git: d0a737fa905e - main - Revert "math/*: Improve and expand pkg-descr"
Date: Tue, 30 Sep 2025 07:11:07 UTC
The branch main has been updated by yuri:
URL: https://cgit.FreeBSD.org/ports/commit/?id=d0a737fa905e1eec6ccf7c7fbbdc3df78b21471a
commit d0a737fa905e1eec6ccf7c7fbbdc3df78b21471a
Author: Yuri Victorovich <yuri@FreeBSD.org>
AuthorDate: 2025-09-30 07:10:39 +0000
Commit: Yuri Victorovich <yuri@FreeBSD.org>
CommitDate: 2025-09-30 07:10:55 +0000
Revert "math/*: Improve and expand pkg-descr"
This reverts commit 5f90970e571a0fbd9caee91a04409f5c8ab1f9fe.
---
math/R-cran-combinat/pkg-descr | 18 +-----------
math/R-cran-conf.design/pkg-descr | 26 ++----------------
math/R-cran-cvar/pkg-descr | 30 +++++---------------
math/R-cran-fracdiff/pkg-descr | 23 ++--------------
math/R-cran-gbutils/pkg-descr | 25 ++++++-----------
math/R-cran-magic/pkg-descr | 30 ++++++++------------
math/R-cran-nortest/pkg-descr | 18 +-----------
math/R-cran-quadprog/pkg-descr | 21 ++------------
math/R-cran-qualityTools/pkg-descr | 29 ++++++--------------
math/algae/pkg-descr | 23 +++-------------
math/apc/pkg-descr | 31 ++++++++++-----------
math/aribas/pkg-descr | 28 ++++---------------
math/arpack++/pkg-descr | 22 +++------------
math/atlas/pkg-descr | 37 ++++++++++++-------------
math/blacs/pkg-descr | 28 ++++---------------
math/blocksolve95/pkg-descr | 26 ++++++++----------
math/brial/pkg-descr | 31 +++++++--------------
math/clblas/pkg-descr | 28 ++++++-------------
math/clblast/pkg-descr | 24 ++--------------
math/clfft/pkg-descr | 27 ++++--------------
math/cliquer/pkg-descr | 28 +++++--------------
math/clrng/pkg-descr | 31 ++++++---------------
math/cocoalib/pkg-descr | 24 ++++------------
math/concorde/pkg-descr | 32 ++++++++--------------
math/crlibm/pkg-descr | 39 ++++++++++++--------------
math/dieharder/pkg-descr | 37 +++++++++++++------------
math/edenmath/pkg-descr | 22 ++-------------
math/eispack/pkg-descr | 28 ++++++++-----------
math/emc2/pkg-descr | 26 +++++-------------
math/ent/pkg-descr | 25 ++++-------------
math/fftw/pkg-descr | 37 ++++++++++---------------
math/frobby/pkg-descr | 32 ++++++++--------------
math/gexpr/pkg-descr | 15 ++--------
math/glgraph/pkg-descr | 17 ++----------
math/gmp-ecm/pkg-descr | 22 ++-------------
math/grace/pkg-descr | 36 ++++++++++--------------
math/grpn/pkg-descr | 26 ++++--------------
math/ised/pkg-descr | 29 ++++++--------------
math/jags/pkg-descr | 28 ++++++-------------
math/jeuclid/pkg-descr | 25 +++--------------
math/jlatexmath/pkg-descr | 39 ++++++++++++--------------
math/lcalc/pkg-descr | 21 ++------------
math/ldouble/pkg-descr | 22 ++-------------
math/libbraiding/pkg-descr | 25 ++++-------------
math/libhomfly/pkg-descr | 25 ++++-------------
math/libocas/pkg-descr | 27 +++++-------------
math/libranlip/pkg-descr | 22 ++++-----------
math/linpack/pkg-descr | 24 +++-------------
math/lll_spect/pkg-descr | 27 ++++--------------
math/lrng/pkg-descr | 12 ++------
math/m4ri/pkg-descr | 29 ++++----------------
math/m4rie/pkg-descr | 23 ++--------------
math/math77/pkg-descr | 19 ++-----------
math/mbasecalc/pkg-descr | 18 ++----------
math/miracl/pkg-descr | 35 ++++++++++--------------
math/mtrxmath/pkg-descr | 24 +++-------------
math/mumps4/pkg-descr | 34 ++++++++++-------------
math/nfft/pkg-descr | 35 ++++++++++--------------
math/ngraph/pkg-descr | 43 ++++++++++++++++++-----------
math/numdiff/pkg-descr | 25 ++++-------------
math/ocamlgsl/pkg-descr | 24 ++--------------
math/physcalc/pkg-descr | 25 +++--------------
math/plplot/pkg-descr | 37 +++++++++----------------
math/primegen/pkg-descr | 28 ++++---------------
math/prng/pkg-descr | 26 +++---------------
math/py-claripy/pkg-descr | 22 ++-------------
math/py-fvcore/pkg-descr | 25 +++--------------
math/py-luminol/pkg-descr | 26 ++----------------
math/py-pytorchvideo/pkg-descr | 28 ++++---------------
math/py-svgmath/pkg-descr | 22 ++-------------
math/qtiplot-doc/pkg-descr | 25 ++---------------
math/randlib/pkg-descr | 41 ++++++++++++++--------------
math/reduce-psl/pkg-descr | 34 ++++++++++-------------
math/rngstreams/pkg-descr | 28 ++++++-------------
math/sc/pkg-descr | 29 +++++---------------
math/scilab-toolbox-swt/pkg-descr | 34 +++++++++--------------
math/scilab/pkg-descr | 56 ++++++++++++++++++++++----------------
math/sfft/pkg-descr | 25 ++++-------------
math/slatec/pkg-descr | 24 ++--------------
math/snns/pkg-descr | 41 ++++++++++++++--------------
math/solitaire/pkg-descr | 27 ++++--------------
math/spblas/pkg-descr | 31 +++++----------------
math/tomsfastmath/pkg-descr | 20 ++------------
math/trlan/pkg-descr | 31 +++++----------------
math/tvmet/pkg-descr | 28 +++----------------
math/ump/pkg-descr | 18 ++----------
math/xplot/pkg-descr | 10 +------
math/xspread/pkg-descr | 18 ++----------
88 files changed, 658 insertions(+), 1738 deletions(-)
diff --git a/math/R-cran-combinat/pkg-descr b/math/R-cran-combinat/pkg-descr
index 322223dcabdd..e27b37a777d3 100644
--- a/math/R-cran-combinat/pkg-descr
+++ b/math/R-cran-combinat/pkg-descr
@@ -1,17 +1 @@
-The R-cran-combinat package provides a collection of essential routines
-for combinatorial mathematics within the R environment. Combinatorics is
-a branch of mathematics concerning the study of finite or countable
-discrete structures.
