| Name | pycwt JSON |
| Version |
0.4.0b0
JSON |
| download |
| home_page | |
| Summary | Continuous wavelet transform module for Python. |
| upload_time | 2023-03-15 02:37:56 |
| maintainer | |
| docs_url | None |
| author | Nabil Freij, and contributors |
| requires_python | >=3.8 |
| license | PyCWT is released under a BSD-style open source licence: Copyright (c) 2023 Sebastian Krieger, Nabil Freij, and contributors. All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS “AS IS” AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
| keywords |
wavelet
spectral analysis
signal processing
data science
timeseries
time series
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
|ReadTheDocs| |PyPi| |Travis|
PyCWT
=====
A Python module for continuous wavelet spectral analysis. It includes a
collection of routines for wavelet transform and statistical analysis via FFT
algorithm. In addition, the module also includes cross-wavelet transforms,
wavelet coherence tests and sample scripts.
Please read the documentation `here <http://pycwt.readthedocs.io/en/latest/>`__\.
This module requires ``NumPy``, ``SciPy``, ``tqdm``. In addition, you will
also need ``matplotlib`` to run the examples.
The sample scripts (``sample.py``, ``sample_xwt.py``) illustrate the use of
the wavelet and inverse wavelet transforms, cross-wavelet transform and
wavelet transform coherence. Results are plotted in figures similar to the
sample images.
Disclaimer
----------
This module is based on routines provided by C. Torrence and G. P. Compo
available at http://paos.colorado.edu/research/wavelets/, on routines
provided by A. Grinsted, J. Moore and S. Jevrejeva available at
http://noc.ac.uk/using-science/crosswavelet-wavelet-coherence, and
on routines provided by A. Brazhe available at
http://cell.biophys.msu.ru/static/swan/.
This software is released under a BSD-style open source license. Please read
the license file for further information. This routine is provided as is
without any express or implied warranties whatsoever.
Installation
------------
We recommend using PyPI to install this package.
.. code-block:: sh
$ pip install pycwt
However, if you want to install directly from GitHub, use:
.. code-block:: sh
$ pip install git+https://github.com/regeirk/pycwt
Acknowledgements
----------------
We would like to thank Christopher Torrence, Gilbert P. Compo, Aslak Grinsted,
John Moore, Svetlana Jevrejevaand and Alexey Brazhe for their code and also
Jack Ireland and Renaud Dussurget for their attentive eyes, feedback and
debugging.
Contributors
------------
- Sebastian Krieger
- Nabil Freij
- Ken Mankoff
- Aaron Nielsen
- Rodrigo Nemmen
- Ondrej Grover
- Joscelin Rocha Hidalgo
- Stuart Mumford
- ymarcon1
- Tariq Hassan
References
----------
1. Torrence, C. and Compo, G. P.. A Practical Guide to Wavelet
Analysis. Bulletin of the American Meteorological Society, *American
Meteorological Society*, **1998**, 79, 61-78.
2. Torrence, C. and Webster, P. J.. Interdecadal changes in the
ENSO-Monsoon system, *Journal of Climate*, **1999**, 12(8),
2679-2690.
3. Grinsted, A.; Moore, J. C. & Jevrejeva, S. Application of the cross
wavelet transform and wavelet coherence to geophysical time series.
*Nonlinear Processes in Geophysics*, **2004**, 11, 561-566.
4. Mallat, S.. A wavelet tour of signal processing: The sparse way.
*Academic Press*, **2008**, 805.
5. Addison, P. S. The illustrated wavelet transform handbook:
introductory theory and applications in science, engineering,
medicine and finance. *IOP Publishing*, **2002**.
6. Liu, Y., Liang, X. S. and Weisberg, R. H. Rectification of the bias
in the wavelet power spectrum. *Journal of Atmospheric and Oceanic
Technology*, **2007**, 24, 2093-2102.
.. |ReadTheDocs| image:: https://readthedocs.org/projects/pycwt/badge/?version=latest
:target: http://pycwt.readthedocs.io/en/latest/?badge=latest
.. |PyPi| image:: https://badge.fury.io/py/pycwt.svg
:target: https://badge.fury.io/py/pycwt
.. |Travis| image:: https://travis-ci.org/regeirk/pycwt.svg?branch=master
:target: https://travis-ci.org/regeirk/pycwt
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