m17-cxx-demod/filter-taps.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%pylab inline\n",
    "from commpy.filters import rrcosfilter\n",
    "\n",
    "sample_rate = 48000\n",
    "samples_per_symbol = 10\n",
    "\n",
    "def response_plot(taps, sample_rate, legend):\n",
    "\n",
    "    duration = len(taps) / sample_rate\n",
    "    t = np.linspace(0, duration, len(taps), endpoint=True)\n",
    "    plt.figure()\n",
    "    plt.rcParams['figure.figsize'] = [12, 4]\n",
    "    ax = plt.subplot(1, 1, 1)\n",
    "    plt.xlabel('Time (msec)')\n",
    "    plt.locator_params(axis='y', nbins=8)\n",
    "    plt.grid()\n",
    "    plt.xticks(np.arange(0, duration, 1.0/4800.0), rotation=45)\n",
    "    plt.plot(t, taps)\n",
    "    plt.legend(legend)\n",
    "\n",
    "taps = rrcosfilter(int(40 * 8), 0.5, 1.0, 40.0)[1][1:]\n",
    "response_plot(taps, sample_rate, [\"Erroneous Filter Resoponse\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "40.07977085248521\n",
      "1.1366197723675815\n",
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      "31986,\n",
      "32326,\n",
      "32570,\n",
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      "32766,\n",
      "32717,\n",
      "32570,\n",
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      "31986,\n",
      "31553,\n",
      "31029,\n",
      "30417,\n",
      "29721,\n",
      "28944,\n",
      "28093,\n",
      "27171,\n",
      "26183,\n",
      "25137,\n",
      "24037,\n",
      "22890,\n",
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      "20481,\n",
      "19232,\n",
      "17963,\n",
      "16681,\n",
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      "14102,\n",
      "12818,\n",
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      "2524,\n",
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      "-777,\n",
      "-1445,\n",
      "-2048,\n",
      "-2587,\n",
      "-3059,\n",
      "-3467,\n",
      "-3812,\n",
      "-4094,\n",
      "-4316,\n",
      "-4480,\n",
      "-4587,\n",
      "-4642,\n",
      "-4648,\n",
      "-4606,\n",
      "-4522,\n",
      "-4398,\n",
      "-4239,\n",
      "-4049,\n",
      "-3831,\n",
      "-3589,\n",
      "-3328,\n",
      "-3051,\n",
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      "1023,\n",
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      "854,\n",
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      "300,\n",
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      "413,\n",
      "439,\n",
      "460,\n",
      "474,\n",
      "482,\n",
      "484,\n",
      "479,\n",
      "470,\n",
      "454,\n",
      "434,\n",
      "408,\n",
      "379,\n",
      "345,\n",
      "308,\n",
      "269,\n",
      "228,\n",
      "185,\n",
      "141,\n",
      "96,\n",
      "52,\n",
      "9,\n",
      "-33,\n",
      "-73,\n",
      "-111,\n",
      "-146,\n",
      "-177,\n",
      "-206,\n",
      "-230,\n",
      "-251,\n",
      "-268,\n",
      "-280,\n",
      "-288,\n",
      "-292\n"
     ]
    }
   ],
   "source": [
    "gain = sum(taps)\n",
    "print(gain)\n",
    "print(max(taps))\n",
    "print(32767 // max(taps))\n",
    "\n",
    "print(\",\\n\".join([str(int(t * 32767 // max(taps))) for t in taps]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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