{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "import pandas\n",
    "import shelve\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import itertools\n",
    "import glob\n",
    "from sklearn.metrics import precision_recall_fscore_support\n",
    "import utils\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "def show_network_TRANS(scores,zero=10,unite=120,tailleu=100,title=\"Transform NEwtork\"):\n",
    "    plt.figure(figsize=(20,10))\n",
    "    plt.axes()\n",
    "    plt.title(title)\n",
    "    #zero=10\n",
    "    #unite=200\n",
    "    #tailleu=100\n",
    "    inside=0\n",
    "    rectangle = plt.Rectangle((zero, zero), tailleu, tailleu, fc='b')\n",
    "    plt.gca().add_patch(rectangle)\n",
    "    if \"ASR_SPARSE\" in scores:\n",
    "        plt.text(zero+inside,zero+inside,scores[\"ASR_SPARSE\"],color=\"white\")\n",
    "        #plt.text(zero+inside+60,zero+inside,\"0.58\",color=\"red\")\n",
    " \n",
    "    rectangle = plt.Rectangle((zero, zero+unite), tailleu, tailleu, fc='b')\n",
    "    plt.gca().add_patch(rectangle)\n",
    "    if \"ASR_AE_H1\" in scores:\n",
    "        plt.text(zero+inside,zero+1*unite+inside,scores[\"ASR_AE_H1\"],color=\"white\")\n",
    " \n",
    "    rectangle = plt.Rectangle((zero, zero+2*unite), tailleu, tailleu, fc='b')\n",
    "    plt.gca().add_patch(rectangle)\n",
    "    if \"ASR_AE_H2\" in scores:\n",
    "        plt.text(zero+inside,zero+2*unite+inside,scores[\"ASR_AE_H2\"],color=\"white\")\n",
    " \n",
    "    rectangle = plt.Rectangle((zero, zero+3*unite), tailleu, tailleu, fc='b')\n",
    "    plt.gca().add_patch(rectangle)\n",
    "    if \"ASR_AE_OUT\" in scores:\n",
    "        plt.text(zero+inside,zero+3*unite+inside,scores[\"ASR_AE_OUT\"],color=\"white\")\n",
    " \n",
    "    \n",
    "    rectangle = plt.Rectangle((zero+3*unite, zero), tailleu, tailleu, fc='y')\n",
    "    plt.gca().add_patch(rectangle)\n",
    "    if \"TRS_SPARSE\" in scores:\n",
    "        plt.text(zero+3*unite+inside,zero+inside,scores[\"TRS_SPARSE\"],color=\"black\")\n",
    " \n",
    "    rectangle = plt.Rectangle((zero+3*unite, zero+1*unite), tailleu, tailleu, fc='y')\n",
    "    plt.gca().add_patch(rectangle)\n",
    "    if \"TRS_AE_H1\" in scores:\n",
    "        plt.text(zero+3*unite+inside,zero+1*unite+inside,scores[\"TRS_AE_H1\"],color=\"black\")\n",
    " \n",
    "    rectangle = plt.Rectangle((zero+3*unite, zero+2*unite), tailleu, tailleu, fc='y')\n",
    "    plt.gca().add_patch(rectangle)\n",
    "    if \"TRS_AE_H2\" in scores:\n",
    "        plt.text(zero+3*unite+inside,zero+2*unite+inside,scores[\"TRS_AE_H2\"],color=\"black\")\n",
    "    if \"ASR_H1_TRANFORMED_TRSH2\" in scores:\n",
    "        plt.text(zero+3*unite+tailleu/2,zero+2*unite+inside,scores[\"ASR_H1_TRANFORMED_TRSH2\"],color=\"red\")   \n",
    "    if \"ASR_H2_TRANFORMED_TRSH2\" in scores:\n",
    "        plt.text(zero+3*unite-tailleu/2,zero+2*unite+inside,scores[\"ASR_H2_TRANFORMED_TRSH2\"],color=\"green\")\n",
    " \n",
    "    rectangle = plt.Rectangle((zero+3*unite, zero+3*unite), tailleu, tailleu, fc='y')\n",
    "    plt.gca().add_patch(rectangle)\n",
    "    if \"TRS_AE_OUT\" in scores:\n",
    "        plt.text(zero+3*unite+inside,zero+3*unite+inside,scores[\"TRS_AE_OUT\"],color=\"black\")\n",
    "    if \"ASR_H1_TRANFORMED_OUT\" in scores:\n",
    "        plt.text(zero+3*unite+tailleu/2,zero+3*unite+inside,scores[\"ASR_H1_TRANFORMED_OUT\"],color=\"red\")\n",
    "    if \"ASR_H2_TRANFORMED_OUT\" in scores:\n",
    "        plt.text(zero+3*unite-tailleu/2,zero+3*unite+inside,scores[\"ASR_H2_TRANFORMED_OUT\"],color=\"green\")\n",
    "\n",
    "    rectangle = plt.Rectangle((zero+1*unite, zero+1*unite), tailleu, tailleu, fc='r')\n",
    "    plt.gca().add_patch(rectangle)\n",
    "    if \"ASR_H1_TRANSFORMED_W1\" in scores:\n",
    "        plt.text(zero+1*unite+inside,zero+1*unite+inside,scores[\"ASR_H1_TRANSFORMED_W1\"],color=\"black\")\n",
    " \n",
    "    rectangle = plt.Rectangle((zero+1*unite, zero+2*unite), tailleu, tailleu, fc='green')\n",
    "    plt.gca().add_patch(rectangle)\n",
    "    if \"ASR_H2_TRANSFORMED_W1\" in scores:\n",
    "        plt.text(zero+1*unite+inside,zero+2*unite+inside,scores[\"ASR_H2_TRANSFORMED_W1\"],color=\"white\")\n",
    " \n",
    "\n",
    "    rectangle = plt.Rectangle((zero+2*unite, zero+1*unite), tailleu, tailleu, fc='r')\n",
    "    plt.gca().add_patch(rectangle)\n",
    "    if \"ASR_H1_TRANSFORMED_W2\" in scores:\n",
    "        plt.text(zero+2*unite+inside,zero+1*unite+inside,scores[\"ASR_H1_TRANSFORMED_W2\"],color=\"black\")\n",
    " \n",
    "    rectangle = plt.Rectangle((zero+2*unite, zero+2*unite), tailleu, tailleu, fc='green')\n",
    "    plt.gca().add_patch(rectangle)\n",
    "    if \"ASR_H2_TRANSFORMED_W2\" in scores:\n",
    "        plt.text(zero+2*unite+inside,zero+2*unite+inside,scores[\"ASR_H2_TRANSFORMED_W2\"],color=\"white\")\n",
    "\n",
    "    plt.axis('scaled')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "\n",
    "def show_network_RSPE(scores,zero=10,unite=120,tailleu=100,title=\"REAL SPE NEwtork\"):\n",
    "    plt.figure(figsize=(20,10))\n",
    "    plt.axes()\n",
    "    plt.title(title)\n",
    "    #zero=10\n",
    "    #unite=200\n",
    "    #tailleu=100\n",
    "    inside=0\n",
    "    rectangle = plt.Rectangle((zero, zero), tailleu, tailleu, fc='b')\n",
    "    plt.gca().add_patch(rectangle)\n",
    "    if \"ASR\" in scores:\n",
    "        plt.text(zero+inside,zero+inside,scores[\"ASR\"],color=\"white\")\n",
    " \n",
    "    rectangle = plt.Rectangle((zero, zero+unite), tailleu, tailleu, fc='b')\n",
    "    plt.gca().add_patch(rectangle)\n",
    "    if \"ASR_AE_H1\" in scores:\n",
    "        plt.text(zero+inside,zero+1*unite+inside,scores[\"ASR_AE_H1\"],color=\"white\")\n",
    " \n",
    "    rectangle = plt.Rectangle((zero, zero+2*unite), tailleu, tailleu, fc='b')\n",
    "    plt.gca().add_patch(rectangle)\n",
    "    if \"ASR_AE_H2\" in scores:\n",
    "        plt.text(zero+inside,zero+2*unite+inside,scores[\"ASR_AE_H2\"],color=\"white\")\n",
    "    if \"ASR_AEH2_SPARSE\" in scores :\n",
    "         plt.text(zero+inside,zero+2*unite+inside,scores[\"ASR_AEH2_SPARSE\"],color=\"white\")\n",
    "    rectangle = plt.Rectangle((zero, zero+3*unite), tailleu, tailleu, fc='b')\n",
    "    plt.gca().add_patch(rectangle)\n",
    "    if \"ASR_AE_OUT\" in scores:\n",
    "        plt.text(zero+inside,zero+3*unite+inside,scores[\"ASR_AE_OUT\"],color=\"white\")\n",
    "    if \"ASR_AEOUT_SPARSE\" in scores :\n",
    "         plt.text(zero+inside,zero+3*unite+inside,scores[\"ASR_AEOUT_SPARSE\"],color=\"white\")\n",
    "    \n",
    "   \n",
    "    plt.axis('scaled')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#'', '', '', '', '', '', '', '', 'ASR_W1_TRANSFORMED', 'ASR_AE_H1']\n",
    "\n",
    "def show_network_UNFIXED(scores,zero=10,unite=120,tailleu=100,title=\"Transform NEwtork\"):\n",
    "    plt.figure(figsize=(20,10))\n",
    "    plt.axes()\n",
    "    plt.title(title)\n",
    "    #zero=10\n",
    "    #unite=200\n",
    "    #tailleu=100\n",
    "    inside=0\n",
    "    rectangle = plt.Rectangle((zero, zero), tailleu, tailleu, fc='b')\n",
    "    plt.gca().add_patch(rectangle)\n",
    "    if \"ASR_SPARSE\" in scores:\n",
    "        plt.text(zero+inside,zero+inside,scores[\"ASR_SPARSE\"],color=\"white\")\n",
    "        #plt.text(zero+inside+60,zero+inside,\"0.58\",color=\"red\")\n",
    " \n",
    "    rectangle = plt.Rectangle((zero, zero+unite), tailleu, tailleu, fc='b')\n",
    "    plt.gca().add_patch(rectangle)\n",
    "    if \"ASR_AE_H1\" in scores:\n",
    "        plt.text(zero+inside,zero+1*unite+inside,scores[\"ASR_AE_H1\"],color=\"white\")\n",
    "    if \"ASR_H1_TRANSFORMED\" in scores:\n",
    "        plt.text(zero+inside+tailleu,zero+1*unite+inside,scores[\"ASR_H1_TRANSFORMED\"],color=\"green\")\n",
    " \n",
    "    rectangle = plt.Rectangle((zero, zero+2*unite), tailleu, tailleu, fc='b')\n",
    "    plt.gca().add_patch(rectangle)\n",
    "    if \"ASR_AE_OUT\" in scores:\n",
    "        plt.text(zero+inside,zero+2*unite+inside,scores[\"ASR_AE_OUT\"],color=\"white\")\n",
    "\n",
    "    \n",
    "    rectangle = plt.Rectangle((zero+3*unite, zero), tailleu, tailleu, fc='y')\n",
    "    plt.gca().add_patch(rectangle)\n",
    "    if \"TRS_SPARSE\" in scores:\n",
    "        plt.text(zero+3*unite+inside,zero+inside,scores[\"TRS_SPARSE\"],color=\"black\")\n",
    " \n",
    "    rectangle = plt.Rectangle((zero+3*unite, zero+1*unite), tailleu, tailleu, fc='y')\n",
    "    plt.gca().add_patch(rectangle)\n",
    "    if \"TRS_AE_H1\" in scores:\n",
    "        plt.text(zero+3*unite+inside,zero+1*unite+inside,scores[\"TRS_AE_H1\"],color=\"black\")\n",
    "    if \"ASR_H2_TRANSFORMED\" in scores:\n",
    "        plt.text(zero+3*unite+inside-tailleu,zero+1*unite+inside,scores[\"ASR_H2_TRANSFORMED\"],color=\"green\")\n",
    " \n",
    "    rectangle = plt.Rectangle((zero+3*unite, zero+2*unite), tailleu, tailleu, fc='y')\n",
    "    plt.gca().add_patch(rectangle)\n",
    "    if \"TRS_AE_OUT\" in scores:\n",
    "        plt.text(zero+3*unite+inside,zero+2*unite+inside,scores[\"TRS_AE_OUT\"],color=\"black\")\n",
    "    if \"ASR_TRANFORMED_OUT\" in scores:\n",
    "        plt.text(zero+3*unite+inside-tailleu,zero+2*unite+inside,scores[\"ASR_TRANFORMED_OUT\"],color=\"green\")\n",
    " \n",
    "\n",
    " \n",
    "    rectangle = plt.Rectangle((zero+1*unite, zero+1*unite), tailleu, tailleu, fc='green')\n",
    "    plt.gca().add_patch(rectangle)\n",
    "    if \"ASR_W1_TRANSFORMED\" in scores:\n",
    "        plt.text(zero+1*unite+inside,zero+1*unite+inside,scores[\"ASR_W1_TRANSFORMED\"],color=\"white\")\n",
    "\n",
    "\n",
    "    plt.axis('scaled')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "#['ASR_H1_TRANFORMED_OUT', 'ASR_H2_TRANFORMED_OUT', 'TRS_AE_OUT', 'TRS_SPARSE', 'ASR_SPARSE']\n",
    "def show_network_RAW(scores,zero=10,unite=120,tailleu=100,title=\"RAW NEwtork\"):\n",
    "    plt.figure(figsize=(20,10))\n",
    "    plt.axes()\n",
    "    plt.title(title)\n",
    "    #zero=10\n",
    "    #unite=200\n",
    "    #tailleu=100\n",
    "    inside=0\n",
    "    rectangle = plt.Rectangle((zero, zero), tailleu, tailleu, fc='b')\n",
    "    plt.gca().add_patch(rectangle)\n",
    "    if \"SPARSE\" in scores:\n",
    "        plt.text(zero+inside,zero+inside,scores[\"ASR\"],color=\"white\")\n",
    " \n",
    "    rectangle = plt.Rectangle((zero, zero+unite), tailleu, tailleu, fc='b')\n",
    "    plt.gca().add_patch(rectangle)\n",
    "    if \"ASR_AE_H1\" in scores:\n",
    "        plt.text(zero+inside,zero+1*unite+inside,scores[\"ASR_AE_H1\"],color=\"white\")\n",
    " \n",
    "    rectangle = plt.Rectangle((zero, zero+2*unite), tailleu, tailleu, fc='b')\n",
    "    plt.gca().add_patch(rectangle)\n",
    "    if \"ASR_AE_H2\" in scores:\n",
    "        plt.text(zero+inside,zero+2*unite+inside,scores[\"ASR_AE_H2\"],color=\"white\")\n",
    "    if \"ASR_AEH2_SPARSE\" in scores :\n",
    "         plt.text(zero+inside,zero+2*unite+inside,scores[\"ASR_AEH2_SPARSE\"],color=\"white\")\n",
    "    rectangle = plt.Rectangle((zero, zero+3*unite), tailleu, tailleu, fc='b')\n",
    "    plt.gca().add_patch(rectangle)\n",
    "    if \"ASR_AE_OUT\" in scores:\n",
    "        plt.text(zero+inside,zero+3*unite+inside,scores[\"ASR_AE_OUT\"],color=\"white\")\n",
    "    if \"ASR_AEOUT_SPARSE\" in scores :\n",
    "         plt.text(zero+inside,zero+3*unite+inside,scores[\"ASR_AEOUT_SPARSE\"],color=\"white\")\n",
    "    \n",
    "   \n",
    "    plt.axis('scaled')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "scores/DECODA_MINIAE_TANH_H50_DO.shelve\n"
     ]
    },
    {
     "data": {
      "image/png": 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x9epWJKcn43Twacw8OhMA8Pdbf6Pp0qZ4q8Vb0Gj1g4rdndxx4t4JzO46G18d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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f79574b4650>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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ph5XM/JsOnfcfKAPNJW0ABg1dwOsoc5T0zQX0M8odSr0R0dUM4h1H+TtqUFq2Wm/PncCK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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f79605d8dd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "scores/MINIAE_TANH_H100_DO50.shelve\n"
     ]
    },
    {
     "data": {
      "image/png": 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H5yDgYQAyFBnwC/GDz20fZCozNX14LeYaGtg1wMwuM3Hh4QW8u+9d+I3N/ZXx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\nRxUa+NSJyJqANQWeuxl7M08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QjBLETTmIM8aYQZT9JYaciTPGmMGUeRB/ouRMnDHGDMU4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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f795e212890>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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MeOGG0tLVBXw3IrLZ//zMnBsRPwcuioiTgXsoTyySmfMi4iJgHrAcOG3QdCVJ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\nqGYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f796a9ad5d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "scores/MINIAE_TANH_H100_DOmlp.shelve\n"
     ]
    },
    {
     "data": {
      "image/png": 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DC4EXEBYfhpJWJVHHrg461+qMiYcnwtbaFhc+u4ALgRfQr2E/1Heuj5DYECy9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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f795c2c7cd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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9OGBBy3MXNuskSZI61mDvXtwvM/8YEdsDV0XEnaw40r3zRtVJkiQN0qBCV2b+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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f795eee7510>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "scores/DECODA_MINIAE_TANH_TFIDF_H30_DO.shelve\n"
     ]
    },
    {
     "data": {
      "image/png": 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hMWEYYzgZd5Lh7e0X8ODZg8zfPZ8RHUcwculI5u2eR2JqIsPbD2fYkmEU9yyO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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f798a54de10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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09MwZ6mIMO50TOuld0DvUxRh2OsZ30HNfz1AXY1jxXmnPe6W9SZM6mT/f+6Wv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\n6OIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f79601db210>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "scores_ordoned={}\n",
    "for i in glob.glob(\"scores/*DO*.bak\"):\n",
    "    #if \"MINIAE\" not in i :\n",
    "     #   continue\n",
    "    scores={}\n",
    "    print i[:-4]\n",
    "    data=shelve.open(i[:-4])\n",
    "    for key,table in data.iteritems():\n",
    "        scores[key]=round(table[1][np.argmax([x[0] for x in table[0]])][0],3)\n",
    "        if key not in scores_ordoned:\n",
    "            scores_ordoned[key]=[scores[key]]\n",
    "        else :\n",
    "            scores_ordoned[key].append(scores[key])\n",
    "            \n",
    "    pandas.DataFrame(zip([x[0] for x in data[\"ASR_H1_TRANSFORMED_W1\"][0] ],[x[0] for x in data[\"ASR_H1_TRANSFORMED_W1\"][1] ])).plot()\n",
    "    data.close()\n",
    "    show_network_TRANS(scores,title=i,unite=200)\n",
    "    #except:\n",
    "    #    print \"C4EST LA MERDE\",i"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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DZq4CVgLztmujJe1UDJKdSEQcDLwC+BegLzMHoIQNMLMWmw2s6ZhsbR0mSWNi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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7962573290>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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jB+ukrYmfqJGP3tksXKiracORs9wBfdcMt9z5bOi8PN2ygRzud6fUOGhtDlvu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\nABLJPQiCYADyFxwqhuWLhx2jAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f795f579890>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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B8DiavIKR7OvMjHGukCYZ70gmucxcnZl31vc/AZZQAuIU4PI62eXAqfX9ycCC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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f795f5793d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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U1QHXXBMeufsr2yxyV+eHCheGyJ0xtoYxdpAxdpgx9mON7/MZY28xxnYzxmoZ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\nFq12EO5zQv4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f796883cc50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "for i in glob.glob(\"real_spe_scores/*DO*.bak\"):\n",
    "    scores={}\n",
    "    data=shelve.open(i[:-4])\n",
    "    for key,table in data.iteritems():\n",
    "        scores[key]=round(table[1][np.argmax([x[0] for x in table[0]])][0],3)\n",
    "    show_network_RSPE(scores,title=i)\n",
    "    pandas.DataFrame(zip([x[0] for x in data[\"ASR_AE_H1\"][0] ],[x[0] for x in data[\"ASR_AE_H1\"][1] ])).plot()\n",
    "    data.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DECODA_AEUNFIXED_TANH_TFIDF_DO.shelve.bak\r\n",
      "DECODA_AEUNFIXED_TANH_TFIDF_DO.shelve.dat\r\n",
      "DECODA_AEUNFIXED_TANH_TFIDF_DO.shelve.dir\r\n",
      "DECODA_AEUNFIXED_TANH_TFIDF_MODELS.shelve.bak\r\n",
      "DECODA_AEUNFIXED_TANH_TFIDF_MODELS.shelve.dat\r\n",
      "DECODA_AEUNFIXED_TANH_TFIDF_MODELS.shelve.dir\r\n"
     ]
    }
   ],
   "source": [
    "ls UNFIXED_TRANS_scores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "UNFIXED_TRANS_scores/DECODA_AEUNFIXED_TANH_TFIDF_DO.shelve\n",
      "['TRS_AE_H1', 'TRS_AE_OUT', 'TRS_SPARSE', 'ASR_AE_OUT', 'ASR_H2_TRANSFORMED', 'ASR_SPARSE', 'ASR_TRANFORMED_OUT', 'ASR_H1_TRANSFORMED', 'ASR_W1_TRANSFORMED', 'ASR_AE_H1']\n"
     ]
    },
    {
     "data": {
      "image/png": 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F0ZWgK4kHxupLq8nngA/lHJOTuq3vlip9WEwYeUz1oDkn56Ta9izyGcXEG7+l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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f79518de350>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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0Jdn9xN0z/QPTM/ths7PbQ3ZLkpx+2emZNXVWHjftcfftCqynHvKQFV8vDQhL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\nFHEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f79650b2d50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "scores_ordoned={}\n",
    "for i in glob.glob(\"UNFIXED_TRANS_scores/*DO*.bak\"):\n",
    "    scores={}\n",
    "    print i[:-4]\n",
    "    data=shelve.open(i[:-4])\n",
    "    print data.keys()\n",
    "    for key,table in data.iteritems():\n",
    "        scores[key]=round(table[1][np.argmax([x[0] for x in table[0]])][0],3)\n",
    "        if key not in scores_ordoned:\n",
    "            scores_ordoned[key]=[scores[key]]\n",
    "        else :\n",
    "            scores_ordoned[key].append(scores[key])\n",
    "            \n",
    "    pandas.DataFrame(zip([x[0] for x in data[\"ASR_W1_TRANSFORMED\"][0] ],[x[0] for x in data[\"ASR_W1_TRANSFORMED\"][1] ])).plot()\n",
    "    data.close()\n",
    "    show_network_UNFIXED(scores,title=i,unite=200)\n",
    "    #except:\n",
    "    #    print \"C4EST LA MERDE\",i"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "# Ci dessous  Mes tests rien de super interessant"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "pred_train=data[\"TRS_AE_H2\"][2].pred_train\n",
    "y_pred_train=np.argmax(pred_train,axis=1)\n",
    "\n",
    "pred_dev=data[\"TRS_AE_H2\"][2].pred_dev\n",
    "y_pred_dev=np.argmax(pred_dev,axis=1)\n",
    "\n",
    "pred_test=data[\"TRS_AE_H2\"][2].pred_test\n",
    "y_pred_test=np.argmax(pred_test,axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "[0,1,2]*3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "corps=shelve.open(\"models/DECODA_AE_TANH_MINIBIN.shelve\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "y_train=corps[\"LABEL\"][\"TRAIN\"].apply(utils.select).values\n",
    "y_dev=corps[\"LABEL\"][\"DEV\"].apply(utils.select).values\n",
    "y_test=corps[\"LABEL\"][\"TEST\"].apply(utils.select).values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "y_pred_train+1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "y_train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "precision_recall_fscore_support(y_train,y_pred_train+1,average=\"micro\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "precision_recall_fscore_support(y_dev,y_pred_dev+1,average=\"micro\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "precision_recall_fscore_support(y_test,y_pred_test+1,average=\"micro\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data=shelve.open(\"scores/DECODA_AE_TANH_MINIBIN.shelve\")\n",
    "#data.close()\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data=shelve.open(\"./scores/DECODA_MINIAE_TANH.shelve\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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6dZIkSesJ70gvSZJUgKFLkiSpAEOXJElSAYYuSZKkAgxdkiRJBRi6JEmSCjB0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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7966f3cb90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "scores={}\n",
    "#del scores_ordoned\n",
    "for key,table in data.iteritems():\n",
    "    scores[key]=round(table[1][np.argmax([x[0] for x in table[0]])][0],3)\n",
    "   # if key not in scores_ordoned:\n",
    "   #     scores_ordoned[key]=[scores[key]]\n",
    "   # else :\n",
    "   #     scores_ordoned[key].append(scores[key])\n",
    "#data.close()\n",
    "show_network_TRANS(scores,title=i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f7968041f10>"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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7BoCT2p3E6R1P508X/Kmk7d78vfR9si9r71gbxdvw389n/Zx+7ftxTZ9rymyP/L/NPZTL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\nIiIBpiQuIhJg/x8BfgCfnnzDaQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7965dfab10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pandas.DataFrame(zip([x[0] for x in data[\"ASR_AE_H1\"][0] ],[x[0] for x in data[\"ASR_AE_H1\"][1] ])).plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "histo=data[\"ASR_AE_H1\"][3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "corps=data=shelve.open(\"./models/DECODA_MINIAE_TANH.shelve\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>...</th>\n",
