TEST_EIGEN\
Test Matrices for Eigenvalue Analysis {#test_eigen-test-matrices-for-eigenvalue-analysis align=”center”}
=====================================
TEST_EIGEN is a C++ library which generates eigenvalue tests.
The current version of the code can only generate a symmetric matrix
with eigenvalues distributed according to a normal distribution whose
mean and standard deviation are specified by the user in R8SYMM_GEN.
Licensing: {#licensing align=”center”}
The computer code and data files described and made available on this
web page are distributed under the GNU LGPL
license.
Languages: {#languages align=”center”}
TEST_EIGEN is available in a C
version and a C++
version and a FORTRAN77
version and a FORTRAN90
version and a MATLAB
version and a Python
version.
EISPACK, a C++ library which
carries out eigenvalue computations. It includes a function to compute
the singular value decomposition (SVD) of a rectangular matrix.
superseded by LAPACK;
JACOBI_EIGENVALUE,
a C++ library which implements the Jacobi iteration for the iterative
determination of the eigenvalues and eigenvectors of a real symmetric
matrix.
POWER_METHOD, a C++
library which carries out the power method for finding a dominant
eigenvalue and its eigenvector.
TEST_MAT, a C++ library which
defines test matrices.
TOMS343, a FORTRAN77 library which
computes the eigenvalues and eigenvectors of a general real matrix;\
this is a FORTRAN77 version of ACM TOMS algorithm 343.
TOMS384, a FORTRAN77 library which
computes the eigenvalues and eigenvectors of a symmetric matrix;\
this is a FORTRAN77 version of ACM TOMS algorithm 384.
Reference: {#reference align=”center”}
- Robert Gregory, David Karney,\
A Collection of Matrices for Testing Computational Algorithms,\
Wiley, 1969,\
ISBN: 0882756494,\
LC: QA263.G68.
- 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: {#source-code align=”center”}
Examples and Tests: {#examples-and-tests align=”center”}
List of Routines: {#list-of-routines align=”center”}
- I4_MAX returns the maximum of two I4’s.
- I4_MIN returns the minimum of two I4’s.
- R8_ABS returns the absolute value of an R8.
- R8_NORMAL_01 samples the standard normal probability
distribution.
- R8_SIGN returns the sign of an R8.
- R8_UNIFORM_01 returns a unit pseudorandom R8.
- R8BIN_PRINT prints the bins of a real vector.
- R8MAT_COPY copies one R8MAT to another.
- R8MAT_HOUSE_AXH_NEW computes A*H where H is a compact
Householder matrix.
- R8MAT_IDENTITY returns an identity matrix.
- R8MAT_MM_NEW multiplies two matrices.
- R8MAT_ORTH_UNIFORM returns a random orthogonal matrix.
- R8MAT_PRINT prints an R8MAT.
- R8MAT_PRINT_SOME prints some of an R8MAT.
- R8SYMM_TEST determines a symmetric matrix with a certain
eigenstructure.
- R8VEC_BIN computes bins based on a given R8VEC.
- R8VEC_COPY copies an R8VEC.
- R8VEC_HOUSE_COLUMN defines a Householder premultiplier that
“packs” a column.
- R8VEC_MAX returns the value of the maximum element in an R8VEC.
- R8VEC_MIN returns the value of the minimum element in an R8VEC.
- R8VEC_NORM_L2 returns the L2 norm of an R8VEC.
- R8VEC_NORMAL returns a scaled pseudonormal R8VEC.
- R8VEC_PRINT prints an R8VEC.
- R8VEC_UNIFORM_01_NEW returns a new unit pseudorandom R8VEC.
- R8VEC_ZERO_NEW creates and zeroes an R8VEC.
- R8VEC2_PRINT prints an R8VEC2.
- TIMESTAMP prints the current YMDHMS date as a time stamp.
You can go up one level to the C++ source codes.
Last revised on 22 February 2012.