def make_spatial_bias_plot(df,
out_name,
vmin,
vmax,
col1='OZONE',
col2='O3',
date=None,
region='domain',
**kwargs):
ax = monet.plots.sp_scatter_bias(df,
col1=col1,
col2=col2,
map_kwargs=dict(states=True),
val_max=vmax,
val_min=vmin,
**kwargs)
date = pd.Timestamp(date)
dt = date - initial_datetime
dtstr = str(dt.days * 24 + dt.seconds // 3600).zfill(3)
plt.title(date.strftime('time=%Y/%m/%d %H:00 | CMAQ - AIRNOW '))
if region == 'domain':
latmin = 25.0
lonmin = -130.0
latmax = 55.0
lonmax = -55.0
else:
from monet.util.tools import get_epa_region_bounds as get_epa_bounds
latmin, lonmin, latmax, lonmax, acro = get_epa_bounds(index=None,
acronym=region)
plt.xlim([lonmin, lonmax])
plt.ylim([latmin, latmax])
plt.tight_layout(pad=0)
savename = "{}.{}.{}.jpg".format(out_name,
initial_datetime.strftime('spbias'),
dtstr)
print(savename)
monet.plots.savefig(savename, bbox_inches='tight', dpi=100, decorate=True)
plt.close()
def make_spatial_plot(da,
lev,
alt_label,
outname,
proj,
startdate,
enddate,
count,
vmin,
vmax,
region='domain'):
cbar_kwargs = dict(aspect=30, shrink=.8) #dict(aspect=30)
if region == 'domain':
latmin = 25.0
lonmin = -130.0
latmax = 48.0
lonmax = -70.0
else:
from monet.util.tools import get_epa_region_bounds as get_epa_bounds
latmin, lonmin, latmax, lonmax, acro = get_epa_bounds(index=None,
acronym=region)
# import stratify
# lev3d=(daz*0.0)+(lev) #convert target level to 3d
# new_da = stratify.interpolate(lev3d, daz, da,
# axis=0)
da.values = da
extent = [lonmin, lonmax, latmin, latmax]
ax = da[lev, :, :].monet.quick_map(cbar_kwargs=cbar_kwargs,
figsize=(15, 8),
map_kwarg={
'states': True,
'crs': proj,
'extent': extent
},
robust=True,
vmin=vmin,
vmax=vmax,
cmap=plt.cm.get_cmap('Spectral_r'))
plt.gcf().canvas.draw()
plt.tight_layout(pad=0)
if startdate == None and enddate == None:
date = pd.Timestamp(da.time.values)
initial_datetime = date
# dt = date - initial_datetime
# dtstr = str(dt.days * 24 + dt.seconds // 3600).zfill(3)
dt = count
dtstr = str(dt).zfill(3)
plt.title(
date.strftime(
'time=%Y/%m/%d %H:00 | CMAQ | Meters AGL ~ {}'.format(
alt_label)))
else:
plt.title(
'average time period | CMAQ | Meters AGL ~ {}'.format(alt_label))
cbar = ax.figure.get_axes()[1]
if vmin == None and vmax == None:
vmin, vmax = cbar.get_ybound()
# vars = df.keys()
# varname = [x for x in vars if x not in ['latitude','longitude']][0]
# ax.scatter(df.longitude.values,df.latitude.values,s=25,c=df[varname],transform=ccrs.PlateCarree(),edgecolor='b',linewidth=.50,vmin=vmin,vmax=vmax,cmap=plt.cm.get_cmap('Spectral_r'))
ax.set_extent(extent, crs=ccrs.PlateCarree())
if startdate == None and enddate == None:
savename = "{}.{}.{}.jpg".format(outname,
initial_datetime.strftime('sp'),
dtstr)
else:
savename = "{}.{}.jpg".format(outname, 'sp')
print(savename)
monet.plots.savefig(savename, bbox_inches='tight', dpi=100, decorate=True)
plt.close()