       "      <th>40</th>\n",
       "      <th>41</th>\n",
       "      <th>42</th>\n",
       "      <th>43</th>\n",
       "      <th>44</th>\n",
       "      <th>45</th>\n",
       "      <th>46</th>\n",
       "      <th>47</th>\n",
       "      <th>48</th>\n",
       "      <th>49</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "      <td>740.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.000490</td>\n",
       "      <td>0.003229</td>\n",
       "      <td>0.000185</td>\n",
       "      <td>-0.003558</td>\n",
       "      <td>-0.000550</td>\n",
       "      <td>0.004855</td>\n",
       "      <td>-0.000353</td>\n",
       "      <td>-0.004828</td>\n",
       "      <td>0.000823</td>\n",
       "      <td>-0.004653</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.002893</td>\n",
       "      <td>0.001393</td>\n",
       "      <td>0.000034</td>\n",
       "      <td>-0.000325</td>\n",
       "      <td>-0.000867</td>\n",
       "      <td>-0.001082</td>\n",
       "      <td>-0.004496</td>\n",
       "      <td>-0.005450</td>\n",
       "      <td>0.006736</td>\n",
       "      <td>0.001526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.078052</td>\n",
       "      <td>0.076671</td>\n",
       "      <td>0.080473</td>\n",
       "      <td>0.080584</td>\n",
       "      <td>0.080445</td>\n",
       "      <td>0.083181</td>\n",
       "      <td>0.080656</td>\n",
       "      <td>0.080346</td>\n",
       "      <td>0.078400</td>\n",
       "      <td>0.084584</td>\n",
       "      <td>...</td>\n",
       "      <td>0.075171</td>\n",
       "      <td>0.082434</td>\n",
       "      <td>0.076875</td>\n",
       "      <td>0.078159</td>\n",
       "      <td>0.081996</td>\n",
       "      <td>0.080196</td>\n",
       "      <td>0.084964</td>\n",
       "      <td>0.083766</td>\n",
       "      <td>0.081879</td>\n",
       "      <td>0.081213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-0.222832</td>\n",
       "      <td>-0.210684</td>\n",
       "      <td>-0.203158</td>\n",
       "      <td>-0.220618</td>\n",
       "      <td>-0.251787</td>\n",
       "      <td>-0.245800</td>\n",
       "      <td>-0.319214</td>\n",
       "      <td>-0.257791</td>\n",
       "      <td>-0.256614</td>\n",
       "      <td>-0.269018</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.205919</td>\n",
       "      <td>-0.272927</td>\n",
       "      <td>-0.216589</td>\n",
       "      <td>-0.232542</td>\n",
       "      <td>-0.239660</td>\n",
       "      <td>-0.215522</td>\n",
       "      <td>-0.237121</td>\n",
       "      <td>-0.217695</td>\n",
       "      <td>-0.253268</td>\n",
       "      <td>-0.216798</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-0.049280</td>\n",
       "      <td>-0.051630</td>\n",
       "      <td>-0.055798</td>\n",
       "      <td>-0.060583</td>\n",
       "      <td>-0.053978</td>\n",
       "      <td>-0.050834</td>\n",
       "      <td>-0.055398</td>\n",
       "      <td>-0.058382</td>\n",
       "      <td>-0.045658</td>\n",
       "      <td>-0.061431</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.052172</td>\n",
       "      <td>-0.051161</td>\n",
       "      <td>-0.054269</td>\n",
       "      <td>-0.053610</td>\n",
       "      <td>-0.054938</td>\n",
       "      <td>-0.056238</td>\n",
       "      <td>-0.066248</td>\n",
       "      <td>-0.068832</td>\n",
       "      <td>-0.048655</td>\n",
       "      <td>-0.054703</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>-0.003148</td>\n",
       "      <td>-0.002347</td>\n",
       "      <td>0.003714</td>\n",
       "      <td>-0.000112</td>\n",
       "      <td>-0.003216</td>\n",
       "      <td>0.007316</td>\n",
       "      <td>-0.000941</td>\n",
       "      <td>-0.004883</td>\n",
       "      <td>0.007292</td>\n",
       "      <td>-0.004308</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.004255</td>\n",
       "      <td>0.000609</td>\n",
       "      <td>-0.001102</td>\n",
       "      <td>-0.001316</td>\n",
       "      <td>-0.002811</td>\n",
       "      <td>0.000356</td>\n",
       "      <td>-0.000773</td>\n",
       "      <td>-0.008352</td>\n",
       "      <td>0.006316</td>\n",
       "      <td>-0.005236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.053316</td>\n",
       "      <td>0.051167</td>\n",
       "      <td>0.051243</td>\n",
       "      <td>0.054151</td>\n",
       "      <td>0.044473</td>\n",
       "      <td>0.058679</td>\n",
       "      <td>0.054497</td>\n",
       "      <td>0.044757</td>\n",
       "      <td>0.052775</td>\n",
       "      <td>0.050786</td>\n",
       "      <td>...</td>\n",
       "      <td>0.044183</td>\n",
       "      <td>0.056505</td>\n",
       "      <td>0.054361</td>\n",
       "      <td>0.052624</td>\n",
       "      <td>0.049942</td>\n",
       "      <td>0.053420</td>\n",
       "      <td>0.056256</td>\n",
       "      <td>0.049547</td>\n",
       "      <td>0.060626</td>\n",
       "      <td>0.050734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>0.202271</td>\n",
       "      <td>0.241509</td>\n",
       "      <td>0.310983</td>\n",
       "      <td>0.215986</td>\n",
       "      <td>0.279413</td>\n",
       "      <td>0.259838</td>\n",
       "      <td>0.224492</td>\n",
       "      <td>0.234719</td>\n",
       "      <td>0.283880</td>\n",
       "      <td>0.251888</td>\n",
       "      <td>...</td>\n",
       "      <td>0.229372</td>\n",
       "      <td>0.252486</td>\n",
       "      <td>0.237473</td>\n",
       "      <td>0.236919</td>\n",
       "      <td>0.300617</td>\n",
       "      <td>0.227033</td>\n",
       "      <td>0.250967</td>\n",
       "      <td>0.276590</td>\n",
       "      <td>0.261683</td>\n",
       "      <td>0.316733</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 50 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               0           1           2           3           4           5   \\\n",
       "count  740.000000  740.000000  740.000000  740.000000  740.000000  740.000000   \n",
       "mean     0.000490    0.003229    0.000185   -0.003558   -0.000550    0.004855   \n",
       "std      0.078052    0.076671    0.080473    0.080584    0.080445    0.083181   \n",
       "min     -0.222832   -0.210684   -0.203158   -0.220618   -0.251787   -0.245800   \n",
       "25%     -0.049280   -0.051630   -0.055798   -0.060583   -0.053978   -0.050834   \n",
       "50%     -0.003148   -0.002347    0.003714   -0.000112   -0.003216    0.007316   \n",
       "75%      0.053316    0.051167    0.051243    0.054151    0.044473    0.058679   \n",
       "max      0.202271    0.241509    0.310983    0.215986    0.279413    0.259838   \n",
       "\n",
       "               6           7           8           9      ...              40  \\\n",
       "count  740.000000  740.000000  740.000000  740.000000     ...      740.000000   \n",
       "mean    -0.000353   -0.004828    0.000823   -0.004653     ...       -0.002893   \n",
       "std      0.080656    0.080346    0.078400    0.084584     ...        0.075171   \n",
       "min     -0.319214   -0.257791   -0.256614   -0.269018     ...       -0.205919   \n",
       "25%     -0.055398   -0.058382   -0.045658   -0.061431     ...       -0.052172   \n",
       "50%     -0.000941   -0.004883    0.007292   -0.004308     ...       -0.004255   \n",
       "75%      0.054497    0.044757    0.052775    0.050786     ...        0.044183   \n",
       "max      0.224492    0.234719    0.283880    0.251888     ...        0.229372   \n",
       "\n",
       "               41          42          43          44          45          46  \\\n",
       "count  740.000000  740.000000  740.000000  740.000000  740.000000  740.000000   \n",
       "mean     0.001393    0.000034   -0.000325   -0.000867   -0.001082   -0.004496   \n",
       "std      0.082434    0.076875    0.078159    0.081996    0.080196    0.084964   \n",
       "min     -0.272927   -0.216589   -0.232542   -0.239660   -0.215522   -0.237121   \n",
       "25%     -0.051161   -0.054269   -0.053610   -0.054938   -0.056238   -0.066248   \n",
       "50%      0.000609   -0.001102   -0.001316   -0.002811    0.000356   -0.000773   \n",
       "75%      0.056505    0.054361    0.052624    0.049942    0.053420    0.056256   \n",
       "max      0.252486    0.237473    0.236919    0.300617    0.227033    0.250967   \n",
       "\n",
       "               47          48          49  \n",
       "count  740.000000  740.000000  740.000000  \n",
       "mean    -0.005450    0.006736    0.001526  \n",
       "std      0.083766    0.081879    0.081213  \n",
       "min     -0.217695   -0.253268   -0.216798  \n",
       "25%     -0.068832   -0.048655   -0.054703  \n",
       "50%     -0.008352    0.006316   -0.005236  \n",
       "75%      0.049547    0.060626    0.050734  \n",
       "max      0.276590    0.261683    0.316733  \n",
       "\n",
       "[8 rows x 50 columns]"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pandas.DataFrame(corps[\"ASR_AE_H1\"][\"TRAIN\"]).describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "corps.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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Tnzjcf9ppyZ/8yRBszLTKbLzOqip3Z4itC5M8JsnTkpyVIcLW+/MkP0vyziQ/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\ngegCAOhAdAEAdPD/A3/Pztj3soiSAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7968a860d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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ZNGwT9SvWZ/ep3QRPCmbJg0s4ePYgH6z6gM2Pb85e1sGzBynlUYo3l72Jv48/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\nGsSVUsqFaRBXSikX9v9GJVy78s6pUwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7964811fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data=shelve.open(\"./scores/DECODA_MINIAE_TANH_TFIDF_H30.shelve\")\n",
    "scores={}\n",
    "#del scores_ordoned\n",
    "for key,table in data.iteritems():\n",
    "    scores[key]=round(table[1][np.argmax([x[0] for x in table[0]])][0],3)\n",
    "   # if key not in scores_ordoned:\n",
    "   #     scores_ordoned[key]=[scores[key]]\n",
    "   # else :\n",
    "   #     scores_ordoned[key].append(scores[key])\n",
    "#data.close()\n",
    "show_network_TRANS(scores)\n",
    "pandas.DataFrame(zip([x[0] for x in data[\"ASR_AE_H1\"][0] ],[x[0] for x in data[\"ASR_AE_H1\"][1] ])).plot()\n",
    "data.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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GNyb3vW9y6qnJfvsNr01MJOvXJ3vskdxyS7LLLskXv5i87nXJl740bO/CC5PW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\n1XxXge3g/I0v5268OX87t7l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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7959a247d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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QqV3btrSqVrXvlS1rv1jHj4vcfbf9uZmYaPMbN84eWNK33fvvi3TrZtNHR9t5t91mu2my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\nEaZBXCmlijAN4kopVYRpEFdKqSLs/wG1uJNL8RfZnwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f795cb007d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data=shelve.open(\"./scores/DECODA_MINIAE_TANH_TFIDF_H30_DO.shelve\")\n",
    "scores={}\n",
    "#del scores_ordoned\n",
    "for key,table in data.iteritems():\n",
    "    scores[key]=round(table[1][np.argmax([x[0] for x in table[0]])][0],3)\n",
    "   # if key not in scores_ordoned:\n",
    "   #     scores_ordoned[key]=[scores[key]]\n",
    "   # else :\n",
    "   #     scores_ordoned[key].append(scores[key])\n",
    "#data.close()\n",
    "show_network_TRANS(scores)\n",
    "pandas.DataFrame(zip([x[0] for x in data[\"ASR_AE_H1\"][0] ],[x[0] for x in data[\"ASR_AE_H1\"][1] ])).plot()\n",
    "data.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.1998101 ,  0.12073141,  0.10901488, ...,  0.25165449,\n",
       "        0.07732746,  0.08457387])"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shelve.open(\"./Sparse_mat_tfidf.shelve\")[\"ASR\"][\"TRAIN\"].data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data=shelve.open(\"./real_spe_scores/REAL_SPE_1060_TFIDF.shelve\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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dwAl9GPKrwOeByjcd9Rj3ROAZSbeVhzY3Szqmv2NHxHPATcA2oBN4ISKW1mnO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\njtrScdSWjqO2dBy1pfP/ARY+jY+DVQ54AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7957629e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f795be7b150>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "scores={}\n",
    "#del scores_ordoned\n",
    "for key,table in data.iteritems():\n",
    "    scores[key]=round(table[1][np.argmax([x[0] for x in table[0]])][0],3)\n",
    "   # if key not in scores_ordoned:\n",
    "   #     scores_ordoned[key]=[scores[key]]\n",
    "   # else :\n",
    "   #     scores_ordoned[key].append(scores[key])\n",
    "#data.close()\n",
    "show_network_RSPE(scores)pandas.DataFrame(zip([x[0] for x in data[\"ASR_AE_H1\"][0] ],[x[0] for x in data[\"ASR_AE_H1\"][1] ])).plot()\n",
    "data.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['ASR', 'TRS_AE_OUT', 'ASR_AE_OUT', 'TRS', 'ASR_AE_H2', 'ASR_AE_H1']"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Zjz+euffeL12+aFHmhg2ZP/hB5ne+k3n99d0+kjUTT2N/nQdf626/N4eeZsS/CjF37oEM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\nRiQVGZFUZERS0f8HCCKkAcjDk6gAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7989b39d10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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biwTwfnKPsXIPbMvMXz+fRZctouj2Ipb8cAlprdIY0X0EBXsKQlYGtbaWj3d9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\n/AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f79595c9410>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data=shelve.open(\"./real_spe_scores/DECODA_MINIAE_REAL_SPE_H50.shelve\")\n",
    "scores={}\n",
    "#del scores_ordoned\n",
    "for key,table in data.iteritems():\n",
    "    scores[key]=round(table[1][np.argmax([x[0] for x in table[0]])][0],3)\n",
    "   # if key not in scores_ordoned:\n",
    "   #     scores_ordoned[key]=[scores[key]]\n",
    "   # else :\n",
    "   #     scores_ordoned[key].append(scores[key])\n",
    "#data.close()\n",
    "show_network_RSPE(scores,title=\"DECODA_MINIAE_REAL_SPE_H50\")\n",
    "pandas.DataFrame(zip([x[0] for x in data[\"ASR_AE_H1\"][0] ],[x[0] for x in data[\"ASR_AE_H1\"][1] ])).plot()\n",
    "data.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data=shelve.open(\"./scores/DECODA_MINIAE_TANH_TFIDF_H30_DO.shelve\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['TRS_AE_H1',\n",
       " 'TRS_AE_OUT',\n",
       " 'TRS_SPARSE',\n",
       " 'ASR_H1_TRANFORMED_TRSH1',\n",
       " 'ASR_AE_OUT',\n",
       " 'ASR_H2_TRANFORMED_OUT',\n",
       " 'ASR_SPARSE',\n",
       " 'ASR_H1_TRANSFORMED_W1',\n",
       " 'ASR_AE_H1']"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "scores/DECODA_MINIAE_TANH_H50_DO.shelve\n"
     ]
    },
    {
     "data": {
      "image/png": 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x9epWJKcn43Twacw8OhMA8Pdbf6Pp0qZ4q8Vb0Gj1g4rdndxx4t4JzO46G18d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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f795883e850>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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ph5XM/JsOnfcfKAPNJW0ABg1dwOsoc5T0zQX0M8odSr0R0dUM4h1H+TtqUFq2Wm/PncCK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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f795883e9d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "scores/MINIAE_TANH_H100_DO50.shelve\n"
     ]
    },
    {
     "data": {
      "image/png": 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H5yDgYQAyFBnwC/GDz20fZCozNX14LeYaGtg1wMwuM3Hh4QW8u+9d+I3N/ZXx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\nRxUa+NSJyJqANQWeuxl7M08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QjBLETTmIM8aYQZT9JYaciTPGmMGUeRB/ouRMnDHGDMU4\nwymCgzhjjBmCUa5O4UycMcYMwyjDKWb5MnEXFxcIISrEn4uLS1l3KWOsEjPUj0Lo7IkiG6Yi733E\nw8LCUNJ9zcsLvjsjY6wsGWE4JQvmwqqsF8sYYxWSEe5imAlzYVnWi2WMsQqp7MfEVZmwMOFMnDHG\nDKHsh1OUWRzEGWPMQIxwdUomzE14OIUxxgyh7IM4ZcKynGXiiYmJGDp0KGxtbdGoUSNs27bN2E1i\njDEAxrjEUJWFqqblKxP/+OOPYWVlhUePHiEwMBCvvvoq2rRpgxYtWhi7aYyxSq7MM/FsVSYsTctP\nJp6eno49e/Zg/vz5qFKlCrp06YLBgwdj06ZNxm4aY4wZIYhTJqzMyk8Qv3PnDszNzeHq6qqZ5+Hh\ngRs3bhixVYwxJpX5cEo2ZcGiFMMphvgiZGm+FJqamgo7O7s88+zs7PD48WP9G8QYY3rSKRMXQngJ\nIW4JIe4IIWYW8vxrQogrQohLQogLQoheRdVV2kycSP+/0rC1tUVKSkqeecnJyahatWrpKmSMMQMq\nMYgLIUwArATQD4A7gFFCCLd8xY4QkQcRtQUwHsC6oupTIBNVytFwSrNmzaBQKBASEqKZd+XKFbi7\nuxuxVYwxJumSiXcAcJeIwogoG8B2AIO1CxBRutakLYC4oipTUBYszcrP1SnW1tYYNmwY5syZg/T0\ndJw8eRL79+/H2LFjjd00xhjTKYjXBxChNf0gZ14eQoghQoggAAcBfFZUZQpkoop5+cnEAWDVqlVI\nT0+Ho6Mj3nrrLfzyyy98eSFj7LlgsBObRLQXwF4hRFcAmwA0L6zc47NBOBmxHd7B5+Hp6QlPT09D\nNeGZcXBwwN9//23sZjDGKgl/f3/4+/vrVFaUdB9vIUQnAN5E5JUzPQsAEdHiYl4TAqADEcXnm0/2\nU1+Gd9clmDKsi/b8CnU/8YqyLoyx50NOXCn0Gj1dhlMCADQRQjgLISwAjATgk28BrlqP2wFA/gCu\nphSZsLYoX8MpjDH2vCpxOIWIlEKISQD8IIP+70QUJISYIJ+mdQCGCyHeBvAEQBqAEUXVJ4N4+Tmx\nyRhjzzOdxsSJyBf5xriJaK3W4yUAluhSl9I0vdyd2GSMsedV2d/F0Po+bCw5iDPGmCGUeRAHAGtL\nHk5hjDFDMEoQ50ycMcYMo8yDeJ3DR1CtCt93hDHGDKHMg7hJWG+Ym5f1UhljrGIq8yD+8CHKXRBf\ntWoVXnrpJVhZWeHdd981dnMYY0yjzO8nDgBmRllq6dWvXx/ffPMNDh8+jIyMDGM3hzHGNIwSTstb\nJj5kyBAAQEBAACIjI43cGsYYy2WUq1Os+OIUxhgziLL/ebbs0g2niO/0/302+pZvTMUYq1jKPIiX\ndjycAzBjjBVklOEUxhhjhsFBXAdKpRKZmZlQKpVQKBTIysqCUqk0drMYY4yDuC7mz58Pa2trLF68\nGFu2bIG1tTUWLFhg7GYxxljJv+xj0IUJQYUtryL9Gk5FWhfG2PNB31/2YYwx9pziIM4YY+UYB3HG\nGCvHOIgzxlg5xkGcMcbKMQ7ijDFWjj0XN4V1dnaGEPrfG+V54OzsbOwmMMYqEZ2uExdCeAFYDpm5\n/05Ei/M9PxrAzJzJxwA+IqJrhdRT6HXijDHGiqbXdeJCCBMAKwH0A+AOYJQQwi1fsXsAuhORB4D5\nAH7Vr8kVn7+/v7Gb8NzgvsjFfZEX90fJdBkT7wDgLhGFEVE2gO0ABmsXIKKzRJScM3kWQH3DNrPi\n4Y0zF/dFLu6LvLg/SqZLEK8PIEJr+gGKD9LvAzikT6MYY4zpxqAnNoUQPQGMB9DVkPUyxhgrXIkn\nNoUQnQB4E5FXzvQsAFTIyc3WAHYD8CKikCLq4rOajDFWCkWd2NQlEw8A0EQI4QwgCsBIAKO0Cwgh\nnCAD+NiiAnhxjWCMMVY6JQZxIlIKISYB8EPuJYZBQogJ8mlaB+AbANUBrBbygu9sIurwLBvOGGOs\njO8nzhhjzLDK7Gv3QggvIcQtIcQdIcTMkl9RvgkhfhdCxAghrmrNcxBC+AkhbgshDgsh7LWemy2E\nuCuECBJC9DVOq58NIUQDIcR/QogbQohrQojPcuZXuv4QQlgKIc4JIS7l9MfCnPmVri8A+T0UIUSg\nEMInZ7pS9oNeiOiZ/0HuLIIBOAMwB3AZgFtZLNtYf5BX6LQBcFVr3mIAM3IezwSwKOfxCwAuQQ5v\nueT0lTD2OhiwL+oAaJPz2BbAbQBulbg/rHP+m0J+r6JLJe6LqQA2A/DJma6U/aDPX1ll4iV+Yaii\nIaKTABLzzR4MYEPO4w0AhuQ8fg3AdiJSENF9AHch+6xCIKJoIrqc8zgVQBCABqi8/ZGe89ASMsFJ\nRCXsCyFEAwADAPymNbvS9YO+yiqIP+0XhioqRyKKAWRgA+CYMz9//0SigvaPEMIF8gjlLIDalbE/\ncjBhHw4AAAGrSURBVIYQLgGIBuBPRDdROfviJwBfANA+MVcZ+0EvfCta46pUZ5WFELYAdgGYnJOR\n51//StEfRKQioraQRyPdhBCeqGR9IYR4FUBMzhFacZceV+h+MISyCuKRAJy0phvkzKtsYoQQtQFA\nCFEHQGzO/EgADbXKVbj+EUKYQQbwTUS0L2d2pe0PACCiFAAHAbRH5euLLgBeE0LcA7ANQC8hxCYA\n0ZWsH/RWVkFc84UhIYQF5BeGfMpo2cYkkDfL8AHwTs7jcQD2ac0fKYSwEEI0AtAEwPmyamQZ+QPA\nTSL6WWtepesPIURN9RUXQogqAPpAnrCrVH1BRF8SkRMRNYaMB/8R0VgA+1GJ+sEgyuoMKgAvyKsS\n7gKYZewzumWwvlsBPASQBSAc8p4yDgCO5PSDH4BqWuVnQ55xDwLQ19jtN3BfdAGghLwq6RKAwJzt\noXpl6w8ArXLW/xKAKwCm58yvdH2htX49kHt1SqXth9L+8Zd9GGOsHOMTm4wxVo5xEGeMsXKMgzhj\njJVjHMQZY6wc4yDOGGPlGAdxxhgrxziIM8ZYOcZBnDHGyrH/B29lV1rlBPanAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f795a61c7d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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MeOGG0tLVBXw3IrLZ//zMnBsRPwcuioiTgXsoTyySmfMi4iJgHrAcOG3QdCVJ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\nqGYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f797db69710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "scores/DECODA_MINIAE_TANH_TFIDF_H30_DO.shelve\n"
     ]
    },
    {
     "data": {
      "image/png": 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hMWEYYzgZd5Lh7e0X8ODZg8zfPZ8RHUcwculI5u2eR2JqIsPbD2fYkmEU9yyO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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f79601f2210>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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09MwZ6mIMO50TOuld0DvUxRh2OsZ30HNfz1AXY1jxXmnPe6W9SZM6mT/f+6Wv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\n6OIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f79605a94d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "scores_ordoned={}\n",
    "for i in glob.glob(\"scores/*DO*.bak\"):\n",
    "    if \"MINIAE\" not in i :\n",
    "        continue\n",
    "    scores={}\n",
    "    print i[:-4]\n",
    "    data=shelve.open(i[:-4])\n",
    "    for key,table in data.iteritems():\n",
    "        scores[key]=round(table[1][np.argmax([x[0] for x in table[0]])][0],3)\n",
    "        if key not in scores_ordoned:\n",
    "            scores_ordoned[key]=[scores[key]]\n",
    "        else :\n",
    "            scores_ordoned[key].append(scores[key])\n",
    "            \n",
    "    pandas.DataFrame(zip([x[0] for x in data[\"ASR_H1_TRANSFORMED_W1\"][0] ],[x[0] for x in data[\"ASR_H1_TRANSFORMED_W1\"][1] ])).plot()\n",
    "    data.close()\n",
    "    show_network_TRANS(scores,title=i,unite=200)\n",
    "    #except:\n",
    "    #    print \"C4EST LA MERDE\",i"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ASR_H1_TRANFORMED_OUT 0.697\n",
      "ASR_H2_TRANFORMED_OUT 0.682\n",
      "TRS_AE_OUT 0.838\n",
      "TRS_SPARSE 0.841\n",
      "ASR_SPARSE 0.78\n"
     ]
    },
    {
     "data": {
