audio spectrum_pt1_waveform_viewer.ipynb

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    "\"\"\"\n",
    "Notebook for streaming data from a microphone in realtime\n",
    "\n",
    "audio is captured using pyaudio\n",
    "then converted from binary data to ints using struct\n",
    "then displayed using matplotlib\n",
    "\n",
    "if you don't have pyaudio, then run\n",
    "\n",
    ">>> pip install pyaudio\n",
    "\n",
    "note: with 2048 samples per chunk, I'm getting 20FPS\n",
    "\"\"\"\n",
    "\n",
    "import pyaudio\n",
    "import os\n",
    "import struct\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import time\n",
    "from tkinter import TclError\n",
    "\n",
    "# use this backend to display in separate Tk window\n",
    "%matplotlib tk\n",
    "\n",
    "# constants\n",
    "CHUNK = 1024 * 2             # samples per frame\n",
    "FORMAT = pyaudio.paInt16     # audio format (bytes per sample?)\n",
    "CHANNELS = 1                 # single channel for microphone\n",
    "RATE = 44100                 # samples per second"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "stream started\n",
      "stream stopped\n",
      "average frame rate = 21 FPS\n"
     ]
    }
   ],
   "source": [
    "# create matplotlib figure and axes\n",
    "fig, ax = plt.subplots(1, figsize=(15, 7))\n",
    "\n",
    "# pyaudio class instance\n",
    "p = pyaudio.PyAudio()\n",
    "\n",
    "# stream object to get data from microphone\n",
    "stream = p.open(\n",
    "    format=FORMAT,\n",
    "    channels=CHANNELS,\n",
    "    rate=RATE,\n",
    "    input=True,\n",
    "    output=True,\n",
    "    frames_per_buffer=CHUNK\n",
    ")\n",
    "\n",
    "# variable for plotting\n",
    "x = np.arange(0, 2 * CHUNK, 2)\n",
    "\n",
    "# create a line object with random data\n",
    "line, = ax.plot(x, np.random.rand(CHUNK), '-', lw=2)\n",
    "\n",
    "# basic formatting for the axes\n",
    "ax.set_title('AUDIO WAVEFORM')\n",
    "ax.set_xlabel('samples')\n",
    "ax.set_ylabel('volume')\n",
    "ax.set_ylim(0, 255)\n",
    "ax.set_xlim(0, 2 * CHUNK)\n",
    "plt.setp(ax, xticks=[0, CHUNK, 2 * CHUNK], yticks=[0, 128, 255])\n",
    "\n",
    "# show the plot\n",
    "plt.show(block=False)\n",
    "\n",
    "print('stream started')\n",
    "\n",
    "# for measuring frame rate\n",
    "frame_count = 0\n",
    "start_time = time.time()\n",
    "\n",
    "while True:\n",
    "    \n",
    "    # binary data\n",
    "    data = stream.read(CHUNK)  \n",
    "    \n",
    "    # convert data to integers, make np array, then offset it by 127\n",
    "    data_int = struct.unpack(str(2 * CHUNK) + 'B', data)\n",
    "    \n",
    "    # create np array and offset by 128\n",
    "    data_np = np.array(data_int, dtype='b')[::2] + 128\n",
    "    \n",
    "    line.set_ydata(data_np)\n",
    "    \n",
    "    # update figure canvas\n",
    "    try:\n",
    "        fig.canvas.draw()\n",
    "        fig.canvas.flush_events()\n",
    "        frame_count += 1\n",
    "        \n",
    "    except TclError:\n",
    "        \n",
    "        # calculate average frame rate\n",
    "        frame_rate = frame_count / (time.time() - start_time)\n",
    "        \n",
    "        print('stream stopped')\n",
    "        print('average frame rate = {:.0f} FPS'.format(frame_rate))\n",
    "        break"
   ]
  },
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   "execution_count": null,
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