{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Trainer:\n",
    "\n",
    "Md. Jalal Uddin, Founder and director of Research Society \n",
    "\n",
    "email: dmjalal90@gmail.com, 20205103002@nuist.edu.cn"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Install netcdf4\n",
    "\n",
    "step 1: run Anaconda as Administrator\n",
    "\n",
    "step 2: you need to use the following command if you are a anaconda user\n",
    "\n",
    "conda install -c anaconda netcdf4 \n",
    "\n",
    "Or you need to use the following command if you are a python user\n",
    "\n",
    "pip install netCDF4"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Install Cartopy\n",
    "\n",
    "step 1: run Anaconda as Administrator\n",
    "    \n",
    "step 2: you need to use the following command if you are a anaconda user\n",
    "\n",
    "conda install -c conda-forge cartopy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Install xarray\n",
    "\n",
    "step 1: run Anaconda as Administrator\n",
    "    \n",
    "step 2: you need to use the following command if you are a anaconda user\n",
    "\n",
    "conda install -c anaconda xarray"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from netCDF4 import Dataset\n",
    "import xarray as xr\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from scipy.io import netcdf\n",
    "import cartopy.crs as ccrs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Know your data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dict_keys(['gwgt', 'lat', 'lon', 'time', 'prc'])\n"
     ]
    }
   ],
   "source": [
    "data = Dataset(r'precipitation.nc')\n",
    "\n",
    "print(data.variables.keys())  # print the variable name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'netCDF4._netCDF4.Variable'>\n",
      "float32 gwgt(lat)\n",
      "    long_name: gaussian weights\n",
      "    short_name: gwgts\n",
      "    units: dimensionless\n",
      "unlimited dimensions: \n",
      "current shape = (64,)\n",
      "filling on, default _FillValue of 9.969209968386869e+36 used\n",
      "<class 'netCDF4._netCDF4.Variable'>\n",
      "float32 lat(lat)\n",
      "    short_name: lat\n",
      "    long_name: latitude\n",
      "    units: degrees_north\n",
      "unlimited dimensions: \n",
      "current shape = (64,)\n",
      "filling on, default _FillValue of 9.969209968386869e+36 used\n",
      "<class 'netCDF4._netCDF4.Variable'>\n",
      "float32 lon(lon)\n",
      "    short_name: lon\n",
      "    long_name: longitude\n",
      "    units: degrees_east\n",
      "unlimited dimensions: \n",
      "current shape = (128,)\n",
      "filling on, default _FillValue of 9.969209968386869e+36 used\n",
      "<class 'netCDF4._netCDF4.Variable'>\n",
      "int32 time(time)\n",
      "    long_name: Year-Month\n",
      "    short_name: YRMO\n",
      "    units: yyyymm\n",
      "    _FillValue: -999\n",
      "unlimited dimensions: \n",
      "current shape = (216,)\n",
      "filling on\n",
      "<class 'netCDF4._netCDF4.Variable'>\n",
      "float32 prc(time, lat, lon)\n",
      "    short_name: PRC\n",
      "    long_name: Precipitation\n",
      "    units: mm/day\n",
      "    _FillValue: -999.0\n",
      "unlimited dimensions: \n",
      "current shape = (216, 64, 128)\n",
      "filling on\n"
     ]
    }
   ],
   "source": [
    "for var in data.variables.values():\n",
    "    print(var)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "</symbol>\n",
       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "</symbol>\n",
       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt, dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (lat: 64, lon: 128, time: 216)\n",
       "Coordinates:\n",
       "  * lat      (lat) float32 -87.8638 -85.09653 -82.31291 ... 85.09653 87.8638\n",
