Plot_RRFS_Reflectivity_Forecast_SkipFirstTwoCrashLast.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0wecjt2rsGsg"
      },
      "source": [
        "# RRFS Data\n",
        "\n",
        "The Rapid Refresh Forecast System (RRFS) is undergoing rapid development. There are prototype products available on the cloud on AWS. Some files have an index file, others do not."
      ],
      "id": "0wecjt2rsGsg"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ncFko210FuRm"
      },
      "source": [
        "## **1 - Start here!**\n",
        "\n",
        "This cell will install conda, which will allow us to install newer versions of some packages we need than pip alone on Google Colab. Run it by mousing over it and clicking the play button that appears on the left side. It will restart the notebook when it finishes, which will make a popup in the lower left corner saying the notebook crashed. It did not, we restarted it! You can close that and move on when it happens."
      ],
      "id": "ncFko210FuRm"
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install -q condacolab\n",
        "import condacolab\n",
        "condacolab.install()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0dPHWHDbjm23",
        "outputId": "64317e0e-be2b-4190-b074-9877748697b2"
      },
      "id": "0dPHWHDbjm23",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "⏬ Downloading https://github.com/jaimergp/miniforge/releases/latest/download/Mambaforge-colab-Linux-x86_64.sh...\n",
            "📦 Installing...\n",
            "📌 Adjusting configuration...\n",
            "🩹 Patching environment...\n",
            "⏲ Done in 0:00:12\n",
            "🔁 Restarting kernel...\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fjW_wFnPGGrv"
      },
      "source": [
        "## **2 - Install and import**\n",
        "\n",
        "This cell will usually take a minute or two to run. It will install and import all the python packages we need."
      ],
      "id": "fjW_wFnPGGrv"
    },
    {
      "cell_type": "code",
      "source": [
        "# This installs and imports all the python packages/modules we need and will use later\n",
        "!mamba install -q -c conda-forge cartopy contextily pyepsg pyproj pygrib netCDF4\n",
        "import numpy as np\n",
        "import os\n",
        "from urllib.request import urlretrieve\n",
        "\n",
        "import matplotlib\n",
        "from matplotlib.colors import LinearSegmentedColormap\n",
        "import matplotlib.patches as mpatches\n",
        "from matplotlib.lines import Line2D\n",
        "import matplotlib.pyplot as plt\n",
        "import matplotlib.axes as maxes\n",
        "import matplotlib.patheffects as PathEffects\n",
        "from matplotlib.path import Path\n",
        "from matplotlib.textpath import TextToPath\n",
        "from matplotlib.font_manager import FontProperties\n",
        "matplotlib.rcParams['font.sans-serif'] = 'Liberation Sans'\n",
        "matplotlib.rcParams['font.family'] = \"sans-serif\"\n",
        "from cartopy import cartopy, crs as ccrs, feature as cfeature\n",
        "\n",
        "import xarray as xr\n",
        "import pygrib\n",
        "import netCDF4 as nc\n",
        "import pandas as pd\n",
        "import json\n",
        "import requests\n",
        "from pyproj.crs import CRS\n",
        "\n",
        "from datetime import datetime, timedelta\n",
        "import contextily as cx\n",
        "\n",
        "import warnings\n",
        "warnings.filterwarnings(\"ignore\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5Ui2YBdPj04u",
        "outputId": "d6cf144a-484c-4000-8c4c-a9fed83775d0"
      },
      "id": "5Ui2YBdPj04u",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.9/site-packages/pyproj/__init__.py:89: UserWarning: pyproj unable to set database path.\n",
            "  _pyproj_global_context_initialize()\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# This installs and imports all the python packages/modules we need and will use later\n",
        "#!mamba install -q -c conda-forge cartopy contextily pyepsg pyproj pygrib netCDF4\n",
        "!pip install netCDF4\n",
        "!pip install contextily\n",
        "!pip install pyepsg\n",
        "!pip install pyproj\n",
        "import numpy as np\n",
        "import os\n",
        "from urllib.request import urlretrieve\n",
        "\n",
        "import matplotlib\n",
        "from matplotlib.colors import LinearSegmentedColormap\n",
        "import matplotlib.patches as mpatches\n",
        "from matplotlib.lines import Line2D\n",
        "import matplotlib.pyplot as plt\n",
        "import matplotlib.axes as maxes\n",
        "import matplotlib.patheffects as PathEffects\n",
        "from matplotlib.path import Path\n",
        "from matplotlib.textpath import TextToPath\n",
        "from matplotlib.font_manager import FontProperties\n",
        "matplotlib.rcParams['font.sans-serif'] = 'Liberation Sans'\n",
        "matplotlib.rcParams['font.family'] = \"sans-serif\"\n",
        "from cartopy import cartopy, crs as ccrs, feature as cfeature\n",
        "\n",
        "import xarray as xr\n",
        "import pygrib\n",
        "import netCDF4 as nc\n",
        "import pandas as pd\n",
        "import json\n",
        "import requests\n",
        "from pyproj.crs import CRS\n",
        "\n",
        "from datetime import datetime, timedelta\n",
        "import contextily as cx\n",
        "\n",
        "import warnings\n",
        "warnings.filterwarnings(\"ignore\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "597d15bb-5355-42d8-98cb-09df66a6abf7",
        "id": "immJqHHbVYee"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: netCDF4 in /usr/local/lib/python3.9/dist-packages (1.6.3)\n",
            "Requirement already satisfied: cftime in /usr/local/lib/python3.9/dist-packages (from netCDF4) (1.6.2)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.9/dist-packages (from netCDF4) (1.22.4)\n",
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: contextily in /usr/local/lib/python3.9/dist-packages (1.3.0)\n",