-
-This package offers functions to generate and manipulate various combinatorial
-objects, including permutations, combinations, and partitions. It is
-invaluable for researchers, statisticians, and data scientists who need
-to perform tasks such as:
-
-- Generating all possible orderings of a set of items.
-- Selecting subsets of items without regard to their order.
-- Enumerating ways to divide a set into non-empty subsets.
-
-By providing these fundamental combinatorial tools, R-cran-combinat
-facilitates a wide range of applications in probability, statistics,
-computer science, and experimental design.
+Routines for combinatorics.
diff --git a/math/R-cran-conf.design/pkg-descr b/math/R-cran-conf.design/pkg-descr
index de393137be7b..73da04d8c40a 100644
--- a/math/R-cran-conf.design/pkg-descr
+++ b/math/R-cran-conf.design/pkg-descr
@@ -1,24 +1,2 @@
-The R-cran-conf.design package provides a specialized set of tools
-within the R environment for the construction and manipulation of
-confounded and fractional factorial designs. These experimental designs
-are fundamental in statistics and engineering for efficiently studying
-the effects of multiple factors on an outcome, especially when resources
-are limited.
-
-Confounded designs allow for the study of a large number of factors
-with a smaller number of experimental runs by strategically sacrificing
-information about higher-order interactions. Fractional factorial designs
-are a type of confounded design that uses a fraction of the full factorial
-experiment, making them highly efficient for screening important factors.
-
-This library simplifies the process of setting up and analyzing such
-designs, making it invaluable for:
-
-- Experiment design in industrial and scientific research.
-- Quality improvement and process optimization.
-- Situations where a full factorial experiment is impractical due to
- cost or time constraints.
-
-By offering these simple yet powerful tools, R-cran-conf.design enables
-researchers and practitioners to conduct more efficient and insightful
-experiments.
+This small library contains a series of simple tools for constructing and
+manipulating confounded and fractional factorial designs.
diff --git a/math/R-cran-cvar/pkg-descr b/math/R-cran-cvar/pkg-descr
index efad457a0534..ca1bec8d7a68 100644
--- a/math/R-cran-cvar/pkg-descr
+++ b/math/R-cran-cvar/pkg-descr
@@ -1,23 +1,7 @@
-The R-cran-cvar package provides essential tools for risk management,
-enabling the computation of Expected Shortfall (ES) and Value at Risk (VaR).
-ES, also known as Conditional Value at Risk (CVaR), and VaR are key metrics
-used to quantify potential financial losses in portfolios or investments.
-
-This package offers high flexibility, allowing users to compute these
-risk measures from various input types, including:
-
-- Quantile functions
-- Distribution functions
-- Random number generators
-- Probability density functions
-
-It supports virtually any continuous distribution, making it adaptable
-to diverse financial models. The functions are vectorized for efficient
-computation across multiple arguments. The calculations are performed
-directly from their definitions, as detailed by Acerbi and Tasche (2002).
-Additionally, the package includes some support for GARCH (Generalized
-Autoregressive Conditional Heteroskedasticity) models, further enhancing
-its utility for analyzing financial time series volatility.
-
-R-cran-cvar is an invaluable resource for financial analysts, risk managers,
-and quantitative researchers working with R to assess and manage financial risk.
+Compute expected shortfall (ES) and Value at Risk (VaR) from a quantile
+function, distribution function, random number generator or probability density
+function. ES is also known as Conditional Value at Risk (CVaR). Virtually any
+continuous distribution can be specified. The functions are vectorized over the
+arguments. The computations are done directly from the definitions, see e.g.
+Acerbi and Tasche (2002) <doi:10.1111/1468-0300.00091>. Some support for GARCH
+models is provided, as well.
diff --git a/math/R-cran-fracdiff/pkg-descr b/math/R-cran-fracdiff/pkg-descr
index 229027fb8b72..2058c9e95b8e 100644
--- a/math/R-cran-fracdiff/pkg-descr
+++ b/math/R-cran-fracdiff/pkg-descr
@@ -1,20 +1,3 @@
-The R-cran-fracdiff package provides robust functionality for the
-maximum likelihood estimation of parameters in fractionally differenced
-ARIMA(p,d,q) models. These models are a powerful extension of traditional
-ARIMA models, designed to capture long-range dependence in time series data,
-where the 'd' parameter (differencing order) can be a non-integer value.
-
-Fractionally differenced ARIMA models are particularly useful for
-analyzing phenomena that exhibit persistent memory effects, such as:
-
-- Financial time series (e.g., stock prices, volatility)
-- Hydrological data (e.g., river flows, rainfall)
-- Environmental data (e.g., temperature anomalies)
-- Long-memory processes in various scientific and engineering fields
-
-Based on the methodology by Haslett and Raftery (Applied Statistics, 1989),
-this package offers a reliable and statistically sound approach to
-modeling time series with fractional integration. It enables researchers
-and practitioners in R to accurately estimate the parameters of these
-complex models, leading to more precise forecasts and a deeper understanding
-of long-memory processes.
+Maximum likelihood estimation of the parameters of a fractionally
+differenced ARIMA(p,d,q) model (Haslett and Raftery, Appl.Statistics,
+1989).
diff --git a/math/R-cran-gbutils/pkg-descr b/math/R-cran-gbutils/pkg-descr
index 6d016a6ddf25..8182290d8372 100644
--- a/math/R-cran-gbutils/pkg-descr
+++ b/math/R-cran-gbutils/pkg-descr
@@ -1,17 +1,8 @@
-The R-cran-gbutils package offers general-purpose utilities for numerical
-and statistical computations in R, enhancing flexibility and ease of use.