       "  * lon      (lon) float32 0.0 2.8125 5.625 8.4375 ... 351.5625 354.375 357.1875\n",
       "  * time     (time) float64 7.901e+03 7.902e+03 ... 9.611e+03 9.612e+03\n",
       "Data variables:\n",
       "    gwgt     (lat) float32 0.0017832807 0.004147033 ... 0.004147033 0.0017832807\n",
       "    prc      (time, lat, lon) float32 ...\n",
       "Attributes:\n",
       "    title:        CPC Merged Monthly Precipitation Estimates\n",
       "    source:       Pingping Xie and Phil Arkin (CPC); xping@sgi17.wwb.noaa.gov\n",
       "    history:      \\nFile read in the original format received \\nCPC source na...\n",
       "    references:   \\nXie and Arkin, 1996:\\nAnalyses of Global Monthly Precipit...\n",
       "    Conventions:  none</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-c1615748-0a33-498f-9917-8cde47f95fdd' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-c1615748-0a33-498f-9917-8cde47f95fdd' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 64</li><li><span class='xr-has-index'>lon</span>: 128</li><li><span class='xr-has-index'>time</span>: 216</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-7932cd0a-aab5-4268-a910-b3904f89df89' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7932cd0a-aab5-4268-a910-b3904f89df89' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-87.8638 -85.09653 ... 87.8638</div><input id='attrs-dd992efa-685a-4c2a-962f-dc529f58caba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dd992efa-685a-4c2a-962f-dc529f58caba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-75cdfbcf-5f54-4c9d-bcf1-fdc9136b2e37' class='xr-var-data-in' type='checkbox'><label for='data-75cdfbcf-5f54-4c9d-bcf1-fdc9136b2e37' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>short_name :</span></dt><dd>lat</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-87.8638  , -85.09653 , -82.31291 , -79.525604, -76.7369  , -73.94752 ,\n",
       "       -71.15775 , -68.36776 , -65.57761 , -62.787354, -59.99702 , -57.20663 ,\n",
       "       -54.4162  , -51.625732, -48.83524 , -46.044727, -43.254196, -40.46365 ,\n",
       "       -37.673088, -34.882523, -32.091946, -29.30136 , -26.510769, -23.720175,\n",
       "       -20.929575, -18.138971, -15.348365, -12.557756,  -9.767145,  -6.976533,\n",
       "        -4.185921,  -1.395307,   1.395307,   4.185921,   6.976533,   9.767145,\n",
       "        12.557756,  15.348365,  18.138971,  20.929575,  23.720175,  26.510769,\n",
       "        29.30136 ,  32.091946,  34.882523,  37.673088,  40.46365 ,  43.254196,\n",
       "        46.044727,  48.83524 ,  51.625732,  54.4162  ,  57.20663 ,  59.99702 ,\n",
       "        62.787354,  65.57761 ,  68.36776 ,  71.15775 ,  73.94752 ,  76.7369  ,\n",
       "        79.525604,  82.31291 ,  85.09653 ,  87.8638  ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 2.8125 ... 354.375 357.1875</div><input id='attrs-f7a28b4c-6314-455b-9994-93260669a396' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f7a28b4c-6314-455b-9994-93260669a396' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-68b5b5ad-5533-4aba-b136-3dc472edd9fe' class='xr-var-data-in' type='checkbox'><label for='data-68b5b5ad-5533-4aba-b136-3dc472edd9fe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>short_name :</span></dt><dd>lon</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([  0.    ,   2.8125,   5.625 ,   8.4375,  11.25  ,  14.0625,  16.875 ,\n",
       "        19.6875,  22.5   ,  25.3125,  28.125 ,  30.9375,  33.75  ,  36.5625,\n",
       "        39.375 ,  42.1875,  45.    ,  47.8125,  50.625 ,  53.4375,  56.25  ,\n",
       "        59.0625,  61.875 ,  64.6875,  67.5   ,  70.3125,  73.125 ,  75.9375,\n",
       "        78.75  ,  81.5625,  84.375 ,  87.1875,  90.    ,  92.8125,  95.625 ,\n",