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            "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.9/dist-packages (from matplotlib->contextily) (1.0.7)\n",
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            "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.9/dist-packages (from requests->contextily) (1.26.15)\n",
            "Requirement already satisfied: charset-normalizer~=2.0.0 in /usr/local/lib/python3.9/dist-packages (from requests->contextily) (2.0.12)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.9/dist-packages (from requests->contextily) (3.4)\n",
            "Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.9/dist-packages (from importlib-resources>=3.2.0->matplotlib->contextily) (3.15.0)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.9/dist-packages (from python-dateutil>=2.7->matplotlib->contextily) (1.16.0)\n",
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting pyepsg\n",
            "  Downloading pyepsg-0.4.0-py3-none-any.whl (6.0 kB)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.9/dist-packages (from pyepsg) (2.27.1)\n",
            "Requirement already satisfied: charset-normalizer~=2.0.0 in /usr/local/lib/python3.9/dist-packages (from requests->pyepsg) (2.0.12)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.9/dist-packages (from requests->pyepsg) (2022.12.7)\n",
            "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.9/dist-packages (from requests->pyepsg) (1.26.15)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.9/dist-packages (from requests->pyepsg) (3.4)\n",
            "Installing collected packages: pyepsg\n",
            "Successfully installed pyepsg-0.4.0\n",
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: pyproj in /usr/local/lib/python3.9/dist-packages (3.5.0)\n",
            "Requirement already satisfied: certifi in /usr/local/lib/python3.9/dist-packages (from pyproj) (2022.12.7)\n"
          ]
        }
      ],
      "id": "immJqHHbVYee"
    },
    {
      "cell_type": "code",
      "source": [
        "from datetime import datetime, timedelta\n",
        "import os, requests\n",
        "from urllib.request import urlretrieve\n",
        "import numpy as np"
      ],
      "metadata": {
        "id": "vZj4JN5vMbZa"
      },
      "id": "vZj4JN5vMbZa",
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install pygrib\n",
        "import pygrib"
      ],
      "metadata": {
        "id": "kQx69k0-N9yG",
        "outputId": "7118e251-7765-42c6-d3ec-a7ae9f2368ca",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "id": "kQx69k0-N9yG",
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: pygrib in /usr/local/lib/python3.9/dist-packages (2.1.4)\n",
            "Requirement already satisfied: pyproj in /usr/local/lib/python3.9/dist-packages (from pygrib) (3.5.0)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.9/dist-packages (from pygrib) (1.22.4)\n",
            "Requirement already satisfied: certifi in /usr/local/lib/python3.9/dist-packages (from pyproj->pygrib) (2022.12.7)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install cartopy\n",
        "from cartopy import cartopy, crs as ccrs, feature as cfeature"
      ],
      "metadata": {
        "id": "-NxGWD1eNAyb",
        "outputId": "d0183651-7eb7-4cbb-a639-e5cac896ebf5",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "id": "-NxGWD1eNAyb",
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: cartopy in /usr/local/lib/python3.9/dist-packages (0.21.1)\n",
            "Requirement already satisfied: pyshp>=2.1 in /usr/local/lib/python3.9/dist-packages (from cartopy) (2.3.1)\n",
            "Requirement already satisfied: pyproj>=3.0.0 in /usr/local/lib/python3.9/dist-packages (from cartopy) (3.5.0)\n",
            "Requirement already satisfied: matplotlib>=3.1 in /usr/local/lib/python3.9/dist-packages (from cartopy) (3.7.1)\n",
            "Requirement already satisfied: shapely>=1.6.4 in /usr/local/lib/python3.9/dist-packages (from cartopy) (2.0.1)\n",
            "Requirement already satisfied: numpy>=1.18 in /usr/local/lib/python3.9/dist-packages (from cartopy) (1.22.4)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.9/dist-packages (from matplotlib>=3.1->cartopy) (0.11.0)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.9/dist-packages (from matplotlib>=3.1->cartopy) (1.4.4)\n",
            "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.9/dist-packages (from matplotlib>=3.1->cartopy) (4.39.3)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.9/dist-packages (from matplotlib>=3.1->cartopy) (23.1)\n",
            "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.9/dist-packages (from matplotlib>=3.1->cartopy) (3.0.9)\n",
            "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.9/dist-packages (from matplotlib>=3.1->cartopy) (1.0.7)\n",
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            "Requirement already satisfied: pillow>=6.2.0 in /usr/local/lib/python3.9/dist-packages (from matplotlib>=3.1->cartopy) (8.4.0)\n",
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            "Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.9/dist-packages (from importlib-resources>=3.2.0->matplotlib>=3.1->cartopy) (3.15.0)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.9/dist-packages (from python-dateutil>=2.7->matplotlib>=3.1->cartopy) (1.16.0)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib\n",
        "from matplotlib.colors import LinearSegmentedColormap\n",
        "import matplotlib.patches as mpatches\n",
        "from matplotlib.lines import Line2D\n",
        "import matplotlib.pyplot as plt\n",
        "import matplotlib.axes as maxes\n",
        "import matplotlib.patheffects as PathEffects\n",
        "from matplotlib.path import Path\n",
        "from matplotlib.textpath import TextToPath\n",
        "from matplotlib.font_manager import FontProperties\n",
        "matplotlib.rcParams['font.sans-serif'] = 'Liberation Sans'\n",
