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{ "cells": [ { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "# Import supporting package" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import xarray as xr\n", "import numpy as np\n", "import copy\n", "\n", "from uncertainties import ufloat\n", "from uncertainties import unumpy as unp\n", "from uncertainties import umath\n", "import random\n", "import matplotlib.pyplot as plt\n", "plt.rcParams['font.size'] = 12\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 NewFitModel, DensityProfileBEC2dModel\n", "from ToolFunction.ToolFunction import *\n", "\n", "from scipy.optimize import curve_fit\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()\n", "\n", "# %matplotlib notebook" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## Start a client for parallel computing" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "<div>\n", " <div style=\"width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;\"> </div>\n", " <div style=\"margin-left: 48px;\">\n", " <h3 style=\"margin-bottom: 0px;\">Client</h3>\n", " <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Client-8ba1675f-1745-11ee-81b0-80e82ce2fa8e</p>\n", " <table style=\"width: 100%; text-align: left;\">\n", "\n", " <tr>\n", " \n", " <td style=\"text-align: left;\"><strong>Connection method:</strong> Cluster object</td>\n", " <td style=\"text-align: left;\"><strong>Cluster type:</strong> distributed.LocalCluster</td>\n", " \n", " </tr>\n", "\n", " \n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:8787/status\" target=\"_blank\">http://127.0.0.1:8787/status</a>\n", " </td>\n", " <td style=\"text-align: left;\"></td>\n", " </tr>\n", " \n", "\n", " </table>\n", "\n", " \n", "\n", " \n", " <details>\n", " <summary style=\"margin-bottom: 20px;\"><h3 style=\"display: inline;\">Cluster Info</h3></summary>\n", " <div class=\"jp-RenderedHTMLCommon jp-RenderedHTML jp-mod-trusted jp-OutputArea-output\">\n", " <div style=\"width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;\">\n", " </div>\n", " <div style=\"margin-left: 48px;\">\n", " <h3 style=\"margin-bottom: 0px; margin-top: 0px;\">LocalCluster</h3>\n", " <p style=\"color: #9D9D9D; margin-bottom: 0px;\">5686383f</p>\n", " <table style=\"width: 100%; text-align: left;\">\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Dashboard:</strong> <a href=\"http://127.0.0.1:8787/status\" target=\"_blank\">http://127.0.0.1:8787/status</a>\n", " </td>\n", " <td style=\"text-align: left;\">\n", " <strong>Workers:</strong> 8\n", " </td>\n", " </tr>\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Total threads:</strong> 128\n", " </td>\n", " <td style=\"text-align: left;\">\n", " <strong>Total memory:</strong> 149.01 GiB\n", " </td>\n", " </tr>\n", " \n", " <tr>\n", " <td style=\"text-align: left;\"><strong>Status:</strong> running</td>\n", " <td style=\"text-align: left;\"><strong>Using processes:</strong> True</td>\n", "</tr>\n", "\n", " \n", " </table>\n", "\n", " <details>\n", " <summary style=\"margin-bottom: 20px;\">\n", " <h3 style=\"display: inline;\">Scheduler Info</h3>\n", " </summary>\n", "\n", " <div style=\"\">\n", " <div>\n", " <div style=\"width: 24px; height: 24px; background-color: #FFF7E5; border: 3px solid #FF6132; border-radius: 5px; position: absolute;\"> </div>\n", " <div style=\"margin-left: 48px;\">\n", " <h3 style=\"margin-bottom: 0px;\">Scheduler</h3>\n", " <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Scheduler-579b49b9-56d3-437e-8497-ccb704499216</p>\n", " <table style=\"width: 100%; text-align: left;\">\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Comm:</strong> tcp://127.0.0.1:58438\n", " </td>\n", " <td style=\"text-align: left;\">\n", " <strong>Workers:</strong> 8\n", " </td>\n", " </tr>\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Dashboard:</strong> <a href=\"http://127.0.0.1:8787/status\" target=\"_blank\">http://127.0.0.1:8787/status</a>\n", " </td>\n", " <td style=\"text-align: left;\">\n", " <strong>Total threads:</strong> 128\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> 149.01 GiB\n", " </td>\n", " </tr>\n", " </table>\n", " </div>\n", " </div>\n", "\n", " <details style=\"margin-left: 48px;\">\n", " <summary style=\"margin-bottom: 20px;\">\n", " <h3 style=\"display: inline;\">Workers</h3>\n", " </summary>\n", "\n", " \n", " <div style=\"margin-bottom: 20px;\">\n", " <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n", " <div style=\"margin-left: 48px;\">\n", " <details>\n", " <summary>\n", " <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 0</h4>\n", " </summary>\n", " <table style=\"width: 100%; text-align: left;\">\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Comm: </strong> tcp://127.0.0.1:58495\n", " </td>\n", " <td style=\"text-align: left;\">\n", " <strong>Total threads: </strong> 16\n", " </td>\n", " </tr>\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:58496/status\" target=\"_blank\">http://127.0.0.1:58496/status</a>\n", " </td>\n", " <td style=\"text-align: left;\">\n", " <strong>Memory: </strong> 18.63 GiB\n", " </td>\n", " </tr>\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Nanny: </strong> tcp://127.0.0.1:58441\n", " </td>\n", " <td style=\"text-align: left;\"></td>\n", " </tr>\n", " <tr>\n", " <td colspan=\"2\" style=\"text-align: left;\">\n", " <strong>Local directory: </strong> C:\\Users\\data\\AppData\\Local\\Temp\\dask-worker-space\\worker-fjkqs65s\n", " </td>\n", " </tr>\n", "\n", " \n", "\n", " \n", "\n", " </table>\n", " </details>\n", " </div>\n", " </div>\n", " \n", " <div style=\"margin-bottom: 20px;\">\n", " <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n", " <div style=\"margin-left: 48px;\">\n", " <details>\n", " <summary>\n", " <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 1</h4>\n", " </summary>\n", " <table style=\"width: 100%; text-align: left;\">\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Comm: </strong> tcp://127.0.0.1:58478\n", " </td>\n", " <td style=\"text-align: left;\">\n", " <strong>Total threads: </strong> 16\n", " </td>\n", " </tr>\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:58481/status\" target=\"_blank\">http://127.0.0.1:58481/status</a>\n", " </td>\n", " <td style=\"text-align: left;\">\n", " <strong>Memory: </strong> 18.63 GiB\n", " </td>\n", " </tr>\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Nanny: </strong> tcp://127.0.0.1:58442\n", " </td>\n", " <td style=\"text-align: left;\"></td>\n", " </tr>\n", " <tr>\n", " <td colspan=\"2\" style=\"text-align: left;\">\n", " <strong>Local directory: </strong> C:\\Users\\data\\AppData\\Local\\Temp\\dask-worker-space\\worker-2zpxzh7e\n", " </td>\n", " </tr>\n", "\n", " \n", "\n", " \n", "\n", " </table>\n", " </details>\n", " </div>\n", " </div>\n", " \n", " <div style=\"margin-bottom: 20px;\">\n", " <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n", " <div style=\"margin-left: 48px;\">\n", " <details>\n", " <summary>\n", " <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 2</h4>\n", " </summary>\n", " <table style=\"width: 100%; text-align: left;\">\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Comm: </strong> tcp://127.0.0.1:58485\n", " </td>\n", " <td style=\"text-align: left;\">\n", " <strong>Total threads: </strong> 16\n", " </td>\n", " </tr>\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:58489/status\" target=\"_blank\">http://127.0.0.1:58489/status</a>\n", " </td>\n", " <td style=\"text-align: left;\">\n", " <strong>Memory: </strong> 18.63 GiB\n", " </td>\n", " </tr>\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Nanny: </strong> tcp://127.0.0.1:58443\n", " </td>\n", " <td style=\"text-align: left;\"></td>\n", " </tr>\n", " <tr>\n", " <td colspan=\"2\" style=\"text-align: left;\">\n", " <strong>Local directory: </strong> C:\\Users\\data\\AppData\\Local\\Temp\\dask-worker-space\\worker-xj22aq7d\n", " </td>\n", " </tr>\n", "\n", " \n", "\n", " \n", "\n", " </table>\n", " </details>\n", " </div>\n", " </div>\n", " \n", " <div style=\"margin-bottom: 20px;\">\n", " <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n", " <div style=\"margin-left: 48px;\">\n", " <details>\n", " <summary>\n", " <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 3</h4>\n", " </summary>\n", " <table style=\"width: 100%; text-align: left;\">\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Comm: </strong> tcp://127.0.0.1:58483\n", " </td>\n", " <td style=\"text-align: left;\">\n", " <strong>Total threads: </strong> 16\n", " </td>\n", " </tr>\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:58486/status\" target=\"_blank\">http://127.0.0.1:58486/status</a>\n", " </td>\n", " <td style=\"text-align: left;\">\n", " <strong>Memory: </strong> 18.63 GiB\n", " </td>\n", " </tr>\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Nanny: </strong> tcp://127.0.0.1:58444\n", " </td>\n", " <td style=\"text-align: left;\"></td>\n", " </tr>\n", " <tr>\n", " <td colspan=\"2\" style=\"text-align: left;\">\n", " <strong>Local directory: </strong> C:\\Users\\data\\AppData\\Local\\Temp\\dask-worker-space\\worker-ywxt37o0\n", " </td>\n", " </tr>\n", "\n", " \n", "\n", " \n", "\n", " </table>\n", " </details>\n", " </div>\n", " </div>\n", " \n", " <div style=\"margin-bottom: 20px;\">\n", " <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n", " <div style=\"margin-left: 48px;\">\n", " <details>\n", " <summary>\n", " <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 4</h4>\n", " </summary>\n", " <table style=\"width: 100%; text-align: left;\">\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Comm: </strong> tcp://127.0.0.1:58460\n", " </td>\n", " <td style=\"text-align: left;\">\n", " <strong>Total threads: </strong> 16\n", " </td>\n", " </tr>\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:58473/status\" target=\"_blank\">http://127.0.0.1:58473/status</a>\n", " </td>\n", " <td style=\"text-align: left;\">\n", " <strong>Memory: </strong> 18.63 GiB\n", " </td>\n", " </tr>\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Nanny: </strong> tcp://127.0.0.1:58445\n", " </td>\n", " <td style=\"text-align: left;\"></td>\n", " </tr>\n", " <tr>\n", " <td colspan=\"2\" style=\"text-align: left;\">\n", " <strong>Local directory: </strong> C:\\Users\\data\\AppData\\Local\\Temp\\dask-worker-space\\worker-r165h314\n", " </td>\n", " </tr>\n", "\n", " \n", "\n", " \n", "\n", " </table>\n", " </details>\n", " </div>\n", " </div>\n", " \n", " <div style=\"margin-bottom: 20px;\">\n", " <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n", " <div style=\"margin-left: 48px;\">\n", " <details>\n", " <summary>\n", " <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 5</h4>\n", " </summary>\n", " <table style=\"width: 100%; text-align: left;\">\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Comm: </strong> tcp://127.0.0.1:58492\n", " </td>\n", " <td style=\"text-align: left;\">\n", " <strong>Total threads: </strong> 16\n", " </td>\n", " </tr>\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:58493/status\" target=\"_blank\">http://127.0.0.1:58493/status</a>\n", " </td>\n", " <td style=\"text-align: left;\">\n", " <strong>Memory: </strong> 18.63 GiB\n", " </td>\n", " </tr>\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Nanny: </strong> tcp://127.0.0.1:58446\n", " </td>\n", " <td style=\"text-align: left;\"></td>\n", " </tr>\n", " <tr>\n", " <td colspan=\"2\" style=\"text-align: left;\">\n", " <strong>Local directory: </strong> C:\\Users\\data\\AppData\\Local\\Temp\\dask-worker-space\\worker-y9scwwnw\n", " </td>\n", " </tr>\n", "\n", " \n", "\n", " \n", "\n", " </table>\n", " </details>\n", " </div>\n", " </div>\n", " \n", " <div style=\"margin-bottom: 20px;\">\n", " <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n", " <div style=\"margin-left: 48px;\">\n", " <details>\n", " <summary>\n", " <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 6</h4>\n", " </summary>\n", " <table style=\"width: 100%; text-align: left;\">\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Comm: </strong> tcp://127.0.0.1:58477\n", " </td>\n", " <td style=\"text-align: left;\">\n", " <strong>Total threads: </strong> 16\n", " </td>\n", " </tr>\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:58479/status\" target=\"_blank\">http://127.0.0.1:58479/status</a>\n", " </td>\n", " <td style=\"text-align: left;\">\n", " <strong>Memory: </strong> 18.63 GiB\n", " </td>\n", " </tr>\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Nanny: </strong> tcp://127.0.0.1:58447\n", " </td>\n", " <td style=\"text-align: left;\"></td>\n", " </tr>\n", " <tr>\n", " <td colspan=\"2\" style=\"text-align: left;\">\n", " <strong>Local directory: </strong> C:\\Users\\data\\AppData\\Local\\Temp\\dask-worker-space\\worker-6gncvkv7\n", " </td>\n", " </tr>\n", "\n", " \n", "\n", " \n", "\n", " </table>\n", " </details>\n", " </div>\n", " </div>\n", " \n", " <div style=\"margin-bottom: 20px;\">\n", " <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n", " <div style=\"margin-left: 48px;\">\n", " <details>\n", " <summary>\n", " <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 7</h4>\n", " </summary>\n", " <table style=\"width: 100%; text-align: left;\">\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Comm: </strong> tcp://127.0.0.1:58484\n", " </td>\n", " <td style=\"text-align: left;\">\n", " <strong>Total threads: </strong> 16\n", " </td>\n", " </tr>\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:58488/status\" target=\"_blank\">http://127.0.0.1:58488/status</a>\n", " </td>\n", " <td style=\"text-align: left;\">\n", " <strong>Memory: </strong> 18.63 GiB\n", " </td>\n", " </tr>\n", " <tr>\n", " <td style=\"text-align: left;\">\n", " <strong>Nanny: </strong> tcp://127.0.0.1:58448\n", " </td>\n", " <td style=\"text-align: left;\"></td>\n", " </tr>\n", " <tr>\n", " <td colspan=\"2\" style=\"text-align: left;\">\n", " <strong>Local directory: </strong> C:\\Users\\data\\AppData\\Local\\Temp\\dask-worker-space\\worker-4vducatr\n", " </td>\n", " </tr>\n", "\n", " \n", "\n", " \n", "\n", " </table>\n", " </details>\n", " </div>\n", " </div>\n", " \n", "\n", " </details>\n", "</div>\n", "\n", " </details>\n", " </div>\n", "</div>\n", " </details>\n", " \n", "\n", " </div>\n", "</div>" ], "text/plain": [ "<Client: 'tcp://127.0.0.1:58438' processes=8 threads=128, memory=149.01 GiB>" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from dask.distributed import Client\n", "client = Client(n_workers=8, threads_per_worker=16, processes=True, memory_limit='20GB')\n", "client" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## Start a client for Mongo DB" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "import pymongo\n", "import xarray_mongodb\n", "\n", "from DataContainer.MongoDB import MongoDB\n", "\n", "mongoClient = pymongo.MongoClient('mongodb://control:DyLab2021@127.0.0.1:27017/?authMechanism=DEFAULT')" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## Set global path for experiment" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "groupList = [\n", " \"images/MOT_3D_Camera/in_situ_absorption\",\n", " \"images/ODT_1_Axis_Camera/in_situ_absorption\",\n", " \"images/ODT_2_Axis_Camera/in_situ_absorption\",\n", "]\n", "\n", "dskey = {\n", " \"images/MOT_3D_Camera/in_situ_absorption\": \"camera_0\",\n", " \"images/ODT_1_Axis_Camera/in_situ_absorption\": \"camera_1\",\n", " \"images/ODT_2_Axis_Camera/in_situ_absorption\": \"camera_2\",\n", "}\n" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "img_dir = 'C:/Users/control/DyLab/Experiments/DyBEC/'\n", "SequenceName = \"Repetition_scan\"\n", "folderPath = img_dir + SequenceName + \"/\" + get_date()\n", "\n", "mongoDB = mongoClient[SequenceName]\n", "\n", "DB = MongoDB(mongoClient, mongoDB, date=get_date())" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "# Repetition Scans" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## scan MOT freq" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The detected scaning axes and values are: \n", "\n", "{'initial_freq': array([101. , 101.25, 101.5 , 101.75, 102. , 102.25, 102.5 , 102.75,\n", " 103. , 103.25]), 'runs': array([0., 1., 2.])}\n" ] }, { "data": { "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n if (typeof WebSocket !== 'undefined') {\n return WebSocket;\n } else if (typeof MozWebSocket !== 'undefined') {\n return MozWebSocket;\n } else {\n alert(\n 'Your browser does not have WebSocket support. ' +\n 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n 'Firefox 4 and 5 are also supported but you ' +\n 'have to enable WebSockets in about:config.'\n );\n }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n this.id = figure_id;\n\n this.ws = websocket;\n\n this.supports_binary = this.ws.binaryType !== undefined;\n\n if (!this.supports_binary) {\n var warnings = document.getElementById('mpl-warnings');\n if (warnings) {\n warnings.style.display = 'block';\n warnings.textContent =\n 'This browser does not support binary websocket messages. ' +\n 'Performance may be slow.';\n }\n }\n\n this.imageObj = new Image();\n\n this.context = undefined;\n this.message = undefined;\n this.canvas = undefined;\n this.rubberband_canvas = undefined;\n this.rubberband_context = undefined;\n this.format_dropdown = undefined;\n\n this.image_mode = 'full';\n\n this.root = document.createElement('div');\n this.root.setAttribute('style', 'display: inline-block');\n this._root_extra_style(this.root);\n\n parent_element.appendChild(this.root);\n\n this._init_header(this);\n this._init_canvas(this);\n this._init_toolbar(this);\n\n var fig = this;\n\n this.waiting = false;\n\n this.ws.onopen = function () {\n fig.send_message('supports_binary', { value: fig.supports_binary });\n fig.send_message('send_image_mode', {});\n if (fig.ratio !== 1) {\n fig.send_message('set_device_pixel_ratio', {\n device_pixel_ratio: fig.ratio,\n });\n }\n fig.send_message('refresh', {});\n };\n\n this.imageObj.onload = function () {\n if (fig.image_mode === 'full') {\n // Full images could contain transparency (where diff images\n // almost always do), so we need to clear the canvas so that\n // there is no ghosting.