{

 "cells": [

  {

   "cell_type": "markdown",

   "metadata": {},

   "source": [

    "## Error analysis\n",

    "\n",

    "Some studies on neural network results"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 1,

   "metadata": {

    "collapsed": false

   },

   "outputs": [

    {

     "name": "stderr",

     "output_type": "stream",

     "text": [

      "Using Theano backend.\n",

      "Using gpu device 0: GeForce GTX 980 Ti (CNMeM is disabled, cuDNN 4007)\n"

     ]

    }

   ],

   "source": [

    "from bs4 import BeautifulSoup\n",

    "import urllib\n",

    "import pdb\n",

    "import json\n",

    "import os\n",

    "import pandas as pd\n",

    "import pickle\n",

    "import matplotlib.pyplot as plt\n",

    "import numpy as np\n",

    "from keras.utils.data_utils import get_file\n",

    "from keras.layers.embeddings import Embedding\n",

    "from keras.layers.core import Dense, Merge, Dropout, RepeatVector\n",

    "from keras.layers import recurrent\n",

    "from keras.layers.recurrent import LSTM, GRU\n",

    "from keras.models import Sequential\n",

    "from keras.preprocessing.sequence import pad_sequences\n",

    "from keras.callbacks import ModelCheckpoint, Callback\n",

    "\n",

    "from utils import create_vectors_dataset, get_spacy_vectors\n",

    "import h5py\n",

    "import theano.tensor as T\n",

    "from spacy.en import English\n",

    "from itertools import izip_longest\n",

    "\n",

    "\n",

    "%matplotlib inline"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 43,

   "metadata": {

    "collapsed": false

   },

   "outputs": [

    {

     "name": "stdout",

     "output_type": "stream",

     "text": [

      "-\n",

      "('Vocab size:', 21520, 'unique words')\n",

      "('Story max length:', 1647, 'words')\n",

      "('Number of training stories:', 133093)\n",

      "('Number of test stories:', 59394)\n",

      "-\n",

      "Here's what a \"story\" tuple looks like (input, query, answer):\n",

      "([u'barrett', u'esophagus', u'itself', u'does', u'not', u'cause', u'symptoms', u'.', u'many', u'people', u'with', u'this', u'condition', u'do', u'not', u'have', u'any', u'symptoms', u'.', u'the', u'acid', u'reflux', u'that', u'causes', u'barrett', u'esophagus', u'often', u'leads', u'to', u'symptoms', u'of', u'heartburn', u'.'], u'barrett esophagus')\n",

      "-\n",

      "Vectorizing the word sequences...\n",

      "Answers dict len: 2350\n"

     ]

    }

   ],

   "source": [

    "training_set_file = 'data/training_set.dat'\n",

    "test_set_file = 'data/test_set.dat'\n",

    "\n",

    "train_facts = pickle.load(open(training_set_file,'r'))\n",

    "\n",

    "test_facts = pickle.load(open(test_set_file,'r'))\n",

    "\n",

    "train_stories = [(reduce(lambda x,y: x + y, map(list,fact)),q) for fact,q in train_facts]\n",

    "test_stories = [(reduce(lambda x,y: x + y, map(list,fact)),q) for fact,q in test_facts]\n",

    "\n",

    "\n",

    "vocab = sorted(reduce(lambda x, y: x | y, (set(story + [answer]) for story, answer in train_stories + test_stories)))\n",

    "story_vocab = sorted(reduce(lambda x, y: x | y, (set(story) for story, answer in train_stories + test_stories)))\n",

    "\n",

    "# Reserve 0 for masking via pad_sequences\n",

    "vocab_size = len(vocab) + 1\n",

    "story_maxlen = max(map(len, (x for x, _ in train_stories + test_stories)))\n",

    "\n",

    "\n",

    "print('-')\n",

    "print('Vocab size:', vocab_size, 'unique words')\n",

    "print('Story max length:', story_maxlen, 'words')\n",

    "print('Number of training stories:', len(train_stories))\n",

    "print('Number of test stories:', len(test_stories))\n",

    "print('-')\n",

    "print('Here\\'s what a \"story\" tuple looks like (input, query, answer):')\n",

    "print(train_stories[0])\n",

    "print('-')\n",

    "print('Vectorizing the word sequences...')\n",

    "\n",

    "answer_vocab = sorted(reduce(lambda x, y: x | y, (set([answer]) for _, answer in train_stories + test_stories)))\n",

    "# Reserve 0 for masking via pad_sequences\n",

    "answer_dict = dict((word, i) for i, word in enumerate(answer_vocab))\n",

    "print('Answers dict len: {0}'.format(len(answer_dict)))\n"

   ]

  },

  {

   "cell_type": "markdown",

   "metadata": {},

   "source": [

    "### Training curves"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 18,

   "metadata": {

    "collapsed": false

   },

   "outputs": [

    {

     "data": {

      "text/plain": [

       "<matplotlib.text.Text at 0x7fc9e6bf1fd0>"

      ]

     },

     "execution_count": 18,

     "metadata": {},

     "output_type": "execute_result"

    },

    {

     "data": {

      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYMAAAEPCAYAAACgFqixAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nIigMREQEhYGIiKAwEBER4P8DyqkDLUCRmXcAAAAASUVORK5CYII=\n",