      "image/png": 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blp7dOXPInLRtSzH6yEhqiXXpQtvOnevdiXsT8ZEjqVI+doyun1RKrdR773Ud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\niUspXavI2Sq+VVQnWBOHoKPcE3/yBO+Z9R6SiST7ju4jUZm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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f795924e810>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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G4jxPtnohj3RwNS5WXERWmWvod+edpLbLyqgjX7iQriOTud5poFPc4+LonURF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\nRJqYgriISBNTEBcRaWL/D0/4iN+zdJOWAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f797d2cd6d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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O82XZsWV58MJBRkc7GFo1lj4dB7HEyBDKoFL0HupDr/csLP1WM+J/oWzRbSdHbxxNiRA2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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f79855e59d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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qCPg1AF4eXhj33Dh4eniiQekGyOudN03d+gT3QWRsJK7dvpa4b6w+thqnrp/C\nO4vfwYrOKzI/wJ5edL8XL9xlT3zfPvOwh2++IQcPNvfnPZuyg8ARG0ew17JeGZbTYU4HIhDs+ntX\n/nH0DyIQnLdvXobLXIm6wncWvUOrzcpvNn3DFtNasPX01ok9sgQTtk1gx7kdE7+tP1/zOREITto+\niR8s+yCxt0uSF25eYM6vcjLfsHzcf3E/JVDYYFLKB1/+c+YfIhB8f+n7JE1vAoFghe8r8JOVn3Do\n+qEMXBfI3it6M2hbEFtNb8Xd53cz1+BcvBp1lc/PfJ4SKOyzsg8v3brE95e+zzhrBjf1jrf3wl62\nmNaCm0+bJzYk9CbPR55ngeEFEnvccdY45huWj82nNM+0zOTm7p2b2BOdvGNyYvqQ9UN48pr9W91F\nxUZRAoVFRhZJ/HXlqBu3b/Dfi//NCzez7kbkQ9YP4cB1A9liWovEHuTsPbPpO9SXCASLfV2M0XHR\n9Bnsw+i4aO4+v5ulvi3FrWe3EoHg5tOb+eHyD2m1WfnWwrc4bqt5NM6zU59l3aC6bD6lOQsML8DQ\n8FCuPbaWtuQ3Yk+mzYw2zD8sP7/e9DVf+e0VTt81nVablZ6DPBP3hRhLDNcdX8fFYYv5r5//RZKc\nunMqf9//O0nTSy32dTGuO76OHyz7gAPXDUx3u4t+XZTnbpxj21ltE5f/bNVnHLp+aJq88/bNY4Hh\nBVhmVBl6DPLgzvCdJMmlB5eyyMgi/HTVp4nbtf3cdj4y+pEUy687vi6xvuGR4Wwzow2fmJB0k/QT\nESc4dstYfrrq08RfPWO3jGWPJT3YYU4HWm1W9l7Rm82nNGer6a145MoRkuaXV/FvijNoWxBvxd7i\ny3NfZotpLfhL6C98ZuozzDU4F0OOh/Bq1FWS5Oqjq9n458Z22+PrTV+z+ZTmrDOhDhv/3Jghx0NS\nzN9yZgurj63OZ6c+y4+Wf8SxW8Zy7JaxfHTso5y+azrrT6yf+BlDdn8oxGuvmSfBNGhgbo06c2bK\n+TabjU1/bZq446TnhZkvEIGmDkeuHKEECq9EXclwmeSOXj3K9rPbE4Fg2KWwDPNarBZ+v/l7uz+F\nrTYrvb/yZpXRVRgVG0UEgl+u/TLN8vmH5ef8/fMT0xAIvjbvtTTlLT24lAgE60yow3LflUtMn7pz\nKk9fP+3w9tkza88sPj/zebaZ0Yafrfosxby2s9ry01Wf3lF5m09vJgLBkRtHJn4QHFFgeAG2nt76\njtZ1v5nADY7YAAAbOklEQVS8YzLLjCrDpyaZR9TUHFeTG05u4HtL3uOAtQNotVk56q9RKYLy6H9G\n84kJTzA0PJR5h+ZN7AwErgtk5R8rE4Hgwcvm/rBrj61laHgoVx5eyd/2/Ua/4X48cOkAi31djAVH\nFOT2c9tJkoVGFEocVvo19FciEKz0Y6UUX6rJBR8JZvFvitNvuF+6X7QkWX9ifW48uZG1x9fm1rNb\nSZpA9snKTxLzxFpiGbgukIVHFubWs1tZZXQV5h+Wn40mN+JHyz9i0a+LctOpTSnKtdqsLDyycIp9\n+ecdP7PbgqSnc0RERzDPkDyJX/IvzHyBz898nj2X9uTAdQMTA3nPpT255tiajN4mztw9k+du2Hkc\nF8l6E+sx1+Bc/GnLT5y7dy5rjqvJrzd9nWF5cdY4Bq4LZJGRRfjBsg/Ye0XvxC+Qj5Z/xNVHV7Pn\n0p6Jr+83f0+bzcaNJzfyzxN/kszGwymjRpmbwV++bB4q8N139h94MHHHRFy4dQEtK7XMsLwxbcZg\ncLPBAICKfhWx7PVlKOjj+C3WKvpVxPxX5mPlkZV4pFDGdyjy9PBE7wb2D3Z6iAdK5yuNEr4l4JPD\nB6V8S6F5xeZplp//ynw0KtsoRfpTpZ9KU14J3xIAzM/Tlv5JbdC1ZleHtisjLfxb4LM/PkMFvwqJ\nbZdgaLOhyON9Z7eLrFuyLlZ0XoFWldJ5ukU6SuQtgTol6tzRMvebt2u/jTM3zuDQFfMU5p51e6LT\n/E4gie3vboeHeKDPU31SLPNq9Vdx5sYZPP3L03i0yKOJP7n7PNUHhXMXxpRdU7D93HZULlgZPZf1\nxNXoq7DSiojoCIx4ZgSqFq6K4C7B2HR6Ex4vZp5SUdCnIK5GX0WRPEUwKXQShjUfBr9cfuhcw/5p\nni38W+CXdr8gxhKTOAxnT0W/ijh+7TjO3DiDMvnKAAAK5y6MPRf3wGqzotvCbjh05RDy5cyH+a/M\nR92SdTG742z4evti+eHlsNKKWR1moWGZhinK9RAPNKvQDC/NeSnxzJ+jV4+i02NJz2svkKuAGQ6c\n3gqvVH8FG05twOk+p5HXOy8sNgsalmmIFv4tHHqfOtXolO68OsXrYMvZLZi4YyLCb4ZjaLOheKPW\nGxmW5+XhhYEBA/HcI89h46mNienlC5RHuyrtUMGvQprPP4A0n/10pRfdmbIH3QpAGIBDAPramV8I\nwAoAOwHsAfBmOuVk+I2V2tNPm2c15stnnkdnz+Erh1l4ZOFMe8b3mya/NGGneZ1IkmGXwtL9SZzc\nocuHaLGmfeLq+cjziUMUH6/42OV1PX39NK9FX3N5uXei9fTWXBy22K11cIUbt28kHiy02Wz888Sf\nPBFxItPl/jr1Fw9dTvtUiCHrh/A/wf/hnyf+ZLUx1bjlzBbuv7if+y7uS3efajCpATed2sT9F/ez\n+DfFGWuJdW6j4vX7ox8RiBQ94iUHl7DNjDbccmYLK/1YicsOLXPogF9qp6+f5tKDS1O8Lt+6nCJP\naHgoB6wdwFyDc7Hj3I4u2abUfg39lWVGlSECwdH/jL4n67AHzvTERcQDwBgAzQGcA7BVRBaRTH6O\nTi8AO0m2FpHCAA6KyHSSd33ipNVqbu6+cSOwdq05Dzy125bb+G7zd3iz5puJB5WyizL5y6BobnO7\nOkfrXrlQZbvpxfIWw41+N/DYuMdQtXBVl9UxQel8pV1e5p2a+/Jc5MmR/Z8K4ZvTF745zc3BRQRP\nl3vaoeWeKpP2Fxhgfpn1WNoDRyOOonud7niyVOaXLhf0KYgrUVfwwz8/4J3a7yCHZw7HNyADjxZ5\nFMXzFseOd3cknlRQOHdhXLp1CQvCFqB1pdZoU7nNXZVdOl/pTPfDWsVroZRvKXy1/is0r5C2Z+sK\nXR7vgucfeR7NpzZP95dLVnNkOKUegMMkTwKAiMwG0A6mZ57gPIAa8f/7ArjiTAAHzP1QSpQwzxSs\nWTPt/IOXD2LKrilYengp1nZb68yq3KJp+abIn9N1t6vzzemLjtU6Ov4TLJtJfWRfGQHlA/D8I89j\nw6kN6Fazm0PLFPQpiOGbhiM6Lhq/tvvVZXXpWrNrmiG8wrkLY+u5rTh+7TjmvTzPZetKT5E8RdDl\n8S53/WWRGU8PTxTKXQg739t5T8q/G5nexVBEOgBoSfLd+OkuAOqR/ChZHg8AawBUAZAXwKskV9gp\ni5mtL8HHH5vHQg0blnYeSRT/tjg8xANjWo9Bh0c7OFSmUgrovaI3pu+Zjm3/3oYKfhXu6bqu3b4G\nvxF+CHkjBE3KN7mn63qQZXQXQ1cd2OwPYBfJpiLiD+APEXmcZJrbwQUGBib+HxAQgICAALsFzp5t\nhlLsORt5FhdvXQQAVCtSzcmqK/Vw6VazGzo/3vmeB3AAyJ8zP35q85PDw0bKCAkJQUhIiEN5HemJ\nNwAQSLJV/HQ/mEH2EcnyLAcwhOSm+Ok1MAdAt6Uqy6Ge+PXrQMmSwM2b5iG5qS0KW4T2c9rDQzxw\n67+37vgCDqWUyk6cvZ/4VgCVRKSciHgDeA3A4lR5DgB4Jn5lxQA8AuCu76Jz9Kh5Uo+9AB52OQw9\nl/VE2yptUa1INQ3gSqmHWqbDKSStItILwCqYoD+Z5AER6WFmMwjAMAC/iMguAALgM5Jpr+11UEaP\nW/tp60/oXKMzhjYf6ra7himl1P3CoTFxkithDlomT5uQ7P/LAF5wpiJxcea2srlyAYcPpwzi4ZHh\nIIibsTcxb/88rH9rPXJ45nDZqVFKKZVd3TdXbI4bZ25sFRkJkMCPPybN676ke+LtRwv5FIK/n7+b\naqmUUveX++J+4lOnAl99BUycCAwaZNLatTN/T18/jb/P/I3xz41HQZ+CqFOijj7IVSml4rm1Jx4T\nY67M/PRTYMoU4OmngUaNgNatAe/4+/P/svMXvFb9NfSo2wPbzm1LvHeCUkopB04xdOnKUp1iWK4c\ncOMG8PjjwJ9/JuXrtbwXCvkUwkf1P8Lj4x/H0k5LUbtEbVy7fQ2e4pl42bJSSj0MsuJin7ty6pT5\n+3Sq6wAmh07GbcttbD6zGZ1rdEbtErUBpHyAgVJKKTcH8fLlgRMngHr1UqYXzVMURfMURQnfEhja\nfKg7qqaUUtmCW4N46dJpg3hUXBQu3rqIYx8dg6eHp9vqppRS2YFbz06Jjga2bAGKFUtKO3DpAPz9\n/DWAK6WUA9waxG/eBHxTHaOct39eiqfTKKWUSp9bh1Nu3gTWXJiN9/8JwvWY6yiRtwRCToRg27vb\nMl9YKaWUe3vikbE38MXm95E/V35ULlgZFpsFZz85e0+eTqOUUg8it/XESSCy3Gy0LReABa/+7q5q\nKKVUtua2nnhMDCBl/sZzj7R2VxWUUirbc1sQv3kT8PKJ0qsvlVLKCW4N4p65ouDj5eOuKiilVLbn\n1iDukTMauXPkdlcVlFIq23NrEBfvKPjk0J64UkrdLbcGcXhpT1wppZzhtiAeHQ3QS8fElVLKGQ4F\ncRFpJSJhInJIRPramf8fEQkVkR0iskdELCKS4X1jY2IAm2eU9sSVUsoJmQZxEfEAMAZASwDVAXQS\nkRSXVJL8hmRtknUA9AcQQvJaRuXGxAA2Dx1OUUopZzjSE68H4DDJkyTjAMwG0C6D/J0AzMqs0JgY\nwOqhBzaVUsoZjgTxUgBOJ5s+E5+Whoj4AGgFYH5mhd6+TVgkWsfElVLKCa6+d8oLADZmNJQSGBgI\nANi02QKPEp5633CllEolJCQEISEhDuXN9EHJItIAQCDJVvHT/QCQ5Ag7eX8HMJfk7HTKSnxQ8pfD\nrmJkjD9uB0Y4VFGllHpYZfSgZEeGU7YCqCQi5UTEG8BrABbbWUl+AE0ALHKkUrdio+ENPaiplFLO\nyHQ4haRVRHoBWAUT9CeTPCAiPcxsBsVnfRFAMMloR1Z8KzYKObx1PFwppZzh0Jg4yZUAqqRKm5Bq\negqAKY6uOCo2Gt45tSeulFLOcNsVm7dio5DTU3viSinlDPdddm+JQk4P7YkrpZQz3BbEb1tikNMz\np7tWr5RSDwT3PZ7NEgtvDeJKKeUUtwXxWEssvD293bV6pZR6ILivJ26NRU4vDeJKKeUMt/bENYgr\npZRz3BfEbbHIpUFcKaWc4rYgHmeNRc4cGsSVUsoZ7gvitljk0iCulFJOcV8QpwZxpZRyllt74j7e\nOdy1eqWUeiC4LYhbGItc3toTV0opZ7g1iOfWIK6UUk5xWxC3SZyOiSullJPcFsQperGPUko5y31B\n3EPPTlFKKWe5JYiTJohrT1wppZzjliBuswHw1J64Uko5y6EgLiKtRCRMRA6JSN908gSISKiI7BWR\ndRmVZ7UC4qW3olVKKWdl+qBkEfEAMAZAcwDnAGwVkUUkw5LlyQ9gLIAWJM+KSOGMytQgrpRSruFI\nT7wegMMkT5KMAzAbQLtUeV4HMJ/kWQAgeTmjAi0WABrElVLKaY4E8VIATiebPhOfltwjAAqKyDoR\n2SoiXTMq0GoFxFODuFJKOSvT4ZQ7KKcOgGYA8gDYLCKbSR5JnTEwMBBRUYAt9Cj2btmLgPIBLqqC\nUko9GEJCQhASEuJQXiGZcQaRBgACSbaKn+4HgCRHJMvTF0AukoPipycBWEFyfqqySBIXLwKlBtXF\n5s/Ho27JunewaUop9fAREZAUe/McGU7ZCqCSiJQTEW8ArwFYnCrPIgD/EhFPEckNoD6AA+kVaLEA\n0OEUpZRyWqbDKSStItILwCqYoD+Z5AER6WFmM4hkmIgEA9gNwAogiOT+9Mq0WgF4xiKHh96KViml\nnOHQmDjJlQCqpEqbkGr6GwDfOFKe1QpQe+JKKeU0t1yxabUC8IjTIK6UUk5ySxC3WAB4aE9cKaWc\n5baeuA6nKKWU89w6nOLl4arT1JVS6uHktuEUikWDuFJKOcl9wylihaeHpztWr5RSDwz3DaeIFZ6i\nQVwppZzhpuEUAkJ4iNueDqeUUg8Et0TRmDgrQA+I2L0VgFJKKQe5JYjHWa0Q6lCKUko5yz1B3GKF\nUM9MUUopZ7kliMdaLBBoT1wppZzlxp64BnGllHKW+8bEtSeulFJO0564UkplY27riXtoT1wppZzm\nvp64BnGllHKaG3vieoqhUko5y01BXE8xVEopV3AoiItIKxEJE5FDItLXzvwmInJNRHbEv77IqDwd\nE1dKKdfIdExDRDwAjAHQHMA5AFtFZBHJsFRZ15Ns68hKdUxcKaVcw5GeeD0Ah0meJBkHYDaAdnby\nOXw3K4v2xJVSyiUcCeKlAJxONn0mPi21p0Rkp4gsE5FHMyrQYtMgrpRSruCqU0S2AyhLMkpEWgNY\nCOARexkDAwPx51/nEH37IkJCQhAQEOCiKiil1IMhJCQEISEhDuUVkhlnEGkAIJBkq/jpfgBIckQG\nyxwH8ATJq6nSSRK9v/4Hc258iPNfbXGokkop9TATEZC0O2TtyHDKVgCVRKSciHgDeA3A4lQrKJbs\n/3owXw5XkQ6L1QoPfTSbUko5LdPhFJJWEekFYBVM0J9M8oCI9DCzGQSgo4j0BBAHIBrAqxmVqWPi\nSinlGg6NiZNcCaBKqrQJyf4fC2CsoyvVnrhSSrmGex6UbNMn3SullCu4J4hrT1wppVzCLUHcarPC\nU/QGWEop5Sz33ADLZtGeuFJKuYCOiSulVDbmxuEUDeJKKeUsDeJKKZWNuW04RcfElVLKee7riXto\nEFdKKWe5LYh76SmGSinlNDcNp1i0J66UUi7gnp449cCmUkq5gvuCuPbElVLKae4bE9cgrpRSTtOz\nU5RSKhvT4RSllMrG3BPEYUEODz3FUCmlnOWWIG7TnrhSSrmEHthUSqlszKEgLiKtRCRMRA6JSN8M\n8j0pInEi8lJG5WlPXCmlXCPTIC4iHgDGAGgJoDqATiJSNZ18wwEEZ1amFVbk8NQgrpRSznKkJ14P\nwGGSJ0nGAZgNoJ2dfB8CmAfgYmYFak9cKaVcw5EgXgrA6WTTZ+LTEolISQAvkhwHQDIr0EYrcnjq\n2SlKKeUsV0XS7wEkHytPN5AHBgbi+s712H4rD0JKNUBAQICLqqCUUg+GkJAQhISEOJRXSGacQaQB\ngECSreKn+wEgyRHJ8hxL+BdAYQC3ALxLcnGqskgSxbr1wesvlMF3L3/i4CYppdTDS0RA0m7n2JGe\n+FYAlUSkHIBwAK8B6JQ8A8mKyVb2C4AlqQN4clZakUPHxJVSymmZBnGSVhHpBWAVzBj6ZJIHRKSH\nmc2g1ItkVqYNVnjp2SlKKeU0h8bESa4EUCVV2oR08r6daXl6iqFSSrmEey671564Ukq5hNvunaJB\nXCmlnOeeIC6xyOWV0x2rVkqpB4pbgjg9YpErh3fidPny5SEiD8SrfPny7mhSpdRDyi2XTdokFjmT\nBfGTJ08is/PVswuRTC9YVUopl3HjcIp35hmVUkpl6L4YTlFKKXV3NIgrpVQ2pkFcKaWyMTcF8RgN\n4kop5QLuCeKesfDxzj5BPCIiAu3bt0fevHlRoUIFzJo1y91VUkopAG46xRAescjtnX0u9nn//feR\nK1cuXLp0CTt27MBzzz2HWrVqoVq1au6umlLqIZflPXGbDYBn9hkTj4qKwu+//47BgwfDx8cHjRo1\nQrt27TBt2jR3V00ppbI+iFutADxj4e2ZPYL4oUOHkCNHDvj7+yem1axZE/v27XNjrZRSysjy4RSr\nFYDXnQdxV1wIeTcXhd68eRP58uVLkZYvXz5ERkY6XyGllHKSe4L4XfTE3XVVft68eXHjxo0Uadev\nX4evr697KqSUUslk+XCKxQLAI/sMpzzyyCOwWCw4evRoYtquXbtQvXp1N9ZKKaUMNwRxAl6xyOGZ\nI6tXfVdy586Nl156CV9++SWioqKwceNGLFmyBF27dnV31ZRSyrEgLiKtRCRMRA6JSF8789uKyC4R\nCRWRbSLSLL2ybsfFAVYveIhbTlG/K2PHjkVUVBSKFi2KLl26YPz48Xp6oVLqviCZ3QJWRDwAHALQ\nHMA5AFsBvEYyLFme3CSj4v+vAWAByUp2yuKRU5GoNKEYOPhW8vQH6la0D8q2KKXuD/Fxxe7pHY50\nh+sBOEzyJMk4ALMBtEueISGAx8sL4HJ6hUXFxkJs2WM8XCml7neOBPFSAE4nmz4Tn5aCiLwoIgcA\nLAfwUXqF3Y6NhVizz9WaSil1P3PZwDTJhSSrAXgBQLqXM8ZYtCeulFKu4sh54mcBlE02XTo+zS6S\nG0XES0QKkbySen7QmG/APTcRGBiIgIAABAQE3HGllVLqQRYSEoKQkBCH8jpyYNMTwEGYA5vhALYA\n6ETyQLI8/iSPxv9fB8BvJP3tlMXFm/eh49yOiBm1P3n6A3Mw8EHaFqXU/SGjA5uZ9sRJWkWkF4BV\nMMMvk0keEJEeZjaDAHQQkW4AYgHcAvBqeuXFWGLhQR1OUUopV3DosnuSKwFUSZU2Idn/IwGMdKSs\n2zomrpRSLpPlV9zExGlPXCmlXCXLg/jtuBgN4kop5SJZHsTHHfoCHsxe54mPHTsWTz75JHLlyoW3\n337b3dVRSqlEWX4r2tfL9cW8FVUyz3gfKVWqFAYMGIDg4GBER0e7uzpKKZUoy4N4Q78XEXw7q9fq\nnBdffBEAsHXrVpw9m+4p8kopleXc8ng2T8+sXqtSSj2Y3PJkH6+7WKsMcv75bByoF+EopR4sWR7E\nhw0DfHzufDkNwEoplVaWB/Hu3QF9splSSrlGlgfxzp2zeo3Os1qtiIuLg9VqhcViQUxMDLy8vOCp\ng/tKKTfLPs9Ic6PBgwcjd+7cGDFiBGbMmIHcuXNjyJAh7q6WUkplfhdDl65MhPbW9yDd+e9B2hal\n1P3B2cezKaWUuk9pEFdKqWxMg7hSSmVjGsSVUiob0yCulFLZmAZxpZTKxrL8Yh97ypUrBxHn741y\nPyhXrpy7q6CUeog4dJ64iLQC8D2SHpQ8ItX81wH0jZ+MBNCT5B475dg9T1wppVT6nDpPXEQ8AIwB\n0BJAdQCdRKRqqmzHADxNsiaAwQAmOlflB19ISIi7q3Df0LZIom2RkrZH5hwZE68H4DDJkyTjAMwG\n0C55BpJ/k7weP/k3gFKureaDR3fOJNoWSbQtUtL2yJwjQbwUgNPJps8g4yDdHcAKZyqllFLKMS49\nsCkiTQG8BeBfrixXKaWUfZke2BSRBgACSbaKn+4HgHYObj4OYD6AViSPplOWHtVUSqm7kN6BTUd6\n4lsBVBKRcgDCAbwGoFPyDCJSFiaAd00vgGdUCaWUUncn0yBO0ioivQCsQtIphgdEpIeZzSAAAwAU\nBPCTmBO+40jWu5cVV0oplcX3E1dKKeVaWXbZvYi0EpEwETkkIn0zXyJ7E5HJInJBRHYnS/MTkVUi\nclBEgkUkf7J5/UXksIgcEJEW7qn1vSEipUVkrYjsE5E9IvJRfPpD1x4iklNE/hGR0Pj2GBqf/tC1\nBWCuQxGRHSKyOH76oWwHp5C85y+YL4sjAMoByAFgJ4CqWbFud71gztCpBWB3srQRAD6L/78vgOHx\n/z8KIBRmeKt8fFuJu7fBhW1RHECt+P/zAjgIoOpD3B654/96wlxX0eghbos+AKYDWBw//VC2gzOv\nrOqJZ3rB0IOG5EYAEamS2wGYEv//FAAvxv/fFsBskhaSJwAchmmzBwLJ8yR3xv9/E8ABAKXx8LZH\nVPy/OWE6OBF4CNtCREoDaANgUrLkh64dnJVVQfxOLxh6UBUleQEwgQ1A0fj01O1zFg9o+4hIeZhf\nKH8DKPYwtkf8EEIogPMAQkjux8PZFt8B+BRA8gNzD2M7OEVvReteD9VRZRHJC2AegN7xPfLU2/9Q\ntAdJG8naML9GGotIAB6ythCR5wBciP+FltGpxw90O7hCVgXxswDKJpsuHZ/2sLkgIsUAQESKA7gY\nn34WQJlk+R649hERL5gAPo3kovjkh7Y9AIDkDQDLAdTFw9cWjQC0FZFjAGYBaCYi0wCcf8jawWlZ\nFcQTLxgSEW+YC4YWZ9G63UmQspexGMCb8f+/AWBRsvTXRMRbRCoAqARgS1ZVMov8DGA/yR+SpT10\n7SEihRPOuBARHwDPwhywe6jaguR/SZYlWREmHqwl2RXAEjxE7eASWXUEFUArmLMSDgPo5+4julmw\nvTMBnAMQA+AUzD1l/ACsjm+HVQAKJMvfH+aI+wEALdxdfxe3RSMAVpizkkIB7IjfHwo+bO0BoEb8\n9ocC2AXgP/HpD11bJNu+Jkg6O+WhbYe7fenFPkoplY3pgU2llMrGNIgrpVQ2pkFcKaWyMQ3iSimV\njWkQV0qpbEyDuFJKZWMaxJVSKhvTIK6UUtnY/wMFcHQjp/06BAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7964ac8590>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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41oGrgytOPTiFt+u8nWte3xz9Bl6PvbBnyB4M3D4Qpx+ehlKthIpU6FW/F/YP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\nuUqAGdlr2wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f797c06cd90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data=shelve.open(\"./scores/RAW_ASR_TRAIN.shelve\")\n",
    "scores={}\n",
    "#del scores_ordoned\n",
    "for key,table in data.iteritems():\n",
    "    scores[key]=round(table[1][np.argmax([x[0] for x in table[0]])][0],3)\n",
    "    print key,scores[key]\n",
    "   # if key not in scores_ordoned:\n",
    "   #     scores_ordoned[key]=[scores[key]]\n",
    "   # else :\n",
    "   #     scores_ordoned[key].append(scores[key])\n",
    "#data.close()\n",
    "#show_network_TRANS(scores)\n",
    "    pandas.DataFrame(zip([x[0] for x in data[key][0] ],[x[0] for x in data[key][1] ])).plot()\n",
    "data.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "scores/MINIAE_BIGBIN_TANH.shelve\n"
     ]
    },
    {
     "data": {
      "image/png": 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rqD+/PrwcvTCr6yz8ceYPlLcrj75/9MXNpJuo614Xy08ux6moU2hXtR1ae7dG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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f79605d8fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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kSVIFhi5JkqQKDF2SJEkVGLokSZIqMHRJkiRVYOiSJEmqwNAlSZJUgaFLkiSp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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f795e02b410>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "scores/DECODA_AE_TANH_TFIDF_BIGTRANS.shelve\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f797d40d750>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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gNy22v/XwTd+KOGHChNWPGxsbaWxsfLObkCRJ6nJTp05l6tSpXbrNdQ4ZERFD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\n5Q1xAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f795d2667d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "scores/DECODA_MINIAE_TANH_H50_DO.shelve\n"
     ]
    },
    {
     "data": {
      "image/png": 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x9epWJKcn43Twacw8OhMA8Pdbf6Pp0qZ4q8Vb0Gj1g4rdndxx4t4JzO46G18d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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f79643eae90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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ph5XM/JsOnfcfKAPNJW0ABg1dwOsoc5T0zQX0M8odSr0R0dUM4h1H+TtqUFq2Wm/PncCK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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f798bf31d90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "scores/MINIAE_TANH_H100_DO50.shelve\n"
     ]
    },
    {
     "data": {
      "image/png": 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H5yDgYQAyFBnwC/GDz20fZCozNX14LeYaGtg1wMwuM3Hh4QW8u+9d+I3N/ZXx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\nRxUa+NSJyJqANQWeuxl7M08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QjBLETTmIM8aYQZT9JYaciTPGmMGUeRB/ouRMnDHGDMU4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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7964811650>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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MeOGG0tLVBXw3IrLZ//zMnBsRPwcuioiTgXsoTyySmfMi4iJgHrAcOG3QdCVJ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\nqGYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f79631c5ad0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "scores/MINIAE_TANH_H100_DOmlp.shelve\n"
     ]
    },
    {
     "data": {
      "image/png": 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DC4EXEBYfhpJWJVHHrg461+qMiYcnwtbaFhc+u4ALgRfQr2E/1Heuj5DYECy9\nsBS9HHvl6G74+fTP6UeMNSvURN8GfXEm4Az2f7AfjvaO2OG5AwHRAVh4biE+afFJgfWt0+vwzb/f\noLRNaXzc/GO4eLvAQlmgS50uBS6bXbIuGaP2j8Kaq2uwrNsyjGw9EgBw/cF1TPp3Eh4lPkLn2p3R\n2qE1ErQJ2OHJO/YNbhvQrEozNHuRuw6uhlzF2mtr8XHzj9F/e394jvaEjaWNQWU4ff80AmMCodPr\nYGlhiZDYEOz03JnvMk9FENdqgQ4d+CabhATg7bdzf2ZyQV57rfDPCvZ75IdkXTKGNR2Gf+78g/r2\n9bHn1h78duE3NK7cGJeDL2NYs2HpwTAiIQJBMUHpy6foUjDo70GITY7NEcR9Inxw1Pco/vL4C9+9\n8R0239gMa0trtHFog8XnFsPSwhIPEx7CysIKdSvWxan7p9D8xeaY9O8kJGoTkahNRGRCJKYenYrP\nWnyGhecWYmK7iTjscxhJ8dxKa1K5CbrU7oLdt3ajceXGAIBP936aUYZMQfzP63+ijUMbnPU/iyvB\nV9CkShPY29qjRvkaGL53OCISIjDx8ER4R3jD2sIa9SvVx1b3rXkGcfdQd3hFeCEqMQrlS5bPs44P\neB2ArbVtrv32Xx38CsOaDkMvx154peIr8Az3RMuqLbHhOh9aeoR6ZDl5u/zicrxe/XU0qZLx7IH/\nfP+DXSk7jHttHH469RNKWZWCd4Q3bCxtEJsci2RdMmwsbeAd4Y1RB0bhpbIvodfWXrAraYc+jn1w\n/cF1DGg0ANtubkN8SjyaVmmKBG0CPmzyIXZ47kCKLiXXfuqFZxfiYtBFDGkyBGcCuHW8xX0LDngd\nwLWQawiLD8MBrwM4evcovnz1S/xx9Q/EJMeglFUpOJRzgFeEFxrYN8CloEsIjQtFt1e6oUe9Hmi8\nvDHGthmL9W7r0aNeD/hH+aNuxbq4EXoDO97fgbZr2qLLxi4Iiw9DLbtaeKfOO5h2dBrKlyyPyR0m\nwz3UHSUsMx5yfj/qPm6F30Jtu9q4G3kXjSo3yvV7uhZyDf0a9MO+O/vwMOEh9tzeg90Dd6PPX33w\nc5efsfDsQvg98oOVhRVec3gNjSo3Ss+rbsW6CIkNwcwTM2FlYYXRbUZnyXu/135sH7AdNSvUxJxT\nc7D80nLcGHkD1crxD354i+GISYrBvNPzQERZThzOPzMfI18didI2fENIeHw4Jv87GYnaRKx3W4/O\ntTpjyK7NHx4NAAAgAElEQVQhsFAWuPLFFTiUc8hzW8yNR6gHjvoexSfNP8lycjntiGf2ydn4vfvv\nAIBGLzSCe6h7+lFK1bJVcf6z85h/Zj4exD7AkKZDoHHS4KjvUYzcNxIdqneAhbJAQHQAJrSbAFtr\nW2zz2IZdt3ahaeWmmNpxKnZ57sL2m9uh1WvxIO4BqpapiuF7hsPFJ/8rlcwaxFNSOGifOsXjZ8/y\n5YI2hu20cjDmGm+fSB/UrVgXHap3wF8ef6HkhZLYc3sPAmMCMfbQWLiHusPR3hHjXcanLxMcG5w+\nPPvkbFQsVREeYR5I1CaipBU/H1ar12LIriHwCPUAgTC8xXDMPDET5UqUQ1/HvnC+6IzhzYdjv9d+\n7P9gPwKiA/CD6w/49+6/SNQmAgCikqLwf5v+D2/VeguTO0zGwnMLUceuDgCg+yvdcdzvOBpXboxB\njQeh2+Zu6T9cC2UBPfFzCTJvlLNPzsbo1qOx4vIKLOm6BPa29gCAhi80xO3w25jgMgGNKzfGfq/9\niEqMwty352Lyv5Ox4MwCTGw/EQDw08mfUKN8DdiVsoNPpA8c7R3hGe6JttXapq/noNdBrHNbh2Xd\nlsH5gjM0xzXoVKMTXD92zVL32z2242LQRVwdwYeejSs3xgc7PkDdinXhEeaBfg364eM9H6PRC43Q\nx7EPatvVxpQjU/By+Zdx+YvLKGlVEjq9DqMPjMbMN2eib4O+GO8yHtXKVcPlLy7DL8oPYw6MgddD\nLzSq3Ajrrq3DR80+Sv8+3b50g+s9V5zwOwEiwo0HN9CrPrciJ7SbAGsLa1wOvgy3B2549SV+G8F/\nvv9Bq9eiRdUWmH58Oka0GoHZJ2fjftR9aPVaXA6+jNsPb2PasWmwVJZQSmHfB/sw++RsvPrSq5j3\n9jzYWtsiUZuIQTsGYeHZhVjvth460sHe1h7WltY4Pfw0HMo64K1ab+Gj3R8hSZuExpUbo9ELjeBQ\nzgHHhh3D7Ye3UcKyBIbsGoLe9Xtjv9d+lLQqiVP3T+HOwzsoY1MGIbEheLHMi9jgtgF9HPsgMCYQ\nfbf1xbCmwzDtjZxdK+6h7tA4afD1a1+j5cqWGNBwAHrW74krI66g+YvNERgdiMXnF2Nlj5V4t27W\nBwqt6LECQ3YOwdWQq3APdQcAXAi8gMtBl/Hlq1/CI9QDHap3QMVSFbHyvZW4H3U/PYCnKVuiLEpb\nl0ZIbAiqlq0KgLsQJ/07CZeCLiFZl4x21dqhll0trL22Fl1qd0FIbAja/9Ee414bBx3p8PbGt7Hw\nnYX4v1f+Lz3fRWcXoZdjL9S2q53jM6d97rbV2qJ/w/7ovbU32r/cHv0a9sNR36NwKOuAwJhADGg0\nAABQybYSSluXxo+uP2JKhynwDPdE0+VNEZEQARtLG7iP4s8+uPFgTPp3Ev64lnFeq45dHZzxP4Ot\nHlvx89s/Y+7puThx/wQuBl7E4q6LsejcItyPuo99d/bhQdwD9G/YH9uQ9zkbs74UIu0die3a8dvZ\nzWHx2cXkE+FDSy8spc/3fk5+j/yo1KxSpDSKoAH12dqHoAGVmFmCys0pR9CAqvxShaABvbvxXVpz\nZQ1129SNKv9SmQKjA+mVX1+hVitaUfdN3enXc79Sxz86Uuf1nanm4prktM6JiIjs5toRNKB1V9cR\nNKB7kffoxgN+h1hiSiJVmFuBoAE5rXOi6yHXCRpQ903d6UHsAyIiqvtrXTrsfZh8InwoMSWRai+p\nTbNPzCa9Xk8u3i4EDcj+Z3uq/1t9emfjOwQNqOSskvTHlT8oPC6coAF9tOsjKvNTGUrWZn2b7yGv\nQ6Q0ij7b8xktv7icoAGdDzhPR3yOkP3P9jT2wFj6ZPcnBA3IcrollZxVkhydHWnQ34Noo9vGLHn1\n/asvWc2woq03tlLZn8rS+EPjqdcWfjdaYHQgTXSZSAFRAVTllyp0zv9c+nLjDo4jaEB/e/xNvpG+\nNPXIVIIGNMN1Bjmtc6Jhu4bR4rOLacC2AdRqRSsavns4uXi7UMsVLdPzeGfjOzTddXqWsow/NJ5m\nuM6gmotr0qXAS5SsTaZbYbeIiOiw92F6a/1bFBYXRhXmVqDA6EAKjQ1NX37EPyOo7eq25PfIj4iI\n3lj7BjVa2og6/tGR3t/+PgVFBxE0oH5/9SNHZ0eCBnTE5wjV+60etVzRktxC3IiI6FHCI/KP8k/P\nNzElkWxm2lDFeRXp6N2j9J/vf7lupx/v/pigASmNonEHx+WYf8rvFNX9tS5NdJlIfo/8qMuGLgQN\naMq/U6iBcwNadHYRVZpXiW6H36auf3YlaEAV5lag6yHXqf+2/tR/W38KiQmh/x35H0GD9M/u/dCb\nkrRZ3xQcnRhNuz13U0JK7m8jeW/ze+ll7bG5B704/0WqMLcCbXPfRi8teCnXZbJru7otnfQ7mT7+\n438/Us3FNan07NK00W0jlZtTjuacnEPQgKYemUpB0UG0/85+StGlUIouhSYfnkzDdg1LXz4sLoys\nZljRm+vezLGumKQY+v7Y9zTp8CSadXwW+T3yS//NHLt7jGosqkHBMcHkG+mbZbm0OvZ+6E2xSbG0\n23M3hcSE0O3w2+lpkrRJdCf8Dl0KvEQ2M20IGlC5OeXIaZ1T+jbhH+VPO27uoKvB/GLdPlv70NyT\nc8n+Z3vyCPUgj1CPp/cdm0OG8Atxra35TSlFTa/XU5VfqtDaq2tpwqEJNO/UPCIicvV1pcPeh8li\nugVdD7lOFtMt6GrwVTrpd5L8o/xpw7UN9MLPL1DT5U2pxe8taPHZxelfnKOzI1WcV5FWX15NFtMt\naLrrdIpMiKQhO4fQd0e/IyIOANCAztw/Q9UXVc9RLu+H3hQWF0bhceFERHQv8h6l6FLS598Jv5Nl\nvP2a9rT31t70cd9IX1pybgn139afYpJi6P6j+7Tbcze9OP9F2nlzJ1nPsCaL6RbpO5XsnNY50a/n\nfqXQ2FCCBhQcE0xERNUWVqPqi6pTw6UNqe6vdanawmp0MfAi3Xhwg6YdnUaa/zQ56nbkvpHUZ2sf\nemnBS3Tm/hlqs6oNERH13tqbKsytQJV/qUzfH/s+y/pjkmLS10lEFJccR4HRgRQUHUR2c+2owtwK\nFBQdRLFJsbTv9j5qvKwxOTo70i+nf0lfxu+RH8UkxaSPu/q6ktIosptrRz239CR9tleve4Z5Ut1f\n69KVoCvUdHnOt+MGxwTT+EPj6c11b9Lt8NtkN9eOKs2rRF8f/JoexvPGW3tJbdrmvo0Wn11M0ID0\nej0N/nswdd/UPdd6TlN9UXV6Y+0b+aZJSEmgPbf2EDSgbe7bck0TFB2U/pmTtcl0L/IeJWuTafP1\nzWQ1w4qcz/Prh8LjwikiPoKG7hxKjs6O1GNzD3pv83vUZlUbspphRdAY9yqcT3Z/kp6P83lnOn3/\nNM07NY9qLq5J72x8x6A8huwcQqsvryYi3pbq/1afTt8/Td4PvYmIqP+2/vTywpdp5L6R6b+TzM4H\nnM+yU191eRX1/asvlfmpDEUm8KuagqKDaPT+0bTmyhqCBlRzcU3a7bmbiHh7qfJLFRr892BaemFp\nrmX0fuidpfFRkGbLm9GHOz4kF2+X9DLkZtzBcWQ1w4oWnV2UPu2pDeL9+/ObyufNM7geTCYkJoTe\nXPcmQQPqtLYTVf6lMu24mfW1814PvbL8T5OYkkiXAi9RqVmlyHa2LSWmZLwhNywujOKS+TXy3g+9\n04NFaGwoRSVGERHRorOLCBqQTq8jnwgfoz/Lvch7pNVps0yLTYrNEgiJiFquaEmv/PoKfbrnU4IG\nNP/0/FzzSwuQaZ8hzaC/B9GUf6dQWFwYxSTFUGB0YPq8tVfX0tCdQ2nsgbEUHhdO3g+96aUFL9Ep\nv1MEDajz+s7kG+lLpWeXpkF/D6Lyc8pTcEwwHbt7LMsOKT96vZ4qzquYozX1y+lf6OWFL9OjhEf5\nLu/10CtLoMssNimWoAG1+L1FnkFXq9NS+zXtqeK8ijT/9Hy6/+h+lnr3ifAhnV5Her2e7j/i17DP\nOTmHRvwzIt9ydV7fmZZdKPhQNCElgWxm2mSpd0Nl3hbTeIZ5UslZJemQ1yH61+dfKjmrJHmEeqSX\nvbC+cfmG6v1WL/2ohYi3UYvpFnTI65BBeay9upZ6b+1NiSmJNGDbAKq1uFaW8q+6vIqgAa25sibX\n5WOSYgga0FcHviIioi/2fkFLLyylTms7pZfh/e3vU6V5lch2ti05OjtSw6UN048u9Ho9QQOCBulH\nwMYaunNoloZGXh7EPqDj946TTp/xhvCnNoj36EG0dy8VuR03d1DNxTXTvyRoQOMOjstx2JgfrU5L\n0IA6rOnw2OvX6XVG/1AK45DXIbKcbkl3wu8QNHjsMoTFhaUH9+xO+Z2iqvOrpneDrL+2ngZsG0A6\nvY6URlHfv/pSQkpCen0P2TmkUJ/BaZ0Trby0Msu0ZG2ySX5oaWXr91e/PNM8SnhEZ/3PZvmB5Sc2\nKTbXlmJmgdGBObq18pI5MJpCYHQg6fV60uv1FBAVYJI8556cS53Wdsp1XYaKTIikcnPKkaOzI723\n+b0sXVBExF0MGtBh78N55pH2faboUqj9mvZ0/N5xmnZ0Gr2//X0a8c8IKjenHPk98qMz989QfHJ8\n+hFV5uXz2xYeV36/n4I8tUH87beJDuf9HTwRfo/8yP5ne/rn9j+UkJJAB+4cSO/aeFw3Q2+abMMv\nKmnBrjCtufxodVrqsKYDlZ9Tnmxm2pDFdAtafHYxERHFJ8ent36hAY3cN5KiE6MLtZ6QmBCDW+6P\nKywujErPLk0f7PjgieT/vFh/bX2hd9KZ+UT40Jn7Z3Lte9fpdWT/s32Oo+TMwuLCqM6SOnQz9CaV\nm1OOwuPCKSg6iCrOq0iW0y3J0dkx3/U/jH+Y4wjXXPIL4ma9OiUxsehf8jveZTzGvTYOPerxm4xf\nfelVlLUpi5ZVWz52Xg1eaGDq4j1xlUvzrawvlX3JpPlaWlji36H/4rT/aXTZyNfodqzREQByXI/8\nVq23ULZE2UKtp0qZKsYVNB/2tvYInhgMK4un4srbYmtQ40HoVb+X0fnUtqud55UkFsoCN0fdTL+H\nIjf2tvZoXLkxNt/YjDI2ZVDJthIA4M6YO5h/Zn76fRl5qViqYuELX4TM+uyU1q2BZcv4/5Og1Wsx\ndNdQjHx1JJwvOCMmOQZn/M/g7ti76V8owDea2JWSN0GYStot6mVsyuSYJ3UtipLGVYMZx2fg9x6/\n44tWX6RPT9ImQavXpl9z/rTL79kpZg3iTZvyM0+exLsiw+LC0GZ1G5SwLIF7j+6h3cvtEBIbAgDw\nHO1p+hUKIZ46SdokBMcGF9mDqp4Uo952/yQlJvKjZU3t64Nf42b4TVQuXRknPzmZ3vpbcGZBvg8