python-awips/examples/Grid Display.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Python AWIPS Data Access Framework\n",
    "\n",
    "The `python-awips` package provides a Data Acccess Framework (DAF) for requesting data from a remote AWIPS II EDEX server.  \n",
    "\n",
    "The AWIPS II Python Stack installed via RPM contains the DAF, matplotlib, numpy, scipy, basemap, pint, shapely, and other packages. \n",
    "\n",
    "## Listing a Grid Inventory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "GFSLAMP5\n",
      "GFSGuide\n",
      "ECMF6\n",
      "ECMF3\n",
      "ECMF4\n",
      "HPCqpfNDFD\n",
      "ECMF-Global\n",
      "RAP13\n",
      "ECMF5\n",
      "RTMA5\n",
      "AVN211\n",
      "NamDNG\n",
      "ECMF9\n",
      "QPE-MSR\n",
      "estofsUS\n",
      "ECMF12\n",
      "ECMF10\n",
      "ECMF8\n",
      "MRMS_1000\n",
      "ETA\n",
      "LAMP2p5\n",
      "HRRR\n",
      "URMA25\n",
      "GFS40\n",
      "GFS\n",
      "RAP40\n",
      "RTMA\n",
      "AVN225\n",
      "NAM12\n",
      "ECMF1\n",
      "ECMF2\n",
      "ECMF11\n",
      "DGEX\n",
      "NamDNG5\n",
      "estofsPR\n",
      "NCWF\n",
      "ECMF7\n",
      "NOHRSC-SNOW\n",
      "HPCGuide\n",
      "NAM40\n"
     ]
    }
   ],
   "source": [
    "from awips.dataaccess import DataAccessLayer\n",
    "\n",
    "# Set host\n",
    "DataAccessLayer.changeEDEXHost(\"edex-cloud.unidata.ucar.edu\")\n",
    "\n",
    "# Init data request\n",
    "request = DataAccessLayer.newDataRequest()\n",
    "\n",
    "# Set datatype\n",
    "request.setDatatype(\"grid\")\n",
    "\n",
    "# getAvailableLocationNames method will return a list of all available models\n",
    "available_grids = DataAccessLayer.getAvailableLocationNames(request)\n",
    "for grid in available_grids:\n",
    "    print grid\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "**LocationNames** is different for different plugins\n",
    "- radar is icao\n",
    "- satellite is sector\n",
    "\n",
    "\n",
    "## Requesting a Grid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RAP40\n",
      "2016-02-23 15:00:00 (12)\n",
      "Unit is %\n",
      "Parameter is RH\n",
      "[[ 100.02842712  100.02842712  100.02842712 ...,   60.02842712\n",
      "    60.02842712   63.02842712]\n",
      " [  63.02842712   60.02842712   52.02842712 ...,   90.02842712\n",
      "    91.02842712   91.02842712]\n",
      " [  90.02842712   91.02842712   90.02842712 ...,   41.02842712\n",
      "    40.02842712   38.02842712]\n",
      " ..., \n",
      " [  54.02842712   62.02842712   62.02842712 ...,   51.02842712\n",
      "    57.02842712   50.02842712]\n",
      " [  40.02842712   37.02842712   31.02842712 ...,    1.02842677\n",
      "     3.02842665    5.02842665]\n",
      " [   7.02842665    7.02842665    9.02842712 ...,   69.02842712\n",
      "    65.02842712   65.02842712]]\n",
      "lat array = [[ 54.24940109  54.35071945  54.45080566 ...,  57.9545517   57.91926193\n",
      "   57.88272858]\n",
      " [ 57.84495163  57.80593109  57.76566696 ...,  58.07667542  58.08861542\n",
      "   58.09931183]\n",
      " [ 58.10876846  58.11697769  58.12394714 ...,  56.40270996  56.46187973\n",
      "   56.51980972]\n",
      " ..., \n",
      " [ 19.93209648  19.89832115  19.86351395 ...,  20.054636    20.06362152\n",
      "   20.07156372]\n",
      " [ 20.0784626   20.08431816  20.08912849 ...,  18.58354759  18.63155174\n",
      "   18.67854691]\n",
      " [ 18.72453308  18.76950836  18.81346893 ...,  17.49624634  17.42861557\n",
      "   17.36001205]]\n",
      "lon array = [[-139.83120728 -139.32348633 -138.81448364 ...,  -79.26060486\n",
      "   -78.70166016  -78.14326477]\n",
      " [ -77.58544922  -77.02822876  -76.47161865 ..., -100.70157623\n",
      "  -100.13801575  -99.57427216]\n",
      " [ -99.01037598  -98.44634247  -97.88218689 ..., -121.69165039\n",
      "  -121.15060425 -120.60871887]\n",
      " ..., \n",
      " [ -82.65139008  -82.26644897  -81.88170624 ...,  -98.52494049\n",
      "   -98.13802338  -97.75105286]\n",
      " [ -97.36403656  -96.97698212  -96.58989716 ..., -113.07767487\n",
      "  -112.69831085 -112.31866455]\n",
      " [-111.93874359 -111.5585556  -111.17810822 ...,  -69.85433197\n",
      "   -69.48160553  -69.10926819]]\n"
     ]
    }
   ],
   "source": [
    "# Grid request\n",
    "request.setLocationNames('RAP40')\n",
    "request.setParameters(\"RH\")\n",
    "request.setLevels(\"850MB\")\n",
