python-awips/examples/notebooks/NEXRAD_Level3_Radar.ipynb

{
 "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",
    "# NEXRAD Level 3 Radar\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/NEXRAD_Level3_Radar_preview.png\" alt=\"NEXRAD Composite Reflectivity Example\" style=\"height: 300px;\"></div>\n",
    "\n",
    "\n",
    "# Objectives\n",
    "\n",
    "* Use python-awips to connect to an edex server\n",
    "* Define and filter data request for radar data\n",
    "* Plot NEXRAD 3 algorithm, precipitation, and derived products (not base data)\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=\"#EDEX-Connection\" data-toc-modified-id=\"EDEX-Connection-2\"><span class=\"toc-item-num\">2&nbsp;&nbsp;</span>EDEX Connection</a></span></li><li><span><a href=\"#Investigate-Data\" data-toc-modified-id=\"Investigate-Data-3\"><span class=\"toc-item-num\">3&nbsp;&nbsp;</span>Investigate Data</a></span><ul class=\"toc-item\"><li><span><a href=\"#Available-Locations\" data-toc-modified-id=\"Available-Locations-3.1\"><span class=\"toc-item-num\">3.1&nbsp;&nbsp;</span>Available Locations</a></span></li><li><span><a href=\"#Available-Parameters\" data-toc-modified-id=\"Available-Parameters-3.2\"><span class=\"toc-item-num\">3.2&nbsp;&nbsp;</span>Available Parameters</a></span></li><li><span><a href=\"#Radar-Product-IDs-and-Names\" data-toc-modified-id=\"Radar-Product-IDs-and-Names-3.3\"><span class=\"toc-item-num\">3.3&nbsp;&nbsp;</span>Radar Product IDs and Names</a></span></li></ul></li><li><span><a href=\"#Function:-make_map()\" data-toc-modified-id=\"Function:-make_map()-4\"><span class=\"toc-item-num\">4&nbsp;&nbsp;</span>Function: make_map()</a></span></li><li><span><a href=\"#Plot-the-Data!\" data-toc-modified-id=\"Plot-the-Data!-5\"><span class=\"toc-item-num\">5&nbsp;&nbsp;</span>Plot the Data!</a></span></li><li><span><a href=\"#See-Also\" data-toc-modified-id=\"See-Also-6\"><span class=\"toc-item-num\">6&nbsp;&nbsp;</span>See Also</a></span><ul class=\"toc-item\"><li><span><a href=\"#Related-Notebooks\" data-toc-modified-id=\"Related-Notebooks-6.1\"><span class=\"toc-item-num\">6.1&nbsp;&nbsp;</span>Related Notebooks</a></span></li><li><span><a href=\"#Additional-Documention\" data-toc-modified-id=\"Additional-Documention-6.2\"><span class=\"toc-item-num\">6.2&nbsp;&nbsp;</span>Additional Documention</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": [
    "import warnings\n",
    "from awips.dataaccess import DataAccessLayer\n",
    "import matplotlib.pyplot as plt\n",
    "import cartopy.crs as ccrs\n",
    "import cartopy.feature as cfeature\n",
    "import numpy as np\n",
    "from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a href=\"#top\">Top</a>\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## EDEX Connection\n",
    "\n",
    "First we establish a connection to Unidata's public EDEX server. This sets the proper server on the **DataAccessLayer**, which we will use numerous times throughout the notebook."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "DataAccessLayer.changeEDEXHost(\"edex-cloud.unidata.ucar.edu\")\n",
    "request = DataAccessLayer.newDataRequest(\"radar\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a href=\"#top\">Top</a>\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Investigate Data\n",