W\nEkI8W0pYlSj2AbwgZn0A1uP0iR/zPYaqC6pi9ZXV6dM+3v0xfjr5U5Z0PhE++PXCrzhy9wga2DeA\njaUNqpSpAhtLG0zuMBm/dXv8J6wJIcTTqtgE8VH7R6Fj9Y447nccAD+Oc73b+hwPh9nivgXv1uFb\ngdNuTU9jaWEpJ62EEM8Us3enFBTE31r/Fka1HoXw+HB80/4bdN/cHeXnlke5EuXwWYvPsO3mNmj1\nWjitc0KiNhEJ2gQs774cx/2Oo07FOvlnLoQQxdxT3RJP1CbiuN9xfLjzQ7R/uT0avdAID+MfYljT\nYahYqiLGtR2HVyq+gqbLm8LtgRseJT5CTFIMXq/+OjrV6IRmVQx8q4QQQhRTZmuJ6/X8CFq9SoJW\nn3s3h2+kL+rY1cHbtd9G8xebo7RNaXSs0RFj2oxJ79u++PlFNFjaAK1fao3ejr0RlxwHC2WBQ0MO\nFfVHEkKIIme2IJ6UBFhXvouqC1uh9UutcXhozjefeEd4o07FOljWfVn6tOMfH8+SRimFEa34gfhj\nXxv7ZAsthBBPGbMF8cREAO0W4v2G7+Nvz79BRNDqtbBQFukvf/WJ9EFdu7oF5jW+3fgC0wghxLPI\nbH3iiYmAhW0UXq/+OiyUBfyi/PDVwa/w24WMSwC9HnqhbsWCg7gQQjyvDAriSqmuSqlbSqk7Sqkc\n789RSn2jlLqqlLqilLqhlNIqpSrkl2diImBhk4hS1qVgZWGFWktqYfvN7XC955r+BniPMI/0V40J\nIYTIqcAgrpSyAOAM4F0AjQAMVkpleYUxEc0nohZE1BLAVACuRPQov3wTEwFlza8xG9N6DBzKOiA2\nORZ7bu9B61WtQURwD3WXIC6EEPkwpE+8DQAvIvIDAKXUVgC9ANzKI/1gAFsKyjRzEJ/2xjT0rN8T\n666tg3sYv3zUxccFSqn0p+4JIYTIyZAg7gDAP9N4ADiw56CUKgWgK4DRuc3PLDERUFYZLxRuUqUJ\nFry7AAAw8/hMDN8zHB2rd8zytmshhBBZmfrqlPcAnMqvK0Wj0QAAfH0BbUJoehDPbHKHybj76C6m\nO003cfGEEOLp5+rqCldXV4PSFvgoWqVUWwAaIuqaOv4t+C0T83JJuxPANiLamkde6Y+iPXAAGHi8\nCc5O3CL93kIIkY/8HkVryNUpFwHUVUrVUErZABgEYG8uKykPoBOAPYYUKiYGgGViri1xIYQQhimw\nO4WIdEqpMQAOg4P+GiLyVEqN4Nm0MjVpbwAuRJRgyIqjowGSIC6EEEYxqE+ciA4BqJ9t2ops4+sB\nrDd0xTExgN5CgrgQQhjDbHdsRkcDOiVBXAghjGG2IB4TA2gliAshhFHMFsQfRWsBkLxpRwghjGC2\nIB4VmwRrJa1wIYQwhvla4nGJKGEpQVwIIYxhvhOb8QmwsShhrtULIcQzwYxBXE5qCiGEscwWxGMT\nE1HSWoK4EEIYw6xB3NZGgrgQQhjDfK9n0yailLTEhRDCKGYL4lokoqSVnNgUQghjmCWIEwE6JKOk\ntQRxIYQwhlmCuE4HKKtklLCyMcfqhRDimWGWIJ6SAljapMDawtocqxdCiGeG+YK4dQqsLSWICyGE\nMczYEk+GjaV0pwghhDHM2xKX7hQhhDCK2YK4hXWKtMSFEMJI5gviNsnSEhdCCCOZrzvFSk5sCiGE\nscwWxJV0pwghhNHM151iJd0pQghhLPO1xKU7RQghjGZQEFdKdVVK3VJK3VFKTckjjZNS6qpSyl0p\n9V9++XFLXLpThBDCWAW+al4pZQHAGUBnAEEALiql9hDRrUxpygNYCuAdIgpUStnnlye3xKU7RQgh\njGVIS7wNAC8i8iOiFABbAfTKluYDADuIKBAAiCg8vwxTUgBYSneKEEIYy5Ag7gDAP9N4QOq0zOoB\nqKiU+k8pdVEpNTS/DFNSAGUp3SlCCGGsArtTHiOflgDeAlAawFml1Fki8s6eUKPR4NYtIOruBfi0\nsANamagEQgjxjHB1dYWrq6tBaQ0J4oEAqmcar5Y6LbMAAOFElAggUSl1AkAzALkG8b//Bs6c8kKT\n15oYVEghhHieODk5wcnJKX18+vTpeaY1pDvlIoC6SqkaSikbAIMA7M2WZg+A15VSlkopWwCvAfDM\nK8O0PnHpThFCCOMU2BInIp1SagyAw+Cgv4aIPJVSI3g2rSSiW0opFwDXAegArCSim3nlmZICkIVc\nnSKEEMYyqE+ciA4BqJ9t2ops4/MBzDckv5QUABZydYoQQhjLbHdskoV0pwghhLHMGMSlO0UIIYxl\n1pa4dKcIIYRxzBbE9UresSmEEMYySxDXagFS8o5NIYQwlvm6U5R0pwghhLHMFsR10p0ihBBGM1+f\nOKQ7RQghjGXGE5vSnSKEEMYyX3cKpDtFCCGMJd0pQghRjJkxiGthZWGqx5kLIcTzySxBXK8HdKSV\nPnEhhDCS2YK4tMSFEMJ4ZgniOj1BDx0slaU5Vi+EEM8MMwVxHSxgCaWUOVYvhBDPDPMEcdLCUklX\nihBCGMtsQdzCsJcKCSGEyIe0xIUQohiTIC6EEMWY+bpT5MoUIYQwmrTEhRCiGDNTENfBUk5sCiGE\n0QwK4kqprkqpW0qpO0qpKbnM76SUeqSUupL6911++UlLXAghTKPASKqUsgDgDKAzgCAAF5VSe4jo\nVrakJ4iopyEr1UMLS7nlXgghjGZIS7wNAC8i8iOiFABbAfTKJZ3Bt1/qpSUuhBAmYUgQdwDgn2k8\nIHVadu2UUteUUvuVUg3zy1C6U4QQwjRMFUkvA6hORPFKqf8DsBtAvdwSajQa3L8VhMT4ULi2doWT\nk5OJiiCEEM8GV1dXuLq6GpRWEVH+CZRqC0BDRF1Tx78FQEQ0L59lfAG0IqKIbNOJiNCq13nEdxoL\nzwnnDSqkEEI8z5RSIKJcu6wN6U65CKCuUqqGUsoGwCAAe7OtoEqm4TbgnUME8qCHdKcIIYQpFBhJ\niUinlBoD4DA46K8hIk+l1AieTSsB9FdKjQSQAiABwMD88tRDCysJ4kIIYTSDIikRHQJQP9u0FZmG\nlwJYauhK9aSFjVxiKIQQRjPPHZvQylt9hBDCBMzzjk15v6YQQpiEeYI46eTEphBCmIC0xIUQohiT\nIC6EEMWY2YK4PABLCCGMZ76WuPSJCyGE0aQ7RQghijEJ4kIIUYyZJ4grLawsJYgLIYSxzBLECVpY\nS0tcCCGMJlenCCFEMWaelriSlrgQQpiCGVvi8gAsIYQwlpn6xHXSEhdCCBOQq1OEEKIYkz5xIYQo\nxsx2iaHc7COEEMYzW0tculOEEMJ4ZusTt5YgLoQQRjNfn7gEcSGEMJqc2BRCiGJMWuJCCFGMGRTE\nlVJdlVK3lFJ3lFJT8knXWimVopTqm19+EsSFEMI0CgziSikLAM4A3gXQCMBgpZRjHunmAnApKE+5\nOkUIIUzDkJZ4GwBeRORHRCkAtgLolUu6rwD8DSC0wByVFlby7BQhhDCaIUHcAYB/pvGA1GnplFIv\nAehNRMsBqIIylO4UIYQwDVNF0sUAMveV5xnINRoNdDc8sHvV36g20B5OTk4mKoIQQjwbXF1d4erq\nalBaRUT5J1CqLQANEXVNHf8WABHRvExp7qYNArAHEAfgCyLamy0vIiJYDOmBHVO/RJ9GPQz8SEII\n8fxSSoGIcm0cG9ISvwigrlKqBoBgAIMADM6cgIhqZ1rZWgD/ZA/gWVhId4oQQphCgZGUiHRKqTEA\nDoP70NcQkadSagTPppXZFykwT+kTF0IIkzAokhLRIQD1s01bkUfa4QVmKC1xIYQwiSK/Y5MIEsSF\nEMJEJIgLIUQxVuRBXK8HYCEvhRBCCFMwTxC3lCAuhBCmYJYgrqQlLoQQJiHdKUIIUYyZ7cSmpZIH\nYAkhhLHM1BLXSUtcCCFMQLpThBCiGJMgLoQQxZgEcSGEKMbME8RV1iBes2ZNKKWeib+aNWsWdZUK\nIZ5jRd4czq0l7ufnh4Kea15cKFXgi42EEMJkzHKJIUl3ihBCmMRT0Z0ihBCicIo8iOt0BFhqYSlv\nuxdCCKMVeRDX6vSA3gIWqshXLYQQz5wij6TJOi1A0pUihBCmUORBPEWrhaLi1ZUSGRmJPn36oEyZ\nMqhVqxa2bNli7iIJIQQAM1ximKLXAfri1RIfNWoUSpYsibCwMFy5cgXdu3dH8+bN0aBBA3MXTQjx\nnDNDn7gWqhh1p8THx2Pnzp2YNWsWSpUqhQ4dOqBXr17YuHGjuYsmhBBm6E4pZkH8zp07sLa2Rp06\nddKnNWvWDB4eHmYslRBCsKLvTilkEDfFjZCFuSk0NjYW5cqVyzKtXLlyiImJMb5AQghhJINa4kqp\nrkqpW0qpO0qpKbnM76mUclNKXVVKXVJKvZVXXik6baH6xImM/yuMMmXKIDo6Osu0qKgolC1btnAZ\nCiGECRUYxJVSFgCcAbwLoBGAwUopx2zJjhBRMyJqAeATACvzyq+4dafUq1cPWq0WPj4+6dPc3NzQ\nqFEjM5ZKCCGYIS3xNgC8iMiPiFIAbAXQK3MCIorPNFoGQHhemRW3IG5ra4u+ffvihx9+QHx8PE6d\nOoV//vkHQ4cONXfRhBDCoCDuAMA/03hA6rQslFK9lVKeAA4AGJtXZsUtiAPA0qVLER8fj8qVK2PI\nkCH4/fff5fJCIcRTwWTRlIh2A9itlHodwEYA9XNLt+WP36C9/RAajQZOTk5wcnIyVRGeGDs7O+za\ntcvcxRBCPCdcXV3h6upqUFpV0HO8lVJtAWiIqGvq+LcAiIjm5bOMD4A2RPQw23TaeOQyvtj/GeIX\nXsk8/Zl6nviz8lmEEE+H1LiS6zV6hnSnXARQVylVQyllA2AQgL3ZVlAn03BLAMgewNOk6LSwKGbd\nKUII8bQqMJoSkU4pNQbAYXDQX0NEnkqpETybVgLop5QaBiAZQByAgXnlVxz7xIUQ4mllUDQlokPI\n1sdNRCsyDf8M4GdD8tLqtVAoXg/AEkKIp5UZnp2ik5a4EEKYSNEHcZI+cSGEMJUiD+Jr7v4ARdZF\nvVohhHgmFXmTeFC1KfjnSK6XkAshhHhMRd4Sb1+xN8omyt2OQghhCkUexPV6wKKYvSN56dKlaN26\nNUqWLInhw4ebuzhCCJGuyLtTimMQd3BwwPfffw8XFxckJCSYuzhCCJHOLEHcFC94KEq9e/cGAFy8\neBGBgYFmLo0QQmQo8jbxwIFAmTJFvVYhhHg2FXlL/O5doDAvxVHTjW++04/yYCohxLOlyIO4vX3h\nlpMALIQQORWzU4xCCCEykyBuAJ1Oh8TEROh0Omi1WiQlJUGn05m7WEIIIUHcELNmzYKtrS3mzZuH\nTZs2wdbWFrNnzzZ3sYQQouA3+5h0ZUpRbut7lt6G8yx9FiHE08HYN/sIIYR4SkkQF0KIYkyCuBBC\nFGMSxIUQohiTIC6EEMWYBHEhhCjGnoqXXdaoUQOquD3aMA81atQwdxGEEM8Rg64TV0p1BbAY3HJf\nQ0Tzss3/AMCU1NEYACOJ6EYu+eR6nbgQQoi8GXWduFLKAoAzgHcBNAIwWCnlmC3ZXQBvEFEzALMA\nrJZNmZIAAAPqSURBVDKuyM8+V1dXcxfhqSF1kUHqIiupj4IZ0ifeBoAXEfkRUQqArQB6ZU5AROeI\nKCp19BwAB9MW89kjG2cGqYsMUhdZSX0UzJAg7gDAP9N4APIP0p8BOGhMoYQQQhjGpCc2lVJvAvgE\nwOumzFcIIUTuCjyxqZRqC0BDRF1Tx78FQLmc3GwKYAeArkTkk0declZTCCEKIa8Tm4a0xC8CqKuU\nqgEgGMAgAIMzJ1BKVQcH8KF5BfD8CiGEEKJwCgziRKRTSo0BcBgZlxh6KqVG8GxaCeB7ABUBLFN8\nwXcKEbV5kgUXQghRxM8TF0IIYVpFdtu9UqqrUuqWUuqOUmpKwUsUb0qpNUqpB0qp65mm2SmlDiul\nbiulXJRS5TPNm6qU8lJKeSql3jFPqZ8MpVQ1pdQxpZSHUuqGUmps6vTnrj6UUiWUUueVUldT6+On\n1OnPXV0AfB+KUuqKUmpv6vhzWQ9GIaIn/gfeWXgDqAHAGsA1AI5FsW5z/YGv0GkO4HqmafMATE4d\nngJgbupwQwBXwd1bNVPrSpn7M5iwLl4E0Dx1uAyA2wAcn+P6sE39bwm+r6LDc1wX4wH8CWBv6vhz\nWQ/G/BVVS7zAG4aeNUR0CkBktsm9AKxPHV4PoHfqcE8AW4lIS0T3AHiB6+yZQEQhRHQtdTgWgCeA\nanh+6yM+dbAEuIETieewLpRS1QB0A7A60+Tnrh6MVVRB/HFvGHpWVSaiBwAHNgCVU6dnr59APKP1\no5SqCT5COQegyvNYH6ldCFcBhABwJaKbeD7rYhGASQAyn5h7HuvBKPIoWvN6rs4qK6XKAPgbwNep\nLfLsn/+5qA8i0hNRC/DRSEellBOes7pQSnUH8CD1CC2/S4+f6XowhaIK4oEAqmcar5Y67XnzQClV\nBQCUUi8CCE2dHgjg5Uzpnrn6UUpZgQP4RiLakzr5ua0PACCiaAAHALyK568uOgDoqZS6C2ALgLeU\nUhsBhDxn9WC0ogri6TcMKaVswDcM7S2idZuTQtZWxl4AH6cOfwRgT6bpg5RSNkqpWgDqArhQVIUs\nIn8AuElESzJNe+7qQylln3bFhVKqFIAu4BN2z1VdENH/iKg6EdUGx4NjRDQUwD94jurBJIrqDCqA\nruCrErwAfGvuM7pF8Hk3AwgCkATgPviZMnYAjqTWw2EAFTKlnwo+4+4J4B1zl9/EddEBgA58VdJV\nAFdSt4eKz1t9AGiS+vmvAnAD8E3q9OeuLjJ9vk7IuDrlua2Hwv7JzT5CCFGMyYlNIYQoxiSICyFE\nMSZBXAghijEJ4kIIUYxJEBdCiGJMgrgQQhRjEsSFEKIYkyAuhBDF2P8DSSN3y7QTDX8AAAAASUVO\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f798bbe4950>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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9OGBBy3MXNuskSZI61mDvXtwvM/8YEdsDV0XEnaw40r3zRtVJkiQN0qBCV2b+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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f796a9b25d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "scores/DECODA_MINIAE_TANH.shelve\n"
     ]
    },
    {
     "data": {
      "image/png": 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RmU0DvgJKgCeccwvCXc80xFBEJGaiahN3zk0FDg859q+Q/QeBB2u6lmriIiKx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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7957cf7a10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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KMHRJkiQVYOiSJEkqwNAlSZJUgKFLkiSpAEOXJElSAYYuSZKkAgxdkiRJBRi6JEmSCjB0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\nJEmSCjB0SZIkFfD/AVUKik622ouCAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7957cf73d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "scores/RAW_TRS_TRAIN.shelve\n"
     ]
    },
    {
     "ename": "KeyError",
     "evalue": "'ASR_H1_TRANSFORMED_W1'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-155-90df67f98f27>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m     13\u001b[0m             \u001b[0mscores_ordoned\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mscores\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     14\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 15\u001b[1;33m     \u001b[0mpandas\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mDataFrame\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mzip\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mx\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m\"ASR_H1_TRANSFORMED_W1\"\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[1;33m,\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mx\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m\"ASR_H1_TRANSFORMED_W1\"\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mplot\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     16\u001b[0m     \u001b[0mdata\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mclose\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     17\u001b[0m     \u001b[0mshow_network_TRANS\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mscores\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mtitle\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0munite\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m200\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/shelve.pyc\u001b[0m in \u001b[0;36m__getitem__\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m    119\u001b[0m             \u001b[0mvalue\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcache\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    120\u001b[0m         \u001b[1;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 121\u001b[1;33m             \u001b[0mf\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mStringIO\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdict\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mkey\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    122\u001b[0m             \u001b[0mvalue\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mUnpickler\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mf\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mload\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    123\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwriteback\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/dumbdbm.pyc\u001b[0m in \u001b[0;36m__getitem__\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m    118\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    119\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m__getitem__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 120\u001b[1;33m         \u001b[0mpos\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msiz\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_index\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m]\u001b[0m     \u001b[1;31m# may raise KeyError\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    121\u001b[0m         \u001b[1;32mwith\u001b[0m \u001b[0m_open\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_datfile\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'rb'\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    122\u001b[0m             \u001b[0mf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mseek\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpos\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mKeyError\u001b[0m: 'ASR_H1_TRANSFORMED_W1'"
     ]
    }
   ],
   "source": [
    "scores_ordoned={}\n",
    "for i in glob.glob(\"scores/**.bak\"):\n",
    "    #if \"MINIAE\" not in i :\n",
    "     #   continue\n",
    "    scores={}\n",
    "    print i[:-4]\n",
    "    data=shelve.open(i[:-4])\n",
    "    for key,table in data.iteritems():\n",
    "        scores[key]=round(table[1][np.argmax([x[0] for x in table[0]])][0],3)\n",
    "        if key not in scores_ordoned:\n",
    "            scores_ordoned[key]=[scores[key]]\n",
    "        else :\n",
    "            scores_ordoned[key].append(scores[key])\n",
    "            \n",
    "    pandas.DataFrame(zip([x[0] for x in data[\"ASR_H1_TRANSFORMED_W1\"][0] ],[x[0] for x in data[\"ASR_H1_TRANSFORMED_W1\"][1] ])).plot()\n",
    "    data.close()\n",
    "    show_network_TRANS(scores,title=i,unite=200)\n",
    "    #except:\n",
    "    #    print \"C4EST LA MERDE\",i"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "UNFIXED_TRANS_scores/MINIAE_TANH_H100_MODELDO50_DOMLP.shelve\n",
      "[]\n"
     ]
    },
    {
     "ename": "KeyError",
     "evalue": "'ASR_W1_TRANSFORMED'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-12-4daed94a92f0>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m     12\u001b[0m             \u001b[0mscores_ordoned\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mscores\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     13\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 14\u001b[1;33m     \u001b[0mpandas\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mDataFrame\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mzip\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mx\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m\"ASR_W1_TRANSFORMED\"\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[1;33m,\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mx\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m\"ASR_W1_TRANSFORMED\"\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mplot\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     15\u001b[0m     \u001b[0mdata\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mclose\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     16\u001b[0m     \u001b[0mshow_network_UNFIXED\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mscores\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mtitle\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0munite\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m200\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/shelve.pyc\u001b[0m in \u001b[0;36m__getitem__\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m    119\u001b[0m             \u001b[0mvalue\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcache\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    120\u001b[0m         \u001b[1;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 121\u001b[1;33m             \u001b[0mf\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mStringIO\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdict\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mkey\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    122\u001b[0m             \u001b[0mvalue\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mUnpickler\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mf\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mload\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    123\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwriteback\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/dumbdbm.pyc\u001b[0m in \u001b[0;36m__getitem__\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m    118\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    119\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m__getitem__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 120\u001b[1;33m         \u001b[0mpos\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msiz\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_index\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m]\u001b[0m     \u001b[1;31m# may raise KeyError\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    121\u001b[0m         \u001b[1;32mwith\u001b[0m \u001b[0m_open\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_datfile\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'rb'\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    122\u001b[0m             \u001b[0mf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mseek\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpos\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mKeyError\u001b[0m: 'ASR_W1_TRANSFORMED'"
     ]
    }
   ],
   "source": [
    "scores_ordoned={}\n",
    "for i in glob.glob(\"UNFIXED_TRANS_scores/MINIAE*.bak\"):\n",
    "    scores={}\n",
    "    print i[:-4]\n",
    "    data=shelve.open(i[:-4])\n",
    "    print data.keys()\n",
    "    for key,table in data.iteritems():\n",
    "        scores[key]=round(table[1][np.argmax([x[0] for x in table[0]])][0],3)\n",
    "        if key not in scores_ordoned:\n",
    "            scores_ordoned[key]=[scores[key]]\n",
    "        else :\n",
    "            scores_ordoned[key].append(scores[key])\n",
    "            \n",
    "    pandas.DataFrame(zip([x[0] for x in data[\"ASR_W1_TRANSFORMED\"][0] ],[x[0] for x in data[\"ASR_W1_TRANSFORMED\"][1] ])).plot()\n",
    "    data.close()\n",
    "    show_network_UNFIXED(scores,title=i,unite=200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DECODA_AEUNFIXED_TANH_TFIDF_DO.shelve.bak\r\n",
      "DECODA_AEUNFIXED_TANH_TFIDF_DO.shelve.dat\r\n",
      "DECODA_AEUNFIXED_TANH_TFIDF_DO.shelve.dir\r\n",
      "DECODA_AEUNFIXED_TANH_TFIDF_MODELS.shelve.bak\r\n",
      "DECODA_AEUNFIXED_TANH_TFIDF_MODELS.shelve.dat\r\n",
      "DECODA_AEUNFIXED_TANH_TFIDF_MODELS.shelve.dir\r\n",
      "DECODA_MINIAE_TANH_TFIDF_H30_DOMLP.shelve.bak\r\n",
      "DECODA_MINIAE_TANH_TFIDF_H30_DOMLP.shelve.dat\r\n",
      "DECODA_MINIAE_TANH_TFIDF_H30_DOMLP.shelve.dir\r\n",
      "DECODA_MINIAE_TANH_TFIDF_H30.shelve.bak\r\n",
      "DECODA_MINIAE_TANH_TFIDF_H30.shelve.dat\r\n",
      "DECODA_MINIAE_TANH_TFIDF_H30.shelve.dir\r\n",
      "MINIAE_TANH_H100_DOMLP.shelve.bak\r\n",
      "MINIAE_TANH_H100_DOMLP.shelve.dat\r\n",
      "MINIAE_TANH_H100_DOMLP.shelve.dir\r\n",
      "MINIAE_TANH_H100_MODELDO50_DOMLP.shelve.bak\r\n",
      "MINIAE_TANH_H100_MODELDO50_DOMLP.shelve.dat\r\n",
      "MINIAE_TANH_H100_MODELDO50_DOMLP.shelve.dir\r\n",
      "MINIAE_TANH_H100_MODELDO50.shelve.bak\r\n",
      "MINIAE_TANH_H100_MODELDO50.shelve.dat\r\n",
      "MINIAE_TANH_H100_MODELDO50.shelve.dir\r\n",
      "MINIAE_TANH_H100.shelve.bak\r\n",
      "MINIAE_TANH_H100.shelve.dat\r\n",
      "MINIAE_TANH_H100.shelve.dir\r\n",
      "MINIAE_TANH_H100_W3000_DOMLP.shelve.bak\r\n",
      "MINIAE_TANH_H100_W3000_DOMLP.shelve.dat\r\n",
      "MINIAE_TANH_H100_W3000_DOMLP.shelve.dir\r\n",
      "MINIAE_TANH_H100_W3000_MODELDO_DOMLP.shelve.bak\r\n",
      "MINIAE_TANH_H100_W3000_MODELDO_DOMLP.shelve.dat\r\n",
      "MINIAE_TANH_H100_W3000_MODELDO_DOMLP.shelve.dir\r\n",
      "MINIAE_TANH_H100_W3000_MODELDO.shelve.bak\r\n",
      "MINIAE_TANH_H100_W3000_MODELDO.shelve.dat\r\n",
      "MINIAE_TANH_H100_W3000_MODELDO.shelve.dir\r\n",
      "MINIAE_TANH_H100_W3000.shelve.bak\r\n",
      "MINIAE_TANH_H100_W3000.shelve.dat\r\n",
      "MINIAE_TANH_H100_W3000.shelve.dir\r\n",
      "MINIAE_TANH_H30_W3000_DOMLP.shelve.bak\r\n",
      "MINIAE_TANH_H30_W3000_DOMLP.shelve.dat\r\n",
      "MINIAE_TANH_H30_W3000_DOMLP.shelve.dir\r\n",
      "MINIAE_TANH_H30_W3000_MODELDO_DOMLP.shelve.bak\r\n",
      "MINIAE_TANH_H30_W3000_MODELDO_DOMLP.shelve.dat\r\n",
      "MINIAE_TANH_H30_W3000_MODELDO_DOMLP.shelve.dir\r\n",
      "MINIAE_TANH_H30_W3000_MODELDO.shelve.bak\r\n",
      "MINIAE_TANH_H30_W3000_MODELDO.shelve.dat\r\n",
      "MINIAE_TANH_H30_W3000_MODELDO.shelve.dir\r\n",
      "MINIAE_TANH_H30_W3000.shelve.bak\r\n",
      "MINIAE_TANH_H30_W3000.shelve.dat\r\n",
      "MINIAE_TANH_H30_W3000.shelve.dir\r\n",
      "MINIAE_TANH_H30_W300_MODELSDO_DOMLP.shelve.bak\r\n",
      "MINIAE_TANH_H30_W300_MODELSDO_DOMLP.shelve.dat\r\n",
      "MINIAE_TANH_H30_W300_MODELSDO_DOMLP.shelve.dir\r\n",
      "MINIAE_TANH_H30_W300_MODELSDO.shelve.bak\r\n",
      "MINIAE_TANH_H30_W300_MODELSDO.shelve.dat\r\n",
      "MINIAE_TANH_H30_W300_MODELSDO.shelve.dir\r\n",
      "MINIAE_TANH_H50_W3000_DOMLP.shelve.bak\r\n",
      "MINIAE_TANH_H50_W3000_DOMLP.shelve.dat\r\n",
      "MINIAE_TANH_H50_W3000_DOMLP.shelve.dir\r\n",
      "MINIAE_TANH_H50_W3000_MODELSDO_DOMLP.shelve.bak\r\n",
      "MINIAE_TANH_H50_W3000_MODELSDO_DOMLP.shelve.dat\r\n",
      "MINIAE_TANH_H50_W3000_MODELSDO_DOMLP.shelve.dir\r\n",
      "MINIAE_TANH_H50_W3000_MODELSDO.shelve.bak\r\n",
      "MINIAE_TANH_H50_W3000_MODELSDO.shelve.dat\r\n",
      "MINIAE_TANH_H50_W3000_MODELSDO.shelve.dir\r\n",
      "MINIAE_TANH_H50_W3000.shelve.bak\r\n",
      "MINIAE_TANH_H50_W3000.shelve.dat\r\n",
      "MINIAE_TANH_H50_W3000.shelve.dir\r\n",
      "MINIAE_TANH_H50_W300_DOMLP.shelve.bak\r\n",
      "MINIAE_TANH_H50_W300_DOMLP.shelve.dat\r\n",
      "MINIAE_TANH_H50_W300_DOMLP.shelve.dir\r\n",
      "MINIAE_TANH_H50_W300_MODELSDO_DOMLP.shelve.bak\r\n",
      "MINIAE_TANH_H50_W300_MODELSDO_DOMLP.shelve.dat\r\n",
      "MINIAE_TANH_H50_W300_MODELSDO_DOMLP.shelve.dir\r\n",
      "MINIAE_TANH_H50_W300_MODELSDO.shelve.bak\r\n",
      "MINIAE_TANH_H50_W300_MODELSDO.shelve.dat\r\n",
      "MINIAE_TANH_H50_W300_MODELSDO.shelve.dir\r\n",
      "MINIAE_TANH_H50_W300.shelve.bak\r\n",
      "MINIAE_TANH_H50_W300.shelve.dat\r\n",
      "MINIAE_TANH_H50_W300.shelve.dir\r\n"
     ]
    }
   ],
   "source": [
    "ls UNFIXED_TRANS_scores/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TRS_AE_H1 92\n"
     ]
    },
    {
     "data": {
      "image/png": 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aSJKI2Ai2mt6K5yLP8UbcDXr386b/VH+XX09kXCTbzmqbqqnDZrPxjUVv8J0l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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdde972e910>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TRS_AE_OUT 129\n"
     ]
    },
    {
     "data": {
