python-awips/examples/notebooks/Precip_Accumulation_Region_of_Interest.ipynb

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    "<a name=\"top\"></a>\n",
    "<div style=\"width:1000 px\">\n",
    "\n",
    "<div style=\"float:right; width:98 px; height:98px;\">\n",
    "<img src=\"https://docs.unidata.ucar.edu/images/logos/unidata_logo_vertical_150x150.png\" alt=\"Unidata Logo\" style=\"height: 98px;\">\n",
    "</div>\n",
    "\n",
    "# Precipitation Accumulation Region of Interest\n",
    "**Python-AWIPS Tutorial Notebook**\n",
    "\n",
    "<div style=\"clear:both\"></div>\n",
    "</div>\n",
    "\n",
    "---\n",
    "\n",
    "<div style=\"float:right; width:250 px\"><img src=\"../images/precip_roi_preview.png\" alt=\"Colorized Precipation Accumulation with Identified Region of Interest\" style=\"height: 300px;\"></div>\n",
    "\n",
    "\n",
    "# Objectives\n",
    "\n",
    "* Access the model data from an EDEX server and limit the data returned by using model specific parameters\n",
    "* Calculate the total precipitation over several model runs\n",
    "* Create a colorized plot for the continental US of the accumulated precipitation data\n",
    "* Calculate and identify area of highest of precipitation\n",
    "* Use higher resolution data to draw region of interest\n",
    "\n",
    "---"
   ]
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   "source": [
    "<h1>Table of Contents<span class=\"tocSkip\"></span></h1>\n",
    "<div class=\"toc\"><ul class=\"toc-item\"><li><span><a href=\"#Imports\" data-toc-modified-id=\"Imports-1\"><span class=\"toc-item-num\">1&nbsp;&nbsp;</span>Imports</a></span></li><li><span><a href=\"#Initial-Setup\" data-toc-modified-id=\"Initial-Setup-2\"><span class=\"toc-item-num\">2&nbsp;&nbsp;</span>Initial Setup</a></span><ul class=\"toc-item\"><li><span><a href=\"#Geographic-Filter\" data-toc-modified-id=\"Geographic-Filter-2.1\"><span class=\"toc-item-num\">2.1&nbsp;&nbsp;</span>Geographic Filter</a></span></li><li><span><a href=\"#EDEX-Connection\" data-toc-modified-id=\"EDEX-Connection-2.2\"><span class=\"toc-item-num\">2.2&nbsp;&nbsp;</span>EDEX Connection</a></span></li><li><span><a href=\"#Refine-the-Request\" data-toc-modified-id=\"Refine-the-Request-2.3\"><span class=\"toc-item-num\">2.3&nbsp;&nbsp;</span>Refine the Request</a></span></li><li><span><a href=\"#Get-Times\" data-toc-modified-id=\"Get-Times-2.4\"><span class=\"toc-item-num\">2.4&nbsp;&nbsp;</span>Get Times</a></span></li></ul></li><li><span><a href=\"#Function:-calculate_accumulated_precip()\" data-toc-modified-id=\"Function:-calculate_accumulated_precip()-3\"><span class=\"toc-item-num\">3&nbsp;&nbsp;</span>Function: calculate_accumulated_precip()</a></span></li><li><span><a href=\"#Fuction:-make_map()\" data-toc-modified-id=\"Fuction:-make_map()-4\"><span class=\"toc-item-num\">4&nbsp;&nbsp;</span>Fuction: make_map()</a></span></li><li><span><a href=\"#Get-the-Data!\" data-toc-modified-id=\"Get-the-Data!-5\"><span class=\"toc-item-num\">5&nbsp;&nbsp;</span>Get the Data!</a></span></li><li><span><a href=\"#Plot-the-Data!\" data-toc-modified-id=\"Plot-the-Data!-6\"><span class=\"toc-item-num\">6&nbsp;&nbsp;</span>Plot the Data!</a></span><ul class=\"toc-item\"><li><span><a href=\"#Create-CONUS-Image\" data-toc-modified-id=\"Create-CONUS-Image-6.1\"><span class=\"toc-item-num\">6.1&nbsp;&nbsp;</span>Create CONUS Image</a></span></li><li><span><a href=\"#Create-Region-of-Interest-Image\" data-toc-modified-id=\"Create-Region-of-Interest-Image-6.2\"><span class=\"toc-item-num\">6.2&nbsp;&nbsp;</span>Create Region of Interest Image</a></span></li></ul></li><li><span><a href=\"#High-Resolution-ROI\" data-toc-modified-id=\"High-Resolution-ROI-7\"><span class=\"toc-item-num\">7&nbsp;&nbsp;</span>High Resolution ROI</a></span><ul class=\"toc-item\"><li><span><a href=\"#New-Data-Request\" data-toc-modified-id=\"New-Data-Request-7.1\"><span class=\"toc-item-num\">7.1&nbsp;&nbsp;</span>New Data Request</a></span></li><li><span><a href=\"#Calculate-Data\" data-toc-modified-id=\"Calculate-Data-7.2\"><span class=\"toc-item-num\">7.2&nbsp;&nbsp;</span>Calculate Data</a></span></li><li><span><a