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": 15,
   "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": 16,
   "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": 17,
   "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', '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": 18,
   "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', '197', '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', 'RRC', 'Rain Rate Classification', '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": 19,
   "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', '197', '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', 'Rain Rate Classification', '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": 20,
   "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": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Recs :  1\n",
      "Time : 2025-02-12 23:42:47\n",
      "Name : klwx_0.0_464_464\n",
      "Prod : Composite Refl\n",
      "Range: 5.0  to  40.0  (Unit : dBZ )\n",
      "Size : (464, 464)\n",
      "\n"
     ]
    },
    {
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       "<Figure size 1600x1600 with 2 Axes>"
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     "metadata": {},
     "output_type": "display_data"
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    {
     "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 : 2025-02-12 23:48:37\n",
      "Name : klwx_0.0_230_360_0.0_359.0\n",
      "Prod : Digital Hybrid Scan Refl\n",
      "Range: -29.0  to  39.5  (Unit : dBZ )\n",
      "Size : (230, 360)\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1600x1600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Recs :  1\n",
      "Time : 2025-02-12 23:48:37\n",
      "Name : klwx_0.0_920_360_0.0_359.0\n",
      "Prod : Digital Inst Precip Rate\n",
      "Range: 7.0555557e-09  to  2.998611e-06  (Unit : m*sec^-1 )\n",
      "Size : (920, 360)\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1600x1600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Recs :  1\n",
      "Time : 2025-02-12 23:48:37\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 1600x1600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Recs :  1\n",
      "Time : 2025-02-12 23:48:37\n",
      "Name : klwx_0.0_460_360_0.0_359.0\n",
      "Prod : Digital Vert Integ Liq\n",
      "Range: 0.0  to  2.2850013  (Unit : kg*m^-2 )\n",
      "Size : (460, 360)\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1600x1600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Recs :  1\n",
