def test_deepcopy(self): """ Tests deepcopy method of Stats object. """ stats = Stats() stats.network = 'BW' stats['station'] = 'ROTZ' stats['other1'] = {'test1': '1'} stats['other2'] = AttribDict({'test2': '2'}) stats['other3'] = 'test3' stats2 = copy.deepcopy(stats) stats.network = 'CZ' stats.station = 'RJOB' self.assertEqual(stats2.__class__, Stats) self.assertEqual(stats2.network, 'BW') self.assertEqual(stats2.station, 'ROTZ') self.assertEqual(stats2.other1.test1, '1') self.assertEqual(stats2.other1.__class__, AttribDict) self.assertEqual(len(stats2.other1), 1) self.assertEqual(stats2.other2.test2, '2') self.assertEqual(stats2.other2.__class__, AttribDict) self.assertEqual(len(stats2.other2), 1) self.assertEqual(stats2.other3, 'test3') self.assertEqual(stats.network, 'CZ') self.assertEqual(stats.station, 'RJOB')
def test_deepcopy(self): """ Tests deepcopy method of Stats object. """ stats = Stats() stats.network = "BW" stats["station"] = "ROTZ" stats["other1"] = {"test1": "1"} stats["other2"] = AttribDict({"test2": "2"}) stats["other3"] = "test3" stats2 = copy.deepcopy(stats) stats.network = "CZ" stats.station = "RJOB" self.assertEqual(stats2.__class__, Stats) self.assertEqual(stats2.network, "BW") self.assertEqual(stats2.station, "ROTZ") self.assertEqual(stats2.other1.test1, "1") self.assertEqual(stats2.other1.__class__, AttribDict) self.assertEqual(len(stats2.other1), 1) self.assertEqual(stats2.other2.test2, "2") self.assertEqual(stats2.other2.__class__, AttribDict) self.assertEqual(len(stats2.other2), 1) self.assertEqual(stats2.other3, "test3") self.assertEqual(stats.network, "CZ") self.assertEqual(stats.station, "RJOB")
def test_deepcopy(self): """ Tests deepcopy method of Stats object. """ stats = Stats() stats.network = 'BW' stats['station'] = 'ROTZ' stats['other1'] = {'test1': '1'} stats['other2'] = AttribDict({'test2': '2'}) stats['other3'] = 'test3' stats2 = copy.deepcopy(stats) stats.network = 'CZ' stats.station = 'RJOB' assert stats2.__class__ == Stats assert stats2.network == 'BW' assert stats2.station == 'ROTZ' assert stats2.other1.test1 == '1' assert stats2.other1.__class__ == AttribDict assert len(stats2.other1) == 1 assert stats2.other2.test2 == '2' assert stats2.other2.__class__ == AttribDict assert len(stats2.other2) == 1 assert stats2.other3 == 'test3' assert stats.network == 'CZ' assert stats.station == 'RJOB'
def test_casted_stats_nscl_writes_to_mseed(self): """ Ensure a Stream object that has had its nslc types cast to str can still be written. """ st = Stream(traces=read()[0]) # Get a new stats object with just the basic items in it stats_items = set(Stats()) new_stats = Stats() new_stats.__dict__.update({x: st[0].stats[x] for x in stats_items}) with warnings.catch_warnings(record=True): new_stats.network = 1 new_stats.station = 1.1 new_stats.channel = 'Non' st[0].stats = new_stats # try writing stream to bytes buffer bio = io.BytesIO() st.write(bio, 'mseed') bio.seek(0) # read bytes and compare stt = read(bio) # remove _mseed so streams can compare equal stt[0].stats.pop('mseed') del stt[0].stats._format # format gets added upon writing self.assertEqual(st, stt)
def ascii(path, filename): """ Reads SPECFEM3D-style ASCII data :type path: str :param path: path to datasets :type filenames: list :param filenames: files to read """ st = Stream() stats = Stats() time, data = loadtxt(os.path.join(path, filename)).T stats.filename = filename stats.starttime = time[0] stats.delta = time[1] - time[0] stats.npts = len(data) try: parts = filename.split(".") stats.network = parts[0] stats.station = parts[1] stats.channel = parts[2] except: pass st.append(Trace(data=data, header=stats)) return st
def ascii(path, filenames): """ Reads SPECFEM3D-style ascii data """ from numpy import loadtxt from obspy.core import Stream, Stats, Trace stream = Stream() for filename in filenames: stats = Stats() data = loadtxt(path +'/'+ filename) stats.filename = filename stats.starttime = data[0,0] stats.sampling_rate = data[0,1] - data[0,0] stats.npts = len(data[:,0]) try: parts = filename.split('.') stats.network = parts[0] stats.station = parts[1] stats.channel = temp[2] except: pass stream.append(Trace(data=data[:,1], header=stats)) return stream
