svd_powers, a Python code which applies singular value decomposition (SVD) analysis to a set of powers x(i)^(j-1).


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


svd_powers is available in a MATLAB version and a Python version.

Related Data and Programs:

svd_circle, a Python code which analyzes a linear map of the unit circle caused by an arbitrary 2x2 matrix a, using the singular value decomposition (SVD).

svd_lls, a Python code which uses the singular value decomposition (SVD) to construct and plot the best affine and linear relationships in the sense of least square, between two vectors of data.

svd_snowfall, a Python code which reads a file containing historical snowfall data and analyzes the data with the Singular Value Decomposition (SVD).

svd_test, a Python code which demonstrates the singular value decomposition (SVD) for a simple example.


Source Code:

Plots of the SVD vectors:

Plots of the projection of an arbitrary data vector onto the SVD vectors:

Last revised on 31 March 2022.