      "image/png": 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BK6VUVnJbTmkL4ATJkMSVLQbQFUCgQ5sLAJonPr8DwJW0AbwwCY4IRsdvHkOV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\nlFKFmAZxpZQqxDSIK6VUIfb/VJpnn3dhEF8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fde1a7eacd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TRS_SPARSE 46\n"
     ]
    },
    {
     "data": {
      "image/png": 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dZ9G7Ue9C+Ux+ivwJ9f3qo0ONwj3d8Z72Hjot6YSeDXpifKfxICKM2zEO6fp0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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fde1c1307d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ASR_H1_TRANFORMED_TRSH1 181\n"
     ]
    },
    {
     "data": {
      "image/png": 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MzWefBdq1A3r2dL6vP8P+RPel3VG9RHXMe2YeivoUdb5TpZRKQU+7T+H6dXNi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\nSinlxjSIK6WUG9MgrpRSbuz/AUk+yV8otw//AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fde1a7d49d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ASR_AE_OUT 104\n"
     ]
    },
    {
     "data": {
      "image/png": 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jE6M5Y/8MSzbV6Y9OLDGuBF/87UWevHGSL/z6AledWmUp//W2r+k+0p0Tdk+w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\naRBgj2sAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdde34137d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ASR_H2_TRANFORMED_OUT 123\n"
     ]
    },
    {
     "data": {
      "image/png": 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I8m+IDAXQUER2AVgF4GOSUbnV6Nt15Yr5LcHHH7/9Os7EnEGHmR0wdcfUlHkk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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fde1c12b350>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ASR_SPARSE 199\n"
     ]
    },
    {
     "data": {
      "image/png": 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yzbQ23Be6L6VTknaP0pU6zOjADUEbWGdSHX7/5/dcd3IdY6xmNOWLURe59sTa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\nxJVSqhj7f4AHQ/RvPt1jAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdde2b077d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ASR_H1_TRANSFORMED_W1 109\n"
     ]
    },
    {
     "data": {
      "image/png": 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nzuE//wxs2ADUqAEMGpSRbecn0ZGIVmGt8EXfLxDcJLhI2ywici4XTRDfvx+4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\nMQVxEZFS7P8Bo/FPX67i1fcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fddecc31e50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ASR_AE_H1 116\n"
     ]
    },
    {
     "data": {
      "image/png": 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7tzvXnF6TUu6d395hmQllOP3Q9HSvN1vMbDijYUrW2WlxJ/Zd1ZftF7bP9P/t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\nQhRiEsSFEKIQkyAuhBCFmARxIYQoxP4fRt1FqjJyrh0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdde31bf7d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data=shelve.open(\"AUTO_scores/MINIAE_TANH_H50_W300_MODELSDO_DOMLP.shelve\")\n",
    "for key,table in data.iteritems():\n",
    "    print key, np.argmax([x[0] for x in data[key][0] ][2:])\n",
    "    pandas.DataFrame(zip([x[0] for x in data[key][0][:200] ],[x[0] for x in data[key][1][:200]  ])).plot()\n",
    "    plt.show()\n",
    "data.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ASR_AE_OUT 39\n"
     ]
    },
    {
     "data": {
      "image/png": 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oX77g9k6W4k3hozUf8dKilwBof257vuj7BS8sfIGYIzF8fcfXpxy8qw+u5kDC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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdde3333f90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ASR 48\n"
     ]
    },
    {
     "data": {
      "image/png": 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jEuN0Y/RGvXrc1Tp5y+Q8nx8RHaE1Pqyhsedi9ctdX2rDiQ1zDBc8fv641ptQ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\niRMRWRiTOBGRhf0/qVFAde//ku8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fddec8ce8d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TRS 66\n"
     ]
    },
    {
     "data": {
      "image/png": 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nsKDfAiZwIrKsgK6JZ5dSPEnPSseMbTOwfP9y9Lu6X5FnC0yyJeHlJS/jeMpx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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fddec956150>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TRS_AE_OUT 127\n"
     ]
    },
    {
     "data": {
      "image/png": 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XIgb8RkRA48YX59gHTh2gz6w+nE48DdjROo8ueZQNRzfw08M/OXLRoXGdxnH8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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdde3fcf3d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ASR_AE_H0 120\n"
     ]
    },
    {
     "data": {
      "image/png": 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Ot7d9W+brQi/auYi96Xu5ofUNx/+ilFLl5oSSuDEmAtgEdAV2A0uBviKywU/5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\nWgAD16oAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdde3b87d90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data=shelve.open(\"AUTO_real_spe_scores/V2_REAL_SPE_TANH_DOMODELS_50_DOMLP.shelve\")\n",
    "for key,table in data.iteritems():\n",
    "    print key, np.argmax([x[0] for x in data[key][0] ])\n",
    "    pandas.DataFrame(zip([x[0] for x in data[key][0][:200] ],[x[0] for x in data[key][1][:200]  ])).plot()\n",
    "    plt.show()\n",
    "data.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TRS_AE_H1 110\n"
     ]
    },
    {
     "data": {
      "image/png": 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1d3p7RW3T8U348/ifeL/1++6uilLp8ruLoUNBXESCAIyBuThoKsmQbMsrA5gJ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\n4kopVYxpEFdKqWJMg7hSShVj/w8RZoUFUEB4bgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdde3f80a50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TRS_AE_OUT 29\n"
     ]
    },
    {
     "data": {
      "image/png": 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kkHXup/GZ9TjXfcfXd/D3g+Y4vfPszqw6oiqf+vEp/m/p/xgYHsjNRzczLiWOTSc05cSN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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fde1c176bd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TRS_SPARSE 54\n"
     ]
    },
    {
     "data": {
      "image/png": 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nbp9Ki83C0bGj2ee3Pm4vqVuNacUWo1vQarPy/h/uZ7nB5Ri9Jtrr5Thw/gB7\n/NrDcQUw63+zGPV7FJMzkr2ehjujY0cztF8o+y7v6whSlYdUZuxR5+v9ZuycwYV7zMuwEy4m8M1f\n38zRpEOSGdYMDv9jODv91IlPTHuCu8+4f3nzovhFbDOuDUny2w3fssv0LrTZbaw5rCa7z+/uyGZy\n+/usv7PXsl6sNKQSR6wfwapDqzpOXj/v+Jk3fXdTngw93ZLO60dc77hqyXb4wmFWiK7Ag+cPcsCq\nAWz5fUtWHlKZ7Se3Z6efOnHMxjGOzHDq9qms81UdTts+jV2md+EHSz5wTOfPI38SUXBcJZAm4L23\n+D3O3z2f6ZZ0Dl07NEdGnc1ut/PTFZ9yyrYpHjPW5fuXs+awmkxMT2S1L6sV2DzkTmJ6IitEV+Ch\nC+YlJb/t+431v67P3st6s/W41ryQdoH3/3C/Y/t60uPXHqz3dT2+OvfVfMtdDRIuJvDdRe86YoDd\nbmeL0S04e9ds3jnhTrad0JbtfmzHKkOr8F+L/8UqQ6s4riTd2XlqJ1/45QV2+qkTO/3UiY9MecTR\nxDhj5ww2/KYhF8cvvrQgDnMb4l4AdQGEZQXqJrnKfAZgUNb/lQCcBVDMzbQKfaWuXWte8emPAasG\nMLRfKJ/++WkePH/Q0T/hYgJrDa/FGTtn5DO2ZysPrmT/lf29DqLTd0x3tHPGnY7j4NWD873cvFKs\nNqsjoyZN0Fqy9/K90jHTmsnKQypz/u75OU4W7y1+j6H9QvNkM9k2HNlARIHvLHyHJDn8j+GMnBRJ\nu93Ouybe5XE7Lo5fzBrDaji2fUpmCm8bexsHrTbv/k2zpLHnop6ObNudsRvH8snpT/KlOS/xQlrO\nH6QcsGoAT6cU8iscXTw36zk+NvUx3vDNDX5Po+einvxo6UdMzkjmTd/dxFn/m0W73c6ei3qy2pfV\nGDEggmdSzuQ7jVUHVxFRKPD7oKvVxM0TWfyL4o7snCT/Ov4X31n4DreeKODHT93Yf24/u8/vzien\nP8nPfv+MJC85iN8OYJFLd+/c2TiA7gBGZv1fH8AeD9PyfQ0VYNiwvD+t5I1MayZrDqvJPw7/wajf\no1ghugJ7L+vNiZsn8ubRN3PIGje/5Ksuuzfmv8GQfiH871bnD5ruP7ef4zeNz3e86DXRjqsci83C\n5t81Z5/f+rD28Nr5to1mt+9P3DyRHad05Au/vBAUJ1BvHL5wmCX7l+S7i971exp7z+5l+cHlWXt4\nbb4297UzwEsjAAAXgUlEQVQcy77x6EZ+HvN5gdOw2W0cvHpwobZBFyVpljR+uuLTfK/QL1V+QbzA\nd6eIyJMAHiL5elb38wBak3zHpUwIgOUAGgMoDeAZkovcTIsFzc8XNhvQuDEwaZJ5MtMX03dMx+iN\noxHzUgwAc8P/8HXDcTHjIppXbo737nivcG8DUl7Zc3YP/kj4I9/bJr2xfP9yPDj5QQx+YDB63dXL\nYzmS+Hr919h2ahsqR1TGF/d9gRLFSlzSvK+kmf+biZuq3OTV/duefLPhG7Sq3gp31fHxIFJXzCW9\nAMvLIN4XQGWSPUXkegDLANxMMjnXtPjZZ585uiMjIxEZGenfUgGYORMYPhxYu9bzm9Jsdhtmx83G\nIzc8goiwCADmwL1z4p348M4P0aVpF7/nr4LbmI1j8EzzZ1AuvFygq6KUT2JiYhATE+Po7tev3yUF\n8dsBRJHskNXdGya1j3YpsxDAAJJrs7qXwzS5bMw1rUvKxNPSzCP2ERHmb5s2QJ8+wOOPex7ng6Uf\nYOqOqQiVUAxpNwTPNHsGUTFRWLxvMda+shbFQq6K552UUlex/DJxbyJYLICGIlIXwHEAzwLolqvM\nLgAPAlgrIlUBNAKw3/8qu/fvf5t3pKxcaV5ib7UCjz3mufzo2NH4dc+v2PHmDmw/tR3vLn4XA1cP\nRHJmMta9uk4DuFKqyPPqfeIi0gHACJg7VSaQHCwi3WEy8rEiUgnAfwDUASAwd6pMdTMdnzPxzZuB\nm282L6S//nrz/44dgN1uXmZfo4azbLo1HZO2TEK35t2wNmEtXpv3Gta8ssbxPgab3Yaftv+E22vd\n7ngcVymlgl2R/VGIEyeAunWB778H/vY3k3Xv22deK/vUUyaoZ7PTjudmPYetJ7fiQvoF2Ow2zOs2\nD7fXuv0yLIlSSl05RTaI9+ljmk+Sk4Fu3czPRI0Y4b7s5ys/x5J9S7D8H8ux89ROpFhScE/dewqp\n5kopFThFMognJppXy/75J/D000B8vPmRh/vvz1uWJGoOr4mVL63UZhKl1FWnSP4827hxQLt2JpB/\n9BFQrBhw993uy8afi0doSCgaVmh4ZSuplFIBFpS3Z2RmAl99BcybZ7q7djW/Ah3m4VXdKw+uxL11\n79WHc5RS15ygzMR/+glo2hRo1cp0iwC1ankuv/KQCeJKKXWtCbogbrebu08++si78iRNEK+nQVwp\nde0JuiC+cCFQogTw4IMFlwWAAxcOwGq34oYK+oWmUuraE3RBfMgQk4V707ydbk3H8HXDEVkvUtvD\nlVLXpKAK4uvWAUeOmAd5CrL33F40+64Zjicfx5AHh1z+yimlVBAKqiA+ZAjw/vvmdkJXCRcT8PSM\np7Hp2CYAwNnUs3hkyiP48M4PMavrrKD+5XOllLqcguphnypVgK1bgerVc/b/cOmH2Hh8I3ad3oVq\npavhTOoZ/P2mvyO6XbT7CSml1FWkyDyxGR4ObD10CO8t74FP7/kUbWq1QUpmCup+XRex/4xFpYhK\niD8Xj7CQMDSv0lzbwZVS14RLfRXtFZGRYW4v3H52I+LPxqPLz13wQP0HcH3563FXnbtQv3x9AECr\n6q0CXFOllAoeQdMmnpQElC0LHDi/H482ehRxb8WhZpmaGLRmEHre3jPQ1VNKqaAUNEE8MREoUwbY\nf34/GpRvgDIlymDQg4Nwrtc5RNaLDHT1lFIqKAVVEC9bFth/Yb/jRxwAOH4XUymlVF5BE8Szm1Oy\nM3GllFIFC5ognpgIlClrw+GLh1GvXL1AV0cppYqEoArixSocQeWIyggvFh7o6iilVJEQVEGc5Q5o\nU4pSSvkgqIK4pbS2hyullC+CKoinhWsQV0opXwRVEE8O0yCulFK+8CqIi0gHEYkTkT0i0svN8A9E\n5C8R2Swi20XEKiLlfKlIYiJwQTSIK6WULwoM4iISAmAkgIcANAPQTUSauJYh+SXJliRbAfgYQAzJ\nC75UJDEROG9PQO2y+lpZpZTyljeZeGsA8SQPkbQAmAagcz7luwGY6mtFEhOBDCbhuvDrfB1VKaWu\nWd4E8ZoAEly6j2T1y0NESgLoAGCWrxW5mEik21JQKqyUr6MqpdQ1q7BfRdsJwJr8mlKioqIc/0dG\nRiIyMhIAkJiaiuKhJRAaElrIVVJKqaIlJiYGMTExXpUt8EchROR2AFEkO2R19wZAknl+VkdEfgHw\nM8lpHqbl8Uchqt9wEtbXbsbpXie9qrhSSl0r8vtRCG+aU2IBNBSRuiJSHMCzAOa5mcl1AO4FMNef\nSialJ6N0idL+jKqUUtesAptTSNpE5G0AS2GC/gSSu0SkuxnMsVlFHwewhGSar5Ww24FUWxLKahBX\nSimfeNUmTnIxgMa5+o3J1f0DgB/8qURyMhB+nWbiSinlq6B4YjMxEYi4LhllipcJdFWUUqpICZog\nXqJMMkoX10xcKaV8ETxBvGySBnGllPJR0ATxsFLanKKUUr4KniAeoc0pSinlq6AJ4iEltTlFKaV8\nFRRBPCkJCAnXTFwppXwVFEE8MRFA8WSUKaFt4kop5YugCeIM00xcKaV8FRRBPC0NsIRom7hSSvkq\nKIK41QpkQjNxpZTyVfAEcep94kop5augCOI2G5ChmbhSSvksKIK41Wp+X1ODuFJK+SZogni6XTNx\npZTyVXAEcZsdmUxDqeL6I8lKKeWLoAjiGfZUlAgpiRAJiuoopVSRERRRM92ehPAQbUpRSilfBUUQ\nz0QySoZqEFdKKV8FRRDPQDJKhuo94kop5augCOKZSEJEMc3ElVLKV0ESxJMRoc0pSinls6AI4hZJ\n1kxcKaX84FUQF5EOIhInIntEpJeHMpEi8peI7BCR332phEWSUSpM28SVUspXxQoqICIhAEYCeADA\nMQCxIjKXZJxLmesAjALQnuRREankSyUsIUkoFaaZuFJK+cqbTLw1gHiSh0haAEwD0DlXmecAzCJ5\nFABInvGlEiYT1yCulFK+8iaI1wSQ4NJ9JKufq0YAKojI7yISKyIv+FIJW4i+N0UppfxRYHOKD9Np\nBeB+AKUArBORdST35i4YFRXl+D8yMhKRkZGwhqQgIqxaIVVFKaWKtpiYGMTExHhV1psgfhRAHZfu\nWln9XB0BcIZkOoB0EVkFoAWAfIN4NptkIrxYca8qrJRSV7vsBDdbv379PJb1pjklFkBDEakrIsUB\nPAtgXq4ycwHcJSKhIhIBoA2AXd5WmLAirFhhXRQopdS1o8DISdImIm8DWAoT9CeQ3CUi3c1gjiUZ\nJyJLAGwDYAMwluT/vK2EHRaUKBbm5yIopdS1y6v0l+RiAI1z9RuTq/tLAF/6Uwk7rCiumbhSSvks\nKJ7YtItm4kop5Y+gCOIUbRNXSil/BEUQt4sF4WGaiSullK+CIohTtE1cKaX8ESRB3IISmokrpZTP\ngiSIW1EiTDNxpZTyVZAEcb07RSml/BHwIG63AwixahBXSik/BDyI22wAQi0IC9XmFKWU8lXAg7jV\nCkioFWGhmokrpZSvgiKII9SCYiGaiSullK8CHsRtNkBCrAgL0UxcKaV8FfAgrpm4Ukr5L+BB3GYD\nEKJt4kop5Y+AB3GrFUCIZuJKKeWPIAni2iaulFL+CHgQt9kAaiaulFJ+CXgQd2Ti2iaulFI+C4og\nrpm4Ukr5JwiCOIEQqwZxpZTyQ8CDeIbFBjAEIRLwqiilVJET8MiZYbFC7NoerpRS/gh8ELdaINSm\nFKWU8odXQVxEOohInIjsEZFebobfKyIXRGRz1uff3lYg02KFUDNxpZTyR4EpsIiEABgJ4AEAxwDE\nishcknG5iq4i+ZivFUi3WBCimbhSSvnFm0y8NYB4kodIWgBMA9DZTTnxpwKZVs3ElVLKX94E8ZoA\nEly6j2T1y+0OEdkiIgtE5EZvK5BhtSCk4AsCpZRSbhRW9NwEoA7JVBF5GMAcAI3cFYyKinL8HxkZ\nCYu1tmbiSinlIiYmBjExMV6VFZL5FxC5HUAUyQ5Z3b0BkGR0PuMcAHAryXO5+jP3/L77OQ4f/dUZ\nyYN2e1VhpZS61ogISLptsvamOSUWQEMRqSsixQE8C2BerhlUdfm/NczJ4Ry8kGm1IkQzcaWU8kuB\nzSkkbSLyNoClMEF/AsldItLdDOZYAE+JyJsALADSADzjbQUytU1cKaX85lX0JLkYQONc/ca4/D8K\nwCh/KpBpsyIEmokrpZQ/Av7EZqbVglDNxJVSyi8BD+IWmxUhopm4Ukr5I+BBXDNxpZTyX8CDuMVm\nRai2iSullF8CHsQz7RaEiGbiSinlj4AHcYvVilBtE1dKKb8EPIhb7RaEaiaulFJ+CXgQt9isKKaZ\nuFJK+SXwQVwzcaWU8lvAg7jVrpm4Ukr5K+BB3GKzIDREM3GllPJH4IO4ZuJKKeW3gAdxq92CYpqJ\nK6WUX4IgiGsmrpRS/gp8EKdm4kop5a+AB3Gb3YqwEM3ElVLKHwEP4lbq3SlKKeWvwAdxuxVhoZqJ\nK6WUPwIexG20IEwzcaWU8kvAg7iV2iaulFL+CngQt8GCsFDNxJVSyh+BD+LaJq6UUn4LfBCHRYO4\nUkr5yasgLiIdRCRORPaISK98yt0mIhYR6eJtBey0anOKUkr5qcAgLiIhAEYCeAhAMwDdRKSJh3KD\nASzxpQI2WFBcM3GllPKLN5l4awDxJA+RtACYBqCzm3L/B2AmgFO+VMCmmbhSSvnNmyBeE0CCS/eR\nrH4OIlIDwOMkRwMQXypgFwuKF9NMXCml/FFYKfDXAFzbyj0G8qioKMf/kZGR2iaulFK5xMTEICYm\nxquyQjL/AiK3A4gi2SGruzcAkox2KbM/+18AlQCkAHid5Lxc02Lu+ZX/vw7oc39PfPhEB68qrJRS\n1xoRAUm3ybE3KXAsgIYiUhfAcQDPAujmWoBkA5eZ/QfA/NwB3BOKFcWLaSaulFL+KDB6krSJyNsA\nlsK0oU8guUtEupvBHJt7FF8qYIe2iSullL+8SoFJLgbQOFe/MR7KvuJLBeyaiSullN8C/sSmHRaU\nCNNMXCml/BHwIE6xorjenaKUUn4JeBC3iwXhmokrpZRfAh7EKVaEaZu4Ukr5JQiCuGbiSinlryAI\n4laUCNNMXCml/BH4IB6id6copZS/Ah/ENRNXSim/BTyII8SCksU1E1dKKX8EPIjru1OUUsp/AQ/i\nmokrpZT/giCIW3Fri6YQkaviU69evUCvUaXUNSSg7RgkgVArDh8+hILea15UiPj0w0ZKKXVJApqJ\nW+02wB4ayCoopVSRFtAgnp5pAWzaHq6UUv4KcBC3Ana9M0UppfwV2CBusQB2zcSVUspfAQ3iGRYr\nhJqJK6WUvwLfJl4EMvHz58/jiSeeQOnSpVG/fn1MnTo10FVSSikAAb7FMMNqMvFgv7mwR48eCA8P\nx+nTp7F582Z07NgRt9xyC5o2bRroqimlrnEBz8QlyDPx1NRU/PLLL+jfvz9KliyJtm3bonPnzpg8\neXKgq6aUUtomXpA9e/YgLCwM119/vaNfixYtsHPnzgDWSimljAA3p1gg9C4TL4wHIf15KDQ5ORll\ny5bN0a9s2bJISkq69AoppdQl8ioTF5EOIhInIntEpJeb4Y+JyFYR+UtENorI/d5MN9OHTJy89I8/\nSpcujcTExBz9Ll68iDJlyvg3QaWUKkQFBnERCQEwEsBDAJoB6CYiTXIV+41kC5ItAbwMYKw3M8+w\nWhDiZSYeKI0aNYLVasW+ffsc/bZu3YpmzZoFsFZKKWV4k4m3BhBP8hBJC4BpADq7FiCZ6tJZGsAZ\nb2aeaQ3+NvGIiAh06dIFn376KVJTU7FmzRrMnz8fL7zwQqCrppRSXgXxmgASXLqPZPXLQUQeF5Fd\nABYCeMebmadbgj8TB4BRo0YhNTUVVapUwfPPP4/vv/9eby9USgWFQkuDSc4BMEdE7gIwGUBjd+Wi\noqIc/x8slo7iGTWQUliVuEzKly+P2bNnB7oaSqlrRExMDGJiYrwqKwW9x1tEbgcQRbJDVndvACQZ\nnc84+wC0Jnk2V3+6zu/JiT0Qu7gREmb866p6n/jVsixKqeCQFVfc3qPnTXNKLICGIlJXRIoDeBbA\nvFwzuN7l/1YAkDuAu7Pjwnpcl9TGiyoopZRyp8DmFJI2EXkbwFKYoD+B5C4R6W4GcyyAJ0XkHwAy\nAaQAeKag6aZaUnE4ZTduTWt5aUuglFLXMK/axEkuRq42bpJjXP4fAmCILzPefHwz6pRshoji4b6M\nppRSykXAHrtff2Q9KmW0wY03BqoGSilV9AUsiG84ugE40gYtWgSqBkopVfRd8SdtHp/2OADg94O/\no+qWgWjxzytdA6WUunoUeIthoc5MhLN3mfutizECT7VqhwvnBSVLXj235ekthkqpwpbfLYZXPhNv\nYjLxzZuBGxoC4fq9plJK+S1gbeJbt6LItIePGjUKt912G8LDw/HKK68EujpKKeUQsLdPFaUgXrNm\nTXzyySdYsmQJ0tLSAl0dpZRyCFgmvmULcMstgZq7bx5//HE89thjqFChQqCropRSOVzxTLxSJfM3\nKanoBHGllApWVzyIx8WZv8WLA7l+9Sxf0u/Sf5+Nn+ldI0qpq0vAMnFfaQBWSqm8Avpr90oppS6N\nBnEv2Gw2pKenw2azwWq1IiMjAzabLdDVUkopDeLe6N+/PyIiIhAdHY0pU6YgIiICAwYMCHS1lFLq\nyj92725+V9Oj6lfTsiilgsOl/rKPUkqpIKVBXCmlijAN4kopVYRpEFdKqSJMg7hSShVhGsSVUqoI\nC9iraF3VrVsXIpf+bpRgULdu3UBXQSl1DfHqPnER6QDga5jMfQLJ6FzDnwPQK6szCcCbJLe7mY7b\n+8SVUkp5dkn3iYtICICRAB4C0AxANxFpkqvYfgD3kGwBoD+AcZdWZeWNmJiYQFfhqqLrs/DpOr38\nvGkTbw0gnuQhkhYA0wB0di1Acj3Ji1md6wHULNxqKnf0AClcuj4Ln67Ty8+bIF4TQIJL9xHkH6Rf\nA7DoUiqllFLKO4X6xaaI3AfgZQB3FeZ0lVJKuVfgF5sicjuAKJIdsrp7A6CbLzdvBjALQAeS+zxM\nS7/VVEopP3j6YtObTDwWQEMRqQvgOIBnAXRzLSAidWAC+AueAnh+lVBKKeWfAoM4SZuIvA1gKZy3\nGO4Ske5mMMcC+ARABQDfibnh20Ky9eWsuFJKqSv8PnGllFKF64o9di8iHUQkTkT2iEivgsdQuYnI\nQRHZKiJ/icifWf3Ki8hSEdktIktE5LpA1zNYicgEETkpIttc+nlcfyLysYjEi8guEWkfmFoHLw/r\n8zMROSIim7M+HVyG6fq8DK5IEPfygSFVMDuASJItXZqregP4jWRjACsAfByw2gW//8Dsg67crj8R\nuRFAVwBNATwMZ1OhcnK3PgFgOMlWWZ/FACAiTaHr87K4Upl4gQ8MKa8I8m6zzgB+yPr/BwCPX9Ea\nFSEk1wA4n6u3p/X3GIBpJK0kDwKIh9mPVRYP6xMw+2lunaHr87K4UkHc1weGlHsEsExEYkXktax+\nVUmeBACSJwBUCVjtiqYqHtZf7n32KHSf9dbbIrJFRMa7NE/p+rxM9FW0RUtbkq0APALgLRG5Gyaw\nu9Jvqi+Nrr9L8x2ABiRvAXACwLAA1+eqd6WC+FEAdVy6a2X1Uz4geTzr72kAc2AuR0+KSFUAEJFq\nAE4FroZFkqf1dxRAbZdyus96geRpl1eVjoOzyUTX52VypYK444EhESkO88DQvCs076uCiESISOms\n/0sBaA9gO8x6fCmr2IsA5gakgkWHIGebraf1Nw/AsyJSXETqA2gI4M8rVckiJMf6zDoRZusCYEfW\n/7o+L5Mr8qMQnh4YuhLzvopUBTA769UFxQBMIblURDYC+FlEXgFwCOYOAOWGiPwEIBJARRE5DOAz\nAIMBzMi9/kj+T0R+BvA/ABYAPfRl+Dl5WJ/3icgtMHdSHQTQHdD1eTnpwz5KKVWE6RebSilVhGkQ\nV0qpIkyDuFJKFWEaxJVSqgjTIK6UUkWYBnGllCrCNIgrpVQRpkFcKaWKsP8Hq9K6JXB4DbAAAAAA\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdde1841e50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ASR_AE_OUT 75\n"
     ]
    },
    {
     "data": {
      "image/png": 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TW+FvacURFTN86AvCo9Mf1Tpj62To9eGK45eOq/dgbx29NpuLf5Kqqj43+znt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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdde2be6d10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ASR_H2_TRANSFORMED 68\n"
     ]
    },
    {
     "data": {
      "image/png": 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sKwdVZsvJLTn675zzeKYHyFRzKquPqc77pt2XY1tSShLrj6/Prou75qhvbTO9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\ngrgQQhRjEsSFEKIY+3+WIFwhekuuPgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdde9051e50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ASR_SPARSE 95\n"
     ]
    },
    {
     "data": {
      "image/png": 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26WRNb/aB2Ww6oylH7RjFkzdP8tcjv/LVRa/m6P64q/zo8ncdxAuk69j0Te7Y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\niAshRD4mQVwIIfIxCeJCCJGP/T/bHeRSVbXBOAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdde1d98f10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ASR_TRANFORMED_OUT 64\n"
     ]
    },
    {
     "data": {
      "image/png": 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pY5/1fVh+cHmGbgxlUHgQFxxawEpDKznk8d9Y/IbtGgFJ9o/oz+CRwWw6oSlH\nbB/B+8bfx65LuxKhsLUmX1/0Orst68bU9FQGDgrkxYSLtFqt7LyoMx+e+jBrjKjBd5a8w56/6ZtU\nno07yydnPUmf/j784LcPeC7uHK8kXcnx92G1Wnk58TIvJ17OVm7OgTl8/md9a/vd0bt55493kiTH\n7RzHd5a8w+fmPsfwbeE8GXuSNUfW5PJjy7n06FJWGVaFz855lg9MeiD3X8gN5nQzH5j0AAdtGcRz\ncedYdXhV7jmvJwa5lHiJgYMC+diMxzhr/yyH980/OJ+PzXiMJDn9r+l8Zf4rOe7no5UfcfCWwXxr\nyVu2IJNh8+nNtvQgSX7w2we8a/RdfGbOM+yzvk+O2113ch3rj6nPByY9wPpj6rPF5BZccEjPEnXq\n2im+uuBVRsZEsvuy7uy0sJPtWHdb1o2dFnYiSd7xwx08ekXfXXr/xf22AOwq9dFtWTcO2TqE9UbX\nY7+Ifvwn9h8GhQdx+xk9i9bFhIv0C/Pjb8d/45WkKyw7qCwDBwXyesp1tv+5PafsnUJS/+13mNeB\nD0x6gDP3zWTNkTXZZlobh30N2TrE1npvMqEJP1v9GZtPas4nZj7BpUez334r6noUg8KDOP/gfFYO\nr8w1J9bwUuIlXkq8ZEvVbY3aytqjahfPIP7JJ3oynvR0PbNgxjwHKSn6TiLuBF9XNm/WfTHvvDP7\naMxLiZdsgdNitbDL4i6sP6Y+/zzneP+0d5a8Q4SCkTGRedp3s4nNGLYpLMcyX679kv0i+rHx+Mb8\n42weJh0uQlarlZcSLzkss1gtLvvFJ5mTbH+YQ7YOIULBRYcdb4B59MpRVhxakfGmeMaZ4lhxaEUe\nvXKUHeZ1YMDAAB6/qk+17PcRZ4qztcJenv8yp+ydwkFbBvHusXczyZzEL9Z8Qd/vfR3eY7VaeS7u\nnOcHgZmn0SlpKfxk1Se2M7Pd0btZYUgFVh1e1ZZX3xq1lQEDA1jnhzrcfHozk83J9B/gz4RU925p\n8+XaL/nsnGdtrdhRO0axw7wOtuddFnfhpD2T+OqCV5luSee3G77lwUsH+eycZzlz30ySOlgGhQfZ\nAuT1lOv8cu2X7LyoM79e/zUtVgsb/dSIO87u4MZTG1lvdD1eSLjAZHMyP139qe3L55X5r3D6X9NZ\nf0x9JqQm8NS1U6wwpAIvJlzk0K1D2XlRZ9sj42yjy+IuHLVjFNMsafzz3J+c9/c8Vh9RnaY0E7su\n7co209qxsaFVAAAcE0lEQVSw/ODyrPtjXYcWcGp6qu11u7ntuPiwvk3RgkML2GFeB/aP6O/ymkqb\naW24/uR6nrl+ho/NeIylwkpxyNYhDmXszyA6zOvA1xa+RpJcfHgx7xt/H2OSYxi2KYytp7W2NUwS\nUhNsF10zXE+5zjo/1GHoxlBWG16NqempvH3Y7Sz5fclsZTMsPbqUCAUHbnYxGTz1RdFiE8TtA+pd\nd+lHx456+snIvMVKWq1Wzt4/m3039uUPf/zg0Lo8d05/8owpKu3N3j+bCAVn75/NgZsH8uGpD2fL\nHZP6FxwwMCDPV5sjYyJzvbi04tgKtpjcgn5hftkurN0KLFaLrSWUVcbp7Iu/vGhr1cSb4m0XaHMy\n/a/pLBVWii0mt7CdIZjTzdwdvbvgKu/Ew1Mf5rKjyxgUHmT7Uk9NT2XJ70ty1I5RDmV3nN3hELRb\nTW3F1ZFOJvjOYuXxlaw+orpDqiTZnMzbh93Or9Z+xbo/1uW6k+sYHR/N8oPL8+v1X/M/4/7DikMr\nMnBQoMM+a46sySNXjnDH2R2sMaIGuy3rxln7Z/HByQ+y17peLDOwDM3pZlqtVn674VtWDq/MO3+8\nk68ueJVXkq4wJS2F9/50LwMGBjj8Xrou7cpyg8vxqVlPcea+mZy1fxZn7pvJuj/W5eQ9kxk4KDBb\nyuWZOc+w97rerDCkAq8mXeWJmBPZrsfY67Wul60RNGDzAH619ivuPb+XtUfVZrwpnlarlQsPLbR9\nSVcZVoVnrutTdovVwo2nNub4P3s+/ryt91GaJY0frfyIVYZVYeXwym598e88t5M+/X1s18Q+X/M5\nG/3UKMf37Di7I8c67b+4v3gE8dOn9exiR45kzj524YJOeWS9I7srVquVy48t54x9M/jEzCfYbGIz\n9t3Yl80mNuOAzQNs5SwWPbLz0qXs2/h6/dd88ZcXeduQ2xgUHuSyZZmSlpKnVEpeXE+5Tq9+Xmw2\nsVmhbP9mFh0fzX4R/dgvoh+j46Pz9N6E1ATO2Dej0NJMrgzeMph3jb6LLae0dFi+4tiKXL+Ev93w\nrUMa4kLChWxfWNHx0awcXjlbbyZS95bJ2lBpOqEpg8KDeD7+PP+J/SfbBeM3Fr/B/hH9WXV4VVur\nliTPXD/DCkMqZLsmsit6ly3Xm+HUtVPZUhgXEi5w3t/zsqWc9pzfw5Lfl7SlneztOLuDCIXTjgDO\nzNg3g68vep0k+eavb3Lynsm0Wq3surQra42qxbaz29L3e19+v+l7JqQm0C/ML9/d+jJsPr3Z5TUs\nZzLSIqQ+s98atdWj/ZP0PIgDaAvgKIDjAHo5Wf8FgL8A7AXwN4B0AOWclHNawYy7btSvryeumT6d\nfCXntJ1Te87vYaWhldhlcReGbwu3nfqcjTvLyuGVOffAXG47sy3Hf6wO8zpw/sH5XHhoITee2pj3\nShSQJhOa8P0V7xu2f+G+vy/9TYQix37Crqw7uc4W/FPTU9l8UnMGDAzgNxu+sXVR7Lq0K79a+1VO\nm3Gw4tgKbjuzzeX6KXunEKHg1+u/zrYu4lQE155Ym8dPkbuFhxba+vRnNXLHSF5NuurWdnZF77K1\nbB+c/CA3n868x+CKYys4fPtwLji0gI/PfJx7z+/lf8b9x/PK3wQ8CuLQozpPAAgG4ANgH4D6OZR/\nDsB6F+ucVrBfP/Lll3XKpFIlHcCdzT6Wm34R/bJdBc6w9sRatpzSktWGV+PYnWNty7P216w3uh4P\nXjqY9e1FbuLuiW4PqBHGslqt7PlbT9vFvrxITE1k6QGlefraaX66+lM+N/c5no8/z0emP8KPV33M\n09dO21INBeV8/Hm+t/w9t/sq30ySzEksP7g8T107xduG3OZ04FVsciwDBgZw1v5ZOXY/LE48DeIt\nAKyye93bWWvcbv0cAP/nYp3TCnbtqidyJ8lHH9W1OnEi7x/0/on35xr4ZuybYbs6v+TIEtYfU982\nOs2UZmLJ70u67K4kRGF46ZeXGBQexMbjG9uCdUxyDGuOrMlmE5u5nWr4t+izvg9fmf8Kyw4q67JX\nUePxjd3qMVNc5BTE3Zk7pRqAs3avz91Ylo1Syu9G6mWRG9u1SU4GSpfWz7t3B+rU0Y+8uJR4CZGx\nkXi45sM5lmsT3AabojaBJBYdWYTktGT0+K0HSOJ4zHHULl8bvt6+edu5EB5Y2HEhLn1xCX+9+xdu\nK30bAKCCXwX8/NLPOJ9wHp89KHcksffZg59hZeRK1LutHpSLeaLbBLfBqshVqHdbvSKuXdEr6Amw\n2gHYSjL7tHg5SE7WMw0CQMeOeh7wvM7hvTJyJZ6o80SuATi4XDD8Svjh8JXDWHViFdZ0WYN9F/dh\n/qH5OHzlMO6udHfedixEIWlZoyXOfnoWlfwrGV2Vm0rF0hXxYfMP0bBSQ5dl2gS3AcF/RRB356YQ\n0QBq2r2ufmOZM68B+DmnjYWGhtqeh4SEICQkBCkpmS1xpdyfiD1DfGo8pu6biq73dXWrfJtabTB0\n+1BUCaiC+hXr44e2P+CDlR/g5btfzvEPQ4ii5qVuqYlGC8yAxwYgJS3F5frWwa2hoHBnhTuLsFYF\nJyIiAhEREe4VdpVnYWYe2xuZFzZ9oS9sNnBSLhBADAC/HLblNN/TqlXmhFR5deDiAQaPDGb3Zd3d\n7lM9de9UqlBly5dZrVa2nNKSFYZUsA2hFkIUbxkTyd0K4ElOnKQFQE8AawEcAjCP5BGl1LtKqe52\nRTsAWEPS9dejC/bplLyasGcC3mr8Fia0m4BSJXK4X5OdNrX0qdazdz4LAFBK4bvW3yE2JVbSKULc\nIu6tXER3hTCYW/fYJLkawF1Zlk3I8noGgBn5qYR9OiUnCakJsNCCcqUyb+IXcToC09pPy9P+aper\njWFPDEOL6i1sy56840mMe2YcGlRskKdtCSGEkZRuqRfRzpSis/3Vrq1vjVa7dvb3pKanomQJfefW\njgs6wtvLGz+/pNPuV5Ov4o4f70DMVzEo4XVL3fNZCCFslFIg6bS7x00R+VylU9Kt6ag7ui6+f+R7\n3F/1fkScjoDZYkacKQ6BpQKxOWozWtZoKQFcCPGvdVNc+rZPp2yO2oxW01rBYrVgzYk18Cvhhy/X\nfYkPVn6AL1p+gcfqPIb5h+YDADad3oQ2wW0MrLkQQhjL8CBOOrbEv9v4HQ5cOoBFRxZhxv4Z+OzB\nzzDosUE4dOUQejTrgTcbvYmZB2YCADZFSRAXQvy7GZ4TN5sBf38gLU23rLsu74rhTw7HV+u+wsXE\nizj18SmU9yuPJHMS/H39kWZJQ/WR1XHf7fdh+9ntiPkqBj7ePkX2GYQQoqjllBM3PIjHxQE1a+qf\nj898HF3u7YI3G72J5pObo3a52pj/yvxs24mMiURkbCQq+1dG06pNi6r6QghhiJs6iF+4ADRpAmw5\ndAIPTX0I5z49Bx9vH5yIPQEfLx8ElwsusvoJIcTN6KbunZKRD5+5fyZev+d1W2qkboW6BtdMCCFu\nfoZf2ExJAfxKWzHrwCz8t9