Date: Tue, 30 Sep 2025 04:04:35 GMT From: Yuri Victorovich <yuri@FreeBSD.org> To: ports-committers@FreeBSD.org, dev-commits-ports-all@FreeBSD.org, dev-commits-ports-main@FreeBSD.org Subject: git: 5f90970e571a - main - math/*: Improve and expand pkg-descr Message-ID: <202509300404.58U44Zfj051505@gitrepo.freebsd.org>
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The branch main has been updated by yuri: URL: https://cgit.FreeBSD.org/ports/commit/?id=5f90970e571a0fbd9caee91a04409f5c8ab1f9fe commit 5f90970e571a0fbd9caee91a04409f5c8ab1f9fe Author: Yuri Victorovich <yuri@FreeBSD.org> AuthorDate: 2025-09-30 03:57:50 +0000 Commit: Yuri Victorovich <yuri@FreeBSD.org> CommitDate: 2025-09-30 04:04:32 +0000 math/*: Improve and expand pkg-descr All ports maintained by ports@FreeBSD.org Content generated by Gemini AI. --- 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, 1738 insertions(+), 658 deletions(-) diff --git a/math/R-cran-combinat/pkg-descr b/math/R-cran-combinat/pkg-descr index e27b37a777d3..322223dcabdd 100644 --- a/math/R-cran-combinat/pkg-descr +++ b/math/R-cran-combinat/pkg-descr @@ -1 +1,17 @@ -Routines for combinatorics. +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. diff --git a/math/R-cran-conf.design/pkg-descr b/math/R-cran-conf.design/pkg-descr index 73da04d8c40a..de393137be7b 100644 --- a/math/R-cran-conf.design/pkg-descr +++ b/math/R-cran-conf.design/pkg-descr @@ -1,2 +1,24 @@ -This small library contains a series of simple tools for constructing and -manipulating confounded and fractional factorial designs. +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. diff --git a/math/R-cran-cvar/pkg-descr b/math/R-cran-cvar/pkg-descr index ca1bec8d7a68..efad457a0534 100644 --- a/math/R-cran-cvar/pkg-descr +++ b/math/R-cran-cvar/pkg-descr @@ -1,7 +1,23 @@ -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. +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. diff --git a/math/R-cran-fracdiff/pkg-descr b/math/R-cran-fracdiff/pkg-descr index 2058c9e95b8e..229027fb8b72 100644 --- a/math/R-cran-fracdiff/pkg-descr +++ b/math/R-cran-fracdiff/pkg-descr @@ -1,3 +1,20 @@ -Maximum likelihood estimation of the parameters of a fractionally -differenced ARIMA(p,d,q) model (Haslett and Raftery, Appl.Statistics, -1989). +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. diff --git a/math/R-cran-gbutils/pkg-descr b/math/R-cran-gbutils/pkg-descr index 8182290d8372..6d016a6ddf25 100644 --- a/math/R-cran-gbutils/pkg-descr +++ b/math/R-cran-gbutils/pkg-descr @@ -1,8 +1,17 @@ -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. +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. diff --git a/math/R-cran-magic/pkg-descr b/math/R-cran-magic/pkg-descr index 500c3c8314bf..973187f4cb25 100644 --- a/math/R-cran-magic/pkg-descr +++ b/math/R-cran-magic/pkg-descr @@ -1,11 +1,19 @@ -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". +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. diff --git a/math/R-cran-nortest/pkg-descr b/math/R-cran-nortest/pkg-descr index c6ea3f75138a..9931aa8c41fa 100644 --- a/math/R-cran-nortest/pkg-descr +++ b/math/R-cran-nortest/pkg-descr @@ -1 +1,17 @@ -Five omnibus tests for testing the composite hypothesis of normality. +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. diff --git a/math/R-cran-quadprog/pkg-descr b/math/R-cran-quadprog/pkg-descr index 95c41d16dc00..c4a3622d3ad8 100644 --- a/math/R-cran-quadprog/pkg-descr +++ b/math/R-cran-quadprog/pkg-descr @@ -1,3 +1,18 @@ -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. +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. diff --git a/math/R-cran-qualityTools/pkg-descr b/math/R-cran-qualityTools/pkg-descr index a5da45e35c2e..22f262d64ea9 100644 --- a/math/R-cran-qualityTools/pkg-descr +++ b/math/R-cran-qualityTools/pkg-descr @@ -1,10 +1,21 @@ -qualityTools: Statistical Methods for Quality Science +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. -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. +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. diff --git a/math/algae/pkg-descr b/math/algae/pkg-descr index ddbd3871533e..153feada2264 100644 --- a/math/algae/pkg-descr +++ b/math/algae/pkg-descr @@ -1,4 +1,19 @@ -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. +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. diff --git a/math/apc/pkg-descr b/math/apc/pkg-descr index 7d46f00f722e..f5785f99e19e 100644 --- a/math/apc/pkg-descr +++ b/math/apc/pkg-descr @@ -1,17 +1,20 @@ - the Auto Payment Calculator V1.0 Release - Copyright (C) 1997 Eric A. Griff +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. -Auto Payment Calculator is a simple, xforms based, application for -use under the X-windows system, that calculates auto loan payments. +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. -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. +Key features include: -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. +- **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. diff --git a/math/aribas/pkg-descr b/math/aribas/pkg-descr index 165f8177d398..31ea2becfaf4 100644 --- a/math/aribas/pkg-descr +++ b/math/aribas/pkg-descr @@ -1,6 +1,22 @@ -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. +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. diff --git a/math/arpack++/pkg-descr b/math/arpack++/pkg-descr index be857c4234e9..2e84fa9b3d96 100644 --- a/math/arpack++/pkg-descr +++ b/math/arpack++/pkg-descr @@ -1,4 +1,18 @@ -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. +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. diff --git a/math/atlas/pkg-descr b/math/atlas/pkg-descr index 6e7e6aed22a0..c07eeac58026 100644 --- a/math/atlas/pkg-descr +++ b/math/atlas/pkg-descr @@ -1,18 +1,21 @@ -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 (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. -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 +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. diff --git a/math/blacs/pkg-descr b/math/blacs/pkg-descr index 23b4f5cf0aa5..ee27799d8874 100644 --- a/math/blacs/pkg-descr +++ b/math/blacs/pkg-descr @@ -1,5 +1,23 @@ -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. +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. diff --git a/math/blocksolve95/pkg-descr b/math/blocksolve95/pkg-descr index 522f5f3c5f41..6b4bed580e5d 100644 --- a/math/blocksolve95/pkg-descr +++ b/math/blocksolve95/pkg-descr @@ -1,13 +1,15 @@ -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. +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 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). +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. diff --git a/math/brial/pkg-descr b/math/brial/pkg-descr index bc7e9d80a98b..4b7d2deb9b3a 100644 --- a/math/brial/pkg-descr +++ b/math/brial/pkg-descr @@ -1,11 +1,22 @@ -BRiAl is the successor to PolyBoRi. +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. -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. +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. diff --git a/math/clblas/pkg-descr b/math/clblas/pkg-descr index a63d390014d0..6b9073ad0249 100644 --- a/math/clblas/pkg-descr +++ b/math/clblas/pkg-descr @@ -1,11 +1,21 @@ -clBLAS +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. -a software library containing BLAS functions written in OpenCL +The primary goal of clBLAS is to empower developers to leverage the +performance and power efficiency of heterogeneous computing environments. +It achieves this by: -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. +- **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. diff --git a/math/clblast/pkg-descr b/math/clblast/pkg-descr index cf3cfb06b914..c3c31015723b 100644 --- a/math/clblast/pkg-descr +++ b/math/clblast/pkg-descr @@ -1,2 +1,22 @@ -Modern, lightweight, performant and tunable OpenCL BLAS library. Tuned for -Intel, AMD, and NVIDIA accelerators. +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. diff --git a/math/clfft/pkg-descr b/math/clfft/pkg-descr index 321354154a5f..4c745e85430d 100644 --- a/math/clfft/pkg-descr +++ b/math/clfft/pkg-descr @@ -1,7 +1,24 @@ -clFFT +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. -a software library containing FFT functions written in OpenCL +Leveraging the OpenCL framework, clFFT enables efficient computation +of FFTs on a wide range of parallel processing devices. Its key features +include: -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. +- **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. diff --git a/math/cliquer/pkg-descr b/math/cliquer/pkg-descr index 421b623dcc63..e23a63616285 100644 --- a/math/cliquer/pkg-descr +++ b/math/cliquer/pkg-descr @@ -1,9 +1,23 @@ -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. +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. -Note: this port do not use the upstream version, but the version autotoolized -by Dima Pasechnik. +This library implements an exact branch-and-bound algorithm developed +by Patric Ostergard, ensuring optimal solutions. Cliquer is meticulously +designed to be: -See also: https://github.com/dimpase/autocliquer +- **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. diff --git a/math/clrng/pkg-descr b/math/clrng/pkg-descr index 93c0bf766561..4d94cc188962 100644 --- a/math/clrng/pkg-descr +++ b/math/clrng/pkg-descr @@ -1,11 +1,24 @@ -clRNG +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. -a library for uniform random number generation in OpenCL. +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. -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. +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. diff --git a/math/cocoalib/pkg-descr b/math/cocoalib/pkg-descr index 6b610cd891f4..7d3c9bd0133c 100644 --- a/math/cocoalib/pkg-descr +++ b/math/cocoalib/pkg-descr @@ -1,6 +1,20 @@ -CoCoALib is a C++ library for Computations in Commutative Algebra, -focused mainly on polynomial rings, ideals, Groebner basis and -similar topics. +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. -You might like to install CoCoA-5 too, a shell that lets you interact -with most of CoCoALib without the need to learn C++. +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. diff --git a/math/concorde/pkg-descr b/math/concorde/pkg-descr index 2fe47df09e48..84039a11969c 100644 --- a/math/concorde/pkg-descr +++ b/math/concorde/pkg-descr @@ -1,14 +1,22 @@ -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. +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's TSP solver has been used to obtain the optimal solutions to -106 of the 110 TSPLIB instances; the largest having 15,112 cities. +Key features and capabilities include: -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. +- **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. diff --git a/math/crlibm/pkg-descr b/math/crlibm/pkg-descr index 7a3c0fe62f25..04d020e0cfb8 100644 --- a/math/crlibm/pkg-descr +++ b/math/crlibm/pkg-descr @@ -1,21 +1,24 @@ -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. +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. -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 +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 development. -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. +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. diff --git a/math/dieharder/pkg-descr b/math/dieharder/pkg-descr index 327aac1c5bda..4efd18b2e129 100644 --- a/math/dieharder/pkg-descr +++ b/math/dieharder/pkg-descr @@ -1,22 +1,21 @@ -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. +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. -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. +This suite incorporates a diverse collection of tests, including: -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. +- **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. -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. +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. diff --git a/math/edenmath/pkg-descr b/math/edenmath/pkg-descr index addee44d96db..2a4a94c42681 100644 --- a/math/edenmath/pkg-descr +++ b/math/edenmath/pkg-descr @@ -1,4 +1,20 @@ -EdenMath is a scientific calculator. It does standard arithmetic, -probability, and trigonometric functions. +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, *** 2025 LINES SKIPPED ***home | help
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