2016-3-30ProbabilityOfAVideoBeingAGoodPPGSignal.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Finding and Graphing the Probability of a Video Being a Good Video"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we refer to the time window as the frame. Each frame is 0.033 sec front and back (so 0.67 total)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import numpy\n",
    "import matplotlib.pyplot as plt\n",
    "fps = 30.323427803\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def readFromFile(fileName):\n",
    "    l =numpy.loadtxt(fileName)\n",
    "    return l[0], l[1], l[2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def detectPeak(colorL, frameThreshold):\n",
    "    peakL = list()\n",
    "    colorlistLen = len(colorL)\n",
    "    for i in range(1, colorlistLen-1):\n",
    "        biggerThanPrevious = colorL[i] > colorL[i-1]\n",
    "        biggerThanAfter = colorL[i] > colorL[i+1]\n",
    "        #if it is a local maximum, then check if it is a RR peak by comparing its maxima interval to frameThreshold\n",
    "        if biggerThanPrevious and biggerThanAfter:\n",
    "            for k in range(2, frameThreshold+1):\n",
    "                if i-k >= 0:\n",
    "                    if not colorL[i] > colorL[i-k]:\n",
    "                        #this is not a rr peak\n",
    "                        break\n",
    "                if i+k < colorlistLen:\n",
    "                    if not colorL[i] > colorL[i+k]:\n",
    "                        #this is not a rr peak\n",
    "                        break\n",
    "            else:\n",
    "                #this IS a rr peak, store the array index\n",
    "                peakL.append(i)\n",
    "    return peakL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def constructRRIntervalList(peakL):\n",
    "    return [ (peakL[i]-peakL[i-1])/fps for i in range(1, len(peakL))]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This function defines the criteria for being a true RR interval."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def isTrueRRInterval(rrInterval):\n",
    "    if 0.54 <= rrInterval and rrInterval <= 1.2:\n",
    "        return True\n",
    "    else:\n",
    "        return False"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We define the percent error as following:\n",
    "\n",
    "$$\\epsilon^{(i)} = \\frac{\\text{# of wrong RR}}{\\text{# of RR}} x100$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This function detect the amount of errors in a list of RR interval, as judged by function isTrueRRInterval"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def getPercentError(rrL):\n",
    "    errorNum = 0\n",
    "    for rrInterval in rrL:\n",
    "        if (not isTrueRRInterval(rrInterval)):\n",
    "            errorNum += 1\n",
    "    return 100.0*errorNum/len(rrL) if len(rrL) else 0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This function analyze the rgb txt file of a PPG video and return important information."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def analyzeVideoAndFindPercentErrorList(fileName):\n",
    "    rErrorL = []\n",
    "    gErrorL = []\n",
    "    bErrorL = []\n",
    "    rL, gL, bL = readFromFile(fileName)\n",
    "    for frameThreshold in range(1, 26):\n",
    "        rRRL = constructRRIntervalList(detectPeak(rL, frameThreshold))\n",
    "        gRRL = constructRRIntervalList(detectPeak(gL, frameThreshold))\n",
    "        bRRL = constructRRIntervalList(detectPeak(bL, frameThreshold))\n",
    "        rErrorL.append(getPercentError(rRRL))\n",
    "        gErrorL.append(getPercentError(gRRL))\n",
    "        bErrorL.append(getPercentError(bRRL))\n",
    "    return rErrorL, gErrorL, bErrorL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "videoList = [\"/home/mong/Desktop/map/map/videos/VID_20150123_172926_F.mp4.txt\",\n",
    "                \"/home/mong/Desktop/map/map/videos/VID_20150123_173259_Q.mp4.txt\",\n",
    "                \"/home/mong/Desktop/map/map/videos/VID_20150123_173329_F.mp4.txt\",\n",
    "                \"/home/mong/Desktop/map/map/videos/VID_20150123_173358_Q.mp4.txt\",\n",
    "                \"/home/mong/Desktop/map/map/videos/VID_20150123_173427_F.mp4.txt\",\n",
    "                \"/home/mong/Desktop/map/map/videos/VID_20150123_173457_Q.mp4.txt\",\n",
    "                \"/home/mong/Desktop/map/map/videos/VID_20150123_173556_Q.mp4.txt\",\n",
    "                \"/home/mong/Desktop/map/map/videos/VID_20150123_173629_F.mp4.txt\",\n",
    "                \"/home/mong/Desktop/map/map/videos/VID_20150123_173700_Q.mp4.txt\",\n",
    "                \"/home/mong/Desktop/map/map/videos/VID_20150123_173757_Q.mp4.txt\",\n",
    "                \"/home/mong/Desktop/map/map/videos/VID_20150123_173028_F.mp4.txt\",\n",
    "                \"/home/mong/Desktop/map/map/videos/VID_20150123_172857_Q.mp4.txt\",\n",
    "                \"/home/mong/Desktop/map/map/videos/VID_20150123_173727_F.mp4.txt\",\n",
    "                \"/home/mong/Desktop/map/map/videos/VID_20150123_173527_F.mp4.txt\",\n",
    "                \"/home/mong/Desktop/map/map/videos/VID_20150123_173230_F.mp4.txt\",\n",
    "                \"/home/mong/Desktop/map/map/videos/VID_20150123_173157_Q.mp4.txt\",\n",
    "                \"/home/mong/Desktop/map/map/videos/VID_20150123_173127_F.mp4.txt\",\n",
    "                \"/home/mong/Desktop/map/map/videos/VID_20150123_173057_Q.mp4.txt\",\n",
    "                \"/home/mong/Desktop/map/map/videos/VID_20150123_172956_Q.mp4.txt\",\n",
    "                \"/home/mong/Desktop/map/map/videos/VID_20150123_172827_F.mp4.txt\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "rAvgErrorL = [0 for i in range(0, 25)]\n",
    "gAvgErrorL = [0 for i in range(0, 25)]\n",
    "bAvgErrorL = [0 for i in range(0, 25)]\n",
    "vidPPGL = {}\n",
    "for video in videoList:\n",
    "    rErrorL, gErrorL, bErrorL = analyzeVideoAndFindPercentErrorList(video)\n",
    "    vidPPGL[video+'|red|'+str(rErrorL.index(min(rErrorL))*2+2)] = min(rErrorL)\n",