\n fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n }\n fig.context.drawImage(fig.imageObj, 0, 0);\n };\n\n this.imageObj.onunload = function () {\n fig.ws.close();\n };\n\n this.ws.onmessage = this._make_on_message_function(this);\n\n this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n var titlebar = document.createElement('div');\n titlebar.classList =\n 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n var titletext = document.createElement('div');\n titletext.classList = 'ui-dialog-title';\n titletext.setAttribute(\n 'style',\n 'width: 100%; text-align: center; padding: 3px;'\n );\n titlebar.appendChild(titletext);\n this.root.appendChild(titlebar);\n this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n var fig = this;\n\n var canvas_div = (this.canvas_div = document.createElement('div'));\n canvas_div.setAttribute(\n 'style',\n 'border: 1px solid #ddd;' +\n 'box-sizing: content-box;' +\n 'clear: both;' +\n 'min-height: 1px;' +\n 'min-width: 1px;' +\n 'outline: 0;' +\n 'overflow: hidden;' +\n 'position: relative;' +\n 'resize: both;'\n );\n\n function on_keyboard_event_closure(name) {\n return function (event) {\n return fig.key "text/plain": [ "<IPython.core.display.Javascript object>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "<img 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], "text/plain": [ "<IPython.core.display.HTML object>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "%matplotlib notebook\n", "shotNum = \"0000\"\n", "filePath = folderPath + \"/\" + shotNum + \"/*.h5\"\n", "\n", "dataSetDict = {\n", " dskey[groupList[i]]: read_hdf5_file(filePath, groupList[i])\n", " for i in range(len(groupList))\n", "}\n", "\n", "dataSet = dataSetDict[\"camera_1\"]\n", "\n", "print_scanAxis(dataSet)\n", "\n", "scanAxis = get_scanAxis(dataSet)\n", "\n", "dataSet = auto_rechunk(dataSet)\n", "\n", "dataSet = imageAnalyser.get_absorption_images(dataSet)\n", "\n", "imageAnalyser.center = (310, 825)\n", "imageAnalyser.span = (550, 1250)\n", "imageAnalyser.fraction = (0.1, 0.1)\n", "\n", "dataSet_cropOD = imageAnalyser.crop_image(dataSet.OD)\n", "dataSet_cropOD = imageAnalyser.substract_offset(dataSet_cropOD).load()\n", "\n", "Ncount = imageAnalyser.get_Ncount(dataSet_cropOD)\n", "Ncount_mean = calculate_mean(Ncount)\n", "Ncount_std = calculate_std(Ncount)\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "Ncount_mean.plot.errorbar(ax=ax, yerr = Ncount_std, fmt='ob')\n", "plt.xlabel('MOT AOM Freq (MHz)')\n", "plt.ylabel('NCount')\n", "plt.tight_layout()\n", "plt.grid(visible=1)\n", "plt.show()\n", "\n", "# DB.create_global(shotNum, dataSet)\n", "# DB.add_data(shotNum, dataSet_cropOD, engine='xarray')" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## scan Push freq" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The detected scaning axes and values are: \n", "\n", "{'push_freq': array([101.1, 101.6, 102.1, 102.6, 103.1, 103.6, 104.1, 104.6, 105.1,\n", " 105.6, 106.1]), 'runs': array([0., 1., 2.])}\n" ] }, { "data": { "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n if (typeof WebSocket !== 'undefined') {\n return WebSocket;\n } else if (typeof MozWebSocket !== 'undefined') {\n return MozWebSocket;\n } else {\n alert(\n 'Your browser does not have WebSocket support. ' +\n 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n 'Firefox 4 and 5 are also supported but you ' +\n 'have to enable WebSockets in about:config.'\n );\n }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n this.id = figure_id;\n\n this.ws = websocket;\n\n this.supports_binary = this.ws.binaryType !== undefined;\n\n if (!this.supports_binary) {\n var warnings = document.getElementById('mpl-warnings');\n if (warnings) {\n warnings.style.display = 'block';\n warnings.textContent =\n 'This browser does not support binary websocket messages. ' +\n 'Performance may be slow.';\n }\n }\n\n this.imageObj = new Image();\n\n this.context = undefined;\n this.message = undefined;\n this.canvas = undefined;\n this.rubberband_canvas = undefined;\n this.rubberband_context = undefined;\n this.format_dropdown = undefined;\n\n this.image_mode = 'full';\n\n this.root = document.createElement('div');\n this.root.setAttribute('style', 'display: inline-block');\n this._root_extra_style(this.root);\n\n parent_element.appendChild(this.root);\n\n this._init_header(this);\n this._init_canvas(this);\n this._init_toolbar(this);\n\n var fig = this;\n\n this.waiting = false;\n\n this.ws.onopen = function () {\n fig.send_message('supports_binary', { value: fig.supports_binary });\n fig.send_message('send_image_mode', {});\n if (fig.ratio !== 1) {\n fig.send_message('set_device_pixel_ratio', {\n device_pixel_ratio: fig.ratio,\n });\n }\n fig.send_message('refresh', {});\n };\n\n this.imageObj.onload = function () {\n if (fig.image_mode === 'full') {\n // Full images could contain transparency (where diff images\n // almost always do), so we need to clear the canvas so that\n // there is no ghosting.\n fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n }\n fig.context.drawImage(fig.imageObj, 0, 0);\n };\n\n this.imageObj.onunload = function () {\n fig.ws.close();\n };\n\n this.ws.onmessage = this._make_on_message_function(this);\n\n this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n var titlebar = document.createElement('div');\n titlebar.classList =\n 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n var titletext = document.createElement('div');\n titletext.classList = 'ui-dialog-title';\n titletext.setAttribute(\n 'style',\n 'width: 100%; text-align: center; padding: 3px;'\n );\n titlebar.appendChild(titletext);\n this.root.appendChild(titlebar);\n this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n var fig = this;\n\n var canvas_div = (this.canvas_div = document.createElement('div'));\n canvas_div.setAttribute(\n 'style',\n 'border: 1px solid #ddd;' +\n 'box-sizing: content-box;' +\n 'clear: both;' +\n 'min-height: 1px;' +\n 'min-width: 1px;' +\n 'outline: 0;' +\n 'overflow: hidden;' +\n 'position: relative;' +\n 'resize: both;'\n );\n\n function on_keyboard_event_closure(name) {\n return function (event) {\n return fig.key "text/plain": [ "<IPython.core.display.Javascript object>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "<img 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], "text/plain": [ "<IPython.core.display.HTML object>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "%matplotlib notebook\n", "shotNum = \"0001\"\n", "filePath = folderPath + \"/\" + shotNum + \"/*.h5\"\n", "\n", "dataSetDict = {\n", " dskey[groupList[i]]: read_hdf5_file(filePath, groupList[i])\n", " for i in range(len(groupList))\n", "}\n", "\n", "dataSet = dataSetDict[\"camera_1\"]\n", "\n", "print_scanAxis(dataSet)\n", "\n", "scanAxis = get_scanAxis(dataSet)\n", "\n", "dataSet = auto_rechunk(dataSet)\n", "\n", "dataSet = imageAnalyser.get_absorption_images(dataSet)\n", "\n", "imageAnalyser.center = (310, 825)\n", "imageAnalyser.span = (550, 1250)\n", "imageAnalyser.fraction = (0.1, 0.1)\n", "\n", "dataSet_cropOD = imageAnalyser.crop_image(dataSet.OD)\n", "dataSet_cropOD = imageAnalyser.substract_offset(dataSet_cropOD).load()\n", "\n", "Ncount = imageAnalyser.get_Ncount(dataSet_cropOD)\n", "Ncount_mean = calculate_mean(Ncount)\n", "Ncount_std = calculate_std(Ncount)\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "Ncount_mean.plot.errorbar(ax=ax, yerr = Ncount_std, fmt='ob')\n", "plt.xlabel('Push AOM Freq (MHz)')\n", "plt.ylabel('NCount')\n", "plt.tight_layout()\n", "plt.grid(visible=1)\n", "plt.show()\n", "\n", "# DB.create_global(shotNum, dataSet)\n", "# DB.add_data(shotNum, dataSet_cropOD, engine='xarray')" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## scan Z comp current" ] }, { "cell_type": "code", "execution_count": 24, "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The detected scaning axes and values are: \n", "\n", "{'compZ_final_current': array([0.242 , 0.2427, 0.2434, 0.2441, 0.2448, 0.2455, 0.2462, 0.2469,\n", " 0.2476, 0.2483, 0.249 , 0.2497, 0.2504, 0.2511, 0.2518]), 'runs': array([0., 1., 2.])}\n" ] }, { "data": { "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n if (typeof WebSocket !== 'undefined') {\n return WebSocket;\n } else if (typeof MozWebSocket !== 'undefined') {\n return MozWebSocket;\n } else {\n alert(\n 'Your browser does not have WebSocket support. ' +\n 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n 'Firefox 4 and 5 are also supported but you ' +\n 'have to enable WebSockets in about:config.'\n );\n }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n this.id = figure_id;\n\n this.ws = websocket;\n\n this.supports_binary = this.ws.binaryType !== undefined;\n\n if (!this.supports_binary) {\n var warnings = document.getElementById('mpl-warnings');\n if (warnings) {\n warnings.style.display = 'block';\n warnings.textContent =\n 'This browser does not support binary websocket messages. ' +\n 'Performance may be slow.';\n }\n }\n\n this.imageObj = new Image();\n\n this.context = undefined;\n this.message = undefined;\n this.canvas = undefined;\n this.rubberband_canvas = undefined;\n this.rubberband_context = undefined;\n this.format_dropdown = undefined;\n\n this.image_mode = 'full';\n\n this.root = document.createElement('div');\n this.root.setAttribute('style', 'display: inline-block');\n this._root_extra_style(this.root);\n\n parent_element.appendChild(this.root);\n\n this._init_header(this);\n this._init_canvas(this);\n this._init_toolbar(this);\n\n var fig = this;\n\n this.waiting = false;\n\n this.ws.onopen = function () {\n fig.send_message('supports_binary', { value: fig.supports_binary });\n fig.send_message('send_image_mode', {});\n if (fig.ratio !== 1) {\n fig.send_message('set_device_pixel_ratio', {\n device_pixel_ratio: fig.ratio,\n });\n }\n fig.send_message('refresh', {});\n };\n\n this.imageObj.onload = function () {\n if (fig.image_mode === 'full') {\n // Full images could contain transparency (where diff images\n // almost always do), so we need to clear the canvas so that\n // there is no ghosting.\n fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n }\n fig.context.drawImage(fig.imageObj, 0, 0);\n };\n\n this.imageObj.onunload = function () {\n fig.ws.close();\n };\n\n this.ws.onmessage = this._make_on_message_function(this);\n\n this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n var titlebar = document.createElement('div');\n titlebar.classList =\n 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n var titletext = document.createElement('div');\n titletext.classList = 'ui-dialog-title';\n titletext.setAttribute(\n 'style',\n 'width: 100%; text-align: center; padding: 3px;'\n );\n titlebar.appendChild(titletext);\n this.root.appendChild(titlebar);\n this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n var fig = this;\n\n var canvas_div = (this.canvas_div = document.createElement('div'));\n canvas_div.setAttribute(\n 'style',\n 'border: 1px solid #ddd;' +\n 'box-sizing: content-box;' +\n 'clear: both;' +\n 'min-height: 1px;' +\n 'min-width: 1px;' +\n 'outline: 0;' +\n 'overflow: hidden;' +\n 'position: relative;' +\n 'resize: both;'\n );\n\n function on_keyboard_event_closure(name) {\n return function (event) {\n return fig.key "text/plain": [ "<IPython.core.display.Javascript object>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "<img 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], "text/plain": [ "<IPython.core.display.HTML object>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "%matplotlib notebook\n", "shotNum = \"0005\"\n", "filePath = folderPath + \"/\" + shotNum + \"/*.h5\"\n", "\n", "dataSetDict = {\n", " dskey[groupList[i]]: read_hdf5_file(filePath, groupList[i])\n", " for i in [0, 1]\n", "}\n", "\n", "dataSet = dataSetDict[\"camera_1\"]\n", "\n", "print_scanAxis(dataSet)\n", "\n", "scanAxis = get_scanAxis(dataSet)\n", "\n", "dataSet = auto_rechunk(dataSet)\n", "\n", "dataSet = imageAnalyser.get_absorption_images(dataSet)\n", "\n", "imageAnalyser.center = (305, 870)\n", "imageAnalyser.span = (400, 400)\n", "imageAnalyser.fraction = (0.1, 0.1)\n", "\n", "dataSet_cropOD = imageAnalyser.crop_image(dataSet.OD)\n", "dataSet_cropOD = imageAnalyser.substract_offset(dataSet_cropOD).load()\n", "\n", "Ncount = imageAnalyser.get_Ncount(dataSet_cropOD)\n", "Ncount_mean = calculate_mean(Ncount)\n", "Ncount_std = calculate_std(Ncount)\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "Ncount_mean.plot.errorbar(ax=ax, yerr = Ncount_std, fmt='ob')\n", "plt.xlabel('comp Z current (A)')\n", "plt.ylabel('NCount')\n", "plt.tight_layout()\n", "plt.grid(visible=1)\n", "plt.show()\n", "\n", "# DB.create_global(shotNum, dataSet)\n", "# DB.add_data(shotNum, dataSet_cropOD, engine='xarray')" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "# Evaporative Cooling" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "img_dir = '//DyLabNAS/Data/'\n", "SequenceName = \"Evaporative_Cooling\" + \"/\"\n", "folderPath = img_dir + SequenceName + '2023/06/30'# get_date()\n", "\n", "# mongoDB = mongoClient[SequenceName]\n", "\n", "# DB = MongoDB(mongoClient, mongoDB, date=get_date())" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "# Check BEC" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "ename": "OSError", "evalue": "no files to open", "output_type": "error", "traceback": [ "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[1;31mOSError\u001b[0m Traceback (most recent call last)", "\u001b[1;32mf:\\Jianshun\\analyseScript\\20230630_Data_Analysis_2.ipynb Cell 20\u001b[0m in \u001b[0;36m4\n\u001b[0;32m <a href='vscode-notebook-cell:/f%3A/Jianshun/analyseScript/20230630_Data_Analysis_2.ipynb#X25sZmlsZQ%3D%3D?line=0'>1</a>\u001b[0m shotNum \u001b[39m=\u001b[39m \u001b[39m\"\u001b[39m\u001b[39m0000\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m <a href='vscode-notebook-cell:/f%3A/Jianshun/analyseScript/20230630_Data_Analysis_2.ipynb#X25sZmlsZQ%3D%3D?line=1'>2</a>\u001b[0m filePath \u001b[39m=\u001b[39m folderPath \u001b[39m+\u001b[39m \u001b[39m\"\u001b[39m\u001b[39m/\u001b[39m\u001b[39m\"\u001b[39m \u001b[39m+\u001b[39m shotNum \u001b[39m+\u001b[39m \u001b[39m\"\u001b[39m\u001b[39m/*.h5\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[1;32m----> <a href='vscode-notebook-cell:/f%3A/Jianshun/analyseScript/20230630_Data_Analysis_2.ipynb#X25sZmlsZQ%3D%3D?line=3'>4</a>\u001b[0m dataSetDict \u001b[39m=\u001b[39m {\n\u001b[0;32m <a href='vscode-notebook-cell:/f%3A/Jianshun/analyseScript/20230630_Data_Analysis_2.ipynb#X25sZmlsZQ%3D%3D?line=4'>5</a>\u001b[0m dskey[groupList[i]]: read_hdf5_file(filePath, groupList[i])\n\u001b[0;32m <a href='vscode-notebook-cell:/f%3A/Jianshun/analyseScript/20230630_Data_Analysis_2.ipynb#X25sZmlsZQ%3D%3D?line=5'>6</a>\u001b[0m \u001b[39mfor\u001b[39;00m i \u001b[39min\u001b[39;00m [\u001b[39m0\u001b[39m]\n\u001b[0;32m <a href='vscode-notebook-cell:/f%3A/Jianshun/analyseScript/20230630_Data_Analysis_2.ipynb#X25sZmlsZQ%3D%3D?line=6'>7</a>\u001b[0m }\n\u001b[0;32m <a href='vscode-notebook-cell:/f%3A/Jianshun/analyseScript/20230630_Data_Analysis_2.ipynb#X25sZmlsZQ%3D%3D?line=8'>9</a>\u001b[0m dataSet \u001b[39m=\u001b[39m dataSetDict[\u001b[39m\"\u001b[39m\u001b[39mcamera_0\u001b[39m\u001b[39m\"\u001b[39m]\n\u001b[0;32m <a href='vscode-notebook-cell:/f%3A/Jianshun/analyseScript/20230630_Data_Analysis_2.ipynb#X25sZmlsZQ%3D%3D?line=10'>11</a>\u001b[0m print_scanAxis(dataSet)\n", "\u001b[1;32mf:\\Jianshun\\analyseScript\\20230630_Data_Analysis_2.ipynb Cell 20\u001b[0m in \u001b[0;36m5\n\u001b[0;32m <a href='vscode-notebook-cell:/f%3A/Jianshun/analyseScript/20230630_Data_Analysis_2.ipynb#X25sZmlsZQ%3D%3D?line=0'>1</a>\u001b[0m shotNum \u001b[39m=\u001b[39m \u001b[39m\"\u001b[39m\u001b[39m0000\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m <a href='vscode-notebook-cell:/f%3A/Jianshun/analyseScript/20230630_Data_Analysis_2.ipynb#X25sZmlsZQ%3D%3D?line=1'>2</a>\u001b[0m filePath \u001b[39m=\u001b[39m folderPath \u001b[39m+\u001b[39m \u001b[39m\"\u001b[39m\u001b[39m/\u001b[39m\u001b[39m\"\u001b[39m \u001b[39m+\u001b[39m shotNum \u001b[39m+\u001b[39m \u001b[39m\"\u001b[39m\u001b[39m/*.h5\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m <a href='vscode-notebook-cell:/f%3A/Jianshun/analyseScript/20230630_Data_Analysis_2.ipynb#X25sZmlsZQ%3D%3D?line=3'>4</a>\u001b[0m dataSetDict \u001b[39m=\u001b[39m {\n\u001b[1;32m----> <a href='vscode-notebook-cell:/f%3A/Jianshun/analyseScript/20230630_Data_Analysis_2.ipynb#X25sZmlsZQ%3D%3D?line=4'>5</a>\u001b[0m dskey[groupList[i]]: read_hdf5_file(filePath, groupList[i])\n\u001b[0;32m <a href='vscode-notebook-cell:/f%3A/Jianshun/analyseScript/20230630_Data_Analysis_2.ipynb#X25sZmlsZQ%3D%3D?line=5'>6</a>\u001b[0m \u001b[39mfor\u001b[39;00m i \u001b[39min\u001b[39;00m [\u001b[39m0\u001b[39m]\n\u001b[0;32m <a href='vscode-notebook-cell:/f%3A/Jianshun/analyseScript/20230630_Data_Analysis_2.ipynb#X25sZmlsZQ%3D%3D?line=6'>7</a>\u001b[0m }\n\u001b[0;32m <a href='vscode-notebook-cell:/f%3A/Jianshun/analyseScript/20230630_Data_Analysis_2.ipynb#X25sZmlsZQ%3D%3D?line=8'>9</a>\u001b[0m dataSet \u001b[39m=\u001b[39m dataSetDict[\u001b[39m\"\u001b[39m\u001b[39mcamera_0\u001b[39m\u001b[39m\"\u001b[39m]\n\u001b[0;32m <a href='vscode-notebook-cell:/f%3A/Jianshun/analyseScript/20230630_Data_Analysis_2.ipynb#X25sZmlsZQ%3D%3D?line=10'>11</a>\u001b[0m print_scanAxis(dataSet)\n", "File \u001b[1;32mf:\\Jianshun\\analyseScript\\DataContainer\\ReadData.py:150\u001b[0m, in \u001b[0;36mread_hdf5_file\u001b[1;34m(filePath, group, datesetOfGlobal, preprocess, join, parallel, engine, phony_dims, excludeAxis, maxFileNum, **kwargs)\u001b[0m\n\u001b[0;32m 139\u001b[0m kwargs\u001b[39m.\u001b[39mupdate(\n\u001b[0;32m 140\u001b[0m {\n\u001b[0;32m 141\u001b[0m \u001b[39m'\u001b[39m\u001b[39mjoin\u001b[39m\u001b[39m'\u001b[39m: join, \n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 146\u001b[0m }\n\u001b[0;32m 147\u001b[0m )\n\u001b[0;32m 149\u001b[0m \u001b[39mif\u001b[39;00m datesetOfGlobal \u001b[39mis\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[1;32m--> 150\u001b[0m datesetOfGlobal \u001b[39m=\u001b[39m xr\u001b[39m.