href=\"#Plot-ROI\" data-toc-modified-id=\"Plot-ROI-7.3\"><span class=\"toc-item-num\">7.3&nbsp;&nbsp;</span>Plot ROI</a></span></li></ul></li><li><span><a href=\"#See-Also\" data-toc-modified-id=\"See-Also-8\"><span class=\"toc-item-num\">8&nbsp;&nbsp;</span>See Also</a></span><ul class=\"toc-item\"><li><span><a href=\"#Related-Notebooks\" data-toc-modified-id=\"Related-Notebooks-8.1\"><span class=\"toc-item-num\">8.1&nbsp;&nbsp;</span>Related Notebooks</a></span></li><li><span><a href=\"#Additional-Documentation\" data-toc-modified-id=\"Additional-Documentation-8.2\"><span class=\"toc-item-num\">8.2&nbsp;&nbsp;</span>Additional Documentation</a></span></li></ul></li></ul></div>"
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   "source": [
    "## Imports\n",
    "\n",
    "The imports below are used throughout the notebook. Note the first import is coming directly from python-awips and allows us to connect to an EDEX server. The subsequent imports are for data manipulation and visualization."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
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   "source": [
    "from awips.dataaccess import DataAccessLayer\n",
    "import cartopy.crs as ccrs\n",
    "import matplotlib.pyplot as plt\n",
    "from metpy.units import units\n",
    "import numpy as np\n",
    "from shapely.geometry import Point, Polygon"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a href=\"#top\">Top</a>\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Initial Setup"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Geographic Filter\n",
    "\n",
    "By defining a bounding box for the Continental US (CONUS), we’re able to optimize the data request sent to the EDEX server."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "conus=[-125, -65, 25, 55]\n",
    "conus_envelope = Polygon([(conus[0],conus[2]),(conus[0],conus[3]),\n",
    "                          (conus[1],conus[3]),(conus[1],conus[2]),\n",
    "                          (conus[0],conus[2])])"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### EDEX Connection\n",
    "\n",
    "First we establish a connection to Unidata’s public EDEX server. With that connection made, we can create a [new data request object](http://unidata.github.io/python-awips/api/IDataRequest.html) and set the data type to **grid**, and use the geographic envelope we just created."
   ]
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   "cell_type": "code",
   "execution_count": 3,
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   "source": [
    "DataAccessLayer.changeEDEXHost(\"edex-cloud.unidata.ucar.edu\")\n",
    "request = DataAccessLayer.newDataRequest(\"grid\", envelope=conus_envelope)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Refine the Request\n",
    "\n",
    "Here we specify which model we're interested in by setting the *LocationNames*, and the specific data we're interested in by setting the *Levels* and *Parameters*."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
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   "source": [
    "request.setLocationNames(\"GFS1p0\")\n",
    "request.setLevels(\"0.0SFC\")\n",
    "request.setParameters(\"TP\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Get Times\n",
    "\n",
    "We need to get the available times and cycles for our model data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "cycles = DataAccessLayer.getAvailableTimes(request, True)\n",
    "times = DataAccessLayer.getAvailableTimes(request)\n",
    "fcstRun = DataAccessLayer.getForecastRun(cycles[-1], times)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a href=\"#top\">Top</a>\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Function: calculate_accumulated_precip()\n",
    "\n",
    "Since we'll want to calculate the accumulated precipitation of our data more than once, it makes sense to create a function that we can call instead of duplicating the logic.\n",
    "\n",
    "This function cycles through all the grid data responses and adds up all of the rainfall to produce a numpy array with the total ammount of rainfall for the given data request.  It also finds the maximum rainfall point in x and y coordinates."
