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  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# - compatibility with Python 3\n",
      "from __future__ import print_function  # print('me') instead of print 'me'\n",
      "from __future__ import division  # 1/2 == 0.5, not 0"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# - show figures inside the notebook\n",
      "%matplotlib inline"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# - import common modules\n",
      "import numpy as np  # the Python array package\n",
      "import matplotlib.pyplot as plt  # the Python plotting package"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Reshaping with `np.newaxis`"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "We often want to reshape, adding a single axis length 1.  For example, let's say we had a 1d array:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "arr_1d = np.array([3, 2, 5])\n",
      "arr_1d"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 4,
       "text": [
        "array([3, 2, 5])"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "We may want to make this into a 2D column vector array, with shape `(3, 1)`.  Obviously we could do that with `reshape`:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "col_vector = arr_1d.reshape(3, 1)\n",
      "col_vector"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 5,
       "text": [
        "array([[3],\n",
        "       [2],\n",
        "       [5]])"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "This need, of adding a single length 1 dimension, is so common, that numpy has a fancy way of doing that.  To do this, you use the constant `np.newaxis` inside a slicing operation, to return the requested slice, but with an extra length 1 axis in the position you specified:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "arr_1d[:, np.newaxis]  # Add length 1 axis to end, make column vector"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 6,
       "text": [
        "array([[3],\n",
        "       [2],\n",
        "       [5]])"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "arr_1d[np.newaxis, :]  # Add length 1 axis to start, make row vector"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 7,
       "text": [
        "array([[3, 2, 5]])"
       ]
      }
     ],
     "prompt_number": 7
    }
   ],
   "metadata": {}
  }
 ]
}