\u001b[39;49mopen_mfdataset(\n\u001b[0;32m 151\u001b[0m fullFilePath, \n\u001b[0;32m 152\u001b[0m group\u001b[39m=\u001b[39;49m\u001b[39m\"\u001b[39;49m\u001b[39mglobals\u001b[39;49m\u001b[39m\"\u001b[39;49m, \n\u001b[0;32m 153\u001b[0m concat_dim\u001b[39m=\u001b[39;49m\u001b[39m\"\u001b[39;49m\u001b[39mfileNum\u001b[39;49m\u001b[39m\"\u001b[39;49m, \n\u001b[0;32m 154\u001b[0m combine\u001b[39m=\u001b[39;49m\u001b[39m\"\u001b[39;49m\u001b[39mnested\u001b[39;49m\u001b[39m\"\u001b[39;49m, \n\u001b[0;32m 155\u001b[0m preprocess\u001b[39m=\u001b[39;49m_read_shot_number_from_hdf5, \n\u001b[0;32m 156\u001b[0m engine\u001b[39m=\u001b[39;49m\u001b[39m\"\u001b[39;49m\u001b[39mh5netcdf\u001b[39;49m\u001b[39m\"\u001b[39;49m, \n\u001b[0;32m 157\u001b[0m phony_dims\u001b[39m=\u001b[39;49m\u001b[39m\"\u001b[39;49m\u001b[39maccess\u001b[39;49m\u001b[39m\"\u001b[39;49m, \n\u001b[0;32m 158\u001b[0m combine_attrs\u001b[39m=\u001b[39;49m_read_globals_attrs,\n\u001b[0;32m 159\u001b[0m parallel\u001b[39m=\u001b[39;49m\u001b[39mTrue\u001b[39;49;00m, )\n\u001b[0;32m 161\u001b[0m datesetOfGlobal\u001b[39m.\u001b[39mattrs[\u001b[39m'\u001b[39m\u001b[39mscanAxis\u001b[39m\u001b[39m'\u001b[39m] \u001b[39m=\u001b[39m np\u001b[39m.\u001b[39msetdiff1d(datesetOfGlobal\u001b[39m.\u001b[39mattrs[\u001b[39m'\u001b[39m\u001b[39mscanAxis\u001b[39m\u001b[39m'\u001b[39m], excludeAxis)\n\u001b[0;32m 163\u001b[0m _assgin_scan_axis \u001b[39m=\u001b[39m partial(_assign_scan_axis_partial, datesetOfGlobal\u001b[39m=\u001b[39mdatesetOfGlobal, fullFilePath\u001b[39m=\u001b[39mfullFilePath)\n", "File \u001b[1;32m~\\AppData\\Roaming\\Python\\Python39\\site-packages\\xarray\\backends\\api.py:947\u001b[0m, in \u001b[0;36mopen_mfdataset\u001b[1;34m(paths, chunks, concat_dim, compat, preprocess, engine, data_vars, coords, combine, parallel, join, attrs_file, combine_attrs, **kwargs)\u001b[0m\n\u001b[0;32m 944\u001b[0m paths \u001b[39m=\u001b[39m [os\u001b[39m.\u001b[39mfspath(p) \u001b[39mif\u001b[39;00m \u001b[39misinstance\u001b[39m(p, os\u001b[39m.\u001b[39mPathLike) \u001b[39melse\u001b[39;00m p \u001b[39mfor\u001b[39;00m p \u001b[39min\u001b[39;00m paths]\n\u001b[0;32m 946\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m paths:\n\u001b[1;32m--> 947\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mOSError\u001b[39;00m(\u001b[39m\"\u001b[39m\u001b[39mno files to open\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[0;32m 949\u001b[0m \u001b[39mif\u001b[39;00m combine \u001b[39m==\u001b[39m \u001b[39m\"\u001b[39m\u001b[39mnested\u001b[39m\u001b[39m\"\u001b[39m:\n\u001b[0;32m 950\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39misinstance\u001b[39m(concat_dim, (\u001b[39mstr\u001b[39m, DataArray)) \u001b[39mor\u001b[39;00m concat_dim \u001b[39mis\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n", "\u001b[1;31mOSError\u001b[0m: no files to open" ] } ], "source": [ "shotNum = \"0000\"\n", "filePath = folderPath + \"/\" + shotNum + \"/*.h5\"\n", "\n", "dataSetDict = {\n", " dskey[groupList[i]]: read_hdf5_file(filePath, groupList[i])\n", " for i in [0]\n", "}\n", "\n", "dataSet = dataSetDict[\"camera_0\"]\n", "\n", "print_scanAxis(dataSet)\n", "\n", "scanAxis = get_scanAxis(dataSet)\n", "\n", "dataSet = auto_rechunk(dataSet)\n", "\n", "dataSet = imageAnalyser.get_absorption_images(dataSet)\n", "\n", "imageAnalyser.center = (880, 990)\n", "imageAnalyser.span = (150, 150)\n", "imageAnalyser.fraction = (0.1, 0.1)\n", "\n", "dataSet_cropOD = imageAnalyser.crop_image(dataSet.OD)\n", "dataSet_cropOD = imageAnalyser.substract_offset(dataSet_cropOD).load()\n", "\n", "Ncount = imageAnalyser.get_Ncount(dataSet_cropOD)\n", "Ncount_mean = calculate_mean(Ncount)\n", "Ncount_std = calculate_std(Ncount)\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "Ncount_mean.plot.errorbar(ax=ax, yerr = Ncount_std, fmt='-ob')\n", "plt.xlabel('comp Z current (A)')\n", "plt.ylabel('NCount')\n", "plt.tight_layout()\n", "plt.grid(visible=1)\n", "plt.show()\n", "\n", "# DB.create_global(shotNum, dataSet)\n", "# DB.add_data(shotNum, dataSet_cropOD, engine='xarray')" ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The detected scaning axes and values are: \n", "\n", "{'compZ_current_sg': array([0.195, 0.196, 0.197, 0.198, 0.199, 0.2 , 0.201, 0.202, 0.203,\n", " 0.204]), 'runs': array([0., 1., 2.])}\n" ] }, { "data": { "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n if (typeof WebSocket !== 'undefined') {\n return WebSocket;\n } else if (typeof MozWebSocket !== 'undefined') {\n return MozWebSocket;\n } else {\n alert(\n 'Your browser does not have WebSocket support. 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' +\n 'Performance may be slow.';\n }\n }\n\n this.imageObj = new Image();\n\n this.context = undefined;\n this.message = undefined;\n this.canvas = undefined;\n this.rubberband_canvas = undefined;\n this.rubberband_context = undefined;\n this.format_dropdown = undefined;\n\n this.image_mode = 'full';\n\n this.root = document.createElement('div');\n this.root.setAttribute('style', 'display: inline-block');\n this._root_extra_style(this.root);\n\n parent_element.appendChild(this.root);\n\n this._init_header(this);\n this._init_canvas(this);\n this._init_toolbar(this);\n\n var fig = this;\n\n this.waiting = false;\n\n this.ws.onopen = function () {\n fig.send_message('supports_binary', { value: fig.supports_binary });\n fig.send_message('send_image_mode', {});\n if (fig.ratio !== 1) {\n fig.send_message('set_device_pixel_ratio', {\n device_pixel_ratio: fig.ratio,\n });\n }\n fig.send_message('refresh', {});\n };\n\n this.imageObj.onload = function () {\n if (fig.image_mode === 'full') 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], "text/plain": [ "<IPython.core.display.HTML object>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "shotNum = \"0001\"\n", "filePath = folderPath + \"/\" + shotNum + \"/*.h5\"\n", "\n", "dataSetDict = {\n", " dskey[groupList[i]]: read_hdf5_file(filePath, groupList[i])\n", " for i in [0]\n", "}\n", "\n", "dataSet = dataSetDict[\"camera_0\"]\n", "\n", "print_scanAxis(dataSet)\n", "\n", "scanAxis = get_scanAxis(dataSet)\n", "\n", "dataSet = auto_rechunk(dataSet)\n", "\n", "dataSet = imageAnalyser.get_absorption_images(dataSet)\n", "\n", "imageAnalyser.center = (880, 990)\n", "imageAnalyser.span = (150, 150)\n", "imageAnalyser.fraction = (0.1, 0.1)\n", "\n", "dataSet_cropOD = imageAnalyser.crop_image(dataSet.OD)\n", "dataSet_cropOD = imageAnalyser.substract_offset(dataSet_cropOD).load()\n", "\n", "Ncount = imageAnalyser.get_Ncount(dataSet_cropOD)\n", "Ncount_mean = calculate_mean(Ncount)\n", "Ncount_std = calculate_std(Ncount)\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "Ncount_mean.plot.errorbar(ax=ax, yerr = Ncount_std, fmt='-ob')\n", "plt.xlabel('comp Z current (A)')\n", "plt.ylabel('NCount')\n", "plt.tight_layout()\n", "plt.grid(visible=1)\n", "plt.show()\n", "\n", "# DB.create_global(shotNum, dataSet)\n", "# DB.add_data(shotNum, dataSet_cropOD, engine='xarray')" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## Measure magnification of side-imaging again" ] }, { "cell_type": "code", "execution_count": 99, "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The detected scaning axes and values are: \n", "\n", "{'TOF_free': array([0.005, 0.006, 0.007, 0.008, 0.009, 0.01 , 0.011, 0.012, 0.013,\n", " 0.014, 0.015, 0.016, 0.017, 0.018, 0.019, 0.02 , 0.021]), 'runs': array([0., 1., 2.])}\n" ] }, { "data": { "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = 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' +\n 'Performance may be slow.';\n }\n }\n\n this.imageObj = new Image();\n\n this.context = undefined;\n this.message = undefined;\n this.canvas = undefined;\n this.rubberband_canvas = undefined;\n this.rubberband_context = undefined;\n this.format_dropdown = undefined;\n\n this.image_mode = 'full';\n\n this.root = document.createElement('div');\n this.root.setAttribute('style', 'display: inline-block');\n this._root_extra_style(this.root);\n\n parent_element.appendChild(this.root);\n\n this._init_header(this);\n this._init_canvas(this);\n this._init_toolbar(this);\n\n var fig = this;\n\n this.waiting = false;\n\n this.ws.onopen = function () {\n fig.send_message('supports_binary', { value: fig.supports_binary });\n fig.send_message('send_image_mode', {});\n if (fig.ratio !== 1) {\n fig.send_message('set_device_pixel_ratio', {\n device_pixel_ratio: fig.ratio,\n });\n }\n fig.send_message('refresh', {});\n };\n\n this.imageObj.onload = function () {\n if (fig.image_mode === 'full') {\n // Full images could contain transparency (where diff images\n // almost always do), so we need to clear the canvas so that\n // there is no ghosting.\n fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n }\n fig.context.drawImage(fig.imageObj, 0, 0);\n };\n\n this.imageObj.onunload = function () {\n fig.ws.close();\n };\n\n this.ws.onmessage = this._make_on_message_function(this);\n\n this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n var titlebar = document.createElement('div');\n titlebar.classList =\n 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n var titletext = document.createElement('div');\n titletext.classList = 'ui-dialog-title';\n titletext.setAttribute(\n 'style',\n 'width: 100%; text-align: center; padding: 3px;'\n );\n titlebar.appendChild(titletext);\n this.root.appendChild(titlebar);\n this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n var fig = this;\n\n var canvas_div = (this.canvas_div = document.createElement('div'));\n canvas_div.setAttribute(\n 'style',\n 'border: 1px solid #ddd;' +\n 'box-sizing: content-box;' +\n 'clear: both;' +\n 'min-height: 1px;' +\n 'min-width: 1px;' +\n 'outline: 0;' +\n 'overflow: hidden;' +\n 'position: relative;' +\n 'resize: both;'\n );\n\n function on_keyboard_event_closure(name) {\n return function (event) {\n return fig.key "text/plain": [ "<IPython.core.display.Javascript object>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "<img 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], "text/plain": [ "<IPython.core.display.HTML object>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "shotNum = \"0005\"\n", "filePath = folderPath + \"/\" + shotNum + \"/*.h5\"\n", "\n", "dataSetDict = {\n", " dskey[groupList[i]]: read_hdf5_file(filePath, groupList[i])\n", " for i in [0]\n", "}\n", "\n", "dataSet = dataSetDict[\"camera_0\"]\n", "\n", "print_scanAxis(dataSet)\n", "\n", "scanAxis = get_scanAxis(dataSet)\n", "\n", "dataSet = auto_rechunk(dataSet)\n", "\n", "dataSet = imageAnalyser.get_absorption_images(dataSet)\n", "\n", "imageAnalyser.center = (550, 990)\n", "imageAnalyser.span = (1000, 200)\n", "imageAnalyser.fraction = (0.1, 0.1)\n", "\n", "dataSet_cropOD = imageAnalyser.crop_image(dataSet.OD)\n", "dataSet_cropOD = imageAnalyser.substract_offset(dataSet_cropOD).load()\n", "\n", "Ncount = imageAnalyser.get_Ncount(dataSet_cropOD)\n", "Ncount_mean = calculate_mean(Ncount)\n", "Ncount_std = calculate_std(Ncount)\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "Ncount_mean.plot.errorbar(ax=ax, yerr = Ncount_std, fmt='ob')\n", "plt.xlabel('TOF (s)')\n", "plt.ylabel('NCount')\n", "plt.tight_layout()\n", "plt.grid(visible=1)\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 100, "metadata": {}, "outputs": [ { "data": { "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n if (typeof WebSocket !== 'undefined') {\n return WebSocket;\n } else if (typeof MozWebSocket !== 'undefined') {\n return MozWebSocket;\n } else {\n alert(\n 'Your browser does not have WebSocket support. ' +\n 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n 'Firefox 4 and 5 are also supported but you ' +\n 'have to enable WebSockets in about:config.'\n );\n }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n this.id = figure_id;\n\n this.ws = websocket;\n\n this.supports_binary = this.ws.binaryType !== undefined;\n\n if (!this.supports_binary) {\n var warnings = document.getElementById('mpl-warnings');\n if (warnings) {\n warnings.style.display = 'block';\n warnings.textContent =\n 'This browser does not support binary websocket messages. ' +\n 'Performance may be slow.';\n }\n }\n\n this.imageObj = new Image();\n\n this.context = undefined;\n this.message = undefined;\n this.canvas = undefined;\n this.rubberband_canvas = undefined;\n this.rubberband_context = undefined;\n this.format_dropdown = undefined;\n\n this.image_mode = 'full';\n\n this.root = document.createElement('div');\n this.root.setAttribute('style', 'display: inline-block');\n this._root_extra_style(this.root);\n\n parent_element.appendChild(this.root);\n\n this._init_header(this);\n this._init_canvas(this);\n this._init_toolbar(this);\n\n var fig = this;\n\n this.waiting = false;\n\n this.ws.onopen = function () {\n fig.send_message('supports_binary', { value: fig.supports_binary });\n fig.send_message('send_image_mode', {});\n if (fig.ratio !== 1) {\n fig.send_message('set_device_pixel_ratio', {\n device_pixel_ratio: fig.ratio,\n });\n }\n fig.send_message('refresh', {});\n };\n\n this.imageObj.onload = function () {\n if (fig.image_mode === 'full') {\n // Full images could contain transparency (where diff images\n // almost always do), so we need to clear the canvas so that\n // there is no ghosting.\n fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n }\n fig.context.drawImage(fig.imageObj, 0, 0);\n };\n\n this.imageObj.onunload = function () {\n fig.ws.close();\n };\n\n this.ws.onmessage = this._make_on_message_function(this);\n\n this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n var titlebar = document.createElement('div');\n titlebar.classList =\n 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n var titletext = document.createElement('div');\n titletext.classList = 'ui-dialog-title';\n titletext.setAttribute(\n 'style',\n 'width: 100%; text-align: center; padding: 3px;'\n );\n titlebar.appendChild(titletext);\n this.root.appendChild(titlebar);\n this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n var fig = this;\n\n var canvas_div = (this.canvas_div = document.createElement('div'));\n canvas_div.setAttribute(\n 'style',\n 'border: 1px solid #ddd;' +\n 'box-sizing: content-box;' +\n 'clear: both;' +\n 'min-height: 1px;' +\n 'min-width: 1px;' +\n 'outline: 0;' +\n 'overflow: hidden;' +\n 'position: relative;' +\n 'resize: both;'\n );\n\n function on_keyboard_event_closure(name) {\n return function (event) {\n return fig.key "text/plain": [ "<IPython.core.display.Javascript object>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "<img src=\"data:image/png;base64,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 ], "text/plain": [ "<IPython.core.display.HTML object>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "remove_bad_shots(dataSet_cropOD, TOF_free=0.005)\n", "Ncount = imageAnalyser.get_Ncount(dataSet_cropOD)\n", "Ncount_mean = calculate_mean(Ncount)\n", "Ncount_std = calculate_std(Ncount)\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "Ncount_mean.plot.errorbar(ax=ax, yerr = Ncount_std, fmt='ob')\n", "plt.xlabel('TOF (s)')\n", "plt.ylabel('NCount')\n", "plt.tight_layout()\n", "plt.grid(visible=1)\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 101, "metadata": { "scrolled": false }, "outputs": [], "source": [ "dataSet_cropOD = dataSet_cropOD[1:-1, :, :, :]\n", "dataSet_cropOD_chunk = dataSet_cropOD.chunk((1, 1, 1000, 200))\n", "fitAnalyser = FitAnalyser(\"Gaussian-2D\", fitDim=2)\n", "params = fitAnalyser.guess(dataSet_cropOD_chunk, dask=\"parallelized\")\n", "fitResult = fitAnalyser.fit(dataSet_cropOD_chunk, params, dask=\"parallelized\").load()" ] }, { "cell_type": "code", "execution_count": 102, "metadata": {}, "outputs": [ { "data": { "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n if (typeof WebSocket !== 'undefined') {\n return WebSocket;\n } else if (typeof MozWebSocket !== 'undefined') {\n return MozWebSocket;\n } else {\n alert(\n 'Your browser does not have WebSocket support. ' +\n 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n 'Firefox 4 and 5 are also supported but you ' +\n 'have to enable WebSockets in about:config.'\n );\n }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n this.id = figure_id;\n\n this.ws = websocket;\n\n this.supports_binary = this.ws.binaryType !== undefined;\n\n if (!this.supports_binary) {\n var warnings = document.getElementById('mpl-warnings');\n if (warnings) {\n warnings.style.display = 'block';\n warnings.textContent =\n 'This browser does not support binary websocket messages. ' +\n 'Performance may be slow.';\n }\n }\n\n this.imageObj = new Image();\n\n this.context = undefined;\n this.message = undefined;\n this.canvas = undefined;\n this.rubberband_canvas = undefined;\n this.rubberband_context = undefined;\n this.format_dropdown = undefined;\n\n this.image_mode = 'full';\n\n this.root = document.createElement('div');\n this.root.setAttribute('style', 'display: inline-block');\n this._root_extra_style(this.root);\n\n parent_element.appendChild(this.root);\n\n this._init_header(this);\n this._init_canvas(this);\n this._init_toolbar(this);\n\n var fig = this;\n\n this.waiting = false;\n\n this.ws.onopen = function () {\n fig.send_message('supports_binary', { value: fig.supports_binary });\n fig.send_message('send_image_mode', {});\n if (fig.ratio !== 1) {\n fig.send_message('set_device_pixel_ratio', {\n device_pixel_ratio: fig.ratio,\n });\n }\n fig.send_message('refresh', {});\n };\n\n this.imageObj.onload = function () {\n if (fig.image_mode === 'full') {\n // Full images could contain transparency (where diff images\n // almost always do), so we need to clear the canvas so that\n // there is no ghosting.