{ "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": [ "
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Client

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Client-6b96bd98-14cc-11ee-84cc-80e82ce2fa8e

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Connection method: Cluster objectCluster type: distributed.LocalCluster
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Cluster Info

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LocalCluster

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4e95eff3

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Status: runningUsing processes: True
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Scheduler Info

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Scheduler

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Scheduler-06ee832c-dd0b-4c48-a7b6-ae1064b4a1bf

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\n", " Comm: tcp://127.0.0.1:62877\n", " \n", " Workers: 8\n", "
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Workers

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Worker: 0

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\n", " Comm: tcp://127.0.0.1:62921\n", " \n", " Total threads: 16\n", "
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\n", " Nanny: tcp://127.0.0.1:62880\n", "
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Worker: 1

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Worker: 2

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\n", " Nanny: tcp://127.0.0.1:62882\n", "
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Worker: 3

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Worker: 4

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Worker: 5

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Worker: 6

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Worker: 7

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" ], "text/plain": [ "" ] }, "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())" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fx = [751.71168, 736.56597, 885.97705, 1118.95297, 1538.68901, 3085.17389, 4700.81524, 6434.98779, 8223.48942]\n", "dfx = [1.32859, 1.28606, 0.99619, 0.99134, 1.03403, 0.35958, 0.33758, 0.38790, 0.31241]\n", "x_offset_current = [0, 0.03, 0.05, 0.07, 0.1, 0.2, 0.3, 0.4, 0.515]\n", "\n", "fy = [751.71168, 918.67701, 1129.74687, 1429.82911, 1749.75310, 3089.87897, 4314.90128, 5387.64638, 6666.03670]\n", "dfy = [1.32859, 0.90271, 1.33691, 1.77735, 1.42421, 1.58909, 1.73638, 1.40175, 1.00526]\n", "y_offset_current = [0.0, 0.015, 0.03, 0.05, 0.07, 0.15, 0.22, 0.28, 0.35]\n", "\n", "fz = [751.71168, 1223.54627, 1739.13344, 2364.93284, 2798.24971, 3178.49790, 4275.39905, 5352.17283, 6637.80418, 8288.35264, 9573.59333]\n", "dfz = [1.32859, 0.35554, 0.48471, 0.69762, 0.36873, 0.29413, 0.20667, 0.20818, 0.21978, 0.20285, 0.18495]\n", "z_offset_current = [0.0, 0.03, 0.06, 0.095, 0.119, 0.140, 0.2, 0.259, 0.329, 0.419, 0.489]\n", "\n", "f = fy\n", "df = dfy\n", "offset_current = y_offset_current\n", "\n", "f_fit = fy[4:]\n", "df_fit = dfy[4:]\n", "offset_current_fit = y_offset_current[4:]\n", "\n", "x = np.array(offset_current_fit)\n", "y = np.array(f_fit)\n", "\n", "# Degree of the fitting polynomial\n", "deg = 1\n", "# Parameters from the fit of the polynomial\n", "p = np.polyfit(x, y, deg)\n", "m = p[0] # Gradient\n", "c = p[1] # y-intercept\n", "\n", "#print(f'The fitted straight line has equation y = {m:.1f}x {c:=+6.1f}')\n", "\n", "# Model the data using the parameters of the fitted straight line\n", "y_model = np.polyval(p, x)\n", "\n", "# Create the linear (1 degree polynomial) model\n", "model = np.poly1d(p)\n", "# Fit the model\n", "y_model = model(x)\n", "\n", "# Mean\n", "y_bar = np.mean(y)\n", "# Coefficient of determination, R²\n", "R2 = np.sum((y_model - y_bar)**2) / np.sum((y - y_bar)**2)\n", "\n", "#print(f'R² = {R2:.2f}')\n", "\n", "fitted_SlopeInkHz = m\n", "fitted_offsetInkHz = c\n", "muB = 9.274e-24\n", "hbar = 6.626e-34 / (2 * np.pi)\n", "gJ = 1.24\n", "Slope = (((2 * np.pi * fitted_SlopeInkHz * 1e3)*hbar) / (muB*gJ)) * 1e4\n", "Offset = (((2 * np.pi * fitted_offsetInkHz * 1e3)*hbar) / (muB*gJ)) * 1e4\n", "\n", "def