Revert pkglint-induced nonsense.

1 files changed, 35 insertions, 23 deletions

diff --git a/math/arpack/DESCR b/math/arpack/DESCR
index 3205bcda348..ded552c3db2 100644
--- a/math/arpack/DESCR
+++ b/math/arpack/DESCR
@@ -1,23 +1,35 @@
-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.
-   ...and more!
+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.