2220 lines
643 KiB
Plaintext
2220 lines
643 KiB
Plaintext
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{
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"cells": [
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Import supporting package"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import xarray as xr\n",
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"import numpy as np\n",
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"import copy\n",
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"\n",
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"from uncertainties import ufloat\n",
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"from uncertainties import unumpy as unp\n",
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"from uncertainties import umath\n",
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"import random\n",
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"import matplotlib.pyplot as plt\n",
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"plt.rcParams['font.size'] = 12\n",
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"\n",
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"from DataContainer.ReadData import read_hdf5_file\n",
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"from Analyser.ImagingAnalyser import ImageAnalyser\n",
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"from Analyser.FitAnalyser import FitAnalyser\n",
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"from Analyser.FitAnalyser import NewFitModel, DensityProfileBEC2dModel\n",
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"from ToolFunction.ToolFunction import *\n",
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"\n",
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"from scipy.optimize import curve_fit\n",
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"\n",
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"from ToolFunction.HomeMadeXarrayFunction import errorbar, dataarray_plot_errorbar\n",
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"xr.plot.dataarray_plot.errorbar = errorbar\n",
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"xr.plot.accessor.DataArrayPlotAccessor.errorbar = dataarray_plot_errorbar\n",
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"\n",
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"imageAnalyser = ImageAnalyser()\n",
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"\n",
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"# %matplotlib notebook"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Start a client for parallel computing"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"C:\\Users\\data\\AppData\\Roaming\\Python\\Python39\\site-packages\\distributed\\node.py:182: UserWarning: Port 8787 is already in use.\n",
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"Perhaps you already have a cluster running?\n",
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"Hosting the HTTP server on port 64025 instead\n",
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" warnings.warn(\n"
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]
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},
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{
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"data": {
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"text/html": [
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"<div>\n",
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" <div style=\"width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;\"> </div>\n",
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" <div style=\"margin-left: 48px;\">\n",
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" <h3 style=\"margin-bottom: 0px;\">Client</h3>\n",
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" <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Client-62d9ff1a-1663-11ee-a424-80e82ce2fa8e</p>\n",
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" <table style=\"width: 100%; text-align: left;\">\n",
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"\n",
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" <tr>\n",
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" \n",
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" <td style=\"text-align: left;\"><strong>Connection method:</strong> Cluster object</td>\n",
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" <td style=\"text-align: left;\"><strong>Cluster type:</strong> distributed.LocalCluster</td>\n",
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" \n",
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" </tr>\n",
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"\n",
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" \n",
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" <tr>\n",
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" <td style=\"text-align: left;\">\n",
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" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:64025/status\" target=\"_blank\">http://127.0.0.1:64025/status</a>\n",
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" </td>\n",
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" <td style=\"text-align: left;\"></td>\n",
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" </tr>\n",
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" \n",
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"\n",
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" </table>\n",
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"\n",
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" \n",
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"\n",
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" \n",
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" <details>\n",
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" <summary style=\"margin-bottom: 20px;\"><h3 style=\"display: inline;\">Cluster Info</h3></summary>\n",
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" <div class=\"jp-RenderedHTMLCommon jp-RenderedHTML jp-mod-trusted jp-OutputArea-output\">\n",
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" <div style=\"width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;\">\n",
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" </div>\n",
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" <div style=\"margin-left: 48px;\">\n",
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" <h3 style=\"margin-bottom: 0px; margin-top: 0px;\">LocalCluster</h3>\n",
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" <p style=\"color: #9D9D9D; margin-bottom: 0px;\">c9b6fb7f</p>\n",
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" <table style=\"width: 100%; text-align: left;\">\n",
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" <tr>\n",
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" <td style=\"text-align: left;\">\n",
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" <strong>Dashboard:</strong> <a href=\"http://127.0.0.1:64025/status\" target=\"_blank\">http://127.0.0.1:64025/status</a>\n",
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" </td>\n",
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" <td style=\"text-align: left;\">\n",
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" <strong>Workers:</strong> 8\n",
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" </td>\n",
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" </tr>\n",
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" <tr>\n",
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" <td style=\"text-align: left;\">\n",
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" <strong>Total threads:</strong> 128\n",
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" </td>\n",
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" <td style=\"text-align: left;\">\n",
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" <strong>Total memory:</strong> 149.01 GiB\n",
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" </td>\n",
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" </tr>\n",
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" \n",
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" <tr>\n",
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" <td style=\"text-align: left;\"><strong>Status:</strong> running</td>\n",
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" <td style=\"text-align: left;\"><strong>Using processes:</strong> True</td>\n",
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"</tr>\n",
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"\n",
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" \n",
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" </table>\n",
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"\n",
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" <details>\n",
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" <summary style=\"margin-bottom: 20px;\">\n",
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" <h3 style=\"display: inline;\">Scheduler Info</h3>\n",
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" </summary>\n",
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"\n",
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" <div style=\"\">\n",
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" <div>\n",
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" <div style=\"width: 24px; height: 24px; background-color: #FFF7E5; border: 3px solid #FF6132; border-radius: 5px; position: absolute;\"> </div>\n",
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" <div style=\"margin-left: 48px;\">\n",
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" <h3 style=\"margin-bottom: 0px;\">Scheduler</h3>\n",
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" <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Scheduler-aec9e7c3-d306-41ff-adef-79b6d2ae756f</p>\n",
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" <table style=\"width: 100%; text-align: left;\">\n",
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" <tr>\n",
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" <td style=\"text-align: left;\">\n",
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" <strong>Comm:</strong> tcp://127.0.0.1:64028\n",
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" </td>\n",
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" <td style=\"text-align: left;\">\n",
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" <strong>Workers:</strong> 8\n",
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" </td>\n",
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" </tr>\n",
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" <tr>\n",
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" <td style=\"text-align: left;\">\n",
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" <strong>Dashboard:</strong> <a href=\"http://127.0.0.1:64025/status\" target=\"_blank\">http://127.0.0.1:64025/status</a>\n",
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" </td>\n",
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" <td style=\"text-align: left;\">\n",
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" <strong>Total threads:</strong> 128\n",