-
-Key functionalities include:
-
-- **Distribution Analysis**: Plotting density/distribution functions,
- numerically inverting distributions for quantiles, and simulating
- real/complex numbers from magnitude/argument distributions.
-- **Polynomial Manipulation**: Creating polynomials from roots
- (Cartesian or polar form).
-- **Programming Utilities**: Checking for NA identity, counting
- positional arguments, computing set intersections for multiple sets,
- identifying unnamed arguments, and graphing S4 classes.
-
-This invaluable toolkit streamlines common tasks in data analysis,
-statistical modeling, and numerical programming, boosting productivity
-and analytical capabilities for R users.
+Plot density and distribution functions with automatic selection of suitable
+regions. Numerically invert (compute quantiles) distribution functions.
+Simulate real and complex numbers from distributions of their magnitude and
+arguments. Optionally, the magnitudes and/or arguments may be fixed in almost
+arbitrary ways. Create polynomials from roots given in Cartesian or polar form.
+Small programming utilities: check if an object is identical to NA, count
+positional arguments in a call, set intersection of more than two sets, check
+if an argument is unnamed, compute the graph of S4 classes in packages.
diff --git a/math/R-cran-magic/pkg-descr b/math/R-cran-magic/pkg-descr
index 973187f4cb25..500c3c8314bf 100644
--- a/math/R-cran-magic/pkg-descr
+++ b/math/R-cran-magic/pkg-descr
@@ -1,19 +1,11 @@
-The R-cran-magic package provides efficient, vectorized algorithms for
-creating and investigating magic squares and hypercubes. It includes
-functions for manipulating and analyzing multi-dimensional arrays.
-
-Key features:
-
-- **Magic Square Creation**: Methods for generating normal magic
- squares of any order greater than 2.
-- **Analysis Tools**: Functions for the manipulation and analysis of
- arbitrarily dimensioned arrays, including numerical verification
- of magic square properties (e.g., determinant of odd-ordered
- semimagic squares).
-- **Antimagic Functionality**: Support for antimagic squares and
- related concepts.
-
-The package aims to be a comprehensive computerized embodiment of magic
-square knowledge, offering direct numerical verification of their
-properties. It is a valuable resource for mathematicians, statisticians,
-and R users interested in combinatorial designs and recreational mathematics.
+A collection of efficient, vectorized algorithms for the creation
+and investigation of magic squares and hypercubes, including a
+variety of functions for the manipulation and analysis of arbitrarily
+dimensioned arrays. The package includes methods for creating normal
+magic squares of any order greater than 2. The ultimate intention
+is for the package to be a computerized embodiment all magic square
+knowledge, including direct numerical verification of properties
+of magic squares (such as recent results on the determinant of
+odd-ordered semimagic squares). Some antimagic functionality is
+included. The package also serves as a rebuttal to the often-heard
+comment "I thought R was just for statistics".
diff --git a/math/R-cran-nortest/pkg-descr b/math/R-cran-nortest/pkg-descr
index 9931aa8c41fa..c6ea3f75138a 100644
--- a/math/R-cran-nortest/pkg-descr
+++ b/math/R-cran-nortest/pkg-descr
@@ -1,17 +1 @@
-The R-cran-nortest package provides a suite of five omnibus tests
-for assessing the composite hypothesis of normality in statistical data.
-Normality tests are crucial in statistics to determine if a data set
-is well-modeled by a normal distribution, which is a common assumption
-for many parametric statistical methods.
-
-This package includes implementations of the following widely used tests:
-- Anderson-Darling test
-- Cramer-von Mises test
-- Shapiro-Francia test
-- Lilliefors test (Kolmogorov-Smirnov test with estimated parameters)
-- Pearson chi-square test
-
-These tests are valuable tools for statisticians, researchers, and data
-analysts working with R, enabling them to rigorously evaluate the
-distributional assumptions of their data before applying further
-statistical procedures.
+Five omnibus tests for testing the composite hypothesis of normality.
diff --git a/math/R-cran-quadprog/pkg-descr b/math/R-cran-quadprog/pkg-descr
index c4a3622d3ad8..95c41d16dc00 100644
--- a/math/R-cran-quadprog/pkg-descr
+++ b/math/R-cran-quadprog/pkg-descr
@@ -1,18 +1,3 @@
-The R-cran-quadprog package provides an efficient and reliable implementation
-of the dual method by Goldfarb and Idnani (1982, 1983) for solving
-quadratic programming problems.
-
-Quadratic programming is a type of mathematical optimization problem that
-involves minimizing a quadratic objective function subject to linear
-constraints. This package is particularly useful for tasks such as
-portfolio optimization, support vector machines, and other statistical
-modeling applications where such optimization is required.
-
-Specifically, it solves problems of the form:
-minimize -d'b + 1/2 b'Db
-subject to A'b >= b0
-
-where 'b' is the vector of variables to be optimized, 'd' is a vector,
-'D' is a symmetric positive-definite matrix, 'A' is a matrix, and 'b0'
-is a vector. The routine ensures accurate and robust solutions for
-these types of constrained optimization problems within the R environment.
+This routine implements the dual method of Goldfarb and Idnani
+(1982, 1983) for solving quadratic programming problems of the form
+min(?dT b + 1/2bT Db) with the constraints AT b >= b0.
diff --git a/math/R-cran-qualityTools/pkg-descr b/math/R-cran-qualityTools/pkg-descr
index 22f262d64ea9..a5da45e35c2e 100644
--- a/math/R-cran-qualityTools/pkg-descr
+++ b/math/R-cran-qualityTools/pkg-descr
@@ -1,21 +1,10 @@
-The R-cran-qualityTools package provides a comprehensive suite of
-statistical methods essential for Quality Science and Six Sigma
-Quality Management, particularly supporting the Define, Measure,
-Analyze, Improve, and Control (DMAIC) cycle.
+qualityTools: Statistical Methods for Quality Science
-Key functionalities include:
-
-- **Distribution Fitting**: Tools for fitting various statistical
- distributions to data.
-- **Process Capability Analysis**: Calculation of normal and non-normal
- process capability indices.
-- **Measurement Systems Analysis (MSA)**: Techniques such as gauge
- capability indices and Gauge Repeatability and Reproducibility (GR&R)
- studies.