      "text/plain": [

       "<matplotlib.figure.Figure at 0x7fc9ea3e7c10>"

      ]

     },

     "metadata": {},

     "output_type": "display_data"

    }

   ],

   "source": [

    "results = np.loadtxt('logs/log_GRU_128_drop_0.5.txt')\n",

    "X = range(results.shape[0])\n",

    "plt.plot(X,results[:,0])\n",

    "plt.ylabel('training loss')\n",

    "plt.xlabel('epochs')"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 19,

   "metadata": {

    "collapsed": false

   },

   "outputs": [

    {

     "data": {

      "text/plain": [

       "<matplotlib.text.Text at 0x7fc9e6b10fd0>"

      ]

     },

     "execution_count": 19,

     "metadata": {},

     "output_type": "execute_result"

    },

    {

     "data": {

      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYMAAAEPCAYAAACgFqixAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\niIigZCAiIsD/B1/Y1wIX6pENAAAAAElFTkSuQmCC\n",

      "text/plain": [

       "<matplotlib.figure.Figure at 0x7fc9ea420090>"

      ]

     },

     "metadata": {},

     "output_type": "display_data"

    }

   ],

   "source": [

    "X = range(results.shape[0])\n",

    "plt.plot(X,results[:,1])\n",

    "plt.ylabel('training accuracy')\n",

    "plt.xlabel('epochs')"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 20,

   "metadata": {

    "collapsed": false

   },

   "outputs": [

    {

     "name": "stdout",

     "output_type": "stream",

     "text": [

      "RNN / HIDDENS = <class 'keras.layers.recurrent.LSTM'>, 128\n",

      "Compiling model...\n",

      "Compilation done...\n"

     ]

    }

   ],

   "source": [

    "RNN = recurrent.LSTM\n",

    "NUM_HIDDEN_UNITS = 128\n",

    "BATCH_SIZE = 32\n",

    "EPOCHS = 40\n",

    "DROPOUT_FACTOR = 0.5\n",

    "print('RNN / HIDDENS = {}, {}'.format(RNN, NUM_HIDDEN_UNITS))\n",

    "\n",

    "vocab_size = 2350\n",

    "max_len = 500\n",

    "word_vec_dim = 300\n",

    "\n",

    "model = Sequential()\n",

    "model.add(GRU(output_dim = NUM_HIDDEN_UNITS, activation='tanh', \n",

    "               return_sequences=True, input_shape=(max_len, word_vec_dim)))\n",

    "model.add(Dropout(DROPOUT_FACTOR))\n",

    "model.add(GRU(NUM_HIDDEN_UNITS, return_sequences=False))\n",

    "model.add(Dense(vocab_size, init='uniform',activation='softmax'))\n",

    "\n",

    "print('Compiling model...')\n",

    "model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])\n",

    "print('Compilation done...')\n",

    "model.load_weights('models/weights_GRU_{0}_drop_0.5.hdf5'.format(NUM_HIDDEN_UNITS))\n"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 21,

   "metadata": {

    "collapsed": false

   },

   "outputs": [],

   "source": [

    "import random\n",

    "random.seed(1337)\n",

    "# Pickle to avoid reload\n",

    "n_test = len(test_stories)\n",

    "# Reserve 0 for masking via pad_sequences\n",

    "\n",

    "nlp = English()\n"

   ]

  },

  {

   "cell_type": "markdown",

   "metadata": {},

   "source": [

    "### Relationship between large of stories and error?"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 27,

   "metadata": {

    "collapsed": false

   },

   "outputs": [

    {

     "name": "stdout",

     "output_type": "stream",

     "text": [

      "(59394,)\n",

      "59394\n"

     ]

    },

    {

     "data": {

      "text/plain": [

       "(0, 120)"

      ]

     },

     "execution_count": 27,

     "metadata": {},

     "output_type": "execute_result"

    },

    {

     "data": {

      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYYAAAEPCAYAAABGP2P1AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nQxAEQVBCOIYgCIKghP8BJwHhmcYvUWsAAAAASUVORK5CYII=\n",

      "text/plain": [

       "<matplotlib.figure.Figure at 0x7fc9e60b5bd0>"

      ]

     },

     "metadata": {},

     "output_type": "display_data"

    }

   ],

   "source": [

    "\n",

    "all_err = np.loadtxt('logs/error.dat')\n",

    "stories_len = map(len, (x for x, _ in test_stories))\n",

    "\n",

    "print all_err.shape\n",

    "print len(test_stories)\n",

    "\n",

    "plt.scatter(stories_len, all_err, alpha=1., s=5.)\n",

    "plt.xlabel('Number words')\n",

    "plt.ylabel('Crossentropy error')\n",

    "plt.ylim([0,25])\n",

    "plt.xlim([0,120])\n",

    "\n",

    "#print all_err\n"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 28,

   "metadata": {

    "collapsed": false

   },

   "outputs": [

    {

     "data": {

      "text/plain": [

       "<matplotlib.text.Text at 0x7fc9ea46ae90>"

      ]

     },

     "execution_count": 28,

     "metadata": {},

     "output_type": "execute_result"

    },

    {

     "data": {

      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYwAAAEPCAYAAABRHfM8AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nrkJggg==\n",

