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{ "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 numpy as np\n", "\n", "from uncertainties import ufloat\n", "from uncertainties import unumpy as unp\n", "from uncertainties import umath\n", "\n", "import matplotlib.pyplot as plt\n", "\n", "from DataContainer.ReadData import read_hdf5_file\n", "from Analyser.ImagingAnalyser import ImageAnalyser\n", "from Analyser.FitAnalyser import FitAnalyser\n", "from Analyser.FitAnalyser import ThomasFermi2dModel, DensityProfileBEC2dModel, Polylog22dModel\n", "from Analyser.FitAnalyser import NewFitModel\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-5bad68a1-052c-11ee-8848-80e82ce2fa8e</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;\">d405c69f</p>\n", " <table style=\"width: 100%; text-align: left;\">\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Dashboard:</strong> <a href=\"http://127.0.0.1:8787/status\" target=\"_blank\">http://127.0.0.1:8787/status</a>\n", " </td>\n", " <td style=\"text-align: left;\">\n", " <strong>Workers:</strong> 6\n", " </td>\n", " </tr>\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Total threads:</strong> 60\n", " </td>\n", " <td style=\"text-align: left;\">\n", " <strong>Total memory:</strong> 55.88 GiB\n", " </td>\n", " </tr>\n", " \n", " <tr>\n", " <td style=\"text-align: left;\"><strong>Status:</strong> running</td>\n", " <td style=\"text-align: left;\"><strong>Using processes:</strong> True</td>\n", "</tr>\n", "\n", " \n", " </table>\n", "\n", " <details>\n", " <summary style=\"margin-bottom: 20px;\">\n", " <h3 style=\"display: inline;\">Scheduler Info</h3>\n", " </summary>\n", "\n", " <div style=\"\">\n", " <div>\n", " <div style=\"width: 24px; height: 24px; background-color: #FFF7E5; border: 3px solid #FF6132; border-radius: 5px; position: absolute;\"> </div>\n", " <div style=\"margin-left: 48px;\">\n", " <h3 style=\"margin-bottom: 0px;\">Scheduler</h3>\n", " <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Scheduler-d5ec295c-c64d-4d85-87ec-4686a4807eda</p>\n", " <table style=\"width: 100%; text-align: left;\">\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Comm:</strong> tcp://127.0.0.1:61303\n", " </td>\n", " <td style=\"text-align: left;\">\n", " <strong>Workers:</strong> 6\n", " </td>\n", " </tr>\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Dashboard:</strong> <a href=\"http://127.0.0.1:8787/status\" target=\"_blank\">http://127.0.0.1:8787/status</a>\n", " </td>\n", " <td style=\"text-align: left;\">\n", " <strong>Total threads:</strong> 60\n", " </td>\n", " </tr>\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Started:</strong> Just now\n", " </td>\n", " <td style=\"text-align: left;\">\n", " <strong>Total memory:</strong> 55.88 GiB\n", " </td>\n", " </tr>\n", " </table>\n", " </div>\n", " </div>\n", "\n", " <details style=\"margin-left: 48px;\">\n", " <summary style=\"margin-bottom: 20px;\">\n", " <h3 style=\"display: inline;\">Workers</h3>\n", " </summary>\n", "\n", " \n", " <div style=\"margin-bottom: 20px;\">\n", " <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n", " <div style=\"margin-left: 48px;\">\n", " <details>\n", " <summary>\n", " <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 0</h4>\n", " </summary>\n", " <table style=\"width: 100%; text-align: left;\">\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Comm: </strong> tcp://127.0.0.1:61374\n", " </td>\n", " <td style=\"text-align: left;\">\n", " <strong>Total threads: </strong> 10\n", " </td>\n", " </tr>\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:61376/status\" target=\"_blank\">http://127.0.0.1:61376/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://127.0.0.1:61306\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-d4a_wgcz\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://127.0.0.1:61365\n", " </td>\n", " <td style=\"text-align: left;\">\n", " <strong>Total threads: </strong> 10\n", " </td>\n", " </tr>\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:61372/status\" target=\"_blank\">http://127.0.0.1:61372/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://127.0.0.1:61307\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-gn02nkkl\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://127.0.0.1:61383\n", " </td>\n", " <td style=\"text-align: left;\">\n", " <strong>Total threads: </strong> 10\n", " </td>\n", " </tr>\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:61384/status\" target=\"_blank\">http://127.0.0.1:61384/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://127.0.0.1:61308\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-18dyy66z\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://127.0.0.1:61360\n", " </td>\n", " <td style=\"text-align: left;\">\n", " <strong>Total threads: </strong> 10\n", " </td>\n", " </tr>\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:61363/status\" target=\"_blank\">http://127.0.0.1:61363/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://127.0.0.1:61309\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-zjpds1ei\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://127.0.0.1:61380\n", " </td>\n", " <td style=\"text-align: left;\">\n", " <strong>Total threads: </strong> 10\n", " </td>\n", " </tr>\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:61381/status\" target=\"_blank\">http://127.0.0.1:61381/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://127.0.0.1:61310\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-3ffyhsw7\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://127.0.0.1:61375\n", " </td>\n", " <td style=\"text-align: left;\">\n", " <strong>Total threads: </strong> 10\n", " </td>\n", " </tr>\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:61378/status\" target=\"_blank\">http://127.0.0.1:61378/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://127.0.0.1:61311\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-g8kf7aki\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://127.0.0.1:61303' processes=6 threads=60, memory=55.88 GiB>" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from dask.distributed import Client\n", "client = Client(n_workers=6, threads_per_worker=10, processes=True, memory_limit='10GB')\n", "client" ] }, { "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_1\",\n", " \"images/ODT_1_Axis_Camera/in_situ_absorption\": \"camera_2\",\n", " \"images/ODT_2_Axis_Camera/in_situ_absorption\": \"camera_3\",\n", "}\n" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "img_dir = '//DyLabNAS/Data/'\n", "SequenceName = \"Repetition_scan\" + \"/\"\n", "folderPath = img_dir + SequenceName + '2023/06/07'# get_date()" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "# An example for one experimental run" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## Load the data" ] }, { "cell_type": "code", "execution_count": 76, "metadata": {}, "outputs": [ { "data": { "text/html": [ "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n", "<defs>\n", "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n", "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n", "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n", "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n", "</symbol>\n", "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n", "<path d=\"M28.681 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display: block !important;\n", " min-width: 300px;\n", " max-width: 700px;\n", "}\n", "\n", ".xr-text-repr-fallback {\n", " /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n", " display: none;\n", "}\n", "\n", ".xr-header {\n", " padding-top: 6px;\n", " padding-bottom: 6px;\n", " margin-bottom: 4px;\n", " border-bottom: solid 1px var(--xr-border-color);\n", "}\n", "\n", ".xr-header > div,\n", ".xr-header > ul {\n", " display: inline;\n", " margin-top: 0;\n", " margin-bottom: 0;\n", "}\n", "\n", ".xr-obj-type,\n", ".xr-array-name {\n", " margin-left: 2px;\n", " margin-right: 10px;\n", "}\n", "\n", ".xr-obj-type {\n", " color: var(--xr-font-color2);\n", "}\n", "\n", ".xr-sections {\n", " padding-left: 0 !important;\n", " display: grid;\n", " grid-template-columns: 150px auto auto 1fr 20px 20px;\n", "}\n", "\n", ".xr-section-item {\n", " display: contents;\n", "}\n", "\n", ".xr-section-item input {\n", " display: none;\n", "}\n", "\n", ".xr-section-item input + label {\n", " color: var(--xr-disabled-color);\n", "}\n", "\n", ".xr-section-item input:enabled + label {\n", " cursor: pointer;\n", " color: var(--xr-font-color2);\n", "}\n", "\n", ".xr-section-item input:enabled + label:hover {\n", " color: var(--xr-font-color0);\n", "}\n", "\n", ".xr-section-summary {\n", " grid-column: 1;\n", " color: var(--xr-font-color2);\n", " font-weight: 500;\n", "}\n", "\n", ".xr-section-summary > span {\n", " display: inline-block;\n", " padding-left: 0.5em;\n", "}\n", "\n", ".xr-section-summary-in:disabled + label {\n", " color: var(--xr-font-color2);\n", "}\n", "\n", ".xr-section-summary-in + label:before {\n", " display: inline-block;\n", " content: '►';\n", " font-size: 11px;\n", " width: 15px;\n", " text-align: center;\n", "}\n", "\n", ".xr-section-summary-in:disabled + label:before {\n", " color: var(--xr-disabled-color);\n", "}\n", "\n", ".xr-section-summary-in:checked + label:before {\n", " content: '▼';\n", "}\n", "\n", ".xr-section-summary-in:checked + label > span {\n", " display: none;\n", "}\n", "\n", ".xr-section-summary,\n", ".xr-section-inline-details {\n", " padding-top: 4px;\n", " padding-bottom: 4px;\n", "}\n", "\n", ".xr-section-inline-details {\n", " grid-column: 2 / -1;\n", "}\n", "\n", ".xr-section-details {\n", " display: none;\n", " grid-column: 1 / -1;\n", " margin-bottom: 5px;\n", "}\n", "\n", ".xr-section-summary-in:checked ~ .xr-section-details {\n", " display: contents;\n", "}\n", "\n", ".xr-array-wrap {\n", " grid-column: 1 / -1;\n", " display: grid;\n", " grid-template-columns: 20px auto;\n", "}\n", "\n", ".xr-array-wrap > label {\n", " grid-column: 1;\n", " vertical-align: top;\n", "}\n", "\n", ".xr-preview {\n", " color: var(--xr-font-color3);\n", "}\n", "\n", ".xr-array-preview,\n", ".xr-array-data {\n", " padding: 0 5px !important;\n", " grid-column: 2;\n", "}\n", "\n", ".xr-array-data,\n", ".xr-array-in:checked ~ .xr-array-preview {\n", " display: none;\n", "}\n", "\n", ".xr-array-in:checked ~ .xr-array-data,\n", ".xr-array-preview {\n", " display: inline-block;\n", "}\n", "\n", ".xr-dim-list {\n", " display: inline-block !important;\n", " list-style: none;\n", " padding: 0 !important;\n", " margin: 0;\n", "}\n", "\n", ".xr-dim-list li {\n", " display: inline-block;\n", " padding: 0;\n", " margin: 0;\n", "}\n", "\n", ".xr-dim-list:before {\n", " content: '(';\n", "}\n", "\n", ".xr-dim-list:after {\n", " content: ')';\n", "}\n", "\n", ".xr-dim-list li:not(:last-child):after {\n", " content: ',';\n", " padding-right: 5px;\n", "}\n", "\n", ".xr-has-index {\n", " font-weight: bold;\n", "}\n", "\n", ".xr-var-list,\n", ".xr-var-item {\n", " display: contents;\n", "}\n", "\n", ".xr-var-item > div,\n", ".xr-var-item label,\n", ".xr-var-item > .xr-var-name span {\n", " background-color: var(--xr-background-color-row-even);\n", " margin-bottom: 0;\n", "}\n", "\n", ".xr-var-item > .xr-var-name:hover span {\n", " padding-right: 5px;\n", "}\n", "\n", ".xr-var-list > li:nth-child(odd) > div,\n", ".xr-var-list > li:nth-child(odd) > label,\n", ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n", " background-color: var(--xr-background-color-row-odd);\n", "}\n", "\n", ".xr-var-name {\n", " grid-column: 1;\n", "}\n", "\n", ".xr-var-dims {\n", " grid-column: 2;\n", "}\n", "\n", ".xr-var-dtype {\n", " grid-column: 3;\n", " text-align: right;\n", " color: var(--xr-font-color2);\n", "}\n", "\n", ".xr-var-preview {\n", " grid-column: 4;\n", "}\n", "\n", ".xr-index-preview {\n", " grid-column: 2 / 5;\n", " color: var(--xr-font-color2);\n", "}\n", "\n", ".xr-var-name,\n", ".xr-var-dims,\n", ".xr-var-dtype,\n", ".xr-preview,\n", ".xr-attrs dt {\n", " white-space: nowrap;\n", " overflow: hidden;\n", " text-overflow: ellipsis;\n", " padding-right: 10px;\n", "}\n", "\n", ".xr-var-name:hover,\n", ".xr-var-dims:hover,\n", ".xr-var-dtype:hover,\n", ".xr-attrs dt:hover {\n", " overflow: visible;\n", " width: auto;\n", " z-index: 1;\n", "}\n", "\n", ".xr-var-attrs,\n", ".xr-var-data,\n", ".xr-index-data {\n", " display: none;\n", " background-color: var(--xr-background-color) !important;\n", " padding-bottom: 5px !important;\n", "}\n", "\n", ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n", ".xr-var-data-in:checked ~ .xr-var-data,\n", ".xr-index-data-in:checked ~ .xr-index-data {\n", " display: block;\n", "}\n", "\n", ".xr-var-data > table {\n", " float: right;\n", "}\n", "\n", ".xr-var-name span,\n", ".xr-var-data,\n", ".xr-index-name div,\n", ".xr-index-data,\n", ".xr-attrs {\n", " padding-left: 25px !important;\n", "}\n", "\n", ".xr-attrs,\n", ".xr-var-attrs,\n", ".xr-var-data,\n", ".xr-index-data {\n", " grid-column: 1 / -1;\n", "}\n", "\n", "dl.xr-attrs {\n", " padding: 0;\n", " margin: 0;\n", " display: grid;\n", " grid-template-columns: 125px auto;\n", "}\n", "\n", ".xr-attrs dt,\n", ".xr-attrs dd {\n", " padding: 0;\n", " margin: 0;\n", " float: left;\n", " padding-right: 10px;\n", " width: auto;\n", "}\n", "\n", ".xr-attrs dt {\n", " font-weight: normal;\n", " grid-column: 1;\n", "}\n", "\n", ".xr-attrs dt:hover span {\n", " display: inline-block;\n", " background: var(--xr-background-color);\n", " padding-right: 10px;\n", "}\n", "\n", ".xr-attrs dd {\n", " grid-column: 2;\n", " white-space: pre-wrap;\n", " word-break: break-all;\n", "}\n", "\n", ".xr-icon-database,\n", ".xr-icon-file-text2,\n", ".xr-no-icon {\n", " display: inline-block;\n", " vertical-align: middle;\n", " width: 1em;\n", " height: 1.5em !important;\n", " stroke-width: 0;\n", " stroke: currentColor;\n", " fill: currentColor;\n", "}\n", "</style><pre class='xr-text-repr-fallback'><xarray.Dataset>\n", "Dimensions: (TOF_free: 15, runs: 3, y: 1200, x: 1920)\n", "Coordinates:\n", " * TOF_free (TOF_free) float64 0.001 0.002 0.003 0.004 ... 0.013 0.014 0.015\n", " * runs (runs) float64 0.0 1.0 2.0\n", "Dimensions without coordinates: y, x\n", "Data variables:\n", " atoms (TOF_free, runs, y, x) uint16 dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray>\n", " background (TOF_free, runs, y, x) uint16 dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray>\n", " dark (TOF_free, runs, y, x) uint16 dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray>\n", " shotNum (TOF_free, runs) <U2 dask.array<chunksize=(15, 3), meta=np.ndarray>\n", " OD (TOF_free, runs, y, x) float64 dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray>\n", "Attributes: (12/126)\n", " abs_img_freq: 109.36\n", " absorption_imaging_flag: True\n", " backup_data: True\n", " blink_off_mod_depth: 0.35\n", " blink_off_power: 0\n", " blink_off_time: nan\n", " ... ...\n", " z_offset: 0.189\n", " z_offset_img: 0\n", " TOF_free: [0.001 0.002 0.003 0.004 0.005 0.006 0...\n", " runs: [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0...\n", " scanAxis: ['TOF_free' 'runs']\n", " scanAxisLength: [45. 45.]</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-75c1aff1-c332-4a20-a85c-d62298eacff1' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-75c1aff1-c332-4a20-a85c-d62298eacff1' 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'>TOF_free</span>: 15</li><li><span class='xr-has-index'>runs</span>: 3</li><li><span>y</span>: 1200</li><li><span>x</span>: 1920</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-33069984-599b-473d-8344-64108c2747ca' class='xr-section-summary-in' type='checkbox' checked><label for='section-33069984-599b-473d-8344-64108c2747ca' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>TOF_free</span></div><div class='xr-var-dims'>(TOF_free)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.001 0.002 0.003 ... 0.014 0.015</div><input id='attrs-fedd8a59-4292-4c0a-ba2a-9a28c353cee5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fedd8a59-4292-4c0a-ba2a-9a28c353cee5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6f065cd4-86e5-4ad5-9eb4-64ec1a6d63e1' class='xr-var-data-in' type='checkbox'><label for='data-6f065cd4-86e5-4ad5-9eb4-64ec1a6d63e1' 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([0.001, 0.002, 0.003, 0.004, 0.005, 0.006, 0.007, 0.008, 0.009, 0.01 ,\n", " 0.011, 0.012, 0.013, 0.014, 0.015])</pre></div></li><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</div><input id='attrs-bdba1a5f-e3cc-46c9-8329-18f670ba938d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bdba1a5f-e3cc-46c9-8329-18f670ba938d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4897cc0-0aa5-43a0-9f79-784838c30de6' class='xr-var-data-in' type='checkbox'><label for='data-a4897cc0-0aa5-43a0-9f79-784838c30de6' 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.