def preprocess(db, stations, comps, goal_day, params, responses=None):
"""
Fetches data for each ``stations`` and each ``comps`` using the
data_availability table in the database.
To correct for instrument responses, make sure to set ``remove_response``
to "Y" in the config and to provide the ``responses`` DataFrame.
:Example:
>>> from msnoise.api import connect, get_params, preload_instrument_responses
>>> from msnoise.preprocessing import preprocess
>>> db = connect()
>>> params = get_params(db)
>>> responses = preload_instrument_responses(db)
>>> st = preprocess(db, ["YA.UV06","YA.UV10"], ["Z",], "2010-09-01", params, responses)
>>> st
2 Trace(s) in Stream:
YA.UV06.00.HHZ | 2010-09-01T00:00:00.000000Z - 2010-09-01T23:59:59.950000Z | 20.0 Hz, 1728000 samples
YA.UV10.00.HHZ | 2010-09-01T00:00:00.000000Z - 2010-09-01T23:59:59.950000Z | 20.0 Hz, 1728000 samples
:type db: :class:`sqlalchemy.orm.session.Session`
:param db: A :class:`~sqlalchemy.orm.session.Session` object, as
obtained by :func:`msnoise.api.connect`.
:type stations: list of str
:param stations: a list of station names, in the format NET.STA.
:type comps: list of str
:param comps: a list of component names, in Z,N,E,1,2.
:type goal_day: str
:param goal_day: the day of data to load, ISO 8601 format: e.g. 2016-12-31.
:type params: class
:param params: an object containing the config parameters, as obtained by
:func:`msnoise.api.get_params`.
:type responses: :class:`pandas.DataFrame`
:param responses: a DataFrame containing the instrument responses, as
obtained by :func:`msnoise.api.preload_instrument_responses`.
:rtype: :class:`obspy.core.stream.Stream`
:return: A Stream object containing all traces.
"""
datafiles = {}
output = Stream()
MULTIPLEX = False
MULTIPLEX_files = {}
for station in stations:
datafiles[station] = {}
net, sta, loc = station.split('.')
gd = datetime.datetime.strptime(goal_day, '%Y-%m-%d')
files = get_data_availability(db,
net=net,
sta=sta,
loc=loc,
starttime=gd,
endtime=gd)
for comp in comps:
datafiles[station][comp] = []
for file in files:
if file.sta != "MULTIPLEX":
if file.chan[-1] not in comps:
continue
fullpath = os.path.join(file.path, file.file)
datafiles[station][file.chan[-1]].append(fullpath)
else:
MULTIPLEX = True
print("Mutliplex mode, reading the files")
fullpath = os.path.join(file.path, file.file)
multiplexed = sorted(glob.glob(fullpath))
for comp in comps:
for fn in multiplexed:
if fn in MULTIPLEX_files:
_ = MULTIPLEX_files[fn]
else:
# print("Reading %s" % fn)
_ = read(fn, format=params.archive_format or None)
traces = []
for tr in _:
if "%s.%s" % (
tr.stats.network, tr.stats.station
) in stations and tr.stats.channel[-1] in comps:
traces.append(tr)
del _
_ = Stream(traces=traces)
MULTIPLEX_files[fn] = _
datafiles[station][comp].append(_)
for istation, station in enumerate(stations):
net, sta, loc = station.split(".")
for comp in comps:
files = eval("datafiles['%s']['%s']" % (station, comp))
if len(files) != 0:
logger.debug("%s.%s Reading %i Files" %
(station, comp, len(files)))
traces = []
for file in files:
if isinstance(file, Stream):
st = file.select(network=net,
station=sta,
component=comp).copy()
else:
try:
# print("Reading %s" % file)
# t= time.time()
st = read(file,
dytpe=np.float,
starttime=UTCDateTime(gd),
endtime=UTCDateTime(gd) + 86400,
station=sta,
format=params.archive_format or None)
# print("done in", time.time()-t)
except:
logger.debug("ERROR reading file %s" % file)
# TODO add traceback (optional?)
continue
for tr in st:
if len(tr.stats.channel) == 2:
tr.stats.channel += tr.stats.location
tr.stats.location = "00"
tmp = st.select(network=net, station=sta, component=comp)
if not len(tmp):
for tr in st:
tr.stats.network = net
st = st.select(network=net,
station=sta,
component=comp)
else:
st = tmp
for tr in st:
tr.data = tr.data.astype(np.float)
tr.stats.network = tr.stats.network.upper()
tr.stats.station = tr.stats.station.upper()
tr.stats.channel = tr.stats.channel.upper()
if tr.stats.location == "":
tr.stats.location = "--"
traces.append(tr)
del st
stream = Stream(traces=traces)
if not (len(stream)):
continue
f = io.BytesIO()
stream.write(f, format='MSEED')
f.seek(0)
stream = read(f, format="MSEED")
stream.sort()