\n fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n }\n fig.context.drawImage(fig.imageObj, 0, 0);\n };\n\n this.imageObj.onunload = function () {\n fig.ws.close();\n };\n\n this.ws.onmessage = this._make_on_message_function(this);\n\n this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n var titlebar = document.createElement('div');\n titlebar.classList =\n 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n var titletext = document.createElement('div');\n titletext.classList = 'ui-dialog-title';\n titletext.setAttribute(\n 'style',\n 'width: 100%; text-align: center; padding: 3px;'\n );\n titlebar.appendChild(titletext);\n this.root.appendChild(titlebar);\n this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n var fig = this;\n\n var canvas_div = (this.canvas_div = document.createElement('div'));\n canvas_div.setAttribute(\n 'style',\n 'border: 1px solid #ddd;' +\n 'box-sizing: content-box;' +\n 'clear: both;' +\n 'min-height: 1px;' +\n 'min-width: 1px;' +\n 'outline: 0;' +\n 'overflow: hidden;' +\n 'position: relative;' +\n 'resize: both;'\n );\n\n function on_keyboard_event_closure(name) {\n return function (event) {\n return fig.key "text/plain": [ "<IPython.core.display.Javascript object>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "<img src=\"data:image/png;base64,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 ], "text/plain": [ "<IPython.core.display.HTML object>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "val = fitAnalyser.get_fit_value(fitResult)\n", "std = fitAnalyser.get_fit_std(fitResult)\n", "\n", "fitCurve = fitAnalyser.eval(fitResult, x=np.arange(990), y=np.arange(350), dask=\"parallelized\").load()\n", "\n", "# dataKey = 'sigmax'\n", "dataKey = 'centerx'\n", "# dataKey = 'sigmay'\n", "# dataKey = 'centery'\n", "\n", "val_mean = val[dataKey].mean(dim='runs')\n", "std_mean = val[dataKey].std(dim='runs')\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "\n", "val_mean.plot.errorbar(yerr=std_mean, fmt='--ob')\n", "\n", "plt.grid()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 103, "metadata": {}, "outputs": [ { "data": { "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n if (typeof WebSocket !== 'undefined') {\n return WebSocket;\n } else if (typeof MozWebSocket !== 'undefined') {\n return MozWebSocket;\n } else {\n alert(\n 'Your browser does not have WebSocket support. ' +\n 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n 'Firefox 4 and 5 are also supported but you ' +\n 'have to enable WebSockets in about:config.'\n );\n }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n this.id = figure_id;\n\n this.ws = websocket;\n\n this.supports_binary = this.ws.binaryType !== undefined;\n\n if (!this.supports_binary) {\n var warnings = document.getElementById('mpl-warnings');\n if (warnings) {\n warnings.style.display = 'block';\n warnings.textContent =\n 'This browser does not support binary websocket messages. ' +\n 'Performance may be slow.';\n }\n }\n\n this.imageObj = new Image();\n\n this.context = undefined;\n this.message = undefined;\n this.canvas = undefined;\n this.rubberband_canvas = undefined;\n this.rubberband_context = undefined;\n this.format_dropdown = undefined;\n\n this.image_mode = 'full';\n\n this.root = document.createElement('div');\n this.root.setAttribute('style', 'display: inline-block');\n this._root_extra_style(this.root);\n\n parent_element.appendChild(this.root);\n\n this._init_header(this);\n this._init_canvas(this);\n this._init_toolbar(this);\n\n var fig = this;\n\n this.waiting = false;\n\n this.ws.onopen = function () {\n fig.send_message('supports_binary', { value: fig.supports_binary });\n fig.send_message('send_image_mode', {});\n if (fig.ratio !== 1) {\n fig.send_message('set_device_pixel_ratio', {\n device_pixel_ratio: fig.ratio,\n });\n }\n fig.send_message('refresh', {});\n };\n\n this.imageObj.onload = function () {\n if (fig.image_mode === 'full') {\n // Full images could contain transparency (where diff images\n // almost always do), so we need to clear the canvas so that\n // there is no ghosting.\n fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n }\n fig.context.drawImage(fig.imageObj, 0, 0);\n };\n\n this.imageObj.onunload = function () {\n fig.ws.close();\n };\n\n this.ws.onmessage = this._make_on_message_function(this);\n\n this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n var titlebar = document.createElement('div');\n titlebar.classList =\n 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n var titletext = document.createElement('div');\n titletext.classList = 'ui-dialog-title';\n titletext.setAttribute(\n 'style',\n 'width: 100%; text-align: center; padding: 3px;'\n );\n titlebar.appendChild(titletext);\n this.root.appendChild(titlebar);\n this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n var fig = this;\n\n var canvas_div = (this.canvas_div = document.createElement('div'));\n canvas_div.setAttribute(\n 'style',\n 'border: 1px solid #ddd;' +\n 'box-sizing: content-box;' +\n 'clear: both;' +\n 'min-height: 1px;' +\n 'min-width: 1px;' +\n 'outline: 0;' +\n 'overflow: hidden;' +\n 'position: relative;' +\n 'resize: both;'\n );\n\n function on_keyboard_event_closure(name) {\n return function (event) {\n return fig.key "text/plain": [ "<IPython.core.display.Javascript object>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "<img 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], "text/plain": [ "<IPython.core.display.HTML object>" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "M = 2.3513 ± 0.0036 \n" ] } ], "source": [ "def free_fall(x, A, B):\n", " return A*(x**2) + B\n", "\n", "fitModel_freefall = NewFitModel(free_fall)\n", "fitAnalyser_freefall = FitAnalyser(fitModel_freefall, fitDim=1)\n", "\n", "params = fitAnalyser_freefall.fitModel.make_params()\n", "params.add(name=\"A\", value= 1e6, max = np.inf, min =-np.inf, vary = True)\n", "params.add(name=\"B\", value= 1000, max = np.inf, min =-np.inf, vary = True)\n", "\n", "fitResult_freefall = fitAnalyser_freefall.fit(val_mean, params, x='TOF_free', dask=\"parallelized\")\n", "\n", "val = fitAnalyser_freefall.get_fit_value(fitResult_freefall)\n", "std = fitAnalyser_freefall.get_fit_std(fitResult_freefall)\n", "\n", "fit_vals = tuple([val['A'].item(), val['B'].item()])\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "val_mean.plot.errorbar(ax=ax, yerr=std_mean, fmt='or')\n", "tof = np.linspace(5,21,50)*1e-3\n", "plt.plot(tof, free_fall(tof, *fit_vals), 'b--',label='fit: A=%5.3f, B=%5.3f' % fit_vals)\n", "plt.grid(visible =1)\n", "plt.xlabel('TOF (s)')\n", "plt.ylabel('Cloud Center (pixels)')\n", "plt.legend()\n", "plt.show()\n", "\n", "#pixel= 3.45e-6\n", "pixel = 5.86e-6\n", "g = 9.80998\n", "M = val['A'].item() * 2 * pixel/g\n", "dM = std['A'].item() * 2 * pixel/g\n", "\n", "print('M = %.4f \\u00B1 %.4f '% tuple([M,dM]))" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## Measure temperature at the end of evaporative cooling 2, truncation 0.7" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The detected scaning axes and values are: \n", "\n", "{'TOF_free': array([0.002, 0.003, 0.004, 0.005, 0.006, 0.007, 0.008, 0.009, 0.01 ,\n", " 0.011, 0.012, 0.013, 0.014, 0.015]), 'runs': array([0., 1., 2.])}\n" ] }, { "data": { "image/png": "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 "text/plain": [ "<Figure size 640x480 with 1 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "shotNum = \"0007\"\n", "filePath = folderPath + \"/\" + shotNum + \"/*.h5\"\n", "\n", "dataSetDict = {\n", " dskey[groupList[i]]: read_hdf5_file(filePath, groupList[i])\n", " for i in [0]\n", "}\n", "\n", "dataSet = dataSetDict[\"camera_0\"]\n", "\n", "print_scanAxis(dataSet)\n", "\n", "scanAxis = get_scanAxis(dataSet)\n", "\n", "dataSet = auto_rechunk(dataSet)\n", "\n", "dataSet = imageAnalyser.get_absorption_images(dataSet)\n", "\n", "imageAnalyser.center = (350, 990)\n", "imageAnalyser.span = (650, 200)\n", "imageAnalyser.fraction = (0.1, 0.1)\n", "\n", "dataSet_cropOD = imageAnalyser.crop_image(dataSet.OD)\n", "dataSet_cropOD = imageAnalyser.substract_offset(dataSet_cropOD).load()\n", "\n", "Ncount = imageAnalyser.get_Ncount(dataSet_cropOD)\n", "Ncount_mean = calculate_mean(Ncount)\n", "Ncount_std = calculate_std(Ncount)\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "Ncount_mean.plot.errorbar(ax=ax, yerr = Ncount_std, fmt='ob')\n", "plt.xlabel('TOF (s)')\n", "plt.ylabel('NCount')\n", "plt.tight_layout()\n", "plt.grid(visible=1)\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "dataSet_cropOD_chunk = dataSet_cropOD.chunk((1, 1, 650, 200))\n", "fitAnalyser = FitAnalyser(\"Gaussian-2D\", fitDim=2)\n", "params = fitAnalyser.guess(dataSet_cropOD_chunk, dask=\"parallelized\")\n", "fitResult = fitAnalyser.fit(dataSet_cropOD_chunk, params, dask=\"parallelized\").load()" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "3.769727404282448\n", "0.07242840439128356\n" ] } ], "source": [ "data = fitAnalyser.get_fit_value(fitResult)\n", "\n", "print(data.amplitude.sel(TOF_free=0.01).mean('runs').item() * 147 / 1e5)\n", "print(data.amplitude.sel(TOF_free=0.01).std('runs').item() * 147 / 1e5)" ] }, { "cell_type": "code", "execution_count": 123, "metadata": {}, "outputs": [ { "data": { "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n if (typeof WebSocket !== 'undefined') {\n return WebSocket;\n } else if (typeof MozWebSocket !== 'undefined') {\n return MozWebSocket;\n } else {\n alert(\n 'Your browser does not have WebSocket support. ' +\n 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n 'Firefox 4 and 5 are also supported but you ' +\n 'have to enable WebSockets in about:config.'\n );\n }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n this.id = figure_id;\n\n this.ws = websocket;\n\n this.supports_binary = this.ws.binaryType !== undefined;\n\n if (!this.supports_binary) {\n var warnings = document.getElementById('mpl-warnings');\n if (warnings) {\n warnings.style.display = 'block';\n warnings.textContent =\n 'This browser does not support binary websocket messages. ' +\n 'Performance may be slow.';\n }\n }\n\n this.imageObj = new Image();\n\n this.context = undefined;\n this.message = undefined;\n this.canvas = undefined;\n this.rubberband_canvas = undefined;\n this.rubberband_context = undefined;\n this.format_dropdown = undefined;\n\n this.image_mode = 'full';\n\n this.root = document.createElement('div');\n this.root.setAttribute('style', 'display: inline-block');\n this._root_extra_style(this.root);\n\n parent_element.appendChild(this.root);\n\n this._init_header(this);\n this._init_canvas(this);\n this._init_toolbar(this);\n\n var fig = this;\n\n this.waiting = false;\n\n this.ws.onopen = function () {\n fig.send_message('supports_binary', { value: fig.supports_binary });\n fig.send_message('send_image_mode', {});\n if (fig.ratio !== 1) {\n fig.send_message('set_device_pixel_ratio', {\n device_pixel_ratio: fig.ratio,\n });\n }\n fig.send_message('refresh', {});\n };\n\n this.imageObj.onload = function () {\n if (fig.image_mode === 'full') {\n // Full images could contain transparency (where diff images\n // almost always do), so we need to clear the canvas so that\n // there is no ghosting.\n fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n }\n fig.context.drawImage(fig.imageObj, 0, 0);\n };\n\n this.imageObj.onunload = function () {\n fig.ws.close();\n };\n\n this.ws.onmessage = this._make_on_message_function(this);\n\n this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n var titlebar = document.createElement('div');\n titlebar.classList =\n 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n var titletext = document.createElement('div');\n titletext.classList = 'ui-dialog-title';\n titletext.setAttribute(\n 'style',\n 'width: 100%; text-align: center; padding: 3px;'\n );\n titlebar.appendChild(titletext);\n this.root.appendChild(titlebar);\n this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n var fig = this;\n\n var canvas_div = (this.canvas_div = document.createElement('div'));\n canvas_div.setAttribute(\n 'style',\n 'border: 1px solid #ddd;' +\n 'box-sizing: content-box;' +\n 'clear: both;' +\n 'min-height: 1px;' +\n 'min-width: 1px;' +\n 'outline: 0;' +\n 'overflow: hidden;' +\n 'position: relative;' +\n 'resize: both;'\n );\n\n function on_keyboard_event_closure(name) {\n return function (event) {\n return fig.key "text/plain": [ "<IPython.core.display.Javascript object>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "<img 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], "text/plain": [ "<IPython.core.display.HTML object>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "val = fitAnalyser.get_fit_value(fitResult)\n", "std = fitAnalyser.get_fit_std(fitResult)\n", "\n", "fitCurve = fitAnalyser.eval(fitResult, x=np.arange(990), y=np.arange(350), dask=\"parallelized\").load()\n", "\n", "dataKey = 'sigmax'\n", "# dataKey = 'centerx'\n", "# dataKey = 'sigmay'\n", "# dataKey = 'centery'\n", "\n", "val_mean = val[dataKey].mean(dim='runs')\n", "std_mean = val[dataKey].std(dim='runs')\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "\n", "val_mean.plot.errorbar(yerr=std_mean, fmt='--ob')\n", "\n", "plt.grid()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 119, "metadata": {}, "outputs": [ { "data": { "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n if (typeof WebSocket !== 'undefined') {\n return WebSocket;\n } else if (typeof MozWebSocket !== 'undefined') {\n return MozWebSocket;\n } else {\n alert(\n 'Your browser does not have WebSocket support. ' +\n 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n 'Firefox 4 and 5 are also supported but you ' +\n 'have to enable WebSockets in about:config.'\n );\n }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n this.id = figure_id;\n\n this.ws = websocket;\n\n this.supports_binary = this.ws.binaryType !== undefined;\n\n if (!this.supports_binary) {\n var warnings = document.getElementById('mpl-warnings');\n if (warnings) {\n warnings.style.display = 'block';\n warnings.textContent =\n 'This browser does not support binary websocket messages. ' +\n 'Performance may be slow.';\n }\n }\n\n this.imageObj = new Image();\n\n this.context = undefined;\n this.message = undefined;\n this.canvas = undefined;\n this.rubberband_canvas = undefined;\n this.rubberband_context = undefined;\n this.format_dropdown = undefined;\n\n this.image_mode = 'full';\n\n this.root = document.createElement('div');\n this.root.setAttribute('style', 'display: inline-block');\n this._root_extra_style(this.root);\n\n parent_element.appendChild(this.root);\n\n this._init_header(this);\n this._init_canvas(this);\n this._init_toolbar(this);\n\n var fig = this;\n\n this.waiting = false;\n\n this.ws.onopen = function () {\n fig.send_message('supports_binary', { value: fig.supports_binary });\n fig.send_message('send_image_mode', {});\n if (fig.ratio !== 1) {\n fig.send_message('set_device_pixel_ratio', {\n device_pixel_ratio: fig.ratio,\n });\n }\n fig.send_message('refresh', {});\n };\n\n this.imageObj.onload = function () {\n if (fig.image_mode === 'full') {\n // Full images could contain transparency (where diff images\n // almost always do), so we need to clear the canvas so that\n // there is no ghosting.\n fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n }\n fig.context.drawImage(fig.imageObj, 0, 0);\n };\n\n this.imageObj.onunload = function () {\n fig.ws.close();\n };\n\n this.ws.onmessage = this._make_on_message_function(this);\n\n this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n var titlebar = document.createElement('div');\n titlebar.classList =\n 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n var titletext = document.createElement('div');\n titletext.classList = 'ui-dialog-title';\n titletext.setAttribute(\n 'style',\n 'width: 100%; text-align: center; padding: 3px;'\n );\n titlebar.appendChild(titletext);\n this.root.appendChild(titlebar);\n this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n var fig = this;\n\n var canvas_div = (this.canvas_div = document.createElement('div'));\n canvas_div.setAttribute(\n 'style',\n 'border: 1px solid #ddd;' +\n 'box-sizing: content-box;' +\n 'clear: both;' +\n 'min-height: 1px;' +\n 'min-width: 1px;' +\n 'outline: 0;' +\n 'overflow: hidden;' +\n 'position: relative;' +\n 'resize: both;'\n );\n\n function on_keyboard_event_closure(name) {\n return function (event) {\n return fig.key "text/plain": [ "<IPython.core.display.Javascript object>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "<img src=\"data:image/png;base64,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 ], "text/plain": [ "<IPython.core.display.HTML object>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "val = fitAnalyser.get_fit_value(fitResult)\n", "std = fitAnalyser.get_fit_std(fitResult)\n", "\n", "fitCurve = fitAnalyser.eval(fitResult, x=np.arange(990), y=np.arange(950), dask=\"parallelized\").load()\n", "\n", "# dataKey = 'sigmax'\n", "# dataKey = 'centerx'\n", "dataKey = 'sigmay'\n", "# dataKey = 'centery'\n", "\n", "val_mean = val[dataKey].mean(dim='runs')\n", "std_mean = val[dataKey].std(dim='runs')\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "\n", "val_mean.plot.errorbar(yerr=std_mean, fmt='--ob')\n", "\n", "plt.grid()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 125, "metadata": {}, "outputs": [ { "data": { "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n if (typeof WebSocket !== 'undefined') {\n return WebSocket;\n } else if (typeof MozWebSocket !== 'undefined') {\n return MozWebSocket;\n } else {\n alert(\n 'Your browser does not have WebSocket support. ' +\n 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n 'Firefox 4 and 5 are also supported but you ' +\n 'have to enable WebSockets in about:config.'\n );\n }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n this.id = figure_id;\n\n this.ws = websocket;\n\n this.supports_binary = this.ws.binaryType !== undefined;\n\n if (!this.supports_binary) {\n var warnings = document.getElementById('mpl-warnings');\n if (warnings) {\n warnings.style.display = 'block';\n warnings.textContent =\n 'This browser does not support binary websocket messages. ' +\n 'Performance may be slow.';\n }\n }\n\n this.imageObj = new Image();\n\n this.context = undefined;\n this.message = undefined;\n this.canvas = undefined;\n this.rubberband_canvas = undefined;\n this.rubberband_context = undefined;\n this.format_dropdown = undefined;\n\n this.image_mode = 'full';\n\n this.root = document.createElement('div');\n this.root.setAttribute('style', 'display: inline-block');\n this._root_extra_style(this.root);\n\n parent_element.appendChild(this.root);\n\n this._init_header(this);\n this._init_canvas(this);\n this._init_toolbar(this);\n\n var fig = this;\n\n this.waiting = false;\n\n this.ws.onopen = function () {\n fig.send_message('supports_binary', { value: fig.supports_binary });\n fig.send_message('send_image_mode', {});\n if (fig.ratio !