for i, tri in enumerate(trimestres):
# ano, membro, lat, lon
y_season = np.full((itime, 20, 72, 109), np.nan)
for a, y in enumerate(ltime):
data_all, seaccum, monaccum, seamean, monmean, \
lats, lons = post.PostModel(fcst_month, ntrimetres[i], y,
model='RSM97')
# Faz o acumulado da estação
r = 31 * len(ntrimetres[i])
data_all = np.nansum(np.swapaxes(data_all, 1, 2) \
.reshape(r, 20, 72, 109), axis=0)
y_season[a, :] = data_all[:]
y_season = np.swapaxes(y_season, 0, 1)
# Usado no hindcast
fname = 'pcp-seasonacc-rsm97-hind8110-{0}-8110-{1}.nc' \
.format(fcst_month, tri.upper())
writenc4(y_season, lats, lons, fname, itime, nmon[i])
# Usado no forecast
# fname = 'pcp-seasonacc-rsm97-hind8110-{0}{2}_{2}{1}.nc' \
# .format(fcst_month, tri.upper(), y)
# writenc4(y_season, lats, lons, fname, itime)
# Faz o acumulado da estação
r = 31 * len(ntrimetres[i])
data_all = np.nansum(np.swapaxes(data_all, 1, 2) \
.reshape(r, 20, 72, 109), axis=0)
y_season[a, :] = data_all[:]
y_season = np.swapaxes(y_season, 0, 1)
# Usado no hindcast
yy = 1981
mm = ntrimetres[i][0]
if mm > 12:
yy = 1982
mm = mm - 12
fname = 'pcp-seasonacc-rsm97-hind8110-{0}-8110-{1}.nc' \
.format(fcst_month, tri.upper())
writenc4(y_season, lats, lons, fname, itime,
fcst_month, mm, yy)
fname = 'pcp-seasonacc-rsm97-hind8110-{0}-8110-{1}' \
.format(fcst_month, tri.upper())
np.save(fname, y_season)
# Usado no forecast
# fname = 'pcp-seasonacc-rsm97-hind8110-{0}{2}_{2}{1}.nc' \
# .format(fcst_month, tri.upper(), y)
# writenc4(y_season, lats, lons, fname, itime)
# raw_input('Enter...')