    "\n",
    "Now that we've created a new radar data request, let's take a look at what locations and parameters are available for our current request."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Available Locations\n",
    "\n",
    "We can take a look at what \"locations\" are available for our radar request.  For radar, we'll see that radar station names are returned when looking at the availalbe location names.\n",
    "\n",
    "For this example we'll use Baltimore, MD/Washington, DC as our region of interest.  You can easily look up other station IDs and where they are using [this NWS webpage](https://radar.weather.gov/station/KMHX/standard)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['kabr', 'kabx', 'kakq', 'kama', 'kamx', 'kapx', 'karx', 'katx', 'kbbx', 'kbgm', 'kbhx', 'kbis', 'kblx', 'kbmx', 'kbox', 'kbro', 'kbuf', 'kbyx', 'kcae', 'kcbw', 'kcbx', 'kccx', 'kcle', 'kclx', 'kcrp', 'kcxx', 'kcys', 'kdax', 'kddc', 'kdfx', 'kdgx', 'kdix', 'kdlh', 'kdmx', 'kdox', 'kdtx', 'kdvn', 'kdyx', 'keax', 'kemx', 'kenx', 'keox', 'kepz', 'kesx', 'kevx', 'kewx', 'keyx', 'kfcx', 'kfdr', 'kfdx', 'kffc', 'kfsd', 'kfsx', 'kftg', 'kfws', 'kggw', 'kgjx', 'kgld', 'kgrb', 'kgrk', 'kgrr', 'kgsp', 'kgwx', 'kgyx', 'khdc', 'khdx', 'khgx', 'khnx', 'khpx', 'khtx', 'kict', 'kicx', 'kiln', 'kilx', 'kind', 'kinx', 'kiwa', 'kiwx', 'kjax', 'kjgx', 'kjkl', 'klbb', 'klch', 'klgx', 'klnx', 'klot', 'klrx', 'klsx', 'kltx', 'klvx', 'klwx', 'klzk', 'kmaf', 'kmax', 'kmbx', 'kmhx', 'kmkx', 'kmlb', 'kmob', 'kmpx', 'kmqt', 'kmrx', 'kmsx', 'kmtx', 'kmux', 'kmvx', 'kmxx', 'knkx', 'knqa', 'koax', 'kohx', 'kokx', 'kotx', 'kpah', 'kpbz', 'kpdt', 'kpoe', 'kpux', 'krax', 'krgx', 'kriw', 'krlx', 'krtx', 'ksfx', 'ksgf', 'kshv', 'ksjt', 'ksox', 'ksrx', 'ktbw', 'ktfx', 'ktlh', 'ktlx', 'ktwx', 'ktyx', 'kudx', 'kuex', 'kvax', 'kvbx', 'kvnx', 'kvtx', 'kvwx', 'kyux', 'pabc', 'pacg', 'paec', 'pahg', 'paih', 'pakc', 'papd', 'phki', 'phkm', 'phmo', 'phwa', 'rkjk', 'rksg', 'tadw', 'tatl', 'tbna', 'tbos', 'tbwi', 'tclt', 'tcmh', 'tcvg', 'tdal', 'tday', 'tdca', 'tden', 'tdfw', 'tdtw', 'tewr', 'tfll', 'thou', 'tiad', 'tiah', 'tich', 'tids', 'tjfk', 'tjua', 'tlas', 'tlve', 'tmci', 'tmco', 'tmdw', 'tmem', 'tmia', 'tmke', 'tmsp', 'tmsy', 'tokc', 'tord', 'tpbi', 'tphl', 'tphx', 'tpit', 'trdu', 'tsdf', 'tsju', 'tslc', 'tstl', 'ttpa', 'ttul']\n"
     ]
    }
   ],
   "source": [
    "available_locs = DataAccessLayer.getAvailableLocationNames(request)\n",
    "available_locs.sort()\n",
    "print(available_locs)\n",
    "\n",
    "# Set our location to Baltimore (klwx)\n",
    "request.setLocationNames(\"klwx\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Available Parameters\n",
    "\n",
    "Next, let's look at the parameters returned from the available parameters request.  If we look closely, we can see that some of the parameters appear different from the others."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['134', '135', '141', '153', '154', '159', '161', '163', '165', '166', '169', '170', '172', '173', '176', '177', '32', '37', '56', '57', '58', '81', '99', 'CC', 'CZ', 'Composite Refl', 'Correlation Coeff', 'DAA', 'DHR', 'DPA', 'DPR', 'DUA', 'DVL', 'Diff Reflectivity', 'Digital Hybrid Scan Refl', 'Digital Inst Precip Rate', 'Digital Precip Array', 'Digital Vert Integ Liq', 'EET', 'Enhanced Echo Tops', 'HC', 'HHC', 'HV', 'HZ', 'Hybrid Hydrometeor Class', 'Hydrometeor Class', 'KDP', 'MD', 'ML', 'Melting Layer', 'Mesocyclone', 'OHA', 'One Hour Accum', 'One Hour Unbiased Accum', 'Reflectivity', 'SRM', 'STA', 'STI', 'Specific Diff Phase', 'Storm Rel Velocity', 'Storm Total Accum', 'Storm Track', 'User Select Accum', 'V', 'VIL', 'Velocity', 'Vert Integ Liq', 'ZDR']\n"