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" </td>\n",
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" </tr>\n",
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" <tr>\n",
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" <td style=\"text-align: left;\">\n",
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" <strong>Started:</strong> Just now\n",
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" </td>\n",
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" <td style=\"text-align: left;\">\n",
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" <strong>Total memory:</strong> 149.01 GiB\n",
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" </td>\n",
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" </tr>\n",
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" </table>\n",
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" </div>\n",
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" </div>\n",
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"\n",
|
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" <details style=\"margin-left: 48px;\">\n",
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" <summary style=\"margin-bottom: 20px;\">\n",
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" <h3 style=\"display: inline;\">Workers</h3>\n",
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" </summary>\n",
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"\n",
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" \n",
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" <div style=\"margin-bottom: 20px;\">\n",
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" <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
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" <div style=\"margin-left: 48px;\">\n",
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" <details>\n",
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" <summary>\n",
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" <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 0</h4>\n",
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" </summary>\n",
|
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|
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" <table style=\"width: 100%; text-align: left;\">\n",
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" <tr>\n",
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" <td style=\"text-align: left;\">\n",
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" <strong>Comm: </strong> tcp://127.0.0.1:64070\n",
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" </td>\n",
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" <td style=\"text-align: left;\">\n",
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" <strong>Total threads: </strong> 16\n",
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" </td>\n",
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" </tr>\n",
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" <tr>\n",
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" <td style=\"text-align: left;\">\n",
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" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:64073/status\" target=\"_blank\">http://127.0.0.1:64073/status</a>\n",
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" </td>\n",
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" <td style=\"text-align: left;\">\n",
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" <strong>Memory: </strong> 18.63 GiB\n",
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" </td>\n",
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" </tr>\n",
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" <tr>\n",
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" <td style=\"text-align: left;\">\n",
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" <strong>Nanny: </strong> tcp://127.0.0.1:64031\n",
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" </td>\n",
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" <td style=\"text-align: left;\"></td>\n",
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" </tr>\n",
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" <tr>\n",
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" <td colspan=\"2\" style=\"text-align: left;\">\n",
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" <strong>Local directory: </strong> C:\\Users\\data\\AppData\\Local\\Temp\\dask-worker-space\\worker-a5t3uhr6\n",
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" </td>\n",
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" </tr>\n",
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"\n",
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" \n",
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"\n",
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" \n",
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"\n",
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" </table>\n",
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" </details>\n",
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" </div>\n",
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" </div>\n",
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" \n",
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" <div style=\"margin-bottom: 20px;\">\n",
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" <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
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" <div style=\"margin-left: 48px;\">\n",
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" <details>\n",
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" <summary>\n",
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" <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 1</h4>\n",
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" </summary>\n",
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" <table style=\"width: 100%; text-align: left;\">\n",
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" <tr>\n",
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" <td style=\"text-align: left;\">\n",
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" <strong>Comm: </strong> tcp://127.0.0.1:64064\n",
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" </td>\n",
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" <td style=\"text-align: left;\">\n",
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" <strong>Total threads: </strong> 16\n",
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" </td>\n",
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" </tr>\n",
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" <tr>\n",
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" <td style=\"text-align: left;\">\n",
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" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:64067/status\" target=\"_blank\">http://127.0.0.1:64067/status</a>\n",
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" </td>\n",
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" <td style=\"text-align: left;\">\n",
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" <strong>Memory: </strong> 18.63 GiB\n",
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" </td>\n",
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" </tr>\n",
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" <tr>\n",
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" <td style=\"text-align: left;\">\n",
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" <strong>Nanny: </strong> tcp://127.0.0.1:64032\n",
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" </td>\n",
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" <td style=\"text-align: left;\"></td>\n",
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" </tr>\n",
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" <tr>\n",
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" <td colspan=\"2\" style=\"text-align: left;\">\n",
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" <strong>Local directory: </strong> C:\\Users\\data\\AppData\\Local\\Temp\\dask-worker-space\\worker-axcwdu0y\n",
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" </td>\n",
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" </tr>\n",
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"\n",
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" \n",
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"\n",
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" \n",
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"\n",
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" </table>\n",
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" </details>\n",
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" </div>\n",
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" </div>\n",
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" \n",
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" <div style=\"margin-bottom: 20px;\">\n",
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" <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
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" <div style=\"margin-left: 48px;\">\n",
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" <details>\n",
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" <summary>\n",
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" <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 2</h4>\n",
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" </summary>\n",
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" <table style=\"width: 100%; text-align: left;\">\n",
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" <tr>\n",
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" <td style=\"text-align: left;\">\n",
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" <strong>Comm: </strong> tcp://127.0.0.1:64084\n",
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" </td>\n",
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" <td style=\"text-align: left;\">\n",
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" <strong>Total threads: </strong> 16\n",
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" </td>\n",
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" </tr>\n",
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" <tr>\n",
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" <td style=\"text-align: left;\">\n",
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" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:64085/status\" target=\"_blank\">http://127.0.0.1:64085/status</a>\n",
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" </td>\n",
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" <td style=\"text-align: left;\">\n",
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" <strong>Memory: </strong> 18.63 GiB\n",
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" </td>\n",
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" </tr>\n",
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" <tr>\n",
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" <td style=\"text-align: left;\">\n",
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" <strong>Nanny: </strong> tcp://127.0.0.1:64033\n",
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" </td>\n",