       "        98.4375, 101.25  , 104.0625, 106.875 , 109.6875, 112.5   , 115.3125,\n",
       "       118.125 , 120.9375, 123.75  , 126.5625, 129.375 , 132.1875, 135.    ,\n",
       "       137.8125, 140.625 , 143.4375, 146.25  , 149.0625, 151.875 , 154.6875,\n",
       "       157.5   , 160.3125, 163.125 , 165.9375, 168.75  , 171.5625, 174.375 ,\n",
       "       177.1875, 180.    , 182.8125, 185.625 , 188.4375, 191.25  , 194.0625,\n",
       "       196.875 , 199.6875, 202.5   , 205.3125, 208.125 , 210.9375, 213.75  ,\n",
       "       216.5625, 219.375 , 222.1875, 225.    , 227.8125, 230.625 , 233.4375,\n",
       "       236.25  , 239.0625, 241.875 , 244.6875, 247.5   , 250.3125, 253.125 ,\n",
       "       255.9375, 258.75  , 261.5625, 264.375 , 267.1875, 270.    , 272.8125,\n",
       "       275.625 , 278.4375, 281.25  , 284.0625, 286.875 , 289.6875, 292.5   ,\n",
       "       295.3125, 298.125 , 300.9375, 303.75  , 306.5625, 309.375 , 312.1875,\n",
       "       315.    , 317.8125, 320.625 , 323.4375, 326.25  , 329.0625, 331.875 ,\n",
       "       334.6875, 337.5   , 340.3125, 343.125 , 345.9375, 348.75  , 351.5625,\n",
       "       354.375 , 357.1875], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.901e+03 7.902e+03 ... 9.612e+03</div><input id='attrs-c1ba7d08-46d3-49f1-89cc-9636cfb3d486' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c1ba7d08-46d3-49f1-89cc-9636cfb3d486' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5eca0970-dca2-4af2-8595-6dd36851bcb4' class='xr-var-data-in' type='checkbox'><label for='data-5eca0970-dca2-4af2-8595-6dd36851bcb4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Year-Month</dd><dt><span>short_name :</span></dt><dd>YRMO</dd><dt><span>units :</span></dt><dd>yyyymm</dd></dl></div><div class='xr-var-data'><pre>array([7901., 7902., 7903., ..., 9610., 9611., 9612.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-920f0131-370e-42c3-89b9-6ef0c9bb58e5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-920f0131-370e-42c3-89b9-6ef0c9bb58e5' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>gwgt</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f2cfb5e3-73d7-43d7-9582-e7ef13459ff3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f2cfb5e3-73d7-43d7-9582-e7ef13459ff3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6ac525e0-874d-47d2-ab5a-d2082a21ed78' class='xr-var-data-in' type='checkbox'><label for='data-6ac525e0-874d-47d2-ab5a-d2082a21ed78' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>gaussian weights</dd><dt><span>short_name :</span></dt><dd>gwgts</dd><dt><span>units :</span></dt><dd>dimensionless</dd></dl></div><div class='xr-var-data'><pre>array([0.001783, 0.004147, 0.006504, 0.008847, 0.011168, 0.013463, 0.015726,\n",
       "       0.017952, 0.020135, 0.02227 , 0.024353, 0.026377, 0.02834 , 0.030235,\n",
       "       0.032058, 0.033805, 0.035472, 0.037055, 0.03855 , 0.039954, 0.041263,\n",
       "       0.042474, 0.043584, 0.044591, 0.045492, 0.046285, 0.046968, 0.04754 ,\n",
       "       0.047999, 0.048345, 0.048575, 0.048691, 0.048691, 0.048575, 0.048345,\n",
       "       0.047999, 0.04754 , 0.046968, 0.046285, 0.045492, 0.044591, 0.043584,\n",
       "       0.042474, 0.041263, 0.039954, 0.03855 , 0.037055, 0.035472, 0.033805,\n",
       "       0.032058, 0.030235, 0.02834 , 0.026377, 0.024353, 0.02227 , 0.020135,\n",
       "       0.017952, 0.015726, 0.013463, 0.011168, 0.008847, 0.006504, 0.004147,\n",
