plot_radar.py

import matplotlib.pyplot as plt
from matplotlib.colors import Normalize
from metpy.plots import colortables as ct
import os
import numpy as np
import cartopy.crs as ccrs
import cartopy.feature as cfeature
from matplotlib.colorbar import make_axes
from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER
import gzip as gz
from netCDF4 import Dataset
import xarray as xr


def load_file(filename: str, level):
    with gz.open(filename, 'r') as file_gz:
        nc_bytes = file_gz.read()
        nc = Dataset("in-mem-file", mode='r', memory=nc_bytes)
        nc = xr.open_dataset(xr.backends.NetCDF4DataStore(nc))
    dbz = nc['DBZc'].data[0]
    lon = nc['lon0'].data
    lat = nc['lat0'].data
    bbox = (lon.ravel().min(), lon.ravel().max(),
                 lat.ravel().min(), lat.ravel().max())

    cmap = ct.get_colortable('NWSReflectivity')
    norm = Normalize(0, 65)
    projection = ccrs.PlateCarree()
    title = filename.split(os.sep)[-1]
    title = title.split('_')
    title = "%s %sZ" % (title[2], title[3][:4])
    title = "Manaus S-Band %s" % (title)

    title_font = dict(fontsize=16, fontweight=500)

    fig, ax = plt.subplots(figsize=(20, 9),
                           subplot_kw=dict(projection=projection))
    ax.set_extent(bbox, crs=ccrs.PlateCarree())

    ax.add_feature(cfeature.LAND)
    ax.add_feature(cfeature.COASTLINE)
    ax.add_feature(cfeature.RIVERS, alpha=.5)

    ax.set_title(title, pad=20, fontdict=title_font)

    plot = ax.pcolor(lon, lat, dbz[level], cmap=cmap,
                     norm=norm)
    cax, kw = make_axes(ax, location='bottom', pad=0.075, shrink=.375)
    out = fig.colorbar(plot, cax=cax, extend='both', **kw)
    out.set_label('Reflectivity in dBZ', size=10)

    gl = ax.gridlines(crs=projection, draw_labels=True, linewidth=1,
                      color='gray', alpha=.5, linestyle='--')
    gl.xlabels_top = False
    gl.ylabels_right = False
    gl.xformatter = LONGITUDE_FORMATTER
    gl.yformatter = LATITUDE_FORMATTER
    ax.text(bbox[1] - .525, bbox[3], '%skm' % (.5 + (level * .5)),
            fontsize=14)

    plt.savefig('imgame_radar.png', dpi=72, bbox_inches='tight',
                transparent=False, pad_inches=0.1)
    plt.show()

if __name__ == "__main__":
    filename = "/home/adriano/thunderstorm/data-cappi/02/sbmn_cappi_20140212_1000.nc.gz"

    load_file(filename=filename, level=5)