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b55cc959-45a5-4ea3-acc6-c024efbf409f' class='xr-section-summary-in' type='checkbox' checked><label for='section-b55cc959-45a5-4ea3-acc6-c024efbf409f' class='xr-section-summary' >Data variables: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>atoms</span></div><div class='xr-var-dims'>(TOF_free, runs, y, x)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray></div><input id='attrs-9a96f649-c020-470c-a033-ee11b223fee3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9a96f649-c020-470c-a033-ee11b223fee3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0ed9d639-db53-4a42-a773-38069cd21755' class='xr-var-data-in' type='checkbox'><label for='data-0ed9d639-db53-4a42-a773-38069cd21755' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>IMAGE_SUBCLASS :</span></dt><dd>IMAGE_GRAYSCALE</dd><dt><span>IMAGE_VERSION :</span></dt><dd>1.2</dd><dt><span>IMAGE_WHITE_IS_ZERO :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><table>\n", " <tr>\n", " <td>\n", " <table style=\"border-collapse: collapse;\">\n", " <thead>\n", " <tr>\n", " <td> </td>\n", " <th> Array </th>\n", " <th> Chunk </th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " \n", " <tr>\n", " <th> Bytes </th>\n", " <td> 197.75 MiB </td>\n", " <td> 118.65 MiB </td>\n", " </tr>\n", " \n", " <tr>\n", " <th> Shape </th>\n", " <td> (15, 3, 1200, 1920) </td>\n", " <td> (9, 3, 1200, 1920) </td>\n", " </tr>\n", " <tr>\n", " <th> Dask graph </th>\n", " <td colspan=\"2\"> 2 chunks in 140 graph layers </td>\n", " </tr>\n", " <tr>\n", " <th> Data type </th>\n", " <td colspan=\"2\"> uint16 numpy.ndarray </td>\n", " </tr>\n", " </tbody>\n", " </table>\n", " </td>\n", " <td>\n", " <svg width=\"374\" height=\"139\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n", "\n", " <!-- Horizontal lines -->\n", " <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n", " <line x1=\"0\" y1=\"25\" x2=\"25\" y2=\"25\" style=\"stroke-width:2\" />\n", "\n", " <!-- Vertical lines -->\n", " <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n", " <line x1=\"15\" y1=\"0\" x2=\"15\" y2=\"25\" />\n", " <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"25\" style=\"stroke-width:2\" />\n", "\n", " <!-- Colored Rectangle -->\n", " <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n", "\n", " <!-- Text -->\n", " <text x=\"12.706308\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >15</text>\n", " <text x=\"45.412617\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,45.412617,12.706308)\">1</text>\n", "\n", "\n", " <!-- Horizontal lines -->\n", " <line x1=\"95\" y1=\"0\" x2=\"109\" y2=\"14\" style=\"stroke-width:2\" />\n", " <line x1=\"95\" y1=\"75\" x2=\"109\" y2=\"89\" style=\"stroke-width:2\" />\n", "\n", " <!-- Vertical lines -->\n", " <line x1=\"95\" y1=\"0\" x2=\"95\" y2=\"75\" style=\"stroke-width:2\" />\n", " <line x1=\"109\" y1=\"14\" x2=\"109\" y2=\"89\" style=\"stroke-width:2\" />\n", "\n", " <!-- Colored Rectangle -->\n", " <polygon points=\"95.0,0.0 109.9485979497544,14.948597949754403 109.9485979497544,89.9485979497544 95.0,75.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n", "\n", " <!-- Horizontal lines -->\n", " <line x1=\"95\" y1=\"0\" x2=\"215\" y2=\"0\" style=\"stroke-width:2\" />\n", " <line x1=\"109\" y1=\"14\" x2=\"229\" y2=\"14\" style=\"stroke-width:2\" />\n", "\n", " <!-- Vertical lines -->\n", " <line x1=\"95\" y1=\"0\" x2=\"109\" y2=\"14\" style=\"stroke-width:2\" />\n", " <line x1=\"215\" y1=\"0\" x2=\"229\" y2=\"14\" style=\"stroke-width:2\" />\n", "\n", " <!-- Colored Rectangle -->\n", " <polygon points=\"95.0,0.0 215.0,0.0 229.9485979497544,14.948597949754403 109.9485979497544,14.948597949754403\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n", "\n", " <!-- Horizontal lines -->\n", " <line x1=\"109\" y1=\"14\" x2=\"229\" y2=\"14\" style=\"stroke-width:2\" />\n", " <line x1=\"109\" y1=\"89\" x2=\"229\" y2=\"89\" style=\"stroke-width:2\" />\n", "\n", " <!-- Vertical lines -->\n", " <line x1=\"109\" y1=\"14\" x2=\"109\" y2=\"89\" style=\"stroke-width:2\" />\n", " <line x1=\"229\" y1=\"14\" x2=\"229\" y2=\"89\" style=\"stroke-width:2\" />\n", "\n", " <!-- Colored Rectangle -->\n", " <polygon points=\"109.9485979497544,14.948597949754403 229.9485979497544,14.948597949754403 229.9485979497544,89.9485979497544 109.9485979497544,89.9485979497544\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n", "\n", " <!-- Text -->\n", " <text x=\"169.948598\" y=\"109.948598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1920</text>\n", " <text x=\"249.948598\" y=\"52.448598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,249.948598,52.448598)\">1200</text>\n", " <text x=\"92.474299\" y=\"102.474299\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,92.474299,102.474299)\">3</text>\n", "</svg>\n", " </td>\n", " </tr>\n", "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>background</span></div><div class='xr-var-dims'>(TOF_free, runs, y, x)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray></div><input id='attrs-68e51e45-b5cf-49c9-9f0e-383638103e35' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-68e51e45-b5cf-49c9-9f0e-383638103e35' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-75996c1c-7027-45f2-80fd-39ea2f477bf7' class='xr-var-data-in' type='checkbox'><label for='data-75996c1c-7027-45f2-80fd-39ea2f477bf7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>IMAGE_SUBCLASS :</span></dt><dd>IMAGE_GRAYSCALE</dd><dt><span>IMAGE_VERSION :</span></dt><dd>1.2</dd><dt><span>IMAGE_WHITE_IS_ZERO :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><table>\n", " <tr>\n", " <td>\n", " <table style=\"border-collapse: collapse;\">\n", " <thead>\n", " <tr>\n", " <td> </td>\n", " <th> Array </th>\n", " <th> Chunk </th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " \n", " <tr>\n", " <th> Bytes </th>\n", " <td> 197.75 MiB </td>\n", " <td> 118.65 MiB </td>\n", " </tr>\n", " \n", " <tr>\n", " <th> Shape </th>\n", " <td> (15, 3, 1200, 1920) </td>\n", " <td> (9, 3, 1200, 1920) </td>\n", " </tr>\n", " <tr>\n", " <th> Dask graph </th>\n", " <td colspan=\"2\"> 2 chunks in 140 graph layers </td>\n", " </tr>\n", " <tr>\n", " <th> Data type </th>\n", " <td colspan=\"2\"> uint16 numpy.ndarray </td>\n", " </tr>\n", " </tbody>\n", " </table>\n", " </td>\n", " <td>\n", " <svg width=\"374\" height=\"139\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n", "\n", " <!-- Horizontal lines -->\n", " <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n", " <line x1=\"0\" y1=\"25\" x2=\"25\" y2=\"25\" style=\"stroke-width:2\" />\n", "\n", " <!-- Vertical lines -->\n", " <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n", " <line x1=\"15\" y1=\"0\" x2=\"15\" y2=\"25\" />\n", " <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"25\" style=\"stroke-width:2\" />\n", "\n", " <!-- Colored Rectangle -->\n", " <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n", 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meta=np.ndarray></div><input id='attrs-3380c906-5c82-4d9a-ba62-551958852363' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3380c906-5c82-4d9a-ba62-551958852363' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a7b9cdb9-026e-4d27-970e-2270d50d8e40' class='xr-var-data-in' type='checkbox'><label for='data-a7b9cdb9-026e-4d27-970e-2270d50d8e40' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>IMAGE_SUBCLASS :</span></dt><dd>IMAGE_GRAYSCALE</dd><dt><span>IMAGE_VERSION :</span></dt><dd>1.2</dd><dt><span>IMAGE_WHITE_IS_ZERO :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><table>\n", " <tr>\n", " <td>\n", " <table style=\"border-collapse: collapse;\">\n", " <thead>\n", " <tr>\n", " <td> </td>\n", " <th> Array </th>\n", " <th> Chunk </th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " \n", " <tr>\n", " <th> Bytes </th>\n", " <td> 197.75 MiB </td>\n", " <td> 118.65 MiB </td>\n", " </tr>\n", " \n", " <tr>\n", " <th> Shape </th>\n", " <td> (15, 3, 1200, 1920) </td>\n", " <td> (9, 3, 1200, 1920) </td>\n", " </tr>\n", " <tr>\n", " <th> Dask graph </th>\n", " <td colspan=\"2\"> 2 chunks in 140 graph layers </td>\n", " </tr>\n", " <tr>\n", " <th> Data type </th>\n", " <td colspan=\"2\"> uint16 numpy.ndarray </td>\n", " </tr>\n", " </tbody>\n", " </table>\n", " </td>\n", " <td>\n", " <svg width=\"374\" height=\"139\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n", "\n", " <!-- Horizontal lines -->\n", " <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n", " <line x1=\"0\" y1=\"25\" x2=\"25\" y2=\"25\" style=\"stroke-width:2\" />\n", "\n", " <!-- Vertical lines -->\n", " <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n", " <line x1=\"15\" y1=\"0\" x2=\"15\" y2=\"25\" />\n", " <line x1=\"25\" y1=\"0\" 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x1=\"109\" y1=\"14\" x2=\"109\" y2=\"89\" style=\"stroke-width:2\" />\n", " <line x1=\"229\" y1=\"14\" x2=\"229\" y2=\"89\" style=\"stroke-width:2\" />\n", "\n", " <!-- Colored Rectangle -->\n", " <polygon points=\"109.9485979497544,14.948597949754403 229.9485979497544,14.948597949754403 229.9485979497544,89.9485979497544 109.9485979497544,89.9485979497544\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n", "\n", " <!-- Text -->\n", " <text x=\"169.948598\" y=\"109.948598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1920</text>\n", " <text x=\"249.948598\" y=\"52.448598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,249.948598,52.448598)\">1200</text>\n", " <text x=\"92.474299\" y=\"102.474299\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,92.474299,102.474299)\">3</text>\n", "</svg>\n", " </td>\n", " </tr>\n", "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>shotNum</span></div><div class='xr-var-dims'>(TOF_free, runs)</div><div class='xr-var-dtype'><U2</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(15, 3), meta=np.ndarray></div><input id='attrs-9f5ed541-b3c9-4f92-909f-716b2e33fcb6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9f5ed541-b3c9-4f92-909f-716b2e33fcb6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-81cfea04-fe0a-4721-a9ff-43b36f391296' class='xr-var-data-in' type='checkbox'><label for='data-81cfea04-fe0a-4721-a9ff-43b36f391296' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n", " <tr>\n", " <td>\n", " <table style=\"border-collapse: collapse;\">\n", " <thead>\n", " <tr>\n", " <td> </td>\n", " <th> Array </th>\n", " <th> Chunk </th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " \n", " <tr>\n", " <th> Bytes </th>\n", " <td> 360 B </td>\n", " <td> 360 B </td>\n", " </tr>\n", " \n", " <tr>\n", " <th> Shape </th>\n", " <td> (15, 3) </td>\n", " <td> (15, 3) </td>\n", " </tr>\n", " <tr>\n", " <th> Dask graph </th>\n", " <td colspan=\"2\"> 1 chunks in 1 graph layer </td>\n", " </tr>\n", " <tr>\n", " <th> Data type </th>\n", " <td colspan=\"2\"> <U2 numpy.ndarray </td>\n", " </tr>\n", " </tbody>\n", " </table>\n", " </td>\n", " <td>\n", " <svg width=\"92\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n", "\n", " <!-- Horizontal lines -->\n", " <line x1=\"0\" y1=\"0\" x2=\"42\" y2=\"0\" style=\"stroke-width:2\" />\n", " <line x1=\"0\" y1=\"120\" x2=\"42\" y2=\"120\" style=\"stroke-width:2\" />\n", "\n", " <!-- Vertical lines -->\n", " <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n", " <line x1=\"42\" y1=\"0\" x2=\"42\" y2=\"120\" style=\"stroke-width:2\" />\n", "\n", " <!-- Colored Rectangle -->\n", " <polygon points=\"0.0,0.0 42.00989029700999,0.0 42.00989029700999,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n", "\n", " <!-- Text -->\n", " <text x=\"21.004945\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3</text>\n", " <text x=\"62.009890\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,62.009890,60.000000)\">15</text>\n", "</svg>\n", " </td>\n", " </tr>\n", "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>OD</span></div><div class='xr-var-dims'>(TOF_free, runs, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray></div><input id='attrs-59007226-c1d1-4c83-83b0-3d6cf76b2231' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-59007226-c1d1-4c83-83b0-3d6cf76b2231' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c25019a2-3672-4538-9f1e-ec8e8c6ee6eb' class='xr-var-data-in' type='checkbox'><label for='data-c25019a2-3672-4538-9f1e-ec8e8c6ee6eb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>IMAGE_SUBCLASS :</span></dt><dd>IMAGE_GRAYSCALE</dd><dt><span>IMAGE_VERSION :</span></dt><dd>1.2</dd><dt><span>IMAGE_WHITE_IS_ZERO :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><table>\n", " <tr>\n", " <td>\n", " <table style=\"border-collapse: collapse;\">\n", " <thead>\n", " <tr>\n", " <td> </td>\n", " <th> Array </th>\n", " <th> Chunk </th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " \n", " <tr>\n", " <th> Bytes </th>\n", " <td> 791.02 MiB </td>\n", " <td> 474.61 MiB </td>\n", " </tr>\n", " \n", " <tr>\n", " <th> Shape </th>\n", " <td> (15, 3, 1200, 1920) </td>\n", " <td> (9, 3, 1200, 1920) </td>\n", " </tr>\n", " <tr>\n", " <th> Dask graph </th>\n", " <td colspan=\"2\"> 2 chunks in 430 graph layers </td>\n", " </tr>\n", " <tr>\n", " <th> Data type </th>\n", " <td colspan=\"2\"> float64 numpy.ndarray </td>\n", " </tr>\n", " </tbody>\n", " </table>\n", " </td>\n", " <td>\n", " <svg width=\"374\" height=\"139\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n", "\n", " <!-- Horizontal lines -->\n", " <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n", " <line x1=\"0\" y1=\"25\" x2=\"25\" y2=\"25\" style=\"stroke-width:2\" />\n", "\n", " <!-- Vertical lines -->\n", " <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n", " <line x1=\"15\" y1=\"0\" x2=\"15\" y2=\"25\" />\n", " <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"25\" style=\"stroke-width:2\" />\n", "\n", " <!-- Colored Rectangle -->\n", " <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,25.412616514582485 0.0,25.412616514582485\" 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<polygon points=\"109.9485979497544,14.948597949754403 229.9485979497544,14.948597949754403 229.9485979497544,89.9485979497544 109.9485979497544,89.9485979497544\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n", "\n", " <!-- Text -->\n", " <text x=\"169.948598\" y=\"109.948598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1920</text>\n", " <text x=\"249.948598\" y=\"52.448598\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,249.948598,52.448598)\">1200</text>\n", " <text x=\"92.474299\" y=\"102.474299\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,92.474299,102.474299)\">3</text>\n", "</svg>\n", " </td>\n", " </tr>\n", "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-0e38d8bc-5351-4b99-a5cc-8c3c930bce2d' class='xr-section-summary-in' type='checkbox' ><label for='section-0e38d8bc-5351-4b99-a5cc-8c3c930bce2d' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>TOF_free</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-19a49534-b4d2-4f72-89b9-742490dabcae' class='xr-index-data-in' type='checkbox'/><label for='index-19a49534-b4d2-4f72-89b9-742490dabcae' 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([0.001, 0.002, 0.003, 0.004, 0.005, 0.006, 0.007, 0.008, 0.009,\n", " 0.01, 0.011, 0.012, 0.013, 0.014, 0.015],\n", " dtype='float64', name='TOF_free'))</pre></div></li><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-7378cd1f-23f4-4f39-81c6-f77eb7a05125' class='xr-index-data-in' type='checkbox'/><label for='index-7378cd1f-23f4-4f39-81c6-f77eb7a05125' 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], dtype='float64', name='runs'))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7e4c751b-3761-482f-a10e-280f39787fc4' class='xr-section-summary-in' type='checkbox' ><label for='section-7e4c751b-3761-482f-a10e-280f39787fc4' class='xr-section-summary' >Attributes: <span>(126)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>abs_img_freq :</span></dt><dd>109.36</dd><dt><span>absorption_imaging_flag :</span></dt><dd>True</dd><dt><span>backup_data :</span></dt><dd>True</dd><dt><span>blink_off_mod_depth :</span></dt><dd>0.35</dd><dt><span>blink_off_power :</span></dt><dd>0</dd><dt><span>blink_off_time :</span></dt><dd>nan</dd><dt><span>blink_on_mod_depth :</span></dt><dd>0.43</dd><dt><span>blink_on_power :</span></dt><dd>0.09</dd><dt><span>blink_on_time :</span></dt><dd>nan</dd><dt><span>c_duration :</span></dt><dd>0.1</dd><dt><span>carrier_amp :</span></dt><dd>3</dd><dt><span>carrier_freq :</span></dt><dd>nan</dd><dt><span>carrier_offset :</span></dt><dd>0</dd><dt><span>carrier_phase :</span></dt><dd>0</dd><dt><span>channel_in_use :</span></dt><dd>1</dd><dt><span>cmot_final_current :</span></dt><dd>0.25</dd><dt><span>cmot_hold :</span></dt><dd>0</dd><dt><span>cmot_initial_current :</span></dt><dd>0.18</dd><dt><span>compX_current :</span></dt><dd>0</dd><dt><span>compX_current_sg :</span></dt><dd>0.0</dd><dt><span>compX_final_current :</span></dt><dd>0</dd><dt><span>compX_initial_current :</span></dt><dd>0</dd><dt><span>compY_current :</span></dt><dd>0</dd><dt><span>compY_current_sg :</span></dt><dd>0.0</dd><dt><span>compY_final_current :</span></dt><dd>0</dd><dt><span>compY_initial_current :</span></dt><dd>0</dd><dt><span>compZ_current :</span></dt><dd>0</dd><dt><span>compZ_current_sg :</span></dt><dd>0.189</dd><dt><span>compZ_final_current :</span></dt><dd>0.09</dd><dt><span>compZ_initial_current :</span></dt><dd>0</dd><dt><span>default_camera :</span></dt><dd>0</dd><dt><span>deltaf :</span></dt><dd>0.0021</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>0.16</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>2.76</dd><dt><span>evap_2_arm_2_start_pow :</span></dt><dd>5</dd><dt><span>evap_2_ramp_duration :</span></dt><dd>0.3</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 " 0.013 0.014 0.015 0.001 0.002 0.003 0.004 0.005 0.006 0.007 0.008 0.009\n", " 0.01 0.011 0.012 0.013 0.014 0.015 0.001 0.002 0.003 0.004 0.005 0.006\n", " 0.007 0.008 0.009 0.01 0.011 0.012 0.013 0.014 0.015]</dd><dt><span>runs :</span></dt><dd>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1. 