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analyseScript/backupScript/3DMOT optimize.ipynb

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{
"cells": [
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"# Import supporting package"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import xarray as xr\n",
"import numpy as np\n",
"\n",
"from uncertainties import ufloat\n",
"from uncertainties import unumpy as unp\n",
"from uncertainties import umath\n",
"\n",
"import matplotlib.pyplot as plt\n",
"\n",
"from DataContainer.ReadData import read_hdf5_file\n",
"from Analyser.ImagingAnalyser import ImageAnalyser\n",
"from Analyser.FitAnalyser import FitAnalyser\n",
"from Analyser.FitAnalyser import ThomasFermi2dModel, DensityProfileBEC2dModel, Polylog22dModel\n",
"from Analyser.FitAnalyser import NewFitModel\n",
"from ToolFunction.ToolFunction import *\n",
"\n",
"from ToolFunction.HomeMadeXarrayFunction import errorbar, dataarray_plot_errorbar\n",
"xr.plot.dataarray_plot.errorbar = errorbar\n",
"xr.plot.accessor.DataArrayPlotAccessor.errorbar = dataarray_plot_errorbar\n",
"\n",
"imageAnalyser = ImageAnalyser()"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"\n",
"from matplotlib.colors import ListedColormap, LinearSegmentedColormap\n",
"\n",
"import matplotlib.pyplot as plt\n",
"plt.rcParams[\"font.family\"] = \"arial\""
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"def Ncount_to_atoms():\n",
" return 1 / 8.4743e-14 / 0.3725 * 5.86e-6**2 / 0.6606**2"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"import csv\n",
"\n",
"colormap = np.zeros((1024, 3))\n",
"\n",
"with open('smooth-cool-warm-table-float-1024.csv', newline='') as csvfile:\n",
" spamreader = csv.reader(csvfile, delimiter=' ', quotechar='|')\n",
" i = 0\n",
" for row in spamreader:\n",
" try:\n",
" a = row[0].split(',')\n",
" colormap[i, 0] = float(a[1])\n",
" colormap[i, 1] = float(a[2])\n",
" colormap[i, 2] = float(a[3])\n",
" i = i + 1\n",
" except:\n",
" pass\n",
"\n",
"colormap = ListedColormap(colormap)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"data_colors = colormap(np.linspace(0, 1, 7))\n",
"plot_blue = data_colors[-3]\n",
"plot_red = data_colors[-1]\n",
"plot_red_alpha = 1"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## Start a client for parallel computing"
]
},
{
"cell_type": "code",
"execution_count": 6,
"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-65877ea1-1120-11ee-bd28-9c7bef43b4fb</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",
" <button style=\"margin-bottom: 12px;\" data-commandlinker-command=\"dask:populate-and-launch-layout\" data-commandlinker-args='{\"url\": \"http://127.0.0.1:8787/status\" }'>\n",
" Launch dashboard in JupyterLab\n",
" </button>\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;\">ee7c3b53</p>\n",
" <table style=\"width: 100%; text-align: left;\">\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Dashboard:</strong> <a href=\"http://127.0.0.1:8787/status\" target=\"_blank\">http://127.0.0.1:8787/status</a>\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Workers:</strong> 6\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total threads:</strong> 60\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total memory:</strong> 55.88 GiB\n",
" </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <td style=\"text-align: left;\"><strong>Status:</strong> running</td>\n",
" <td style=\"text-align: left;\"><strong>Using processes:</strong> True</td>\n",
"</tr>\n",
"\n",
" \n",
" </table>\n",
"\n",
" <details>\n",
" <summary style=\"margin-bottom: 20px;\">\n",
" <h3 style=\"display: inline;\">Scheduler Info</h3>\n",
" </summary>\n",
"\n",
" <div style=\"\">\n",
" <div>\n",
" <div style=\"width: 24px; height: 24px; background-color: #FFF7E5; border: 3px solid #FF6132; border-radius: 5px; position: absolute;\"> </div>\n",
" <div style=\"margin-left: 48px;\">\n",
" <h3 style=\"margin-bottom: 0px;\">Scheduler</h3>\n",
" <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Scheduler-f17926fd-5020-4803-9692-4e5947c8d4dd</p>\n",
" <table style=\"width: 100%; text-align: left;\">\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Comm:</strong> tcp://127.0.0.1:63894\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Workers:</strong> 6\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Dashboard:</strong> <a href=\"http://127.0.0.1:8787/status\" target=\"_blank\">http://127.0.0.1:8787/status</a>\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total threads:</strong> 60\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Started:</strong> Just now\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total memory:</strong> 55.88 GiB\n",
