random_matrix_eigenvalues


random_matrix_eigenvalues, a Python code which demonstrates how, for certain probability density functions (PDF), a symmetric matrix with entries sampled from that PDF will have eigenvalues distributed according to Wigner's semicircle distribution.

Licensing:

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

Languages:

random_matrix_eigenvalues is available in a Python version.

Related Data and Programs:

test_mat, a Python code which defines test matrices for which the condition, determinant, eigenvalues, inverse, null vectors, P*L*U factorization or linear system solution are already known, including the Vandermonde and Wathen matrix.

Reference:

  1. John D Cook, Heavy-tailed random matrices, https://www.johndcook.com/blog/

Source Code:


Last revised on 10 February 2017.