1. 1.\n", " 1. 1. 1. 1. 1. 1. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2.]</dd><dt><span>scanAxis :</span></dt><dd>['TOF_free' 'runs']</dd><dt><span>scanAxisLength :</span></dt><dd>[45. 45.]</dd></dl></div></li></ul></div></div>" ], "text/plain": [ "<xarray.Dataset>\n", "Dimensions: (TOF_free: 15, runs: 3, y: 1200, x: 1920)\n", "Coordinates:\n", " * TOF_free (TOF_free) float64 0.001 0.002 0.003 0.004 ... 0.013 0.014 0.015\n", " * runs (runs) float64 0.0 1.0 2.0\n", "Dimensions without coordinates: y, x\n", "Data variables:\n", " atoms (TOF_free, runs, y, x) uint16 dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray>\n", " background (TOF_free, runs, y, x) uint16 dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray>\n", " dark (TOF_free, runs, y, x) uint16 dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray>\n", " shotNum (TOF_free, runs) <U2 dask.array<chunksize=(15, 3), meta=np.ndarray>\n", " OD (TOF_free, runs, y, x) float64 dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray>\n", "Attributes: (12/126)\n", " abs_img_freq: 109.36\n", " absorption_imaging_flag: True\n", " backup_data: True\n", " blink_off_mod_depth: 0.35\n", " blink_off_power: 0\n", " blink_off_time: nan\n", " ... ...\n", " z_offset: 0.189\n", " z_offset_img: 0\n", " TOF_free: [0.001 0.002 0.003 0.004 0.005 0.006 0...\n", " runs: [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0...\n", " scanAxis: ['TOF_free' 'runs']\n", " scanAxisLength: [45. 45.]" ] }, "execution_count": 76, "metadata": {}, "output_type": "execute_result" } ], "source": [ "shotNum = \"0025\"\n", "filePath = folderPath + \"/\" + shotNum + \"/*.h5\"\n", "# filePath = \"//DyLabNAS/Data/Evaporative_Cooling/2023/05/12/0065/*.h5\"\n", "\n", "dataSetDict = {\n", " dskey[groupList[i]]: read_hdf5_file(filePath, groupList[i])\n", " for i in [0] # range(len(groupList))\n", "}\n", "\n", "dataSet = dataSetDict[\"camera_1\"]\n", "dataSet = swap_xy(dataSet)\n", "\n", "scanAxis = get_scanAxis(dataSet)\n", "\n", "dataSet = auto_rechunk(dataSet)\n", "\n", "dataSet = imageAnalyser.get_absorption_images(dataSet)\n", "\n", "dataSet" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## Calculate an plot OD images" ] }, { "cell_type": "code", "execution_count": 77, "metadata": {}, "outputs": [ { "data": { "image/png": "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 "text/plain": [ "<Figure size 4600x900 with 46 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "imageAnalyser.center = (1385, 495)\n", "imageAnalyser.span = (1045, 960)\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", "dataSet_cropOD.plot.pcolormesh(cmap='jet', vmin=0, vmax=0.5, col=scanAxis[0], row=scanAxis[1])\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 78, "metadata": {}, "outputs": [], "source": [ "dataSet_cropOD = dataSet_cropOD.chunk((1,1045,960))\n", "fitAnalyser = FitAnalyser(\"Gaussian-2D\", fitDim=2)\n", "params = fitAnalyser.guess(dataSet_cropOD, dask=\"parallelized\")\n", "fitResult = fitAnalyser.fit(dataSet_cropOD, params).load()" ] }, { "cell_type": "code", "execution_count": 79, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "<xarray.plot.facetgrid.FacetGrid at 0x1950475a670>" ] }, "execution_count": 79, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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 "text/plain": [ "<Figure size 4600x900 with 46 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fitCurve = fitAnalyser.eval(fitResult, x=np.arange(1045), y=np.arange(960), dask=\"parallelized\").load()\n", "\n", "fitCurve.plot.pcolormesh(cmap='jet', vmin=0, vmax=.3, col=scanAxis[0], row=scanAxis[1], x='x', y='y')" ] }, { "cell_type": "code", "execution_count": 94, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "<xarray.plot.facetgrid.FacetGrid at 0x198a5ec1ac0>" ] }, "execution_count": 94, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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 "text/plain": [ "<Figure size 4600x900 with 46 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "(fitCurve-dataSet_cropOD).plot.pcolormesh(cmap='jet', vmin=-0.1, vmax=.1, col=scanAxis[0], row=scanAxis[1], x='x', y='y')" ] }, { "cell_type": "code", "execution_count": 85, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "<xarray.DataArray (TOF_free: 15, runs: 3)>\n", "array([[1.38857533, 1.4296049 , 1.43043703],\n", " [1.38547994, 1.41019837, 1.41377556],\n", " [1.36176503, 1.37257089, 1.37512008],\n", " [1.31676702, 1.32164997, 1.32461436],\n", " [1.26726609, 1.2715255 , 1.27045011],\n", " [1.22092353, 1.22216891, 1.22254248],\n", " [1.1766153 , 1.17831669, 1.17648499],\n", " [1.13787332, 1.13826565, 1.13929405],\n", " [1.1010388 , 1.10524765, 1.10616018],\n", " [1.07627628, 1.07935572, 1.0800134 ],\n", " [1.05431525, 1.05729812, 1.05673536],\n", " [1.04106693, 1.04238898, 1.04132909],\n", " [1.02834896, 1.02867543, 1.0272658 ],\n", " [1.01853434, 1.01937933, 1.01871028],\n", " [1.01329279, 1.01146408, 1.01185732]])\n", "Coordinates:\n", " * TOF_free (TOF_free) float64 0.001 0.002 0.003 0.004 ... 0.013 0.014 0.015\n", " * runs (runs) float64 0.0 1.0 2.0\n" ] } ], "source": [ "val = fitAnalyser.get_fit_value(fitResult)\n", "print(val['sigmax'] / val['sigmay'])" ] }, { "cell_type": "code", "execution_count": 96, "metadata": {}, "outputs": [ { "data": { "image/png": "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 "text/plain": [ "<Figure size 640x480 with 1 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "val = fitAnalyser.get_fit_value(fitResult)\n", "std = fitAnalyser.get_fit_std(fitResult)\n", "\n", "# fitCurve = fitAnalyser.eval(fitResult, x=np.arange(1045), y=np.arange(960), dask=\"parallelized\").load()\n", "\n", "dataKey = 'sigmax'\n", "# dataKey = 'centerx'\n", "# dataKey = 'sigmay'\n", "# dataKey = 'centery'\n", "\n", "val_mean = val[dataKey].mean(dim='runs')\n", "std_mean = val[dataKey].std(dim='runs')\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "\n", "val_mean.plot.errorbar(yerr=std_mean, fmt='--ob')\n", "\n", "plt.grid()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 97, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "T = 359.17 ± 1.98 uK\n" ] }, { "data": { "image/png": "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 "text/plain": [ "<Figure size 640x480 with 1 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "def expansion(x, A, B):\n", " return np.sqrt(A*x*x+B*B)\n", "\n", "val_truncated = val_mean[7:]\n", "std_mean_truncated = std_mean[7:]\n", "\n", "fitModel_temperature = NewFitModel(expansion)\n", "fitAnalyser_temperature = FitAnalyser(fitModel_temperature, fitDim=1)\n", "\n", "params = fitAnalyser_temperature.fitModel.make_params()\n", "params.add(name=\"A\", value= 1e6, max = np.inf, min = 1, vary = True)\n", "params.add(name=\"B\", value= 1000, max = np.inf, min = 0, vary = True)\n", "\n", "fitResult_temperature = fitAnalyser_temperature.fit(val_truncated, params, x='TOF_free', dask=\"parallelized\")\n", "\n", "val = fitAnalyser_temperature.get_fit_value(fitResult_temperature)\n", "std = fitAnalyser_temperature.get_fit_std(fitResult_temperature)\n", "\n", "fit_vals = tuple([val['A'].item(), val['B'].item()])\n", "fit_vals_std = tuple([std['A'].item(), std['B'].item()])\n", "\n", "tof = (np.arange(1,16,0.1)*1e-3)\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "val_mean.plot.errorbar(ax=ax, yerr=std_mean, fmt='or')\n", "plt.plot(tof, expansion(tof, *fit_vals), 'b--',\n", " label='fit: A=%.3f, B=%.3f' % tuple(fit_vals))\n", "plt.xlabel('TOF (s)')\n", "plt.ylabel('Cloud Width (pixels)')\n", "plt.tight_layout()\n", "plt.grid(visible=1)\n", "plt.legend()\n", "\n", "\n", "m = 164*1.673e-27\n", "kb = 1.38e-23\n", "pixel = 5.86e-6\n", "M = 0.6827\n", "\n", "T = fit_vals[0] * (m/kb) * ((pixel*pixel)/(M*M)) / (1e-6)\n", "dT = fit_vals_std[0] * (m/kb) * ((pixel*pixel)/(M*M)) / (1e-6)\n", "\n", "print('T = %.2f \\u00B1 %.2f uK'% tuple([T,dT]))" ] }, { "cell_type": "code", "execution_count": 72, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "<ErrorbarContainer object of 3 artists>" ] }, "execution_count": 72, "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": [ "val = fitAnalyser.get_fit_value(fitResult)\n", "std = fitAnalyser.get_fit_std(fitResult)\n", "\n", "val['centery'].plot.errorbar(hue='runs', fmt='o')" ] }, { "cell_type": "code", "execution_count": 73, "metadata": {}, "outputs": [ { "ename": "ValueError", "evalue": "Dataset does not contain the dimensions: ['runs']", "output_type": "error", "traceback": [ "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[1;31mValueError\u001b[0m Traceback (most recent call last)", "\u001b[1;32mf:\\Jianshun\\analyseScript\\Example.ipynb Cell 16\u001b[0m in \u001b[0;36m1\n\u001b[1;32m----> <a href='vscode-notebook-cell:/f%3A/Jianshun/analyseScript/Example.ipynb#Y123sZmlsZQ%3D%3D?line=0'>1</a>\u001b[0m val_mean \u001b[39m=\u001b[39m val\u001b[39m.\u001b[39;49mmean(dim\u001b[39m=\u001b[39;49m\u001b[39m'\u001b[39;49m\u001b[39mruns\u001b[39;49m\u001b[39m'\u001b[39;49m)\n\u001b[0;32m <a href='vscode-notebook-cell:/f%3A/Jianshun/analyseScript/Example.ipynb#Y123sZmlsZQ%3D%3D?line=1'>2</a>\u001b[0m val_mean[\u001b[39m'\u001b[39m\u001b[39mcentery\u001b[39m\u001b[39m'\u001b[39m]\u001b[39m.\u001b[39mplot\u001b[39m.\u001b[39merrorbar(fmt\u001b[39m=\u001b[39m\u001b[39m'\u001b[39m\u001b[39mo\u001b[39m\u001b[39m'\u001b[39m)\n", "File \u001b[1;32m~\\AppData\\Roaming\\Python\\Python39\\site-packages\\xarray\\core\\_aggregations.py:508\u001b[0m, in \u001b[0;36mDatasetAggregations.mean\u001b[1;34m(self, dim, skipna, keep_attrs, **kwargs)\u001b[0m\n\u001b[0;32m 426\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mmean\u001b[39m(\n\u001b[0;32m 427\u001b[0m \u001b[39mself\u001b[39m,\n\u001b[0;32m 428\u001b[0m dim: Dims \u001b[39m=\u001b[39m \u001b[39mNone\u001b[39;00m,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 432\u001b[0m \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs: Any,\n\u001b[0;32m 433\u001b[0m ) \u001b[39m-\u001b[39m\u001b[39m>\u001b[39m Dataset:\n\u001b[0;32m 434\u001b[0m \u001b[39m\"\"\"\u001b[39;00m\n\u001b[0;32m 435\u001b[0m \u001b[39m Reduce this Dataset's data by applying ``mean`` along some dimension(s).\u001b[39;00m\n\u001b[0;32m 436\u001b[0m \n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 506\u001b[0m \u001b[39m da float64 nan\u001b[39;00m\n\u001b[0;32m 507\u001b[0m \u001b[39m \"\"\"\u001b[39;00m\n\u001b[1;32m--> 508\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mreduce(\n\u001b[0;32m 509\u001b[0m duck_array_ops\u001b[39m.\u001b[39mmean,\n\u001b[0;32m 510\u001b[0m dim\u001b[39m=\u001b[39mdim,\n\u001b[0;32m 511\u001b[0m skipna\u001b[39m=\u001b[39mskipna,\n\u001b[0;32m 512\u001b[0m numeric_only\u001b[39m=\u001b[39m\u001b[39mTrue\u001b[39;00m,\n\u001b[0;32m 513\u001b[0m keep_attrs\u001b[39m=\u001b[39mkeep_attrs,\n\u001b[0;32m 514\u001b[0m \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs,\n\u001b[0;32m 515\u001b[0m )\n", "File \u001b[1;32m~\\AppData\\Roaming\\Python\\Python39\\site-packages\\xarray\\core\\dataset.py:5868\u001b[0m, in \u001b[0;36mDataset.reduce\u001b[1;34m(self, func, dim, keep_attrs, keepdims, numeric_only, **kwargs)\u001b[0m\n\u001b[0;32m 5866\u001b[0m missing_dimensions \u001b[39m=\u001b[39m [d \u001b[39mfor\u001b[39;00m d \u001b[39min\u001b[39;00m dims \u001b[39mif\u001b[39;00m d \u001b[39mnot\u001b[39;00m \u001b[39min\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mdims]\n\u001b[0;32m 5867\u001b[0m \u001b[39mif\u001b[39;00m missing_dimensions:\n\u001b[1;32m-> 5868\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mValueError\u001b[39;00m(\n\u001b[0;32m 5869\u001b[0m \u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mDataset does not contain the dimensions: \u001b[39m\u001b[39m{\u001b[39;00mmissing_dimensions\u001b[39m}\u001b[39;00m\u001b[39m\"\u001b[39m\n\u001b[0;32m 5870\u001b[0m )\n\u001b[0;32m 5872\u001b[0m \u001b[39mif\u001b[39;00m keep_attrs \u001b[39mis\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[0;32m 5873\u001b[0m keep_attrs \u001b[39m=\u001b[39m _get_keep_attrs(default\u001b[39m=\u001b[39m\u001b[39mFalse\u001b[39;00m)\n", "\u001b[1;31mValueError\u001b[0m: Dataset does not contain the dimensions: ['runs']" ] } ], "source": [ "val_mean = val.mean(dim='runs')\n", "val_mean['centery'].plot.errorbar(fmt='o')" ] }, { "cell_type": "code", "execution_count": 74, "metadata": {}, "outputs": [ { "data": { "image/png": "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 "text/plain": [ "<Figure size 640x480 with 1 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "def free_fall(x, A, B, C):\n", " return A*x**2 + C\n", "\n", "val = fitAnalyser.get_fit_value(fitResult)\n", "std = fitAnalyser.get_fit_std(fitResult)\n", "\n", "val_mean = val['centery']#.mean(dim='runs')\n", "std_mean = std['centery']#.mean(dim='runs')\n", "\n", "fitModel_freefall = NewFitModel(free_fall)\n", "fitAnalyser_freefall = FitAnalyser(fitModel_freefall, fitDim=1)\n", "\n", "params = fitAnalyser_freefall.fitModel.make_params()\n", "params.add(name=\"A\", value= 1e6, max = np.inf, min =-np.inf, vary = True)\n", "params.add(name=\"B\", value= 1000, max = np.inf, min =-np.inf, vary = True)\n", "params.add(name=\"C\", value= 1000, max = np.inf, min =-np.inf, vary = True)\n", "\n", "fitResult_freefall = fitAnalyser_freefall.fit(val_mean, params, x='TOF_free', dask=\"parallelized\")\n", "\n", "val = fitAnalyser_freefall.get_fit_value(fitResult_freefall)\n", "std = fitAnalyser_freefall.get_fit_std(fitResult_freefall)\n", "\n", "fit_vals = tuple([val['A'].item(), val['B'].item(), val['C'].item()])\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "val_mean.plot.errorbar(ax=ax, yerr=std_mean, fmt='or')\n", "tof = np.linspace(0,19,50)*1e-3\n", "plt.plot(tof, free_fall(tof, *fit_vals), 'b--',label='fit: A=%5.3f, B=%5.3f, C=%5.3f' % fit_vals)\n", "plt.grid(visible =1)\n", "plt.xlabel('TOF (s)')\n", "plt.ylabel('Cloud Center (pixels)')\n", "plt.legend()\n", "plt.show()\n", "\n", "#pixel= 3.45e-6\n", "pixel = 5.86e-6\n", "g = 9.80998\n", "M = 2*val['A'].item()*pixel/g\n", "# dM = 2*std['A'].item()*pixel/g\n", "\n", "# print('M = %.4f \\u00B1 %.4f '% tuple([M,dM]))" ] }, { "cell_type": "code", "execution_count": 75, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.7644689869504484" ] }, "execution_count": 75, "metadata": {}, "output_type": "execute_result" } ], "source": [ "M" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## Do a 2D two-peak gaussian fit to the OD images" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "### Do the fit" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "fitModel = DensityProfileBEC2dModel()\n", "# fitModel = ThomasFermi2dModel()\n", "\n", "fitAnalyser = FitAnalyser(fitModel, fitDim=2)\n", "\n", "# fitAnalyser = FitAnalyser(\"Gaussian-2D\", fitDim=2)\n", "\n", "dataSet_cropOD = dataSet_cropOD.chunk((1,100,100))\n", "\n", "params = fitAnalyser.guess(dataSet_cropOD, guess_kwargs=dict(pureBECThreshold=0.5), dask=\"parallelized\")\n", "fitResult = fitAnalyser.fit(dataSet_cropOD, params).load()" ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "f:\\Jianshun\\analyseScript\\Analyser\\FitAnalyser.py:84: RuntimeWarning: invalid value encountered in power\n", " res = (1- ((x-centerx)/(sigmax))**2 - ((y-centery)/(sigmay))**2)**(3 / 2)\n" ] }, { "data": { "text/plain": [ "<xarray.plot.facetgrid.FacetGrid at 0x239efc5dd30>" ] }, "execution_count": 34, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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"text/plain": [ "<Figure size 6100x300 with 21 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fitCurve = fitAnalyser.eval(fitResult, x=np.arange(100), y=np.arange(100), dask=\"parallelized\").load()\n", "\n", "fitCurve.plot.pcolormesh(cmap='jet', vmin=0, vmax=2, col=scanAxis[0], row=scanAxis[1], x='x', y='y')" ] }, { "cell_type": "code", "execution_count": 51, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "<xarray.plot.facetgrid.FacetGrid at 0x239efc16760>" ] }, "execution_count": 51, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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"text/plain": [ "<Figure size 6100x300 with 21 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "(dataSet_cropOD - fitCurve).plot.pcolormesh(cmap='jet', vmin=-0.1, vmax=0.1, col=scanAxis[0], row=scanAxis[1])" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/html": [ "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n", "<defs>\n", "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n", "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n", "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n", "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n", "</symbol>\n", "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n", "<path d=\"M28.681 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input + label {\n", " color: var(--xr-disabled-color);\n", "}\n", "\n", ".xr-section-item input:enabled + label {\n", " cursor: pointer;\n", " color: var(--xr-font-color2);\n", "}\n", "\n", ".xr-section-item input:enabled + label:hover {\n", " color: var(--xr-font-color0);\n", "}\n", "\n", ".xr-section-summary {\n", " grid-column: 1;\n", " color: var(--xr-font-color2);\n", " font-weight: 500;\n", "}\n", "\n", ".xr-section-summary > span {\n", " display: inline-block;\n", " padding-left: 0.5em;\n", "}\n", "\n", ".xr-section-summary-in:disabled + label {\n", " color: var(--xr-font-color2);\n", "}\n", "\n", ".xr-section-summary-in + label:before {\n", " display: inline-block;\n", " content: '►';\n", " font-size: 11px;\n", " width: 15px;\n", " text-align: center;\n", "}\n", "\n", ".xr-section-summary-in:disabled + label:before {\n", " color: var(--xr-disabled-color);\n", "}\n", "\n", ".xr-section-summary-in:checked + label:before {\n", " content: '▼';\n", "}\n", "\n", ".xr-section-summary-in:checked + label > span {\n", " display: none;\n", "}\n", "\n", ".xr-section-summary,\n", ".xr-section-inline-details {\n", " padding-top: 4px;\n", " padding-bottom: 4px;\n", "}\n", "\n", ".xr-section-inline-details {\n", " grid-column: 2 / -1;\n", "}\n", "\n", ".xr-section-details {\n", " display: none;\n", " grid-column: 1 / -1;\n", " margin-bottom: 5px;\n", "}\n", "\n", ".xr-section-summary-in:checked ~ .xr-section-details {\n", " display: contents;\n", "}\n", "\n", ".xr-array-wrap {\n", " grid-column: 1 / -1;\n", " display: grid;\n", " grid-template-columns: 20px auto;\n", "}\n", "\n", ".xr-array-wrap > label {\n", " grid-column: 1;\n", " vertical-align: top;\n", "}\n", "\n", ".xr-preview {\n", " color: var(--xr-font-color3);\n", "}\n", "\n", ".xr-array-preview,\n", ".xr-array-data {\n", " padding: 0 5px !important;\n", " grid-column: 2;\n", "}\n", "\n", ".xr-array-data,\n", ".xr-array-in:checked ~ .xr-array-preview {\n", " display: none;\n", "}\n", "\n", ".xr-array-in:checked ~ .xr-array-data,\n", ".xr-array-preview {\n", " display: inline-block;\n", "}\n", "\n", ".xr-dim-list {\n", " display: inline-block !important;\n", " list-style: none;\n", " padding: 0 !important;\n", " margin: 0;\n", "}\n", "\n", ".xr-dim-list li {\n", " display: inline-block;\n", " padding: 0;\n", " margin: 0;\n", "}\n", "\n", ".xr-dim-list:before {\n", " content: '(';\n", "}\n", "\n", ".xr-dim-list:after {\n", " content: ')';\n", "}\n", "\n", ".xr-dim-list li:not(:last-child):after {\n", " content: ',';\n", " padding-right: 5px;\n", "}\n", "\n", ".xr-has-index {\n", " font-weight: bold;\n", "}\n", "\n", ".xr-var-list,\n", ".xr-var-item {\n", " display: contents;\n", "}\n", "\n", ".xr-var-item > div,\n", ".xr-var-item label,\n", ".xr-var-item > .xr-var-name span {\n", " background-color: var(--xr-background-color-row-even);\n", " margin-bottom: 0;\n", "}\n", "\n", ".xr-var-item > .xr-var-name:hover span {\n", " padding-right: 5px;\n", "}\n", "\n", ".xr-var-list > li:nth-child(odd) > div,\n", ".xr-var-list > li:nth-child(odd) > label,\n", ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n", " background-color: var(--xr-background-color-row-odd);\n", "}\n", "\n", ".xr-var-name {\n", " grid-column: 1;\n", "}\n", "\n", ".xr-var-dims {\n", " grid-column: 2;\n", "}\n", "\n", ".xr-var-dtype {\n", " grid-column: 3;\n", " text-align: right;\n", " color: var(--xr-font-color2);\n", "}\n", "\n", ".xr-var-preview {\n", " grid-column: 4;\n", "}\n", "\n", ".xr-index-preview {\n", " grid-column: 2 / 5;\n", " color: var(--xr-font-color2);\n", "}\n", "\n", ".xr-var-name,\n", ".xr-var-dims,\n", ".xr-var-dtype,\n", ".xr-preview,\n", ".xr-attrs dt {\n", " white-space: nowrap;\n", " overflow: hidden;\n", " text-overflow: ellipsis;\n", " padding-right: 10px;\n", "}\n", "\n", ".xr-var-name:hover,\n", ".xr-var-dims:hover,\n", ".xr-var-dtype:hover,\n", ".xr-attrs dt:hover {\n", " overflow: visible;\n", " width: auto;\n", " z-index: 1;\n", "}\n", "\n", ".xr-var-attrs,\n", ".xr-var-data,\n", ".xr-index-data {\n", " display: none;\n", " background-color: var(--xr-background-color) !important;\n", " padding-bottom: 5px !important;\n", "}\n", "\n", ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n", ".xr-var-data-in:checked ~ .xr-var-data,\n", ".xr-index-data-in:checked ~ .xr-index-data {\n", " display: block;\n", "}\n", "\n", ".xr-var-data > table {\n", " float: right;\n", "}\n", "\n", ".xr-var-name span,\n", ".xr-var-data,\n", ".xr-index-name div,\n", ".xr-index-data,\n", ".xr-attrs {\n", " padding-left: 25px !important;\n", "}\n", "\n", ".xr-attrs,\n", ".xr-var-attrs,\n", ".xr-var-data,\n", ".xr-index-data {\n", " grid-column: 1 / -1;\n", "}\n", "\n", "dl.xr-attrs {\n", " padding: 0;\n", " margin: 0;\n", " display: grid;\n", " grid-template-columns: 125px auto;\n", "}\n", "\n", ".xr-attrs dt,\n", ".xr-attrs dd {\n", " padding: 0;\n", " margin: 0;\n", " float: left;\n", " padding-right: 10px;\n", " width: auto;\n", "}\n", "\n", ".xr-attrs dt {\n", " font-weight: normal;\n", " grid-column: 1;\n", "}\n", "\n", ".xr-attrs dt:hover span {\n", " display: inline-block;\n", " background: var(--xr-background-color);\n", " padding-right: 10px;\n", "}\n", "\n", ".xr-attrs dd {\n", " grid-column: 2;\n", " white-space: pre-wrap;\n", " word-break: break-all;\n", "}\n", "\n", ".xr-icon-database,\n", ".xr-icon-file-text2,\n", ".xr-no-icon {\n", " display: inline-block;\n", " vertical-align: middle;\n", " width: 1em;\n", " height: 1.5em !important;\n", " stroke-width: 0;\n", " stroke: currentColor;\n", " fill: currentColor;\n", "}\n", "</style><pre class='xr-text-repr-fallback'><xarray.DataArray 'OD' (runs: 20)>\n", "array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", " 0., 0., 0.])\n", "Coordinates:\n", " * runs (runs) float64 0.0 1.0 2.0 3.0 4.0 5.0 ... 15.0 16.0 17.0 18.0 19.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'OD'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>runs</span>: 20</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-a2313552-07be-460f-ac03-18206b4a87c7' class='xr-array-in' type='checkbox' checked><label for='section-a2313552-07be-460f-ac03-18206b4a87c7' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0</span></div><div class='xr-array-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", " 0., 0., 0.])</pre></div></div></li><li class='xr-section-item'><input id='section-bcb983e5-04a5-49e0-a452-1906a3213229' class='xr-section-summary-in' type='checkbox' checked><label for='section-bcb983e5-04a5-49e0-a452-1906a3213229' 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 3.0 ... 17.0 18.0 19.0</div><input id='attrs-7f11840e-bc64-4fd4-8174-a99cdc24316e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7f11840e-bc64-4fd4-8174-a99cdc24316e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1557858a-f286-4207-91e1-a8b9aed27415' class='xr-var-data-in' type='checkbox'><label for='data-1557858a-f286-4207-91e1-a8b9aed27415' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0., 1., 2., 3., 4., 5., 6., 7., 8., 9., 10., 11., 12., 13.,\n", " 14., 15., 16., 17., 18., 19.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a81a4e8a-3f27-4293-8363-4519a0929f2b' class='xr-section-summary-in' type='checkbox' ><label for='section-a81a4e8a-3f27-4293-8363-4519a0929f2b' 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-1d02c9df-62fb-43a5-bc2a-953a52636956' class='xr-index-data-in' type='checkbox'/><label for='index-1d02c9df-62fb-43a5-bc2a-953a52636956' 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, 9.0, 10.0,\n", " 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0],\n", " dtype='float64', name='runs'))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8bb37b9f-1cfe-4a89-82e9-8ed773c1955e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-8bb37b9f-1cfe-4a89-82e9-8ed773c1955e' 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' (runs: 20)>\n", "array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", " 0., 0., 0.])\n", "Coordinates:\n", " * runs (runs) float64 0.0 1.0 2.0 3.0 4.0 5.0 ... 15.0 16.0 17.0 18.0 19.0" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "fitModel2 = Polylog22dModel(prefix='thermal_')\n", "fitAnalyser2 = FitAnalyser(fitModel2, fitDim=2)\n", "fitCurve2 = fitAnalyser2.eval(fitResult, x=np.arange(100), y=np.arange(100), dask=\"parallelized\").load()\n", "fitCurve2.sum(dim=['x', 'y'])" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "C:\\Users\\data\\AppData\\Roaming\\Python\\Python39\\site-packages\\numpy\\lib\\function_base.py:2246: RuntimeWarning: invalid value encountered in _get_fit_full_result_single (vectorized)\n", " outputs = ufunc(*inputs)\n" ] } ], "source": [ "value = fitAnalyser.get_fit_full_result(fitResult)" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/html": [ "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n", "<defs>\n", "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n", "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n", "<path 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"\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'><xarray.Dataset>\n", "Dimensions: (runs: 20)\n", "Coordinates:\n", " * runs (runs) float64 0.0 1.0 2.0 3.0 ... 16.0 17.0 18.0 19.0\n", "Data variables:\n", " BEC_amplitude (runs) object 678.2635955189662+/-nan ... 704.529111...\n", " thermal_amplitude (runs) object 0.0+/-nan 0.0+/-nan ... 0.0+/-nan\n", " BEC_centerx (runs) object 41.68161303986658+/-nan ... 43.3093895...\n", " BEC_centery (runs) object 48.263472046762345+/-nan ... 47.371206...\n", " thermal_centerx (runs) object 44.13847419706019+/-nan ... 45.5424640...\n", " thermal_centery (runs) object 48.10984924238203+/-nan ... 48.2021514...\n", " BEC_sigmax (runs) object 11.148402342086538+/-nan ... 11.240485...\n", " BEC_sigmay (runs) object 28.173710962485302+/-nan ... 28.020501...\n", " thermal_sigmax (runs) object 20.210666526427037+/-nan ... 19.265726...\n", " thermal_sigmay (runs) object 22.827594738210404+/-nan ... 20.307830...\n", " thermalAspectRatio (runs) object 1.1294825288597745+/-nan ... 1.0540910...\n", " condensate_fraction (runs) object 1.0+/-nan 1.0+/-nan ... 1.0+/-nan</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-bf5faab5-ee4e-44bc-9db5-78d284375ca6' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-bf5faab5-ee4e-44bc-9db5-78d284375ca6' 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>: 20</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-17fe7f40-c74e-4434-a411-f2c896fb962d' class='xr-section-summary-in' type='checkbox' checked><label for='section-17fe7f40-c74e-4434-a411-f2c896fb962d' 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 3.0 ... 17.0 18.0 19.0</div><input id='attrs-360aef93-e051-42cd-86ee-6b25705b0b8f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-360aef93-e051-42cd-86ee-6b25705b0b8f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e027773a-9364-4ca0-bf27-72b29602cb55' class='xr-var-data-in' type='checkbox'><label for='data-e027773a-9364-4ca0-bf27-72b29602cb55' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0., 1., 2., 3., 4., 5., 6., 7., 8., 9., 10., 11., 12., 13.,\n", " 14., 15., 16., 17., 18., 19.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6f7fd351-036c-4ee5-86f4-d15adef03086' class='xr-section-summary-in' type='checkbox' checked><label for='section-6f7fd351-036c-4ee5-86f4-d15adef03086' class='xr-section-summary' >Data variables: <span>(12)</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>BEC_amplitude</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>678.2635955189662+/-nan ... 704....</div><input id='attrs-96e2131b-2b6a-4010-9524-892405d1c305' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-96e2131b-2b6a-4010-9524-892405d1c305' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-04f79c7a-6b6a-4363-904f-34689b9144c1' class='xr-var-data-in' type='checkbox'><label for='data-04f79c7a-6b6a-4363-904f-34689b9144c1' 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([678.2635955189662+/-nan, 570.9300691040178+/-nan,\n", " 729.7439048133908+/-nan, 561.4816558162713+/-nan,\n", " 767.46198583519+/-nan, 791.6371068647577+/-nan,\n", " 738.3120441940093+/-nan, 718.0327650311755+/-nan,\n", " 713.2635798843459+/-nan, 770.4724349923216+/-nan,\n", " 745.2630547187833+/-nan, 713.6190864987104+/-nan,\n", " 730.4155945253933+/-nan, 766.7164328868425+/-nan,\n", " 711.4300692582335+/-nan, 765.9705661810385+/-nan,\n", " 744.9363853076882+/-nan, 695.0804563161535+/-nan,\n", " 740.9492233678551+/-nan, 704.5291114313244+/-nan], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>thermal_amplitude</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>0.0+/-nan 0.0+/-nan ... 0.0+/-nan</div><input id='attrs-bc7d2cd1-c037-4342-ae65-f478b1a11798' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bc7d2cd1-c037-4342-ae65-f478b1a11798' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4e2358f-64db-4925-a08c-9c0013290c45' class='xr-var-data-in' type='checkbox'><label for='data-a4e2358f-64db-4925-a08c-9c0013290c45' 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([0.0+/-nan, 0.0+/-nan, 0.0+/-nan, 0.0+/-nan, 0.0+/-nan, 0.0+/-nan,\n", " 0.0+/-nan, 0.0+/-nan, 0.0+/-nan, 0.0+/-nan, 0.0+/-nan, 0.0+/-nan,\n", " 0.0+/-nan, 0.0+/-nan, 0.0+/-nan, 0.0+/-nan, 0.0+/-nan, 0.0+/-nan,\n", " 0.0+/-nan, 0.0+/-nan], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>BEC_centerx</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>41.68161303986658+/-nan ... 43.3...</div><input id='attrs-c4b2a8aa-37e7-4301-84a7-a1ff5b2b18da' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c4b2a8aa-37e7-4301-84a7-a1ff5b2b18da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bf2c0111-07da-4025-ab86-a6d0b805a5ed' class='xr-var-data-in' type='checkbox'><label for='data-bf2c0111-07da-4025-ab86-a6d0b805a5ed' 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([41.68161303986658+/-nan, 43.54643075547984+/-nan,\n", " 44.010352486593824+/-nan, 42.23001931117413+/-nan,\n", " 42.766374066460976+/-nan, 43.064151852282954+/-nan,\n", " 43.516086914287854+/-nan, 41.760592913348056+/-nan,\n", " 43.51494443994783+/-nan, 42.96251968226675+/-nan,\n", " 43.37005744679945+/-nan, 43.56655154931581+/-nan,\n", " 41.772287573081385+/-nan, 43.57692836638424+/-nan,\n", " 45.61015214662576+/-nan, 41.40326837431126+/-nan,\n", " 44.13412837882349+/-nan, 44.00010352323085+/-nan,\n", " 42.32311435664195+/-nan, 43.309389528876224+/-nan], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>BEC_centery</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>48.263472046762345+/-nan ... 