{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<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",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "toc": true
   },
   "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>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "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,
   "metadata": {},
   "outputs": [],
   "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"
   ]
  },
  {
   "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])])"
   ]
  },
  {
   "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."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "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,
   "metadata": {},
   "outputs": [],
   "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."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "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."
   ]
  },
  {
   "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."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0 22.1875 6.0\n",
      "0.0 43.1875 12.0\n",
      "0.0 55.8125 18.0\n",
      "0.0 57.9375 24.0\n",
      "0.0 96.75 30.0\n",
      "0.0 111.0625 36.0\n",
      "0.0 126.375 42.0\n",
      "0.0 137.75 48.0\n",
      "0.0 140.25 54.0\n",
      "0.0 140.4375 60.0\n",
      "0.0 140.4375 66.0\n",
      "0.0 140.4375 72.0\n",
      "0.0 140.5625 78.0\n",
      "0.0 155.125 84.0\n",
      "0.0 155.1875 90.0\n",
      "0.0 155.3125 96.0\n",
      "0.0 155.375 102.0\n",
      "0.0 155.375 108.0\n",
      "0.0 155.375 114.0\n",
      "0.0 155.375 120.0\n",
      "0.0 155.375 126.0\n",
      "0.0 155.375 132.0\n",
      "0.0 155.375 138.0\n",
      "0.0 155.375 144.0\n",
      "0.0 155.8125 150.0\n",
      "0.0 159.5 156.0\n",
      "0.0 160.125 162.0\n",
      "0.0 160.1875 168.0\n",
      "0.0 160.3125 174.0\n",
      "0.0 160.375 180.0\n",
      "0.0 160.4375 186.0\n",
      "0.0 160.4375 192.0\n",
      "0.0 160.4375 198.0\n",
      "0.0 160.4375 204.0\n",
      "0.0 160.8125 210.0\n",
      "0.0 160.875 216.0\n",
      "0.0 160.875 222.0\n",
      "0.0 160.875 228.0\n",
      "0.0 160.875 234.0\n",
      "0.0 160.875 240.0\n",
      "0.0 inch 6.3336615562438965 inch\n",
      "POINT (-88 36)\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."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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     "execution_count": 9,
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     "data": {
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",
      "text/plain": [
       "<Figure size 2000x1400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "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": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7fac67d102d0>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x1400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "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": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[<awips.dataaccess.PyGridData.PyGridData object at 0x7fac67d43890>]\n",
      "0.0 45.4375 3.0\n",
      "0.0 47.9375 6.0\n",
      "0.0 48.1875 9.0\n",
      "0.0 51.75 12.0\n",
      "0.0 71.1875 15.0\n",
      "0.0 72.375 18.0\n",
      "0.0 72.4375 21.0\n",
      "0.0 81.75 24.0\n",
      "0.0 107.5 27.0\n",
      "0.0 131.8125 30.0\n",
      "0.0 141.6875 33.0\n",
      "0.0 149.9375 36.0\n",
      "0.0 159.5 39.0\n",
      "0.0 171.5625 42.0\n",
      "0.0 181.9375 45.0\n",
      "0.0 186.0 48.0\n",
      "0.0 187.75 51.0\n",
      "0.0 189.625 54.0\n",
      "0.0 189.875 57.0\n",
      "0.0 189.875 60.0\n",
      "0.0 189.875 63.0\n",
      "0.0 189.875 66.0\n",
      "0.0 189.875 69.0\n",
      "0.0 189.875 72.0\n",
      "0.0 190.0625 75.0\n",
      "0.0 190.0625 78.0\n",
      "0.0 200.375 81.0\n",
      "0.0 200.8125 84.0\n",
      "0.0 200.875 90.0\n",
      "0.0 201.0625 96.0\n",
      "0.0 201.1875 102.0\n",
      "0.0 201.25 108.0\n",
      "0.0 201.25 114.0\n",
      "0.0 201.25 120.0\n",
      "0.0 201.25 126.0\n",
      "0.0 201.25 132.0\n",
      "0.0 201.25 138.0\n",
      "0.0 201.25 144.0\n",
      "0.0 201.375 150.0\n",
      "0.0 205.9375 156.0\n",
      "0.0 206.75 162.0\n",
      "0.0 206.9375 168.0\n",
      "0.0 207.0625 174.0\n",
      "0.0 207.1875 180.0\n",
      "0.0 207.1875 186.0\n",
      "0.0 207.1875 192.0\n",
      "0.0 207.1875 198.0\n",
      "0.0 207.1875 204.0\n",
      "0.0 207.875 210.0\n",
      "0.0 208.25 216.0\n",
      "0.0 208.25 222.0\n",
      "0.0 208.25 228.0\n",
      "0.0 208.25 234.0\n",
      "0.0 208.25 240.0\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": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7fac67c23390>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x1400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "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 (ipykernel)",
   "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": "3.13.1"
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  "toc": {
   "base_numbering": 1,
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   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": true,
   "toc_position": {},
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   "toc_window_display": true
  }
 },
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}