Python 3 LPSD algorithm
Overview
This repository contains a Python 3 implementation of the LPSD algorithm. The implementation is similiar to the LPSD implementation in the Matlab package LTPDA. The core of the algorithm can be run as Python 3 or as (faster) C code. Both deliver the same results. To run the C core the file ltpda_dft.c has to be compiled to a shared library.
Installation
Install directly with pip:
pip install lpsd
Usage
Fully working examples can be found in /doc/examples.
With a DataFrame
Recommended interface, direct usage of a DataFrame
import pandas as pd
from lpsd import lpsd
# read time series
data = pd.read_csv("time_series.csv.gz", index_col=0)
# select column and calculate
spectrum = lpsd(data["column"])
# plot PSD
spectrum["psd"].plot(logx=True, logy=True)
Using numpy arrays
Use the traditional method lpsd_trad, which uses simple numpy arrays.
References
- Improved spectrum estimation from digitized time series on a logarithmic frequency axis Authors: Michael Tröbs and Gerhard Heinzel
- Spectrum and spectral density estimation by the Discrete Fourier transform (DFT), including a comprehensive list of window functions and some new flat-top windows Authors: Gerhard Heinzel, Albrecht Rüdiger and Roland Schilling
- MATLAB Toolbox LTPDA Author: Martin Hewitson
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