47....</div><input id='attrs-5627d1ee-0560-4283-8731-128f18ea284d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5627d1ee-0560-4283-8731-128f18ea284d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aeca68be-4985-47d3-a947-744dc40aa6d2' class='xr-var-data-in' type='checkbox'><label for='data-aeca68be-4985-47d3-a947-744dc40aa6d2' 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([48.263472046762345+/-nan, 47.92156369156314+/-nan,\n", " 47.92387786596079+/-nan, 48.10018864805499+/-nan,\n", " 51.08989375819018+/-nan, 49.75067493119259+/-nan,\n", " 47.485012496868826+/-nan, 50.089735490415876+/-nan,\n", " 45.30492159070581+/-nan, 48.163658266991035+/-nan,\n", " 48.69045819525425+/-nan, 47.71273537630479+/-nan,\n", " 46.667368211637175+/-nan, 49.78442036595954+/-nan,\n", " 49.765165402627545+/-nan, 47.198228609116065+/-nan,\n", " 49.29418992339359+/-nan, 49.08225642928532+/-nan,\n", " 49.653591948991554+/-nan, 47.371206413802184+/-nan], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>thermal_centerx</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>44.13847419706019+/-nan ... 45.5...</div><input id='attrs-526cc799-320b-4324-b6e2-b51f608d3165' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-526cc799-320b-4324-b6e2-b51f608d3165' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1e0f673f-15e0-4147-ba44-84560451169e' class='xr-var-data-in' type='checkbox'><label for='data-1e0f673f-15e0-4147-ba44-84560451169e' 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([44.13847419706019+/-nan, 45.625985468547086+/-nan,\n", " 46.533925797896586+/-nan, 44.62165814130569+/-nan,\n", " 46.27250825767642+/-nan, 45.434316947514525+/-nan,\n", " 45.79001967569101+/-nan, 44.373678858979716+/-nan,\n", " 44.30970039095943+/-nan, 46.16331722441009+/-nan,\n", " 46.08105971750488+/-nan, 46.27372376784467+/-nan,\n", " 43.18101816774123+/-nan, 46.21990395299141+/-nan,\n", " 47.65613216970865+/-nan, 45.44757204102094+/-nan,\n", " 46.15125411738556+/-nan, 46.75599053582757+/-nan,\n", " 44.32872271444131+/-nan, 45.542464092852626+/-nan], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>thermal_centery</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>48.10984924238203+/-nan ... 48.2...</div><input id='attrs-c078280c-7362-4f0a-ba09-1b8af75909c9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c078280c-7362-4f0a-ba09-1b8af75909c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-161100d5-ed5e-4ea6-97b7-b8d3a816fd7c' class='xr-var-data-in' type='checkbox'><label for='data-161100d5-ed5e-4ea6-97b7-b8d3a816fd7c' 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([48.10984924238203+/-nan, 48.29776864170357+/-nan,\n", " 47.89841719607176+/-nan, 48.637843612341435+/-nan,\n", " 50.37205105787732+/-nan, 50.155873982348055+/-nan,\n", " 48.27111751663431+/-nan, 48.07814079982143+/-nan,\n", " 45.50313397295916+/-nan, 47.714487832172104+/-nan,\n", " 49.05731548616915+/-nan, 47.50811202696543+/-nan,\n", " 46.1817067496195+/-nan, 48.94577010119909+/-nan,\n", " 50.1565406150817+/-nan, 48.077286151654334+/-nan,\n", " 48.57662656783241+/-nan, 47.78555906193826+/-nan,\n", " 48.99216045013127+/-nan, 48.20215142491456+/-nan], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>BEC_sigmax</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>11.148402342086538+/-nan ... 11....</div><input id='attrs-a2fe2418-af5b-4e33-9dd3-b43c2272f130' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a2fe2418-af5b-4e33-9dd3-b43c2272f130' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ca79232-b13c-41a9-8fcf-16198212e543' class='xr-var-data-in' type='checkbox'><label for='data-5ca79232-b13c-41a9-8fcf-16198212e543' 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([11.148402342086538+/-nan, 10.846082348511317+/-nan,\n", " 9.936114826926607+/-nan, 11.472841060977212+/-nan,\n", " 11.087130045409271+/-nan, 12.11490129467912+/-nan,\n", " 10.612355566718353+/-nan, 12.24460010310613+/-nan,\n", " 11.069876144733835+/-nan, 10.847949190512326+/-nan,\n", " 11.320238906819718+/-nan, 10.45963696150712+/-nan,\n", " 12.117828903680287+/-nan, 11.034145701375415+/-nan,\n", " 11.355872074606202+/-nan, 12.116194146665793+/-nan,\n", " 10.903573947256424+/-nan, 10.129303376358745+/-nan,\n", " 12.01520389393174+/-nan, 11.240485207644735+/-nan], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>BEC_sigmay</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>28.173710962485302+/-nan ... 28....</div><input id='attrs-a3a4df22-e9ae-4cfa-bcf7-aef2956fbc10' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a3a4df22-e9ae-4cfa-bcf7-aef2956fbc10' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-25090a3b-7cdd-426a-98b0-7e9631f66a74' class='xr-var-data-in' type='checkbox'><label for='data-25090a3b-7cdd-426a-98b0-7e9631f66a74' 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([28.173710962485302+/-nan, 27.472729730893885+/-nan,\n", " 29.009610740653653+/-nan, 27.419395208369675+/-nan,\n", " 28.78082785775886+/-nan, 29.10278079322779+/-nan,\n", " 28.744306416044882+/-nan, 28.069840269388685+/-nan,\n", " 28.200854516406597+/-nan, 28.446834155244442+/-nan,\n", " 28.515211832123114+/-nan, 28.154729425094988+/-nan,\n", " 28.34634650648515+/-nan, 28.194266087711572+/-nan,\n", " 27.522060885732127+/-nan, 28.19518556065402+/-nan,\n", " 28.682484626873705+/-nan, 28.440019920248236+/-nan,\n", " 27.80547930051193+/-nan, 28.020501236848293+/-nan], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>thermal_sigmax</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>20.210666526427037+/-nan ... 19....</div><input id='attrs-b42be749-186c-4699-a239-d6f6038f9513' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b42be749-186c-4699-a239-d6f6038f9513' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-20c38154-dd2a-46c6-b8ee-16b5763ceffe' class='xr-var-data-in' type='checkbox'><label for='data-20c38154-dd2a-46c6-b8ee-16b5763ceffe' 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([20.210666526427037+/-nan, 24.757561807686848+/-nan,\n", " 21.016275726385558+/-nan, 21.258035446764737+/-nan,\n", " 24.070593277746358+/-nan, 23.659615215915654+/-nan,\n", " 22.266005090386873+/-nan, 26.698202895570923+/-nan,\n", " 22.43670433550361+/-nan, 23.011456416631702+/-nan,\n", " 20.891865108307083+/-nan, 22.19060404180224+/-nan,\n", " 23.75360558398967+/-nan, 21.489022009835708+/-nan,\n", " 23.143154840521934+/-nan, 24.664786557573173+/-nan,\n", " 24.428932400629346+/-nan, 20.908575597007076+/-nan,\n", " 26.44651418579941+/-nan, 19.26572608786609+/-nan], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>thermal_sigmay</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>22.827594738210404+/-nan ... 20....</div><input id='attrs-22cc9fc7-498e-4c10-b86c-7c24d2ee04e7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-22cc9fc7-498e-4c10-b86c-7c24d2ee04e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bc1dc8aa-547f-4675-8b6c-529ac0f95b0d' class='xr-var-data-in' type='checkbox'><label for='data-bc1dc8aa-547f-4675-8b6c-529ac0f95b0d' 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([22.827594738210404+/-nan, 29.354713384227505+/-nan,\n", " 22.789693923460963+/-nan, 23.18921200858366+/-nan,\n", " 28.78685175806023+/-nan, 28.391538259098784+/-nan,\n", " 25.912070215608463+/-nan, 32.037843474685104+/-nan,\n", " 26.19017971689124+/-nan, 27.613747699958044+/-nan,\n", " 23.91984106587037+/-nan, 26.384204859722296+/-nan,\n", " 28.504326700787605+/-nan, 25.393825266679013+/-nan,\n", " 27.77178580862632+/-nan, 29.597743869087807+/-nan,\n", " 29.314718880755215+/-nan, 22.642030075368012+/-nan,\n", " 31.73581702295929+/-nan, 20.30783021305562+/-nan], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>thermalAspectRatio</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1.1294825288597745+/-nan ... 1.0...</div><input id='attrs-84165e27-5e1b-4e91-b3d2-b5bd07d162a9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-84165e27-5e1b-4e91-b3d2-b5bd07d162a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e46054b-432f-434c-afa5-013f36cc15f3' class='xr-var-data-in' type='checkbox'><label for='data-4e46054b-432f-434c-afa5-013f36cc15f3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1.1294825288597745+/-nan, 1.1856867656132968+/-nan,\n", " 1.0843830857647585+/-nan, 1.090844545191161+/-nan,\n", " 1.1959344510496186+/-nan, 1.2+/-nan, 1.1637503050242157+/-nan,\n", " 1.2+/-nan, 1.167291743264102+/-nan, 1.2+/-nan,\n", " 1.1449356456144881+/-nan, 1.1889809222867584+/-nan, 1.2+/-nan,\n", " 1.1817115388060027+/-nan, 1.2+/-nan, 1.2+/-nan, 1.2+/-nan,\n", " 1.0829063878750818+/-nan, 1.2+/-nan, 1.0540910900755445+/-nan],\n", " dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>condensate_fraction</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1.0+/-nan 1.0+/-nan ... 1.0+/-nan</div><input id='attrs-28b68693-c5b1-4b99-a0f1-e128ade63856' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-28b68693-c5b1-4b99-a0f1-e128ade63856' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b126802e-2e20-4301-927a-3e28908f8cbe' class='xr-var-data-in' type='checkbox'><label for='data-b126802e-2e20-4301-927a-3e28908f8cbe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1.0+/-nan, 1.0+/-nan, 1.0+/-nan, 1.0+/-nan, 1.0+/-nan, 1.0+/-nan,\n", " 1.0+/-nan, 1.0+/-nan, 1.0+/-nan, 1.0+/-nan, 1.0+/-nan, 1.0+/-nan,\n", " 1.0+/-nan, 1.0+/-nan, 1.0+/-nan, 1.0+/-nan, 1.0+/-nan, 1.0+/-nan,\n", " 1.0+/-nan, 1.0+/-nan], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-244e583a-6404-438a-a610-3d225e7aa06b' class='xr-section-summary-in' type='checkbox' ><label for='section-244e583a-6404-438a-a610-3d225e7aa06b' 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-8205b11f-4659-4f73-87a7-d2aec2863f80' class='xr-index-data-in' type='checkbox'/><label for='index-8205b11f-4659-4f73-87a7-d2aec2863f80' 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, 9.0, 10.0,\n", " 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0],\n", " dtype='float64', name='runs'))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-92338550-34a4-4904-b2ad-09855698df24' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-92338550-34a4-4904-b2ad-09855698df24' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>" ], "text/plain": [ "<xarray.Dataset>\n", "Dimensions: (runs: 20)\n", "Coordinates:\n", " * runs (runs) float64 0.0 1.0 2.0 3.0 ... 16.0 17.0 18.0 19.0\n", "Data variables:\n", " BEC_amplitude (runs) object 678.2635955189662+/-nan ... 704.529111...\n", " thermal_amplitude (runs) object 0.0+/-nan 0.0+/-nan ... 0.0+/-nan\n", " BEC_centerx (runs) object 41.68161303986658+/-nan ... 43.3093895...\n", " BEC_centery (runs) object 48.263472046762345+/-nan ... 47.371206...\n", " thermal_centerx (runs) object 44.13847419706019+/-nan ... 45.5424640...\n", " thermal_centery (runs) object 48.10984924238203+/-nan ... 48.2021514...\n", " BEC_sigmax (runs) object 11.148402342086538+/-nan ... 11.240485...\n", " BEC_sigmay (runs) object 28.173710962485302+/-nan ... 28.020501...\n", " thermal_sigmax (runs) object 20.210666526427037+/-nan ... 19.265726...\n", " thermal_sigmay (runs) object 22.827594738210404+/-nan ... 20.307830...\n", " thermalAspectRatio (runs) object 1.1294825288597745+/-nan ... 1.0540910...\n", " condensate_fraction (runs) object 1.0+/-nan 1.0+/-nan ... 1.0+/-nan" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "value" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "### Get the result of the fit" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [], "source": [ "value = fitAnalyser.get_fit_value(fitResult)" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [], "source": [ "std = fitAnalyser.get_fit_std(fitResult)" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "C:\\Users\\data\\AppData\\Roaming\\Python\\Python39\\site-packages\\numpy\\lib\\function_base.py:2246: RuntimeWarning: invalid value encountered in _get_fit_full_result_single (vectorized)\n", " outputs = ufunc(*inputs)\n" ] }, { "data": { "text/html": [ "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n", 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".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'><xarray.Dataset>\n", "Dimensions: (runs: 20)\n", "Coordinates:\n", " * runs (runs) float64 0.0 1.0 2.0 3.0 ... 16.0 17.0 18.0 19.0\n", "Data variables:\n", " BEC_amplitude (runs) object 678.2635955189662+/-nan ... 704.529111...\n", " thermal_amplitude (runs) object 0.0+/-nan 0.0+/-nan ... 0.0+/-nan\n", " BEC_centerx (runs) object 41.68161303986658+/-nan ... 43.3093895...\n", " BEC_centery (runs) object 48.263472046762345+/-nan ... 47.371206...\n", " thermal_centerx (runs) object 44.13847419706019+/-nan ... 45.5424640...\n", " thermal_centery (runs) object 48.10984924238203+/-nan ... 48.2021514...\n", " BEC_sigmax (runs) object 11.148402342086538+/-nan ... 11.240485...\n", " BEC_sigmay (runs) object 28.173710962485302+/-nan ... 28.020501...\n", " thermal_sigmax (runs) object 20.210666526427037+/-nan ... 19.265726...\n", " thermal_sigmay (runs) object 22.827594738210404+/-nan ... 20.307830...\n", " thermalAspectRatio (runs) object 1.1294825288597745+/-nan ... 1.0540910...\n", " condensate_fraction (runs) object 1.0+/-nan 1.0+/-nan ... 1.0+/-nan</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-1a216d6f-cd96-41a0-95c3-de1b2dec949e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-1a216d6f-cd96-41a0-95c3-de1b2dec949e' 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>: 20</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-7dd206d7-461b-4171-a8b6-2806bd261265' class='xr-section-summary-in' type='checkbox' checked><label for='section-7dd206d7-461b-4171-a8b6-2806bd261265' 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 3.0 ... 17.0 18.0 19.0</div><input id='attrs-e3498fae-5355-46f7-8718-836f13f0f1b5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e3498fae-5355-46f7-8718-836f13f0f1b5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1715c2b8-d0c0-4f5a-aaf3-d3d7210b5b88' class='xr-var-data-in' type='checkbox'><label for='data-1715c2b8-d0c0-4f5a-aaf3-d3d7210b5b88' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0., 1., 2., 3., 4., 5., 6., 7., 8., 9., 10., 11., 12., 13.,\n", " 14., 15., 16., 17., 18., 19.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f4926267-dbc5-40b8-876b-0acc33017207' class='xr-section-summary-in' type='checkbox' checked><label for='section-f4926267-dbc5-40b8-876b-0acc33017207' class='xr-section-summary' >Data variables: <span>(12)</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>BEC_amplitude</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>678.2635955189662+/-nan ... 704....</div><input id='attrs-94f3126e-f6ad-485c-8ce7-79235ca3d1a5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-94f3126e-f6ad-485c-8ce7-79235ca3d1a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-131a9007-9639-4708-b3eb-039a61c0f0a5' class='xr-var-data-in' type='checkbox'><label for='data-131a9007-9639-4708-b3eb-039a61c0f0a5' 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([678.2635955189662+/-nan, 570.9300691040178+/-nan,\n", " 729.7439048133908+/-nan, 561.4816558162713+/-nan,\n", " 767.46198583519+/-nan, 791.6371068647577+/-nan,\n", " 738.3120441940093+/-nan, 718.0327650311755+/-nan,\n", " 713.2635798843459+/-nan, 770.4724349923216+/-nan,\n", " 745.2630547187833+/-nan, 713.6190864987104+/-nan,\n", " 730.4155945253933+/-nan, 766.7164328868425+/-nan,\n", " 711.4300692582335+/-nan, 765.9705661810385+/-nan,\n", " 744.9363853076882+/-nan, 695.0804563161535+/-nan,\n", " 740.9492233678551+/-nan, 704.5291114313244+/-nan], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>thermal_amplitude</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>0.0+/-nan 0.0+/-nan ... 0.0+/-nan</div><input id='attrs-1c8827c4-0e30-42b2-baa6-977a735159ca' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1c8827c4-0e30-42b2-baa6-977a735159ca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4a244b95-44d5-45d1-b408-453c79701d65' class='xr-var-data-in' type='checkbox'><label for='data-4a244b95-44d5-45d1-b408-453c79701d65' 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([0.0+/-nan, 0.0+/-nan, 0.0+/-nan, 0.0+/-nan, 0.0+/-nan, 0.0+/-nan,\n", " 0.0+/-nan, 0.0+/-nan, 0.0+/-nan, 0.0+/-nan, 0.0+/-nan, 0.0+/-nan,\n", " 0.0+/-nan, 0.0+/-nan, 0.0+/-nan, 0.0+/-nan, 0.0+/-nan, 0.0+/-nan,\n", " 0.0+/-nan, 0.0+/-nan], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>BEC_centerx</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>41.68161303986658+/-nan ... 