{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Indexing and Broadcasting in Numpy"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Embedding mini-languages in Python has a long tradition. In this section of the tutorial, we will explore some examples of this practice."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "The first example we will consider is so-called *broadcasting* in numpy. It may look shallow at first sight, but it and its associated operations constitute a considerable subset of the array programming language APL."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "import numpy as np"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "collapsed": false
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "[0 1 2 3]\n",
            "[ 0 10 20]\n"
          ]
        }
      ],
      "source": [
        "a = np.arange(4)\n",
        "b = np.arange(3) * 10\n",
        "print(a)\n",
        "print(b)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "collapsed": false
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "(4, 1)"
            ]
          },
          "execution_count": 7,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "a.reshape(-1, 1).shape"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "collapsed": false
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "array([[ 0, 10, 20],\n",
              "       [ 1, 11, 21],\n",
              "       [ 2, 12, 22],\n",
              "       [ 3, 13, 23]])"
            ]
          },
          "execution_count": 10,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "x = a.reshape(-1, 1) + b\n",
        "x"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "collapsed": false
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "array([ 6, 46, 86])"
            ]
          },
          "execution_count": 12,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "np.sum(x, axis=0)"
      ]
    }
  ],
  "metadata": {},
  "nbformat": 4,
  "nbformat_minor": 0
}