      "Time : 2025-02-12 23:48:37\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": "iVBORw0KGgoAAAANSUhEUgAABHEAAAR1CAYAAAA9eVlXAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjAsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvlHJYcgAAAAlwSFlzAAAPYQAAD2EBqD+naQABAABJREFUeJzs3Xd0VNX7/v33pCekEkroCb330HsxgBTpSFGwUESliFLEhggIKIKoCFJUBKRJk96L9CKR0GsogRDS6yQzzx8+5PflY6MknElyvdZiQSbn7HPN5BCYO3vf22S1Wq2IiIiIiIiIiIhNszM6gIiIiIiIiIiI/DcVcUREREREREREsgAVcUREREREREREsgAVcUREREREREREsgAVcUREREREREREsgAVcUREREREREREsgAVcUREREREREREsgAHowNktKSkJFJSUoyOISIiIiIiIiLy0JycnHBxcfnXY7JVEScpKYmAgADCwsKMjiIiIiIiIiIi8tD8/Py4fPnyvxZyslURJyUlhbCwMEJDQ/H09DQ6ToY4ffo0165dw8PDg1KlSpE3b16jIz11ZrOZzZs388wzz+Do6Gh0nAyVlpbG9evXSUxM5Pfff6dOnTosW7aMYcOG8dlnnzFixAimT59Ojx49OHr0KMWLFyc1NRWz2UzRokW5cuUKVatW5dy5c1SoUIHQ0FAKFChAcnIyycnJpKSkcO3aNYoUKcKiRYsYMmQIO3bsoEWLFlgsFuzt7dOzpKamYmdnR3h4OPnz5+fMmTOULFmS48ePU6xYMa5du4aDgwP29vZcuHCBwMBAlixZwvDhw5k6dSojRozg888/p3v37pw8eZKGDRvi7OyMs7Ozga+wbbHFezkxMRGz2czhw4cpX748q1evZsCAAZhMJqOjiQ2zxXtZ5HHpfpbsQveyZCcZfT+fOXOG8+fP065duwxIlzliYmIoUqQIKSkp/1rEMVmtVutTzJWpYmJi8PLyIjo6OlsUcT777DOGDBkCgINDtqq3PRKz2cz69etp06aN/kHKAPeLQUuWLKFu3bokJCRQokQJvLy8cHZ2fuI372lpacTHx3Py5Em8vLzYtWtX+teuSJEiGfQssiZbuZf37dtH+fLlWbRoEQ0bNiQhIYHixYun3wMi/8VW7mWRjKD7WbIL3cuSnWT0/Txo0CBmzJhh0383HraeocbGNuju3bvs3LmT1157DQcHhxxdwJGMV6NGDXx8fBg0aBDlypWjcuXKnDx5ksjISCZOnEhaWhrjx48nLS2NCRMmEBoaysqVKzl16hTBwcH8/vvvREREEB4ezt/VgO3t7dm+fTv169dn9erVdO7cmRMnTrB48WLMZrMBz1juu//1TU5Oxtvbm9dee43KlStTp04d8uXLpwKOiIiIiGQ70dHR2aq4qeqAjdm/fz9Vq1alSJEiuLq6Gh1Hsrn7y51atmwJwJgxYwAYO3Zs+sepqak888wzpKSkYLVauXXrFnZ2dvzyyy/069ePqVOnMmTIEP744w9SU1OxWq2UKlUKq9WaPk6nTp2MeYICgMViYe7cuYwePRqAZs2aGZxIREREROTpmD9/PiVLljQ6RoZREcdGJCUlce3aNaxWK3Z2dpQoUcLoSCLAn0v53N3d0z/29fUF4JVXXgFg2LBhmM1m0tLSqFKlCk5OTg/02hFjRUREkJCQwHPPPWd0FBERERGRpy5//vy0atXK6BgZRsupbMCVK1dITk7mxo0b1KtXT0saJEtxcnIiV65c1K5dG1dXVxVwbITVamXJkiUkJiYSHh6eI5uii4iIiEjOduvWLc6dO5etWpSoiGMgq9XK3bt3OXr0KI6OjjRt2tToSCKSDcydO5eIiAhq1qxJ4cKFqV69utGRRERERESeup9++olBgwYZHSNDZZ9yVBYTFxdHYmIiu3fvpnPnzkbHEZEsLiwsjJiYGE6cOEHv3r1xdnYmT548RscSERERETGExWLBw8Mj2/2fWDNxDGCxWFi0aBG5cuVSAUdEHovZbCYlJYVZs2aRkpLC2rVrKV26NN26ddOSTBERERHJ8bZu3UpSUhJ2dtmr7KGZOE9ZdHQ0P/74I6+//rrRUUQkC7p58yanTp0iNTUVf39/nn/+eRwdHXn11VeNjiYiIiIiYjNMJhM9e/Y0OkaGy14lKRu3fPly7ty5owKOiDyWqVOnkidPHipVqkTr1q0pV64cXl5emEwmo6OJiIiIiNiMlJQUFi9enC0399BMnKfAYrEwY8YMXn/99WzVFVtEno7k5GSOHTvG66+/jpOTE35+fkZHEhERERGxWfv27WPkyJFGx8gUmomTyebPn8+dO3d49dVXVcARkUd27949zGYzDg4OuLi4GB1HRERERMTm7d27N9s1NL5PVYVMcH/r8JUrV/LKK69gb29vdCQRyWLu3r1LSEgICQkJlC1blsDAQKMjiYiIiIjYvOvXr2OxWPD19TU6SqbQTJwMZLVaSU1NZdKkSeTOnZv+/furgCMijyQtLY0JEybg7u5OwYIFadWqFf7+/kbHEhERERHJEqKionj22WeNjpFpNBMng8THx3PixAnS0tIYPXq00XFEJAs6