AudioDemo.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "from ConversionUtilities import *\n",
    "from matplotlib import pyplot as plt\n",
    "from IPython.display import Audio\n",
    "import numpy as np\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "def encodeLoad(load, character):\n",
    "    \"\"\"\n",
    "    Encodes the raw data in the given RTP packet with a character. The given character replaces the first byte in the\n",
    "    RTP payload.\n",
    "    @param packet: preconfigured Scapy RTP packet\n",
    "    @param character: the ascii (256bit) character to encode\n",
    "    @return: the same packet with encoded payload\n",
    "    \"\"\"          \n",
    "    return hex(ord(character))[2:] + load[2:]\n",
    "\n",
    "def encodeLoad2(rawData, message, bitCounter):\n",
    "    k = 12  # Audio begins at 12th bit of raw load\n",
    "    rawData = bytearray.fromhex(rawData)\n",
    "    while bitCounter < len(message) << 4 and k < len(rawData):\n",
    "        # Encode the least significant bit.\n",
    "        rawData[k] = rawData[k] | 1 if (ord(message[bitCounter >> 4]) >> (bitCounter & 7)) & 1 else rawData[k] & ~1\n",
    "        bitCounter += 1\n",
    "        k += 1\n",
    "    \n",
    "    return str(rawData), bitCounter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "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": {
      "text/html": [
       "\n",
       "                <audio  controls=\"controls\" >\n",
       "                    <source 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type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "file = open(\"VoicemailASCIIHex\", \"r\")  # Original voicemail file\n",
    "lines = file.readlines()\n",
    "\n",
    "originalIntensity = []\n",
    "for line in lines:\n",
    "    originalIntensity += getAudacityFormat(line)   \n",
    "\n",
    "plt.plot(np.arange(0, len(originalIntensity))/8000, originalIntensity)\n",
    "plt.title(\"Original Signal\")\n",
    "plt.show()\n",
    "\n",
    "Audio(np.array(originalIntensity), rate=8000)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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QS0/L2orj5LabOoxecrloF690VPzQo3I7LPgasKKba1Y4WomGqlVOsOPAMadN0IwTg7ZumZy097A+96ARODLTeljwfcIrc3JN25YVDzYra8My8dHTcr7uncXmG8I4Dgt+HN799U/8vu2ApfvQMqc1Xu3Zl7M3mmKPm/l0iT2he/uPFGHCjD8UJ8Rpwa4spjscKrSjBqXnDrt0rIcFPw6PffsHRrwWe1DVDLRoygyX5ZKxm9Xb7ane9di3a/Dm/D/xo8bykPG4yOLfkR7cNrvVZeb4EhZ8GUrLRKUiIjd/EEouNclg+J/WGyy6xXP3pyvwiQ0TVKy68TZKrVy3+/PDPSkzZ70el0kvIYeRVu67v/4p+/nwV3/FgaNVffJPzVyrf2eMJ2HBl2HJlv2V3odbepPnbXbCnEo88HXVIhlyN3OYvTZPkY/Hqz/lIv/QCbzw4wanTfEl8QRc7uE1c9UuK83RzAFO5GY5pgg+EQ0lovVElEtE42WWjyOiP4hoJRFlE1ErM/ZrBVv3HcHIye7I86I2YqPvxDkxl324cKtZ5gAw1gKdtmIHTpswmwdwXYAbe1ludHv5DcOCT0SJAF4DcB6AzgCuIqLOUastB5AlhOgO4AsAzxrdr1XECkczI7ujVldJrGiZYxGZDTfnH8YRGzMd/rZpn/JKjG6sGrcM/5KKS8twzVsL0SdOI8FJjrkw5bSfMKOF3wtArhBisxCiCMBUACMiVxBC/CSECE+jWwiguQn7tZXvVu5w2oRyXsqucIlcPGmBrfvWWvTCi1gRC2/GJDol1DQovlyah19z3fvQ/s8c/0ebOYkZgt8MQGSaxjzps1jcCOB7uQVEdAsR5RBRTn6+NUWw9XKi2D0Tm45HtIK4gIW/uO3jZbq+V1JahpI4vdBVeYXIHD8D411eKJ1b+NZi66AtEV0LIAvAc3LLhRCThRBZQoisjIwMO00rJ1ZD7OBx48Kq1Sl08Fj8urBuC6uzErVRLkHlyIn45+fVn8ybmOdmDhwtsqSesl8wQ/C3A2gR8b659FkliGgwgAcBDBdCuCd0RCVPzrA/hG29wmSdd3/dYsl+3fgcuZoLpsRFaXa03kyqZmLHxKoej/+Is/891/odeRQzBH8JgPZE1JqIUgCMBDA9cgUiOgXAfxES+z0m7DPQTFmyDUKIKkVF/EppmcCyvw44bYYsantZPIlUHdnr9E922y5FHtldvMVLGBZ8IUQJgDEAfgCwFsBnQog1RPQ4EQ2XVnsOQDqAz4loBRFNj7E5X2OWC6aopAw5WwtM2ZYX+FRnJS87mKtQVcou3Ngr08O2/frDRS/msE5FkszYiBBiJoCZUZ89EvF6sBn7sQMrW2LLtx3AaZn1TNnW5W/8hprV1F2+vIKjaF43TfW2rUieZoRDJoyfWAUPMipz8wc5GNqlseX72eOBsplOwzNtozhw1DpxeeK7P0zd3iGVg1NmT75yI/ESy7kBK/3XRSVlOFHi3uP/8Y/duOfz3502gwELfiWWbt2P699bYtn2/dLtdiPXvLXIvI15zOF+9r/novfT2U6b4So+y3GvG9BJWPAjWG7xwKBTrpLVHilxZ4TFf+5XXkklOVvM25Yd5BW4L02CHGqLqkxbsd3weNfc9RwbIgcLfgR2zIZ0Aq0zK4PeE9ES5RH0c6WF535Yr2q9u6auwOy1LNhWwIJvI9HisPug88Uqdrm4YAYTXCJnkL85bzOmLNaWFnzmql2BmpioFlOidBh1RP/+XprtfN6Ql2ZzqmLG3UyQ0j5f1aulpu+dKClDanKiFSZ5Fm7hR2B2FI0SbvAgydlw7dsmDoAyAKwrTr4gd68l23ULrwUkJYRdcAvfRpzsYJaUliEpserzXa7Xa/XgtZ9wes5C9jp3+bqPFZWiekqoVb2r8Dg27zVWNeyjiJDiEyWlqJakvsXOHp2qcAvfRqJ9inJtvjIT8u7L4eXkWW7oCbkVp0Ttr31HZT//55cry1/3mZiNq980r7f45HdcktEoLPgSbkguBVjXC9ga4waNRbyyiVayMu9Alc8+Wmh9Hd8weQXazlNQiZU9doOU8K+4tAxG2i5TZQZpN+WbV2M4qLDgSzztQEFnuZarWyILnlUZQmc2w1+tmg/lr/32ifC4T3lGqBnM/kN/EjQA5bmiuHNnLiz4EnbIrBott8oOrQ8Stzx47Ka4zJoUBUUWpX5wegwhFnoLuUTy5rzNld5rde2d9MgsvMoVtCrBgi8R1JaE3/3j2w8c8/Vcgz/3HnHahCqY1ViYMHMtdkRcOz2bff5/HHYcCQu+hB3Cp6Y1FtCGtWX0nThHU54ZzYXmHb5ec9e7Iz1zJG7LY/O/NbucNsE1sOBLWBUnHUm0OMjt0y1ddKeFTA+FJmQ6XbHtgHFDDOL1geP/ZNsfEVYaZ4T4g9+24keDYwp+gQVfIsGGMxH9k5QTd6uEVutmvSj4T8ywd+KcWrS6OPo985NFlliPEBWVp8wmXi88e21sQf8ldy9u/iDHAou8Bwt+Of52Zk9bsUP28ymL3dX9NkK8Quc/qZig9NWyPM37vHPKcsV1vPjwBPT1mJzqoRaXevQk2wwLvoQtPvyoO1+u2IpbxGFHoTdS7kYS79RNmqvsZnj6+3XmGROBSy6pZtZLMfVa2HHA2gHybfuPYt/hE8iPqm7lFleo2+HUCjYS/ZP8buVOR+xQw/yNHszREueeVzNGY9UzP0ghrodVVmHTw6HjJTjz2Qp315aJw8pfB+gUG4Jb+BI/uyTagVsq+ol37hY7WNRki8ZZzow8K/MqF/KZPG9T3MFapios+BJWDTRFomriFf9+daN07o4WxW99WuXWO//l+dZs2GLcPkfjqZnr8N3K0NgU3zbqYMF3iFjFT/iHqx8lwVdqDFr1sLVqlu34iERlQeXIidBAfZDcZkZgwbeRQ8crWpizVstPBnHTD9cNtmjpsu87or40odcQQmDf4crHN3WJfyKs9JJXcBQ7VPbOdxUed8Vv2klY8G1kb8QNm5Dg8v4yqraIlzjgB58wQ31SuyVbCrB1X+xUA0pn3M1S8N95m3Hqk7NjpiW2Avf/QoFJczehz8Q5+PC3rYrr9n46G2/8vFlxPT/Dgu8QsfTeStHZG9VCjA5ti+b71Tux51CF62nN9sI4a1vDzFXaIpnyCipae2pbfmH01iKwI5X0D1J6gLwDFYJfs5q1QXZumHWslnB2TSWembXOspoTXoAF3yESYoyIWdnjvOG9JZXeX//e4rjrj/lkOUa9HX8dqykzcEL6TJxT6b3SlvTua8wnsSdfKQ0UqyVchWza8ooJdNWSrb19n9TQu/IS36zY7rQJjsGCD2CnjZOMwm6RObFmfloo+FuiMiuqmSQT2WK2i1HvLEaxNNBp5ulQ8t/qDfGLl/umuETfNm/+IEfW3q8lsSorE9h72B1Fe7zGwWPGcy55FRZ8AJPn2efXu+2jpQDgSDKnaP1QI3CRE2nIpji9eRvyyyt0nYiTLkGOSAsb10qttKwkxvR7IQSOF5fieIm+aJpYZ/FESanuXsOPf+yWje4pKimDEMKWMOJ4GOl5OY1VUVNegAUfQKKNAcdKrTJLJ15FHWahypaOM75cgV827sXB4/pdIo1qVav0/qzn5JOSTZq7CZ0enoUinYJfIFMec+nWAnR8aBbmbtBfZDyWpn64cGulGadO8Ni37kxUp4anZq5T/dv3Gyz4sD86I9q1EklRSRkW5O61pMbuoeMl5TVHtfBKtv1Vg5b/dQDzNmqf/bxkS8XgXfR1PXS8BLNW76ziKnnOYDnHyIfS+l2HkLvnEHIk1928DfpTVMR60H6z3D4fdKwxiKUqB0ndSnSIq9xyNb3wgiNFWJDrnTQkLPiwf3brgOfnxlz21My1uPqtRbjmrUWW7PucF+dp/k72uj04UaLNtWKUe79YGdMFE48XZ1dUONq0p2rR61s/WlYph1G8DJtaWLMjFMF07kvzMPiFinNcYiAiZOTkhbKfL5MGcO3goa9X27YvO1G6Ko9MW4ObP8jBoRjF2sNc+/YiXP3WIpR4xE3EydPgrvw130hpjNfuPGjZPlZvL0TnJrU0fWfO2j22T7V/59c/dX2vuLQMD3+zGkeK5MVcKRxVD2OnLMfscf3L34czb85dr9+lAwDzN+bjzPYZhrZhhK+Wb8eATg0x/OSmjtlgBY9MW42Pb+pd/v75H9bj+9U7USZCvezwGEm3R/+HBunVkJaSiEPHi/HSyFPQv0PF9VizI3SfjnpnMT65uTfcDrfwEbz8NY9OX6O55WlGUWq7yNlSEHcWarEFrbFN+Udk/cKHDIxBAMCN7zlfuGOsipz/XuPX3H0oLRMoLi1DWZnAqz/lYlP+Efy590iVAfG9h0/gr/1HUXC0uDzoIpoFm/bZYbZhuIUfQHK2FqDDQ99r/t4j09ZYYI35XPWmvCskzNPfr8OMVTsxfUw/dHp4lmn7vfK/8ferh6LSMizd6lymzzC/bNyLfu0bAIg/BuUl2j4wU/N3jkq9xtw9hyq57oDQeclsUMMU26zClBY+EQ0lovVElEtE42WWVyOiT6Xli4go04z9msWm/Kq+XsbfrMwrNG1SVBg9BUPU8NA3zj9or317Ef6TvREfLdzqSIoNNyGEwMLNVc/Bf+dtwqq8QizZst/WFBhaMNzCJ6JEAK8BGAIgD8ASIpouhIiM27oRQIEQoh0RjQTwDIArje7bLDxZ7IMxzBX//c1pE1Rh5XiOFl74MTQgXr9GisOWOMuMVTtl02lMWbytUsnQyAItbsEMl04vALlCiM0AQERTAYwAECn4IwA8Kr3+AsCrRETCotR1L/64AX/EuUn2HynC0q0FGHxSQ9smEzHuY/V2dwip19hnQciwlxjzyXLUSlWWTiOF09s0qIH7zz9J9/djYYbgNwMQOUKWB+D0WOsIIUqIqBBAfQCVmtZEdAuAWwCgZcuWug164+dNSK+WhIZRMy3DhFtMv23ah5b13e1zYxjGfaQkJQKI7xI0kpYk3aLEeK4atBVCTAYwGQCysrJ0t/5LywRG9mqBe8/tJLt83Kcr8NXy7Zh6yxno1rw2MsfP0LsrxsO8fk1PT0UfOU3rBjXw0z8GYO76PRj97hLlL/iYN0ediosnLYi7zvd3nWmTNeoxQ/C3A2gR8b659JncOnlElASgNgBL4piEECgpE0hMiD0e/diILujfMQPdmte2wgRfkpRAhiYRuZGhXRs7bYIqTmpSyxV+/Blj+wEABnRs6LAl5jC6TyaIgAbp1VTPtv7pHwMwf2M+ujevU2XZJT2boX3DmujUpCbSkhNNttYczIjSWQKgPRG1JqIUACMBTI9aZzqA66TXlwGYY5X/PqxJSXEKjNRMTcaIHs3K35/eup4VpviK6/tmOm2CqTx1cTcQEUad0cppUxSZcWc/p01ASmIC0lJc5RAwRHIi4dHhXfCvC7vgjoHt0CA9lHdp8QODsO6JoTG/l1k/DaPOyESijL7cclYb3DagLQZ2bIjT29S3zHYjGBZ8IUQJgDEAfgCwFsBnQog1RPQ4EQ2XVnsbQH0iygUwDkCV0E2zKCkLTaqRuyCxePqSblaZ40p+vncAbuzXWtN3xp93Ero01TY71ylWPDIENVLit7Cu6hXqlP7rwi6m7XfpQ4NN21YkbqiOtvLRc5w2wVRSq7TARaVlix8YhFWPnoP59w3E4gcHlS+LDPJY89i5aFU/zWpTTcWUOHwhxEwhRAchRFshxATps0eEENOl18eFEJcLIdoJIXqFI3qsQNJ7TYKfnOi+CcetLZzA0ap+DU2C/8gFnZGYQKjnkXC8OmkpODeOu+a+oR3Lb1wtvxMl6qdXQ1arugCAi09pprC2d3h39GkyAultXriih/wC6efQsFYqaqYmo0W9NDSsmYrnLz8ZZ0oTz8LUqJZUqdeT6YEAEPcpnUHCLfx4Lp1ozLzpzaJfuwbKK+mgZb1Qi6Rpneqq1r9jYFvcID0cMtKrKaxtDlMM5CQJu56axzi+t0Zl4fYB7XRvX4kvbuuDLROHlQt+tEiYwdmd7POhzx7XHwNt3J8dbJk4DEM6N6r0mZKD+bJTm+PDG6ODDyuK6swY288TD0XfCX64qIcWEY9VbtAKxp7dDu/f0Ctm2FW1pAT0aFEH48+TjzAyQv8OGfjv307V9J3IcdrHRpjn/oi/T/3DO/dJkVm3D5QXdavE8se/n1Xpfal0DEbmeWTf0x+vXd2zyuevX1v1M6to1zBd9vNowfQK711/WtzlpLN0u97v2Y3vBL9El+BbZU1Vxp3TEf07ZKBXjIHi5y8/Gd/c0Rc1LIjDffKirjgpIktmtSTlyx/pt6+Zmmy6TXI0rh2aP3Gyjiiq6pLvPlZrS84fbnTQ/r6hHdG+Uc1KnzWTehi92+jfdtuMdAzr3qTK59WSnG9JntKyjtMm6CJWhJHeJka4B+cVd6fvBL9WajI+uel0TS0QJ2bbxtqjlaZEi132Pf1jrFnBBd3tTYtbMzUJbTPSsWD82fj81j748rYzdG9rlcqBxvdv6IVFDwzSPJAdjw6NamL+fQNx61ltTdumm9DiMnWaTo1DD+M+bZUjZ7Tef/8c2gnz7xtY3khxO74T/JSkBPRp1wBNaqvzUQP2tvDD3HJWG9nPrewaNkiv3ApRarE7cVP3aFEHQGiMISUpAZ2b6J8rEX18E2NEY6UmJ6JRrVTU0tmDiXXNWtRL0x1hEy1O4Z6Wmin9dnBe16o9D7cSfpBH1ziORG+UeFJiAlrU806kju8EXw9OtPBjxelaaUoVV4DCb7yuA93U6GsRZ/6cZkb2ip+uQ28hHDWuMa1EF9MIR4A8JT20nE7M5QWR2zJxGLZMHKZpjM47/RZ9sOC7DDsb1bXT4rdoP/8//e4UvUQfv50D6nrHiq/prT/vk1rkHkYnaaxa5kfaNKhRqQJVmOlj+pa/VnNZ/TWHPDYs+K7DPW0MJ4o5RB99ogbB79bMWKoMvTe9U4OoF8gM6AaNOf8YgGcv617lc7nUB2puLb9nz3WHQ9Bh3HSJPTQWZglVXTrqT8hncXoktw9QMXjqsVqXPtemKiRQRZjwgvFnl1efalQrFSmJCSgyULrSY5deN9zCBywJgZSjpQv9nrHCQ71I9TjpFDqpcH9Ydc83NTGCI3KA2OrY79rV7QnDVcvfB3cof920TvVKcwSeu7xqK18Pfn+GsuAjFNljB/+6sLPiOnZ3KUf3ybR1f0pYdfTJKnoKVrXyFtw/SHklBcLZXyN/Hlb/VO63YPKfEXq2qls+EBtNZDLEmASkFR8PFnwbUXODWnUP36bGpeECzBaxV68+BQkEDPbQzNDOMr2RRy/sjNF9MivNL9EyvuElYs2GVjraWA0qLWfJp6e0HBZ8l2HVD65vW205XT64oZc1hihi7gm4oHtTbH56mCsT5MWin0z+nfrp1fDo8C6VjqN5XfVzTfTglPjFdLEq2BNu5Q8+SXv6DIuytbsOHrQNCHIiAsR2Y/i9pSOH3jh8s1F76q0u4KJnjKB1gxr4c+8RC6xRtqdejRR8cesZhsJVvZITRy/eafb4ELniG24R2lhJs6zGLcfvKCrPgeXjPTo237tNvUqDq3p3Kxdb3zZDOUw4K7NelR4Cx+FXwILvII+P6Oq0CTEFVktqCjPxq953bRaUSVKEuwa3N7yV9yNcii9d2QNbJg5DwzipEVSh5sfl1x+gBAu+y7C7S2mn67KuwsxeQP4B9PzlJ1tgTVVuPlM+v1E8/DxvQs+h3dbfeHDA/ec7EB0UkCY+C77LqFXd3mGVOipE2CxeHnkKzlCo9SnXs7js1OYYfrL1WTvrpGnPHTT4JPOjf9ziR9aT1qJeurH8S/PvG1j+GwhPllNKAWImfncpsuC7jFNb2TsRqq9FlbXkEAAeHHZS3HVuHyjfQnRr3WG1AqFFxN0iOnrsMGp6ZFK2uwd3wGtX98QAGX++2QSkgc+CH2bkaS2cNsEyxp5tXUk/LbSuX0MxlDApRnpMu2ZDa0WtkGspkNFboRdkF3pa+EYeVjdF1SNISUrAsO5NbJ2M6JJnrWWw4Es8dbH1LUinuup/H6ItauKFK6zxmbesn6bLbRLm53sHxFz29e19dG/XCGq1qJaGNAVyESqx+O7OfqrX1Yq+Fr7+3/gD58fv/VlJUOLwWfAl9Baq8AJaW0hWZH80o5ZsvMlTZk2suk4mVDYealvBVgmKllKedhA+HXrKU1p1D2o5937PlsmCz1TBjN/8JT0r5za5oa955QOt5LERXSuFBCpR3+AgpVHCxVdG9DB/UNuI+E0bY13PQy/xeh/BaN+z4DNWEXUH9W3nDr+0GrS0CP9xbkd129RrjAKtG9TAExd1rTQYfq1JBVmMNrjfvf403KPRneg0/m7fs+AzFnGyVJs2jF+7yqkq3V9K4ah6ISL8rXcrNKxZMSmpW7PaODNGKg1N29Yhf5GXeWDHhjilZV3DdthBQFz4LPiMNtRWWYr02a99fKjq7bvhsaDl3lf7HLvmdOvLIEby1nVZhrehp4Uf/ZAIn59OjWsatscOfNouKYcF34PcPbg9+rStj5vPtN8vrmdAN15hEi3YdTP2bFEXddKSTS0AYmcPZ2DHhqiWlIhxBt0puqJ0or7TrXlt1KuR4oo0IvGS47klcZ7VsOBHYHkrxKR7/sKTm+KTm3vjwWGdsWXiMHRoZF+isyDcGLXTkrHikXPw4Y3Kg7dmy/i5XYzP3A3nnLm2t7aIo2j0PKSiv1ErNRnLHh7iaGU1v7oT9cCC70GiQwHfu74XHh/RxZZ9Wz2XwGuPExYTc3jj2p6WbTsoMfZqYMG3kSYm1TatlVp51mnTOtUx6oxMU7ZtFlbcY/EeNlpmspqJ2XJv5nmTE7o7LZ51rfcBOLSrurEhI6hprLglj5FVuHO+ukNY3RDo1NicFLn106vJfn5B9yb4buXOyuvaLITVkxNxrLgUALD4wUFIjpEqIRZ6brfkRELTOs6kc3YTSx4cHHci1qy7z0SHhjXRu019zN+4F2/8vCnu9vRcC6/KZVA6AdzCj+DOQe7IOaMXuVZukzrm9CrUEjkRqWHNVNTV+MBJT43dBqlbQ34QtU0DZ4q1AO6K6sioWS1mT2fCxV3RqXEtJCQQ+rZrgMtOba64vaREe3PpuAGv268EC34EF3SPP1vxxSvtycuuF7lWip4uqpHp+kZumE6Na8ZNkVAtKVHXlH29qGn1udmHH7atae1UXHN65QHcdg3TsWXiMFXfj4VcVbR43xndJzPu9pwkIA18Fny7aFU/TXklBbo0rYVPbjo95nKzImgGmZD3xqponknXnmrJdv1IvRopuPfcjvj45t66vq/0KNM6GDruHG/NuvUjhgSfiOoR0Y9EtFH6X2VaHRH1IKLfiGgNEa0koiuN7NMpjAq2lgyIsZgx9kz0iZO/vm2GPtfGkM6VQwGTdCYiI7J+0KsZ++o1ccfAdmjdQLkWrB60PtJrpdpXyEQzAWniG23hjweQLYRoDyBbeh/NUQCjhBBdAAwF8BIR1TG4X8uIFS887Y6+lu/b6I15nUykjhqPwz+Hqi8pF297kYvUNP7Cib+YCuzWnecu6x5zmV3uqsUPDrJ0+1bMnPYqRu+4EQDel16/D+Ci6BWEEBuEEBul1zsA7AFgfQkbnbSJIbpG8rgD6qIXlIqDKJGQQEjXUSgkWcfgnBxjB7XXdMM8cZE5sy9H9800ZTvRmOGGczsZNeUjvlRhwtPpniEdKuUBspJ4v80gTCgEjAt+IyFEOA5wF4C40wSJqBeAFACy8WBEdAsR5RBRTn5+vkHT9CH3owjXffVCjO7qx851ZL+vXn0K7h5c4aNVc/tckWVOlbGrelmTp8boQz6aG6MqOrmBeK14RR++Cfu/c1B7E7ZiHl64x42gKPhENJuIVsv8jYhcT4RGcGL+BoioCYAPAVwvhCiTW0cIMVkIkSWEyMrIcKYTcO+56t0bZnLN6S3xzKWxu9d6sfvna2R/b/h8QNaNLqy+bb2TttpKghKHr9j/F0IMjrWMiHYTURMhxE5J0PfEWK8WgBkAHhRCLNRtrQ3IxTF3bGR9pr8JFpVYVDOQa+THfmv/tnjj501Vzpue6eyZFg0uMrGJN0Cv5J7zY8oC9uHHZzqA66TX1wGYFr0CEaUA+BrAB0KILwzuzxZmj+tf6f3kUcZTzdrJVxH1Xa16kIS555wOeGd0Fvq0DUUP2THQl31Pf+WVPIoTGvryyB66vldm0FY9401W4b9HlzxGBX8igCFEtBHAYOk9iCiLiN6S1rkCwFkARhPRCumvh8H9Wkq7humom1YRQmZmmlw76BlRdMKs1MSxSE5MwNmdqg7dWHkDtc1I91QFLbcTqziLkj97mMraCLHoEVUkxw34vIFvLJeOEGIfgCoxVUKIHAA3Sa8/AvCRkf04wdKHhqC4rAxJGnPBBB2tN8yYge3w6k+5lthiBuOGdMALP25w2gxLCadT1spFPZrh9bnx8/HEw03uEz+6p+RgNYtBQgKhWlKioTQDkbh5Cr4WlI7ipZE9MKRzI7Sqpy6kMcGk82sVZlrnNUnxyU8W53VtjL7t6uPuwcoRQX65T2PBgu9TUpOtubRKcdvdm9fBm6OydM/WdRvxkr9ZoQ2NahmIizeZNAV3oNHY9cY6exZaqZmajI9v6o3mdWM3QoISMOCeURMPoOUH/tGNp+PatxcprvfzvQOwveCYEbNkmT2uPzbnHzF9u2PObodJBrrxADBjbD+UlFY+l1qLbtvVA7+qV0s89M1qW/b10pU9MLRrY1v2Fc38+wZi1updmDBzLVKSEvDcZd0tL0D+mE1Fe9Qw9ZbeWJVXaFqP3q34oxnmQvqpFLBW9WvEzY+jl+Z103CWyvw9WrQzXjZLtXRpWhsnRw3YndpKm7iU2aT4VgpA5MzqFvWq46JTmiE12dpB9li0qJdWnjI5LSURI3o0U/yO0UuQluKe9mbDmqkYdJLx8pJuhwWf8SR+G2Pz+wxPxh2w4FtIH5NmMZ7VIQNPX2JdPL2WDJRmy9KVp7VAszrVcbnGNAthwe/cxJwqYnZwdVQKiKcu7oaxUmqBCRebk1fICLWqJ6NL01p4/jJ3131g9OOePpUPeXxEFwx+YZ7h7XxwQy8TrIlNioYp/5ENazOKkTSrUx2/jj9b8/fC4ymPDrfeD1wnLRkHjhYb3k6LiMilYd2b4KwOGTirQwbGDXFHnvjEBMKMsWfasq8xA71dXc6rcAuf8SThWZ5OjrEF3QnjN7daEGDBt5DIbIsnt9DeGu7Zso6J1qhDU94gB2OWw+6yRjaE9g2SmUlslCyNg9QMYwbs0rGQBunV8Ov4s3GiuBRtdFSj+vim3jh03LgrQQuReXiUcLKFe/fgDrjytBZxY6vN4ulLuuHyrOaYtXoX3luwxZRturm+q1qiw5RrxilAH+aGvq3xzq9/WmUSowALvgb0dGGNlOSrnpJoeS6caJQm27iFxASyReyB0BhH7zb1seOAefMl/D6jMxZ10ryVl8pvsEuHAQDUklpnSg+1YMpUiOg5CDVcFEfuBHoaQOGaAFbNBGfiE+xfrAWc3KKOaeGYdvLNHX0xf+Nexdw2fkmZoIfzuzXBnVOWl7//z1WnaN7G+zf0QkmpbP2fQHBdn0wcOVGCm85s47QpgYQF32S+uq2PJ6dnt8lI1zzOEDSvRGIC4Yqs5vgsJw+Avnqw/VXOfvYian4OqcmJGHdOR8ttYeQJbnONMUzA9J5hPA8Lvsl4sHGvm9sHBG/yzKU9m5e/bqEyBXRQ+LtLJpAxsWGXjskEKfpicGf/J5uK5vQ29bFl4jCnzXAF0YO21/dt7YwhjGq4hc8wDBMQWPA1YMesTobxCrWqs4PAa7Dga6CvBXnrGcartKofjCpRfoIFXydmZIpkGIaxExZ8vQRocJZhGH/Agq+TSdf0rDKJ5otbz3DIGnt55tJueOIi5wt2MM4TLtP43Z39HLaEUQOPuuikWZ3qeObS7uj9dHb5Z1mZ9Ry0yD6uPK2l8kpMIPjln9qL1zDOwS18hmGYgMCCbwA1+b8ZhmHcAgu+AWpUY8FnGMY7sOAzDMMEBBZ8hmGYgMCCbxKPj+jitAkMwzBxYcE3iVFnZDptAsMwTFxY8BmGYQICCz7DMExAYMFnGIYJCIYEn4jqEdGPRLRR+l83zrq1iCiPiF41sk+GYRhGH0Zb+OMBZAsh2gPIlt7H4gkA8wzuz3Wc3joY+XMYhvE+RqeKjgAwQHr9PoC5AP4ZvRIRnQqgEYBZALIM7tNVvHd9L+w9fMJpMxiGYRQx2sJvJITYKb3ehZCoV4KIEgD8G8A/lDZGRLcQUQ4R5eTn5xs0zR6qpySiRb00p81gGIZRRLGFT0SzATSWWfRg5BshhCAiIbPe7QBmCiHySKFoiBBiMoDJAJCVlSW3LYZhGEYnioIvhBgcaxkR7SaiJkKInUTUBMAemdXOAHAmEd0OIB1AChEdFkLE8/e7lqm39Mb2gmNOm8EwDKMZoz786QCuAzBR+j8tegUhxDXh10Q0GkCWV8UeAHq3qe+0CQzDMLow6sOfCGAIEW0EMFh6DyLKIqK3jBrHMAzDmAcJ4U5XeVZWlsjJyXHaDIZhGE9BREuFELLRkDzTlmEYJiCw4DMMwwQEFnyGYZiAwILPMAwTEFjwGYZhAgILPsMwTEBwbVgmEeUD2GpgEw0A7DXJHDfh1+MC+Ni8iF+PC/DusbUSQmTILXCt4BuFiHJixaJ6Gb8eF8DH5kX8elyAP4+NXToMwzABgQWfYRgmIPhZ8Cc7bYBF+PW4AD42L+LX4wJ8eGy+9eEzDMMwlfFzC59hGIaJgAWfYRgmIHha8IloKBGtJ6JcIqpSVIWIqhHRp9LyRUSU6YCZulBxbKOJKJ+IVkh/Nzlhp1aI6B0i2kNEq2MsJyL6j3TcK4mop9026kXFsQ0gosKIa/aI3TbqgYhaENFPRPQHEa0hortk1vHkdVN5bJ68brIIITz5ByARwCYAbQCkAPgdQOeodW4H8Ib0eiSAT52228RjGw3gVadt1XFsZwHoCWB1jOXnA/geAAHoDWCR0zabeGwDAHzntJ06jqsJgJ7S65oANsj8Hj153VQemyevm9yfl1v4vQDkCiE2CyGKAEwFMCJqnREA3pdefwFgEClVUncHao7Nkwgh5gHYH2eVEQA+ECEWAqgj1Ut2PSqOzZMIIXYKIZZJrw8BWAugWdRqnrxuKo/NN3hZ8JsB2BbxPg9VL1T5OkKIEgCFALxQlFbNsQHApVL3+QsiamGPaZaj9ti9yhlE9DsRfU9EXZw2RiuSW/QUAIuiFnn+usU5NsDj1y2MlwU/6HwLIFMI0R3Aj6joyTDuZRlCeU5OBvAKgG+cNUcbRJQO4EsAdwshDjptj5koHJunr1skXhb87QAiW7XNpc9k1yGiJAC1AeyzxTpjKB6bEGKfEOKE9PYtAKfaZJvVqLmunkQIcVAIcVh6PRNAMhE1cNgsVRBRMkKC+LEQ4iuZVTx73ZSOzcvXLRovC/4SAO2JqDURpSA0KDs9ap3pAK6TXl8GYI6QRmFcjuKxRflHhyPke/QD0wGMkqI+egMoFELsdNooMyCixuExJCLqhdD95/oGiGTz2wDWCiFeiLGaJ6+bmmPz6nWTI8lpA/QihCghojEAfkAoquUdIcQaInocQI4QYjpCF/JDIspFaDBtpHMWq0flsY0louEAShA6ttGOGawBIpqCUNRDAyLKA/AvAMkAIIR4A8BMhCI+cgEcBXC9M5ZqR8WxXQbgNiIqAXAMwEiPNED6AvgbgFVEtEL67AEALQHPXzc1x+bV61YFTq3AMAwTELzs0mEYhmE0wILPMAwTEFjwGYZhAgILPsMwTEBgwWcYhgkILPgMwzABgQWfYRgmIPw/BO2MyT/K7gwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio  controls=\"controls\" >\n",
       "                    <source 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type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "message = \"Hello World! I am in the audio!\"\n",
    "if len(message) % 2 != 0:\n",
    "    message += \" \"\n",
    "\n",
    "sep = 4\n",
    "for i in range(len(message)):\n",
    "    lines[i * sep] = encodeLoad(lines[i * sep], message[i])\n",
    "    \n",
    "    \n",
    "intensity = []\n",
    "for line in lines:\n",
    "    intensity += getAudacityFormat(line)     \n",
    "    \n",
    "plt.plot(np.arange(0, len(intensity))/8000, intensity)\n",
    "plt.title(\"Encoded Signal\")\n",
    "plt.show()\n",
    "\n",
    "Audio(np.array(intensity), rate=8000)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['7e7e7e7d7d7dfffffffefffffefefefefefefefefe7effff7e7e7effffff7e7e7effffff7e7e7e7efefffffffffffefeff7efffffefffffeffff7e7eff7e7e7e7d7d7effffff7e7e7e7e7e7effffff7e7e7d7e7e7d7e7e7d7e7e7d7e7e7d7e7effffff7e7e7e7d7e7e7d7d7eff7e7e7e7e7e7d7e7effff7e7e7e7d7e7effffff7d7e7efffffffefffffefefffefefffefefffefefffefefffefefffefefffefe\\n', 'ffff7effff7e7efffeffff7e7e7e7d7e7eff7e7efeffff7e7e7e7d7e7eff7eff7e7e7e7d7e7e7d7e7d7d7e7d7e7e7d7e7eff7eff7e7e7efffffffefffffefefe7effff7e7e7e7d7e7eff7efffefffffffefffefefefefefefefefefefefefefefefefefefefefefefefefe7effff7e7e7efffffffeffffffffff7efffffefffffefffe7effff7e7e7effffff7e7e7e7d7e7e7d7e7e7d7e7eff7efffefffffeff\\n', '7efffffeffff7e7efffeffff7e7efffffffffefefffefefffefefefefefe7efffefefffffefefeff7efefe7e7eff7e7e7dffff7efffffe7e7eff7e7e7e7d7e7d7d7d7d7d7d7eff7e7e7d7e7eff7effff7e7eff7e7e7effff7e7d7e7e7d7e7e7e7e7effff7efffeff7e7eff7e7e7e7d7e7d7d7d7d7d7d7e7e7d7d7e7d7d7d7d7d7d7e7d7d7e7e7efffffffeffff7effff7e7e7e7e7e7d7d7e7e7e7e7e7d7d7e7e\\n', 'ff7e7efffffffefefefdfefdfdfdfefffefeffffff7e7e7e7d7d7d7c7c7c7c7c7c7d7d7d7d7d7e7e7effffff7e7e7effffff7efffffeffff7efffffefffffefefefdfdfdfefefe7e7e7e7d7d7d7c7c7d7d7d7c7c7d7e7e7e7d7d7e7d7d7d7c7c7c7b7c7c7d7d7dfffffffefefefdfdfefffefffefefefdfdfefefdfdfdfcfdfdfcfcfdfcfcfdfcfcfdfcfcfdfcfcfdfefefeffffff7d7d7e7d7d7d7e7e7effff\\n', 'ff7e7e7efffffffefefefdfdfdfcfdfdfcfdfdfefefefefeff7e7e7eff7e7e7e7e7e7d7d7d7c7c7c7c7d7d7e7d7e7efffffffffffffffefefefefdfcfcfcfdfdfdfeff7e7d7c7c7b7b7b7a7a7a7b7c7c7e7efffefdfdfcfcfdfcfcfdfefeff7e7d7d7c7c7c7d7d7dfffffefffffffefefeffff7efffffffffefefefdfdfdfefefefefefffefefefcfcfcfdfdfefefefe7e7e7eff7eff7e7e7efffffffbfbfbfb\\n']\n"
     ]
    },
    {
     "ename": "Error",
     "evalue": "Odd-length string",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mError\u001b[0m                                     Traceback (most recent call last)",