-- **Experimental Design**: Support for factorial and fractional
- factorial designs.
-- **Response Surface Methods**: Including the use of desirability functions.
-
-This package is an invaluable resource for quality engineers, statisticians,
-and practitioners implementing Six Sigma methodologies, enabling robust
-analysis and improvement of processes.
+Contains methods associated with the Define, Measure, Analyze, Improve and
+Control (i.e. DMAIC) cycle of the Six Sigma Quality Management
+methodology.It covers distribution fitting, normal and non-normal process
+capability indices, techniques for Measurement Systems Analysis especially
+gage capability indices and Gage Repeatability (i.e Gage RR) and
+Reproducibility studies, factorial and fractional factorial designs as
+well as response surface methods including the use of desirability
+functions.
diff --git a/math/algae/pkg-descr b/math/algae/pkg-descr
index 153feada2264..ddbd3871533e 100644
--- a/math/algae/pkg-descr
+++ b/math/algae/pkg-descr
@@ -1,19 +1,4 @@
-Algae is a specialized programming language meticulously designed for
-numerical analysis, particularly adept at tackling complex and large-scale
-computational problems. Developed by the Boeing Company, Algae was
-created to meet the demanding requirements of a fast, versatile, and
-robust tool for advanced engineering and scientific applications.
-
-Its core strengths lie in efficiently handling numerical computations
-involving large systems, making it suitable for:
-
-- Solving differential equations
-- Performing matrix operations
-- Implementing optimization algorithms
-- Simulating complex physical phenomena
-
-With a proven track record of over a decade in aerospace and related
-fields, Algae continues to be a valuable asset for researchers and
-engineers who require a powerful and reliable language for high-performance
-numerical analysis. Its design emphasizes both speed and the ability
-to manage extensive datasets and intricate models.
+Algae is a programming language for numerical analysis. It was written in
+the Boeing Company to fulfill their need for a fast and versatile tool,
+capable of handling large systems. Algae has been applied to interesting
+problems in aerospace and related fields for more than a decade.
diff --git a/math/apc/pkg-descr b/math/apc/pkg-descr
index f5785f99e19e..7d46f00f722e 100644
--- a/math/apc/pkg-descr
+++ b/math/apc/pkg-descr
@@ -1,20 +1,17 @@
-APC (Auto Payment Calculator) is a simple, Xforms-based graphical
-application designed for the X Window System. It provides a user-friendly
-interface for calculating auto loan payments.
+ the Auto Payment Calculator V1.0 Release
+ Copyright (C) 1997 Eric A. Griff
-Users can easily input the principal amount, loan term (in months),
-and interest rate. Upon calculation, it displays the monthly payment,
-as well as the number of weeks and the corresponding weekly payment.
+Auto Payment Calculator is a simple, xforms based, application for
+use under the X-windows system, that calculates auto loan payments.
-Key features include:
+It is pretty straight forward. You enter the Principal (Amount),
+Term (in months), and Rate, and then with either [RETURN]
+(or [enter] or whatever your keyboard equivelent is), (ALT-C), or
+clicking the calculate button; you will have the payment in months,
+as well as number of weeks, and weekly payment.
-- **Intuitive Interface**: Built with Xforms for a straightforward
- graphical user experience.
-- **Loan Calculation**: Quickly determines monthly and weekly payments
- based on user-provided loan details.
-- **Interactive Input**: Supports keyboard navigation (e.g., Tab, Enter)
- and mouse interaction for efficient data entry.
-
-APC is a practical utility for individuals needing to quickly estimate
-car loan payments, offering a clear and concise solution within the
-X Window environment.
+You may also [TAB] through the Amount, Term, and Rate, as well as
+hold down ALT and press the character in its Name that is underlined
+to go do that function. As long as all three are filled in, you may
+hit [ENTER] to Calculate right there. This makes it easy to cycle
+quickly through numerous terms, amounts, and rates.
diff --git a/math/aribas/pkg-descr b/math/aribas/pkg-descr
index 31ea2becfaf4..165f8177d398 100644
--- a/math/aribas/pkg-descr
+++ b/math/aribas/pkg-descr
@@ -1,22 +1,6 @@
-ARIBAS is an interactive interpreter designed for advanced arithmetic,
-offering robust support for both big integer and multi-precision
-floating-point calculations. Its Pascal/Modula-like syntax provides
-a familiar and structured environment for users to perform complex
-mathematical operations.
-
-This powerful tool comes equipped with a rich set of built-in functions
-specifically tailored for algorithmic number theory, including:
-
-- **Number Theoretic Functions**: Greatest Common Divisor (GCD),
- Jacobi symbol, and continued fraction expansions.
-- **Primality Testing**: Rabin probabilistic prime test for efficient
- identification of prime numbers.
-- **Integer Factorization Algorithms**:
- - Quadratic sieve factorization for general integers.
- - Pollard's rho factorization for finding smaller prime factors.
-
-ARIBAS is an invaluable resource for mathematicians, computer scientists,
-and cryptographers who require precise and efficient tools for number
-theoretic research, cryptographic analysis, and other applications
-involving large numbers and complex arithmetic. Its interactive nature
-makes it ideal for experimentation and exploration of numerical properties.
+ARIBAS is an interactive interpreter for big integer arithmetic and
+multi-precision floating point arithmetic with a Pascal/Modula like
+syntax. It has several builtin functions for algorithmic number
+theory like gcd, Jacobi symbol, Rabin probabilistic prime test,
+continued fraction and quadratic sieve factorization, Pollard rho
+factorization, etc.
diff --git a/math/arpack++/pkg-descr b/math/arpack++/pkg-descr
index 2e84fa9b3d96..be857c4234e9 100644
--- a/math/arpack++/pkg-descr
+++ b/math/arpack++/pkg-descr
@@ -1,18 +1,4 @@
-ARPACK++ provides an object-oriented C++ interface to ARPACK (ARnoldi
-PACKage), a widely used Fortran library for solving large-scale
-eigenvalue problems. This wrapper allows C++ developers to leverage
-ARPACK's power within a modern programming paradigm.