        "matplotlib.rcParams['font.family'] = \"sans-serif\""
      ],
      "metadata": {
        "id": "AM1VxUE5Ul1Y"
      },
      "id": "AM1VxUE5Ul1Y",
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sp5UcB7XGPvG"
      },
      "source": [
        "## **3 - Set options and go!**\n",
        "\n",
        "Set all your options in the form below and go!\n",
        "\n",
        "This is currently hard-coded to the 06UTC model run, with forecast hour=18, resulting in a map valid at 00UTC"
      ],
      "id": "sp5UcB7XGPvG"
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qQyBebPpqYFp",
        "outputId": "aec9e2b6-85a0-4308-885b-38db8aa1929c"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "20230425\n",
            "12\n",
            "038\n"
          ]
        }
      ],
      "source": [
        "#################### FORM STUFF HERE ###################################################################################\n",
        "#@title Plot Config { vertical-output: true, form-width: \"50%\", display-mode: \"form\" }\n",
        "#@markdown Which Initialization Date?\n",
        "init_date = \"2023-04-25\" #@param {type:\"date\"}\n",
        "init_date = datetime.strptime(init_date,'%Y-%m-%d')\n",
        "init_strftime = init_date.strftime('%Y%m%d')\n",
        "print(init_strftime)\n",
        "init_cyc = \"12\" #@param {type:\"string\"}\n",
        "#init_cyc = \"06\"\n",
        "#init_cyc = datetime.strptime(init_cyc,'%H')\n",
        "#init_strfcyc = init_cyc.strftime('%H')\n",
        "#init_strfcyc = int(init_cyc)\n",
        "init_strfcyc = init_cyc\n",
        "print(init_strfcyc)\n",
        "#init_fhr = \"18\" #@param {type:\"date\"}\n",
        "init_fhr = \"038\" #@param {type:\"string\"}\n",
        "#init_fhr = \"30\"\n",
        "#init_fhr = datetime.strptime(init_fhr,'%H')\n",
        "#init_strfhr = init_fhr.strftime('%H')\n",
        "init_strfhr = init_fhr\n",
        "print(init_strfhr)\n",
        "\n",
        "\n",
        "\n"
      ],
      "id": "qQyBebPpqYFp"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "991304b3"
      },
      "source": [
        "Sets the AWS GRIB file to download\n"
      ],
      "id": "991304b3"
    },
    {
      "cell_type": "code",
      "source": [
        "# AWS Direct URL\n",
        "#url = f\"https://noaa-rrfs-pds.s3.amazonaws.com/rrfs_a/rrfs_a.20230403/17/rrfs.t17z.natlev.f015.conus_3km.grib2\"\n",
        "#  https://noaa-hrrr-bdp-pds.s3.amazonaws.com/hrrr.20220201/conus/hrrr.t12z.wrfsfcf36.grib2\n",
        "#print(url)\n",
        "\n",
        "url2 = f\"https://noaa-rrfs-pds.s3.amazonaws.com/rrfs_a/rrfs_a.\" + init_strftime+ \"/\" + init_strfcyc + \"/rrfs.t\" + init_strfcyc + \"z.natlev.f\" + init_strfhr + \".conus_3km.grib2\"\n",
        "print(url2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ez-tn_55mS3w",
        "outputId": "a461f505-40b7-44d1-a9ff-89d2344a7743"
      },
      "id": "ez-tn_55mS3w",
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "https://noaa-rrfs-pds.s3.amazonaws.com/rrfs_a/rrfs_a.20230425/12/rrfs.t12z.natlev.f038.conus_3km.grib2\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fldeZzGrumm5",
        "outputId": "745da5ba-9c11-4ede-e405-b40ff51db6b0"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking for grib file...\n",
            "   > Grib already exists\n",
            "   > Processing grib file\n",
            "     >> Max: 67%\n",
            "     >> Min: -20%\n"
          ]
        }
      ],
      "source": [
        "#################### FORM STUFF HERE ###################################################################################\n",
        "\n",
        "day = \"1\"\n",
        "#orig valid_date = init_date + timedelta(hours = 12, days = int(day))\n",
        "valid_date = init_date + timedelta(hours = int(init_fhr), days = int(day))\n",
        "#valid_date = init_date + timedelta(hours = 18, days = int(day))\n",
        "#orig valid_date_start = valid_date - timedelta(hours = 24)\n",
        "valid_date_start = valid_date - timedelta(hours = 0)\n",
        "valid_strftime = valid_date.strftime('%HZ %m-%d-%Y')\n",
        "\n",
        "hazard = \"Severe\"\n",
        "\n",
        "severe_hazard = \"TOR\"\n",
        "\n",
        "#@markdown What map domain?\n",
        "dom = \"TXOK\" #@param [\"Custom\", \"CONUS\", \"ECONUS\", \"---- WESTERN REGION ----\", \"WR\",\"NR\",\"UT\",\"AZ\",\"SWUS\",\"PNW\", \"---- CENTRAL REGION ----\",\"CR\", \"NP\", \"GL\", \"CUS\", \"CO\", \"---- SOUTHERN REGION ----\", \"SR\", \"TXOK\", \"SE\", \"---- EASTERN REGION ----\", \"ER\", \"NE\"]\n",
        "\n",
        "#@markdown Pick a map theme\n",
        "map_theme = \"ESRI Dark Grey\" #@param [\"Light Shaded Relief\", \"Stamen Toner Light\", \"Positron\", \"Dark Matter\", \"Dark Grey Matter\", \"ESRI Light Grey\", \"ESRI Dark Grey\"]\n",
        "if \"Dark\" in map_theme:\n",
        "  font_color='w'\n",
        "  face_color='#272727'\n",
        "else:\n",
        "  font_color = 'k'\n",
        "  face_color = 'w'\n",
        "#@markdown Set the map scale offset from default (i.e. a 1 would scale up one level [make labels bigger])\n",
        "map_scale_offset = \"1\" #@param [\"-2\",\"-1\", \"0\", \"1\",\"2\"]\n",
        "map_zoom_offset = int(map_scale_offset)\n",
        "\n",
        "pp_verif = False \n",
        "\n",
        "lsr_opt = False \n",
        "heavy_rain_threshold =  1.0\n",
        "\n",
        "s4ariffg = False \n",
        "#@markdown Enter custom lat/lon bounding box if custom was selected\n",
        "custom_bottom_lat =  29.4284 #@param {type:\"number\"}\n",
        "custom_left_lon = -105.811 #@param {type:\"number\"}\n",
        "custom_top_lat =  40.7025#@param {type:\"number\"}\n",
        "custom_right_lon = -88.8568 #@param {type:\"number\"}\n",
        "\n",
        "#@markdown Enter a custom name if you want (mainly used for filename)\n",
        "custom_name = \"RRFS\" #@param {type:\"string\"}\n",
        "\n",
        "day1_elements = [\"NSSL1\", \"NSSL2\", \"NSSL3\", \"NSSL4\", \"NSSL5\", \"HRRR\", \"HRRR2\", \"BLEND\"]\n",