" </td>\n",
" </tr>\n",
" </table>\n",
" </div>\n",
" </div>\n",
"\n",
" <details style=\"margin-left: 48px;\">\n",
" <summary style=\"margin-bottom: 20px;\">\n",
" <h3 style=\"display: inline;\">Workers</h3>\n",
" </summary>\n",
"\n",
" \n",
" <div style=\"margin-bottom: 20px;\">\n",
" <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
" <div style=\"margin-left: 48px;\">\n",
" <details>\n",
" <summary>\n",
" <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 0</h4>\n",
" </summary>\n",
" <table style=\"width: 100%; text-align: left;\">\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Comm: </strong> tcp://127.0.0.1:63924\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total threads: </strong> 10\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:63932/status\" target=\"_blank\">http://127.0.0.1:63932/status</a>\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Memory: </strong> 9.31 GiB\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Nanny: </strong> tcp://127.0.0.1:63897\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\\JIANSH~1\\AppData\\Local\\Temp\\dask-worker-space\\worker-oaisnlk0\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://127.0.0.1:63928\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total threads: </strong> 10\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:63941/status\" target=\"_blank\">http://127.0.0.1:63941/status</a>\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Memory: </strong> 9.31 GiB\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Nanny: </strong> tcp://127.0.0.1:63898\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\\JIANSH~1\\AppData\\Local\\Temp\\dask-worker-space\\worker-lgn_00uq\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://127.0.0.1:63921\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total threads: </strong> 10\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:63930/status\" target=\"_blank\">http://127.0.0.1:63930/status</a>\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Memory: </strong> 9.31 GiB\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Nanny: </strong> tcp://127.0.0.1:63899\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\\JIANSH~1\\AppData\\Local\\Temp\\dask-worker-space\\worker-1ozf7xf0\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://127.0.0.1:63926\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total threads: </strong> 10\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:63937/status\" target=\"_blank\">http://127.0.0.1:63937/status</a>\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Memory: </strong> 9.31 GiB\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Nanny: </strong> tcp://127.0.0.1:63900\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\\JIANSH~1\\AppData\\Local\\Temp\\dask-worker-space\\worker-53pv7g96\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://127.0.0.1:63927\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total threads: </strong> 10\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:63938/status\" target=\"_blank\">http://127.0.0.1:63938/status</a>\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Memory: </strong> 9.31 GiB\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Nanny: </strong> tcp://127.0.0.1:63901\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\\JIANSH~1\\AppData\\Local\\Temp\\dask-worker-space\\worker-tr6dxqb7\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://127.0.0.1:63925\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total threads: </strong> 10\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:63934/status\" target=\"_blank\">http://127.0.0.1:63934/status</a>\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Memory: </strong> 9.31 GiB\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Nanny: </strong> tcp://127.0.0.1:63902\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\\JIANSH~1\\AppData\\Local\\Temp\\dask-worker-space\\worker-7qa0mcnj\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://127.0.0.1:63894' processes=6 threads=60, memory=55.88 GiB>"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from dask.distributed import Client\n",
"client = Client(n_workers=6, threads_per_worker=10, processes=True, memory_limit='10GB')\n",
"client"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## Set global path for experiment"
]
},
{
"cell_type": "code",
"execution_count": 7,
"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": 8,
"metadata": {},
"outputs": [],
"source": [
"img_dir = '//DyLabNAS/Data/'\n",
"SequenceName = \"Repetition_scan\" + \"/\""