      "text/plain": [

       "<matplotlib.figure.Figure at 0x7fc9e60b5550>"

      ]

     },

     "metadata": {},

     "output_type": "display_data"

    }

   ],

   "source": [

    "\n",

    "n_bins = 100\n",

    "n,vals = np.histogram(stories_len, bins=n_bins)\n",

    "e = (vals[:-1] + vals[1:]) / 2\n",

    "# Avoiding values with more than 60 -> avoid high var\n",

    "#max_ind = np.argmax(e > 60)\n",

    "max_ind = e.shape[0]\n",

    "sy,_ = np.histogram(stories_len, bins=n_bins, weights=all_err)\n",

    "sy2, _ = np.histogram(stories_len, bins=n_bins, weights=all_err*all_err)\n",

    "mean = sy / n\n",

    "std = np.sqrt(sy2/n - mean*mean)\n",

    "\n",

    "mean[np.isnan(mean)] = 0\n",

    "\n",

    "#plt.errorbar(e[:max_ind],mean[:max_ind],yerr=std[:max_ind])\n",

    "plt.plot(e[:max_ind],mean[:max_ind],'r.')\n",

    "m, b = np.polyfit(e[:max_ind], mean[:max_ind], 1)\n",

    "plt.plot(e, m*e + b,'-')\n",

    "\n",

    "plt.xlabel('Story large')\n",

    "plt.ylabel('Mean Crossentropy')\n"

   ]

  },

  {

   "cell_type": "markdown",

   "metadata": {

    "collapsed": true

   },

   "source": [

    "Some relation but not so clear"

   ]

  },

  {

   "cell_type": "markdown",

   "metadata": {},

   "source": [

    "### Visualizing neuron activations"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 29,

   "metadata": {

    "collapsed": false

   },

   "outputs": [],

   "source": [

    "from keras import backend as K\n",

    "\n",

    "# Compute activations from first layer for example and n_words\n",

    "get_1_layer_output = K.function([model.layers[0].input,K.learning_phase()],\n",

    "                               [model.layers[1].output])"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 63,

   "metadata": {

    "collapsed": false

   },

   "outputs": [],

   "source": [

    "n_test = 50\n",

    "nlp = English()\n",

    "rec_test_stories = test_stories[9922:9922+n_test]\n",

    "rec_test_facts = test_facts[9922:9922+n_test]\n",

    "inputs_test, answers_test = get_spacy_vectors(rec_test_stories, answer_dict, max_len, nlp)"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 64,

   "metadata": {

    "collapsed": false

   },

   "outputs": [

    {

     "data": {

      "image/png": "iVBORw0KGgoAAAANSUhEUgAABIYAABY1CAYAAAAw8Ek8AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nKjjillY0uEkAAAAASUVORK5CYII=\n",

      "text/plain": [

       "<matplotlib.figure.Figure at 0x7fca04d17f90>"

      ]

     },

     "metadata": {},

     "output_type": "display_data"

    }

   ],

   "source": [

    "# Activations from layer 1\n",

    "n_words = 50\n",

    "example = 0\n",

    "\n",

    "layer_output = get_1_layer_output([inputs_test[example:example+1],0])[0]\n",

    "# Compute tanh of activations of a random cell to keep it in -1 - 1\n",

    "#activation = layer_output.sum(axis=2)\n",

    "#activation = np.tanh(activation)\n",

    "activation = np.tanh(layer_output[:,:,:])\n",

    "# Only considering non zero activation\n",

    "activation = activation[0,-len(rec_test_stories[example][0]):,:]\n",

    "#activation_word = zip(test_stories[example][0:n_words],activation.flatten()[0:n_word])\n",

    "f, ax = plt.subplots(10,figsize=(20,100))\n",

    "start = 21\n",

    "\n",

    "for n in range(start,start+10):\n",

    "    ax[n-start].bar(range(len(rec_test_stories[example][0][0:n_words])),activation[:,n].flatten()[0:n_words])\n",

    "    ax[n-start].set_xticks(range(len(rec_test_stories[example][0][0:n_words])))\n",

    "    _ = ax[n-start].set_xticklabels(rec_test_stories[example][0][0:n_words],rotation='vertical')\n",

    "\n"

   ]

  },

  {

   "cell_type": "markdown",

   "metadata": {},

   "source": [

    "### Predictions on dataset "

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 66,

   "metadata": {

    "collapsed": false

   },

   "outputs": [

    {

     "name": "stdout",

     "output_type": "stream",

     "text": [

      "Prediction for data:\n",

      "Disease: atrial fibrillation or flutter\n",

      "5 most prob. diseases: [u'separation anxiety in children', u'aortic insufficiency', u'ventricular tachycardia', u'pulmonary edema', u'pulmonary embolus']\n",

      "Prediction for data:\n",

      "Disease: attention deficit hyperactivity disorder\n",

      "5 most prob. diseases: [u'attention deficit hyperactivity disorder', u'persistent depressive disorder', u'oppositional defiant disorder', u'failure to thrive', u'seasonal affective disorder']\n",

      "Prediction for data:\n",

      "Disease: atrial fibrillation or flutter\n",

      "5 most prob. diseases: [u'atrial fibrillation or flutter', u'ventricular tachycardia', u'pulmonary embolus', u'arrhythmias', u'unconsciousness first aid']\n",

