else: # get station information
all_tags = [1]
sta = tmps.split('/')[-1]
#----loop through each stream----
for itag in range(len(all_tags)):
if flag:
print("working on station %s and trace %s" %
(sta, all_tags[itag]))
# read waveform data
if input_fmt == 'asdf':
source = ds.waveforms[tmps][all_tags[itag]]
else:
source = obspy.read(tmps)
inv1 = noise_module.stats2inv(source[0].stats, fc_para, locs)
sta, net, lon, lat, elv, loc = noise_module.sta_info_from_inv(
inv1)
# channel info
comp = source[0].stats.channel
if comp[-1] == 'U': comp.replace('U', 'Z')
if len(source) == 0: continue
# cut daily-long data into smaller segments (dataS always in 2D)
trace_stdS, dataS_t, dataS = noise_module.cut_trace_make_statis(
fc_para, source) # optimized version:3-4 times faster
if not len(dataS): continue
N = dataS.shape[0]
# do normalization if needed
source = obspy.Stream()
for ifile in tttfiles:
try:
tr = obspy.read(ifile)
for ttr in tr:
source.append(ttr)
except Exception as inst:
print(inst);continue
# jump if no good data left
if not len(source):continue
# make inventory to save into ASDF file
t1=time.time()
inv1 = noise_module.stats2inv(source[0].stats,prepro_para,locs=locs)
tr = noise_module.preprocess_raw(source,inv1,prepro_para,date_info)
if np.all(tr[0].data==0):continue
t2 = time.time()
if flag:print('pre-processing takes %6.2fs'%(t2-t1))
# jump if no good data left
if not len(tr):continue
# ready for output
ff=os.path.join(DATADIR,all_chunk[ick]+'T'+all_chunk[ick+1]+'.h5')
if not os.path.isfile(ff):
with pyasdf.ASDFDataSet(ff,mpi=False,compression="gzip-3",mode='w') as ds:
pass
with pyasdf.ASDFDataSet(ff,mpi=False,compression="gzip-3",mode='a') as ds:
#--------------------------------------------------------------
#---what if this station has several segments in that day------
#--------------------------------------------------------------
sacfile = os.path.basename(tfile)
try:
source = obspy.read(tfile)
except Exception as inst:
print(inst)
continue
comp = source[0].stats.channel
if flag:
print("working on sacfile %s" % sacfile)
#---------make an inventory---------
inv1 = noise_module.stats2inv(source[0].stats)
if prepro:
t0 = time.time()
source = noise_module.preprocess_raw(
source, downsamp_freq, checkt, pre_filt, resp,
resp_dir)
if len(source) == 0:
continue
t1 = time.time()
if flag:
print("prepro takes %f s" % (t1 - t0))
#----------variables to define days with earthquakes----------
all_madS = noise_module.mad(source[0].data)
all_stdS = np.std(source[0].data)
#--------------------------------------------------------------
#---what if this station has several segments in that day------
#--------------------------------------------------------------
sacfile = os.path.basename(tfile)
try:
source = obspy.read(tfile)
except Exception as inst:
print(inst)
continue
comp = source[0].stats.channel
if flag:
print("working on sacfile %s" % sacfile)
#---------make an inventory---------
inv1 = noise_module.stats2inv(source[0].stats)
if prepro:
t0 = time.time()
source = noise_module.preprocess_raw(
source, inv1, downsamp_freq, checkt, pre_filt,
resp, resp_dir)
if len(source) == 0:
continue
t1 = time.time()
if flag:
print("prepro takes %f s" % (t1 - t0))
#----------variables to define days with earthquakes----------
all_madS = noise_module.mad(source[0].data)
all_stdS = np.std(source[0].data)
try:
source1 = obspy.read(tfile)
bigsource.append(source1[0])
print(source1)
except Exception as inst:
print(type(inst))
continue
if flag:
print("working on sacfile %s" % sacfile)
if len(bigsource) == 0:
continue
print(bigsource)
#---------make an inventory---------
inv1 = noise_module.stats2inv(bigsource[0].stats,
locs=locs)
#------------Pre-Processing-----------
#source = obspy.Stream()
bigsource = bigsource.merge(method=1,
fill_value='interpolate') #[0]
bigsource = noise_module.preprocess_raw(bigsource,
downsamp_freq,
clean_time=True,
pre_filt=None,
resp=None,
respdir=None)
print(bigsource)
with pyasdf.ASDFDataSet(data_h5,
mpi=False,