From d31ea5a51f0cc17b0556423896b7b0b7b3c2c217 Mon Sep 17 00:00:00 2001
From: andreas128 <Andreas>
Date: Tue, 29 Nov 2016 12:00:01 +0100
Subject: Add lut_generator.ipynb to generate a lut from a measurement

---
 lut_generator.ipynb | 184 ++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 184 insertions(+)
 create mode 100644 lut_generator.ipynb

(limited to 'lut_generator.ipynb')

diff --git a/lut_generator.ipynb b/lut_generator.ipynb
new file mode 100644
index 0000000..489203f
--- /dev/null
+++ b/lut_generator.ipynb
@@ -0,0 +1,184 @@
+{
+ "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
+}
-- 
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