TEST_EIGEN
Test Matrices for Eigenvalue Analysis

TEST_EIGEN is a Python library which generates eigenvalue tests.

The current version of the code can only generate a symmetric or nonsymmetric matrix of arbitrary size, with eigenvalues distributed according to a normal distribution whose mean and standard deviation are specified by the user (subroutines R8SYMM_GEN and R8NSYMM_GEN).

Licensing:

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

Languages:

TEST_EIGEN 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:

JACOBI_EIGENVALUE, a Python library which implements the Jacobi iteration for the iterative determination of the eigenvalues and eigenvectors of a real symmetric matrix.

TEST_MAT, a Python library which defines test matrices.

Reference:

1. Robert Gregory, David Karney,
   A Collection of Matrices for Testing Computational Algorithms,
   Wiley, 1969,
   ISBN: 0882756494,
   LC: QA263.G68.
2. Pete Stewart,
   Efficient Generation of Random Orthogonal Matrices With an Application to Condition Estimators,
   SIAM Journal on Numerical Analysis,
   Volume 17, Number 3, June 1980, pages 403-409.

Source Code:

• test_eigen.py, the source code;
• test_eigen.sh, runs the tests.
• test_eigen.txt, the output file.

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