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{
"cells": [
{
"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
"outputs": [],
"source": [
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"import pymongo\n",
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"import xarray_mongodb\n",
"import bson\n",
"import datetime\n",
"\n",
"# datetime.datetime.utcnow()"
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]
},
{
"cell_type": "code",
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"execution_count": 172,
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"metadata": {},
"outputs": [],
"source": [
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"mongoClient = pymongo.MongoClient('mongodb://userAdmin:DyLab2021userAdmin@127.0.0.1:27017/?authMechanism=DEFAULT')\n",
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"mongoDB = mongoClient.testDB\n",
"mongoCollection = mongoDB.testCollection"
]
},
{
"cell_type": "code",
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"execution_count": 174,
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"metadata": {},
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"outputs": [
{
"data": {
"text/plain": [
"{'ok': 1.0}"
]
},
"execution_count": 174,
"metadata": {},
"output_type": "execute_result"
}
],
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"source": [
"# mongoClient.admin.command(\n",
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"# 'createUser', 'control', \n",
"# pwd='DyLab2021',\n",
"# roles=[{'role': 'readWriteAnyDatabase', 'db': 'admin'}]\n",
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"# )"
]
},
{
"cell_type": "code",
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"execution_count": 173,
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"metadata": {},
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"outputs": [
{
"data": {
"text/plain": [
"{'ok': 1.0}"
]
},
"execution_count": 173,
"metadata": {},
"output_type": "execute_result"
}
],
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"source": [
"# mongoClient.admin.command(\n",
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"# 'dropUser', 'contorl'\n",
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"# )"
]
},
{
"cell_type": "code",
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"execution_count": 175,
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"metadata": {},
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"outputs": [
{
"data": {
"text/plain": [
"{'users': [{'_id': 'admin.control',\n",
" 'userId': Binary(b'\\xef\\x01\\xec\\xf4\\xfc\\xe2Bp\\x84v\\xcaZ\\xa3D\\xbb\\x18', 4),\n",
" 'user': 'control',\n",
" 'db': 'admin',\n",
" 'roles': [{'role': 'readWriteAnyDatabase', 'db': 'admin'}],\n",
" 'mechanisms': ['SCRAM-SHA-1', 'SCRAM-SHA-256']},\n",
" {'_id': 'admin.dbAdmin',\n",
" 'userId': Binary(b'\\xfc\\x84\\x07\\x13\\xfc\\x81F\\xc9\\x87\\xbc<\\xe6D\\xf7\\xcc\\xe0', 4),\n",
" 'user': 'dbAdmin',\n",
" 'db': 'admin',\n",
" 'roles': [{'role': 'dbAdminAnyDatabase', 'db': 'admin'}],\n",
" 'mechanisms': ['SCRAM-SHA-1', 'SCRAM-SHA-256']},\n",
" {'_id': 'admin.root',\n",
" 'userId': Binary(b'\\x07\\xe1\\xc7\\x18\\xca\\xacN5\\x93\\xf7{s`+\\xc2\\xf7', 4),\n",
" 'user': 'root',\n",
" 'db': 'admin',\n",
" 'roles': [{'role': 'root', 'db': 'admin'}],\n",
" 'mechanisms': ['SCRAM-SHA-1', 'SCRAM-SHA-256']},\n",
" {'_id': 'admin.userAdmin',\n",
" 'userId': Binary(b'\\x83U\\xb4YraK\\xc7\\xadB\\x11\\xcb\\x08\\x0eL\\x9a', 4),\n",
" 'user': 'userAdmin',\n",
" 'db': 'admin',\n",
" 'roles': [{'role': 'userAdminAnyDatabase', 'db': 'admin'}],\n",
" 'mechanisms': ['SCRAM-SHA-1', 'SCRAM-SHA-256']}],\n",
" 'ok': 1.0}"
]
},
"execution_count": 175,
"metadata": {},
"output_type": "execute_result"
}
],
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"source": [
"# mongoClient.admin.command('usersInfo')"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
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"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Task executing\n",
"\n",
"Task2 executing \n",
"\n",
"Task2 done\n",
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"Task done\n",
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"\n",
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"\n"
]
}
],
"source": [
"from time import sleep\n",
"from multiprocessing.pool import ThreadPool\n",
" \n",
"# task executed in a worker thread\n",
"def task():\n",
" # report a message\n",
" print(f'Task executing\\n')\n",
" # block for a moment\n",
" sleep(1)\n",
" # report a message\n",
" print(f'Task done\\n')\n",
" \n",
"def task2():\n",
" # report a message\n",
" print(f'Task2 executing \\n')\n",
" # block for a moment\n",
" sleep(1)\n",
" # report a message\n",
" print(f'Task2 done\\n')\n",
" \n",
"# protect the entry point\n",
"if __name__ == '__main__':\n",
" # create and configure the thread pool\n",
" pool = ThreadPool()\n",
" # issue tasks to the thread pool\n",
" pool.apply_async(task)\n",
" pool.apply_async(task2)\n",
" # close the thread pool\n",
" pool.close()\n",
" # wait for all tasks to finish\n",
" pool.join()"
]
},
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{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"# Import supporting package"
]
},
{
"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
"outputs": [],
"source": [
"import xarray as xr\n",
"import pandas as pd\n",
"import numpy as np\n",
"import copy\n",
"\n",
"import glob\n",
"\n",
"import xrft\n",
"import finufft\n",
"\n",
"from uncertainties import ufloat\n",
"from uncertainties import unumpy as unp\n",
"from uncertainties import umath\n",
"\n",
"from datetime import datetime\n",
"\n",
"import matplotlib.pyplot as plt\n",
"plt.rcParams['font.size'] = 18\n",
"\n",
"from DataContainer.ReadData import read_hdf5_file, read_hdf5_global, read_hdf5_run_time, read_csv_file\n",
"from Analyser.ImagingAnalyser import ImageAnalyser\n",
"from Analyser.FitAnalyser import FitAnalyser\n",
"from Analyser.FitAnalyser import ThomasFermi2dModel, DensityProfileBEC2dModel, Polylog22dModel\n",
"from Analyser.FFTAnalyser import fft, ifft, fft_nutou\n",
"from ToolFunction.ToolFunction import *\n",
"\n",
"from ToolFunction.HomeMadeXarrayFunction import errorbar, dataarray_plot_errorbar\n",
"xr.plot.dataarray_plot.errorbar = errorbar\n",
"xr.plot.accessor.DataArrayPlotAccessor.errorbar = dataarray_plot_errorbar\n",
"\n",
"imageAnalyser = ImageAnalyser()"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"# Import supporting package"
]
},
{
"cell_type": "code",
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"execution_count": 8,
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"metadata": {},
"outputs": [],
"source": [
"import xarray as xr\n",
"import numpy as np\n",
"\n",
"from uncertainties import ufloat\n",
"from uncertainties import unumpy as unp\n",
"from uncertainties import umath\n",
"\n",
"import matplotlib.pyplot as plt\n",
"\n",
"from DataContainer.ReadData import read_hdf5_file\n",
"from Analyser.ImagingAnalyser import ImageAnalyser\n",
"from Analyser.FitAnalyser import FitAnalyser\n",
"from Analyser.FitAnalyser import ThomasFermi2dModel, DensityProfileBEC2dModel, Polylog22dModel\n",
"from Analyser.FitAnalyser import NewFitModel\n",
"from ToolFunction.ToolFunction import *\n",
"\n",
"from ToolFunction.HomeMadeXarrayFunction import errorbar, dataarray_plot_errorbar\n",
"xr.plot.dataarray_plot.errorbar = errorbar\n",
"xr.plot.accessor.DataArrayPlotAccessor.errorbar = dataarray_plot_errorbar\n",
"\n",
"imageAnalyser = ImageAnalyser()"
]
},
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{
"cell_type": "code",
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"execution_count": 9,
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"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1738.8478693742436\n"
]
}
],
"source": [
"sigma = 8.4743e-14 * 0.5\n",
"M = 0.6827\n",
"print(1/sigma*5.86e-6**2 / M**2)"
]
},
{
"cell_type": "code",
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"execution_count": 10,
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"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"8.583565255602754e-06"
]
},
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"execution_count": 10,
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"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"5.86e-6/M"
]
},
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{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## Start a client for parallel computing"
]
},
{
"cell_type": "code",
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"execution_count": 11,
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"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
" <div style=\"width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;\"> </div>\n",
" <div style=\"margin-left: 48px;\">\n",
" <h3 style=\"margin-bottom: 0px;\">Client</h3>\n",
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" <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Client-8ed8b0e1-09e5-11ee-bf58-80e82ce2fa8e</p>\n",
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" <table style=\"width: 100%; text-align: left;\">\n",
"\n",
" <tr>\n",
" \n",
" <td style=\"text-align: left;\"><strong>Connection method:</strong> Cluster object</td>\n",
" <td style=\"text-align: left;\"><strong>Cluster type:</strong> distributed.LocalCluster</td>\n",
" \n",
" </tr>\n",
"\n",
" \n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:8787/status\" target=\"_blank\">http://127.0.0.1:8787/status</a>\n",
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" </td>\n",
" <td style=\"text-align: left;\"></td>\n",
" </tr>\n",
" \n",
"\n",
" </table>\n",
"\n",
" \n",
"\n",
" \n",
" <details>\n",
" <summary style=\"margin-bottom: 20px;\"><h3 style=\"display: inline;\">Cluster Info</h3></summary>\n",
" <div class=\"jp-RenderedHTMLCommon jp-RenderedHTML jp-mod-trusted jp-OutputArea-output\">\n",
" <div style=\"width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;\">\n",
" </div>\n",
" <div style=\"margin-left: 48px;\">\n",
" <h3 style=\"margin-bottom: 0px; margin-top: 0px;\">LocalCluster</h3>\n",
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" <p style=\"color: #9D9D9D; margin-bottom: 0px;\">5b1feb01</p>\n",
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" <table style=\"width: 100%; text-align: left;\">\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Dashboard:</strong> <a href=\"http://127.0.0.1:8787/status\" target=\"_blank\">http://127.0.0.1:8787/status</a>\n",
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" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Workers:</strong> 6\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total threads:</strong> 60\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total memory:</strong> 55.88 GiB\n",
" </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <td style=\"text-align: left;\"><strong>Status:</strong> running</td>\n",
" <td style=\"text-align: left;\"><strong>Using processes:</strong> True</td>\n",
"</tr>\n",
"\n",
" \n",
" </table>\n",
"\n",
" <details>\n",
" <summary style=\"margin-bottom: 20px;\">\n",
" <h3 style=\"display: inline;\">Scheduler Info</h3>\n",
" </summary>\n",
"\n",
" <div style=\"\">\n",
" <div>\n",
" <div style=\"width: 24px; height: 24px; background-color: #FFF7E5; border: 3px solid #FF6132; border-radius: 5px; position: absolute;\"> </div>\n",
" <div style=\"margin-left: 48px;\">\n",
" <h3 style=\"margin-bottom: 0px;\">Scheduler</h3>\n",
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" <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Scheduler-26a37a65-33ec-4a1b-8178-b6175add1767</p>\n",
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" <table style=\"width: 100%; text-align: left;\">\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Comm:</strong> tcp://127.0.0.1:51440\n",
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" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Workers:</strong> 6\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Dashboard:</strong> <a href=\"http://127.0.0.1:8787/status\" target=\"_blank\">http://127.0.0.1:8787/status</a>\n",
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" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total threads:</strong> 60\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Started:</strong> Just now\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total memory:</strong> 55.88 GiB\n",
" </td>\n",
" </tr>\n",
" </table>\n",
" </div>\n",
" </div>\n",
"\n",
" <details style=\"margin-left: 48px;\">\n",
" <summary style=\"margin-bottom: 20px;\">\n",
" <h3 style=\"display: inline;\">Workers</h3>\n",
" </summary>\n",
"\n",
" \n",
" <div style=\"margin-bottom: 20px;\">\n",
" <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
" <div style=\"margin-left: 48px;\">\n",
" <details>\n",
" <summary>\n",
" <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 0</h4>\n",
" </summary>\n",
" <table style=\"width: 100%; text-align: left;\">\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Comm: </strong> tcp://127.0.0.1:51467\n",
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" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total threads: </strong> 10\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:51468/status\" target=\"_blank\">http://127.0.0.1:51468/status</a>\n",
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" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Memory: </strong> 9.31 GiB\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Nanny: </strong> tcp://127.0.0.1:51443\n",
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" </td>\n",
" <td style=\"text-align: left;\"></td>\n",
" </tr>\n",
" <tr>\n",
" <td colspan=\"2\" style=\"text-align: left;\">\n",
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" <strong>Local directory: </strong> C:\\Users\\data\\AppData\\Local\\Temp\\dask-worker-space\\worker-dx7rbtlb\n",
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" </td>\n",
" </tr>\n",
"\n",
" \n",
"\n",
" \n",
"\n",
" </table>\n",
" </details>\n",
" </div>\n",
" </div>\n",
" \n",
" <div style=\"margin-bottom: 20px;\">\n",
" <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
" <div style=\"margin-left: 48px;\">\n",
" <details>\n",
" <summary>\n",
" <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 1</h4>\n",
" </summary>\n",
" <table style=\"width: 100%; text-align: left;\">\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Comm: </strong> tcp://127.0.0.1:51473\n",
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" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total threads: </strong> 10\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:51476/status\" target=\"_blank\">http://127.0.0.1:51476/status</a>\n",
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" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Memory: </strong> 9.31 GiB\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Nanny: </strong> tcp://127.0.0.1:51444\n",
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" </td>\n",
" <td style=\"text-align: left;\"></td>\n",
" </tr>\n",
" <tr>\n",
" <td colspan=\"2\" style=\"text-align: left;\">\n",
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" <strong>Local directory: </strong> C:\\Users\\data\\AppData\\Local\\Temp\\dask-worker-space\\worker-qg83_2a9\n",
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" </td>\n",
" </tr>\n",
"\n",
" \n",
"\n",
" \n",
"\n",
" </table>\n",
" </details>\n",
" </div>\n",
" </div>\n",
" \n",
" <div style=\"margin-bottom: 20px;\">\n",
" <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
" <div style=\"margin-left: 48px;\">\n",
" <details>\n",
" <summary>\n",
" <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 2</h4>\n",
" </summary>\n",
" <table style=\"width: 100%; text-align: left;\">\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Comm: </strong> tcp://127.0.0.1:51470\n",
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" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total threads: </strong> 10\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:51471/status\" target=\"_blank\">http://127.0.0.1:51471/status</a>\n",
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" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Memory: </strong> 9.31 GiB\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Nanny: </strong> tcp://127.0.0.1:51445\n",
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" </td>\n",
" <td style=\"text-align: left;\"></td>\n",
" </tr>\n",
" <tr>\n",
" <td colspan=\"2\" style=\"text-align: left;\">\n",
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" <strong>Local directory: </strong> C:\\Users\\data\\AppData\\Local\\Temp\\dask-worker-space\\worker-_5umuerf\n",
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" </td>\n",
" </tr>\n",
"\n",
" \n",
"\n",
" \n",
"\n",
" </table>\n",
" </details>\n",
" </div>\n",
" </div>\n",
" \n",
" <div style=\"margin-bottom: 20px;\">\n",
" <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
" <div style=\"margin-left: 48px;\">\n",
" <details>\n",
" <summary>\n",
" <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 3</h4>\n",
" </summary>\n",
" <table style=\"width: 100%; text-align: left;\">\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Comm: </strong> tcp://127.0.0.1:51479\n",
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" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total threads: </strong> 10\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:51480/status\" target=\"_blank\">http://127.0.0.1:51480/status</a>\n",
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" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Memory: </strong> 9.31 GiB\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Nanny: </strong> tcp://127.0.0.1:51446\n",
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" </td>\n",
" <td style=\"text-align: left;\"></td>\n",
" </tr>\n",
" <tr>\n",
" <td colspan=\"2\" style=\"text-align: left;\">\n",
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" <strong>Local directory: </strong> C:\\Users\\data\\AppData\\Local\\Temp\\dask-worker-space\\worker-72uth4_y\n",
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" </td>\n",
" </tr>\n",
"\n",
" \n",
"\n",
" \n",
"\n",
" </table>\n",
" </details>\n",
" </div>\n",
" </div>\n",
" \n",
" <div style=\"margin-bottom: 20px;\">\n",
" <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
" <div style=\"margin-left: 48px;\">\n",
" <details>\n",
" <summary>\n",
" <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 4</h4>\n",
" </summary>\n",
" <table style=\"width: 100%; text-align: left;\">\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Comm: </strong> tcp://127.0.0.1:51482\n",
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" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total threads: </strong> 10\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:51483/status\" target=\"_blank\">http://127.0.0.1:51483/status</a>\n",
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" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Memory: </strong> 9.31 GiB\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Nanny: </strong> tcp://127.0.0.1:51447\n",
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" </td>\n",
" <td style=\"text-align: left;\"></td>\n",
" </tr>\n",
" <tr>\n",
" <td colspan=\"2\" style=\"text-align: left;\">\n",
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" <strong>Local directory: </strong> C:\\Users\\data\\AppData\\Local\\Temp\\dask-worker-space\\worker-zjy152o_\n",
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" </td>\n",
" </tr>\n",
"\n",
" \n",
"\n",
" \n",
"\n",
" </table>\n",
" </details>\n",
" </div>\n",
" </div>\n",
" \n",
" <div style=\"margin-bottom: 20px;\">\n",
" <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
" <div style=\"margin-left: 48px;\">\n",
" <details>\n",
" <summary>\n",
" <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 5</h4>\n",
" </summary>\n",