def read_ascii(path, NR, nt): from numpy import loadtxt from obspy.core import Stream, Stats, Trace dat_type = 'semd' comp1 = 'FXX' comp2 = 'FXY' stream = Stream() for rec_x in range(0,NR): file_name_in1 = path + 'P.R' + str(int(rec_x+1)) + '.' + comp1 + '.' + dat_type file_name_in2 = path + 'P.R' + str(int(rec_x+1)) + '.' + comp2 + '.' + dat_type xz1 = np.genfromtxt(file_name_in1) xz2 = np.genfromtxt(file_name_in2) deg = 0.0 alpha = np.arctan(xz2[:nt,1]/(1.0e-40 + xz1[:nt,1])) # angle of projection direction = np.sign(np.cos(deg*np.pi/180.0)*xz1[:nt,1]*np.cos(alpha) + np.sin(deg*np.pi/180.0)*xz2[:nt,1]*np.cos(alpha)) data = direction*np.sqrt(xz1[:nt,1]**2 + xz2[:nt,1]**2)*np.cos(alpha) # scalar radial component stats = Stats() stats.filename = path + 'P.R' + str(int(rec_x+1)) stats.starttime = xz1[0,0] stats.delta = xz1[1,0] - xz1[0,0] stats.npts = len(xz1[:nt,0]) try: parts = filename.split('.') stats.network = parts[0] stats.station = parts[1] stats.channel = temp[2] except: pass stream.append(Trace(data=data[:], header=stats)) return stream
def ascii(path, filenames): from numpy import loadtxt from obspy.core import Stream, Stats, Trace stream = Stream() for filename in filenames: stats = Stats() data = loadtxt(path + '/' + filename) stats.filename = filename stats.starttime = data[0, 0] stats.sampling_rate = data[0, 1] - data[0, 0] stats.npts = len(data[:, 0]) try: parts = filename.split('.') stats.network = parts[0] stats.station = parts[1] stats.channel = temp[2] except: pass stream.append(Trace(data=data[:, 1], header=stats)) return stream
def test_casted_stats_nscl_writes_to_mseed(self): """ Ensure a Stream object that has had its nslc types cast to str can still be written. """ st = Stream(traces=read()[0]) # Get a new stats object with just the basic items in it stats_items = set(Stats()) new_stats = Stats() new_stats.__dict__.update({x: st[0].stats[x] for x in stats_items}) new_stats.network = 1 new_stats.station = 1.1 new_stats.channel = 'Non' st[0].stats = new_stats # try writing stream to bytes buffer bio = io.BytesIO() st.write(bio, 'mseed') bio.seek(0) # read bytes and compare stt = read(bio) # remove _mseed so streams can compare equal stt[0].stats.pop('mseed') del stt[0].stats._format # format gets added upon writing self.assertEqual(st, stt)
def get_obspy_trace(self): """ Return class contents as obspy.Trace object """ stat = Stats() stat.network = self.net.split(b'\x00')[0].decode() stat.station = self.sta.split(b'\x00')[0].decode() location = self.loc.split(b'\x00')[0].decode() if location == '--': stat.location = '' else: stat.location = location stat.channel = self.chan.split(b'\x00')[0].decode() stat.starttime = UTCDateTime(self.start) stat.sampling_rate = self.rate stat.npts = len(self.data) return Trace(data=self.data, header=stat)
def read_specfem_seismogram(output_files, network, station, band): st = Stream() for component in 'ZNE': channel = '%sX%s' % (band, component) filename = os.path.join( output_files, '%s.%s.%s.sem.ascii' % (network, station, channel)) tmp = np.genfromtxt(filename) stats = Stats() stats.network = network stats.station = station stats.channel = channel stats.delta = tmp[1, 0] - tmp[0, 0] stats.npts = tmp.shape[0] stats.starttime = tmp[0, 0] tr = Trace(tmp[:, 1], stats) st += tr return st
def read_specfem_seismogram(output_files, network, station, band): st = Stream() for component in 'ZNE': channel = '%sX%s' % (band, component) filename = os.path.join(output_files, '%s.%s.%s.sem.ascii' % (network, station, channel)) tmp = np.genfromtxt(filename) stats = Stats() stats.network = network stats.station = station stats.channel = channel stats.delta = tmp[1, 0] - tmp[0, 0] stats.npts = tmp.shape[0] stats.starttime = tmp[0, 0] tr = Trace(tmp[:, 1], stats) st += tr return st