d+4cly5dYsyYMQCULFnS4EQiIiIiIlnL5MmTmTdvntExMo2KOE8oPDwcHx8f5syZw9ChQ42OIyJZVEhICP7+/hQoUMDoKCIiIiIiWVJoaCgvv/xytu5Hq+VUjyklJYVLly6xf/9+7t69qwKOiDy21NRUIiIiMJvNeHh4GB1HRERERCRL+vnnn7N1AQdUxHks+/fvJzk5mXPnztG+fXtt9ysiT2Tq1Kk0bNgQLy8vo6OIiIiIiGRJqamp2NvbU69ePaOjZKrsXaLKYJcuXSI5OZnk5GTc3Nxo1aqV0ZFEJAu7e/cua9euZdSoUUZHERERERHJ0sLDw3F3d8dkMhkdJVNpJs5D2rNnD25ubnh6etKkSRPtOiUij81isTBz5kzc3Nzo2bOn0XFERERERLK8adOm0alTJ6NjZDrNxHkIVqsVi8VC/vz5s31VT0Qyh9ls5uzZswAcOHCA/v374+TkZHAqEREREZGsLzk5mdq1a+Pr62t0lEynmTj/wWq1MmHCBBo3bqwCjog8lu+++w6Ay5cvA1CvXj0VcEREREREMsiqVau4d++e0TGeChVx/oXFYmHDhg28++67RkcRkSzo/PnzbN26lfbt2+Pg4KA+WiIiIiIimcDBwYFevXoZHeOpUBHnX1gsFooUKWJ0DBHJgrZs2UKRIkUIDAwkX758msknIiIiIpIJkpKS2Lt3L25ubkZHeSpUxPkXmzdvxtnZ2egYIpKFREdH8/vvv5M3b14cHBy0bbiIiIiISCb6+eefGThwoNExnhoVcf6BxWKhefPmFC1a1OgoImLjfv/9d6xWK+PHj8dqtQJQtWpVHBzUO15EREREJDMlJSXlqBU0KuL8g4sXL7JmzRpcXFyMjiIiNiYqKoqrV6+ybNkyzpw5w40bN7BYLLz77rt4e3tTpUoVoyOKiIiIiGR7ISEhhIaG5pilVKAtxv9WWload+/epWvXrkZHEREbkpaWxvTp0+nevTvh4eF06dIFk8lE2bJljY4mIiIiIpLjREVF8dJLLxkd46nSTJy/kZKSYnQEEbEx3333HREREbz22msUKlSImjVrqlmxiIiIiIhBrFYr33zzDQEBAUZHeapUxOHPL/5HH33Ezp07AZgxYwZ169Y1NpSI2ITw8HC+/fZb+vXrR758+bTEUkRERETEBpw8eZIhQ4bkuB+s5ugiTmJiIps2beLIkSOMGjUKDw8PAIYNG2ZwMhExmtVqZeLEifj4+NC/f3/s7e2NjiQiIiIiIv+/Xbt24erqanSMpy5HFnFu3rxJSkoKc+bMISgoiMDAQM6cOYPVauXmzZv8+OOPRkcUEYOkpaVx+PBhNm/ezOjRo3FwcMhx1X0REREREVuWmJjIzZs3qVChgtFRnrocVcSJjIzk0qVL7Nmzh5SUFN58800A7ty5Q6lSpfD398fX1zfHNUYSEbh69Spms5nJkycTGBhIUFCQ0ZFERERERORv3Llzh2b
      "text/plain": [
       "<Figure size 1600x1600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Recs :  1\n",
      "Time : 2025-02-12 23:48:37\n",
      "Name : klwx_0.0_920_360_0.0_359.0\n",
      "Prod : Hybrid Hydrometeor Class\n",
      "Range: 1.0  to  9.0  (Unit : count )\n",
      "Size : (920, 360)\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1600x1600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "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 : 2025-02-12 23:48:37\n",
      "Name : klwx_0.0_115_360_359.0_359.0\n",
      "Prod : One Hour Accum\n",
      "Range: 0.0  to  0.00254  (Unit : m )\n",
      "Size : (115, 360)\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1600x1600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Recs :  1\n",
      "Time : 2025-02-12 23:48:37\n",
      "Name : klwx_0.0_920_360_0.0_359.0\n",
      "Prod : One Hour Unbiased Accum\n",
      "Range: 2.5482457e-05  to  0.0048997905  (Unit : m )\n",
      "Size : (920, 360)\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1600x1600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Recs :  1\n",
      "Time : 2025-02-12 23:48:37\n",
