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Pakage for Time Series Analysis

License: GNU General Public License v3.0

Shell 0.54% C++ 93.69% Python 0.98% Makefile 4.51% CMake 0.29%

p4tsa's Introduction

P4TSA (package for Time Series Analysis)

Foo Build Status

([email protected]) https://www.elenacuoco.com

This library is a 'spin-off' of C++ Noise Analysis Package (NAP). The core library is written in C++ and should be compiled before using the python interface.

The Python interface to the library is pyTSA (you can call it pi'za)

What is this repository for?

p4TSA is a minimal package containing ad hoc function to work with time series. It includes

  • Whitening in time domain
  • Double Whitening (equivalent to dividing by Power Spectral density) in time domain
  • Wavelet decomposition
  • Wavelet Detection Filter

How do I get set up?

  • You need to have a python environment setup and some extralibrary (boost, FramLib,gsl,fftw3 installed)

  • You should run cmake CMakeList.txt

  • Dependencies: gsl, fftw3, gslcblas, Framelib

  • Python Binding: it depends on binder and pybind11 which should be installed

  • Database configuration: none

  • How to run tests: under dir test run

    python test.py

  • Deployment instructions: under python-wrapper directory run

    python setup.py install

Contribution guidelines

  • Writing tests
  • Code review
  • Other guidelines

Who do I talk to?

p4tsa's People

Contributors

elenacuoco avatar filipmor avatar

Watchers

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