Plot Smoke Polygons

Get HMS Smoke from RSIG and create daily plots.

import matplotlib.pyplot as plt
import matplotlib.colors as mc
import pandas as pd
import pycno
import pyrsig


cno = pycno.cno()
api = pyrsig.RsigApi()

Retrieve data from RSIG (or cache)

hmsfs = []
dates = pd.date_range('2023-06-12', '2023-06-15')
for bdate in dates:
    hmsf = api.to_dataframe("hms.smoke", bdate=bdate)
    hmsfs.append(hmsf)

hmsf = pd.concat(hmsfs)

Make Plot

# set up colormap and normalization
levels = [0, 7.5, 20, 35]
colors = ['green', 'yellow', 'red']
cmap, norm = mc.from_levels_and_colors(levels, colors)

# create multipanel figure
gskw = dict(left=0.05, right=0.915, bottom=0.05, top=0.9)
fig, axx = plt.subplots(
    2, 2, figsize=(11, 8), gridspec_kw=gskw, sharex=True, sharey=True
)
# add axes for colorbar
cax = fig.add_axes([0.925, 0.1, 0.025, 0.8])

# add maps to each panel
for di, date in enumerate(dates):
    jdate = date.strftime('%Y%j')
    ax = axx.ravel()[di]
    plotf = hmsf.query(f'YYYYDDD1 == {jdate}').sort_values(['DENS_UGM3'])
    plotf.plot('DENS_UGM3', cmap=cmap, norm=norm, ax=ax, aspect=None)
    topts = dict(size=16, transform=ax.transAxes, bbox=dict(facecolor='white'))
    ax.text(0.02, 0.04, date.strftime('%F'), **topts)
    cno.drawstates(ax=ax)

# set extent to data extent
ax.set(xlim=api.bbox[::2], ylim=api.bbox[1::2])
# add colorbar with categories
cb = fig.colorbar(ax.collections[0], cax=cax, ticks=[3.25, 13.75, 27.5])
cb.ax.set_yticklabels(
    ['Light', 'Medium', 'Heavy'], rotation=90, verticalalignment='center',
    size=16
)
fig.suptitle('HMS Smoke Qualitative Categories from GOES', size=20)
fig.savefig('hms_smoke.png')