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" <td style=\"text-align: left;\"></td>\n",
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" </tr>\n",
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" <tr>\n",
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" <td colspan=\"2\" style=\"text-align: left;\">\n",
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" <strong>Local directory: </strong> C:\\Users\\data\\AppData\\Local\\Temp\\dask-worker-space\\worker-ewtdqzqy\n",
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" </td>\n",
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" </tr>\n",
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"\n",
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" \n",
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"\n",
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" \n",
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"\n",
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" </table>\n",
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||
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" </details>\n",
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" </div>\n",
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" </div>\n",
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" \n",
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" <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://127.0.0.1:64076\n",
|
||
|
|
" </td>\n",
|
||
|
|
" <td style=\"text-align: left;\">\n",
|
||
|
|
" <strong>Total threads: </strong> 16\n",
|
||
|
|
" </td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <td style=\"text-align: left;\">\n",
|
||
|
|
" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:64079/status\" target=\"_blank\">http://127.0.0.1:64079/status</a>\n",
|
||
|
|
" </td>\n",
|
||
|
|
" <td style=\"text-align: left;\">\n",
|
||
|
|
" <strong>Memory: </strong> 18.63 GiB\n",
|
||
|
|
" </td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <td style=\"text-align: left;\">\n",
|
||
|
|
" <strong>Nanny: </strong> tcp://127.0.0.1:64034\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-imeu1_9t\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://127.0.0.1:64075\n",
|
||
|
|
" </td>\n",
|
||
|
|
" <td style=\"text-align: left;\">\n",
|
||
|
|
" <strong>Total threads: </strong> 16\n",
|
||
|
|
" </td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <td style=\"text-align: left;\">\n",
|
||
|
|
" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:64077/status\" target=\"_blank\">http://127.0.0.1:64077/status</a>\n",
|
||
|
|
" </td>\n",
|
||
|
|
" <td style=\"text-align: left;\">\n",
|
||
|
|
" <strong>Memory: </strong> 18.63 GiB\n",
|
||
|
|
" </td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <td style=\"text-align: left;\">\n",
|
||
|
|
" <strong>Nanny: </strong> tcp://127.0.0.1:64035\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-y0dpc96g\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://127.0.0.1:64063\n",
|
||
|
|
" </td>\n",
|
||
|
|
" <td style=\"text-align: left;\">\n",
|
||
|
|
" <strong>Total threads: </strong> 16\n",
|
||
|
|
" </td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <td style=\"text-align: left;\">\n",
|
||
|
|
" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:64065/status\" target=\"_blank\">http://127.0.0.1:64065/status</a>\n",
|
||
|
|
" </td>\n",
|
||
|
|
" <td style=\"text-align: left;\">\n",
|
||
|
|
" <strong>Memory: </strong> 18.63 GiB\n",
|
||
|
|
" </td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <td style=\"text-align: left;\">\n",
|
||
|
|
" <strong>Nanny: </strong> tcp://127.0.0.1:64036\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-hrqxp7t9\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: 6</h4>\n",
|
||
|
|
" </summary>\n",
|
||
|
|
" <table style=\"width: 100%; text-align: left;\">\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <td style=\"text-align: left;\">\n",
|
||
|
|
" <strong>Comm: </strong> tcp://127.0.0.1:64069\n",
|
||
|
|
" </td>\n",
|
||
|
|
" <td style=\"text-align: left;\">\n",
|
||
|
|
" <strong>Total threads: </strong> 16\n",
|
||
|
|
" </td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <td style=\"text-align: left;\">\n",
|
||
|
|
" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:64071/status\" target=\"_blank\">http://127.0.0.1:64071/status</a>\n",
|
||
|
|
" </td>\n",
|
||
|
|
" <td style=\"text-align: left;\">\n",
|
||
|
|
" <strong>Memory: </strong> 18.63 GiB\n",
|
||
|
|
" </td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <td style=\"text-align: left;\">\n",
|
||
|
|
" <strong>Nanny: </strong> tcp://127.0.0.1:64037\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-dv2tpx5b\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: 7</h4>\n",
|
||
|
|
" </summary>\n",
|
||
|
|
" <table style=\"width: 100%; text-align: left;\">\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <td style=\"text-align: left;\">\n",
|
||
|
|
" <strong>Comm: </strong> tcp://127.0.0.1:64081\n",
|
||
|
|
" </td>\n",
|
||
|
|
" <td style=\"text-align: left;\">\n",
|
||
|
|
" <strong>Total threads: </strong> 16\n",
|
||
|
|
" </td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <td style=\"text-align: left;\">\n",
|
||
|
|
" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:64082/status\" target=\"_blank\">http://127.0.0.1:64082/status</a>\n",
|
||
|
|
" </td>\n",
|
||
|
|
" <td style=\"text-align: left;\">\n",
|
||
|
|
" <strong>Memory: </strong> 18.63 GiB\n",
|
||
|
|
" </td>\n",
|
||
|
|
" </tr>\n",
|
||
|
|
" <tr>\n",
|
||
|
|
" <td style=\"text-align: left;\">\n",
|
||
|
|
" <strong>Nanny: </strong> tcp://127.0.0.1:64038\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-e907936d\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://127.0.0.1:64028' processes=8 threads=128, memory=149.01 GiB>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 2,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"from dask.distributed import Client\n",
|
||
|
|
"client = Client(n_workers=8, threads_per_worker=16, processes=True, memory_limit='20GB')\n",
|
||
|
|
"client"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"attachments": {},
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"## Start a client for Mongo DB"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 3,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"import pymongo\n",
|
||
|
|
"import xarray_mongodb\n",
|
||
|
|
"\n",
|
||
|
|
"from DataContainer.MongoDB import MongoDB\n",
|
||
|
|
"\n",
|
||
|
|
"mongoClient = pymongo.MongoClient('mongodb://control:DyLab2021@127.0.0.1:27017/?authMechanism=DEFAULT')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"attachments": {},
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"## Set global path for experiment"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 4,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"groupList = [\n",
|
||
|
|
" \"images/MOT_3D_Camera/in_situ_absorption\",\n",
|
||
|
|
" \"images/ODT_1_Axis_Camera/in_situ_absorption\",\n",
|
||
|
|
" \"images/ODT_2_Axis_Camera/in_situ_absorption\",\n",
|
||
|
|
"]\n",
|
||
|
|
"\n",
|
||
|
|
"dskey = {\n",
|
||
|
|
" \"images/MOT_3D_Camera/in_situ_absorption\": \"camera_0\",\n",
|
||
|
|
" \"images/ODT_1_Axis_Camera/in_situ_absorption\": \"camera_1\",\n",
|
||
|
|
" \"images/ODT_2_Axis_Camera/in_situ_absorption\": \"camera_2\",\n",
|
||
|
|
"}\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 5,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"img_dir = 'C:/Users/control/DyLab/Experiments/DyBEC/'\n",
|
||
|
|
"SequenceName = \"Repetition_scan\"\n",
|
||
|
|
"folderPath = img_dir + SequenceName + \"/\" + get_date()\n",
|
||
|
|
"\n",
|
||
|
|
"mongoDB = mongoClient[SequenceName]\n",
|
||
|
|
"\n",
|
||
|
|
"DB = MongoDB(mongoClient, mongoDB, date=get_date())"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"attachments": {},
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"# Repetition Scans"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"attachments": {},
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"## scan MOT freq"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 6,
|
||
|
|
"metadata": {
|
||
|
|
"scrolled": false
|
||
|
|
},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"The detected scaning axes and values are: \n",
|
||
|
|
"\n",
|
||
|
|
"{'initial_freq': array([102. , 102.25, 102.5 , 102.75, 103. , 103.25, 103.5 , 103.75,\n",
|
||
|
|
" 104. , 104.25, 104.5 , 104.75]), 'runs': array([0., 1., 2.])}\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
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{
|
||
|
|
"data": {
|
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|
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],
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|
"<IPython.core.display.HTML object>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"%matplotlib notebook\n",
|
||
|
|
"shotNum = \"0000\"\n",
|
||
|
|
"filePath = folderPath + \"/\" + shotNum + \"/*.h5\"\n",
|
||
|
|
"\n",
|
||
|
|
"dataSetDict = {\n",
|
||
|
|
" dskey[groupList[i]]: read_hdf5_file(filePath, groupList[i])\n",
|
||
|
|
" for i in range(len(groupList))\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
"dataSet = dataSetDict[\"camera_1\"]\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 = (310, 825)\n",
|
||
|
|
"imageAnalyser.span = (550, 1250)\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 = calculate_mean(Ncount)\n",
|
||
|
|
"Ncount_std = calculate_std(Ncount)\n",
|
||
|
|
"\n",
|
||
|
|
"fig = plt.figure()\n",
|
||
|
|
"ax = fig.gca()\n",
|
||
|
|
"Ncount_mean.plot.errorbar(ax=ax, yerr = Ncount_std, fmt='ob')\n",
|
||
|
|
"plt.xlabel('MOT AOM Freq (MHz)')\n",
|
||
|
|
"plt.ylabel('NCount')\n",
|
||
|
|
"plt.tight_layout()\n",
|
||
|
|
"plt.grid(visible=1)\n",
|
||
|
|
"plt.show()\n",
|
||
|
|
"\n",
|
||
|
|
"# DB.create_global(shotNum, dataSet)\n",
|
||
|
|
"# DB.add_data(shotNum, dataSet_cropOD, engine='xarray')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"dataSet_cropOD.plot.pcolormesh(cmap='jet', vmin=0, vmax=2, col=scanAxis[0], row=scanAxis[1])"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"attachments": {},
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"## scan Push freq"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 7,
|
||
|
|
"metadata": {
|
||
|
|
"scrolled": false
|
||
|
|
},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"The detected scaning axes and values are: \n",
|
||
|
|
"\n",
|
||
|
|
"{'push_freq': array([101.1, 101.6, 102.1, 102.6, 103.1, 103.6, 104.1, 104.6, 105.1,\n",
|
||
|
|
