvMb3HrrrbHf9fX1KCkpwZgxY5CXl+dqGpubm1FVVYWzzjoLGRkZrp6bIJyye3d7CzAn5xzXWuitrcCNN6pFl74xp0BRGBYtOhkzZ7a3un8wPAMAsrLOwfPPp5kcH2X//k6YPfvkuBZ4To6CuXPt0zd27Ak4/fSfcN9PR2LcOGDqVKB79+jvlStbMHp0BtLShgA
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fitFullResult = fitAnalyser.get_fit_full_result(fitResult)\n",
    "condensateFraction = fitFullResult['A_amplitude'] / (fitFullResult['A_amplitude'] + fitFullResult['B_amplitude'])\n",
    "condensateFraction_value, condensateFraction_std = seperate_uncertainty(condensateFraction)\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "condensateFraction_value.plot.errorbar(ax=ax, yerr=condensateFraction_std, fmt='ob')\n",
    "\n",
    "plt.ylabel('Condensate Fraction')\n",
    "plt.tight_layout()\n",
    "plt.grid(visible=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The total Ncount is:  849.84 ±  73.69\n",
      "The total Ncount from fit is:  853.43 ±  66.18\n",
      "The Ncount of the BEC part is:  528.79 ±  65.37\n",
      "The Ncount of the thermal part is:  324.64 ±  35.62\n",
      "The x-axis width of the BEC part is:  4.06 ±  0.28\n",
      "The y-axis width of the BEC part is:  11.03 ±  0.36\n",
      "The x-axis width of the thermal part is:  15.30 ±  0.91\n",
      "The y-axis width of the thermal part is:  12.99 ±  0.61\n",
      "The x-axis center of the BEC part is:  47.44 ±  1.82\n",
      "The y-axis center of the BEC part is:  51.13 ±  1.83\n",
      "The x-axis center of the thermal part is:  49.62 ±  1.54\n",
      "The y-axis center of the thermal part is:  51.17 ±  1.37\n",
      "The condensate fraction is:  0.6180 ±  0.0464\n"
     ]
    }
   ],
   "source": [
    "val = Ncount.mean().item()\n",
    "std = Ncount.std().item()\n",
    "print(f'The total Ncount is: {val: .2f} \\u00B1 {std: .2f}')\n",
    "\n",
    "val = total_Ncount_val.mean().item()\n",
    "std = total_Ncount_val.std().item()\n",
    "print(f'The total Ncount from fit is: {val: .2f} \\u00B1 {std: .2f}')\n",
    "\n",
    "val = BEC_Ncount_val.mean().item()\n",
    "std = BEC_Ncount_val.std().item()\n",
    "print(f'The Ncount of the BEC part is: {val: .2f} \\u00B1 {std: .2f}')\n",
    "\n",
    "val = thermal_Ncount_val.mean().item()\n",
    "std = thermal_Ncount_val.std().item()\n",
    "print(f'The Ncount of the thermal part is: {val: .2f} \\u00B1 {std: .2f}')\n",
    "\n",
    "val = BEC_width_x_val.mean().item()\n",
    "std = BEC_width_x_val.std().item()\n",
    "print(f'The x-axis width of the BEC part is: {val: .2f} \\u00B1 {std: .2f}')\n",
    "\n",
    "val = BEC_width_y_val.mean().item()\n",
    "std = BEC_width_y_val.std().item()\n",
    "print(f'The y-axis width of the BEC part is: {val: .2f} \\u00B1 {std: .2f}')\n",
    "\n",
    "val = thermal_width_x_val.mean().item()\n",
    "std = thermal_width_x_val.std().item()\n",
    "print(f'The x-axis width of the thermal part is: {val: .2f} \\u00B1 {std: .2f}')\n",
    "\n",
    "val = thermal_width_y_val.mean().item()\n",
    "std = thermal_width_y_val.std().item()\n",
    "print(f'The y-axis width of the thermal part is: {val: .2f} \\u00B1 {std: .2f}')\n",
    "\n",
    "val = BEC_center_x_val.mean().item()\n",
    "std = BEC_center_x_val.std().item()\n",
    "print(f'The x-axis center of the BEC part is: {val: .2f} \\u00B1 {std: .2f}')\n",
    "\n",
    "val = BEC_center_y_val.mean().item()\n",
    "std = BEC_center_y_val.std().item()\n",
    "print(f'The y-axis center of the BEC part is: {val: .2f} \\u00B1 {std: .2f}')\n",
    "\n",
    "val = thermal_center_x_val.mean().item()\n",
    "std = thermal_center_x_val.std().item()\n",
    "print(f'The x-axis center of the thermal part is: {val: .2f} \\u00B1 {std: .2f}')\n",
    "\n",
    "val = thermal_center_y_val.mean().item()\n",
    "std = thermal_center_y_val.std().item()\n",
    "print(f'The y-axis center of the thermal part is: {val: .2f} \\u00B1 {std: .2f}')\n",
    "\n",
    "val = condensateFraction_value.mean().item()\n",
    "std = condensateFraction_value.std().item()\n",
    "print(f'The condensate fraction is: {val: .4f} \\u00B1 {std: .4f}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
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       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
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       "  margin-right: 10px;\n",
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       "\n",
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       "\n",
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       "  width: 15px;\n",
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       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
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       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
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       "\n",
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       "\n",
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       "\n",
       ".xr-section-details {\n",
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       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
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       "\n",
       ".xr-array-wrap {\n",
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       "\n",
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       "\n",
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       "  grid-column: 2;\n",
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       "\n",
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       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
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       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
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       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
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       "\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",
       ".xr-dim-list li:not(:last-child):after {\n",
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       "\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",
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       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
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       "\n",
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       "\n",
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       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
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       ".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",
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       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
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       "  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: 550)\n",
       "Coordinates:\n",
       "  * runs     (runs) float64 0.0 1.0 2.0 3.0 4.0 ... 546.0 547.0 548.0 549.0\n",
       "Data variables:\n",
       "    runTine  (runs) datetime64[ns] 2023-05-09T14:30:03 ... 2023-05-09T15:56:53\n",
       "Attributes: (12/101)\n",
       "    TOF_free:                          0.02\n",
       "    abs_img_freq:                      110.858\n",
       "    absorption_imaging_flag:           True\n",
       "    backup_data:                       True\n",
       "    blink_off_time:                    nan\n",
       "    blink_on_time:                     nan\n",
       "    ...                                ...\n",
