location.append(chan1.location_code)
nsta += 1
if oput_CSV:
noise_module.make_stationlist_CSV(inv, direc)
##################################
########DOWNLOAD SECTION##########
##################################
#--------MPI---------
comm = MPI.COMM_WORLD
rank = comm.Get_rank()
size = comm.Get_size()
if rank == 0:
all_chunck = noise_module.get_event_list(start_date[0], end_date[0],
inc_hours)
if all_chunck < 1:
raise ValueError('Abort! no data chunck between %s and %s' %
(start_date[0], end_date[0]))
splits = len(all_chunck) - 1
else:
splits, all_chunck = [None for _ in range(2)]
# broadcast the variables
splits = comm.bcast(splits, root=0)
all_chunck = comm.bcast(all_chunck, root=0)
extra = splits % size
#--------MPI: loop through each time chunck--------
for ick in range(rank, splits + size - extra, size):
if ick < splits:
#if auto_corr and method=='coherence':
# raise ValueError('Please set method to decon: coherence cannot be applied when auto_corr is wanted!')
#---------MPI-----------
comm = MPI.COMM_WORLD
rank = comm.Get_rank()
size = comm.Get_size()
#-----------------------
#-------form a station pair to loop through-------
if rank == 0:
if not os.path.isdir(CCFDIR):
os.mkdir(CCFDIR)
sfiles = sorted(glob.glob(os.path.join(FFTDIR, '*.h5')))
day = noise_module.get_event_list(start_date, end_date, inc_days)
splits = len(day)
if not sfiles:
raise IOError('Abort! No FFT data in %s' % FFTDIR)
else:
splits, sfiles, day = [None for _ in range(3)]
#------split the common variables------
splits = comm.bcast(splits, root=0)
day = comm.bcast(day, root=0)
sfiles = comm.bcast(sfiles, root=0)
extra = splits % size
for ii in range(rank, splits + size - extra, size):
NSV = 2
if not allstation:
h5files = [
'/Users/chengxin/Documents/Harvard/Kanto_basin/Mesonet_BW/STACK1/E.ABHM/E.ABHM_E.OHSM.h5'
]
nsta = len(h5files)
else:
h5files = sta
nsta = len(sta)
for ista in range(nsta):
h5file = h5files[ista]
#--------assume continous recordings for each stacked segments---------
tlist = noise_module.get_event_list(start_date, end_date, stack_days)
tags_allstack = ['Allstacked']
for ii in range(len(tlist) - 1):
tags_allstack.append('F' + tlist[ii].replace('_', '') + 'T' +
tlist[ii + 1].replace('_', ''))
nstacks = len(tags_allstack)
#-------open ASDF file to read data-----------
with pyasdf.ASDFDataSet(h5file, mode='r') as ds:
slist = ds.auxiliary_data.list()
#------loop through the reference waveforms------
if slist[0] == 'Allstacked':
#------useful parameters from ASDF file------
rlist = ds.auxiliary_data[slist[0]].list()