" 105.6, 106.1]), 'runs': array([0., 1., 2.])}\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n if (typeof WebSocket !== 'undefined') {\n return WebSocket;\n } else if (typeof MozWebSocket !== 'undefined') {\n return MozWebSocket;\n } else {\n alert(\n 'Your browser does not have WebSocket support. ' +\n 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n 'Firefox 4 and 5 are also supported but you ' +\n 'have to enable WebSockets in about:config.'\n );\n }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n this.id = figure_id;\n\n this.ws = websocket;\n\n this.supports_binary = this.ws.binaryType !== undefined;\n\n if (!this.supports_binary) {\n var warnings = document.getElementById('mpl-warnings');\n if (warnings) {\n warnings.style.display = 'block';\n warnings.textContent =\n 'This browser does not support binary websocket messages. ' +\n 'Performance may be slow.';\n }\n }\n\n this.imageObj = new Image();\n\n this.context = undefined;\n this.message = undefined;\n this.canvas = undefined;\n this.rubberband_canvas = undefined;\n this.rubberband_context = undefined;\n this.format_dropdown = undefined;\n\n this.image_mode = 'full';\n\n this.root = document.createElement('div');\n this.root.setAttribute('style', 'display: inline-block');\n this._root_extra_style(this.root);\n\n parent_element.appendChild(this.root);\n\n this._init_header(this);\n this._init_canvas(this);\n this._init_toolbar(this);\n\n var fig = this;\n\n this.waiting = false;\n\n this.ws.onopen = function () {\n fig.send_message('supports_binary', { value: fig.supports_binary });\n fig.send_message('send_image_mode', {});\n if (fig.ratio !== 1) {\n fig.send_message('set_device_pixel_ratio', {\n device_pixel_ratio: fig.ratio,\n });\n }\n fig.send_message('refresh', {});\n };\n\n this.imageObj.onload = function () {\n if (fig.image_mode === 'full') {\n // Full images could contain transparency (where diff images\n // almost always do), so we need to clear the canvas so that\n // there is no ghosting.\n fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n }\n fig.context.drawImage(fig.imageObj, 0, 0);\n };\n\n this.imageObj.onunload = function () {\n fig.ws.close();\n };\n\n this.ws.onmessage = this._make_on_message_function(this);\n\n this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n var titlebar = document.createElement('div');\n titlebar.classList =\n 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n var titletext = document.createElement('div');\n titletext.classList = 'ui-dialog-title';\n titletext.setAttribute(\n 'style',\n 'width: 100%; text-align: center; padding: 3px;'\n );\n titlebar.appendChild(titletext);\n this.root.appendChild(titlebar);\n this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n var fig = this;\n\n var canvas_div = (this.canvas_div = document.createElement('div'));\n canvas_div.setAttribute(\n 'style',\n 'border: 1px solid #ddd;' +\n 'box-sizing: content-box;' +\n 'clear: both;' +\n 'min-height: 1px;' +\n 'min-width: 1px;' +\n 'outline: 0;' +\n 'overflow: hidden;' +\n 'position: relative;' +\n 'resize: both;'\n );\n\n function on_keyboard_event_closure(name) {\n return function (event) {\n return fig.key
|
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"data": {
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"text/html": [
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"<img src=\"data:image/png;base64,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
|
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],
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||
|
|
"text/plain": [
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||
|
|
"<IPython.core.display.HTML object>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"%matplotlib notebook\n",
|
||
|
|
"shotNum = \"0001\"\n",
|
||
|
|
"filePath = folderPath + \"/\" + shotNum + \"/*.h5\"\n",
|
||
|
|
"\n",
|
||
|
|
"dataSetDict = {\n",
|
||
|
|
" dskey[groupList[i]]: read_hdf5_file(filePath, groupList[i])\n",
|
||
|
|
" for i in range(len(groupList))\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
"dataSet = dataSetDict[\"camera_1\"]\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 = (310, 825)\n",
|
||
|
|
"imageAnalyser.span = (550, 1250)\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 = calculate_mean(Ncount)\n",
|
||
|
|
"Ncount_std = calculate_std(Ncount)\n",
|
||
|
|
"\n",
|
||
|
|
"fig = plt.figure()\n",
|
||
|
|
"ax = fig.gca()\n",
|
||
|
|
"Ncount_mean.plot.errorbar(ax=ax, yerr = Ncount_std, fmt='ob')\n",
|
||
|
|
"plt.xlabel('Push AOM Freq (MHz)')\n",
|
||
|
|
"plt.ylabel('NCount')\n",
|
||
|
|
"plt.tight_layout()\n",
|
||
|
|
"plt.grid(visible=1)\n",
|
||
|
|
"plt.show()\n",
|
||
|
|
"\n",
|
||
|
|
"# DB.create_global(shotNum, dataSet)\n",
|
||
|
|
"# DB.add_data(shotNum, dataSet_cropOD, engine='xarray')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"attachments": {},
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"## scan Z comp current"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 8,
|
||
|
|
"metadata": {
|
||
|
|
"scrolled": false
|
||
|
|
},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"The detected scaning axes and values are: \n",
|
||
|
|
"\n",
|
||
|
|
"{'compZ_final_current': array([0.248, 0.249, 0.25 , 0.251, 0.252, 0.253, 0.254, 0.255, 0.256,\n",
|
||
|
|
" 0.257, 0.258]), 'runs': array([0., 1., 2.])}\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n if (typeof WebSocket !== 'undefined') {\n return WebSocket;\n } else if (typeof MozWebSocket !== 'undefined') {\n return MozWebSocket;\n } else {\n alert(\n 'Your browser does not have WebSocket support. ' +\n 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n 'Firefox 4 and 5 are also supported but you ' +\n 'have to enable WebSockets in about:config.'\n );\n }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n this.id = figure_id;\n\n this.ws = websocket;\n\n this.supports_binary = this.ws.binaryType !== undefined;\n\n if (!this.supports_binary) {\n var warnings = document.getElementById('mpl-warnings');\n if (warnings) {\n warnings.style.display = 'block';\n warnings.textContent =\n 'This browser does not support binary websocket messages. ' +\n 'Performance may be slow.';\n }\n }\n\n this.imageObj = new Image();\n\n this.context = undefined;\n this.message = undefined;\n this.canvas = undefined;\n this.rubberband_canvas = undefined;\n this.rubberband_context = undefined;\n this.format_dropdown = undefined;\n\n this.image_mode = 'full';\n\n this.root = document.createElement('div');\n this.root.setAttribute('style', 'display: inline-block');\n this._root_extra_style(this.root);\n\n parent_element.appendChild(this.root);\n\n this._init_header(this);\n this._init_canvas(this);\n this._init_toolbar(this);\n\n var fig = this;\n\n this.waiting = false;\n\n this.ws.onopen = function () {\n fig.send_message('supports_binary', { value: fig.supports_binary });\n fig.send_message('send_image_mode', {});\n if (fig.ratio !== 1) {\n fig.send_message('set_device_pixel_ratio', {\n device_pixel_ratio: fig.ratio,\n });\n }\n fig.send_message('refresh', {});\n };\n\n this.imageObj.onload = function () {\n if (fig.image_mode === 'full') {\n // Full images could contain transparency (where diff images\n // almost always do), so we need to clear the canvas so that\n // there is no ghosting.\n fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n }\n fig.context.drawImage(fig.imageObj, 0, 0);\n };\n\n this.imageObj.onunload = function () {\n fig.ws.close();\n };\n\n this.ws.onmessage = this._make_on_message_function(this);\n\n this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n var titlebar = document.createElement('div');\n titlebar.classList =\n 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n var titletext = document.createElement('div');\n titletext.classList = 'ui-dialog-title';\n titletext.setAttribute(\n 'style',\n 'width: 100%; text-align: center; padding: 3px;'\n );\n titlebar.appendChild(titletext);\n this.root.appendChild(titlebar);\n this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n var fig = this;\n\n var canvas_div = (this.canvas_div = document.createElement('div'));\n canvas_div.setAttribute(\n 'style',\n 'border: 1px solid #ddd;' +\n 'box-sizing: content-box;' +\n 'clear: both;' +\n 'min-height: 1px;' +\n 'min-width: 1px;' +\n 'outline: 0;' +\n 'overflow: hidden;' +\n 'position: relative;' +\n 'resize: both;'\n );\n\n function on_keyboard_event_closure(name) {\n return function (event) {\n return fig.key
|
||
|
|
"text/plain": [
|
||
|
|
"<IPython.core.display.Javascript object>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/html": [
|
||
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"<img src=\"data:image/png;base64,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
|
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|
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],
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|
"text/plain": [
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||
|
|
"<IPython.core.display.HTML object>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"%matplotlib notebook\n",
|
||
|
|
"shotNum = \"0002\"\n",
|
||
|
|
"filePath = folderPath + \"/\" + shotNum + \"/*.h5\"\n",
|
||
|
|
"\n",
|
||
|
|
"dataSetDict = {\n",
|
||
|
|
" dskey[groupList[i]]: read_hdf5_file(filePath, groupList[i])\n",
|
||
|
|
" for i in range(len(groupList))\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
"dataSet = dataSetDict[\"camera_1\"]\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 = (305, 870)\n",
|
||
|
|
"imageAnalyser.span = (400, 400)\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 = calculate_mean(Ncount)\n",
|
||
|
|
"Ncount_std = calculate_std(Ncount)\n",
|
||
|
|
"\n",
|
||
|
|
"fig = plt.figure()\n",
|
||
|
|
"ax = fig.gca()\n",
|
||
|
|
"Ncount_mean.plot.errorbar(ax=ax, yerr = Ncount_std, fmt='ob')\n",
|
||
|
|
"plt.xlabel('comp Z current (A)')\n",
|
||
|
|
"plt.ylabel('NCount')\n",
|
||
|
|
"plt.tight_layout()\n",
|
||
|
|
"plt.grid(visible=1)\n",
|
||
|
|
"plt.show()\n",
|
||
|
|
"\n",
|
||
|
|
"# DB.create_global(shotNum, dataSet)\n",
|
||
|
|
"# DB.add_data(shotNum, dataSet_cropOD, engine='xarray')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"attachments": {},
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"## scan cMOT final amp"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 9,
|
||
|
|
"metadata": {
|
||
|
|
"scrolled": false
|
||
|
|
},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"The detected scaning axes and values are: \n",
|
||
|
|
"\n",
|
||
|
|
"{'final_amp': array([3.00e-05, 5.50e-05, 8.00e-05, 1.05e-04, 1.30e-04, 1.55e-04,\n",
|
||
|
|