       "       0.001783], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>prc</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-89034e4c-971f-4499-bded-66bc63285769' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-89034e4c-971f-4499-bded-66bc63285769' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3fd7de44-cdea-45bd-b543-617a544ba750' class='xr-var-data-in' type='checkbox'><label for='data-3fd7de44-cdea-45bd-b543-617a544ba750' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>short_name :</span></dt><dd>PRC</dd><dt><span>long_name :</span></dt><dd>Precipitation</dd><dt><span>units :</span></dt><dd>mm/day</dd></dl></div><div class='xr-var-data'><pre>[1769472 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2f7f0aee-dd31-4803-bd07-c2d6e45d2d72' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2f7f0aee-dd31-4803-bd07-c2d6e45d2d72' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>title :</span></dt><dd>CPC Merged Monthly Precipitation Estimates</dd><dt><span>source :</span></dt><dd>Pingping Xie and Phil Arkin (CPC); xping@sgi17.wwb.noaa.gov</dd><dt><span>history :</span></dt><dd>\n",
       "File read in the original format received \n",
       "CPC source name; merge_mon_v9708.txt\n",
       "NCAR source name; ds728.1 ; MSS=/DSS/Y39635\n",
       "msread -f CH merge_mon_v9708.txt /DSS/Y39635\n",
       "\n",
       "The data were the rain1 field which combines\n",
       "observed and model data. No grid pts are missing.\n",
       "\n",
       "Creation date: Tue Mar  3 18:45:03 MST 1998</dd><dt><span>references :</span></dt><dd>\n",
       "Xie and Arkin, 1996:\n",
       "Analyses of Global Monthly Precipitation\n",
       "Using Gauge Observations, Satellite Estimates, and\n",
       "Numerical Model Predictions.  J. Climate, 9, 840-858.\n",
       "------------------------------------------------------\n",
       "Xie and Arkin, 1997:\n",
       "Global Precipitation: A 17-Year Monthly Analysis\n",
       "Based on Gauge Observations, Satellite Estimates\n",
       "and Numerical Model Outputs. BAMS, 78, </dd><dt><span>Conventions :</span></dt><dd>none</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (lat: 64, lon: 128, time: 216)\n",
       "Coordinates:\n",
       "  * lat      (lat) float32 -87.8638 -85.09653 -82.31291 ... 85.09653 87.8638\n",
       "  * lon      (lon) float32 0.0 2.8125 5.625 8.4375 ... 351.5625 354.375 357.1875\n",
       "  * time     (time) float64 7.901e+03 7.902e+03 ... 9.611e+03 9.612e+03\n",
       "Data variables:\n",
       "    gwgt     (lat) float32 ...\n",
       "    prc      (time, lat, lon) float32 ...\n",
       "Attributes:\n",
       "    title:        CPC Merged Monthly Precipitation Estimates\n",
       "    source:       Pingping Xie and Phil Arkin (CPC); xping@sgi17.wwb.noaa.gov\n",
       "    history:      \\nFile read in the original format received \\nCPC source na...\n",
       "    references:   \\nXie and Arkin, 1996:\\nAnalyses of Global Monthly Precipit...\n",
       "    Conventions:  none"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds = xr.open_dataset('precipitation.nc')\n",
    "ds"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Know your variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<class 'netCDF4._netCDF4.Variable'>\n",
       "float32 prc(time, lat, lon)\n",
       "    short_name: PRC\n",
       "    long_name: Precipitation\n",
       "    units: mm/day\n",
       "    _FillValue: -999.0\n",
       "unlimited dimensions: \n",
       "current shape = (216, 64, 128)\n",
       "filling on"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.variables['prc']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# We need to know the minimum and maximum latlon for mapping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "min_lat  =  -87.8638\n",
      "max_lat  =  87.8638\n",
      "min_lon  =  0.0\n",
      "max_lon  =  357.1875\n"
     ]
    }
   ],
   "source": [
    "print(\"min_lat  = \", min(data.variables['lat']))\n",
    "print(\"max_lat  = \", max(data.variables['lat']))\n",