" <table style=\"width: 100%; text-align: left;\">\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Comm: </strong> tcp://127.0.0.1:51474\n",
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" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total threads: </strong> 10\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:51475/status\" target=\"_blank\">http://127.0.0.1:51475/status</a>\n",
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" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Memory: </strong> 9.31 GiB\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
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" <strong>Nanny: </strong> tcp://127.0.0.1:51448\n",
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" </td>\n",
" <td style=\"text-align: left;\"></td>\n",
" </tr>\n",
" <tr>\n",
" <td colspan=\"2\" style=\"text-align: left;\">\n",
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" <strong>Local directory: </strong> C:\\Users\\data\\AppData\\Local\\Temp\\dask-worker-space\\worker-j1fo7yyx\n",
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" </td>\n",
" </tr>\n",
"\n",
" \n",
"\n",
" \n",
"\n",
" </table>\n",
" </details>\n",
" </div>\n",
" </div>\n",
" \n",
"\n",
" </details>\n",
"</div>\n",
"\n",
" </details>\n",
" </div>\n",
"</div>\n",
" </details>\n",
" \n",
"\n",
" </div>\n",
"</div>"
],
"text/plain": [
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"<Client: 'tcp://127.0.0.1:51440' processes=6 threads=60, memory=55.88 GiB>"
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]
},
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"execution_count": 11,
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"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from dask.distributed import Client\n",
"client = Client(n_workers=6, threads_per_worker=10, processes=True, memory_limit='10GB')\n",
"client"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## Set global path for experiment"
]
},
{
"cell_type": "code",
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"execution_count": 12,
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"metadata": {},
"outputs": [],
"source": [
"# filepath = \"//DyLabNAS/Data/Evaporative_Cooling/2023/05/03/0043/*.h5\"\n",
"# filepath = \"//DyLabNAS/Data/Evaporative_Cooling/2023/04/18/0003/2023-04-18_0003_Evaporative_Cooling_000.h5\"\n",
"\n",
"# filepath = \"//DyLabNAS/Data/Repetition_scan/2023/04/21/0002/*.h5\"\n",
"\n",
"# filepath = r\"./testData/0002/*.h5\"\n",
"\n",
"# filepath = r\"./testData/0002/2023-04-21_0002_Evaporative_Cooling_0.h5\"\n",
"\n",
"# filepath = r'd:/Jianshun Gao/Simulations/analyseScripts/testData/0002/2023-04-21_0002_Evaporative_Cooling_0.h5'\n",
"\n",
"# filepath = \"//DyLabNAS/Data/Evaporative_Cooling/2023/04/18/0003/*.h5\"\n",
"\n",
"# filepath = \"//DyLabNAS/Data/Evaporative_Cooling/2023/05/04/0000/*.h5\"\n",
"\n",
"filepath = './result_from_experiment/2023-04-24/0013/2023-04-24_0013_Evaporative_Cooling_08.h5'"
]
},
{
"cell_type": "code",
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"execution_count": 13,
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"metadata": {},
"outputs": [],
"source": [
"groupList = [\n",
" \"images/MOT_3D_Camera/in_situ_absorption\",\n",
" \"images/ODT_1_Axis_Camera/in_situ_absorption\",\n",
" \"images/ODT_2_Axis_Camera/in_situ_absorption\",\n",
"]\n",
"\n",
"dskey = {\n",
" \"images/MOT_3D_Camera/in_situ_absorption\": \"camera_1\",\n",
" \"images/ODT_1_Axis_Camera/in_situ_absorption\": \"camera_2\",\n",
" \"images/ODT_2_Axis_Camera/in_situ_absorption\": \"camera_3\",\n",
"}\n"
]
},
{
"cell_type": "code",
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"execution_count": 14,
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"metadata": {},
"outputs": [],
"source": [
"img_dir = '//DyLabNAS/Data/'\n",
"SequenceName = \"Evaporative_Cooling\" + \"/\"\n",
"folderPath = img_dir + SequenceName + '2023/05/23'# get_date()"
]
},
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{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"# An example for one experimental run"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## Load the data"
]
},
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{
"cell_type": "code",
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"execution_count": 37,
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"metadata": {},
"outputs": [
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"</style><pre class='xr-text-repr-fallback'><xarray.Dataset>\n",
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"Dimensions: (compX_final_current: 11, runs: 3, y: 1200, x: 1920)\n",
"Coordinates:\n",
" * compX_final_current (compX_final_current) float64 0.0 0.002 ... 0.018 0.02\n",
" * runs (runs) float64 0.0 1.0 2.0\n",
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"Dimensions without coordinates: y, x\n",
2023-05-24 19:59:04 +02:00
"Data variables:\n",
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" atoms (compX_final_current, runs, y, x) uint16 dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray>\n",
" background (compX_final_current, runs, y, x) uint16 dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray>\n",
" dark (compX_final_current, runs, y, x) uint16 dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray>\n",
" shotNum (compX_final_current, runs) <U2 dask.array<chunksize=(11, 3), meta=np.ndarray>\n",
" OD (compX_final_current, runs, y, x) float64 dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray>\n",
"Attributes: (12/120)\n",
" TOF_free: 0.022\n",
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" abs_img_freq: 110.858\n",
" absorption_imaging_flag: True\n",
" backup_data: True\n",
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" blink_off_time: 0.001\n",
" blink_on_time: 0.001\n",
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" ... ...\n",
" z_offset: 0.189\n",
" z_offset_img: 0.189\n",
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" compX_final_current: [0. 0.002 0.004 0.006 0.008 0.01 0...\n",
" runs: [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 1...\n",
" scanAxis: ['compX_final_current' 'runs']\n",
" scanAxisLength: [33. 33.]</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-1387e95f-ac8c-4a1d-b324-7d3145dcbf46' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-1387e95f-ac8c-4a1d-b324-7d3145dcbf46' 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'>compX_final_current</span>: 11</li><li><span class='xr-has-index'>runs</span>: 3</li><li><span>y</span>: 1200</li><li><span>x</span>: 1920</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-e93c3a5b-5de8-4da9-908b-748379fa19e5' class='xr-section-summary-in' type='checkbox' checked><label for='section-e93c3a5b-5de8-4da9-908b-748379fa19e5' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>compX_final_current</span></div><div class='xr-var-dims'>(compX_final_current)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.002 0.004 ... 0.018 0.02</div><input id='attrs-0bcc527c-454e-4998-ab55-ea975806f9a2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0bcc527c-454e-4998-ab55-ea975806f9a2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-70695823-aaa0-4e73-844a-74a4640c109f' class='xr-var-data-in' type='checkbox'><label for='data-70695823-aaa0-4e73-844a-74a4640c109f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0. , 0.002, 0.004, 0.006, 0.008, 0.01 , 0.012, 0.014, 0.016, 0.018,\n",
" 0.02 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>runs</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.0 2.0</div><input id='attrs-993bc1f3-e76f-4fe3-8230-d38ab663021a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-993bc1f3-e76f-4fe3-8230-d38ab663021a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-76cd9466-bcab-44a6-90f6-b00fde183e45' class='xr-var-data-in' type='checkbox'><label for='data-76cd9466-bcab-44a6-90f6-b00fde183e45' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0., 1., 2.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-575ae3c0-830f-4b0f-a5d0-1936fb2f9891' class='xr-section-summary-in' type='checkbox' checked><label for='section-575ae3c0-830f-4b0f-a5d0-1936fb2f9891' class='xr-section-summary' >Data variables: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>atoms</span></div><div class='xr-var-dims'>(compX_final_current, runs, y, x)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray></div><input id='attrs-ad2be5de-fd7c-4e48-be38-cf901131bed9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ad2be5de-fd7c-4e48-be38-cf901131bed9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-04a81c96-3f44-4b30-a75e-0e7b6cb8027b' class='xr-var-data-in' type='checkbox'><label for='data-04a81c96-3f44-4b30-a75e-0e7b6cb8027b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>IMAGE_SUBCLASS :</span></dt><dd>IMAGE_GRAYSCALE</dd><dt><span>IMAGE_VERSION :</span></dt><dd>1.2</dd><dt><span>IMAGE_WHITE_IS_ZERO :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><table>\n",
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" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
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" <td> 145.02 MiB </td>\n",
" <td> 118.65 MiB </td>\n",
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" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
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" <td> (11, 3, 1200, 1920) </td>\n",
" <td> (9, 3, 1200, 1920) </td>\n",
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" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
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" <td colspan=\"2\"> 2 chunks in 104 graph layers </td>\n",
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" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> uint16 numpy.ndarray </td>\n",
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" </table>\n",
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" <td>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>background</span></div><div class='xr-var-dims'>(compX_final_current, runs, y, x)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray></div><input id='attrs-03face6b-70e3-46ec-8ebf-2e82aad50a44' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-03face6b-70e3-46ec-8ebf-2e82aad50a44' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3f816186-8f4a-442a-82f9-a872f95f4a37' class='xr-var-data-in' type='checkbox'><label for='data-3f816186-8f4a-442a-82f9-a872f95f4a37' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>IMAGE_SUBCLASS :</span></dt><dd>IMAGE_GRAYSCALE</dd><dt><span>IMAGE_VERSION :</span></dt><dd>1.2</dd><dt><span>IMAGE_WHITE_IS_ZERO :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><table>\n",
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" <tr>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dark</span></div><div class='xr-var-dims'>(compX_final_current, runs, y, x)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray></div><input id='attrs-a45fbbb5-3189-4efb-81ba-0f0a53f58e80' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a45fbbb5-3189-4efb-81ba-0f0a53f58e80' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e0c9402f-11f2-4026-808b-ee211c99c9be' class='xr-var-data-in' type='checkbox'><label for='data-e0c9402f-11f2-4026-808b-ee211c99c9be' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>IMAGE_SUBCLASS :</span></dt><dd>IMAGE_GRAYSCALE</dd><dt><span>IMAGE_VERSION :</span></dt><dd>1.2</dd><dt><span>IMAGE_WHITE_IS_ZERO :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><table>\n",
2023-06-02 18:42:18 +02:00
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
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" <td> 145.02 MiB </td>\n",
" <td> 118.65 MiB </td>\n",
2023-06-02 18:42:18 +02:00
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" <tr>\n",
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2023-06-13 18:16:24 +02:00
" <td> (11, 3, 1200, 1920) </td>\n",
" <td> (9, 3, 1200, 1920) </td>\n",
2023-06-02 18:42:18 +02:00
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
2023-06-13 18:16:24 +02:00
" <td colspan=\"2\"> 2 chunks in 104 graph layers </td>\n",
2023-06-02 18:42:18 +02:00
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> uint16 numpy.ndarray </td>\n",
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2023-06-13 18:16:24 +02:00
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2023-06-02 18:42:18 +02:00
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2023-06-13 18:16:24 +02:00
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2023-06-02 18:42:18 +02:00
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2023-06-13 18:16:24 +02:00
" <td> 264 B </td>\n",
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2023-06-02 18:42:18 +02:00
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2023-06-13 18:16:24 +02:00
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" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 1 chunks in 1 graph layer </td>\n",
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" <tr>\n",
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" <td colspan=\"2\"> <U2 numpy.ndarray </td>\n",
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2023-06-02 18:42:18 +02:00
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2023-06-13 18:16:24 +02:00
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2023-06-02 18:42:18 +02:00
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2023-06-13 18:16:24 +02:00
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"</svg>\n",
" </td>\n",
" </tr>\n",
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"</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-b5cd912d-8c64-4466-b154-e9c33aa04958' class='xr-section-summary-in' type='checkbox' ><label for='section-b5cd912d-8c64-4466-b154-e9c33aa04958' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>compX_final_current</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-74025258-c9a3-45d7-866c-fc4e87fc3be4' class='xr-index-data-in' type='checkbox'/><label for='index-74025258-c9a3-45d7-866c-fc4e87fc3be4' 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, 0.002, 0.004, 0.006, 0.008, 0.01, 0.012, 0.014, 0.016,\n",
" 0.018, 0.02],\n",
" dtype='float64', name='compX_final_current'))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>runs</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0e66a8d5-0da2-4de3-bf7f-de5760cce97e' class='xr-index-data-in' type='checkbox'/><label for='index-0e66a8d5-0da2-4de3-bf7f-de5760cce97e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([0.0, 1.0, 2.0], dtype='float64', name='runs'))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-dc7f40a0-956c-4521-b44d-6e7c2ae38d63' class='xr-section-summary-in' type='checkbox' ><label for='section-dc7f40a0-956c-4521-b44d-6e7c2ae38d63' class='xr-section-summary' >Attributes: <span>(120)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>TOF_free :</span></dt><dd>0.022</dd><dt><span>abs_img_freq :</span></dt><dd>110.858</dd><dt><span>absorption_imaging_flag :</span></dt><dd>True</dd><dt><span>backup_data :</span></dt><dd>True</dd><dt><span>blink_off_time :</span></dt><dd>0.001</dd><dt><span>blink_on_time :</span></dt><dd>0.001</dd><dt><span>c_duration :</span></dt><dd>0.2</dd><dt><span>carrier_amp :</span></dt><dd>3</dd><dt><span>carrier_freq :</span></dt><dd>0.85</dd><dt><span>carrier_offset :</span></dt><dd>0</dd><dt><span>carrier_phase :</span></dt><dd>0</dd><dt><span>channel_in_use :</span></dt><dd>1</dd><dt><span>cmot_final_current :</span></dt><dd>0.65</dd><dt><span>cmot_hold :</span></dt><dd>0.06</dd><dt><span>cmot_initial_current :</span></dt><dd>0.18</dd><dt><span>compX_current :</span></dt><dd>0</dd><dt><span>compX_current_sg :</span></dt><dd>0.0</dd><dt><span>compX_initial_current :</span></dt><dd>0</dd><dt><span>compY_current :</span></dt><dd>0</dd><dt><span>compY_current_sg :</span></dt><dd>0.0</dd><dt><span>compY_final_current :</span></dt><dd>0</dd><dt><span>compY_initial_current :</span></dt><dd>0</dd><dt><span>compZ_current :</span></dt><dd>0</dd><dt><span>compZ_current_sg :</span></dt><dd>0.189</dd><dt><span>compZ_final_current :</span></dt><dd>0.264</dd><dt><span>compZ_initial_current :</span></dt><dd>0</dd><dt><span>default_camera :</span></dt><dd>0</dd><dt><span>deltaf :</span></dt><dd>0.161</dd><dt><span>evap_1_arm_1_final_pow :</span></dt><dd>0.35</dd><dt><span>evap_1_arm_1_mod_depth_final :</span></dt><dd>0</dd><dt><span>evap_1_arm_1_mod_depth_initial :</span></dt><dd>1.0</dd><dt><span>evap_1_arm_1_mod_ramp_duration :</span></dt><dd>1.15</dd><dt><span>evap_1_arm_1_pow_ramp_duration :</span></dt><dd>1.65</dd><dt><span>evap_1_arm_1_start_pow :</span></dt><dd>7</dd><dt><span>evap_1_arm_2_final_pow :</span></dt><dd>5</dd><dt><span>evap_1_arm_2_ramp_duration :</span></dt><dd>0.5</dd><dt><span>evap_1_arm_2_start_pow :</span></dt><dd>0</dd><dt><span>evap_1_mod_ramp_trunc_value :</span></dt><dd>1</dd><dt><span>evap_1_pow_ramp_trunc_value :</span></dt><dd>1.0</dd><dt><span>evap_1_rate_constant_1 :</span></dt><dd>0.525</dd><dt><span>evap_1_rate_constant_2 :</span></dt><dd>0.51</dd><dt><span>evap_2_arm_1_final_pow :</span></dt><dd>0.037</dd><dt><span>evap_2_arm_1_start_pow :</span></dt><dd>0.35</dd><dt><span>evap_2_arm_2_final_pow :</span></dt><dd>0.09</dd><dt><span>evap_2_arm_2_start_pow :</span></dt><dd>5</dd><dt><span>evap_2_ramp_duration :</span></dt><dd>1.0</dd><dt><span>evap_2_ramp_trunc_value :</span></dt><dd>1.0</dd><dt><span>evap_2_rate_constant_1 :</span></dt><dd>0.37</dd><dt><span>evap_2_rate_constant_2 :</span></dt><dd>0.71</dd><dt><span>evap_3_arm_1_final_pow :</span></dt><dd>0.1038</dd><dt><span>evap_3_arm_1_mod_depth_final :</span></dt><dd>0.43</dd><dt><span>evap_3_arm_1_mod_depth_initial :</span></dt><dd>0</dd><dt><span>evap_3_arm_1_start_pow :</span></dt><dd>0.037</dd><dt><span>evap_3_ramp_duration :</span></dt><dd>0.1</dd><dt><span>evap_3_ramp_trunc_value :</span></dt><dd>1.0</dd><dt><span>evap_3_rate_constant_1 :</sp
" 0.002 0.004 0.006 0.008 0.01 0.012 0.014 0.016 0.018 0.02 0. 0.002\n",
" 0.004 0.006 0.008 0.01 0.012 0.014 0.016 0.018 0.02 ]</dd><dt><span>runs :</span></dt><dd>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 2. 2.\n",
" 2. 2. 2. 2. 2. 2. 2. 2. 2.]</dd><dt><span>scanAxis :</span></dt><dd>['compX_final_current' 'runs']</dd><dt><span>scanAxisLength :</span></dt><dd>[33. 33.]</dd></dl></div></li></ul></div></div>"
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],
"text/plain": [
"<xarray.Dataset>\n",
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"Dimensions: (compX_final_current: 11, runs: 3, y: 1200, x: 1920)\n",
"Coordinates:\n",
" * compX_final_current (compX_final_current) float64 0.0 0.002 ... 0.018 0.02\n",
" * runs (runs) float64 0.0 1.0 2.0\n",
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"Dimensions without coordinates: y, x\n",
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"Data variables:\n",
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" atoms (compX_final_current, runs, y, x) uint16 dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray>\n",
" background (compX_final_current, runs, y, x) uint16 dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray>\n",
" dark (compX_final_current, runs, y, x) uint16 dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray>\n",
" shotNum (compX_final_current, runs) <U2 dask.array<chunksize=(11, 3), meta=np.ndarray>\n",
" OD (compX_final_current, runs, y, x) float64 dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray>\n",
"Attributes: (12/120)\n",
" TOF_free: 0.022\n",
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" abs_img_freq: 110.858\n",
" absorption_imaging_flag: True\n",
" backup_data: True\n",
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" blink_off_time: 0.001\n",
" blink_on_time: 0.001\n",
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" ... ...\n",
" z_offset: 0.189\n",
" z_offset_img: 0.189\n",
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" compX_final_current: [0. 0.002 0.004 0.006 0.008 0.01 0...\n",
" runs: [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 1...\n",
" scanAxis: ['compX_final_current' 'runs']\n",
" scanAxisLength: [33. 33.]"