        "\n",
        "if hazard == \"ERO\" and int(day) > 1 and ero_version in day1_elements:\n",
        "  print(\"Selected ERO product is only available on Day 1. Fixing this for you this time, but next time, try to be more careful!\")\n",
        "  day = \"1\"\n",
        "else:\n",
        "  pass\n",
        "\n",
        "if hazard == \"Severe\" and int(day) > 3:\n",
        "  print(\"Hey now, severe outlooks in this notebook are only available out to day 3 (if you know where the days 4+ gribs are, lemme know). Setting it back to day 3 for you.\")\n",
        "  day = \"3\"\n",
        "else:\n",
        "  pass\n",
        "  \n",
        "# set up some global variables here\n",
        "#proj = ccrs.epsg(3857)\n",
        "proj = ccrs.Mercator.GOOGLE\n",
        "latloncrs = ccrs.PlateCarree()\n",
        "\n",
        "# Setup a domain dictionary to make things a bit easier\n",
        "# Zoom offset will be the integeter subtracted from the calculated zoom scale for map tiles\n",
        "# Legend is the legend location: 0=best, 1=UR, 2=UL, 3=LL, 4=LR, 5=R, 6=CL, 7=CR, 8=LC, 9=UC, 10=C\n",
        "\n",
        "domain_dict = {\"Custom\":{\"west\":custom_left_lon,\n",
        "                        \"south\":custom_bottom_lat,\n",
        "                        \"east\":custom_right_lon,\n",
        "                        \"north\":custom_top_lat,\n",
        "                        \"zoom_adj\": map_zoom_offset,\n",
        "                        \"legend\":3},\n",
        "               \n",
        "               \"CONUS\":{\"west\":-125.650,\n",
        "                    \"south\":23.377,\n",
        "                    \"east\":--66.488,\n",
        "                    \"north\":50.924,\n",
        "                    \"zoom_adj\": 0,\n",
        "                    \"legend\":4},\n",
        "               \n",
        "               \"ECONUS\":{\"west\":-104.36,\n",
        "                    \"south\":24.735,\n",
        "                    \"east\":-66.453,\n",
        "                    \"north\":49.755,\n",
        "                    \"zoom_adj\": 0,\n",
        "                    \"legend\":4},\n",
        "\n",
        "               \"WR\":{\"west\":-126.917,\n",
        "                    \"south\":30.586,\n",
        "                    \"east\":-102.740,\n",
        "                    \"north\":49.755,\n",
        "                    \"zoom_adj\": 1,\n",
        "                     \"legend\":4},\n",
        "\n",
        "               \"UT\":{\"west\":-117.02,\n",
        "                      \"east\":-106.92,\n",
        "                      \"north\":42.13,\n",
        "                      \"south\":36.80,\n",
        "                      \"zoom_adj\": 1,\n",
        "                     \"legend\":4},\n",
        "               \n",
        "               \"NR\":{\"west\":-117.5177,\n",
        "                    \"south\":41.9071,\n",
        "                    \"east\":-103.38071,\n",
        "                    \"north\":49.3085,\n",
        "                    \"zoom_adj\": 1,\n",
        "                    \"legend\":4},\n",
        "               \n",
        "               \"PNW\":{\"west\":-125.4510,\n",
        "                    \"south\":41.8754,\n",
        "                    \"east\":-110.9318,\n",
        "                    \"north\":49.5767,\n",
        "                    \"zoom_adj\": 0,\n",
        "                    \"legend\":4},\n",
        "               \n",
        "               \"SWUS\":{\"west\":-125.582,\n",
        "                    \"south\":31.136,\n",
        "                    \"east\":-108.689,\n",
        "                    \"north\":42.859,\n",
        "                    \"zoom_adj\": 0,\n",
        "                    \"legend\":3},\n",
        "               \n",
        "               \"AZ\":{\"west\":-115.596,\n",
        "                    \"south\":31.113,\n",
        "                    \"east\":-107.887,\n",
        "                    \"north\":37.446,\n",
        "                    \"zoom_adj\": 0,\n",
        "                    \"legend\":4},\n",
        "              \n",
        "               \"CR\":{\"west\":-111.534,\n",
        "                    \"south\":35.118,\n",
        "                    \"east\":-82.263,\n",
        "                    \"north\":49.755,\n",
        "                    \"zoom_adj\": 1,\n",
        "                    \"legend\":1},\n",
        "               \n",
        "               \"NP\":{\"west\":-105.244,\n",
        "                    \"south\":42.173,\n",
        "                    \"east\":-89.426,\n",
        "                    \"north\":49.474,\n",
        "                    \"zoom_adj\": 1,\n",
        "                    \"legend\":4},\n",
        "               \n",
        "               \"GL\":{\"west\":-97.606,\n",
        "                    \"south\":38.735,\n",
        "                    \"east\":-74.916,\n",
        "                    \"north\":49.292,\n",
        "                    \"zoom_adj\": 1,\n",
        "                    \"legend\":3},\n",
        "               \n",
        "               \"CUS\":{\"west\":-111.553,\n",
        "                    \"south\":34.794,\n",
        "                    \"east\":-88.533,\n",
        "                    \"north\":46.357,\n",
        "                    \"zoom_adj\": 1,\n",
        "                    \"legend\":3},\n",
        "               \n",
        "               \"CO\":{\"west\":-109.2934,\n",
        "                    \"south\":36.8186,\n",
        "                    \"east\":-101.8524,\n",
        "                    \"north\":47.35,\n",
        "                    \"zoom_adj\": 1,\n",
        "                    \"legend\":4},\n",
        "               \n",
        "               \"SR\":{\"west\":-109.758,\n",
        "                    \"south\":23.313,\n",