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"# MOT optimize"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## 09.06.2023"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The detected scaning axes and values are: \n",
"\n",
"{'cmot_initial_current': array([0.1 , 0.12, 0.14, 0.16, 0.18, 0.2 , 0.22, 0.24, 0.26, 0.28]), 'initial_freq': array([100.5, 100.9, 101.3, 101.7, 102.1, 102.5, 102.9, 103.3, 103.7,\n",
" 104.1]), 'runs': array([0., 1., 2.])}\n"
]
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"folderPath = img_dir + SequenceName + '2023/06/09'# get_date()\n",
"\n",
"shotNum = \"0010\"\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_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 = (690, 1435)\n",
"imageAnalyser.span = (1000, 700)\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.pcolormesh()\n",
"plt.xlabel('MOT AOM Frequency (MHz)')\n",
"plt.ylabel('MOT Gradient Coil Current (A)')\n",
"plt.tight_layout()\n",
"# plt.grid(visible=1)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [],
"source": [
"freq = -(Ncount_mean.initial_freq.to_numpy() - 99.969) *2 / 0.136\n",
"current = Ncount_mean.cmot_initial_current.to_numpy() * 5.17\n",
"data = Ncount_mean.to_numpy() * Ncount_to_atoms()\n",
"\n",
"X, Y = np.meshgrid(freq, current)"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 816x1615.68 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"from mpl_toolkits.axes_grid1 import make_axes_locatable\n",
"\n",
"fig = plt.figure(figsize=(6.8, 6.8/4*3*2*(1 + 16/50)), dpi=120)\n",
"grid = fig.add_gridspec(4, 1, height_ratios=[2, 50, 10, 50], wspace=0.4, hspace=0.1)\n",
"\n",
"filter = ''\n",
"edgecolor = None\n",
"\n",
"colorbar_ticks = np.linspace(0, 2.5e8, 6)\n",
"\n",
"plot_axes = plt.subplot(grid[1, 0])\n",
"\n",
"im = plot_axes.pcolormesh(X, Y, data, cmap=colormap, edgecolor=edgecolor, vmin=0)\n",
"\n",
"colorbar = fig.colorbar(im, ax=plot_axes, ticks=np.array([0, 0.5, 1, 1.5, 2])*1e8)\n",
"colorbar.formatter.set_powerlimits((0, 0))\n",
"colorbar.formatter.set_useMathText(True)\n",
"colorbar.ax.yaxis.set_offset_position('left')\n",
"colorbar.ax.tick_params(axis='both', labelsize=20)\n",
"colorbar.ax.yaxis.offsetText.set_fontsize(20)\n",
"\n",
"plot_axes.set_xlabel(\"3D-MOT detuning $\\delta_\\mathrm{3D}$ $(\\Gamma_\\mathrm{626})$\", fontsize=20)\n",
"plot_axes.set_ylabel(\"3D-MOT gradient $b'_\\mathrm{3D}$ (G/cm)\", fontsize=20)\n",
"colorbar.set_label(\"Loaded atom number $N_\\mathrm{4s}$\", fontsize=20)\n",
"\n",
"plot_axes.tick_params(axis='both', which='major', labelsize=20)\n",
"plot_axes.tick_params(axis='both', which='minor', labelsize=16)\n",
"plot_axes.xaxis.offsetText.set_fontsize(20)\n",
"plot_axes.yaxis.offsetText.set_fontsize(20)\n",
"\n",
"plt.setp(plot_axes.spines.values(), linewidth=3)\n",
"plot_axes.xaxis.set_tick_params(width=3)\n",
"plot_axes.yaxis.set_tick_params(width=3)\n",
"plot_axes.tick_params(direction='in', length=10)\n",
"\n",
"# # plotting.figure[dataExtractor_key].colorbar_min = 0\n",
"# # plotting.figure[dataExtractor_key].colorbar_max = 2.5e8\n",
"\n",
"# plotting.figure[dataExtractor_key].add_pcolormesh_plot(cmap=colormap, edgecolor=edgecolor, grid=plot_axes)\n",
"# plotting.figure[dataExtractor_key].add_axes_label()\n",
"# # plotting.figure[dataExtractor_key].add_color_bar(ticks=colorbar_ticks)\n",
"# plotting.figure[dataExtractor_key].add_color_bar(ticks=np.linspace(0, 8, 5))\n",
"# plotting.figure[dataExtractor_key].colorbar.ax.set_yticklabels(['{:.1f}'.format(x) for x in np.linspace(0, 8, 5)])\n",
"\n",
"# plotting.figure[dataExtractor_key].colorbar.ax.text(3.3, 7.69, '$\\\\times 10^{7}$', va='bottom', weight='bold', fontsize=20)\n",
"\n",
"# # plotting.figure[dataExtractor_key].set_color_bar_offset_position(0, 1.07)\n",
"\n",
"# # plotting.figure[dataExtractor_key].plot_axes.set_xlim([-30, -55])\n",
"# # plotting.figure[dataExtractor_key].plot_axes.set_ylim([0.15, 0.65])\n",
"\n",
"# # plt.xticks([-40])\n",
"\n",
"# plotting.figure[dataExtractor_key].plot_axes.set_xlabel(\"3D-MOT detuning $\\delta_\\mathrm{3D} / \\Gamma_{626}$\", fontsize=20)\n",
"# plotting.figure[dataExtractor_key].plot_axes.set_ylabel(\"3D-MOT gradient $b'_\\mathrm{3D}$ (G/cm)\", fontsize=20)\n",
"# plotting.figure[dataExtractor_key].colorbar.set_label(\"Loaded atom number $N_\\mathrm{4s}$\", fontsize=20)\n",
"\n",
"# plot_axes = plt.subplot(grid[0, 0])\n",
"# plot_axes.text(-0.17, 1.0, '(a)', va='bottom', weight='bold', fontsize=20)\n",
"# plot_axes.set_axis_off()\n",
"\n",
"fig.savefig('figS3_v1.pdf', bbox_inches = \"tight\")\n",
"\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.10"
},
"orig_nbformat": 4
},
"nbformat": 4,
"nbformat_minor": 2
}