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]
},
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"execution_count": 37,
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"metadata": {},
"output_type": "execute_result"
}
],
"source": [
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"shotNum = \"0069\"\n",
"filePath = folderPath + \"/\" + shotNum + \"/*.h5\"\n",
"# filePath = \"//DyLabNAS/Data/Evaporative_Cooling/2023/05/12/0065/*.h5\"\n",
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"# filePath = './result_from_experiment/2023-04-24/0013/2023-04-24_0013_Evaporative_Cooling_08.h5'\n",
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"\n",
"dataSetDict = {\n",
" dskey[groupList[i]]: read_hdf5_file(filePath, groupList[i])\n",
" for i in [0] # range(len(groupList))\n",
"}\n",
"\n",
"dataSet = dataSetDict[\"camera_1\"]\n",
"dataSet = swap_xy(dataSet)\n",
"\n",
"scanAxis = get_scanAxis(dataSet)\n",
"\n",
"dataSet = auto_rechunk(dataSet)\n",
"\n",
"dataSet = imageAnalyser.get_absorption_images(dataSet)\n",
"\n",
"dataSet"
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]
},
{
"cell_type": "code",
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"execution_count": 43,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(11, 3)"
]
},
"execution_count": 43,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dataSet.shotNum.shape"
]
},
{
"cell_type": "code",
"execution_count": 16,
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"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
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"['atoms', 'background', 'dark', 'shotNum', 'OD']"
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]
},
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"execution_count": 16,
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"metadata": {},
"output_type": "execute_result"
}
],
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"source": [
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"list(dataSet.data_vars)"
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]
},
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{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## Calculate an plot OD images"
]
},
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{
"cell_type": "code",
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"execution_count": 34,
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"metadata": {},
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"outputs": [
{
"data": {
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"image/png": "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
"text/plain": [
"<Figure size 3400x900 with 34 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# imageAnalyser.center = (960, 1040)\n",
"# imageAnalyser.span = (100, 100)\n",
"# imageAnalyser.fraction = (0.1, 0.1)\n",
"\n",
"imageAnalyser.center = (960, 875)\n",
"imageAnalyser.span = (300, 300)\n",
"imageAnalyser.fraction = (0.1, 0.1)\n",
"\n",
"dataSet_cropOD = imageAnalyser.crop_image(dataSet.OD)\n",
"dataSet_cropOD = imageAnalyser.substract_offset(dataSet_cropOD).load()\n",
"\n",
"dataSet_cropOD.plot.pcolormesh(cmap='jet', vmin=0, col=scanAxis[0], row=scanAxis[1])\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 62,
"metadata": {},
"outputs": [
{
"data": {
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2023-06-13 18:16:24 +02:00
"</style><pre class='xr-text-repr-fallback'><xarray.Dataset>\n",
"Dimensions: (compX_final_current: 11, runs: 3, y: 1200, x: 1920)\n",
"Coordinates:\n",
" * compX_final_current (compX_final_current) float64 0.0 0.002 ... 0.018 0.02\n",
" * runs (runs) float64 0.0 1.0 2.0\n",
2023-06-09 18:59:56 +02:00
"Dimensions without coordinates: y, x\n",
2023-06-13 18:16:24 +02:00
"Data variables:\n",
" atoms (compX_final_current, runs, y, x) uint16 dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray>\n",
" background (compX_final_current, runs, y, x) uint16 dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray>\n",
" dark (compX_final_current, runs, y, x) uint16 dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray>\n",
" shotNum (compX_final_current, runs) <U2 '00' '11' ... '21' '32'\n",
" OD (compX_final_current, runs, y, x) float64 dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray>\n",
"Attributes: (12/120)\n",
" TOF_free: 0.022\n",
2023-06-09 18:59:56 +02:00
" abs_img_freq: 110.858\n",
" absorption_imaging_flag: True\n",
2023-06-13 18:16:24 +02:00
" backup_data: True\n",
" blink_off_time: 0.001\n",
" blink_on_time: 0.001\n",
2023-06-09 18:59:56 +02:00
" ... ...\n",
2023-06-13 18:16:24 +02:00
" z_offset: 0.189\n",
" z_offset_img: 0.189\n",
" compX_final_current: [0. 0.002 0.004 0.006 0.008 0.01 0...\n",
" runs: [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 1...\n",
" scanAxis: ['compX_final_current' 'runs']\n",
" scanAxisLength: [33. 33.]</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-77336239-9c8d-47a1-a385-6bac244b6801' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-77336239-9c8d-47a1-a385-6bac244b6801' 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'>compX_final_current</span>: 11</li><li><span class='xr-has-index'>runs</span>: 3</li><li><span>y</span>: 1200</li><li><span>x</span>: 1920</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-75e6eb94-35eb-498f-886e-8a22c17a4c2c' class='xr-section-summary-in' type='checkbox' checked><label for='section-75e6eb94-35eb-498f-886e-8a22c17a4c2c' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>compX_final_current</span></div><div class='xr-var-dims'>(compX_final_current)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.002 0.004 ... 0.018 0.02</div><input id='attrs-53ed74a7-662f-46e0-a552-2b043c87d3ec' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-53ed74a7-662f-46e0-a552-2b043c87d3ec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-531cb325-0f5c-4755-aac8-bde0c9e00232' class='xr-var-data-in' type='checkbox'><label for='data-531cb325-0f5c-4755-aac8-bde0c9e00232' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0. , 0.002, 0.004, 0.006, 0.008, 0.01 , 0.012, 0.014, 0.016, 0.018,\n",
" 0.02 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>runs</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.0 2.0</div><input id='attrs-4eecfeff-6145-4954-ab29-2e80a2757f08' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4eecfeff-6145-4954-ab29-2e80a2757f08' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4dcc5bdd-fe41-4e2e-8864-f55baa38c51d' class='xr-var-data-in' type='checkbox'><label for='data-4dcc5bdd-fe41-4e2e-8864-f55baa38c51d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0., 1., 2.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-783fd9eb-a696-42be-b25d-97f7f9c60b7f' class='xr-section-summary-in' type='checkbox' checked><label for='section-783fd9eb-a696-42be-b25d-97f7f9c60b7f' class='xr-section-summary' >Data variables: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>atoms</span></div><div class='xr-var-dims'>(compX_final_current, runs, y, x)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray></div><input id='attrs-4821195f-4f05-486b-9411-349f3e7385e4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4821195f-4f05-486b-9411-349f3e7385e4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0101606-0850-4561-8732-b4f92cc2eac3' class='xr-var-data-in' type='checkbox'><label for='data-f0101606-0850-4561-8732-b4f92cc2eac3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>IMAGE_SUBCLASS :</span></dt><dd>IMAGE_GRAYSCALE</dd><dt><span>IMAGE_VERSION :</span></dt><dd>1.2</dd><dt><span>IMAGE_WHITE_IS_ZERO :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><table>\n",
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" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 145.02 MiB </td>\n",
" <td> 118.65 MiB </td>\n",
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" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (11, 3, 1200, 1920) </td>\n",
" <td> (9, 3, 1200, 1920) </td>\n",
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" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 2 chunks in 104 graph layers </td>\n",
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" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> uint16 numpy.ndarray </td>\n",
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" </td>\n",
" </tr>\n",
"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>background</span></div><div class='xr-var-dims'>(compX_final_current, runs, y, x)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray></div><input id='attrs-4abb3c1a-cb23-4355-bd7c-d3853cda84ec' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4abb3c1a-cb23-4355-bd7c-d3853cda84ec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-40c897e9-652f-454c-90e7-0f9f74ee6bb7' class='xr-var-data-in' type='checkbox'><label for='data-40c897e9-652f-454c-90e7-0f9f74ee6bb7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>IMAGE_SUBCLASS :</span></dt><dd>IMAGE_GRAYSCALE</dd><dt><span>IMAGE_VERSION :</span></dt><dd>1.2</dd><dt><span>IMAGE_WHITE_IS_ZERO :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 145.02 MiB </td>\n",
" <td> 118.65 MiB </td>\n",
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" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (11, 3, 1200, 1920) </td>\n",
" <td> (9, 3, 1200, 1920) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 2 chunks in 104 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> uint16 numpy.ndarray </td>\n",
" </tr>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dark</span></div><div class='xr-var-dims'>(compX_final_current, runs, y, x)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray></div><input id='attrs-7390e04c-0fd6-48f8-8580-8834195dbe7e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7390e04c-0fd6-48f8-8580-8834195dbe7e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ab051997-0ff5-4e81-843f-7dbaea98263f' class='xr-var-data-in' type='checkbox'><label for='data-ab051997-0ff5-4e81-843f-7dbaea98263f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>IMAGE_SUBCLASS :</span></dt><dd>IMAGE_GRAYSCALE</dd><dt><span>IMAGE_VERSION :</span></dt><dd>1.2</dd><dt><span>IMAGE_WHITE_IS_ZERO :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 145.02 MiB </td>\n",
" <td> 118.65 MiB </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (11, 3, 1200, 1920) </td>\n",
" <td> (9, 3, 1200, 1920) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 2 chunks in 104 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> uint16 numpy.ndarray </td>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>shotNum</span></div><div class='xr-var-dims'>(compX_final_current, runs)</div><div class='xr-var-dtype'><U2</div><div class='xr-var-preview xr-preview'>'00' '11' '22' ... '10' '21' '32'</div><input id='attrs-397b696e-dd93-40c7-8250-86e04be05206' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-397b696e-dd93-40c7-8250-86e04be05206' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-50b2c6cd-1dbc-40fa-8536-be726de7466e' class='xr-var-data-in' type='checkbox'><label for='data-50b2c6cd-1dbc-40fa-8536-be726de7466e' 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([['00', '11', '22'],\n",
" ['01', '12', '23'],\n",
" ['02', '13', '24'],\n",
" ['03', '14', '25'],\n",
" ['04', '15', '26'],\n",
" ['05', '16', '27'],\n",
" ['06', '17', '28'],\n",
" ['07', '18', '29'],\n",
" ['08', '19', '30'],\n",
" ['09', '20', '31'],\n",
" ['10', '21', '32']], dtype='<U2')</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>OD</span></div><div class='xr-var-dims'>(compX_final_current, runs, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray></div><input id='attrs-842ec245-f37c-4171-b60d-760ac687862a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-842ec245-f37c-4171-b60d-760ac687862a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e1e8c99-712f-4713-b6f9-94f156c595b5' class='xr-var-data-in' type='checkbox'><label for='data-5e1e8c99-712f-4713-b6f9-94f156c595b5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>IMAGE_SUBCLASS :</span></dt><dd>IMAGE_GRAYSCALE</dd><dt><span>IMAGE_VERSION :</span></dt><dd>1.2</dd><dt><span>IMAGE_WHITE_IS_ZERO :</span></dt><dd>0</dd><dt><span>TOF_free :</span></dt><dd>0.022</dd><dt><span>abs_img_freq :</span></dt><dd>110.858</dd><dt><span>absorption_imaging_flag :</span></dt><dd>True</dd><dt><span>backup_data :</span></dt><dd>True</dd><dt><span>blink_off_time :</span></dt><dd>0.001</dd><dt><span>blink_on_time :</span></dt><dd>0.001</dd><dt><span>c_duration :</span></dt><dd>0.2</dd><dt><span>carrier_amp :</span></dt><dd>3</dd><dt><span>carrier_freq :</span></dt><dd>0.85</dd><dt><span>carrier_offset :</span></dt><dd>0</dd><dt><span>carrier_phase :</span></dt><dd>0</dd><dt><span>channel_in_use :</span></dt><dd>1</dd><dt><span>cmot_final_current :</span></dt><dd>0.65</dd><dt><span>cmot_hold :</span></dt><dd>0.06</dd><dt><span>cmot_initial_current :</span></dt><dd>0.18</dd><dt><span>compX_current :</span></dt><dd>0</dd><dt><span>compX_current_sg :</span></dt><dd>0.0</dd><dt><span>compX_initial_current :</span></dt><dd>0</dd><dt><span>compY_current :</span></dt><dd>0</dd><dt><span>compY_current_sg :</span></dt><dd>0.0</dd><dt><span>compY_final_current :</span></dt><dd>0</dd><dt><span>compY_initial_current :</span></dt><dd>0</dd><dt><span>compZ_current :</span></dt><dd>0</dd><dt><span>compZ_current_sg :</span></dt><dd>0.189</dd><dt><span>compZ_final_current :</span></dt><dd>0.264</dd><dt><span>compZ_initial_current :</span></dt><dd>0</dd><dt><span>default_camera :</span></dt><dd>0</dd><dt><span>deltaf :</span></dt><dd>0.161</dd><dt><span>evap_1_arm_1_final_pow :</span></dt><dd>0.35</dd><dt><span>evap_1_arm_1_mod_depth_final :</span></dt><dd>0</dd><dt><span>evap_1_arm_1_mod_depth_initial :</span></dt><dd>1.0</dd><dt><span>evap_1_arm_1_mod_ramp_duration :</span></dt><dd>1.15</dd><dt><span>evap_1_arm_1_pow_ramp_duration :</span></dt><dd>1.65</dd><dt><span>evap_1_arm_1_start_pow :</span></dt><dd>7</dd><dt><span>evap_1_arm_2_final_pow :</span></dt><dd>5</dd><dt><span>evap_1_arm_2_ramp_duration :</span></dt><dd>0.5</dd><dt><span>evap_1_arm_2_start_pow :</span></dt><dd>0</dd><dt><span>evap_1_mod_ramp_trunc_value :</span></dt><dd>1</dd><dt><span>evap_1_pow_ramp_trunc_value :</span></dt><dd>1.0</dd><dt><span>evap_1_rate_constant_1 :</span></dt><dd>0.525</dd><dt><span>evap_1_rate_constant_2 :</span></dt><dd>0.51</dd><dt><span>evap_2_arm_1_final_pow :</span></dt><dd>0.037</dd><dt><span>evap_2_arm_1_start_pow :</span></dt><dd>0.35</dd><dt><span>evap_2_arm_2_final_pow :</span></dt><dd>0.09</dd><dt><span>evap_2_arm_2_start_pow :</span></dt><dd>5</dd><dt><span>evap_2_ramp_duration :</span></dt><dd>1.0</dd><dt><span>evap_2_ramp_trunc_value :</span></dt><dd>1.0</dd><dt><span>evap_2_rate_constant_1 :</span></dt><dd>0.37</dd><dt><span>evap_2_rate_constant_2 :</span></dt><dd>0.71</dd><dt><span>evap_3_arm_1_final_pow :</span></dt><dd>0.1038</dd><dt><span>evap_3_arm_1_mod_depth_final :</span></dt><dd>0.43</dd><dt><span>evap_3_arm_1_mod_depth_initial :</span></dt><dd>0</dd><dt><span>evap_3_arm_1_start_pow :</span></dt><dd>0.037</dd><dt><span>evap_3_ramp_duration
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},
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"dataSet"
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{
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"execution_count": 46,
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{
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"text/plain": [
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"('compX_final_current', 'runs')"
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"execution_count": 102,
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" 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: (y: 1200, x: 1920, z: 33)\n",
"Coordinates:\n",
" * z (z) object MultiIndex\n",
" * compX_final_current (z) float64 0.0 0.0 0.0 0.002 ... 0.018 0.02 0.02 0.02\n",
" * runs (z) float64 0.0 1.0 2.0 0.0 1.0 ... 1.0 2.0 0.0 1.0 2.0\n",
"Dimensions without coordinates: y, x\n",
"Data variables:\n",
" atoms (y, x, z) uint16 dask.array<chunksize=(1200, 1920, 27), meta=np.ndarray>\n",
" background (y, x, z) uint16 dask.array<chunksize=(1200, 1920, 27), meta=np.ndarray>\n",
" dark (y, x, z) uint16 dask.array<chunksize=(1200, 1920, 27), meta=np.ndarray>\n",
" shotNum (z) <U2 '00' '11' '22' '01' ... '31' '10' '21' '32'\n",
" OD (y, x, z) float64 dask.array<chunksize=(1200, 1920, 27), meta=np.ndarray>\n",
"Attributes: (12/120)\n",
" TOF_free: 0.022\n",
" abs_img_freq: 110.858\n",
" absorption_imaging_flag: True\n",
" backup_data: True\n",
" blink_off_time: 0.001\n",
" blink_on_time: 0.001\n",
" ... ...\n",
" z_offset: 0.189\n",
" z_offset_img: 0.189\n",
" compX_final_current: [0. 0.002 0.004 0.006 0.008 0.01 0...\n",
" runs: [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 1...\n",
" scanAxis: ['compX_final_current' 'runs']\n",
" scanAxisLength: [33. 33.]</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-59519555-73ef-4d1d-8e30-a662b6f4df5f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-59519555-73ef-4d1d-8e30-a662b6f4df5f' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>y</span>: 1200</li><li><span>x</span>: 1920</li><li><span class='xr-has-index'>z</span>: 33</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-4f925aea-83cf-4fb6-be15-855a5b5ad8b7' class='xr-section-summary-in' type='checkbox' checked><label for='section-4f925aea-83cf-4fb6-be15-855a5b5ad8b7' class='xr-section-summary' >Coordinates: <span>(3)</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'>z</span></div><div class='xr-var-dims'>(z)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>MultiIndex</div><input id='attrs-b38666d5-5964-455d-b816-608bd93be5c8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b38666d5-5964-455d-b816-608bd93be5c8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-25d5bbd7-8faf-4de2-8458-f3c1b8aaf5d9' class='xr-var-data-in' type='checkbox'><label for='data-25d5bbd7-8faf-4de2-8458-f3c1b8aaf5d9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([(0.0, 0.0), (0.0, 1.0), (0.0, 2.0), (0.002, 0.0), (0.002, 1.0),\n",
" (0.002, 2.0), (0.004, 0.0), (0.004, 1.0), (0.004, 2.0), (0.006, 0.0),\n",
" (0.006, 1.0), (0.006, 2.0), (0.008, 0.0), (0.008, 1.0), (0.008, 2.0),\n",
" (0.01, 0.0), (0.01, 1.0), (0.01, 2.0), (0.012, 0.0), (0.012, 1.0),\n",
" (0.012, 2.0), (0.014, 0.0), (0.014, 1.0), (0.014, 2.0), (0.016, 0.0),\n",
" (0.016, 1.0), (0.016, 2.0), (0.018, 0.0), (0.018, 1.0), (0.018, 2.0),\n",
" (0.02, 0.0), (0.02, 1.0), (0.02, 2.0)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>compX_final_current</span></div><div class='xr-var-dims'>(z)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 ... 0.02 0.02 0.02</div><input id='attrs-b460d9c3-e240-4c9c-a3ff-f766a6344231' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b460d9c3-e240-4c9c-a3ff-f766a6344231' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb44c072-c7a6-4803-9608-bc722c37f4a6' class='xr-var-data-in' type='checkbox'><label for='data-bb44c072-c7a6-4803-9608-bc722c37f4a6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0. , 0. , 0. , 0.002, 0.002, 0.002, 0.004, 0.004, 0.004, 0.006,\n",
" 0.006, 0.006, 0.008, 0.008, 0.008, 0.01 , 0.01 , 0.01 , 0.012, 0.012,\n",
" 0.012, 0.014, 0.014, 0.014, 0.016, 0.016, 0.016, 0.018, 0.018, 0.018,\n",
" 0.02 , 0.02 , 0.02 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>runs</span></div><div class='xr-var-dims'>(z)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.0 2.0 0.0 ... 2.0 0.0 1.0 2.0</div><input id='attrs-0b5dbf07-2684-405d-84aa-610bac3fee98' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0b5dbf07-2684-405d-84aa-610bac3fee98' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66b2eddb-a50d-454b-822b-775e28468e33' class='xr-var-data-in' type='checkbox'><label for='data-66b2eddb-a50d-454b-822b-775e28468e33' 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., 0., 1., 2., 0., 1., 2., 0., 1., 2., 0., 1., 2., 0., 1., 2.,\n",