    "def isInRange(begin, end, value):\n",
    "    return begin <= value and value < end\n",
    "def numOfVidInBeam(begin, end):\n",
    "    num = 0\n",
    "    for vidName in vidPPGL:\n",
    "        if isInRange(begin, end, vidPPGL[vidName]):\n",
    "            num += 1\n",
    "    return num\n",
    "probabilityArray = [numOfVidInBeam(0,3),\n",
    "                    numOfVidInBeam(3,5),\n",
    "                    numOfVidInBeam(5,10),\n",
    "                    numOfVidInBeam(10,15),\n",
    "                    numOfVidInBeam(15,25),\n",
    "                    numOfVidInBeam(25,101)]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/home/mong/Desktop/map/map/videos/VID_20150123_173127_F.mp4.txt|red|8     2.3255813953488373\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_173629_F.mp4.txt|red|14     21.21212121212121\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_173527_F.mp4.txt|red|24     33.333333333333336\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_173230_F.mp4.txt|red|14     4.761904761904762\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_173757_Q.mp4.txt|red|10     0.0\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_173457_Q.mp4.txt|red|10     0.0\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_172857_Q.mp4.txt|red|20     0.0\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_173556_Q.mp4.txt|red|12     0.0\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_173157_Q.mp4.txt|red|12     0.0\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_173329_F.mp4.txt|red|10     53.57142857142857\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_173358_Q.mp4.txt|red|14     0.0\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_172827_F.mp4.txt|red|10     2.3255813953488373\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_173057_Q.mp4.txt|red|12     3.225806451612903\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_173427_F.mp4.txt|red|20     0.0\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_173700_Q.mp4.txt|red|12     0.0\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_172956_Q.mp4.txt|red|10     0.0\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_172926_F.mp4.txt|red|14     2.5641025641025643\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_173727_F.mp4.txt|red|18     14.285714285714286\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_173028_F.mp4.txt|red|8     0.0\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_173259_Q.mp4.txt|red|12     0.0\n"
     ]
    }
   ],
   "source": [
    "for v in vidPPGL:\n",
    "    print(v, '   ',vidPPGL[v])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
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B9O5pHBo5XQ6sV1VvHtbXxlW1rFt9NXDdsO0HAF+tqru6c1X3Wm+k2vbee9Gq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\nJgOjJEmSmv5/7qVMruyUhPoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f32a55ba0f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "plt.rcParams['figure.figsize'] = (10, 6)\n",
    "plt.rcParams['figure.figsize'] = (10, 6)\n",
    "beams = ('0%-3%', '3%-5%', '5%-10%', '10-15%', '15-25%','25%-100%')\n",
    "y_pos = numpy.arange(len(beams))\n",
    "\n",
    "plt.barh(y_pos, probabilityArray,align='center', alpha=0.4)\n",
    "plt.yticks(y_pos, beams)\n",
    "plt.xlabel('Number of Video')\n",
    "plt.ylabel('Percent Error')\n",
    "plt.xlim(0, len(videoList))\n",
    "plt.title('Percent Errors in 4 Beams')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If we define a good video to have percent error less than 10%, then the probability of a video being a good one is:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "numOfVidInBeam(0,10)/len(videoList)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "But if we define a good video to have percent error less than 25%, then the probability of a video being a good one is:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "numOfVidInBeam(0,25)/len(videoList)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/home/mong/Desktop/map/map/videos/VID_20150123_172926_F.mp4.txt|red|14     2.5641025641025643\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_173230_F.mp4.txt|red|14     4.761904761904762\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_172857_Q.mp4.txt|red|20     0.0\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_173700_Q.mp4.txt|red|12     0.0\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_173727_F.mp4.txt|red|18     14.285714285714286\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_173259_Q.mp4.txt|red|12     0.0\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_173427_F.mp4.txt|red|20     0.0\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_173057_Q.mp4.txt|red|12     3.225806451612903\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_172827_F.mp4.txt|red|10     2.3255813953488373\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_173329_F.mp4.txt|red|10     53.57142857142857\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_173527_F.mp4.txt|red|24     33.333333333333336\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_173757_Q.mp4.txt|red|10     0.0\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_173028_F.mp4.txt|red|8     0.0\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_173157_Q.mp4.txt|red|12     0.0\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_173457_Q.mp4.txt|red|10     0.0\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_173556_Q.mp4.txt|red|12     0.0\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_173629_F.mp4.txt|red|14     21.21212121212121\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_172956_Q.mp4.txt|red|10     0.0\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_173358_Q.mp4.txt|red|14     0.0\n",
      "/home/mong/Desktop/map/map/videos/VID_20150123_173127_F.mp4.txt|red|8     2.3255813953488373\n"
     ]
    }
   ],
   "source": [
    "for vidName in vidPPGL:\n",
    "    print(vidName, \"   \",vidPPGL[vidName])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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