calib_fit(x, B):\n", " alpha = ((2 * np.pi * fitted_SlopeInkHz * 1e3)*hbar) / (muB*gJ)\n", " beta = ((2 * np.pi * fitted_offsetInkHz * 1e3)*hbar) / (muB*gJ)\n", " delta_nu = ((muB * gJ) / hbar) * np.sqrt((B**2-beta**2) + ((alpha * x) + beta)**2)\n", " return delta_nu / (2 * np.pi * 1e3)\n", "\n", "\n", "popt, pcov = curve_fit(calib_fit, offset_current, f, np.array([0.1*1e-4]))\n", "Boffset = popt[0] * 1e4\n", "dBoffset = pcov[0][0]**0.5 * 1e4\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "plt.clf\n", "plt.errorbar(offset_current, f, yerr=df, fmt='o')\n", "xvals = np.linspace(0, 0.55, 500)\n", "plt.plot(np.array(xvals), p[1] + p[0] * np.array(xvals), label=f'Line Fit')\n", "plt.plot(xvals, calib_fit(xvals, *popt), label=f'Curve Fit')\n", "plt.text(0.25, 2200, f'Line Slope = {Slope:.3f} G/A', fontsize=12)\n", "plt.text(0.25, 1500, f'Line Offset = {Offset:=.3f} G', fontsize=12)\n", "plt.text(0.25, 800, f'Bo= {Boffset:=.3f} +/- {dBoffset:=.3f} G', fontsize=12)\n", "plt.xlabel('Y Offset Coil Current (A)', fontsize=12)\n", "plt.ylabel('Resonance Frequency (kHz)', fontsize=12)\n", "plt.xticks(fontsize=12)\n", "plt.yticks(fontsize=12)\n", "plt.legend(fontsize=12)\n", "#plt.xlim(-0.01, 0.04)\n", "plt.ylim(0, 10000)\n", "plt.grid(visible=1)\n", "plt.tight_layout()\n", "plt.show()" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "# X-comp coil" ] }, { "cell_type": "code", "execution_count": 126, "metadata": {}, "outputs": [ { "data": { "image/png": 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+n44fP97seOvXr9fIkSPlcrk0dOhQZWZmqq6urknfmTNnNGfOHHm9XoWFhSk5OVmFhYVtOQUAAGBjQQec5557ThMnTlRkZKR+8YtfaPv27XrkkUdkjLF6SktLlZqaqsuXL2vTpk3auHGj3nrrLaWkpOjs2bMB42VlZWnRokXy+XzauXOnFixYoDVr1mjhwoUBfbW1tUpLS1NhYaGys7O1detWDRw4UOnp6dq7d28bTx8AANiSCcI777xj+vXrZ77+9a9/bN/MmTON1+s1VVVVVu3EiRMmNDTULFmyxKpVVFQYt9tt5s+fH/D8rKws43A4TElJiVXLyckxksz+/futWl1dnUlISDDjxo0L5jRMVVWVkRQwPwAA0L0F8/od1BWcp59+Wh988IEeeeSRFnvq6+u1bds2zZgxQxEREVZ9yJAhmjRpkgoKCqzajh075Pf7lZGRETBGRkaGjDHasmWLVSsoKNCIESOUnJxs1ZxOp2bNmqWDBw+qrKwsmFMBAAA2FlTA+f3vfy+Px6PS0lKNGTNGTqdTAwYM0Ne+9jVVV1dLko4dO6ZLly4pKSmpyfOTkpJ09OhR+f1+SdKRI0ckSYmJiQF9MTEx8nq91vHG3pbGlKSSkpIW511bW6vq6uqABwAAsK+gAk5ZWZkuXryomTNn6r777tPu3bv1H//xH/rFL36hu+66S8YYVVZWSpI8Hk+T53s8HhljdP78eUlSZWWlXC6X+vXr12xv41iNvS2N2Xi8JWvXrlVkZKT1iI+PD+a0AQBAD+MMpvnq1avy+/1atWqVli5dKklKTU1Vnz59tHjxYhUWFiosLEyS5HA4Whzn2mOt7Qu291rLli3Tt7/9bevn6upqQg4AADYW1BWc6OhoSdKdd94ZUP/CF74gqeHW8Mae5q6onDt3Tg6HQ1FRUdZ4fr9fFy9ebLb32is20dHRLY4pNX/FqJHL5VJERETAAwAA2FdQAae5z8BIsm4Rv+GGGzRs2DD17dtXxcXFTfqKi4s1fPhwud1uSR9+9uajveXl5aqoqNDo0aOtWmJiYotjSgroBQAAvVtQAWfGjBmSpN/97ncB9e3bt0uSJkyYIKfTqalTpyo/P181NTVWz8mTJ1VUVCSfz2fV0tPT5Xa7lZubGzBebm6uHA6Hpk2bZtWmT5+u0tJSHThwwKrV19crLy9P48ePV2xsbDCnAgAA7CzYe9CnTp1qXC6Xefzxx82uXbvM2rVrjdvtNnfffbfV88Ybb5jw8HDzuc99zmzfvt3k5+eb0aNHm9jYWHPmzJmA8Z544gnjcDjMo48+avbs2WO+//3vG5fLZb761a8G9Pn9fjNq1CgTHx9vnn32WbNr1y4zffp043Q6zZ49e4I6B/bBAQCg5wnm9TvogHPx4kXzyCOPmPj4eON0Os3gwYPNsmXLjN/vD+h77bXXTFpamgkLCzMRERFm2rRp5ujRo82OmZ2dbW677TbTp08fM3jwYLNq1Spz+fLlJn3l5eVm9uzZxuPxGLfbbSZMmGB27doV7CkQcAAA6IGCef12GHPNdyz0EtXV1YqMjFRVVRUfOAYAoIcI5vWbbxMHAAC2Q8ABAAC2Q8ABAAC2Q8ABAAC2Q8ABAAC2Q8ABAAC2Q8ABAAC2Q8ABAAC2Q8ABAAC2Q8ABAAC2Q8ABAAC2Q8ABAAC2Q8ABAAC2Q8ABAAC2Q8ABAAC2Q8ABAAC2Q8ABAAC2Q8ABAAC2Q8ABAAC2Q8ABAAC2Q8ABAAC2Q8ABAAC2Q8ABAAC2Q8ABAAC2Q8ABAAC2Q8ABAAC2Q8ABAAC2Q8ABAAC2Q8ABAAC2Q8ABAAC2Q8ABAAC2E1TA2bNnjxwOR7OPV199NaD38OHDmjx5ssLDwxUVFSWfz6fjx483O+769es1cuRIuVwuDR06VJmZmaqrq2vSd+bMGc2ZM0der1dhYWFKTk5WYWFhMKcAAAB6AWdbnrRmzRpNmjQpoDZ69Gjrv0tLS5WamqoxY8Zo06ZN8vv9WrlypVJSUvT666+rf//+Vm9WVpZWrFihpUuXasqUKTp06JCWL1+usrIyPfXUU1ZfbW2t0tLSdOHCBWVnZ2vAgAHKyclRenq6du/erYkTJ7blVAAAgB2ZIBQVFRlJ5sUXX/zYvpkzZxqv12uqqqqs2okTJ0xoaKhZsmSJVauoqDBut9vMnz8/4PlZWVnG4XCYkpISq5aTk2Mkmf3791u1uro6k5CQYMaNGxfMaZiqqiojKWB+AACgewvm9bvDP4NTX1+vbdu2acaMGYqIiLDqQ4YM0aRJk1RQUGDVduzYIb/fr4yMjIAxMjIyZIzRli1brFpBQYFGjBih5ORkq+Z0OjVr1iwdPHhQZWVlHX0qAACgh2pTwFm4cKGcTqciIiJ055136g9/+IN17NixY7p06ZKSkpKaPC8pKUlHjx6V3++XJB05ckSSlJiYGNAXExMjr9drHW/sbWlMSSopKWnLqQAAABsK6jM4kZGRWrRokVJTUxUdHa2jR4/q+9//vlJTU/Xb3/5Wd955pyorKyVJHo+nyfM9Ho+MMTp//rxiYmJUWVkpl8ulfv36NdvbOJYkVVZWtjhm4/GW1NbWqra21vq5urq69ScNAAB6nKACzqc//Wl9+tOftn5OSUnR9OnTlZiYqCVLlujOO++0jjkcjhbHufZYa/uC7b3W2rVrlZmZ2eJxAABgL+3+DE5UVJTuvvtu/eUvf9GlS5cUHR0tqfkrKufOnZPD4VBUVJQkKTo6Wn6/XxcvXmy299orNtHR0S2OKTV/xajRsmXLVFVVZT1OnToV1DkCAICepUM+ZGyMkdRwFWXYsGHq27eviouLm/QVFxdr+PDhcrvdkj787M1He8vLy1VRURFw63liYmKLY0qBt6l/lMvlUkRERMADAADYV7sDzvnz57Vt2zaNGTNGbrdbTqdTU6dOVX5+vmpqaqy+kydPqqioSD6fz6qlp6fL7XYrNzc3YMzc3Fw5HA5NmzbNqk2fPl2lpaU6cOCAVauvr1deXp7Gjx+v2NjY9p4KAACwiaA+g/Ov//qvGjx4sD772c/K6/Xq7bff1g9/+EO99957ASElMzNTY8eO1d13362lS5daG/15vV49/PDDVp/H49Hy5cu1YsUKeTwea6O/1atXa968eUpISLB6586dq5ycHM2cOVPr1q3TgAEDtGHDBr355pvavXt3+1cCAADYRzAb7Kxdu9aMGTPGREZGmpCQENO/f38zffp0c/DgwSa9r732mklLSzNhYWEmIiLCTJs2zRw9erTZcbOzs81tt91m+vTpYwYPHmxWrVplLl++3KSvvLzczJ4923g8HuN2u82ECRPMrl27gjkFYwwb/QEA0BMF8/rtMOb/PkDTi1RXVysyMlJVVVV8HgcAgB4imNdvvk0cAADYTpu+bBMA0DpXrkj79kmnT0sxMVJKihQS0tWzAuyPgAMAnSQ/X1q0SHrnnQ9rcXFSdrZ0zQ2lADoBb1EBQCfIz5fuvTcw3EhSWVlDPT+/a+YF9BYEHADoYFeuNFy5ae4Wjsba4sUNfQA6BwEHADrYvn1Nr9xcyxjp1KmGPgCdg4ADAB3s9OmO7QMQPAIOAHSwmJiO7QMQPAIOAHSwlJSGu6UcjuaPOxxSfHxDH4DOQcABgA4WEtJwK7jUNOQ0/vzkk+yHA3QmAg4AdAKfT9q8Wbr55sB6XFxDnX1wgM7FRn8A0El8Pumee9jJGOgKBBwA6EQhIVJqalfPAuh9eIsKAADYDgEHAADYDgEHAADYDgEHAADYDgEHAADYDgEHAADYDgEHAADYDgEHAADYDgEHAADYDgEHAADYDgEHAADYDgEHAADYDgEHAADYDgEHAADYDgEHAADYDgEHAADYDgEHAADYDgEHAADYDgEHAADYTrsDztNPPy2Hw6Hw8PAmxw4fPqzJkycrPDxcUVFR8vl8On78eLPjrF+/XiNHjpTL5dLQoUOVmZmpurq6Jn1nzpzRnDlz5PV6FRYWpuTkZBUWFrb3NAAAgI20K+CUlZXpO9/5jmJjY5scKy0tVWpqqi5fvqxNmzZp48aNeuutt5SSkqKzZ88G9GZlZWnRokXy+XzauXOnFixYoDVr1mjhwoUBfbW1tUpLS1NhYaGys7O1detWDRw4UOnp6dq7d297TgUAANiIwxhj2vrkqVOnyuFwyOPxaPPmzXr//fetY1/+8pdVVFSkY8eOKSIiQpL097//Xbfeequ+9a1v6Xvf+54kqbKyUnFxcZo9e7Z++tOfWs9fs2aNli9friNHjighIUGStGHDBi1cuFD79+9XcnKyJKm+vl6f+tSnFB4ergMHDrRq3tXV1YqMjFRVVZU1NwAA0L0F8/rd5is4eXl52rt3rzZs2NDkWH19vbZt26YZM2YETGDIkCGaNGmSCgoKrNqOHTvk9/uVkZERMEZGRoaMMdqyZYtVKygo0IgRI6xwI0lOp1OzZs3SwYMHVVZW1tbTAQAANtKmgHPmzBktXrxY69atU1xcXJPjx44d06VLl5SUlNTkWFJSko4ePSq/3y9JOnLkiCQpMTExoC8mJkZer9c63tjb0piSVFJS0ux8a2trVV1dHfAAAAD21aaAs2DBAo0YMUJf//rXmz1eWVkpSfJ4PE2OeTweGWN0/vx5q9flcqlfv37N9jaO1djb0pjX/t6PWrt2rSIjI61HfHz8PzhDAADQkwUdcH7961/rpZde0v/8z//I4XB8bO/HHb/2WGv7gu1ttGzZMlVVVVmPU6dOtTgGAADo+ZzBNL///vtauHChvvGNbyg2NlYXLlyQJF2+fFmSdOHCBYWGhio6OlpS81dUzp07J4fDoaioKElSdHS0/H6/Ll68qLCwsCa9t99+u/VzdHR0i2NKzV8xkiSXyyWXyxXMqQIAgB4sqCs4FRUVeu+99/TDH/5QN910k/V4/vnn9cEHH+imm27SV77yFQ0bNkx9+/ZVcXFxkzGKi4s1fPhwud1uSR9+9uajveXl5aqoqNDo0aOtWmJiYotjSgroBQAAvVdQAWfQoEEqKipq8rjzzjvldrtVVFSkJ554Qk6nU1OnTlV+fr5qamqs5588eVJFRUXy+XxWLT09XW63W7m5uQG/Kzc3Vw6HQ9OmTbNq06dPV2lpacDt4PX19crLy9P48eOb3Y8HAAD0Pu3aB6fRnDlzmuyDU1paqrFjx+ozn/mMli5dKr/fr5UrV+rcuXN6/fXX1b9/f6s3KytLK1as0LJlyzRlyhQdOnRIy5cv1+zZs/XUU09ZfbW1tbr99ttVXV2tdevWacCAAdqwYYNeeukl7d69WxMnTmzVfNkHBwCAnue67IPzj4wcOVJ79uxRaGio7r33Xs2ZM0fDhw/X73//+4BwI0mPPfaYnnzySW3evFlTpkzR+vXrtXTpUuXk5AT0uVwuFRYWatKkSfrGN76hqVOn6vTp0/rd737X6nADAADsr0Ou4PQ0XMEBAKDn6RZXcAAAALoKAQcAANgOAQcAANgOAQcAANgOAQcAANgOAQcAANgOAQcAANgOAQcAANgOAQcAANgOAQcAANgOAQcAANgOAQcAANgOAQcAANgOAQcAANgOAQcAANgOAQcAANgOAQcAANgOAQcAANgOAQcAANgOAQcAANgOAQcAANgOAQcAANgOAQcAANgOAQcAANgOAQcAANgOAQcAANgOAQcAANgOAQcAANiOs6snAKDrXbki7dsnnT4txcRIKSlSSEhXzwoA2o6AA/Ry+fnSokXSO+98WIuLk7KzJZ+v6+YFAO3BW1RAL5afL917b2C4kaSysoZ6fn7XzAsA2ouAA/RSV640XLkxpumxxtrixQ19ANDTBBVwXn/9dX3xi1/U4MGD1bdvX3k8HiUnJysvL69J7+HDhzV58mSFh4crKipKPp9Px48fb3bc9evXa+TIkXK5XBo6dKgyMzNVV1fXpO/MmTOaM2eOvF6vwsLClJycrMLCwmBOAcD/2bev6ZWbaxkjnTrV0AcAPU1QAefChQuKj4/XmjVrtH37dv3iF7/QLbfcon/7t3/TE088YfWVlpYqNTVVly9f1qZNm7Rx40a99dZbSklJ0dmzZwPGzMrK0qJFi+Tz+bRz504tWLBAa9as0cKFCwP6amtrlZaWpsLCQmVnZ2vr1q0aOHCg0tPTtXfv3nYsAdA7nT7dsX0A0K2YDjB+/HgTHx9v/Txz5kzj9XpNVVWVVTtx4oQJDQ01S5YssWoVFRXG7Xab+fPnB4yXlZVlHA6HKSkpsWo5OTlGktm/f79Vq6urMwkJCWbcuHFBzbeqqspICpgf0NsUFRnTcJ3m4x9FRV09UwBoEMzrd4d8Bsfr9crpbLghq76+Xtu2bdOMGTMUERFh9QwZMkSTJk1SQUGBVduxY4f8fr8yMjICxsvIyJAxRlu2bLFqBQUFGjFihJKTk62a0+nUrFmzdPDgQZWVlXXEqQC9RkpKw91SDkfzxx0OKT6+oQ8Aepo2BZyrV6+qvr5eZ8+e1YYNG7Rz50498sgjkqRjx47p0qVLSkpKavK8pKQkHT16VH6/X5J05MgRSVJiYmJAX0xMjLxer3W8sbelMSWppKSkxfnW1taquro64AH0diEhDbeCS01DTuPPTz7JfjgAeqY2BZwFCxYoNDRUAwYM0Le+9S39+Mc/1r//+79LkiorKyVJHo+nyfM8Ho+MMTp//rzV63K51K9fv2Z7G8dq7G1pzGt/b3PWrl2ryMhI6xEfHx/E2QL25fNJmzdLN98cWI+La6izDw6AnqpNG/09+uijmjdvns6cOaOXXnpJDz30kD744AN95zvfsXocLV33/six1vYF23utZcuW6dvf/rb1c3V1NSEH+D8+n3TPPexkDMBe2hRwBg8erMGDB0uS7rrrLkkNIeKBBx5QdHS0pOavqJw7d04Oh0NRUVGSpOjoaPn9