" 0., 1., 2., 0., 1., 2., 0., 1., 2., 0., 1., 2., 0., 1., 2.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-bdecf554-b3e0-4f43-9ee9-4e622255c04d' class='xr-section-summary-in' type='checkbox' checked><label for='section-bdecf554-b3e0-4f43-9ee9-4e622255c04d' class='xr-section-summary' >Data variables: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>atoms</span></div><div class='xr-var-dims'>(y, x, z)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1200, 1920, 27), meta=np.ndarray></div><input id='attrs-94ac09d2-42e2-4bdf-9061-582dde4470ae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-94ac09d2-42e2-4bdf-9061-582dde4470ae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3f29e441-215e-4aa4-898d-55c6323adc58' class='xr-var-data-in' type='checkbox'><label for='data-3f29e441-215e-4aa4-898d-55c6323adc58' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>IMAGE_SUBCLASS :</span></dt><dd>IMAGE_GRAYSCALE</dd><dt><span>IMAGE_VERSION :</span></dt><dd>1.2</dd><dt><span>IMAGE_WHITE_IS_ZERO :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 145.02 MiB </td>\n",
" <td> 118.65 MiB </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (1200, 1920, 33) </td>\n",
" <td> (1200, 1920, 27) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 2 chunks in 106 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> uint16 numpy.ndarray </td>\n",
" </tr>\n",
" </tbody>\n",
" </table>\n",
" </td>\n",
" <td>\n",
" <svg width=\"132\" height=\"214\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
"\n",
" <!-- Horizontal lines -->\n",
" <line x1=\"10\" y1=\"0\" x2=\"54\" y2=\"44\" style=\"stroke-width:2\" />\n",
" <line x1=\"10\" y1=\"120\" x2=\"54\" y2=\"164\" style=\"stroke-width:2\" />\n",
"\n",
" <!-- Vertical lines -->\n",
" <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"120\" style=\"stroke-width:2\" />\n",
" <line x1=\"54\" y1=\"44\" x2=\"54\" y2=\"164\" style=\"stroke-width:2\" />\n",
"\n",
" <!-- Colored Rectangle -->\n",
" <polygon points=\"10.0,0.0 54.11764705882353,44.11764705882353 54.11764705882353,164.11764705882354 10.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
"\n",
" <!-- Horizontal lines -->\n",
" <line x1=\"10\" y1=\"0\" x2=\"38\" y2=\"0\" style=\"stroke-width:2\" />\n",
" <line x1=\"54\" y1=\"44\" x2=\"82\" y2=\"44\" style=\"stroke-width:2\" />\n",
"\n",
" <!-- Vertical lines -->\n",
" <line x1=\"10\" y1=\"0\" x2=\"54\" y2=\"44\" style=\"stroke-width:2\" />\n",
" <line x1=\"33\" y1=\"0\" x2=\"77\" y2=\"44\" />\n",
" <line x1=\"38\" y1=\"0\" x2=\"82\" y2=\"44\" style=\"stroke-width:2\" />\n",
"\n",
" <!-- Colored Rectangle -->\n",
" <polygon points=\"10.0,0.0 38.19037141100563,0.0 82.30801846982916,44.11764705882353 54.11764705882353,44.11764705882353\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
"\n",
" <!-- Horizontal lines -->\n",
" <line x1=\"54\" y1=\"44\" x2=\"82\" y2=\"44\" style=\"stroke-width:2\" />\n",
" <line x1=\"54\" y1=\"164\" x2=\"82\" y2=\"164\" style=\"stroke-width:2\" />\n",
"\n",
" <!-- Vertical lines -->\n",
" <line x1=\"54\" y1=\"44\" x2=\"54\" y2=\"164\" style=\"stroke-width:2\" />\n",
" <line x1=\"77\" y1=\"44\" x2=\"77\" y2=\"164\" />\n",
" <line x1=\"82\" y1=\"44\" x2=\"82\" y2=\"164\" style=\"stroke-width:2\" />\n",
"\n",
" <!-- Colored Rectangle -->\n",
" <polygon points=\"54.11764705882353,44.11764705882353 82.30801846982916,44.11764705882353 82.30801846982916,164.11764705882354 54.11764705882353,164.11764705882354\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
"\n",
" <!-- Text -->\n",
" <text x=\"68.212833\" y=\"184.117647\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >33</text>\n",
" <text x=\"102.308018\" y=\"104.117647\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,102.308018,104.117647)\">1920</text>\n",
" <text x=\"22.058824\" y=\"162.058824\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,22.058824,162.058824)\">1200</text>\n",
"</svg>\n",
" </td>\n",
" </tr>\n",
"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>background</span></div><div class='xr-var-dims'>(y, x, z)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1200, 1920, 27), meta=np.ndarray></div><input id='attrs-8633baad-b13b-44bd-a2d7-8963f30771ef' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8633baad-b13b-44bd-a2d7-8963f30771ef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ae237264-0f01-4589-a05f-84fc44f8d85d' class='xr-var-data-in' type='checkbox'><label for='data-ae237264-0f01-4589-a05f-84fc44f8d85d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>IMAGE_SUBCLASS :</span></dt><dd>IMAGE_GRAYSCALE</dd><dt><span>IMAGE_VERSION :</span></dt><dd>1.2</dd><dt><span>IMAGE_WHITE_IS_ZERO :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 145.02 MiB </td>\n",
" <td> 118.65 MiB </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (1200, 1920, 33) </td>\n",
" <td> (1200, 1920, 27) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 2 chunks in 106 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> uint16 numpy.ndarray </td>\n",
" </tr>\n",
" </tbody>\n",
" </table>\n",
" </td>\n",
" <td>\n",
" <svg width=\"132\" height=\"214\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
"\n",
" <!-- Horizontal lines -->\n",
" <line x1=\"10\" y1=\"0\" x2=\"54\" y2=\"44\" style=\"stroke-width:2\" />\n",
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"\n",
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"</svg>\n",
" </td>\n",
" </tr>\n",
"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dark</span></div><div class='xr-var-dims'>(y, x, z)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1200, 1920, 27), meta=np.ndarray></div><input id='attrs-87a98a5b-c62f-4d68-b536-54a566d34489' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-87a98a5b-c62f-4d68-b536-54a566d34489' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5381390c-1c46-4836-be95-a5d7f2233f09' class='xr-var-data-in' type='checkbox'><label for='data-5381390c-1c46-4836-be95-a5d7f2233f09' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>IMAGE_SUBCLASS :</span></dt><dd>IMAGE_GRAYSCALE</dd><dt><span>IMAGE_VERSION :</span></dt><dd>1.2</dd><dt><span>IMAGE_WHITE_IS_ZERO :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 145.02 MiB </td>\n",
" <td> 118.65 MiB </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (1200, 1920, 33) </td>\n",
" <td> (1200, 1920, 27) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 2 chunks in 106 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> uint16 numpy.ndarray </td>\n",
" </tr>\n",
" </tbody>\n",
" </table>\n",
" </td>\n",
" <td>\n",
" <svg width=\"132\" height=\"214\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
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" <!-- Horizontal lines -->\n",
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"\n",
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"\n",
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"\n",
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" <text x=\"22.058824\" y=\"162.058824\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,22.058824,162.058824)\">1200</text>\n",
"</svg>\n",
" </td>\n",
" </tr>\n",
"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>shotNum</span></div><div class='xr-var-dims'>(z)</div><div class='xr-var-dtype'><U2</div><div class='xr-var-preview xr-preview'>'00' '11' '22' ... '10' '21' '32'</div><input id='attrs-9a4bbaac-fa18-4aba-8742-99639b304c0a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9a4bbaac-fa18-4aba-8742-99639b304c0a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c884c2e-e8f6-4907-8acf-4c92591ba581' class='xr-var-data-in' type='checkbox'><label for='data-3c884c2e-e8f6-4907-8acf-4c92591ba581' 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(['00', '11', '22', '01', '12', '23', '02', '13', '24', '03', '14',\n",
" '25', '04', '15', '26', '05', '16', '27', '06', '17', '28', '07',\n",
" '18', '29', '08', '19', '30', '09', '20', '31', '10', '21', '32'],\n",
" dtype='<U2')</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>OD</span></div><div class='xr-var-dims'>(y, x, z)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1200, 1920, 27), meta=np.ndarray></div><input id='attrs-ba7ccae9-a367-4275-b4ce-407bbb5974e9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ba7ccae9-a367-4275-b4ce-407bbb5974e9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-149c75d9-ec4c-4a4b-9313-9445c694c2c0' class='xr-var-data-in' type='checkbox'><label for='data-149c75d9-ec4c-4a4b-9313-9445c694c2c0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>IMAGE_SUBCLASS :</span></dt><dd>IMAGE_GRAYSCALE</dd><dt><span>IMAGE_VERSION :</span></dt><dd>1.2</dd><dt><span>IMAGE_WHITE_IS_ZERO :</span></dt><dd>0</dd><dt><span>TOF_free :</span></dt><dd>0.022</dd><dt><span>abs_img_freq :</span></dt><dd>110.858</dd><dt><span>absorption_imaging_flag :</span></dt><dd>True</dd><dt><span>backup_data :</span></dt><dd>True</dd><dt><span>blink_off_time :</span></dt><dd>0.001</dd><dt><span>blink_on_time :</span></dt><dd>0.001</dd><dt><span>c_duration :</span></dt><dd>0.2</dd><dt><span>carrier_amp :</span></dt><dd>3</dd><dt><span>carrier_freq :</span></dt><dd>0.85</dd><dt><span>carrier_offset :</span></dt><dd>0</dd><dt><span>carrier_phase :</span></dt><dd>0</dd><dt><span>channel_in_use :</span></dt><dd>1</dd><dt><span>cmot_final_current :</span></dt><dd>0.65</dd><dt><span>cmot_hold :</span></dt><dd>0.06</dd><dt><span>cmot_initial_current :</span></dt><dd>0.18</dd><dt><span>compX_current :</span></dt><dd>0</dd><dt><span>compX_current_sg :</span></dt><dd>0.0</dd><dt><span>compX_initial_current :</span></dt><dd>0</dd><dt><span>compY_current :</span></dt><dd>0</dd><dt><span>compY_current_sg :</span></dt><dd>0.0</dd><dt><span>compY_final_current :</span></dt><dd>0</dd><dt><span>compY_initial_current :</span></dt><dd>0</dd><dt><span>compZ_current :</span></dt><dd>0</dd><dt><span>compZ_current_sg :</span></dt><dd>0.189</dd><dt><span>compZ_final_current :</span></dt><dd>0.264</dd><dt><span>compZ_initial_current :</span></dt><dd>0</dd><dt><span>default_camera :</span></dt><dd>0</dd><dt><span>deltaf :</span></dt><dd>0.161</dd><dt><span>evap_1_arm_1_final_pow :</span></dt><dd>0.35</dd><dt><span>evap_1_arm_1_mod_depth_final :</span></dt><dd>0</dd><dt><span>evap_1_arm_1_mod_depth_initial :</span></dt><dd>1.0</dd><dt><span>evap_1_arm_1_mod_ramp_duration :</span></dt><dd>1.15</dd><dt><span>evap_1_arm_1_pow_ramp_duration :</span></dt><dd>1.65</dd><dt><span>evap_1_arm_1_start_pow :</span></dt><dd>7</dd><dt><span>evap_1_arm_2_final_pow :</span></dt><dd>5</dd><dt><span>evap_1_arm_2_ramp_duration :</span></dt><dd>0.5</dd><dt><span>evap_1_arm_2_start_pow :</span></dt><dd>0</dd><dt><span>evap_1_mod_ramp_trunc_value :</span></dt><dd>1</dd><dt><span>evap_1_pow_ramp_trunc_value :</span></dt><dd>1.0</dd><dt><span>evap_1_rate_constant_1 :</span></dt><dd>0.525</dd><dt><span>evap_1_rate_constant_2 :</span></dt><dd>0.51</dd><dt><span>evap_2_arm_1_final_pow :</span></dt><dd>0.037</dd><dt><span>evap_2_arm_1_start_pow :</span></dt><dd>0.35</dd><dt><span>evap_2_arm_2_final_pow :</span></dt><dd>0.09</dd><dt><span>evap_2_arm_2_start_pow :</span></dt><dd>5</dd><dt><span>evap_2_ramp_duration :</span></dt><dd>1.0</dd><dt><span>evap_2_ramp_trunc_value :</span></dt><dd>1.0</dd><dt><span>evap_2_rate_constant_1 :</span></dt><dd>0.37</dd><dt><span>evap_2_rate_constant_2 :</span></dt><dd>0.71</dd><dt><span>evap_3_arm_1_final_pow :</span></dt><dd>0.1038</dd><dt><span>evap_3_arm_1_mod_depth_final :</span></dt><dd>0.43</dd><dt><span>evap_3_arm_1_mod_depth_initial :</span></dt><dd>0</dd><dt><span>evap_3_arm_1_start_pow :</span></dt><dd>0.037</dd><dt><span>evap_3_ramp_duration :</span></dt><dd>0.1</dd><dt><span>evap_3_ramp_trunc_value :</span></dt><dd>1.
" 0.002 0.004 0.006 0.008 0.01 0.012 0.014 0.016 0.018 0.02 0. 0.002\n",
" 0.004 0.006 0.008 0.01 0.012 0.014 0.016 0.018 0.02 ]</dd><dt><span>runs :</span></dt><dd>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 2. 2.\n",
" 2. 2. 2. 2. 2. 2. 2. 2. 2.]</dd><dt><span>scanAxis :</span></dt><dd>['compX_final_current' 'runs']</dd><dt><span>scanAxisLength :</span></dt><dd>[33. 33.]</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 580.08 MiB </td>\n",
" <td> 474.61 MiB </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (1200, 1920, 33) </td>\n",
" <td> (1200, 1920, 27) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 2 chunks in 324 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
" </tr>\n",
" </tbody>\n",
" </table>\n",
" </td>\n",
" <td>\n",
" <svg width=\"132\" height=\"214\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
"\n",
" <!-- Horizontal lines -->\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",
" <!-- Vertical lines -->\n",
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"\n",
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"\n",
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" <text x=\"22.058824\" y=\"162.058824\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,22.058824,162.058824)\">1200</text>\n",
"</svg>\n",
" </td>\n",
" </tr>\n",
"</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-27a9f26f-fc5b-4693-8e95-3c74e24c4d99' class='xr-section-summary-in' type='checkbox' ><label for='section-27a9f26f-fc5b-4693-8e95-3c74e24c4d99' 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>z<br>compX_final_current<br>runs</div></div><div class='xr-index-preview'>PandasMultiIndex</div><div></div><input id='index-ab76463e-130a-49f1-a2b2-c5986e2e1e4e' class='xr-index-data-in' type='checkbox'/><label for='index-ab76463e-130a-49f1-a2b2-c5986e2e1e4e' 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(MultiIndex([( 0.0, 0.0),\n",
" ( 0.0, 1.0),\n",
" ( 0.0, 2.0),\n",
" (0.002, 0.0),\n",
" (0.002, 1.0),\n",
" (0.002, 2.0),\n",
" (0.004, 0.0),\n",
" (0.004, 1.0),\n",
" (0.004, 2.0),\n",
" (0.006, 0.0),\n",
" (0.006, 1.0),\n",
" (0.006, 2.0),\n",
" (0.008, 0.0),\n",
" (0.008, 1.0),\n",
" (0.008, 2.0),\n",
" ( 0.01, 0.0),\n",
" ( 0.01, 1.0),\n",
" ( 0.01, 2.0),\n",
" (0.012, 0.0),\n",
" (0.012, 1.0),\n",
" (0.012, 2.0),\n",
" (0.014, 0.0),\n",
" (0.014, 1.0),\n",
" (0.014, 2.0),\n",
" (0.016, 0.0),\n",
" (0.016, 1.0),\n",
" (0.016, 2.0),\n",
" (0.018, 0.0),\n",
" (0.018, 1.0),\n",
" (0.018, 2.0),\n",
" ( 0.02, 0.0),\n",
" ( 0.02, 1.0),\n",
" ( 0.02, 2.0)],\n",
" name='z'))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e2cdd6a3-d3ed-4b7c-8c32-859c83445a80' class='xr-section-summary-in' type='checkbox' ><label for='section-e2cdd6a3-d3ed-4b7c-8c32-859c83445a80' class='xr-section-summary' >Attributes: <span>(120)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>TOF_free :</span></dt><dd>0.022</dd><dt><span>abs_img_freq :</span></dt><dd>110.858</dd><dt><span>absorption_imaging_flag :</span></dt><dd>True</dd><dt><span>backup_data :</span></dt><dd>True</dd><dt><span>blink_off_time :</span></dt><dd>0.001</dd><dt><span>blink_on_time :</span></dt><dd>0.001</dd><dt><span>c_duration :</span></dt><dd>0.2</dd><dt><span>carrier_amp :</span></dt><dd>3</dd><dt><span>carrier_freq :</span></dt><dd>0.85</dd><dt><span>carrier_offset :</span></dt><dd>0</dd><dt><span>carrier_phase :</span></dt><dd>0</dd><dt><span>channel_in_use :</span></dt><dd>1</dd><dt><span>cmot_final_current :</span></dt><dd>0.65</dd><dt><span>cmot_hold :</span></dt><dd>0.06</dd><dt><span>cmot_initial_current :</span></dt><dd>0.18</dd><dt><span>compX_current :</span></dt><dd>0</dd><dt><span>compX_current_sg :</span></dt><dd>0.0</dd><dt><span>compX_initial_current :</span></dt><dd>0</dd><dt><span>compY_current :</span></dt><dd>0</dd><dt><span>compY_current_sg :</span></dt><dd>0.0</dd><dt><span>compY_final_current :</span></dt><dd>0</dd><dt><span>compY_initial_current :</span></dt><dd>0</dd><dt><span>compZ_current :</span></dt><dd>0</dd><dt><span>compZ_current_sg :</span></dt><dd>0.189</dd><dt><span>compZ_final_current :</span></dt><dd>0.264</dd><dt><span>compZ_initial_current :</span></dt><dd>0</dd><dt><span>default_camera :</span></dt><dd>0</dd><dt><span>deltaf :</span></dt><dd>0.161</dd><dt><span>evap_1_arm_1_final_pow :</span></dt><dd>0.35</dd><dt><span>evap_1_arm_1_mod_depth_final :</span></dt><dd>0</dd><dt><span>evap_1_arm_1_mod_depth_initial :</span></dt><dd>1.0</dd><dt><span>evap_1_arm_1_mod_ramp_duration :</span></dt><dd>1.15</dd><dt><span>evap_1_arm_1_pow_ramp_duration :</span></dt><dd>1.65</dd><dt><span>evap_1_arm_1_start_pow :</span></dt><dd>7</dd><dt><span>evap_1_arm_2_final_pow :</span></dt><dd>5</dd><dt><span>evap_1_arm_2_ramp_duration :</span></dt><dd>0.5</dd><dt><span>evap_1_arm_2_start_pow :</span></dt><dd>0</dd><dt><span>evap_1_mod_ramp_trunc_value :</span></dt><dd>1</dd><dt><span>evap_1_pow_ramp_trunc_value :</span></dt><dd>1.0</dd><dt><span>evap_1_rate_constant_1 :</span></dt><dd>0.525</dd><dt><span>evap_1_rate_constant_2 :</span></dt><dd>0.51</dd><dt><span>evap_2_arm_1_final_pow :</span></dt><dd>0.037</dd><dt><span>evap_2_arm_1_start_pow :</span></dt><dd>0.35</dd><dt><span>evap_2_arm_2_final_pow :</span></dt><dd>0.09</dd><dt><span>evap_2_arm_2_start_pow :</span></dt><dd>5</dd><dt><span>evap_2_ramp_duration :</span></dt><dd>1.0</dd><dt><span>evap_2_ramp_trunc_value :</span></dt><dd>1.0</dd><dt><span>evap_2_rate_constant_1 :</span></dt><dd>0.37</dd><dt><span>evap_2_rate_constant_2 :</span></dt><dd>0.71</dd><dt><span>evap_3_arm_1_final_pow :</span></dt><dd>0.1038</dd><dt><span>evap_3_arm_1_mod_depth_final :</span></dt><dd>0.43</dd><dt><span>evap_3_arm_1_mod_depth_initial :</span></dt><dd>0</dd><dt><span>evap_3_arm_1_start_pow :</span></dt><dd>0.037</dd><dt><span>evap_3_ramp_duration :</span></dt><dd>0.1</dd><dt><span>evap_3_ramp_trunc_value :</span></dt><dd>1.0</dd><dt><span>evap_3_rate_constant_1 :</span></dt><dd>-0.879</dd><dt><span>evap_3_rate_constant_2 :</span></dt><dd>-0.297</dd><dt><span>final_amp :</span></dt><dd>0.00012</dd><dt><span>final_freq :</span></dt><dd>104.0</dd><dt><span>final_pow_1 :</span></dt><dd>0.1038</dd><dt><span>final_pow_2 :</span></dt><dd>0.09</dd><dt><span>gradCoil_current :</span></dt><dd>0.18</dd><dt><span>gradCoil_current_sg :</span></dt><dd>0</dd><dt><span>imaging_method :</span></dt><dd>in_situ_absorption</dd><dt><span>imaging_pulse_duration :</span></dt><dd>2.5e-05</dd><dt><span>imaging_wavelength :</span></dt><dd>4.21291e-07</dd><dt><span>init
" 0.002 0.004 0.006 0.008 0.01 0.012 0.014 0.016 0.018 0.02 0. 0.002\n",
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" blink_off_time: 0.001\n",
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{
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"['compX_final_current', 'runs']"
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" background (compX_final_current, runs, y, x) uint16 dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray>\n",
" dark (compX_final_current, runs, y, x) uint16 dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray>\n",
" shotNum (compX_final_current, runs) <U2 '00' '11' ... '21' '32'\n",
" OD (compX_final_current, runs, y, x) float64 dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray>\n",
"Attributes: (12/120)\n",
" TOF_free: 0.022\n",
" abs_img_freq: 110.858\n",
" absorption_imaging_flag: True\n",
" backup_data: True\n",
" blink_off_time: 0.001\n",
" blink_on_time: 0.001\n",
" ... ...\n",
" z_offset: 0.189\n",
" z_offset_img: 0.189\n",
" compX_final_current: [0.0, 0.002, 0.004, 0.006, 0.008, 0.01...\n",
" runs: [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0....\n",
" scanAxis: ['compX_final_current', 'runs']\n",
" scanAxisLength: [33.0, 33.0]</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-3f9a5bbd-3726-49d5-93dc-cb9a9d130f64' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3f9a5bbd-3726-49d5-93dc-cb9a9d130f64' 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'>compX_final_current</span>: 11</li><li><span class='xr-has-index'>runs</span>: 3</li><li><span>y</span>: 1200</li><li><span>x</span>: 1920</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-8129af36-6065-4f62-bb1a-5837f8bfe066' class='xr-section-summary-in' type='checkbox' checked><label for='section-8129af36-6065-4f62-bb1a-5837f8bfe066' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>compX_final_current</span></div><div class='xr-var-dims'>(compX_final_current)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.002 0.004 ... 0.018 0.02</div><input id='attrs-7ec7e64b-3e82-44b1-8d3d-a05ef3021e23' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7ec7e64b-3e82-44b1-8d3d-a05ef3021e23' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-85f9bd4a-650a-424c-a162-2d81434c4869' class='xr-var-data-in' type='checkbox'><label for='data-85f9bd4a-650a-424c-a162-2d81434c4869' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0. , 0.002, 0.004, 0.006, 0.008, 0.01 , 0.012, 0.014, 0.016, 0.018,\n",