" 1.80e-04, 2.05e-04, 2.30e-04, 2.55e-04, 2.80e-04]), 'runs': array([0., 1., 2.])}\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n if (typeof WebSocket !== 'undefined') {\n return WebSocket;\n } else if (typeof MozWebSocket !== 'undefined') {\n return MozWebSocket;\n } else {\n alert(\n 'Your browser does not have WebSocket support. ' +\n 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n 'Firefox 4 and 5 are also supported but you ' +\n 'have to enable WebSockets in about:config.'\n );\n }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n this.id = figure_id;\n\n this.ws = websocket;\n\n this.supports_binary = this.ws.binaryType !== undefined;\n\n if (!this.supports_binary) {\n var warnings = document.getElementById('mpl-warnings');\n if (warnings) {\n warnings.style.display = 'block';\n warnings.textContent =\n 'This browser does not support binary websocket messages. ' +\n 'Performance may be slow.';\n }\n }\n\n this.imageObj = new Image();\n\n this.context = undefined;\n this.message = undefined;\n this.canvas = undefined;\n this.rubberband_canvas = undefined;\n this.rubberband_context = undefined;\n this.format_dropdown = undefined;\n\n this.image_mode = 'full';\n\n this.root = document.createElement('div');\n this.root.setAttribute('style', 'display: inline-block');\n this._root_extra_style(this.root);\n\n parent_element.appendChild(this.root);\n\n this._init_header(this);\n this._init_canvas(this);\n this._init_toolbar(this);\n\n var fig = this;\n\n this.waiting = false;\n\n this.ws.onopen = function () {\n fig.send_message('supports_binary', { value: fig.supports_binary });\n fig.send_message('send_image_mode', {});\n if (fig.ratio !== 1) {\n fig.send_message('set_device_pixel_ratio', {\n device_pixel_ratio: fig.ratio,\n });\n }\n fig.send_message('refresh', {});\n };\n\n this.imageObj.onload = function () {\n if (fig.image_mode === 'full') {\n // Full images could contain transparency (where diff images\n // almost always do), so we need to clear the canvas so that\n // there is no ghosting.\n fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n }\n fig.context.drawImage(fig.imageObj, 0, 0);\n };\n\n this.imageObj.onunload = function () {\n fig.ws.close();\n };\n\n this.ws.onmessage = this._make_on_message_function(this);\n\n this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n var titlebar = document.createElement('div');\n titlebar.classList =\n 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n var titletext = document.createElement('div');\n titletext.classList = 'ui-dialog-title';\n titletext.setAttribute(\n 'style',\n 'width: 100%; text-align: center; padding: 3px;'\n );\n titlebar.appendChild(titletext);\n this.root.appendChild(titlebar);\n this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n var fig = this;\n\n var canvas_div = (this.canvas_div = document.createElement('div'));\n canvas_div.setAttribute(\n 'style',\n 'border: 1px solid #ddd;' +\n 'box-sizing: content-box;' +\n 'clear: both;' +\n 'min-height: 1px;' +\n 'min-width: 1px;' +\n 'outline: 0;' +\n 'overflow: hidden;' +\n 'position: relative;' +\n 'resize: both;'\n );\n\n function on_keyboard_event_closure(name) {\n return function (event) {\n return fig.key
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||
|
|
"text/plain": [
|
||
|
|
"<IPython.core.display.Javascript object>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/html": [
|
||
|
|
"<img src=\"data:image/png;base64,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
|
||
|
|
],
|
||
|
|
"text/plain": [
|
||
|
|
"<IPython.core.display.HTML object>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"%matplotlib notebook\n",
|
||
|
|
"shotNum = \"0003\"\n",
|
||
|
|
"filePath = folderPath + \"/\" + shotNum + \"/*.h5\"\n",
|
||
|
|
"\n",
|
||
|
|
"dataSetDict = {\n",
|
||
|
|
" dskey[groupList[i]]: read_hdf5_file(filePath, groupList[i])\n",
|
||
|
|
" for i in range(len(groupList))\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
"dataSet = dataSetDict[\"camera_1\"]\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 = (306, 872)\n",
|
||
|
|
"imageAnalyser.span = (400, 400)\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 = calculate_mean(Ncount)\n",
|
||
|
|
"Ncount_std = calculate_std(Ncount)\n",
|
||
|
|
"\n",
|
||
|
|
"fig = plt.figure()\n",
|
||
|
|
"ax = fig.gca()\n",
|
||
|
|
"Ncount_mean.plot.errorbar(ax=ax, yerr = Ncount_std, fmt='ob')\n",
|
||
|
|
"#plt.xlabel('comp Z current (A)')\n",
|
||
|
|
"plt.ylabel('NCount')\n",
|
||
|
|
"plt.tight_layout()\n",
|
||
|
|
"plt.grid(visible=1)\n",
|
||
|
|
"plt.show()\n",
|
||
|
|
"\n",
|
||
|
|
"# DB.create_global(shotNum, dataSet)\n",
|
||
|
|
"# DB.add_data(shotNum, dataSet_cropOD, engine='xarray')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"attachments": {},
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"# Evaporative Cooling"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 6,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"img_dir = '//DyLabNAS/Data/'\n",
|
||
|
|
"SequenceName = \"Evaporative_Cooling\" + \"/\"\n",
|
||
|
|
"folderPath = img_dir + SequenceName + '2023/06/29'# get_date()\n",
|
||
|
|
"\n",
|
||
|
|
"# mongoDB = mongoClient[SequenceName]\n",
|
||
|
|
"\n",
|
||
|
|
"# DB = MongoDB(mongoClient, mongoDB, date=get_date())"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"attachments": {},
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"# Check BEC"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 22,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"The detected scaning axes and values are: \n",
|
||
|
|
"\n",
|
||
|
|
"{'runs': array([0., 1., 2., 3., 4., 5., 6., 7., 8., 9.])}\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 640x480 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"shotNum = \"0002\"\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 = (880, 980)\n",
|
||
|
|
"imageAnalyser.span = (80, 80)\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#calculate_mean(Ncount)\n",
|
||
|
|
"Ncount_std = None#calculate_std(Ncount)\n",
|
||
|
|
"\n",
|
||
|
|
"fig = plt.figure()\n",
|
||
|
|
"ax = fig.gca()\n",
|
||
|
|
"Ncount_mean.plot.errorbar(ax=ax, yerr = None, fmt='-ob')\n",
|
||
|
|
"plt.xlabel('comp Z current (A)')\n",
|
||
|
|
"plt.ylabel('NCount')\n",
|
||
|
|
"plt.tight_layout()\n",
|
||
|
|
"plt.grid(visible=1)\n",
|
||
|
|
"plt.show()\n",
|
||
|
|
"\n",
|
||
|
|
"# DB.create_global(shotNum, dataSet)\n",
|
||
|
|
"# DB.add_data(shotNum, dataSet_cropOD, engine='xarray')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 23,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"<xarray.plot.facetgrid.FacetGrid at 0x2821278a490>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 23,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 3100x300 with 11 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"dataSet_cropOD.plot.pcolormesh(cmap='jet', vmin=0, vmax=5, col=scanAxis[0])"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 27,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"data = dataSet_cropOD#.sel(runs = 0)\n",
|
||
|
|
"\n",
|
||
|
|
"fitModel = DensityProfileBEC2dModel()\n",
|
||
|
|
"fitAnalyser_1 = FitAnalyser(fitModel, fitDim=2)\n",
|
||
|
|
"\n",
|
||
|
|
"params = fitAnalyser_1.guess(data, dask=\"parallelized\", guess_kwargs=dict(pureBECThreshold=1.2))\n",
|
||
|
|
"\n",
|
||
|
|
"fitResult_1 = fitAnalyser_1.fit(data, params).load()\n",
|
||
|
|
"\n",
|
||
|
|
"# fitCurve = fitAnalyser.eval(fitResult, x=np.range(150), y=np.range(150), dask=\"parallelized\").load()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 28,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/html": [
|
||
|
|
"<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
|
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|
|
"<defs>\n",
|
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|
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"<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
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|
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"<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",
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"<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",
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"<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",
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|
"</symbol>\n",
|
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"<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
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"<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 1h7v19.5z\"></path>\n",
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"<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
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"<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
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"<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
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|
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"</symbol>\n",
|
||
|
|
"</defs>\n",
|
||
|
|
"</svg>\n",
|
||
|
|
"<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
|
||
|
|
" *\n",
|
||
|
|
" */\n",
|
||
|
|
"\n",
|
||
|
|
":root {\n",
|
||
|
|
" --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
|
||
|
|
" --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
|
||
|
|
" --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
|
||
|
|
" --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
|
||
|
|
" --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
|
||
|
|
" --xr-background-color: var(--jp-layout-color0, white);\n",
|
||
|
|
" --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
|
||
|
|
" --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
"html[theme=dark],\n",
|
||
|
|
"body[data-theme=dark],\n",
|
||
|
|
"body.vscode-dark {\n",
|
||
|
|
" --xr-font-color0: rgba(255, 255, 255, 1);\n",
|
||
|
|
" --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
|
||
|
|
" --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
|
||
|
|
" --xr-border-color: #1F1F1F;\n",
|
||
|
|
" --xr-disabled-color: #515151;\n",
|
||
|
|
" --xr-background-color: #111111;\n",
|
||
|
|
" --xr-background-color-row-even: #111111;\n",
|
||
|
|
" --xr-background-color-row-odd: #313131;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-wrap {\n",
|
||
|
|
" display: block !important;\n",
|
||
|
|
" min-width: 300px;\n",
|
||
|
|
" max-width: 700px;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-text-repr-fallback {\n",
|
||
|
|
" /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
|
||
|
|
" display: none;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-header {\n",
|
||
|
|
" padding-top: 6px;\n",
|
||
|
|
" padding-bottom: 6px;\n",
|
||
|
|
" margin-bottom: 4px;\n",
|
||
|
|
" border-bottom: solid 1px var(--xr-border-color);\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-header > div,\n",
|
||
|
|
".xr-header > ul {\n",
|
||
|
|
" display: inline;\n",
|
||
|
|
" margin-top: 0;\n",
|
||
|
|
" margin-bottom: 0;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-obj-type,\n",
|
||
|
|
".xr-array-name {\n",
|
||
|
|
" margin-left: 2px;\n",
|
||
|
|
" margin-right: 10px;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-obj-type {\n",
|
||
|
|
" color: var(--xr-font-color2);\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-sections {\n",
|
||
|
|
" padding-left: 0 !important;\n",
|
||
|
|
" display: grid;\n",
|
||
|
|
" grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-section-item {\n",
|
||
|
|
" display: contents;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-section-item input {\n",
|
||
|
|
" display: none;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-section-item input + label {\n",
|
||
|
|
" color: var(--xr-disabled-color);\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-section-item input:enabled + label {\n",
|
||
|
|
" cursor: pointer;\n",
|
||
|
|
" color: var(--xr-font-color2);\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-section-item input:enabled + label:hover {\n",
|
||
|
|
" color: var(--xr-font-color0);\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-section-summary {\n",
|
||
|
|
" grid-column: 1;\n",
|
||
|
|
" color: var(--xr-font-color2);\n",
|
||
|
|
" font-weight: 500;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-section-summary > span {\n",
|
||
|
|
" display: inline-block;\n",
|
||
|
|
" padding-left: 0.5em;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-section-summary-in:disabled + label {\n",
|
||
|
|
