def stack(st, stats=None, kw_stack={}, kw_snr={}):
"""
Stack traces in stream.
"""
if st.count() == 0:
logger.error('No traces!')
return st
elif st.count() == 1:
return st
# Find lap
if kw_stack.get('sort', False):
st.sort(keys=['endtime'])
st.trim(
starttime=st[0].stats.starttime,
endtime=st[0].stats.endtime,
pad=True,
fill_value=0,
)
sk = Trace()
data = _data_stack(st, **kw_stack, **kw_snr)
if data is None:
return
else:
sk.data = data
sk.stats = _hdr_stack(st, stats, **kw_stack, **kw_snr)
key_snr = kw_stack.get('snr', 'user2')
weight = kw_stack.get('weight', 'None').lower()
if 'none' not in weight:
sk.stats.sac[key_snr] = snr(sk, **kw_snr)
return sk
def rand_stack(st, stats=None, kw_stack={}, kw_snr={}):
nsub = kw_stack.get('nsub', 4)
key_nsrc = kw_stack.get('key_nsrc', 'user0')
ntr = st.count()
if ntr < 2:
return st
sk = Trace()
sk.stats = _hdr_stack(st, stats, **kw_stack, **kw_snr)
if ntr <= nsub:
for tr in st:
yield tr
else:
ind = np.arange(ntr)
np.random.shuffle(ind)
for sub in np.array_split(ind, nsub):
data = 0
for i in sub:
data += st[i].data
n = sub.size
data /= n
sk.stats.sac[key_nsrc] = n
sk.data = data
yield sk
return
def sym_xc(xc, noeven=False):
"""
Symmetrize a cross-correlation.
"""
pair = f'{xc.stats.sac.kevnm.split()[0]}-{xc.stats.station}'
if not _is_sym(xc):
logger.debug(f'Asymmetric {pair}')
end = min(abs(xc.stats.sac.b), xc.stats.sac.e)
xc = sliced(xc, -end, end)
if _even_npts(xc) and noeven:
logger.error(f'Even npts to symmexcize {pair}')
else:
sym = Trace()
sym.data = _data_sym(xc.data)
sym.stats = _hd_sym(xc.stats, npts=sym.data.size)
return sym
def get_stream(self,
processed_path,
kstnm,
kinst,
force_without_loc=False):
# Check if an interpolated station location exists
if self.station_loc is None and not force_without_loc:
return
# Save data into a Stream object
trace = Trace()
trace.stats = self.obspy_trace_stats
trace.data = self.processed_data
stream = Stream(traces=[trace])
return stream
def to_sac_and_mseed(self, export_path, station_number, force_without_loc):
# Check if file exist
export_path_sac = export_path + self.get_export_file_name() + ".sac"
export_path_msd = export_path + self.get_export_file_name() + ".mseed"
#export_path_wav = export_path + self.get_export_file_name() + ".wav"
if os.path.exists(export_path_sac) and os.path.exists(export_path_msd):
return
# Check if the station location have been calculated
if self.station_loc is None and not force_without_loc:
print self.get_export_file_name() + ": Skip sac/mseed generation, wait the next ascent to compute location"
return
# Fill header info
stats = Stats()
stats.sampling_rate = self.decimated_fs
stats.network = "MH"
stats.station = station_number
stats.starttime = self.date
stats.sac = dict()
if not force_without_loc:
stats.sac["stla"] = self.station_loc.latitude
stats.sac["stlo"] = self.station_loc.longitude
stats.sac["stdp"] = self.depth
stats.sac["user0"] = self.snr
stats.sac["user1"] = self.criterion
stats.sac["iztype"] = 9 # 9 == IB in sac format
# Save data into a Stream object
trace = Trace()
trace.stats = stats
trace.data = self.data
stream = Stream(traces=[trace])
# Save stream object
print export_path_sac
stream.write(export_path_sac, format='SAC')
print export_path_msd
stream.write(export_path_msd, format='MSEED')
def invert_raw():
######################################
# Binary
######################################
if mode == "Binary":
catch_files = []
files = glob.glob(file_path + "*")
for file in files:
catch = re.findall(
".*[0-9]{4}-[0-9]{2}-[0-9]{2}T[0-9]{2}_[0-9]{2}_[0-9]{2}\.[0-9]{6}",
file)
if len(catch) > 0:
catch_files.append(file)
######################################
# Freq file
######################################
freq_file = glob.glob(file_path + "*_freq")
if len(freq_file) > 1:
print "warning : more than one freq file in folder"
if len(freq_file) == 0:
print "warning no freq file discovered use :" + str(sampling_freq)
else:
content = "40.000000"
with open(freq_file[0], "r") as f:
content = f.read()
sampling_freq = float(content)
print "Sampling used : " + str(sampling_freq)
files_nb = len(catch_files)
file_offset = 1
for catch_file in catch_files:
print catch_file
print "File nb : " + str(file_offset) + "/" + str(files_nb)
date = UTCDateTime(
re.findall(
".*([0-9]{4}-[0-9]{2}-[0-9]{2}T[0-9]{2}_[0-9]{2}_[0-9]{2}\.[0-9]{6})",
catch_file)[0])
rawdata = numpy.fromfile(catch_file, numpy.int32)
######################################
# Plot plotly file
######################################
# Add acoustic values to the graph
#data_line = graph.Scattergl(x=[date + i/sampling_freq for i in range(0,len(rawdata))],
# y=rawdata,
# name="counts",
# line=dict(color='blue', width=2),
# mode='lines')
#plotlydata = [data_line]
#layout = graph.Layout(title="Plot",
# xaxis=dict(title='Date', titlefont=dict(size=18)),
# yaxis=dict(title='Counts', titlefont=dict(size=18)),
# hovermode='closest'
# )
#plotly.plot({'data': plotlydata, 'layout': layout},
# filename=catch_file + ".html",
# auto_open=False)
######################################
# Create SAC file
######################################
# Fill header info
stats = Stats()
stats.sampling_rate = sampling_freq
stats.network = "test"
stats.station = 0
stats.starttime = date
stats.sac = dict()
# Save data into a Stream object
trace = Trace()
trace.stats = stats
trace.data = rawdata
stream = Stream(traces=[trace])
# Save stream object
stream.write(catch_file + ".sac", format='SAC')
stream.write(catch_file + ".mseed", format='MSEED')
file_offset = file_offset + 1
else:
######################################
# Text
######################################
#filename = "tool_invert_raw/1553771378.490936"
#date = UTCDateTime(1553771378.490936)
# text
#f = open(filename, 'r')
#rawdata = numpy.array(f.read().rstrip('\n').split('\n'))
#f.close()
# binary
######################################
# Plot plotly file
######################################
# Add acoustic values to the graph
data_line = graph.Scattergl(
x=[date + i / sampling_freq for i in range(0, len(rawdata))],
y=rawdata,
name="counts",
line=dict(color='blue', width=2),
mode='lines')
plotlydata = [data_line]
layout = graph.Layout(title="Plot",
xaxis=dict(title='Date',
titlefont=dict(size=18)),
yaxis=dict(title='Counts',
titlefont=dict(size=18)),
hovermode='closest')
plotly.plot({
'data': plotlydata,
'layout': layout
},
filename=filename + ".html",
auto_open=False)
######################################
# Create SAC file
######################################
# Fill header info
stats = Stats()
stats.sampling_rate = sampling_freq
stats.network = "test"
stats.station = 0
stats.starttime = date
stats.sac = dict()
# Save data into a Stream object
trace = Trace()
trace.stats = stats
trace.data = rawdata
stream = Stream(traces=[trace])
# Save stream object
stream.write(filename + ".sac", format='SAC')
# store stats
stationname = sta + '%04d' % i
channelnameN = cha + '%s' % 'N'
channelnameE = cha + '%s' % 'E'
# for NS components
statsN = Stats()
statsN.sampling_rate = 1.0 / sampling_rate_x
statsN.delta = sampling_rate_x
statsN.starttime = starttime
statsN.npts = len(traceN.data)
statsN.network = net
statsN.station = stationname
statsN.location = ''
statsN.channel = channelnameN
traceN.stats = statsN
traceN.stats.sac = obspy.core.AttribDict()
traceN.stats.sac.back_azimuth = plottheta # use this as azimuth of station
#---applying filters---#
traceN.filter('bandpass', freqmin=freqmin, freqmax=freqmax)
tN = traceN.stats.starttime
traceN.trim(starttime=tN, endtime=tN + trim_end_time)
traceN.taper(0.05, side='right')
#----------------------#
stemp += Stream(traceN)
# for EW components
statsE = Stats()
statsE.sampling_rate = 1.0 / sampling_rate_z
statsE.delta = sampling_rate_z