== 1) {\n fig.send_message('set_device_pixel_ratio', {\n device_pixel_ratio: fig.ratio,\n });\n }\n fig.send_message('refresh', {});\n };\n\n this.imageObj.onload = function () {\n if (fig.image_mode === 'full') {\n // Full images could contain transparency (where diff images\n // almost always do), so we need to clear the canvas so that\n // there is no ghosting.\n fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n }\n fig.context.drawImage(fig.imageObj, 0, 0);\n };\n\n this.imageObj.onunload = function () {\n fig.ws.close();\n };\n\n this.ws.onmessage = this._make_on_message_function(this);\n\n this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n var titlebar = document.createElement('div');\n titlebar.classList =\n 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n var titletext = document.createElement('div');\n titletext.classList = 'ui-dialog-title';\n titletext.setAttribute(\n 'style',\n 'width: 100%; text-align: center; padding: 3px;'\n );\n titlebar.appendChild(titletext);\n this.root.appendChild(titlebar);\n this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n var fig = this;\n\n var canvas_div = (this.canvas_div = document.createElement('div'));\n canvas_div.setAttribute(\n 'style',\n 'border: 1px solid #ddd;' +\n 'box-sizing: content-box;' +\n 'clear: both;' +\n 'min-height: 1px;' +\n 'min-width: 1px;' +\n 'outline: 0;' +\n 'overflow: hidden;' +\n 'position: relative;' +\n 'resize: both;'\n );\n\n function on_keyboard_event_closure(name) {\n return function (event) {\n return fig.key "text/plain": [ "<IPython.core.display.Javascript object>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "<img 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], "text/plain": [ "<IPython.core.display.HTML object>" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "T = 0.526 ± 0.006 uK\n" ] } ], "source": [ "def expansion(x, A, B):\n", " return np.sqrt(A*x*x+B)\n", "\n", "val_truncated = val_mean[0:]\n", "std_mean_truncated = std_mean[0:]\n", "\n", "fitModel_temperature = NewFitModel(expansion)\n", "fitAnalyser_temperature = FitAnalyser(fitModel_temperature, fitDim=1)\n", "\n", "params = fitAnalyser_temperature.fitModel.make_params()\n", "params.add(name=\"A\", value= 1e6, max = np.inf, min = 1, vary = True)\n", "params.add(name=\"B\", value= 1000, max = np.inf, min = 0, vary = True)\n", "\n", "fitResult_temperature = fitAnalyser_temperature.fit(val_truncated, params, x='TOF_free', dask=\"parallelized\")\n", "\n", "val = fitAnalyser_temperature.get_fit_value(fitResult_temperature)\n", "std = fitAnalyser_temperature.get_fit_std(fitResult_temperature)\n", "\n", "fit_vals = tuple([val['A'].item(), val['B'].item()])\n", "fit_vals_std = tuple([std['A'].item(), std['B'].item()])\n", "\n", "tof = (np.arange(2,16,0.1)*1e-3)\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "val_mean.plot.errorbar(ax=ax, yerr=std_mean, fmt='or')\n", "plt.plot(tof, expansion(tof, *fit_vals), 'b--',\n", " label='fit: A=%.3f, B=%.3f' % tuple(fit_vals))\n", "plt.xlabel('TOF (s)')\n", "plt.ylabel('Cloud Width - Vertical (pixels)')\n", "#plt.ylabel('Cloud Width - Horizontal (pixels)')\n", "plt.tight_layout()\n", "plt.grid(visible=1)\n", "plt.legend()\n", "\n", "\n", "m = 164*1.673e-27\n", "kb = 1.38e-23\n", "pixel = 5.86e-6\n", "M = 2.3513\n", "\n", "T = fit_vals[0] * (m/kb) * ((pixel*pixel)/(M*M)) / (1e-6)\n", "dT = fit_vals_std[0] * (m/kb) * ((pixel*pixel)/(M*M)) / (1e-6)\n", "\n", "print('T = %.3f \\u00B1 %.3f uK'% tuple([T,dT]))" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## Measure temperature at the end of evaporative cooling 2, truncation 0.65" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The detected scaning axes and values are: \n", "\n", "{'TOF_free': array([0.002, 0.003, 0.004, 0.005, 0.006, 0.007, 0.008, 0.009, 0.01 ,\n", " 0.011, 0.012, 0.013, 0.014, 0.015]), 'runs': array([0., 1., 2.])}\n" ] }, { "data": { "image/png": "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 "text/plain": [ "<Figure size 640x480 with 1 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "shotNum = \"0008\"\n", "filePath = folderPath + \"/\" + shotNum + \"/*.h5\"\n", "\n", "dataSetDict = {\n", " dskey[groupList[i]]: read_hdf5_file(filePath, groupList[i])\n", " for i in [0]\n", "}\n", "\n", "dataSet = dataSetDict[\"camera_0\"]\n", "\n", "print_scanAxis(dataSet)\n", "\n", "scanAxis = get_scanAxis(dataSet)\n", "\n", "dataSet = auto_rechunk(dataSet)\n", "\n", "dataSet = imageAnalyser.get_absorption_images(dataSet)\n", "\n", "imageAnalyser.center = (350, 990)\n", "imageAnalyser.span = (650, 200)\n", "imageAnalyser.fraction = (0.1, 0.1)\n", "\n", "dataSet_cropOD = imageAnalyser.crop_image(dataSet.OD)\n", "dataSet_cropOD = imageAnalyser.substract_offset(dataSet_cropOD).load()\n", "\n", "Ncount = imageAnalyser.get_Ncount(dataSet_cropOD)\n", "Ncount_mean = calculate_mean(Ncount)\n", "Ncount_std = calculate_std(Ncount)\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "Ncount_mean.plot.errorbar(ax=ax, yerr = Ncount_std, fmt='ob')\n", "plt.xlabel('TOF (s)')\n", "plt.ylabel('NCount')\n", "plt.tight_layout()\n", "plt.grid(visible=1)\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [], "source": [ "dataSet_cropOD_chunk = dataSet_cropOD.chunk((1, 1, 650, 200))\n", "fitAnalyser = FitAnalyser(\"Gaussian-2D\", fitDim=2)\n", "params = fitAnalyser.guess(dataSet_cropOD_chunk, dask=\"parallelized\")\n", "fitResult = fitAnalyser.fit(dataSet_cropOD_chunk, params, dask=\"parallelized\").load()" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "4.158908069274802\n", "0.17858152215917347\n" ] } ], "source": [ "data = fitAnalyser.get_fit_value(fitResult)\n", "\n", "print(data.amplitude.sel(TOF_free=0.01).mean('runs').item() * 147 / 1e5)\n", "print(data.amplitude.sel(TOF_free=0.01).std('runs').item() * 147 / 1e5)" ] }, { "cell_type": "code", "execution_count": 109, "metadata": {}, "outputs": [ { "data": { "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n if (typeof WebSocket !== 'undefined') {\n return WebSocket;\n } else if (typeof MozWebSocket !== 'undefined') {\n return MozWebSocket;\n } else {\n alert(\n 'Your browser does not have WebSocket support. ' +\n 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n 'Firefox 4 and 5 are also supported but you ' +\n 'have to enable WebSockets in about:config.'\n );\n }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n this.id = figure_id;\n\n this.ws = websocket;\n\n this.supports_binary = this.ws.binaryType !== undefined;\n\n if (!this.supports_binary) {\n var warnings = document.getElementById('mpl-warnings');\n if (warnings) {\n warnings.style.display = 'block';\n warnings.textContent =\n 'This browser does not support binary websocket messages. ' +\n 'Performance may be slow.';\n }\n }\n\n this.imageObj = new Image();\n\n this.context = undefined;\n this.message = undefined;\n this.canvas = undefined;\n this.rubberband_canvas = undefined;\n this.rubberband_context = undefined;\n this.format_dropdown = undefined;\n\n this.image_mode = 'full';\n\n this.root = document.createElement('div');\n this.root.setAttribute('style', 'display: inline-block');\n this._root_extra_style(this.root);\n\n parent_element.appendChild(this.root);\n\n this._init_header(this);\n this._init_canvas(this);\n this._init_toolbar(this);\n\n var fig = this;\n\n this.waiting = false;\n\n this.ws.onopen = function () {\n fig.send_message('supports_binary', { value: fig.supports_binary });\n fig.send_message('send_image_mode', {});\n if (fig.ratio !== 1) {\n fig.send_message('set_device_pixel_ratio', {\n device_pixel_ratio: fig.ratio,\n });\n }\n fig.send_message('refresh', {});\n };\n\n this.imageObj.onload = function () {\n if (fig.image_mode === 'full') {\n // Full images could contain transparency (where diff images\n // almost always do), so we need to clear the canvas so that\n // there is no ghosting.\n fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n }\n fig.context.drawImage(fig.imageObj, 0, 0);\n };\n\n this.imageObj.onunload = function () {\n fig.ws.close();\n };\n\n this.ws.onmessage = this._make_on_message_function(this);\n\n this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n var titlebar = document.createElement('div');\n titlebar.classList =\n 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n var titletext = document.createElement('div');\n titletext.classList = 'ui-dialog-title';\n titletext.setAttribute(\n 'style',\n 'width: 100%; text-align: center; padding: 3px;'\n );\n titlebar.appendChild(titletext);\n this.root.appendChild(titlebar);\n this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n var fig = this;\n\n var canvas_div = (this.canvas_div = document.createElement('div'));\n canvas_div.setAttribute(\n 'style',\n 'border: 1px solid #ddd;' +\n 'box-sizing: content-box;' +\n 'clear: both;' +\n 'min-height: 1px;' +\n 'min-width: 1px;' +\n 'outline: 0;' +\n 'overflow: hidden;' +\n 'position: relative;' +\n 'resize: both;'\n );\n\n function on_keyboard_event_closure(name) {\n return function (event) {\n return fig.key "text/plain": [ "<IPython.core.display.Javascript object>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "<img 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], "text/plain": [ "<IPython.core.display.HTML object>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "val = fitAnalyser.get_fit_value(fitResult)\n", "std = fitAnalyser.get_fit_std(fitResult)\n", "\n", "fitCurve = fitAnalyser.eval(fitResult, x=np.arange(990), y=np.arange(350), dask=\"parallelized\").load()\n", "\n", "dataKey = 'sigmax'\n", "# dataKey = 'centerx'\n", "# dataKey = 'sigmay'\n", "# dataKey = 'centery'\n", "\n", "val_mean = val[dataKey].mean(dim='runs')\n", "std_mean = val[dataKey].std(dim='runs')\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "\n", "val_mean.plot.errorbar(yerr=std_mean, fmt='--ob')\n", "\n", "plt.grid()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 112, "metadata": {}, "outputs": [ { "data": { "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n if (typeof WebSocket !== 'undefined') {\n return WebSocket;\n } else if (typeof MozWebSocket !== 'undefined') {\n return MozWebSocket;\n } else {\n alert(\n 'Your browser does not have WebSocket support. ' +\n 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n 'Firefox 4 and 5 are also supported but you ' +\n 'have to enable WebSockets in about:config.'\n );\n }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n this.id = figure_id;\n\n this.ws = websocket;\n\n this.supports_binary = this.ws.binaryType !== undefined;\n\n if (!this.supports_binary) {\n var warnings = document.getElementById('mpl-warnings');\n if (warnings) {\n warnings.style.display = 'block';\n warnings.textContent =\n 'This browser does not support binary websocket messages. ' +\n 'Performance may be slow.';\n }\n }\n\n this.imageObj = new Image();\n\n this.context = undefined;\n this.message = undefined;\n this.canvas = undefined;\n this.rubberband_canvas = undefined;\n this.rubberband_context = undefined;\n this.format_dropdown = undefined;\n\n this.image_mode = 'full';\n\n this.root = document.createElement('div');\n this.root.setAttribute('style', 'display: inline-block');\n this._root_extra_style(this.root);\n\n parent_element.appendChild(this.root);\n\n this._init_header(this);\n this._init_canvas(this);\n this._init_toolbar(this);\n\n var fig = this;\n\n this.waiting = false;\n\n this.ws.onopen = function () {\n fig.send_message('supports_binary', { value: fig.supports_binary });\n fig.send_message('send_image_mode', {});\n if (fig.ratio !== 1) {\n fig.send_message('set_device_pixel_ratio', {\n device_pixel_ratio: fig.ratio,\n });\n }\n fig.send_message('refresh', {});\n };\n\n this.imageObj.onload = function () {\n if (fig.image_mode === 'full') {\n // Full images could contain transparency (where diff images\n // almost always do), so we need to clear the canvas so that\n // there is no ghosting.\n fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n }\n fig.context.drawImage(fig.imageObj, 0, 0);\n };\n\n this.imageObj.onunload = function () {\n fig.ws.close();\n };\n\n this.ws.onmessage = this._make_on_message_function(this);\n\n this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n var titlebar = document.createElement('div');\n titlebar.classList =\n 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n var titletext = document.createElement('div');\n titletext.classList = 'ui-dialog-title';\n titletext.setAttribute(\n 'style',\n 'width: 100%; text-align: center; padding: 3px;'\n );\n titlebar.appendChild(titletext);\n this.root.appendChild(titlebar);\n this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n var fig = this;\n\n var canvas_div = (this.canvas_div = document.createElement('div'));\n canvas_div.setAttribute(\n 'style',\n 'border: 1px solid #ddd;' +\n 'box-sizing: content-box;' +\n 'clear: both;' +\n 'min-height: 1px;' +\n 'min-width: 1px;' +\n 'outline: 0;' +\n 'overflow: hidden;' +\n 'position: relative;' +\n 'resize: both;'\n );\n\n function on_keyboard_event_closure(name) {\n return function (event) {\n return fig.key "text/plain": [ "<IPython.core.display.Javascript object>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "<img 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], "text/plain": [ "<IPython.core.display.HTML object>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "val = fitAnalyser.get_fit_value(fitResult)\n", "std = fitAnalyser.get_fit_std(fitResult)\n", "\n", "fitCurve = fitAnalyser.eval(fitResult, x=np.arange(990), y=np.arange(950), dask=\"parallelized\").load()\n", "\n", "# dataKey = 'sigmax'\n", "# dataKey = 'centerx'\n", "dataKey = 'sigmay'\n", "# dataKey = 'centery'\n", "\n", "val_mean = val[dataKey].mean(dim='runs')\n", "std_mean = val[dataKey].std(dim='runs')\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "\n", "val_mean.plot.errorbar(yerr=std_mean, fmt='--ob')\n", "\n", "plt.grid()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 114, "metadata": {}, "outputs": [ { "data": { "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n if (typeof WebSocket !== 'undefined') {\n return WebSocket;\n } else if (typeof MozWebSocket !== 'undefined') {\n return MozWebSocket;\n } else {\n alert(\n 'Your browser does not have WebSocket support. ' +\n 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n 'Firefox 4 and 5 are also supported but you ' +\n 'have to enable WebSockets in about:config.'\n );\n }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n this.id = figure_id;\n\n this.ws = websocket;\n\n this.supports_binary = this.ws.binaryType !== undefined;\n\n if (!this.supports_binary) {\n var warnings = document.getElementById('mpl-warnings');\n if (warnings) {\n warnings.style.display = 'block';\n warnings.textContent =\n 'This browser does not support binary websocket messages. ' +\n 'Performance may be slow.';\n }\n }\n\n this.imageObj = new Image();\n\n this.context = undefined;\n this.message = undefined;\n this.canvas = undefined;\n this.rubberband_canvas = undefined;\n this.rubberband_context = undefined;\n this.format_dropdown = undefined;\n\n this.image_mode = 'full';\n\n this.root = document.createElement('div');\n this.root.setAttribute('style', 'display: inline-block');\n this._root_extra_style(this.root);\n\n parent_element.appendChild(this.root);\n\n this._init_header(this);\n this._init_canvas(this);\n this._init_toolbar(this);\n\n var fig = this;\n\n this.waiting = false;\n\n this.ws.onopen = function () {\n fig.send_message('supports_binary', { value: fig.supports_binary });\n fig.send_message('send_image_mode', {});\n if (fig.ratio !== 1) {\n fig.send_message('set_device_pixel_ratio', {\n device_pixel_ratio: fig.ratio,\n });\n }\n fig.send_message('refresh', {});\n };\n\n this.imageObj.onload = function () {\n if (fig.image_mode === 'full') {\n // Full images could contain transparency (where diff images\n // almost always do), so we need to clear the canvas so that\n // there is no ghosting.\n fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n }\n fig.context.drawImage(fig.imageObj, 0, 0);\n };\n\n this.imageObj.onunload = function () {\n fig.ws.close();\n };\n\n this.ws.onmessage = this._make_on_message_function(this);\n\n this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n var titlebar = document.createElement('div');\n titlebar.classList =\n 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n var titletext = document.createElement('div');\n titletext.classList = 'ui-dialog-title';\n titletext.setAttribute(\n 'style',\n 'width: 100%; text-align: center; padding: 3px;'\n );\n titlebar.appendChild(titletext);\n this.root.appendChild(titlebar);\n this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n var fig = this;\n\n var canvas_div = (this.canvas_div = document.createElement('div'));\n canvas_div.setAttribute(\n 'style',\n 'border: 1px solid #ddd;' +\n 'box-sizing: content-box;' +\n 'clear: both;' +\n 'min-height: 1px;' +\n 'min-width: 1px;' +\n 'outline: 0;' +\n 'overflow: hidden;' +\n 'position: relative;' +\n 'resize: both;'\n );\n\n function on_keyboard_event_closure(name) {\n return function (event) {\n return fig.key "text/plain": [ "<IPython.core.display.Javascript object>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "<img 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], "text/plain": [ "<IPython.core.display.HTML object>" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "T = 0.649 ± 0.005 uK\n" ] } ], "source": [ "def expansion(x, A, B):\n", " return np.sqrt(A*x*x+B)\n", "\n", "val_truncated = val_mean[2:]\n", "std_mean_truncated = std_mean[2:]\n", "\n", "fitModel_temperature = NewFitModel(expansion)\n", "fitAnalyser_temperature = FitAnalyser(fitModel_temperature, fitDim=1)\n", "\n", "params = fitAnalyser_temperature.fitModel.make_params()\n", "params.add(name=\"A\", value= 1e6, max = np.inf, min = 1, vary = True)\n", "params.add(name=\"B\", value= 1000, max = np.inf, min = 0, vary = True)\n", "\n", "fitResult_temperature = fitAnalyser_temperature.fit(val_truncated, params, x='TOF_free', dask=\"parallelized\")\n", "\n", "val = fitAnalyser_temperature.get_fit_value(fitResult_temperature)\n", "std = fitAnalyser_temperature.get_fit_std(fitResult_temperature)\n", "\n", "fit_vals = tuple([val['A'].item(), val['B'].item()])\n", "fit_vals_std = tuple([std['A'].item(), std['B'].item()])\n", "\n", "tof = (np.arange(2,16,0.1)*1e-3)\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "val_mean.plot.errorbar(ax=ax, yerr=std_mean, fmt='or')\n", "plt.plot(tof, expansion(tof, *fit_vals), 'b--',\n", " label='fit: A=%.3f, B=%.3f' % tuple(fit_vals))\n", "plt.xlabel('TOF (s)')\n", "#plt.ylabel('Cloud Width - Vertical (pixels)')\n", "plt.ylabel('Cloud Width - Horizontal (pixels)')\n", "plt.tight_layout()\n", "plt.grid(visible=1)\n", "plt.legend()\n", "\n", "\n", "m = 164*1.673e-27\n", "kb = 1.38e-23\n", "pixel = 5.86e-6\n", "M = 2.3513\n", "\n", "T = fit_vals[0] * (m/kb) * ((pixel*pixel)/(M*M)) / (1e-6)\n", "dT = fit_vals_std[0] * (m/kb) * ((pixel*pixel)/(M*M)) / (1e-6)\n", "\n", "print('T = %.3f \\u00B1 %.3f uK'% tuple([T,dT]))" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## Measure temperature at the end of evaporative cooling 2, truncation 0.6" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The detected scaning axes and values are: \n", "\n", "{'TOF_free': array([0.002, 0.003, 0.004, 0.005, 0.006, 0.007, 0.008, 0.009, 0.01 ,\n", " 0.011, 0.012, 0.013, 0.014, 0.015]), 'runs': array([0., 1., 2.])