    "print(\"min_lon  = \", min(data.variables['lon']))\n",
    "print(\"max_lon  = \", max(data.variables['lon']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0.328615   0.32649407 0.32465214 ... 0.3369908  0.333855   0.33105692]\n",
      " [0.2591474  0.26262572 0.26580238 ... 0.24838836 0.25187734 0.25541523]\n",
      " [0.39385906 0.39131266 0.38667652 ... 0.3910227  0.39348662 0.3945333 ]\n",
      " ...\n",
      " [0.57567424 0.5975326  0.6245758  ... 0.55330473 0.5529246  0.56047904]\n",
      " [0.64617604 0.65975326 0.67477953 ... 0.61600125 0.6242001  0.6342811 ]\n",
      " [0.5605251  0.57392156 0.5873435  ... 0.52158374 0.5343335  0.5472972 ]]\n"
     ]
    }
   ],
   "source": [
    "lat  = data.variables['lat'][:]\n",
    "lon  = data.variables['lon'][:]\n",
    "time = data.variables['time'][:]\n",
    "prc  = data.variables['prc'][:]\n",
    "\n",
    "mean_rainfall = np.mean(prc, axis=0)\n",
    "print(mean_rainfall)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Latitude')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.contourf(lon, lat, mean_rainfall)\n",
    "plt.xlim(60,100)\n",
    "plt.ylim(5,30)\n",
    "plt.xlabel('Longitude')\n",
    "plt.ylabel('Latitude')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Understanding the transform and projection keywords\n",
    "\n",
    "https://scitools.org.uk/cartopy/docs/latest/tutorials/understanding_transform.html\n",
    "\n",
    "https://scitools.org.uk/cartopy/docs/v0.15/crs/projections.html   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dataset = netcdf.netcdf_file('precipitation.nc', maskandscale = True, mmap = False)\n",
    "\n",
    "prc  = dataset.variables['prc'][0, :, :]\n",
    "lats = dataset.variables['lat'][:]\n",
    "lons = dataset.variables['lon'][:]\n",
    "\n",
    "ax   = plt.axes(projection=ccrs.PlateCarree())\n",
    "\n",
    "plt.contourf(lons, lats, prc, cmap = 'YlOrRd', transform=ccrs.PlateCarree())\n",
    "\n",
    "\n",
    "ax.set_extent([30, 170, -30, 30])   # regional map (x0, x1, y0, y1)  \n",
    "ax.coastlines()\n",
    "ax.gridlines(draw_labels=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Adding Features to the Map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import cartopy.feature\n",
    "\n",
    "ax   = plt.axes(projection=ccrs.PlateCarree())\n",
    "\n",
    "plot = plt.contourf(lons, lats, prc, cmap = 'YlOrRd', transform=ccrs.PlateCarree())\n",
    "plt.colorbar(plot, ax=ax, shrink=0.8)\n",
    "\n",
    "ax.set_extent([30, 170, -30, 30])   # regional map (x0, x1, y0, y1)  \n",
    "ax.coastlines()\n",
    "\n",
    "gl = ax.gridlines(draw_labels=True)\n",
    "gl.top_labels   = False\n",
    "gl.right_labels = False\n",
    "\n",
    "\n",
    "ax.add_feature(cartopy.feature.OCEAN)\n",
    "ax.add_feature(cartopy.feature.LAND, edgecolor='black')\n",
    "ax.add_feature(cartopy.feature.LAKES, edgecolor='black')\n",
    "ax.add_feature(cartopy.feature.RIVERS)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds = xr.open_dataset('precipitation.nc')\n",
    "\n",
    "prc  = ds.prc[0,:,:]\n",
    "\n",
    "ax1   = plt.axes(projection = ccrs.PlateCarree())\n",
    "ax1.set_extent([30, 170, -30, 30])   # regional map (x0, x1, y0, y1)  \n",
    "ax1.coastlines()\n",
    "\n",
    "gl = ax1.gridlines(draw_labels=True)\n",
    "gl.top_labels   = False\n",
    "gl.right_labels = False\n",
    "\n",
    "prc.plot(ax=ax1, cmap = 'YlOrRd', transform=ccrs.PlateCarree(),cbar_kwargs={'shrink': 0.8})\n",
    "plt.title('')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "A good tutorial:  https://rabernat.github.io/research_computing_2018/maps-with-cartopy.html"
   ]
  }
 ],
 "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": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