" 0.02 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>runs</span></div><div class='xr-var-dims'>(runs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.0 2.0</div><input id='attrs-6d660272-7c88-46aa-98bc-163c82a80d8a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6d660272-7c88-46aa-98bc-163c82a80d8a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-61af6b8e-ec32-4310-b3b2-b9a4d0698535' class='xr-var-data-in' type='checkbox'><label for='data-61af6b8e-ec32-4310-b3b2-b9a4d0698535' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0., 1., 2.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-233e0d8f-c460-4151-bc3c-982e05e43202' class='xr-section-summary-in' type='checkbox' checked><label for='section-233e0d8f-c460-4151-bc3c-982e05e43202' class='xr-section-summary' >Data variables: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>atoms</span></div><div class='xr-var-dims'>(compX_final_current, runs, y, x)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray></div><input id='attrs-decab481-9c7b-4194-8a12-8510facfbace' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-decab481-9c7b-4194-8a12-8510facfbace' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ad179120-7183-4c93-9a24-c35f46259ddf' class='xr-var-data-in' type='checkbox'><label for='data-ad179120-7183-4c93-9a24-c35f46259ddf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>IMAGE_SUBCLASS :</span></dt><dd>IMAGE_GRAYSCALE</dd><dt><span>IMAGE_VERSION :</span></dt><dd>1.2</dd><dt><span>IMAGE_WHITE_IS_ZERO :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 145.02 MiB </td>\n",
" <td> 118.65 MiB </td>\n",
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" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (11, 3, 1200, 1920) </td>\n",
" <td> (9, 3, 1200, 1920) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 2 chunks in 104 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> uint16 numpy.ndarray </td>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>background</span></div><div class='xr-var-dims'>(compX_final_current, runs, y, x)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray></div><input id='attrs-bfdcce6d-86c1-4d33-84dc-1f93263d056b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bfdcce6d-86c1-4d33-84dc-1f93263d056b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b69e94b3-5b13-4689-9e3b-0075cca7a54a' class='xr-var-data-in' type='checkbox'><label for='data-b69e94b3-5b13-4689-9e3b-0075cca7a54a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>IMAGE_SUBCLASS :</span></dt><dd>IMAGE_GRAYSCALE</dd><dt><span>IMAGE_VERSION :</span></dt><dd>1.2</dd><dt><span>IMAGE_WHITE_IS_ZERO :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><table>\n",
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" <th> Chunk </th>\n",
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" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 145.02 MiB </td>\n",
" <td> 118.65 MiB </td>\n",
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" \n",
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" <td> (11, 3, 1200, 1920) </td>\n",
" <td> (9, 3, 1200, 1920) </td>\n",
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" <td colspan=\"2\"> 2 chunks in 104 graph layers </td>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dark</span></div><div class='xr-var-dims'>(compX_final_current, runs, y, x)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray></div><input id='attrs-ee535bcb-d2ff-40e6-9085-737dd3bca8c6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ee535bcb-d2ff-40e6-9085-737dd3bca8c6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eb7aaad6-dc07-4cb4-bf3e-9062f6bab4cc' class='xr-var-data-in' type='checkbox'><label for='data-eb7aaad6-dc07-4cb4-bf3e-9062f6bab4cc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>IMAGE_SUBCLASS :</span></dt><dd>IMAGE_GRAYSCALE</dd><dt><span>IMAGE_VERSION :</span></dt><dd>1.2</dd><dt><span>IMAGE_WHITE_IS_ZERO :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><table>\n",
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" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
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" <tr>\n",
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" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 145.02 MiB </td>\n",
" <td> 118.65 MiB </td>\n",
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" <td> (11, 3, 1200, 1920) </td>\n",
" <td> (9, 3, 1200, 1920) </td>\n",
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" <td colspan=\"2\"> 2 chunks in 104 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
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"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>shotNum</span></div><div class='xr-var-dims'>(compX_final_current, runs)</div><div class='xr-var-dtype'><U2</div><div class='xr-var-preview xr-preview'>'00' '11' '22' ... '10' '21' '32'</div><input id='attrs-dd3f50dc-d8d2-4d0d-ad66-f292e054fc4c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-dd3f50dc-d8d2-4d0d-ad66-f292e054fc4c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2b513c23-104a-40ef-b2b1-c83036c8dd7c' class='xr-var-data-in' type='checkbox'><label for='data-2b513c23-104a-40ef-b2b1-c83036c8dd7c' 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([['00', '11', '22'],\n",
" ['01', '12', '23'],\n",
" ['02', '13', '24'],\n",
" ['03', '14', '25'],\n",
" ['04', '15', '26'],\n",
" ['05', '16', '27'],\n",
" ['06', '17', '28'],\n",
" ['07', '18', '29'],\n",
" ['08', '19', '30'],\n",
" ['09', '20', '31'],\n",
" ['10', '21', '32']], dtype='<U2')</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>OD</span></div><div class='xr-var-dims'>(compX_final_current, runs, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray></div><input id='attrs-626fa374-680c-4490-9ae9-9ccac6a0bc1c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-626fa374-680c-4490-9ae9-9ccac6a0bc1c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d7cea1b3-ed6f-430f-b923-1339b08f3156' class='xr-var-data-in' type='checkbox'><label for='data-d7cea1b3-ed6f-430f-b923-1339b08f3156' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>IMAGE_SUBCLASS :</span></dt><dd>IMAGE_GRAYSCALE</dd><dt><span>IMAGE_VERSION :</span></dt><dd>1.2</dd><dt><span>IMAGE_WHITE_IS_ZERO :</span></dt><dd>0</dd><dt><span>TOF_free :</span></dt><dd>0.022</dd><dt><span>abs_img_freq :</span></dt><dd>110.858</dd><dt><span>absorption_imaging_flag :</span></dt><dd>True</dd><dt><span>backup_data :</span></dt><dd>True</dd><dt><span>blink_off_time :</span></dt><dd>0.001</dd><dt><span>blink_on_time :</span></dt><dd>0.001</dd><dt><span>c_duration :</span></dt><dd>0.2</dd><dt><span>carrier_amp :</span></dt><dd>3</dd><dt><span>carrier_freq :</span></dt><dd>0.85</dd><dt><span>carrier_offset :</span></dt><dd>0</dd><dt><span>carrier_phase :</span></dt><dd>0</dd><dt><span>channel_in_use :</span></dt><dd>1</dd><dt><span>cmot_final_current :</span></dt><dd>0.65</dd><dt><span>cmot_hold :</span></dt><dd>0.06</dd><dt><span>cmot_initial_current :</span></dt><dd>0.18</dd><dt><span>compX_current :</span></dt><dd>0</dd><dt><span>compX_current_sg :</span></dt><dd>0.0</dd><dt><span>compX_initial_current :</span></dt><dd>0</dd><dt><span>compY_current :</span></dt><dd>0</dd><dt><span>compY_current_sg :</span></dt><dd>0.0</dd><dt><span>compY_final_current :</span></dt><dd>0</dd><dt><span>compY_initial_current :</span></dt><dd>0</dd><dt><span>compZ_current :</span></dt><dd>0</dd><dt><span>compZ_current_sg :</span></dt><dd>0.189</dd><dt><span>compZ_final_current :</span></dt><dd>0.264</dd><dt><span>compZ_initial_current :</span></dt><dd>0</dd><dt><span>default_camera :</span></dt><dd>0</dd><dt><span>deltaf :</span></dt><dd>0.161</dd><dt><span>evap_1_arm_1_final_pow :</span></dt><dd>0.35</dd><dt><span>evap_1_arm_1_mod_depth_final :</span></dt><dd>0</dd><dt><span>evap_1_arm_1_mod_depth_initial :</span></dt><dd>1.0</dd><dt><span>evap_1_arm_1_mod_ramp_duration :</span></dt><dd>1.15</dd><dt><span>evap_1_arm_1_pow_ramp_duration :</span></dt><dd>1.65</dd><dt><span>evap_1_arm_1_start_pow :</span></dt><dd>7</dd><dt><span>evap_1_arm_2_final_pow :</span></dt><dd>5</dd><dt><span>evap_1_arm_2_ramp_duration :</span></dt><dd>0.5</dd><dt><span>evap_1_arm_2_start_pow :</span></dt><dd>0</dd><dt><span>evap_1_mod_ramp_trunc_value :</span></dt><dd>1</dd><dt><span>evap_1_pow_ramp_trunc_value :</span></dt><dd>1.0</dd><dt><span>evap_1_rate_constant_1 :</span></dt><dd>0.525</dd><dt><span>evap_1_rate_constant_2 :</span></dt><dd>0.51</dd><dt><span>evap_2_arm_1_final_pow :</span></dt><dd>0.037</dd><dt><span>evap_2_arm_1_start_pow :</span></dt><dd>0.35</dd><dt><span>evap_2_arm_2_final_pow :</span></dt><dd>0.09</dd><dt><span>evap_2_arm_2_start_pow :</span></dt><dd>5</dd><dt><span>evap_2_ramp_duration :</span></dt><dd>1.0</dd><dt><span>evap_2_ramp_trunc_value :</span></dt><dd>1.0</dd><dt><span>evap_2_rate_constant_1 :</span></dt><dd>0.37</dd><dt><span>evap_2_rate_constant_2 :</span></dt><dd>0.71</dd><dt><span>evap_3_arm_1_final_pow :</span></dt><dd>0.1038</dd><dt><span>evap_3_arm_1_mod_depth_final :</span></dt><dd>0.43</dd><dt><span>evap_3_arm_1_mod_depth_initial :</span></dt><dd>0</dd><dt><span>evap_3_arm_1_start_pow :</span></dt><dd>0.037</dd><dt><span>evap_3_ramp_duration
" 0.002 0.004 0.006 0.008 0.01 0.012 0.014 0.016 0.018 0.02 0. 0.002\n",
" 0.004 0.006 0.008 0.01 0.012 0.014 0.016 0.018 0.02 ]</dd><dt><span>runs :</span></dt><dd>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 2. 2.\n",
" 2. 2. 2. 2. 2. 2. 2. 2. 2.]</dd><dt><span>scanAxis :</span></dt><dd>['compX_final_current' 'runs']</dd><dt><span>scanAxisLength :</span></dt><dd>[33. 33.]</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 580.08 MiB </td>\n",
" <td> 474.61 MiB </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (11, 3, 1200, 1920) </td>\n",
" <td> (9, 3, 1200, 1920) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 2 chunks in 322 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
" </tr>\n",
" </tbody>\n",
" </table>\n",
" </td>\n",
" <td>\n",
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" <text x=\"92.474299\" y=\"102.474299\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,92.474299,102.474299)\">3</text>\n",
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"</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-351cb1f7-8c97-4b8a-ac30-701244786fec' class='xr-section-summary-in' type='checkbox' ><label for='section-351cb1f7-8c97-4b8a-ac30-701244786fec' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>compX_final_current</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c61543bb-3e25-40af-b459-3cdf9c34886e' class='xr-index-data-in' type='checkbox'/><label for='index-c61543bb-3e25-40af-b459-3cdf9c34886e' 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, 0.002, 0.004, 0.006, 0.008, 0.01, 0.012, 0.014, 0.016,\n",
" 0.018, 0.02],\n",
" dtype='float64', name='compX_final_current'))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>runs</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1b44a02e-2eb1-49c2-a411-bc677a43a0a3' class='xr-index-data-in' type='checkbox'/><label for='index-1b44a02e-2eb1-49c2-a411-bc677a43a0a3' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([0.0, 1.0, 2.0], dtype='float64', name='runs'))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7755803d-1fae-4c63-ae16-a1698fb16772' class='xr-section-summary-in' type='checkbox' ><label for='section-7755803d-1fae-4c63-ae16-a1698fb16772' class='xr-section-summary' >Attributes: <span>(120)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>TOF_free :</span></dt><dd>0.022</dd><dt><span>abs_img_freq :</span></dt><dd>110.858</dd><dt><span>absorption_imaging_flag :</span></dt><dd>True</dd><dt><span>backup_data :</span></dt><dd>True</dd><dt><span>blink_off_time :</span></dt><dd>0.001</dd><dt><span>blink_on_time :</span></dt><dd>0.001</dd><dt><span>c_duration :</span></dt><dd>0.2</dd><dt><span>carrier_amp :</span></dt><dd>3</dd><dt><span>carrier_freq :</span></dt><dd>0.85</dd><dt><span>carrier_offset :</span></dt><dd>0</dd><dt><span>carrier_phase :</span></dt><dd>0</dd><dt><span>channel_in_use :</span></dt><dd>1</dd><dt><span>cmot_final_current :</span></dt><dd>0.65</dd><dt><span>cmot_hold :</span></dt><dd>0.06</dd><dt><span>cmot_initial_current :</span></dt><dd>0.18</dd><dt><span>compX_current :</span></dt><dd>0</dd><dt><span>compX_current_sg :</span></dt><dd>0.0</dd><dt><span>compX_initial_current :</span></dt><dd>0</dd><dt><span>compY_current :</span></dt><dd>0</dd><dt><span>compY_current_sg :</span></dt><dd>0.0</dd><dt><span>compY_final_current :</span></dt><dd>0</dd><dt><span>compY_initial_current :</span></dt><dd>0</dd><dt><span>compZ_current :</span></dt><dd>0</dd><dt><span>compZ_current_sg :</span></dt><dd>0.189</dd><dt><span>compZ_final_current :</span></dt><dd>0.264</dd><dt><span>compZ_initial_current :</span></dt><dd>0</dd><dt><span>default_camera :</span></dt><dd>0</dd><dt><span>deltaf :</span></dt><dd>0.161</dd><dt><span>evap_1_arm_1_final_pow :</span></dt><dd>0.35</dd><dt><span>evap_1_arm_1_mod_depth_final :</span></dt><dd>0</dd><dt><span>evap_1_arm_1_mod_depth_initial :</span></dt><dd>1.0</dd><dt><span>evap_1_arm_1_mod_ramp_duration :</span></dt><dd>1.15</dd><dt><span>evap_1_arm_1_pow_ramp_duration :</span></dt><dd>1.65</dd><dt><span>evap_1_arm_1_start_pow :</span></dt><dd>7</dd><dt><span>evap_1_arm_2_final_pow :</span></dt><dd>5</dd><dt><span>evap_1_arm_2_ramp_duration :</span></dt><dd>0.5</dd><dt><span>evap_1_arm_2_start_pow :</span></dt><dd>0</dd><dt><span>evap_1_mod_ramp_trunc_value :</span></dt><dd>1</dd><dt><span>evap_1_pow_ramp_trunc_value :</span></dt><dd>1.0</dd><dt><span>evap_1_rate_constant_1 :</span></dt><dd>0.525</dd><dt><span>evap_1_rate_constant_2 :</span></dt><dd>0.51</dd><dt><span>evap_2_arm_1_final_pow :</span></dt><dd>0.037</dd><dt><span>evap_2_arm_1_start_pow :</span></dt><dd>0.35</dd><dt><span>evap_2_arm_2_final_pow :</span></dt><dd>0.09</dd><dt><span>evap_2_arm_2_start_pow :</span></dt><dd>5</dd><dt><span>evap_2_ramp_duration :</span></dt><dd>1.0</dd><dt><span>evap_2_ramp_trunc_value :</span></dt><dd>1.0</dd><dt><span>evap_2_rate_constant_1 :</span></dt><dd>0.37</dd><dt><span>evap_2_rate_constant_2 :</span></dt><dd>0.71</dd><dt><span>evap_3_arm_1_final_pow :</span></dt><dd>0.1038</dd><dt><span>evap_3_arm_1_mod_depth_final :</span></dt><dd>0.43</dd><dt><span>evap_3_arm_1_mod_depth_initial :</span></dt><dd>0</dd><dt><span>evap_3_arm_1_start_pow :</span></dt><dd>0.037</dd><dt><span>evap_3_ramp_duration :</span></dt><dd>0.1</dd><dt><span>evap_3_ramp_trunc_value :</span></dt><dd>1.0</dd><dt><span>evap_3_rate_constant_1 :</sp
],
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (compX_final_current: 11, runs: 3, y: 1200, x: 1920)\n",
"Coordinates:\n",
" * compX_final_current (compX_final_current) float64 0.0 0.002 ... 0.018 0.02\n",
" * runs (runs) float64 0.0 1.0 2.0\n",
"Dimensions without coordinates: y, x\n",
"Data variables:\n",
" atoms (compX_final_current, runs, y, x) uint16 dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray>\n",
" background (compX_final_current, runs, y, x) uint16 dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray>\n",
" dark (compX_final_current, runs, y, x) uint16 dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray>\n",
" shotNum (compX_final_current, runs) <U2 '00' '11' ... '21' '32'\n",
" OD (compX_final_current, runs, y, x) float64 dask.array<chunksize=(9, 3, 1200, 1920), meta=np.ndarray>\n",
"Attributes: (12/120)\n",
" TOF_free: 0.022\n",
" abs_img_freq: 110.858\n",
" absorption_imaging_flag: True\n",
" backup_data: True\n",
" blink_off_time: 0.001\n",
" blink_on_time: 0.001\n",
" ... ...\n",
" z_offset: 0.189\n",
" z_offset_img: 0.189\n",
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" runs: [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0....\n",
" scanAxis: ['compX_final_current', 'runs']\n",
" scanAxisLength: [33.0, 33.0]"
]
},
"execution_count": 148,
"metadata": {},
"output_type": "execute_result"
}
],
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"source": [
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"dataSet"
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]
},
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"cell_type": "code",
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"execution_count": 147,
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"metadata": {},
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"outputs": [
{
"ename": "TypeError",
"evalue": "`group` must be an xarray.DataArray or the name of an xarray variable or dimension. Received ['compX_final_current', 'runs'] instead.",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32mf:\\Jianshun\\analyseScript\\testMongoDB.ipynb Cell 30\u001b[0m in \u001b[0;36m1\n\u001b[1;32m----> <a href='vscode-notebook-cell:/f%3A/Jianshun/analyseScript/testMongoDB.ipynb#Y162sZmlsZQ%3D%3D?line=0'>1</a>\u001b[0m rrr \u001b[39m=\u001b[39m dataSet\u001b[39m.\u001b[39;49mgroupby(\u001b[39mlist\u001b[39;49m(scanAxis))\n",
"File \u001b[1;32m~\\AppData\\Roaming\\Python\\Python39\\site-packages\\xarray\\core\\dataset.py:8966\u001b[0m, in \u001b[0;36mDataset.groupby\u001b[1;34m(self, group, squeeze, restore_coord_dims)\u001b[0m\n\u001b[0;32m 8961\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39misinstance\u001b[39m(squeeze, \u001b[39mbool\u001b[39m):\n\u001b[0;32m 8962\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mTypeError\u001b[39;00m(\n\u001b[0;32m 8963\u001b[0m \u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39m`squeeze` must be True or False, but \u001b[39m\u001b[39m{\u001b[39;00msqueeze\u001b[39m}\u001b[39;00m\u001b[39m was supplied\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m 8964\u001b[0m )\n\u001b[1;32m-> 8966\u001b[0m \u001b[39mreturn\u001b[39;00m DatasetGroupBy(\n\u001b[0;32m 8967\u001b[0m \u001b[39mself\u001b[39;49m, group, squeeze\u001b[39m=\u001b[39;49msqueeze, restore_coord_dims\u001b[39m=\u001b[39;49mrestore_coord_dims\n\u001b[0;32m 8968\u001b[0m )\n",
"File \u001b[1;32m~\\AppData\\Roaming\\Python\\Python39\\site-packages\\xarray\\core\\groupby.py:465\u001b[0m, in \u001b[0;36mGroupBy.__init__\u001b[1;34m(self, obj, group, squeeze, grouper, bins, restore_coord_dims, cut_kwargs)\u001b[0m\n\u001b[0;32m 463\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39misinstance\u001b[39m(group, (DataArray, IndexVariable)):\n\u001b[0;32m 464\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m hashable(group):\n\u001b[1;32m--> 465\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mTypeError\u001b[39;00m(\n\u001b[0;32m 466\u001b[0m \u001b[39m\"\u001b[39m\u001b[39m`group` must be an xarray.DataArray or the \u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m 467\u001b[0m \u001b[39m\"\u001b[39m\u001b[39mname of an xarray variable or dimension. \u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m 468\u001b[0m \u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mReceived \u001b[39m\u001b[39m{\u001b[39;00mgroup\u001b[39m!r}\u001b[39;00m\u001b[39m instead.\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m 469\u001b[0m )\n\u001b[0;32m 470\u001b[0m group \u001b[39m=\u001b[39m obj[group]\n\u001b[0;32m 471\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mlen\u001b[39m(group) \u001b[39m==\u001b[39m \u001b[39m0\u001b[39m:\n",
"\u001b[1;31mTypeError\u001b[0m: `group` must be an xarray.DataArray or the name of an xarray variable or dimension. Received ['compX_final_current', 'runs'] instead."