def save_wave(self): # Fetch a wave from Ring 0 wave = self.ring2buff.get_wave(0) # if wave is empty return if wave == {}: return # Lets try to buffer with python dictionaries and obspy name = wave["station"] + '.' + wave["channel"] + '.' + wave[ "network"] + '.' + wave["location"] if name in self.wave_buffer: # Determine max samples for buffer max_samp = wave["samprate"] * 60 * self.minutes # Create a header: wavestats = Stats() wavestats.station = wave["station"] wavestats.network = wave["network"] wavestats.channel = wave["channel"] wavestats.location = wave["location"] wavestats.sampling_rate = wave["samprate"] wavestats.starttime = UTCDateTime(wave['startt']) # Create a trace wavetrace = Trace(header=wavestats) wavetrace.data = wave["data"] # Try to append data to buffer, if gap shutdown. try: self.wave_buffer[name].append(wavetrace, gap_overlap_check=True) except TypeError as err: logger.warning(err) self.runs = False except: raise self.runs = False # Debug data if self.debug: logger.info("Station Channel combo is in buffer:") logger.info(name) logger.info("Size:") logger.info(self.wave_buffer[name].count()) logger.debug("Data:") logger.debug(self.wave_buffer[name]) else: # First instance of data in buffer, create a header: wavestats = Stats() wavestats.station = wave["station"] wavestats.network = wave["network"] wavestats.channel = wave["channel"] wavestats.location = wave["location"] wavestats.sampling_rate = wave["samprate"] wavestats.starttime = UTCDateTime(wave['startt']) # Create a trace wavetrace = Trace(header=wavestats) wavetrace.data = wave["data"] # Create a RTTrace rttrace = RtTrace(int(self.minutes * 60)) self.wave_buffer[name] = rttrace # Append data self.wave_buffer[name].append(wavetrace, gap_overlap_check=True) # Debug data if self.debug: logger.info("First instance of station/channel:") logger.info(name) logger.info("Size:") logger.info(self.wave_buffer[name].count()) logger.debug("Data:") logger.debug(self.wave_buffer[name])
# Time_stamps reference to beginning of a week # Set the correct year, month, and day for Time_stamps sttime = UTCDateTime(Time_stamps[0]) endtime = UTCDateTime(Time_stamps[len(Time_stamps) - 1]) sttime._set_year(2017) endtime._set_year(2017) sttime._set_month(8) endtime._set_month(8) sttime._set_day(13 + UTCDateTime(Time_stamps[0]).day) endtime._set_day(13 + UTCDateTime(Time_stamps[len(Time_stamps) - 1]).day) # Define stats stats = Stats() stats.starttime = sttime stats.station = station stats.network = 'NT' stats.location = 'R0' stats.data_interval = '256Hz' stats.delta = .00390625 stats.data_type = 'variation' # Create list of arrays and channel names and intialize counter k arrays = [Hx, Hy, Ex, Ey] k = 0 # Loop over channels to create an obspy stream of the data for ar in arrays: stats.npts = len(ar) stats.channel = channels[k] ar = np.asarray(ar) trace = Trace(ar, stats)
def rf_test(phase, dip, rfloc='output/waveforms/RF', geom_file='3D.geom', decon_meth='it'): """ Creates synthetic PRFs from Raysum data. Parameters ---------- phase : string "P" or "S". dip : int Dip of the LAB in deg, determines, which files to use rfloc : The parental directory, in which the RFs are saved. geom_file : str, optional Filename of the geometry file Returns ------- rfs: list List of RFTrace objects. Will in addition be saved in SAC format. """ # Determine filenames PSS_file = [] for i in range(16): PSS_file.append('3D_' + str(dip) + '_' + str(i) + '.tr') # Read geometry baz, q, dN, dE = read_geom(geom_file, phase) # statlat = dN/(DEG2KM*1000) d = np.sqrt(np.square(dN) + np.square(dE)) az = np.rad2deg(np.arccos(dN / d)) i = np.where(dE < 0) az[i] = az[i] + 180 statlat = [] statlon = [] for azimuth, delta in zip(az, d): if delta == 0: statlat.append(0) statlon.append(0) continue coords = Geodesic.WGS84.Direct(0, 0, azimuth, delta) statlat.append(coords["lat2"]) statlon.append(coords["lon2"]) # for n, longitude in enumerate(lon): # y, _, _ = gps2dist_azimuth(latitude, 0, latitude, longitude) # statlon = dE/(DEG2KM*1000) rayp = q * DEG2KM * 1000 # Read traces stream = [] for f in PSS_file: PSS, dt, _, N, shift = read_raysum(phase, PSS_file=f) stream.append(PSS) streams = np.vstack(stream) del stream M = len(baz) if M != streams.shape[0]: raise ValueError([ "Number of traces", streams.shape[0], """does not equal the number of backazimuths in the geom file""", M ]) rfs = [] odir = os.path.join(rfloc, phase, 'raysum', str(dip)) ch = ['BHP', 'BHV', 'BHH'] # Channel names os.makedirs(odir, exist_ok=True) # Create RF objects for i, st in enumerate(streams): s = Stream() for j, tr in enumerate(st): stats = Stats() stats.npts = N stats.delta = dt stats.st # if old: stats.channel = ch[j] stats.network = 'RS' stats.station = str(dip) s.append(Trace(data=tr, header=stats)) # Create info dictionary for rf creation info = { 'onset': [UTCDateTime(0) + shift], 'starttime': [UTCDateTime(0)], 'statlat': statlat[i], 'statlon': statlon[i], 'statel': 0, 'rayp_s_deg': [rayp[i]], 'rbaz': [baz[i]], 'rdelta': [np.nan], 'ot_ret': [0], 'magnitude': [np.nan], 'evt_depth': [np.nan], 'evtlon': [np.nan], 'evtlat': [np.nan] } rf = createRF(s, phase=phase, method=decon_meth, info=info) # Write RF rf.write(os.path.join(odir, str(i) + '.sac'), format='SAC') rfs.append(rf) return rfs, statlat, statlon
def _read_tspair(filename, headonly=False, **kwargs): # @UnusedVariable """ Reads a ASCII TSPAIR file and returns an ObsPy Stream object. .. warning:: This function should NOT be called directly, it registers via the ObsPy :func:`~obspy.core.stream.read` function, call this instead. :type filename: str :param filename: ASCII file to be read. :type headonly: bool, optional :param headonly: If set to True, read only the headers. This is most useful for scanning available data in huge (temporary) data sets. :rtype: :class:`~obspy.core.stream.Stream` :return: A ObsPy Stream object. .. rubric:: Example >>> from obspy import read >>> st = read('/path/to/tspair.ascii') """ with open(filename, 'rt') as fh: # read file and split text into channels buf = [] key = False for line in fh: if line.isspace(): # blank line continue elif line.startswith('TIMESERIES'): # new header line key = True buf.append((line, io.StringIO())) elif headonly: # skip data for option headonly continue elif key: # data entry - may be written in multiple columns buf[-1][1].write(line.strip().split()[-1] + ' ') # create ObsPy stream object stream = Stream() for header, data in buf: # create Stats stats = Stats() parts = header.replace(',', '').split() temp = parts[1].split('_') stats.network = temp[0] stats.station = temp[1] stats.location = temp[2] stats.channel = temp[3] stats.sampling_rate = parts[4] # quality only used in MSEED # don't put blank quality code into 'mseed' dictionary # (quality code is mentioned as optional by format specs anyway) if temp[4]: stats.mseed = AttribDict({'dataquality': temp[4]}) stats.ascii = AttribDict({'unit': parts[-1]}) stats.starttime = UTCDateTime(parts[6]) stats.npts = parts[2] if headonly: # skip data stream.append(Trace(header=stats)) else: data = _parse_data(data, parts[8]) stream.append(Trace(data=data, header=stats)) return stream
def readTSPAIR(filename, headonly=False, **kwargs): # @UnusedVariable """ Reads a ASCII TSPAIR file and returns an ObsPy Stream object. .. warning:: This function should NOT be called directly, it registers via the ObsPy :func:`~obspy.core.stream.read` function, call this instead. :type filename: str :param filename: ASCII file to be read. :type headonly: bool, optional :param headonly: If set to True, read only the headers. This is most useful for scanning available data in huge (temporary) data sets. :rtype: :class:`~obspy.core.stream.Stream` :return: A ObsPy Stream object. .. rubric:: Example >>> from obspy import read >>> st = read('/path/to/tspair.ascii') """ fh = open(filename, "rt") # read file and split text into channels headers = {} key = None for line in fh: if line.isspace(): # blank line continue elif line.startswith("TIMESERIES"): # new header line key = line headers[key] = StringIO() elif headonly: # skip data for option headonly continue elif key: # data entry - may be written in