F/ja6OEEIUK4YH8eRkwFJtC8r4lkHj2xsbXR0hhChWboognlh9GTo2\n7OhybmAhhBDOGR7EU1IAVSoOlf0rG10VIYQodgwP4snJgPIxwc8nn9MYCiHEv9hNEcThk+L2NLJC\nCCEyGR7EU1IAlEiBXwlpiQshRF4ZHsSTkwF6SzpFCCHyw/AgnpICWL0lnSKEEPlheBBPTgasXiZJ\npwghRD7cFEHcoqQlLoQQ+WF4EE9JAdJViuTEhRAiHwwP4snJgAWSThFCiPy4KYJ4GiSdIoQQ+WF4\nEE9JAdIoXQyFECI/DA/iSckWWJgOHy+5xZoQQuSV4UE8MTUFJb38ZAZDIYTIB8ODeLLZhFJyUVMI\nIfLF8CCeZE5BSW+5qCmEEPlheBBPTpM+4kIIkV+GB3FTmgl+0r1QCCHyxa0grpRqq5Q6qpQ6rpTq\n5aJMiFLqL6XUQaXURncrYEpPQWlfaYkLIUR+lMitgFLKC8AYAI8BOA9gl1JqKcmjdmUCAYwF8CTJ\naKVURXd2brUCZprgL0FcCCHyxZ2WeHMAkSSjSKYBmAegfZYyrwNYRDIaAEhedWfnJhPgWzoFpXwk\nnSKEEPnhThCvBuCs3etzN5bZqwegglJqo1Jql1LqDXd2npysg7jMmyKEEPmTazolD9tpAuBRAP4A\ndiildpA8kbVgaGio7XmDBiHwLW2SeVOEEMJOREQEIiIi3CrrThCPBlDT7nX1G8vsnQNwlaQJgEkp\ntRlAIwA5BvFjxwCf0lOli6EQQtgJCQlBSEiI7XW/fv1clnUnnbILQF2lVLBSyhfAawCWZSmzFMDD\nSilvpVRpAA8AOJLbhpOTgRKlZBpaIYTIr1xb4iQtSqmeANZCB/0pJI8opd7VqzmR5FGl1BoABwBY\nAEwkeTi3besgLtPQCiFEfrmVEye5GsBdWZZNyPJ6GIBhedm5yQR4lZQLm0IIkV+GjthMSwNQQi5s\nCiFEfhkfxH1k7hQhhMgv44O4t1zYFEKI/DI0iJvNAEvIhU0hhMgvw1vi9JZ0ihBC5NdNEMQlnSKE\nEPlleBC3eks6RQgh8sv4IO4l6RQhhMgvw4O4xUv6iQshRH4ZH8SVjNgUQoj8ugmCuEnSKUIIkU83\nQRCXC5tCCJFfhgfxdEmnCCFEvhkfxCEXNoUQIr+MHXafRqRBuhgKIUR+GRrEU9PSoeCFEl4FdatP\nIYT4dzE0iJvSU+CjJJUihBD5ZXgQ91WSShFCiPwyNohbTNISF0IIDxibE7ekoKSXtMSFECK/DA7i\nJvh6SxAXQoj8ugla4pJOEUKI/DI2iFtNKOktQVwIIfLL2BGbVhNKSTpFCCHyzdgRmzTB17ukkVUQ\nQohizdiWOGXeFCGE8ITB6ZRUCeJCCOEBQ4N4Okwo5SNBXAgh8sutIK6UaquUOqqUOq6U6uVkfRul\n1HWl1N4bj2/d2a6ehlZy4kIIkV+5Th+olPICMAbAYwDOA9illFpK8miWoptJPp+XnafDBD9piQsh\nRL650xJvDiCSZBTJNADzALR3Uk7ldefpSJUgLoQQHnAniFcDcNbu9bkby7J6UCm1Tyn1m1Lqbnd2\nboEJfj6SThFCiPwqqLsx7AFQk2SyUuppAEsA1HNWMDQ01PbcfDUSpX1bFlAVhBDi1hAREYGIiAi3\nyiqSORdQqgWAUJJtb7zuDYAkh+TwnlMAmpKMzbKc9vsr+eL7CPvoHnwZ8r5blRVCiH8jpRRIOk1Z\nu5NO2QWgrlIqWCnlC+A1AMuy7KCy3fPm0F8OsciF1csE/5KSExdCiPzKNZ1C0qKU6glgLXTQn0Ly\niFLqXb2aEwG8rJTqASANQAqAV93ZudXLBD9fyYkLIUR+uZUTJ7kawF1Zlk2wez4WwNi87tzqZUKA\ntMSFECLfDBuxabEA8E5FaV8J4kIIkV+GBXGzGVC+JpSUEZtCCJFvhgXxtDRA+cgshkII4Qljg3gJ\nmcVQCCE8YWgQRwlpiQshhCcMD+Il5c4+QgiRb4YHcWmJCyFE/hkbxL0lJy6EEJ4wNIjTW7oYCiGE\nJwwN4lZvSacIIYQnDAviJrMFUBb4ePkYVQUhhCj2DAviyamp8LKWglJ5viGQEEKIGwwL4kmpJnhZ\nJR8uhBCeMK4lbjbBi5IPF0IITxgYxFPhbZUgLoQQnjC2JQ5JpwghhCcMC+IpZhNKSDpFCCE8YlwQ\nT0uFNySICyGEJwwM4iaUkCAuhBAeMTiIS05cCCE8YVwQTzfBR0lLXAghPGFYEE9NT5UgLoQQHjJu\n7pR0E3yUpFOEEMITxrXELSb4eElLXAghPGFYEDdbUuEr6RQhhPCIoS1xX28J4kII4Qljg7iX5MSF\nEMITxqVTrCaUlJa4EEJ4xK0grpRqq5Q6qpQ6rpTqlUO5+5VSaUqpF3PbZpo1VYK4EEJ4KNcgrpTy\nAjAGwFMAGgLopJSq76LcYABr3NmxmSaU9JZ0ihBCeMKdlnhzAJEko0imAZgHoL2Tch8CWAjgsjs7\nTqPcJFkIITzlThCvBuCs3etzN5bZKKWqAuhA8icAbt00M52pEsSFEMJDJQpoO6MA2OfKXQby0NBQ\nAMDVbXtx1XJnAe1eCCFuHREREYiIiHCrrCKZcwGlWgAIJdn2xuveAEhyiF2ZfzKeAqgIIAlAd5LL\nsmyLGfur+sVz6FL/XQzt2s6tigohxL+VUgoknTaO3WmJ7wJQVykVDOACgNcAdLIvQLKO3c6mAVie\nNYBnlQ4T/HwknSKEEJ7INYiTtCilegJYC51Dn0LyiFLqXb2aE7O+xZ0dpyMVfr4SxIUQwhNu5cRJ\nrgZwV5ZlE1yUfcedbVpggp+PdDEUQghPGDZi06JMKC0tcSGE8IiBQTwV/iUliAshhCcMC+JWL2mJ\nCyGEp4wN4iUlJy6EEJ4wMIinSDpFCCE8ZEgQJwmrdzICSwUYsXshhLhlGBLEU9JToKy+KFXS24jd\nCyHELcOQIJ5kToJK94ePjxF7F0KIW4cxQTwtCUgLkCAuhBAeMiSIJ5oToczSEhdCCE8Zlk6h2R++\nvkbsXQghbh2GBPGE1ERYTQHw9zdi70IIceswJIhfS0qCV7o/ShTULSmEEOJfypAgHpuYiBJW6SMu\nhBCeMiiIJ8EHkksRQghPGRLEryclwldJS1wIITxlSBCPS0lCSSUtcSGE8JQxQdyUCD8vaYkLIYSn\njOliaEqCXwlpiQshhKeMGbGZmojSPtISF0IITxk2d4q/j7TEhRDCUwYF8USU8ZWWuBBCeMqY+cQt\nSSjjl9kSr1WrFpRSt8SjVq1aRhxSIcS/lCED302WJIe7+kRFRYGkEVUpcEopo6sghPgXMaQlnspE\nBPpJTlwIITxlSBA3Mwnl/CUnLoQQnjImiKtEVAiQlrgQQnjKkCCerpJQIUBa4kII4Sm3grhSqq1S\n6qhS6rhSqpeT9c8rpfYrpf5SSu1WSj3qaltmixkAUa6M3NZHCCE8lWsQV0p5ARgD4CkADQF0UkrV\nz1JsPclGJO8D8DaAia62l2ROgpeleN3V59q1a3jhhRcQEBCA2rVr4+effza6SkIIAcC9LobNAUSS\njAIApdQ8AO0BHM0oQDLZrnwAgKuuNpZoToRK80dxyqa8//77KFWqFK5cuYK9e/fi2WefRePGjdGg\nQQOjqyaE+JdzJ51SDcBZu9fnbixzoJTqoJQ6AmAlgI9cbSwpLQlIKz4t8eTkZCxevBhhYWHw8/PD\nQw89hPbt22PWrFlGV00IIQruwibJJSQbAGgHwGWESzQngqn+xSaIHz9+HD4+Prjjjjtsyxo1aoRD\nhw4ZWCshhNDcSadEA6hp97r6jWVOkdyqlCqhlLqNZEzW9WOGjoFl+1X88EMonnwyBCEhIW5VtCAG\nQuZnUGhiYiLKli3rsKxs2bJISEjwvEJCCOFEREQEIiIi3CrrThDfBaCuUioYwAUArwHoZF9AKXUH\nyZM3njcBAGcBHABe6vEKZly9jLCwUHjl4TzAqFH5AQEBiI+Pd1gWFxeHMmXKGFMhIcQtLyTEsYHb\nr18/l2VzDeIkLUqpngDWQqdfppA8opR6V6/mRAAvKaX+C8AMIAnAq662dy0xCd6WgDwFcCPVq1cP\n6enpOHnypC2lsn//fjRs2NDgmgkhhJsTYJFcDeCuLMsm2D0fCmCoO9uKSUhECRaThDiA0qVL48UX\nX8R3332HSZMmYe/evVi+fDm2b99udNWEEKLoR2xeT0qCL4pPEAeAsWPHIjk5GUFBQejSpQvGjx8v\n3QuFEDeFIp+K9npyEkqqYtRJHED58uXx66+/Gl0NIYTIpshb4nEpiSjlVbxa4kIIcbMq8iAeb0pC\nKe/i1RIXQoibVZEH8W0xS+BfQoK4EEIUhCLPiXeqMALnzC4nORRCCJEHRR7EG+AFJPkV9V6FEOLW\nVOTplKQkFJt5U4QQ4mZnSBAvTtPQCiHEzUxa4kIIUYwVeRBPTJQgLoQQBaXIg/j48UDlykW9V8+M\nHTsW999/P0qVKoV33nnH6OoIIYRNkfdOiYsrfi3xatWq4X//+x/WrFmDlJQUo6sjhBA2RR7Ei1sA\nB4AOHToAAHbt2oXoaJf3wxBCiCJXTGb1FkII4UyRt8TzS/Xz/P5s7GvQ7YGEEKKQFJsgLgFYCCGy\nk3SKEEIUYxLE3WCxWGAymWCxWJCeno7U1FRYLBajqyWEEBLE3REWFobSpUtjyJAhmDNnDkqXLo0B\nAwYYXS0hhIAiiy7XrJSis/0ppVCU9ShMt9JnEULcHG7EFae9O6QlLoQQxZgEcSGEKMYkiAshRDEm\nQVwIIYoxCeJCCFGMSRAXQohi7KYYdh8cHAylPJ8b5WYQHBxsdBWEEP8ibvUTV0q1BTAKuuU+heSQ\nLOtfB9DrxssEAD1I/u1kO077iQshhHDNo37iSikvAGMAPAWgIYBOSqn6WYr9A6A1yUYAwgBM8qzK\nwh0RERFGV+GWIsez4MkxLXzu5MSbA4gkGUUyDcA8AO3tC5D8g2TcjZd/AKhWsNUUzsg/SMGS41nw\n5JgWPneCeDUAZ+1en0POQborgFWeVEoIIYR7CvTCplLqEQBvA3i4ILcrhBDCuVwvbCqlWgAIJdn2\nxuveAOjk4ua9ABYBaEvypIttyVVNIYTIB1cXNt1pie8CUFcpFQzgAoDXAHSyL6CUqgkdwN9wFcBz\nqoQQQoj8yTWIk7QopXoCWIvMLoZHlFLv6tWcCOB/ACoAGKd0h+80ks0Ls+JCCCGKeD5xIYQQBavI\nht0rpdoqpY4qpY4rpXrl/g6RlVLqtFJqv1LqL6XUzhvLyiul1iqljiml1iilAo2u581KKTVFKXVJ\nKXXAbpnL46eU6qOUilRKHVFKPWlMrW9eLo5nX6XUOaXU3huPtnbr5HgWgiIJ4m4OGBK5swIIIXmf\nXbqqN4D1JO8C8DuAPobV7uY3Dfpv0J7T46eUuhtARwANADyNzFShyOTseALACJJNbjxWA4BSqgHk\neBaKomqJ5zpgSLhFIfvvrD2AGTeezwDQoUhrVIyQ3ArgWpbFro7f8wDmkUwneRpAJPTfsbjBxfEE\n9N9pVu0hx7NQFFUQz+uAIeEcAaxTSu1SSnW9sawyyUsAQPIigCDDalc8Bbk4fln/ZqMhf7Pu6qmU\n2qeUmmyXnpLjWUhkKtri5SGSTQA8A+ADpVQr6MBuT65Ue0aOn2fGAahDsjGAiwCGG1yfW15RBfFo\nADXtXle/sUzkAckLN35eAbAE+nT0klKqMgAopW4HcNm4GhZLro5fNIAaduXkb9YNJK/YTVU6CZkp\nEzmehaSogrhtwJBSyhd6wNCyItr3LUEpVVopFXDjuT+AJwH8DX0c37pR7E0ASw2pYPGh4JizdXX8\nlgF4TSnlq5SqDaAugJ1FVclixOF43vgizPAigIM3nsvxLCRFclMIVwOGimLft5DKAH69MXVBCQBz\nSK5VSu0GMF8p9Q6AKOgeAMIJpdRcACEAblNKnQHQF8BgAAuyHj+Sh5VS8wEcBpAG4H2ZDN+Ri+P5\niFKqMXRPqtMA3gXkeBYmGewjhBDFmFzYFEKIYkyCuBBCFGMSxIUQohiTIC6EEMWYBHEhhCjGJIgL\nIUQxJkFcCCGKMQniQghRjP0/WW9NwtloLw0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdde3908f90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ASR_H1_TRANSFORMED 101\n"
     ]
    },
    {
     "data": {
      "image/png": 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XH13PoZFDWeGzCqw3th5HRY1ik/FNcmwdudp4fCP7Le6X4wfN6XTy8fmP8+av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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdde9262710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ASR_W1_TRANSFORMED 59\n"
     ]
    },
    {
     "data": {
      "image/png": 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BVav0/z/l8v/ERH0WbX0m1K6dfo/1EElrgwfr/oOqVXWO3Nmz7qFDdTqwcmV9ECpaVJ/V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\nIh/7fw11vS1KdNi0AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdde13f9ad0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ASR_AE_H1 132\n"
     ]
    },
    {
     "data": {
      "image/png": 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3T5Nb66T+EUSRr4qw1IRS/G7fd1mvqBAiW5DNlngQgJpKqaoArgLoD2BAqjLB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\nQogCTEJcCCEKMAlxIYQowP4f/cRxm7IIKtUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdde3b775d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data=shelve.open(\"UNFIXED_TRANS_scores/V2_UNFIXED_TANH_50_W300_DOMLP.shelve\")\n",
    "for key,table in data.iteritems():\n",
    "    print key, np.argmax([x[0] for x in data[key][0] ])\n",
    "    pandas.DataFrame(zip([x[0] for x in data[key][0][:200] ],[x[0] for x in data[key][1][:200]  ])).plot()\n",
    "    plt.show()\n",
    "data.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TRS_AE_H1 94\n"
     ]
    },
    {
     "data": {
      "image/png": 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aSJKI2Ai2mt6K5yLP8UbcDXr386b/VH+XX09kXCTbzmqbqqnDZrPxjUVv8J0l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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdde138bb90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TRS_AE_OUT 131\n"
     ]
    },
    {
     "data": {
      "image/png": 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BK6VUVnJbTmkL4ATJkMSVLQbQFUCgQ5sLAJonPr8DwJW0AbwwCY4IRsdvHkOV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\nlFKFmAZxpZQqxDSIK6VUIfb/VJpnn3dhEF8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdde98c5150>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TRS_SPARSE 48\n"
     ]
    },
    {
     "data": {
      "image/png": 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dZ9G7Ue9C+Ux+ivwJ9f3qo0ONwj3d8Z72Hjot6YSeDXpifKfxICKM2zEO6fp0\nzOpq5fz1TAajAX1W90Fpr9J4pckrGLF5BNa8vAZP1ci5S/emc5vwyc5PEHM3BlEjolC5dOUC17n3\nL71x+NphxLwfU6B1O2T9EDSv0hzvtXsv13iNToMm3zbBjz1/RMeaHVF7Tm1sH7Qdj/s/nj3doeuH\n4E7uqFamGta+sha9fumFm6k3UbZEWZxKOIWPn/44z8NNDUYDFh1dhANXD6By6cqY03UOutbvWvAz\nNokoCMAcqEMSFzHzVLPXKwD4GUBVAO4AZjLzEgvzeeAhHhoKHD4MLLlv6eoknmefBSZNUqctO2L7\nhe3ovrw7lvVehv7N+iMuOQ6jtozCuqh1WPDiArzd6m28+/u7OBh3EDXK1kC/pv3Q7/F+ICKE/hOK\nj/78CL0b9caKl1Zkz3Px0cVo6t8Ubau3tbkeV+9exX+2/wcZ+gwMaz0M3R7rluv1DH0G/Kb5YUzH\nMbm6RYSw1fWU6+i+ojvKeJVBgG8A9sTswZ+v/4lGFfO/0EmqNhXvbXkPCWkJaB/QHuOeGZfrdSMb\n0XBuQ9QuVxt/DPqjUOp7PP44jl4/ijdavFGg+fx6+lcsOroIa19Zi+0XtkNv1AMAdl7aifjUeKx9\nZS0AYNLuSYhLjsOCHgtw5PoRvLDiBUSNiIKPpw+6r+iOS0mX8FiFx7Cx/0Z4uHng2I1jmH5gOlIy\nUvJcfqdanTCy7Uj8cfEPfLDtAzSu2BgbB2x0vDsFKrjPA6gFwBPAMQCNzMpMADAl83lFAIkAPCzM\ny+bNCUd17qzuQmLN2bPW78SenxPxJ7jStEr80faPuP0P7dloNHLnpZ35/S3v88azG7npvKacmJbI\n5b4qx9dTLN9hd9aBWdk7VB607yK+y96BJIQj9AY9Lzy0kCfvnlygnbCWbD63mXdf3l2o8ywMdzR3\nuPSXpbnm7Jr87JJn+aVfXuKXfnmJ+//aP1eX2Y2UG1zuq3K89NhSbvd9O154aGGuefx323/v6/ax\nV7ounafum1qw7hQiag9gAjN3yxwemznDqSZlhgJoxswjiagOgG3M3MDCvDi/5Tlq1Cjgzx1GxPJB\n3DjUHqVKFe78jWxEux/aYWiroXirxVuoH1ofAx4fgHVn1yHy3Ui4kzse/+5x1ClXB37efvip90+F\nWwEhRJGZeWAmWldrjU61O+VZbv6h+dh7ZS+qlKqCac9Pg7vbg7mWTYF2bAJ4CcBCk+GBAL7h+1vr\nuwBcA5C+GtWRAAAXdklEQVQMoJuVeRXoV8kao1HdreOTX5YxQsBRCVGFvowlR5dw2+/bZu/UmbF/\nBiMEvO38tuwy8yPmM0LAEXFWbmkvhBAOQB4t8cK6dsrHACKZ+VkiqgfgDyJ6gpnvmRcMCQnJfh4Y\nGIjAwMACL/zGDcDgfg9LYseiW/1umHtwLkK7O3AFfqi+5vVn18PIRrzw2Auo51cPyRnJGLdzHNa+\nsjZ75+Hbrd6Gj6cPutTrkj3toOaDYGQjWldrXeD3JIR4dIWHhyM8PNymsrZ2p4Qwc1DmsKXulM0A\nvmDm/ZnDOwCMYeZDZvPi/JbniK1bgWGrx6PDixcw7blpaPZdM1wafcni8bq7L+9GRZ+KaOrfNNd4\nZsZX+77CjL9mILhhMBiMXZd2Yd/gfXh749uoW64u5r1w/5l9QgjxoBX0zj4RAOoTUS0i8gLQD8AG\nszJnADyXubDKABoAuOh4le0TGQkk1ViBMR3HoLpvdXSt3xU/Hv0RgOrLXnpsKe6m38XemL3ou6Yv\nnl36LEZvGQ2D0ZA9jyn7pmD16dU4/M5h/Bj8IxYHL8aQJ4egybwmYGZ83e3rono7QghhO2v9LJy7\nLzsIwFkA0QDGZo4bCuAdzjkiZSOASADHAfS3Mp8H0l/U+7UE9p7om91ffeTaEa4yowrf0dzhJUeX\nsP90f64yowr7T/fnbee38a3UW9z2+7a86MgiZmZecXwF15xd875Tu41GI/945McC72EWQoiCwMN+\nsk/NzptR7aVZ+Hv4n9njhqwfAi93L2w4twFhr4TBw80DCWkJCKofBACIiItA8KpgLOq5CG+sewM7\nXt+BZpWbFXrdhBCioIrlnX0OHwZWrlT3JfzgA3Wfyyw//wwcO6ZuIPvuu8A1t38w4LF2uab/ovMX\naBDaAL0a9UK7gHYw16Z6G3St3xU9V/XEpgGbJMCFEMWSy7bEg4KAWrXURapOnAB27QLKlFGn1bds\nCYwdq+747eMD/P1YVywfPQI9G/bMNY/9V/ajUcVGqOBTweIybmtu43j8cQTWDizoWxNCiAem2N0o\nOTlZXWnw2jWgdGlg2DAgOlrdeHbsWMDTU10P5e5doFOgEWd6VMCVjwrn+gtCCOFqCnp0SpHbuhXo\n2FG1vImAefOAihWBvn2Bn35Sd/8GgLJlgUW/RaNKuXIS4EKIR5JLhviGDUBwcM6wuzuwbJm66XHf\nvqqVnuWfhB14qub9fd5CCPEocLnuFJ0OqFxZ9YObhjUAGI3q4ZG5O/bwtcPotrwbNr+2Wc6SFEI8\ntIrV0SkREWqHpnmAA+rel1n3v0xITUDwqmB83+N7CXAhxCPL5bpTjh0D2rTJv9xnuz5D3yZ9Edwo\nOP/CQgjxkHK5lvixY0Dz5nmXibwRid+ifkPUiKiiqZQQQrgol2uJR0bmHeIn4k/gjXVvIKRTCMp7\nly+6igkhhAtyqR2bBgNQpkYMGo9/GUz6+15nMOKS4zC+03gMbzM81z0lhRDiYVVsdmxGRwO+DY6i\nTEkfqzdjrVu+LsqVLFfENRNCCNfkUiEeGQn4N4jB4/6Po2XVls6ujhBCuDyX6o+IjARKVb+M2uVq\nO7sqQghRLLhciKNsDGqVreXsqgghRLHgUiF++jSQ7CYtcSGEsJVL9YmnpQF302IkxIUQwkYuFeJa\npEBrSEdFn4rOrooQQhQLLtWdkuEdgxq+tUBk8XBIIYQQZlwqxHWlLqNWOdmpKYQQtnKZEGcG9KVi\nUKd8bWdXRQghig2XCXGDAaDyl1FbWuJCCGEzlwlxnQ6g8nJkihBC2MOmECeiICKKIqJzRDTGwusf\nEtFRIjpCRCeISE9Edl3gRKsFUP6ynOgjhBB2yDfEicgNwFwAXQE0BdCfiBqZlmHmGcz8JDO3BPAx\ngHBmvmNPRXQ6AKWuo1qZavZMJoQQjzRbWuJtAUQzcwwz6wCsApDX7XT6A1hpb0V0OgAeGfD29LZ3\nUiGEeGTZEuLVAVw1GY7NHHcfIvIGEARgrb0V0WoBdtPCy93L3kmFEOKRVdhnbPYAsC+vrpSQkJDs\n54GBgQgMDASQ2RJ3lxAXQojw8HCEh4fbVDbfO/sQUXsAIcwclDk8FgAz81QLZcMArGbmVVbmZfXO\nPqdPA01/8YBuQjo83FzqagBCCOFUed3Zx5bulAgA9YmoFhF5AegHYIOFhZQF0AnAekcqma41AGSE\nO7k7MrkQQjyS8m3yMrOBiEYC2A4V+ouY+QwRDVUv88LMor0AbGNmjSMV0WToQEZPuW6KEELYwaZ+\nC2beCqCh2bgFZsNLASx1tCJpGVoQS3+4EELYw2XO2EzL0MJNQlwIIeziMiGu0UqICyGEvVwmxNO1\nOglxIYSwk8uEuEanhbuEuBBC2MV1QjxDCzdIiAshhD1cJsTTdVq4S4gLIYRdXCfE9Vp4SIgLIYRd\nXCfEtVq4k4S4EELYw3VCXK+FO3k6uxpCCFGsuEyIZ0h3ihBC2M11QlynhaebhLgQQtjDdULcoIWH\n9IkLIYRdXCbEtXqdtMSFEMJOrhPiBulOEUIIe0mICyFEMSYhLoQQxZhLhbjcJFkIIezjMiGuM2rh\n6S4n+wghhD1cKsRLeEhLXAgh7OFSIS7dKUIIYR+XCvESEuJCCGEXlwlxPetQwlNCXAgh7OFCIS59\n4kIIYS+bQpyIgogoiojOEdEYK2UCiegoEZ0kol32VkRCXAgh7OeRXwEicgMwF0BnANcARBDRemaO\nMilTFsA8AF2YOY6IKtpbEQNrUVK6U4QQwi62tMTbAohm5hhm1gFYBSDYrMwAAGuZOQ4AmPmWvRXR\nQ0JcCCHsZUuIVwdw1WQ4NnOcqQYA/IhoFxFFENEgeytigBbeEuJCCGGXfLtT7JhPSwD/BlAKwF9E\n9BcznzcvGBISkv08MDAQgYGBAAAjtCjhKWdsCiFEeHg4wsPDbSprS4jHAahpMhyQOc5ULIBbzJwO\nIJ2I9gBoDiDPEDdlgBbeXtISF0II0wYuAEycONFqWVu6UyIA1CeiWkTkBaAfgA1mZdYDeJqI3InI\nB0A7AGfsqbSRJMSFEMJe+bbEmdlARCMBbIcK/UXMfIaIhqqXeSEzRxHRNgDHARgALGTm0/ZUxEg6\nCXEhhLCTTX3izLwVQEOzcQvMhmcAmOFoRaQlLoQQ9nOZMzaNpIVPSQlxIYSwh8uEOLtp4SMtcSGE\nsItrhXgJCXEhhLCHS4V4KelOEUIIu7hEiDMDcJeWuBBC2MslQlynA+CuhZfcY1MIIeziYiEuLXEh\nhLCHS4S4VgsJcSGEcICLhDgD7jp4SneKEELYxSVCPC1DDxg94EYuUR0hhCg2XCI109K1IIN0pQgh\nhL1cI8S1WpBRQlwIIezlEiGemq4FsYS4EELYyyVCXKPVwk1a4kIIYTfXCPEMLdwgR6YIIYS9XCLE\n07RauEl3ihBC2M0lQjxdQlwIIRziEiGu0ergBglxIYSwl0uEeLpOC3dpiQshhN1cJ8RJQlwIIezl\nEiGu0WnhId0pQghhN5cI8QydFu4S4kIIYTfXCHG9Fh7SnSKEEHazKcSJKIiIoojoHBGNsfB6JyK6\nQ0RHMh+f2lOJdJ2EuBBCOMIjvwJE5AZgLoDOAK4BiCCi9cwcZVZ0DzP3dKQSGQYtPNzkjE0hhLCX\nLS3xtgCimTmGmXUAVgEItlCOHK1Ehk4LT2mJCyGE3WwJ8eoArpoMx2aOM/cUER0jok1E1MSeSmgN\nWni4SYgLIYS98u1OsdFhADWZOY2IugFYB6CBpYIhISHZzwMDAxEYGAidQQcvCXEhhAAAhIeHIzw8\n3KayxMx5FyBqDyCEmYMyh8cCYGaemsc0lwC0YubbZuPZ0vKemzAdGreb2D9huk2VFkKIRwkRgZkt\ndlnb0p0SAaA+EdUiIi8A/QBsMFtAZZPnbaF+HG7DRjqDFp7SEhdCCLvl253CzAYiGglgO1ToL2Lm\nM0Q0VL3MCwH0JaJhAHQANABetacSWqMWZdwlxIUQwl429Ykz81YADc3GLTB5Pg/APEcroTNq4eXu\n6+jkQgjxyHKJMza1ei28PaUlLoQQ9nKJEM8waFHSS072EUIIe7lGiBs1KFXC29nVEEKIYsclQlxr\n1KC0hLgQQtjNJUJcxxqU8ZYQF0IIe7lOiJcs6exqCCFEseMSIa5HOsr4SEtcCCHs5RohThqUkxAX\nQgi7uUSIG9w0KFtKQlwIIezlEiFudNOgXGkJcSGEsJdrhLi7hLgQQjjC6SFuMABwT0dZHzk6RQgh\n7OX0ENdoAHhq4OMpLXEhhLCX00M8NZUBDw28JcSFEMJuTg/x5FQdADd4uBXWneKEEOLR4fQQv3NP\nAzeDtMKFEMIRTg/xJAlxIYRwmNNDPDktHe4sIS6EEI5weojfTdXAneXwQiGEcITTQzxZo4EHpCUu\nhBCOcH6Ip2ngKSEuhBAOcXqIp2Ro4EkS4kII4Qinh/i99HSUcJMQF0IIR9gU4kQURERRRHSOiMbk\nUa4NEemIqI+tFUjN0MBLQlwIIRySb4gTkRuAuQC6AmgKoD8RNbJS7isA2+ypQGqGBiXc5egUIYRw\nhC0t8bYAopk5hpl1AFYBCLZQbhSAXwHctKcCaToNSrpLS1wIIRxhS4hXB3DVZDg2c1w2IqoGoBcz\nfweA7KlAmlYufiWEEI4qrKtOzQFg2lduNchDQkKynwcGBiJdr4GfhLgQQmQLDw9HeHi4TWWJmfMu\nQNQeQAgzB2UOjwXAzDzVpMzFrKcAKgJIBfAOM28wmxebL++J0RNQv54bwt6bYFOFhRDiUUNEYGaL\njWNbWuIRAOoTUS0A1wH0A9DftAAz1zVZ2GIAG80D3Jp0vQalvCraUlQIIYSZfEOcmQ1ENBLAdqg+\n9EXMfIaIhqqXeaH5JPZUQGvUwMdLjk4RQghH2NQnzsxbATQ0G7fAStnB9lQgw6hB6ZLSJy6EEI5w\n+hmbOtagjIS4EEI4xPkhDg18vSXEhRDCEU4PcT3SUUZCXAghHOICIa5B2VIS4kII4Qinh7jBTYOy\nPnJ0ihBCOMLpIW5006BcaWmJCyGEI5wa4gYDwB4alPWREBdCCEc4NcQ1GoA80+HjJSEuhBCOcHqI\nw1MDbw8JcSGEcIRTQzwtDYCHXIpWCCEc5eQQZ7C7BiU95OgUIYRwhFNDPCVNB8AN9evWBxE9FI/a\ntWs7c5UKIR4xhXVTCIck3dPA3eiNmJgY5Hdd8+KCyK4bGwkhRIE4tSV+JyUd7kbpDxdCCEc5NcQT\n7mjgAQlxIYRwlFND/HayBp4kIS6EEI5yaognpmjg5SZHpgghhKOcGuJJKRqUdJeWuBBCOMq53Smp\nySjlWcaZVbBJUlISevfujdKlS6NOnTpYuXKls6skhBAAnHyIYWLGdVQqWQ1RzqyEDYYPH46SJUsi\nISEBR44cwQsvvIAWLVqgcePGzq6aEOIR59yWuO4aqvhUc2YV8pWWloawsDBMnjwZ3t7e6NixI4KD\ng7Fs2TJnV00IIZwb4sl8DdXLunaInzt3Dp6enqhXr172uObNm+PUqVNOrJUQQihODfFUt2uoVd62\nECcq+MMR9+7dg6+vb65xvr6+SElJcWyGQghRiGwKcSIKIqIoIjpHRGMsvN6TiCKJ6CgRHSKif9sy\n33TPa6hbybYQZy74wxGlS5dGcnJyrnF3795FmTKuv0NWCPHwyzfEicgNwFwAXQE0BdCfiBqZFfuT\nmZsz85MA3gKw0JaF672voX4V1+5OadCgAfR6PS5cuJA9LjIyEk2bNnVirYQQQrGlJd4WQDQzxzCz\nDsAqAMGmBZg5zWSwNIBb+c00Q2sA+9xEPf8q9tS3yPn4+KBPnz4YP3480tLSsG/fPmzcuBGDBg1y\ndtWEEMKmEK8O4KrJcGzmuFyIqBcRnQGwGcB7+c30wo0EUEZ5lPD0tLWuTjNv3jykpaXB398fAwcO\nxPz58+XwQiGESyi048SZeR2AdUT0NIBlABpaKhcSEgIAiIq7DvfE4tGvXL58efz222/OroYQ4hER\nHh6O8PBwm8pSftfxJqL2AEKYOShzeCwAZuapeUxzAUBbZk40G89Zy5uz5XdM2PAd7n63CUT0UF1P\n/GF5L0II15CZKxaPsbOlOyUCQH0iqkVEXgD6AdhgtoB6Js9bAoB5gJu7cvsaShlde6emEEK4uny7\nU5jZQEQjAWyHCv1FzHyGiIaql3khgJeI6HUAWgCpAF7Nb75xydfg6yYhLoQQBWFTnzgzb4VZHzcz\nLzB5Pg3ANHsWfCP1Gvw8WtkziRBCCDNOO2PzVsY1VCopLXEhhCgIp4X4bd01VC4lIS6EEAVR5Jei\n7bWqFwDgFqJQ3VdCXAghCqLIQ/zNFm8CAFLDR6BW7apFvXghhHioFH1LvJFqiS+5AZQrV9RLF0KI\nh4vT+sTv3AHKlnXW0u0zb948tGnTBiVLlsTgwYOdXR0hhMjmtNuz3blTfFri1atXx2effYZt27ZB\no9E4uzpCCJFNQtwGvXqpLqCIiAjExcU5uTZCCJGjyEO8YkX1NzkZqFChqJcuhBAPlyIP8ajMW9t7\neQFmdz3LE0108P5qJniCXJhKCPFwcVpL3F4SwEIIcT+n3ihZCCFEwUiI28BgMCA9PR0GgwF6vR4Z\nGRkwGAzOrpYQQkiI22Ly5Mnw8fHB1KlTsXz5cvj4+OCLL75wdrWEECL/O/sU6sJM7uxjNv6huRvO\nw/RehBCuoaB39hFCCOGiJMSFEKIYkxAXQohiTEJcCCGKMQlxIYQoxiTEhRCiGHPaVQxN1apVC0QF\nvzaKK6hVq5azqyCEeITYdJw4EQUBmAPVcl/EzFPNXh8AYEzmYAqAYcx8wsJ8LB4nLoQQwroCHSdO\nRG4A5gLoCqApgP5E1Mis2EUA/2Lm5gAmA/i+YFUWtggPD3d2FR4qsj4Ln6zTB8+WPvG2AKKZOYaZ\ndQBWAQg2LcDMfzPz3czBvwFUL9xqCkvkH6RwyfosfLJOHzxbQrw6gKsmw7HIO6T/D8CWglRKCCGE\nbQp1xyYRPQvgLQBPF+Z8hRBCWJbvjk0iag8ghJmDMofHAmALOzefALAWQBAzX7AyL9mrKYQQDrC2\nY9OWlngEgPpEVAvAdQD9APQ3LUBENaECfJC1AM+rEkIIIRyTb4gzs4GIRgLYjpxDDM8Q0VD1Mi8E\n8BkAPwDfkjrgW8fMbR9kxYUQQhTx9cSFEEIUriI77Z6IgogoiojOEdGY/KcQ5ojoMhFFEtFRIjqY\nOa48EW0norNEtI2Iyjq7nq6KiBYRUTwRHTcZZ3X9EdHHRBRNRGeIqItzau26rKzPCUQUS0RHMh9B\nJq/J+nwAiiTEbTxhSOTPCCCQmZ806a4aC+BPZm4IYCeAj51WO9e3GOo7aMri+iOiJgBeAdAYQDfk\ndBWKHJbWJwDMYuaWmY+tAEBEjSHr84EoqpZ4vicMCZsQ7v/MggEszXy+FECvIq1RMcLM+wAkmY22\ntv56AljFzHpmvgwgGup7LDJZWZ+A+p6aC4aszweiqELc3hOGhGUM4A8iiiCi/8scV5mZ4wGAmW8A\n8Hda7Yonfyvrz/w7Gwf5ztpqJBEdI6IfTLqnZH0+IHIp2uKlIzO3BNAdwAgiegYq2E3JnuqCkfVX\nMN8CqMvMLQDcADDTyfV56BVViMcBqGkyHJA5TtiBma9n/k0AsA5qczSeiCoDABFVAXDTeTUslqyt\nvzgANUzKyXfWBsycYHKp0u+R02Ui6/MBKaoQzz5hiIi8oE4Y2lBEy34oEJEPEZXOfF4KQBcAJ6DW\n45uZxd4AsN4pFSw+CLn7bK2tvw0A+hGRFxHVAVAfwMGiqmQxkmt9Zv4QZukD4GTmc1mfD0iR3BTC\n2glDRbHsh0hlAL9lXrrAA8ByZt5ORIcArCaiwQBioI4AEBYQ0QoAgQAqENEVABMAfAVgjfn6Y+bT\nRLQawGkAOgDD5WL4uVlZn88SUQuoI6kuAxgKyPp8kORkHyGEKMZkx6YQQhRjEuJCCFGMSYgLIUQx\nJiEuhBDFmIS4EEIUYxLiQghRjEmICyFEMSYhLoQQxdj/A4Akv0bNlRIGAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdde146f450>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ASR_H1_TRANFORMED_TRSH1 183\n"
     ]
    },
    {
     "data": {
      "image/png": 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MzWefBdq1A3r2dL6vP8P+RPel3VG9RHXMe2YeivoUdb5TpZRKQU+7T+H6dXNi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\nSinlxjSIK6WUG9MgrpRSbuz/AUk+yV8otw//AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdde4b47910>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ASR_AE_OUT 106\n"
     ]
    },
    {
     "data": {
      "image/png": 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jE6M5Y/8MSzbV6Y9OLDGuBF/87UWevHGSL/z6AledWmUp//W2r+k+0p0Tdk+w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\naRBgj2sAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdde1513150>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ASR_H2_TRANFORMED_OUT 125\n"
     ]
    },
    {
     "data": {