]
}
],
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"source": [
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"rrr = dataSet.groupby(list(scanAxis))"
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]
},
{
"cell_type": "code",
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"execution_count": 135,
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"metadata": {},
"outputs": [],
"source": [
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"for i in rrr:\n",
" b = i"
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]
},
{
"cell_type": "code",
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"execution_count": 140,
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"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
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"array(['compX_final_current', 'runs'], dtype='<U19')"
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"execution_count": 140,
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"metadata": {},
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"source": [
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{
"cell_type": "code",
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"execution_count": 139,
2023-06-02 18:42:18 +02:00
"metadata": {},
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" runs: [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 1...\n",
" scanAxis: ['compX_final_current' 'runs']\n",
" scanAxisLength: [33. 33.]</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-aafcbe6b-f1bb-4c8a-8a19-bc8fef4a4b7f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-aafcbe6b-f1bb-4c8a-8a19-bc8fef4a4b7f' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>y</span>: 1200</li><li><span>x</span>: 1920</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-e7a926ac-e828-410d-b25b-cfa774fc5ecd' class='xr-section-summary-in' type='checkbox' checked><label for='section-e7a926ac-e828-410d-b25b-cfa774fc5ecd' class='xr-section-summary' >Coordinates: <span>(3)</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>z</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>(0.02, 2.0)</div><input id='attrs-3b413688-4781-475f-b316-72dd8bb7c95c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3b413688-4781-475f-b316-72dd8bb7c95c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-67b45563-cabf-4ea6-bc41-85fc180bbbce' class='xr-var-data-in' type='checkbox'><label for='data-67b45563-cabf-4ea6-bc41-85fc180bbbce' 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((0.02, 2.0), dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>compX_final_current</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.02</div><input id='attrs-c3292ec3-7973-4992-b41c-b00bc3c21446' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c3292ec3-7973-4992-b41c-b00bc3c21446' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-21c5741b-fde6-4b66-93d2-6b2874f2f69b' class='xr-var-data-in' type='checkbox'><label for='data-21c5741b-fde6-4b66-93d2-6b2874f2f69b' 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(0.02)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>runs</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.0</div><input id='attrs-98a7f343-b657-4d13-b71f-54f0ed47c7b9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-98a7f343-b657-4d13-b71f-54f0ed47c7b9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e365791c-2f4f-4f14-a381-e0a0f9718379' class='xr-var-data-in' type='checkbox'><label for='data-e365791c-2f4f-4f14-a381-e0a0f9718379' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(2.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b367d48a-2332-4cbd-a01c-cca6b655918d' class='xr-section-summary-in' type='checkbox' checked><label for='section-b367d48a-2332-4cbd-a01c-cca6b655918d' class='xr-section-summary' >Data variables: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>atoms</span></div><div class='xr-var-dim
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 4.39 MiB </td>\n",
" <td> 4.39 MiB </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (1200, 1920) </td>\n",
" <td> (1200, 1920) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 1 chunks in 107 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> uint16 numpy.ndarray </td>\n",
" </tr>\n",
" </tbody>\n",
" </table>\n",
" </td>\n",
" <td>\n",
" <svg width=\"170\" height=\"125\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
"\n",
" <!-- Horizontal lines -->\n",
" <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
" <line x1=\"0\" y1=\"75\" x2=\"120\" y2=\"75\" style=\"stroke-width:2\" />\n",
"\n",
" <!-- Vertical lines -->\n",
" <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"75\" style=\"stroke-width:2\" />\n",
" <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"75\" style=\"stroke-width:2\" />\n",
"\n",
" <!-- Colored Rectangle -->\n",
" <polygon points=\"0.0,0.0 120.0,0.0 120.0,75.0 0.0,75.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
"\n",
" <!-- Text -->\n",
" <text x=\"60.000000\" y=\"95.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1920</text>\n",
" <text x=\"140.000000\" y=\"37.500000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,37.500000)\">1200</text>\n",
"</svg>\n",
" </td>\n",
" </tr>\n",
"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>background</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1200, 1920), meta=np.ndarray></div><input id='attrs-49c1c10d-b8a2-42fe-a0e4-f50d7df53358' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-49c1c10d-b8a2-42fe-a0e4-f50d7df53358' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-933eec24-7b6e-4f53-8f2d-7feb516a70b6' class='xr-var-data-in' type='checkbox'><label for='data-933eec24-7b6e-4f53-8f2d-7feb516a70b6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>IMAGE_SUBCLASS :</span></dt><dd>IMAGE_GRAYSCALE</dd><dt><span>IMAGE_VERSION :</span></dt><dd>1.2</dd><dt><span>IMAGE_WHITE_IS_ZERO :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 4.39 MiB </td>\n",
" <td> 4.39 MiB </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (1200, 1920) </td>\n",
" <td> (1200, 1920) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 1 chunks in 107 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> uint16 numpy.ndarray </td>\n",
" </tr>\n",
" </tbody>\n",
" </table>\n",
" </td>\n",
" <td>\n",
" <svg width=\"170\" height=\"125\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
"\n",
" <!-- Horizontal lines -->\n",
" <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
" <line x1=\"0\" y1=\"75\" x2=\"120\" y2=\"75\" style=\"stroke-width:2\" />\n",
"\n",
" <!-- Vertical lines -->\n",
" <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"75\" style=\"stroke-width:2\" />\n",
" <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"75\" style=\"stroke-width:2\" />\n",
"\n",
" <!-- Colored Rectangle -->\n",
" <polygon points=\"0.0,0.0 120.0,0.0 120.0,75.0 0.0,75.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
"\n",
" <!-- Text -->\n",
" <text x=\"60.000000\" y=\"95.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1920</text>\n",
" <text x=\"140.000000\" y=\"37.500000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,37.500000)\">1200</text>\n",
"</svg>\n",
" </td>\n",
" </tr>\n",
"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dark</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1200, 1920), meta=np.ndarray></div><input id='attrs-dcadc02f-2083-4244-aa8b-3286b8dc97d0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dcadc02f-2083-4244-aa8b-3286b8dc97d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b20d8cd8-0a23-4290-83e1-835a49fb7a17' class='xr-var-data-in' type='checkbox'><label for='data-b20d8cd8-0a23-4290-83e1-835a49fb7a17' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>IMAGE_SUBCLASS :</span></dt><dd>IMAGE_GRAYSCALE</dd><dt><span>IMAGE_VERSION :</span></dt><dd>1.2</dd><dt><span>IMAGE_WHITE_IS_ZERO :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 4.39 MiB </td>\n",
" <td> 4.39 MiB </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (1200, 1920) </td>\n",
" <td> (1200, 1920) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 1 chunks in 107 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> uint16 numpy.ndarray </td>\n",
" </tr>\n",
" </tbody>\n",
" </table>\n",
" </td>\n",
" <td>\n",
" <svg width=\"170\" height=\"125\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
"\n",
" <!-- Horizontal lines -->\n",
" <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
" <line x1=\"0\" y1=\"75\" x2=\"120\" y2=\"75\" style=\"stroke-width:2\" />\n",
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"\n",
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" <!-- Vertical lines -->\n",
" <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"75\" style=\"stroke-width:2\" />\n",
" <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"75\" style=\"stroke-width:2\" />\n",
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"\n",
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" <!-- Colored Rectangle -->\n",
" <polygon points=\"0.0,0.0 120.0,0.0 120.0,75.0 0.0,75.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
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"\n",
2023-06-13 18:16:24 +02:00
" <!-- Text -->\n",
" <text x=\"60.000000\" y=\"95.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1920</text>\n",
" <text x=\"140.000000\" y=\"37.500000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,37.500000)\">1200</text>\n",
"</svg>\n",
" </td>\n",
" </tr>\n",
"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>shotNum</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'><U2</div><div class='xr-var-preview xr-preview'>'32'</div><input id='attrs-b6b5c234-5f37-42b2-8295-18a8a6cced56' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b6b5c234-5f37-42b2-8295-18a8a6cced56' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b506315-c21f-4931-8ff9-7bd40cba7d9f' class='xr-var-data-in' type='checkbox'><label for='data-5b506315-c21f-4931-8ff9-7bd40cba7d9f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array('32', dtype='<U2')</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>OD</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1200, 1920), meta=np.ndarray></div><input id='attrs-e4308663-742d-4a50-bceb-250aa66316fa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e4308663-742d-4a50-bceb-250aa66316fa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fdb5fd3d-6538-471e-aa84-7bc7bef45231' class='xr-var-data-in' type='checkbox'><label for='data-fdb5fd3d-6538-471e-aa84-7bc7bef45231' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>IMAGE_SUBCLASS :</span></dt><dd>IMAGE_GRAYSCALE</dd><dt><span>IMAGE_VERSION :</span></dt><dd>1.2</dd><dt><span>IMAGE_WHITE_IS_ZERO :</span></dt><dd>0</dd><dt><span>TOF_free :</span></dt><dd>0.022</dd><dt><span>abs_img_freq :</span></dt><dd>110.858</dd><dt><span>absorption_imaging_flag :</span></dt><dd>True</dd><dt><span>backup_data :</span></dt><dd>True</dd><dt><span>blink_off_time :</span></dt><dd>0.001</dd><dt><span>blink_on_time :</span></dt><dd>0.001</dd><dt><span>c_duration :</span></dt><dd>0.2</dd><dt><span>carrier_amp :</span></dt><dd>3</dd><dt><span>carrier_freq :</span></dt><dd>0.85</dd><dt><span>carrier_offset :</span></dt><dd>0</dd><dt><span>carrier_phase :</span></dt><dd>0</dd><dt><span>channel_in_use :</span></dt><dd>1</dd><dt><span>cmot_final_current :</span></dt><dd>0.65</dd><dt><span>cmot_hold :</span></dt><dd>0.06</dd><dt><span>cmot_initial_current :</span></dt><dd>0.18</dd><dt><span>compX_current :</span></dt><dd>0</dd><dt><span>compX_current_sg :</span></dt><dd>0.0</dd><dt><span>compX_initial_current :</span></dt><dd>0</dd><dt><span>compY_current :</span></dt><dd>0</dd><dt><span>compY_current_sg :</span></dt><dd>0.0</dd><dt><span>compY_final_current :</span></dt><dd>0</dd><dt><span>compY_initial_current :</span></dt><dd>0</dd><dt><span>compZ_current :</span></dt><dd>0</dd><dt><span>compZ_current_sg :</span></dt><dd>0.189</dd><dt><span>compZ_final_current :</span></dt><dd>0.264</dd><dt><span>compZ_initial_current :</span></dt><dd>0</dd><dt><span>default_camera :</span></dt><dd>0</dd><dt><span>deltaf :</span></dt><dd>0.161</dd><dt><span>evap_1_arm_1_final_pow :</span></dt><dd>0.35</dd><dt><span>evap_1_arm_1_mod_depth_final :</span></dt><dd>0</dd><dt><span>evap_1_arm_1_mod_depth_initial :</span></dt><dd>1.0</dd><dt><span>evap_1_arm_1_mod_ramp_duration :</span></dt><dd>1.15</dd><dt><span>evap_1_arm_1_pow_ramp_duration :</span></dt><dd>1.65</dd><dt><span>evap_1_arm_1_start_pow :</span></dt><dd>7</dd><dt><span>evap_1_arm_2_final_pow :</span></dt><dd>5</dd><dt><span>evap_1_arm_2_ramp_duration :</span></dt><dd>0.5</dd><dt><span>evap_1_arm_2_start_pow :</span></dt><dd>0</dd><dt><span>evap_1_mod_ramp_trunc_value :</span></dt><dd>1</dd><dt><span>evap_1_pow_ramp_trunc_value :</span></dt><dd>1.0</dd><dt><span>evap_1_rate_constant_1 :</span></dt><dd>0.525</dd><dt><span>evap_1_ra
" 0.002 0.004 0.006 0.008 0.01 0.012 0.014 0.016 0.018 0.02 0. 0.002\n",
" 0.004 0.006 0.008 0.01 0.012 0.014 0.016 0.018 0.02 ]</dd><dt><span>runs :</span></dt><dd>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 2. 2.\n",
" 2. 2. 2. 2. 2. 2. 2. 2. 2.]</dd><dt><span>scanAxis :</span></dt><dd>['compX_final_current' 'runs']</dd><dt><span>scanAxisLength :</span></dt><dd>[33. 33.]</dd></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
" <td>\n",
" <table style=\"border-collapse: collapse;\">\n",
" <thead>\n",
" <tr>\n",
" <td> </td>\n",
" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 17.58 MiB </td>\n",
" <td> 17.58 MiB </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (1200, 1920) </td>\n",
" <td> (1200, 1920) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 1 chunks in 325 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
" </tr>\n",
" </tbody>\n",
" </table>\n",
" </td>\n",
" <td>\n",
" <svg width=\"170\" height=\"125\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
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"\n",
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" <!-- Horizontal lines -->\n",
" <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
" <line x1=\"0\" y1=\"75\" x2=\"120\" y2=\"75\" style=\"stroke-width:2\" />\n",
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"\n",
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" <!-- Vertical lines -->\n",
" <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"75\" style=\"stroke-width:2\" />\n",
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"\n",
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"\n",
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" <!-- Text -->\n",
" <text x=\"60.000000\" y=\"95.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1920</text>\n",
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"</svg>\n",
" </td>\n",
" </tr>\n",
"</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-23160cc1-cf45-4c3e-a68b-7d10483dc36a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-23160cc1-cf45-4c3e-a68b-7d10483dc36a' class='xr-section-summary' title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-31975503-1606-4c4e-ac82-ab354e686e70' class='xr-section-summary-in' type='checkbox' ><label for='section-31975503-1606-4c4e-ac82-ab354e686e70' class='xr-section-summary' >Attributes: <span>(120)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>TOF_free :</span></dt><dd>0.022</dd><dt><span>abs_img_freq :</span></dt><dd>110.858</dd><dt><span>absorption_imaging_flag :</span></dt><dd>True</dd><dt><span>backup_data :</span></dt><dd>True</dd><dt><span>blink_off_time :</span></dt><dd>0.001</dd><dt><span>blink_on_time :</span></dt><dd>0.001</dd><dt><span>c_duration :</span></dt><dd>0.2</dd><dt><span>carrier_amp :</span></dt><dd>3</dd><dt><span>carrier_freq :</span></dt><dd>0.85</dd><dt><span>carrier_offset :</span></dt><dd>0</dd><dt><span>carrier_phase :</span></dt><dd>0</dd><dt><span>channel_in_use :</span></dt><dd>1</dd><dt><span>cmot_final_current :</span></dt><dd>0.65</dd><dt><span>cmot_hold :</span></dt><dd>0.06</dd><dt><span>cmot_initial_current :</span></dt><dd>0.18</dd><dt><span>compX_current :</span></dt><dd>0</dd><dt><span>compX_current_sg :</span></dt><dd>0.0</dd><dt><span>compX_initial_current :</span></dt><dd>0</dd><dt><span>compY_current :</span></dt><dd>0</dd><dt><span>compY_current_sg :</span></dt><dd>0.0</dd><dt><span>compY_final_current :</span></dt><dd>0</dd><dt><span>compY_initial_current :</span></dt><dd>0</dd><dt><span>compZ_current :</span></dt><dd>0</dd><dt><span>compZ_current_sg :</span></dt><dd>0.189</dd><dt><span>compZ_final_current :</span></dt><dd>0.264</dd><dt><span>compZ_initial_current :</span></dt><dd>0</dd><dt><span>default_camera :</span></dt><dd>0</dd><dt><span>deltaf :</span></dt><dd>0.161</dd><dt><span>evap_1_arm_1_final_pow :</span></dt><dd>0.35</dd><dt><span>evap_1_arm_1_mod_depth_final :</span></dt><dd>0</dd><dt><span>evap_1_arm_1_mod_depth_initial :</span></dt><dd>1.0</dd><dt><span>evap_1_arm_1_mod_ramp_duration :</span></dt><dd>1.15</dd><dt><span>evap_1_arm_1_pow_ramp_duration :</span></dt><dd>1.65</dd><dt><span>evap_1_arm_1_start_pow :</span></dt><dd>7</dd><dt><span>evap_1_arm_2_final_pow :</span></dt><dd>5</dd><dt><span>evap_1_arm_2_ramp_duration :</span></dt><dd>0.5</dd><dt><span>evap_1_arm_2_start_pow :</span></dt><dd>0</dd><dt><span>evap_1_mod_ramp_trunc_value :</span></dt><dd>1</dd><dt><span>evap_1_pow_ramp_trunc_value :</span></dt><dd>1.0</dd><dt><span>evap_1_rate_constant_1 :</span></dt><dd>0.525</dd><dt><span>evap_1_rate_constant_2 :</span></dt><dd>0.51</dd><dt><span>evap_2_arm_1_final_pow :</span></dt><dd>0.037</dd><dt><span>evap_2_arm_1_start_pow :</span></dt><dd>0.35</dd><dt><span>evap_2_arm_2_final_pow :</span></dt><dd>0.09</dd><dt><span>evap_2_arm_2_start_pow :</span></dt><dd>5</dd><dt><span>evap_2_ramp_duration :</span></dt><dd>1.0</dd><dt><span>evap_2_ramp_trunc_value :</span></dt><dd>1.0</dd><dt><span>evap_2_rate_constant_1 :</span></dt><dd>0.37</dd><dt><span>evap_2_rate_constant_2 :</span></dt><dd>0.71</dd><dt><span>evap_3_arm_1_final_pow :</span></dt><dd>0.1038</dd><dt><span>evap_3_arm_1_mod_depth_final :</span></dt><dd>0.43</dd><dt><span>evap_3_arm_1_mod_depth_initial :</span></dt><dd>0</dd><dt><span>evap_3_arm_1_start_pow :</span></dt><dd>0.037</dd><dt><span>evap_3_ramp_duration :</span></dt><dd>0.1</dd><dt><span>evap_3_ramp_trunc_value :</span></dt><dd>1.0</dd><dt><span>evap_3_rate_constant_1 :</span></dt><dd>-0.879</dd><dt><span>evap_3_rate_constant_2 :</span></dt><dd>-0.297</dd><dt><span>final_amp :</span></dt><dd>0.00012</dd><dt><span>final_freq :</span></dt><dd>104.0</dd><dt><span>final_pow_1 :</sp
" 0.002 0.004 0.006 0.008 0.01 0.012 0.014 0.016 0.018 0.02 0. 0.002\n",
" 0.004 0.006 0.008 0.01 0.012 0.014 0.016 0.018 0.02 ]</dd><dt><span>runs :</span></dt><dd>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 2. 2.\n",
" 2. 2. 2. 2. 2. 2. 2. 2. 2.]</dd><dt><span>scanAxis :</span></dt><dd>['compX_final_current' 'runs']</dd><dt><span>scanAxisLength :</span></dt><dd>[33. 33.]</dd></dl></div></li></ul></div></div>"
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],
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"<xarray.Dataset>\n",
"Dimensions: (y: 1200, x: 1920)\n",
"Coordinates:\n",
" z object (0.02, 2.0)\n",
" compX_final_current float64 0.02\n",
" runs float64 2.0\n",
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"Dimensions without coordinates: y, x\n",
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"Data variables:\n",
" atoms (y, x) uint16 dask.array<chunksize=(1200, 1920), meta=np.ndarray>\n",
" background (y, x) uint16 dask.array<chunksize=(1200, 1920), meta=np.ndarray>\n",
" dark (y, x) uint16 dask.array<chunksize=(1200, 1920), meta=np.ndarray>\n",
" shotNum <U2 '32'\n",
" OD (y, x) float64 dask.array<chunksize=(1200, 1920), meta=np.ndarray>\n",
"Attributes: (12/120)\n",
" TOF_free: 0.022\n",
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" abs_img_freq: 110.858\n",
" absorption_imaging_flag: True\n",
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" backup_data: True\n",
" blink_off_time: 0.001\n",
" blink_on_time: 0.001\n",
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" ... ...\n",
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" z_offset: 0.189\n",
" z_offset_img: 0.189\n",
" compX_final_current: [0. 0.002 0.004 0.006 0.008 0.01 0...\n",
" runs: [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 1...\n",
" scanAxis: ['compX_final_current' 'runs']\n",
" scanAxisLength: [33. 33.]"