      "Prediction for data:\n",

      "Disease: attention deficit hyperactivity disorder\n",

      "5 most prob. diseases: [u'attention deficit hyperactivity disorder', u'neuromyotonia', u'systemic lupus erythematosus', u'menopause', u'fibromyalgia']\n",

      "Prediction for data:\n",

      "Disease: athlete s foot\n",

      "5 most prob. diseases: [u'athlete s foot', u'kwashiorkor', u'carbuncle', u'pulmonary actinomycosis', u'acute myeloid leukemia']\n",

      "Prediction for data:\n",

      "Disease: atrial fibrillation or flutter\n",

      "5 most prob. diseases: [u'atrial fibrillation or flutter', u'myocardial contusion', u'pneumonia weakened immune system', u'pulmonary embolus', u'obsessive compulsive disorder']\n",

      "Prediction for data:\n",

      "Disease: attention deficit hyperactivity disorder\n",

      "5 most prob. diseases: [u'attention deficit hyperactivity disorder', u'persistent depressive disorder', u'vascular dementia', u'age related hearing loss', u'oppositional defiant disorder']\n",

      "Prediction for data:\n",

      "Disease: attention deficit hyperactivity disorder\n",

      "5 most prob. diseases: [u'attention deficit hyperactivity disorder', u'oppositional defiant disorder', u'seasonal affective disorder', u'anorexia nervosa', u'language disorder children']\n",

      "Prediction for data:\n",

      "Disease: atrial fibrillation or flutter\n",

      "5 most prob. diseases: [u'atrial fibrillation or flutter', u'claustrophobia', u'ventricular tachycardia', u'cmv pneumonia', u'chronic subdural hematoma']\n",

      "Prediction for data:\n",

      "Disease: attention deficit hyperactivity disorder\n",

      "5 most prob. diseases: [u'attention deficit hyperactivity disorder', u'anxiety disorders in children', u'failure to thrive', u'oppositional defiant disorder', u'anemia caused by low iron children']\n",

      "Prediction for data:\n",

      "Disease: attention deficit hyperactivity disorder\n",

      "5 most prob. diseases: [u'attention deficit hyperactivity disorder', u'oppositional defiant disorder', u'language disorder children', u'failure to thrive', u'dependent personality disorder']\n",

      "Prediction for data:\n",

      "Disease: attention deficit hyperactivity disorder\n",

      "5 most prob. diseases: [u'attention deficit hyperactivity disorder', u'alzheimer disease', u'oppositional defiant disorder', u'developmental co ordination disorder dyspraxia in children', u'personality disorders']\n",

      "Prediction for data:\n",

      "Disease: attention deficit hyperactivity disorder\n",

      "5 most prob. diseases: [u'attention deficit hyperactivity disorder', u'hydrocephalus', u'tay sachs disease', u'clinical depression', u'developmental co ordination disorder dyspraxia in children']\n",

      "Prediction for data:\n",

      "Disease: atrial fibrillation or flutter\n",

      "5 most prob. diseases: [u'atrial fibrillation or flutter', u'wolff parkinson white syndrome', u'insomnia overview', u'panic disorder', u'unconsciousness first aid']\n",

      "Prediction for data:\n",

      "Disease: attention deficit hyperactivity disorder\n",

      "5 most prob. diseases: [u'attention deficit hyperactivity disorder', u'developmental co ordination disorder dyspraxia in children', u'personality disorders', u'clinical depression', u'vascular dementia']\n",

      "Prediction for data:\n",

      "Disease: attention deficit hyperactivity disorder\n",

      "5 most prob. diseases: [u'attention deficit hyperactivity disorder', u'personality disorders', u'pick disease', u'hydrocephalus', u'language disorder children']\n",

      "Prediction for data:\n",

      "Disease: attention deficit hyperactivity disorder\n",

      "5 most prob. diseases: [u'attention deficit hyperactivity disorder', u'oppositional defiant disorder', u'major depression with psychotic features', u'persistent depressive disorder', u'paranoid personality disorder']\n",

      "Prediction for data:\n",

      "Disease: attention deficit hyperactivity disorder\n",

      "5 most prob. diseases: [u'attention deficit hyperactivity disorder', u'alzheimer disease', u'post traumatic stress disorder', u'personality disorders', u'vascular dementia']\n",

      "Prediction for data:\n",

      "Disease: attention deficit hyperactivity disorder\n",

      "5 most prob. diseases: [u'attention deficit hyperactivity disorder', u'oppositional defiant disorder', u'avoidant personality disorder', u'developmental co ordination disorder dyspraxia in children', u'dependent personality disorder']\n",

      "Prediction for data:\n",

      "Disease: athlete s foot\n",

      "5 most prob. diseases: [u'athlete s foot', u'type i tyrosinemia', u'squamous cell skin cancer', u'polymyositis adult', u'erythema multiforme']\n",

      "Prediction for data:\n",

      "Disease: attention deficit hyperactivity disorder\n",

      "5 most prob. diseases: [u'attention deficit hyperactivity disorder', u'oppositional defiant disorder', u'persistent depressive disorder', u'major depression with psychotic features', u'nemaline myopathy']\n",

