Climate Traces

climo-traces.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import sys\n",
    "import datetime\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.dates as mdates\n",
    "from scipy.ndimage import convolve\n",
    "from matplotlib.lines import Line2D\n",
    "from matplotlib.patches import Rectangle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def moving_average(x, n, type='simple'):\n",
    "    \"\"\"\n",
    "    compute an n period moving average.\n",
    "\n",
    "    type is 'simple' | 'exponential'\n",
    "\n",
    "    \"\"\"\n",
    "    x = np.asarray(x)\n",
    "    if type=='simple':\n",
    "        weights = np.ones(n)\n",
    "    else:\n",
    "        weights = np.exp(np.linspace(-1., 0., n))\n",
    "    weights /= weights.sum()\n",
    "    try:\n",
    "        return convolve(x, weights, mode='mirror')\n",
    "    except:\n",
    "        return convolve(x, weights, mode='same')\n",
    "\n",
    "def add_legend(ax):\n",
    "    dist = 30\n",
    "    line0 = Line2D(range(dist), range(dist), ls='-', lw=4, color='r')\n",
    "    line1 = Line2D(range(dist), range(dist), ls='-', lw=4, color='b')\n",
    "    line2 = Line2D(range(dist), range(dist), ls='--', lw=2, color='r')\n",
    "    line3 = Line2D(range(dist), range(dist), ls='--', lw=2, color='b')\n",
    "    rect0 = Rectangle((0,0), 1, 1, ec='k', fc='k', alpha=0.35, lw=3)\n",
    "    rect1 = Rectangle((0,0), 1, 1, ec='#C0C0C0', fc='#888888', alpha=0.67, lw=3)\n",
    "    label0 = 'High Temperature'\n",
    "    label1 = 'Low Temperature'\n",
    "    label2 = '15-day High Temperature Running Mean'\n",
    "    label3 = '15-day Low Temperature Running Mean'\n",
    "    label4 = 'Daily Normals'\n",
    "    label5 = 'All-time Temperature Range'\n",
    "    lines = [line0, line1, line2, line3, rect0, rect1]\n",
    "    labels = [label0, label1, label2, label3, label4, label5]\n",
    "    leg = ax.legend(lines, labels, loc=8, shadow=True, fancybox=True)\n",
    "    return leg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "datapath = r\"/Users/pmarshwx/dropbox/data/datasets/climo/stations\"\n",
    "stn = 'mspthr'\n",
    "STN = stn[:3].upper()\n",
    "df = pd.read_csv(os.path.join(datapath, stn+'.csv'), delimiter='|', na_values=['M'])\n",
    "dfYR = df.groupby(\"yr\")\n",
    "dfDOY366 = df.groupby(\"doy366\")\n",
    "genericYear = np.asarray([datetime.datetime.strptime(str(i), '%j') for i in range(1, 367)])\n",
    "YR = 2016\n",
    "doys = range(1, 367)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "min_year = df.yr.values[0]\n",
    "max_year = df.yr.values[-1]\n",
    "movingMaxT = moving_average(dfYR.get_group(YR).maxt.values, 15)\n",
    "movingMinT = moving_average(dfYR.get_group(YR).mint.values, 15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {

climo-traces.py

mspthr.csv