}\n" ] }, { "data": { "image/png": "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 "text/plain": [ "<Figure size 640x480 with 1 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "shotNum = \"0009\"\n", "filePath = folderPath + \"/\" + shotNum + \"/*.h5\"\n", "\n", "dataSetDict = {\n", " dskey[groupList[i]]: read_hdf5_file(filePath, groupList[i])\n", " for i in [0]\n", "}\n", "\n", "dataSet = dataSetDict[\"camera_0\"]\n", "\n", "print_scanAxis(dataSet)\n", "\n", "scanAxis = get_scanAxis(dataSet)\n", "\n", "dataSet = auto_rechunk(dataSet)\n", "\n", "dataSet = imageAnalyser.get_absorption_images(dataSet)\n", "\n", "imageAnalyser.center = (350, 990)\n", "imageAnalyser.span = (650, 200)\n", "imageAnalyser.fraction = (0.1, 0.1)\n", "\n", "dataSet_cropOD = imageAnalyser.crop_image(dataSet.OD)\n", "dataSet_cropOD = imageAnalyser.substract_offset(dataSet_cropOD).load()\n", "\n", "Ncount = imageAnalyser.get_Ncount(dataSet_cropOD)\n", "Ncount_mean = calculate_mean(Ncount)\n", "Ncount_std = calculate_std(Ncount)\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "Ncount_mean.plot.errorbar(ax=ax, yerr = Ncount_std, fmt='ob')\n", "plt.xlabel('TOF (s)')\n", "plt.ylabel('NCount')\n", "plt.tight_layout()\n", "plt.grid(visible=1)\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [], "source": [ "dataSet_cropOD_chunk = dataSet_cropOD.chunk((1, 1, 650, 200))\n", "fitAnalyser = FitAnalyser(\"Gaussian-2D\", fitDim=2)\n", "params = fitAnalyser.guess(dataSet_cropOD_chunk, dask=\"parallelized\")\n", "fitResult = fitAnalyser.fit(dataSet_cropOD_chunk, params, dask=\"parallelized\").load()" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "4.809698089774189\n", "0.160561481247611\n" ] } ], "source": [ "data = fitAnalyser.get_fit_value(fitResult)\n", "\n", "print(data.amplitude.sel(TOF_free=0.01).mean('runs').item() * 147 / 1e5)\n", "print(data.amplitude.sel(TOF_free=0.01).std('runs').item() * 147 / 1e5)" ] }, { "cell_type": "code", "execution_count": 134, "metadata": {}, "outputs": [ { "data": { "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n if (typeof WebSocket !== 'undefined') {\n return WebSocket;\n } else if (typeof MozWebSocket !== 'undefined') {\n return MozWebSocket;\n } else {\n alert(\n 'Your browser does not have WebSocket support. ' +\n 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n 'Firefox 4 and 5 are also supported but you ' +\n 'have to enable WebSockets in about:config.'\n );\n }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n this.id = figure_id;\n\n this.ws = websocket;\n\n this.supports_binary = this.ws.binaryType !== undefined;\n\n if (!this.supports_binary) {\n var warnings = document.getElementById('mpl-warnings');\n if (warnings) {\n warnings.style.display = 'block';\n warnings.textContent =\n 'This browser does not support binary websocket messages. ' +\n 'Performance may be slow.';\n }\n }\n\n this.imageObj = new Image();\n\n this.context = undefined;\n this.message = undefined;\n this.canvas = undefined;\n this.rubberband_canvas = undefined;\n this.rubberband_context = undefined;\n this.format_dropdown = undefined;\n\n this.image_mode = 'full';\n\n this.root = document.createElement('div');\n this.root.setAttribute('style', 'display: inline-block');\n this._root_extra_style(this.root);\n\n parent_element.appendChild(this.root);\n\n this._init_header(this);\n this._init_canvas(this);\n this._init_toolbar(this);\n\n var fig = this;\n\n this.waiting = false;\n\n this.ws.onopen = function () {\n fig.send_message('supports_binary', { value: fig.supports_binary });\n fig.send_message('send_image_mode', {});\n if (fig.ratio !== 1) {\n fig.send_message('set_device_pixel_ratio', {\n device_pixel_ratio: fig.ratio,\n });\n }\n fig.send_message('refresh', {});\n };\n\n this.imageObj.onload = function () {\n if (fig.image_mode === 'full') {\n // Full images could contain transparency (where diff images\n // almost always do), so we need to clear the canvas so that\n // there is no ghosting.\n fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n }\n fig.context.drawImage(fig.imageObj, 0, 0);\n };\n\n this.imageObj.onunload = function () {\n fig.ws.close();\n };\n\n this.ws.onmessage = this._make_on_message_function(this);\n\n this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n var titlebar = document.createElement('div');\n titlebar.classList =\n 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n var titletext = document.createElement('div');\n titletext.classList = 'ui-dialog-title';\n titletext.setAttribute(\n 'style',\n 'width: 100%; text-align: center; padding: 3px;'\n );\n titlebar.appendChild(titletext);\n this.root.appendChild(titlebar);\n this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n var fig = this;\n\n var canvas_div = (this.canvas_div = document.createElement('div'));\n canvas_div.setAttribute(\n 'style',\n 'border: 1px solid #ddd;' +\n 'box-sizing: content-box;' +\n 'clear: both;' +\n 'min-height: 1px;' +\n 'min-width: 1px;' +\n 'outline: 0;' +\n 'overflow: hidden;' +\n 'position: relative;' +\n 'resize: both;'\n );\n\n function on_keyboard_event_closure(name) {\n return function (event) {\n return fig.key "text/plain": [ "<IPython.core.display.Javascript object>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "<img 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], "text/plain": [ "<IPython.core.display.HTML object>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "val = fitAnalyser.get_fit_value(fitResult)\n", "std = fitAnalyser.get_fit_std(fitResult)\n", "\n", "fitCurve = fitAnalyser.eval(fitResult, x=np.arange(990), y=np.arange(350), dask=\"parallelized\").load()\n", "\n", "dataKey = 'sigmax'\n", "# dataKey = 'centerx'\n", "# dataKey = 'sigmay'\n", "# dataKey = 'centery'\n", "\n", "val_mean = val[dataKey].mean(dim='runs')\n", "std_mean = val[dataKey].std(dim='runs')\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "\n", "val_mean.plot.errorbar(yerr=std_mean, fmt='--ob')\n", "\n", "plt.grid()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 132, "metadata": {}, "outputs": [ { "data": { "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n if (typeof WebSocket !== 'undefined') {\n return WebSocket;\n } else if (typeof MozWebSocket !== 'undefined') {\n return MozWebSocket;\n } else {\n alert(\n 'Your browser does not have WebSocket support. ' +\n 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n 'Firefox 4 and 5 are also supported but you ' +\n 'have to enable WebSockets in about:config.'\n );\n }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n this.id = figure_id;\n\n this.ws = websocket;\n\n this.supports_binary = this.ws.binaryType !== undefined;\n\n if (!this.supports_binary) {\n var warnings = document.getElementById('mpl-warnings');\n if (warnings) {\n warnings.style.display = 'block';\n warnings.textContent =\n 'This browser does not support binary websocket messages. ' +\n 'Performance may be slow.';\n }\n }\n\n this.imageObj = new Image();\n\n this.context = undefined;\n this.message = undefined;\n this.canvas = undefined;\n this.rubberband_canvas = undefined;\n this.rubberband_context = undefined;\n this.format_dropdown = undefined;\n\n this.image_mode = 'full';\n\n this.root = document.createElement('div');\n this.root.setAttribute('style', 'display: inline-block');\n this._root_extra_style(this.root);\n\n parent_element.appendChild(this.root);\n\n this._init_header(this);\n this._init_canvas(this);\n this._init_toolbar(this);\n\n var fig = this;\n\n this.waiting = false;\n\n this.ws.onopen = function () {\n fig.send_message('supports_binary', { value: fig.supports_binary });\n fig.send_message('send_image_mode', {});\n if (fig.ratio !== 1) {\n fig.send_message('set_device_pixel_ratio', {\n device_pixel_ratio: fig.ratio,\n });\n }\n fig.send_message('refresh', {});\n };\n\n this.imageObj.onload = function () {\n if (fig.image_mode === 'full') {\n // Full images could contain transparency (where diff images\n // almost always do), so we need to clear the canvas so that\n // there is no ghosting.\n fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n }\n fig.context.drawImage(fig.imageObj, 0, 0);\n };\n\n this.imageObj.onunload = function () {\n fig.ws.close();\n };\n\n this.ws.onmessage = this._make_on_message_function(this);\n\n this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n var titlebar = document.createElement('div');\n titlebar.classList =\n 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n var titletext = document.createElement('div');\n titletext.classList = 'ui-dialog-title';\n titletext.setAttribute(\n 'style',\n 'width: 100%; text-align: center; padding: 3px;'\n );\n titlebar.appendChild(titletext);\n this.root.appendChild(titlebar);\n this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n var fig = this;\n\n var canvas_div = (this.canvas_div = document.createElement('div'));\n canvas_div.setAttribute(\n 'style',\n 'border: 1px solid #ddd;' +\n 'box-sizing: content-box;' +\n 'clear: both;' +\n 'min-height: 1px;' +\n 'min-width: 1px;' +\n 'outline: 0;' +\n 'overflow: hidden;' +\n 'position: relative;' +\n 'resize: both;'\n );\n\n function on_keyboard_event_closure(name) {\n return function (event) {\n return fig.key "text/plain": [ "<IPython.core.display.Javascript object>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "<img src=\"data:image/png;base64,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 ], "text/plain": [ "<IPython.core.display.HTML object>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "val = fitAnalyser.get_fit_value(fitResult)\n", "std = fitAnalyser.get_fit_std(fitResult)\n", "\n", "fitCurve = fitAnalyser.eval(fitResult, x=np.arange(990), y=np.arange(950), dask=\"parallelized\").load()\n", "\n", "# dataKey = 'sigmax'\n", "# dataKey = 'centerx'\n", "dataKey = 'sigmay'\n", "# dataKey = 'centery'\n", "\n", "val_mean = val[dataKey].mean(dim='runs')\n", "std_mean = val[dataKey].std(dim='runs')\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "\n", "val_mean.plot.errorbar(yerr=std_mean, fmt='--ob')\n", "\n", "plt.grid()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 136, "metadata": {}, "outputs": [ { "data": { "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n if (typeof WebSocket !== 'undefined') {\n return WebSocket;\n } else if (typeof MozWebSocket !== 'undefined') {\n return MozWebSocket;\n } else {\n alert(\n 'Your browser does not have WebSocket support. ' +\n 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n 'Firefox 4 and 5 are also supported but you ' +\n 'have to enable WebSockets in about:config.'\n );\n }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n this.id = figure_id;\n\n this.ws = websocket;\n\n this.supports_binary = this.ws.binaryType !== undefined;\n\n if (!this.supports_binary) {\n var warnings = document.getElementById('mpl-warnings');\n if (warnings) {\n warnings.style.display = 'block';\n warnings.textContent =\n 'This browser does not support binary websocket messages. ' +\n 'Performance may be slow.';\n }\n }\n\n this.imageObj = new Image();\n\n this.context = undefined;\n this.message = undefined;\n this.canvas = undefined;\n this.rubberband_canvas = undefined;\n this.rubberband_context = undefined;\n this.format_dropdown = undefined;\n\n this.image_mode = 'full';\n\n this.root = document.createElement('div');\n this.root.setAttribute('style', 'display: inline-block');\n this._root_extra_style(this.root);\n\n parent_element.appendChild(this.root);\n\n this._init_header(this);\n this._init_canvas(this);\n this._init_toolbar(this);\n\n var fig = this;\n\n this.waiting = false;\n\n this.ws.onopen = function () {\n fig.send_message('supports_binary', { value: fig.supports_binary });\n fig.send_message('send_image_mode', {});\n if (fig.ratio !== 1) {\n fig.send_message('set_device_pixel_ratio', {\n device_pixel_ratio: fig.ratio,\n });\n }\n fig.send_message('refresh', {});\n };\n\n this.imageObj.onload = function () {\n if (fig.image_mode === 'full') {\n // Full images could contain transparency (where diff images\n // almost always do), so we need to clear the canvas so that\n // there is no ghosting.\n fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n }\n fig.context.drawImage(fig.imageObj, 0, 0);\n };\n\n this.imageObj.onunload = function () {\n fig.ws.close();\n };\n\n this.ws.onmessage = this._make_on_message_function(this);\n\n this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n var titlebar = document.createElement('div');\n titlebar.classList =\n 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n var titletext = document.createElement('div');\n titletext.classList = 'ui-dialog-title';\n titletext.setAttribute(\n 'style',\n 'width: 100%; text-align: center; padding: 3px;'\n );\n titlebar.appendChild(titletext);\n this.root.appendChild(titlebar);\n this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n var fig = this;\n\n var canvas_div = (this.canvas_div = document.createElement('div'));\n canvas_div.setAttribute(\n 'style',\n 'border: 1px solid #ddd;' +\n 'box-sizing: content-box;' +\n 'clear: both;' +\n 'min-height: 1px;' +\n 'min-width: 1px;' +\n 'outline: 0;' +\n 'overflow: hidden;' +\n 'position: relative;' +\n 'resize: both;'\n );\n\n function on_keyboard_event_closure(name) {\n return function (event) {\n return fig.key "text/plain": [ "<IPython.core.display.Javascript object>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "<img 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], "text/plain": [ "<IPython.core.display.HTML object>" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "T = 0.858 ± 0.004 uK\n" ] } ], "source": [ "def expansion(x, A, B):\n", " return np.sqrt(A*x*x+B)\n", "\n", "val_truncated = val_mean[2:]\n", "std_mean_truncated = std_mean[2:]\n", "\n", "fitModel_temperature = NewFitModel(expansion)\n", "fitAnalyser_temperature = FitAnalyser(fitModel_temperature, fitDim=1)\n", "\n", "params = fitAnalyser_temperature.fitModel.make_params()\n", "params.add(name=\"A\", value= 1e6, max = np.inf, min = 1, vary = True)\n", "params.add(name=\"B\", value= 1000, max = np.inf, min = 0, vary = True)\n", "\n", "fitResult_temperature = fitAnalyser_temperature.fit(val_truncated, params, x='TOF_free', dask=\"parallelized\")\n", "\n", "val = fitAnalyser_temperature.get_fit_value(fitResult_temperature)\n", "std = fitAnalyser_temperature.get_fit_std(fitResult_temperature)\n", "\n", "fit_vals = tuple([val['A'].item(), val['B'].item()])\n", "fit_vals_std = tuple([std['A'].item(), std['B'].item()])\n", "\n", "tof = (np.arange(2,16,0.1)*1e-3)\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "val_mean.plot.errorbar(ax=ax, yerr=std_mean, fmt='or')\n", "plt.plot(tof, expansion(tof, *fit_vals), 'b--',\n", " label='fit: A=%.3f, B=%.3f' % tuple(fit_vals))\n", "plt.xlabel('TOF (s)')\n", "plt.ylabel('Cloud Width - Vertical (pixels)')\n", "# plt.ylabel('Cloud Width - Horizontal (pixels)')\n", "plt.tight_layout()\n", "plt.grid(visible=1)\n", "plt.legend()\n", "\n", "\n", "m = 164*1.673e-27\n", "kb = 1.38e-23\n", "pixel = 5.86e-6\n", "M = 2.3513\n", "\n", "T = fit_vals[0] * (m/kb) * ((pixel*pixel)/(M*M)) / (1e-6)\n", "dT = fit_vals_std[0] * (m/kb) * ((pixel*pixel)/(M*M)) / (1e-6)\n", "\n", "print('T = %.3f \\u00B1 %.3f uK'% tuple([T,dT]))" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## Measure temperature at the end of evaporative cooling 2, truncation 0.675" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The detected scaning axes and values are: \n", "\n", "{'TOF_free': array([0.002, 0.003, 0.004, 0.005, 0.006, 0.007, 0.008, 0.009, 0.01 ,\n", " 0.011, 0.012, 0.013, 0.014, 0.015]), 'runs': array([0., 1., 2.])}\n" ] }, { "data": { "image/png": "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 "text/plain": [ "<Figure size 640x480 with 1 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "shotNum = \"0010\"\n", "filePath = folderPath + \"/\" + shotNum + \"/*.h5\"\n", "\n", "dataSetDict = {\n", " dskey[groupList[i]]: read_hdf5_file(filePath, groupList[i])\n", " for i in [0]\n", "}\n", "\n", "dataSet = dataSetDict[\"camera_0\"]\n", "\n", "print_scanAxis(dataSet)\n", "\n", "scanAxis = get_scanAxis(dataSet)\n", "\n", "dataSet = auto_rechunk(dataSet)\n", "\n", "dataSet = imageAnalyser.get_absorption_images(dataSet)\n", "\n", "imageAnalyser.center = (350, 990)\n", "imageAnalyser.span = (650, 200)\n", "imageAnalyser.fraction = (0.1, 0.1)\n", "\n", "dataSet_cropOD = imageAnalyser.crop_image(dataSet.OD)\n", "dataSet_cropOD = imageAnalyser.substract_offset(dataSet_cropOD).load()\n", "\n", "Ncount = imageAnalyser.get_Ncount(dataSet_cropOD)\n", "Ncount_mean = calculate_mean(Ncount)\n", "Ncount_std = calculate_std(Ncount)\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "Ncount_mean.plot.errorbar(ax=ax, yerr = Ncount_std, fmt='ob')\n", "plt.xlabel('TOF (s)')\n", "plt.ylabel('NCount')\n", "plt.tight_layout()\n", "plt.grid(visible=1)\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [], "source": [ "dataSet_cropOD_chunk = dataSet_cropOD.chunk((1, 1, 650, 200))\n", "fitAnalyser = FitAnalyser(\"Gaussian-2D\", fitDim=2)\n", "params = fitAnalyser.guess(dataSet_cropOD_chunk, dask=\"parallelized\")\n", "fitResult = fitAnalyser.fit(dataSet_cropOD_chunk, params, dask=\"parallelized\").load()" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "4.027352128668683\n", "0.03427747912979168\n" ] } ], "source": [ "data = fitAnalyser.get_fit_value(fitResult)\n", "\n", "print(data.amplitude.sel(TOF_free=0.01).mean('runs').item() * 147 / 1e5)\n", "print(data.amplitude.sel(TOF_free=0.01).std('runs').item() * 147 / 1e5)" ] }, { "cell_type": "code", "execution_count": 147, "metadata": {}, "outputs": [ { "data": { "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n if (typeof WebSocket !