      "Prediction for data:\n",

      "Disease: athlete s foot\n",

      "5 most prob. diseases: [u'athlete s foot', u'fungal nail infection', u'pubic lice', u'neuroblastoma', u'thrush in men']\n",

      "Prediction for data:\n",

      "Disease: attention deficit hyperactivity disorder\n",

      "5 most prob. diseases: [u'attention deficit hyperactivity disorder', u'clinical depression', u'hydrocephalus', u'developmental co ordination disorder dyspraxia in children', u'personality disorders']\n",

      "Prediction for data:\n",

      "Disease: attention deficit hyperactivity disorder\n",

      "5 most prob. diseases: [u'attention deficit hyperactivity disorder', u'oppositional defiant disorder', u'anorexia nervosa', u'dependent personality disorder', u'developmental co ordination disorder dyspraxia in children']\n",

      "Prediction for data:\n",

      "Disease: athlete s foot\n",

      "5 most prob. diseases: [u'athlete s foot', u'enterobiasis', u'adult still s disease', u'tinea corporis', u'alkaptonuria']\n",

      "Prediction for data:\n",

      "Disease: attention deficit hyperactivity disorder\n",

      "5 most prob. diseases: [u'attention deficit hyperactivity disorder', u'language disorder children', u'alzheimer disease', u'personality disorders', u'seasonal affective disorder']\n",

      "Prediction for data:\n",

      "Disease: attention deficit hyperactivity disorder\n",

      "5 most prob. diseases: [u'attention deficit hyperactivity disorder', u'oppositional defiant disorder', u'adrenocortical carcinoma', u'anorexia nervosa', u'developmental co ordination disorder dyspraxia in children']\n",

      "Prediction for data:\n",

      "Disease: attention deficit hyperactivity disorder\n",

      "5 most prob. diseases: [u'attention deficit hyperactivity disorder', u'alzheimer disease', u'developmental co ordination disorder dyspraxia in children', u'oppositional defiant disorder', u'adrenocortical carcinoma']\n",

      "Prediction for data:\n",

      "Disease: attention deficit hyperactivity disorder\n",

      "5 most prob. diseases: [u'attention deficit hyperactivity disorder', u'developmental reading disorder', u'alzheimer disease', u'vascular dementia', u'developmental co ordination disorder dyspraxia in children']\n",

      "Prediction for data:\n",

      "Disease: attention deficit hyperactivity disorder\n",

      "5 most prob. diseases: [u'attention deficit hyperactivity disorder', u'dependent personality disorder', u'post traumatic stress disorder', u'vascular dementia', u'alzheimer disease']\n",

      "Prediction for data:\n",

      "Disease: attention deficit hyperactivity disorder\n",

      "5 most prob. diseases: [u'attention deficit hyperactivity disorder', u'oppositional defiant disorder', u'stuttering', u'autism spectrum disorder', u'developmental co ordination disorder dyspraxia in children']\n",

      "Prediction for data:\n",

      "Disease: attention deficit hyperactivity disorder\n",

      "5 most prob. diseases: [u'attention deficit hyperactivity disorder', u'oppositional defiant disorder', u'language disorder children', u'personality disorders', u'adrenocortical carcinoma']\n",

      "Prediction for data:\n",

      "Disease: attention deficit hyperactivity disorder\n",

      "5 most prob. diseases: [u'attention deficit hyperactivity disorder', u'oppositional defiant disorder', u'adrenocortical carcinoma', u'tricho hepato enteric syndrome', u'seasonal affective disorder']\n",

      "Prediction for data:\n",

      "Disease: attention deficit hyperactivity disorder\n",

      "5 most prob. diseases: [u'attention deficit hyperactivity disorder', u'alzheimer disease', u'schizophrenia', u'personality disorders', u'post traumatic stress disorder']\n",

      "Prediction for data:\n",

      "Disease: athlete s foot\n",

      "5 most prob. diseases: [u'geographic tongue', u'athlete s foot', u'polymyositis adult', u'ascher s syndrome', u'gynecomastia']\n",

      "Prediction for data:\n",

      "Disease: attention deficit hyperactivity disorder\n",

      "5 most prob. diseases: [u'attention deficit hyperactivity disorder', u'personality disorders', u'paranoid personality disorder', u'developmental co ordination disorder dyspraxia in children', u'alzheimer disease']\n",

      "Prediction for data:\n",

      "Disease: atrial fibrillation or flutter\n",

      "5 most prob. diseases: [u'atrial fibrillation or flutter', u'claustrophobia', u'ventricular tachycardia', u'unconsciousness first aid', u'hospital acquired pneumonia']\n",

      "Prediction for data:\n",

      "Disease: atrial fibrillation or flutter\n",

      "5 most prob. diseases: [u'atrial fibrillation or flutter', u'parkinson disease', u'chronic motor tic disorder', u'peritonitis', u'wolff parkinson white syndrome']\n",

      "Prediction for data:\n",

      "Disease: attention deficit hyperactivity disorder\n",

      "5 most prob. diseases: [u'attention deficit hyperactivity disorder', u'developmental co ordination disorder dyspraxia in children', u'tay sachs disease', u'personality disorders', u'tourette s syndrome']\n",