       "    y_offset_img:                      0\n",
       "    z_offset:                          0.189\n",
       "    z_offset_img:                      0.189\n",
       "    runs:                              [  0.   1.   2.   3.   4.   5.   6.   ...\n",
       "    scanAxis:                          [&#x27;runs&#x27;]\n",
       "    scanAxisLength:                    [550.]</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-ddf8c0d4-fd62-4c9d-92fd-966540ef3e7b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ddf8c0d4-fd62-4c9d-92fd-966540ef3e7b' 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>: 550</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-479e9297-4700-45b8-b6cd-9392bcc63bfc' class='xr-section-summary-in' type='checkbox'  checked><label for='section-479e9297-4700-45b8-b6cd-9392bcc63bfc' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>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 ... 547.0 548.0 549.0</div><input id='attrs-fc27e770-fcb1-4dd4-8e45-98154ef6f686' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fc27e770-fcb1-4dd4-8e45-98154ef6f686' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1ac5a3e4-e181-45f8-beb6-c6d55a9238b1' class='xr-var-data-in' type='checkbox'><label for='data-1ac5a3e4-e181-45f8-beb6-c6d55a9238b1' 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., ..., 547., 548., 549.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e9bc9bad-b00e-45b9-9526-eacd740499bc' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e9bc9bad-b00e-45b9-9526-eacd740499bc' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>runTine</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2023-05-09T14:30:03 ... 2023-05-...</div><input id='attrs-178bc396-32dc-467e-a4fa-1ecbccbecc8a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-178bc396-32dc-467e-a4fa-1ecbccbecc8a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d8375792-148d-47f7-b22e-84c6f3bc34a7' class='xr-var-data-in' type='checkbox'><label for='data-d8375792-148d-47f7-b22e-84c6f3bc34a7' 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([&#x27;2023-05-09T14:30:03.000000000&#x27;, &#x27;2023-05-09T14:30:11.000000000&#x27;,\n",
       "       &#x27;2023-05-09T14:30:19.000000000&#x27;, &#x27;2023-05-09T14:30:27.000000000&#x27;,\n",
       "       &#x27;2023-05-09T14:30:35.000000000&#x27;, &#x27;2023-05-09T14:30:43.000000000&#x27;,\n",
       "       &#x27;2023-05-09T14:30:52.000000000&#x27;, &#x27;2023-05-09T14:31:00.000000000&#x27;,\n",
       "       &#x27;2023-05-09T14:31:08.000000000&#x27;, &#x27;2023-05-09T14:31:16.000000000&#x27;,\n",
       "       &#x27;2023-05-09T14:31:24.000000000&#x27;, &#x27;2023-05-09T14:31:33.000000000&#x27;,\n",
       "       &#x27;2023-05-09T14:31:41.000000000&#x27;, &#x27;2023-05-09T14:31:49.000000000&#x27;,\n",
       "       &#x27;2023-05-09T14:31:57.000000000&#x27;, &#x27;2023-05-09T14:32:05.000000000&#x27;,\n",
       "       &#x27;2023-05-09T14:32:13.000000000&#x27;, &#x27;2023-05-09T14:32:22.000000000&#x27;,\n",
       "       &#x27;2023-05-09T14:32:30.000000000&#x27;, &#x27;2023-05-09T14:32:38.000000000&#x27;,\n",
       "       &#x27;2023-05-09T14:32:46.000000000&#x27;, &#x27;2023-05-09T14:32:54.000000000&#x27;,\n",
       "       &#x27;2023-05-09T14:33:03.000000000&#x27;, &#x27;2023-05-09T14:33:11.000000000&#x27;,\n",
       "       &#x27;2023-05-09T14:33:19.000000000&#x27;, &#x27;2023-05-09T14:33:27.000000000&#x27;,\n",
       "       &#x27;2023-05-09T14:33:35.000000000&#x27;, &#x27;2023-05-09T14:33:44.000000000&#x27;,\n",
       "       &#x27;2023-05-09T14:33:52.000000000&#x27;, &#x27;2023-05-09T14:34:00.000000000&#x27;,\n",
       "       &#x27;2023-05-09T14:34:08.000000000&#x27;, &#x27;2023-05-09T14:34:16.000000000&#x27;,\n",
       "       &#x27;2023-05-09T14:34:24.000000000&#x27;, &#x27;2023-05-09T14:34:32.000000000&#x27;,\n",
       "       &#x27;2023-05-09T14:34:41.000000000&#x27;, &#x27;2023-05-09T14:34:49.000000000&#x27;,\n",
       "       &#x27;2023-05-09T14:34:57.000000000&#x27;, &#x27;2023-05-09T14:35:05.000000000&#x27;,\n",
       "       &#x27;2023-05-09T14:35:13.000000000&#x27;, &#x27;2023-05-09T14:35:21.000000000&#x27;,\n",
       "...\n",
       "       &#x27;2023-05-09T15:51:57.000000000&#x27;, &#x27;2023-05-09T15:52:05.000000000&#x27;,\n",
       "       &#x27;2023-05-09T15:52:13.000000000&#x27;, &#x27;2023-05-09T15:52:21.000000000&#x27;,\n",
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       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-98cb9dc3-3874-4279-a93f-f6a454cb0e4a' class='xr-section-summary-in' type='checkbox'  ><label for='section-98cb9dc3-3874-4279-a93f-f6a454cb0e4a' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>runs</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3dc46abb-e999-4ea2-bc98-705d8880370d' class='xr-index-data-in' type='checkbox'/><label for='index-3dc46abb-e999-4ea2-bc98-705d8880370d' 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,   5.0,   6.0,   7.0,   8.0,\n",
       "                9.0,\n",
       "              ...\n",
       "              540.0, 541.0, 542.0, 543.0, 544.0, 545.0, 546.0, 547.0, 548.0,\n",
       "              549.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;runs&#x27;, length=550))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-460c6fd0-04c4-4397-9c75-2fa61d0ae7bb' class='xr-section-summary-in' type='checkbox'  ><label for='section-460c6fd0-04c4-4397-9c75-2fa61d0ae7bb' class='xr-section-summary' >Attributes: <span>(101)</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>110.858</dd><dt><span>absorption_imaging_flag :</span></dt><dd>True</dd><dt><span>backup_data :</span></dt><dd>True</dd><dt><span>blink_off_time :</span></dt><dd>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>0.005</dd><dt><span>compX_initial_current :</span></dt><dd>0.005</dd><dt><span>compY_current :</span></dt><dd>0</dd><dt><span>compY_current_sg :</span></dt><dd>0</dd><dt><span>compY_final_current :</span></dt><dd>0.0</dd><dt><span>compY_initial_current :</span></dt><dd>0</dd><dt><span>compZ_current :</span></dt><dd>0</dd><dt><span>compZ_current_sg :</span></dt><dd>0.189</dd><dt><span>compZ_final_current :</span></dt><dd>0.2729</dd><dt><span>compZ_initial_current :</span></dt><dd>0</dd><dt><span>default_camera :</span></dt><dd>0</dd><dt><span>evap_1_arm_1_final_pow :</span></dt><dd>0.35</dd><dt><span>evap_1_arm_1_mod_depth_final :</span></dt><dd>0</dd><dt><span>evap_1_arm_1_mod_depth_initial :</span></dt><dd>1.0</dd><dt><span>evap_1_arm_1_mod_ramp_duration :</span></dt><dd>1.15</dd><dt><span>evap_1_arm_1_pow_ramp_duration :</span></dt><dd>1.65</dd><dt><span>evap_1_arm_1_start_pow :</span></dt><dd>7</dd><dt><span>evap_1_arm_2_final_pow :</span></dt><dd>5</dd><dt><span>evap_1_arm_2_ramp_duration :</span></dt><dd>0.5</dd><dt><span>evap_1_arm_2_start_pow :</span></dt><dd>0</dd><dt><span>evap_1_mod_ramp_trunc_value :</span></dt><dd>1</dd><dt><span>evap_1_pow_ramp_trunc_value :</span></dt><dd>1.0</dd><dt><span>evap_1_rate_constant_1 :</span></dt><dd>0.525</dd><dt><span>evap_1_rate_constant_2 :</span></dt><dd>0.51</dd><dt><span>evap_2_arm_1_final_pow :</span></dt><dd>0.037</dd><dt><span>evap_2_arm_1_start_pow :</span></dt><dd>0.35</dd><dt><span>evap_2_arm_2_final_pow :</span></dt><dd>0.09</dd><dt><span>evap_2_arm_2_start_pow :</span></dt><dd>5</dd><dt><span>evap_2_ramp_duration :</span></dt><dd>1.0</dd><dt><span>evap_2_ramp_trunc_value :</span></dt><dd>1.0</dd><dt><span>evap_2_rate_constant_1 :</span></dt><dd>0.37</dd><dt><span>evap_2_rate_constant_2 :</span></dt><dd>0.71</dd><dt><span>evap_3_arm_1_final_pow :</span></dt><dd>0.1038</dd><dt><span>evap_3_arm_1_mod_depth_final :</span></dt><dd>0.43</dd><dt><span>evap_3_arm_1_mod_depth_initial :</span></dt><dd>0</dd><dt><span>evap_3_arm_1_start_pow :</span></dt><dd>0.037</dd><dt><span>evap_3_ramp_duration :</span></dt><dd>0.1</dd><dt><span>evap_3_ramp_trunc_value :</span></dt><dd>1.0</dd><dt><span>evap_3_rate_constant_1 :</span></dt><dd>-0.879</dd><dt><span>evap_3_rate_constant_2 :</span></dt><dd>-0.297</dd><dt><span>final_amp :</span></dt><dd>0.0001</dd><dt><span>final_freq :</span></dt><dd>104.0</dd><dt><span>gradCoil_current :</span></dt><dd>0.18</dd><dt><span>gradCoil_current_sg :</span></dt><dd>0</dd><dt><span>imaging_method :</span></dt><dd>in_situ_absorption</dd><dt><span>imaging_pulse_duration :</span></dt><dd>2.5e-05</dd><dt><span>imaging_wavelength :</span></dt><dd>4.21291e-07</dd><dt><span>initial_amp :</span></dt><dd>0.62</dd><dt><span>initial_freq :</span></dt><dd>102.13</dd><dt><span>mod_depth_initial :</span></dt><dd>1.0</dd><dt><span>mot_3d_amp :</span></dt><dd>0.62</dd><dt><span>mot_3d_camera_exposure_time :</span></dt><dd>0.002</dd><dt><span>mot_3d_camera_tri
       "  14.  15.  16.  17.  18.  19.  20.  21.  22.  23.  24.  25.  26.  27.\n",
       "  28.  29.  30.  31.  32.  33.  34.  35.  36.  37.  38.  39.  40.  41.\n",
       "  42.  43.  44.  45.  46.  47.  48.  49.  50.  51.  52.  53.  54.  55.\n",
       "  56.  57.  58.  59.  60.  61.  62.  63.  64.  65.  66.  67.  68.  69.\n",
       "  70.  71.  72.  73.  74.  75.  76.  77.  78.  79.  80.  81.  82.  83.\n",
       "  84.  85.  86.  87.  88.  89.  90.  91.  92.  93.  94.  95.  96.  97.\n",
       "  98.  99. 100. 101. 102. 103. 104. 105. 106. 107. 108. 109. 110. 111.\n",
       " 112. 113. 114. 115. 116. 117. 118. 119. 120. 121. 122. 123. 124. 125.\n",
       " 126. 127. 128. 129. 130. 131. 132. 133. 134. 135. 136. 137. 138. 139.\n",
       " 140. 141. 142. 143. 144. 145. 146. 147. 148. 149. 150. 151. 152. 153.\n",
       " 154. 155. 156. 157. 158. 159. 160. 161. 162. 163. 164. 165. 166. 167.\n",
       " 168. 169. 170. 171. 172. 173. 174. 175. 176. 177. 178. 179. 180. 181.\n",
       " 182. 183. 184. 185. 186. 187. 188. 189. 190. 191. 192. 193. 194. 195.\n",
       " 196. 197. 198. 199. 200. 201. 202. 203. 204. 205. 206. 207. 208. 209.\n",
       " 210. 211. 212. 213. 214. 215. 216. 217. 218. 219. 220. 221. 222. 223.\n",
       " 224. 225. 226. 227. 228. 229. 230. 231. 232. 233. 234. 235. 236. 237.\n",
       " 238. 239. 240. 241. 242. 243. 244. 245. 246. 247. 248. 249. 250. 251.\n",
       " 252. 253. 254. 255. 256. 257. 258. 259. 260. 261. 262. 263. 264. 265.\n",
       " 266. 267. 268. 269. 270. 271. 272. 273. 274. 275. 276. 277. 278. 279.\n",
       " 280. 281. 282. 283. 284. 285. 286. 287. 288. 289. 290. 291. 292. 293.\n",
       " 294. 295. 296. 297. 298. 299. 300. 301. 302. 303. 304. 305. 306. 307.\n",
       " 308. 309. 310. 311. 312. 313. 314. 315. 316. 317. 318. 319. 320. 321.\n",
       " 322. 323. 324. 325. 326. 327. 328. 329. 330. 331. 332. 333. 334. 335.\n",
       " 336. 337. 338. 339. 340. 341. 342. 343. 344. 345. 346. 347. 348. 349.\n",
       " 350. 351. 352. 353. 354. 355. 356. 357. 358. 359. 360. 361. 362. 363.\n",
       " 364. 365. 366. 367. 368. 369. 370. 371. 372. 373. 374. 375. 376. 377.\n",
       " 378. 379. 380. 381. 382. 383. 384. 385. 386. 387. 388. 389. 390. 391.\n",
       " 392. 393. 394. 395. 396. 397. 398. 399. 400. 401. 402. 403. 404. 405.\n",
       " 406. 407. 408. 409. 410. 411. 412. 413. 414. 415. 416. 417. 418. 419.\n",
       " 420. 421. 422. 423. 424. 425. 426. 427. 428. 429. 430. 431. 432. 433.\n",
       " 434. 435. 436. 437. 438. 439. 440. 441. 442. 443. 444. 445. 446. 447.\n",
       " 448. 449. 450. 451. 452. 453. 454. 455. 456. 457. 458. 459. 460. 461.\n",
       " 462. 463. 464. 465. 466. 467. 468. 469. 470. 471. 472. 473. 474. 475.\n",
       " 476. 477. 478. 479. 480. 481. 482. 483. 484. 485. 486. 487. 488. 489.\n",
       " 490. 491. 492. 493. 494. 495. 496. 497. 498. 499. 500. 501. 502. 503.\n",
       " 504. 505. 506. 507. 508. 509. 510. 511. 512. 513. 514. 515. 516. 517.\n",
       " 518. 519. 520. 521. 522. 523. 524. 525. 526. 527. 528. 529. 530. 531.\n",
       " 532. 533. 534. 535. 536. 537. 538. 539. 540. 541. 542. 543. 544. 545.\n",
       " 546. 547. 548. 549.]</dd><dt><span>scanAxis :</span></dt><dd>[&#x27;runs&#x27;]</dd><dt><span>scanAxisLength :</span></dt><dd>[550.]</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (runs: 550)\n",
       "Coordinates:\n",
       "  * runs     (runs) float64 0.0 1.0 2.0 3.0 4.0 ... 546.0 547.0 548.0 549.0\n",
       "Data variables:\n",
       "    runTine  (runs) datetime64[ns] 2023-05-09T14:30:03 ... 2023-05-09T15:56:53\n",
       "Attributes: (12/101)\n",
       "    TOF_free:                          0.02\n",
       "    abs_img_freq:                      110.858\n",
       "    absorption_imaging_flag:           True\n",
       "    backup_data:                       True\n",
       "    blink_off_time:                    nan\n",
       "    blink_on_time:                     nan\n",
       "    ...                                ...\n",
       "    y_offset_img:                      0\n",
       "    z_offset:                          0.189\n",
       "    z_offset_img:                      0.189\n",
       "    runs:                              [  0.   1.   2.   3.   4.   5.   6.   ...\n",
       "    scanAxis:                          ['runs']\n",
       "    scanAxisLength:                    [550.]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "i=0\n",
    "runTime = read_hdf5_run_time(filePath, datesetOfGlobal=dataSetOfGlobalDict[dskey[groupList[i]]])\n",
    "runTime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
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       "\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.DataArray &#x27;OD&#x27; (time: 550)&gt;\n",
       "array([ 750.47641876,  738.34281204,  784.41476569,  796.02169322,\n",
       "        952.51855344,  882.92079597,  863.59651678,  866.57709198,\n",
       "        941.99125428,  783.16551019,  946.27689189,  918.33176133,\n",
       "        941.81141492,  947.74774665,  892.61913887,  977.17520626,\n",
       "        945.34126351,  956.52682689,  804.78165476,  939.49484698,\n",
       "        953.56682753,  879.61475127,  846.05592616,  830.90774024,\n",
       "        910.80224254,  839.43361196,  863.23083974,  873.50170576,\n",
       "        850.29285459,  949.59349556,  707.93266373,  946.74069024,\n",
       "        941.71185143,  946.57095286,  914.32343568,  947.09283187,\n",
       "        954.03294364,  784.23261906,  786.97273688,  832.62952621,\n",
       "        903.46885276,  794.84132388,  987.33131008,  920.97693631,\n",
       "        982.49210229,  790.82171889,  796.04783468,  672.41580595,\n",
       "        726.07270248,  709.64654892,  820.34697312,  839.24755133,\n",
       "        830.20821813,  905.60581009,  832.01909227,  614.3819873 ,\n",
       "        723.89815083,  930.88065587,  825.30243762,  842.16853182,\n",
       "        960.03822443,  970.87588969,  867.93951095,  796.77918204,\n",
       "        715.07236109,  867.86554561,  949.15778283,  938.56330193,\n",
       "        857.52360377,  880.71776388,  856.94886599,  923.54732893,\n",