      "Input \u001b[1;32mIn [5]\u001b[0m, in \u001b[0;36m<cell line: 13>\u001b[1;34m()\u001b[0m\n\u001b[0;32m     12\u001b[0m intensity \u001b[38;5;241m=\u001b[39m []\n\u001b[0;32m     13\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m line \u001b[38;5;129;01min\u001b[39;00m lines:\n\u001b[1;32m---> 14\u001b[0m     intensity \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[43mgetAudacityFormat\u001b[49m\u001b[43m(\u001b[49m\u001b[43mline\u001b[49m\u001b[43m)\u001b[49m     \n\u001b[0;32m     16\u001b[0m plt\u001b[38;5;241m.\u001b[39mplot(np\u001b[38;5;241m.\u001b[39marange(\u001b[38;5;241m0\u001b[39m, \u001b[38;5;28mlen\u001b[39m(intensity))\u001b[38;5;241m/\u001b[39m\u001b[38;5;241m8000\u001b[39m, intensity)\n\u001b[0;32m     17\u001b[0m plt\u001b[38;5;241m.\u001b[39mtitle(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mEncoded Signal\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
      "File \u001b[1;32mB:\\College\\2021-2022\\ComputerNetworks\\FinalProject\\ConversionUtilities.py:40\u001b[0m, in \u001b[0;36mgetAudacityFormat\u001b[1;34m(rawStream)\u001b[0m\n\u001b[0;32m     34\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mgetAudacityFormat\u001b[39m(rawStream):\n\u001b[0;32m     35\u001b[0m     \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m     36\u001b[0m \u001b[38;5;124;03m    Returns the ydata of a given raw byte data stream.\u001b[39;00m\n\u001b[0;32m     37\u001b[0m \u001b[38;5;124;03m    @param rawStream: a stream of raw bytes\u001b[39;00m\n\u001b[0;32m     38\u001b[0m \u001b[38;5;124;03m    @return: the ydata of the given stream\u001b[39;00m\n\u001b[0;32m     39\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[1;32m---> 40\u001b[0m     hexStream \u001b[38;5;241m=\u001b[39m rawToHexString(audioop\u001b[38;5;241m.\u001b[39mulaw2lin(\u001b[43mhexStringToRaw\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrawStream\u001b[49m\u001b[43m)\u001b[49m, \u001b[38;5;241m1\u001b[39m))\n\u001b[0;32m     41\u001b[0m     yArr \u001b[38;5;241m=\u001b[39m []\n\u001b[0;32m     42\u001b[0m     \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;241m0\u001b[39m, \u001b[38;5;28mlen\u001b[39m(hexStream) \u001b[38;5;241m-\u001b[39m \u001b[38;5;241m2\u001b[39m, \u001b[38;5;241m2\u001b[39m):\n",
      "File \u001b[1;32mB:\\College\\2021-2022\\ComputerNetworks\\FinalProject\\ConversionUtilities.py:11\u001b[0m, in \u001b[0;36mhexStringToRaw\u001b[1;34m(hexstring)\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mhexStringToRaw\u001b[39m(hexstring):\n\u001b[0;32m      6\u001b[0m     \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m      7\u001b[0m \u001b[38;5;124;03m    Converts string of hex values to raw bytes.\u001b[39;00m\n\u001b[0;32m      8\u001b[0m \u001b[38;5;124;03m    @param hexstring: string of hex values\u001b[39;00m\n\u001b[0;32m      9\u001b[0m \u001b[38;5;124;03m    @return: the converted raw bytes\u001b[39;00m\n\u001b[0;32m     10\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[1;32m---> 11\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mbinascii\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43munhexlify\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mjoin\u001b[49m\u001b[43m(\u001b[49m\u001b[43mhexstring\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msplit\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n",
      "\u001b[1;31mError\u001b[0m: Odd-length string"
     ]
    }
   ],
   "source": [
    "file = open(\"VoicemailASCIIHex\", \"r\")  # Original voicemail file\n",
    "lines = file.readlines()\n",
    "print(lines[:5])\n",
    "\n",
    "bitCounter = 0\n",
    "bMessage = message.encode()\n",
    "\n",
    "for i in range(len(message)):\n",
    "    lines[i], bitCounter = encodeLoad2(lines[i], message, bitCounter)\n",
    "\n",
    "\n",
    "intensity = []\n",
    "for line in lines:\n",
    "    intensity += getAudacityFormat(line)     \n",
    "    \n",
    "plt.plot(np.arange(0, len(intensity))/8000, intensity)\n",