      "Prediction for data:\n",

      "Disease: atrial fibrillation or flutter\n",

      "5 most prob. diseases: [u'atrial fibrillation or flutter', u'ventricular tachycardia', u'claustrophobia', u'cmv pneumonia', u'unconsciousness first aid']\n",

      "Prediction for data:\n",

      "Disease: attention deficit hyperactivity disorder\n",

      "5 most prob. diseases: [u'attention deficit hyperactivity disorder', u'personality disorders', u'developmental co ordination disorder dyspraxia in children', u'tourette s syndrome', u'failure to thrive']\n",

      "Prediction for data:\n",

      "Disease: attention deficit hyperactivity disorder\n",

      "5 most prob. diseases: [u'attention deficit hyperactivity disorder', u'developmental co ordination disorder dyspraxia in children', u'personality disorders', u'angelman syndrome', u'clinical depression']\n",

      "Prediction for data:\n",

      "Disease: attention deficit hyperactivity disorder\n",

      "5 most prob. diseases: [u'attention deficit hyperactivity disorder', u'clinical depression', u'hydrocephalus', u'developmental co ordination disorder dyspraxia in children', u'personality disorders']\n",

      "Prediction for data:\n",

      "Disease: attention deficit hyperactivity disorder\n",

      "5 most prob. diseases: [u'attention deficit hyperactivity disorder', u'persistent depressive disorder', u'chronic traumatic encephalopathy', u'failure to thrive', u'oppositional defiant disorder']\n",

      "Prediction for data:\n",

      "Disease: attention deficit hyperactivity disorder\n",

      "5 most prob. diseases: [u'attention deficit hyperactivity disorder', u'vascular dementia', u'hydrocephalus', u'creutzfeldt jakob disease', u'tay sachs disease']\n",

      "Prediction for data:\n",

      "Disease: attention deficit hyperactivity disorder\n",

      "5 most prob. diseases: [u'attention deficit hyperactivity disorder', u'developmental co ordination disorder dyspraxia in children', u'language disorder children', u'failure to thrive', u'vascular dementia']\n",

      "Prediction for data:\n",

      "Disease: atrial fibrillation or flutter\n",

      "5 most prob. diseases: [u'aortic insufficiency', u'duchenne muscular dystrophy', u'premenstrual syndrome', u'cmv pneumonia', u'atrial fibrillation or flutter']\n",

      "Prediction for data:\n",

      "Disease: atrial fibrillation or flutter\n",

      "5 most prob. diseases: [u'pneumonia adults community acquired', u'ventricular tachycardia', u'acute mountain sickness', u'narcolepsy', u'parathyroid adenoma']\n",

      "Prediction for data:\n",

      "Disease: attention deficit hyperactivity disorder\n",

      "5 most prob. diseases: [u'attention deficit hyperactivity disorder', u'oppositional defiant disorder', u'developmental co ordination disorder dyspraxia in children', u'anorexia nervosa', u'seasonal affective disorder']\n",

      "Prediction for data:\n",

      "Disease: atrial fibrillation or flutter\n",

      "5 most prob. diseases: [u'atrial fibrillation or flutter', u'somatic symptom disorder', u'anemia of chronic disease', u'claustrophobia', u'heart attack first aid']\n"

     ]

    }

   ],

   "source": [

    "print_n = 50\n",

    "\n",

    "choose = np.random.choice(inputs_test.shape[0],print_n,replace=False)\n",

    "\n",

    "predictions = model.predict(inputs_test[choose])\n",

    "\n",

    "for k,pred in enumerate(predictions):\n",

    "    prediction = np.argsort(pred)[-5:][::-1]\n",

    "    pred_words = [answer_dict.keys()[answer_dict.values().index(pred)] for pred in prediction]\n",

    "    print('Prediction for data:')\n",

    "    #print(rec_test_facts[choose[k]][0])\n",

    "    print('Disease: {0}'.format(rec_test_stories[choose[k]][1]))\n",

    "    print('5 most prob. diseases: {0}'.format(pred_words))"

   ]

  },

  {

   "cell_type": "markdown",

   "metadata": {

    "collapsed": false

   },

   "source": [

    "### Trying predictions on self-made symptoms"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 34,

   "metadata": {

    "collapsed": false

   },

   "outputs": [],

   "source": [

    "facts = [[\n",

    "    #'acne'\n",

    "    u'oily skin',\n",

    "    u'painful touch skin',\n",

    "    u'face affected almost everywhere',\n",

    "    u'chest affected',\n",

    "    u'some blackheads',\n",

    "    u'a lot of papules',\n",

    "    u'papules',\n",

    "    u'nodules',\n",

    "    u'cysts'\n",

    "    ],\n",

    "    #'abdominal aortic aneurysm'\n",

    "    [u'pulsating feeling in stomach',\n",

    "    u'persistent back pain',\n",

    "    u'abdominal pain',\n",

    "    u'severe pain in the middle abdomen',\n",

    "    u'dizziness',\n",

    "    u'clammy skin',\n",

    "    u'tachycardia',\n",

    "    u'loss of consciousness'],\n",

    "    #'brain abscess'\n",

    "    [u'symptoms for two weeks',\n",

    "     u'headache severe, cannot be relieved by painkillers',\n",

    "     u'confusion and irritability',\n",

    "     u'fever',\n",

    "     u'seizures',\n",

    "     u'vomiting and nausea',\n",

    "     u'changes in vision',\n",

    "     u'muscle weakness'    \n",

    "    ],\n",

    "    #'brain abscess'\n",

    "    # This case is discovered only using the second fact ... which is very bad ... is not identifying the important first \n",