   ]
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    "def calculate_accumulated_precip(dataRequest, forecastRun):\n",
    "\n",
    "    for i, tt in enumerate(forecastRun):\n",
    "        response = DataAccessLayer.getGridData(dataRequest, [tt])\n",
    "        grid = response[0]\n",
    "        if i>0:\n",
    "            data += grid.getRawData()\n",
    "        else:\n",
    "            data = grid.getRawData()\n",
    "        data[data <= -9999] = 0\n",
    "        print(data.min(), data.max(), grid.getDataTime().getFcstTime()/3600)\n",
    "\n",
    "    # Convert from mm to inches\n",
    "    result = (data * units.mm).to(units.inch)\n",
    "    \n",
    "    ii,jj = np.where(result==result.max())\n",
    "    i=ii[0]\n",
    "    j=jj[0]\n",
    "\n",
    "    return result, i, j"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a href=\"#top\">Top</a>\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fuction: make_map()\n",
    "\n",
    "This function creates the basics of the map we're going to plot our data on. It takes in a bounding box to determine the extent and then adds coastlines for easy frame of reference."
   ]
  },
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   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_map(bbox, projection=ccrs.PlateCarree()):\n",
    "    fig, ax = plt.subplots(figsize=(20, 14),\n",
    "            subplot_kw=dict(projection=projection))\n",
    "    ax.set_extent(bbox)\n",
    "    ax.coastlines(resolution='50m')\n",
    "    return fig, ax"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a href=\"#top\">Top</a>\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Get the Data!\n",
    "\n",
    "Access the data from the DataAccessLayer interface using the *getGridData* function.  Use that data to calculate the accumulated rainfall, the maximum rainfall point, and the region of interest bounding box."
   ]
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     "text": [
      "0.0 10.0625 6.0\n",
      "0.0 21.75 12.0\n",
      "0.0 35.1875 18.0\n",
      "0.0 43.5 24.0\n",
      "0.0 45.5625 42.0\n",
      "0.0 47.9375 48.0\n",
      "0.0 52.0625 54.0\n",
      "0.0 56.375 60.0\n",
      "0.0 86.625 66.0\n",
      "0.0 92.4375 72.0\n",
      "0.0 94.375 78.0\n",
      "0.0 95.375 84.0\n",
      "0.0 98.3125 90.0\n",
      "0.0 100.125 96.0\n",
      "0.0 101.6875 102.0\n",
      "0.0 104.0 108.0\n",
      "0.0 107.1875 114.0\n",
      "0.0 115.25 120.0\n",
      "0.0 129.0 126.0\n",
      "0.0 136.375 132.0\n",
      "0.0 141.125 138.0\n",
      "0.0 145.25 144.0\n",
      "0.0 147.375 150.0\n",
      "0.0 5.802169\n",
      "POINT (-124 42)\n"
     ]
    }
   ],
   "source": [
    "## get the grid response from edex\n",
    "response = DataAccessLayer.getGridData(request, [fcstRun[-1]])    \n",
    "## take the first result to get the location information from\n",
    "grid = response[0]\n",
    "\n",
    "## get the location coordinates and create a bounding box for our map\n",
    "lons, lats = grid.getLatLonCoords()\n",
    "bbox = [lons.min(), lons.max(), lats.min(), lats.max()]\n",
    "fcstHr = int(grid.getDataTime().getFcstTime()/3600)\n",
    "\n",
    "## calculate the total precipitation\n",
    "tp_inch, i, j = calculate_accumulated_precip(request, fcstRun)\n",
    "print(tp_inch.min(), tp_inch.max())\n",
    "\n",
    "## use the max points coordinates to get the max point in lat/lon coords\n",
    "maxPoint = Point(lons[i][j], lats[i][j])\n",
    "inc = 3.5\n",
    "## create a region of interest bounding box\n",
    "roi_box=[maxPoint.x-inc, maxPoint.x+inc, maxPoint.y-inc, maxPoint.y+inc]\n",
    "roi_polygon = Polygon([(roi_box[0],roi_box[2]),(roi_box[0],roi_box[3]), \n",
    "                (roi_box[1],roi_box[3]),(roi_box[1],roi_box[2]),(roi_box[0],roi_box[2])])\n",
    "\n",
    "print(maxPoint)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a href=\"#top\">Top</a>\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot the Data!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create CONUS Image\n",
    "\n",
    "Plot our data on our CONUS map."
