6.2.11.1.3. eqcorrscan.utils.pre_processing.shortproc

eqcorrscan.utils.pre_processing.shortproc(st, lowcut, highcut, filt_order, samp_rate, parallel=False, num_cores=False, starttime=None, endtime=None, seisan_chan_names=False, fill_gaps=True, ignore_length=False, ignore_bad_data=False, fft_threads=1)[source]

Basic function to bandpass and downsample.

Works in place on data. This is employed to ensure all parts of the data are processed in the same way.

Parameters:
  • st (obspy.core.stream.Stream) – Stream to process
  • lowcut (float) – Low cut for bandpass in Hz
  • highcut (float) – High cut for bandpass in Hz
  • filt_order (int) – Number of corners for bandpass filter
  • samp_rate (float) – Sampling rate desired in Hz
  • parallel (bool) – Set to True to process traces in parallel, for small numbers of traces this is often slower than serial processing, defaults to False
  • num_cores (int) – Control the number of cores for parallel processing, if set to False then this will use all the cores available.
  • starttime (obspy.core.utcdatetime.UTCDateTime) – Desired data start time, will trim to this before processing
  • endtime (obspy.core.utcdatetime.UTCDateTime) – Desired data end time, will trim to this before processing
  • seisan_chan_names (bool) – Whether channels are named like seisan channels (which are two letters rather than SEED convention of three) - defaults to True.
  • fill_gaps (bool) – Whether to pad any gaps found with zeros or not.
  • ignore_length (bool) – Whether to allow data that are less than 80% of the requested length. Defaults to False which will error if short data are found.
  • ignore_bad_data (bool) – If False (default), errors will be raised if data are excessively gappy or are mostly zeros. If True then no error will be raised, but an empty trace will be returned.
  • fft_threads (int) – Number of threads to use for pyFFTW FFT in resampling. Note that it is not recommended to use fft_threads > 1 and num_cores > 1.
Returns:

Processed stream
Return type:

obspy.core.stream.Stream

Note

If your data contain gaps you should NOT fill those gaps before using the pre-process functions. The pre-process functions will fill the gaps internally prior to processing, process the data, then re-fill the gaps with zeros to ensure correlations are not incorrectly calculated within gaps. If your data have gaps you should pass a merged stream without the fill_value argument (e.g.: st = st.merge()).

Warning

If you intend to use this for processing templates you should consider how resampling will impact your cross-correlations. Minor differences in resampling between day-long files (which you are likely to use for continuous detection) and shorter files will reduce your cross-correlations!

Example, bandpass

>>> from obspy import read
>>> from eqcorrscan.utils.pre_processing import shortproc
>>> # Get the path to the test data
>>> import eqcorrscan
>>> import os
>>> TEST_PATH = os.path.dirname(eqcorrscan.__file__) + '/tests/test_data'
>>> st = read(TEST_PATH + '/WAV/TEST_/2013-09-01-0410-35.DFDPC_024_00')
>>> st = shortproc(st=st, lowcut=2, highcut=9, filt_order=3, samp_rate=20,
...                parallel=True, num_cores=2)
>>> print(st[0])
AF.LABE..SHZ | 2013-09-01T04:10:35.700000Z - 2013-09-01T04:12:05.650000Z | 20.0 Hz, 1800 samples

Example, low-pass

>>> from obspy import read
>>> from eqcorrscan.utils.pre_processing import shortproc
>>> # Get the path to the test data
>>> import eqcorrscan
>>> import os
>>> TEST_PATH = os.path.dirname(eqcorrscan.__file__) + '/tests/test_data'
>>> st = read(TEST_PATH + '/WAV/TEST_/2013-09-01-0410-35.DFDPC_024_00')
>>> st = shortproc(st=st, lowcut=None, highcut=9, filt_order=3,
...                samp_rate=20)
>>> print(st[0])
AF.LABE..SHZ | 2013-09-01T04:10:35.700000Z - 2013-09-01T04:12:05.650000Z | 20.0 Hz, 1800 samples

Example, high-pass

>>> from obspy import read
>>> from eqcorrscan.utils.pre_processing import shortproc
>>> # Get the path to the test data
>>> import eqcorrscan
>>> import os
>>> TEST_PATH = os.path.dirname(eqcorrscan.__file__) + '/tests/test_data'
>>> st = read(TEST_PATH + '/WAV/TEST_/2013-09-01-0410-35.DFDPC_024_00')
>>> st = shortproc(st=st, lowcut=2, highcut=None, filt_order=3,
...                samp_rate=20)
>>> print(st[0])
AF.LABE..SHZ | 2013-09-01T04:10:35.700000Z - 2013-09-01T04:12:05.650000Z | 20.0 Hz, 1800 samples