{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# Probando CDO\n",
    "\n",
    "## Integrantes: \n",
    "\n",
    "* Carla Gulizia\n",
    "* Natalia Zazulie\n",
    "* Natalia Montroull\n",
    "\n",
    "## Instalación:\n",
    "\n",
    "    # Instalar cdo desde la terminal\n",
    "    $ sudo apt-get install cdo\n",
    "\n",
    "    # Instalar con conda el python-cdo:\n",
    "    $conda install -c conda-forge cdo=1.7.1\n",
    "\n",
    "    # Es necesaria una libreriaa extra para cdo:\n",
    "    sudo apt-get install libjpeg9"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Load required module\n",
    "import numpy as np\n",
    "import netCDF4\n",
    "from cdo import *\n",
    "from matplotlib import pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "path = '../../../data/'\n",
    "file = path + 'pr_Amon_CanESM2_historical_r1i1p1_193101-200512_SA.nc'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "cdo = Cdo()\n",
    "# Compute the South America mean monthly precipitation and return it as a numpy array:\n",
    "mean_pr = np.squeeze(cdo.fldmean(input=file, returnArray='pr')) # Field Mean pr SA (da una serie temporal) \n",
    "years = cdo.showyear(input=file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(900,)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pr_box.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fbe377c63c8>]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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lX3Sil2SiPdvTRzh0PT5FH0P0kkz48Q884PfouTKSRP+LXwA//WnW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\n+7bh5tcglWSMdSNDIOvEaacBv/999p7yzgWcLwRRa1f8Wvm20bGQ7Ub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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fbe4d740518>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#pr_ene = np.squeeze(cdo.fldmean(input=file, returnArray='pr'))\n",
    "pr_box = np.squeeze(cdo.fldmean (input='-sellonlatbox,280,300,-40,-20 ' + file, returnArray='pr'))\n",
    "pr_box.shape\n",
    "plt.plot(pr_box*60*60*24)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "prSA_anom = np.squeeze(cdo.sub(input = '-fldmean ' + file + ' -timmean -selyear,1971/2000 -fldmean ' + file, returnArray='pr', options = '-L'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "pr_anu = cdo.yearmean (input= '-fldmean ' + file, returnArray='pr')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<link href='http://fonts.googleapis.com/css?family=Alegreya+Sans:100,300,400,500,700,800,900,100italic,300italic,400italic,500italic,700italic,800italic,900italic' rel='stylesheet' type='text/css'>\n",
       "<link href='http://fonts.googleapis.com/css?family=Arvo:400,700,400italic' rel='stylesheet' type='text/css'>\n",
       "<link href='http://fonts.googleapis.com/css?family=PT+Mono' rel='stylesheet' type='text/css'>\n",
       "<link href='http://fonts.googleapis.com/css?family=Shadows+Into+Light' rel='stylesheet' type='text/css'>\n",
       "<link href='http://fonts.googleapis.com/css?family=Nixie+One' rel='stylesheet' type='text/css'>\n",
       "\n",
       "<style>\n",
       "@font-face {\n",
       "    font-family: \"Computer Modern\";\n",
       "    src: url('http://mirrors.ctan.org/fonts/cm-unicode/fonts/otf/cmunss.otf');\n",
       "}\n",
       "\n",
       "/* main background */\n",
       "#notebook_panel {\n",
       "    background: rgb(245,245,245);\n",
       "}\n",
       "\n",
       "/* centre the content */\n",
       "div #notebook {\n",
       "    background: #fff; /* white background for content */\n",
       "    width: 100%;\n",
       "    margin-right: 0px;\n",
       "    margin-left: 0px;\n",
       "    padding-left: 0em;\n",
       "}\n",
       "\n",
       "/* More space between bullet points */\n",
       "#notebook li {\n",
       "    margin-top:0.8em;\n",
       "}\n",
       "\n",
       "/* set cell width */\n",
       "div.cell {\n",
       "    width: 95%;\n",
       "}\n",
       "\n",
       "/* draw border around running cells */\n",
       "div.cell.border-box-sizing.code_cell.running {\n",
