ardoi/gist:114257dd2c2f7cd907a4

## gistfile1.txt
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "%pylab inline\n",
    "import numpy as np\n",
    "import datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "days = 30\n",
    "today = datetime.datetime.today()\n",
    "dates = [today + datetime.timedelta(days=x) for x in range(0, days, 4)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#convert dates to days since start\n",
    "days_num = [(date - today).days for date in dates]\n",
    "#or using mdates.date2num"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data = np.arange(len(dates))*2 + 5*np.random.rand(len(dates))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([datetime.datetime(2015, 4, 17, 13, 49, 1, 541893),\n",
       "  datetime.datetime(2015, 4, 21, 13, 49, 1, 541893),\n",
       "  datetime.datetime(2015, 4, 25, 13, 49, 1, 541893),\n",
       "  datetime.datetime(2015, 4, 29, 13, 49, 1, 541893),\n",
       "  datetime.datetime(2015, 5, 3, 13, 49, 1, 541893),\n",
       "  datetime.datetime(2015, 5, 7, 13, 49, 1, 541893),\n",
       "  datetime.datetime(2015, 5, 11, 13, 49, 1, 541893),\n",
       "  datetime.datetime(2015, 5, 15, 13, 49, 1, 541893)],\n",
       " [0, 4, 8, 12, 16, 20, 24, 28],\n",
       " array([  4.39314161,   5.412016  ,   4.03196394,   6.48156241,\n",
       "          8.00741845,  12.72411756,  16.17466089,  14.24425011]))"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dates, days_num, data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#fit data\n",
    "pf = np.poly1d(np.polyfit(days_num,data,1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "extra_dates = [today + datetime.timedelta(days=x) for x in range(0, days*2)]\n",
    "extra_days_num = [(date - today).days for date in extra_dates]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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LuiRJYxdVRFTxMuAq4FZgcwcvael6fbbjU4ELgSsoURNQLiVxCSXvZUOWEjXhni9J6j9R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\nAAAj+gd/rZCEWfDaGwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x112424310>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure(figsize=(10,8))\n",
    "plot(dates, data, 'o')\n",
    "plot(extra_dates, pf(extra_days_num))\n",
    "gcf().autofmt_xdate()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}