== 'undefined') {\n return WebSocket;\n } else if (typeof MozWebSocket !== 'undefined') {\n return MozWebSocket;\n } else {\n alert(\n 'Your browser does not have WebSocket support. ' +\n 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n 'Firefox 4 and 5 are also supported but you ' +\n 'have to enable WebSockets in about:config.'\n );\n }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n this.id = figure_id;\n\n this.ws = websocket;\n\n this.supports_binary = this.ws.binaryType !== undefined;\n\n if (!this.supports_binary) {\n var warnings = document.getElementById('mpl-warnings');\n if (warnings) {\n warnings.style.display = 'block';\n warnings.textContent =\n 'This browser does not support binary websocket messages. ' +\n 'Performance may be slow.';\n }\n }\n\n this.imageObj = new Image();\n\n this.context = undefined;\n this.message = undefined;\n this.canvas = undefined;\n this.rubberband_canvas = undefined;\n this.rubberband_context = undefined;\n this.format_dropdown = undefined;\n\n this.image_mode = 'full';\n\n this.root = document.createElement('div');\n this.root.setAttribute('style', 'display: inline-block');\n this._root_extra_style(this.root);\n\n parent_element.appendChild(this.root);\n\n this._init_header(this);\n this._init_canvas(this);\n this._init_toolbar(this);\n\n var fig = this;\n\n this.waiting = false;\n\n this.ws.onopen = function () {\n fig.send_message('supports_binary', { value: fig.supports_binary });\n fig.send_message('send_image_mode', {});\n if (fig.ratio !== 1) {\n fig.send_message('set_device_pixel_ratio', {\n device_pixel_ratio: fig.ratio,\n });\n }\n fig.send_message('refresh', {});\n };\n\n this.imageObj.onload = function () {\n if (fig.image_mode === 'full') {\n // Full images could contain transparency (where diff images\n // almost always do), so we need to clear the canvas so that\n // there is no ghosting.\n fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n }\n fig.context.drawImage(fig.imageObj, 0, 0);\n };\n\n this.imageObj.onunload = function () {\n fig.ws.close();\n };\n\n this.ws.onmessage = this._make_on_message_function(this);\n\n this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n var titlebar = document.createElement('div');\n titlebar.classList =\n 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n var titletext = document.createElement('div');\n titletext.classList = 'ui-dialog-title';\n titletext.setAttribute(\n 'style',\n 'width: 100%; text-align: center; padding: 3px;'\n );\n titlebar.appendChild(titletext);\n this.root.appendChild(titlebar);\n this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n var fig = this;\n\n var canvas_div = (this.canvas_div = document.createElement('div'));\n canvas_div.setAttribute(\n 'style',\n 'border: 1px solid #ddd;' +\n 'box-sizing: content-box;' +\n 'clear: both;' +\n 'min-height: 1px;' +\n 'min-width: 1px;' +\n 'outline: 0;' +\n 'overflow: hidden;' +\n 'position: relative;' +\n 'resize: both;'\n );\n\n function on_keyboard_event_closure(name) {\n return function (event) {\n return fig.key "text/plain": [ "<IPython.core.display.Javascript object>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "<img 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], "text/plain": [ "<IPython.core.display.HTML object>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "val = fitAnalyser.get_fit_value(fitResult)\n", "std = fitAnalyser.get_fit_std(fitResult)\n", "\n", "fitCurve = fitAnalyser.eval(fitResult, x=np.arange(990), y=np.arange(350), dask=\"parallelized\").load()\n", "\n", "dataKey = 'sigmax'\n", "# dataKey = 'centerx'\n", "# dataKey = 'sigmay'\n", "# dataKey = 'centery'\n", "\n", "val_mean = val[dataKey].mean(dim='runs')\n", "std_mean = val[dataKey].std(dim='runs')\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "\n", "val_mean.plot.errorbar(yerr=std_mean, fmt='--ob')\n", "\n", "plt.grid()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 150, "metadata": {}, "outputs": [ { "data": { "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n if (typeof WebSocket !== 'undefined') {\n return WebSocket;\n } else if (typeof MozWebSocket !== 'undefined') {\n return MozWebSocket;\n } else {\n alert(\n 'Your browser does not have WebSocket support. ' +\n 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n 'Firefox 4 and 5 are also supported but you ' +\n 'have to enable WebSockets in about:config.'\n );\n }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n this.id = figure_id;\n\n this.ws = websocket;\n\n this.supports_binary = this.ws.binaryType !== undefined;\n\n if (!this.supports_binary) {\n var warnings = document.getElementById('mpl-warnings');\n if (warnings) {\n warnings.style.display = 'block';\n warnings.textContent =\n 'This browser does not support binary websocket messages. ' +\n 'Performance may be slow.';\n }\n }\n\n this.imageObj = new Image();\n\n this.context = undefined;\n this.message = undefined;\n this.canvas = undefined;\n this.rubberband_canvas = undefined;\n this.rubberband_context = undefined;\n this.format_dropdown = undefined;\n\n this.image_mode = 'full';\n\n this.root = document.createElement('div');\n this.root.setAttribute('style', 'display: inline-block');\n this._root_extra_style(this.root);\n\n parent_element.appendChild(this.root);\n\n this._init_header(this);\n this._init_canvas(this);\n this._init_toolbar(this);\n\n var fig = this;\n\n this.waiting = false;\n\n this.ws.onopen = function () {\n fig.send_message('supports_binary', { value: fig.supports_binary });\n fig.send_message('send_image_mode', {});\n if (fig.ratio !== 1) {\n fig.send_message('set_device_pixel_ratio', {\n device_pixel_ratio: fig.ratio,\n });\n }\n fig.send_message('refresh', {});\n };\n\n this.imageObj.onload = function () {\n if (fig.image_mode === 'full') {\n // Full images could contain transparency (where diff images\n // almost always do), so we need to clear the canvas so that\n // there is no ghosting.\n fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n }\n fig.context.drawImage(fig.imageObj, 0, 0);\n };\n\n this.imageObj.onunload = function () {\n fig.ws.close();\n };\n\n this.ws.onmessage = this._make_on_message_function(this);\n\n this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n var titlebar = document.createElement('div');\n titlebar.classList =\n 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n var titletext = document.createElement('div');\n titletext.classList = 'ui-dialog-title';\n titletext.setAttribute(\n 'style',\n 'width: 100%; text-align: center; padding: 3px;'\n );\n titlebar.appendChild(titletext);\n this.root.appendChild(titlebar);\n this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n var fig = this;\n\n var canvas_div = (this.canvas_div = document.createElement('div'));\n canvas_div.setAttribute(\n 'style',\n 'border: 1px solid #ddd;' +\n 'box-sizing: content-box;' +\n 'clear: both;' +\n 'min-height: 1px;' +\n 'min-width: 1px;' +\n 'outline: 0;' +\n 'overflow: hidden;' +\n 'position: relative;' +\n 'resize: both;'\n );\n\n function on_keyboard_event_closure(name) {\n return function (event) {\n return fig.key "text/plain": [ "<IPython.core.display.Javascript object>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "<img 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], "text/plain": [ "<IPython.core.display.HTML object>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "val = fitAnalyser.get_fit_value(fitResult)\n", "std = fitAnalyser.get_fit_std(fitResult)\n", "\n", "fitCurve = fitAnalyser.eval(fitResult, x=np.arange(990), y=np.arange(950), dask=\"parallelized\").load()\n", "\n", "# dataKey = 'sigmax'\n", "# dataKey = 'centerx'\n", "dataKey = 'sigmay'\n", "# dataKey = 'centery'\n", "\n", "val_mean = val[dataKey].mean(dim='runs')\n", "std_mean = val[dataKey].std(dim='runs')\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "\n", "val_mean.plot.errorbar(yerr=std_mean, fmt='--ob')\n", "\n", "plt.grid()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 152, "metadata": {}, "outputs": [ { "data": { "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n if (typeof WebSocket !== 'undefined') {\n return WebSocket;\n } else if (typeof MozWebSocket !== 'undefined') {\n return MozWebSocket;\n } else {\n alert(\n 'Your browser does not have WebSocket support. ' +\n 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n 'Firefox 4 and 5 are also supported but you ' +\n 'have to enable WebSockets in about:config.'\n );\n }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n this.id = figure_id;\n\n this.ws = websocket;\n\n this.supports_binary = this.ws.binaryType !== undefined;\n\n if (!this.supports_binary) {\n var warnings = document.getElementById('mpl-warnings');\n if (warnings) {\n warnings.style.display = 'block';\n warnings.textContent =\n 'This browser does not support binary websocket messages. ' +\n 'Performance may be slow.';\n }\n }\n\n this.imageObj = new Image();\n\n this.context = undefined;\n this.message = undefined;\n this.canvas = undefined;\n this.rubberband_canvas = undefined;\n this.rubberband_context = undefined;\n this.format_dropdown = undefined;\n\n this.image_mode = 'full';\n\n this.root = document.createElement('div');\n this.root.setAttribute('style', 'display: inline-block');\n this._root_extra_style(this.root);\n\n parent_element.appendChild(this.root);\n\n this._init_header(this);\n this._init_canvas(this);\n this._init_toolbar(this);\n\n var fig = this;\n\n this.waiting = false;\n\n this.ws.onopen = function () {\n fig.send_message('supports_binary', { value: fig.supports_binary });\n fig.send_message('send_image_mode', {});\n if (fig.ratio !== 1) {\n fig.send_message('set_device_pixel_ratio', {\n device_pixel_ratio: fig.ratio,\n });\n }\n fig.send_message('refresh', {});\n };\n\n this.imageObj.onload = function () {\n if (fig.image_mode === 'full') {\n // Full images could contain transparency (where diff images\n // almost always do), so we need to clear the canvas so that\n // there is no ghosting.\n fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n }\n fig.context.drawImage(fig.imageObj, 0, 0);\n };\n\n this.imageObj.onunload = function () {\n fig.ws.close();\n };\n\n this.ws.onmessage = this._make_on_message_function(this);\n\n this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n var titlebar = document.createElement('div');\n titlebar.classList =\n 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n var titletext = document.createElement('div');\n titletext.classList = 'ui-dialog-title';\n titletext.setAttribute(\n 'style',\n 'width: 100%; text-align: center; padding: 3px;'\n );\n titlebar.appendChild(titletext);\n this.root.appendChild(titlebar);\n this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n var fig = this;\n\n var canvas_div = (this.canvas_div = document.createElement('div'));\n canvas_div.setAttribute(\n 'style',\n 'border: 1px solid #ddd;' +\n 'box-sizing: content-box;' +\n 'clear: both;' +\n 'min-height: 1px;' +\n 'min-width: 1px;' +\n 'outline: 0;' +\n 'overflow: hidden;' +\n 'position: relative;' +\n 'resize: both;'\n );\n\n function on_keyboard_event_closure(name) {\n return function (event) {\n return fig.key "text/plain": [ "<IPython.core.display.Javascript object>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "<img 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], "text/plain": [ "<IPython.core.display.HTML object>" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "T = 0.553 ± 0.004 uK\n" ] } ], "source": [ "def expansion(x, A, B):\n", " return np.sqrt(A*x*x+B)\n", "\n", "val_truncated = val_mean[2:]\n", "std_mean_truncated = std_mean[2:]\n", "\n", "fitModel_temperature = NewFitModel(expansion)\n", "fitAnalyser_temperature = FitAnalyser(fitModel_temperature, fitDim=1)\n", "\n", "params = fitAnalyser_temperature.fitModel.make_params()\n", "params.add(name=\"A\", value= 1e6, max = np.inf, min = 1, vary = True)\n", "params.add(name=\"B\", value= 1000, max = np.inf, min = 0, vary = True)\n", "\n", "fitResult_temperature = fitAnalyser_temperature.fit(val_truncated, params, x='TOF_free', dask=\"parallelized\")\n", "\n", "val = fitAnalyser_temperature.get_fit_value(fitResult_temperature)\n", "std = fitAnalyser_temperature.get_fit_std(fitResult_temperature)\n", "\n", "fit_vals = tuple([val['A'].item(), val['B'].item()])\n", "fit_vals_std = tuple([std['A'].item(), std['B'].item()])\n", "\n", "tof = (np.arange(2,16,0.1)*1e-3)\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "val_mean.plot.errorbar(ax=ax, yerr=std_mean, fmt='or')\n", "plt.plot(tof, expansion(tof, *fit_vals), 'b--',\n", " label='fit: A=%.3f, B=%.3f' % tuple(fit_vals))\n", "plt.xlabel('TOF (s)')\n", "# plt.ylabel('Cloud Width - Vertical (pixels)')\n", "plt.ylabel('Cloud Width - Horizontal (pixels)')\n", "plt.tight_layout()\n", "plt.grid(visible=1)\n", "plt.legend()\n", "\n", "\n", "m = 164*1.673e-27\n", "kb = 1.38e-23\n", "pixel = 5.86e-6\n", "M = 2.3513\n", "\n", "T = fit_vals[0] * (m/kb) * ((pixel*pixel)/(M*M)) / (1e-6)\n", "dT = fit_vals_std[0] * (m/kb) * ((pixel*pixel)/(M*M)) / (1e-6)\n", "\n", "print('T = %.3f \\u00B1 %.3f uK'% tuple([T,dT]))" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## Measure temperature at the end of evaporative cooling 2, truncation 0.725" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The detected scaning axes and values are: \n", "\n", "{'TOF_free': array([0.002, 0.003, 0.004, 0.005, 0.006, 0.007, 0.008, 0.009, 0.01 ,\n", " 0.011, 0.012, 0.013, 0.014, 0.015]), 'runs': array([0., 1., 2.])}\n" ] }, { "data": { "image/png": "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 "text/plain": [ "<Figure size 640x480 with 1 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "shotNum = \"0011\"\n", "filePath = folderPath + \"/\" + shotNum + \"/*.h5\"\n", "\n", "dataSetDict = {\n", " dskey[groupList[i]]: read_hdf5_file(filePath, groupList[i])\n", " for i in [0]\n", "}\n", "\n", "dataSet = dataSetDict[\"camera_0\"]\n", "\n", "print_scanAxis(dataSet)\n", "\n", "scanAxis = get_scanAxis(dataSet)\n", "\n", "dataSet = auto_rechunk(dataSet)\n", "\n", "dataSet = imageAnalyser.get_absorption_images(dataSet)\n", "\n", "imageAnalyser.center = (350, 990)\n", "imageAnalyser.span = (650, 200)\n", "imageAnalyser.fraction = (0.1, 0.1)\n", "\n", "dataSet_cropOD = imageAnalyser.crop_image(dataSet.OD)\n", "dataSet_cropOD = imageAnalyser.substract_offset(dataSet_cropOD).load()\n", "\n", "Ncount = imageAnalyser.get_Ncount(dataSet_cropOD)\n", "Ncount_mean = calculate_mean(Ncount)\n", "Ncount_std = calculate_std(Ncount)\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "Ncount_mean.plot.errorbar(ax=ax, yerr = Ncount_std, fmt='ob')\n", "plt.xlabel('TOF (s)')\n", "plt.ylabel('NCount')\n", "plt.tight_layout()\n", "plt.grid(visible=1)\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [], "source": [ "dataSet_cropOD_chunk = dataSet_cropOD.chunk((1, 1, 650, 200))\n", "fitAnalyser = FitAnalyser(\"Gaussian-2D\", fitDim=2)\n", "params = fitAnalyser.guess(dataSet_cropOD_chunk, dask=\"parallelized\")\n", "fitResult = fitAnalyser.fit(dataSet_cropOD_chunk, params, dask=\"parallelized\").load()" ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "3.338057111672083\n", "0.07935760046682089\n" ] } ], "source": [ "data = fitAnalyser.get_fit_value(fitResult)\n", "\n", "print(data.amplitude.sel(TOF_free=0.01).mean('runs').item() * 147 / 1e5)\n", "print(data.amplitude.sel(TOF_free=0.01).std('runs').item() * 147 / 1e5)" ] }, { "cell_type": "code", "execution_count": 160, "metadata": {}, "outputs": [ { "data": { "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n if (typeof WebSocket !== 'undefined') {\n return WebSocket;\n } else if (typeof MozWebSocket !== 'undefined') {\n return MozWebSocket;\n } else {\n alert(\n 'Your browser does not have WebSocket support. ' +\n 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n 'Firefox 4 and 5 are also supported but you ' +\n 'have to enable WebSockets in about:config.'\n );\n }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n this.id = figure_id;\n\n this.ws = websocket;\n\n this.supports_binary = this.ws.binaryType !== undefined;\n\n if (!this.supports_binary) {\n var warnings = document.getElementById('mpl-warnings');\n if (warnings) {\n warnings.style.display = 'block';\n warnings.textContent =\n 'This browser does not support binary websocket messages. ' +\n 'Performance may be slow.';\n }\n }\n\n this.imageObj = new Image();\n\n this.context = undefined;\n this.message = undefined;\n this.canvas = undefined;\n this.rubberband_canvas = undefined;\n this.rubberband_context = undefined;\n this.format_dropdown = undefined;\n\n this.image_mode = 'full';\n\n this.root = document.createElement('div');\n this.root.setAttribute('style', 'display: inline-block');\n this._root_extra_style(this.root);\n\n parent_element.appendChild(this.root);\n\n this._init_header(this);\n this._init_canvas(this);\n this._init_toolbar(this);\n\n var fig = this;\n\n this.waiting = false;\n\n this.ws.onopen = function () {\n fig.send_message('supports_binary', { value: fig.supports_binary });\n fig.send_message('send_image_mode', {});\n if (fig.ratio !== 1) {\n fig.send_message('set_device_pixel_ratio', {\n device_pixel_ratio: fig.ratio,\n });\n }\n fig.send_message('refresh', {});\n };\n\n this.imageObj.onload = function () {\n if (fig.image_mode === 'full') {\n // Full images could contain transparency (where diff images\n // almost always do), so we need to clear the canvas so that\n // there is no ghosting.