   ]
  },
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\n",
      "text/plain": [
       "<Figure size 1440x1008 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cmap = plt.get_cmap('rainbow')\n",
    "fig, ax = make_map(bbox=bbox)\n",
    "cs = ax.pcolormesh(lons, lats, tp_inch, cmap=cmap)\n",
    "cbar = fig.colorbar(cs, shrink=0.7, orientation='horizontal')\n",
    "cbar.set_label(grid.getLocationName() + \" Total accumulated precipitation in inches, \" \\\n",
    "               + str(fcstHr) + \"-hr fcst valid \" + str(grid.getDataTime().getRefTime()))\n",
    "\n",
    "ax.scatter(maxPoint.x, maxPoint.y, s=300,\n",
    "           transform=ccrs.PlateCarree(),marker=\"+\",facecolor='black')\n",
    "\n",
    "ax.add_geometries([roi_polygon], ccrs.PlateCarree(), facecolor='none', edgecolor='white', linewidth=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create Region of Interest Image\n",
    "\n",
    "Now crop the data and zoom in on the region of interest (ROI) to create a new plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x13ed521c0>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1008 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# cmap = plt.get_cmap('rainbow')\n",
    "fig, ax = make_map(bbox=roi_box)\n",
    "\n",
    "cs = ax.pcolormesh(lons, lats, tp_inch, cmap=cmap)\n",
    "cbar = fig.colorbar(cs, shrink=0.7, orientation='horizontal')\n",
    "cbar.set_label(grid.getLocationName() + \" Total accumulated precipitation in inches, \" \\\n",
    "               + str(fcstHr) + \"-hr fcst valid \" + str(grid.getDataTime().getRefTime()))\n",
    "\n",
    "ax.scatter(maxPoint.x, maxPoint.y, s=300,\n",
    "           transform=ccrs.PlateCarree(),marker=\"+\",facecolor='black')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a href=\"#top\">Top</a>\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## High Resolution ROI"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### New Data Request\n",
    "\n",
    "To see the region of interest more clearly, we can redo the process with a higher resolution model (GFS20 vs. GFS1.0)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "roiRequest = DataAccessLayer.newDataRequest(\"grid\", envelope=conus_envelope)\n",
    "roiRequest.setLocationNames(\"GFS20\")\n",
    "roiRequest.setLevels(\"0.0SFC\")\n",
    "roiRequest.setParameters(\"TP\")\n",
    "\n",
    "roiCycles = DataAccessLayer.getAvailableTimes(roiRequest, True)\n",
    "roiTimes = DataAccessLayer.getAvailableTimes(roiRequest)\n",
    "roiFcstRun = DataAccessLayer.getForecastRun(roiCycles[-1], roiTimes)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calculate Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[<awips.dataaccess.PyGridData.PyGridData object at 0x13ecb4eb0>]\n",
      "0.0 22.5625 3.0\n",
      "0.0 35.375 6.0\n",
      "0.0 38.375 9.0\n",
      "0.0 38.375 12.0\n",
      "0.0 41.375 15.0\n",
      "0.0 48.625 18.0\n",
      "0.0 73.0625 30.0\n",
      "0.0 94.9375 33.0\n",
      "0.0 96.125 36.0\n",
      "0.0 97.0 39.0\n",
      "0.0 99.375 45.0\n",
      "0.0 100.0625 48.0\n",
      "0.0 100.25 51.0\n",
      "0.0 100.4375 57.0\n",
      "0.0 100.4375 63.0\n",
      "0.0 118.25 66.0\n",
      "0.0 127.625 69.0\n",
      "0.0 131.125 75.0\n",
