def make_spatial_bias_plot(df,
out_name,
vmin,
vmax,
col1='pm25_ug3',
col2='sfc_pm25',
date=None,
region='domain',
**kwargs):
if region == 'domain':
ax = monet.plots.sp_scatter_bias(df,
col1=col1,
col2=col2,
map_kwargs=dict(states=False),
val_max=vmax,
val_min=vmin,
**kwargs)
else:
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 = -90.0
lonmin = -180.0
latmax = 90.0
lonmax = 180.0
else:
from monet.util.tools import get_giorgi_region_bounds as get_giorgi_bounds
latmin, lonmin, latmax, lonmax, acro = get_giorgi_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()
startdatename_obj = datetime.datetime.strptime(
startdate, '%Y-%m-%d %H:%M:%S')
enddatename_obj = datetime.datetime.strptime(
enddate, '%Y-%m-%d %H:%M:%S')
startdatename = str(
datetime.datetime.strftime(startdatename_obj, '%Y-%m-%d_%H'))
enddatename = str(
datetime.datetime.strftime(enddatename_obj, '%Y-%m-%d_%H'))
else:
startdatename = 'Entire'
enddatename = 'Period'
if subset_giorgi is True:
#df.query('giorgi_region == '+'"'+ee+'"',inplace=True)
from monet.util.tools import get_giorgi_region_bounds as get_giorgi_bounds
latmin, lonmin, latmax, lonmax, acro = get_giorgi_bounds(
index=None, acronym=ee)
df = df[(df['latitude'] >= latmin) & (df['latitude'] <= latmax)]
df = df[(df['longitude'] >= lonmin) & (df['longitude'] <= lonmax)]
if reg is True and subset_giorgi is False:
stats = open(
finput[0].replace('.hdf', '_') + startdatename + '_' +
enddatename + '_reg_stats_domain.txt', 'w')
elif reg is True and subset_giorgi is True:
stats = open(
finput[0].replace('.hdf', '_') + startdatename + '_' +
enddatename + '_reg_stats_' + ee + '.txt', 'w')
elif reg is False and subset_giorgi is True:
stats = open(
finput[0].replace('.hdf', '_') + startdatename + '_' +
enddatename + '_stats_' + ee + '.txt', 'w')
