def get_greens_tensor(self, station, origin):
# download and unizp data
dirname = unzip(download_greens_tensor(self.model, station, origin))
# read data
stream = Stream()
stream.id = station.id
for filename in GREENS_TENSOR_FILENAMES:
stream += obspy.read(dirname + '/' + filename, format='sac')
# what are the start and end times of the data?
t1_new = float(station.starttime)
t2_new = float(station.endtime)
dt_new = float(station.delta)
# what are the start and end times of the Green's function?
t1_old = float(stream[0].stats.starttime)
t2_old = float(stream[0].stats.endtime)
dt_old = float(stream[0].stats.delta)
for trace in stream:
# resample Green's functions
data_old = trace.data
data_new = resample(data_old, t1_old, t2_old, dt_old, t1_new,
t2_new, dt_new)
trace.data = data_new
trace.stats.starttime = t1_new
trace.stats.delta = dt_new
trace.stats.npts = len(data_new)
traces = [trace for trace in stream]
return GreensTensor(traces, station, origin)
def get_greens_tensor(self, station, origin):
"""
Reads a Greens tensor from a directory tree organized by model, event
depth, and event distance
"""
stream = Stream()
# what are the start and end times of the data?
t1_new = float(station.starttime)
t2_new = float(station.endtime)
dt_new = float(station.delta)
dep = str(int(round(origin.depth / 1000.)))
#dst = str(int(round(station.distance)))
dst = str(int(ceil(station.distance)))
# See cap/fk documentation for indexing scheme details;
# here we try to follow as closely as possible the cap way of
# doing things
channels = [
'TSS',
'TDS',
'REP',
'RSS',
'RDS',
'RDD',
'ZEP',
'ZSS',
'ZDS',
'ZDD',
]
extensions = [
'8',
'5', # t
'b',
'7',
'4',
'1', # r
'a',
'6',
'3',
'0', # z
]
for _i, ext in enumerate(extensions):
trace = obspy.read('%s/%s_%s/%s.grn.%s' %
(self.path, self.model, dep, dst, ext),
format='sac')[0]
trace.stats.channel = channels[_i]
# what are the start and end times of the Green's function?
t1_old = float(origin.time) + float(trace.stats.starttime)
t2_old = float(origin.time) + float(trace.stats.endtime)
dt_old = float(trace.stats.delta)
# resample Green's function
data_old = trace.data
data_new = resample(data_old, t1_old, t2_old, dt_old, t1_new,
t2_new, dt_new)
trace.data = data_new
# convert from 10^-20 dyne to N^-1
trace.data *= 1.e-15
trace.stats.starttime = t1_new
trace.stats.delta = dt_new
stream += trace
stream.id = station.id
traces = [trace for trace in stream]
return GreensTensor(traces, station, origin)