fl28eFFhYWFNem+//Xbr5+jo6BbHlJq/YtTI5XLJ5XIFcYZA7xISIqWmdvUsAKDjdMiHjMeNG6f6+nodP35cw4YNU9++fVVcXNykr7i4WMOHD5fb7Zb04WdvPtpbXl6uiooKjR492qolJia2OKakgF4AANC7dUjAKSoq0g033KBPfOITcjqdmjp1qvLz81VTU2P1nDx5UkVFRfJd86Z+enq63G63cnNzA8bLzc2Vw+HQtGnTrNr06dNVWlqqAwcOWLX6+nrl5eVp/Pjxio2N7YhTAQAANhDUW1Tz589XRESExo0bp4EDB6qiokIvvviifvWrX+k//uM/1L9/f0lSZmamxo4dq7vvvltLly6V3+/XypUr5fV69fDDD1vjeTweLV++XCtWrJDH49GUKVN06NAhrV69WvPmzVNCQoLVO3fuXOXk5GjmzJlat26dBgwYoA0bNujNN9/U7t27O2g5AACALQSzwc7GjRtNSkqK8Xq9xul0mqioKDNx4kTzy1/+sknva6+9ZtLS0kxYWJiJiIgw06ZNM0ePHm123OzsbHPbbbeZPn36mMGDB5tVq1aZy5cvN+krLy83s2fPNh6Px7jdbjNhwgSza9euYE7BGMNGfwAA9ETBvH47jGnuq/bsrbq6WpGRkaqqqgrYjBAAAHRfwbx+823iAADAdgg4AADAdgg4AADAdgg4AADAdgg4AADAdgg4AADAdgg4AADAdgg4AADAdgg4AADAdgg4AADAdgg4AADAdgg4AADAdgg4AADAdgg4AADAdgg4AADAdgg4AADAdgg4AADAdgg4AADAdgg4AADAdgg4AADAdgg4AADAdgg4AADAdgg4AADAdgg4AADAdgg4AADAdgg4AADAdgg4AADAdgg4AADAdgg4AADAdgg4AADAdgg4AADAdgg4AADAdoIKOC+//LLmzp2rkSNHql+/frr55pt1zz336E9/+lOT3sOHD2vy5MkKDw9XVFSUfD6fjh8/3uy469ev18iRI+VyuTR06FBlZmaqrq6uSd+ZM2c0Z84ceb1ehYWFKTk5WYWFhcGcAgAA6AWCCjg/+clPdOLECS1atEjbt29Xdna2zpw5owkTJujll1+2+kpLS5WamqrLly9r06ZN2rhxo9566y2lpKTo7NmzAWNmZWVp0aJF8vl82rlzpxYsWKA1a9Zo4cKFAX21tbVKS0tTYWGhsrOztXXrVg0cOFDp6enau3dvO5YAAADYjgnCe++916RWU1NjBg4caNLS0qzazJkzjdfrNVVVVVbtxIkTJjQ01CxZssSqVVRUGLfbbebPnx8wZlZWlnE4HKakpMSq5eTkGElm//79Vq2urs4kJCSYcePGBXMapqqqykgKmB8AAOjegnn9DuoKzoABA5rUwsPDlZCQoFOnTkmS6uvrtW3bNs2YMUMRERFW35AhQzRp0iQVFBRYtR07dsjv9ysjIyNgzIyMDBljtGXLFqtWUFCgESNGKDk52ao5nU7NmjVLBw8eVFlZWTCnAgAAbKzdHzKuqqrS4cOHNWrUKEnSsWPHdOnSJSUlJTXpTUpK0tGjR+X3+yVJR44ckSQlJiYG9MXExMjr9VrHG3tbGlOSSkpKWpxjbW2tqqurAx4AAMC+2h1wFi5cqA8++ECPPfaYJKmyslKS5PF4mvR6PB4ZY3T+/Hmr1+VyqV+/fs32No7V2NvSmNf+3uasXbtWkZGR1iM+Pj6IMwQAAD1NuwLOihUr9Oyzz+pHP/qRbr/99oBjDoejxedde6y1fcH2XmvZsmWqqqqyHo1vpwEAAHtytvWJmZmZeuKJJ5SVlaWHHnrIqkdHR0tq/orKuXPn5HA4FBUVZfX6/X5dvHhRYWFhTXqvDU3R0dEtjik1f8Wokcvlksvlav3JAQCAHq1NV3AyMzO1evVqrV69Wo8++mjAsWHDhqlv374qLi5u8rzi4mINHz5cbrdb0oefvflob3l5uSoqKjR69GirlpiY2OKYkgJ6AQBA7xZ0wHn88ce1evVqLV++XKtWrWpy3Ol0aurUqcrPz1dNTY1VP3nypIqKiuTz+axaenq63G63cnNzA8bIzc2Vw+HQtGnTrNr06dNVWlqqAwcOWLX6+nrl5eVp/Pjxio2NDfZUAACATTmMMaa1zT/84Q/1ne98R+np6c2GmwkTJkhq2Ohv7Nix+sxnPqOlS5fK7/dr5cqVOnfunF5//XX179/fek5WVpZWrFihZcuWacqUKTp06JCWL1+u2bNn66mnnrL6amtrdfvtt6u6ulrr1q3TgAEDtGHDBr300kvavXu3Jk6c2OqTrq6uVmRkpKqqqgJuZQcAAN1XMK/fQQWc1NTUj901+Nqh/vSnP+mRRx7RK6+8IqfTqc9//vP6wQ9+oGHDhjV53o9//GPl5OToxIkTGjRokDIyMvTYY48pNDQ0oO+9997TkiVLtG3bNl28eFFjxozR448/rsmTJ7f2FCQRcAAA6Ik6LeDYBQEHAICeJ5jXb75NHAAA2A4BBwAA2A4BBwAA2A4BBwAA2A4BBwAA2A4BBwAA2A4BBwAA2A4BBwAA2E6bv00cuJ6uXJH27ZNOn5ZiYqSUFCkkpKtnBQDorgg46Pby86VFi6R33vmwFhcnZWdL13x3KwAAFt6iQreWny/de29guJGksrKGen5+18wLANC9EXDQbV250nDlprlvS2usLV7c0AcAwLUIOOi29u1reuXmWsZIp0419AEAcC0CDrqt06c7tg8A0HsQcNBtxcR0bB8AoPcg4KDbSklpuFvK4Wj+uMMhxcc39AEAcC0CDrqtkJCGW8GlpiGn8ecnn2Q/HABAUwQcdGs+n7R5s3TzzYH1uLiGOvvgAACaw0Z/6PZ8Pumee9jJGADQegQc9AghIVJqalfPAgDQU/AWFQAAsB0CDgAAsB0CDgAAsB0CDgAAsB0CDgAAsB0CDgAAsB0CDgAAsB32wUG7XLnCBnwAgO6HgIM2y8+XFi2S3nnnw1pcXMP3R/EVCgCArsRbVGiT/Hzp3nsDw40klZU11PPzu2ZeAABIBBy0wZUrDVdujGl6rLG2eHFDHwAAXYGAg6Dt29f0ys21jJFOnWroAwCgKwQdcGpqarRkyRJNmTJF/fv3l8Ph0OrVq5vtPXz4sCZPnqzw8HBFRUXJ5/Pp+PHjzfauX79eI0eOlMvl0tChQ5WZmam6uromfWfOnNGcOXPk9XoVFham5ORkFRYWBnsaaIfTpzu2DwCAjhZ0wKmsrNRTTz2l2tpaTZs2rcW+0tJSpaam6vLly9q0aZM2btyot956SykpKTp79mxAb1ZWlhYtWiSfz6edO3dqwYIFWrNmjRYuXBjQV1tbq7S0NBUWFio7O1tbt27VwIEDlZ6err179wZ7KmijmJiO7QMAoMOZIF29etVcvXrVGGPM2bNnjSSzatWqJn0zZ840Xq/XVFVVWbUTJ06Y0NBQs2TJEqtWUVFh3G63mT9/fsDzs7KyjMPhMCUlJVYtJyfHSDL79++3anV1dSYhIcGMGzeu1edQVVVlJAXMDa1XX29MXJwxDocxDW9IBT4cDmPi4xv6AADoKMG8fgd9BcfhcMjhcHxsT319vbZt26YZM2YoIiLCqg8ZMkSTJk1SQUGBVduxY4f8fr8yMjICxsjIyJAxRlu2bLFqBQUFGjFihJKTk62a0+nUrFmzdPDgQZWVlQV7OmiDkJCGW8El6aN/FRp/fvJJ9sMBAHSdTvmQ8bFjx3Tp0iUlJSU1OZaUlKSjR4/K7/dLko4cOSJJSkxMDOiLiYmR1+u1jjf2tjSmJJWUlDQ7n9raWlVXVwc80D4+n7R5s3TzzYH1uLiGOvvgAAC6Uqds9FdZWSlJ8ng8TY55PB4ZY3T+/HnFxMSosrJSLpdL/fr1a7a3cazGcVsa89rf+1Fr165VZmZmm87Fztq7C7HPJ91zDzsZAwC6n07dyfjj3sq69lhr+4LtbbRs2TJ9+9vftn6urq5WfHx8i+P0Bh21C3FIiJSa2uHTAwCgXTrlLaro6GhJzV9ROXfunBwOh6Kioqxev9+vixcvNtt77RWb6OjoFseUmr9iJEkul0sREREBj96MXYgBAHbXKQFn2LBh6tu3r4qLi5scKy4u1vDhw+V2uyV9+Nmbj/aWl5eroqJCo0ePtmqJiYktjikpoBfNYxdiAEBv0CkBx+l0aurUqcrPz1dNTY1VP3nypIqKiuS75j2Q9PR0ud1u5ebmBoyRm5srh8MRsNfO9OnTVVpaqgMHDli1+vp65eXlafz48YqNje2M07EVdiEGAPQGbfoMzu9+9zt98MEHVnj561//qs2bN0uS7rrrLoWFhSkzM1Njx47V3XffraVLl8rv92vlypXyer16+OGHrbE8Ho+WL1+uFStWyOPxaMqUKTp06JBWr16tefPmKSEhweqdO3eucnJyNHPmTK1bt04DBgzQhg0b9Oabb2r37t3tWYdeg12IAQC9Qls22hkyZIiR1Ozjb3/7m9X32muvmbS0NBMWFmYiIiLMtGnTzNGjR5sdMzs729x2222mT58+ZvDgwWbVqlXm8uXLTfrKy8vN7NmzjcfjMW6320yYMMHs2rUrqPl31kZ/9fXGFBUZ89xzDX92x43uioqa35zvo4+ioq6eKQAAgYJ5/XYY09ynMeyturpakZGRqqqq6rAPHHfUXUmt0Z7bu69ckW65peEDxc39X97haJj33/7G7d4AgO4lmNdvvk28A1zPu5Ly8xsCyqRJ0r/+a8Oft9zS+t/BLsQAgN6AgNNO1/OupI4KUuxCDACwO96iaudbVHv2NFxF+UeKitq3IV7jW0st3QHVlreW2ruTMQAA11Mwr9+dupNxb3C97koK5vbu1gYpdiEGANgVb1G1U0xMx/a1hNu7AQBoPQJOO6WkNLw11NJXZDkcUnx8Q197XK8gBQCAHRBw2ul63ZV0vYIUAAB2QMDpANfjriRu7wYAoPW4i6oDv1n8etyV1NyGgvHxDeGG27sBAHYWzOs3AacDA871wu3dAIDeiNvEbY7buwEA+Hh8BgcAANgOAQcAANgOAQcAANgOAQcAANgOAQcAANgOAQcAANgOAQcAANgOAQcAANgOAQcAANhOr9zJuPHbKaqrq7t4JgAAoLUaX7db8y1TvTLg1NTUSJLi4+O7eCYAACBYNTU1ioyM/NieXvllm1evXtW7776rG2+8UQ6Ho0PHrq6uVnx8vE6dOtUjv8izO2NtOxfr23lY287F+nau7rS+xhjV1NQoNjZWN9zw8Z+y6ZVXcG644QbFxcV16u+IiIjo8r8IdsXadi7Wt/Owtp2L9e1c3WV9/9GVm0Z8yBgAANgOAQcAANgOAaeDuVwurVq1Si6Xq6unYjusbedifTsPa9u5WN/O1VPXt1d+yBgAANgbV3AAAIDtEHAAAIDtEHAAAIDtEHBa6f3339fixYsVGxsrt9utMWPG6IUXXmjVc8+cOaM5c+bI6/UqLCxMycnJKiws7OQZ9xxtXdt33nlHixcv1sSJExUVFSWHw6Hc3NzOn3AP09b1zc/P1/3336/hw4erb9++uuWWW/SVr3xFb7/99nWYdc/Q1rXdvXu37rjjDsXGxsrlcmnAgAH6/Oc/r+3bt1+HWfcc7fl391rLly+Xw+HQ6NGjO2GWPVNb1zY3N1cOh6PZR3l5+XWYeRAMWuWOO+4wUVFR5r//+7/Nyy+/bObNm2ckmWefffZjn+f3+83o0aNNXFycycvLM//7v/9r7rnnHuN0Os2ePXuu0+y7t7aubVFRkfF6vWby5Mnm/vvvN5LMz372s+sz6R6kres7btw486Uvfcls3LjR7Nmzx/zyl780n/zkJ014eLg5cuTIdZp999bWtX3hhRfMokWLzAsvvGD27Nlj8vPzzZQpU4wk88tf/vI6zb77a+v6XuvPf/6zcblcZuDAgWbUqFGdONuepa1r+7Of/cz6t/aVV14JeFy+fPk6zb51CDit8Nvf/tZIMs8991xA/Y477jCxsbGmvr6+xefm5OQYSWb//v1Wra6uziQkJJhx48Z12px7ivas7ZUrV6z/PnToEAGnGe1Z3/fee69JrayszISGhpoHH3yww+fa07RnbZtz+fJlc/PNN5uUlJSOnGaP1RHrW1dXZ8aMGWO++c1vmokTJxJw/k971rYx4Bw6dKizp9luvEXVCgUFBQoPD9fMmTMD6hkZGXr33Xd14MCBj33uiBEjlJycbNWcTqdmzZqlgwcPqqysrNPm3RO0Z23/0feQoH3rO2DAgCa12NhYxcXF6dSpUx0+156mPWvbnNDQUEVFRcnp7JXfoNNER6zvunXrdO7cOWVlZXXWNHukjv67213xCtEKR44c0Sc/+ckm//AkJSVZxz/uuY19zT23pKSkA2fa87RnbfGPdfT6Hj9+XH//+981atSoDptjT9URa3v16lXV19fr3Xff1apVq/TWW2/p4Ycf7pT59jTtXd+//vWveuKJJ/STn/xE4eHhnTbPnqgj/u7efffdCgkJkcfjkc/n65b/VvP/KrRCZWWlPvGJTzSpezwe6/jHPbexL9jn9gbtWVv8Yx25vvX19XrwwQcVHh6ub33rWx02x56qI9b2rrvu0s6dOyU1fJHhr371K33xi1/s2In2UO1Z36tXr2ru3Lny+Xy66667Om2OPVV71nbQoEF67LHHNGHCBEVERKi4uFjr1q3ThAkT9Mc//lGf+tSnOm3ewSLgtJLD4WjTsfY+tzdgfTpXR6yvMUYPPvig9u3bp1//+teKj4/vqOn1aO1d2/Xr1+vChQs6ffq08vLydN999+nnP/+57r///o6cZo/V1vX9r//6L7399tv6zW9+0xnTsoW2rm16errS09Otnz/3uc/pi1/8ohITE7Vy5Upt3bq1Q+fZHgScVoiOjm420Z47d06Smr1C0xHP7Q1Yn87VEetrjNG8efOUl5enn//857rnnns6fJ49UUes7a233mr995e+9CV94Qtf0MKFC3Xffff1+s+YtXV9T548qZUrV2rdunXq06ePLly4IKnhCuTVq1d14cIFuVwu9e3bt9Pm3t119L+7t9xyi/7f//t/evXVVztkfh2ld/8vqJUSExP1xhtvqL6+PqBeXFwsSR+7t0JiYqLVF+xze4P2rC3+sfaub2O4+dnPfqann35as2bN6rS59jSd8Xd33LhxOn/+vM6ePdshc+zJ2rq+x48f16VLl7Ro0SLddNNN1uOPf/yj3njjDd10001atmxZp8+/O+uMv7vGmO4Xyrv2Jq6eYfv27UaSeeGFFwLq6enp//CWug0bNhhJ5tVXX7VqdXV1ZtSoUWb8+PGdNueeoj1rey1uE29ee9b36tWr5sEHHzQOh8M89dRTnT3VHqej/u42unr1qpk4caKJiooydXV1HTnVHqmt63v+/HlTVFTU5PGpT33K3HLLLaaoqMi8/fbb1+MUuq2O/rt7/PhxEx4ebqZNm9aR02w3Ak4r3XHHHeamm24yTz31lHn55ZfNV7/6VSPJ5OXlWT1z5841ISEh5sSJE1bN7/ebUaNGmfj4ePPss8+aXbt2menTp7PR3zXaurbGGPPiiy+aF1980Xzve98zkszChQutGhq0dX0feughI8nMnTu3yYZehw8f7opT6XbaurZf+tKXzIoVK8yvf/1rs2fPHvPcc89ZG/3l5OR0xal0S+35t+Gj2AcnUFvXNi0tzWRmZpqCggJTWFhonnzySRMbG2tuvPFGU1xc3BWn0iICTivV1NSYb37zm2bQoEGmT58+JikpyTz//PMBPQ888ICRZP72t78F1MvLy83s2bONx+MxbrfbTJgwwezates6zr57a8/aSmrxgQZtXd8hQ4a0uLZDhgy5vifRTbV1bb/3ve+ZsWPHmptuusmEhISY6Ohoc+edd5pt27Zd5zPo3trzb8NHEXACtXVtFy9ebBISEsyNN95onE6niY2NNbNmzTJvvvnmdT6Df8xhjDGd+yYYAADA9dXNPhEEAADQfgQcAABgOwQcAABgOwQcAABgOwQcAABgOwQcAABgOwQcAABgOwQcAABgOwQcAABgOwQcAABgOwQcAABgOwQcAD2e3+/Xpz/9aQ0fPlxVVVVWvby8XIMGDVJqaqquXLnShTMEcL0RcAD0eG63W5s2bdKZM2c0d+5cSdLVq1f1la98RcYYPf/88woJCeniWQK4npxdPQEA6Ai33nqrnn76ad13333Kzs7WuXPntGfPHu3YsUMxMTFdPT0A15nDGGO6ehIA0FEWLFigp59+WleuXNGjjz6qxx9/vKunBKALEHAA2Mprr72msWPHqk+fPnrnnXfUv3//rp4SgC5AwAFgGx988IE++9nP6urVq3rvvfc0ceJEbd26taunBaAL8CFjALbxta99TSdPnlR+fr6eeeYZ/eY3v9GPfvSjrp4WgC5AwAFgC08//bTy8vKUk5OjUaNGacaMGXrooYf0yCOP6ODBg109PQDXGW9RAejxiouLNX78eH35y19Wbm6uVa+trdU///M/q7KyUn/+858VFRXVZXMEcH0RcAAAgO3wFhUAALAdAg4AALAdAg4AALAdAg4AALAdAg4AALAdAg4AALAdAg4AALAdAg4AALAdAg4AALAdAg4AALAdAg4AALCd/w/xHxTQRMjnugAAAABJRU5ErkJggg==", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fx = [751.71168, 736.56597, 885.97705, 1118.95297, 1538.68901, 3085.17389, 4700.81524, 6434.98779, 8223.48942]\n", "dfx = [1.32859, 1.28606, 0.99619, 0.99134, 1.03403, 0.35958, 0.33758, 0.38790, 0.31241]\n", "x_offset_current = [0, 0.03, 0.05, 0.07, 0.1, 0.2, 0.3, 0.4, 0.515]\n", "\n", "# fx = [736.56597, 885.97705, 1118.95297, 1538.68901, 3085.17389, 4700.81524, 6434.98779, 8223.48942]\n", "# dfx = [1.28606, 0.99619, 0.99134, 1.03403, 0.35958, 0.33758, 0.38790, 0.31241]\n", "# x_offset_current = [0.03, 0.05, 0.07, 0.1, 0.2, 0.3, 0.4, 0.515]\n", "\n", "data = xr.DataArray(\n", " data=fx,\n", " dims=['x'],\n", " coords={\n", " 'x': x_offset_current\n", " } \n", ")\n", "\n", "data_std = xr.DataArray(\n", " data=dfx,\n", " dims=['x'],\n", " coords={\n", " 'x': x_offset_current\n", " } \n", ")\n", "\n", "data.plot.errorbar(fmt='ob', yerr=data_std)\n", "\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 127, "metadata": {}, "outputs": [], "source": [ "def magnetic_field_func(x, b0=0, by0=0, alpha=1):\n", " return 1 / (1e3 * 6.626e-34) * (9.273e-24 * 1.24) * np.sqrt( (b0**2 - by0**2) + (alpha * x + by0)**2 )\n", "\n", "data_quadratic = data\n", "\n", "fitModel_quadratic = NewFitModel(magnetic_field_func)\n", "fitAnalyser_quadratic = FitAnalyser(fitModel_quadratic, fitDim=1)\n", "params_quadratic = fitAnalyser_quadratic.fitModel.make_params()\n", "params_quadratic.add(name=\"b0\", value= 0.3, max=np.inf, min=-np.inf, vary=True)\n", "params_quadratic.add(name=\"by0\", value= 0.07, max=np.inf, min=-np.inf, vary=True)\n", "params_quadratic.add(name=\"alpha\", value= 100, max=np.inf, min=-np.inf, vary=True)\n", "fitResult_quadratic = fitAnalyser_quadratic.fit(data_quadratic, params_quadratic).load()\n", "\n", "fitCurve_quadratic = fitAnalyser_quadratic.eval(fitResult_quadratic, x=np.linspace(0, 0.6, 100), dask=\"parallelized\").load()" ] }, { "cell_type": "code", "execution_count": 128, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "data_linear = data[3:]\n", "\n", "fitAnalyser_linear = FitAnalyser('Linear', fitDim=1)\n", "params_linear = fitAnalyser_linear.guess(data_linear, dask=\"parallelized\")\n", "fitResult_linear = fitAnalyser_linear.fit(data_linear, params_linear).load()\n", "\n", "fitCurve_linear = fitAnalyser_linear.eval(fitResult_linear, x=np.linspace(0, 0.5, 100), dask=\"parallelized\").load()\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "\n", "data.plot.errorbar(ax=ax, fmt='ob', yerr=data_std)\n", "# fitCurve_linear.plot.errorbar(ax=ax)\n", "fitCurve_quadratic.plot.errorbar(ax=ax)\n", "\n", "plt.xlabel('X Offset Coil Current (A)', fontsize=12)\n", "plt.ylabel('Resonance Frequency (kHz)', fontsize=12)\n", "plt.xticks(fontsize=12)\n", "plt.yticks(fontsize=12)\n", "# plt.legend(fontsize=12)\n", "#plt.xlim(-0.01, 0.04)\n", "# plt.ylim(0, 10000)\n", "plt.grid(visible=1)\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 129, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
<xarray.Dataset>\n",
       "Dimensions:  ()\n",
       "Data variables:\n",
       "    b0       object 0.435+/-0.016\n",
       "    by0      object -0.164+/-0.017\n",
       "    alpha    object 9.52+/-0.05
" ], "text/plain": [ "\n", "Dimensions: ()\n", "Data variables:\n", " b0 object 0.435+/-0.016\n", " by0 object -0.164+/-0.017\n", " alpha object 9.52+/-0.05" ] }, "execution_count": 129, "metadata": {}, "output_type": "execute_result" } ], "source": [ "fitAnalyser_quadratic.get_fit_full_result(fitResult_quadratic) * 1e4" ] }, { "cell_type": "code", "execution_count": 130, "metadata": {}, "outputs": [], "source": [ "val_x = fitAnalyser_quadratic.get_fit_value(fitResult_quadratic) * 1e4\n", "std_x = fitAnalyser_quadratic.get_fit_std(fitResult_quadratic) * 1e4\n", "res_x = fitAnalyser_quadratic.get_fit_full_result(fitResult_quadratic) * 1e4" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "# Y-comp coil" ] }, { "cell_type": "code", "execution_count": 131, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fy = [751.71168, 918.67701, 1129.74687, 1429.82911, 1749.75310, 3089.87897, 4314.90128, 5387.64638, 6666.03670]\n", "dfy = [1.32859, 0.90271, 1.33691, 1.77735, 1.42421, 1.58909, 1.73638, 1.40175, 1.00526]\n", "y_offset_current = [0.0, 0.015, 0.03, 0.05, 0.07, 0.15, 0.22, 0.28, 0.35]\n", "\n", "# fy = [918.67701, 1129.74687, 1429.82911, 1749.75310, 3089.87897, 4314.90128, 5387.64638, 6666.03670]\n", "# dfy = [0.90271, 1.33691, 1.77735, 1.42421, 1.58909, 1.73638, 1.40175, 1.00526]\n", "# y_offset_current = [0.015, 0.03, 0.05, 0.07, 0.15, 0.22, 0.28, 0.35]\n", "\n", "data = xr.DataArray(\n", " data=fy,\n", " dims=['x'],\n", " coords={\n", " 'x': y_offset_current\n", " } \n", ")\n", "\n", "data_std = xr.DataArray(\n", " data=dfy,\n", " dims=['x'],\n", " coords={\n", " 'x': y_offset_current\n", " } \n", ")\n", "\n", "data.plot.errorbar(fmt='ob', yerr=data_std)\n", "\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 132, "metadata": {}, "outputs": [], "source": [ "def magnetic_field_func(x, b0=0, by0=0, alpha=1):\n", " return 1 / (1e3 * 6.626e-34) * (9.273e-24 * 1.24) * np.sqrt( (b0**2 - by0**2) + (alpha * x + by0)**2 )\n", "\n", "data_quadratic = data\n", "\n", "fitModel_quadratic = NewFitModel(magnetic_field_func)\n", "fitAnalyser_quadratic = FitAnalyser(fitModel_quadratic, fitDim=1)\n", "params_quadratic = fitAnalyser_quadratic.fitModel.make_params()\n", "params_quadratic.add(name=\"b0\", value= 0.3, max=np.inf, min=-np.inf, vary=True)\n", "params_quadratic.add(name=\"by0\", value= 0.07, max=np.inf, min=-np.inf, vary=True)\n", "params_quadratic.add(name=\"alpha\", value= 100, max=np.inf, min=-np.inf, vary=True)\n", "fitResult_quadratic = fitAnalyser_quadratic.fit(data_quadratic, params_quadratic).load()\n", "\n", "fitCurve_quadratic = fitAnalyser_quadratic.eval(fitResult_quadratic, x=np.linspace(0, 0.6, 100), dask=\"parallelized\").load()" ] }, { "cell_type": "code", "execution_count": 133, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "data_linear = data[3:]\n", "\n", "fitAnalyser_linear = FitAnalyser('Linear', fitDim=1)\n", "params_linear = fitAnalyser_linear.guess(data_linear, dask=\"parallelized\")\n", "fitResult_linear = fitAnalyser_linear.fit(data_linear, params_linear).load()\n", "\n", "fitCurve_linear = fitAnalyser_linear.eval(fitResult_linear, x=np.linspace(0, 0.5, 100), dask=\"parallelized\").load()\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "\n", "data.plot.errorbar(ax=ax, fmt='ob', yerr=data_std)\n", "# fitCurve_linear.plot.errorbar(ax=ax)\n", "fitCurve_quadratic.plot.errorbar(ax=ax)\n", "\n", "plt.xlabel('Y Offset Coil Current (A)', fontsize=12)\n", "plt.ylabel('Resonance Frequency (kHz)', fontsize=12)\n", "plt.xticks(fontsize=12)\n", "plt.yticks(fontsize=12)\n", "# plt.legend(fontsize=12)\n", "#plt.xlim(-0.01, 0.04)\n", "# plt.ylim(0, 10000)\n", "plt.grid(visible=1)\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 134, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
<xarray.Dataset>\n",
       "Dimensions:  ()\n",
       "Data variables:\n",
       "    b0       object 0.440+/-0.009\n",
       "    by0      object 0.202+/-0.015\n",
       "    alpha    object 10.30+/-0.05
" ], "text/plain": [ "\n", "Dimensions: ()\n", "Data variables:\n", " b0 object 0.440+/-0.009\n", " by0 object 0.202+/-0.015\n", " alpha object 10.30+/-0.05" ] }, "execution_count": 134, "metadata": {}, "output_type": "execute_result" } ], "source": [ "fitAnalyser_quadratic.get_fit_full_result(fitResult_quadratic) * 1e4" ] }, { "cell_type": "code", "execution_count": 135, "metadata": {}, "outputs": [], "source": [ "val_y = fitAnalyser_quadratic.get_fit_value(fitResult_quadratic) * 1e4\n", "std_y = fitAnalyser_quadratic.get_fit_std(fitResult_quadratic) * 1e4\n", "res_y = fitAnalyser_quadratic.get_fit_full_result(fitResult_quadratic) * 1e4" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "# Z-comp coil" ] }, { "cell_type": "code", "execution_count": 136, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fz = [751.71168, 1223.54627, 1739.13344, 2364.93284, 2798.24971, 3178.49790, 4275.39905, 5352.17283, 6637.80418, 8288.35264, 9573.59333]\n", "dfz = [1.32859, 0.35554, 0.48471, 0.69762, 0.36873, 0.29413, 0.20667, 