if len(stream) == 0:
continue
if USE_TWS_AFTER_SW:
dist = data.stations.dist(correlation[0][:-1], correlation[1][:-1])
if dist > 550:
continue
direct = int(round(dist / 3.))
tws = (((-direct - 30 - 80, direct + 30), 80),)
stream.trim2(-trim_stream, trim_stream, 'middle')
stretches = None
if reftr:
stretches = []
for tw in tws[i][0]:
if tw <= border_time:
npzfile = np.load(fit_file % (getCor(*correlation), tw))
stretches.append(-npzfile['sinus_exp'])
result = stream.stretch(reftr=reftr, stretch=stretches, str_range=str_range, nstr=nstr, time_windows=tws[i], sides='right')
if period == 24 * 3600:
dates = [(time + 12 * 3600).toordinal() for time in stream.getHI('starttime')]
else:
def get_ord(time):
day = (time + period / 2)
day = day.toordinal() + 1.*day.hour / 24 + 1.*day.minute / 24 / 60 + 1.*day.second / 24 / 3600
return day
dates = [get_ord(time) for time in stream.getHI('starttime')]
dates = _correct_dates(dates)
print np.array([dates[j + 1] - dates[j] for j in range(len(dates) - 1)])
checkDir(path + 'bla')
np.savez(path + 'data_stretching_%s%s%s%s' % (getCor(*correlation), getFilter(filters[i]), getStack(None, period, stack), add_to_file), tw_start=tws[i][0], tw_width=tws[i][1], dates=dates, **result) #corr=corr, stretch=stretch)
############# script starts here
print 'Use method %s' % METHOD
if alternative_npzfile:
print 'Alternative npz file: ON'
fff = 5
for filter_, correlation in itertools.product(filters, correlations):
# labels = ['%s_%d' % (getCor(*correlation), year) for year in range(2007, 2012)]
# labels.append(st)
XCORR = correlation[0] != correlation[1]
if alternative_npzfile:
npzfile = np.load(alternative_npzfile)
l = '%s' % (getCor(*correlation),)
else:
l = '%s%s%s%s' % (getCor(*correlation), getFilter(filter_), getStack(None, period, stack), add_to_file)
try:
#print path + 'data_stretching_%s.npz' % l
npzfile = np.load(path + 'data_stretching_%s.npz' % l)
except Exception as ex:
print ex
print 'Error for %s-%s' % correlation
continue
tw_start, tw_width, corr, stretch, dates, sim_mat, stretch_vec = 7 * [None]
vars().update(npzfile)
sum_to_one_day = False
if sum_to_one_day:
sim_mat_new = np.empty((sim_mat.shape[0], 24, sim_mat.shape[2]))
for i in range(24):
sim_mat_new[:, i, :] = np.average(sim_mat[:, i::24, :], axis=1)
sim_mat = sim_mat_new