Fast Konno-Ohmachi Spectral Smoothing

Implemented in Rust with a Python interface. The performance gain measured against the widely used Python/numpy implementation that comes with obspy approaches approximately a factor of 2.5 for large and 10 for small vectors (see Benchmarks).

konno-ohmachi demo

Installation

Installation from pypi:

pip install konnoohmachi

Installation from source:

pip install .

Usage

This smoothes some random numbers:

Python

import konnoohmachi

bandwidth = 40

# using fake random data
frequencies = np.arange(1000)
amplitudes = np.random.rand(1000)

smoothed_amplitudes = konnoohmachi.smooth(frequencies, amplitudes, bandwidth)

Rust

use konnoohmachi;

let frequencies = Array1::<f64>::zeros(10);
let amplitudes = Array1::<f64>::ones(10);
let bandwidth = 40.0;
konnoohmachi_smooth(
    frequencies.view().into_dyn(),
    amplitudes.view().into_dyn(),
    bandwidth,
);

Benchmarks

Measuring the execution time based of increasing sized spectra yields: