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path: root/Mod/Lab/LoadAM.ipynb
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{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9757b098-ed50-4026-be3a-3e8cf07af185",
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "\n",
    "import math\n",
    "import numpy as np\n",
    "import matplotlib\n",
    "import matplotlib.pylab as pylab\n",
    "import matplotlib.pyplot as plot\n",
    "import scipy.fftpack\n",
    "from scipy.signal import butter,filtfilt,sosfilt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9b8a466d-a194-466e-b719-067b3b113cec",
   "metadata": {},
   "source": [
    "# Helper functions to draw fft"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "5aee97c7-cbdc-4ceb-a100-30c742af2cc1",
   "metadata": {},
   "outputs": [],
   "source": [
    "#some util for fft\n",
    "def draw_fft(signal,title=\"just FFT\"):\n",
    "    len_signal = len(signal)\n",
    "    yfft = scipy.fft.fft(signal,norm=\"forward\")\n",
    "    print(yfft.size)\n",
    "    xf = np.linspace(0.0, 1.0/(2.0*(1.0/len_signal)), len_signal//2)\n",
    "    #plot.plot(xf,2.0/len(signal) * np.abs(yfft[:len(signal)//2]))\n",
    "    plot.plot(xf,2.0/len_signal * np.abs(yfft[:len_signal//2]))\n",
    "    plot.title(title)\n",
    "    plot.show()\n",
    "    \n",
    "#some util for fft\n",
    "def draw_fft(signal,title=\"just FFT\",bw=None):\n",
    "    len_signal = len(signal)\n",
    "    yfft = scipy.fft.fft(signal,norm=\"forward\")\n",
    "    print(yfft.size)\n",
    "    xf = np.linspace(0.0, 1.0/(2.0*(1.0/len_signal)), len_signal//2)\n",
    "    #plot.plot(xf,2.0/len(signal) * np.abs(yfft[:len(signal)//2]))\n",
    "    plot.plot(xf,2.0/len_signal * np.abs(yfft[:len_signal//2]))\n",
    "    plot.title(title)\n",
    "    plot.show()\n",
    "\n",
    "def draw_fft2(signal,title=\"just FFT2\"):\n",
    "    len_signal = len(signal)\n",
    "    yfft = scipy.fft.fft(signal)\n",
    "    xf = np.linspace(0.0, 1.0/((1.0/len_signal)), len_signal)\n",
    "    #plot.plot(xf,2.0/len(signal) * np.abs(yfft[:len(signal)//2]))\n",
    "    plot.plot(xf,1.0/len_signal * np.abs(yfft[:len_signal]))\n",
    "    plot.title(title)\n",
    "    plot.show()\n",
    "def iq_abs(c):\n",
    "    return (math.sqrt((c.real ** 2 + c.imag ** 2)))\n",
    "\n",
    "def draw_fft3(signal,title=\"just FFT3\"):\n",
    "    len_signal = len(signal)\n",
    "    \n",
    "    #get fft\n",
    "    spect = np.fft.fft(signal,n=len_signal)\n",
    "    #spect = spect[0:int((len(spect) / 2))]\n",
    "    spect = spect[0:int((len(spect)))]\n",
    "    \n",
    "    #normalize\n",
    "    spect_n = [(1.0 / (len_signal * len(spect))) * iq_abs(x) ** 2 for x in spect]\n",
    "    spect_n = (10 * np.log10(spect_n)).tolist()\n",
    "\n",
    "    \n",
    "    #plot results\n",
    "    len_spec_n = len(spect_n)\n",
    "    xf = np.linspace(0.0, 1.0/(1.0*(1.0/len_spec_n)), len_spec_n)\n",
    "    print(len(xf))\n",
    "    plot.plot(xf,spect_n)\n",
    "    plot.title(title)\n",
    "    plot.show()\n",
    "\n",
    "def draw_fft4(signal, title=\"just FFT4\"):\n",
    "    len_signal = len(signal)\n",
    "    \n",
    "    #get fft\n",
    "    spect = np.fft.fft(signal,n=len_signal)\n",
    "    #spect = spect[0:int((len(spect) / 2))]\n",
    "    #spect = spect[0:int((len(spect)))]\n",
    "    \n",
    "    n = signal.size\n",
    "    timestamp=1.0\n",
    "    freq = np.fft.fftfreq(n,d=1.0/660000)\n",
    "    \n",
    "    \n",
    "    #normalize\n",
    "    spect_n = [(1.0 / (len_signal * len(spect))) * iq_abs(x) ** 2 for x in spect]\n",
    "    spect_n = (10 * np.log10(spect_n)).tolist()\n",
    "\n",
    "    \n",
    "    #plot results\n",
    "    #len_spec_n = len(spect_n)\n",
    "    #xf = np.linspace(0.0, 1.0/(1.0*(1.0/len_spec_n)), len_spec_n)\n",
    "    #print(len(xf))\n",
    "    plot.plot(freq,spect_n)\n",
    "    plot.title(title)\n",
    "    plot.show()\n",
    "\n",
    "    \n",
    "def draw_fft5(signal,title=\"FFT 5\",fc=None, bw=None, sr=None):\n",
    "    len_signal = len(signal)\n",
    "    yfft = scipy.fft.fft(signal,norm=\"forward\")\n",
    "    print(yfft.size)\n",
    "    xf = np.linspace(fc-bw/2, fc+bw/2, sr)\n",
    "    #plot.plot(xf,2.0/len(signal) * np.abs(yfft[:len(signal)//2]))\n",
    "    plot.plot(xf,np.abs(yfft[:len_signal]))\n",
    "    plot.title(title)\n",
    "    plot.show()\n",
    "\n",
    "def draw_peaks(signal,title=\"FFT 5\",fc=None, bw=None, sr=None):\n",
    "    len_signal = len(signal)\n",
    "    yfft = scipy.fft.fft(signal,norm=\"forward\")\n",
    "    print(yfft.size)\n",
    "    xf = np.linspace(0, sr, sr)\n",
    "    print(xf.size)\n",
    "    #plot.plot(xf,2.0/len(signal) * np.abs(yfft[:len(signal)//2]))\n",
    "    peaks, _ = scipy.signal.find_peaks(yfft,height=0.5,distance=1000)\n",
    "    print(peaks)\n",
    "    plot.plot(xf,np.abs(yfft[:len_signal]))\n",
    "    plot.plot(peaks,yfft[peaks],\"x\")\n",
    "    plot.plot(np.full_like(xf,0.5), \"--\", color=\"gray\")\n",
    "    plot.title(title)\n",
    "    plot.show()\n",
    "\n",
    "def plot_signal(signal,title=\"signal SIMPLE\"):\n",
    "    xf = np.linspace(0.0,1.0,len(signal))\n",
    "    plot.plot(xf,signal)\n",
    "    plot.title(title)\n",
    "    plot.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4eb2ffa8-e8b9-42c5-a013-9c52928230d3",
   "metadata": {},
   "source": [
    "# Modulate AM function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "701016da-c5ad-483b-abd2-7234746c9366",
   "metadata": {},
   "outputs": [],
   "source": [
    "def mod_am(amplitude, signal, fc, samplerate):\n",
    "    modulated = []\n",
    "    sample_per_hz = 1.0*samplerate/fc\n",
    "    hz_step = 2*math.pi/sample_per_hz\n",
    "    start = 0.0\n",
    "    for i in range(0,len(signal)):\n",
    "        carrier = math.cos(start)\n",
    "        modulated.append(amplitude*(1+signal[i])*carrier)\n",
    "        #modulated.append(amplitude*carrier)\n",
    "        start+=hz_step\n",
    "    return modulated\n",
    "\n",
    "def generate_sin(amplitude,freq,samplerate,samplenum, noise=True):\n",
    "    ret = []\n",
    "    gausian = []\n",
    "    sample_per_hz = 1.0*samplerate/freq\n",
    "    hz_step = 2*math.pi/sample_per_hz\n",
    "    start = 0.0\n",
    "    if noise:\n",
    "        gausian = np.random.normal(0,0.1,samplenum)\n",
    "    for i in range(0,samplenum):\n",
    "        if noise:\n",
    "            ret.append(amplitude*math.cos(start)+gausian[i])\n",
    "        else:\n",
    "            ret.append(amplitude*math.cos(start))\n",
    "        start += hz_step\n",
    "    return ret\n",
    "\n",
    "def generate_sin_c(amplitude,freq,samplerate,samplenum, noise=True):\n",
    "    ret = []\n",
    "    gausian = []\n",
    "    sample_per_hz = 1.0*samplerate/freq\n",
    "    hz_step = 2*math.pi/sample_per_hz\n",
    "    start = 0.0\n",
    "    if noise:\n",
    "        gausian = np.random.normal(0,0.1,samplenum)\n",
    "    for i in range(0,samplenum):\n",
    "        if noise:\n",
    "            v = amplitude*math.cos(start)+gausian[i]\n",
    "            ret.append(np.complex64(v))\n",
    "        else:\n",
    "            v = amplitude*math.cos(start)\n",
    "            ret.append(np.complex64(v))\n",
    "        start += hz_step\n",
    "    return ret"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "98938978-b753-44a8-b621-afcc3fe9fe72",
   "metadata": {},
   "source": [
    "# Low pass filter for AM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b0c32191-3fdc-4a13-a5ac-49c750428daa",
   "metadata": {},
   "outputs": [],
   "source": [
    "def lpf_filter(signal,cutoff,fs=40000):\n",
    "    sos = butter(100, cutoff, 'low', fs=40000, output='sos')\n",
    "    return sosfilt(sos, signal)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "8bb2f001-793a-40d2-a990-a130b51eff40",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "signal samples 40000\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "40000\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "signal = generate_sin(0.5, 1000, 40000, 40000, False)\n",
    "print(\"signal samples\", len(signal))\n",
    "plot_signal(signal[0:1000])\n",
    "draw_fft(signal)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "ea381af4-49f6-4a47-a435-6add9457bbc4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "samples modulated =  40000\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "40000\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "am_mod = mod_am(0.5,signal, 10000, 40000)\n",
    "print(\"samples modulated = \",len(am_mod))\n",
    "plot_signal(am_mod[0:300])\n",
    "draw_fft(am_mod)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0f0fd968-63b6-437b-9752-7fdcc21e5d29",
   "metadata": {},
   "source": [
    "# Demodulate AM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "6fc15ee9-d5be-4fe4-9975-fa70a9ab7891",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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7DmV4fqGwZ8osQ0Nvk9VKnel0/7ANWE1Tq5V64NUO1wvWMPDpbTal+akxlgMOMVUbLRbWqxyfGb/pPi0BHXRjTauteGW5xKn9kzfdd2w23c0xBImWi7jz0I2G/uTcOG01GrpGT15Z48h06oaQ576pJAemkt3hOEFydW2D5WKNNxzL3nD73Ucy1Jttzo5QUtsNoaG3yVqlQTa1s0evlBXiCZKlYpV9k8muDv1W9k2OBV51oyWde7V4NPsmk8SjEnhC9nK+Qr3Z5rYtHj3AidnxbtVQkHQN/RaP/sSctYFeGIEO46eurN/gzWtec2CSV5aDX98LC1Ye5nU9jXu9P++VOcuhobfJWqXebdXvh/agVyvBDglfKtTY1yc+r5mfTAbu0S+sW6Gjg5mbDX00IsxPjHVzDUGhyxP7Gfrjs+OslOsUAx4I//xCgbmJsZtKfk92KpmCPnWUa02urG5wx8GbT0UnZtNcyJUDb5zS7/Op/Te+zydm08QiwvkR2CxNEBp6m6xWGtuGQ4BuWGc14Gak5WKtq73Tj9nxBKsBnzq0R38oe3MeAWB+KvjNqNvQNdfPo093HhOsV39u+eYcAsD0eIJMKh64kdJ//9b5/qeiYq3JSsCfxZeXiuyfGrtJFyoWjXB0Jh34e2yK0NDboNposdFo7ZiM1fetBWzoV8o1Zncw9NPpBIVqM9Akk/boD2S2MfQjUMF0KV9hKhkj0+c916qgQSeMz+fKnJy/Oc8BVvgmaI/+lWXLW761z2Z0ckTCS68slTi17+YTB1jNfEFvlqawZehF5J0i8qKInBWRj/W5/wEReUpEnhCRMyLy1p77LojI0/o+k4v3i/UN64i+c+hGe/TBHefbbUW+XO8rvKaZGdchpuA2pIX1DeYmEozFon3vn58cDUN/rE9VEFjicGBJTQTFarnOaqXBLXP9Df0tc+OcDzgG/spSiYjc3P0Mm3mEIA2pUoqzS6W+4TnQuZjgw0smGGjoRSQKfBJ4F3An8AERuXPLw/4MuFcp9Xrg54HPbrn/HUqp1yulTrtfsv+sdYz3TlU32XTwBnRto0Fbbd/UBdaxHmC1HNyGdG2t2jc+r5mfHCNfrgU6yOVSvtIdv7iV2fEE8agEqgR6vuOtn9zG0B+bSbNQqAZaYnl2ucTx2fG+G/qR6RTRiAR66lhYr1Kut3Yw9GnK9dZIlE27xY5H/2bgrFLqnFKqDnwOeKD3AUqpktrc9saB3b8F9qCN906hm1Q8SiIWYT1Ajz5ftrzgnUI3ehMIsjpoYX2Dg9uEbcAy9G0FKwHF6dttxZX8xg2DW3qJRIR9k0murwdo6Dve+oltDP2hbBKlgj11vLJU5tZtQkvxaISj06lAG8/OdV7DW3YIf0HwSW0T2DH0h4Fezc4rndtuQETeKyIvAF/G8uo1Cvi6iDwmIh/a7o+IyIc6YZ8zy8vL9lbvE2s2DL2IVbsepEevPY/ZHTx6begDDd2sVbst+/3Y1OQJxtBfL1apt9rbevRgdR4H6dFfWCkTjUjfuQOwWdEU1BrbbcWFlfK2Jw7oCNgF2AGt+wy26i1pTswGH14yhR1D368g+yaPXSn1BaXU7cB7gI/33PX9Sqn7sEI/f1dE3tbvjyilPqOUOq2UOj0/P9/vIYFhJ3Sj7w8yRq+99NmdYvSdawiq2qFYbVCsNQd69EBglTeXOpUWOxn6A5kki0F69LkyR6ZTJGL9v8L69b0WkCFdLtWoNXfeLA9mkiyuB2foL69WiEeFA310oQAOZVOIBPcamsSOob8CHO35+QiwrVizUupbwK0iMtf5+Vrn/0vAF7BCQbsKbbx38uj1/UFW3ehQx04xep1QDqrEUocStqu4geBHM17uVNNs5y3D5rSuoBJ1l1c3Bm5EQGCb0aU+c4u3cjCbYqlYC6wC7FK+wuFsalv9qkQswtzEGAtrwUuGuMWOoX8UOCUiJ0UkAbwf+FLvA0TkNum0YorIfUACWBGRcRGZ7Nw+DvwY8IzJC/CDtUqdRCxCKt6/SkQTtEevvfSdTh6JWITJsVhgMfpNGWUbHn1Ahl57mTttRgczSSr1FsVa069l3cDV1UpXLqIfk8k4k2Oxbimr3/QbUL+VQ5lg8wiX85Ud1wfW+7wwAtpQbokNeoBSqikiHwG+BkSB31RKPSsiH+7c/2ngrwEfFJEGsAH8DaWUEpH9wBc6e0AM+H2l1Fc9uhbPKFQt+YPtZAU02XQiYI++TjYdJx7def+emUgEFqPXcfeduneT8SiTyVhghn5hvcrMeILkDht7t8RyvXpTs43XbHQqQY7scOIAa6NaCCg0cjlv/d1+Iy01vaeOQdfiBZfzFe7uaNBvx8FMspu03c0MNPQASqkHgQe33Pbpnn9/AvhEn+edA+51ucbAWd9oMLWDzo3GCt00UEoN3BS8IF+u7xi20UynE4F59Np76zcYpZfZ8eDWuLhe3TZuq9H3LxaqfYXPvERLOO/k0UOweYRL+Qr7p8Z23Cx1Qv5aAGssVhusVho2PPoU3zm74tOqvCPsjLVBYaPJVHLwnjidjtNsK0oBHedzpRpz4zsbULBi+IGFboo10onoTQNHtjI9HtypY2G9umOyGDbDSysB1FhrZc9Bhv5QJhVc6Ga1smOOAzYTxgsBJDv1iWOnPAdYayzVmoHrGrklNPQ2KFTtevSWN70WUJzerkevTx5BcL1QZd/k2MATz0yAp47FQnXH+Dxs9ioEMVVMSy8MCnfsz1iaQUEkO6/s0HCmmUzGmQgoj6BPRTuFlsBKGAOBbZimCA29DQobDVtx2KCFzdY2GkyPD15nJhXvyjr4zVKx1nfM4VamAxJfqzZa5Mv1gR79VDJGPCqBdE1eWd0gEY3sKF4HVngsCOnsZqvNYqHanRa2EwczyUDKF3Xu4uA2wnqa7qkjNPR7n0K1yVTKXugGgtG7UUqxVqmTSQ326DOpOKVaM5AhKcvF2sD4PHTCSwFsmJvlnzsbKRFhdnwskO7dK6sVDmWTRLYpC9TMBVSmulyq0VY7Vy1pDmSCUSq9tlYlHpWBoc4gw0smCQ39AJRSFDYaZByFbvw3UJV6i0ZL7SilrNHXUqz6n0u4Xqh2K1Z2YjqdoNpo+z5AelMrf/AaZycSgTSeLa7vrBWkmZ+0Po9+h5d0AnhQQhuCm7W8sL7BgczgzVKXAQc9H8EtoaEfwEajRbOtbIVuNqWK/ffo7ejxaPS1+B2+KdWaVOotmx69tUa/vfrFARLKvcxNBOPR28khAMxPWI/x25DqU5GdDV0rlfrdeLawVuXg1ODNMhGLMJ2Os1wKQzd7Gm0MbSVjU8EpWK51u3fthW7Af0OvDc7WiUj9mA6og3fBgTc6O5HwPUavlGKpULNlROe6Hn1Ar6GtzWiMWrPte+PZQmFjYHxeMwqy2W4JDf0AChvWB9CORx+LRphMxgLx6Lua+TY2JD1Mw29Dr0MIcwOSiBCcyubi+gZTyRjjA8o/oePRl/31RvPlOvVWmwM7NJxp0okY44mo/6GbQpVENNLVVdqJILqg221lO/wFoaF/VVCoao/eVm9ZRwbBf49+M3Rj36Mv+FwbvOLA0E8HpLK54MAAzI5beYSyj3mERRtaQb3MBWCkrq9X2Tc1NjD+DcEY+ly5RqOlth1luZX5ibHAR1u6JTT0Ayjo0I3NNndLqth/j35TYdN+Mtb30E0nhLDTBCxNV2XT57CD3fg3bNbS+xmndxL/BmtTDcKjtxP6gmAqg7RImd01BpVHMElo6Aew6dHbM/RB6d3ov9lvxulWgkrG2lHX1GRScSISlEdv19D7HwNfXLdeQ7ub0XwQhn7d/mapPXo/12hHQbWX+ckxqo12YB3vJggN/QB0jN5OeSUQ2PCRtUqDdCK67RzWXpLxCIloJJAY/XQ6TmyA6BpYU5yyPnfH1pttcqWa/bDIuP8e/WKhSkQY2CylmZtM+OotK6UcefTZVJxYRHxdow7D7KSg2kvQaqomCA39AHToZtKG1g1ojz6A0M1Gw1YiFqxmn6lUvHttfrFSqtuKz2v87uBdKlZRyv6RvltO6+Mar69XmZsYs7VZghUaWa00fJNBKGw0qTbatjfLSER8r6VfKtQQ2XlATy9BlamaJDT0A1jfsDzlQdK/mmw6TrHqf9fpWqVOxkYiVpNJxbqnFb/IlWq2v1xghcv8NPROauhh09D7OSfYSQ4BNsNkfjkfiw5zCGB5zH6OjVwu1ZhJJ2x/p4OeeGaC0NAPoFhtDlRa7EXXf/vp5YH1RbaTiNUEoXezUqrvOLh8KxmfTx2bXbH2qm4mxmLEIuJrqM5uZ7Fm2udu7a6GjMPNyM/XcKlQs9XLodGPXdrF3bGhoR9Aqda0HbaB3u5Yf+P0axsNW12xmiAM/XKpZju2DP6vcbOixd4aRcRSAvXz1OEg/g29Qnv+rNFpVRD4L5u9XHJm6IMqDDBJaOgHUKw1mXQwQSio0sW1St1WDb3G77BIrdmiWG0ya6PiRpNJxXxd43KpRiIasZ14h85m5JMRrTZarFUajkI32bS/3dq6KsjpqcPPvFau6MzQRwMoDDBNaOgHUKo2HHr0liHz00BZypX2k7Hgv7es6+HnHHpShWrTt/rlXLHO3ETC0XSwrI8NcjqH4MiIjvsrJbFYqDI7niARs29aptOWmmqt6X3jmVKqo6Bq/zWE4KrpTBEa+gE4jdFrb9BPD6VUa9JsK8ehm0K1QbvtjxHVht6ZRx+n5ePErlyp5mgjAqs80O9Ep5PQzUwAoRsnJw7Y3Iz8eB3XNxrUW21HHj3A7PhY6NHvZUo1Z4Y+G0DoxomgmSaTiqMUlOr+GVFw7tGDf6/lctFZDgGs19yv9W02+thfYyoRZSwW8TEZ6yyHAP7qGnWH0zs09NPjcVbLu3ecYGjoB1CqOovRTwVg6J0Immm66/TJ0+saehszbTV+G/pcqeaozh/0WMbRDd2Av/pL1wtV9jv16H2czOZEQbWXoAbhmCI09DvQbitK9SYTDmL00YgwOeavgqX+gkw7DIuAn0ZUx+idJYzBnzW224qVct2xAcim4pTrLepN7/smFgtVxhNRR44HWJtR3gdvtN5sky/X2e80/t2ZPeCHxzysoZ9OW6Mtd6veTWjod6Bcb6IUTDoI3YClN+Nn/Xc3dOPEo+8YC7/WuVKqkYpHSSec5zv8WONqpU6rrWwJrvWS1fHlDe+9vWG8ZdBVLd6vTzscTpriYDOP4IfHvFS0TkVOQzcz4wmabeW7br4pQkO/AzoJ6MSjB8tA+Vlb7UTQTBNIWMSBNw+9ht77L5fuepx36I1mfQyBDZNDAP8aklYcqJP2kvVxyMxysUYyHnGUd4PgBuGYIjT0O1DqzFR1+qHIpv0tXdz06B2EbtL+atKvlOvMOojPg7+bUa44rJHyT+9mpVR3XBUEOo/gw/rK1mbppPsZrHF9k2MxXzajpU5ppZMSWthMGAcxI9gEoaHfAX1Mc1JHDx2P3sfEzdpGg/FE1FHtchAVLU4TnRNjMaIR8WWNeiao8xi9f55ezmFnsWY6nWBtw/tSWu3R25Gh3sr0eMI3j97pewz+9yOYxpZlEJF3isiLInJWRD7W5/4HROQpEXlCRM6IyFvtPneU0R69c0OfYN1HwbBVh12xAOOJqG9GFCxPyKm3LCJMJf3pju169E4NvU8efa3ZouCws1iTTVv9CMWqt59J7e06qazSTKfj5H0KfzmNz0NPHmGvGnoRiQKfBN4F3Al8QETu3PKwPwPuVUq9Hvh54LMOnjuyFLuhG2dVDlqMy68M/XrFmc4N+GtE221FvuxMoljjVwfvcqnGWCeE4AS/FCy1gXEaFgH/yhdXSjViEbE9drMXvzz6paE9en+lJExjx6N/M3BWKXVOKVUHPgc80PsApVRJbVq1cUDZfe4oU6pZX95hkrH1VpuNhj+zRJ0KmmksI+r9yWNto0GrrRxXY4B/hj7XCS05jd3q8JLXVTfDJjphM5TitZHKl+vMjDuTkNDM+FDrX2u2WN9oDOXRT4zFiEfFlzJVL7Bj6A8Dl3t+vtK57QZE5L0i8gLwZSyv3vZzO8//UCfsc2Z5ednO2j2nOGTopuvl+RQWGSZ0A/7JAOccDAXfil/ia8tDyB9AR8Ey5f2cYF0VNIxHv6mo6u0ac6X6UPF58MejH7aGHqz3WdfS70bsGPp+2/NNMQml1BeUUrcD7wE+7uS5ned/Ril1Wil1en5+3sayvEeXV447qP0G//Vu1h0Kmmn8MqK5rpFybgT8moQ1bOkidKqsPH6vtUc/bDIWvI8v58vOE+6a6bTVeFb18BTsxtDD7u6OtWPorwBHe34+Alzb7sFKqW8Bt4rInNPnjhqlarObtHSCn3o3SinWNhrdL7MT/PPohzdSvoVuSnXmHdb5a7LphA+hm+E3S99i9OX6UOsDf4TNuoZ+wnnTGbDnPfpHgVMiclJEEsD7gS/1PkBEbpNOYE5E7gMSwIqd544yxaoz+QPNlI8efbHWpOVQuVLjl0e/4iLsoA29l4ntVluRL7vw6H1QsMyVrEafdGLw8PetTCZjRMT7z+OKi9DNjA+bkT7RzAy5Gc1M7F6PfqAVU0o1ReQjwNeAKPCbSqlnReTDnfs/Dfw14IMi0gA2gL/RSc72fa5H12Icp8qVGm10/fCWdcjAybAMzVQy7nnJHVhGKhqRocJLmVScZltRqbcYH+K9sEO+XKetnJdWarLpBC8sFg2v6kb0YPVhEp2RiHgubFZttCjVmsOHbnyoU9fln8OUqEInYbxLPXpb3xyl1IPAg1tu+3TPvz8BfMLuc3cLTqdLaboxeh/0T7qCZkOEbqZSMeqtNtVGi2TcuadoF+3pRRyGwODGxi6vDP3mkX74GL3XDXLLpdpQJyJN1uPBGV1vedhkrA96N/lynXQiOvRnfXo80a0gcxrODZqwM3YHnE6X0vjZ0bmpRe98Q9KbmNcyCMPI/2r86OAdRiu/Fz8ULFdKdeaGNKKg48vevYZ5l97ypoKlt4Z+2I0IYCZtzXDwe0yoCUJDvwNOp0tpRMS3JKLuyBymvHKqs4l5LRqWKznvitX4YehNePTg7QluxUVFC3g/8tBNZRX4M8Tc0ltysVn6OCDFNKGh34FhY/Sg9W788OitD91QydiOR1/0waMf9gu2Kzx6PSfYo/e73VaslIavaAGYGff287jp0Q/3GsajESaTMU+NaL5cc+fR+9R45gWhod8Bp9OlevHNo3eTjO20qhe81kApDSd/AP559Kl4lPEhKlrAe72bQrVBs61cxein01bFiFfVS92ZwK42I29PHflSnZkhNyLwrx/BC0JDvw3DTJfqxS9Dv1qpMzkWIx51/lZO+uDRl2tNNhqtoY2ULlX1soJJa+UPU9EC3itY5lzIH2iy6QT1pneyHLlyjUTUuc57L9l0wjMjqpRyVecPPR59aOj3DpVGa6jpUhq/NOnXKw1HA0d62Zwy5Z1H79bTmxyLIeJ16KY+dHwevJe8cCMhofF6jflOaGnYzRKsZKdXHn2l3qLWbBsJ3exGTfrQ0G+D9nLdePS+xOiH7IqF3tCNh2GRkrtEZyQiTCW93TSH0crvpbthehQCMxEW8VqWY8VlRQt4ewp2W/4JkIxHScYjYdXNXmLY6VKabCpOoer9sAdL0Gw4jz4Vt+QdvAzdmPBGvQ6D5YYUNNNoZ8CrNerJTW5fQ/ByjXVXOQSwQjdeJbTdNktpsinv5u/+t8eu8M+/5E0/aWjot2HY6VKaqZRVc+v1MOH1SmOoRCxsatL7EbpxOi+2l6lUzLMO3marTb7iLnQTjQiTyZhneYRcsUZEhmuK03hu6F1UVmkyqTiFqiXpYZp8Z7N0e+rwcizjQ6+s8KfPXffkd4eGfhuGnS6l6X6xPA7frFbqrgzAZDLui0fv5gs25eEa8+U6yoX8gWYq6Z1AXK4TFnHTjen15zHvskYdeofBm19jN/zlouoGOiFZj97n1Uq92zhmmtDQb8Ow06U03dpqD0MO7bZifcihI5qpVMzT8spcqcZUMsZYbHiJhUkPTx1LLpulNJlOqM4LLG/Z5fo8TMZW6k0q9eErqzReJozdCpppvJSkzpfdOW07ERr6bRh2upTGD72bYq1JWw3XFavx0luGTg29CW/ZozXqE8ewEsWaqZR3m1HOZbMUWNVLXslybHrL7o0oeNOPkC/XScQiQ/dKaLIp7ySp3Uo07ERo6Ldh2OlSGj+mTHW7YoeM0YO33jJ0Jje59Ea9HD7iVqNc42XCeMWFVpDGyxnBm/NszYRuvEh2avkDN+Wf4G2MfjX06P1n2OlSGj+mTOnf7Sau56W3DJvNSG6YSlqiYc2WedGwnIFkMXj7OrqVP9B4FV9eMZTozKS8C3eaCotk0nFqzbbxSVj1Zptiren6VLQdoaHfhmGnS2n8aN3XX1r9BRmGSY816d3IH2j0qarkQQXTcrHGeCJKesgNXeOVR19ttCi60Hnvxas1bg4uH90YvduuWI3ugjbtwOlTzHRo6P1l2OlSmmQ8ylgs4mnrvhtBM81UKkap5k1JW73ZZn2j4TqRuCmDYN7Qu62h10yl4lTqLRqGTx26/tuN/IEmk054ZkTBhEfv3Sl41VD82yulUq3DH8bofcaNcqXG6+7YbujGZTIWNstJTdJt9HEdFvGugzdXGn6EYC9elQbmOjkEt5sleDcjOF+uDz3msJd41EqWehW6MWLoPdqMdJ4jjNH7zLDTpXrxWu9G64JMuTh5THpoRE0d6bsevQdrdCt/oPFKCVRvlmZi9DFPEp25Tvmn20QndAatGzaitaY15tBE/FuXqZpeox4KE3r0PjPsdKlerOSXd+WVa5UGU8kYsSGUKzVTHuYSlrvyBy5LAz0ckGIiWQybJyPTr2PO0GYJm52npqWKTSWLQecRDIdFuqEl96+hLmU2vWHmuzH6sGHKV4adLtVLJpVg3cPSRatZyowR9SIhq8MOrj16j0YeNlptVisN16WV4GHoxoBWkCabStBqK+NJbRNdsRovwp36ZGk0dGP4fV4NQzfBYCpGv+7hIAU3gmYar4wo9CYSTSVjvTEARjx6j8JLK6U644koKZfxb/Au2blSqhnxlsGbcKepOn+AdCJKIhrxJEY/lRxuroQdQkO/DSWXVTfgfYx+reLeo98cJ+iNR28iSac16U3Hv93Oiu3Fq3LalVLNtbSAxoswnR7oYaIqCDoNSR4ZehMevYiQSXsTXvIqPg+hoe+Lni7lNhmbSVmNPqZL7jRrlbqrrljoSSJ6sCHlOh2dbpN0kYgwMRYzLtXgdlZsL14NcTEhf6DRpz+T73XZwECPXqZSlpaMyTyCKYliTdaD8JIlaBYael9xO11K43XT1JpLQTPY1Nv3KnRjIrYMWh1ydD36ZDxCImp+KEXOgPyBxovPY747FMVQ6CaVoN5qU22Yc47y5RrRzgAbE3ghg5Av15nxKD4PoaHvi9vpUhovO/2aLasZya0nFevULnsRurFKF818eCeTMeObUXf6lQGPXkQ6SqCGQzcGwyIZDxKJOYPln+BNQ5KWP4i4kHnuJZNKeJKMDT16n3E7XUoz5WGn3/pGA6XMxB29Eg3LGZA/0HixxuVijcmxGMm4+0QndMIOBtfYbqtORcvoevSmlCs1XiSMV0rmqoJASxWbL68MY/Q+43a6lCbrUbUIbDZLuU3GgnWdpj36VluRL5sLO0x5oMljSv5AY3r4yNpGg1ZbGfPo04ko8ahZqeJ816M3FbrxILxkONGZNSwOt1FvUW20PSutBJuGXkTeKSIvishZEflYn/t/VkSe6vz3kIjc23PfBRF5WkSeEJEzJhfvFW6nS2m81KTP6046Ax8OL5QX1yp12srckX7Kg9CNKfkDjelTx0rJrBEVEeN16jnTHr0Hnaf5ct31wJFesmlL16jWNKNgqZulvFKuBBuGXkSiwCeBdwF3Ah8QkTu3POw88Hal1D3Ax4HPbLn/HUqp1yulThtYs+fohpJhp0tpulOmPAjddLUxDHTSTaW88JbNdXSCd6EbEzX0Gt15aorlktn4N5h/HfNlq87fVPhrczKbOedoxWBDF1jicGDu1NFtlgo4dPNm4KxS6pxSqg58Dnig9wFKqYeUUqudHx8Gjphdpr+YSsZqDRovNMBXDardeZHoNNnRCdZrWaw1aRtU2cyV3A0F34rpwR46/m1yjVnDeQSTdf5gPkbfMFS00Es3vGRojZvqn97IH4A9Q38YuNzz85XObdvxC8BXen5WwNdF5DER+dB2TxKRD4nIGRE5s7y8bGNZ3lE0lIyNRSNMjnkz1UcbehNxPS8GW+cM6dxoplJxlIJy3YzHXGu2WN9oGNuIYFMd0lQNeM5w6AbMa9KvGI5/jyeixAyOPFz1ICxieuSh1/IHYM/Q96tJ6vtJFpF3YBn6j/bc/P1KqfuwQj9/V0Te1u+5SqnPKKVOK6VOz8/P21iWd2yGbtwZejBfiaFZLddJxc0cmXUy1mSTiunQzabKphlDvyl/YDZG32wrNgxNH1op1YlGxHVTXC+mhfaswTLmDJSIGO2ONSlopjE9fMRk5+522DH0V4CjPT8fAa5tfZCI3AN8FnhAKbWib1dKXev8fwn4AlYoaKRxO12ql0zKm6nx+bK546hpAwWWNxqLSPco7pbNzlMzr6XJZimN6fLFlXKNmXFz9d9g/vOo12iSKYNr1A1dJlUhux69oRLL1UrdaENXP+wY+keBUyJyUkQSwPuBL/U+QESOAZ8Hfk4p9VLP7eMiMqn/DfwY8IypxXuF2+lSvXild2O1TJs1oiYTspbQlTkjZVrYzKT8gca0DMJy0WwSEaxEoqlch1KdOn+DmyWYzSNsyh8Y3NANN0JaDV1xoxv6VgYaeqVUE/gI8DXgeeAPlVLPisiHReTDnYf9KjALfGpLGeV+4Nsi8iTwCPBlpdRXjV+FYUwoV2q8Gshsatgx9Oq9my27Mxn/Nr0ZdT16g4beC4/e5PrAWqNSZl7HQrVJo6WMb0bZdMJYeMlk0YJmcixGNCLGQjeWCq13YRsAW9ZMKfUg8OCW2z7d8+9fBH6xz/POAfduvX3UKVQbrgXNNF569Mdn00Z+lxcSu6abkUxPwuomOg0aANMCcSulOsdnzLzHmt7ejoxLnSST8r+9ZFJxXrpeNPK7dC5m2uW19tLtRzC0GXmtXAlhZ2xfitWm62YpjRdqfNDRxjDt0RsN3dSZM2pEzcfop5Lm5A/AvEefM1y6CGbX2G3oMhgWAbOVQauVOplU3NUUtn6YVLD0WtAMQkPfl2K1YU7pzgM1vkarTaHaNGboTSc6lVIse+bRm9mMcqW60fWB2SEulXqTSr1lNPwFZoX2VjyqFsmmrQa+pgF5b5PTr3rJGDyp58sNT5ulIDT0fTHp0XshJKU9CVMNFlOGxwkWa03qzbbRsrt41BpgYtKjN1lxA5ubkRlv2buwCJgpDTQ1/H0r3bGMBj6PeY9UIU159EopVit1T5ulIDT0ffHC0JusXe42SxksrwRz8e9NRUPzHrOpzch0DgGsBrmJsZiRqhvTDWcaL0I3pgdamzx1mCxa6MVUwrhQbdJqK0+bpSA09DfRaLXZaLSMJWN1Emi1bFZfBMwImgGMxayhGebKAs2XLoJZqYZlw4JmGlPia157y6ZCN5PJGGMxc3kO6G1Icm9IPQvdGPLoVz1KaG8lNPRbMKVcqdFe96pB/Wr94TBVkiUine5YM0Z0qVgFYP+UYY8+ZUZls9poUaw2jZcugrlO6BXD8r+aZDzKWCxiJARmWixMkzEkMaDDIp6EbgzlEfIGpUx2IjT0Wyh2Db0Zj15/EbQXboK8B7XBUwaVF5cKlpHaN5k08vs0U8nRDouAOXVI0/K/vZjyRvNl81VB0HPqcLnGYs2bOn8wp5uvO3fD8kqf0R6jKY9ee92rBg29/pK6nRfbi1mPvkY8KkZrl0HLKbtfoxfNUhpTpYG5ktnpV72YWqPpyU0aU0bUS/lf/b12e+oIPfqAKBoO3SRiloJl3mDoxrQGOJhVsFwqVNk3mUTEbEu3FaM34dF7E/8GcwnjXKnuWdzWVBPfStmbNZqqDOo2dHkZXnK5xlUfBM0gNPQ3oT3GSZdDR3qZHk8Y9ei9GCQ8lTI3TnCpaL51HzY3I7fNZ7vBozet896LCVkO0/Nse9HVS26rWvIeevTThgak5Ct1EjGrdNhLQkO/BdMePVgftLzJ0WgV8yVjk2PmxgkuFavs8yjRaUJlM+dRRydYG2ap5j5JZ1r+txcTeYT1zjxbrzxRExum6eq0XrKGTh2rnYS26dPvVvaMoW+3Ff/wj57kj5+46ur3FA3H6AFm0vFd4dGbauq6Xqixz3DFDZgTNlsu1sim4yRi5j/+ptbohfyBxoQRXfG4LDCbdi9V3DX0Hqwxayh0ky83PI/Pwx4y9JGI8OcvLPGX5/Oufo/pqhvoePSGq25mDCc6s+kE1UabqktvudqwJjftN1xxA+ZUNnOlmifxeejt6hx+ja22Il8xq/7ZSzaVoFRr0nBx6vBK50ZjIryUr9RJRCOMexAWmUzGEXGfjLW6YkND74iDmSQLaxuufkep1rQaiAx6ezNps4Z+tdwwLmvaNVAuP7g6/u2JR2+og9cL+QPNlIGKkdVKHaW8Kf8EyBhQ2fRKuVJjImGcL1lG1IuwiB4Usu6yyMIriYat7DFDn2JhverqdxSqTaPePFge/UajxUbd/QSnaqNFqWa+2cfUHMylojc19LCpyeO2lt4L+QPN5oY5/Bq9zCGAmcEZOY8NfSaVcB//9qhZSmNi5KGlXOmtzg3sMUN/KJvkmkuP3lKuNBefh83SKRPdsV15AcNfMFNzMJcK1kY7yh59rlT30KN3r5u/KX/gkbec0hUjLjz6krf135ZHX3dVYeVV567GrbBZs9VmfcN75UrYY4b+YCZFodqkXBvemzIpaKbRXwYT4ZvNrk6PPHqXm5GXHr0JqeKNunUimpv0rloEXHrLJW/kDzQmwksrZSuhHTes867JpOI0WoqKi1OwF0ULvWTSCVcevX6ul5uRZk8Z+kNZy7gsrA/v1RcNTpfS6OPtihFD763YlfvQTZVoRDz58JrQzfdqo9SYWaO3Hr2JzWil5G0S0UR3rNdhkWzKXYzey87drewpQ38wkwLg2trwcXovPHptVHSlghtWPBhqDT3SsC5DN9cLVqLTi0HHyXiURCziKiyy5GGzFEA6ESUWEZdGtEYsIl2DbBojhr5cY86jHAK4L1/Uw3lmPF6jG8fIyzr/rewxQ2/Co/fC0FtvZM6Aofdi1inAhB547LLTb6noTQ29xuqOdZ/o9CpGLyKuVTZXOvIHXjXRmBAN89qjn+qeMIf7PG4OBffYo99o0G4Pl0fwsnN3K3vK0B/IJBFx69GbD91MjMVIxCLdJJsbciVLA9y02JWIGJmaY+nceGjoU+703r2UP9BMJWOsu9yMvKq4Abot9269US811HXCeNgQWNdb9vB1zKQTKDV8c5wXKrTbsacMfTwaYX5ibGiPvtVWlOst4x69iDA/McayAY/eq4EZYGYO5nKxxr4p84lYTcZl+7726L38crleY9n8PNutuOmO1Q1dXiWLwX3oZtNb9tajBxenju5cibC80jEHs8PX0pc86IrVzE4kzHj0RW+7Ot0Y+nqzzUq57qlH7/bUsVysMTOe8KxaBNwPH8kVa8x57OW5ea/XOg1dXlaLuC0O2FSuHOXNqMHEmPkJXf3Yc4b+UGb4WvquFv2YWY8erISsqRi9Z92ILo2ovj4vSis1bmd1LhVrnm5E4G4SllKKlbJ377HGjaH3WucGrKR2PDp8UnvVD4/eZZOhX/IHsAcNve6OHabRwgvlSs3suBmPfqXsoQaKASMK5kcI9uJ2OpJXEsq9uEkYV+otqo22Z++xJpMaXjTMj/CXiLjqjs13ZjR7KRiWcTnb1i/5A9iDhv5QNkml3hrqi7apXGneC5ibHGOlXHPV6VdrtlirNDzzSN0a0cVObmS/hzF6t7M6cz4Yeh2jH+a99rpZSuPGo9dhEe83o9jQeu/5co2pZMzTEF3WpZSEX/IHYNPQi8g7ReRFETkrIh/rc//PishTnf8eEpF77T7XNN1a+iESsl579I2WclUaqGex7s94Y0jdGlGdGzno0fqgd+CD8y+XUspKFnsYWgKrMqjealNrOn8dvW6W0rgRDVvxac5pNp0Y3ohWGp6vz+0krJHy6EUkCnwSeBdwJ/ABEblzy8POA29XSt0DfBz4jIPnGuWgi+7YUs07Q6+9SDeVN0tFy5B65THrKoJhJQYW1quMxSLedky6iIuuVRrUW23PY/RuGpJWPO7c1WRScTYaLWpN5xIDK+U6It7POXWTM8qXa54b+riehDXkGlcrdV+apcCeR/9m4KxS6pxSqg58Dnig9wFKqYeUUqudHx8Gjth9rmkOdTz6q0PU0nsauul8cd0kZK8XvI2BdwceDxlzvLa2wcGM+VmxvbjxorzuitW4kUHQHr0fyVgYfjOaSSeIetD93Esm7cbQe+/Rg9bNd/59qTZaVOqt0fHogcPA5Z6fr3Ru245fAL4y5HNdMz85RiwiQ+nSFzwM3WjjfL0wfDPXYic04sVQD+gZeDzkcXlxvcoBD8M2sLkZDRO77Wrl7wKP3suyQOhRAh1ijfmyP9Ui7vII3nv0MPwkLN2564egGdgz9P227b5ZJhF5B5ah/+gQz/2QiJwRkTPLy8s2ltWfaETYP5Ucqpa+WG2SiEaMd50C3SYiHWcfhuvFKoloxLMGi6zL1viF9Wr3ROUVbmZ16tCXlw1d4E5OeaVcZyoZ82TMYS9ZF7kOLdHgNcNOwlJKsVr2R/53WL0bP+UPwJ6hvwIc7fn5CHBt64NE5B7gs8ADSqkVJ88FUEp9Ril1Wil1en5+3s7at+XgkLX0lvyBeW8erNr8VDzqyqNf6sxi9So00g3dDOEtt9qKxUK1myPxCjdNKv6FbqzP0DBGdNnDMYe9uAmB5creSjRo9Hvt9NRRrreot9q+xL+zqcRQcyY2JRpGx9A/CpwSkZMikgDeD3yp9wEicgz4PPBzSqmXnDzXC4btjvVC0EwjIuyfGuN60U2Mvupt6aKLL/9ysUarrTjgsUffndU5xJdruVgjnYgy4UFDXC9uRMNWfDb0w2xGXuvcaIbtjs37VBUEHdmQId7nrkc/KslYpVQT+AjwNeB54A+VUs+KyIdF5MOdh/0qMAt8SkSeEJEzOz3Xg+u4gUOZJIvrVceqcoVqo3vs9oJ9U0lXHr1l6L0UDBve0Osqp0Mex+ijHfneYY7LfnTFgrv2/ZxvYZHhDH2j1WbNh9JFGH7koZ9iYdnOZ9Fpz8Sqzx69LddGKfUg8OCW2z7d8+9fBH7R7nO95mAmSb1l6a44OaavVRqeaYCDVRb59JW1oZ+/VKjxA6fchbV2whp4HBvKy9usoffWo4fhy+6WClXPwzYAsWiEyeRwZXe5Uo233DrrwapuZNgpU34mEYfNGeXL3nfuarLpOK22olRzNms6X2kggqf2ppc91xkLVugGnNfSFzY8NvSTYywWhpNnKFQbFGvN7hQtr7BK2pyHRXROxOv1wfAj3JZL3jdLaabTCcevo+589kqdtJdoRJgcogY8V7SuyY8Nc/Nk5Ox11PIH/hj64WYtr5brZFNxz0tUNXvS0B8actLU2kbDU8nQ/VNJqo32UA1J2pAezqZNL+sGsqnhuhEX16sk4xFfPJRhR7gtF7yXP9Bk03FWnRrRkn9GFDriaw7f62WfGrqgpzLI8evoj4wEDB8C87MrFvaooR+mO1YpxbrHHr2evLQ0RJz+6qo/HvOw5WK6tNLLZinNMGvcqLco1po+GnrnHr0fQ1F6GUYGIefjGnX1ktP3OleskYxHGE94L/87rEefK3k7inEre9LQz44nSMQijipvSrUmrbby1NAfmNIb0BCGXnv0097GwIdVNby2vuF5aaVmmBi9X81SmukhNqPNNfrzOg6T1PbTox8215HrVC755XSA8/BSruTf6RL2qKEXEce19Nqz0SPMvOBQVoeUnNf4X13bIBGLeO4FDOvRL65XOTDlfSIWrBh9odqg5aCqyq9mKU02Fe9WVtjFb49+mM7TXLFGKh5l3OMSVc1Qayw5K8Jww7AlycvFmufCdb3sSUMPVuWNE89Zv1FellceyCSJyKZ37oSrqxscyiSJeJy8yaaskIOT0tRmq831QtWXRCxY3rJSzhppus1SPniiYB3pCw6VQLWh96O8EoYzoss+e6LDhJeWPZzCtpVhqpdqzRaFatO3NcIeNvSHMilHejfaaHiZjI1HIxyYSnbj7U64trbhedgGLCPTVs7iokvFGm3lT2klDKdg2Q2LeNiH0Eu3q9NB4n25VPV8zGEvekawkyowKyzinyeqHQ8n5HxqOgNIxqOk4lFHp7cVn5PusIcN/cFskuudbk07aKPhddXI4ekUV4Yw9FfXNjzXkYHNSoUVByqbOuntX4zeucrmUrFKNCK+ycLqjkcn7fHLRe8Gv/cjk4pTb7apNuyfOnJF/8Ii4DyP0Gy1yVf8XeO0wwor7XSEHr0BDmZStNqq+6IOYt0Hjx7gyHTaceim2mixVKz54tHrodQ5B2MPtSS0HxsRDKeyeb1gGVGvQ1+aYTR5/Bhz2MswMgh+afFopsed5TryZWtw+byPp46ZiUS3ScsOuvxzLvTo3aPjxXYnTekvpOcefTbFYqHqKHZ7OV9BKTg5N+7hyiy6Hr2DD+6llTIAx2a8rfHXDNMxubjuveBaL8No+y/7bOidnjoarTarPnvLM+NjrG3YT7z7WRWkmRkf62rX2KFr6MNkrHt0BciCzaap9Y0GiWiElAcSxb0cnk51lR7tcj5nGdITs34YeuvD52SQ+aV8hfnJMVI+1C3DphF1Eha5tr7h6YjDrUx3PHq7R3o95jAQQ2/TSGlv2U8jOjueQCn777XfTWdgnYKdnIDD0I1BDjlsmlrfqDOVintee3u4U2LpJE5/oeMxn/DBo59OJxBxFqO/lK/45s1DTyONAyPqZ/knOPfoi7UmtWbb1xh9d1O3aeiDMFBaxsCux5wLaI3OPPo6k8mYJ3MvtmPPGvpMKk4qHrUtg2B1xXpfG3x81jKIFzvG2w7ncxVmxhO+yAvohGXOwQf3cn7DV0Mfi0Ycia8Vqk0q9ZavHv1UMkY8Ko6NqF9VQeDciOqwiJ/eshZPs3vCXA4g/j0zkWCj0WKjbm/+7nLJ36Q77GFDLyIczCZte/R+jUc7Mp0mEY1wLmff0F/IlTkx658hnZ1I2Pbo680219Y3OOqjoQdnEgN6BKOfMXoRYTqd6GqjD2LZ5zp/6Dm9OfSW/VzjzIRzj94v+QNNdzOymddaLtZ83YhgDxt6sKpArtlsmlotN3wZAhCNCMdn05xfdmDoV8q+hG00s+Njtj2oq2sbKOVfIlaTTcfJ2wzddMs/ffTowfKYnXr0fnrL0YiQTcVtV4xsess+VrR0Tx321qilBfyQP9DoaVu2N6PQozfLwUySRZse/YpPU3PAqp6x69GXa00W1quc9CERq5mdsG+gLuUrwGZIyi9mx+2XtOkOaa+nX21l1kHZnV9jDrcy7SC+nCvWGU9ESSf8kT+AzYSx7VNHqe5rfB42Tx12naOcz/IH8Cow9EvF2sDhwu22YrXiT+gG4Jb5CS6ulG2VjL14vQjA7QenvF5Wl7mJsW4J2CC0offbo5+dsH/qWFivIuKfoJnGSdndcrFGPCq+DaLQzI4n7Bson+UPwOomz6Tijl5Hvw39Zuhm8BqrDUv+wO/XcW8b+mwKpRg4vq9YtZQr/ZrfeMvcOI2W4spqZeBjX1joGPoDk14vq8vcRIJitUm1MTi5dDlfYSwW8f0oOtcx9Hba9xfXN9g3OeabtIDGiRHVXbF+hhzACo3YLV0MwohC53V0EhbxfUO3H17S1+H367i3DX3GniywTqL4Fbq5Zd4Kw7yyXBr42BcXC0yMxTjiQ1esRg8gtzPf9tJKhaMzad86TjVzEwnqLXtDXBbWq76HbcAyUFbZ5OAN02+xMI2TU4efGjK9zIzbKw7Q8gd+r3FiLEYiFrG1GQVR/gl73NDblQX2eyL7azve+XPXCgMf+/xikdcemPTV0zuQ0YZ+8JfL7xp6jf6i2AkxLa5XOeiTPHEvOna7Wh6cNPa7WUozO55gtdKwpVYa3GZkL48QhPwBWBVWc+OJ7pjFnQhC/gD2uKG369HrD9GsTxNfJpNxTsymeXaAoVdK8cJCwdewDWwOSBnUvauU4nJAht5JB6/l0ftv6J2U3VmDy/1f4/R4glZbDexJqDfbrFUawYRubOZjgqjz18xPjnX//k4EUV0Fe9zQTybjTI7FBsoVa0M/46Mn8LrDGZ65tr7jYy6sVChUm7zuUManVVno4RzXB2yQaxVrYLnfNfRg36MvVhuUak3fSyvBCovA4LK7WrPFSrkeyBrtJhL1ZhWUEc1X6gP1obQMQRCb0fxk0taI0O48Wx/nxcIeN/RghW+uDuiOzXeSUX5J2AK87tAUl/MbOwpznbmQB+D0iWm/lgVYXZ2peHSgRx9UxQ30evQ7G/rNZin/Y/R2O0+XOiGyIE4d2nAPUnnVawzC0O+bHEOpwZtRUPFvsF4XO2HEIOQP4FVg6I9MpwbKAudLdVLxqG+iXEDXS392B6/+sYurZFJxbpuf8GtZgBVzPJBJDjT0F3xWrexlptPVuTzgSK/DdkF4y7pWepDgVZBr1CWnetTidgS5Rr25LA3IGQXViwDW67hSHnzqCCoX86ow9IPKGP2SP+jl9UezRAQePp/f9jGPXsjzxuPTvle0AOyfGhsYunllqURE4MSc/4Y+Fo0wnR5cjaE9+gMBJGMzqTiJaGSgtxxU5y7Y9+h142EQpw69GS2Xdv48Xi9UmUzGfJtn28t859QxaFNfKlZ9L0WGV4GhPzydolht7phsWgnA0GdSce46nOGhs7m+9y8Vq7yyXPY9bKM5MDXYo39lucyxmTRjMX+PoZq5icF16noewf4ADL2IMD85NtBbXgyocxc6m1Fs8Ga0WKiRiEZ8DW9q7Hr0Cz5LUfeyz+aGubBe7VYD+smeN/RHpi1vcyev/nqhyn4fVQM1b7l1jicur1Gu3VwL/j+eWwLgh27f5/eyANifSbJUqO3YkHR2qcStPoeVepmfHOP6oJDDWpW5iTESsWA+6vumxmwYqCqTYzEmAvBERYT5iTFbHv2+Kf8mdPVi/9QRTL8EbBYw7LSpt9uK64VgKsBsffpF5J0i8qKInBWRj/W5/3YR+a6I1ETkH26574KIPC0iT4jIGVMLt4tuNNpJ/32pWOu+UX7y/bfN0mwrvvvKyk33ff25RY7NpHntfn9LKzVHsinqrXY37rmVZqvN+VyZ2/YFZ+gPTKUGhpcur1Y4OhPMlx8sT8+ORx/El19jnToGb0ZBectjsSiZVNzeGgP4HkPPqWOHNebKNRotFcjrONDQi0gU+CTwLuBO4AMicueWh+WBvwf8621+zTuUUq9XSp12s9hh0B791W0Mfa3ZIl+uBxLDvf/kLNPpOF94/OoNt6+W6zx0doUfvXO/7y3xmmMdEbWLK/1PQpdXN6i32twaoKE/mBk8AP7yajB1/pr9U8mBjWeLAXl5GlubUSE4bxmsNe7k0TdabZZLtcBeR51432mN3QqwAF5HOx79m4GzSqlzSqk68Dnggd4HKKWWlFKPAvaHePrEdDpOOhHd1qPXx+ogQjeJWIT3vOEwf/rc9RvGuf3Owxept9r89Omjvq9Jc3xm5wEpZ5cs+YYgQzcHMklabbVtWVuj1ebaWjVQQ79vcoz1jcaOukEL6xuBOBqafVM7G9HNCV3+f0c0g3IdS8UaSgWT0Abr1JFNx3dcox6CNJIePXAYuNzz85XObXZRwNdF5DER+dB2DxKRD4nIGRE5s7y87ODX74yIcHQ63a353op+Y4II3QD89Omj1FttPv3NVwBr4PV/fugC73jtfFcqIQgOT6eIRmTb1+2FBaur9zX7g/XoYfvO54W1Kq22CqShS6M/V9sZ0mqjxfVCrXvyDIL5iSSrlQb1Zv/SwLVKg1qzHbhHv1NYJMiqIM2BqWTXa+9HkGu0k/3pFzuwN5Ld4vuVUtdEZB/wpyLyglLqWzf9QqU+A3wG4PTp005+/0COz6a31X/Xx+qgPKo7Dk7x/jcd5T/+xTmOzKT56jMLFKoN/vcffU0g69HEoxEOZZNc2CZ08+y1Aidm00wm/ZXV7UV/YRbXN+Bo9qb79SZ1NEAj2lun3m/D0TpMgeYRpja7jPtVhFwLsPxTo4sD2m3VNyG8EGBYRHN4QHPmQqFKIhrxvSsW7Hn0V4DeGMIR4JrdP6CUutb5/xLwBaxQkK+cmBvn0kqlbyxXKzQGUX6n+Uc/cQf3HMnyT7/4DA+fy/N/vedu7jmSDWw9muMz41zaJnTz3ELBd2mGregv9XYefbdz1+ehKL3s6+jXbFd5c7kTUgzSo9dhy+1ex8t5vcbgjKguDtguTLewFly/hOZQNrWjgOLCmpWLCSLvZsfQPwqcEpGTIpIA3g98yc4vF5FxEZnU/wZ+DHhm2MUOy4nZceqtdt/5sYudXXY6HZxnmknF+fz/9hb+6MN/hYf/0Q/z028KLjbfy7HZNBf7hG4K1QaX8hXuPOTfMJR+TKetGvDtjsuXVyvEoxLol18b0e0kn3XZb5Ae/eFsp2BhGyPVXWOAm5E+aey0xslkjKmU/yWqmsPTKdY3LG2lflxbC67Of6ChV0o1gY8AXwOeB/5QKfWsiHxYRD4MICIHROQK8CvAPxGRKyIyBewHvi0iTwKPAF9WSn3Vq4vZDt25eSF3s9FaKtTYN+X/wIetRCLCm07MBNIevR23zI2zVmnc1H36fEd1M2hDL2IZ8e080Qu5Mkem00QDqP3WzIwnGItFtp1dfDm/QTwq7A9AuVJzuOOpb1eZdjlfYXIsRjZAZ2iQoddy2UF+jwfJol8MSOkV7MXoUUo9CDy45bZP9/x7ESuks5UCcK+bBZrgZGew9vmVMm89NXfDfdfWgq14GGW0IX/mWoG3v2a+e/sTl9cAuCvg0A1YcePtvlhnl0qB1vmDtRkdnk5xeZuk9uXVCoezqUAakTQTYzEyqThX17YvpT0SsBHVm9F27/WlfIXXBNRzojmctezI1bWNm9ZSqTdZLtZ8n62s2fOdsQD7J5Mk4xEu9knIXlypcNzHwdu7CR2Df+bqjcJrf3k+zy3z4yNx+jg5N94VV+ul2WpzYSXYhi7N0ek0l7fpzL6yuhFoVZDmcDa1o0d/NMD4PMBUR3K83xrbbcXl1Y1Ay2hhZ49+M18UjK15VRj6SEQ4MTt+0+i+jXqLxUKVkwGIcu0GMqk4x2fTNxj6Vlvx6IU895+cCXBlm5ycGydXqt+kZXQxX6HRUr4rf/bj6Eyqm9DcyuV8JdAkp+bwNiqvSqmR2Yy2kxxfKtaoN9uBr3HfZJJYRPoaet14eDygNb4qDD1YZYwvLBZvuE17gqFHvz13Hc7wdI+hf36hQLHa5P6TswGuahMdlruw5bT28nVrUx8Vj359o0GheuNmlC/XyZfrgTadabRHv1XbKFeqs9FoBe7Rw/abUZBzEXqJRix5736b+iVt6MPQjbfcfmCShfUqaz0T77Vx0MYi5GbuPZLhyupG10v5ny9YYmv33zIaHr0etH5+i6HXp7cgJRo02tPcGqfX3cWjsBkdmU5RrrduPhnpmQMBlqhqDmdTXMlXbtqMuv0SI3DquGV+gnO50k23X8yXmUrGyAag/gmvIkN/x0Ersfjcwuac1vOdD/GJ0NBvy4+/7gAAf/LkNZRSfP7xq9x/cibQxpRejs6kiQg3NcS9dL3IoUwyEEXIreiyxK2e3stL1glzVAw93LzGlzono1P7gk10Atw6P06x1rypy/h8rkQ0IhwOQP53K7fNT/DKUvmmYetB5wJfdYb+hYXN8M2FXJm5ibGRMAajyvHZcV5/NMsXn7jGd19Z4XyuzPve2K/AKhjGYlGOTKdv8uifvLzG3UeCrwqCzRr5S/kb13h2qUQqHuXQCGyaerM5u3xjePOl60XSiehIGNFTnUqWl5du9JhfXCxyy9x4YFLUvdy6b5yNRqvbTax56XqRUwHKhQT/yvjE/OQYcxOJGzz6l66XuCX05gfy108f4fmFAn/ztx7hUCbJT9x9MOgl3cBt+ya62jtgxb4vrFR4w7FghrZsJZOKMzeR6HrHGl3+GWRppeb47DjxqPDi4o1rfHmpyKkRWeMpvRltMfTPLxQD1YXqRSf/e9e4UqpxvVDjzoPB9Z28agw9wBuOTfPwuRWUUlTqTZ65us4bA5rgtJv4mTcf42Pvup1T+yb5nV+8P5BRbTtx37EsLy+VuvmXJy6vAvCGPvo3QSAi3Hkow7PXCjfc/vL14Ov8NfFohFvnJ3jp+laPvtT1pINmfnKMyWSsG/ICKFYbXF3b6J7Yg+a2PpvR850oQmjofeJtr5nnyuoG53NlHru4SrOtRqZMcJQRET789lt58O//wEhUiGzl9AnrPXzsomXgH7+0RjQiIxO6AetLfnap2FWIXFjfYLFQ5a7Do7PGU/