     ]
    }
   ],
   "source": [
    "availableParms = DataAccessLayer.getAvailableParameters(request)\n",
    "availableParms.sort()\n",
    "print(availableParms)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Radar Product IDs and Names\n",
    "\n",
    "As we saw above, some parameters seem to be describing different things from the rest.  The DataAccessLayer has a built in function to parse the available parameters into the separate **Product IDs** and **Product Names**.  Here, we take a look at the two different arrays that are returned when parsing the *availableParms* array we just recieved in the previous code cell."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['134', '135', '141', '153', '154', '159', '161', '163', '165', '166', '169', '170', '172', '173', '176', '177', '32', '37', '56', '57', '58', '81', '99']\n",
      "['Composite Refl', 'Correlation Coeff', 'Diff Reflectivity', 'Digital Hybrid Scan Refl', 'Digital Inst Precip Rate', 'Digital Precip Array', 'Digital Vert Integ Liq', 'Enhanced Echo Tops', 'Hybrid Hydrometeor Class', 'Hydrometeor Class', 'Melting Layer', 'Mesocyclone', 'One Hour Accum', 'One Hour Unbiased Accum', 'Reflectivity', 'Specific Diff Phase', 'Storm Rel Velocity', 'Storm Total Accum', 'Storm Track', 'User Select Accum', 'Velocity', 'Vert Integ Liq']\n"
     ]
    }
   ],
   "source": [
    "productIDs = DataAccessLayer.getRadarProductIDs(availableParms)\n",
    "productNames = DataAccessLayer.getRadarProductNames(availableParms)\n",
    "print(productIDs)\n",
    "print(productNames)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a href=\"#top\">Top</a>\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Function: make_map()\n",
    "\n",
    "In order to plot more than one image, it's easiest to define common logic in a function.  Here, a new function called **make_map** is defined.  This function uses the [matplotlib.pyplot package (plt)](https://matplotlib.org/3.3.3/api/_as_gen/matplotlib.pyplot.html) to create a figure and axis.  The coastlines (continental boundaries) are added, along with lat/lon grids."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_map(bbox, projection=ccrs.PlateCarree()):\n",
    "    fig, ax = plt.subplots(figsize=(16, 16),\n",
    "                           subplot_kw=dict(projection=projection))\n",
    "    ax.set_extent(bbox)\n",
    "    ax.coastlines(resolution='50m')\n",
    "    ax.add_feature(cfeature.STATES, linestyle=':', edgecolor='black', linewidth=0.5)\n",
    "    gl = ax.gridlines(draw_labels=True)\n",
    "    gl.top_labels = gl.right_labels = False\n",
    "    gl.xformatter = LONGITUDE_FORMATTER\n",
    "    gl.yformatter = LATITUDE_FORMATTER\n",
    "    return fig, ax"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a href=\"#top\">Top</a>\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot the Data!\n",
    "\n",