      "image/png": 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I8m+IDAXQUER2AVgF4GOSUbnV6Nt15Yr5LcHHH7/9Os7EnEGHmR0wdcfUlHkk\n0WtBLzSa3AiD1mb/e0+LDy7G9rPbsfTwUjxz3zOoX6E+dpzdgbUn1qJ1QGsAwBNVn8DGkxsRmxiL\nzac3o0mlJtnW+UjAI9h7YS+i4qIwvt34dMveb/w+om9Go1VAq9vc4ltXr3w9NPZvnGfrU+qfzKGc\nOMnlAO7PMG9imr8vAejg2qa53tKl5vcgixSxv3zMX2NwJuYMHq7wMLrU7mK3zIStE9CgQgOM2TIG\n7zR6B17ihfBL4SiSvwg2vrYRrX5ohWaVmuHJak8CACKjIzE/fD56PNQDm05tQu/FJo977eY17Hxr\nJw5dPoRxW8fhTMwZTO4wGQBQomAJ1K9QHzP3zMRfp/9CE//sg3iBfAUw+4XZaHFPCxTIVyDdshce\neAFF8hdByYIlb2FPKaU8RlZXPHPjBTePTunSxTwnxJ7kMc5D1g2hX4gf91/I/BtccYlxLDu8LMMv\nhrPe9/VSbnIZv2U8X17wMklyQfgC1h5XmzE3Yzh47WCWCi7F9jPas0xIGfqF+HHzqc28GneVM3bP\noM1m46lrp1h8aHEW+7pYurvu1kesZ9XvqprHfeowOqX+0aC33af+MEJWj1AN3R7KrnO7kiRHbhrJ\ntr+0zVRm4raJKfN/2PEDn/r5KZJk17ldUx4TarPZ+NiPj7HksJJ8fvbzKXfi7Tm/x+4zMGw2G/1C\n/FLqSisuMY5z9s7Jdly2Uuru948O4omJ5sdumzXL/pGxnWd3Tnk2xE3LTdYYU4MLwlN/w+qv03/R\nL8Qv5Slq8YnxrPpdVa46uirlaXLJIq5GcN0Jx38088mfnnTL7b1KKc+QXRDPcYihK7ljiOG2bUD3\n7sC4ccBDDwEVKqQu23thL9aeWIs3G7yJsiPK4sC7B1CuaDkAwKZTm9BxVkf8r9f/cDX+Krr92g0T\n209Eh/tTU/8LwhfgvWXvwUu8ENEvAiJ2RwDlaO+FvShftDz8Cvs5ta1KqbuTs0MMPdrGjcBjjwFP\nPZV+fmR0JJ6Z/gystGJz5GZUL1U9JYADQPN7mmPM02PQcmpL+Bbyxfh249MFcADoVLMTxmwZA//i\n/rcdwAHgwbIP3vZ7lVL/bB4dxK1WwNvb/G2xAPnsbM3GjUD79unnxdyMQfuZ7fFOo3fQpXYXNJ3S\n1O6djN0e7IaAEgGoW75uujHhyUQEs1+YDYvN4orNUUqpW+ax6ZRjx4DGjYHly4GyZYGWLYFXXgEG\npRmmTQJ1HnP6AAAVR0lEQVSVKgHr1gHVku7Bsdgs6DirIyoWrYhJHSZBRBBxNQK+hXxT7oBUSqk7\nyV2ZTlm7FvDzAzp0AIoVA15/HZgxw/TMW7YEatUCEhJMb71qVfMekui3vB8SrYkY3258SgokoGSA\nG7dEKaVun8f2xN94A6hXDyhdGjhzBvjoI+DkSaBvXyAmBjh0CHjrLWDXLmDePPOeb//8FlN3TsWG\nVzegRMESLmmHUkrltux64jnedn8nOXECOHzY/L1xI9CihRl58tFHZl7xsldR4tWXMH/pFfz3MxsG\nbvoAlZuaZ3CFnQjDiD9H4Pcev2sAV0rdNTwqnfL558CRI8CSJUBkpBkymFbo9lAsPbwUp6NPo37V\n+ija4iccLBsBYD6CNwZjyGNDULlEZbe0XSmlcsMd2xNftAjYsCF1OjHRPPvk1CkgOBho0iT9aBSr\nzYqxW8diSfclKFGgBBYfWox97+/AX+fXYsWRFdh+dju6Pdgt7zdEKaVy0R3ZE1+yBPjXv4Dq1YHt\n2wERE9CrVAF69wbefhv44osM7zm0BOWKlEOze5rh1y6/Ii4xDsUKFMMrdV/Bi3NfxL+b/BsF8xV0\nzwYppVQuueN64uvXA6++CqxaZXrfq1aZ+QsXAh07Ar16AeXKAa1bp75nw8kN+M+q/6Bf034AgHxe\n+VCsQDEAQN/GfeHt5Y23G72d15uilFK57o4anbJzp7mzcvp04MkngZ9+Mq9Vq8w4799+Mz+tdvUq\nULIkcOraKXz8x8fYeHIjQp4MQdfaXe3eOZlgTUB+7/y5uWlKKZVrshud4tYgvm0b0KoVYLMlLwd+\n+QV44QUznZBgLl4ePw7UrGmGC4oA7Wa0w+bTm2GxWdCvST983OJjFMmfxUPClVLKw92xN/scPmxu\nif/lFzPt5QX4+KQuz58f2L8/9ZZ6EeD89fPYdGoTDvY9iKL5i9q9HV4ppf4p3JoTP38eqFgR8Pax\nIHT3eNQYXwU7z+1MV8bbGyhQIPUZKcuPLMfjVR5H2SJlNYArpf7x3BrEz50DypcH3v39XczcOxNd\nHuiCfsv7pTwn96blJhKtienes/SI+W1KpZRSd0AQL+R3AXP2z8GCrgsw5PEhiIqLwhdrvkC9ifVQ\nbGgxFPm6CF5d+CrOxpyFxWbBqqOr0LZ6W3c2Wyml7hhuT6dsl8noXKsz/Ar7IZ9XPox+ejQWHFiA\nLx75Ajc/u4lLH19CmcJl8NCEh9BnSR8ElAxAxWIV3dlspZS6Y7h1dEq9+ok40/Ve/PHKMtQpVyfb\n9x6+fBgf//ExWlVuhQ+bfZjbTVVKqTvGHTvEsHT9tbjnjf9g5ztb8qwNSinlaZx+iqGItBWRAyJy\nSET621n+fyKyQ0S2i8geEbGISMns6rRagauW86hWWp/lrZRStyvHIC4iXgDGAmgDoDaA7iJSM20Z\nkiNIPkyyPoBPAISRvJpdvZcvA4VKRaFMkdK333qllPqHc6Qn3hjAYZIRJBMBzALQMZvy3QHMzKnS\n8+eBIn5RKFWolGMtVUoplYkjQdwfwKk006eT5mUiIoUAtAUwL6dKz50DCvpe1iCulFJOcPVt9x0A\nbMgulRIUFATAPAclMd8+lC70oIuboJRSni0sLAxhYWEOlc1xdIqINAUQRLJt0vQAACQZbKfsfABz\nSM7Koq6U0SkjRgATrj6LkT1fR8ea2WVnlFLqn83Z0SlbAVQXkQARyQ+gG4BFdlZSAkBrAAsdadS5\nc4CtQBRKF9YLm0opdbtyTKeQtIpIXwArYYJ+KMlwEXnLLOakpKKdAKwgGefIis+dAxJK6YVNpZRy\nhttu9nnySWDbo+UQ/v4ulC9aPs/aoJRSnsbpm31yw9lzxHWL9sSVUsoZbgvi56/EoEC+gvqzaUop\n5QS3BfE4RMG3oPbClVLKGW4L4hafyyhdSEemKKWUM9wWxK35NR+ulFLOcl8QL6BBXCmlnOW2IM6C\nl+GnTzBUSimnuCWI22wACkWhtPbElVLKKW4J4hYLIEUu6y33SinlJLcEcasVkMKaE1dKKWe5LYij\nkAZxpZRylvuCeGEdJ66UUs5yXxAvqD1xpZRyltsubLJgFHwL+bpj9UopdddwX088XzwK+xR2x+qV\nUuqu4b4g7mVBPi9X/8SnUkr9s7gtiFMs8BZvd6xeKaXuGu7riYtVe+JKKeUktwTxhEQb4GWDl7jt\n0S1KKXVXcE8Qt1gBmzdE7P5knFJKKQe5JYgnWqwQaipFKaWc5aaeuEWDuFJKuYDbgjioI1OUUspZ\nDgVxEWkrIgdE5JCI9M+iTKCI7BCRvSKyJrv6EhI1naKUUq6QYyQVES8AYwE8DuAMgK0ispDkgTRl\nSgAYB+ApkpEi4pddnZpOUUop13CkJ94YwGGSESQTAcwC0DFDmR4A5pGMBACSl7Kr0ARxTacopZSz\nHAni/gBOpZk+nTQvrRoASonIGhHZKiIvZVdhotUKr5xPApRSSuXAVZE0H4D6AB4DUATAnyLyJ8kj\nGQsGBQVh96ErsJyMQVhYGAIDA13UBKWUujuEhYUhLCzMobJCMvsCIk0BBJFsmzQ9AABJBqcp0x9A\nQZJfJk1PAbCM5LwMdZEkpi48hL5/tkPssMO3sFlKKfXPJCIgaffuSEfSKVsBVBeRABHJD6AbgEUZ\nyiwE0FJEvEWkMIAmAMKzqjDRaoGXXthUSimn5RhJSVpFpC+AlTBBP5RkuIi8ZRZzEskDIrICwG4A\nVgCTSO7Pqs5EqxWiOXGllHKaQ5GU5HIA92eYNzHD9AgAIxypL9FigRd0dIpSSjnLPc9OsVp0dIpS\nSrmAe2671yGGSinlEtoTV0opD+aeX7u3ak5cKaVcwU1BXNMpSinlCu5Lp4gGcaWUcpYbc+KaTlFK\nKWe5J51is8Jbe+JKKeU0HZ2ilFIezE09cQu8RdMpSinlLLelU/TCplJKOc9t48Q1J66UUs7TdIpS\nSnkwHZ2ilFIezD1BnJpOUUopV3BLELfaLPD20nSKUko5S9MpSinlwdx2YTOflwZxpZRylnvSKdTR\nKUop5Qpuy4lrT1wppZznpp645sSVUsoVNCeulFIezG058Xw6xFAppZzmUBAXkbYickBEDolIfzvL\nW4vIVRHZnvT6LLv6rLRqT1wppVwgx0gqIl4AxgJ4HMAZAFtFZCHJAxmKriP5rCMrtVHTKUop5QqO\n9MQbAzhMMoJkIoBZADraKSeOrtRKvWNTKaVcwZEg7g/gVJrp00nzMmomIjtF5HcReSC7Cq20wsdb\ne+JKKeUsV0XSvwFUJhkrIk8D+A1ADXsFg4KCcPHPzdh95ATCaj+IwMBAFzVBKaXuDmFhYQgLC3Oo\nrJDMvoBIUwBBJNsmTQ8AQJLB2bznOIAGJKMyzCdJVPn3G3iqdhNMfLO3Q41USql/MhEBSbspa0fS\nKVsBVBeRABHJD6AbgEUZVlAuzd+NYQ4OUciCjVb46IVNpZRyWo6RlKRVRPoCWAkT9ENJhovIW2Yx\nJwF4QUTeBpAIIA5A1+zqtMKCfJoTV0oppzkUSUkuB3B/hnkT0/w9DsA4R1dqowX5vHV0ilJKOcst\nd2zaYEV+7YkrpZTT3BTELTrEUCmlXMBtQVzTKUop5Ty3pVO0J66UUs7TdIpSSnkwtwRxwgKffJpO\nUUopZ+noFKWU8mDu6YmLplOUUsoV3JcT13SKUko5zW09cU2nKKWU89x0YdOK/D4axJVSylnu64nn\n0yCulFLOcuOFTc2JK6WUs9wUxK3aE1dKKRfQdIpSSnkw9wVxH02nKKWUs9yWTimgPXGllHKaW4I4\nxKJDDJVSygXc0xP3siC/3rGplFJOc1NPXEenKKWUK7gniHtZUDC/BnGllHKW24K4plOUUsp5bkun\nFNALm0op5TSHgriItBWRAyJySET6Z1OukYgkisjzWZWxWgl466NolVLKFXIM4iLiBWAsgDYAagPo\nLiI1syg3DMCK7OpLSLQBFHiJe04ClFLqbuJIJG0M4DDJCJKJAGYB6Gin3HsAfgVwIbvKEixWwKap\nFKWUcgVHgrg/gFNppk8nzUshIhUBdCI5AYBkV9nNRIsGcaWUchFXRdNRANLmyrMM5EO//grYbEFQ\nUBACAwMRGBjooiYopdTdISwsDGFhYQ6VFZLZFxBpCiCIZNuk6QEASDI4TZljyX8C8ANwA8CbJBdl\nqItHI6NQfUxV2IZecXBzlFLqn01EQNJu59iRnvhWANVFJADAWQDdAHRPW4Bk1TQr+wHA4owBPFl8\nogWgplOUUsoVcoymJK0i0hfASpgceijJcBF5yyzmpIxvya6+BIsFojlxpZRyCYeiKcnlAO7PMG9i\nFmVfy66uhEQLQB0jrpRSrpDng7UTLFaIplOUUsol3BDELRrElVLKRfI8iN+0WCCaTlFKKZfI8yCe\naLFCXDY8XSml/tncEMQ1naKUUq6S9zlxq6ZTlFLKVdySTvHSdIpSSrmEjk5RSikP5pYg7gVNpyil\nlCvkeRC3WHV0ilJKuUre58StFnhpOkUppVzCPaNTJH065d5774WI3BWve++9N693qVLqHyzPu8SJ\nVmumnnhERARyeq65pxDJ9oeNlFLKpdySTvEWTacopZQruOHCpgWio1OUUsol3DI6xVtHpyillEu4\nZ3SKBnGllHIJ9wRxzYkrpZRL5H06xWb1uDs2r1y5gueeew5FixZFlSpVMHPmTHc3SSmlALhjiKHN\n80anvPPOOyhYsCAuXryI7du3o127dqhXrx5q1arl7qYppf7h3DI6xZOCeGxsLObPn4/BgwejUKFC\naNGiBTp27Iiff/7Z3U1TSqm8D+JWmxVe4jnplEOHDsHHxwfVqlVLmVe3bl3s27fPja1SSinDDXds\n3l5P3BU3Qt7OTaHXr19H8eLF080rXrw4YmJinG+QUko5yaGeuIi0FZEDInJIRPrbWf6siOwSkR0i\nsk1EHsuqLstt5sRJ51+3o2jRooiOjk4379q1ayhWrNjtVaiUUi6UYxAXES8AYwG0AVAbQHcRqZmh\n2B8k65J8GMCrACZlVZ+FFnh7UDqlRo0asFgsOHr0aMq8Xbt2oXbt2m5slVJKGY70xBsDOEwygmQi\ngFkAOqYtQDI2zWRRAJeyqsxqs3rUhc3ChQvj+eefxxdffIHY2Fhs2LABixcvxksvveTupimllENB\n3B/AqTTTp5PmpSMinUQkHMBSAO9nVZnFZoG3l+cEcQAYN24cYmNjUbZsWfTs2RPff/+9Di9USt0R\nXBZNSf4G4DcRaQngZwD32yt3aNVqWBK9ERQUhMDAQAQGBrqqCbnG19cXCxYscHczlFL/EGFhYQgL\nC3OorOT0HG8RaQogiGTbpOkBAEgyOJv3HAXQmOTlDPPZetAAML441g75JO38u+p54nfLtiil7gxJ\nccXuGD1H0ilbAVQXkQARyQ+gG4BFGVZQLc3f9QEgYwBPZqEF+TwsnaKUUneqHKMpSauI9AWwEibo\nh5IMF5G3zGJOAtBZRHoBSABwA0DXrOqz0gJvL88ZnaKUUncyh7rEJJcjQ46b5MQ0f4cACHGkLqvN\n6nEXNpVS6k6V989OoQX5PGiIoVJK3cny/tkpmk5RSimXyfMgftxrBfJ7++T1apVS6q6U53mN1nHf\noW7xR/N6tUopdVfK8yBeJb4TimpKXCmlXCLvL2xaAG8PS4mPGzcOjRo1QsGCBfHaa6+5uzlKKZUi\nz/vEVqvnBXF/f398/vnnWLFiBeLi4tzdHKWUSuGWIJ7Pw9IpnTp1AgBs3boVkZGRbm6NUkqlyvN0\nys8/A/p7Ckop5Rp53ieOjARKl77198mXzv8+Gwfqg6mUUneXPA/ifn639z4NwEoplVmep1OUUkq5\njgZxB1itVsTHx8NqtcJiseDmzZuwWq3ubpZSSmkQd8TgwYNRuHBhBAcHY/r06ShcuDCGDBni7mYp\npVTOv+zj0pWJ0N767qZfw7mbtkUpdWdw9pd9lFJK3aE0iCullAfTIK6UUh5Mg7hSSnkwDeJKKeXB\nNIgrpZQHuyOeJxgQEAAR55+NcicICAhwdxOUUv8gDo0TF5G2AEbB9NxDSQZnWN4DQP+kyRgAb5Pc\nY6ceu+PElVJKZc2pceIi4gVgLIA2AGoD6C4iNTMUOwbgEZJ1AQwGMNm5JitHhIWFubsJdxXdn66n\n+zT3OZITbwzgMMkIkokAZgHomLYAyc0kryVNbgbg79pmKnv0C+Jauj9dT/dp7nMkiPsDOJVm+jSy\nD9JvAFjmTKOUUko5xqUXNkXkUQCvAmjpynqVUkrZl+OFTRFpCiCIZNuk6QEAaOfiZh0A8wC0JXk0\ni7r0qqZSSt2GrC5sOtIT3wqguogEADgLoBuA7mkLiEhlmAD+UlYBPLtGKKWUuj05BnGSVhHpC2Al\nUocYhovIW2YxJwH4HEApAOPFDPhOJNk4NxuulFIqj58nrpRSyrXy7LZ7EWkrIgdE5JCI9M/5HSoj\nETkhIrtEZIeIbEma5ysiK0XkoIisEJES7m7nnUpEQkXkvIjsTjMvy/0nIp+IyGERCReRp9zT6jtX\nFvtzoIicFpHtSa+2aZbp/swFeRLEHbxhSOXMBiCQ5MNp0lUDAPxB8n4AqwF84rbW3fl+gPkMpmV3\n/4nIAwC6AKgF4GmkpgpVKnv7EwBGkqyf9FoOACJSC7o/c0Ve9cRzvGFIOUSQ+f+sI4Afk/7+EUCn\nPG2RByG5AcCVDLOz2n/PAphF0kLyBIDDMJ9jlSSL/QmYz2lGHaH7M1fkVRC/1RuGlH0EsEpEtorI\nG0nzypE8DwAkzwEo67bWeaayWey/jJ/ZSOhn1lF9RWSniExJk57S/ZlL9FG0nqUFyfoAngHwroi0\nggnsaemVaufo/nPOeABVSdYDcA7AN25uz10vr4J4JIDKaaYrJc1Tt4Dk2aR/LwL4DeZ09LyIlAMA\nESkP4IL7WuiRstp/kQDuSVNOP7MOIHkxzaNKJyM1ZaL7M5fkVRBPuWFIRPLD3DC0KI/WfVcQkcIi\nUjTp7yIAngKwB2Y/vpJU7GUAC93SQM8hSJ+zzWr/LQLQTUTyi0gVANUBbMmrRnqQdPsz6UCY7HkA\ne5P+1v2ZS/LkRyGyumEoL9Z9FykHYEHSowvyAZhOcqWIbAMwR0ReAxABMwJA2SEiMwAEAigtIicB\nDAQwDMDcjPuP5H4RmQNgP4BEAO/ow/DTy2J/Pioi9WBGUp0A8Bag+zM36c0+SinlwfTCplJKeTAN\n4kop5cE0iCullAfTIK6UUh5Mg7hSSnkwDeJKKeXBNIgrpZQH0yCulFIe7P8Ba4WozsfomosAAAAA\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdde2d2f290>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ASR_SPARSE 201\n"
     ]
    },
    {
     "data": {
      "image/png": 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yzbQ23Be6L6VTknaP0pU6zOjADUEbWGdSHX7/5/dcd3IdY6xmNOWLURe59sTa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\nxJVSqhj7f4AHQ/RvPt1jAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fde1c2aad90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ASR_H1_TRANSFORMED_W1 111\n"
     ]
    },
    {
     "data": {
      "image/png": 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nzuE//wxs2ADUqAEMGpSRbecn0ZGIVmGt8EXfLxDcJLhI2ywici4XTRDfvx+4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\nMQVxEZFS7P8Bo/FPX67i1fcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdde3f91bd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ASR_AE_H1 118\n"
     ]
    },
    {
     "data": {
      "image/png": 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7tzvXnF6TUu6d395hmQllOP3Q9HSvN1vMbDijYUrW2WlxJ/Zd1ZftF7bP9P/t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\nQhRiEsSFEKIQkyAuhBCFmARxIYQoxP4fRt1FqjJyrh0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdde2dc0110>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data=shelve.open(\"AUTO_scores/MINIAE_TANH_H50_W300_MODELSDO_DOMLP.shelve\")\n",
    "for key,table in data.iteritems():\n",
    "    print key, np.argmax([x[0] for x in data[key][0] ])\n",
    "    pandas.DataFrame(zip([x[0] for x in data[key][0][:200] ],[x[0] for x in data[key][1][:200]  ])).plot()\n",
    "    plt.show()\n",
    "data.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['TRS_AE_H1', 'TRS_AE_OUT', 'TRS_SPARSE', 'LABEL', 'ASR_AE_OUT', 'ASR_H2_TRANFORMED_OUT', 'ASR_SPARSE', 'ASR_H1_TRANFORMED_TRSH1', 'ASR_H1_TRANSFORMED_W1', 'ASR_AE_H1']\n"
     ]
    }
   ],
   "source": [
    "data=shelve.open(\"./models/MINIAE_TANH_H50_W300.shelve\")\n",
    "print data.keys()\n",
    "data.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data=shelve.open(\"./UNFIXED_TRANS_scores/DECODA_AEUNFIXED_TANH_TFIDF_MODELS.shelve\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['TRS_AE_H1',\n",
       " 'TRS_AE_OUT',\n",
       " 'TRS_SPARSE',\n",
       " 'ASR_AE_OUT',\n",
       " 'ASR_H2_TRANSFORMED',\n",
       " 'ASR_SPARSE',\n",
       " 'ASR_TRANFORMED_OUT',\n",
       " 'ASR_H1_TRANSFORMED',\n",
       " 'ASR_W1_TRANSFORMED',\n",
       " 'ASR_AE_H1']"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.keys()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "AssertionError",
     "evalue": "(AssertionError('The following error happened while compiling the node', MaxAndArgmax(y, TensorConstant{(1,) of 1}), '\\n'), <function _constructor_Function at 0x7fbb1b6e4140>, (<theano.compile.function_module.FunctionMaker object at 0x7fbab61abc10>, [<None>, <None>, <None>, <<CudaNdarray object at 0x7fbab99bc8b0>>, <<CudaNdarray object at 0x7fbab5abfaf0>>, <<CudaNdarray object at 0x7fbab5e048f0>>, <<CudaNdarray object at 0x7fbab5c050f0>>, <<CudaNdarray object at 0x7fbab5df9cb0>>, <<CudaNdarray object at 0x7fbab5d5ddf0>>, <<CudaNdarray object at 0x7fbab5c2b3f0>>, <<CudaNdarray object at 0x7fbab5c34db0>>], [None, None, None, <CudaNdarray object at 0x7fbab99bc8b0>, <CudaNdarray object at 0x7fbab5abfaf0>, <CudaNdarray object at 0x7fbab5e048f0>, <CudaNdarray object at 0x7fbab5c050f0>, <CudaNdarray object at 0x7fbab5df9cb0>, <CudaNdarray object at 0x7fbab5d5ddf0>, <CudaNdarray object at 0x7fbab5c2b3f0>, <CudaNdarray object at 0x7fbab5c34db0>]))",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mAssertionError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-25-584a6fed03b7>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mdata\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m\"ASR_TRANFORMED_OUT\"\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/shelve.pyc\u001b[0m in \u001b[0;36m__getitem__\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m    120\u001b[0m         \u001b[1;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    121\u001b[0m             \u001b[0mf\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mStringIO\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdict\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 122\u001b[1;33m             \u001b[0mvalue\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mUnpickler\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mf\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mload\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    123\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwriteback\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    124\u001b[0m                 \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcache\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/site-packages/theano/compile/function_module.pyc\u001b[0m in \u001b[0;36m_constructor_Function\u001b[1;34m(maker, input_storage, inputs_data)\u001b[0m\n\u001b[0;32m    745\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mtheano\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mconfig\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0munpickle_function\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    746\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mNone\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 747\u001b[1;33m     \u001b[0mf\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mmaker\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcreate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minput_storage\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtrustme\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    748\u001b[0m     \u001b[1;32massert\u001b[0m \u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minput_storage\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m==\u001b[0m \u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minputs_data\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    749\u001b[0m     \u001b[1;32mfor\u001b[0m \u001b[0mcontainer\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mx\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mzip\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minput_storage\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0minputs_data\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/site-packages/theano/compile/function_module.pyc\u001b[0m in \u001b[0;36mcreate\u001b[1;34m(self, input_storage, trustme)\u001b[0m\n\u001b[0;32m   1322\u001b[0m             \u001b[0mtheano\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mconfig\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtraceback\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlimit\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1323\u001b[0m             _fn, _i, _o = self.linker.make_thunk(\n\u001b[1;32m-> 1324\u001b[1;33m                 input_storage=input_storage_lists)\n\u001b[0m\u001b[0;32m   1325\u001b[0m         \u001b[1;32mfinally\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1326\u001b[0m             \u001b[0mtheano\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mconfig\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtraceback\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlimit\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mlimit_orig\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/site-packages/theano/gof/link.pyc\u001b[0m in \u001b[0;36mmake_thunk\u001b[1;34m(self, input_storage, output_storage)\u001b[0m\n\u001b[0;32m    517\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mmake_thunk\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0minput_storage\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0moutput_storage\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    518\u001b[0m         return self.make_all(input_storage=input_storage,\n\u001b[1;32m--> 519\u001b[1;33m                              output_storage=output_storage)[:3]\n\u001b[0m\u001b[0;32m    520\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    521\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mmake_all\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0minput_storage\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0moutput_storage\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/site-packages/theano/gof/vm.pyc\u001b[0m in \u001b[0;36mmake_all\u001b[1;34m(self, profiler, input_storage, output_storage)\u001b[0m\n\u001b[0;32m    895\u001b[0m                                                  \u001b[0mstorage_map\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    896\u001b[0m                                                  \u001b[0mcompute_map\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 897\u001b[1;33m                                                  no_recycling))\n\u001b[0m\u001b[0;32m    898\u001b[0m                 \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mhasattr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mthunks\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'lazy'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    899\u001b[0m                     \u001b[1;31m# We don't want all ops maker to think about lazy Ops.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/site-packages/theano/gof/op.pyc\u001b[0m in \u001b[0;36mmake_thunk\u001b[1;34m(self, node, storage_map, compute_map, no_recycling)\u001b[0m\n\u001b[0;32m    737\u001b[0m                 \u001b[0mlogger\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdebug\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Trying CLinker.make_thunk'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    738\u001b[0m                 outputs = cl.make_thunk(input_storage=node_input_storage,\n\u001b[1;32m--> 739\u001b[1;33m                                         output_storage=node_output_storage)\n\u001b[0m\u001b[0;32m    740\u001b[0m                 \u001b[0mfill_storage\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnode_input_filters\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnode_output_filters\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0moutputs\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    741\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/site-packages/theano/gof/cc.pyc\u001b[0m in \u001b[0;36mmake_thunk\u001b[1;34m(self, input_storage, output_storage, keep_lock)\u001b[0m\n\u001b[0;32m   1071\u001b[0m         cthunk, in_storage, out_storage, error_storage = self.__compile__(\n\u001b[0;32m   1072\u001b[0m             \u001b[0minput_storage\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0moutput_storage\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1073\u001b[1;33m             keep_lock=keep_lock)\n\u001b[0m\u001b[0;32m   1074\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1075\u001b[0m         \u001b[0mres\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0m_CThunk\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcthunk\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0minit_tasks\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtasks\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0merror_storage\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/site-packages/theano/gof/cc.pyc\u001b[0m in \u001b[0;36m__compile__\u001b[1;34m(self, input_storage, output_storage, keep_lock)\u001b[0m\n\u001b[0;32m   1013\u001b[0m                                     \u001b[0minput_storage\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1014\u001b[0m                                     \u001b[0moutput_storage\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1015\u001b[1;33m                                     keep_lock=keep_lock)\n\u001b[0m\u001b[0;32m   1016\u001b[0m         return (thunk,\n\u001b[0;32m   1017\u001b[0m                 [link.Container(input, storage) for input, storage in\n",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/site-packages/theano/gof/cc.pyc\u001b[0m in \u001b[0;36mcthunk_factory\u001b[1;34m(self, error_storage, in_storage, out_storage, keep_lock)\u001b[0m\n\u001b[0;32m   1440\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1441\u001b[0m             module = get_module_cache().module_from_key(\n\u001b[1;32m-> 1442\u001b[1;33m                 key=key, lnk=self, keep_lock=keep_lock)\n\u001b[0m\u001b[0;32m   1443\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1444\u001b[0m         \u001b[0mvars\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minputs\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0moutputs\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0morphans\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/site-packages/theano/gof/cmodule.pyc\u001b[0m in \u001b[0;36mmodule_from_key\u001b[1;34m(self, key, lnk, keep_lock)\u001b[0m\n\u001b[0;32m   1049\u001b[0m         \u001b[0mlock_taken\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mFalse\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1050\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1051\u001b[1;33m         \u001b[0msrc_code\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mlnk\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_src_code\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   1052\u001b[0m         \u001b[1;31m# Is the source code already in the cache?\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1053\u001b[0m         \u001b[0mmodule_hash\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mget_module_hash\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msrc_code\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/site-packages/theano/gof/cc.pyc\u001b[0m in \u001b[0;36mget_src_code\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m   1313\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1314\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mget_src_code\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[1;32m-> 1315\u001b[1;33m         \u001b[0mmod\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_dynamic_module\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   1316\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mmod\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcode\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1317\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/site-packages/theano/gof/cc.pyc\u001b[0m in \u001b[0;36mget_dynamic_module\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m   1368\u001b[0m         \"\"\"\n\u001b[0;32m   1369\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mhasattr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'_mod'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1370\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcode_gen\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   1371\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1372\u001b[0m             \u001b[0mmod\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcmodule\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mDynamicModule\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/site-packages/theano/gof/cc.pyc\u001b[0m in \u001b[0;36mcode_gen\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    747\u001b[0m             \u001b[1;31m# emit c_code\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    748\u001b[0m             \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 749\u001b[1;33m                 \u001b[0mbehavior\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mop\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mc_code\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnode\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mname\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0misyms\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mosyms\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msub\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    750\u001b[0m             \u001b[1;32mexcept\u001b[0m \u001b[0mutils\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mMethodNotDefined\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    751\u001b[0m                 \u001b[1;32mraise\u001b[0m \u001b[0mNotImplementedError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"%s cannot produce C code\"\u001b[0m \u001b[1;33m%\u001b[0m \u001b[0mop\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/site-packages/theano/tensor/basic.pyc\u001b[0m in \u001b[0;36mc_code\u001b[1;34m(self, node, name, inp, out, sub)\u001b[0m\n\u001b[0;32m   1300\u001b[0m             \u001b[0maxis_code\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m\"axis = NPY_MAXDIMS;\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1301\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1302\u001b[1;33m             \u001b[1;32massert\u001b[0m \u001b[0mnode\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minputs\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mndim\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1303\u001b[0m             axis_code = \"\"\"\n\u001b[0;32m   1304\u001b[0m             \u001b[0maxis\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdtype_\u001b[0m\u001b[1;33m%\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0maxis\u001b[0m\u001b[1;33m)\u001b[0m\u001b[0ms\u001b[0m\u001b[1;33m*\u001b[0m\u001b[1;33m)\u001b[0m\u001b[0mPyArray_DATA\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m%\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0maxis\u001b[0m\u001b[1;33m)\u001b[0m\u001b[0ms\u001b[0m\u001b[1;33m)\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[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mAssertionError\u001b[0m: (AssertionError('The following error happened while compiling the node', MaxAndArgmax(y, TensorConstant{(1,) of 1}), '\\n'), <function _constructor_Function at 0x7fbb1b6e4140>, (<theano.compile.function_module.FunctionMaker object at 0x7fbab61abc10>, [<None>, <None>, <None>, <<CudaNdarray object at 0x7fbab99bc8b0>>, <<CudaNdarray object at 0x7fbab5abfaf0>>, <<CudaNdarray object at 0x7fbab5e048f0>>, <<CudaNdarray object at 0x7fbab5c050f0>>, <<CudaNdarray object at 0x7fbab5df9cb0>>, <<CudaNdarray object at 0x7fbab5d5ddf0>>, <<CudaNdarray object at 0x7fbab5c2b3f0>>, <<CudaNdarray object at 0x7fbab5c34db0>>], [None, None, None, <CudaNdarray object at 0x7fbab99bc8b0>, <CudaNdarray object at 0x7fbab5abfaf0>, <CudaNdarray object at 0x7fbab5e048f0>, <CudaNdarray object at 0x7fbab5c050f0>, <CudaNdarray object at 0x7fbab5df9cb0>, <CudaNdarray object at 0x7fbab5d5ddf0>, <CudaNdarray object at 0x7fbab5c2b3f0>, <CudaNdarray object at 0x7fbab5c34db0>]))"