-
-ARPACK is known for efficiently computing a few eigenvalues and
-eigenvectors of large, sparse matrices, making it vital in quantum
-mechanics, structural engineering, and data analysis. ARPACK++ retains
-the original Fortran package's strengths:
-
-- **Full Capability**: Access to all ARPACK functionalities for
- various eigenvalue problems.
-- **High Performance**: Maintains computational speed and efficiency.
-- **Exceptional Accuracy**: Delivers precise numerical results.
-- **Low Memory Requirements**: Optimized for large matrices.
-
-By integrating ARPACK's robust numerical algorithms with C++ flexibility,
-ARPACK++ offers a powerful solution for complex eigenvalue computations.
+ARPACK++ is a collection of classes that offers c++ programmers an interface
+to ARPACK. It preserves the full capability, performance, accuracy and low
+memory requirements of the FORTRAN package, but takes advantage of the C++
+object-oriented programming environment.
diff --git a/math/atlas/pkg-descr b/math/atlas/pkg-descr
index c07eeac58026..6e7e6aed22a0 100644
--- a/math/atlas/pkg-descr
+++ b/math/atlas/pkg-descr
@@ -1,21 +1,18 @@
-ATLAS (Automatically Tuned Linear Algebra Software) is a high-performance
-software library for numerical linear algebra. It focuses on applying
-empirical optimization techniques to deliver portable and efficient
-performance across diverse hardware architectures.
+The ATLAS (Automatically Tuned Linear Algebra Software) project is an ongoing
+research effort focusing on applying empirical techniques in order to provide
+portable performance. At present, it provides C and Fortran77 interfaces to
+a portable, efficient BLAS implementation, as well as enhanced versions of a
+few routines from LAPACK. To link with ATLAS shared libraries:
-ATLAS provides optimized implementations of:
-
-- **BLAS (Basic Linear Algebra Subprograms)**: Offers C and Fortran77
- interfaces for Level 1, 2, and 3 BLAS routines, crucial for vector,
- matrix-vector, and matrix-matrix operations. Both serial (thread-safe)
- and multi-threaded versions are available.
-- **LAPACK (Linear Algebra Package)**: Includes enhanced versions of
- key LAPACK routines, providing efficient solutions for problems
- like solving systems of linear equations, eigenvalue problems, and
- singular value decomposition.
-
-The project's core strength lies in its ability to automatically tune
-itself to the specific characteristics of the underlying hardware during
-installation, ensuring optimal performance. ATLAS is an invaluable
-resource for scientific computing, engineering simulations, and any
-application requiring fast and reliable linear algebra computations.
+Serial (thread-safe) Fortran77 BLAS:
+ -lf77blas
+Multi-threaded Fortran77 BLAS:
+ -lptf77blas
+Serial (thread-safe) C BLAS:
+ -lcblas
+Multi-threaded C BLAS:
+ -lptcblas
+ATLAS-enhanced LAPACK, serial (thread-safe) interface:
+ -lalapack -lf77blas -lcblas
+ATLAS-enhanced LAPACK, multi-threaded interface:
+ -lalapack -lptf77blas -lptcblas
diff --git a/math/blacs/pkg-descr b/math/blacs/pkg-descr
index ee27799d8874..23b4f5cf0aa5 100644
--- a/math/blacs/pkg-descr
+++ b/math/blacs/pkg-descr
@@ -1,23 +1,5 @@
-The BLACS (Basic Linear Algebra Communication Subprograms) library is a
-fundamental component for high-performance parallel computing, specifically
-designed to facilitate linear algebra operations on distributed memory
-platforms. It provides a standardized and efficient message passing
-interface tailored for numerical linear algebra algorithms.
-
-BLACS enables the communication and synchronization of data between
-processors in a parallel computing environment, which is crucial for
-implementing scalable versions of dense linear algebra routines. This
-makes it an essential building block for:
-
-- **Distributed Linear Algebra Libraries**: Such as ScaLAPACK, which
- relies on BLACS for inter-processor communication.
-- **Scientific Simulations**: Large-scale computations in physics,
- engineering, and other fields that require solving complex linear
- systems or eigenvalue problems across multiple nodes.
-- **High-Performance Computing (HPC)**: Optimizing numerical workloads
- on clusters and supercomputers.
-
-By offering a uniform and efficient communication layer, BLACS allows
-developers to write portable and high-performing parallel linear algebra
-code, ensuring that numerical applications can effectively utilize the
-power of distributed memory architectures.
+The BLACS (Basic Linear Algebra Communication Subprograms)
+project is an ongoing investigation whose purpose is to create
+a linear algebra oriented message passing interface
+that may be implemented efficiently and uniformly across
+a large range of distributed memory platforms.
diff --git a/math/blocksolve95/pkg-descr b/math/blocksolve95/pkg-descr
index 6b4bed580e5d..522f5f3c5f41 100644
--- a/math/blocksolve95/pkg-descr
+++ b/math/blocksolve95/pkg-descr
@@ -1,15 +1,13 @@
-BlockSolve95 is a scalable parallel software library designed for the
-efficient solution of large, sparse linear systems. It is particularly
-optimized for problems arising from physical models, especially those
-with multiple degrees of freedom at each node (e.g., finite element
-methods in structural engineering).
+BlockSolve95 is a scalable parallel software library primarily intended for the
+solution of sparse linear systems that arise from physical models, especially
+problems involving multiple degrees of freedom at each node. For example, when
+the finite element method is used to solve practical problems in structural
+engineering, each node typically has two to five degrees of freedom;
+BlockSolve95 is designed to take advantage of problems with this type of local
+structure. BlockSolve95 is also reasonably efficient for problems that have
+only one degree of freedom associated with each node, such as the three-
+dimensional Poisson problem.
-The library effectively handles problems with this local structure,
-while also remaining reasonably efficient for systems with a single
-degree of freedom per node (e.g., three-dimensional Poisson problems).
-
-BlockSolve95 is a general-purpose solver, requiring only that matrices
-are sparse and symmetric in structure (though not necessarily in value).
-It provides a robust solution for complex scientific and engineering
-simulations that demand high-performance parallel computation for
-large sparse linear systems.