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]
},
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"execution_count": 139,
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"metadata": {},
"output_type": "execute_result"
}
],
"source": [
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"b[1]"
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]
},
{
"cell_type": "code",
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"execution_count": 125,
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"metadata": {},
"outputs": [
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"</style><pre class='xr-text-repr-fallback'><xarray.DataArray 'shotNum' ()>\n",
"array('32', dtype='<U2')\n",
"Coordinates:\n",
" compX_final_current float64 0.02\n",
" runs float64 2.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'shotNum'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-7462aa17-2425-4194-8e87-6b42edaf2c98' class='xr-array-in' type='checkbox' checked><label for='section-7462aa17-2425-4194-8e87-6b42edaf2c98' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>'32'</span></div><div class='xr-array-data'><pre>array('32', dtype='<U2')</pre></div></div></li><li class='xr-section-item'><input id='section-b5ca348a-22ec-4b8c-917d-f788c12fa00a' class='xr-section-summary-in' type='checkbox' checked><label for='section-b5ca348a-22ec-4b8c-917d-f788c12fa00a' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>compX_final_current</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.02</div><input id='attrs-53a5bac0-5ad8-492f-af7d-8910702dc322' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-53a5bac0-5ad8-492f-af7d-8910702dc322' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66506acd-5879-443a-9d68-8552f168c5ca' class='xr-var-data-in' type='checkbox'><label for='data-66506acd-5879-443a-9d68-8552f168c5ca' 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(0.02)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>runs</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.0</div><input id='attrs-f7cacbb6-af84-4f35-93f6-02de99ea26e1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f7cacbb6-af84-4f35-93f6-02de99ea26e1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e1c9f05-260d-4101-ad69-a8078e9dd7a6' class='xr-var-data-in' type='checkbox'><label for='data-8e1c9f05-260d-4101-ad69-a8078e9dd7a6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(2.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7dbe584a-898a-4289-aae2-a4810fad089d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7dbe584a-898a-4289-aae2-a4810fad089d' class='xr-section-summary' title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-1ef07dce-2638-463d-8a38-8b7550bbf0cb' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-1ef07dce-2638-463d-8a38-8b7550bbf0cb' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
2023-06-02 18:42:18 +02:00
],
"text/plain": [
2023-06-13 18:16:24 +02:00
"<xarray.DataArray 'shotNum' ()>\n",
"array('32', dtype='<U2')\n",
"Coordinates:\n",
" compX_final_current float64 0.02\n",
" runs float64 2.0"
]
},
"execution_count": 125,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"b.drop('z')"
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\data\\AppData\\Roaming\\Python\\Python39\\site-packages\\xarray\\core\\variable.py:1745: PerformanceWarning: Reshaping is producing a large chunk. To accept the large\n",
"chunk and silence this warning, set the option\n",
" >>> with dask.config.set(**{'array.slicing.split_large_chunks': False}):\n",
" ... array.reshape(shape)\n",
"\n",
"To avoid creating the large chunks, set the option\n",
" >>> with dask.config.set(**{'array.slicing.split_large_chunks': True}):\n",
" ... array.reshape(shape)Explictly passing ``limit`` to ``reshape`` will also silence this warning\n",
" >>> array.reshape(shape, limit='128 MiB')\n",
" result = result._stack_once(dims, new_dim)\n"
]
}
],
"source": [
"aaa = dataSet.stack(z=tuple(dataSet.scanAxis))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"type(np.array([0]))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"name in dataSet.OD.attrs"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"list(dataSet.data_vars)"
]
},
{
"cell_type": "code",
"execution_count": 120,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['compX_final_current', 'runs']"
]
},
"execution_count": 120,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"list(dataSet.OD.coords)"
]
},
{
"cell_type": "code",
"execution_count": 170,
"metadata": {},
"outputs": [],
"source": [
2023-06-13 19:23:56 +02:00
"from collections import OrderedDict\n",
"\n",
2023-06-13 18:16:24 +02:00
"import pymongo\n",
"import xarray_mongodb\n",
"import bson\n",
"import builtins\n",
"\n",
"import xarray as xr\n",
"\n",
"from ToolFunction.ToolFunction import get_date\n",
"\n",
"\n",
"npTypeDict = {v: getattr(builtins, k) for k, v in np.sctypeDict.items() if k in vars(builtins)}\n",
"npArrayType = type(np.array([0]))\n",
"\n",
"\n",
"class MongoDB:\n",
" \n",
" def __init__(self, mongoClient, mongoDB, date=None) -> None:\n",
" self.mongoClient = mongoClient\n",
" self.mongoDB = mongoDB\n",
" self.xdb = xarray_mongodb.XarrayMongoDB(mongoDB)\n",
" \n",
" if date is None:\n",
" date= get_date()\n",
" self.set_date(date)\n",
" \n",
" def _convert_numpy_type(self, data):\n",
" for key in data:\n",
" typeKey = type(data[key])\n",
" if typeKey in npTypeDict:\n",
" data[key] = data[key].item()\n",
" elif typeKey == npArrayType:\n",
" data[key] = data[key].tolist()\n",
" else:\n",
" try:\n",
" data[key] = data[key].item()\n",
" except:\n",
" pass\n",
" return data\n",
" \n",
" def _break_dataSet(self, dataSet, scanAxis=None):\n",
" \n",
" if scanAxis is None:\n",
" scanAxis = dataSet.attrs['scanAxis'] \n",
" \n",
" dataArray = dataSet.shotNum\n",
" \n",
" stackedDataArray = dataArray.stack(_scanAxis=tuple(scanAxis)) \n",
"\n",
" return stackedDataArray\n",
" \n",
" def set_date(self, date):\n",
" date = date.split(\"/\")\n",
" self.year = int(date[0])\n",
" self.month = int(date[1])\n",
" self.day = int(date[2])\n",
" \n",
" def create_global(self, shotNum, dataSet=None, date=None):\n",
" if not date is None:\n",
" self.set_date(date)\n",
" \n",
" data = {\n",
" 'year': self.year,\n",
" 'month': self.month,\n",
" 'day': self.day,\n",
" 'shotNum': shotNum,\n",
" 'runNum': 0,\n",
" 'global_parameters' : {},\n",
" }\n",
" \n",
" global_parameters = self._convert_numpy_type(dataSet.attrs)\n",
" \n",
" if not dataSet is None:\n",
" data['global_parameters'].update(global_parameters)\n",
" \n",
" data = self._convert_numpy_type(data)\n",
" \n",
" if 'scanAxis' in dataSet.attrs:\n",
" \n",
" del data['global_parameters']['scanAxis']\n",
" del data['global_parameters']['scanAxisLength']\n",
" \n",
" scanAxis = dataSet.attrs['scanAxis']\n",
" data['global_parameters'].update(\n",
" {\n",
" key:0\n",
" for key in scanAxis\n",
" }\n",
" )\n",
" \n",
" stackedDataArray = self._break_dataSet(dataSet)\n",
" stackedDataArray = stackedDataArray.groupby('_scanAxis')\n",
" \n",
" for i in stackedDataArray:\n",
" \n",
" stackedDataArray_single = i[1]\n",
" \n",
" data.update(\n",
" {\n",
" 'runNum': int(stackedDataArray_single.item())\n",
" }\n",
" )\n",
" \n",
" data['global_parameters'].update(\n",
" {\n",
" key: stackedDataArray_single[key].item()\n",
" for key in scanAxis\n",
" }\n",
" )\n",
" \n",
" if '_id' in data:\n",
" del data['_id']\n",
" \n",
" self.mongoDB['global'].insert_one(data)\n",
" \n",
" else:\n",
" self.mongoDB['global'].insert_one(data)\n",
" \n",
" def _add_data_normal(self, shotNum, runNum, data):\n",
" \n",
" if runNum is None:\n",
" runNum = 0\n",
" \n",
" filter = { \n",
" 'year': self.year,\n",
" 'month': self.month,\n",
" 'day': self.day,\n",
" 'shotNum': shotNum,\n",
" 'runNum': runNum,\n",
" }\n",
" \n",
" self.mongoDB['global'].update_one(filter, {\"$set\": data}, upsert=False)\n",
" \n",
" def _add_data_xarray_dataArray(self, shotNum, dataArray, scanAxis=None):\n",
" \n",
" if scanAxis is None:\n",
" scanAxis = list(dataArray.coords)\n",
" \n",
" dataArray.attrs = self._convert_numpy_type(dataArray.attrs)\n",
" \n",
" stackedDataArray = dataArray.stack(_scanAxis=tuple(scanAxis))\n",
" stackedDataArray = stackedDataArray.groupby('_scanAxis')\n",
" \n",
" filter = { \n",
" 'year': self.year,\n",
" 'month': self.month,\n",
" 'day': self.day,\n",
" 'shotNum': shotNum,\n",
" }\n",
" \n",
" for i in stackedDataArray:\n",
" \n",
" stackedDataArray_single = i[1].drop('_scanAxis')\n",
" \n",
" global_parameters = {\n",
" 'global_parameters.' + key: stackedDataArray_single[key].item()\n",
" for key in scanAxis\n",
" }\n",
"\n",
" filter.update(global_parameters)\n",
" \n",
" mongoID, _ = self.xdb.put(stackedDataArray_single)\n",
" \n",
" data_label = {\n",
" dataArray.name: \n",
" {\n",
" 'name': dataArray.name,\n",
" 'mongoID': mongoID,\n",
" 'engine': 'xarray',\n",
" 'dtype': 'dataArray',\n",
" }\n",
" }\n",
" \n",
" self.mongoDB['global'].update_one(filter, {\"$set\": data_label}, upsert=False)\n",
" \n",
" def _add_data_xarray_dataSet(self, shotNum, dataSet, name, scanAxis=None):\n",
" \n",
" if scanAxis is None:\n",
" scanAxis = list(dataSet.coords)\n",
" \n",
" dataSet.attrs = self._convert_numpy_type(dataSet.attrs)\n",
" \n",
" for key in list(dataSet.data_vars):\n",
" dataSet[key].attrs = self._convert_numpy_type(dataSet[key].attrs)\n",
" \n",
" stackedDataSet = dataSet.stack(_scanAxis=tuple(scanAxis))\n",
" stackedDataSet = stackedDataSet.groupby('_scanAxis')\n",
" \n",
" filter = { \n",
" 'year': self.year,\n",
" 'month': self.month,\n",
" 'day': self.day,\n",
" 'shotNum': shotNum,\n",
" }\n",
" \n",
" for i in stackedDataSet:\n",
" \n",
" stackedDataSet_single = i[1].drop('_scanAxis')\n",
" \n",
" global_parameters = {\n",
" 'global_parameters.' + key: stackedDataSet_single[key].item()\n",
" for key in scanAxis\n",
" }\n",
"\n",
" filter.update(global_parameters)\n",
" \n",
" mongoID, _ = self.xdb.put(dataSet)\n",
" \n",
" data_label = {\n",
" name: \n",
" {\n",
" 'name': name,\n",
" 'mongoID': mongoID,\n",
" 'engine': 'xarray',\n",
" 'dtype': 'dataSet',\n",
" }\n",
" }\n",
" \n",
" self.mongoDB['global'].update_one(filter, {\"$set\": data_label}, upsert=False)\n",
" \n",
" def _add_data_additional(self, shotNum, runNum, data, name):\n",
" \n",
" if runNum is None:\n",
" runNum = 0\n",
" \n",
" filter = { \n",
" 'year': self.year,\n",
" 'month': self.month,\n",
" 'day': self.day,\n",
" 'shotNum': shotNum,\n",
" 'runNum': runNum,\n",
" }\n",
" \n",
" mongoID = self.mongoDB.additional.insert_one(data).inserted_id\n",
" \n",
" data_label = {\n",
" name: \n",
" {\n",
" 'name': name,\n",
" 'mongoID': mongoID,\n",
" 'engine': 'additional',\n",
" 'dtype': 'dict',\n",
" }\n",
" }\n",
" \n",
" self.mongoDB['global'].update_one(filter, {\"$set\": data_label}, upsert=False)\n",
" \n",
" def add_data(self, shotNum, data, runNum=None, date=None, name=None, engine='normal'):\n",
" if not date is None:\n",
" self.set_date(date)\n",
" \n",
" if engine == 'normal':\n",
" self._add_data_normal(shotNum=shotNum, runNum=runNum, data=data)\n",
" elif engine == 'xarray':\n",
" if isinstance(data, type(xr.Dataset())):\n",
" self._add_data_xarray_dataSet(shotNum=shotNum, data=data, name=name)\n",
" else:\n",
" self._add_data_xarray_dataArray(shotNum=shotNum, data=data, name=name)\n",
" elif engine == 'additional':\n",
" self._add_data_additional(shotNum=shotNum, runNum=runNum, data=data, name=name)\n",
" \n",
" def read_global_single(self, shotNum, runNum, date=None):\n",
" \n",
" if not date is None:\n",
" self.set_date(date)\n",
" \n",
" filter = { \n",
" 'year': self.year,\n",
" 'month': self.month,\n",
" 'day': self.day,\n",
" 'shotNum': shotNum,\n",
" 'runNum': runNum,\n",
" }\n",
" \n",
" return self.mongoDB['global'].find_one(filter)\n",
" \n",
2023-06-13 19:23:56 +02:00
" def read_global_all(self, shotNum, date=None):\n",
" \n",
" from xarray.core.utils import equivalent\n",
" \n",
" if not date is None:\n",
" self.set_date(date)\n",
" \n",
" filter = { \n",
" 'year': self.year,\n",
" 'month': self.month,\n",
" 'day': self.day,\n",
" 'shotNum': shotNum,\n",
" }\n",
" \n",
" result = {}\n",
" dropped_attrs = OrderedDict()\n",
" \n",
" for doc in self.mongoDB['global'].find(filter):\n",
" \n",
" result.update(\n",
" {\n",
" key: value\n",
" for key, value in attrs.items()\n",
" if key not in result and key not in dropped_attrs.keys()\n",
" }\n",
" )\n",
" result = {\n",
" key: value\n",
" for key, value in result.items()\n",
" if key not in attrs or equivalent(attrs[key], value)\n",
" }\n",
" dropped_attrs.update(\n",
" {\n",
" key: []\n",
" for key in attrs if key not in result \n",
" }\n",
" )\n",
" \n",
" \n",
2023-06-13 18:16:24 +02:00
" def _load_data_single(self, mongoID, engine):\n",
" if engine == 'xarray':\n",
" return self.xdb.get(mongoID)\n",
" if engine == 'additional':\n",
" return self.mongoDB.additional.find_one({'_id': mongoID})\n",
" \n",
" def load_data_single(self, shotNum=None, runNum=None, globalDict=None, date=None, field=None):\n",
" \n",
" if not date is None:\n",
" self.set_date(date)\n",
" \n",
" if globalDict is None:\n",
" globalDict = self.read_global_single(shotNum=shotNum, runNum=runNum)\n",
" \n",
" if field is None:\n",
" field = globalDict\n",
" \n",
" res = field\n",
" \n",
" for key in field:\n",
" if isinstance(globalDict[key], dict) and ('mongoID' in globalDict[key]):\n",
" mongoID = globalDict[key]['mongoID']\n",
" engine = globalDict[key]['engine']\n",
" \n",
" res.update(\n",
" {\n",
" key: self._load_data_single(mongoID=mongoID, engine=engine)\n",
" }\n",
" )\n",
" \n",
" return res\n",
" \n",
" def load_data(self, shotNum=None, globalDict=None, date=None, field=None):\n",
" pass\n",
2023-06-13 19:23:56 +02:00
" \n",
2023-06-13 18:16:24 +02:00
"DB = MongoDB(mongoClient, mongoDB, date='2023/05/23')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"res = DB.load_data_single(shotNum='0069', field=['test'])\n",
"res"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"data = {\n",
" 'test':100\n",
"}\n",
"DB._add_data_additional(shotNum, data, name='test')"
]
},
{
"cell_type": "code",
"execution_count": 161,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<xarray.DataArray 'OD' (y: 300, x: 300)>\n",
"array([[ 0.1152197 , -0.01741923, 0.09469807, ..., -0.06412552,\n",
" 0.06190824, 0.02570519],\n",
" [ 0.04898483, -0.05190541, 0.04817805, ..., -0.04506388,\n",
" -0.07363725, 0.05574082],\n",
" [-0.06730349, 0.01648232, -0.03138377, ..., 0.10636001,\n",
" -0.05618196, 0.04319051],\n",
" ...,\n",
" [-0.07122968, -0.07122968, -0.04409723, ..., -0.03570343,\n",
" -0.04940228, -0.05279787],\n",
" [-0.07293278, 0.09247831, 0.0459079 , ..., -0.09443087,\n",
" 0.13291928, 0.06498517],\n",
" [-0.18293367, 0.0419475 , -0.13718765, ..., -0.10924595,\n",
" -0.01459836, 0.14135815]])\n",
"Coordinates:\n",
" compX_final_current float64 0.0\n",
" runs float64 0.0\n",
"Dimensions without coordinates: y, x\n",
"Attributes: (12/131)\n",
" IMAGE_SUBCLASS: IMAGE_GRAYSCALE\n",
" IMAGE_VERSION: 1.2\n",
" IMAGE_WHITE_IS_ZERO: 0\n",
" TOF_free: 0.022\n",
" abs_img_freq: 110.858\n",
" absorption_imaging_flag: True\n",
" ... ...\n",
" y_end: 1025\n",
" y_start: 725\n",
" x_center: 960\n",
" y_center: 875\n",
" x_span: 300\n",
" y_span: 300\n",
"<xarray.DataArray 'OD' (y: 300, x: 300)>\n",
"array([[ 0.01548795, 0.03431875, -0.06531109, ..., -0.03202512,\n",
" 0.0142653 , -0.06976544],\n",
" [ 0.0659188 , -0.1299843 , -0.15734163, ..., 0.01404251,\n",
" -0.00077257, 0.0423996 ],\n",
" [-0.01703309, -0.04878179, -0.11660439, ..., 0.02908039,\n",
" -0.00077257, 0.02864131],\n",
" ...,\n",
" [ 0.16628151, -0.02376209, 0.16628151, ..., 0.03312898,\n",
" -0.09314589, 0.01473161],\n",
" [ 0.11985542, 0.19028266, 0.02392004, ..., -0.07833081,\n",
" -0.04522434, 0.03201725],\n",
" [-0.00077257, 0.09019921, -0.00077257, ..., -0.06636986,\n",
" -0.00077257, 0.04367919]])\n",
"Coordinates:\n",
" compX_final_current float64 0.0\n",
" runs float64 1.0\n",
"Dimensions without coordinates: y, x\n",
"Attributes: (12/131)\n",
" IMAGE_SUBCLASS: IMAGE_GRAYSCALE\n",
" IMAGE_VERSION: 1.2\n",
" IMAGE_WHITE_IS_ZERO: 0\n",
" TOF_free: 0.022\n",
" abs_img_freq: 110.858\n",
" absorption_imaging_flag: True\n",
" ... ...\n",
" y_end: 1025\n",
" y_start: 725\n",
" x_center: 960\n",
" y_center: 875\n",
" x_span: 300\n",
" y_span: 300\n",
"<xarray.DataArray 'OD' (y: 300, x: 300)>\n",
"array([[ 0.2166106 , -0.06159272, -0.00653295, ..., -0.05454217,\n",
" 0.0247196 , 0.03543125],\n",
" [ 0.1175197 , -0.03879381, 0.00999635, ..., -0.03730461,\n",