     ]
    }
   ],
   "source": [
    "data[\"ASR_TRANFORMED_OUT\"].key()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using gpu device 1: GeForce GTX TITAN X\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "(KeyboardInterrupt(), <function _constructor_Function at 0x7fbb1b6e4140>, (<theano.compile.function_module.FunctionMaker object at 0x7fbb2603f5d0>, [<None>, <None>, <None>, <<CudaNdarray object at 0x7fbabf90ec70>>, <<CudaNdarray object at 0x7fbabf90eab0>>, <<CudaNdarray object at 0x7fbabf91c0b0>>, <<CudaNdarray object at 0x7fbabf90ef30>>, <<CudaNdarray object at 0x7fbabf91c4b0>>, <<CudaNdarray object at 0x7fbabf91c370>>, <<CudaNdarray object at 0x7fbabf91c8b0>>, <<CudaNdarray object at 0x7fbabf91c770>>], [None, None, None, <CudaNdarray object at 0x7fbabf90ec70>, <CudaNdarray object at 0x7fbabf90eab0>, <CudaNdarray object at 0x7fbabf91c0b0>, <CudaNdarray object at 0x7fbabf90ef30>, <CudaNdarray object at 0x7fbabf91c4b0>, <CudaNdarray object at 0x7fbabf91c370>, <CudaNdarray object at 0x7fbabf91c8b0>, <CudaNdarray object at 0x7fbabf91c770>]))",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-8-04e41364c71e>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[1;32mfor\u001b[0m \u001b[0mkey\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mtable\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0miteritems\u001b[0m\u001b[1;33m(\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      2\u001b[0m     \u001b[1;32mprint\u001b[0m \u001b[0mkey\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0margmax\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mx\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mkey\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[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      3\u001b[0m     \u001b[0mpandas\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mDataFrame\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mzip\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mx\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mkey\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[1;33m:\u001b[0m\u001b[1;36m200\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mx\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;36m200\u001b[0m\u001b[1;33m]\u001b[0m  \u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m     \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mshow\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mclose\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/UserDict.pyc\u001b[0m in \u001b[0;36miteritems\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    109\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0miteritems\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    110\u001b[0m         \u001b[1;32mfor\u001b[0m \u001b[0mk\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 111\u001b[1;33m             \u001b[1;32myield\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mk\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mk\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    112\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0miterkeys\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    113\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__iter__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/shelve.pyc\u001b[0m in \u001b[0;36m__getitem__\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m    120\u001b[0m         \u001b[1;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    121\u001b[0m             \u001b[0mf\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mStringIO\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdict\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 122\u001b[1;33m             \u001b[0mvalue\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mUnpickler\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mf\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mload\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    123\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwriteback\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    124\u001b[0m                 \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcache\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/site-packages/theano/compile/function_module.pyc\u001b[0m in \u001b[0;36m_constructor_Function\u001b[1;34m(maker, input_storage, inputs_data)\u001b[0m\n\u001b[0;32m    745\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mtheano\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mconfig\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0munpickle_function\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    746\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mNone\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 747\u001b[1;33m     \u001b[0mf\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mmaker\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcreate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minput_storage\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtrustme\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    748\u001b[0m     \u001b[1;32massert\u001b[0m \u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minput_storage\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m==\u001b[0m \u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minputs_data\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    749\u001b[0m     \u001b[1;32mfor\u001b[0m \u001b[0mcontainer\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mx\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mzip\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minput_storage\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0minputs_data\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/site-packages/theano/compile/function_module.pyc\u001b[0m in \u001b[0;36mcreate\u001b[1;34m(self, input_storage, trustme)\u001b[0m\n\u001b[0;32m   1322\u001b[0m             \u001b[0mtheano\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mconfig\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtraceback\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlimit\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1323\u001b[0m             _fn, _i, _o = self.linker.make_thunk(\n\u001b[1;32m-> 1324\u001b[1;33m                 input_storage=input_storage_lists)\n\u001b[0m\u001b[0;32m   1325\u001b[0m         \u001b[1;32mfinally\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1326\u001b[0m             \u001b[0mtheano\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mconfig\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtraceback\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlimit\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mlimit_orig\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/site-packages/theano/gof/link.pyc\u001b[0m in \u001b[0;36mmake_thunk\u001b[1;34m(self, input_storage, output_storage)\u001b[0m\n\u001b[0;32m    517\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mmake_thunk\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0minput_storage\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0moutput_storage\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    518\u001b[0m         return self.make_all(input_storage=input_storage,\n\u001b[1;32m--> 519\u001b[1;33m                              output_storage=output_storage)[:3]\n\u001b[0m\u001b[0;32m    520\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    521\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mmake_all\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0minput_storage\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0moutput_storage\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/site-packages/theano/gof/vm.pyc\u001b[0m in \u001b[0;36mmake_all\u001b[1;34m(self, profiler, input_storage, output_storage)\u001b[0m\n\u001b[0;32m    895\u001b[0m                                                  \u001b[0mstorage_map\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    896\u001b[0m                                                  \u001b[0mcompute_map\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 897\u001b[1;33m                                                  no_recycling))\n\u001b[0m\u001b[0;32m    898\u001b[0m                 \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mhasattr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mthunks\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'lazy'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    899\u001b[0m                     \u001b[1;31m# We don't want all ops maker to think about lazy Ops.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/site-packages/theano/gof/op.pyc\u001b[0m in \u001b[0;36mmake_thunk\u001b[1;34m(self, node, storage_map, compute_map, no_recycling)\u001b[0m\n\u001b[0;32m    737\u001b[0m                 \u001b[0mlogger\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdebug\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Trying CLinker.make_thunk'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    738\u001b[0m                 outputs = cl.make_thunk(input_storage=node_input_storage,\n\u001b[1;32m--> 739\u001b[1;33m                                         output_storage=node_output_storage)\n\u001b[0m\u001b[0;32m    740\u001b[0m                 \u001b[0mfill_storage\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnode_input_filters\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnode_output_filters\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0moutputs\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    741\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/site-packages/theano/gof/cc.pyc\u001b[0m in \u001b[0;36mmake_thunk\u001b[1;34m(self, input_storage, output_storage, keep_lock)\u001b[0m\n\u001b[0;32m   1071\u001b[0m         cthunk, in_storage, out_storage, error_storage = self.__compile__(\n\u001b[0;32m   1072\u001b[0m             \u001b[0minput_storage\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0moutput_storage\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1073\u001b[1;33m             keep_lock=keep_lock)\n\u001b[0m\u001b[0;32m   1074\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1075\u001b[0m         \u001b[0mres\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0m_CThunk\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcthunk\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0minit_tasks\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtasks\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0merror_storage\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/site-packages/theano/gof/cc.pyc\u001b[0m in \u001b[0;36m__compile__\u001b[1;34m(self, input_storage, output_storage, keep_lock)\u001b[0m\n\u001b[0;32m   1013\u001b[0m                                     \u001b[0minput_storage\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1014\u001b[0m                                     \u001b[0moutput_storage\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1015\u001b[1;33m                                     keep_lock=keep_lock)\n\u001b[0m\u001b[0;32m   1016\u001b[0m         return (thunk,\n\u001b[0;32m   1017\u001b[0m                 [link.Container(input, storage) for input, storage in\n",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/site-packages/theano/gof/cc.pyc\u001b[0m in \u001b[0;36mcthunk_factory\u001b[1;34m(self, error_storage, in_storage, out_storage, keep_lock)\u001b[0m\n\u001b[0;32m   1440\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1441\u001b[0m             module = get_module_cache().module_from_key(\n\u001b[1;32m-> 1442\u001b[1;33m                 key=key, lnk=self, keep_lock=keep_lock)\n\u001b[0m\u001b[0;32m   1443\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1444\u001b[0m         \u001b[0mvars\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minputs\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0moutputs\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0morphans\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/site-packages/theano/gof/cmodule.pyc\u001b[0m in \u001b[0;36mmodule_from_key\u001b[1;34m(self, key, lnk, keep_lock)\u001b[0m\n\u001b[0;32m   1074\u001b[0m             \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1075\u001b[0m                 \u001b[0mlocation\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mdlimport_workdir\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdirname\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1076\u001b[1;33m                 \u001b[0mmodule\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mlnk\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcompile_cmodule\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlocation\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1077\u001b[0m                 \u001b[0mname\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mmodule\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__file__\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1078\u001b[0m                 \u001b[1;32massert\u001b[0m \u001b[0mname\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstartswith\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlocation\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/site-packages/theano/gof/cc.pyc\u001b[0m in \u001b[0;36mcompile_cmodule\u001b[1;34m(self, location)\u001b[0m\n\u001b[0;32m   1352\u001b[0m                 \u001b[0mlib_dirs\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlib_dirs\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1353\u001b[0m                 \u001b[0mlibs\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mlibs\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1354\u001b[1;33m                 preargs=preargs)\n\u001b[0m\u001b[0;32m   1355\u001b[0m         \u001b[1;32mexcept\u001b[0m \u001b[0mException\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1356\u001b[0m             \u001b[0me\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0margs\u001b[0m \u001b[1;33m+=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mstr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfgraph\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/site-packages/theano/gof/cmodule.pyc\u001b[0m in \u001b[0;36mcompile_str\u001b[1;34m(module_name, src_code, location, include_dirs, lib_dirs, libs, preargs, py_module)\u001b[0m\n\u001b[0;32m   1986\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1987\u001b[0m         \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1988\u001b[1;33m             \u001b[0mp_out\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0moutput_subprocess_Popen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcmd\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1989\u001b[0m             \u001b[0mcompile_stderr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mdecode\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mp_out\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1990\u001b[0m         \u001b[1;32mexcept\u001b[0m \u001b[0mException\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/site-packages/theano/misc/windows.pyc\u001b[0m in \u001b[0;36moutput_subprocess_Popen\u001b[1;34m(command, **params)\u001b[0m\n\u001b[0;32m     74\u001b[0m     \u001b[1;31m# we need to use communicate to make sure we don't deadlock around\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     75\u001b[0m     \u001b[1;31m# the stdour/stderr pipe.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 76\u001b[1;33m     \u001b[0mout\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcommunicate\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     77\u001b[0m     \u001b[1;32mreturn\u001b[0m \u001b[0mout\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mreturncode\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/subprocess.pyc\u001b[0m in \u001b[0;36mcommunicate\u001b[1;34m(self, input)\u001b[0m\n\u001b[0;32m    797\u001b[0m             \u001b[1;32mreturn\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mstdout\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstderr\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    798\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 799\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_communicate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minput\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    800\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    801\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/subprocess.pyc\u001b[0m in \u001b[0;36m_communicate\u001b[1;34m(self, input)\u001b[0m\n\u001b[0;32m   1407\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1408\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0m_has_poll\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1409\u001b[1;33m                 \u001b[0mstdout\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstderr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_communicate_with_poll\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minput\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1410\u001b[0m             \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1411\u001b[0m                 \u001b[0mstdout\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstderr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_communicate_with_select\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minput\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m/home/laboinfo/janod/.pyenv/versions/2.7.10/lib/python2.7/subprocess.pyc\u001b[0m in \u001b[0;36m_communicate_with_poll\u001b[1;34m(self, input)\u001b[0m\n\u001b[0;32m   1461\u001b[0m             \u001b[1;32mwhile\u001b[0m \u001b[0mfd2file\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1462\u001b[0m                 \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1463\u001b[1;33m                     \u001b[0mready\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpoller\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpoll\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   1464\u001b[0m                 \u001b[1;32mexcept\u001b[0m \u001b[0mselect\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0merror\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1465\u001b[0m                     \u001b[1;32mif\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m==\u001b[0m \u001b[0merrno\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mEINTR\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: (KeyboardInterrupt(), <function _constructor_Function at 0x7fbb1b6e4140>, (<theano.compile.function_module.FunctionMaker object at 0x7fbb2603f5d0>, [<None>, <None>, <None>, <<CudaNdarray object at 0x7fbabf90ec70>>, <<CudaNdarray object at 0x7fbabf90eab0>>, <<CudaNdarray object at 0x7fbabf91c0b0>>, <<CudaNdarray object at 0x7fbabf90ef30>>, <<CudaNdarray object at 0x7fbabf91c4b0>>, <<CudaNdarray object at 0x7fbabf91c370>>, <<CudaNdarray object at 0x7fbabf91c8b0>>, <<CudaNdarray object at 0x7fbabf91c770>>], [None, None, None, <CudaNdarray object at 0x7fbabf90ec70>, <CudaNdarray object at 0x7fbabf90eab0>, <CudaNdarray object at 0x7fbabf91c0b0>, <CudaNdarray object at 0x7fbabf90ef30>, <CudaNdarray object at 0x7fbabf91c4b0>, <CudaNdarray object at 0x7fbabf91c370>, <CudaNdarray object at 0x7fbabf91c8b0>, <CudaNdarray object at 0x7fbabf91c770>]))"
     ]
    }
   ],
   "source": [
    "for key,table in data.iteritems():\n",
    "    print key, np.argmax([x[0] for x in data[key][0] ])\n",
    "    pandas.DataFrame(zip([x[0] for x in data[key][0][:200] ],[x[0] for x in data[key][1][:200]  ])).plot()\n",
    "    plt.show()\n",
    "data.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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