P4TSA (package for Time Series Analysis)

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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?

• Repo owner or admin (info@elenacuoco.com)
• Other community or team contact (elena.cuoco@ego-gw.it, giancarlo.cella@pi.infn.it, fmorawski@camk.edu.pl)