    "Here we'll create a plot for each of the Radar Product Names from our *productNames* array from the [previous section](#Radar-Product-IDs-and-Names)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Recs :  1\n",
      "Time : 2024-05-22 21:49:25\n",
      "Name : klwx_0.0_464_464\n",
      "Prod : Composite Refl\n",
      "Range: 5.0  to  55.0  (Unit : dBZ )\n",
      "Size : (464, 464)\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1152x1152 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No levels found for Correlation Coeff\n",
      "No levels found for Diff Reflectivity\n",
      "\n",
      "Recs :  1\n",
      "Time : 2024-05-22 21:49:25\n",
      "Name : klwx_0.0_230_360_0.0_359.0\n",
      "Prod : Digital Hybrid Scan Refl\n",
      "Range: -14.5  to  56.0  (Unit : dBZ )\n",
      "Size : (230, 360)\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1152x1152 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Recs :  1\n",
      "Time : 2024-05-22 21:49:25\n",
      "Name : klwx_0.0_920_360_0.0_359.0\n",
      "Prod : Digital Inst Precip Rate\n",
      "Range: 7.0555557e-09  to  3.5997444e-05  (Unit : m*sec^-1 )\n",
      "Size : (920, 360)\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAxoAAAMlCAYAAAD0bIUqAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8rg+JYAAAACXBIWXMAAAsTAAALEwEAmpwYAAEAAElEQVR4nOzdd1xT5/4H8M9JQoCwt0wnqCgoCi5UELWOatU6WrXu1ra2rq5fe3tbq729Hbetq9XacbWt1Q5tq7Z13Kq4RUBFQFHc7L0hCUnO74+YkIQAARNOEr7v1ysv4OSMbwjj+Z7n+T4Pw7IsCCGEEEIIIcSYeFwHQAghhBBCCLE+lGgQQgghhBBCjI4SDUIIIYQQQojRUaJBCCGEEEIIMTpKNAghhBBCCCFGJ+A6gKaMHz+eLS4ubvVxtbW1EIlEJojIvEmlUgiFQq7DICZA7611ovfVetF7a73ovbUuRUVF8PLyovf1ISUnJx9mWXa8vufMNtEoLi5GUlJSq4/75ZdfMHPmTBNEZN7i4+MRGxvLdRjEBOi9tU70vlovem+tF7231uXWrVu4desWhEIhva8PgWEYz6aes7qhUzk5OVyHQAghhBBCzFz37t1RXFwMhULBdShWy+oSDXt7e65DIIQQQgghFmD06NGoqKjgOgyrZXWJxsCBA7kOgRBCCCGEWAAfHx8IhUL873//4zoUq2R1iUZ2djbXIRBCCCGEEAvh4OAAPp+Pffv2gWVZrsOxKlaXaNy9e5frEAghhBBCiAWJi4tD79698fnnn+PGjRuoq6vjOiSrYLazTrUVTU9GCCGEEEJaKyQkBN26dUNiYiKuXr0KuVyO8vJyiEQijBgxAgEBAVyHaHGsLtGgGg1CCCGEENIWAoEAQ4cO1dpWU1ODY8eO4cqVKxg3bhz4fD5H0Vkeqxs61ZZF/gghhBBCCNHHwcEBkydPRmBgIP744w+uw7EoVpdoZGZmch0CIYQQQgixMmFhYXBzc8PevXtRW1vLdTgWweqGTgkEVveSCCGEEEKIGRg5ciRycnKwf/9+8Pl8CIVCODk5wcHBARKJBBKJBHfu3IGnpyfs7e0xePBguLu7cx02Z6yuVT5gwACuQyCEEEIIIVbK398fTz75JACgtrYW169fh6urK2xtbWFnZ4fo6GjY29ujqKgIp0+fRnl5OWbOnKm1qLRqNXIez+oGF2mxukSjurqa6xAIIYQQQkgHIBKJEBERofc5b29vPPbYY6irq8N3330HFxcX2NraQiqVgs/no6CgADNnzoS3t3c7R91+rC7RuHr1Kh555BGuwyCEEEIIIQT29vZYunQpSkpK4OjoCDs7OwCARCLBjz/+iAULFnAcoelYXX8NwzBch0AIIYQQQogawzDw9PRUJxkAYGtrC1dXV1y7do3DyEzL6hINWkeDEEIIIYRYgsceewxHjx5V12xYG6tLNOrr67kOgRBCCCGEkBYxDIPFixfjiy++4DoUk7C6RCMlJYXrEAghhBBCCDGISCTChAkTsHfvXq5DMTqrSzQIIYQQQgixJF27doVQKLS6haetLtHo378/1yEQQgghhBDSKuPHj7e6kTlWl2jw+XyuQyCEEEIIIaRVbGxsrK4o3OoSjYsXL3IdAiGEEEIIIa1SVVWF+/fvY+vWraisrOQ6HKOwugX7WJblOgRCCCGEEEKaJJfLkZGRAYFAgEuXLqG0tBQuLi5YsmQJpFIpTp8+DR6PBy8vL4teusHqEo0+ffpwHQIhhBBCCCF6JSQk4MKFC3j88cchEAgwdOhQeHp6wsHBQb3PxIkTUVdXh6tXr2LDhg2YMGECevbsyWHUbWN1iYbmm0QIIYQQQgjXqqurcfjwYdy/fx/h4eF48cUXwTBMs8fY29tj4MCBGDhwIH799VecOXMGo0aNQmBgIAQCy2jCW0aUrZCcnIxhw4ZxHQYhhBBCCCEAgAsXLmDYsGGYPn16m45//PHHwbIsLly4gLS0NFRXV2PWrFlmPwmS1SUacrmc6xAIIYQQQggBAJw5cwZCoRC+vr4PdR6GYTB48GAAQE1NDT7//HN4enriySefBI9nnvM7mWdUDyE4OJjrEAghhBBCCMGWLVsgl8uNPtrGwcEBK1aswMiRI/Hdd9/h9OnTuH37tlGvYQxW16Ph5eXFdQiEEEIIIaQDk8vl2LRpE5577jnY29ub7DoBAQFYuHAhcnNzkZubi5MnT2LIkCHo1auXya7ZGlbXo5GUlMR1CIQQQgghpIO6evUqNm/ejNWrV5s0ydDk5+eHyMhIzJ8/HxkZGdiwYQNKSkra5drNsboeDalUynUIhBBCCCGkg5FKpdi1axfc3NywatUqTmLg8XiYOnUqWJbF77//Dh6PB3d3d0RHR3NSx2F1iUaXLl24DoEQQgghhHQgLMviyy+/xOzZs+Hh4cF1OGAYBtOmTYNCoUB+fj527NgBoVCIp556ql3jsLpEw9/fn+sQCCGEEEJIB/Lrr7/i6aefhp2dHdehaOHxePDz88PixYuRnZ2NjRs3IiIiAhEREXBycjL99U1+hXZ28eJFrkMghBBCCCEdSOfOnc0uydAVEBCAlStXwsfHBwkJCThw4IDJZ6qyukSjrq6O6xAIIYQQQkgHcunSJa5DMFjPnj0xZswYxMXF4fr169iwYQPKyspMci0aOkUIIYQQQkgbnTt3Dt27d+c6jFZzcHDAhAkTMH78eGzfvh1CoRAjR45EUFCQ0a5hdYmGJb7RhBBCCCHEMl24cAErV67kOow2YxgGixcvhkwmw6VLl3D+/HnY2Nhg2rRpD31uqxs6lZyczHUIhBBCCCGkA7hy5QpGjBjBdRhGIRAIEBUVhZkzZ2LQoEHYsGEDjh49CplM1uZzWl2iUVNTw3UIhBBCCCGkA6ioqLC6pRUYhoG/vz9WrVoFFxcX/Pzzz0hKSkJ+fn6rz2V1iYa3tzfXIRBCCCGEECtXXV2NqqoquLu7cx2KyURGRmLOnDnw8fFBWloatm3bhtLSUoOPt7oajb59+3IdAiGEEEIIsXK7d+/GwoULuQ6jXQQGBiIwMBCjR4/GN998A7lcjqeeegoODg7NHmd1iUZiYiLCw8O5DoMQQgghhFipu3fvwsHBATY2NlyH0q4YhsHTTz8NsViMP//8s+MlGlVVVVyHQAghhBBCrNhvv/2G1atXcx0GZ+zs7DB9+nTU19c3u5/VJRpubm5ch0AIIYQQQqwQy7LYuHFjh04yNLXUo2N1xeADBw7kOgRCCCGEEGJlVEnGqlWruA7FYlhdopGYmMh1CIQQQgghxIrU19dj48aNFr0wHxesbuhURUUF1yEQQgghhBArUVdXh6+//hovvvgiGIbhOhyLYnWJhpOTE9chEEIIIYQQK1BZWYmff/4ZixYtgkBgdc1mk7O679igQYO4DoEQQgghhFi4c+fO4e7du5g0aRIcHR25DsciWV2NRkpKCtchEEIIIYQQC3Xjxg1s3LgRfD4fU6ZMQadOnbgOyWJZXY9GcXEx1yEQQgghhBALI5FI8NVXX8HX15eKvo3E6hKNllYoJIQQQgghRJNCocDWrVvx4osvUi2GEVnd0KnIyEiuQyCEEEIIIRaEx+OhU6dOlGQYmdUlGjdv3uQ6BEIIIYQQYkE+++wzmlDIBKwubcvJyeE6BEIIIYQQYiEKCwvx9NNPw87OjutQrI7V9WjY29tzHQIhhBBCCLEA69evh7e3NyUZJmJ1icbAgQO5DoEQQgghhJi5DRs2YNWqVVyHYdWsLtHIzs7mOgRCCCGEEGKmFAoFNm3ahBdeeAEMw3AdjlWzuhqNu3fvch0CIYRYvDdF2l/z5IYf29y+Cr5h51Pt19L292oNj4sQQk6ePIkrV67g2WefhY2NDdfhWD2rSzSEQiHXIRBCiNl7y1b/dt2GvOLBfwmZnv15ckDYxoZ+U4mEoc8DytjecAZ4MsOvy5MDAqny8zWs4ccRQixTcXExampqcPXqVWRkZCAqKgovvvgi12F1GAYnGgzD8AEkAchhWXYSwzAzAbwDoDeAQSzLJmns+x8AowC8zLLsCYZhugC4A2AFy7KbH+z
      "text/plain": [
       "<Figure size 1152x1152 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Recs :  1\n",
      "Time : 2024-05-22 21:49:25\n",
      "Name : klwx_0.0_13_13\n",
      "Prod : Digital Precip Array\n",
      "Range: -60.0  to  690.0  (Unit : count )\n",
      "Size : (13, 13)\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1152x1152 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Recs :  1\n",
      "Time : 2024-05-22 21:49:25\n",
      "Name : klwx_0.0_460_360_0.0_359.0\n",
      "Prod : Digital Vert Integ Liq\n",
      "Range: 0.0  to  36.763355  (Unit : kg*m^-2 )\n",
      "Size : (460, 360)\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1152x1152 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Recs :  1\n",
      "Time : 2024-05-22 21:49:25\n",
      "Name : klwx_0.0_346_360_0.0_359.0\n",
      "Prod : Enhanced Echo Tops\n",
      "Range: nan  to  nan  (Unit : m )\n",
      "Size : (346, 