+BlockSolve95 is general purpose; we do not require that the matrices have any
+particular structure other than being sparse and being symmetric in structure
+(but not necessarily in value).
diff --git a/math/brial/pkg-descr b/math/brial/pkg-descr
index 4b7d2deb9b3a..bc7e9d80a98b 100644
--- a/math/brial/pkg-descr
+++ b/math/brial/pkg-descr
@@ -1,22 +1,11 @@
-BRiAl (Boolean Rings and Algebra) is a powerful C++ library for
-computations with polynomials over Boolean rings, serving as the
-successor to PolyBoRi. It provides high-level data types and efficient
-algorithms for symbolic computation in this specialized algebraic domain.
+BRiAl is the successor to PolyBoRi.
-Key features include:
-
-- **High-level Data Types**: For Boolean polynomials, monomials,
- exponent vectors, and related algebraic structures.
-- **Binary Decision Diagrams (BDDs)**: Utilizes BDDs as the internal
- storage type for polynomial structures, enabling efficient
- representation and manipulation.
-- **Python Interface**: Offers a convenient Python binding, allowing
- for parsing complex polynomial systems and implementing sophisticated
- strategies for Grobner basis computation.
-- **Grobner Basis Computation**: Provides a robust and powerful
- reference implementation for Grobner basis algorithms, essential
- for solving systems of polynomial equations.
-
-BRiAl is an invaluable tool for researchers and developers in areas
-such as cryptography, coding theory, formal verification, and computer
-algebra, where efficient manipulation of Boolean polynomials is critical.
+The core of PolyBoRi is a C++ library, which provides high-level data
+types for Boolean polynomials and monomials, exponent vectors, as well
+as for the underlying polynomial rings and subsets of the powerset of
+the Boolean variables. As a unique approach, binary decision diagrams
+are used as internal storage type for polynomial structures. On top of
+this C++-library we provide a Python interface. This allows parsing of
+complex polynomial systems, as well as sophisticated and extendable
+strategies for Groebner base computation. PolyBoRi features a powerful
+reference implementation for Groebner basis computation.
diff --git a/math/clblas/pkg-descr b/math/clblas/pkg-descr
index 6b9073ad0249..a63d390014d0 100644
--- a/math/clblas/pkg-descr
+++ b/math/clblas/pkg-descr
@@ -1,21 +1,11 @@
-clBLAS is a high-performance software library that provides optimized
-BLAS (Basic Linear Algebra Subprograms) functions implemented in OpenCL.
-BLAS routines are fundamental building blocks for numerical linear algebra,
-widely used in scientific computing, engineering, and data analysis.
+clBLAS
-The primary goal of clBLAS is to empower developers to leverage the
-performance and power efficiency of heterogeneous computing environments.
-It achieves this by:
+a software library containing BLAS functions written in OpenCL
-- **OpenCL Integration**: Directly utilizes OpenCL interfaces, allowing
- users full control over OpenCL state management for maximum
- performance and flexibility.
-- **Optimized Kernel Generation**: Automatically generates and enqueues
- optimized OpenCL kernels, freeing users from the complex task of
- writing, optimizing, and maintaining kernel code.
-
-clBLAS is an invaluable resource for developers and researchers who need
-to accelerate their linear algebra workloads by harnessing the parallel
-processing capabilities of GPUs and other OpenCL-compatible devices.
-It streamlines the development of high-performance computing applications
-by providing a robust and efficient foundation for numerical operations.
+The primary goal of clBLAS is to make it easier for developers to utilize the
+inherent performance and power efficiency benefits of heterogeneous computing.
+clBLAS interfaces do not hide nor wrap OpenCL interfaces, but rather leaves
+OpenCL state management to the control of the user to allow for maximum
+performance and flexibility. The clBLAS library does generate and enqueue
+optimized OpenCL kernels, relieving the user from the task of writing,
+optimizing and maintaining kernel code themselves.
diff --git a/math/clblast/pkg-descr b/math/clblast/pkg-descr
index c3c31015723b..cf3cfb06b914 100644
--- a/math/clblast/pkg-descr
+++ b/math/clblast/pkg-descr
@@ -1,22 +1,2 @@
-CLBlast is a cutting-edge, lightweight, and highly performant OpenCL
-BLAS (Basic Linear Algebra Subprograms) library. It provides efficient
-and accelerated linear algebra computations on OpenCL-compatible devices.
-
-BLAS routines are fundamental building blocks for numerical algorithms
-in scientific computing, machine learning, and data analysis. CLBlast
-leverages OpenCL to offload these tasks to GPUs and other accelerators,
-significantly speeding up applications.
-
-Key features and benefits:
-
-- **Modern Design**: Built with contemporary OpenCL practices for
- optimal performance.
-- **Lightweight Footprint**: Minimizes overhead for diverse systems.
-- **High Performance**: Achieves superior execution speeds through
- careful optimization.
-- **Tunable**: Allows fine-grained control to extract maximum
- performance from specific hardware (Intel, AMD, NVIDIA accelerators).
-
-CLBlast is an invaluable resource for developers and researchers seeking
-to accelerate numerical workloads by harnessing parallel processing
-capabilities of modern hardware through OpenCL.
+Modern, lightweight, performant and tunable OpenCL BLAS library. Tuned for
+Intel, AMD, and NVIDIA accelerators.
diff --git a/math/clfft/pkg-descr b/math/clfft/pkg-descr
index 4c745e85430d..321354154a5f 100644
--- a/math/clfft/pkg-descr
+++ b/math/clfft/pkg-descr
@@ -1,24 +1,7 @@
-clFFT is a high-performance software library providing optimized Fast
-Fourier Transform (FFT) functions implemented in OpenCL. The FFT is a
-fundamental algorithm in digital signal processing and numerical analysis,
-used for tasks such as spectral analysis, image processing, and solving
-partial differential equations.
+clFFT
-Leveraging the OpenCL framework, clFFT enables efficient computation
-of FFTs on a wide range of parallel processing devices. Its key features
-include:
+a software library containing FFT functions written in OpenCL
-- **GPU Acceleration**: Primarily designed to harness the power of
- Graphics Processing Units (GPUs) for significant speedups in FFT
- computations.
-- **CPU Support**: Also supports execution on Central Processing Units
- (CPUs), which is beneficial for debugging, development, and
- heterogeneous computing environments where a mix of device types
- is utilized.