" color: var(--xr-font-color2);\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-section-summary-in + label:before {\n",
|
||
|
|
" display: inline-block;\n",
|
||
|
|
" content: 'â–º';\n",
|
||
|
|
" font-size: 11px;\n",
|
||
|
|
" width: 15px;\n",
|
||
|
|
" text-align: center;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-section-summary-in:disabled + label:before {\n",
|
||
|
|
" color: var(--xr-disabled-color);\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-section-summary-in:checked + label:before {\n",
|
||
|
|
" content: 'â–¼';\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-section-summary-in:checked + label > span {\n",
|
||
|
|
" display: none;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-section-summary,\n",
|
||
|
|
".xr-section-inline-details {\n",
|
||
|
|
" padding-top: 4px;\n",
|
||
|
|
" padding-bottom: 4px;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-section-inline-details {\n",
|
||
|
|
" grid-column: 2 / -1;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-section-details {\n",
|
||
|
|
" display: none;\n",
|
||
|
|
" grid-column: 1 / -1;\n",
|
||
|
|
" margin-bottom: 5px;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-section-summary-in:checked ~ .xr-section-details {\n",
|
||
|
|
" display: contents;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-array-wrap {\n",
|
||
|
|
" grid-column: 1 / -1;\n",
|
||
|
|
" display: grid;\n",
|
||
|
|
" grid-template-columns: 20px auto;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-array-wrap > label {\n",
|
||
|
|
" grid-column: 1;\n",
|
||
|
|
" vertical-align: top;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-preview {\n",
|
||
|
|
" color: var(--xr-font-color3);\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-array-preview,\n",
|
||
|
|
".xr-array-data {\n",
|
||
|
|
" padding: 0 5px !important;\n",
|
||
|
|
" grid-column: 2;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-array-data,\n",
|
||
|
|
".xr-array-in:checked ~ .xr-array-preview {\n",
|
||
|
|
" display: none;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-array-in:checked ~ .xr-array-data,\n",
|
||
|
|
".xr-array-preview {\n",
|
||
|
|
" display: inline-block;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-dim-list {\n",
|
||
|
|
" display: inline-block !important;\n",
|
||
|
|
" list-style: none;\n",
|
||
|
|
" padding: 0 !important;\n",
|
||
|
|
" margin: 0;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-dim-list li {\n",
|
||
|
|
" display: inline-block;\n",
|
||
|
|
" padding: 0;\n",
|
||
|
|
" margin: 0;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-dim-list:before {\n",
|
||
|
|
" content: '(';\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-dim-list:after {\n",
|
||
|
|
" content: ')';\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-dim-list li:not(:last-child):after {\n",
|
||
|
|
" content: ',';\n",
|
||
|
|
" padding-right: 5px;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-has-index {\n",
|
||
|
|
" font-weight: bold;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-var-list,\n",
|
||
|
|
".xr-var-item {\n",
|
||
|
|
" display: contents;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-var-item > div,\n",
|
||
|
|
".xr-var-item label,\n",
|
||
|
|
".xr-var-item > .xr-var-name span {\n",
|
||
|
|
" background-color: var(--xr-background-color-row-even);\n",
|
||
|
|
" margin-bottom: 0;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-var-item > .xr-var-name:hover span {\n",
|
||
|
|
" padding-right: 5px;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-var-list > li:nth-child(odd) > div,\n",
|
||
|
|
".xr-var-list > li:nth-child(odd) > label,\n",
|
||
|
|
".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
|
||
|
|
" background-color: var(--xr-background-color-row-odd);\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-var-name {\n",
|
||
|
|
" grid-column: 1;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-var-dims {\n",
|
||
|
|
" grid-column: 2;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-var-dtype {\n",
|
||
|
|
" grid-column: 3;\n",
|
||
|
|
" text-align: right;\n",
|
||
|
|
" color: var(--xr-font-color2);\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-var-preview {\n",
|
||
|
|
" grid-column: 4;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-index-preview {\n",
|
||
|
|
" grid-column: 2 / 5;\n",
|
||
|
|
" color: var(--xr-font-color2);\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-var-name,\n",
|
||
|
|
".xr-var-dims,\n",
|
||
|
|
".xr-var-dtype,\n",
|
||
|
|
".xr-preview,\n",
|
||
|
|
".xr-attrs dt {\n",
|
||
|
|
" white-space: nowrap;\n",
|
||
|
|
" overflow: hidden;\n",
|
||
|
|
" text-overflow: ellipsis;\n",
|
||
|
|
" padding-right: 10px;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-var-name:hover,\n",
|
||
|
|
".xr-var-dims:hover,\n",
|
||
|
|
".xr-var-dtype:hover,\n",
|
||
|
|
".xr-attrs dt:hover {\n",
|
||
|
|
" overflow: visible;\n",
|
||
|
|
" width: auto;\n",
|
||
|
|
" z-index: 1;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-var-attrs,\n",
|
||
|
|
".xr-var-data,\n",
|
||
|
|
".xr-index-data {\n",
|
||
|
|
" display: none;\n",
|
||
|
|
" background-color: var(--xr-background-color) !important;\n",
|
||
|
|
" padding-bottom: 5px !important;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
|
||
|
|
".xr-var-data-in:checked ~ .xr-var-data,\n",
|
||
|
|
".xr-index-data-in:checked ~ .xr-index-data {\n",
|
||
|
|
" display: block;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-var-data > table {\n",
|
||
|
|
" float: right;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-var-name span,\n",
|
||
|
|
".xr-var-data,\n",
|
||
|
|
".xr-index-name div,\n",
|
||
|
|
".xr-index-data,\n",
|
||
|
|
".xr-attrs {\n",
|
||
|
|
" padding-left: 25px !important;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-attrs,\n",
|
||
|
|
".xr-var-attrs,\n",
|
||
|
|
".xr-var-data,\n",
|
||
|
|
".xr-index-data {\n",
|
||
|
|
" grid-column: 1 / -1;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
"dl.xr-attrs {\n",
|
||
|
|
" padding: 0;\n",
|
||
|
|
" margin: 0;\n",
|
||
|
|
" display: grid;\n",
|
||
|
|
" grid-template-columns: 125px auto;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-attrs dt,\n",
|
||
|
|
".xr-attrs dd {\n",
|
||
|
|
" padding: 0;\n",
|
||
|
|
" margin: 0;\n",
|
||
|
|
" float: left;\n",
|
||
|
|
" padding-right: 10px;\n",
|
||
|
|
" width: auto;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-attrs dt {\n",
|
||
|
|
" font-weight: normal;\n",
|
||
|
|
" grid-column: 1;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-attrs dt:hover span {\n",
|
||
|
|
" display: inline-block;\n",
|
||
|
|
" background: var(--xr-background-color);\n",
|
||
|
|
" padding-right: 10px;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-attrs dd {\n",
|
||
|
|
" grid-column: 2;\n",
|
||
|
|
" white-space: pre-wrap;\n",
|
||
|
|
" word-break: break-all;\n",
|
||
|
|
"}\n",
|
||
|
|
"\n",
|
||
|
|
".xr-icon-database,\n",
|
||
|
|
".xr-icon-file-text2,\n",
|
||
|
|
".xr-no-icon {\n",
|
||
|
|
" display: inline-block;\n",
|
||
|
|
" vertical-align: middle;\n",
|
||
|
|
" width: 1em;\n",
|
||
|
|
" height: 1.5em !important;\n",
|
||
|
|
" stroke-width: 0;\n",
|
||
|
|
" stroke: currentColor;\n",
|
||
|
|
" fill: currentColor;\n",
|
||
|
|
"}\n",
|
||
|
|
"</style><pre class='xr-text-repr-fallback'><xarray.Dataset>\n",
|
||
|
|
"Dimensions: (runs: 10)\n",
|
||
|
|
"Coordinates:\n",
|
||
|
|
" * runs (runs) float64 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0\n",
|
||
|
|
"Data variables: (12/13)\n",
|
||
|
|
" BEC_amplitude (runs) object 622.325100923668+/-nan ... 622.4907683...\n",
|
||
|
|
" thermal_amplitude (runs) object 574.323330298593+/-nan ... 562.0410431...\n",
|
||
|
|
" BEC_centerx (runs) object 40.697673212791095+/-nan ... 41.846469...\n",
|
||
|
|
" BEC_centery (runs) object 38.68619529315486+/-nan ... 40.1657973...\n",
|
||
|
|
" thermal_centerx (runs) object 41.672856011589964+/-nan ... 42.186994...\n",
|
||
|
|
" thermal_centery (runs) object 40.50023901378942+/-nan ... 41.8611854...\n",
|
||
|
|
" ... ...\n",
|
||
|
|
" BEC_sigmay (runs) object 9.925094420566738+/-nan ... 9.27924633...\n",
|
||
|
|
" thermal_sigmax (runs) object 15.219058592618353+/-nan ... 14.193823...\n",
|
||
|
|
" thermal_sigmay (runs) object 18.262870311142024+/-nan ... 17.032587...\n",
|
||
|
|
" deltax (runs) object 18.54999801825887+/-nan ... 15.3119583...\n",
|
||
|
|
" thermalAspectRatio (runs) object 1.2+/-nan 1.2+/-nan ... 1.2+/-nan\n",
|
||
|
|
" condensate_fraction (runs) object 0.5200567557574306+/-nan ... 0.5255162...\n",
|
||
|
|
"Attributes:\n",
|
||
|
|
" IMAGE_SUBCLASS: IMAGE_GRAYSCALE\n",
|
||
|
|
" IMAGE_VERSION: 1.2\n",
|
||
|
|
" IMAGE_WHITE_IS_ZERO: 0\n",
|
||
|
|
" x_start: 840\n",
|
||
|
|
" x_end: 920\n",
|
||
|
|
" y_end: 1020\n",
|
||
|
|
" y_start: 940\n",
|
||
|
|
" x_center: 880\n",
|
||
|
|
" y_center: 980\n",
|
||
|
|
" x_span: 80\n",
|
||
|
|
" y_span: 80</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-60c42fd0-1a85-4919-aa1c-bfb084af74a7' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-60c42fd0-1a85-4919-aa1c-bfb084af74a7' 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>: 10</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-dfa28b62-a15c-4172-838f-098c85289f06' class='xr-section-summary-in' type='checkbox' checked><label for='section-dfa28b62-a15c-4172-838f-098c85289f06' 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 ... 6.0 7.0 8.0 9.0</div><input id='attrs-e6821b36-8258-4c1c-9141-12274eebcbe3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e6821b36-8258-4c1c-9141-12274eebcbe3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-42cb0531-1f9a-4356-b7af-d199d488e654' class='xr-var-data-in' type='checkbox'><label for='data-42cb0531-1f9a-4356-b7af-d199d488e654' 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.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0123b3c4-de0d-45ad-98f2-f83d620f53de' class='xr-section-summary-in' type='checkbox' checked><label for='section-0123b3c4-de0d-45ad-98f2-f83d620f53de' class='xr-section-summary' >Data variables: <span>(13)</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'>622.325100923668+/-nan ... 622.4...</div><input id='attrs-8c78ceea-4cd7-4c4d-ba36-89f2863c3371' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8c78ceea-4cd7-4c4d-ba36-89f2863c3371' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-300ecd0d-3710-4646-8b23-417eafa347e6' class='xr-var-data-in' type='checkbox'><label for='data-300ecd0d-3710-4646-8b23-417eafa347e6' 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([622.325100923668+/-nan, 565.810960428506+/-nan,\n",
|
||
|
|
" 580.1085845591986+/-nan, 636.5250359081975+/-nan,\n",
|
||
|
|
" 600.2141025258858+/-nan, 577.2958286890241+/-nan,\n",
|
||
|
|
" 627.3808268148166+/-nan, 617.2187811344919+/-nan,\n",
|
||
|
|
" 641.2607989957359+/-nan, 622.4907683665502+/-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'>574.323330298593+/-nan ... 562.0...</div><input id='attrs-80a14f33-5cf0-4c13-9c0a-7576c6f3d980' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-80a14f33-5cf0-4c13-9c0a-7576c6f3d980' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-07353150-bab9-408e-bd57-bf3dc30b3157' class='xr-var-data-in' type='checkbox'><label for='data-07353150-bab9-408e-bd57-bf3dc30b3157' 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([574.323330298593+/-nan, 568.4626463236162+/-nan,\n",