       "        840.56332593,  934.82056594,  938.21743126,  841.27262899,\n",
       "        935.776538  ,  810.94173848,  926.17365109,  746.68729357,\n",
       "...\n",
       "        865.51482127,  833.61692314,  821.20906768,  933.87516973,\n",
       "        810.80092789,  824.63722508,  859.85285532,  913.23783203,\n",
       "        789.32182143,  814.52479359,  843.87902457,  857.31154799,\n",
       "        896.47897516,  872.95758519,  761.01860691,  806.85333498,\n",
       "        947.18607913,  882.95786654,  660.90304299,  779.06534297,\n",
       "        824.68260644,  960.00725562,  931.83023265,  925.32091745,\n",
       "        876.67147414,  808.28701944,  865.12927984,  907.22865863,\n",
       "        849.53390823,  827.70871779,  726.90703872,  878.79705242,\n",
       "        960.28888691,  750.46295033,  903.46216093,  862.60511899,\n",
       "        956.07697944,  881.35524969,  837.32695128,  791.87607618,\n",
       "        811.78036383,  902.4373154 ,  942.28581666,  874.3906838 ,\n",
       "        896.64409276,  787.28302139,  963.13514734,  877.87315412,\n",
       "        833.86614596,  826.5946265 ,  735.16788438,  922.53477054,\n",
       "        880.6268579 ,  867.12639832,  852.01398293,  828.11720597,\n",
       "        891.6310036 ,  807.47838578,  895.25022758,  822.18630467,\n",
       "        943.8055441 ,  845.66585589,  729.57792525,  884.88667118,\n",
       "        796.64506694,  855.18595889,  803.11938466,  832.46778894,\n",
       "        858.2150589 ,  937.40605043,  853.13728532,  910.90015676,\n",
       "        780.99561864,  883.83375992,  804.26394636,  978.32360651,\n",
       "        901.75651529,  884.02352999])\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 2023-05-09T14:30:03 ... 2023-05-09T15:56:53</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'>time</span>: 550</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-e8116ef4-0e4f-47e2-bdc8-72f693fa923d' class='xr-array-in' type='checkbox' checked><label for='section-e8116ef4-0e4f-47e2-bdc8-72f693fa923d' 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>750.5 738.3 784.4 796.0 952.5 882.9 ... 883.8 804.3 978.3 901.8 884.0</span></div><div class='xr-array-data'><pre>array([ 750.47641876,  738.34281204,  784.41476569,  796.02169322,\n",
       "        952.51855344,  882.92079597,  863.59651678,  866.57709198,\n",
       "        941.99125428,  783.16551019,  946.27689189,  918.33176133,\n",
       "        941.81141492,  947.74774665,  892.61913887,  977.17520626,\n",
       "        945.34126351,  956.52682689,  804.78165476,  939.49484698,\n",
       "        953.56682753,  879.61475127,  846.05592616,  830.90774024,\n",
       "        910.80224254,  839.43361196,  863.23083974,  873.50170576,\n",
       "        850.29285459,  949.59349556,  707.93266373,  946.74069024,\n",
       "        941.71185143,  946.57095286,  914.32343568,  947.09283187,\n",
       "        954.03294364,  784.23261906,  786.97273688,  832.62952621,\n",
       "        903.46885276,  794.84132388,  987.33131008,  920.97693631,\n",
       "        982.49210229,  790.82171889,  796.04783468,  672.41580595,\n",
       "        726.07270248,  709.64654892,  820.34697312,  839.24755133,\n",
       "        830.20821813,  905.60581009,  832.01909227,  614.3819873 ,\n",
       "        723.89815083,  930.88065587,  825.30243762,  842.16853182,\n",
       "        960.03822443,  970.87588969,  867.93951095,  796.77918204,\n",
       "        715.07236109,  867.86554561,  949.15778283,  938.56330193,\n",
       "        857.52360377,  880.71776388,  856.94886599,  923.54732893,\n",
       "        840.56332593,  934.82056594,  938.21743126,  841.27262899,\n",
       "        935.776538  ,  810.94173848,  926.17365109,  746.68729357,\n",
       "...\n",
       "        865.51482127,  833.61692314,  821.20906768,  933.87516973,\n",
       "        810.80092789,  824.63722508,  859.85285532,  913.23783203,\n",
       "        789.32182143,  814.52479359,  843.87902457,  857.31154799,\n",
       "        896.47897516,  872.95758519,  761.01860691,  806.85333498,\n",
       "        947.18607913,  882.95786654,  660.90304299,  779.06534297,\n",
       "        824.68260644,  960.00725562,  931.83023265,  925.32091745,\n",
       "        876.67147414,  808.28701944,  865.12927984,  907.22865863,\n",
       "        849.53390823,  827.70871779,  726.90703872,  878.79705242,\n",
       "        960.28888691,  750.46295033,  903.46216093,  862.60511899,\n",
       "        956.07697944,  881.35524969,  837.32695128,  791.87607618,\n",
       "        811.78036383,  902.4373154 ,  942.28581666,  874.3906838 ,\n",
       "        896.64409276,  787.28302139,  963.13514734,  877.87315412,\n",
       "        833.86614596,  826.5946265 ,  735.16788438,  922.53477054,\n",
       "        880.6268579 ,  867.12639832,  852.01398293,  828.11720597,\n",
       "        891.6310036 ,  807.47838578,  895.25022758,  822.18630467,\n",
       "        943.8055441 ,  845.66585589,  729.57792525,  884.88667118,\n",
       "        796.64506694,  855.18595889,  803.11938466,  832.46778894,\n",
       "        858.2150589 ,  937.40605043,  853.13728532,  910.90015676,\n",
       "        780.99561864,  883.83375992,  804.26394636,  978.32360651,\n",
       "        901.75651529,  884.02352999])</pre></div></div></li><li class='xr-section-item'><input id='section-abe1e5af-4b5a-4c83-972f-6282f5ca537c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-abe1e5af-4b5a-4c83-972f-6282f5ca537c' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2023-05-09T14:30:03 ... 2023-05-...</div><input id='attrs-ef2accb5-ed39-403d-9411-b78f70b11a1f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ef2accb5-ed39-403d-9411-b78f70b11a1f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e90b44e7-6e09-42e0-be54-fa6a148df7d6' class='xr-var-data-in' type='checkbox'><label for='data-e90b44e7-6e09-42e0-be54-fa6a148df7d6' 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([&#x27;2023-05-09T14:30:03.000000000&#x27;, &#x27;2023-05-09T14:30:11.000000000&#x27;,\n",
       "       &#x27;2023-05-09T14:30:19.000000000&#x27;, ..., &#x27;2023-05-09T15:56:37.000000000&#x27;,\n",
       "       &#x27;2023-05-09T15:56:45.000000000&#x27;, &#x27;2023-05-09T15:56:53.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2eb9b7d3-a0a5-47ef-9495-ce3b0d00ac3a' class='xr-section-summary-in' type='checkbox'  ><label for='section-2eb9b7d3-a0a5-47ef-9495-ce3b0d00ac3a' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ef87f2e7-6012-43f8-bb7a-41b1aff4bd81' class='xr-index-data-in' type='checkbox'/><label for='index-ef87f2e7-6012-43f8-bb7a-41b1aff4bd81' 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(DatetimeIndex([&#x27;2023-05-09 14:30:03&#x27;, &#x27;2023-05-09 14:30:11&#x27;,\n",
       "               &#x27;2023-05-09 14:30:19&#x27;, &#x27;2023-05-09 14:30:27&#x27;,\n",
       "               &#x27;2023-05-09 14:30:35&#x27;, &#x27;2023-05-09 14:30:43&#x27;,\n",
       "               &#x27;2023-05-09 14:30:52&#x27;, &#x27;2023-05-09 14:31:00&#x27;,\n",
       "               &#x27;2023-05-09 14:31:08&#x27;, &#x27;2023-05-09 14:31:16&#x27;,\n",
       "               ...\n",
       "               &#x27;2023-05-09 15:55:41&#x27;, &#x27;2023-05-09 15:55:49&#x27;,\n",
       "               &#x27;2023-05-09 15:55:57&#x27;, &#x27;2023-05-09 15:56:05&#x27;,\n",
       "               &#x27;2023-05-09 15:56:13&#x27;, &#x27;2023-05-09 15:56:21&#x27;,\n",
