if this_c == 'hist':
hist_sc[mn,do] = rain4mon
elif this_c == 'fut':
fut_sc[mn,do] = rain4mon
if whplot != 'meanpr':
wlon = wlon_picks[do]
elon = elon_picks[do]
# Then subset by longitude
print 'Subsetting by latitude?'
print 'Selecting CBs between '+str(wlon)+' and '+str(elon)
dates_ln, cXs_ln, cYs_ln, degs_ln, chs_ln, keys_ln, daynos_ln, tworecdt_ln = \
sset.sel_cen_lon(wlon,elon, dates_dd, cXs_dd, cYs_dd, degs_dd, chs_dd,\
keys_dd, daynos_dd, tworecdt_dd)
nttt=len(dates_ln)
if whplot == 'number':
# Get seasonal cycle
scycle_count = anal.seas_cycle_count(mons,dates_ln)
if relative:
if do==0:
print 'Saving seasonal cycle over dom1, to calculate relative TTTs in dom2'
scycle_count_d1 = scycle_count
if do==1:
print 'Calculating relative TTTs in dom2'
scycle_count_d2 = scycle_count
mon2 = 3
nmon = len(mons)
# First check the season
print 'Subsetting by season?'
print 'Selecting months for : ' + per_ttt_seas
dates_se, cXs_se, cYs_se, degs_se, chs_se, keys_se, daynos_se, tworecdt_se = \
sset.sel_seas(mons, dates_dd, cXs_dd, cYs_dd, degs_dd, chs_dd, keys_dd, daynos_dd,
tworecdt_dd)
# Then subset by longitude
print 'Subsetting by latitude?'
print 'Selecting CBs between ' + str(wlon) + ' and ' + str(
elon)
dates_ln, cXs_ln, cYs_ln, degs_ln, chs_ln, keys_ln, daynos_ln, tworecdt_ln = \
sset.sel_cen_lon(wlon,elon,dates_se, cXs_se, cYs_se, degs_se, \
chs_se, keys_se, daynos_se, tworecdt_se)
nttt = len(dates_ln)
# Computing value for x axis
print 'Getting value for x -axis'
# tot_ttt=len(dates_ln)
# if rel_picks[do]==True:
# tot_ttt=float(tot_ttt)/len(dates_se)*100.0
# else:
# if peryear:
# tot_ttt=tot_ttt/nys
#xvals[cnt,do]=tot_ttt
# Edit to quickly plot something
xvals[cnt, do] = len(dates_se)
if weightlats:
latr = np.deg2rad(rlat)
weights = np.cos(latr)
zonmean = np.nanmean(seasmean, axis=1)
reg_mean = np.ma.average(zonmean, weights=weights)
else:
reg_mean = np.nanmean(seasmean)
# Get bias
bias = reg_mean - reg_ref_mean
yvals[cnt] = bias
# Finally getting intensity
dates_int, cXs_int, cYs_int, degs_int, chs_int, keys_int, daynos_int, tworecdt_int = \
sset.sel_cen_lon(int_ttt_wlon,int_ttt_elon,dates_per, cXs_per, cYs_per, \
degs_per, chs_per, keys_per, daynos_per, tworecdt_per)
n4int = len(dates_int)
print 'Selecting TTTs from rain data'
indices = []
for dt in range(n4int):
ix = my.ixdtimes(rdtime, [dates_int[dt][0]], \
[dates_int[dt][1]], [dates_int[dt][2]], [0])
if len(ix) >= 1:
indices.append(ix)
indices = np.squeeze(np.asarray(indices))
print 'Selecting rain on TTT days'
rainsel = rain[indices, :, :]