The analysers.noise_analyser module

class grond.analysers.noise_analyser.analyser.NoiseAnalyser(nwindows, pre_event_noise_duration, check_events, phase_def, statistic, mode, cutoff, cutoff_exception_on_high_snr)[source]

From the pre-event station noise variance-based trace weights are formed.

By default, the trace weights are the inverse of the noise variance. The correlation of the noise is neglected. Optionally, using a the gCMT global earthquake catalogue, the station data are checked for theoretical phase arrivals of M>5 earthquakes. In case of a very probable contamination the trace weights are set to zero. In case global earthquake phase arrivals are within a 30 min time window before the start of the set pre-event noise window, only a warning is thrown.

It is further possible to disregard data with a noise level exceeding the median by a given cutoff factor. These weights are set to 0. This can be done exclusively (mode='weeding') such that noise weights are either 1 or 0, or in combination with weighting below the median-times-cutoff noise level (mode='weighting').

class grond.analysers.noise_analyser.analyser.NoiseAnalyserConfig(**kwargs)[source]

Configuration parameters for the pre-event noise analysis.

nwindows

int, default: 1

number of windows for trace splitting

pre_event_noise_duration

float, default: 0.0

Total length of noise trace in the analysis

phase_def

str, default: 'P'

Onset of phase_def used for upper limit of window

check_events

bool, default: False

check the GlobalCMT for M>5 earthquakes that produce phase arrivals contaminating and affecting the noise analysis

statistic

builtins.str (pyrocko.guts.StringChoice), default: 'var'

Set weight to inverse of noise variance (var) or standard deviation (std).

mode

builtins.str (pyrocko.guts.StringChoice), default: 'weighting'

Generate weights based on inverse of noise measure (weighting), or discrete on/off style in combination with cutoff value (weeding).

cutoff

float, optional

Set weight to zero, when noise level exceeds median by the given cutoff factor.

cutoff_exception_on_high_snr

float, optional

Exclude from cutoff when max amplitude exceeds standard deviation times this factor.