Continuous wavelet transform module for Python. Includes a collection of 
routines for wavelet transform and statistical analysis via FFT algorithm. 
Most recently cross-wavelet tranforms, wavelet coherence tests and plotting 
functions were added to the module.
This module references to the numpy, scipy, pylab and maybe other Python 
packages.
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
 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 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
 Copy all the contents into a location included in the Python search
 path. On Linux distribution one such option is
 ~/.local/lib/python2.x/site-packages/pycwt
COMMENTS
 There is an errata page at the wavelet website maintaned at the Program 
 in Atmospheric and Oceanic Sciences, University of Colorado, Boulder, 
 Colorado, wich was (is) accessible throught the link
 
 http://paos.colorado.edu/research/wavelets/errata.html
 
 A Practical Guide to Wavelet Analysis
 Christopher Torrence and Gilbert P. Compo
 Errata
 ~~~~~~ 
 - Figure 3: N/(2 sigma^2) should just be N/sigma^2.
 - Equation (17), left-hand side: Factor of 1/2 should be removed.
 - Table 1, DOG, Psi-hat (third column, bottom row): Should be a minus sign 
 in front of the equation.
 - Sec 3f, last paragraph: Plugging N=506, dt=1/4 yr, s0=2dt, and dj=0.125 
 into Eqn (10) actually gives J=64, not J=56 as stated in the text.
 However, in Figure 1b, the scales are only plotted out to J=56 since the
 power is so low at larger scales.
 Additional information
 ~~~~~~~~~~~~~~~~~~~~~~
 Table 3: Cross-wavelet significance levels, from Eqn.(30)-(31). 
 (DOF = degrees of freedom)
 Significance level Real wavelet (1 DOF) Complex wavelet (2 DOF)
 0.10	 1.595	 3.214
 0.05	 2.182	 3.999
 0.01	 3.604	 5.767
ACKNOWLEDGEMENTS
 I 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.
AUTHOR
 Sebastian Krieger
 email: sebastian@nublia.com
REVISION
 4 (2013年03月06日 19:37 -3000)
 3 (2011年04月30日 19:48 -3000)
 2 (2011年04月28日 17:57 -0300)
 1 (2010年12月24日 21:59 -0300)
REFERENCES
 [1] Mallat, S. (2008). A wavelet tour of signal processing: The
 sparse way. Academic Press, 2008, 805.
 [2] Addison, P. S. (2002). The illustrated wavelet transform 
 handbook: introductory theory and applications in science,
 engineering, medicine and finance. IOP Publishing.
 [3] Torrence, C. and Compo, G. P. (1998). A Practical Guide to 
 Wavelet Analysis. Bulletin of the American Meteorological 
 Society, American Meteorological Society, 1998, 79, 61-78.
 [4] Torrence, C. and Webster, P. J. (1999). Interdecadal changes in
 the ENSO-Monsoon system, Journal of Climate, 12(8), 2679-2690.
 [5] Grinsted, A.; Moore, J. C. & Jevrejeva, S. (2004). Application
 of the cross wavelet transform and wavelet coherence to 
 geophysical time series. Nonlinear Processes in Geophysics, 11,
 561-566.
 [6] Liu, Y.; Liang, X. S. and Weisberg, R. H. (2007). Rectification
 of the bias in the wavelet power spectrum. Journal of 
 Atmospheric and Oceanic Technology, 24(12), 2093-2102.