Basic Processing

DASPy integrates three modules: Preprocessing, Filtering and Frequency Attribute to meet basic data processing needs.

Preprocessing

DASPy integrates a large number of commonly used DAS preprocessing tools, including phase2strain , normalization , demeaning , detrending , stacking , cosine_taper , downsampling , trimming , padding , time_integration and time_differential 。

>>> from daspy import read
>>> sec = read()
>>> sec.detrending()

When processing the data, the corresponding attributes will be automatically changed if necessary:

>>> sec.data_type
'strain rate'
>>> sec.time_integration()
>>> sec.data_type
'strain'

Filtering

DASPy contains commonly used filtering methods, including bandpass , bandstop , lowpass , highpass , envelope and lowpass_cheby_2` (mainly used for low-pass filtering before downsampling):

>>> sec.bandpass(1, 15)

Frequency Attribute

The frequency domain attribute analysis supported by DASPy includes spectrum (x-t), spectrogram (f-t) and frequency-wavenumber spectrum (f-k), which are calculated using spectrum, spectrogram and fk-transform respectively. method calculation. spectrogram calculates the average spectrogram of all channels by default. You can use the xmin and xmax parameters to limit the starting and ending channels of the average spectrum:

>>> spec, f = sec.spectrum()
>>> Zxx, f, t = sec.spectrogram(xmin=2600, xmax=2620)
>>> fk, f, k = sec.fk_transform()

If you only need to plot these three frequency domain spectra without outputting the calculation results, you can directly use the plot method. For details, see Visualization .