0.20818, 0.21978, 0.20285, 0.18495]\n", "z_offset_current = [0.0, 0.03, 0.06, 0.095, 0.119, 0.140, 0.2, 0.259, 0.329, 0.419, 0.489]\n", "\n", "data = xr.DataArray(\n", " data=fz,\n", " dims=['x'],\n", " coords={\n", " 'x': z_offset_current\n", " } \n", ")\n", "\n", "data_std = xr.DataArray(\n", " data=dfz,\n", " dims=['x'],\n", " coords={\n", " 'x': z_offset_current\n", " } \n", ")\n", "\n", "data.plot.errorbar(fmt='ob', yerr=data_std)\n", "\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 137, "metadata": {}, "outputs": [], "source": [ "def magnetic_field_func(x, b0=0, by0=0, alpha=1):\n", " return 1 / (1e3 * 6.626e-34) * (9.273e-24 * 1.24) * np.sqrt( (b0**2 - by0**2) + (alpha * x + by0)**2 )\n", "\n", "data_quadratic = data\n", "\n", "fitModel_quadratic = NewFitModel(magnetic_field_func)\n", "fitAnalyser_quadratic = FitAnalyser(fitModel_quadratic, fitDim=1)\n", "params_quadratic = fitAnalyser_quadratic.fitModel.make_params()\n", "params_quadratic.add(name=\"b0\", value= 0.3, max=np.inf, min=-np.inf, vary=True)\n", "params_quadratic.add(name=\"by0\", value= 0.07, max=np.inf, min=-np.inf, vary=True)\n", "params_quadratic.add(name=\"alpha\", value= 100, max=np.inf, min=-np.inf, vary=True)\n", "fitResult_quadratic = fitAnalyser_quadratic.fit(data_quadratic, params_quadratic).load()\n", "\n", "fitCurve_quadratic = fitAnalyser_quadratic.eval(fitResult_quadratic, x=np.linspace(0, 0.6, 100), dask=\"parallelized\").load()" ] }, { "cell_type": "code", "execution_count": 138, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "data_linear = data[3:]\n", "\n", "fitAnalyser_linear = FitAnalyser('Linear', fitDim=1)\n", "params_linear = fitAnalyser_linear.guess(data_linear, dask=\"parallelized\")\n", "fitResult_linear = fitAnalyser_linear.fit(data_linear, params_linear).load()\n", "\n", "fitCurve_linear = fitAnalyser_linear.eval(fitResult_linear, x=np.linspace(0, 0.5, 100), dask=\"parallelized\").load()\n", "\n", "fig = plt.figure()\n", "ax = fig.gca()\n", "\n", "data.plot.errorbar(ax=ax, fmt='ob', yerr=data_std)\n", "# fitCurve_linear.plot.errorbar(ax=ax)\n", "fitCurve_quadratic.plot.errorbar(ax=ax)\n", "\n", "plt.xlabel('Y Offset Coil Current (A)', fontsize=12)\n", "plt.ylabel('Resonance Frequency (kHz)', fontsize=12)\n", "plt.xticks(fontsize=12)\n", "plt.yticks(fontsize=12)\n", "# plt.legend(fontsize=12)\n", "#plt.xlim(-0.01, 0.04)\n", "# plt.ylim(0, 10000)\n", "plt.grid(visible=1)\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 139, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
<xarray.Dataset>\n",
       "Dimensions:  ()\n",
       "Data variables:\n",
       "    b0       object 0.4333+/-0.0007\n",
       "    by0      object 0.3254+/-0.0008\n",
       "    alpha    object 10.6021+/-0.0022
" ], "text/plain": [ "\n", "Dimensions: ()\n", "Data variables:\n", " b0 object 0.4333+/-0.0007\n", " by0 object 0.3254+/-0.0008\n", " alpha object 10.6021+/-0.0022" ] }, "execution_count": 139, "metadata": {}, "output_type": "execute_result" } ], "source": [ "fitAnalyser_quadratic.get_fit_full_result(fitResult_quadratic) * 1e4" ] }, { "cell_type": "code", "execution_count": 140, "metadata": {}, "outputs": [], "source": [ "val_z = fitAnalyser_quadratic.get_fit_value(fitResult_quadratic) * 1e4\n", "std_z = fitAnalyser_quadratic.get_fit_std(fitResult_quadratic) * 1e4\n", "res_z = fitAnalyser_quadratic.get_fit_full_result(fitResult_quadratic) * 1e4" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 145, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.416688520216393+/-0.009836437571434223" ] }, "execution_count": 145, "metadata": {}, "output_type": "execute_result" } ], "source": [ "umath.sqrt(res_x['by0'].item()**2 + res_y['by0'].item()**2 + res_z['by0'].item()**2)" ] }, { "cell_type": "code", "execution_count": 148, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.43640594986928966+/-0.006152786477679057" ] }, "execution_count": 148, "metadata": {}, "output_type": "execute_result" } ], "source": [ "(res_x['b0'].item() + res_y['b0'].item() + res_z['b0'].item())/3" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "base", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.12" }, "orig_nbformat": 4 }, "nbformat": 4, "nbformat_minor": 2 }