obspy.signal - Signal processing routines for ObsPy

Capabilities include filtering, triggering, rotation, instrument correction and coordinate transformations.

copyright:The ObsPy Development Team (devs@obspy.org)
license:GNU Lesser General Public License, Version 3 (https://www.gnu.org/copyleft/lesser.html)


The filter module provides various filters, including different bandpass, lowpass, highpass, bandstop and FIR filter.


Before filtering you should make sure that data is demeaned/detrended, e.g. using detrend(). Otherwise there can be massive artifacts from filtering.

The following example shows how to highpass a seismogram at 1.0Hz. In the example only the first trace is processed to see the changes in comparison with the other traces in the plot.


The filter takes the data explicitly as argument (i.e. an numpy.ndarray) and therefore the sampling_rate needs to be also specified. It returns the filtered data. For Stream and Trace objects simply use their respective filtering methods Stream.filter() and Trace.filter().

>>> from obspy import read
>>> import obspy.signal
>>> st = read()
>>> tr = st[0]
>>> tr.data = obspy.signal.filter.highpass(
...     tr.data, 1.0, corners=1, zerophase=True, df=tr.stats.sampling_rate)
>>> st.plot()  

Working with the convenience methods implemented on Stream/Trace works similar:

>>> tr.filter('highpass', freq=1.0, corners=1, zerophase=True)
<...Trace object at 0x...>

(Source code, png, hires.png)


Instrument Correction

The response of the instrument can be removed by the invsim module. The following example shows how to remove the the instrument response of a STS2 and simulate an instrument with 2Hz corner frequency.

>>> from obspy import read
>>> st = read()
>>> st.plot() 

(Source code, png, hires.png)


Now we apply the instrument correction and simulation:

>>> from obspy.signal.invsim import simulate_seismometer, corn_freq_2_paz
>>> inst2hz = corn_freq_2_paz(2.0)
>>> sts2 = {'gain': 60077000.0,
...         'poles': [(-0.037004+0.037016j),
...                   (-0.037004-0.037016j),
...                   (-251.33+0j),
...                   (-131.04-467.29j),
...                   (-131.04+467.29j)],
...         'sensitivity': 2516778400.0,
...         'zeros': [0j, 0j]}
>>> for tr in st:
...     df = tr.stats.sampling_rate
...     tr.data = simulate_seismometer(tr.data, df, paz_remove=sts2,
...                                    paz_simulate=inst2hz,
...                                    water_level=60.0)
>>> st.plot()  

Again, there are convenience methods implemented on Stream/Trace:

>>> tr.simulate(paz_remove=sts2, paz_simulate=inst2hz, water_level=60.0)
<...Trace object at 0x...>

(Source code, png, hires.png)



The trigger module provides various triggering algorithms, including different STA/LTA routines, Z-Detector, AR picker and the P-picker by M. Bear. The implementation is based on [Withers1998] and [Baer1987].

The following example demonstrates a recursive STA/LTA triggering:

>>> from obspy import read
>>> from obspy.signal.trigger import recursive_sta_lta, plot_trigger
>>> st = read()
>>> tr = st.select(component="Z")[0]
>>> tr.filter("bandpass", freqmin=1, freqmax=20)  
<...Trace object at 0x...>
>>> sta = 0.5
>>> lta = 4
>>> cft = recursive_sta_lta(tr.data, int(sta * tr.stats.sampling_rate),
...                        int(lta * tr.stats.sampling_rate))
>>> thrOn = 4
>>> thrOff = 0.7
>>> plot_trigger(tr, cft, thrOn, thrOff) 

(Source code, png, hires.png)


There is also a convenience method implemented on Stream/Trace. It works on and overwrites the traces waveform data and is intended for batch processing rather than for interactive determination of triggering parameters. But it also means that the trace’s built-in methods can be used.

>>> tr.trigger("recstalta", sta=0.5, lta=4)  
<...Trace object at 0x...>
>>> tr.plot()  

(Source code, png, hires.png)


For more examples check out the trigger in the Tutorial. For network coincidence refer to obspy.signal.trigger.coincidence_trigger() and the same page in the Tutorial. For automated use see the following stalta example scripts.

Classes & Functions

array_processing Method for Seismic-Array-Beamforming/FK-Analysis/Capon
array_rotation_strain This routine calculates the best-fitting rigid body rotation and uniform strain as functions of time, and their formal errors, given three-component ground motion time series recorded on a seismic array.
ar_pick Pick P and S arrivals with an AR-AIC + STA/LTA algorithm.
bandpass Butterworth-Bandpass Filter.
bandstop Butterworth-Bandstop Filter.
carl_sta_trig Computes the carlSTAtrig characteristic function.
classic_sta_lta Computes the standard STA/LTA from a given input array a. The length of
coincidence_trigger Perform a network coincidence trigger.
corn_freq_2_paz Convert corner frequency and damping to poles and zeros.
cosine_taper Cosine Taper.
delayed_sta_lta Delayed STA/LTA.
envelope Envelope of a function.
interpolate_1d Wrapper around some scipy interpolation functions.
weighted_average_slopes Implements the weighted average slopes interpolation scheme proposed in
estimate_magnitude Estimate local magnitude.
evalresp Get the instrument response from a SEED RESP-file.
highpass Butterworth-Highpass Filter.
lowpass Butterworth-Lowpass Filter.
paz_to_freq_resp Convert Poles and Zeros (PAZ) to frequency response.
pk_baer Wrapper for P-picker routine by M. Baer, Schweizer Erdbebendienst.
polarization_analysis Method carrying out polarization analysis with the [Flinn1965b],
linear_regression Use linear least squares to fit a function, f, to data.
PPSD Class to compile probabilistic power spectral densities for one combination of network/station/location/channel/sampling_rate.
MSEEDMetadata A container for MiniSEED specific metadata, including quality control
recursive_sta_lta Recursive STA/LTA.
rotate_ne_rt Rotates horizontal components of a seismogram.
simulate_seismometer Simulate/Correct seismometer.
util_geo_km Transform lon, lat to km with reference to orig_lon and orig_lat on the
util_lon_lat Transform x, y [km] to decimal degree in reference to orig_lon and orig_lat
xcorr Cross correlation of tr1 and tr2 in the time domain using window_len.
z_detect Z-detector.


array_analysis Functions for Array Analysis
calibration Functions for relative calibration.
cpxtrace Complex Trace Analysis
cross_correlation Signal processing routines based on cross correlation techniques.
detrend Python module containing detrend methods.
filter Various Seismogram Filtering Functions
freqattributes Frequency Attributes
hoctavbands Half Octave Bands
invsim Python Module for Instrument Correction (Seismology).
interpolation Some Seismogram Interpolating Functions.
konnoohmachismoothing Functions to smooth spectra with the so called Konno & Ohmachi method.
polarization Functions for polarization analysis.
quality_control Quality control module for ObsPy.
regression Python Module for (Weighted) Linear Regression.
spectral_estimation Various Routines Related to Spectral Estimation
rotate Various Seismogram Rotation Functions
tf_misfit Various Time Frequency Misfit Functions based on [Kristekova2006] and
trigger Various routines related to triggering/picking
util Various additional utilities for obspy.signal.