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-rw-r--r--lut_generator.ipynb184
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+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "%matplotlib inline\n",
+ "import matplotlib.pyplot as plt\n",
+ "import numpy as np, pandas as pd\n",
+ "import pickle\n",
+ "import os\n",
+ "\n",
+ "if not os.path.isdir(\"./lut_plot\"):\n",
+ " os.mkdir(\"./lut_plot\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def get_meas(path):\n",
+ " measurements = pickle.load(open(path, \"rb\"))\n",
+ " df = pd.DataFrame(measurements, columns=[\"ampl\",\"mag_gen_sq\",\"mag_feedback_sq\",\"phase_diff\"])\n",
+ " df[\"mag_gen\"] = np.sqrt(df[\"mag_gen_sq\"])\n",
+ " df[\"mag_feedback\"] = np.sqrt(df[\"mag_feedback_sq\"])\n",
+ " return df"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "df = get_meas(\"./measurements.pkl\")\n",
+ "df_lut = get_meas(\"./measurements_lut.pkl\")\n",
+ "df_lut_sq = get_meas(\"./measurements_lut_sq.pkl\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def get_slope(ampl, mag_feedback):\n",
+ " slope, intersect = np.polyfit(x = ampl[0:20], y = mag_feedback[0:20], deg = 1)\n",
+ " return slope, intersect\n",
+ "\n",
+ "#get_slope(df[\"ampl\"], df[\"mag_feedback\"])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def get_fac(ampl, mag_feedback):\n",
+ " slope, intersect = get_slope(df[\"ampl\", df[\"mag_feedback\"]])\n",
+ " return[(x*slope + intersect) / y for (x,y) in zip(df[\"ampl\"], df[\"mag_feedback\"])]\n",
+ "def interp(x): return np.interp(x, df[\"ampl\"], fac)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "x = np.linspace(0.1, 0.5, num = 50)\n",
+ "\n",
+ "plt.plot(df[\"ampl\"], df[\"mag_feedback\"], label=\"measurement\")\n",
+ "plt.plot(x, x*slope + intersect, label = \"linear model\")\n",
+ "\n",
+ "plt.legend(loc=0)\n",
+ "plt.title(\"Original Measurement\")\n",
+ "\n",
+ "plt.savefig(\"./lut_plot/original_measurement.png\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "slope, intersect = get_slope(df[\"ampl\"], df[\"mag_feedback\"])\n",
+ "\n",
+ "plt.plot(df_lut[\"ampl\"], df_lut[\"mag_feedback\"], label=\"measurement\")\n",
+ "plt.plot(x, x*slope + intersect, label = \"linear model\")\n",
+ "\n",
+ "plt.legend(loc=0)\n",
+ "plt.title(\"Lut Measurement\")\n",
+ "\n",
+ "plt.savefig(\"./lut_plot/lut_measurement.png\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "slope, intersect = get_slope(df[\"ampl\"], df[\"mag_feedback\"])\n",
+ "\n",
+ "plt.plot(df_lut_sq[\"ampl\"], df_lut_sq[\"mag_feedback\"], label=\"measurement\")\n",
+ "plt.plot(x, x*slope + intersect, label = \"linear model\")\n",
+ "\n",
+ "plt.legend(loc=0)\n",
+ "plt.title(\"Lut Squared Measurement\")\n",
+ "\n",
+ "plt.savefig(\"./lut_plot/lut_sq_measurement.png\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "slope, intersect = get_slope(df[\"ampl\"], df[\"mag_feedback\"])\n",
+ "\n",
+ "plt.plot(df[\"ampl\"], df[\"mag_feedback\"], label=\"measurement\")\n",
+ "plt.plot(df_lut[\"ampl\"], df_lut[\"mag_feedback\"], label=\"measurement lut\")\n",
+ "plt.plot(df_lut_sq[\"ampl\"], df_lut_sq[\"mag_feedback\"], label=\"measurement lut sq\")\n",
+ "plt.plot(x, x*slope + intersect, label = \"linear model\")\n",
+ "\n",
+ "plt.legend(loc=0)\n",
+ "plt.title(\"All Measurements\")\n",
+ "\n",
+ "plt.savefig(\"./lut_plot/all_measurement.png\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "pickle.dump({\"ampl\":df[\"ampl\"],\"fac\":[f for f in fac]}, open(\"lut.pkl\", \"wb\"))\n",
+ "pickle.dump({\"ampl\":df[\"ampl\"],\"fac\":[f**2 for f in fac]}, open(\"lut_sq.pkl\", \"wb\"))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}