snebGnMm2tUme5WAtUobQXEeHUvokbjKjemIIa0LOV2YkxptPxG9b43IJVtRbkZvSqMvRvP2V1d37zpWX+8lyeaES6RiJk93LvkSzxqPDoBcvQ/88Xl7jrcIZ0YnROHq87NEWjpbre6JnOWt80QifK1+6f4OraRler5Zmr1gnktQdGw1sGKyn80vVSt/JGe8u3HxwNQw9w95Es37u02v35+YUiBzNJpgNQrdS8qgz9sdk0t8yN8wePXua/P3WNuw5nwkTsHiCViHLX4QzfeHGJ564VeOZqgfe8/lDQy7oBLSehwzdnLuRJJ6KBHue3otv2n+us8aFXcsQiwhuPj85m9Mbj0+TL9W6+45HzeeYmEiORLNZ83y0zvHS9xHLRmrn86IV84Ce3V5WhB/gnf/UOXlgscilf4aM//tqglxNiiP/1/uO8sFjk733uceJR4YHXO5mN4z0nZsfJpuN8++UcAI9eWOUNx7LEoqPzFbz/5CzRiPDNl6xeiYdeWeHeo9mRcoa+v6NV9RcvL9NqK7718jJve8184KKEvfyVW6xmwofPrfD8QpErqxv8yB37Al3T6HzKfOKHbt/Pv3rfPfy7D7yBt9w2N/gJIbuC977hMHcdnuJ8rsxH3nGKmQCPyf2IRoR3332Qrz+3yCPn8zy3UOCtt80PfqKPZNJxTh+f5s+eX6JQbfDUlTXecutodEBrDmdT3DI3znfO5njyyhprlQY/+NpgjehW7u5ECr7x4jJff24REfjhO/YHuqbR2ap95K8HOIs1xBsiEeF3fv5+NhqtvlOSRoGfuu8wv/eXl/il33uMibEYP/PmY0Ev6SZ++I59/NqDL/DxP3mOtmLkjChYRRW//8gl6q020YjwtlOj5bDFohF+6r7D/O7DF5lKxXnT8RnmJoIVAHzVefQhe5fp8cTIGnmA+45N8943HGZ9o8EvvPUkmQD13bfjJ+89xNxEgj967ArvvufgSMXnNX/3HbcxnY7znbMr/MqPviYwWYGd+D9+/LUczKQYT8T4tZ+6O+jlIFt1I0aB06dPqzNnzgS9jJAQT2h2PNFRiiv3cjlf4be+c4FfesetgXui2/HS9SJnLqzygTcfHdnXcb3SIB4T36q/ROQxpdTpvveFhj4kJCRk97OToQ9DNyEhISF7nNDQh4SEhOxxQkMfEhISsscJDX1ISEjIHic09CEhISF7nNDQh4SEhOxxQkMfEhISsscJDX1ISEjIHmckG6ZEZBm4OOTT54CcweXsBsJr3vu82q4Xwmt2ynGlVF+lvJE09G4QkTPbdYftVcJr3vu82q4Xwms2SRi6CQkJCdnjhIY+JCQkZI+zFw39Z4JeQACE17z3ebVdL4TXbIw9F6MPCQkJCbmRvejRh4SEhIT0EBr6kJCQkD3OrjT0IvJOEXlRRM6KyMf63C8i8u869z8lIvcFsU6T2Ljmn+1c61Mi8pCI3BvEOk0y6Jp7HvcmEWmJyPv8XJ8X2LlmEflBEXlCRJ4VkW/6vUbT2PhsZ0TkT0Tkyc41/+0g1mkKEflNEVkSkWe2ud+8/VJK7ar/gCjwCnALkACeBO7c8pifAL4CCPB9wF8GvW4frvktwHTn3+96NVxzz+P+HHgQeF/Q6/bhfc4CzwHHOj/vC3rdPlzzPwY+0fn3PJAHEkGv3cU1vw24D3hmm/uN26/d6NG/GTirlDqnlKoDnwMe2PKYB4DfVhYPA1kROej3Qg0y8JqVUg8ppVY7Pz4MHPF5jaax8z4D/DLw34AlPxfnEXau+WeAzyulLgEopXb7ddu5ZgVMijUcdgLL0Df9XaY5lFLfwrqG7TBuv3ajoT8MXO75+UrnNqeP2U04vZ5fwPIIdjMDr1lEDgPvBT7t47q8xM77/BpgWkS+ISKPicgHfVudN9i55n8P3AFcA54G/r5Squ3P8gLBuP3yZzy5WfqNfN9aI2rnMbsJ29cjIu/AMvRv9XRF3mPnmn8d+KhSqmU5e7seO9ccA94I/DCQAr4rIg8rpV7yenEeYeeafxx4Avgh4FbgT0XkL5RSBY/XFhTG7dduNPRXgKM9Px/B2umdPmY3Yet6ROQe4LPAu5RSKz6tzSvsXPNp4HMdIz8H/ISINJVSX/Rlheax+9nOKaXKQFlEvgXcC+xWQ2/nmv828C+VFcA+KyLngduBR/xZou8Yt1+7MXTzKHBKRE6KSAJ4P/ClLY/5EvDBTvb6+4B1pdSC3ws1yMBrFpFjwOeBn9vF3l0vA69ZKXVSKXVCKXUC+K/AL+1iIw/2Ptt/DPyAiMREJA3cDzzv8zpNYueaL2GdYBCR/cBrgXO+rtJfjNuvXefRK6WaIvIR4GtYGfvfVEo9KyIf7tz/aawKjJ8AzgIVLI9g12Lzmn8VmAU+1fFwm2oXK//ZvOY9hZ1rVko9LyJfBZ4C2sBnlVJ9y/R2Azbf548D/0lEnsYKa3xUKbVr5YtF5L8APwjMicgV4J8BcfDOfoUSCCEhISF7nN0YugkJCQkJcUBo6ENCQkL2OKGhDwkJCdnjhIY+JCQkZI8TGvqQkJCQPU5o6ENCQkL2OKGhDwkJCdnj/P+e6ei60g97gAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "40000\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#am_demod = lpf_filter(am_mod,cutoff=1000)\n",
    "am_demod = mod_am(1.0,am_mod, 10000, 40000)\n",
    "am_demod = lpf_filter(am_demod,cutoff=2000)\n",
    "plot_signal(am_demod[300:600])\n",
    "draw_fft(signal)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5b796105-f1f4-41fa-99ea-9d97e588f7c9",
   "metadata": {},
   "source": [
    "# Testing AM generator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "349baaf0-f088-4dd7-9b0c-04fba1c7777a",
   "metadata": {},
   "outputs": [],
   "source": [
    "SAMPLE_TOTAL=128\n",
    "FILE_IN_S8=\"../out/signal_for_am_1000.s8\"\n",
    "FILE_OUT_S8=\"../out/modulated_am_1000.s8\"\n",
    "signal_s8 = np.fromfile(FILE_IN_S8, np.int8, count=SAMPLE_TOTAL*2).astype(np.float32).view(np.complex64)\n",
    "modulated_s8 = np.fromfile(FILE_OUT_S8, np.int8, count=SAMPLE_TOTAL*2).astype(np.float32).view(np.complex64)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "bf8f44a2-4210-4fd7-8f19-3c8c2bf14ac9",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/fam/downloads/ML/install/anaconda3/lib/python3.9/site-packages/numpy/core/_asarray.py:102: ComplexWarning: Casting complex values to real discards the imaginary part\n",
      "  return array(a, dtype, copy=False, order=order)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "128\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_signal(signal_s8[:48])\n",
    "draw_fft(signal_s8)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d93d1ed9-3892-4008-9efb-47a187e477be",
   "metadata": {},
   "source": [
    "## Modulated signal\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c6c6163a-fc6c-4207-926a-49f44804a176",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/fam/downloads/ML/install/anaconda3/lib/python3.9/site-packages/numpy/core/_asarray.py:102: ComplexWarning: Casting complex values to real discards the imaginary part\n",
      "  return array(a, dtype, copy=False, order=order)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "ename": "ValueError",
     "evalue": "invalid number of data points (0) specified",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m/tmp/ipykernel_14722/1489789555.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0mplot_signal\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodulated_s8\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mdraw_fft\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodulated_s8\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/tmp/ipykernel_14722/4228001597.py\u001b[0m in \u001b[0;36mdraw_fft\u001b[0;34m(signal, title)\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mdraw_fft\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msignal\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mtitle\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"just FFT\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m     \u001b[0mlen_signal\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msignal\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m     \u001b[0myfft\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mscipy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfft\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfft\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msignal\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mnorm\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"forward\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      5\u001b[0m     \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0myfft\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msize\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m     \u001b[0mxf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlinspace\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0.0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m1.0\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m2.0\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1.0\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0mlen_signal\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlen_signal\u001b[0m\u001b[0;34m//\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/downloads/ML/install/anaconda3/lib/python3.9/site-packages/scipy/fft/_backend.py\u001b[0m in \u001b[0;36m__ua_function__\u001b[0;34m(method, args, kwargs)\u001b[0m\n\u001b[1;32m     21\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mfn\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     22\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mNotImplemented\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 23\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mfn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     24\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     25\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/downloads/ML/install/anaconda3/lib/python3.9/site-packages/scipy/fft/_pocketfft/basic.py\u001b[0m in \u001b[0;36mc2c\u001b[0;34m(forward, x, n, axis, norm, overwrite_x, workers, plan)\u001b[0m\n\u001b[1;32m     24\u001b[0m         \u001b[0moverwrite_x\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0moverwrite_x\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mcopied\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     25\u001b[0m     \u001b[0;32melif\u001b[0m \u001b[0mtmp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m<\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 26\u001b[0;31m         raise ValueError(\"invalid number of data points ({0}) specified\"\n\u001b[0m\u001b[1;32m     27\u001b[0m                          .format(tmp.shape[axis]))\n\u001b[1;32m     28\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: invalid number of data points (0) specified"
     ]
    }
   ],
   "source": [
    "plot_signal(modulated_s8)\n",
    "draw_fft(modulated_s8)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ea3795b9-2ab7-4e23-8533-da0c0b1d07de",
   "metadata": {},
   "source": [
    "# Demodulate Radio station"
   ]
  },
  {
   "cell_type": "raw",
   "id": "954a5b6d-5937-47ce-b373-3a244acea524",
   "metadata": {},
   "source": [
    "File will be not provided record your own AM staton recording. \n",
    "Sample rate 768KHz"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "5f030859-89f6-472a-9ad2-43fcb197ae8a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loaded 768000 samples\n"
     ]
    }
   ],
   "source": [
    "#FILE_AM_STATION = \"AM_rec_307000Hz.wav\"\n",
    "FILE_AM_STATION = \"08-27-17_7050410Hz_int16.wav\"\n",
    "#32bit float, 768000 sampling rate\n",
    "am_radio_s16 = np.fromfile(FILE_AM_STATION, np.int16,count=768000*2).astype(np.float32).view(np.complex64)\n",
    "print(\"Loaded %d samples\"%(len(am_radio_s16)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "6eb4791b-5cf5-42c6-9775-9cf9c4d8ce04",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "768000\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "768000\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "draw_fft(am_radio_s16)\n",
    "draw_fft2(am_radio_s16)\n",
    "#draw_fft3(am_radio_s16)\n",
    "#draw_fft4(am_radio_s16)\n",
    "draw_fft5(am_radio_s16,fc=7050410,bw=610000,sr=768000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "0f801e88-9118-4f08-a533-be1b42f8eea9",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "768000\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "768000\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "768000\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "768000\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWoAAAEVCAYAAADJrK/3AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/MnkTPAAAACXBIWXMAAAsTAAALEwEAmpwYAAAVJUlEQVR4nO3de5AdZZ3G8efJDYQkgjIotyQLCqiUcomIsrqAFyKrsl7AsIoLIpRbBaW1i4q66lpigVrl3hDcLAKCC5QIKAIaUYkQCZcJJEBCwgIBEoFkArmHXGbmt3+cTnKYM5czmenut+d8P1Wnck53n+7fO0meec973u52RAgAkK5RZRcAAOgfQQ0AiSOoASBxBDUAJI6gBoDEEdQAkDiCGkmzfYjth2yvs91t+xvZ8uNsLyuxrjNszy7r+GgtBDVS92VJsyJiQkSMiojv9LaR7adtv6/g2oBCENRI3WRJC/I8gGv4v4Bk8Y8TybL9R0nHS7rE9nrb19q+sJftrpE0SdKvs+2+nC0/xvY9tlfbnm/7uLr3zLL9Xdt/lrRR0oG2D7V9h+2XbC+2fWrd9q+1fYvttbbvl3RQro0H6hDUSFZEnCDpbknnRsR4SVv62O50Sc9K+nBEjI+I79veT9Jtki6U9BpJ50u60XZb3VtPl3SOpAmSOiTdIelaSXtLOk3Spbbfkm37I0mbJO0j6bPZAyhEbkFt+wrbK2w/Ogz7Otz2HNsLbD9s+5N16+62PS97PGf7l0M9HkaET0u6PSJuj4juiLhDUrukk+q2uSoiFkREp6Rpkp6OiCsjojMiHpR0o6RP2B4t6eOSvhkRGyLiUUk/Lbg9aGFjctz3VZIukXT1MOxro6TPRMT/2d5X0lzbMyNidUS8e9tGtm+U9KthOB6qb7KkU2x/uG7ZWEl31r1e2mP7d9heXbdsjKRrJLVlz+u3f2ZYqwX6kVtQR8RdtqfUL7N9kGofIdtUC9+zI2JRE/t6vO75c7ZXZPtYXbfvCZJOkHTmcNSPyul5Gcilkq6JiLObfM9SSX+KiPf33CjrUXdKOkDStn+vk4ZQKzAoRY9Rz5B0XkQcpdqY4aWD3YHtoyWNk/Rkj1UflfSHiFg75CpRRcslHVj3+meSPmz7RNujbe+azb3ev4/33yrpYNun2x6bPd5u+00R0SXpJkn/ans322+W9A/5NgfYobCgtj1e0rsk3WB7nqT/Vu2LGdn+mO1He3nM7LGPfVT7KHpmRHT3OMRpkq7LvSFI1UWS/iWb4XF+RCyVdLKkr6n2ReFSSV9SH//mI2KdpA9Imi7pOUkvSPqepF2yTc6VND5bfpWkK3NrCdCD87xxQDb0cWtEHGZ7oqTFEbHPTu5roqRZki6KiBt6rHutpMcl7RcRm4ZWNQCkpbAedTYkscT2KdL2kwze1sx7bY+TdLOkq3uGdOYU1X4hENIARpw8p+ddJ2mOpENsL7N9lqRPSTrL9nzVzjY7ucndnSrpPZLOqJuKd3jd+uli2APACJXr0AcAYOg4MxEAEpfLPOq99torpkyZkseuAWBEmjt37sqIaOttXS5BPWXKFLW3t+exawAYkWz3ebYrQx8AkDiCGgASR1ADQOIIagBIHEENAIkjqAEgcQQ1ACQuqaCetXiFlq3aWHYZAJCUpIL6jCsf0Af+7a6yywCAQVvz8lYtfSmfjmZSQS1JG7d0lV0CAAzaSf9xt979/TsH3nAnJBfUAFBFf1n9cm77zvMu5IM2fpcxOnXqAWWXAQBJSapH7bILAIAEJRXUAIBGyQV1iDvOAEC9tIKasQ8AaJBWUAMAGhDUAJC45IKam6IDwCslFdQMUQNAo6SCuqc8z/QBgKpINqivv/9ZHXvxH3XNvX3emBcAWkJSQW3vGPz4+i8flSR9I/sTAFpVUkENAGhEUAPATlq1YYse/cua3I+TXFAH8/MAVMTHL7tHH/qv2bkfJ6mgNvPzAFREV3foqZUbCjlWUkENAFVx2awnCjtWckG9beCDzjWAlC1evr6wYzUd1LZH237I9q15FUM4A6iKzVuLu7/rYHrUX5D0WF6FAECV/G7h8sKO1VRQ295f0t9KujzfcnZclKmL2R8AIKn5HvW/S/qypO6+NrB9ju122+0dHR07Vcy2MxO3dnVzFT0AyAwY1LY/JGlFRMztb7uImBERUyNialtb25CK2lTg2A8ApK6ZHvWxkj5i+2lJ10s6wfbPcq0KALDdgEEdEV+NiP0jYoqk6ZL+GBGfzqsgbm4LAK+U1DzqbdPziGoA2GHMYDaOiFmSZuVSySuOk/cRAKA6kupRS4Q0APSUVFBzUSYAaJRUUG9HrxoAtksuqMloAHilxIK6NvbBFD0A2CGxoAYA9JRkUDPzAwB2SC6oCWkAeKWkgprpeQCqaOX6zbnuP6mg3oZONYAqmXrh73Pdf4JBHQrGPwBgu6SCmpEPAGg0qIsyFeG6+5fq1oefL7sMAEhGUj3qbdZt6iy7BABIRpJBDQDYIamgZnoeADRKKqgBAI0IagBIXFJBbSboAUCDpIIaANCIoAaAxCUV1Mz6AIBGSQU1AKARQQ0AiSOoASBxSQU1Q9QA0CipoAYANCKoASBxSQW1mZ8HAA2SCmoAQCOCGgASl1RQd3NTWwBokFRQP79mU9klAEBykgpqAECjAYPa9q6277c93/YC298uojAAQM2YJrbZLOmEiFhve6yk2bZ/ExH35lwbAEBNBHVEhKT12cux2YNv/QCgIE2NUdsebXuepBWS7oiI+3KtCgCwXVNBHRFdEXG4pP0lHW37sJ7b2D7Hdrvt9o6OjmEuEwBa16BmfUTEakmzJE3rZd2MiJgaEVPb2tqGpzoAQFOzPtps75E9f5Wk90lalHNdDS76zWOacsFt6u5meBxAa2lm1sc+kn5qe7Rqwf7ziLg137Ia/eTuJZKkrgiN4srVAFpIM7M+HpZ0RAG1AAB6UYkzE595cYM6GfIA0KIqEdTTZ3BuDYBybens1icuu0ftT79U+LErEdTrN3eWXQKAFvf0ixvU/swqffWmRwo/diWCmvMgAbSyagQ1ACSijH5jJYK6/gfDxDwAZSgze6oR1Nz5BUALq0RQ1yOyAbSaSgQ14QwgFas3blFXwed1VCOoSWoAiVi5fot+MHNxocesRFADQNlc923i7xa8UOixKxHUL2/tKrsEANiu6A/5lQjqegyDACjbkpUbCj1e5YIaAMqwYt3m0o5NUANAE/7+f8q7VSxBDQCJSyqo37D3+LJLAIDkJBXUzQhOfwHQYioX1ADQapIK6mYuvtTZRY8aQGtJKqib8dFL/1x2CQBQqMoF9ePL15ddAgAUqnJBDQCtJqmgZvQZABolFdQAgEYENQAkjqAGgMSlFdQMUgNAg7SCGgDQgKAGgMQR1ACQuKSCupv7bAFAg6SCGgDQKKmgpj8NAI2SCmoAQKMBg9r2AbbvtP2Y7QW2v1BEYQCAmjFNbNMp6Z8j4kHbEyTNtX1HRCwc7mL4LhEAGg3Yo46I5yPiwez5OkmPSdovj2K4HyIANBrUGLXtKZKOkHRfL+vOsd1uu72jo2OYygMANB3UtsdLulHSFyNibc/1ETEjIqZGxNS2trbhrBEAWlpTQW17rGoh/b8RcVNexTBGDQCNmpn1YUk/kfRYRPwwz2IIagBo1EyP+lhJp0s6wfa87HFSznUBADIDTs+LiNmSXEAtAIBeJHVmYjD2AQANkgpqAECjpIKa/jQANEoqqAEAjZIKaoaoAaBRWkHN4AcANEgqqAEAjZIK6uVrN5ddAgAkJ6mgBgA0IqgBIHEENQAkjqAGgMQR1ACQOIIaABJHUANA4ghqAEgcQQ0AiSOoASBxBDUAJI6gBoDEEdQAkDiCGgASR1ADQOIIagBIXCWDOri5IoAWUsmg7uomqAG0jkoGte2ySwCAwlQyqLsZ+gDQQioZ1CvXcxNcAK2jkkFNhxpAkVZt2FLq8asZ1GUXAKClPLfm5VKPX8mg7mbWB4ACjSp5AkM1g5qxDwAFIqh3Ah1qAEUaVfKM4AGD2vYVtlfYfrSIgppBjxpAkco+d6OZHvVVkqblXMegcAo5gCKV3TkcMKgj4i5JLxVQS9MY+gBQpIeeXVXq8YdtjNr2Obbbbbd3dHQM1257xbU+ALSSYQvqiJgREVMjYmpbW9tw7bZX6zZ15rp/AKhX9mhrJWd9rNu0tewSAKAwlQxqRj4AtJJmpuddJ2mOpENsL7N9Vv5l9Y9ZHwCKVHbncMxAG0TEaUUUMhhlT5UB0FrmLR0hsz6K1NVddgUAWknZmVPJoA6unweghVQyqJlHDaCVVDKol6zcUHYJAFCYSgb13GfKHdgH0FrKHm6tZFB3djH0AaB1VDKou5ieB6BInEI+eJ1lz5UB0FLK7hpWMqiZ9QGgSGWfDV3JoJ6/bE3ZJQBAYSoZ1ABQpNlPvFjq8QlqAOjHuk1btXL95lJrIKgBoB+bO8ufvFDZoC57cB9Aa0jhap2VDWomfgAoQnf5HerqBnVnCj89ACPekx3ryy6hukHNXGoARdiSwAl2lQ3qToIaQAHGjS4/JsuvYCdtTeCbWAAj3+sm7lJ2CdUNaq5JDaAIWxO4Wmdlg3rVxq1llwCgBWza2lV2CdUN6pcT+OEBGPnGMka98/Z99a5llwCgBewypvyYLL+CncT0PABFuPHBv5RdQnWDer89X1V2CQBaQAo3KqlsUHODWwBF4ISXIZi54IWySwDQAn6/cHnZJVQ3qOc8We6FvAG0hiMm7Vl2CdUN6hSuEQtg5JvzVPmdwsoG9cYtzKMGkL+XNmwpu4S0g/o1u48ruwQAKF3SQf35vzlQh+03sewyALSogU4fP+3oSYXUkXRQS9LBe0/oc92UC24rsBIArebQb/y23/VFnSGddFBPL+i3FQDsjM8fd1Ahx0k6qCfuOlacKA4gVWNHj9IDX39f7sdpKqhtT7O92PYTti/Iu6jBeHH95rJLADDCRIRmLV7R1LZtE/K/scCYgTawPVrSjyS9X9IySQ/YviUiFuZZ2KTX7CZJet3E/seAjrrw95KkBd8+UbvvMmBzAKBfGzZ36i3fmtnn+iMm7aGHnl2tIyft0bDuqx88NJeamkm2oyU9ERFPSZLt6yWdLGnYg/ras9+hi25fpH887iAdNbl2NtA/vf9g7T1hF00/+gD98HeP6/LZS3p9b38/2Mmv3U1jRlm2h7tkABUQEYqQuiPUnf2543Vo+drmP5lfd/Yx+trNj+jij711+7JF35mmH//pSZ1x7JQcqpcc0f8osO1PSJoWEZ/LXp8u6R0RcW6P7c6RdI4kTZo06ahnnnkml4IfWbZGDy2tXZDpm79a0NR7pr3l9Ro9ipAGWtmoUdYoS6NsOftz2+vrH1ja5/vOeNcUHTl5T+0+brTe+6bX5Vaf7bkRMbXXdU0E9SmSTuwR1EdHxHl9vWfq1KnR3t4+hJIBoLX0F9TNfJm4TNIBda/3l/TccBQGABhYM0H9gKQ32v4r2+MkTZd0S75lAQC2GfDLxIjotH2upJmSRku6IiKaGxwGAAxZU/PZIuJ2SbfnXAsAoBdJn5kIACCoASB5BDUAJI6gBoDEDXjCy07t1O6QlM+picNrL0kryy5iGNCOtNCOtFSlHZMjoq23FbkEdVXYbu/rTKAqoR1poR1pGQntYOgDABJHUANA4lo9qGeUXcAwoR1poR1pqXw7WnqMGgCqoNV71ACQPIIaABLXEkFtew/bv7C9yPZjtt/ZY/2rbf/a9nzbC2yfWVat/WmiHXvavtn2w7bvt31YWbX2xfYhtufVPdba/mKPbWz7P7ObKT9s+8iSyu1Tk+041PYc25ttn19SqX1qsg2fyv4OHrZ9j+23lVRun5psx8lZG+bZbrf91yWVu3Nq9xIb2Q9JP5X0uez5OEl79Fj/NUnfy563SXpJ0riy696JdvxA0rey54dK+kPZNQ/QntGSXlBton/98pMk/UaSJR0j6b6ya93Jduwt6e2Svivp/LLr3Mk2vEvSntnzD1b472K8dnwn91ZJi8qudTCPEd+jtj1R0nsk/USSImJLRKzusVlImuDa3W/HqxbUnUXWOZAm2/FmSX/I1i+SNMV2fjd5G7r3SnoyInqexXqypKuj5l5Je9jep/jymtZrOyJiRUQ8IGlrOWUNSl9tuCciVmUv71XtDk8p66sd6yNLaUm7q/Z/vjJGfFBLOlBSh6QrbT9k+3Lbu/fY5hJJb1LtFmOPSPpCRHQXXOdAmmnHfEkfkyTbR0uarLT/Y02XdF0vy/eTVH+30WXZslT11Y4qaaYNZ6n2SSdlfbbD9kdtL5J0m6TPFlrVELVCUI+RdKSkyyLiCEkbJF3QY5sTJc2TtK+kwyVdkvVgU9JMOy6WtKfteZLOk/SQEvtksE12W7ePSLqht9W9LEuyBzRAOyqhmTbYPl61oP5KUXUN1kDtiIibI+JQSX8n6TsFljZkrRDUyyQti4j7ste/UC3w6p0p6abso/YTkpaoNsabkgHbERFrI+LMiDhc0mdUG29fUmiVzfugpAcjYnkv66p0Q+X+2lEV/bbB9lslXS7p5Ih4sdDKBqepv4uIuEvSQbb3KqasoRvxQR0RL0haavuQbNF7JS3ssdmz2XJlY7qHSHqqsCKb0Ew7slkh47KXn5N0V0SsLbDMwThNfX/UvkXSZ7LZH8dIWhMRzxdX2qD0146q6LMNtidJuknS6RHxeKFVDV5/7XhD9h2UsllE4ySl/EvnFVrizETbh6vWIxinWgCfKemTkhQRP7a9r6SrJO2j2sfuiyPiZ6UU248m2vFOSVdL6lItxM+q+yIoGbZ3U20M+sCIWJMt+7y0vR1W7XuDaZI2SjozItrLqrcvTbTj9ZLaJU2U1C1pvaQ3p/TLs4k2XC7p49px2eLOSPBKdE204yuqfcrcKullSV+KiNll1TtYLRHUAFBlI37oAwCqjqAGgMQR1ACQOIIaABJHUAPAENm+wvYK2482uf2pthdmF4G7dsDtmfUBAENj+z2qTb+8OiL6vWql7TdK+rmkEyJile29I2JFf++hRw0AQ5Sd7fhS/TLbB9n+re25tu+2ve1s57Ml/WjbOQ4DhbREUANAXmZIOi8ijpJ0vqRLs+UHSzrY9p9t32t72kA7GpNjkQDQkmyPV+1a3jdkZ65L0i7Zn2MkvVHScapdx+Zu24f1ctni7QhqABh+oyStzi6Q1tMySfdGxFZJS2wvVi24H+hvZwCAYZRdz2WJ7VOk7beX23Ybs19KOj5bvpdqQyH9XgSOoAaAIbJ9naQ5kg6xvcz2WZI+Jeks2/MlLVDtzkWSNFPSi7YXSrpTtQtE9XslP6bnAUDi6FEDQOIIagBIHEENAIkjqAEgcQQ1ACSOoAaAxBHUAJC4/weLqfJ6OhoBoQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "signal_f = 152800\n",
    "bw=10000\n",
    "#coef_c = signal_f * (610000.0/768000.0)\n",
    "scaled = coef_c\n",
    "fc_sign = generate_sin_c(1.0, signal_f, 768000, len(am_radio_s16))\n",
    "#print(len(fc_sign))\n",
    "#am_radio_coef = butter(5,[(scaled-bw),(scaled+bw)],fs=768000,btype=\"bandpass\", output='sos')\n",
    "#am_radio_filt = sosfilt(am_radio_coef, am_radio_s16)\n",
    "draw_fft5(am_radio_s16,bw=610000,sr=768000,fc=7050410,title=\"orig\")\n",
    "draw_fft5(fc_sign,bw=610000,sr=768000,fc=7050410,title=\"orig\")\n",
    "#draw_fft5(am_radio_filt,bw=610000,sr=768000,fc=7050410,title=\"filtered\")\n",
    "am_reloc = []\n",
    "for i in range(0,len(fc_sign)):\n",
    "    am_reloc.append(fc_sign[i]*am_radio_filt[i])\n",
    "draw_fft5(am_reloc,bw=610000,sr=768000,fc=7050410,title=\"multiplied\")\n",
    "\n",
    "# do filtering after relocate the signal\n",
    "#peaks, _ = scipy.signal.find_peaks(am_radio_s16, height=1.0)\n",
    "#draw_peaks(am_radio_s16,bw=384000,sr=768000,fc=384000,title=\"pick\")\n",
    "am_radio_coef = butter(10,[bw*2],fs=768000,btype=\"lowpass\", output='sos')\n",
    "am_radio_filt = sosfilt(am_radio_coef, am_reloc)\n",
    "draw_fft5(am_radio_filt,bw=610000,sr=768000,fc=7050410,title=\"filtered\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fd19cd5c-7f5d-4c3c-ba6f-2c79307ef89d",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}