       "               &#x27;2023-05-09 15:56:29&#x27;, &#x27;2023-05-09 15:56:37&#x27;,\n",
       "               &#x27;2023-05-09 15:56:45&#x27;, &#x27;2023-05-09 15:56:53&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=550, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a460649b-2bf6-46a3-8232-16166a9bfe58' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a460649b-2bf6-46a3-8232-16166a9bfe58' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'OD' (time: 550)>\n",
       "array([ 750.47641876,  738.34281204,  784.41476569,  796.02169322,\n",
       "        952.51855344,  882.92079597,  863.59651678,  866.57709198,\n",
       "        941.99125428,  783.16551019,  946.27689189,  918.33176133,\n",
       "        941.81141492,  947.74774665,  892.61913887,  977.17520626,\n",
       "        945.34126351,  956.52682689,  804.78165476,  939.49484698,\n",
       "        953.56682753,  879.61475127,  846.05592616,  830.90774024,\n",
       "        910.80224254,  839.43361196,  863.23083974,  873.50170576,\n",
       "        850.29285459,  949.59349556,  707.93266373,  946.74069024,\n",
       "        941.71185143,  946.57095286,  914.32343568,  947.09283187,\n",
       "        954.03294364,  784.23261906,  786.97273688,  832.62952621,\n",
       "        903.46885276,  794.84132388,  987.33131008,  920.97693631,\n",
       "        982.49210229,  790.82171889,  796.04783468,  672.41580595,\n",
       "        726.07270248,  709.64654892,  820.34697312,  839.24755133,\n",
       "        830.20821813,  905.60581009,  832.01909227,  614.3819873 ,\n",
       "        723.89815083,  930.88065587,  825.30243762,  842.16853182,\n",
       "        960.03822443,  970.87588969,  867.93951095,  796.77918204,\n",
       "        715.07236109,  867.86554561,  949.15778283,  938.56330193,\n",
       "        857.52360377,  880.71776388,  856.94886599,  923.54732893,\n",
       "        840.56332593,  934.82056594,  938.21743126,  841.27262899,\n",
       "        935.776538  ,  810.94173848,  926.17365109,  746.68729357,\n",
       "...\n",
       "        865.51482127,  833.61692314,  821.20906768,  933.87516973,\n",
       "        810.80092789,  824.63722508,  859.85285532,  913.23783203,\n",
       "        789.32182143,  814.52479359,  843.87902457,  857.31154799,\n",
       "        896.47897516,  872.95758519,  761.01860691,  806.85333498,\n",
       "        947.18607913,  882.95786654,  660.90304299,  779.06534297,\n",
       "        824.68260644,  960.00725562,  931.83023265,  925.32091745,\n",
       "        876.67147414,  808.28701944,  865.12927984,  907.22865863,\n",
       "        849.53390823,  827.70871779,  726.90703872,  878.79705242,\n",
       "        960.28888691,  750.46295033,  903.46216093,  862.60511899,\n",
       "        956.07697944,  881.35524969,  837.32695128,  791.87607618,\n",
       "        811.78036383,  902.4373154 ,  942.28581666,  874.3906838 ,\n",
       "        896.64409276,  787.28302139,  963.13514734,  877.87315412,\n",
       "        833.86614596,  826.5946265 ,  735.16788438,  922.53477054,\n",
       "        880.6268579 ,  867.12639832,  852.01398293,  828.11720597,\n",
       "        891.6310036 ,  807.47838578,  895.25022758,  822.18630467,\n",
       "        943.8055441 ,  845.66585589,  729.57792525,  884.88667118,\n",
       "        796.64506694,  855.18595889,  803.11938466,  832.46778894,\n",
       "        858.2150589 ,  937.40605043,  853.13728532,  910.90015676,\n",
       "        780.99561864,  883.83375992,  804.26394636,  978.32360651,\n",
       "        901.75651529,  884.02352999])\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 2023-05-09T14:30:03 ... 2023-05-09T15:56:53"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Ncount_time = xr.DataArray(\n",
    "    data=Ncount,\n",
    "    dims=[\"time\"],\n",
    "    coords={\n",
    "        \"time\": runTime.runTine.to_numpy(),\n",
    "    }\n",
    ")\n",
    "Ncount_time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1831c4c6fa0>]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Ncount_time.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0, 70000.0)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Ncount_time_interp = Ncount_time.interp(time=pd.date_range(\"2023-05-09T14:30:03.000000000\", \"2023-05-09T15:56:53.000000000\", periods=500))\n",
    "da_fft = xrft.fft(Ncount_time_interp)\n",
    "da_fft_amp = np.abs(da_fft)\n",
    "# da_fft_amp.isel(freq_time=range(251,370)).plot()\n",
    "da_fft_amp.plot()\n",
    "# plt.xlim([-0.05, 0.05])\n",
    "plt.ylim([0, 7e4])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0, 70000.0)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# da_test2.isel(time=range(300)).plot()\n",
    "da_fft = xrft.fft(\n",
    "    Ncount_time.isel(time=range(300)).interp(\n",
    "        time=pd.date_range(\n",
    "            Ncount_time.time[0].item(), Ncount_time.time[299].item(), periods=300\n",
    "            # \"2023-05-09T14:30:03.000000000\", \"2023-05-09T15:10:06.000000000\", periods=300\n",
    "        )\n",
    "    )\n",
    ")\n",
    "# np.abs(da_fft).isel(freq_time=range(151,300)).plot()\n",
    "np.abs(da_fft).plot()\n",
    "# plt.xlim([0, 0.003])\n",
    "plt.ylim([0, 7e4])\n",
    "# plt.yscale(\"log\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "analyserDataArray = Ncount\n",
    "\n",
    "analyserDataArray_time = xr.DataArray(\n",
    "    data=analyserDataArray,\n",
    "    dims=[\"time\"],\n",
    "    coords={\n",
    "        \"time\": runTime.runTine.to_numpy(),\n",
    "    }\n",
    ")\n",
    "\n",
    "# desired number of Fourier modes (uniform outputs)\n",
    "N = 1001\n",
    "\n",
    "# calculate the transform\n",
    "analyserDataArray_time_array = analyserDataArray_time.to_numpy()\n",
    "analyserDataArray_time_array = np.array(analyserDataArray_time_array, dtype=complex)\n",
    "f = xr.DataArray(\n",
    "    data=finufft.nufft1d1(time, analyserDataArray_time_array, N),\n",
    "    dims=['time_freq'],\n",
    "    coords={\n",
    "        \"time_freq\":np.linspace(-0.125/2,0.125/2,N)\n",
    "    }\n",
    ")\n",
    "\n",
    "value = np.abs(f)\n",
    "value[int((N-1)/2)] = np.nan\n",
    "value.where(value.time_freq>0).plot()\n",
    "plt.xlim([0, 0.01])\n",
    "# plt.ylim([0, 2000])\n",
    "plt.xlabel('frequency (Hz)')\n",
    "plt.show()\n",
    "\n",
    "mask = xr.DataArray(\n",
    "    data = np.full(runTime.runTine.shape,fill_value=False, dtype=bool),\n",
    "    dims = [\"time\"],\n",
    "    coords = {\n",
    "        \"time\":runTime.runTine.to_numpy()\n",
    "    }\n",
    ")\n",
    "\n",
    "for i in range(len(mask)):\n",
    "    if (int(mask.time[i]) - 1683642540000000000) % 5.4e11 > 3.6e11:\n",
    "        mask[i] = True\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "xr.where(mask, np.nan, analyserDataArray_time).plot.errorbar(fmt='ob')\n",
    "analyserDataArray_time.where(mask).plot.errorbar(fmt='or')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "analyserDataArray = BEC_Ncount_val\n",
    "\n",
    "analyserDataArray_time = xr.DataArray(\n",
    "    data=analyserDataArray,\n",
    "    dims=[\"time\"],\n",
    "    coords={\n",
    "        \"time\": runTime.runTine.to_numpy(),\n",
    "    }\n",
    ")\n",
    "\n",
    "# desired number of Fourier modes (uniform outputs)\n",
    "N = 1001\n",
    "\n",
    "# calculate the transform\n",
