eqcorrscan.core.subspace.Detector

class eqcorrscan.core.subspace.Detector(name=None, sampling_rate=None, multiplex=None, stachans=None, lowcut=None, highcut=None, filt_order=None, data=None, u=None, sigma=None, v=None, dimension=None)[source]

Bases: object

Class to serve as the base for subspace detections.

Parameters:
  • name (str) Name of subspace detector, used for book-keeping
  • sampling_rate (float) Sampling rate in Hz of original waveforms
  • multiplex (bool) Is this detector multiplexed.
  • stachans (list) List of tuples of (station, channel) used in detector. If multiplexed, these must be in the order that multiplexing was done.
  • lowcut (float) Lowcut filter in Hz
  • highcut (float) Highcut filter in Hz
  • filt_order (int) Number of corners for filtering
  • data (numpy.ndarray) The actual detector
  • u (numpy.ndarray) Full rank U matrix of left (input) singular vectors.
  • sigma (numpy.ndarray) Full rank vector of singular values.
  • v (numpy.ndarray) Full rank right (output) singular vectors.
  • dimension (int) Dimension of data.
__init__(name=None, sampling_rate=None, multiplex=None, stachans=None, lowcut=None, highcut=None, filt_order=None, data=None, u=None, sigma=None, v=None, dimension=None)[source]

Methods

__init__([name, sampling_rate, multiplex, ...])
construct(streams, lowcut, highcut, ...[, ...]) Construct a subspace detector from a list of streams, full rank.
detect(st, threshold, trig_int[, moveout, ...]) Detect within continuous data using the subspace method.
energy_capture() Calculate the average percentage energy capture for this subspace.
partition(dimension) Partition subspace into desired dimension.
read(filename) Read detector from a file, must be HDF5 format.
write(filename) Write detector to a file - uses HDF5 file format.