        "                    \"east\":-78.247,\n",
        "                    \"north\":37.899,\n",
        "                    \"zoom_adj\": 1,\n",
        "                    \"legend\":3},\n",
        "               \n",
        "               \"TXOK\":{\"west\":-106.95,\n",
        "                    \"south\":26.06,\n",
        "                    \"east\":-86.76,\n",
        "                    \"north\":37.76,\n",
        "                    \"zoom_adj\": 0,\n",
        "                    \"legend\":4},\n",
        "               \n",
        "               \"SE\":{\"west\":-92.974,\n",
        "                    \"south\":24.578,\n",
        "                    \"east\":-75.1311,\n",
        "                    \"north\":37.390,\n",
        "                    \"zoom_adj\": 0,\n",
        "                    \"legend\":4},\n",
        "               \n",
        "               \"ER\":{\"west\":-85.629,\n",
        "                    \"south\":31.723,\n",
        "                    \"east\":-66.465,\n",
        "                    \"north\":47.676,\n",
        "                    \"zoom_adj\": 0,\n",
        "                    \"legend\":4},\n",
        "               \n",
        "               \"NE\":{\"west\":-85.629,\n",
        "                    \"south\":37.654,\n",
        "                    \"east\":-66.00,\n",
        "                    \"north\":47.825,\n",
        "                    \"zoom_adj\": 1,\n",
        "                    \"legend\":4},\n",
        "               \n",
        "               \"CONUS\":{\"west\":-125.650,\n",
        "                    \"south\":23.377,\n",
        "                    \"east\":-66.488,\n",
        "                    \"north\":50.924,\n",
        "                    \"zoom_adj\": 0,\n",
        "                    \"legend\":4},\n",
        "               \n",
        "               \"ECONUS\":{\"west\":-104.36,\n",
        "                    \"south\":24.735,\n",
        "                    \"east\":-66.453,\n",
        "                    \"north\":49.755,\n",
        "                    \"zoom_adj\": 0,\n",
        "                    \"legend\":4},\n",
        "\n",
        "}\n",
        "\n",
        "west = domain_dict[dom][\"west\"]\n",
        "south = domain_dict[dom][\"south\"]\n",
        "east = domain_dict[dom][\"east\"]\n",
        "north = domain_dict[dom][\"north\"]\n",
        "map_zoom_offset = domain_dict[dom][\"zoom_adj\"]\n",
        "LLOC = domain_dict[dom][\"legend\"]\n",
        "\n",
        "\n",
        "# Set up the URL\n",
        "#url_base = \"http://schumacher.atmos.colostate.edu/gherman/ffair/\"\n",
        "#if hazard == \"ERO\":\n",
        "#  file = f'EXQPF_DAY{day}_{ero_version_dict[ero_version]}_{init_strftime}.grib2'\n",
        "#elif hazard == \"Severe\":\n",
        "#  if int(day) > 1:\n",
        "#    file = f'SEVERE_DAY{day}_PROBS_V1P1_GEFSO_{init_strftime}.grib2'\n",
        "#  elif day == \"1\":\n",
        "#    file = f'{severe_hazard}_DAY{day}_PROBS_V1P1_GEFSO_{init_strftime}_STD.grib2'\n",
        "#url = url_base+file\n",
        "#init_strftime\n",
        "\n",
        "#file = f'{init_strftime}_rrfs.t17z.natlev.f015.conus_3km.grib2'\n",
        "file = f'{init_strftime}_rrfs_a.t' + init_strfcyc + 'z.natlev.f' + init_strfhr + '.conus_3km.grib2'\n",
        "\n",
        "\n",
        "################## DOWNLOAD HERE #######################################################################################\n",
        "print('Looking for grib file...')\n",
        "if os.path.exists(file):\n",
        "  print(\"   > Grib already exists\")\n",
        "else:\n",
        "  try:\n",
        "    print(\"   > Downloading grib\")\n",
        "    urlretrieve(url2, file)\n",
        "  except:\n",
        "    print(\"     >> Unable to get file\")\n",
        "    \n",
        "print('   > Processing grib file')\n",
        "gribdata = pygrib.open(file)\n",
        "csu_mlp = gribdata.message(1236)\n",
        "lats, lons = csu_mlp.latlons()\n",
        "gribdata.close()\n",
        "print(f'     >> Max: {int(np.max(csu_mlp.values)*1)}%')\n",
        "print(f'     >> Min: {int(np.min(csu_mlp.values)*1)}%')\n",
        "#print(\"     Got it! Proceed.\")\n"
      ],
      "id": "fldeZzGrumm5"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "a_LmXq9snqBm"
      },
      "outputs": [],
      "source": [
        "################## PLOT HERE ###########################################################################################\n",
        "\n",
        "def blankmap():\n",
        "    global maplayertext1, maplayertext2, ax\n",
        "    print('   > Initializing map')\n",
        "    plt.figure(figsize=(10,8),frameon=True, facecolor=face_color)\n",
        "    F = plt.gcf()  # Gets the current figure\n",
        "    ax = plt.axes(projection=proj)\n",
        "    \n",
        "    zoom = (cx.tile._calculate_zoom(west, \n",
        "                                    south, \n",
        "                                    east, \n",
        "                                    north) - map_zoom_offset)\n",
        "\n",
        "    ax.set_extent([west, \n",
        "                  east, \n",
        "                  south, \n",
        "                  north], crs=latloncrs)\n",
        "    \n",
        "\n",
        "    print('   > Adding fancy map tiles')\n",
        "    maplayertext2 = \"\"\n",
        "    maylayertext1 = \"\"\n",
        "    if map_theme == \"Light Shaded Relief\":\n",
        "      ax.add_feature(cfeature.LAND, edgecolor='none', facecolor='#FAFAF8', zorder=-2)\n",
        "      cx.add_basemap(ax, source=\"https://basemap.nationalmap.gov/arcgis/rest/services/USGSShadedReliefOnly/MapServer/tile/{z}/{y}/{x}\", \n",
        "                      attribution=False, alpha =0.8, zorder=-1)\n",
        "      maplayertext1 = \"Map tiles: © USGS Earth Resources Observation & Science (EROS) Center: GMTED2010\" #for USGS Hillshade\n",
