PredictGroup.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "((6502, 3, 12), (6502,))\n"
     ]
    }
   ],
   "source": [
    "import pickle as pkl\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "X = pkl.load(open('/data/SPRINT/X_processed.pkl', 'rb'))\n",
    "y = pkl.load(open('/data/SPRINT/y_processed.pkl', 'rb'))\n",
    "\n",
    "print(X.shape, y.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.94223107569721121"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.metrics import accuracy_score\n",
    "\n",
    "training_size = 6000\n",
    "\n",
    "X_train = X[:training_size]\n",
    "y_train = y[:training_size]\n",
    "\n",
    "X_test = X[training_size:]\n",
    "y_test = y[training_size:]\n",
    "\n",
    "X_train = X_train.reshape((X_train.shape[0], -1))\n",
    "X_test = X_test.reshape((X_test.shape[0], -1))\n",
    "\n",
    "classifier = RandomForestClassifier()\n",
    "y_pred = classifier.fit(X_train, y_train).predict(X_test)\n",
    "\n",
    "accuracy_score(y_test, y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(array([59]),)\n"
     ]
    }
   ],
   "source": [
    "noise = np.random.normal(0, 1, 600)\n",
    "plt.hist(noise, bins=30)\n",
    "print(np.where(abs(noise)<0.01))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#directory = './output/2.0_0.001_200_0.002_100/'\n",
    "#directory = './output/4.0_0.0001_500_0.002_100/'\n",
    "directory = '/data/SPRINT/nonprivate/'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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YsejcuTMOHz6sfdeRkZEoLS2tc97lhgEbERFd0ZoaaIVKXl4ekpOTA7alpqZq73Nzc7Fu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2SGC8T1yTLjbLZBe9ge3rePXzQ18ehB9NDG5Bit/laWjl/Km/Vv8squV7jmuGtw2QYOBnz9xK9z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\nAhsAAEDMEdgAAABi7v8BHWqikykfca0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fb5eacdfb50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import h5py\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "\n",
    "%matplotlib inline\n",
    "plt.figure(figsize=(10,10))\n",
    "\n",
    "hist = pkl.load(open(directory + 'acgan-history.pkl', 'rb'))\n",
    "losses = ['loss', 'generation_loss', 'auxiliary_loss']\n",
    "\n",
    "for p in ['train', 'test']:\n",
    "    for g in ['discriminator', 'generator']:\n",
    "        hist[p][g] = pd.DataFrame(hist[p][g], columns=losses)\n",
    "\n",
    "for p in ['train', 'test']:\n",
    "    for g in ['discriminator', 'generator']:\n",
    "        plt.plot(hist[p][g]['generation_loss'], label='{} ({})'.format(g, p))\n",
    "\n",
    "# get the NE and show as an equilibrium point\n",
    "plt.hlines(-np.log(0.5), 0, hist[p][g]['generation_loss'].shape[0], label='Nash Equilibrium')\n",
    "plt.legend()\n",
    "plt.xlabel('Epoch')\n",
    "plt.ylabel(r'$L_s$')\n",
    "\n",
    "plt.show()\n",
    "\n",
    "# for p in hist['privacy']:\n",
    "#     print(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Transfer Learning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/data/SPRINT/nonprivate/params_generator_epoch_000.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_001.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_002.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_003.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_004.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_005.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_006.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_007.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_008.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_009.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_010.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_011.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_012.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_013.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_014.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_015.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_016.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_017.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_018.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_019.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_020.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_021.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_022.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_023.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_024.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_025.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_026.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_027.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_028.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_029.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_030.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_031.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_032.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_033.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_034.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_035.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_036.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_037.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_038.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_039.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_040.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_041.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_042.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_043.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_044.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_045.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_046.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_047.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_048.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_049.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_050.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_051.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_052.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_053.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_054.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_055.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_056.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_057.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_058.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_059.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_060.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_061.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_062.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_063.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_064.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_065.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_066.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_067.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_068.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_069.h5\n",
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      "/data/SPRINT/nonprivate/params_generator_epoch_383.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_384.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_385.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_386.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_387.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_388.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_389.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_390.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_391.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_392.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_393.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_394.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_395.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_396.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_397.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_398.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_399.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_400.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_401.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_402.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_403.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_404.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_405.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_406.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_407.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_408.