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Continuous wavelet transform module for Python. Includes a collection of routines for wavelet transform and statistical analysis via FFT algorithm. This module references to the numpy, scipy and pylab Python packages.
MHee/kPyWavelet
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Continuous wavelet transform module for Python. Includes a collection of routines for wavelet transform and statistical analysis via FFT algorithm. This module references to the numpy, scipy and pylab Python packages. Now are inclued the wavelet cross-spectrun wavelet The sample script (sample.py) illustrates the use of the wavelet and inverse wavelet transforms and the results are plotted in a figure similar to the sample_nino3.png image file. DISCLAIMER This module is based on routines and data provided by C. Torrence and G. Compo available at http://paos.colorado.edu/research/wavelets/ and on routines provided by A. Brazhe available at http://cell.biophys.msu.ru/static/swan/. This software may be used, copied, or redistributed as long as it is not sold and this copyright notice is reproduced on each copy made. This routine is provided as is without any express or implied warranties whatsoever. INSTALLATION (It is necessary to have setuptools): python setup.py install TODO Smooth operator and coherence AUTHOR Sebastian Krieger email: [email protected] Eduardo S. Pereira email: [email protected] REVISION 4 (2013-03-12 11:13 ) 3 (2011-04-30 19:48 -3000) 2 (2011-04-28 17:57 -0300) 1 (2010-12-24 21:59 -0300) REFERENCES [1] Mallat, Stephane G. (1999). A wavelet tour of signal processing [2] Addison, Paul S. The illustrated wavelet transform handbook [3] Torrence, Christopher and Compo, Gilbert P. (1998). A Practical Guide to Wavelet Analysis [4] Grinsted, A., Moore, J. C. and Jevreja, S., 2004, Nonlinear Processes in Geophysics, 11, 561.
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Continuous wavelet transform module for Python. Includes a collection of routines for wavelet transform and statistical analysis via FFT algorithm. This module references to the numpy, scipy and pylab Python packages.
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