43.3...</div><input id='attrs-583ef8f4-fe00-4c5b-a4f2-c4235ed966f9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-583ef8f4-fe00-4c5b-a4f2-c4235ed966f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-84f30403-ba59-4ce6-81a4-42caf91c5e62' class='xr-var-data-in' type='checkbox'><label for='data-84f30403-ba59-4ce6-81a4-42caf91c5e62' 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([41.68161303986658+/-nan, 43.54643075547984+/-nan,\n", " 44.010352486593824+/-nan, 42.23001931117413+/-nan,\n", " 42.766374066460976+/-nan, 43.064151852282954+/-nan,\n", " 43.516086914287854+/-nan, 41.760592913348056+/-nan,\n", " 43.51494443994783+/-nan, 42.96251968226675+/-nan,\n", " 43.37005744679945+/-nan, 43.56655154931581+/-nan,\n", " 41.772287573081385+/-nan, 43.57692836638424+/-nan,\n", " 45.61015214662576+/-nan, 41.40326837431126+/-nan,\n", " 44.13412837882349+/-nan, 44.00010352323085+/-nan,\n", " 42.32311435664195+/-nan, 43.309389528876224+/-nan], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>BEC_centery</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>48.263472046762345+/-nan ... 47....</div><input id='attrs-b607aed7-4250-44e6-ba96-f68113d8810f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b607aed7-4250-44e6-ba96-f68113d8810f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1f9d701c-22a2-4845-98fc-9a86af0576c6' class='xr-var-data-in' type='checkbox'><label for='data-1f9d701c-22a2-4845-98fc-9a86af0576c6' 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([48.263472046762345+/-nan, 47.92156369156314+/-nan,\n", " 47.92387786596079+/-nan, 48.10018864805499+/-nan,\n", " 51.08989375819018+/-nan, 49.75067493119259+/-nan,\n", " 47.485012496868826+/-nan, 50.089735490415876+/-nan,\n", " 45.30492159070581+/-nan, 48.163658266991035+/-nan,\n", " 48.69045819525425+/-nan, 47.71273537630479+/-nan,\n", " 46.667368211637175+/-nan, 49.78442036595954+/-nan,\n", " 49.765165402627545+/-nan, 47.198228609116065+/-nan,\n", " 49.29418992339359+/-nan, 49.08225642928532+/-nan,\n", " 49.653591948991554+/-nan, 47.371206413802184+/-nan], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>thermal_centerx</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>44.13847419706019+/-nan ... 45.5...</div><input id='attrs-b58221cf-5462-46e1-a60c-f14a56db0b15' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b58221cf-5462-46e1-a60c-f14a56db0b15' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-afbf2cc8-b06d-4b1e-a77e-3035fdd14f47' class='xr-var-data-in' type='checkbox'><label for='data-afbf2cc8-b06d-4b1e-a77e-3035fdd14f47' 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([44.13847419706019+/-nan, 45.625985468547086+/-nan,\n", " 46.533925797896586+/-nan, 44.62165814130569+/-nan,\n", " 46.27250825767642+/-nan, 45.434316947514525+/-nan,\n", " 45.79001967569101+/-nan, 44.373678858979716+/-nan,\n", " 44.30970039095943+/-nan, 46.16331722441009+/-nan,\n", " 46.08105971750488+/-nan, 46.27372376784467+/-nan,\n", " 43.18101816774123+/-nan, 46.21990395299141+/-nan,\n", " 47.65613216970865+/-nan, 45.44757204102094+/-nan,\n", " 46.15125411738556+/-nan, 46.75599053582757+/-nan,\n", " 44.32872271444131+/-nan, 45.542464092852626+/-nan], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>thermal_centery</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>48.10984924238203+/-nan ... 48.2...</div><input id='attrs-b952584c-dfb2-41b9-8740-1c2586992bbe' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b952584c-dfb2-41b9-8740-1c2586992bbe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-416f0dec-da56-4b2e-8030-ccf4ddb992ca' class='xr-var-data-in' type='checkbox'><label for='data-416f0dec-da56-4b2e-8030-ccf4ddb992ca' 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([48.10984924238203+/-nan, 48.29776864170357+/-nan,\n", " 47.89841719607176+/-nan, 48.637843612341435+/-nan,\n", " 50.37205105787732+/-nan, 50.155873982348055+/-nan,\n", " 48.27111751663431+/-nan, 48.07814079982143+/-nan,\n", " 45.50313397295916+/-nan, 47.714487832172104+/-nan,\n", " 49.05731548616915+/-nan, 47.50811202696543+/-nan,\n", " 46.1817067496195+/-nan, 48.94577010119909+/-nan,\n", " 50.1565406150817+/-nan, 48.077286151654334+/-nan,\n", " 48.57662656783241+/-nan, 47.78555906193826+/-nan,\n", " 48.99216045013127+/-nan, 48.20215142491456+/-nan], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>BEC_sigmax</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>11.148402342086538+/-nan ... 11....</div><input id='attrs-9613df5a-194d-4e5d-863f-b8ff0584d35c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9613df5a-194d-4e5d-863f-b8ff0584d35c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6064a1dd-30d4-4217-8ed9-73877723c5e2' class='xr-var-data-in' type='checkbox'><label for='data-6064a1dd-30d4-4217-8ed9-73877723c5e2' 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([11.148402342086538+/-nan, 10.846082348511317+/-nan,\n", " 9.936114826926607+/-nan, 11.472841060977212+/-nan,\n", " 11.087130045409271+/-nan, 12.11490129467912+/-nan,\n", " 10.612355566718353+/-nan, 12.24460010310613+/-nan,\n", " 11.069876144733835+/-nan, 10.847949190512326+/-nan,\n", " 11.320238906819718+/-nan, 10.45963696150712+/-nan,\n", " 12.117828903680287+/-nan, 11.034145701375415+/-nan,\n", " 11.355872074606202+/-nan, 12.116194146665793+/-nan,\n", " 10.903573947256424+/-nan, 10.129303376358745+/-nan,\n", " 12.01520389393174+/-nan, 11.240485207644735+/-nan], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>BEC_sigmay</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>28.173710962485302+/-nan ... 28....</div><input id='attrs-731e9688-9c5e-44b8-8868-0b4840fc4b9c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-731e9688-9c5e-44b8-8868-0b4840fc4b9c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-03cf043b-a549-4b31-8eb8-5acd44941cf4' class='xr-var-data-in' type='checkbox'><label for='data-03cf043b-a549-4b31-8eb8-5acd44941cf4' 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([28.173710962485302+/-nan, 27.472729730893885+/-nan,\n", " 29.009610740653653+/-nan, 27.419395208369675+/-nan,\n", " 28.78082785775886+/-nan, 29.10278079322779+/-nan,\n", " 28.744306416044882+/-nan, 28.069840269388685+/-nan,\n", " 28.200854516406597+/-nan, 28.446834155244442+/-nan,\n", " 28.515211832123114+/-nan, 28.154729425094988+/-nan,\n", " 28.34634650648515+/-nan, 28.194266087711572+/-nan,\n", " 27.522060885732127+/-nan, 28.19518556065402+/-nan,\n", " 28.682484626873705+/-nan, 28.440019920248236+/-nan,\n", " 27.80547930051193+/-nan, 28.020501236848293+/-nan], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>thermal_sigmax</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>20.210666526427037+/-nan ... 19....</div><input id='attrs-af29ddb1-abfe-4bc0-a219-2c8cb7820440' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-af29ddb1-abfe-4bc0-a219-2c8cb7820440' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4a7f1246-974c-4373-9869-2cdd474f1b0e' class='xr-var-data-in' type='checkbox'><label for='data-4a7f1246-974c-4373-9869-2cdd474f1b0e' 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([20.210666526427037+/-nan, 24.757561807686848+/-nan,\n", " 21.016275726385558+/-nan, 21.258035446764737+/-nan,\n", " 24.070593277746358+/-nan, 23.659615215915654+/-nan,\n", " 22.266005090386873+/-nan, 26.698202895570923+/-nan,\n", " 22.43670433550361+/-nan, 23.011456416631702+/-nan,\n", " 20.891865108307083+/-nan, 22.19060404180224+/-nan,\n", " 23.75360558398967+/-nan, 21.489022009835708+/-nan,\n", " 23.143154840521934+/-nan, 24.664786557573173+/-nan,\n", " 24.428932400629346+/-nan, 20.908575597007076+/-nan,\n", " 26.44651418579941+/-nan, 19.26572608786609+/-nan], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>thermal_sigmay</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>22.827594738210404+/-nan ... 20....</div><input id='attrs-34293cce-7870-4a7b-b30f-7362232407a5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-34293cce-7870-4a7b-b30f-7362232407a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-007cd236-2bea-44f3-9453-7b0c5015589e' class='xr-var-data-in' type='checkbox'><label for='data-007cd236-2bea-44f3-9453-7b0c5015589e' 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([22.827594738210404+/-nan, 29.354713384227505+/-nan,\n", " 22.789693923460963+/-nan, 23.18921200858366+/-nan,\n", " 28.78685175806023+/-nan, 28.391538259098784+/-nan,\n", " 25.912070215608463+/-nan, 32.037843474685104+/-nan,\n", " 26.19017971689124+/-nan, 27.613747699958044+/-nan,\n", " 23.91984106587037+/-nan, 26.384204859722296+/-nan,\n", " 28.504326700787605+/-nan, 25.393825266679013+/-nan,\n", " 27.77178580862632+/-nan, 29.597743869087807+/-nan,\n", " 29.314718880755215+/-nan, 22.642030075368012+/-nan,\n", " 31.73581702295929+/-nan, 20.30783021305562+/-nan], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>thermalAspectRatio</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1.1294825288597745+/-nan ... 1.0...</div><input id='attrs-36657bfb-be9d-470f-bae0-8816a86c0fdc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-36657bfb-be9d-470f-bae0-8816a86c0fdc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-20913f5c-b760-41c0-be65-1a45bfa5ce72' class='xr-var-data-in' type='checkbox'><label for='data-20913f5c-b760-41c0-be65-1a45bfa5ce72' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1.1294825288597745+/-nan, 1.1856867656132968+/-nan,\n", " 1.0843830857647585+/-nan, 1.090844545191161+/-nan,\n", " 1.1959344510496186+/-nan, 1.2+/-nan, 1.1637503050242157+/-nan,\n", " 1.2+/-nan, 1.167291743264102+/-nan, 1.2+/-nan,\n", " 1.1449356456144881+/-nan, 1.1889809222867584+/-nan, 1.2+/-nan,\n", " 1.1817115388060027+/-nan, 1.2+/-nan, 1.2+/-nan, 1.2+/-nan,\n", " 1.0829063878750818+/-nan, 1.2+/-nan, 1.0540910900755445+/-nan],\n", " dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>condensate_fraction</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1.0+/-nan 1.0+/-nan ... 1.0+/-nan</div><input id='attrs-90fecb03-5a3c-4bca-ae05-17e5ca62f818' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-90fecb03-5a3c-4bca-ae05-17e5ca62f818' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-94bfdbe5-de37-49e6-aa3b-a6fc284fc16f' class='xr-var-data-in' type='checkbox'><label for='data-94bfdbe5-de37-49e6-aa3b-a6fc284fc16f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1.0+/-nan, 1.0+/-nan, 1.0+/-nan, 1.0+/-nan, 1.0+/-nan, 1.0+/-nan,\n", " 1.0+/-nan, 1.0+/-nan, 1.0+/-nan, 1.0+/-nan, 1.0+/-nan, 1.0+/-nan,\n", " 1.0+/-nan, 1.0+/-nan, 1.0+/-nan, 1.0+/-nan, 1.0+/-nan, 1.0+/-nan,\n", " 1.0+/-nan, 1.0+/-nan], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c0c5a21a-e028-4042-86cb-f37453c07f6a' class='xr-section-summary-in' type='checkbox' ><label for='section-c0c5a21a-e028-4042-86cb-f37453c07f6a' 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-be39d4ae-64ed-4f4c-95dc-94432182fe30' class='xr-index-data-in' type='checkbox'/><label for='index-be39d4ae-64ed-4f4c-95dc-94432182fe30' 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, 9.0, 10.0,\n", " 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0],\n", " dtype='float64', name='runs'))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-81cf425a-e368-4efe-a16d-55c6719dd68e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-81cf425a-e368-4efe-a16d-55c6719dd68e' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>" ], "text/plain": [ "<xarray.Dataset>\n", "Dimensions: (runs: 20)\n", "Coordinates:\n", " * runs (runs) float64 0.0 1.0 2.0 3.0 ... 16.0 17.0 18.0 19.0\n", "Data variables:\n", " BEC_amplitude (runs) object 678.2635955189662+/-nan ... 704.529111...\n", " thermal_amplitude (runs) object 0.0+/-nan 0.0+/-nan ... 0.0+/-nan\n", " BEC_centerx (runs) object 41.68161303986658+/-nan ... 43.3093895...\n", " BEC_centery (runs) object 48.263472046762345+/-nan ... 47.371206...\n", " thermal_centerx (runs) object 44.13847419706019+/-nan ... 45.5424640...\n", " thermal_centery (runs) object 48.10984924238203+/-nan ... 48.2021514...\n", " BEC_sigmax (runs) object 11.148402342086538+/-nan ... 11.240485...\n", " BEC_sigmay (runs) object 28.173710962485302+/-nan ... 28.020501...\n", " thermal_sigmax (runs) object 20.210666526427037+/-nan ... 19.265726...\n", " thermal_sigmay (runs) object 22.827594738210404+/-nan ... 20.307830...\n", " thermalAspectRatio (runs) object 1.1294825288597745+/-nan ... 1.0540910...\n", " condensate_fraction (runs) object 1.0+/-nan 1.0+/-nan ... 1.0+/-nan" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "fitAnalyser.get_fit_full_result(fitResult)" ] }, { "cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [ { "data": { "image/png": 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"text/plain": [ "<Figure size 640x480 with 1 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "value.BEC_amplitude.plot.errorbar(fmt='ob')\n", "plt.grid()" ] }, { "cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [ { "data": { "image/png": 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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'><xarray.DataArray 'BEC_amplitude' ()>\n", "array(717.92545613)</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'>'BEC_amplitude'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-a31f85ed-3657-4e68-abcb-68057cf991fe' class='xr-array-in' type='checkbox' checked><label for='section-a31f85ed-3657-4e68-abcb-68057cf991fe' 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>717.9</span></div><div class='xr-array-data'><pre>array(717.92545613)</pre></div></div></li><li class='xr-section-item'><input id='section-9cca9315-854c-4eaf-a633-d6dfe62131aa' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-9cca9315-854c-4eaf-a633-d6dfe62131aa' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-5f9b9670-24bd-4d42-8ed8-a18f69bc1348' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5f9b9670-24bd-4d42-8ed8-a18f69bc1348' class='xr-section-summary' title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-c511c759-efd6-489f-bd68-df745fa34095' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-c511c759-efd6-489f-bd68-df745fa34095' 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 'BEC_amplitude' ()>\n", "array(717.92545613)" ] }, "execution_count": 45, "metadata": {}, "output_type": "execute_result" } ], "source": [ "calculate_mean(value.BEC_amplitude)" ] }, { "cell_type": "code", "execution_count": 46, "metadata": {}, "outputs": [ { "data": { "text/html": [ "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n", "<defs>\n", "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n", "<path d=\"M16 0c-8.837 0-16 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"</style><pre class='xr-text-repr-fallback'><xarray.DataArray 'BEC_amplitude' ()>\n", "array(57.66059232)</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'>'BEC_amplitude'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-69482eaa-387d-4835-9fb2-e61d7cf795cb' class='xr-array-in' type='checkbox' checked><label for='section-69482eaa-387d-4835-9fb2-e61d7cf795cb' 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>57.66</span></div><div class='xr-array-data'><pre>array(57.66059232)</pre></div></div></li><li class='xr-section-item'><input id='section-d038e492-4082-411e-88d2-4dbb7ef0855d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d038e492-4082-411e-88d2-4dbb7ef0855d' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-0aced48b-9ed2-41fd-ae3e-3296ca20bb22' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0aced48b-9ed2-41fd-ae3e-3296ca20bb22' class='xr-section-summary' title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-0971d935-7798-4ca2-9013-e45de2d0c633' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0971d935-7798-4ca2-9013-e45de2d0c633' 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 'BEC_amplitude' ()>\n", "array(57.66059232)" ] }, "execution_count": 46, "metadata": {}, "output_type": "execute_result" } ], "source": [ "value.BEC_amplitude.std(dim='runs')" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## Get the Ncount" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "### Calculate the mean and standard deviation" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "ename": "TypeError", "evalue": "No numeric data to plot.", "output_type": "error", "traceback": [ "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)", "\u001b[1;32mf:\\Jianshun\\analyseScript\\Example.ipynb Cell 26\u001b[0m in \u001b[0;36m6\n\u001b[0;32m <a href='vscode-notebook-cell:/f%3A/Jianshun/analyseScript/Example.ipynb#X31sZmlsZQ%3D%3D?line=3'>4</a>\u001b[0m Ncount_mean \u001b[39m=\u001b[39m calculate_mean(Ncount)\n\u001b[0;32m <a href='vscode-notebook-cell:/f%3A/Jianshun/analyseScript/Example.ipynb#X31sZmlsZQ%3D%3D?line=4'>5</a>\u001b[0m Ncount_std \u001b[39m=\u001b[39m calculate_std(Ncount)\n\u001b[1;32m----> <a href='vscode-notebook-cell:/f%3A/Jianshun/analyseScript/Example.ipynb#X31sZmlsZQ%3D%3D?line=5'>6</a>\u001b[0m Ncount_mean\u001b[39m.