        "      ax.add_feature(cfeature.OCEAN, edgecolor='none', facecolor='#b3bbbd', zorder=1) # adds fill over the ocean\n",
        "      ax.add_feature(cfeature.LAKES, edgecolor='none', facecolor='#b3bbbd', zorder=1) # adds fill over lakes\n",
        "      cx.add_basemap(ax, source=\"http://services.arcgisonline.com/arcgis/rest/services/Reference/World_Boundaries_and_Places/MapServer/tile/{z}/{y}/{x}\", \n",
        "                      attribution=False, zoom=zoom, zorder=50)\n",
        "      cx.add_basemap(ax, source='http://services.arcgisonline.com/arcgis/rest/services/Reference/World_Transportation/MapServer/tile/{z}/{y}/{x}',\n",
        "                      zorder=49)\n",
        "      maplayertext2 = \"Esri, HERE, Garmin, OpenStreetMap contributors\"\n",
        "\n",
        "    elif map_theme == \"Stamen Toner Light\":\n",
        "      cx.add_basemap(ax, source=cx.providers.Stamen.TonerLite, zoom=zoom, zorder=-1, attribution=False)\n",
        "      cx.add_basemap(ax, source=cx.providers.Stamen.TonerHybrid, zoom=zoom, zorder=49, attribution=False)\n",
        "      maplayertext1 = str(cx.providers.Stamen.TonerLite.attribution)\n",
        "\n",
        "    elif map_theme == \"Positron\":\n",
        "      cx.add_basemap(ax, source=cx.providers.CartoDB.PositronNoLabels, zorder=-1, attribution=False)\n",
        "      ax.add_feature(cfeature.NaturalEarthFeature('cultural', 'admin_1_states_provinces_lines', '50m', edgecolor='#e5e2e3', facecolor='none', linewidth=0.5, zorder=48, alpha=0.5)) # adds state borders\n",
        "      ax.add_feature(cfeature.COASTLINE, edgecolor=\"#FAFAF8\", facecolor=None, linewidth=0.25, alpha=0.5, zorder=48) # adds coastline (since that isn't included)\n",
        "      ax.add_feature(cfeature.BORDERS, edgecolor=\"#FAFAF8\", facecolor=None, linewidth=0.5, alpha=0.75, zorder=48) # adds country borders (since that isn't included)\n",
        "      cx.add_basemap(ax, source=cx.providers.CartoDB.PositronOnlyLabels, zoom=zoom, zorder=49, attribution=False)\n",
        "      maplayertext1 = \"Map tiles: \" + str(cx.providers.CartoDB.Positron.attribution)\n",
        "\n",
        "    elif map_theme == \"Dark Grey Matter\":\n",
        "      ax.add_feature(cfeature.LAND, edgecolor='none', facecolor='#414143', zorder=-2)\n",
        "      ax.add_feature(cfeature.OCEAN, edgecolor='none', facecolor='#232227', zorder=1) # adds fill over the ocean\n",
        "      ax.add_feature(cfeature.LAKES, edgecolor='none', facecolor='#232227', zorder=1) # adds fill over lakes\n",
        "      #cx.add_basemap(ax, source=cx.providers.CartoDB.DarkMatterNoLabels, zorder=-1, attribution=False)\n",
        "      ax.add_feature(cfeature.NaturalEarthFeature('cultural', 'admin_1_states_provinces_lines', '50m', edgecolor='#1c1c1c', facecolor='none', linewidth=0.5, zorder=48, alpha=0.5)) # adds state borders\n",
        "      ax.add_feature(cfeature.COASTLINE, edgecolor='k', facecolor=None, linewidth=0.25, alpha=0.5, zorder=48) # adds coastline (since that isn't included)\n",
        "      ax.add_feature(cfeature.BORDERS, edgecolor='k', facecolor=None, linewidth=0.5, alpha=0.75, zorder=48) # adds country borders (since that isn't included)\n",
        "      cx.add_basemap(ax, source=cx.providers.CartoDB.DarkMatterOnlyLabels, zoom=zoom, zorder=49, attribution=False)\n",
        "      maplayertext1 = \"Map tiles: \" + str(cx.providers.CartoDB.DarkMatter.attribution)\n",
        "\n",
        "    elif map_theme == \"Dark Matter\":\n",
        "      cx.add_basemap(ax, source=cx.providers.CartoDB.DarkMatterNoLabels, zorder=-1, attribution=False)\n",
        "      ax.add_feature(cfeature.NaturalEarthFeature('cultural', 'admin_1_states_provinces_lines', '50m', edgecolor='#1c1c1c', facecolor='none', linewidth=0.5, zorder=48, alpha=0.5)) # adds state borders\n",
        "      ax.add_feature(cfeature.COASTLINE, edgecolor='k', facecolor=None, linewidth=0.25, alpha=0.5, zorder=48) # adds coastline (since that isn't included)\n",
        "      ax.add_feature(cfeature.BORDERS, edgecolor='k', facecolor=None, linewidth=0.5, alpha=0.75, zorder=48) # adds country borders (since that isn't included)\n",
        "      cx.add_basemap(ax, source=cx.providers.CartoDB.DarkMatterOnlyLabels, zoom=zoom, zorder=49, attribution=False)\n",
        "      maplayertext1 = \"Map tiles: \" + str(cx.providers.CartoDB.DarkMatter.attribution)\n",
        "\n",
        "    elif map_theme == \"ESRI Light Grey\":\n",
        "      cx.add_basemap(ax, source='https://server.arcgisonline.com/ArcGIS/rest/services/Canvas/World_Light_Gray_Base/MapServer/tile/{z}/{y}/{x}', zorder=-1, attribution=False)\n",
        "      ax.add_feature(cfeature.NaturalEarthFeature('cultural', 'admin_1_states_provinces_lines', '50m', edgecolor='#e4e4e4', facecolor='none', linewidth=0.5, zorder=48)) # adds state borders\n",
        "      ax.add_feature(cfeature.COASTLINE, edgecolor='#efefef', facecolor=None, linewidth=0.25, alpha=0.5, zorder=48) # adds coastline (since that isn't included)\n",
        "      ax.add_feature(cfeature.BORDERS, edgecolor='#efefef', facecolor=None, linewidth=0.5, alpha=0.75, zorder=48) # adds country borders (since that isn't included)\n",
        "      cx.add_basemap(ax, source='https://server.arcgisonline.com/ArcGIS/rest/services/Canvas/World_Light_Gray_Reference/MapServer/tile/{z}/{y}/{x}', zoom=zoom, zorder=49, attribution=False)\n",
        "      maplayertext1 = \"Map tiles: Esri, HERE, Garmin, FAO, NOAA, USGS, © OpenStreetMap contributors, and the GIS User Community\"\n",
        "\n",
        "    elif map_theme == \"ESRI Dark Grey\":\n",
        "      cx.add_basemap(ax, source='https://server.arcgisonline.com/ArcGIS/rest/services/Canvas/World_Dark_Gray_Base/MapServer/tile/{z}/{y}/{x}', zorder=-1, attribution=False)\n",
        "      ax.add_feature(cfeature.NaturalEarthFeature('cultural', 'admin_1_states_provinces_lines', '50m', edgecolor='#363638', facecolor='none', linewidth=0.5, zorder=48, alpha=0.5)) # adds state borders\n",