-- **OpenCL Standard**: Adheres to the OpenCL standard, ensuring
- portability across different hardware vendors and platforms.
-
-clFFT is an invaluable resource for developers and researchers who need
-to perform fast and efficient Fourier transforms on large datasets,
-particularly in applications that can benefit from the parallel
-processing capabilities of modern GPUs and multi-core CPUs.
+clFFT is a software library containing FFT functions written in OpenCL. In
+addition to GPU devices, the libraries also support running on CPU devices to
+facilitate debugging and heterogeneous programming.
diff --git a/math/cliquer/pkg-descr b/math/cliquer/pkg-descr
index e23a63616285..421b623dcc63 100644
--- a/math/cliquer/pkg-descr
+++ b/math/cliquer/pkg-descr
@@ -1,23 +1,9 @@
-Cliquer is a highly efficient C library designed for finding cliques
-in arbitrary weighted graphs. In graph theory, a clique is a subset
-of vertices where every pair of vertices is connected by an edge.
-Finding cliques is a fundamental problem with applications in social
-network analysis, bioinformatics, and computer vision.
+Cliquer is a set of C routines for finding cliques in an arbitrary weighted
+graph. It uses an exact branch-and-bound algorithm developed by Patric
+Ostergard. It is designed with the aim of being efficient while still being
+flexible and easy to use.
-This library implements an exact branch-and-bound algorithm developed
-by Patric Ostergard, ensuring optimal solutions. Cliquer is meticulously
-designed to be:
+Note: this port do not use the upstream version, but the version autotoolized
+by Dima Pasechnik.
-- **Efficient**: Optimized for performance, even on complex graphs.
-- **Flexible**: Adaptable to various graph structures and problem
- specifications.
-- **Easy to Use**: Provides a straightforward API for integration
- into other applications.
-
-Note that this port utilizes a version of Cliquer that has been
-autotoolized by Dima Pasechnik, enhancing its build system and
-portability. This ensures a robust and well-maintained package.
-
-Cliquer is an invaluable resource for researchers and developers working
-with graph algorithms, offering a powerful and reliable tool for
-identifying dense subgraphs and solving related combinatorial problems.
+See also: https://github.com/dimpase/autocliquer
diff --git a/math/clrng/pkg-descr b/math/clrng/pkg-descr
index 4d94cc188962..93c0bf766561 100644
--- a/math/clrng/pkg-descr
+++ b/math/clrng/pkg-descr
@@ -1,24 +1,11 @@
-clRNG is a specialized library designed for high-quality uniform random
-number generation within OpenCL environments. It provides a robust and
-efficient solution for parallel applications requiring statistically
-sound random numbers on GPUs and other OpenCL-compatible devices.
+clRNG
-The library introduces the concept of "streams of random numbers," which
-act as virtual random number generators. These streams can be created
-in unlimited quantities on the host system and then utilized by work
-items on computing devices to generate random numbers. Each stream also
-features equally-spaced substreams, offering additional flexibility for
-complex simulations.
+a library for uniform random number generation in OpenCL.
-clRNG currently implements a selection of well-regarded pseudorandom
-number generators, including:
-
-- MRG31k3p
-- MRG32k3a
-- LFSR113
-- Philox-4x32-10
-
-This library is an invaluable resource for researchers and developers
-in fields such as Monte Carlo simulations, scientific computing, and
-machine learning, where efficient and reliable parallel random number
-generation is crucial.
+Streams of random numbers act as virtual random number generators.
+They can be created on the host computer in unlimited numbers, and
+then used either on the host or on computing devices by work items
+to generate random numbers. Each stream also has equally-spaced
+substreams, which are occasionally useful. The API is currently
+implemented for four different RNGs, namely the MRG31k3p, MRG32k3a,
+LFSR113 and Philox-4x32-10 generators.
diff --git a/math/cocoalib/pkg-descr b/math/cocoalib/pkg-descr
index 7d3c9bd0133c..6b610cd891f4 100644
--- a/math/cocoalib/pkg-descr
+++ b/math/cocoalib/pkg-descr
@@ -1,20 +1,6 @@
-CoCoALib is a powerful C++ library dedicated to Computations in
-Commutative Algebra. This field of mathematics is fundamental to
-algebraic geometry, number theory, and computer algebra systems,
-focusing on algebraic structures like rings and ideals.
+CoCoALib is a C++ library for Computations in Commutative Algebra,
+focused mainly on polynomial rings, ideals, Groebner basis and
+similar topics.
-The library provides a robust set of tools for working with:
-
-- **Polynomial Rings**: Operations on multivariate polynomials.
-- **Ideals**: Computations with ideals in polynomial rings.
-- **Grobner Bases**: A cornerstone algorithm for solving systems of
- polynomial equations and performing other algebraic manipulations.
-- **Related Topics**: Other advanced concepts in commutative algebra.
-
-For users who prefer an interactive environment without direct C++
-programming, the companion CoCoA-5 shell (available separately) offers
-a user-friendly interface to most of CoCoALib's functionalities.
-
-CoCoALib is an invaluable resource for mathematicians, computer scientists,
-and researchers engaged in algebraic computations, providing a high-performance
-and flexible framework for exploring complex algebraic structures.
+You might like to install CoCoA-5 too, a shell that lets you interact
+with most of CoCoALib without the need to learn C++.
diff --git a/math/concorde/pkg-descr b/math/concorde/pkg-descr
index 84039a11969c..2fe47df09e48 100644
--- a/math/concorde/pkg-descr
+++ b/math/concorde/pkg-descr
@@ -1,22 +1,14 @@
-Concorde is a highly optimized computer code designed for solving the
-Traveling Salesman Problem (TSP) and various related network optimization
-problems. Implemented in ANSI C, it is renowned for its ability to find
-optimal solutions to extremely large and complex instances of the TSP.
+Concorde is a computer code for the traveling salesman problem (TSP)
+and some related network optimization problems. The code is written
+in the ANSI C programming language and it is available for academic
+research use; for other uses, contact bico@isye.gatech.edu for
+licensing options.
-Key features and capabilities include:
+Concorde's TSP solver has been used to obtain the optimal solutions to
+106 of the 110 TSPLIB instances; the largest having 15,112 cities.
