def plusminus(num):
if num == 0:
numstr = '+0'
else:
numstr = atm.format_num(num, ndecimals=0, plus_sym=True)
return numstr
# ----------------------------------------------------------------------
# Composite averages
print('Computing composites relative to onset day')
comp = {}
for nm in varnms:
comp[nm] = {}
for key in data:
compdat = utils.composite(sectordata[key][nm], compdays_all,
daynm='dayrel', return_avg=True)
for dkey in compdat:
key2 = key + '_' + dkey
comp[nm][key2] = compdat[dkey]
# Get max/min values from all composites for setting consistent
# ylimits on plots
ylimits = {}
for nm in varnms:
for i, key in enumerate(comp[nm]):
val1 = comp[nm][key].min().values
val2 = comp[nm][key].max().values
if i == 0:
ylim1, ylim2 = val1, val2
else:
ylim1, ylim2 = min([ylim1, val1]), max([ylim2, val2])
axlims = (-10, 50, 40, 120)
with xray.open_dataset(datafile) as ds:
data = ds['PRECTOT'].load()
# Align daily data relative to onset day
ndays = 30
data = daily_rel2onset(data, d_onset, ndays, ndays, yearnm=yearnm, daynm=daynm)
years = data[yearnm].values
databar = data.mean(dim=yearnm)
# Days for pre/onset/post composites
compdays = comp_days_centered(5)
#compdays = comp_days_centered(1, 9)
# Calculate composites
comp = composite(data, compdays, daynm=daynm + 'rel')
compbar = collections.OrderedDict()
for key in comp:
compbar[key] = comp[key].mean(dim=yearnm)
# Plot pre/onset/post composites - climatology
cmin, cmax = 0, 20
plt.figure(figsize=(12,10))
for i, key in enumerate(comp):
plt.subplot(2, 2, i+1)
atm.pcolor_latlon(compbar[key], axlims=axlims, cmap=cmap)
plt.clim(cmin, cmax)
plt.title(var + ' ' + key)
# Plot pre/onset/post composites - individual years
cmin, cmax = 0, 30
