{
 "metadata": {
  "name": "",
  "signature": "sha256:ae0c5879375aba7ba295a93ec996b322903ae601ca21ee18f4de15b4258c0fc2"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "subplot(1,2,1)\n",
      "plot([1.,1.],[0,3.])\n",
      "ax=gca()\n",
      "ax.spines['left'].set_position('zero')\n",
      "ax.spines['right'].set_color('none')\n",
      "ax.spines['bottom'].set_position('zero')\n",
      "ax.spines['top'].set_color('none')\n",
      "#ax.spines['left'].set_smart_bounds(True)\n",
      "#ax.spines['bottom'].set_smart_bounds(True)\n",
      "ax.xaxis.set_ticks_position('bottom')\n",
      "ax.yaxis.set_ticks_position('left')\n",
      "xlim([-2.,2.])\n",
      "ylim([-1.,3.5])\n",
      "\n",
      "subplot(1,2,2)\n",
      "plot([-10.,10.],[0,0.1])\n",
      "ax=gca()\n",
      "xlim([-2.,2.])\n",
      "ylim([-1.,3.5])\n",
      "\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 14,
       "text": [
        "(-1.0, 3.5)"
       ]
      },
      {
       "metadata": {
        "png": {
         "height": 255,
         "width": 367
        }
       },
       "output_type": "display_data",
       "png": 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I4VuSJEmKiOFbkiRJiojhW5IkSYqI4VuSJEmKiOFbkiRJiojhW5IkSYqI4VuS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\nKT73zgAeAt4GDgAthD3f6c2rWrjs+ZY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DDb6ug7jo1jv+MDEyQcujCqT0GvBpoi/0gmR5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\nkiRJkiRJkiRJkiRJkiRJkiRJkqSm/T8t6kebkYQytwAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x108de6a50>"
       ]
      }
     ],
     "prompt_number": 14
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}