{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Uppsetning\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "A_images = np.load('A_images.npy')\n",
    "A_labels = np.load('A_labels.npy')\n",
    "B_images = np.load('B_images.npy')\n",
    "B_labels = np.load('B_labels.npy')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Vinnum aðeins með gögnin til að koma þeim á þægilegra form"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "N = A_images.shape[0]\n",
    "data = A_images.transpose(1,2,0).reshape(-1,N).transpose()\n",
    "# data er 10000 x 784 fylki\n",
    "print(data.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "x = data[0] # fyrsta mynd, data[0] er fyrsta röðin í fylkinu\n",
    "def plot_img(x):\n",
    "    fig = plt.imshow(x.reshape(28,28),cmap=plt.get_cmap('gray'), interpolation='nearest', vmin=0,vmax=255,)\n",
    "    fig.axes.get_xaxis().set_visible(False)\n",
    "    fig.axes.get_yaxis().set_visible(False)\n",
    "plot_img(x)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Liður A\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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   "file_extension": ".py",
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