def __create_trace(
data,
network="NT",
station="BOU",
channel="H",
location="R0",
data_interval="second",
data_type="interval",
):
"""
Utility to create a trace containing the given numpy array.
Parameters
----------
data: array
The array to be inserted into the trace.
Returns
-------
obspy.core.Stream
Stream containing the channel.
"""
stats = Stats()
stats.starttime = UTCDateTime("2019-12-01")
stats.delta = TimeseriesUtility.get_delta_from_interval(data_interval)
stats.channel = channel
stats.station = station
stats.npts = len(data)
stats.data_interval = data_interval
stats.data_type = data_type
numpy_data = numpy.array(data, dtype=numpy.float64)
return Trace(numpy_data, stats)
def process_step(self, step, stream):
"""Filters stream for one step.
Filters all traces in stream.
Parameters
----------
step : array element
step holding variables for one filtering operation
stream : obspy.core.Stream
stream of data to filter
Returns
-------
out : obspy.core.Stream
stream containing 1 trace per original trace.
"""
# gather variables from step
input_sample_period = step["input_sample_period"]
output_sample_period = step["output_sample_period"]
window = np.array(step["window"])
decimation = int(output_sample_period / input_sample_period)
numtaps = len(window)
window = window / sum(window)
out = Stream()
for trace in stream:
starttime, data = self.align_trace(step, trace)
# check that there is still enough data to filter
if len(data) < numtaps:
continue
filtered = self.firfilter(data, window, decimation)
stats = Stats(trace.stats)
stats.delta = output_sample_period
stats.data_interval = step["data_interval"]
stats.data_interval_type = step["data_interval_type"]
stats.filter_comments = step["filter_comments"]
stats.starttime = starttime
stats.npts = len(filtered)
trace_out = self.create_trace(stats.channel, stats, filtered)
out += trace_out
return out
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)
stream += trace
trace = None