       "    border: 1px solid #111;\n",
       "}\n",
       "\n",
       "/* Put a solid color box around each cell and its output, \n",
       "   visually linking them*/\n",
       "div.cell.code_cell {\n",
       "    background-color: rgb(256,256,256);\n",
       "    border-radius: 0px;\n",
       "    padding: 0.5em;\n",
       "    margin-left:1em;\n",
       "    margin-top: 1em;\n",
       "}\n",
       "\n",
       "div.text_cell_render{\n",
       "    font-family: 'Alegreya Sans' sans-serif;\n",
       "    line-height: 140%;\n",
       "    font-size: 145%;\n",
       "    font-weight: 400;\n",
       "    margin-left:0px;\n",
       "    margin-right:0px;\n",
       "}\n",
       "\n",
       "/* Formatting for header cells */\n",
       ".text_cell_render h1 {\n",
       "    font-family: 'Nixie One', serif;\n",
       "    font-style:regular;\n",
       "    font-weight: 400;\n",
       "    font-size: 45pt;\n",
       "    line-height: 100%;\n",
       "    color: rgb(0,51,102);\n",
       "    margin-bottom: 0.5em;\n",
       "    margin-top: 0.5em;\n",
       "    display: block;\n",
       "}\n",
       "\n",
       ".text_cell_render h2 {\n",
       "    font-family: 'Nixie One', serif;\n",
       "    font-weight: 400;\n",
       "    font-size: 30pt;\n",
       "    line-height: 100%;\n",
       "    color: rgb(0,51,102);\n",
       "    margin-bottom: 0.1em;\n",
       "    margin-top: 0.3em;\n",
       "    display: block;\n",
       "}\n",
       "\n",
       ".text_cell_render h3 {\n",
       "    font-family: 'Nixie One', serif;\n",
       "    margin-top:16px;\n",
       "    font-size: 22pt;\n",
       "    font-weight: 600;\n",
       "    margin-bottom: 3px;\n",
       "    font-style: regular;\n",
       "    color: rgb(102,102,0);\n",
       "}\n",
       "\n",
       ".text_cell_render h4 { /*Use this for captions*/\n",
       "    font-family: 'Nixie One', serif;\n",
       "    font-size: 14pt;\n",
       "    text-align: center;\n",
       "    margin-top: 0em;\n",
       "    margin-bottom: 2em;\n",
       "    font-style: regular;\n",
       "}\n",
       "\n",
       ".text_cell_render h5 { /*Use this for small titles*/\n",
       "    font-family: 'Nixie One', sans-serif;\n",
       "    font-weight: 400;\n",
       "    font-size: 16pt;\n",
       "    color: rgb(163,0,0);\n",
       "    font-style: italic;\n",
       "    margin-bottom: .1em;\n",
       "    margin-top: 0.8em;\n",
       "    display: block;\n",
       "}\n",
       "\n",
       ".text_cell_render h6 { /*use this for copyright note*/\n",
       "    font-family: 'PT Mono', sans-serif;\n",
       "    font-weight: 300;\n",
       "    font-size: 9pt;\n",
       "    line-height: 100%;\n",
       "    color: grey;\n",
       "    margin-bottom: 1px;\n",
       "    margin-top: 1px;\n",
       "}\n",
       "\n",
       ".CodeMirror{\n",
       "    font-family: \"PT Mono\";\n",
       "    font-size: 100%;\n",
       "}\n",
       "\n",
       "</style>\n",
       "\n",
       "<script type=\"text/x-mathjax-config\">\n",
       "MathJax.Hub.Config({\n",
       "\t\t      TeX: {\n",
       "\t\t      extensions: [\"AMSmath.js\"],\n",
       "\t\t      equationNumbers: { autoNumber: \"AMS\", useLabelIds: true}\n",
       "\t\t  },\n",
       "\t\t      tex2jax: {\n",
       "\t\t\t  inlineMath: [ ['$','$'], [\"\\\\(\",\"\\\\)\"] ],\n",
       "\t\t\t  displayMath: [ ['$$','$$'], [\"\\\\[\",\"\\\\]\"] ],\n",
       "\t\t\t  processEscapes: true,\n",
       "\t\t\t  processEnvironments: true\n",
       "\t\t      },\n",
       "\t\t      displayAlign: 'center',\n",
       "\t\t      \"HTML-CSS\": {\n",
       "\t\t\t  styles: {'.MathJax_Display': {\"margin\": 4}}\n",
       "\t\t      }\n",
       "\t\t  });\n",
       "</script>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Este css es trabajo de @LorenaABarba y su grupo\n",
    "from IPython.core.display import HTML\n",
    "css_file = '../../css/personal.css'\n",
    "HTML(open(css_file, \"r\").read())"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}