EDA.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import os\n",
    "import csv\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "INPUT_DATA_DIR = 'input_data/'\n",
    "fnames = sorted([f for f in os.listdir(os.path.join(INPUT_DATA_DIR))  if f.endswith('csv') ])\n",
    "patches_fnames = [os.path.join(INPUT_DATA_DIR, f) for f in fnames if 'patches' in f]\n",
    "ori_fnames = [os.path.join(INPUT_DATA_DIR, f) for f  in fnames if 'ori' in f]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "input_data/DD1_big_patches.csv\n",
      "input_data/DD2_big_patches.csv\n",
      "input_data/DD3_big_patches.csv\n",
      "input_data/DD4_big_patches.csv\n",
      "input_data/DD5_big_patches.csv\n",
      "input_data/DD6_big_patches.csv\n",
      "input_data/bark1_big_patches.csv\n",
      "input_data/bark2_big_patches.csv\n",
      "input_data/bark3_big_patches.csv\n",
      "input_data/bark4_big_patches.csv\n",
      "input_data/bark5_big_patches.csv\n",
      "input_data/bark6_big_patches.csv\n",
      "input_data/boat1_big_patches.csv\n",
      "input_data/boat2_big_patches.csv\n",
      "input_data/boat3_big_patches.csv\n",
      "input_data/boat4_big_patches.csv\n",
      "input_data/boat5_big_patches.csv\n",
      "input_data/boat6_big_patches.csv\n",
      "input_data/build0_big_patches.csv\n",
      "input_data/build1_big_patches.csv\n",
      "input_data/cart0_big_patches.csv\n",
      "input_data/cart1_big_patches.csv\n",
      "input_data/castle0_big_patches.csv\n",
      "input_data/castle1_big_patches.csv\n",
      "input_data/castle2_big_patches.csv\n",
      "input_data/chatnoir1_big_patches.csv\n",
      "input_data/chatnoir2_big_patches.csv\n",
      "input_data/chatnoir3_big_patches.csv\n",
      "input_data/chatnoir4_big_patches.csv\n",
      "input_data/chatnoir5_big_patches.csv\n",
      "input_data/chatnoir6_big_patches.csv\n",
      "input_data/church0_big_patches.csv\n",
      "input_data/church1_big_patches.csv\n",
      "input_data/corridor0_big_patches.csv\n",
      "input_data/corridor1_big_patches.csv\n",
      "input_data/corridor2_big_patches.csv\n",
      "input_data/dante0_big_patches.csv\n",
      "input_data/dante1_big_patches.csv\n",
      "input_data/dc0_big_patches.csv\n",
      "input_data/dc1_big_patches.csv\n",
      "input_data/dc2_big_patches.csv\n",
      "input_data/desk0_big_patches.csv\n",
      "input_data/desk1_big_patches.csv\n",
      "input_data/desk2_big_patches.csv\n",
      "input_data/dtua0_big_patches.csv\n",
      "input_data/dtua1_big_patches.csv\n",
      "input_data/dtua2_big_patches.csv\n",
      "input_data/dtub0_big_patches.csv\n",
      "input_data/dtub1_big_patches.csv\n",
      "input_data/dtub2_big_patches.csv\n",
      "input_data/dtuc0_big_patches.csv\n",
      "input_data/dtuc1_big_patches.csv\n",
      "input_data/dtuc2_big_patches.csv\n",
      "input_data/dtud0_big_patches.csv\n",
      "input_data/dtud1_big_patches.csv\n",
      "input_data/dtud2_big_patches.csv\n",
      "input_data/dtuf0_big_patches.csv\n",
      "input_data/dtuf1_big_patches.csv\n",
      "input_data/dtuf2_big_patches.csv\n",
      "input_data/dtug0_big_patches.csv\n",
      "input_data/dtug1_big_patches.csv\n",
      "input_data/dtug2_big_patches.csv\n",
      "input_data/duckhunt1_big_patches.csv\n",
      "input_data/duckhunt2_big_patches.csv\n",
      "input_data/duckhunt3_big_patches.csv\n",
      "input_data/duckhunt4_big_patches.csv\n",
      "input_data/duckhunt5_big_patches.csv\n",
      "input_data/duckhunt6_big_patches.csv\n",
      "input_data/et0_big_patches.csv\n",
      "input_data/et1_big_patches.csv\n",
      "input_data/et2_big_patches.csv\n",
      "input_data/facade0_big_patches.csv\n",
      "input_data/facade1_big_patches.csv\n",
      "input_data/floor1_big_patches.csv\n",
      "input_data/floor2_big_patches.csv\n",
      "input_data/floor3_big_patches.csv\n",
      "input_data/floor4_big_patches.csv\n",
      "input_data/floor5_big_patches.csv\n",
      "input_data/floor6_big_patches.csv\n",
      "input_data/fountain0_big_patches.csv\n",
      "input_data/fountain1_big_patches.csv\n",
      "input_data/fountain2_big_patches.csv\n",
      "input_data/frame0_big_patches.csv\n",
      "input_data/frame1_big_patches.csv\n",
      "input_data/graf1_big_patches.csv\n",
      "input_data/graf2_big_patches.csv\n",
      "input_data/graf3_big_patches.csv\n",
      "input_data/graf4_big_patches.csv\n",
      "input_data/graf5_big_patches.csv\n",
      "input_data/graf6_big_patches.csv\n",
      "input_data/groupsac0_big_patches.csv\n",
      "input_data/groupsac1_big_patches.csv\n",
      "input_data/herzjesu0_big_patches.csv\n",
      "input_data/herzjesu1_big_patches.csv\n",