    "    # fact at all .. maybe we should invert the order of all the facts?\n",

    "    # It gives a 'LOT OF IMPORTANCE TO LAST FACTS'\n",

    "    [u'modifications in vision such as blur grey of vision or double vision due to the putting pressure on the eye nerve',\n",

    "     u'if you or person you know experiences any of these symptoms phone 999 now and ask for an ambulance'],\n",

    "    #'acid reflux',\n",

    "    [u'uncomfortable burning sensation in the chest',\n",

    "     u'felt below your breastbone',\n",

    "     u'worse after eating',\n",

    "     u'pain when bending over or lying down',\n",

    "     u'stomach contents are brought back up into throat and mouth',\n",

    "     u'stomach acid irritating your airway',\n",

    "     u'tooth decay',\n",

    "     u'a persistent cough or wheezing',\n",

    "     u'sore throat',\n",

    "     u'pain when swallowing'\n",

    "    ],\n",

    "    # 'alcohol-related liver disease'\n",

    "    [u'confusion and memory problems',\n",

    "     u'vomiting blood and black',\n",

    "     u'a tendency to bleed more easily such as frequent bleeding gums',\n",

    "     u'increased sensitivity to alcohol and drugs',\n",

    "     u'Have you ever felt guilty about your drinking',\n",

    "     u'if you answer yes to one or more of the questions you may have an alcohol problem',\n",

    "     u'see your gp as soon as possible if you have symptoms of advanced arld'\n",

    "    ],\n",

    "    #'agoraphobia'\n",

    "    [\n",

    "     u'unable to leave the house',\n",

    "     u'anxiety',\n",

    "     u'the physical symptoms of agoraphobia can be similar to those of a panic attack',\n",

    "     u'rapid heartbeat',\n",

    "     u'feeling hot and sweaty',\n",

    "     u'rapid breathing',\n",

    "     u'difficulty swallowing',\n",

    "     u'diarrhoea',\n",

    "     u'dizziness',\n",

    "     u'feeling faint',\n",

    "     u'avoiding being far away from home',\n",

    "     u'thoughts of suicide or self-harm'\n",

    "    ],\n",

    "    # 'ais'\n",

    "    [u'girls will not have a womb or ovaries and will be unable to get pregnant',\n",

    "     u'hypospadias where the hole that carries urine out of the body is on the underside of the penis rather than at the end',\n",

    "     u'partially undescended testicles',\n",

    "     u'a very small penis or an enlarged clitoris',\n",

    "     u'develop breasts and have growth spurts as normal, although she may end up slightly taller than usual for a girl',\n",

    "     u'develop little or no pubic and underarm hair'\n",

    "    ],\n",

    "    #'atrial fibrillation'\n",

    "    [u'chest pain',\n",

    "     u'feeling faint or lightheaded',\n",

    "     u'breathlessness',\n",

    "     u'tiredness and being less able to exercise',\n",

    "     u'as well as an irregular heartbeat your heart may also beat very fast',\n",

    "     u'heart palpitations',\n",

    "     u'tiredness and feeling lethargic to ageing',\n",

    "     u'you should see your gp immediately if you notice a sudden change in your heartbeat and experience chest pain'      \n",

    "    ],\n",

    "    #'adhd'\n",

    "    [u'problems such as difficulties with relationships, social interaction, drugs and crime',\n",

    "     u'hard to find and stay in a job',\n",

    "     u'obsessive compulsive disorder a condition that causes obsessive thoughts and compulsive behaviour',\n",

    "     u'bipolar disorder',\n",

    "     u'conditions in which an individual differs significantly from an average person in terms of how they think, perceive feel or relate to others',\n",

    "     u'extreme impatience',\n",

    "     u'taking risks in activities',\n",

    "     u'inability to deal with stress',\n",

    "     u'difficulty keeping quiet and speaking out of turn',\n",

    "     u'forgetfulness',\n",

    "     u'poor organisational skills',\n",

    "     u'inability to focus or prioritise',\n",

    "     u'poor organisational skills',\n",

    "     u'little or no sense of danger'\n",

    "    ]\n",

    "    ]\n",

    "diseases = ['acne','abdominal aortic aneurysm','brain abscess','brain abscess','acid reflux',\n",

    "            'alcohol-related liver disease','agoraphobia','ais','atrial fibrillation','adhd']"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 35,

   "metadata": {

    "collapsed": false

   },

   "outputs": [

    {

     "name": "stdout",

     "output_type": "stream",

     "text": [

      "Get word vectors for input\n",

      "Prediction for data:\n",

      "Disease: acne\n",

      "5 most prob. diseases: [u'acne', u'genital warts', u'scarlet fever', u'erythema multiforme', u'measles']\n",

      "Prediction for data:\n",

      "Disease: abdominal aortic aneurysm\n",

      "5 most prob. diseases: [u'pulmonary actinomycosis', u'mucormycosis', u'sleeping sickness', u'acute myeloid leukemia', u'bile duct obstruction']\n",

