Pyntfa

Description

*Pyntfa is a python package for non-stationary time-frequency analysis. This package has a variety of applications in both exploration and earthquake seismology.

Reference

Chen, Y., 2021, Nonstationary local time-frequency transform, Geophysics, 86(3), V245–V254.

Chen, Y., et al., 2025, Pyntfa: A python package for non-stationary time-frequency analysis, TBD.

BibTeX:

@article{ntfa,
  title={Nonstationary local time-frequency transform},
  author={Yangkang Chen},
  journal={Geophysics},
  volume={86},
  number={3},
  issue={3},
  pages={V245–V254},
  doi={10.1190/geo2020-0298.1},
  year={2021}
}

@article{pyntfa,
  title={PYntfa: A python package for non-stationary time-frequency analysis},
  author={Yangkang Chen and co-authors},
  journal={TBD},
  volume={TBD},
  number={TBD},
  issue={TBD},
  pages={TBD},
  doi={TBD},
  year={2025}
}

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Copyright

The pyntfa developing team, 2021-present

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License

GNU General Public License, Version 3
(http://www.gnu.org/copyleft/gpl.html)   

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Install

Using the latest version (Suggested)

git clone https://github.com/chenyk1990/pyntfa
cd pyntfa
pip install -v -e .

or using Pypi

pip install pyntfa

or

pip install git+https://github.com/chenyk1990/pyntfa

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Examples

The "demo" directory contains all runable scripts to demonstrate different applications of pyntfa. 

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Dependence Packages

• scipy
• numpy
• matplotlib

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Modules

xxx.py  -> description

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Development

The development team welcomes voluntary contributions from any open-source enthusiast. 
If you want to make contribution to this project, feel free to contact the development team. 

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Contact

Regarding any questions, bugs, developments, collaborations, please contact  
Yangkang Chen
chenyk2016@gmail.com

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Gallery

The gallery figures of the pyntfapackage can be found at https://github.com/chenyk1990/gallery/tree/main/pyntfa Each figure in the gallery directory corresponds to a DEMO script in the "demo" directory with the exactly the same file name.

The following figure shows a 1D synthetic example using the pyntfa package. Generated by demos/test_pyntfa_syn1d.py

We can further boost the resolution by the following example demos/test_pyntfa_syn1d_2.py

A comparion between CWT and NTFA demos/test_pyntfa_syn1d_noise.py

A noise influence test using NTFA demos/test_pyntfa_syn1d_noise.py

A noise influence test using CWT (This example reproduces the Figure 4 in Zhang et al., 2020, Convolutional neural networks for microseismic waveform classification and arrival picking, Geophysics, 85, WA227-WA240.) demos/test_pyntfa_syn1d_noise.py

The following figure shows an application on one USArray trace (This example reproduces the Figure 5&6 in Chen, 2021, Nonstationary local time-frequency transform, Geophysics, 86(3), V245–V254.) demos/test_pyntfa_usarray1d.py