Efficient implementatins of the Konno Ohmachi filter in Python.
Project description
pykooh
Konno Ohmachi filter implemented in Numba.
This code implements Konno-Ohmachi spectral smoothing as defined in:
Konno, K. and Ohmachi, T., 1998. Ground-motion characteristics estimated
from spectral ratio between horizontal and vertical components of
microtremor. Bulletin of the Seismological Society of America, 88(1),
pp.228-241.
This code was originally written for smoothing sub-module in gmprocess by Bruce Worden. Dave Boore has provided notes on this topic, which also may be of interest. Notes regarding the characteristics of the Konno-Ohmachi filter and the implementation are provided in the implementation Jupyter Notebook.
Installation
pykooh
is available via pip
and can be installed with:
pip install pykooh
By default, pykooh
uses numba
for the fast implementation of the
filter. Performance can be increased by using cython
, but this
requires a C complier. If a C compiler is available, install cython
required dependencies with:
pip install pykooh[cython]
Usage
Smooth a signal using a bandwith of 30.
import pykooh
signal_smooth = pykooh.smooth(freqs, freqs_raw, signal_raw, 30)
Additional examples and comparison with obspy
are provided in
example.
Citation
Please cite this software using the following DOI.
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