        "      ax.add_feature(cfeature.COASTLINE, edgecolor='#3f3f3f', facecolor=None, linewidth=0.25, alpha=0.5, zorder=48) # adds coastline (since that isn't included)\n",
        "      ax.add_feature(cfeature.BORDERS, edgecolor='#3f3f3f', facecolor=None, linewidth=0.5, alpha=0.75, zorder=48) # adds country borders (since that isn't included)\n",
        "      cx.add_basemap(ax, source='https://server.arcgisonline.com/ArcGIS/rest/services/Canvas/World_Dark_Gray_Reference/MapServer/tile/{z}/{y}/{x}', zoom=zoom, zorder=49, attribution=False)\n",
        "      maplayertext1 = \"Map tiles: Esri, HERE, Garmin, © OpenStreetMap contributors, and the GIS User Community\"\n",
        "\n",
        "def drawmap(DATA,TITLESTRING,PROD,UNITS,LEVS,LABS):\n",
        "    F = plt.gcf()  # Gets the current figure\n",
        "    ax = plt.gca()  # Gets the current axes\n",
        "    print('   > Adding legend')\n",
        "    proxy = [mpatches.Patch(color = pc.get_facecolor()[0]) for pc in DATA.collections]\n",
        "    LLABS = LABS\n",
        "    #LLABS = []\n",
        "    #for i in range(0, len(LEVS)-1):\n",
        "    #  label = str(LEVS[i])+\"-\"+str(LEVS[i+1])+UNITS\n",
        "    #  LLABS.append(label)\n",
        "    if hazard == \"ERO\":\n",
        "      if pp_verif:\n",
        "        LLABS.append(\"Verif 5%\")\n",
        "        proxy.append(Line2D([0], [0], color=\"#b9c9ba\", lw=2))\n",
        "        LLABS.append(\"Verif 15%\")\n",
        "        proxy.append(Line2D([0], [0], color=\"#f1c86a\", lw=2))\n",
        "        LLABS.append(\"Verif 27%\")\n",
        "        proxy.append(Line2D([0], [0], color=\"#ed7645\", lw=2))\n",
        "        LLABS.append(\"Verif 40%\")\n",
        "        proxy.append(Line2D([0], [0], color=\"#ce2754\", lw=2))\n",
        "        LLABS.append(\"Verif 70%\")\n",
        "        proxy.append(Line2D([0], [0], color=\"#9f00a6\", lw=2))\n",
        "      if lsr_opt:\n",
        "        LLABS.append(\"Heavy Rain LSR\")\n",
        "        proxy.append(plt.scatter([], [], marker=get_marker(\"\\uf740\"), color=\"#023945\", edgecolor='none', s=50))\n",
        "        LLABS.append(\"Flood LSR\")\n",
        "        proxy.append(plt.scatter([], [], marker=get_marker(\"\\uf773\"), color=\"tab:red\", edgecolor='none', s=50))\n",
        "      \n",
        "      if s4ariffg:\n",
        "        LLABS.append(\"StageIV > 5yr ARI\")\n",
        "        proxy.append(plt.scatter([], [], marker=\"_\", color=\"grey\", edgecolor='none', s=50, linewidths=1))\n",
        "        LLABS.append(\"StageIV > FFG\")\n",
        "        proxy.append(plt.scatter([], [], marker=\"|\", color=\"grey\", edgecolor='none', s=50, linewidths=1))\n",
        "    elif hazard == \"Severe\":\n",
        "      if lsr_opt:\n",
        "        if int(day) > 1:\n",
        "          LLABS.append(\"Wind LSR\")\n",
        "          proxy.append(plt.scatter([], [], marker=get_marker(\"\\uf72e\"), color=\"blue\", edgecolor='none', s=50))\n",
        "          LLABS.append(\"Hail LSR\")\n",
        "          proxy.append(plt.scatter([], [], marker=get_marker(\"\\uf73b\"), color=\"green\", edgecolor='none', s=50))\n",
        "          LLABS.append(\"TOR LSR\")\n",
        "          proxy.append(plt.scatter([], [], marker=get_marker(\"\\uf76f\"), color=\"tab:red\", edgecolor='none', s=50))\n",
        "        elif day == \"1\":\n",
        "          if severe_hazard == \"HAIL\":\n",
        "            LLABS.append(\"Hail LSR\")\n",
        "            proxy.append(plt.scatter([], [], marker=get_marker(\"\\uf73b\"), color=\"green\", edgecolor='none', s=50))\n",
        "          if severe_hazard == \"WIND\":\n",
        "            LLABS.append(\"Wind LSR\")\n",
        "            proxy.append(plt.scatter([], [], marker=get_marker(\"\\uf72e\"), color=\"blue\", edgecolor='none', s=50))\n",
        "          if severe_hazard == \"TOR\":\n",
        "            LLABS.append(\"Tor LSR\")\n",
        "            proxy.append(plt.scatter([], [], marker=get_marker(\"\\uf76f\"), color=\"tab:red\", edgecolor='none', s=50))\n",
        "\n",
        "    proxy = proxy[::-1]\n",
        "    LLABS = LLABS[::-1]\n",
        "\n",
        "    l = plt.legend(handles=proxy, labels=LLABS, fontsize='8',frameon=False,\n",
        "                   bbox_to_anchor=(1.001, 0.5), loc=6)\n",
        "    l.set_zorder(100)\n",
        "    for text in l.get_texts():\n",
        "      text.set_color(font_color)\n",
        "    lframe = l.get_frame()\n",
        "    lframe.set_color(face_color)\n",
        "    #l.set_title(f'CSU MLP Day {str(day)} \\n {element} ERO \\n  Valid {valid_strftime}')\n",
        "    #plt.setp(l.get_title(), multialignment='center', fontsize=8, weight='bold')\n",
        "    l.set_title(f'Map Legend \\n')\n",
        "    plt.setp(l.get_title(), multialignment='center', fontsize=8, weight='bold')\n",
        "    \n",
        "    title_text1 = f'CSU MLP · Day {str(day)} {hazard}'\n",
        "    if hazard == \"ERO\":\n",
        "      title_text2 = f'Version: {ero_version}'\n",
        "    elif hazard ==\"Severe\":\n",
        "      if day == \"1\":\n",
        "        title_text2 = f'{severe_hazard}'\n",
        "      elif int(day) > 1:\n",
        "        title_text2 = f'Aggregate Severe'\n",
        "    title_validtext = f'Valid 24-hrs ending {valid_strftime}'\n",
        "\n",
        "    plt.text(0.0, 1.04, title_text1, transform=ax.transAxes, horizontalalignment='left', verticalalignment='bottom',\n",
        "            fontsize=11, color=font_color, weight='bold')\n",
        "    plt.text(0.0, 1.04, title_text2, transform=ax.transAxes, horizontalalignment='left', verticalalignment='top',\n",
        "            fontsize=11, color=font_color, weight='semibold')\n",
        "    plt.text(1.0, 1.04, title_validtext, transform=ax.transAxes, horizontalalignment='right', verticalalignment='top',\n",
        "            fontsize=11, color=font_color, weight='bold')\n",
        "            \n",
