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test_eigen.html
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<html>
<head>
<title>
TEST_EIGEN - Test Matrices for Eigenvalue Analysis
</title>
</head>
<body bgcolor="#EEEEEE" link="#CC0000" alink="#FF3300" vlink="#000055">
<h1 align = "center">
TEST_EIGEN <br> Test Matrices for Eigenvalue Analysis
</h1>
<hr>
<p>
<b>TEST_EIGEN</b>
is a C++ library which
generates eigenvalue tests.
</p>
<p>
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 (subroutine SYMM_TEST).
</p>
<h3 align = "center">
Licensing:
</h3>
<p>
The computer code and data files described and made available on this web page
are distributed under
<a href = "../../txt/gnu_lgpl.txt">the GNU LGPL license.</a>
</p>
<h3 align = "center">
Languages:
</h3>
<p>
<b>TEST_EIGEN</b> is available in
<a href = "../../c_src/test_eigen/test_eigen.html">a C version</a> and
<a href = "../../cpp_src/test_eigen/test_eigen.html">a C++ version</a> and
<a href = "../../f77_src/test_eigen/test_eigen.html">a FORTRAN77 version</a> and
<a href = "../../f_src/test_eigen/test_eigen.html">a FORTRAN90 version</a> and
<a href = "../../m_src/test_eigen/test_eigen.html">a MATLAB version</a>.
</p>
<h3 align = "center">
Related Data and Programs:
</h3>
<p>
<a href = "../../cpp_src/eispack/eispack.html">
EISPACK</a>,
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superseded by LAPACK;
</p>
<p>
<a href = "../../cpp_src/jacobi_eigenvalue/jacobi_eigenvalue.html">
JACOBI_EIGENVALUE</a>,
a C++ library which
implements the Jacobi iteration for the iterative determination
of the eigenvalues and eigenvectors of a real symmetric matrix.
</p>
<p>
<a href = "../../cpp_src/power_method/power_method.html">
POWER_METHOD</a>,
a C++ library which
carries out the power method for finding a dominant eigenvalue
and its eigenvector.
</p>
<p>
<a href = "../../cpp_src/test_mat/test_mat.html">
TEST_MAT</a>,
a C++ library which
defines test matrices.
</p>
<p>
<a href = "../../f77_src/toms343/toms343.html">
TOMS343</a>,
a FORTRAN77 library which
computes the eigenvalues and
eigenvectors of a general real matrix;<br>
this is a FORTRAN77 version of ACM TOMS algorithm 343.
</p>
<p>
<a href = "../../f77_src/toms384/toms384.html">
TOMS384</a>,
a FORTRAN77 library which
computes the eigenvalues and eigenvectors
of a symmetric matrix;<br>
this is a FORTRAN77 version of ACM TOMS algorithm 384.
</p>
<h3 align = "center">
Reference:
</h3>
<p>
<ol>
<li>
Robert Gregory, David Karney,<br>
A Collection of Matrices for Testing Computational Algorithms,<br>
Wiley, 1969,<br>
ISBN: 0882756494,<br>
LC: QA263.G68.
</li>
<li>
Pete Stewart,<br>
Efficient Generation of Random Orthogonal Matrices With an Application
to Condition Estimators,<br>
SIAM Journal on Numerical Analysis,<br>
Volume 17, Number 3, June 1980, pages 403-409.
</li>
</ol>
</p>
<h3 align = "center">
Source Code:
</h3>
<p>
<ul>
<li>
<a href = "test_eigen.cpp">test_eigen.cpp</a>, the source code;
</li>
<li>
<a href = "test_eigen.hpp">test_eigen.hpp</a>, the include file;
</li>
<li>
<a href = "test_eigen.sh">test_eigen.sh</a>,
commands to compile the source code;
</li>
</ul>
</p>
<h3 align = "center">
Examples and Tests:
</h3>
<p>
<ul>
<li>
<a href = "test_eigen_prb.cpp">test_eigen_prb.cpp</a>,
the calling program;
</li>
<li>
<a href = "test_eigen_prb.sh">test_eigen_prb.sh</a>,
commands to compile, link and run the calling program;
</li>
<li>
<a href = "test_eigen_prb_output.txt">test_eigen_prb_output.txt</a>,
the output file.
</li>
</ul>
</p>
<h3 align = "center">
List of Routines:
</h3>
<p>
<ul>
<li>
<b>I4_MAX</b> returns the maximum of two I4's.
</li>
<li>
<b>I4_MIN</b> returns the minimum of two I4's.
</li>
<li>
<b>R8_ABS</b> returns the absolute value of an R8.
</li>
<li>
<b>R8_NORMAL_01</b> samples the standard normal probability distribution.
</li>
<li>
<b>R8_SIGN</b> returns the sign of an R8.
</li>
<li>
<b>R8_UNIFORM_01</b> returns a unit pseudorandom R8.
</li>
<li>
<b>R8BIN_PRINT</b> prints the bins of a real vector.
</li>
<li>
<b>R8MAT_COPY</b> copies one R8MAT to another.
</li>
<li>
<b>R8MAT_HOUSE_AXH_NEW</b> computes A*H where H is a compact Householder matrix.
</li>
<li>
<b>R8MAT_IDENTITY</b> returns an identity matrix.
</li>
<li>
<b>R8MAT_MM_NEW</b> multiplies two matrices.
</li>
<li>
<b>R8MAT_ORTH_UNIFORM</b> returns a random orthogonal matrix.
</li>
<li>
<b>R8MAT_PRINT</b> prints an R8MAT.
</li>
<li>
<b>R8MAT_PRINT_SOME</b> prints some of an R8MAT.
</li>
<li>
<b>R8SYMM_TEST</b> determines a symmetric matrix with a certain eigenstructure.
</li>
<li>
<b>R8VEC_BIN</b> computes bins based on a given R8VEC.
</li>
<li>
<b>R8VEC_COPY</b> copies an R8VEC.
</li>
<li>
<b>R8VEC_HOUSE_COLUMN</b> defines a Householder premultiplier that "packs" a column.
</li>
<li>
<b>R8VEC_MAX</b> returns the value of the maximum element in an R8VEC.
</li>
<li>
<b>R8VEC_MIN</b> returns the value of the minimum element in an R8VEC.
</li>
<li>
<b>R8VEC_NORM_L2</b> returns the L2 norm of an R8VEC.
</li>
<li>
<b>R8VEC_NORMAL</b> returns a scaled pseudonormal R8VEC.
</li>
<li>
<b>R8VEC_PRINT</b> prints an R8VEC.
</li>
<li>
<b>R8VEC_UNIFORM_01_NEW</b> returns a new unit pseudorandom R8VEC.
</li>
<li>
<b>R8VEC_ZERO_NEW</b> creates and zeroes an R8VEC.
</li>
<li>
<b>R8VEC2_PRINT</b> prints an R8VEC2.
</li>
<li>
<b>TIMESTAMP</b> prints the current YMDHMS date as a time stamp.
</li>
</ul>
</p>
<p>
You can go up one level to <a href = "../cpp_src.html">
the C++ source codes</a>.
</p>
<hr>
<i>
Last revised on 22 February 2012.
</i>
<!-- John Burkardt -->
</body>
</html>