# try:
# # HACK not super clean... should find a way to prevent the
# # same trace id with different sps to occur
# stream.merge(method=1, interpolation_samples=3, fill_value=None)
# except:
# logger.debug("Error while merging...")
# traceback.print_exc()
# continue
# stream = stream.split()
if not len(stream):
continue
logger.debug("%s Checking sample alignment" % stream[0].id)
for i, trace in enumerate(stream):
stream[i] = check_and_phase_shift(
trace, params.preprocess_taper_length)
logger.debug("%s Checking Gaps" % stream[0].id)
if len(getGaps(stream)) > 0:
max_gap = params.preprocess_max_gap * stream[
0].stats.sampling_rate
gaps = getGaps(stream)
while len(gaps):
too_long = 0
for gap in gaps:
if int(gap[-1]) <= max_gap:
try:
stream[gap[0]] = stream[gap[0]].__add__(
stream[gap[1]],
method=1,
fill_value="interpolate")
stream.remove(stream[gap[1]])
except:
stream.remove(stream[gap[1]])
break
else:
too_long += 1
if too_long == len(gaps):
break
gaps = getGaps(stream)
del gaps
stream = stream.split()
for tr in stream:
if tr.stats.sampling_rate < (params.goal_sampling_rate -
1):
stream.remove(tr)
taper_length = params.preprocess_taper_length # seconds
for trace in stream:
if trace.stats.npts < (4 * taper_length *
trace.stats.sampling_rate):
stream.remove(trace)
else:
trace.detrend(type="demean")
trace.detrend(type="linear")
trace.taper(max_percentage=None,
max_length=taper_length)
if not len(stream):
logger.debug(" has only too small traces, skipping...")
continue
for trace in stream:
logger.debug("%s Highpass at %.2f Hz" %
(trace.id, params.preprocess_highpass))
trace.filter("highpass",
freq=params.preprocess_highpass,
zerophase=True,
corners=4)
if trace.stats.sampling_rate != params.goal_sampling_rate:
logger.debug("%s Lowpass at %.2f Hz" %
(trace.id, params.preprocess_lowpass))
trace.filter("lowpass",
freq=params.preprocess_lowpass,
zerophase=True,
corners=8)
if params.resampling_method == "Resample":
logger.debug("%s Downsample to %.1f Hz" %
(trace.id, params.goal_sampling_rate))
trace.data = resample(
trace.data, params.goal_sampling_rate /
trace.stats.sampling_rate, 'sinc_fastest')
elif params.resampling_method == "Decimate":
decimation_factor = trace.stats.sampling_rate / params.goal_sampling_rate
if not int(decimation_factor) == decimation_factor:
logger.warning(
"%s CANNOT be decimated by an integer factor, consider using Resample or Lanczos methods"
" Trace sampling rate = %i ; Desired CC sampling rate = %i"
% (trace.id, trace.stats.sampling_rate,
params.goal_sampling_rate))
sys.stdout.flush()
sys.exit()
logger.debug("%s Decimate by a factor of %i" %
(trace.id, decimation_factor))
trace.data = trace.data[::int(decimation_factor)]
elif params.resampling_method == "Lanczos":
logger.debug("%s Downsample to %.1f Hz" %
(trace.id, params.goal_sampling_rate))
trace.data = np.array(trace.data)
trace.interpolate(
method="lanczos",
sampling_rate=params.goal_sampling_rate,
a=1.0)
trace.stats.sampling_rate = params.goal_sampling_rate
del trace
if params.remove_response:
logger.debug('%s Removing instrument response' %
stream[0].id)
try:
stream.attach_response(responses)
stream.remove_response(
pre_filt=params.response_prefilt, taper=False)
except:
logger.error("Bad or no instrument response "
"information for %s, skipping" %
stream[0].id)
continue
for tr in stream:
tr.data = tr.data.astype(np.float32)
output += stream
del stream
del files
clean_scipy_cache()
del MULTIPLEX_files
return output
stime = UTCDateTime('2019-08-16 12:59:10')
etime = stime + 120
client = Client()
inv = client.get_stations(network=net,
station=sta,
starttime=stime,
endtime=etime,
channel=chan,
level="response")
st = Stream()
st += client.get_waveforms(net, sta, loc, chan, stime, etime)
st.detrend('constant')
st.merge(fill_value=0)
st.attach_response(inv)
st.remove_response(output="DISP")
#st.rotate(method="->ZNE",inventory=inv)
st.filter("bandpass", freqmin=.5, freqmax=5)
tr = st[0]
t = np.linspace(0, (tr.stats.npts - 1) / tr.stats.sampling_rate,
num=tr.stats.npts)
fig = plt.figure(1, figsize=(12, 12))
plt.ylabel('Displacement (mm)', fontsize=14)
plt.xlim([0, 120])
plt.ylim([-.02, .02])
plt.xlabel('seconds after origin', fontsize=14)
plt.title('%s-%s-%s-%s, 2019-08-16, Hutchinson, KS Earthquake' %
(net, sta, loc, chan),
fontsize=14)
