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.

The linear relationship will have the form

  ( y - mean(y) ) = slope * ( x - mean(x) )

The affine relationship will have the form

  y = slope * x + intercept


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


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

Related Data and Programs:

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.


  1. Lloyd Trefethen, David Bau,
    Numerical Linear Algebra,
    SIAM, 1997,
    ISBN: 0-89871-361-7,
    LC: QA184.T74.

Source Code:

Last revised on 31 March 2022.