360)\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAyQAAAMlCAYAAACCVjehAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8rg+JYAAAACXBIWXMAAAsTAAALEwEAmpwYAAEAAElEQVR4nOzdd3hUZd7/8feZkt57TwhJCCEQSiB0QpNiWRWwYEHFghUsj6uu66O7j+6qu+Lqrq66KnaxLKgoCEhCJ5SE0FsgCem915k5vz+Q+YG0AJOclO/rurzw5LTPyZmB+c597vtWVFVFCCGEEEIIIbSg0zqAEEIIIYQQoueSgkQIIYQQQgihGSlIhBBCCCGEEJqRgkQIIYQQQgihGSlIhBBCCCGEEJoxaB3gXKZOnaqWlZVpHeM0LS0tmEwmDAYDZrMZR0dHrSO1SUtLC3Z2dlrHsGpubkan09Hc3IyiKDg4OKDT6bBYLJjNZlRVtf6OW1tbUVUVe3t76zKAvb09qqrS0tKCXq/HaDQC0NTUBIDRaESv11uXDQYDBoOBpqYmdDqdddlkMqEoCnq9Hp1Oh6qq6HTdo07v6Pve3NyM2Wy23k+hnc72nhcdR+59zyT3vee61HtfV1eHi4tLOyQ6tx07dvysqurUs63rtAVJWVkZ27dv1zqGVWpqKqGhofTu3VvrKBctNTWV5ORkrWOcVWNjI1lZWQQHB1NVVYXZbMbJyQkvLy9aWlpQFAVHR0f0ej2Kopz1GMXFxdTW1uLg4MDRo0exs7Ojb9++uLi4oNfrT9tWVVWampowmUwYjUYqKyupr69HVVW8vb05fvw4FRUV6PV6Bg4ciMViwcPDowN+E7bXnve9tbWVwsJCnJ2dOXjwIC0tLcTExBAQECDFSCfQmd/zon3Jve+Z5L73XJdy7ysrK1m+fDmzZ89un1DnoCiKz7nWddqCpLMwmUxs2LBB3ujtxNHRkfj4eAA8PT1PW+fg4NCmY/j7++Pv7w9ASEgITU1NHDt2DC8vLwoLC6mqqkKn09GnTx9KS0spLS3FwcGBPn36YDKZCAsLs3674OjoSHV1NQcOHGDNmjUEBATg7OxM//79bXjVXVtqaioGg4H4+HgcHR0ZOXKk1pGEEEII0UYfffQRDz/8sNYxTiMFyTmoqsrx48fJzs6WYqSLcXBwoG/fvgDWQuWkk8snH+Wyt7dn69atmEwmfH19cXNzQ6/Xyz0/h5SUFJKTk8/ZWiWEEEKIzstsNgOc8QSJ1qQgOYvW1lbS09Px9fVl7NixWscR7eDU1pfRo0drmKTzU1WV/Px8Dh8+zPjx47WOI4QQQohLtHbtWu644w6tY5xBCpLfqK2t5cCBAwwePNjaUVqInqilpYXq6moKCwtxcnKSYkQIIYTo4hwcHDq8M3tbSEHyq4aGBkpKSmhsbGTo0KFaxxFCMydbQ/z8/AgKCmLAgAFaRxJCCCGEDezbt69T9v2UggQoLy+nsLAQf39/IiIitI4jRIc7dOgQTk5OlJSU4OLiIn1ohBBCiG5m6dKlnbIYASlIyM3Npa6ujvDwcFxdXbWOI0SH27RpE3369MHDw4OQkBCt4wghhBCiHWRnZ3PttddqHeOsemxBUlNTw759++jbty8hISEyd4LocVRVJTMzk759+54x5LIQQgghuo99+/YxYcIErWOcU48sSDZu3IiDgwNJSUkyfKnokdatW4der2fo0KEyu68QQgjRzen1ery9vbWOcU49piBRVZXq6moyMjIYNWqUfAgTPZKqqqxdu5YxY8Z0ujHIhRBCCNE+Nm3axJ133ql1jHPqEQVJeXk5+fn5KIoiQ5eKHstsNrN+/XrpsC6EEEL0IMeOHcPR0VHrGOfVrQuSsrIyiouL8fb2pl+/fvKNsOixmpubSUtLk2JECCGE6GGWLFnCY489pnWM8+q2BcnatWvx9/cnJiZGJjgUPVpVVRX79u1j7NixWkcRQgghRAdqamoiMjJS6xgX1C0LkpSUFMaOHSstIqLHUlUVi8VCamoq7u7ujBgxQutIQgghhOhgpaWlXWKC425XkKxdu5Zx48bJML6iR2ppaSE/Px+LxUJzczPTpk3TOpIQQgghNLJ27VpuuukmrWNcULf61L5nzx7i4uKkGBE9Unl5OZmZmQQGBtK7d+9O34FNCCGEEO1HVVVKS0sxGDp/+0PnT3gRGhoa8PX11TqGEB1u27ZtuLi4MGDAAOzt7bWOI4QQQgiNffzxx9x4441ax2iTblOQ1NfXExwcrHUMITpEY2Mjqqqyfft2zGYzSUlJODk5aR1LCCGEEJ2Evb09QUFBWsdok25TkDQ2NnaJJikhLse2bduor68nJiYGvV7P6NGj5RFFIYQQQpymrKysS3RmP6nbfII/cOAAo0eP1jqGEDanqirNzc1s2bKFoUOH4uzsrHUkIYQQQnRiR44cwd3dXesYbdZlC5KqqioyMjJQFAUPDw/69eundSQhbK64uJiqqioaGxtlUkMhhBBCtMnmzZt59NFHtY7RZl3uWY/Gxka2bt3KsWPHSEpKwtHRkaqqKjw9PbWOJoTNtLa2kp6ejk6no1evXgwcOFDrSEIIIYToAjIyMoiNjdU6xkXpMi0keXl5NDc3oygKQ4YMQa/Xk5qaSnJyMsePH9c6nhA2YTab2bx5M3q9nqSkJOkfIoQQQoiLsnfvXm699VatY1yULlGQNDU1kZGRwRVXXGEd0jQlJYXk5GRUVaWpqUnjhEJcnpqaGnJzc6moqGDEiBEYjUatIwkhhBCii2lpaSE6OlrrGBetUxckqqpisVjQ6XSnza+QkpLC+PHjgROjCDQ3N2sZU4hLtm3bNlpbWwkODiY6OlrmEBFCCCHEJaupqaGqqkrrGBet0xYk9fX1lJSUUFBQQENDAy4uLoSHh7Nv3z7Cw8Opq6ujubmZPXv2SGdf0WXU1NRQWFiIk5MTubm5KIqCnZ0d4eHhWkcTQgghRBf3ySefMH/+fK1jXLROW5A4Ozvj7++Pv7//aT+PjY2lsrKS6upqKioqpBgRnV5DQwNFRUXk5ubi6urKoEGD0Ol0hIaGsnPnTgoKCrSOKIQQQogurrW1Fb1e3yX7n3baguRcdDod3t7eADIzu+i0KioqyMzMxN3dnfDwcDw8PIiMjDxjO51O1yX/4hBCCCFE5/Lf//6Xu+66S+sYl6TLFSRCdGZNTU1kZmbi4OBAcnIyiqKcd/vAwEBcXV07KJ0QQgghuqvg4GCcnJy0jnFJpCARwgaKiopobGzEbDaTmJiIXq9v034NDQ1UV1e3czohhBBCdGeqqlJcXNxln7qQgkSIS9DY2EhzczMZGRkoikLv3r0JCAjA0dHxoo5TWVlJQUGBTHwohBBCiEv29ddfM3jwYK1jXDIpSIS4SAcOHECn0+Hu7m4dfvpSKYpywce6hBBCCCHOJy8vjxtuuEHrGJdMChIhTtHY2MiuXbsYPHgwBoPhtGKhqamJ9PR0Bg4ciKOjo00KiYCAAOlDIoQQQohLtmXLli4/6qwUJEL8Ki0tDVVVSUhIIC0tjeDgYAIDAykpKeHo0aPY29szYsQIm7ZotLS00NDQYLPjCSGEEKJnsbOzIyYmRusYl6Vr9nwRwkZUVaWpqYnPP/8cZ2dn7Ozs2LJlC6WlpVRVVVFXV4ednR3Jyck2L0YAysvLyc3NtekxhRBCCNFz5Obm4uLionWMyyItJKLHMplMHDp0iJKSEgYMGEDv3r2prKykpqaG8ePH4+7u3u79O7rqaBhCCCGE0F5zczMWi0XrGJdNChLRY9XW1uLh4UFBQQGOjo5kZ2ej1+s79DlMPz8/7O3tO+x8QgghhOg+qquru3Rn9pOkIBE9UmZmJs3NzQwbNgw/Pz8MBm3eCqqqYjabNTm3EEIIIbqumpoazT6/2Fr3uAoh2sBsNlNVVcXevXuJj4/Hy8sLQNM3c2lpKbm5ucTFxWmWQQghhBBdT05ODu7u7lrHsAkpSES3Z7FYOH78OA0NDRiNRsaOHat1JCGEEEKIy5KTk9PlO7OfJAWJ6LZUVWXjxo0ADB06FDs7u043CaGPjw96vV7
