SoundParser_YuPeixin.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from PIL import Image\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#pathBase = 'E://Chuan//Documents//GitHub//AusculPi//Data//VSD//'\n",
    "#pathBase = 'I://Chuan//Documents//GitHub//AusculPi//Data//VSD//'\n",
    "#pathBase = 'C://Users//Chuan//OneDrive//Dowrun//Text//Manuscripts//Sound//TAVR_post//'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "pathBase = 'C://Users//triti//OneDrive//Dowrun//Text//Manuscripts//Data//YuPeixin//AusculPi//'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "filename = 'Numpy_Array_File_2020-06-12_08_52_02.npy'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "line = pathBase + filename"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "arr = np.load(line)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[  358,   369,   365, ...,    92,    79,    65],\n",
       "       [   10,   -16,     9, ...,   283,   286,   304],\n",
       "       [  341,   369,   392, ...,   241,   217,   230],\n",
       "       ...,\n",
       "       [ 1151,  1154,  1178, ...,  8652,  8670,  8684],\n",
       "       [ 8654,  8676,  8642, ..., -2072, -2206, -2346],\n",
       "       [    3, -6568, -6578, ..., -6175, -6163, -6136]], dtype=int16)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "arr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2583, 512)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "arr.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2022c027388>]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "fig = plt.figure()\n",
    "s = fig.add_subplot(111)\n",
    "s.plot(arr[0], linewidth=1.0, color='black')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2023a39dcc8>]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "fig = plt.figure()\n",
    "s = fig.add_subplot(111)\n",
    "s.plot(arr[:,100], linewidth=1.0, color='black')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "start = 1377\n",
    "end = 1910\n",
    "\n",
    "start_adj = int(start * 2583 / 3000)\n",
    "end_adj = int(end * 2583 / 3000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2023cb89548>]"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "fig = plt.figure()\n",
    "s = fig.add_subplot(111)\n",
    "s.plot(arr[start_adj:end_adj,86], linewidth=1.0, color='black')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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       " <matplotlib.lines.Line2D at 0x2023dea98c8>,\n",
       " <matplotlib.lines.Line2D at 0x2023dea9a88>,\n",
       " <matplotlib.lines.Line2D at 0x2023dea9cc8>,\n",
       " <matplotlib.lines.Line2D at 0x2023dea9ec8>,\n",
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       " <matplotlib.lines.Line2D at 0x2023dead7c8>,\n",
       " <matplotlib.lines.Line2D at 0x2023deada08>,\n",
       " <matplotlib.lines.Line2D at 0x2023deadc48>,\n",
       " <matplotlib.lines.Line2D at 0x2023deade88>,\n",
       " <matplotlib.lines.Line2D at 0x2023deaf108>,\n",
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       " <matplotlib.lines.Line2D at 0x2023df67388>,\n",
       " <matplotlib.lines.Line2D at 0x2023df67608>,\n",
       " <matplotlib.lines.Line2D at 0x2023df67888>,\n",
       " <matplotlib.lines.Line2D at 0x2023df67b08>,\n",
       " <matplotlib.lines.Line2D at 0x2023df67d88>,\n",
       " <matplotlib.lines.Line2D at 0x2023df6a048>,\n",
       " <matplotlib.lines.Line2D at 0x2023df6a2c8>,\n",
       " <matplotlib.lines.Line2D at 0x2023df6a548>,\n",
       " <matplotlib.lines.Line2D at 0x2023df6a7c8>,\n",
       " <matplotlib.lines.Line2D at 0x2023df6aa48>,\n",
       " <matplotlib.lines.Line2D at 0x2023df6acc8>,\n",
       " <matplotlib.lines.Line2D at 0x2023df6af48>,\n",
       " <matplotlib.lines.Line2D at 0x2023df6d208>,\n",
       " <matplotlib.lines.Line2D at 0x2023df6d488>,\n",
       " <matplotlib.lines.Line2D at 0x2023df6d708>]"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "fig = plt.figure()\n",
    "s = fig.add_subplot(111)\n",
    "s.plot(arr[start_adj:end_adj,70:500], linewidth=0.6, color='black')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig.savefig('Phonocardiograph_YuPeixin.png', dpi=400)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "s.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}