|
||
|
|
" 583.7522671412466+/-nan, 520.5663944276968+/-nan,\n",
|
||
|
|
" 629.6233172781357+/-nan, 617.2121947211904+/-nan,\n",
|
||
|
|
" 602.967628810155+/-nan, 562.4835962828049+/-nan,\n",
|
||
|
|
" 604.8087834130785+/-nan, 562.0410431412295+/-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'>40.697673212791095+/-nan ... 41....</div><input id='attrs-b16c5c85-3efc-44ed-975a-7c700a2e5688' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b16c5c85-3efc-44ed-975a-7c700a2e5688' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0729c6f4-263c-403b-a41f-a4ce1ee63511' class='xr-var-data-in' type='checkbox'><label for='data-0729c6f4-263c-403b-a41f-a4ce1ee63511' 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([40.697673212791095+/-nan, 39.45883091234254+/-nan,\n",
|
||
|
|
" 41.22347787951619+/-nan, 40.89898530220542+/-nan,\n",
|
||
|
|
" 41.63210069803921+/-nan, 39.324681218279466+/-nan,\n",
|
||
|
|
" 38.275787736341755+/-nan, 39.60209353554154+/-nan,\n",
|
||
|
|
" 42.00470746236811+/-nan, 41.846469101560324+/-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'>38.68619529315486+/-nan ... 40.1...</div><input id='attrs-437dd93f-05d7-4298-92f4-44d43fa3b773' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-437dd93f-05d7-4298-92f4-44d43fa3b773' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-97a4586b-0749-4e60-b91b-6c4de93e6359' class='xr-var-data-in' type='checkbox'><label for='data-97a4586b-0749-4e60-b91b-6c4de93e6359' 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([38.68619529315486+/-nan, 42.61360351211025+/-nan,\n",
|
||
|
|
" 41.563561921615275+/-nan, 40.06131528825722+/-nan,\n",
|
||
|
|
" 43.90475816622681+/-nan, 44.50753547226045+/-nan,\n",
|
||
|
|
" 43.14256883489733+/-nan, 41.82261283543652+/-nan,\n",
|
||
|
|
" 41.53493261128381+/-nan, 40.165797300781946+/-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'>41.672856011589964+/-nan ... 42....</div><input id='attrs-07aeb4e6-91df-4d08-87d7-459104e1eba5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-07aeb4e6-91df-4d08-87d7-459104e1eba5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5f70a575-c0f1-4498-9777-7eba43808c0c' class='xr-var-data-in' type='checkbox'><label for='data-5f70a575-c0f1-4498-9777-7eba43808c0c' 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([41.672856011589964+/-nan, 41.10729207485836+/-nan,\n",
|
||
|
|
" 42.74513908785217+/-nan, 41.541130169383074+/-nan,\n",
|
||
|
|
" 41.44245089494752+/-nan, 40.150975380806294+/-nan,\n",
|
||
|
|
" 40.2004632958644+/-nan, 41.44977519532488+/-nan,\n",
|
||
|
|
" 42.69309201162166+/-nan, 42.18699416012472+/-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'>40.50023901378942+/-nan ... 41.8...</div><input id='attrs-88335c7f-0add-4a64-939d-704c48fe4979' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-88335c7f-0add-4a64-939d-704c48fe4979' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6f4c67a4-fa1c-4263-90df-7bd0431b4216' class='xr-var-data-in' type='checkbox'><label for='data-6f4c67a4-fa1c-4263-90df-7bd0431b4216' 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([40.50023901378942+/-nan, 44.81057142219622+/-nan,\n",
|
||
|
|
" 43.010161191179634+/-nan, 41.36490168879652+/-nan,\n",
|
||
|
|
" 45.17646234836704+/-nan, 45.95553486593841+/-nan,\n",
|
||
|
|
" 44.574513165193316+/-nan, 43.26958231838+/-nan,\n",
|
||
|
|
" 42.5998739671102+/-nan, 41.86118542627792+/-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'>27.10717775959619+/-nan ... 27.2...</div><input id='attrs-4a1c6250-a107-4a59-aed4-cb370052078a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4a1c6250-a107-4a59-aed4-cb370052078a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1ee2b534-748c-4346-8ee5-528c67591da0' class='xr-var-data-in' type='checkbox'><label for='data-1ee2b534-748c-4346-8ee5-528c67591da0' 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([27.10717775959619+/-nan, 27.813248412756067+/-nan,\n",
|
||
|
|
" 27.180460059842797+/-nan, 28.359108484779306+/-nan,\n",
|
||
|
|
" 27.12902681300635+/-nan, 27.786783488553446+/-nan,\n",
|
||
|
|
" 27.56817106112974+/-nan, 28.162503921088394+/-nan,\n",
|
||
|
|
" 27.38249247770765+/-nan, 27.269511683790224+/-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'>9.925094420566738+/-nan ... 9.27...</div><input id='attrs-7ed7bedc-4010-4cfd-931e-10f017eecf44' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7ed7bedc-4010-4cfd-931e-10f017eecf44' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7d439e7e-f79d-4468-be0f-d8e065206781' class='xr-var-data-in' type='checkbox'><label for='data-7d439e7e-f79d-4468-be0f-d8e065206781' 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([9.925094420566738+/-nan, 8.320083964510589+/-nan,\n",
|
||
|
|
" 8.832237277118526+/-nan, 10.102464552278184+/-nan,\n",
|
||
|
|
" 8.87861409804287+/-nan, 8.215669300544008+/-nan,\n",
|
||
|
|
" 8.96268636585824+/-nan, 8.690636986312713+/-nan,\n",
|
||
|
|
" 9.739827034241756+/-nan, 9.279246332574647+/-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'>15.219058592618353+/-nan ... 14....</div><input id='attrs-56d1bd43-6cdc-4920-b6c7-1fdd6dd2d566' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-56d1bd43-6cdc-4920-b6c7-1fdd6dd2d566' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-060a01be-af83-46f3-bd5e-d170d23f33c1' class='xr-var-data-in' type='checkbox'><label for='data-060a01be-af83-46f3-bd5e-d170d23f33c1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([15.219058592618353+/-nan, 13.845036738454665+/-nan,\n",
|
||
|
|
" 14.10887047132501+/-nan, 13.982332369691441+/-nan,\n",
|
||
|
|
" 14.817239722846576+/-nan, 13.924008993096628+/-nan,\n",
|
||
|
|
" 14.06259374875233+/-nan, 13.970679478445314+/-nan,\n",
|
||
|
|
" 14.551516131029505+/-nan, 14.193823332828861+/-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'>18.262870311142024+/-nan ... 17....</div><input id='attrs-23e8b2e2-657a-42ed-961e-c77b59bfddbc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-23e8b2e2-657a-42ed-961e-c77b59bfddbc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a635959-da98-4d4d-91d0-7ae15ed84d91' class='xr-var-data-in' type='checkbox'><label for='data-1a635959-da98-4d4d-91d0-7ae15ed84d91' 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([18.262870311142024+/-nan, 16.614044086145597+/-nan,\n",
|
||
|
|
" 16.93064456559001+/-nan, 16.77879884362973+/-nan,\n",
|
||
|
|
" 17.78068766741589+/-nan, 16.70881079171595+/-nan,\n",
|
||
|
|
" 16.875112498502794+/-nan, 16.764815374134376+/-nan,\n",
|
||
|
|
" 17.461819357235406+/-nan, 17.032587999394632+/-nan], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>deltax</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>18.54999801825887+/-nan ... 15.3...</div><input id='attrs-81b86ab2-05c4-46af-b7eb-dd9b8692e37d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-81b86ab2-05c4-46af-b7eb-dd9b8692e37d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c10656fe-164c-4f8e-8e49-5e051c6c829b' class='xr-var-data-in' type='checkbox'><label for='data-c10656fe-164c-4f8e-8e49-5e051c6c829b' 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([18.54999801825887+/-nan, 13.721861802607926+/-nan,\n",
|
||
|
|
" 15.146151354132233+/-nan, 13.58788862429502+/-nan,\n",
|
||
|
|
" 17.322692355533373+/-nan, 13.985243490736439+/-nan,\n",
|
||
|
|
" 14.61961018512725+/-nan, 13.749534514247552+/-nan,\n",
|
||
|
|
" 16.272055915380868+/-nan, 15.311958314696358+/-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'>1.2+/-nan 1.2+/-nan ... 1.2+/-nan</div><input id='attrs-50e91101-69c3-41a3-886f-295285e5d10f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-50e91101-69c3-41a3-886f-295285e5d10f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-62611110-afac-4c3b-aec9-0af98ad5fbe9' class='xr-var-data-in' type='checkbox'><label for='data-62611110-afac-4c3b-aec9-0af98ad5fbe9' 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([1.2+/-nan, 1.2+/-nan, 1.2+/-nan, 1.2+/-nan, 1.2+/-nan, 1.2+/-nan,\n",
|
||
|
|
" 1.2+/-nan, 1.2+/-nan, 1.2+/-nan, 1.2+/-nan], 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'>0.5200567557574306+/-nan ... 0.5...</div><input id='attrs-6173a4af-0749-44b3-aae8-5a00f0fed341' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6173a4af-0749-44b3-aae8-5a00f0fed341' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f7f70436-1017-4f50-8a0f-05082a167cfe' class='xr-var-data-in' type='checkbox'><label for='data-f7f70436-1017-4f50-8a0f-05082a167cfe' 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([0.5200567557574306+/-nan, 0.4988311083501699+/-nan,\n",
|
||
|
|
" 0.49843465712558144+/-nan, 0.5501078127624015+/-nan,\n",
|
||
|
|
" 0.4880434542490436+/-nan, 0.4832917128851891+/-nan,\n",
|
||
|
|
" 0.5099212535656252+/-nan, 0.523198726178512+/-nan,\n",
|
||
|
|
" 0.5146267977716745+/-nan, 0.5255162945553884+/-nan], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8e928194-cb1d-475c-84ab-5f5c80f99c34' class='xr-section-summary-in' type='checkbox' ><label for='section-8e928194-cb1d-475c-84ab-5f5c80f99c34' 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-7968ab3e-c4a8-4426-8503-25aff64cc953' class='xr-index-data-in' type='checkbox'/><label for='index-7968ab3e-c4a8-4426-8503-25aff64cc953' 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], dtype='float64', name='runs'))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-abed971f-e595-472e-81a4-10d6ecd56c03' class='xr-section-summary-in' type='checkbox' ><label for='section-abed971f-e595-472e-81a4-10d6ecd56c03' class='xr-section-summary' >Attributes: <span>(11)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>IMAGE_SUBCLASS :</span></dt><dd>IMAGE_GRAYSCALE</dd><dt><span>IMAGE_VERSION :</span></dt><dd>1.2</dd><dt><span>IMAGE_WHITE_IS_ZERO :</span></dt><dd>0</dd><dt><span>x_start :</span></dt><dd>840</dd><dt><span>x_end :</span></dt><dd>920</dd><dt><span>y_end :</span></dt><dd>1020</dd><dt><span>y_start :</span></dt><dd>940</dd><dt><span>x_center :</span></dt><dd>880</dd><dt><span>y_center :</span></dt><dd>980</dd><dt><span>x_span :</span></dt><dd>80</dd><dt><span>y_span :</span></dt><dd>80</dd></dl></div></li></ul></div></div>"
|
||
|
|
],
|
||
|
|
"text/plain": [
|
||
|
|
"<xarray.Dataset>\n",
|
||
|
|
"Dimensions: (runs: 10)\n",
|
||
|
|
"Coordinates:\n",
|
||
|
|
" * runs (runs) float64 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0\n",
|
||
|
|
"Data variables: (12/13)\n",
|
||
|
|
" BEC_amplitude (runs) object 622.325100923668+/-nan ... 622.4907683...\n",
|
||
|
|
" thermal_amplitude (runs) object 574.323330298593+/-nan ... 562.0410431...\n",
|
||
|
|
" BEC_centerx (runs) object 40.697673212791095+/-nan ... 41.846469...\n",
|
||
|
|
" BEC_centery (runs) object 38.68619529315486+/-nan ... 40.1657973...\n",
|
||
|
|
" thermal_centerx (runs) object 41.672856011589964+/-nan ... 42.186994...\n",
|
||
|
|
" thermal_centery (runs) object 40.50023901378942+/-nan ... 41.8611854...\n",
|
||
|
|
" ... ...\n",
|
||
|
|
" BEC_sigmay (runs) object 9.925094420566738+/-nan ... 9.27924633...\n",
|
||
|
|
" thermal_sigmax (runs) object 15.219058592618353+/-nan ... 14.193823...\n",
|
||
|
|
" thermal_sigmay (runs) object 18.262870311142024+/-nan ... 17.032587...\n",
|
||
|
|
" deltax (runs) object 18.54999801825887+/-nan ... 15.3119583...\n",
