def quadrupol_convertfile_miniseed2ts(infile, outfile,combine,invert):
try:
dummystream = read(infile)
except:
raise MTpyError_inputarguments('no valid miniSeed file')
no_traces = len(dummystream)
if no_traces < 4:
print 'found only {0} traces in file - cannot combine all traces'
lo_outfn = []
lo_tuples = []
for trace in range(no_traces):
station, channel, location, network, samplingrate, t0, nsamples, data =\
readfile_obspy(infile,trace)
channel = channel.lower()
ts_tuple = [station.upper(), channel.lower(), samplingrate,t0, int(nsamples)]
ts_tuple.append(data)
lo_tuples.append(ts_tuple)
if combine is True:
lo_newtuples = []
northtup = None
southtup = None
for tup in lo_tuples:
if tup[1].lower()[-1] in ['n']:
northtup = tup
continue
if tup[1].lower()[-1] in ['s']:
southtup = tup
continue
if (northtup is not None) and (southtup is not None):
newtup = [northtup[0], 'ex',northtup[2],northtup[3],northtup[4]]
if invert is True:
data = 0.5*(northtup[5] - southtup[5])
else:
data = 0.5*(northtup[5] + southtup[5])
newtup.append(data)
newtup = tuple(newtup)
elif (northtup is not None):
newtup = northtup
else:
newtup = southtup
lo_newtuples.append(newtup)
easttup = None
westtup = None
for tup in lo_tuples:
if tup[1].lower()[-1] in ['e']:
easttup = tup
continue
if tup[1].lower()[-1] in ['w']:
westtup = tup
continue
if (easttup is not None) and (westtup is not None):
newtup = [easttup[0], 'ey',easttup[2],easttup[3],easttup[4]]
if invert is True:
data = 0.5*(easttup[5] - westtup[5])
else:
data = 0.5*(easttup[5] + westtup[5])
newtup.append(data)
newtup = tuple(newtup)
elif (easttup is not None):
newtup = easttup
else:
newtup = westtup
lo_newtuples.append(newtup)
else:
lo_newtuples = []
for tup in lo_tuples:
if tup[1].lower()[-1] in ['s','w']:
if invert is True:
newtup = tuple([tup[:4],-tup[4]] )
else:
newtup = tup
else:
newtup = tup
lo_newtuples.append(newtup)
for tup in lo_newtuples:
outfilebase = op.splitext(op.abspath(outfile))[0]
newoutfile = '{0}.{1}'.format(outfilebase,tup[1])
outfilename = MTfh.write_ts_file_from_tuple(newoutfile,tup)
#print 'wrote file {0}'.format(outfilename)
lo_outfn.append(outfilename)
return lo_outfn
def convertfile_miniseed2ts(infile, outfile, unit=None, lat = None, lon = None, elev = None):
try:
dummystream = read(infile)
except:
raise MTpyError_inputarguments('infile is not miniSeed')
no_traces = len(dummystream)
lo_outfn = []
for trace in range(no_traces):
station, channel, location, network, samplingrate, t0, nsamples, data =\
readfile_obspy(infile,trace)
channel = channel.lower()
if channel[-1] == 'e':
channel = channel[:-1]+ 'y'
if channel[-1] == 'n':
channel = channel[:-1] +'x'
ts_tuple = [station.upper(), channel.lower(), samplingrate,t0, nsamples]
if unit is not None:
try:
unit = unit.lower()
except:
unit = None
# if unit is None:
# ts_tuple.append('unknown')
if lat is not None:
try:
lat = MTfT._assert_position_format('lat', lat)
except:
lat = None
# if lat is None:
# ts_tuple.append(0.)
if lon is not None:
try:
lon = MTfT._assert_position_format('lon', lon)
except:
lon = None
# if lon is None:
# ts_tuple.append(0.)
if elev is not None:
try:
elev = MTfT._assert_position_format('elev', elev)
except:
