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Commit d394e83

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first notebook to stream audio
this notebook streams audio and displays using matplotlib
1 parent b38818b commit d394e83

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‎audio spectrum.ipynb‎

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 9,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"\"\"\"\n",
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"Notebook for streaming data from a microphone in realtime\n",
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"\n",
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"audio is captured using pyaudio\n",
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"then converted from binary data to ints using struct\n",
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"then displayed using matplotlib\n",
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"\n",
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"pip install pyaudio \n",
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"\n",
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"if you don't have pyaudio\n",
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"\"\"\"\n",
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"\n",
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"import pyaudio\n",
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"import os\n",
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"import struct\n",
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"import numpy as np\n",
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"import matplotlib.pyplot as plt\n",
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"import time\n",
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"\n",
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"# use this backend to display in separate window\n",
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"%matplotlib tk\n",
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"\n",
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"CHUNK = 1024 * 4\n",
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"FORMAT = pyaudio.paInt16\n",
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"CHANNELS = 1\n",
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"RATE = 44100"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"metadata": {
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"scrolled": false
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},
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"outputs": [
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{
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"ename": "TclError",
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"evalue": "this isn't a Tk application",
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"output_type": "error",
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"traceback": [
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"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[1;31mTclError\u001b[0m Traceback (most recent call last)",
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"\u001b[1;32mC:\\Users\\mark\\Anaconda3\\lib\\site-packages\\matplotlib\\backends\\tkagg.py\u001b[0m in \u001b[0;36mblit\u001b[1;34m(photoimage, aggimage, bbox, colormode)\u001b[0m\n\u001b[0;32m 21\u001b[0m \u001b[1;34m\"PyAggImagePhoto\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mphotoimage\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 22\u001b[1;33m id(data), colormode, id(bbox_array))\n\u001b[0m\u001b[0;32m 23\u001b[0m \u001b[1;32mexcept\u001b[0m \u001b[0mTk\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mTclError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
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"\u001b[1;31mTclError\u001b[0m: this isn't a Tk application",
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"\nDuring handling of the above exception, another exception occurred:\n",
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"\u001b[1;31mTclError\u001b[0m Traceback (most recent call last)",
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"\u001b[1;32m<ipython-input-10-99f79adc46a1>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 25\u001b[0m \u001b[0mdata_int\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0marray\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mstruct\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0munpack\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mstr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m2\u001b[0m \u001b[1;33m*\u001b[0m \u001b[0mCHUNK\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;34m'B'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'b'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;36m127\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 26\u001b[0m \u001b[0mline\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset_ydata\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata_int\u001b[0m \u001b[1;33m%\u001b[0m \u001b[1;36m255\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 27\u001b[1;33m \u001b[0mfig\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcanvas\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdraw\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 28\u001b[0m \u001b[0mfig\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcanvas\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mflush_events\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
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"\u001b[1;32mC:\\Users\\mark\\Anaconda3\\lib\\site-packages\\matplotlib\\backends\\backend_tkagg.py\u001b[0m in \u001b[0;36mdraw\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 350\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mdraw\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 351\u001b[0m \u001b[0mFigureCanvasAgg\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdraw\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 352\u001b[1;33m \u001b[0mtkagg\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mblit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_tkphoto\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrenderer\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_renderer\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcolormode\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 353\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_master\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mupdate_idletasks\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 354\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
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"\u001b[1;32mC:\\Users\\mark\\Anaconda3\\lib\\site-packages\\matplotlib\\backends\\tkagg.py\u001b[0m in \u001b[0;36mblit\u001b[1;34m(photoimage, aggimage, bbox, colormode)\u001b[0m\n\u001b[0;32m 28\u001b[0m \u001b[0m_tkagg\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtkinit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mid\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtk\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 29\u001b[0m tk.call(\"PyAggImagePhoto\", photoimage,\n\u001b[1;32m---> 30\u001b[1;33m id(data), colormode, id(bbox_array))\n\u001b[0m\u001b[0;32m 31\u001b[0m \u001b[1;32mexcept\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mImportError\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mAttributeError\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTk\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mTclError\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 32\u001b[0m \u001b[1;32mraise\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
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"\u001b[1;31mTclError\u001b[0m: this isn't a Tk application"
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]
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}
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],
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"source": [
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"fig, ax = plt.subplots(1, figsize=(15, 7))\n",
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"\n",
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"p = pyaudio.PyAudio()\n",
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"\n",
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"stream = p.open(format=FORMAT,\n",
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" channels=CHANNELS,\n",
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" rate=RATE,\n",
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" input=True,\n",
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" output=True,\n",
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" frames_per_buffer=CHUNK)\n",
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"\n",
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"\n",
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"x = np.arange(0, 2 * CHUNK, 2)\n",
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"line, = ax.plot(x, np.random.rand(CHUNK), '-', lw=2)\n",
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"ax.set_title('AUDIO WAVEFORM')\n",
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"ax.set_xlabel('samples')\n",
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"ax.set_ylabel('volume')\n",
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"ax.set_ylim(0, 255)\n",
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"ax.set_xlim(0, 2 * CHUNK)\n",
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"plt.setp(ax, xticks=[0, 1024, 2048], yticks=[0, 128, 255])\n",
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"plt.show(block=False)\n",
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"\n",
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"while True:\n",
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" data = stream.read(CHUNK) # binary data\n",
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" \n",
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" # convert to int, make np array, then offset it by 127\n",
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" data_int = np.array(struct.unpack(str(2 * CHUNK) + 'B', data), dtype='b')[::2] + 127\n",
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" \n",
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" # unpdate matplotlib\n",
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" fig.canvas.draw()\n",
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" fig.canvas.flush_events()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"anaconda-cloud": {},
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"kernelspec": {
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"display_name": "Python [conda root]",
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"language": "python",
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"name": "conda-root-py"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.5.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 1
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}

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