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: sebastian@nublia.com
    Eduardo S. Pereira
    email: pereira.somoza@gmail.com

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.