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_409.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_410.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_411.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_412.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_413.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_414.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_415.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_416.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_417.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_418.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_419.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_420.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_421.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_422.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_423.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_424.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_425.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_426.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_427.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_428.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_429.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_430.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_431.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_432.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_433.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_434.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_435.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_436.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_437.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_438.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_439.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_440.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_441.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_442.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_443.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_444.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_445.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_446.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_447.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_448.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_449.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_450.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_451.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_452.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_453.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_454.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_455.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_456.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_457.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_458.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_459.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_460.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_461.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_462.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_463.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_464.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_465.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_466.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_467.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_468.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_469.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_470.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_471.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_472.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_473.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_474.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_475.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_476.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_477.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_478.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_479.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_480.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_481.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_482.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_483.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_484.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_485.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_486.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_487.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_488.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_489.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_490.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_491.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_492.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_493.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_494.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_495.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_496.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_497.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_498.h5\n",
      "/data/SPRINT/nonprivate/params_generator_epoch_499.h5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "os.environ[\"CUDA_DEVICE_ORDER\"]=\"PCI_BUS_ID\"   # see issue #152\n",
    "os.environ[\"CUDA_VISIBLE_DEVICES\"]=\"0\"\n",
    "\n",
    "acgan = __import__('ac_gan')\n",
    "\n",
    "from glob import glob\n",
    "from keras.models import load_model\n",
    "from sklearn import linear_model\n",
    "\n",
    "latent_size = 100\n",
    "\n",
    "\n",
    "lr_clf = linear_model.LogisticRegression()\n",
    "transfer_clf = RandomForestClassifier()\n",
    "\n",
    "mean_scores = []\n",
    "lr_scores = []\n",
    "#directory = './output/p' + str(9) + '_8.0_0.0001_500_0.002_100/'\n",
    "# directory = './output/acgan_500_0.0002_100/'\n",
    "\n",
    "for i in range(0, 500):\n",
    "    gen_name = sorted(glob(directory + 'params_generator*'))[i]\n",
    "    print(gen_name)\n",
    "    g = load_model(gen_name)\n",
    "\n",
    "    generate_count = training_size\n",
    "\n",
    "    noise = np.random.uniform(-1, 1, (generate_count, latent_size))\n",
    "    sampled_labels = np.random.randint(0, 2, generate_count)\n",
    "    generated_images = g.predict([noise, sampled_labels.reshape((-1, 1))], verbose=0)\n",
    "\n",
    "    gen_X_train = np.reshape(generated_images, (training_size, 3, 12))\n",
    "    gen_X_train = gen_X_train.astype(int)\n",
    "    gen_X_train = gen_X_train.clip(min=0)\n",
    "\n",
    "    gen_X_train = gen_X_train.reshape(generate_count, -1)\n",
    "    gen_y_train = sampled_labels\n",
    "\n",
    "\n",
    "    mean_scores.append(accuracy_score(y_train, transfer_clf.fit(gen_X_train, gen_y_train).predict(X_train)))\n",
    "    lr_scores.append(accuracy_score(y_train, lr_clf.fit(gen_X_train, gen_y_train).predict(X_train)))\n",
    "pkl.dump({'rf': mean_scores, 'lr': lr_scores}, open(directory + 'train_epoch_scores.p', 'wb'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PCA plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1000, 36)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x7f21ac23d850>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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bmkcia6fYmyCUFDjMFNgK9/sO+lLK+wh+Z5/PwdfPXctIXz2kYyqsVXHYfBSK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4Grgd8WF4rIIuD9wCLgncA9IiLe2/8JfNwY0wK0iMg7xmlD2bJu3brpNuGEqWTbQe2fbtT+ymZc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\nKgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f23db4d9e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.decomposition import PCA\n",
    "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n",
    "\n",
    "plot_count = 500\n",
    "X_pca = np.concatenate((gen_X_train[:plot_count], X_train[:plot_count]))\n",
    "print(X_pca.shape)\n",
    "\n",
    "y = np.array([1] * plot_count + [0] * plot_count)\n",
    "\n",
    "pca = PCA(n_components=2)\n",
    "X_r = pca.fit(X_pca).transform(X_pca)\n",
    "\n",
    "target_names = ['Fake', 'Real']\n",
    "colors = ['navy', 'darkorange']\n",
    "lw = 2\n",
    "\n",
    "for color, i, target_name in zip(colors, [0, 1], target_names):\n",
    "    plt.scatter(X_r[y == i, 0], X_r[y == i, 1], color=color, alpha=.8, lw=lw,\n",
    "                label=target_name)\n",
    "plt.legend(loc='best', shadow=False, scatterpoints=1)\n",
    "\n",
    "plt.title('PCA of Real vs. Fake')"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}