      "input_data/herzjesu2_big_patches.csv\n",
      "input_data/horse0_big_patches.csv\n",
      "input_data/horse1_big_patches.csv\n",
      "input_data/kermit0_big_patches.csv\n",
      "input_data/kermit1_big_patches.csv\n",
      "input_data/kermit2_big_patches.csv\n",
      "input_data/marilyn1_big_patches.csv\n",
      "input_data/marilyn2_big_patches.csv\n",
      "input_data/marilyn3_big_patches.csv\n",
      "input_data/marilyn4_big_patches.csv\n",
      "input_data/marilyn5_big_patches.csv\n",
      "input_data/marilyn6_big_patches.csv\n",
      "input_data/mario1_big_patches.csv\n",
      "input_data/mario2_big_patches.csv\n",
      "input_data/mario3_big_patches.csv\n",
      "input_data/mario4_big_patches.csv\n",
      "input_data/mario5_big_patches.csv\n",
      "input_data/mario6_big_patches.csv\n",
      "input_data/op1_big_patches.csv\n",
      "input_data/op2_big_patches.csv\n",
      "input_data/op3_big_patches.csv\n",
      "input_data/op4_big_patches.csv\n",
      "input_data/op5_big_patches.csv\n",
      "input_data/op6_big_patches.csv\n",
      "input_data/outside1_big_patches.csv\n",
      "input_data/outside2_big_patches.csv\n",
      "input_data/outside3_big_patches.csv\n",
      "input_data/outside4_big_patches.csv\n",
      "input_data/outside5_big_patches.csv\n",
      "input_data/outside6_big_patches.csv\n",
      "input_data/pen0_big_patches.csv\n",
      "input_data/pen1_big_patches.csv\n",
      "input_data/pen2_big_patches.csv\n",
      "input_data/plant0_big_patches.csv\n",
      "input_data/plant1_big_patches.csv\n",
      "input_data/posters1_big_patches.csv\n",
      "input_data/posters2_big_patches.csv\n",
      "input_data/posters3_big_patches.csv\n",
      "input_data/posters4_big_patches.csv\n",
      "input_data/posters5_big_patches.csv\n",
      "input_data/posters6_big_patches.csv\n",
      "input_data/rooster0_big_patches.csv\n",
      "input_data/rooster1_big_patches.csv\n",
      "input_data/scale0_big_patches.csv\n",
      "input_data/scale1_big_patches.csv\n",
      "input_data/screen1_big_patches.csv\n",
      "input_data/screen2_big_patches.csv\n",
      "input_data/screen3_big_patches.csv\n",
      "input_data/screen4_big_patches.csv\n",
      "input_data/screen5_big_patches.csv\n",
      "input_data/screen6_big_patches.csv\n",
      "input_data/shelf0_big_patches.csv\n",
      "input_data/shelf1_big_patches.csv\n",
      "input_data/shelf2_big_patches.csv\n",
      "input_data/spidey1_big_patches.csv\n",
      "input_data/spidey2_big_patches.csv\n",
      "input_data/spidey3_big_patches.csv\n",
      "input_data/spidey4_big_patches.csv\n",
      "input_data/spidey5_big_patches.csv\n",
      "input_data/spidey6_big_patches.csv\n",
      "input_data/sponge0_big_patches.csv\n",
      "input_data/sponge1_big_patches.csv\n",
      "input_data/sponge2_big_patches.csv\n",
      "input_data/standing0_big_patches.csv\n",
      "input_data/standing1_big_patches.csv\n",
      "input_data/statue0_big_patches.csv\n",
      "input_data/statue1_big_patches.csv\n",
      "input_data/teddy0_big_patches.csv\n",
      "input_data/teddy1_big_patches.csv\n",
      "input_data/teddy2_big_patches.csv\n",
      "input_data/tribal0_big_patches.csv\n",
      "input_data/tribal1_big_patches.csv\n",
      "input_data/tribal2_big_patches.csv\n",
      "input_data/valbonne0_big_patches.csv\n",
      "input_data/valbonne1_big_patches.csv\n",
      "input_data/valencia0_big_patches.csv\n",
      "input_data/valencia1_big_patches.csv\n",
      "input_data/wall1_big_patches.csv\n",
      "input_data/wall2_big_patches.csv\n",
      "input_data/wall3_big_patches.csv\n",
      "input_data/wall4_big_patches.csv\n",
      "input_data/wall5_big_patches.csv\n",
      "input_data/wall6_big_patches.csv\n",
      "input_data/webcam0_big_patches.csv\n",
      "input_data/webcam1_big_patches.csv\n"
     ]
    }
   ],
   "source": [
    "for f in patches_fnames:\n",
    "    print (f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "fname = patches_fnames[3]\n",
    "patches = np.loadtxt(fname, delimiter=',')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "h,w = patches.shape\n",
    "PS = int(np.sqrt(w))\n",
    "num_p = h"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f2a90f2b690>"
      ]
     },
     "execution_count": 159,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Fixzsibm2Mi96hHiK2Wpe7V1Dmry9eKMVYt5WiRxrq5uB6xaTWlY6OOSVdySn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\nbDNkyJBhFvB/WDr6cC7iKOIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2a90f22050>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#i=0\n",
    "i+=1\n",
    "plt.imshow(255-patches[i,:].reshape(PS,PS))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}