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')