Singular Value Decomposition of Snowfall Data

SVD_SNOWFALL is a Python library which demonstrates the use of the Singular Value Decomposition (SVD) to analyze a set of historical snowfall data.

The snowfall data consists of records for the winters of 1890-1891 to 2016-2017, of the snowfall in inches, over the months from October to May, as measured at Michigan Tech.

This data can be regarded as an 8 by 127 matrix A. Applying the singular value decomposition produces the factors

A = U * S * V'
and it is the purpose of this library to consider what these factors indicate about the snowfall data.


The computer code and data files described and made available on this web page are distributed under the GNU LGPL license.


SVD_SNOWFALL is available in a C version and a C++ version and a FORTRAN90 version and a MATLAB version and a Python version.

Related Data and Programs:

FINGERPRINTS, a dataset directory which contains a few images of fingerprints.

TIME_SERIES, a dataset directory which contains examples of files describing time series.


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    Prentice Hall, 1989,
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Source code:

You can go up one level to the Python source codes.

Last revised on 03 May 2017.