    "analyserDataArray_time_array = analyserDataArray_time.to_numpy()\n",
    "analyserDataArray_time_array = np.array(analyserDataArray_time_array, dtype=complex)\n",
    "f = xr.DataArray(\n",
    "    data=finufft.nufft1d1(time, analyserDataArray_time_array, N),\n",
    "    dims=['time_freq'],\n",
    "    coords={\n",
    "        \"time_freq\":np.linspace(-0.125/2,0.125/2,N)\n",
    "    }\n",
    ")\n",
    "\n",
    "value = np.abs(f)\n",
    "value[int((N-1)/2)] = np.nan\n",
    "value.where(value.time_freq>0).plot()\n",
    "plt.xlim([0, 0.01])\n",
    "# plt.ylim([0, 2000])\n",
    "plt.show()\n",
    "\n",
    "mask = xr.DataArray(\n",
    "    data = np.full(runTime.runTine.shape,fill_value=False, dtype=bool),\n",
    "    dims = [\"time\"],\n",
    "    coords = {\n",
    "        \"time\":runTime.runTine.to_numpy()\n",
    "    }\n",
    ")\n",
    "\n",
    "for i in range(len(mask)):\n",
    "    if (int(mask.time[i]) - 1683642540000000000) % 5.4e11 > 3.6e11:\n",
    "        mask[i] = True\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "xr.where(mask, np.nan, analyserDataArray_time).plot.errorbar(fmt='ob')\n",
    "analyserDataArray_time.where(mask).plot.errorbar(fmt='or')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "analyserDataArray = BEC_width_x_val\n",
    "\n",
    "analyserDataArray_time = xr.DataArray(\n",
    "    data=analyserDataArray,\n",
    "    dims=[\"time\"],\n",
    "    coords={\n",
    "        \"time\": runTime.runTine.to_numpy(),\n",
    "    }\n",
    ")\n",
    "\n",
    "# desired number of Fourier modes (uniform outputs)\n",
    "N = 1001\n",
    "\n",
    "# calculate the transform\n",
    "analyserDataArray_time_array = analyserDataArray_time.to_numpy()\n",
    "analyserDataArray_time_array = np.array(analyserDataArray_time_array, dtype=complex)\n",
    "f = xr.DataArray(\n",
    "    data=finufft.nufft1d1(time, analyserDataArray_time_array, N),\n",
    "    dims=['time_freq'],\n",
    "    coords={\n",
    "        \"time_freq\":np.linspace(-0.125/2,0.125/2,N)\n",
    "    }\n",
    ")\n",
    "\n",
    "value = np.abs(f)\n",
    "value[int((N-1)/2)] = np.nan\n",
    "value.where(value.time_freq>0).plot()\n",
    "plt.xlim([0, 0.01])\n",
    "# plt.ylim([0, 2000])\n",
    "plt.show()\n",
    "\n",
    "mask = xr.DataArray(\n",
    "    data = np.full(runTime.runTine.shape,fill_value=False, dtype=bool),\n",
    "    dims = [\"time\"],\n",
    "    coords = {\n",
    "        \"time\":runTime.runTine.to_numpy()\n",
    "    }\n",
    ")\n",
    "\n",
    "for i in range(len(mask)):\n",
    "    if (int(mask.time[i]) - 1683642540000000000) % 5.4e11 > 3.6e11:\n",
    "        mask[i] = True\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "xr.where(mask, np.nan, analyserDataArray_time).plot.errorbar(fmt='ob')\n",
    "analyserDataArray_time.where(mask).plot.errorbar(fmt='or')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "analyserDataArray = thermal_width_y_val\n",
    "\n",
    "analyserDataArray_time = xr.DataArray(\n",
    "    data=analyserDataArray,\n",
    "    dims=[\"time\"],\n",
    "    coords={\n",
    "        \"time\": runTime.runTine.to_numpy(),\n",
    "    }\n",
    ")\n",
    "\n",
    "# desired number of Fourier modes (uniform outputs)\n",
    "N = 1001\n",
    "\n",
    "# calculate the transform\n",
    "analyserDataArray_time_array = analyserDataArray_time.to_numpy()\n",
    "analyserDataArray_time_array = np.array(analyserDataArray_time_array, dtype=complex)\n",
    "f = xr.DataArray(\n",
    "    data=finufft.nufft1d1(time, analyserDataArray_time_array, N),\n",
    "    dims=['time_freq'],\n",
    "    coords={\n",
    "        \"time_freq\":np.linspace(-0.125/2,0.125/2,N)\n",
    "    }\n",
    ")\n",
    "\n",
    "np.abs(f).plot()\n",
    "# plt.xlim([0, 0.01])\n",
    "# plt.ylim([0, 2000])\n",
    "plt.show()\n",
    "\n",
    "mask = xr.DataArray(\n",
    "    data = np.full(runTime.runTine.shape,fill_value=False, dtype=bool),\n",
    "    dims = [\"time\"],\n",
    "    coords = {\n",
    "        \"time\":runTime.runTine.to_numpy()\n",
    "    }\n",
    ")\n",
    "\n",
    "for i in range(len(mask)):\n",
    "    if (int(mask.time[i]) - 1683642540000000000) % 5.4e11 > 3.6e11:\n",
    "        mask[i] = True\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "xr.where(mask, np.nan, analyserDataArray_time).plot.errorbar(fmt='ob')\n",
    "analyserDataArray_time.where(mask).plot.errorbar(fmt='or')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "analyserDataArray = BEC_center_y_val\n",
    "\n",
    "analyserDataArray_time = xr.DataArray(\n",
    "    data=analyserDataArray,\n",
    "    dims=[\"time\"],\n",
    "    coords={\n",
    "        \"time\": runTime.runTine.to_numpy(),\n",
    "    }\n",
    ")\n",
    "\n",
    "# desired number of Fourier modes (uniform outputs)\n",
    "N = 1001\n",
    "\n",
    "# calculate the transform\n",
    "analyserDataArray_time_array = analyserDataArray_time.to_numpy()\n",
    "analyserDataArray_time_array = np.array(analyserDataArray_time_array, dtype=complex)\n",
    "f = xr.DataArray(\n",
    "    data=finufft.nufft1d1(time, analyserDataArray_time_array, N),\n",
    "    dims=['time_freq'],\n",
    "    coords={\n",
    "        \"time_freq\":np.linspace(-0.125/2,0.125/2,N)\n",
    "    }\n",
    ")\n",
    "\n",
    "np.abs(f).plot()\n",
    "# plt.xlim([0, 0.01])\n",
    "# plt.ylim([0, 2000])\n",
    "plt.show()\n",
    "\n",
    "mask = xr.DataArray(\n",
    "    data = np.full(runTime.runTine.shape,fill_value=False, dtype=bool),\n",
    "    dims = [\"time\"],\n",
    "    coords = {\n",
    "        \"time\":runTime.runTine.to_numpy()\n",
    "    }\n",
    ")\n",
    "\n",
    "for i in range(len(mask)):\n",
    "    if (int(mask.time[i]) - 1683642540000000000) % 5.4e11 > 3.6e11:\n",
    "        mask[i] = True\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "xr.where(mask, np.nan, analyserDataArray_time).plot.errorbar(fmt='ob')\n",
    "analyserDataArray_time.where(mask).plot.errorbar(fmt='or')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "analyserDataArray = thermal_center_y_val\n",
    "\n",
    "analyserDataArray_time = xr.DataArray(\n",
    "    data=analyserDataArray,\n",
    "    dims=[\"time\"],\n",
    "    coords={\n",
    "        \"time\": runTime.runTine.to_numpy(),\n",
    "    }\n",
    ")\n",
    "\n",
    "# desired number of Fourier modes (uniform outputs)\n",
    "N = 1001\n",
    "\n",
    "# calculate the transform\n",
    "analyserDataArray_time_array = analyserDataArray_time.to_numpy()\n",
    "analyserDataArray_time_array = np.array(analyserDataArray_time_array, dtype=complex)\n",
    "f = xr.DataArray(\n",
    "    data=finufft.nufft1d1(time, analyserDataArray_time_array, N),\n",
    "    dims=['time_freq'],\n",
    "    coords={\n",
    "        \"time_freq\":np.linspace(-0.125/2,0.125/2,N)\n",
    "    }\n",
    ")\n",
    "\n",
    "np.abs(f).plot()\n",
    "# plt.xlim([0, 0.01])\n",
    "# plt.ylim([0, 2000])\n",
    "plt.show()\n",
    "\n",
    "mask = xr.DataArray(\n",
    "    data = np.full(runTime.runTine.shape,fill_value=False, dtype=bool),\n",
    "    dims = [\"time\"],\n",
    "    coords = {\n",
    "        \"time\":runTime.runTine.to_numpy()\n",
    "    }\n",
    ")\n",
    "\n",
    "for i in range(len(mask)):\n",
    "    if (int(mask.time[i]) - 1683642540000000000) % 5.4e11 > 3.6e11:\n",