elev = None
# if elev is None:
# ts_tuple.append(0.)
ts_tuple.append(data)
if outfile.lower().endswith('mseed'):
outfilebase = op.splitext(op.abspath(outfile))[0]
newoutfile = '{0}.{1}'.format(outfilebase,ts_tuple[1])
else:
newoutfile = outfile
outfilename = MTfh.write_ts_file_from_tuple(newoutfile,tuple(ts_tuple))
outfilename = newoutfile
lo_outfn.append(outfilename)
return lo_outfn
def quadrupol_convertfile_miniseed2ts(infile, outfile, combine, invert):
try:
dummystream = read(infile)
except:
raise MTpyError_inputarguments('no valid miniSeed file')
no_traces = len(dummystream)
if no_traces < 4:
print 'found only {0} traces in file - cannot combine all traces'
lo_outfn = []
lo_tuples = []
for trace in range(no_traces):
station, channel, location, network, samplingrate, t0, nsamples, data =\
readfile_obspy(infile,trace)
channel = channel.lower()
ts_tuple = [
station.upper(),
channel.lower(), samplingrate, t0,
int(nsamples)
]
ts_tuple.append(data)
lo_tuples.append(ts_tuple)
if combine is True:
lo_newtuples = []
northtup = None
southtup = None
for tup in lo_tuples:
if tup[1].lower()[-1] in ['n']:
northtup = tup
continue
if tup[1].lower()[-1] in ['s']:
southtup = tup
continue
if (northtup is not None) and (southtup is not None):
newtup = [northtup[0], 'ex', northtup[2], northtup[3], northtup[4]]
if invert is True:
data = 0.5 * (northtup[5] - southtup[5])
else:
data = 0.5 * (northtup[5] + southtup[5])
newtup.append(data)
newtup = tuple(newtup)
elif (northtup is not None):
newtup = northtup
else:
newtup = southtup
lo_newtuples.append(newtup)
easttup = None
westtup = None
for tup in lo_tuples:
if tup[1].lower()[-1] in ['e']:
easttup = tup
continue
if tup[1].lower()[-1] in ['w']:
westtup = tup
continue
if (easttup is not None) and (westtup is not None):
newtup = [easttup[0], 'ey', easttup[2], easttup[3], easttup[4]]
if invert is True:
data = 0.5 * (easttup[5] - westtup[5])
else:
data = 0.5 * (easttup[5] + westtup[5])
newtup.append(data)
newtup = tuple(newtup)
elif (easttup is not None):
newtup = easttup
else:
newtup = westtup
lo_newtuples.append(newtup)
else:
lo_newtuples = []
for tup in lo_tuples:
if tup[1].lower()[-1] in ['s', 'w']:
if invert is True:
newtup = tuple([tup[:4], -tup[4]])
else:
newtup = tup
else:
newtup = tup
lo_newtuples.append(newtup)
for tup in lo_newtuples:
outfilebase = op.splitext(op.abspath(outfile))[0]
newoutfile = '{0}.{1}'.format(outfilebase, tup[1])
outfilename = MTfh.write_ts_file_from_tuple(newoutfile, tup)
#print 'wrote file {0}'.format(outfilename)
lo_outfn.append(outfilename)
return lo_outfn
def write_ascii_mt_file(self,
save_fn=None,
save_station='mb',
fmt='%.8e',
ex=1,
ey=1,
notch_dict=None):
"""
write an mtpy time series data file
Arguments:
-----------
**save_fn** : full path to save file, if None file is saved as:
station_YYYYMMDD_hhmmss_df.component
ex. mt01_20130206_120000_256.HX
**save_station** : string
prefix string to add to station number as only
integers can be input into metadata of the zen
boxes. ex. mb001
**fmt** : string format
format of data numbers output to ascii file.
*default* is '%.8e' for 8 significan figures in
scientific notation.
Output:
--------
**fn_mt_ascii** : full path to saved file
"""
try:
self.start_date
except AttributeError:
self.read_3d()
time_series = self.convert_counts()
if save_fn is None:
svfn_directory = os.path.join(os.path.dirname(self.fn), 'TS')
if not os.path.exists(svfn_directory):
os.mkdir(svfn_directory)
svfn_date = ''.join(self.start_date.split('-'))
svfn_time = ''.join(self.start_time.split(':'))
svfn_station = save_station + self.rx_stn
save_fn = os.path.join(
svfn_directory,
'{0}_{1}_{2}_{3}.{4}'.format(svfn_station, svfn_date,
svfn_time, int(self.df),
self.ch_cmp.upper()))
#calibrate electric channels
if self.ch_cmp == 'ex':
time_series /= ex
elif self.ch_cmp == 'ey':
time_series /= ey
#apply notch filter if desired
if notch_dict is not None:
self.apply_adaptive_notch_filter(notch_dict)
print 'Filtered notches: '
for nfilt in self.filt_list:
if type(nfilt[0]) != str:
print '{0}{1:.2f} Hz'.format(' ' * 4, nfilt[0])
header_tuple = (save_station + self.rx_stn, self.ch_cmp, self.df,
time.mktime(time.strptime(self.start_dt,
datetime_fmt)),
time_series.shape[0], 'mV', np.median(self.lat),
np.median(self.lon), 0.0, time_series)
self.fn_mt_ascii = mtfh.write_ts_file_from_tuple(save_fn,
header_tuple,
fmt=fmt)
print 'Wrote mtpy timeseries file to {0}'.format(self.fn_mt_ascii)
def convertfile_miniseed2ts(infile,
outfile,
unit=None,
lat=None,
lon=None,
elev=None):
try:
dummystream = read(infile)
except:
raise MTpyError_inputarguments('infile is not miniSeed')
no_traces = len(dummystream)
lo_outfn = []
for trace in range(no_traces):
station, channel, location, network, samplingrate, t0, nsamples, data =\
readfile_obspy(infile,trace)
channel = channel.lower()
if channel[-1] == 'e':
channel = channel[:-1] + 'y'
if channel[-1] == 'n':
channel = channel[:-1] + 'x'
ts_tuple = [
station.upper(),
channel.lower(), samplingrate, t0, nsamples
]
if unit is not None:
try:
unit = unit.lower()
except:
unit = None
# if unit is None:
# ts_tuple.append('unknown')
if lat is not None:
try:
lat = MTfT._assert_position_format('lat', lat)
except:
lat = None
# if lat is None:
# ts_tuple.append(0.)
if lon is not None:
try:
lon = MTfT._assert_position_format('lon', lon)
except:
lon = None
# if lon is None:
# ts_tuple.append(0.)
if elev is not None:
try:
elev = MTfT._assert_position_format('elev', elev)
except:
elev = None
# if elev is None:
# ts_tuple.append(0.)
ts_tuple.append(data)
if outfile.lower().endswith('mseed'):
outfilebase = op.splitext(op.abspath(outfile))[0]
newoutfile = '{0}.{1}'.format(outfilebase, ts_tuple[1])
else:
newoutfile = outfile
outfilename = MTfh.write_ts_file_from_tuple(newoutfile,
tuple(ts_tuple))
outfilename = newoutfile
lo_outfn.append(outfilename)
return lo_outfn