\u001b[39;49mplot\u001b[39m.\u001b[39;49merrorbar()\u001b[39m#yerr=Ncount_std)\u001b[39;00m\n\u001b[0;32m <a href='vscode-notebook-cell:/f%3A/Jianshun/analyseScript/Example.ipynb#X31sZmlsZQ%3D%3D?line=6'>7</a>\u001b[0m plt\u001b[39m.\u001b[39mshow()\n", "File \u001b[1;32mf:\\Jianshun\\analyseScript\\ToolFunction\\HomeMadeXarrayFunction.py:274\u001b[0m, in \u001b[0;36mdataarray_plot_errorbar\u001b[1;34m(DataArrayPlotAccessor, *args, **kwargs)\u001b[0m\n\u001b[0;32m 273\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mdataarray_plot_errorbar\u001b[39m(DataArrayPlotAccessor, \u001b[39m*\u001b[39margs, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs) \u001b[39m-\u001b[39m\u001b[39m>\u001b[39m \u001b[39mlist\u001b[39m[Line3D] \u001b[39m|\u001b[39m FacetGrid[DataArray]:\n\u001b[1;32m--> 274\u001b[0m \u001b[39mreturn\u001b[39;00m errorbar(DataArrayPlotAccessor\u001b[39m.\u001b[39m_da, \u001b[39m*\u001b[39margs, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs)\n", "File \u001b[1;32mf:\\Jianshun\\analyseScript\\ToolFunction\\HomeMadeXarrayFunction.py:183\u001b[0m, in \u001b[0;36merrorbar\u001b[1;34m(darray, xerr, yerr, row, col, figsize, aspect, size, ax, hue, x, y, xincrease, yincrease, xscale, yscale, xticks, yticks, xlim, ylim, add_legend, _labels, *args, **kwargs)\u001b[0m\n\u001b[0;32m 180\u001b[0m ndims \u001b[39m=\u001b[39m \u001b[39mlen\u001b[39m(darray\u001b[39m.\u001b[39mdims)\n\u001b[0;32m 181\u001b[0m \u001b[39mif\u001b[39;00m ndims \u001b[39m==\u001b[39m \u001b[39m0\u001b[39m \u001b[39mor\u001b[39;00m darray\u001b[39m.\u001b[39msize \u001b[39m==\u001b[39m \u001b[39m0\u001b[39m:\n\u001b[0;32m 182\u001b[0m \u001b[39m# TypeError to be consistent with pandas\u001b[39;00m\n\u001b[1;32m--> 183\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mTypeError\u001b[39;00m(\u001b[39m\"\u001b[39m\u001b[39mNo numeric data to plot.\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[0;32m 184\u001b[0m \u001b[39mif\u001b[39;00m ndims \u001b[39m>\u001b[39m \u001b[39m2\u001b[39m:\n\u001b[0;32m 185\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mValueError\u001b[39;00m(\n\u001b[0;32m 186\u001b[0m \u001b[39m\"\u001b[39m\u001b[39mLine plots are for 1- or 2-dimensional DataArrays. \u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m 187\u001b[0m \u001b[39m\"\u001b[39m\u001b[39mPassed DataArray has \u001b[39m\u001b[39m{ndims}\u001b[39;00m\u001b[39m \u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m 188\u001b[0m \u001b[39m\"\u001b[39m\u001b[39mdimensions\u001b[39m\u001b[39m\"\u001b[39m\u001b[39m.\u001b[39mformat(ndims\u001b[39m=\u001b[39mndims)\n\u001b[0;32m 189\u001b[0m )\n", "\u001b[1;31mTypeError\u001b[0m: No numeric data to plot." ] } ], "source": [ "Ncount = imageAnalyser.get_Ncount(dataSet_cropOD)\n", "\n", "Ncount.load()\n", "Ncount_mean = calculate_mean(Ncount)\n", "Ncount_std = calculate_std(Ncount)\n", "Ncount_mean.plot.errorbar()#yerr=Ncount_std)\n", "plt.show()" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "### Do a 1D fit" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "def gaussian(x, amplitude=1.0, center=0.0, sigma=1.0):\n", " \"\"\"Return a 1-dimensional Gaussian function.\n", "\n", " gaussian(x, amplitude, center, sigma) =\n", " (amplitude/(s2pi*sigma)) * exp(-(1.0*x-center)**2 / (2*sigma**2))\n", "\n", " \"\"\"\n", " return ((amplitude/(max(1e-10, np.sqrt(2*np.pi)*sigma)))\n", " * np.exp(-(1.0*x-center)**2 / max(1e-10, (2*sigma**2))))\n", "\n", "fitModel = NewFitModel(gaussian)\n", "\n", "fitModel.make_params()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "fitAnalyser = FitAnalyser(fitModel, fitDim=1)\n", "\n", "params = fitAnalyser.guess(Ncount_mean, x=\"sin_mod_freq\", dask=\"parallelized\")\n", "fitResult = fitAnalyser.fit(Ncount_mean, params, x=\"sin_mod_freq\").load()\n", "\n", "plot_x = np.linspace(Ncount_mean[\"sin_mod_freq\"].min(), Ncount_mean[\"sin_mod_freq\"].max(), 100)\n", "\n", "fitCurve = fitAnalyser.eval(fitResult, x=plot_x, dask=\"parallelized\").load()\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "\n", "Ncount_mean.plot.errorbar(ax=ax, yerr=Ncount_std)\n", "fitCurve.plot.errorbar(ax=ax, fmt='--g')\n", "\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "fitCurve = fitCurve.rename(dict(x='final_amp'))\n", "plot_dataSe = xr.combine_nested([Ncount_mean, fitCurve], ['plot'])\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "plot_dataSe.sel(plot=[0, 1]).plot.errorbar(ax=ax, hue='plot', x='final_amp', fmt=['ob', '-g'])\n", "plt.show()\n" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "# Select data and remove bad shot" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "plot_dataSe.where( (Ncount_mean[scanAxis[0]]<2e-4) & (Ncount_mean[scanAxis[0]]>1e-4) )" ] }, { "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": [ "img_dir = '//DyLabNAS/Data/'\n", "SequenceName = \"Evaporative_Cooling\" + \"/\"\n", "folderPath = img_dir + SequenceName + '2023/05/17'" ] }, { "cell_type": "code", "execution_count": null, "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", "}" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "dataSet" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "shotNum = \"0023\"\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 = (280, 959)\n", "imageAnalyser.span = (350, 350)\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)\n", "Ncount_mean = Ncount.mean(dim='runs')\n", "Ncount_std = Ncount.std(dim='runs')\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "Ncount_mean.plot.errorbar(ax=ax, yerr = Ncount_std, fmt='ob')\n", "\n", "plt.ylabel('NCount')\n", "plt.tight_layout()\n", "#plt.ylim([0, 800])\n", "plt.grid(visible=1)\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "def sinc_func(x, amplitude=1.0, center=0.0, sigma=1.0, offset=0.0):\n", " x = np.where(x==center, 1e-15, x)\n", " return amplitude * ( np.sin(np.pi*(x-center)*sigma) / (np.pi*( (x-center) )* max(sigma, 1e-15) ) ) + offset\n", "\n", "fitModel = NewFitModel(sinc_func)\n", "\n", "fitModel.make_params()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "fitAnalyser = FitAnalyser(fitModel, fitDim=1)\n", "# params = fitAnalyser.guess(Ncount_mean_1, x=scanAxis[0], guess_kwargs=dict(negative=True), dask=\"parallelized\")\n", "params = fitAnalyser.fitModel.make_params()\n", "params.add(name=\"amplitude\", value= -5000, max=np.inf, min=-np.inf, vary=True)\n", "params.add(name=\"center\", value= 4.24, max=np.inf, min=-np.inf, vary=True)\n", "params.add(name=\"sigma\", value= 100, max=np.inf, min= 0, vary=True)\n", "params.add(name=\"offset\", value= 7000, max=np.inf, min=-np.inf, vary=True)\n", "\n", "fitResult = fitAnalyser.fit(Ncount_mean, params, x=scanAxis[0]).load()\n", "freqdata = np.linspace(4.21, 4.27, 500)\n", "fitCurve = fitAnalyser.eval(fitResult, x=freqdata, dask=\"parallelized\").load()\n", "fitCurve = fitCurve.assign_coords({'x':np.array(freqdata)})\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "\n", "Ncount_mean.plot.errorbar(ax=ax, yerr = Ncount_std, fmt='ob')\n", "fitCurve.plot.errorbar(ax=ax, fmt='--g')\n", "plt.xlabel('Center Frequency (MHz)')\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": [ "fitResult.item()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import lmfit\n", "\n", "def sinc_func(x, amplitude=1.0, center=0.0, sigma=1.0, offset=0.0):\n", " x = np.where(x==center, 1e-5, x)\n", " return amplitude * ( np.sin(np.pi*(x-center)*max(sigma, 1e-5)) / (np.pi*( (x-center) )* max(sigma, 1e-5) ) ) + offset\n", "\n", "def _fit_1D(data, params, x):\n", " \n", " print(x)\n", " print(data)\n", " \n", " res = fitModel.fit(data=data, x=x, params=params, nan_policy='omit')\n", " \n", " print(111)\n", " \n", " # print(res.items())\n", " \n", " return 1\n", "\n", "def fit(dataArray, paramsArray, x=None, y=None, input_core_dims=None, dask='parallelized', vectorize=True, keep_attrs=True, daskKwargs=None, **kwargs):\n", " \n", " kwargs.update(\n", " {\n", " \"dask\": dask,\n", " \"vectorize\": vectorize,\n", " \"input_core_dims\": input_core_dims,\n", " 'keep_attrs': keep_attrs,\n", " }\n", " )\n", " \n", " fitModel = NewFitModel(sinc_func)\n", "\n", " if not daskKwargs is None:\n", " kwargs.update({\"dask_gufunc_kwargs\": daskKwargs})\n", " \n", " if isinstance(paramsArray, type(fitModel.make_params())):\n", "\n", " if input_core_dims is None:\n", " kwargs.update(\n", " {\n", " \"input_core_dims\": [['x']],\n", " }\n", " )\n", "\n", " if x is None:\n", " if 'x' in dataArray.dims:\n", " x = dataArray['x'].to_numpy()\n", " else:\n", " if isinstance(x, str):\n", " if input_core_dims is None:\n", " kwargs.update(\n", " {\n", " \"input_core_dims\": [[x]],\n", " }\n", " )\n", " x = dataArray[x].to_numpy()\n", "\n", " return xr.apply_ufunc(_fit_1D, dataArray, kwargs={'params':paramsArray,'x':x},\n", " output_dtypes=[type(lmfit.model.ModelResult(fitModel, fitModel.make_params()))], \n", " **kwargs)\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "params = fitAnalyser.fitModel.make_params()\n", "params.add(name=\"amplitude\", value= -6000, max=np.inf, min=-np.inf, vary=True)\n", "params.add(name=\"center\", value= 4.24, max=np.inf, min=-np.inf, vary=True)\n", "params.add(name=\"sigma\", value= 1, max=np.inf, min= 0, vary=True)\n", "params.add(name=\"offset\", value= 6000, max=np.inf, min=-np.inf, vary=True)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "fitResult = fit(Ncount_mean, params, x=scanAxis[0]).load()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "def sinc_func(x, amplitude=1.0, center=0.0, sigma=1.0, offset=0.0):\n", " x = np.where(x==center, 1e-5, x)\n", " return amplitude * ( np.sin(np.pi*(x-center)*max(sigma, 1e-5)) / (np.pi*( (x-center) )* max(sigma, 1e-5) ) ) + offset\n", "\n", "fitModel = NewFitModel(sinc_func)\n", "\n", "fitModel.make_params()\n", "\n", "data = Ncount_mean.to_numpy()\n", "x = Ncount_mean.carrier_freq.to_numpy()\n", "\n", "fitModel.fit(data=data, x=x, params=params, nan_policy='omit')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "np.where(x==0, 1, 2)" ] }, { "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": [ { "data": { "text/html": [ "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n", "<defs>\n", "<symbol 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"}\n", "\n", "html[theme=dark],\n", "body[data-theme=dark],\n", "body.vscode-dark {\n", " --xr-font-color0: rgba(255, 255, 255, 1);\n", " --xr-font-color2: rgba(255, 255, 255, 0.54);\n", " --xr-font-color3: rgba(255, 255, 255, 0.38);\n", " --xr-border-color: #1F1F1F;\n", " --xr-disabled-color: #515151;\n", " --xr-background-color: #111111;\n", " --xr-background-color-row-even: #111111;\n", " --xr-background-color-row-odd: #313131;\n", "}\n", "\n", ".xr-wrap {\n", " display: block !important;\n", " min-width: 300px;\n", " max-width: 700px;\n", "}\n", "\n", ".xr-text-repr-fallback {\n", " /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n", " display: none;\n", "}\n", "\n", ".xr-header {\n", " padding-top: 6px;\n", " padding-bottom: 6px;\n", " margin-bottom: 4px;\n", " border-bottom: solid 1px var(--xr-border-color);\n", "}\n", "\n", ".xr-header > div,\n", ".xr-header > ul {\n", " display: inline;\n", " margin-top: 0;\n", " margin-bottom: 0;\n", "}\n", "\n", ".xr-obj-type,\n", ".xr-array-name {\n", " margin-left: 2px;\n", " margin-right: 10px;\n", "}\n", "\n", ".xr-obj-type {\n", " color: var(--xr-font-color2);\n", "}\n", "\n", ".xr-sections {\n", " padding-left: 0 !important;\n", " display: grid;\n", " grid-template-columns: 150px auto auto 1fr 20px 20px;\n", "}\n", "\n", ".xr-section-item {\n", " display: contents;\n", "}\n", "\n", ".xr-section-item input {\n", " display: none;\n", "}\n", "\n", ".xr-section-item input + label {\n", " color: var(--xr-disabled-color);\n", "}\n", "\n", ".xr-section-item input:enabled + label {\n", " cursor: pointer;\n", " color: var(--xr-font-color2);\n", "}\n", "\n", ".xr-section-item input:enabled + label:hover {\n", " color: var(--xr-font-color0);\n", "}\n", "\n", ".xr-section-summary {\n", " grid-column: 1;\n", " color: var(--xr-font-color2);\n", " font-weight: 500;\n", "}\n", "\n", ".xr-section-summary > span {\n", " display: inline-block;\n", " padding-left: 0.5em;\n", "}\n", "\n", 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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 / 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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'><xarray.Dataset>\n", "Dimensions: (index: 1201, fileIndex: 1)\n", "Coordinates:\n", " * index (index) int64 0 1 2 3 4 5 6 ... 1195 1196 1197 1198 1199 1200\n", "Dimensions without coordinates: fileIndex\n", "Data variables:\n", " X (fileIndex, index) float64 nan 0.0 1.0 ... 1.198e+03 1.199e+03\n", " CH1 (fileIndex, index) float64 nan -0.2 -0.3 -0.1 ... 32.3 32.8 32.2\n", " CH2 (fileIndex, index) float64 nan -0.007 -0.007 ... 0.022 0.0115\n", " Start (fileIndex, index) float64 nan nan nan nan ... nan nan nan nan\n", " Increment (fileIndex, index) float64 nan nan nan nan ... nan nan nan nan\n", " Unnamed: 5 (fileIndex, index) float64 nan nan nan nan ... nan nan nan nan</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-d1a81bd0-e01e-48c2-a161-b6b36da23ecb' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d1a81bd0-e01e-48c2-a161-b6b36da23ecb' 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'>index</span>: 1201</li><li><span>fileIndex</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-91bafc75-f88b-4ea0-8797-30c0c0bc7594' class='xr-section-summary-in' type='checkbox' checked><label for='section-91bafc75-f88b-4ea0-8797-30c0c0bc7594' 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'>index</span></div><div class='xr-var-dims'>(index)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 1197 1198 1199 1200</div><input id='attrs-13e60b2e-5229-4547-b25b-ee0f7307e44d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-13e60b2e-5229-4547-b25b-ee0f7307e44d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-36db378a-2cd3-4e51-b364-da0825791a88' class='xr-var-data-in' type='checkbox'><label for='data-36db378a-2cd3-4e51-b364-da0825791a88' 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, ..., 1198, 1199, 1200], dtype=int64)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c6b527db-b944-4b66-b15e-8d6a53b079c5' class='xr-section-summary-in' type='checkbox' checked><label for='section-c6b527db-b944-4b66-b15e-8d6a53b079c5' class='xr-section-summary' >Data variables: <span>(6)</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>X</span></div><div class='xr-var-dims'>(fileIndex, index)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan 0.0 1.0 ... 1.198e+03 1.199e+03</div><input id='attrs-186600c0-090d-44f8-86fd-a76f02a0be65' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-186600c0-090d-44f8-86fd-a76f02a0be65' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-80d35d06-41ea-4605-9e1c-8607e1f98a09' class='xr-var-data-in' type='checkbox'><label for='data-80d35d06-41ea-4605-9e1c-8607e1f98a09' 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([[ nan, 0.000e+00, 1.000e+00, ..., 1.197e+03, 1.198e+03,\n", " 1.199e+03]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH1</span></div><div class='xr-var-dims'>(fileIndex, index)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan -0.2 -0.3 ... 32.3 32.8 32.2</div><input id='attrs-fcd9d11e-cc02-48c1-923c-4b27836e5645' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fcd9d11e-cc02-48c1-923c-4b27836e5645' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c5ff33b2-17a8-4287-ba2b-f8a40026ab7e' class='xr-var-data-in' type='checkbox'><label for='data-c5ff33b2-17a8-4287-ba2b-f8a40026ab7e' 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([[ nan, -0.2, -0.3, ..., 32.3, 32.8, 32.2]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH2</span></div><div class='xr-var-dims'>(fileIndex, index)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan -0.007 -0.007 ... 