    "        mask[i] = True\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "xr.where(mask, np.nan, analyserDataArray_time).plot.errorbar(fmt='ob')\n",
    "analyserDataArray_time.where(mask).plot.errorbar(fmt='or')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "analyserDataArray = condensateFraction_value\n",
    "\n",
    "analyserDataArray_time = xr.DataArray(\n",
    "    data=analyserDataArray,\n",
    "    dims=[\"time\"],\n",
    "    coords={\n",
    "        \"time\": runTime.runTine.to_numpy(),\n",
    "    }\n",
    ")\n",
    "\n",
    "# desired number of Fourier modes (uniform outputs)\n",
    "N = 1001\n",
    "\n",
    "# calculate the transform\n",
    "analyserDataArray_time_array = analyserDataArray_time.to_numpy()\n",
    "analyserDataArray_time_array = np.array(analyserDataArray_time_array, dtype=complex)\n",
    "f = xr.DataArray(\n",
    "    data=finufft.nufft1d1(time, analyserDataArray_time_array, N),\n",
    "    dims=['time_freq'],\n",
    "    coords={\n",
    "        \"time_freq\":np.linspace(-0.125/2,0.125/2,N)\n",
    "    }\n",
    ")\n",
    "\n",
    "np.abs(f).plot()\n",
    "# plt.xlim([0, 0.01])\n",
    "# plt.ylim([0, 2000])\n",
    "plt.show()\n",
    "\n",
    "mask = xr.DataArray(\n",
    "    data = np.full(runTime.runTine.shape,fill_value=False, dtype=bool),\n",
    "    dims = [\"time\"],\n",
    "    coords = {\n",
    "        \"time\":runTime.runTine.to_numpy()\n",
    "    }\n",
    ")\n",
    "\n",
    "for i in range(len(mask)):\n",
    "    if (int(mask.time[i]) - 1683642540000000000) % 5.4e11 > 3.6e11:\n",
    "        mask[i] = True\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "xr.where(mask, np.nan, analyserDataArray_time).plot.errorbar(fmt='ob')\n",
    "analyserDataArray_time.where(mask).plot.errorbar(fmt='or')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Close to the BEC transition point, in evaporative cooling 2 with truncation value = 0.77"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "shotNum = \"0015\"\n",
    "filePath = folderPath + \"/\" + shotNum + \"/*.h5\"\n",
    "\n",
    "dataSetDict = {\n",
    "    dskey[groupList[i]]: read_hdf5_file(filePath, groupList[i])\n",
    "    for i in [0]\n",
    "}\n",
    "\n",
    "dataSet = dataSetDict[\"camera_0\"]\n",
    "\n",
    "print_scanAxis(dataSet)\n",
    "\n",
    "scanAxis = get_scanAxis(dataSet)\n",
    "\n",
    "dataSet = auto_rechunk(dataSet)\n",
    "\n",
    "dataSet = imageAnalyser.get_absorption_images(dataSet)\n",
    "\n",
    "imageAnalyser.center = (879, 956)\n",
    "imageAnalyser.span = (200, 200)\n",
    "imageAnalyser.fraction = (0.1, 0.1)\n",
    "\n",
    "dataSet_cropOD = imageAnalyser.crop_image(dataSet.OD)\n",
    "dataSet_cropOD = imageAnalyser.substract_offset(dataSet_cropOD).load()\n",
    "\n",
    "Ncount = imageAnalyser.get_Ncount(dataSet_cropOD).load()\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "Ncount.plot.errorbar(ax=ax, fmt='ob')\n",
    "\n",
    "plt.ylabel('NCount')\n",
    "plt.tight_layout()\n",
    "plt.grid(visible=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "Ncount.plot.errorbar(ax=ax, fmt='ob')\n",
    "plt.ylim([0, 3000])\n",
    "plt.ylabel('NCount')\n",
    "plt.tight_layout()\n",
    "plt.grid(visible=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "dataSet_cropOD = auto_rechunk(dataSet_cropOD)\n",
    "\n",
    "fitAnalyser = FitAnalyser(\"Gaussian-2D\", fitDim=2)\n",
    "params = fitAnalyser.guess(dataSet_cropOD, dask=\"parallelized\")\n",
    "fitResult = fitAnalyser.fit(dataSet_cropOD, params, dask=\"parallelized\").load()\n",
    "\n",
    "fitValue = fitAnalyser.get_fit_value(fitResult)\n",
    "fitStd = fitAnalyser.get_fit_std(fitResult)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "thermal_Ncount_val = fitValue['amplitude']\n",
    "thermal_Ncount_std = fitStd['amplitude']\n",
    "\n",
    "thermal_width_x_val = fitValue['sigmax']\n",
    "thermal_width_x_std = fitStd['sigmax']\n",
    "thermal_width_y_val = fitValue['sigmay']\n",
    "thermal_width_y_std = fitStd['sigmay']\n",
    "\n",
    "thermal_center_x_val = fitValue['centerx']\n",
    "thermal_center_x_std = fitStd['centerx']\n",
    "thermal_center_y_val = fitValue['centery']\n",
    "thermal_center_y_std = fitStd['centery']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "total_Ncount_val = thermal_Ncount_val\n",
    "total_Ncount_std = thermal_Ncount_std\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "total_Ncount_val.plot.errorbar(ax=ax, yerr=total_Ncount_std, fmt='ob')\n",
    "plt.ylim([0, 3000])\n",
    "plt.ylabel('Ncount from fit')\n",
    "plt.tight_layout()\n",
    "plt.grid(visible=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "thermal_width_x_val.plot.errorbar(ax=ax, yerr=thermal_width_x_std, fmt='or')\n",
    "\n",
    "plt.ylabel('X-axis width of thermal part')\n",
    "plt.tight_layout()\n",
    "plt.grid(visible=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "thermal_width_y_val.plot.errorbar(ax=ax, yerr=thermal_width_y_std, fmt='or')\n",
    "\n",
    "plt.ylabel('Y-axis width of thermal part')\n",
    "plt.tight_layout()\n",
    "plt.grid(visible=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "thermal_center_x_val.plot.errorbar(ax=ax, yerr=thermal_center_x_std, fmt='or')\n",
    "\n",
    "plt.ylabel('X-axis center of thermal part')\n",
    "plt.tight_layout()\n",
    "plt.grid(visible=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "thermal_center_y_val.plot.errorbar(ax=ax, yerr=thermal_center_y_std, fmt='or')\n",
    "\n",
    "plt.ylabel('Y-axis center of thermal part')\n",
    "plt.tight_layout()\n",
    "plt.grid(visible=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "val = Ncount.mean().item()\n",
    "std = Ncount.std().item()\n",
    "print(f'The total Ncount is: {val: .2f} \\u00B1 {std: .2f}')\n",
    "\n",
    "val = total_Ncount_val.mean().item()\n",
    "std = total_Ncount_val.std().item()\n",
    "print(f'The total Ncount from fit is: {val: .2f} \\u00B1 {std: .2f}')\n",
    "\n",
    "val = thermal_width_x_val.mean().item()\n",
    "std = thermal_width_x_val.std().item()\n",
    "print(f'The x-axis width of the thermal part is: {val: .2f} \\u00B1 {std: .2f}')\n",
    "\n",
    "val = thermal_width_y_val.mean().item()\n",
    "std = thermal_width_y_val.std().item()\n",
    "print(f'The y-axis width of the thermal part is: {val: .2f} \\u00B1 {std: .2f}')\n",
    "\n",
    "val = thermal_center_x_val.mean().item()\n",
    "std = thermal_center_x_val.std().item()\n",
    "print(f'The x-axis center of the thermal part is: {val: .2f} \\u00B1 {std: .2f}')\n",
    "\n",
    "val = thermal_center_y_val.mean().item()\n",
    "std = thermal_center_y_val.std().item()\n",
    "print(f'The y-axis center of the thermal part is: {val: .2f} \\u00B1 {std: .2f}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "i=0\n",
    "runTime = read_hdf5_run_time(filePath, datesetOfGlobal=dataSetOfGlobalDict[dskey[groupList[i]]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "analyserDataArray = Ncount\n",
    "\n",
    "analyserDataArray_time = xr.DataArray(\n",
    "    data=analyserDataArray,\n",
    "    dims=[\"time\"],\n",
    "    coords={\n",
    "        \"time\": runTime.runTine.to_numpy(),\n",
    "    }\n",
    ")\n",
    "\n",
    "# desired number of Fourier modes (uniform outputs)\n",
    "N = 1001\n",
    "\n",
    "# calculate the transform\n",
    "analyserDataArray_time_array = analyserDataArray_time.to_numpy()\n",