      "Name : klwx_0.0_920_360_0.0_359.0\n",
      "Prod : Rain Rate Classification\n",
      "Range: 3.0  to  10.0  (Unit : count )\n",
      "Size : (920, 360)\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABGMAAAR1CAYAAAAeIgiCAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjAsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvlHJYcgAAAAlwSFlzAAAPYQAAD2EBqD+naQABAABJREFUeJzs3Xd4U2UDxuFfuluglJa995JtmSJ7IyIKqJRRkOVGBQeogCAqIOKWPWQoKooDlCEbGcr42FM2yCilQElnvj+wsTtpaXuS9Lm9emGTk5Mn6WmbPH3P+5osFosFERERERERERHJEW5GBxARERERERERyU1UxoiIiIiIiIiI5CCVMSIiIiIiIiIiOUhljIiIiIiIiIhIDlIZIyIiIiIiIiKSg1TGiIiIiIiIiIjkIJUxIiIiIiIiIiI5yMPoAFnNbDYTHR1tdAwRERERERERyWW8vLzw8fGxuZ1LlTFms5ly5cpx8eJFo6OIiIiIiIiISC5TtGhR/v77b5uFjEuVMdHR0Vy8eJEzZ87g7++fJfs8evQo77//Pl988UWW7E+SiomJYeXKlbRr1w5PT0+j44gkoeNTHJmOT3FkOj7Fken4FEcTGxvLlClTGDp0KL6+vjo+nVhERASlSpUiOjo6d5UxCfz9/bOsjKlZsyaTJk3Ksv1JUjExMfj5+eHv768fNuJwdHyKI9PxKY5Mx6c4Mh2f4ogefPBBFi1axAsvvKDjM5fQBL42nDp1ijFjxhgdQ0RERERERFxUgwYNKF26NLt27TI6iuQQlTE2lCxZkhdeeMHoGCIiIiIiIuLCOnbsyG+//WZ0DMkhKmNsuHjxIrNnzzY6hoiIiIiIiLiw/PnzExwcbHQMySEqY2wICAigWbNmRscQERERERERF9emTRsAvv32W4OTSHZTGWOD2WzmxIkTRscQERERERGRXOLChQts3brV6BiSjVTG2GCxWIiNjTU6hoiIiIiIiOQSTz75JHv27GH69OlcuXLF6DiSDVxyaeus5OfnR/Xq1Y2OISIiIiIiIrmEh4cHQ4YMYe/evbz33nvW1ZbKlStHoUKFMJlMRkeUu6QyxoZr166xevVqOnXqZHQUERERERERyUVq1qzJpEmT2LdvHxcvXmTWrFn4+vryzz//ULduXfz8/GjYsCGFChUyOqpkkMoYG4oVK8aQIUOMjiEiIiIiIiK5VI0aNahRo4Z1gt/Y2FjOnz/P3r17Wbx4MV5eXgwZMkQjZpyI5oyx4fTp00yaNMnoGCIiIiIiIiLAndOYSpcuTefOnXnuuedo3LgxI0eO5ObNm0ZHEzupjLGhbNmyjBkzxugYIiIiIiIiIqmqXbs2jz76KNOmTSMuLs7oOGIHlTE2nDx5kjfffNPoGCIiIiIiIiJpqlOnDjVr1mTevHncuHHD6Dhig8oYG8qUKcOoUaOMjiEiIiIiIiKSrnbt2lG9enUmTpzIzp07sVgsRkeSNGgCXxvOnTvHxx9/zNSpU42OIiIiIiIiIpKuRo0aUa9ePWbNmsWWLVs4c+YM1atXJz4+nsDAQC5dugSA2WzmypUrBAQEcOHCBcqUKUNkZCShoaFanSkHqIyxISgoiAceeMDoGCIiIiIiIiJ28fLy4sknn7R+Hh4ezrFjx/D396datWrkz58fb29vfHx88Pb2tq7CtHfvXhYuXMjt27cJDQ2lWLFiRj0El6cyxoYbN26wY8cO6xJiIiIiIiIiIs4kICCA4OBgm9vVrFmTmjVrcuPGDSZPnkydOnV48MEHcXd3Jz4+no0bN3Lp0iX+/PNPWrZsSbNmzfDz88uBR+B6VMbY4OHhgb+/v9ExRERERERERHJEvnz5GDNmDL/99hsvvvgihQsXJj4+nmrVqhEcHEzXrl3ZsmULU6dOZeTIkUbHdUoqY2zw9PSkcOHCRscQERERERERyTEmk4kOHTrQoUOHVK9v0aIF//zzDzt37qRevXo5nM75aTUlGyIiIti+fbvRMUREREREREQcStu2bVm7dq3RMZySyhgbihYtSt++fY2OISIiIiIiIuJQAgMDiY2NZf/+/UZHcToqY2w4d+4cn376qdExRERERERERBxO7969WbFiBTdu3DA6ilNRGWNDqVKleOONN4yOISIiIiIiIuJwSpQowYMPPsjnn39OTEyM0XGchsoYG/7++29ee+01o2OIiIiIiIiIOKTKlStTs2ZNpk2bZnQUp6Eyxoby5cvz9ttvGx1DRERERERExGF17NiRoKAg/vjjD6OjOAWVMTacOXOGiRMnGh1DRERERERExKF17dqVVatWERERYXQUh6cyxoYiRYrQq1cvo2OIiIiIiIiIODQ/Pz8eeOAB5s6da3QUh6cyxoawsDCWL19udAwRERERERERh1e3bl2jIzgFlTE2+Pr6Uq