def stack_day(data, correlations, dt=-1, start=None, onefile=False):
#t1 = t1.__class__(t1.date)
#t2 = t2.__class__(t2.date)
log.info('Stack day correlations: %s' % util.parameters())
if start is not None:
dt_log = '%s-%s' % (dt, start)
else:
dt_log = dt
stack = Stream()
for correlation in correlations:
try:
days = read(data.getXDay(correlation, '*') + '.QHD')
except Exception as err:
log.warning('Could not load file, because:/n%s' % str(err))
else:
for somedays in streamdaygen(days, dt=dt, start=start):
tr = somedays.calculate('mean')
stack.append(tr)
if not onefile:
data.writeXDayStack(stack, correlation, dt_log)
stack = Stream()
if onefile:
data.writeXDayStack(stack, ('all', 'all'), dt_log)
channels = 'WKI WDI WII'
#channels = 'WDI_10'
datafile = '/home/richter/Data/climate/2006-2012_%s_%s.npz'
output = '/home/richter/Results/IPOC/climate/%s.pdf'
calculate = False
show = False
if calculate:
ipoc = IPOC()
for station in stations.split():
for channel in channels.split():
stream = ipoc.getChannelFromClient('2006-01-01', '2013-01-01',
station=station, channel=channel)
data = []
dates = []
for day in streamdaygen(stream):
day.merge()
data.append(np.mean(day[0].data))
st = day[0].stats.starttime
et = day[0].stats.endtime
dates.append(st + (et - st) / 2.)
np.savez(datafile % (station, channel), dates=dates, data=data)
else:
#http://stackoverflow.com/questions/7733693/matplotlib-overlay-plots-with-different-scales
fig, ax = plt.subplots()
axes = [ax, ax.twinx(), ax.twinx()]
fig.subplots_adjust(right=0.75)
axes[-1].spines['right'].set_position(('axes', 1.2))
axes[-1].set_frame_on(True)
axes[-1].patch.set_visible(False)
#colors = ('green', 'red', 'blue')
datafile = '/home/richter/Data/climate/2006-2012_%s_%s.npz'
output = '/home/richter/Results/IPOC/climate/%s.pdf'
calculate = False
show = False
if calculate:
ipoc = IPOC()
for station in stations.split():
for channel in channels.split():
stream = ipoc.getChannelFromClient('2006-01-01',
'2013-01-01',
station=station,
channel=channel)
data = []
dates = []
for day in streamdaygen(stream):
day.merge()
data.append(np.mean(day[0].data))
st = day[0].stats.starttime
et = day[0].stats.endtime
dates.append(st + (et - st) / 2.)
np.savez(datafile % (station, channel), dates=dates, data=data)
else:
#http://stackoverflow.com/questions/7733693/matplotlib-overlay-plots-with-different-scales
fig, ax = plt.subplots()
axes = [ax, ax.twinx(), ax.twinx()]
fig.subplots_adjust(right=0.75)
axes[-1].spines['right'].set_position(('axes', 1.2))
axes[-1].set_frame_on(True)
axes[-1].patch.set_visible(False)
#colors = ('green', 'red', 'blue')
