Fibonacci sequence approximates km/mile conversion

fib_miles_km.ipynb

{
 "metadata": {
  "name": "",
  "signature": "sha256:ab61aea63e18fbed6daf8dbc9649fb6bc4ac32bb4b7bf20e885a5320ef4f8fad"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%matplotlib inline"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 9
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "KM_PER_MILE=1.609344\n",
      "N_FIBS=10"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 10
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import matplotlib.pyplot as plt\n",
      "from itertools import islice\n",
      "import numpy as np"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 11
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def fib():\n",
      "    a, b = 1, 1\n",
      "    while True:\n",
      "        yield a, b\n",
      "        a, b = b, (a+b)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 12
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fibs = np.matrix(list(islice(fib(), N_FIBS)))\n",
      "max_miles = fibs[N_FIBS-1, 0]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 13
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.figure(figsize=(10,6))\n",
      "plt.scatter(map(int, fibs[:,0]), map(int, fibs[:,1]))\n",
      "a= plt.plot([0, max_miles], [0, KM_PER_MILE*max_miles])\n",
      "plt.xlabel('Miles')\n",
      "plt.ylabel('KM');"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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       "text": [
        "<matplotlib.figure.Figure at 0x10c959b10>"
       ]
      }
     ],
     "prompt_number": 14
    }
   ],
   "metadata": {}
  }
 ]
}