|
||
|
|
" thermalAspectRatio (runs) object 1.2+/-nan 1.2+/-nan ... 1.2+/-nan\n",
|
||
|
|
" condensate_fraction (runs) object 0.5200567557574306+/-nan ... 0.5255162...\n",
|
||
|
|
"Attributes:\n",
|
||
|
|
" IMAGE_SUBCLASS: IMAGE_GRAYSCALE\n",
|
||
|
|
" IMAGE_VERSION: 1.2\n",
|
||
|
|
" IMAGE_WHITE_IS_ZERO: 0\n",
|
||
|
|
" x_start: 840\n",
|
||
|
|
" x_end: 920\n",
|
||
|
|
" y_end: 1020\n",
|
||
|
|
" y_start: 940\n",
|
||
|
|
" x_center: 880\n",
|
||
|
|
" y_center: 980\n",
|
||
|
|
" x_span: 80\n",
|
||
|
|
" y_span: 80"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 28,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"fitAnalyser_1.get_fit_full_result(fitResult_1)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"attachments": {},
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"# Calibration of the magnetic fields"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"attachments": {},
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"## Z Offset field = 0.489A"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 30,
|
||
|
|
"metadata": {
|
||
|
|
"scrolled": false
|
||
|
|
},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"The detected scaning axes and values are: \n",
|
||
|
|
"\n",
|
||
|
|
"{'carrier_freq': array([9.525, 9.527, 9.529, 9.531, 9.533, 9.535, 9.537, 9.539, 9.541,\n",
|
||
|
|
" 9.543, 9.545, 9.547, 9.549, 9.551, 9.553, 9.555, 9.557, 9.559])}\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n if (typeof WebSocket !== 'undefined') {\n return WebSocket;\n } else if (typeof MozWebSocket !== 'undefined') {\n return MozWebSocket;\n } else {\n alert(\n 'Your browser does not have WebSocket support. ' +\n 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n 'Firefox 4 and 5 are also supported but you ' +\n 'have to enable WebSockets in about:config.'\n );\n }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n this.id = figure_id;\n\n this.ws = websocket;\n\n this.supports_binary = this.ws.binaryType !== undefined;\n\n if (!this.supports_binary) {\n var warnings = document.getElementById('mpl-warnings');\n if (warnings) {\n warnings.style.display = 'block';\n warnings.textContent =\n 'This browser does not support binary websocket messages. ' +\n 'Performance may be slow.';\n }\n }\n\n this.imageObj = new Image();\n\n this.context = undefined;\n this.message = undefined;\n this.canvas = undefined;\n this.rubberband_canvas = undefined;\n this.rubberband_context = undefined;\n this.format_dropdown = undefined;\n\n this.image_mode = 'full';\n\n this.root = document.createElement('div');\n this.root.setAttribute('style', 'display: inline-block');\n this._root_extra_style(this.root);\n\n parent_element.appendChild(this.root);\n\n this._init_header(this);\n this._init_canvas(this);\n this._init_toolbar(this);\n\n var fig = this;\n\n this.waiting = false;\n\n this.ws.onopen = function () {\n fig.send_message('supports_binary', { value: fig.supports_binary });\n fig.send_message('send_image_mode', {});\n if (fig.ratio !== 1) {\n fig.send_message('set_device_pixel_ratio', {\n device_pixel_ratio: fig.ratio,\n });\n }\n fig.send_message('refresh', {});\n };\n\n this.imageObj.onload = function () {\n if (fig.image_mode === 'full') {\n // Full images could contain transparency (where diff images\n // almost always do), so we need to clear the canvas so that\n // there is no ghosting.\n fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n }\n fig.context.drawImage(fig.imageObj, 0, 0);\n };\n\n this.imageObj.onunload = function () {\n fig.ws.close();\n };\n\n this.ws.onmessage = this._make_on_message_function(this);\n\n this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n var titlebar = document.createElement('div');\n titlebar.classList =\n 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n var titletext = document.createElement('div');\n titletext.classList = 'ui-dialog-title';\n titletext.setAttribute(\n 'style',\n 'width: 100%; text-align: center; padding: 3px;'\n );\n titlebar.appendChild(titletext);\n this.root.appendChild(titlebar);\n this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n var fig = this;\n\n var canvas_div = (this.canvas_div = document.createElement('div'));\n canvas_div.setAttribute(\n 'style',\n 'border: 1px solid #ddd;' +\n 'box-sizing: content-box;' +\n 'clear: both;' +\n 'min-height: 1px;' +\n 'min-width: 1px;' +\n 'outline: 0;' +\n 'overflow: hidden;' +\n 'position: relative;' +\n 'resize: both;'\n );\n\n function on_keyboard_event_closure(name) {\n return function (event) {\n return fig.key
|
||
|
|
"text/plain": [
|
||
|
|
"<IPython.core.display.Javascript object>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/html": [
|
||
|
|
"<img src=\"data:image/png;base64,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
|
||
|
|
],
|
||
|
|
"text/plain": [
|
||
|
|
"<IPython.core.display.HTML object>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"%matplotlib notebook\n",
|
||
|
|
"shotNum = \"0008\"\n",
|
||
|
|
"filePath = folderPath + \"/\" + shotNum + \"/*.h5\"\n",
|
||
|
|
"\n",
|
||
|
|
"dataSetDict = {\n",
|
||
|
|
" dskey[groupList[i]]: read_hdf5_file(filePath, groupList[i], excludeAxis = ['sweep_start_freq', 'sweep_stop_freq'])\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 = (135, 990)\n",
|
||
|
|
"imageAnalyser.span = (250, 250)\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 = calculate_mean(Ncount)\n",
|
||
|
|
"Ncount_std = calculate_std(Ncount)\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, 3500])\n",
|
||
|
|
"plt.grid(visible=1)\n",
|
||
|
|
"plt.show()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"Ncount_mean_1 = Ncount_mean\n",
|
||
|
|
"Ncount_std_1 = Ncount_std\n",
|
||
|
|
"\n",
|
||
|
|
"fitAnalyser_1 = FitAnalyser(\"Gaussian With Offset\", fitDim=1)\n",
|
||
|
|
"# params = fitAnalyser.guess(Ncount_mean_1, x=scanAxis[0], guess_kwargs=dict(negative=True), dask=\"parallelized\")\n",
|
||
|
|
"params = fitAnalyser_1.fitModel.make_params()\n",
|
||
|
|
"params.add(name=\"amplitude\", value= -3000, max=np.inf, min=-np.inf, vary=True)\n",
|
||
|
|
"params.add(name=\"center\", value= 2.785, max=np.inf, min=-np.inf, vary=True)\n",
|
||
|
|
"params.add(name=\"sigma\", value= 0.1, max=np.inf, min= 0, vary=True)\n",
|
||
|
|
"params.add(name=\"offset\", value= 3000, max=np.inf, min=-np.inf, vary=True)\n",
|
||
|
|
"\n",
|
||
|
|
"fitResult_1 = fitAnalyser_1.fit(Ncount_mean_1, params, x=scanAxis[0]).load()\n",
|
||
|
|
"freqdata = np.linspace(2.76, 2.81, 500)\n",
|
||
|
|
"fitCurve_1 = fitAnalyser_1.eval(fitResult_1, x=freqdata, dask=\"parallelized\").load()\n",
|
||
|
|
"fitCurve_1 = fitCurve_1.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_1.plot.errorbar(ax=ax, fmt='--g')\n",
|
||
|
|
"plt.xlabel('Center Frequency (MHz)')\n",
|
||
|
|
"plt.ylabel('NCount')\n",
|
||
|
|
"#plt.ylim([0, 3500])\n",
|
||
|
|
"plt.tight_layout()\n",
|
||
|
|
"plt.grid(visible=1)\n",
|
||
|
|
"plt.show()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"f_1 = fitAnalyser_1.get_fit_value(fitResult_1).center\n",
|
||
|
|
"df_1 = fitAnalyser_1.get_fit_std(fitResult_1).center\n",
|
||
|
|
"\n",
|
||
|
|
"print('f = %.5f \\u00B1 %.5f kHz'% tuple([np.abs(f_1)* 1e3,df_1* 1e3]))\n",
|
||
|
|
"\n",
|
||
|
|
"s_1 = fitAnalyser_1.get_fit_value(fitResult_1).sigma\n",
|
||
|
|
"ds_1 = fitAnalyser_1.get_fit_std(fitResult_1).sigma\n",
|
||
|
|
"\n",
|
||
|
|
"fwhm_1 = 2.3548200*s_1 * 1e3\n",
|
||
|
|
"dfwhm_1 = 2.3548200*ds_1 * 1e3\n",
|
||
|
|
"\n",
|
||
|
|
"print('fwhm = %.5f \\u00B1 %.5f kHz'% tuple([np.abs(fwhm_1),dfwhm_1]))"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"%matplotlib notebook\n",
|
||
|
|
"shotNum = \"0016\"\n",
|
||
|
|
"filePath = folderPath + \"/\" + shotNum + \"/*.h5\"\n",
|
||
|
|
"\n",
|
||
|
|
"dataSetDict = {\n",
|
||
|
|
" dskey[groupList[i]]: read_hdf5_file(filePath, groupList[i], excludeAxis = ['sweep_start_freq', 'sweep_stop_freq'])\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 = (135, 990)\n",
|
||
|
|
"imageAnalyser.span = (250, 250)\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 = calculate_mean(Ncount)\n",
|
||
|
|
"Ncount_std = calculate_std(Ncount)\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, 3500])\n",
|
||
|
|
"plt.grid(visible=1)\n",
|
||
|
|
"plt.show()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 29,
|
||
|
|
"metadata": {
|
||
|
|
"scrolled": false
|
||
|
|
},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"[9.525, 9.527, 9.529, 9.531, 9.533, 9.535, 9.537, 9.539, 9.541, 9.543, 9.545, 9.547, 9.549, 9.551, 9.553, 9.555, 9.557, 9.559]\n",
|
||
|
|
"18\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"9.542"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 29,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"l = list(np.arange(9.525, 9.56, 0.002))\n",
|
||
|
|
"# l = np.logspace(np.log10(250e-6), np.log10(500e-3), num=15)\n",
|
||
|
|
"\n",
|
||
|
|
"l = [round(item, 7) for item in l]\n",
|
||
|
|
"#random.shuffle(l)\n",
|
||
|
|
"\n",
|
||
|
|
"print(l)\n",
|
||
|
|
"print(len(l))\n",
|
||
|
|
"np.mean(l)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"[10.25, 10.255, 10.26, 10.265, 10.27, 10.275, 10.28, 10.285, 10.29, 10.295, 10.3, 10.305, 10.31, 10.315, 10.32, 10.325, 10.33, 10.335, 10.34, 10.345, 10.35, 10.355]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"pixel = 5.86e-6\n",
|
||
|
|
"M = 0.6827\n",
|
||
|
|
"F = (1/(0.3725*8.4743e-14)) * (pixel / M)**2\n",
|
||
|
|
"NCount = 85000\n",
|
||
|
|
"AtomNumber = NCount * F / 1e8\n",
|
||
|
|
"print(AtomNumber)\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"muB = 9.274e-24\n",
|
||
|
|
"hbar = 6.626e-34 / (2 * np.pi)\n",
|
||
|
|
"gJ = 1.24\n",
|
||
|
|
"Delta = 2 * np.pi * 100 * 1e3\n",
|
||
|
|
"\n",
|
||
|
|
"Bz = (Delta*hbar) / (muB*gJ)\n",
|
||
|
|
"print(Bz * 1e4)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"attachments": {},
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"## ODT 1 Calibration"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"v_high = 2.7\n",
|
||
|
|
"\"\"\"High Power\"\"\"\n",
|
||
|
|
"P_arm1_high = 5.776 * v_high - 0.683\n",
|
||
|
|
"\n",
|
||
|
|
"v_mid = 0.2076\n",
|
||
|
|
"\"\"\"Intermediate Power\"\"\"\n",
|
||
|
|
"P_arm1_mid = 5.815 * v_mid - 0.03651\n",
|
||
|
|
"\n",
|
||
|
|
"v_low = 0.0587\n",
|
||
|
|
"\"\"\"Low Power\"\"\"\n",
|
||
|
|
"P_arm1_low = 5271 * v_low - 27.5\n",
|
||
|
|
"\n",
|
||
|
|
"print(round(P_arm1_high, 3))\n",
|
||
|
|
"print(round(P_arm1_mid, 3))\n",
|
||
|
|
"print(round(P_arm1_low, 3))"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"attachments": {},
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"## ODT 2 Power Calibration"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"v = 0.7607\n",
|
||
|
|
"P_arm2 = 2.302 * v - 0.06452\n",
|
||
|
|
"print(round(P_arm2, 3))"
|
||
|
|
]
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"metadata": {
|
||
|
|
"kernelspec": {
|
||
|
|
"display_name": "Python 3 (ipykernel)",
|
||
|
|
"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"
|
||
|
|
},
|
||
|
|
"vscode": {
|
||
|
|
"interpreter": {
|
||
|
|
"hash": "c05913ad4f24fdc6b2418069394dc5835b1981849b107c9ba6df693aafd66650"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"nbformat": 4,
|
||
|
|
"nbformat_minor": 2
|
||
|
|
}
|