{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "\n# Plot Max-CAPPI\n\nThis is an example of how to plot a Max-CAPPI\nwithin a Py-ART grid display object.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "print(__doc__)\n\n# Author: Hamid Ali Syed (syed44@purdue.edu)\n# License: BSD 3 clause\n\nimport matplotlib.pyplot as plt\nimport numpy as np\n\nimport pyart\nfrom pyart.testing import get_test_data"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## MAX-CAPPI Display\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "# Define and Read in the test data\ngrid_file = get_test_data(\"20110520100000_nexrad_grid.nc\")\ngrid = pyart.io.read_grid(grid_file)\n\n\n# Create a grid display\ngdisplay = pyart.graph.GridMapDisplay(grid)\ngdisplay.plot_maxcappi(field=\"REF\", range_rings=True, add_slogan=True)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Second Example\n\nLet's read in a Nexrad data and create a grid.\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "import logging\nfrom datetime import datetime\n\nimport fsspec\nimport pytz\n\n\ndef download_nexrad(timezone, date, site, local_date=False):\n    \"\"\"Download NEXRAD radar data from an S3 bucket.\"\"\"\n    try:\n        utc_date = (\n            pytz.timezone(timezone).localize(date).astimezone(pytz.utc)\n            if local_date\n            else date\n        )\n        logging.info(f\"Time: {utc_date}\")\n\n        fs = fsspec.filesystem(\"s3\", anon=True)\n        nexrad_path = utc_date.strftime(\n            f\"s3://unidata-nexrad-level2/%Y/%m/%d/{site}/{site}%Y%m%d_%H*\"\n        )\n        files = sorted(fs.glob(nexrad_path))\n\n        return [file for file in files if not file.endswith(\"_MDM\")]\n    except Exception as e:\n        logging.error(\"Error in processing: %s\", e)\n        return []\n\n\n# Load NEXRAD data from S3 Bucket\nsite = \"PHWA\"\ntimezone = \"UTC\"\ndate = datetime(2024, 8, 25, 8, 29)\n\n# Correctly passing the site and timezone\nfile = download_nexrad(timezone, date, site, local_date=False)[0]\n\n\n# Read the data using nexrad_archive reader\nradar = pyart.io.read_nexrad_archive(\"s3://\" + file)\n\n# Create a 3D grid\n# Mask out last 10 gates of each ray, this removes the \"ring\" around the radar.\nradar.fields[\"reflectivity\"][\"data\"][:, -10:] = np.ma.masked\n\n# Exclude masked gates from the gridding\ngatefilter = pyart.filters.GateFilter(radar)\ngatefilter.exclude_transition()\ngatefilter.exclude_masked(\"reflectivity\")\ngatefilter.exclude_outside(\"reflectivity\", 10, 80)\n\n# Perform Cartesian mapping, limit to the reflectivity field.\nmax_range = np.ceil(radar.range[\"data\"].max())\nif max_range / 1e3 > 250:\n    max_range = 250 * 1e3\n\ngrid = pyart.map.grid_from_radars(\n    (radar,),\n    gatefilters=(gatefilter,),\n    grid_shape=(30, 441, 441),\n    grid_limits=((0, 10000), (-max_range, max_range), (-max_range, max_range)),\n    fields=[\"reflectivity\"],\n)\n\n# Create a grid display\ngdisplay = pyart.graph.GridMapDisplay(grid)\nwith plt.style.context(\"dark_background\"):\n    gdisplay.plot_maxcappi(field=\"reflectivity\", cmap=\"HomeyerRainbow\", add_slogan=True)"
      ]
    }
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