def from_event_mult_in():
"""Code to create files Fault.time, Fault.pos and Niu_model
"""
if not os.path.isfile('Event_mult.in'):
raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT),
'Event_mult.in')
pk_dirs = mng.default_dirs()
create_fault_files = pk_dirs['create_fault_files']
compute_shear = pk_dirs['compute_shear']
p = subprocess.Popen([create_fault_files, 'Event_mult.in', 'no'],
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
p.wait()
p2 = subprocess.Popen([
compute_shear,
'vel_model',
],
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
p2.wait()
##
## create a json file with fault properties, and another for rise_time info
##
# segments, rise_time, point_sources = pl_mng.__read_planes_info()
# dictionary = {
# 'segments': segments,
# 'rise_time': rise_time
# }
# with open('segments_data.json', 'w') as outfile:
# json.dump(dictionary, outfile, sort_keys=True, indent=4,
# separators=(',', ': '), ensure_ascii=False)
return
if line[i] == int(line[i]):
line[i] = int(line[i])
except:
pass
return line
if __name__ == '__main__':
import argparse
import management as mng
parser = argparse.ArgumentParser()
parser.add_argument("-o", "--output", help="name of output file")
parser.add_argument("--lat", help="latitude of hypocenter location")
parser.add_argument("--lon", help="longitude of hypocenter location")
parser.add_argument("--depth", help="depth of hypocenter location")
args = parser.parse_args()
default_dirs = mng.default_dirs()
tensor_info = {
'lat': float(args.lat),
'lon': float(args.lon),
'depth': float(args.depth)
}
velmodel = select_velmodel(tensor_info, default_dirs)
with open(args.output, 'w') as outf:
nlen = len(velmodel['p_vel'])
outf.write('{}\n'.format(nlen))
zipped = zip(velmodel['p_vel'], velmodel['s_vel'], velmodel['thick'],
velmodel['dens'], velmodel['qa'], velmodel['qb'])
for p, s, thick, dens, qa, qb in zipped:
outf.write('{} {} {} {} {} {}\n'.format(p, s, dens, thick, qa, qb))
def input_chen_tele_surf(tensor_info, data_prop):
"""Based on the teleseismic surface body waves acquired, we write some
files with such data as input for Chen's fortran scripts.
:param tensor_info: dictionary with moment tensor information
:param data_prop: dictionary with properties of waveform data
:type tensor_info: dict
:type data_prop: dict
"""
if not os.path.isfile('surf_waves.json'):
return
dirs = mng.default_dirs()
gf_bank = dirs['long_gf_bank']
traces_info = json.load(open('surf_waves.json'))
depth = tensor_info['depth']
event_lat = tensor_info['lat']
event_lon = tensor_info['lon']
nsta = len(traces_info)
date_origin = tensor_info['date_origin']
string = '{:3d} {:>6} {:>8.3f} {:>9.3f} 31' + 3 * ' {:>1}'\
+ 2 * ' {:>7.2f}' + ' 1' + 3 * ' {:>7.2f}' + ' 0\n'
string_fun = lambda i, name, lat, lon, a, b, c, d, e, weight:\
string.format(i, name, lat, lon, a, b, c, d, e,
weight, weight, weight)
with open('Readlp.inf_low', 'w') as outfile:
outfile.write('{}{}{}{}{}{}.{}\n'.format(
date_origin.year, date_origin.month, date_origin.day,
date_origin.hour, date_origin.minute, date_origin.second,
date_origin.microsecond))
outfile.write('{} {} {} {} {} {} {} {} {}\n'.format(
event_lat, event_lon, depth, date_origin.year, date_origin.julday,
date_origin.hour, date_origin.minute, date_origin.second,
date_origin.microsecond))
outfile.write('0.0 90.0 0.0 10 4.0 1.0e+26\n')
outfile.write('4.0 4.0 10 1.0 {}\n'.format(0))
outfile.write('{} {}\n'.format(nsta, nsta))
outfile.write('No STA Lat Lon M V H1 H2 Angle1 Angle2 Io_s Weight\n')
i = 0
for file in traces_info:
weight = file['trace_weight']
name = file['name']
channel = file['component']
lat, lon = file['location']
if channel == 'BHZ': # Rayleigh
outfile.write(
string_fun(i + 1, name, lat, lon, 1, 0, 0, 0, 0, weight))
else: # Love
outfile.write(
string_fun(i + 1, name, lat, lon, 0, 1, 0, 90, 0, weight))
i = i + 1
with open('Wave.str_low', 'w') as file1, open('Obser.str_low',
'w') as file2:
write_files_wavelet_observed(file1,
file2,
4.0,
data_prop,
traces_info,
gf_bank=gf_bank)
write_wavelet_freqs(4.0, 'Wavelets_surf_tele')
return