    "\n",
    "# Get available times\n",
    "t = DataAccessLayer.getAvailableTimes(request)\n",
    "\n",
    "# Select last available time [-1]\n",
    "response = DataAccessLayer.getGridData(request, [t[-1]])\n",
    "data = response[0]\n",
    "\n",
    "# Print info\n",
    "print data.getLocationName()\n",
    "print t[-1]\n",
    "print 'Unit is', data.getUnit()\n",
    "print 'Parameter is', data.getParameter()\n",
    "\n",
    "# Print data array\n",
    "print data.getRawData()\n",
    "\n",
    "# Print lat/lon array\n",
    "lon,lat = data.getLatLonCoords()\n",
    "print \"lat array =\", lat\n",
    "print \"lon array =\", lon"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting a Grid using Basemap\n",
    "\n",
    "Using **matplotlib**, **numpy**, and **basemap**:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f0b83ead710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.tri as mtri\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.transforms import offset_copy\n",
    "from mpl_toolkits.basemap import Basemap, cm\n",
    "import numpy as np\n",
    "from numpy import linspace, transpose\n",
    "from numpy import meshgrid\n",
    "from pint import UnitRegistry\n",
    "\n",
    "plt.figure(figsize=(12, 12), dpi=100)\n",
    "lons,lats = data.getLatLonCoords()\n",
    "\n",
    "map = Basemap(projection='cyl',\n",
    "      resolution = 'c',\n",
    "      llcrnrlon = lons.min(), llcrnrlat = lats.min(),\n",
    "      urcrnrlon =lons.max(), urcrnrlat = lats.max()\n",
    ")\n",
    "map.drawcoastlines()\n",
    "map.drawstates()\n",
    "map.drawcountries()\n",
    "\n",
    "# \n",
    "# We have to reproject our grid, see https://stackoverflow.com/questions/31822553/m\n",
    "#\n",
    "x = linspace(0, map.urcrnrx, data.getRawData().shape[1])\n",
    "y = linspace(0, map.urcrnry, data.getRawData().shape[0])\n",
    "xx, yy = meshgrid(x, y)\n",
    "ngrid = len(x)\n",
    "rlons = np.repeat(np.linspace(np.min(lons), np.max(lons), ngrid),\n",
    "          ngrid).reshape(ngrid, ngrid)\n",
    "rlats = np.repeat(np.linspace(np.min(lats), np.max(lats), ngrid),\n",
    "          ngrid).reshape(ngrid, ngrid).T\n",
    "tli = mtri.LinearTriInterpolator(mtri.Triangulation(lons.flatten(),\n",
    "          lats.flatten()), data.getRawData().flatten())\n",
    "rdata = tli(rlons, rlats)\n",
    "cs = map.pcolormesh(rlons, rlats, rdata, latlon=True, vmin=0, vmax=100, cmap='YlGn')\n",
    "\n",
    "# add colorbar.\n",
    "cbar = map.colorbar(cs,location='bottom',pad=\"5%\")\n",
    "cbar.set_label(data.getParameter() + data.getUnit() )\n",
    "\n",
    "# Show plot\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting a Grid using Cartopy\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "ImportError",
     "evalue": "No module named netCDF4",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mImportError\u001b[0m                               Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-54-90187fbaa2aa>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mos\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mmatplotlib\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpyplot\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[1;32mfrom\u001b[0m \u001b[0mnetCDF4\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mDataset\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mnetcdf_dataset\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      4\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mnumpy\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mImportError\u001b[0m: No module named netCDF4"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import matplotlib.pyplot as plt\n",
    "from netCDF4 import Dataset as netcdf_dataset\n",
    "import numpy as np\n",
    "\n",
    "from cartopy import config\n",
    "import cartopy.crs as ccrs\n",
    "\n",
    "\n",
    "# get the path of the file. It can be found in the repo data directory.\n",
    "fname = os.path.join(config[\"repo_data_dir\"],\n",
    "                     'netcdf', 'HadISST1_SST_update.nc'\n",
    "                     )\n",
    "\n",
    "dataset = netcdf_dataset(fname)\n",
    "sst = dataset.variables['sst'][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, sst, 60,\n",
    "             transform=ccrs.PlateCarree())\n",
    "\n",
    "ax.coastlines()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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