    "plt.title(\"Encoded Signal\")\n",
    "plt.show()\n",
    "\n",
    "Audio(np.array(intensity), rate=8000)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "file = open(\"VoicemailASCIIHex\", \"r\")  # Original voicemail file\n",
    "lines = file.readlines()\n",
    "print(lines[:5])\n",
    "\n",
    "bitCounter = 0\n",
    "bMessage = message.encode()\n",
    "\n",
    "for i in range(len(message)):\n",
    "    print(len(lines[i]))\n",
    "    lines[i], bitCounter = encodeLoad2(lines[i], message, bitCounter)\n",
    "\n",
    "\n",
    "intensity = []\n",
    "for line in lines:\n",
    "    intensity += getAudacityFormat(line)     \n",
    "    \n",
    "plt.plot(np.arange(0, len(intensity))/8000, intensity)\n",
    "plt.title(\"Encoded Signal\")\n",
    "plt.show()\n",
    "\n",
    "Audio(np.array(intensity), rate=8000)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['7e7e7e7d7d7dfffffffefffffefefefefefefefefe7effff7e7e7effffff7e7e7effffff7e7e7e7efefffffffffffefeff7efffffefffffeffff7e7eff7e7e7e7d7d7effffff7e7e7e7e7e7effffff7e7e7d7e7e7d7e7e7d7e7e7d7e7e7d7e7effffff7e7e7e7d7e7e7d7d7eff7e7e7e7e7e7d7e7effff7e7e7e7d7e7effffff7d7e7efffffffefffffefefffefefffefefffefefffefefffefefffefefffefe\\n', 'ffff7effff7e7efffeffff7e7e7e7d7e7eff7e7efeffff7e7e7e7d7e7eff7eff7e7e7e7d7e7e7d7e7d7d7e7d7e7e7d7e7eff7eff7e7e7efffffffefffffefefe7effff7e7e7e7d7e7eff7efffefffffffefffefefefefefefefefefefefefefefefefefefefefefefefefe7effff7e7e7efffffffeffffffffff7efffffefffffefffe7effff7e7e7effffff7e7e7e7d7e7e7d7e7e7d7e7eff7efffefffffeff\\n', '7efffffeffff7e7efffeffff7e7efffffffffefefffefefffefefefefefe7efffefefffffefefeff7efefe7e7eff7e7e7dffff7efffffe7e7eff7e7e7e7d7e7d7d7d7d7d7d7eff7e7e7d7e7eff7effff7e7eff7e7e7effff7e7d7e7e7d7e7e7e7e7effff7efffeff7e7eff7e7e7e7d7e7d7d7d7d7d7d7e7e7d7d7e7d7d7d7d7d7d7e7d7d7e7e7efffffffeffff7effff7e7e7e7e7e7d7d7e7e7e7e7e7d7d7e7e\\n', 'ff7e7efffffffefefefdfefdfdfdfefffefeffffff7e7e7e7d7d7d7c7c7c7c7c7c7d7d7d7d7d7e7e7effffff7e7e7effffff7efffffeffff7efffffefffffefefefdfdfdfefefe7e7e7e7d7d7d7c7c7d7d7d7c7c7d7e7e7e7d7d7e7d7d7d7c7c7c7b7c7c7d7d7dfffffffefefefdfdfefffefffefefefdfdfefefdfdfdfcfdfdfcfcfdfcfcfdfcfcfdfcfcfdfcfcfdfefefeffffff7d7d7e7d7d7d7e7e7effff\\n', 'ff7e7e7efffffffefefefdfdfdfcfdfdfcfdfdfefefefefeff7e7e7eff7e7e7e7e7e7d7d7d7c7c7c7c7d7d7e7d7e7efffffffffffffffefefefefdfcfcfcfdfdfdfeff7e7d7c7c7b7b7b7a7a7a7b7c7c7e7efffefdfdfcfcfdfcfcfdfefeff7e7d7d7c7c7c7d7d7dfffffefffffffefefeffff7efffffffffefefefdfdfdfefefefefefffefefefcfcfcfdfdfefefefe7e7e7eff7eff7e7e7efffffffbfbfbfb\\n']\n",
      "321\n",
      "321\n",
      "321\n",
      "321\n",
      "321\n",
      "321\n",
      "321\n",
      "321\n",
      "321\n",
      "321\n",
      "321\n",
      "321\n",
      "321\n",
      "321\n",
      "321\n",
      "321\n",
      "321\n",
      "321\n",
      "321\n",
      "321\n",
      "321\n",
      "321\n",
      "321\n",
      "321\n",
      "321\n",
      "321\n",
      "321\n",
      "321\n",
      "321\n",
      "321\n",
      "321\n",
      "321\n"
     ]
    },
    {
     "ename": "Error",
     "evalue": "Odd-length string",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mError\u001b[0m                                     Traceback (most recent call last)",
      "Input \u001b[1;32mIn [8]\u001b[0m, in \u001b[0;36m<cell line: 14>\u001b[1;34m()\u001b[0m\n\u001b[0;32m     13\u001b[0m intensity \u001b[38;5;241m=\u001b[39m []\n\u001b[0;32m     14\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m line \u001b[38;5;129;01min\u001b[39;00m lines:\n\u001b[1;32m---> 15\u001b[0m     intensity \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[43mgetAudacityFormat\u001b[49m\u001b[43m(\u001b[49m\u001b[43mline\u001b[49m\u001b[43m)\u001b[49m     \n\u001b[0;32m     17\u001b[0m plt\u001b[38;5;241m.\u001b[39mplot(np\u001b[38;5;241m.\u001b[39marange(\u001b[38;5;241m0\u001b[39m, \u001b[38;5;28mlen\u001b[39m(intensity))\u001b[38;5;241m/\u001b[39m\u001b[38;5;241m8000\u001b[39m, intensity)\n\u001b[0;32m     18\u001b[0m plt\u001b[38;5;241m.\u001b[39mtitle(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mEncoded Signal\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