multiple columns headers[key].write(line.strip().split()[-1] + " ") fh.close() # create ObsPy stream object stream = Stream() for header, data in headers.iteritems(): # create Stats stats = Stats() parts = header.replace(",", "").split() temp = parts[1].split("_") stats.network = temp[0] stats.station = temp[1] stats.location = temp[2] stats.channel = temp[3] stats.sampling_rate = parts[4] # quality only used in MSEED stats.mseed = AttribDict({"dataquality": temp[4]}) stats.ascii = AttribDict({"unit": parts[-1]}) stats.starttime = UTCDateTime(parts[6]) stats.npts = parts[2] if headonly: # skip data stream.append(Trace(header=stats)) else: data = _parse_data(data, parts[8]) stream.append(Trace(data=data, header=stats)) return stream
def readSLIST(filename, headonly=False, **kwargs): # @UnusedVariable """ Reads a ASCII SLIST file and returns an ObsPy Stream object. .. warning:: This function should NOT be called directly, it registers via the ObsPy :func:`~obspy.core.stream.read` function, call this instead. :type filename: str :param filename: ASCII file to be read. :type headonly: bool, optional :param headonly: If set to True, read only the head. This is most useful for scanning available data in huge (temporary) data sets. :rtype: :class:`~obspy.core.stream.Stream` :return: A ObsPy Stream object. .. rubric:: Example >>> from obspy.core import read >>> st = read('/path/to/slist.ascii') """ fh = open(filename, 'rt') # read file and split text into channels headers = {} key = None for line in fh: if line.isspace(): # blank line continue elif line.startswith('TIMESERIES'): # new header line key = line headers[key] = StringIO() elif headonly: # skip data for option headonly continue elif key: # data entry - may be written in multiple columns headers[key].write(line.strip() + ' ') fh.close() # create ObsPy stream object stream = Stream() for header, data in headers.iteritems(): # create Stats stats = Stats() parts = header.replace(',', '').split() temp = parts[1].split('_') stats.network = temp[0] stats.station = temp[1] stats.location = temp[2] stats.channel = temp[3] stats.sampling_rate = parts[4] # quality only used in MSEED stats.mseed = AttribDict({'dataquality': temp[4]}) stats.ascii = AttribDict({'unit': parts[-1]}) stats.starttime = UTCDateTime(parts[6]) stats.npts = parts[2] if headonly: # skip data stream.append(Trace(header=stats)) else: # parse data data.seek(0) if parts[8] == 'INTEGER': data = loadtxt(data, dtype='int', ndlim=1) elif parts[8] == 'FLOAT': data = loadtxt(data, dtype='float32', ndlim=1) else: raise NotImplementedError stream.append(Trace(data=data, header=stats)) return stream
def readSLIST(filename, headonly=False, **kwargs): # @UnusedVariable """ Reads a ASCII SLIST file and returns an ObsPy Stream object. .. warning:: This function should NOT be called directly, it registers via the ObsPy :func:`~obspy.core.stream.read` function, call this instead. :type filename: str :param filename: ASCII file to be read. :type headonly: bool, optional :param headonly: If set to True, read only the head. This is most useful for scanning available data in huge (temporary) data sets. :rtype: :class:`~obspy.core.stream.Stream` :return: A ObsPy Stream object. .. rubric:: Example >>> from obspy import read >>> st = read('/path/to/slist.ascii') """ with open(filename, 'rt') as fh: # read file and split text into channels buf = [] key = False for line in fh: if line.isspace(): # blank line continue elif line.startswith('TIMESERIES'): # new header line key = True buf.append((line, StringIO())) elif headonly: # skip data for option headonly continue elif key: # data entry - may be written in multiple columns buf[-1][1].write(line.strip() + ' ') # create ObsPy stream object stream = Stream() for header, data in buf: # create Stats stats = Stats() parts = header.replace(',', '').split() temp = parts[1].split('_') stats.network = temp[0] stats.station = temp[1] stats.location = temp[2] stats.channel = temp[3] stats.sampling_rate = parts[4] # quality only used in MSEED stats.mseed = AttribDict({'dataquality': temp[4]}) stats.ascii = AttribDict({'unit': parts[-1]}) stats.starttime = UTCDateTime(parts[6]) stats.npts = parts[2] if headonly: # skip data stream.append(Trace(header=stats)) else: data = _parse_data(data, parts[8]) stream.append(Trace(data=data, header=stats)) return stream