\n fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n }\n fig.context.drawImage(fig.imageObj, 0, 0);\n };\n\n this.imageObj.onunload = function () {\n fig.ws.close();\n };\n\n this.ws.onmessage = this._make_on_message_function(this);\n\n this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n var titlebar = document.createElement('div');\n titlebar.classList =\n 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n var titletext = document.createElement('div');\n titletext.classList = 'ui-dialog-title';\n titletext.setAttribute(\n 'style',\n 'width: 100%; text-align: center; padding: 3px;'\n );\n titlebar.appendChild(titletext);\n this.root.appendChild(titlebar);\n this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n var fig = this;\n\n var canvas_div = (this.canvas_div = document.createElement('div'));\n canvas_div.setAttribute(\n 'style',\n 'border: 1px solid #ddd;' +\n 'box-sizing: content-box;' +\n 'clear: both;' +\n 'min-height: 1px;' +\n 'min-width: 1px;' +\n 'outline: 0;' +\n 'overflow: hidden;' +\n 'position: relative;' +\n 'resize: both;'\n );\n\n function on_keyboard_event_closure(name) {\n return function (event) {\n return fig.key "text/plain": [ "<IPython.core.display.Javascript object>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "<img 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], "text/plain": [ "<IPython.core.display.HTML object>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "val = fitAnalyser.get_fit_value(fitResult)\n", "std = fitAnalyser.get_fit_std(fitResult)\n", "\n", "fitCurve = fitAnalyser.eval(fitResult, x=np.arange(990), y=np.arange(350), dask=\"parallelized\").load()\n", "\n", "dataKey = 'sigmax'\n", "# dataKey = 'centerx'\n", "# dataKey = 'sigmay'\n", "# dataKey = 'centery'\n", "\n", "val_mean = val[dataKey].mean(dim='runs')\n", "std_mean = val[dataKey].std(dim='runs')\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "\n", "val_mean.plot.errorbar(yerr=std_mean, fmt='--ob')\n", "\n", "plt.grid()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 162, "metadata": {}, "outputs": [ { "data": { "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n if (typeof WebSocket !== 'undefined') {\n return WebSocket;\n } else if (typeof MozWebSocket !== 'undefined') {\n return MozWebSocket;\n } else {\n alert(\n 'Your browser does not have WebSocket support. ' +\n 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n 'Firefox 4 and 5 are also supported but you ' +\n 'have to enable WebSockets in about:config.'\n );\n }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n this.id = figure_id;\n\n this.ws = websocket;\n\n this.supports_binary = this.ws.binaryType !== undefined;\n\n if (!this.supports_binary) {\n var warnings = document.getElementById('mpl-warnings');\n if (warnings) {\n warnings.style.display = 'block';\n warnings.textContent =\n 'This browser does not support binary websocket messages. ' +\n 'Performance may be slow.';\n }\n }\n\n this.imageObj = new Image();\n\n this.context = undefined;\n this.message = undefined;\n this.canvas = undefined;\n this.rubberband_canvas = undefined;\n this.rubberband_context = undefined;\n this.format_dropdown = undefined;\n\n this.image_mode = 'full';\n\n this.root = document.createElement('div');\n this.root.setAttribute('style', 'display: inline-block');\n this._root_extra_style(this.root);\n\n parent_element.appendChild(this.root);\n\n this._init_header(this);\n this._init_canvas(this);\n this._init_toolbar(this);\n\n var fig = this;\n\n this.waiting = false;\n\n this.ws.onopen = function () {\n fig.send_message('supports_binary', { value: fig.supports_binary });\n fig.send_message('send_image_mode', {});\n if (fig.ratio !== 1) {\n fig.send_message('set_device_pixel_ratio', {\n device_pixel_ratio: fig.ratio,\n });\n }\n fig.send_message('refresh', {});\n };\n\n this.imageObj.onload = function () {\n if (fig.image_mode === 'full') {\n // Full images could contain transparency (where diff images\n // almost always do), so we need to clear the canvas so that\n // there is no ghosting.\n fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n }\n fig.context.drawImage(fig.imageObj, 0, 0);\n };\n\n this.imageObj.onunload = function () {\n fig.ws.close();\n };\n\n this.ws.onmessage = this._make_on_message_function(this);\n\n this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n var titlebar = document.createElement('div');\n titlebar.classList =\n 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n var titletext = document.createElement('div');\n titletext.classList = 'ui-dialog-title';\n titletext.setAttribute(\n 'style',\n 'width: 100%; text-align: center; padding: 3px;'\n );\n titlebar.appendChild(titletext);\n this.root.appendChild(titlebar);\n this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n var fig = this;\n\n var canvas_div = (this.canvas_div = document.createElement('div'));\n canvas_div.setAttribute(\n 'style',\n 'border: 1px solid #ddd;' +\n 'box-sizing: content-box;' +\n 'clear: both;' +\n 'min-height: 1px;' +\n 'min-width: 1px;' +\n 'outline: 0;' +\n 'overflow: hidden;' +\n 'position: relative;' +\n 'resize: both;'\n );\n\n function on_keyboard_event_closure(name) {\n return function (event) {\n return fig.key "text/plain": [ "<IPython.core.display.Javascript object>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "<img 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], "text/plain": [ "<IPython.core.display.HTML object>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "val = fitAnalyser.get_fit_value(fitResult)\n", "std = fitAnalyser.get_fit_std(fitResult)\n", "\n", "fitCurve = fitAnalyser.eval(fitResult, x=np.arange(990), y=np.arange(950), dask=\"parallelized\").load()\n", "\n", "# dataKey = 'sigmax'\n", "# dataKey = 'centerx'\n", "dataKey = 'sigmay'\n", "# dataKey = 'centery'\n", "\n", "val_mean = val[dataKey].mean(dim='runs')\n", "std_mean = val[dataKey].std(dim='runs')\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "\n", "val_mean.plot.errorbar(yerr=std_mean, fmt='--ob')\n", "\n", "plt.grid()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 164, "metadata": {}, "outputs": [ { "data": { "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n if (typeof WebSocket !== 'undefined') {\n return WebSocket;\n } else if (typeof MozWebSocket !== 'undefined') {\n return MozWebSocket;\n } else {\n alert(\n 'Your browser does not have WebSocket support. ' +\n 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n 'Firefox 4 and 5 are also supported but you ' +\n 'have to enable WebSockets in about:config.'\n );\n }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n this.id = figure_id;\n\n this.ws = websocket;\n\n this.supports_binary = this.ws.binaryType !== undefined;\n\n if (!this.supports_binary) {\n var warnings = document.getElementById('mpl-warnings');\n if (warnings) {\n warnings.style.display = 'block';\n warnings.textContent =\n 'This browser does not support binary websocket messages. ' +\n 'Performance may be slow.';\n }\n }\n\n this.imageObj = new Image();\n\n this.context = undefined;\n this.message = undefined;\n this.canvas = undefined;\n this.rubberband_canvas = undefined;\n this.rubberband_context = undefined;\n this.format_dropdown = undefined;\n\n this.image_mode = 'full';\n\n this.root = document.createElement('div');\n this.root.setAttribute('style', 'display: inline-block');\n this._root_extra_style(this.root);\n\n parent_element.appendChild(this.root);\n\n this._init_header(this);\n this._init_canvas(this);\n this._init_toolbar(this);\n\n var fig = this;\n\n this.waiting = false;\n\n this.ws.onopen = function () {\n fig.send_message('supports_binary', { value: fig.supports_binary });\n fig.send_message('send_image_mode', {});\n if (fig.ratio !== 1) {\n fig.send_message('set_device_pixel_ratio', {\n device_pixel_ratio: fig.ratio,\n });\n }\n fig.send_message('refresh', {});\n };\n\n this.imageObj.onload = function () {\n if (fig.image_mode === 'full') {\n // Full images could contain transparency (where diff images\n // almost always do), so we need to clear the canvas so that\n // there is no ghosting.\n fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n }\n fig.context.drawImage(fig.imageObj, 0, 0);\n };\n\n this.imageObj.onunload = function () {\n fig.ws.close();\n };\n\n this.ws.onmessage = this._make_on_message_function(this);\n\n this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n var titlebar = document.createElement('div');\n titlebar.classList =\n 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n var titletext = document.createElement('div');\n titletext.classList = 'ui-dialog-title';\n titletext.setAttribute(\n 'style',\n 'width: 100%; text-align: center; padding: 3px;'\n );\n titlebar.appendChild(titletext);\n this.root.appendChild(titlebar);\n this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n var fig = this;\n\n var canvas_div = (this.canvas_div = document.createElement('div'));\n canvas_div.setAttribute(\n 'style',\n 'border: 1px solid #ddd;' +\n 'box-sizing: content-box;' +\n 'clear: both;' +\n 'min-height: 1px;' +\n 'min-width: 1px;' +\n 'outline: 0;' +\n 'overflow: hidden;' +\n 'position: relative;' +\n 'resize: both;'\n );\n\n function on_keyboard_event_closure(name) {\n return function (event) {\n return fig.key "text/plain": [ "<IPython.core.display.Javascript object>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "<img 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], "text/plain": [ "<IPython.core.display.HTML object>" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "T = 0.432 ± 0.004 uK\n" ] } ], "source": [ "def expansion(x, A, B):\n", " return np.sqrt(A*x*x+B)\n", "\n", "val_truncated = val_mean[3:]\n", "std_mean_truncated = std_mean[3:]\n", "\n", "fitModel_temperature = NewFitModel(expansion)\n", "fitAnalyser_temperature = FitAnalyser(fitModel_temperature, fitDim=1)\n", "\n", "params = fitAnalyser_temperature.fitModel.make_params()\n", "params.add(name=\"A\", value= 1e6, max = np.inf, min = 1, vary = True)\n", "params.add(name=\"B\", value= 1000, max = np.inf, min = 0, vary = True)\n", "\n", "fitResult_temperature = fitAnalyser_temperature.fit(val_truncated, params, x='TOF_free', dask=\"parallelized\")\n", "\n", "val = fitAnalyser_temperature.get_fit_value(fitResult_temperature)\n", "std = fitAnalyser_temperature.get_fit_std(fitResult_temperature)\n", "\n", "fit_vals = tuple([val['A'].item(), val['B'].item()])\n", "fit_vals_std = tuple([std['A'].item(), std['B'].item()])\n", "\n", "tof = (np.arange(2,16,0.1)*1e-3)\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "val_mean.plot.errorbar(ax=ax, yerr=std_mean, fmt='or')\n", "plt.plot(tof, expansion(tof, *fit_vals), 'b--',\n", " label='fit: A=%.3f, B=%.3f' % tuple(fit_vals))\n", "plt.xlabel('TOF (s)')\n", "# plt.ylabel('Cloud Width - Vertical (pixels)')\n", "plt.ylabel('Cloud Width - Horizontal (pixels)')\n", "plt.tight_layout()\n", "plt.grid(visible=1)\n", "plt.legend()\n", "\n", "\n", "m = 164*1.673e-27\n", "kb = 1.38e-23\n", "pixel = 5.86e-6\n", "M = 2.3513\n", "\n", "T = fit_vals[0] * (m/kb) * ((pixel*pixel)/(M*M)) / (1e-6)\n", "dT = fit_vals_std[0] * (m/kb) * ((pixel*pixel)/(M*M)) / (1e-6)\n", "\n", "print('T = %.3f \\u00B1 %.3f uK'% tuple([T,dT]))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 78, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The detected scaning axes and values are: \n", "\n", "{'carrier_freq': array([8.325, 8.33 , 8.335, 8.34 , 8.345, 8.35 , 8.355, 8.36 , 8.365,\n", " 8.37 , 8.375, 8.38 , 8.385, 8.39 , 8.395, 8.4 , 8.405, 8.41 ,\n", " 8.415, 8.42 , 8.425, 8.43 , 8.435, 8.44 , 8.445])}\n" ] }, { "data": { "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n if (typeof WebSocket !== 'undefined') {\n return WebSocket;\n } else if (typeof MozWebSocket !== 'undefined') {\n return MozWebSocket;\n } else {\n alert(\n 'Your browser does not have WebSocket support. ' +\n 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n 'Firefox 4 and 5 are also supported but you ' +\n 'have to enable WebSockets in about:config.'\n );\n }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n this.id = figure_id;\n\n this.ws = websocket;\n\n this.supports_binary = this.ws.binaryType !== undefined;\n\n if (!this.supports_binary) {\n var warnings = document.getElementById('mpl-warnings');\n if (warnings) {\n warnings.style.display = 'block';\n warnings.textContent =\n 'This browser does not support binary websocket messages. ' +\n 'Performance may be slow.';\n }\n }\n\n this.imageObj = new Image();\n\n this.context = undefined;\n this.message = undefined;\n this.canvas = undefined;\n this.rubberband_canvas = undefined;\n this.rubberband_context = undefined;\n this.format_dropdown = undefined;\n\n this.image_mode = 'full';\n\n this.root = document.createElement('div');\n this.root.setAttribute('style', 'display: inline-block');\n this._root_extra_style(this.root);\n\n parent_element.appendChild(this.root);\n\n this._init_header(this);\n this._init_canvas(this);\n this._init_toolbar(this);\n\n var fig = this;\n\n this.waiting = false;\n\n this.ws.onopen = function () {\n fig.send_message('supports_binary', { value: fig.supports_binary });\n fig.send_message('send_image_mode', {});\n if (fig.ratio !== 1) {\n fig.send_message('set_device_pixel_ratio', {\n device_pixel_ratio: fig.ratio,\n });\n }\n fig.send_message('refresh', {});\n };\n\n this.imageObj.onload = function () {\n if (fig.image_mode === 'full') {\n // Full images could contain transparency (where diff images\n // almost always do), so we need to clear the canvas so that\n // there is no ghosting.\n fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n }\n fig.context.drawImage(fig.imageObj, 0, 0);\n };\n\n this.imageObj.onunload = function () {\n fig.ws.close();\n };\n\n this.ws.onmessage = this._make_on_message_function(this);\n\n this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n var titlebar = document.createElement('div');\n titlebar.classList =\n 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n var titletext = document.createElement('div');\n titletext.classList = 'ui-dialog-title';\n titletext.setAttribute(\n 'style',\n 'width: 100%; text-align: center; padding: 3px;'\n );\n titlebar.appendChild(titletext);\n this.root.appendChild(titlebar);\n this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n var fig = this;\n\n var canvas_div = (this.canvas_div = document.createElement('div'));\n canvas_div.setAttribute(\n 'style',\n 'border: 1px solid #ddd;' +\n 'box-sizing: content-box;' +\n 'clear: both;' +\n 'min-height: 1px;' +\n 'min-width: 1px;' +\n 'outline: 0;' +\n 'overflow: hidden;' +\n 'position: relative;' +\n 'resize: both;'\n );\n\n function on_keyboard_event_closure(name) {\n return function (event) {\n return fig.key "text/plain": [ "<IPython.core.display.Javascript object>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "<img 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], "text/plain": [ "<IPython.core.display.HTML object>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "%matplotlib notebook\n", "shotNum = \"0024\"\n", "filePath = folderPath + \"/\" + shotNum + \"/*.h5\"\n", "\n", "dataSetDict = {\n", " dskey[groupList[i]]: read_hdf5_file(filePath, groupList[i], excludeAxis = ['sweep_start_freq', 'sweep_stop_freq'])\n", " for i in [0]\n", "}\n", "\n", "dataSet = dataSetDict[\"camera_0\"]\n", "\n", "print_scanAxis(dataSet)\n", "\n", "scanAxis = get_scanAxis(dataSet)\n", "\n", "dataSet = auto_rechunk(dataSet)\n", "\n", "dataSet = imageAnalyser.get_absorption_images(dataSet)\n", "\n", "imageAnalyser.center = (135, 990)\n", "imageAnalyser.span = (250, 250)\n", "imageAnalyser.fraction = (0.1, 0.1)\n", "\n", "dataSet_cropOD = imageAnalyser.crop_image(dataSet.OD)\n", "dataSet_cropOD = imageAnalyser.substract_offset(dataSet_cropOD).load()\n", "\n", "Ncount = imageAnalyser.get_Ncount(dataSet_cropOD)\n", "Ncount_mean = calculate_mean(Ncount)\n", "Ncount_std = calculate_std(Ncount)\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "Ncount_mean.plot.errorbar(ax=ax, yerr = Ncount_std, fmt='ob')\n", "\n", "plt.ylabel('NCount')\n", "plt.tight_layout()\n", "#plt.ylim([0, 3500])\n", "plt.grid(visible=1)\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 81, "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[0.002, 0.003, 0.004, 0.005, 0.006, 0.007, 0.008, 0.009, 0.01, 0.011, 0.012, 0.013, 0.014, 0.015]\n", "14\n" ] }, { "data": { "text/plain": [ "0.008499999999999999" ] }, "execution_count": 81, "metadata": {}, "output_type": "execute_result" } ], "source": [ "l = list(np.arange(2e-3, 16e-3, 1e-3))\n", "# l = np.logspace(np.log10(250e-6), np.log10(500e-3), num=15)\n", "\n", "l = [round(item, 7) for item in l]\n", "#random.shuffle(l)\n", "\n", "print(l)\n", "print(len(l))\n", "np.mean(l)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "10.6 / 1e3" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "pixel = 5.86e-6\n", "M = 0.6827\n", "F = (1/(0.3725*8.4743e-14)) * (pixel / M)**2\n", "NCount = 85000\n", "AtomNumber = NCount * F / 1e8\n", "print(AtomNumber)\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "muB = 9.274e-24\n", "hbar = 6.626e-34 / (2 * np.pi)\n", "gJ = 1.24\n", "Delta = 2 * np.pi * 100 * 1e3\n", "\n", "Bz = (Delta*hbar) / (muB*gJ)\n", "print(Bz * 1e4)" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## ODT 1 Calibration" ] }, { "cell_type": "code", "execution_count": 165, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "14.912\n", "1.171\n", "299.302\n" ] } ], "source": [ "v_high = 2.7\n", "\"\"\"High Power\"\"\"\n", "P_arm1_high = 5.776 * v_high - 0.683\n", "\n", "v_mid = 0.2076\n", "\"\"\"Intermediate Power\"\"\"\n", "P_arm1_mid = 5.815 * v_mid - 0.03651\n", "\n", "v_low = 0.062\n", "\"\"\"Low Power\"\"\"\n", "P_arm1_low = 5271 * v_low - 27.5\n", "\n", "print(round(P_arm1_high, 3))\n", "print(round(P_arm1_mid, 3))\n", "print(round(P_arm1_low, 3))" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## ODT 2 Power Calibration" ] }, { "cell_type": "code", "execution_count": 166, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1.874\n" ] } ], "source": [ "v = 0.842\n", "P_arm2 = 2.302 * v - 0.06452\n", "print(round(P_arm2, 3))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.12" }, "vscode": { "interpreter": { "hash": "c05913ad4f24fdc6b2418069394dc5835b1981849b107c9ba6df693aafd66650" } } }, "nbformat": 4, "nbformat_minor": 2}
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