      "text/plain": [
       "<Figure size 1152x1152 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Recs :  1\n",
      "Time : 2024-05-22 21:49:25\n",
      "Name : klwx_0.0_920_360_0.0_359.0\n",
      "Prod : Hybrid Hydrometeor Class\n",
      "Range: 1.0  to  10.0  (Unit : count )\n",
      "Size : (920, 360)\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1152x1152 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No levels found for Hydrometeor Class\n",
      "No levels found for Melting Layer\n",
      "\n",
      "Recs :  0\n",
      "\n",
      "Recs :  1\n",
      "Time : 2024-05-22 21:49:25\n",
      "Name : klwx_0.0_115_360_359.0_359.0\n",
      "Prod : One Hour Accum\n",
      "Range: 0.0  to  0.0254  (Unit : m )\n",
      "Size : (115, 360)\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1152x1152 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Recs :  1\n",
      "Time : 2024-05-22 21:49:25\n",
      "Name : klwx_0.0_920_360_0.0_359.0\n",
      "Prod : One Hour Unbiased Accum\n",
      "Range: 2.5504256e-05  to  0.033920657  (Unit : m )\n",
      "Size : (920, 360)\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1152x1152 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No levels found for Reflectivity\n",
      "No levels found for Specific Diff Phase\n",
      "No levels found for Storm Rel Velocity\n",
      "\n",
      "Recs :  1\n",
      "Time : 2024-05-22 21:49:25\n",
      "Name : klwx_0.0_920_360_0.0_359.0\n",
      "Prod : Storm Total Accum\n",
      "Range: 0.000254  to  0.051054  (Unit : m )\n",
      "Size : (920, 360)\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1152x1152 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Recs :  0\n",
      "No levels found for User Select Accum\n",
      "No levels found for Velocity\n",
      "\n",
      "Recs :  1\n",
      "Time : 2024-05-22 21:49:25\n",
      "Name : klwx_0.0_116_116\n",
      "Prod : Vert Integ Liq\n",
      "Range: 1.0  to  35.0  (Unit : kg*m^-2 )\n",
      "Size : (116, 116)\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1152x1152 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# suppress a few warnings that come from plotting\n",
    "warnings.filterwarnings(\"ignore\",category =RuntimeWarning)\n",
    "warnings.filterwarnings(\"ignore\",category =UserWarning)\n",
    "\n",
    "# Cycle through all of the products to try and plot each one\n",
    "for prod in productNames:\n",
    "    \n",
    "    request.setParameters(prod)\n",
    "    availableLevels = DataAccessLayer.getAvailableLevels(request)\n",
    "    \n",
    "    # Check the available levels, if there are none, then skip this product\n",
    "    if availableLevels:\n",
    "        request.setLevels(availableLevels[0])\n",
    "    else:\n",
    "        print(\"No levels found for \" + prod)\n",
    "        continue\n",
    "\n",
    "    cycles = DataAccessLayer.getAvailableTimes(request, True)\n",
    "    times = DataAccessLayer.getAvailableTimes(request)\n",
    "\n",
    "    if times:\n",
