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No arpack release has been published by Rice University for many years, and
arpack-ng aims to provide a common repository of community fixes with a
testsuite.
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pkglint -r --network --only "migrate"
As a side-effect of migrating the homepages, pkglint also fixed a few
indentations in unrelated lines. These and the new homepages have been
checked manually.
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jwbacon@tds.net ==> bacon@NetBSD.org
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Since arpack installs a dynamic library, its BUILDLINK_DEPMETHOD
shouldn't be set to "build" by default.
Bump PKGREVISION of octave for its runtime dependency change.
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effect. Bump revision.
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Problems found locating distfiles:
Package dfftpack: missing distfile dfftpack-20001209.tar.gz
Package eispack: missing distfile eispack-20001130.tar.gz
Package fftpack: missing distfile fftpack-20001130.tar.gz
Package linpack: missing distfile linpack-20010510.tar.gz
Package minpack: missing distfile minpack-20001130.tar.gz
Package odepack: missing distfile odepack-20001130.tar.gz
Package py-networkx: missing distfile networkx-1.10.tar.gz
Package py-sympy: missing distfile sympy-0.7.6.1.tar.gz
Package quadpack: missing distfile quadpack-20001130.tar.gz
Otherwise, existing SHA1 digests verified and found to be the same on
the machine holding the existing distfiles (morden). All existing
SHA1 digests retained for now as an audit trail.
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File too long (should be no more than 24 lines).
Line too long (should be no more than 80 characters).
Trailing empty lines.
Trailing white-space.
Trucated the long files as best as possible while preserving the most info
contained in them.
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Contributed to pkgsrc-wip by Jason Bacon.
ARPACK is a collection of Fortran77 subroutines designed to solve large
scale eigenvalue problems.
The package is designed to compute a few eigenvalues and corresponding
eigenvectors of a general n by n matrix A. It is most appropriate for large
sparse or structured matrices A where structured means that a matrix-vector
product w <- Av requires order n rather than the usual order n**2 floating
point operations. This software is based upon an algorithmic variant of the
Arnoldi process called the Implicitly Restarted Arnoldi Method (IRAM). When
the matrix A is symmetric it reduces to a variant of the Lanczos process
called the Implicitly Restarted Lanczos Method (IRLM). These variants may be
viewed as a synthesis of the Arnoldi/Lanczos process with the Implicitly
Shifted QR technique that is suitable for large scale problems. For many
standard problems, a matrix factorization is not required. Only the action
of the matrix on a vector is needed. ARPACK software is capable of solving
large scale symmetric, nonsymmetric, and generalized eigenproblems from
significant application areas. The software is designed to compute a few (k)
eigenvalues with user specified features such as those of largest real part
or largest magnitude. Storage requirements are on the order of n*k locations.
No auxiliary storage is required. A set of Schur basis vectors for the desired
k-dimensional eigen-space is computed which is numerically orthogonal to working
precision. Numerically accurate eigenvectors are available on request.
Important Features:
o Reverse Communication Interface.
o Single and Double Precision Real Arithmetic Versions for Symmetric,
Non-symmetric, Standard or Generalized Problems.
o Single and Double Precision Complex Arithmetic Versions for Standard
or Generalized Problems.
o Routines for Banded Matrices - Standard or Generalized Problems.
o Routines for The Singular Value Decomposition.
o Example driver routines that may be used as templates to implement
numerous Shift-Invert strategies for all problem types, data types
and precision.
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