0.022 0.0115</div><input id='attrs-450cd4f6-62ab-4903-831b-ef4378a1ec21' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-450cd4f6-62ab-4903-831b-ef4378a1ec21' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f61ca6e4-86d6-439d-9fa1-02f0ed7f803a' class='xr-var-data-in' type='checkbox'><label for='data-f61ca6e4-86d6-439d-9fa1-02f0ed7f803a' 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([[ nan, -0.007 , -0.007 , ..., 0.01 , 0.022 , 0.0115]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Start</span></div><div class='xr-var-dims'>(fileIndex, index)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-186390d3-77a2-4019-8fa9-16359bf02799' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-186390d3-77a2-4019-8fa9-16359bf02799' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8770d88d-5f15-4721-91c8-2801a83ff2a0' class='xr-var-data-in' type='checkbox'><label for='data-8770d88d-5f15-4721-91c8-2801a83ff2a0' 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([[nan, nan, nan, ..., nan, nan, nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Increment</span></div><div class='xr-var-dims'>(fileIndex, index)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-2d4b83cb-e814-4a17-87b4-ccb9c42d73bf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2d4b83cb-e814-4a17-87b4-ccb9c42d73bf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3fcdb06b-f235-42f7-9e5a-9dfbc9f257a8' class='xr-var-data-in' type='checkbox'><label for='data-3fcdb06b-f235-42f7-9e5a-9dfbc9f257a8' 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([[nan, nan, nan, ..., nan, nan, nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Unnamed: 5</span></div><div class='xr-var-dims'>(fileIndex, index)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-0e7529be-b633-43d7-a6 ], "text/plain": [ "<xarray.Dataset>\n", "Dimensions: (index: 1201, fileIndex: 1)\n", "Coordinates:\n", " * index (index) int64 0 1 2 3 4 5 6 ... 1195 1196 1197 1198 1199 1200\n", "Dimensions without coordinates: fileIndex\n", "Data variables:\n", " X (fileIndex, index) float64 nan 0.0 1.0 ... 1.198e+03 1.199e+03\n", " CH1 (fileIndex, index) float64 nan -0.2 -0.3 -0.1 ... 32.3 32.8 32.2\n", " CH2 (fileIndex, index) float64 nan -0.007 -0.007 ... 0.022 0.0115\n", " Start (fileIndex, index) float64 nan nan nan nan ... nan nan nan nan\n", " Increment (fileIndex, index) float64 nan nan nan nan ... nan nan nan nan\n", " Unnamed: 5 (fileIndex, index) float64 nan nan nan nan ... nan nan nan nan" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "filePath = './NewFile5.csv'\n", "data = read_csv_file(filePath)\n", "remove_bad_shots(data, index=0)\n", "data1 = data.astype(float)\n", "\n", "filePath = './NewFile6.csv'\n", "data = read_csv_file(filePath)\n", "remove_bad_shots(data, index=0)\n", "data2 = data.astype(float)\n", "\n", "filePath = './NewFile7.csv'\n", "data = read_csv_file(filePath)\n", "remove_bad_shots(data, index=0)\n", "data3 = data.astype(float)\n", "\n", "filePath = './NewFile8.csv'\n", "data = read_csv_file(filePath)\n", "remove_bad_shots(data, index=0)\n", "data4 = data.astype(float)\n", "\n", "data = (data1 + data2 + data3 + data4) / 4\n", "\n", "data" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ " # %matplotlib widget" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [ { "data": { "image/png": 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"text/plain": [ "<Figure size 800x600 with 1 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig = plt.figure(figsize=(8,6))\n", "ax = fig.gca()\n", "\n", "data.isel(fileIndex=0).CH2.plot(ax=ax)\n", "# plt.xlim([0, 590])\n", "plt.ylim([-0.02, 0.1])\n", "plt.grid()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [ { "data": { "text/html": [ "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n", "<defs>\n", "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n", "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n", "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n", "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n", "</symbol>\n", "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n", 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> 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'><xarray.DataArray 'CH2' ()>\n", "array(0.01528947)</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'>'CH2'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-d2f2bf64-2577-4e87-8a90-3d01ca6133ce' class='xr-array-in' type='checkbox' checked><label for='section-d2f2bf64-2577-4e87-8a90-3d01ca6133ce' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.01529</span></div><div class='xr-array-data'><pre>array(0.01528947)</pre></div></div></li><li class='xr-section-item'><input id='section-01d2cc89-7d19-4d5f-a34c-fbf2e06690a6' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-01d2cc89-7d19-4d5f-a34c-fbf2e06690a6' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-9409588c-69f2-43ac-8fc4-b18acab9863d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-9409588c-69f2-43ac-8fc4-b18acab9863d' class='xr-section-summary' title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-aae06b6f-ab11-4e7a-927b-62d422de944e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-aae06b6f-ab11-4e7a-927b-62d422de944e' 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 'CH2' ()>\n", "array(0.01528947)" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "data.isel(fileIndex=0, index=slice(1000, 1190)).CH2.mean()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [ { "data": { "text/html": [ "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n", "<defs>\n", "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n", "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n", "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n", "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n", "</symbol>\n", "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n", "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 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--xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n", "}\n", "\n", "html[theme=dark],\n", "body[data-theme=dark],\n", "body.vscode-dark {\n", " --xr-font-color0: rgba(255, 255, 255, 1);\n", " --xr-font-color2: rgba(255, 255, 255, 0.54);\n", " --xr-font-color3: rgba(255, 255, 255, 0.38);\n", " --xr-border-color: #1F1F1F;\n", " --xr-disabled-color: #515151;\n", " --xr-background-color: #111111;\n", " --xr-background-color-row-even: #111111;\n", " --xr-background-color-row-odd: #313131;\n", "}\n", "\n", ".xr-wrap {\n", " display: block !important;\n", " min-width: 300px;\n", " max-width: 700px;\n", "}\n", "\n", ".xr-text-repr-fallback {\n", " /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n", " display: none;\n", "}\n", "\n", ".xr-header {\n", " padding-top: 6px;\n", " padding-bottom: 6px;\n", " margin-bottom: 4px;\n", " border-bottom: solid 1px var(--xr-border-color);\n", "}\n", "\n", ".xr-header > div,\n", ".xr-header > ul {\n", " display: inline;\n", " margin-top: 0;\n", " margin-bottom: 0;\n", "}\n", "\n", ".xr-obj-type,\n", ".xr-array-name {\n", " margin-left: 2px;\n", " margin-right: 10px;\n", "}\n", "\n", ".xr-obj-type {\n", " color: var(--xr-font-color2);\n", "}\n", "\n", ".xr-sections {\n", " padding-left: 0 !important;\n", " display: grid;\n", " grid-template-columns: 150px auto auto 1fr 20px 20px;\n", "}\n", "\n", ".xr-section-item {\n", " display: contents;\n", "}\n", "\n", ".xr-section-item input {\n", " display: none;\n", "}\n", "\n", ".xr-section-item input + label {\n", " color: var(--xr-disabled-color);\n", "}\n", "\n", ".xr-section-item input:enabled + label {\n", " cursor: pointer;\n", " color: var(--xr-font-color2);\n", "}\n", "\n", ".xr-section-item input:enabled + label:hover {\n", " color: var(--xr-font-color0);\n", "}\n", "\n", ".xr-section-summary {\n", " grid-column: 1;\n", " color: var(--xr-font-color2);\n", " font-weight: 500;\n", "}\n", "\n", ".xr-section-summary > span {\n", " display: inline-block;\n", " padding-left: 0.5em;\n", "}\n", "\n", ".xr-section-summary-in:disabled + label {\n", " color: var(--xr-font-color2);\n", "}\n", "\n", ".xr-section-summary-in + label:before {\n", " display: inline-block;\n", " content: '►';\n", " font-size: 11px;\n", " width: 15px;\n", " text-align: center;\n", "}\n", "\n", ".xr-section-summary-in:disabled + label:before {\n", " color: var(--xr-disabled-color);\n", "}\n", "\n", ".xr-section-summary-in:checked + label:before {\n", " content: '▼';\n", "}\n", "\n", ".xr-section-summary-in:checked + label > span {\n", " display: none;\n", "}\n", "\n", ".xr-section-summary,\n", ".xr-section-inline-details {\n", " padding-top: 4px;\n", " padding-bottom: 4px;\n", "}\n", "\n", ".xr-section-inline-details {\n", " grid-column: 2 / -1;\n", "}\n", "\n", ".xr-section-details {\n", " display: none;\n", " grid-column: 1 / -1;\n", " margin-bottom: 5px;\n", "}\n", "\n", ".xr-section-summary-in:checked ~ .xr-section-details {\n", " display: contents;\n", "}\n", "\n", ".xr-array-wrap {\n", " grid-column: 1 / -1;\n", " display: grid;\n", " grid-template-columns: 20px auto;\n", "}\n", "\n", ".xr-array-wrap > label {\n", " grid-column: 1;\n", " vertical-align: top;\n", "}\n", "\n", ".xr-preview {\n", " color: var(--xr-font-color3);\n", "}\n", "\n", ".xr-array-preview,\n", ".xr-array-data {\n", " padding: 0 5px !important;\n", " grid-column: 2;\n", "}\n", "\n", ".xr-array-data,\n", ".xr-array-in:checked ~ .xr-array-preview {\n", " display: none;\n", "}\n", "\n", ".xr-array-in:checked ~ .xr-array-data,\n", ".xr-array-preview {\n", " display: inline-block;\n", "}\n", "\n", ".xr-dim-list {\n", " display: inline-block !important;\n", " list-style: none;\n", " padding: 0 !important;\n", " margin: 0;\n", "}\n", "\n", ".xr-dim-list li {\n", " display: inline-block;\n", " padding: 0;\n", " margin: 0;\n", "}\n", "\n", ".xr-dim-list:before {\n", " content: '(';\n", "}\n", "\n", ".xr-dim-list:after {\n", " content: ')';\n", "}\n", "\n", ".xr-dim-list li:not(:last-child):after {\n", " content: ',';\n", " padding-right: 5px;\n", "}\n", "\n", ".xr-has-index {\n", " font-weight: bold;\n", "}\n", "\n", ".xr-var-list,\n", ".xr-var-item {\n", " display: contents;\n", "}\n", "\n", ".xr-var-item > div,\n", ".xr-var-item label,\n", ".xr-var-item > .xr-var-name span {\n", " background-color: var(--xr-background-color-row-even);\n", " margin-bottom: 0;\n", "}\n", "\n", ".xr-var-item > .xr-var-name:hover span {\n", " padding-right: 5px;\n", "}\n", "\n", ".xr-var-list > li:nth-child(odd) > div,\n", ".xr-var-list > li:nth-child(odd) > label,\n", ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n", " background-color: var(--xr-background-color-row-odd);\n", "}\n", "\n", ".xr-var-name {\n", " grid-column: 1;\n", "}\n", "\n", ".xr-var-dims {\n", " grid-column: 2;\n", "}\n", "\n", ".xr-var-dtype {\n", " grid-column: 3;\n", " text-align: right;\n", " color: var(--xr-font-color2);\n", "}\n", "\n", ".xr-var-preview {\n", " grid-column: 4;\n", "}\n", "\n", ".xr-index-preview {\n", " grid-column: 2 / 5;\n", " color: var(--xr-font-color2);\n", "}\n", "\n", ".xr-var-name,\n", ".xr-var-dims,\n", ".xr-var-dtype,\n", ".xr-preview,\n", ".xr-attrs dt {\n", " white-space: nowrap;\n", " overflow: hidden;\n", " text-overflow: ellipsis;\n", " padding-right: 10px;\n", "}\n", "\n", ".xr-var-name:hover,\n", ".xr-var-dims:hover,\n", ".xr-var-dtype:hover,\n", ".xr-attrs dt:hover {\n", " overflow: visible;\n", " width: auto;\n", " z-index: 1;\n", "}\n", "\n", ".xr-var-attrs,\n", ".xr-var-data,\n", ".xr-index-data {\n", " display: none;\n", " background-color: var(--xr-background-color) !important;\n", " padding-bottom: 5px !important;\n", "}\n", "\n", ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n", ".xr-var-data-in:checked ~ .xr-var-data,\n", ".xr-index-data-in:checked ~ .xr-index-data {\n", " display: block;\n", "}\n", "\n", ".xr-var-data > table {\n", " float: right;\n", "}\n", "\n", ".xr-var-name span,\n", ".xr-var-data,\n", ".xr-index-name div,\n", ".xr-index-data,\n", ".xr-attrs {\n", " padding-left: 25px !important;\n", "}\n", "\n", ".xr-attrs,\n", ".xr-var-attrs,\n", ".xr-var-data,\n", ".xr-index-data {\n", " grid-column: 1 / -1;\n", "}\n", "\n", "dl.xr-attrs {\n", " padding: 0;\n", " margin: 0;\n", " display: grid;\n", " grid-template-columns: 125px auto;\n", "}\n", "\n", ".xr-attrs dt,\n", ".xr-attrs dd {\n", " padding: 0;\n", " margin: 0;\n", " float: left;\n", " padding-right: 10px;\n", " width: auto;\n", "}\n", "\n", ".xr-attrs dt {\n", " font-weight: normal;\n", " grid-column: 1;\n", "}\n", "\n", ".xr-attrs dt:hover span {\n", " display: inline-block;\n", " background: var(--xr-background-color);\n", " padding-right: 10px;\n", "}\n", "\n", ".xr-attrs dd {\n", " grid-column: 2;\n", " white-space: pre-wrap;\n", " word-break: break-all;\n", "}\n", "\n", ".xr-icon-database,\n", ".xr-icon-file-text2,\n", ".xr-no-icon {\n", " display: inline-block;\n", " vertical-align: middle;\n", " width: 1em;\n", " height: 1.5em !important;\n", " stroke-width: 0;\n", " stroke: currentColor;\n", " fill: currentColor;\n", "}\n", "</style><pre class='xr-text-repr-fallback'><xarray.DataArray 'CH2' ()>\n", "array(-0.00445586)</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'>'CH2'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-689eacd8-6915-42fc-a8e6-ebb1fe146977' class='xr-array-in' type='checkbox' checked><label for='section-689eacd8-6915-42fc-a8e6-ebb1fe146977' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>-0.004456</span></div><div class='xr-array-data'><pre>array(-0.00445586)</pre></div></div></li><li class='xr-section-item'><input id='section-ee24145a-c632-4796-9062-3cd6744883c8' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ee24145a-c632-4796-9062-3cd6744883c8' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-bafaef9f-98ca-42d5-90a1-f3ca7095ba44' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-bafaef9f-98ca-42d5-90a1-f3ca7095ba44' class='xr-section-summary' title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-0463febf-8d7b-4c80-b7b2-59e1e76ad316' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0463febf-8d7b-4c80-b7b2-59e1e76ad316' 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 'CH2' ()>\n", "array(-0.00445586)" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "data.isel(fileIndex=0, index=slice(0, 590)).CH2.mean()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [ { "data": { "text/html": [ "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n", "<defs>\n", "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n", "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n", "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n", "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n", "</symbol>\n", "<symbol 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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'><xarray.DataArray 'CH2' ()>\n", "array(0.01974533)</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'>'CH2'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-2fe4dbcb-2728-4a3d-b3e8-f4050ae86b85' class='xr-array-in' type='checkbox' checked><label for='section-2fe4dbcb-2728-4a3d-b3e8-f4050ae86b85' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.01975</span></div><div class='xr-array-data'><pre>array(0.01974533)</pre></div></div></li><li class='xr-section-item'><input id='section-b832dbdf-92df-4ae4-ae57-1bfef54b8efd' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b832dbdf-92df-4ae4-ae57-1bfef54b8efd' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-9b7598a6-5297-4a31-9a01-b4b00c2ef4be' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-9b7598a6-5297-4a31-9a01-b4b00c2ef4be' class='xr-section-summary' title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-1ae826d1-1cc4-45df-ace4-ad10ba0161fd' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-1ae826d1-1cc4-45df-ace4-ad10ba0161fd' 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 'CH2' ()>\n", "array(0.01974533)" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "data.isel(fileIndex=0, index=slice(1000, 1190)).CH2.mean() - data.isel(fileIndex=0, index=slice(0, 590)).CH2.mean()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.0519613947368421" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "0.01974533 * 1000 / 10 / 38" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.13463318421052634" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "0.02708149 / 38 *1000/10" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.5484005600526316" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "0.01974533 * 1000 / 10 / 38 * 10.554" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.12" }, "orig_nbformat": 4 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