        "    if maplayertext1 != \"\":\n",
        "      if maplayertext2 !=\"\":\n",
        "          plt.text(0.005, 0.005, 'Map layers: %s // %s' % (maplayertext1,maplayertext2), \n",
        "                transform = ax.transAxes,horizontalalignment='left',fontsize=6,color=font_color, style='italic', zorder=99,\n",
        "                bbox=dict(facecolor=face_color,edgecolor='none', pad=1.8, alpha=0.65))\n",
        "      else:\n",
        "        plt.text(0.005, 0.005, '%s' % (maplayertext1), \n",
        "                  transform = ax.transAxes,horizontalalignment='left',fontsize=6,color=font_color, style='italic', zorder=99,\n",
        "                bbox=dict(facecolor=face_color,edgecolor='none', pad=1.8, alpha=0.65))\n",
        "   \n",
        "    if dom == \"Custom\" and custom_name:\n",
        "      custom_name_sanitized = custom_name.replace(\" \",\"\")\n",
        "      file_id = '%s_%s_%s' % (custom_name_sanitized, PROD, init_strftime)\n",
        "    else:\n",
        "      file_id = '%s_%s_%s' % (dom, PROD, init_strftime)\n",
        "    filename = '%s.png' % (file_id)\n",
        "    plt.savefig(filename, bbox_inches='tight', facecolor=face_color) # Saves the figure with small margins\n",
        "    print(f'   > Plot saved as {filename}')\n",
        "    plt.show()\n",
        "\n",
        "def plot_ML_SVR():\n",
        "    print(\"Making Severe Plot...\")\n",
        "    svr = csu_mlp.values\n",
        "    blankmap()\n",
        "    print('   > Contouring ML SVR')\n",
        "\n",
        "    SVR_COLS = [\"#dcdcdc\", \"#b9c9ba\", \"#f1c86a\", \"#ed7645\", \"#ce2754\", \"#a20435\",\"#630157\"]\n",
        "    SVR_LEVS = [0.02, 0.05, 0.10, 0.15, 0.30, 0.45, 0.60, 1.00]\n",
        "    SVR_LEVS = [0.52, 0.55, 0.58, 0.60, 0.61, 0.62, 0.65]\n",
        "    SVR_LEVS = [20, 32, 42, 47, 52, 57, 62, 65]\n",
        "    SVR_Text = [\"2-5%\", \"5-10%\", \"10-15%\", \"15-30%\", \"30-45%\", \"45-60%\", \"60-100%\"]\n",
        "    SVR_Text = [\"52-55%\", \"55-58%\", \"58-60%\", \"60-61%\", \"61-62%\", \"62-65%\"]\n",
        "    SVR_Text = [\"20-32\", \"32-42\", \"42-47\", \"47-52\", \"52-57\", \"57-62\", \"62-65\"]\n",
        "    SWO = plt.contourf(lons,lats,svr,SVR_LEVS,colors=SVR_COLS,extend='neither',alpha=0.65, transform=latloncrs,antialiased = True)\n",
        "\n",
        "    if lsr_opt:\n",
        "      day_delta = int(day) - 1\n",
        "      lsr_start = init_date + timedelta (days = day_delta, hours = 12)\n",
        "      lsr_start = lsr_start.strftime('%Y-%m-%dT%H:%M')\n",
        "      lsr_end = valid_date.strftime('%Y-%m-%dT%H:%M')\n",
        "      lsr_url = \"https://mesonet.agron.iastate.edu/cgi-bin/request/gis/lsr.py?wfo[]=ALL&sts=\"+lsr_start+\"Z&ets=\"+lsr_end+\"Z&fmt=csv\"\n",
        "      csv_name = \"lsr_\"+lsr_start+\"_\"+lsr_end+\".csv\"\n",
        "\n",
        "      try:\n",
        "        file_exists = os.path.exists(csv_name)\n",
        "        if file_exists:\n",
        "          print(\"   > LSRs file already exists\")\n",
        "        else:\n",
        "          print(\"   > Grabbing LSRs\")\n",
        "          urlretrieve(lsr_url, csv_name)\n",
        "\n",
        "        LSRs = pd.read_csv(csv_name, usecols= ['LAT','LON','MAG','TYPECODE','TYPETEXT'], on_bad_lines='skip')\n",
        "        LSRs['MAG'] = LSRs.MAG.replace('None','0').astype(float)\n",
        "        LSRs['LAT'] = LSRs.LAT.astype(float)\n",
        "        LSRs['LON'] = LSRs.LON.astype(float)\n",
        "        LSRs_hail = LSRs[(LSRs.TYPECODE == 'H') & (LSRs.MAG >= 1)]\n",
        "        hail_lats= LSRs_hail['LAT'].to_numpy()\n",
        "        hail_lons= LSRs_hail['LON'].to_numpy()\n",
        "        LSRs_wind = LSRs[((LSRs.TYPECODE == 'G') & (LSRs.MAG >= 58)) | (LSRs.TYPECODE == 'D')]\n",
        "        wind_lats= LSRs_wind['LAT'].to_numpy()\n",
        "        wind_lons= LSRs_wind['LON'].to_numpy()\n",
        "        LSRs_tor = LSRs[(LSRs.TYPECODE == 'T')]\n",
        "        tor_lats= LSRs_tor['LAT'].to_numpy()\n",
        "        tor_lons= LSRs_tor['LON'].to_numpy()\n",
        "        print(\"     >> Plotting LSRs\")\n",
        "        if int(day) > 1:\n",
        "          plt.scatter(hail_lons, hail_lats, marker=get_marker(\"\\uf73b\"), color=\"green\", edgecolor='none', s=55,transform=latloncrs)\n",
        "          plt.scatter(wind_lons, wind_lats, marker=get_marker(\"\\uf72e\"), color=\"blue\", edgecolor='none', s=55,transform=latloncrs)\n",
        "          plt.scatter(tor_lons, tor_lats, marker=get_marker(\"\\uf76f\"), color=\"tab:red\", edgecolor='none', s=55,transform=latloncrs)\n",
        "        elif severe_hazard == \"WIND\":\n",
        "           plt.scatter(wind_lons, wind_lats, marker=get_marker(\"\\uf72e\"), color=\"blue\", edgecolor='none', s=55,transform=latloncrs)\n",
        "        elif severe_hazard == \"HAIL\":\n",
        "          plt.scatter(hail_lons, hail_lats, marker=get_marker(\"\\uf73b\"), color=\"green\", edgecolor='none', s=55,transform=latloncrs)\n",
        "        elif severe_hazard == \"TOR\":\n",
        "          plt.scatter(tor_lons, tor_lats, marker=get_marker(\"\\uf76f\"), color=\"tab:red\", edgecolor='none', s=55,transform=latloncrs)\n",
        "\n",
        "      except:\n",
        "        print(\"     !> No LSRs for you\")\n",
        "\n",
        "    units = '%'\n",
        "    title = \"\"\n",
        "    if int(day) > 1:\n",
        "      prodid = 'CSU_SVR_Day'+str(day)\n",
        "    else:\n",
        "      prodid = 'CSU_SVR_'+severe_hazard+'_Day'+str(day)\n",
        "\n",
        "    drawmap(SWO, title, prodid, units, SVR_LEVS, SVR_Text)\n",
        "\n",
        "matplotlib.rcParams['figure.dpi'] = 150 # make high quality figure\n",
        "if hazard == \"ERO\":\n",
        "  plot_ML_ERO()\n",
        "elif hazard == \"Severe\":\n",
        "  plot_ML_SVR()\n"
      ],
      "id": "a_LmXq9snqBm"
    }
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