      "File \u001b[1;32mB:\\College\\2021-2022\\ComputerNetworks\\FinalProject\\ConversionUtilities.py:40\u001b[0m, in \u001b[0;36mgetAudacityFormat\u001b[1;34m(rawStream)\u001b[0m\n\u001b[0;32m     34\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mgetAudacityFormat\u001b[39m(rawStream):\n\u001b[0;32m     35\u001b[0m     \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m     36\u001b[0m \u001b[38;5;124;03m    Returns the ydata of a given raw byte data stream.\u001b[39;00m\n\u001b[0;32m     37\u001b[0m \u001b[38;5;124;03m    @param rawStream: a stream of raw bytes\u001b[39;00m\n\u001b[0;32m     38\u001b[0m \u001b[38;5;124;03m    @return: the ydata of the given stream\u001b[39;00m\n\u001b[0;32m     39\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[1;32m---> 40\u001b[0m     hexStream \u001b[38;5;241m=\u001b[39m rawToHexString(audioop\u001b[38;5;241m.\u001b[39mulaw2lin(\u001b[43mhexStringToRaw\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrawStream\u001b[49m\u001b[43m)\u001b[49m, \u001b[38;5;241m1\u001b[39m))\n\u001b[0;32m     41\u001b[0m     yArr \u001b[38;5;241m=\u001b[39m []\n\u001b[0;32m     42\u001b[0m     \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;241m0\u001b[39m, \u001b[38;5;28mlen\u001b[39m(hexStream) \u001b[38;5;241m-\u001b[39m \u001b[38;5;241m2\u001b[39m, \u001b[38;5;241m2\u001b[39m):\n",
      "File \u001b[1;32mB:\\College\\2021-2022\\ComputerNetworks\\FinalProject\\ConversionUtilities.py:11\u001b[0m, in \u001b[0;36mhexStringToRaw\u001b[1;34m(hexstring)\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mhexStringToRaw\u001b[39m(hexstring):\n\u001b[0;32m      6\u001b[0m     \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m      7\u001b[0m \u001b[38;5;124;03m    Converts string of hex values to raw bytes.\u001b[39;00m\n\u001b[0;32m      8\u001b[0m \u001b[38;5;124;03m    @param hexstring: string of hex values\u001b[39;00m\n\u001b[0;32m      9\u001b[0m \u001b[38;5;124;03m    @return: the converted raw bytes\u001b[39;00m\n\u001b[0;32m     10\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[1;32m---> 11\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mbinascii\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43munhexlify\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mjoin\u001b[49m\u001b[43m(\u001b[49m\u001b[43mhexstring\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msplit\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n",
      "\u001b[1;31mError\u001b[0m: Odd-length string"
     ]
    }
   ],
   "source": [
    "file = open(\"VoicemailASCIIHex\", \"r\")  # Original voicemail file\n",
    "lines = file.readlines()\n",
    "print(lines[:5])\n",
    "\n",
    "bitCounter = 0\n",
    "bMessage = message.encode()\n",
    "\n",
    "for i in range(len(message)):\n",
    "    print(len(lines[i]))\n",
    "    lines[i], bitCounter = encodeLoad2(lines[i], message, bitCounter)\n",
    "\n",
    "\n",
    "intensity = []\n",
    "for line in lines:\n",
    "    intensity += getAudacityFormat(line)     \n",
    "    \n",
    "plt.plot(np.arange(0, len(intensity))/8000, intensity)\n",
    "plt.title(\"Encoded Signal\")\n",
    "plt.show()\n",
    "\n",
    "Audio(np.array(intensity), rate=8000)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "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": {
      "text/html": [
       "\n",
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