5cOaNjiIiIiIiIiDg8k8nE7du3OXPmjNFRHJrKGDt4eHgYHUFERERERETEKbRo0YLvvvuO8+fPGx3FYamMsSEyMpLDhw8bHUNERERERETEoV2+fJnPPvuMlStXEh8fz9mzZ3nxxReJi4szOprD0ZAPGwoWLEjXrl2NjiEiIiIiIiLiEK5du8aePXs4e/Yst2/f5ubNm9y6dQsPDw/at2+fZN6YsLAwTpw4wVtvvcXcuXNxd3c3MLnjUBljw8WLF5k3bx4NGjQwOoqIiIiIiIiIYWJiYliyZAnHjx/nvvvuo3Hjxvj6+uLt7Y2vry9+fn4pbtOhQwcApk2bxqhRo2jYsCHlypWjTp06OZzesaiMsaFUqVK89tprRscQERERERERyXHR0dFs2LCB27dv89dff9GgQQPeeOMNTCZThvbj5+fHu+++C0D//v2ZNGkSX331Fc8880x2xHZ4mjPGhhMnTqiMERERERERkVzn8uXLjBkzhvj4eEqWLMmLL75Ip06dMlzEJDdnzhxMJhNFihRh3LhxLF++PIsSOw+NjLGhfPny1vZOREREREREJLeYP38+/fr1o0qVKlm+76CgIHr06EFERAQmk4l27drx888/c+3aNYoUKZLl9+doNDLGhtOnTzNu3DijY4iIiIiIiIjkmHPnzmEymbKliEnM39+ffPnysXLlSi5evMgrr7zChg0bXH5VY5UxNhQvXpwnn3zS6BgiIiIiIiIiOWLLli18+umnOf5euHTp0sydO5erV68SHh7OoEGDiI6OztEMOUWnKdnwzz//sGjRImrXrm10FBEREREREZFsEx8fz6xZs4iKiuL111/H19fXkBzdunUDwGQycfnyZZ577jkWLVqEt7e3IXmyg8oYG/z9/bn33nuNjiEiIiIiIiKSbQ4cOMCiRYvo3r27wyw73aBBAwC+/vprJk6cSOnSpSlWrBgtWrTA3d3d4HR3R6cp2RAbG0tYWJjRMURERERERESynMVi4aeffuKnn37iueeec5giJjEPDw9GjhxJ7969+fnnnwkPD+ett94yOtZdURljQ0xMDFeuXDE6hoiIiIiIiEiWOn/+POPGjcPd3Z1XXnmFwoULGx3Jpg8++AAfHx/q16/Pu+++y+LFi7FYLEbHyjCdpmSDv78/TZo0MTqGiIiIiIiISJbZvn07v/32G3369KFcuXJGx8mQPHny0LFjR9q2bUtUVBQdO3Zk6dKlnDlzJttXf8oqGhljw5UrV1i2bJnRMURERERERESyxNSpU9m3bx+vvfaa0xUxiXl4eJAnTx5+/fVXIiMjmTx5MqtXr2bbtm1GR7NJZYwNJUqU4Pnnnzc6hoiIiIiIiMhdO3nyJB4eHgwYMAAPD9c5WaZgwYLMmDEDT09P3N3dCQkJITIy0uhYaVIZY8PJkycZN26c0TFERERERERE7tq8efPo3bu30TGyTfPmzQkODmb8+PGYzWa6dOlCeHg4sbGxRkdLwnVqsGxSrlw5xo8fb3QMERERERERkbtiNpvJly8fAQEBRkfJdgmnX/34449MmzYNNzc3goKC6NKlC15eXgan08gYm06dOsWYMWOMjiEiIiIiIiJyV/73v/9RrFgxo2PkKJPJxNChQxk8eDB79+7lxo0bvPDCC0bHUhljS6lSpXjppZe
      "text/plain": [
       "<Figure size 1600x1600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "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 : 2025-02-12 23:48:37\n",
      "Name : klwx_0.0_920_360_0.0_359.0\n",
      "Prod : Storm Total Accum\n",
      "Range: 0.000254  to  0.062484  (Unit : m )\n",
      "Size : (920, 360)\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1600x1600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "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 : 2025-02-12 23:48:37\n",
      "Name : klwx_0.0_116_116\n",
      "Prod : Vert Integ Liq\n",
      "Range: 1.0  to  1.0  (Unit : kg*m^-2 )\n",
      "Size : (116, 116)\n",
      "\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 1600x1600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "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",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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