      "Prediction for data:\n",

      "Disease: brain abscess\n",

      "5 most prob. diseases: [u'serotonin syndrome', u'alcoholic ketoacidosis', u'brain abscess', u'barbiturate intoxication and overdose', u'propane poisoning']\n",

      "Prediction for data:\n",

      "Disease: brain abscess\n",

      "5 most prob. diseases: [u'brain abscess', u'conversion disorder', u'labyrinthine fistula', u'malignant brain tumour cancerous', u'coats disease']\n",

      "Prediction for data:\n",

      "Disease: acid reflux\n",

      "5 most prob. diseases: [u'gastroesophageal reflux disease', u'dysphagia swallowing problems', u'pulmonary embolus', u'fire ants', u'thrombophilia']\n",

      "Prediction for data:\n",

      "Disease: alcohol-related liver disease\n",

      "5 most prob. diseases: [u'bronchitis acute', u'pneumonia adults community acquired', u'stomach cancer', u'sunburn', u'esophageal cancer']\n",

      "Prediction for data:\n",

      "Disease: agoraphobia\n",

      "5 most prob. diseases: [u'agoraphobia', u'social anxiety disorder social phobia', u'acute mountain sickness', u'unconsciousness first aid', u'brief psychotic disorder']\n",

      "Prediction for data:\n",

      "Disease: ais\n",

      "5 most prob. diseases: [u'cleft lip and palate', u'pyogenic granuloma', u'stork bite', u'caput succedaneum', u'androgen insensitivity syndrome']\n",

      "Prediction for data:\n",

      "Disease: atrial fibrillation\n",

      "5 most prob. diseases: [u'generalized anxiety disorder', u'mcadd', u'bronchitis acute', u'pneumonia adults community acquired', u'diabetic ketoacidosis']\n",

      "Prediction for data:\n",

      "Disease: adhd\n",

      "5 most prob. diseases: [u'delirium', u'intellectual disability', u'alzheimer disease', u'major depression', u'schizoaffective disorder']\n"

     ]

    }

   ],

   "source": [

    "print('Get word vectors for input')\n",

    "for k,fact in enumerate(facts):\n",

    "    facts_list = fact\n",

    "\n",

    "    facts_list = [fact.split(' ') + ['.'] for fact in facts_list]\n",

    "    facts_list = [facts_list]\n",

    "    x = [reduce(lambda x,y: x + y, map(list,fact)) for fact in facts_list]\n",

    "\n",

    "    #x_vectors = inputs_test[0].reshape(1,inputs_test[0].shape[0],inputs_test[1].shape[1])\n",

    "    x_vectors = get_spacy_vectors([[x[0],None]], None, max_len, nlp)\n",

    "\n",

    "    pred = model.predict(x_vectors[0])\n",

    "\n",

    "    prediction = np.argsort(pred[0])[-5:][::-1]\n",

    "    pred_words = [answer_dict.keys()[answer_dict.values().index(pred)] for pred in prediction]\n",

    "    print('Prediction for data:')\n",

    "    #print(x[0])\n",

    "    print('Disease: {0}'.format(diseases[k]))\n",

    "    print('5 most prob. diseases: {0}'.format(pred_words))"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 15,

   "metadata": {

    "collapsed": false

   },

   "outputs": [],

   "source": [

    "# Save results ordered by how much the network was wrong\n",

    "# Ordering error from bigger to smaller\n",

    "\n",

    "order_err = np.argsort(all_err)[::-1]\n",

    "predictions = model.predict(inputs_test)\n",

    "most_prob = []\n",

    "\n",

    "for k,pred in enumerate(predictions):\n",

    "    prediction = np.argsort(pred)[-5:][::-1]\n",

    "    pred_words = [answer_dict.keys()[answer_dict.values().index(pred)] for pred in prediction]\n",

    "    most_prob.append(pred_words)\n"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 36,

   "metadata": {

    "collapsed": false

   },

   "outputs": [],

   "source": [

    "# Writing to file\n",

    "output_file = 'logs/output_ordered.txt'\n",

    "with open(output_file,'w') as fil:\n",

    "    for k,indx in enumerate(order_err):\n",

    "        facts = test_facts[indx]\n",

    "        for fact in facts[0]:\n",

    "            fil.write(u' '.join(fact).encode('utf-8') + '\\n')\n",

    "        fil.write('Disease: ' + facts[1].encode('utf-8') + '\\n')\n",

    "        fil.write('5 More prob.: ' + str(most_prob[indx]) + '\\n\\n')"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": null,

   "metadata": {

    "collapsed": true

   },

   "outputs": [],

   "source": []

  }

 ],

 "metadata": {

  "kernelspec": {

   "display_name": "Python 2",

   "language": "python",

   "name": "python2"

  },

  "language_info": {

   "codemirror_mode": {

    "name": "ipython",

    "version": 2

   },

   "file_extension": ".py",

   "mimetype": "text/x-python",

   "name": "python",

   "nbconvert_exporter": "python",

   "pygments_lexer": "ipython2",

   "version": "2.7.11"

  }

 },

 "nbformat": 4,

 "nbformat_minor": 0

}