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"Attributes: (12/131)\n",
" IMAGE_SUBCLASS: IMAGE_GRAYSCALE\n",
" IMAGE_VERSION: 1.2\n",
" IMAGE_WHITE_IS_ZERO: 0\n",
" TOF_free: 0.022\n",
" abs_img_freq: 110.858\n",
" absorption_imaging_flag: True\n",
" ... ...\n",
" y_end: 1025\n",
" y_start: 725\n",
" x_center: 960\n",
" y_center: 875\n",
" x_span: 300\n",
" y_span: 300\n",
"<xarray.DataArray 'OD' (y: 300, x: 300)>\n",
"array([[ 0.01130851, 0.06381319, -0.06990448, ..., -0.00639107,\n",
" 0.03741155, 0.02177981],\n",
" [ 0.1504514 , -0.06990448, -0.02319819, ..., -0.00639107,\n",
" 0.02346189, -0.08161449],\n",
" [ 0.02932701, 0.02694535, 0.09369239, ..., 0.02302281,\n",
" 0.1096811 , -0.02142895],\n",
" ...,\n",
" [ 0.01659845, 0.10608691, 0.05814745, ..., 0.06381319,\n",
" -0.06794896, -0.00639107],\n",
" [ 0.07157047, 0.11423692, -0.05185345, ..., -0.02213943,\n",
" -0.09600323, 0.05423355],\n",
" [ 0.0677169 , -0.02992157, -0.05185345, ..., 0.05423355,\n",
" -0.06354949, -0.05220061]])\n",
"Coordinates:\n",
" compX_final_current float64 0.02\n",
" runs float64 0.0\n",
"Dimensions without coordinates: y, x\n",
"Attributes: (12/131)\n",
" IMAGE_SUBCLASS: IMAGE_GRAYSCALE\n",
" IMAGE_VERSION: 1.2\n",
" IMAGE_WHITE_IS_ZERO: 0\n",
" TOF_free: 0.022\n",
" abs_img_freq: 110.858\n",
" absorption_imaging_flag: True\n",
" ... ...\n",
" y_end: 1025\n",
" y_start: 725\n",
" x_center: 960\n",
" y_center: 875\n",
" x_span: 300\n",
" y_span: 300\n",
"<xarray.DataArray 'OD' (y: 300, x: 300)>\n",
"array([[-0.0577009 , 0.00683762, 0.05643456, ..., -0.0577009 ,\n",
" 0.10527769, 0.02044327],\n",
" [-0.0259522 , -0.06462134, 0.00683762, ..., -0.04195254,\n",
" 0.05195806, 0.06839551],\n",
" [ 0.02364474, 0.07466022, 0.03858632, ..., 0.05643456,\n",
" 0.03669058, 0.10621009],\n",
" ...,\n",
" [ 0.10447609, 0.00683762, 0.17591395, ..., -0.12669377,\n",
" 0.02364474, -0.0472296 ],\n",
" [ 0.03350587, 0.05813091, -0.0396824 , ..., 0.12638277,\n",
" 0.00683762, 0.10527769],\n",
" [-0.01983063, 0.05684804, 0.03153023, ..., -0.02441492,\n",
" -0.08413416, -0.02542324]])\n",
"Coordinates:\n",
" compX_final_current float64 0.02\n",
" runs float64 1.0\n",
"Dimensions without coordinates: y, x\n",
"Attributes: (12/131)\n",
" IMAGE_SUBCLASS: IMAGE_GRAYSCALE\n",
" IMAGE_VERSION: 1.2\n",
" IMAGE_WHITE_IS_ZERO: 0\n",
" TOF_free: 0.022\n",
" abs_img_freq: 110.858\n",
" absorption_imaging_flag: True\n",
" ... ...\n",
" y_end: 1025\n",
" y_start: 725\n",
" x_center: 960\n",
" y_center: 875\n",
" x_span: 300\n",
" y_span: 300\n",
"<xarray.DataArray 'OD' (y: 300, x: 300)>\n",
"array([[ 0.04603954, 0.01094822, -0.00614622, ..., -0.07760518,\n",
" -0.02080048, 0.02533695],\n",
" [ 0.05895744, 0.04731586, -0.05464907, ..., -0.05687438,\n",
" -0.0223882 , -0.00505212],\n",
" [-0.02295334, -0.0058589 , 0.06054516, ..., 0.02598609,\n",
" 0.05606865, -0.02131265],\n",
" ...,\n",
" [ 0.1062584 , -0.08669025, 0.07690618, ..., -0.09259246,\n",
" 0.07250611, 0.08505619],\n",
" [ 0.0369237 , 0.06359195, -0.06503769, ..., -0.11041264,\n",
" 0.10191999, 0.06054516],\n",
" [ 0.01094822, 0.14100134, 0.14814934, ..., -0.02030433,\n",
" -0.0462102 , -0.04034508]])\n",
"Coordinates:\n",
" compX_final_current float64 0.02\n",
" runs float64 2.0\n",
"Dimensions without coordinates: y, x\n",
"Attributes: (12/131)\n",
" IMAGE_SUBCLASS: IMAGE_GRAYSCALE\n",
" IMAGE_VERSION: 1.2\n",
" IMAGE_WHITE_IS_ZERO: 0\n",
" TOF_free: 0.022\n",
" abs_img_freq: 110.858\n",
" absorption_imaging_flag: True\n",
" ... ...\n",
" y_end: 1025\n",
" y_start: 725\n",
" x_center: 960\n",
" y_center: 875\n",
" x_span: 300\n",
" y_span: 300\n"
]
}
],
"source": [
"DB._add_data_xarray_dataArray(shotNum, dataSet_cropOD)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"test = DB._convert_numpy_type(dataSet.OD.attrs)\n",
"\n",
"type(test['IMAGE_WHITE_IS_ZERO'])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"type(dataSet.OD.attrs['IMAGE_WHITE_IS_ZERO'])"
]
},
{
"cell_type": "code",
"execution_count": 164,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"atoms\n",
"background\n",
"dark\n",
"shotNum\n",
"OD\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\data\\AppData\\Roaming\\Python\\Python39\\site-packages\\xarray\\core\\variable.py:1745: PerformanceWarning: Reshaping is producing a large chunk. To accept the large\n",
"chunk and silence this warning, set the option\n",
" >>> with dask.config.set(**{'array.slicing.split_large_chunks': False}):\n",
" ... array.reshape(shape)\n",
"\n",
"To avoid creating the large chunks, set the option\n",
" >>> with dask.config.set(**{'array.slicing.split_large_chunks': True}):\n",
" ... array.reshape(shape)Explictly passing ``limit`` to ``reshape`` will also silence this warning\n",
" >>> array.reshape(shape, limit='128 MiB')\n",
" result = result._stack_once(dims, new_dim)\n"
]
}
],
"source": [
"DB._add_data_xarray_dataSet(shotNum, dataSet, 'aaa')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"xdb.put(dataSet_cropOD)"
]
},
{
"cell_type": "code",
"execution_count": 156,
"metadata": {},
"outputs": [],
"source": [
"DB.create_global(shotNum, dataSet)"
]
},
{
"cell_type": "code",
"execution_count": 171,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'_id': ObjectId('64889137f1f9594635fc401c'), 'year': 2023, 'month': 5, 'day': 23, 'shotNum': '0069', 'runNum': 0, 'global_parameters': {'TOF_free': 0.022, 'abs_img_freq': 110.858, 'absorption_imaging_flag': True, 'backup_data': True, 'blink_off_time': 0.001, 'blink_on_time': 0.001, 'c_duration': 0.2, 'carrier_amp': 3, 'carrier_freq': 0.85, 'carrier_offset': 0, 'carrier_phase': 0, 'channel_in_use': 1, 'cmot_final_current': 0.65, 'cmot_hold': 0.06, 'cmot_initial_current': 0.18, 'compX_current': 0, 'compX_current_sg': 0.0, 'compX_initial_current': 0, 'compY_current': 0, 'compY_current_sg': 0.0, 'compY_final_current': 0, 'compY_initial_current': 0, 'compZ_current': 0, 'compZ_current_sg': 0.189, 'compZ_final_current': 0.264, 'compZ_initial_current': 0, 'default_camera': 0, 'deltaf': 0.161, 'evap_1_arm_1_final_pow': 0.35, 'evap_1_arm_1_mod_depth_final': 0, 'evap_1_arm_1_mod_depth_initial': 1.0, 'evap_1_arm_1_mod_ramp_duration': 1.15, 'evap_1_arm_1_pow_ramp_duration': 1.65, 'evap_1_arm_1_start_pow': 7, 'evap_1_arm_2_final_pow': 5, 'evap_1_arm_2_ramp_duration': 0.5, 'evap_1_arm_2_start_pow': 0, 'evap_1_mod_ramp_trunc_value': 1, 'evap_1_pow_ramp_trunc_value': 1.0, 'evap_1_rate_constant_1': 0.525, 'evap_1_rate_constant_2': 0.51, 'evap_2_arm_1_final_pow': 0.037, 'evap_2_arm_1_start_pow': 0.35, 'evap_2_arm_2_final_pow': 0.09, 'evap_2_arm_2_start_pow': 5, 'evap_2_ramp_duration': 1.0, 'evap_2_ramp_trunc_value': 1.0, 'evap_2_rate_constant_1': 0.37, 'evap_2_rate_constant_2': 0.71, 'evap_3_arm_1_final_pow': 0.1038, 'evap_3_arm_1_mod_depth_final': 0.43, 'evap_3_arm_1_mod_depth_initial': 0, 'evap_3_arm_1_start_pow': 0.037, 'evap_3_ramp_duration': 0.1, 'evap_3_ramp_trunc_value': 1.0, 'evap_3_rate_constant_1': -0.879, 'evap_3_rate_constant_2': -0.297, 'final_amp': 0.00012, 'final_freq': 104.0, 'final_pow_1': 0.1038, 'final_pow_2': 0.09, 'gradCoil_current': 0.18, 'gradCoil_current_sg': 0, 'imaging_method': 'in_situ_absorption', 'imaging_pulse_duration': 2.5e-05, 'imaging_wavelength': 4.21291e-07, 'initial_amp': 0.62, 'initial_freq': 102.13, 'mod_depth_fin': 0.43, 'mod_depth_ini': 0, 'mod_depth_initial': 1.0, 'mot_3d_amp': 0.62, 'mot_3d_camera_trigger_duration': 0.00025, 'mot_3d_freq': 102.13, 'mot_load_duration': 2, 'odt_axis_camera_trigger_duration': 0.002, 'odt_hold_time_1': 0.01, 'odt_hold_time_2': 0.1, 'odt_hold_time_3': 0.1, 'odt_hold_time_4': 1.0, 'odt_hold_time_5': 0.01, 'operation_mode': 'SWEEP', 'pow_arm_1': 7, 'pow_arm_2': 0, 'pulse_delay': 8e-05, 'pulse_width': 0.01, 'push_amp': 0.16, 'push_freq': 102.66, 'ramp_duration': 1, 'recomp_ramp_duration': 0.5, 'recomp_ramp_pow_fin_arm_1': 0.1038, 'recomp_ramp_pow_fin_arm_2': 0.09, 'recomp_ramp_pow_ini_arm_1': 0.1038, 'recomp_ramp_pow_ini_arm_2': 0.09, 'save_results': False, 'sin_mod_amplitude': 0.00519, 'sin_mod_dc_offset': 0.1038, 'sin_mod_duration': nan, 'sin_mod_freq': nan, 'sin_mod_phase': 0.0, 'start_pow_1': 0.037, 'start_pow_2': 0.09, 'stern_gerlach_duration': 0.001, 'sweep_duration': 0.4, 'sweep_start_freq': 0.7695, 'sweep_stop_freq': 0.9305, 'tf_meas_ramp_duration': 0.1, 'wait_after_2dmot_off': 0, 'wait_time_between_images': 0.22, 'wavetype': 'SINE', 'x_offset': 0.0, 'x_offset_img': 0, 'y_offset': 0.0, 'y_offset_img': 0, 'z_offset': 0.189, 'z_offset_img': 0.189, 'compX_final_current': 0.0, 'runs': 0.0}, 'OD': {'name': 'OD', 'mongoID': ObjectId('648891baf1f9594635fc403d'), 'engine': 'xarray', 'dtype': 'dataArray'}, 'aaa': {'name': 'aaa', 'mongoID': ObjectId('64889337f1f9594635fc40c1'), 'engine': 'xarray', 'dtype': 'dataSet'}}\n"
]
},
{
"data": {
"text/plain": [
"dict_keys(['_id', 'year', 'month', 'day', 'shotNum', 'runNum', 'global_parameters', 'OD', 'aaa'])"
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]
},
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"execution_count": 171,
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"metadata": {},
"output_type": "execute_result"
}
],
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"source": [
"DB.load_data_single(shotNum='0069', runNum=0).keys()"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## Do a 2D two-peak gaussian fit to the OD images"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"### Do the fit"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from Analyser.FitAnalyser import ThomasFermi2dModel, DensityProfileBEC2dModel, polylog2_2d\n",
"\n",
"fitModel = DensityProfileBEC2dModel()\n",
"# fitModel = ThomasFermi2dModel()\n",
"\n",
"fitAnalyser = FitAnalyser(fitModel, fitDim=2)\n",
"\n",
"# fitAnalyser = FitAnalyser(\"Gaussian-2D\", fitDim=2)\n",
"\n",
"# dataSet_cropOD = dataSet_cropOD.chunk((1,1,100,100))\n",
"\n",
"params = fitAnalyser.guess(dataSet_cropOD, guess_kwargs=dict(pureBECThreshold=0.3), dask=\"parallelized\")\n",
"fitResult = fitAnalyser.fit(dataSet_cropOD, params).load()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"params.compute().item()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"fitCurve = fitAnalyser.eval(fitResult, x=np.arange(300), y=np.arange(300), dask=\"parallelized\").load()\n",
"\n",
"fitCurve.plot.pcolormesh(cmap='jet', vmin=0, col=scanAxis[0], row=scanAxis[1])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"fitModel2 = Polylog22dModel(prefix='thermal_')\n",
"fitAnalyser2 = FitAnalyser(fitModel2, fitDim=2)\n",
"fitCurve2 = fitAnalyser2.eval(fitResult, x=np.arange(300), y=np.arange(300), dask=\"parallelized\").load()\n",
"\n",
"fitModel3 = ThomasFermi2dModel(prefix='BEC_')\n",
"fitAnalyser3 = FitAnalyser(fitModel3, fitDim=2)\n",
"fitCurve3 = fitAnalyser3.eval(fitResult, x=np.arange(300), y=np.arange(300), dask=\"parallelized\").load()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"fig = plt.figure()\n",
"ax = fig.gca()\n",
"\n",
"dataSet_cropOD.sum(dim='x').plot(ax=ax, col=scanAxis[0], row=scanAxis[1])\n",
"fitCurve.sum(dim='x').plot(ax=ax, col=scanAxis[0], row=scanAxis[1])\n",
"fitCurve2.sum(dim='x').plot(ax=ax, col=scanAxis[0], row=scanAxis[1])\n",
"fitCurve3.sum(dim='x').plot(ax=ax, col=scanAxis[0], row=scanAxis[1])\n",
"\n",
"plt.show()\n",
"\n",
"fig = plt.figure()\n",
"ax = fig.gca()\n",
"\n",
"dataSet_cropOD.sum(dim='y').plot(ax=ax, col=scanAxis[0], row=scanAxis[1])\n",
"fitCurve.sum(dim='y').plot(ax=ax, col=scanAxis[0], row=scanAxis[1])\n",
"fitCurve2.sum(dim='y').plot(ax=ax, col=scanAxis[0], row=scanAxis[1])\n",
"fitCurve3.sum(dim='y').plot(ax=ax, col=scanAxis[0], row=scanAxis[1])\n",
"\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"value = fitAnalyser.get_fit_value(fitResult)\n",
"std = fitAnalyser.get_fit_std(fitResult)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"fitResult.item()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"value"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"# upload data to MongoDB"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"xdb = xarray_mongodb.XarrayMongoDB(mongoDB)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"value = fitAnalyser.get_fit_value(fitResult)\n",
"value"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"dataSet_cropOD"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"dataSet_cropOD.attrs['name'] = 'name'"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"dataSet_cropOD.attrs['IMAGE_WHITE_IS_ZERO']"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"dataSet_cropOD"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"type(dataSet_cropOD.attrs['absorption_imaging_flag'].item())"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"del dataSet_cropOD.attrs['IMAGE_WHITE_IS_ZERO']"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import builtins\n",
"npTypeDict = {v: getattr(builtins, k) for k, v in np.typeDict.items() if k in vars(builtins)}\n",
"\n",
"for key in dataSet_cropOD.attrs:\n",
" typeKey = type(dataSet_cropOD.attrs[key])\n",
" if typeKey in npTypeDict:\n",
" dataSet_cropOD.attrs[key] = dataSet_cropOD.attrs[key].item()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import builtins\n",
"a = {v: getattr(builtins, k) for k, v in np.typeDict.items() if k in vars(builtins)}\n",
"a\n",
"a[type(dataSet_cropOD.attrs['absorption_imaging_flag'])]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"_id, _ = xdb.put(dataSet_cropOD)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"_id"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# _id = '646e3cbbdb91e17db4b4cbd2'"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
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"source": [
"xdb.get(_id)"
]
},
{
"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
"c = bson.objectid.ObjectId('646e4919802812f029b385d7')\n",
"c"
]
},
{
"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
"xdb.get(c)"
]
},
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{
"cell_type": "code",
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"execution_count": null,
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"metadata": {},
"outputs": [],
"source": [
"import datetime\n",
"post = {\"author\": \"Mike\",\n",
" \"data_id\": _id,\n",
" \"tags\": [\"mongodb\", \"python\", \"pymongo\"],\n",
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" \"date\": datetime.datetime.utcnow(),\n",
" }\n"
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]
},
{
"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
"posts = mongoCollection\n",
"post_id = posts.insert_one(post).inserted_id\n",
"post_id"
]
},
{
"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"posts.find_one({'_id': bson.objectid.ObjectId('648318ae129ec5a1a24a7353')})"
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]
},
{
"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
"for i in posts.find_one({'_id': bson.objectid.ObjectId('648318ae129ec5a1a24a7353')}):\n",
" bb = i\n",
" \n",
"bb['test']"
]
},
{
"cell_type": "code",
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"execution_count": null,
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"metadata": {},
"outputs": [],
"source": [
"import gridfs\n",
"\n",
"fs = gridfs.GridFS(mongoDB, 'xarray')"
]
},
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{
"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
"f = dataSet_cropOD.to_dict()\n",
"f"
]
},
{
"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
"print(ff)"
]
},
{
"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
"import json\n",
"ff = json.dumps(f) \n",
"fs.put(ff, encoding='utf-8')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
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{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"fs.put(b\"hello world\")"
]
},
{
"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"c = bson.objectid.ObjectId('6482f4a3129ec5a1a24a7342')\n",
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"\n",
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"fs.get(c)"
]
},
{
"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
"print(fs.get(c))"
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]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"np.sqrt(np.sum([0.061**2, 0.334**2, 0.447**2]))"
]
},
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{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "py39",
"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",
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"version": "3.9.12"
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},
"orig_nbformat": 4
},
"nbformat": 4,
"nbformat_minor": 2
}