def raw_import(gzip_filename): """ Makes a 'raw' stream file from the gzipped csv file. The csv file has been downloaded from the JAXA website. The method makes a raw stream which does not yet have the frames reconstructed. :type gzip_filename: str :param gzip_filename: gzipped filename of the CSV file to be read. :rtype: :class:`~obspy.core.stream.Stream` :return: A ObsPy Stream object. """ # read the gzipped csv file with gzip.open(gzip_filename, 'rt') as fh: # read file buf = [] header = next(fh).split(',') # read the header # it should contain either 1 channel or 3 if len(header) == 8: # the RESP files use either 'MH1', 'MH2', 'MHZ' # the JAXA files use 'LPX', 'LPY', 'LPZ' # X should point north, Y east, but this is not always the case # so we rename LPX to MH1, and LPY to MH2 channels = ['MH1', 'MH2', 'MHZ'] raw_channels = ['_M1', '_M2', '_MZ'] for line in fh: temp = line.split(',') try: temp[4] = UTCDateTime(temp[4]) except ValueError as e: # this is a specific error which is found in the csv file if temp[4] == '1975-49-11 19:13:04.232000': temp[4] = UTCDateTime('1975-09-11 19:13:04.232000') else: raise try: temp[0] = int(temp[0]) except ValueError as e: # this is a specific error which is found in the csv file if temp[4] == UTCDateTime( '1975-09-15 12:53:36.849000') and temp[0] == '<3': temp[0] = 83 else: raise buf.append( (temp[1], temp[2], temp[4], int(temp[0]), int(temp[3]), int(temp[5]), int(temp[6]), int(temp[7]))) elif len(header) == 6: channels = ['SPZ'] raw_channels = ['_SZ'] for line in fh: # check the manual list of points which have been removed if line in remove_manually: continue temp = line.split(',') # the original order: # frame_count, ap_station, ground_station, nc, time, spz # make a tuple (in a new order so that it can be sorted): # ap_station, ground_station, time, frame_count, nc, spz buf.append( (temp[1], temp[2], UTCDateTime(temp[4]), int(temp[0]), int(temp[3]), int(temp[5]))) # sort by ap_station, ground_station and time (and also everything else, # but that won't matter) buf.sort() stream = Stream() data_x = [] data_y = [] data_z = [] data_sz = [] abs_times = [] frame_count_ncs = [] corr_frame_count_ncs = [] stats = Stats() stats.delta = DELTA network = 'XA' last_id = None for data in buf: # read in the data from the buffer station = data[0].rjust(3, 'S') ground_station = data[1].rjust(2, '0') time = data[2] frame_count = data[3] nc = data[4] # create a combination of frame count and nc - from 0.0 to 89.75 frame_count_nc = float(frame_count) + (float(nc) - 1.) * 0.25 id = "{0:s}.{1:s}.{2:s}.{3:s}".format(network, station, ground_station, channels[0]) # check whether we are adding to an existing one, or creating a new one if (last_id is None or last_id != id): # before creating the new one, add previous trace(s) to the stream if len(abs_times) > 0: _make_traces(stream=stream, stats=stats, header=header, channels=raw_channels, data_x=data_x, data_y=data_y, data_z=data_z, data_sz=data_sz, abs_times=abs_times, frame_count_ncs=frame_count_ncs) data_x = [] data_y = [] data_z = [] data_sz = [] abs_times = [] frame_count_ncs = [] stats = Stats() stats.delta = DELTA stats.starttime = time stats.network = network stats.station = station stats.location = ground_station # add the data) from any line if len(header) == 8: data_x.append(data[5]) data_y.append(data[6]) data_z.append(data[7]) else: data_sz.append(data[5]) abs_times.append(time.timestamp) frame_count_ncs.append(frame_count_nc) last_id = id # add the last one if len(abs_times) > 0: _make_traces(stream=stream, stats=stats, header=header, channels=raw_channels, data_x=data_x, data_y=data_y, data_z=data_z, data_sz=data_sz, abs_times=abs_times, frame_count_ncs=frame_count_ncs) return stream