-- **Optimal TSP Solutions**: Concorde's TSP solver has successfully
- found optimal solutions for 106 of the 110 TSPLIB instances,
- including problems with up to 15,112 cities.
-- **Extensive Callable Library**: Provides over 700 functions, allowing
- users to develop specialized codes for TSP-like problems and integrate
- Concorde's powerful algorithms into their own applications.
-- **Parallel Computing Support**: All functions are thread-safe for
- shared-memory parallel environments. The main TSP solver also
- supports execution across networks of Unix workstations, enabling
- distributed computation for even larger problems.
-
-Concorde is an invaluable resource for researchers and practitioners
-in combinatorial optimization, operations research, and computer science,
-offering a robust and efficient solution for one of the most famous
-problems in theoretical computer science.
+The Concorde callable library includes over 700 functions permitting
+users to create specialized codes for TSP-like problems. All Concorde
+functions are thread-safe for programming in shared-memory parallel
+environments; the main TSP solver includes code for running over
+networks of Unix workstations.
diff --git a/math/crlibm/pkg-descr b/math/crlibm/pkg-descr
index 04d020e0cfb8..7a3c0fe62f25 100644
--- a/math/crlibm/pkg-descr
+++ b/math/crlibm/pkg-descr
@@ -1,24 +1,21 @@
-CRlibm is an efficient and rigorously proven mathematical library
-providing correctly rounded implementations of double-precision C99
-standard elementary functions. It supports all four IEEE-754 rounding
-modes, offering high accuracy and reliability for numerical computations.
+CRlibm is an efficient and proven mathematical library, which
+provides implementations of the double-precision C99 standard
+elementary functions, correctly rounded in the four IEEE-754 rounding
+modes, and sufficiently efficient in average time, worst-case time,
+and memory consumption to replace existing libms transparently.
-Designed for transparent replacement of existing `libm` implementations,
-CRlibm maintains efficiency in average and worst-case time, along with
-optimized memory consumption. Its development includes extensive
-documentation with formal proofs for each function, making it an
-excellent resource for understanding software elementary function
+The distribution includes extensive documentation with the proof
+of each function (currently more than 100 pages), as well as all
+the Maple scripts used to develop the functions. This makes this
+library an excellent tutorial on software elementary function
development.
-CRlibm also integrates scslib (Software Carry Save Library), a lightweight
-multiple-precision library. scslib is tailored for CRlibm's needs,
-offering precision up to a few hundred bits, portability, IEEE
-floating-point compatibility, and performance comparable to or better
-than GMP, all within a small footprint. It efficiently handles
-multiple-precision additions, subtractions, multiplications, and conversions
-by avoiding carry propagations during multiplication.
-
-CRlibm is an invaluable tool for applications demanding high-precision,
-correctly rounded mathematical functions, particularly in scientific
-computing, financial modeling, and other fields where numerical accuracy
-is paramount.
+CRlibm also includes a lightweight library for multiple precision,
+scslib (Software Carry Save Library). This library has been developed
+specifically to answer the needs of the CRlibm project: precision
+up to a few hundred bits, portability, compatibility with IEEE
+floating-point standards, performance comparable to or better than
+GMP, and a small footprint. It uses a data-structure which allows
+carry propagations to be avoided during multiple-precision
+multiplications, and supports addition, subtraction, multiplication,
+and conversions.
diff --git a/math/dieharder/pkg-descr b/math/dieharder/pkg-descr
index 4efd18b2e129..327aac1c5bda 100644
--- a/math/dieharder/pkg-descr
+++ b/math/dieharder/pkg-descr
@@ -1,21 +1,22 @@
-Dieharder is a comprehensive, GPL-licensed test suite for evaluating
-the quality of random number generators (RNGs). It builds upon the
-legacy of George Marsaglia's "Diehard battery of tests" and expands
-upon it with modern statistical methodologies.
+At the suggestion of Linas Vepstas on the Gnu Scientific Library (GSL) list,
+this GPL'd suite of random number tests will be named "Dieharder". Using a
+movie sequel pun for the name is a double tribute to George Marsaglia, whose
+"Diehard battery of tests" of random number generators has enjoyed years of
+enduring usefulness as a test suite.
-This suite incorporates a diverse collection of tests, including:
+The dieharder suite is more than just the diehard tests cleaned up and given a
+pretty GPL'd source face in native C: tests from the Statistical Test Suite
+(STS) developed by the National Institute for Standards and Technology (NIST)
+are being incorporated, as are new tests developed by rgb. Where possible,
+tests are parametrized and controllable so that failure, at least, is
+unambiguous.
-- **Diehard Tests**: Classic tests for assessing RNG randomness.
-- **NIST Statistical Test Suite (STS)**: Tests developed by the
- National Institute for Standards and Technology.
-- **New Tests**: Additional tests developed by the project's author.
+A further design goal is to provide some indication of *why* a generator fails
+a test, where such information can be extracted during the test process and
+placed in usable form. For example, the bit-distribution tests should
+(eventually) be able to display the actual histogram for the different bit
+n-tuplets.
-Dieharder is designed with extensibility in mind, allowing for the
-incorporation of new tests and analysis methods. A key design goal is
-to provide not just pass/fail results, but also insights into *why* an
-RNG might fail a particular test, offering diagnostic information
-(e.g., displaying histograms for bit distributions).
-
-This makes Dieharder an invaluable tool for researchers, cryptographers,
-and developers who require rigorous validation of RNGs for applications
-in simulations, security, and statistical analysis.
+Dieharder is by design extensible. It is intended to be the "Swiss army knife
+of random number test suites", or if you prefer, "the last suite you'll ever
+ware" for testing random numbers.
diff --git a/math/edenmath/pkg-descr b/math/edenmath/pkg-descr
index 2a4a94c42681..addee44d96db 100644
--- a/math/edenmath/pkg-descr
+++ b/math/edenmath/pkg-descr
@@ -1,20 +1,4 @@
-EdenMath is a user-friendly scientific calculator designed to perform
-a wide array of mathematical computations. It offers a comprehensive
-set of functionalities, making it a versatile tool for students,
-educators, and professionals alike.
+EdenMath is a scientific calculator. It does standard arithmetic,
+probability, and trigonometric functions.
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