      "0.0 131.375 78.0\n",
      "0.0 131.5 81.0\n",
      "0.0 131.875 84.0\n",
      "0.0 132.875 90.0\n",
      "0.0 133.375 96.0\n",
      "0.0 139.1875 102.0\n",
      "0.0 141.625 120.0\n",
      "0.0 141.75 126.0\n",
      "0.0 142.1875 132.0\n",
      "0.0 143.375 138.0\n",
      "0.0 148.6875 144.0\n",
      "0.0 156.25 150.0\n"
     ]
    }
   ],
   "source": [
    "roiResponse = DataAccessLayer.getGridData(roiRequest, [roiFcstRun[-1]])  \n",
    "print(roiResponse)\n",
    "roiGrid = roiResponse[0]\n",
    "\n",
    "roiLons, roiLats = roiGrid.getLatLonCoords()\n",
    "\n",
    "roi_data, i, j = calculate_accumulated_precip(roiRequest, roiFcstRun)\n",
    "\n",
    "roiFcstHr = int(roiGrid.getDataTime().getFcstTime()/3600)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot ROI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/scarter/opt/miniconda3/envs/python3-awips/lib/python3.9/site-packages/cartopy/mpl/geoaxes.py:1702: UserWarning: The input coordinates to pcolormesh are interpreted as cell centers, but are not monotonically increasing or decreasing. This may lead to incorrectly calculated cell edges, in which case, please supply explicit cell edges to pcolormesh.\n",
      "  X, Y, C, shading = self._pcolorargs('pcolormesh', *args,\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x13edc39a0>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1008 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# cmap = plt.get_cmap('rainbow')\n",
    "fig, ax = make_map(bbox=roi_box)\n",
    "\n",
    "cs = ax.pcolormesh(roiLons, roiLats, roi_data, cmap=cmap)\n",
    "cbar = fig.colorbar(cs, shrink=0.7, orientation='horizontal')\n",
    "cbar.set_label(roiGrid.getLocationName() + \" Total accumulated precipitation in inches, \" \\\n",
    "               + str(roiFcstHr) + \"-hr fcst valid \" + str(roiGrid.getDataTime().getRefTime()))\n",
    "\n",
    "ax.scatter(maxPoint.x, maxPoint.y, s=300,\n",
    "           transform=ccrs.PlateCarree(),marker=\"+\",facecolor='black')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a href=\"#top\">Top</a>\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## See Also\n",
    "\n",
    "### Related Notebooks\n",
    "\n",
    "* [Colorized Grid Data](https://unidata.github.io/python-awips/examples/generated/Colorized_Grid_Data.html)\n",
    "* [Grid Levels and Parameters](https://unidata.github.io/python-awips/examples/generated/Grid_Levels_and_Parameters.html)\n",
    "\n",
    "### Additional Documentation\n",
    "\n",
    "**python-awips:**\n",
    "* [awips.DataAccessLayer](http://unidata.github.io/python-awips/api/DataAccessLayer.html)\n",
    "* [awips.PyGridData](http://unidata.github.io/python-awips/api/PyGridData.html)\n",
    "\n",
    "**matplotlib:**\n",
    "* [matplotlib.pyplot](https://matplotlib.org/3.3.3/api/_as_gen/matplotlib.pyplot.html)\n",
    "* [matplotlib.pyplot.subplot](https://matplotlib.org/3.3.3/api/_as_gen/matplotlib.pyplot.subplot.html)\n",
    "* [matplotlib.pyplot.pcolormesh](https://matplotlib.org/3.3.3/api/_as_gen/matplotlib.pyplot.pcolormesh.html)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a href=\"#top\">Top</a>\n",
    "\n",
    "---"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
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