{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "import iris\n",
    "import numpy as np\n",
    "iris.FUTURE.netcdf_promote = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TMAX / (degrees_c)                  (time: 11874)\n",
      "     Dimension coordinates:\n",
      "          time                           x\n",
      "     Scalar coordinates:\n",
      "          elevation: 25.3 m\n",
      "          latitude: 51.478 degrees\n",
      "          longitude: -0.461 degrees\n",
      "     Attributes:\n",
      "          Conventions: CF-1.5\n",
      "          StationID: UKM00003772\n",
      "          StationName: HEATHROW\n"
     ]
    }
   ],
   "source": [
    "cube = iris.load_cube('/Users/scott/DATA/StationData/GHCN-D/NetCDFs/UKM00003772_HEATHROW_TMAX.nc')\n",
    "print cube"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DimCoord([1973-01-01 00:00:00, 1973-01-02 00:00:00, 1973-01-03 00:00:00, ...,\n",
      "       2016-01-10 00:00:00, 2016-01-11 00:00:00, 2016-07-13 00:00:00], standard_name=u'time', calendar=u'gregorian', var_name='time')\n"
     ]
    }
   ],
   "source": [
    "print cube.coord('time')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "ntimes = len(cube.coord('time').points)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "11874 8224\n"
     ]
    }
   ],
   "source": [
    "ts1 = cube.data[0:3650]\n",
    "ts2 = cube.data[ntimes-3650 : -1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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/Bt7P6GK3Y8AtVfXMwHWdAuararDvTyf5PeAlRleLv7Nb9o/AT6vqH7rAfEtV/c3ANX2K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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11c207c10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "n1, bins, patches = plt.hist(ts1, 8, normed=1, histtype='step', lw=1, color='blue', label='first half')\n",
    "n2, bins, patches = plt.hist(ts2, 8, normed=1, histtype='step', lw=1, color='red',  label='second half')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(14.908547945205479, 16.52044395724856)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.mean(ts1), np.mean(ts2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [default]",
   "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": "2.7.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}