    "analyserDataArray_time_array = np.array(analyserDataArray_time_array, dtype=complex)\n",
    "f = xr.DataArray(\n",
    "    data=finufft.nufft1d1(time, analyserDataArray_time_array, N),\n",
    "    dims=['time_freq'],\n",
    "    coords={\n",
    "        \"time_freq\":np.linspace(-0.125/2,0.125/2,N)\n",
    "    }\n",
    ")\n",
    "\n",
    "value = np.abs(f)\n",
    "value[int((N-1)/2)] = np.nan\n",
    "value.where(value.time_freq>0).plot()\n",
    "plt.xlim([0, 0.01])\n",
    "# plt.ylim([0, 2000])\n",
    "plt.xlabel('frequency (Hz)')\n",
    "plt.show()\n",
    "\n",
    "mask = xr.DataArray(\n",
    "    data = np.full(runTime.runTine.shape,fill_value=False, dtype=bool),\n",
    "    dims = [\"time\"],\n",
    "    coords = {\n",
    "        \"time\":runTime.runTine.to_numpy()\n",
    "    }\n",
    ")\n",
    "\n",
    "for i in range(len(mask)):\n",
    "    if (int(mask.time[i]) - 1683642540000000000) % 5.4e11 > 3.6e11:\n",
    "        mask[i] = True\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "xr.where(mask, np.nan, analyserDataArray_time).plot.errorbar(fmt='ob')\n",
    "analyserDataArray_time.where(mask).plot.errorbar(fmt='or')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## At the end of ODT loading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "shotNum = \"0020\"\n",
    "filePath = folderPath + \"/\" + shotNum + \"/*.h5\"\n",
    "\n",
    "dataSetDict = {\n",
    "    dskey[groupList[i]]: read_hdf5_file(filePath, groupList[i])\n",
    "    for i in [0]\n",
    "}\n",
    "\n",
    "dataSet = dataSetDict[\"camera_0\"]\n",
    "\n",
    "print_scanAxis(dataSet)\n",
    "\n",
    "scanAxis = get_scanAxis(dataSet)\n",
    "\n",
    "dataSet = auto_rechunk(dataSet)\n",
    "\n",
    "dataSet = imageAnalyser.get_absorption_images(dataSet)\n",
    "\n",
    "imageAnalyser.center = (550, 800)\n",
    "imageAnalyser.span = (900, 1600)\n",
    "imageAnalyser.fraction = (0.1, 0.1)\n",
    "\n",
    "dataSet_cropOD = imageAnalyser.crop_image(dataSet.OD)\n",
    "dataSet_cropOD = imageAnalyser.substract_offset(dataSet_cropOD).load()\n",
    "\n",
    "Ncount = imageAnalyser.get_Ncount(dataSet_cropOD).load()\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "Ncount.plot.errorbar(ax=ax, fmt='ob')\n",
    "\n",
    "plt.ylabel('NCount')\n",
    "plt.tight_layout()\n",
    "plt.grid(visible=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "dataSet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "Ncount.plot.errorbar(ax=ax, fmt='ob')\n",
    "plt.ylim([0, 150000])\n",
    "plt.ylabel('NCount')\n",
    "plt.tight_layout()\n",
    "plt.grid(visible=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "dataSet_cropOD = dataSet_cropOD.chunk((1, 900, 1600))\n",
    "dataSet_cropOD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "# dataSet_cropOD = auto_rechunk(dataSet_cropOD)\n",
    "\n",
    "fitAnalyser = FitAnalyser(\"Gaussian-2D\", fitDim=2)\n",
    "params = fitAnalyser.guess(dataSet_cropOD, dask=\"parallelized\")\n",
    "fitResult = fitAnalyser.fit(dataSet_cropOD, params, dask=\"parallelized\").load()\n",
    "\n",
    "fitValue = fitAnalyser.get_fit_value(fitResult)\n",
    "fitStd = fitAnalyser.get_fit_std(fitResult)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "thermal_Ncount_val = fitValue['amplitude']\n",
    "thermal_Ncount_std = fitStd['amplitude']\n",
    "\n",
    "thermal_width_x_val = fitValue['sigmax']\n",
    "thermal_width_x_std = fitStd['sigmax']\n",
    "thermal_width_y_val = fitValue['sigmay']\n",
    "thermal_width_y_std = fitStd['sigmay']\n",
    "\n",
    "thermal_center_x_val = fitValue['centerx']\n",
    "thermal_center_x_std = fitStd['centerx']\n",
    "thermal_center_y_val = fitValue['centery']\n",
    "thermal_center_y_std = fitStd['centery']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "total_Ncount_val = thermal_Ncount_val\n",
    "total_Ncount_std = thermal_Ncount_std\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "total_Ncount_val.plot.errorbar(ax=ax, yerr=total_Ncount_std, fmt='ob')\n",
    "plt.ylim([0, 160000])\n",
    "plt.ylabel('Ncount from fit')\n",
    "plt.tight_layout()\n",
    "plt.grid(visible=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "thermal_width_x_val.plot.errorbar(ax=ax, yerr=thermal_width_x_std, fmt='or')\n",
    "\n",
    "plt.ylabel('Y-axis width of thermal part')\n",
    "plt.tight_layout()\n",
    "plt.grid(visible=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "thermal_width_y_val.plot.errorbar(ax=ax, yerr=thermal_width_y_std, fmt='or')\n",
    "\n",
    "plt.ylabel('X-axis width of thermal part')\n",
    "plt.tight_layout()\n",
    "plt.grid(visible=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "thermal_center_x_val.plot.errorbar(ax=ax, yerr=thermal_center_x_std, fmt='or')\n",
    "\n",
    "plt.ylabel('Y-axis center of thermal part')\n",
    "plt.tight_layout()\n",
    "plt.grid(visible=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.gca()\n",
    "\n",
    "thermal_center_y_val.plot.errorbar(ax=ax, yerr=thermal_center_y_std, fmt='or')\n",
    "\n",
    "plt.ylabel('X-axis center of thermal part')\n",
    "plt.tight_layout()\n",
    "plt.grid(visible=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "val = Ncount.mean().item()\n",
    "std = Ncount.std().item()\n",
    "print(f'The total Ncount is: {val: .2f} \\u00B1 {std: .2f}')\n",
    "\n",
    "val = total_Ncount_val.mean().item()\n",
    "std = total_Ncount_val.std().item()\n",
    "print(f'The total Ncount from fit is: {val: .2f} \\u00B1 {std: .2f}')\n",
    "\n",
    "val = thermal_width_x_val.mean().item()\n",
    "std = thermal_width_x_val.std().item()\n",
    "print(f'The y-axis width of the thermal part is: {val: .2f} \\u00B1 {std: .2f}')\n",
    "\n",
    "val = thermal_width_y_val.mean().item()\n",
    "std = thermal_width_y_val.std().item()\n",
    "print(f'The x-axis width of the thermal part is: {val: .2f} \\u00B1 {std: .2f}')\n",
    "\n",
    "val = thermal_center_x_val.mean().item()\n",
    "std = thermal_center_x_val.std().item()\n",
    "print(f'The y-axis center of the thermal part is: {val: .2f} \\u00B1 {std: .2f}')\n",
    "\n",
    "val = thermal_center_y_val.mean().item()\n",
    "std = thermal_center_y_val.std().item()\n",
    "print(f'The x-axis center of the thermal part is: {val: .2f} \\u00B1 {std: .2f}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "l = list(np.arange(0.001, 0.025, 0.0005))\n",
    "# l = np.logspace(np.log10(100e-3), np.log10(20), num=20)\n",
    "\n",
    "l = [round(item, 7) for item in l]\n",
    "#random.shuffle(l)\n",
    "\n",
    "print(l)\n",
    "print(len(l))\n",
    "np.mean(l)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ODT 1 Calibration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "v_high = 2.7\n",
    "\"\"\"High Power\"\"\"\n",
    "P_arm1_high = 5.776 * v_high - 0.683\n",
    "\n",
    "v_mid = 0.2076\n",
    "\"\"\"Intermediate Power\"\"\"\n",
    "P_arm1_mid = 5.815 * v_mid - 0.03651\n",
    "\n",
    "v_low = 0.0587\n",
    "\"\"\"Low Power\"\"\"\n",
    "P_arm1_low = 5271 * v_low - 27.5\n",
    "\n",
    "print(round(P_arm1_high, 3))\n",
    "print(round(P_arm1_mid, 3))\n",
    "print(round(P_arm1_low, 3))"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ODT 2 Power Calibration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "v = 0.7607\n",
    "P_arm2 = 2.302 * v - 0.06452\n",
    "print(round(P_arm2, 3))"
   ]
  }
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