    "        print()\n",
    "        response = DataAccessLayer.getGridData(request, [times[-1]])\n",
    "        print(\"Recs : \", len(response))\n",
    "        \n",
    "        if response:\n",
    "            grid = response[0]\n",
    "        else:\n",
    "            continue\n",
    "        data = grid.getRawData()\n",
    "        lons, lats = grid.getLatLonCoords()\n",
    "        \n",
    "        print('Time :', str(grid.getDataTime()))\n",
    "        flat = np.ndarray.flatten(data)\n",
    "        print('Name :', str(grid.getLocationName()))\n",
    "        print('Prod :', str(grid.getParameter()))\n",
    "        print('Range:' , np.nanmin(flat), \" to \", np.nanmax(flat), \" (Unit :\", grid.getUnit(), \")\")\n",
    "        print('Size :', str(data.shape))\n",
    "        print()\n",
    "\n",
    "        cmap = plt.get_cmap('rainbow')\n",
    "        bbox = [lons.min()-0.5, lons.max()+0.5, lats.min()-0.5, lats.max()+0.5]\n",
    "        fig, ax = make_map(bbox=bbox)\n",
    "        cs = ax.pcolormesh(lons, lats, data, cmap=cmap)\n",
    "        cbar = fig.colorbar(cs, extend='both', shrink=0.5, orientation='horizontal')\n",
    "        cbar.set_label(grid.getParameter() +\" \" + grid.getLevel() + \" \" \\\n",
    "                       + grid.getLocationName() + \" (\" + prod + \"), (\" + grid.getUnit() + \") \" \\\n",
    "                       + \"valid \" + str(grid.getDataTime().getRefTime()))\n",
    "        plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a href=\"#top\">Top</a>\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## See Also\n",
    "\n",
    "\n",
    "### Related Notebooks\n",
    "\n",
    "* [Grid Levels and Parameters](https://unidata.github.io/python-awips/examples/generated/Grid_Levels_and_Parameters.html)\n",
    "\n",
    "\n",
    "### Additional Documention\n",
    "\n",
    "**python-awips**\n",
    "\n",
    "- [DataAccessLayer.changeEDEXHost()](http://unidata.github.io/python-awips/api/DataAccessLayer.html#awips.dataaccess.DataAccessLayer.changeEDEXHost)\n",
    "- [DataAccessLayer.newDataRequest()](http://unidata.github.io/python-awips/api/DataAccessLayer.html#awips.dataaccess.DataAccessLayer.newDataRequest)\n",
    "- [DataAccessLayer.getRadarProductIDs()](http://unidata.github.io/python-awips/api/DataAccessLayer.html#awips.dataaccess.DataAccessLayer.getRadarProductIDs)\n",
    "- [DataAccessLayer.getRadarProductNames()](http://unidata.github.io/python-awips/api/DataAccessLayer.html#awips.dataaccess.DataAccessLayer.getRadarProductNames)\n",
    "\n",
    "**matplotlib**\n",
    "\n",
    "- [matplotlib.pyplot()](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.html)\n",
    "- [matplotlib.pyplot.axes()](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.axes.html)\n",
    "- [matplotlib.pyplot.figure()](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.figure.html)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a href=\"#top\">Top</a>\n",
    "\n",
    "---"
   ]
  }
 ],
 "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": "3.9.5"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": true,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": true,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": true
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}