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#vector sparse

11 packages tagged with “vector sparse”

CenterSpace.NMath.Standard.Windows.X64

Foundational classes for financial, engineering, and scientific applications, including complex number classes, general vector and matrix classes, structured sparse matrix classes and factorizations, general sparse matrix classes and factorizations, general matrix decompositions, least squares solutions, random number generators, Fast Fourier Transforms (FFTs), numerical integration and differentiation methods, function minimization, curve fitting, root-finding, linear and nonlinear programming. This package also provides functions for statistical computation and biostatistics, including descriptive statistics, probability distributions, combinatorial functions, multiple linear regression, hypothesis testing, analysis of variance, multivariate statistics, partial least squares, and nonnegative matrix factorization. Built on .NET Standard 2.0. Requires a minimum of .NET Standard 2.0, .NET 5, .NET Core 2.0 or .NET Framework 4.6.1. Requires Visual Studio 2015-2019 C++ x64 runtime. Requires x64 hardware.

v7.4.2.16↙ 954.0K
mathstatisticsnumericsprobabilitylinear

CenterSpace.NMath.Standard.Linux.X64

Foundational classes for financial, engineering, and scientific applications, including complex number classes, general vector and matrix classes, structured sparse matrix classes and factorizations, general sparse matrix classes and factorizations, general matrix decompositions, least squares solutions, random number generators, Fast Fourier Transforms (FFTs), numerical integration and differentiation methods, function minimization, curve fitting, root-finding, linear and nonlinear programming. This package also provides functions for statistical computation and biostatistics, including descriptive statistics, probability distributions, combinatorial functions, multiple linear regression, hypothesis testing, analysis of variance, multivariate statistics, partial least squares, and nonnegative matrix factorization. Built on .NET Standard 2.0. Requires a minimum of .NET Standard 2.0, .NET 5, .NET Core 2.0 or .NET Framework 4.6.1. Requires libgcc linux. Requires x64 hardware.

v7.4.2.16↙ 333.6K
mathstatisticsnumericsprobabilitylinear

CenterSpace.NMath

Foundational classes for financial, engineering, and scientific applications, including complex number classes, general vector and matrix classes, structured sparse matrix classes and factorizations, general sparse matrix classes and factorizations, general matrix decompositions, least squares solutions, random number generators, Fast Fourier Transforms (FFTs), numerical integration and differentiation methods, function minimization, curve fitting, root-finding, linear and nonlinear programming. If you're using at least .NET Framework 4.6.1 or .NET Core 2.0, we recommend using one of our NMath .NET Standard NuGet packages.

v6.2.0.58↙ 172.2K
mathstatisticsnumericslinearalgebra
pkg

Universal.Common.Mathematics

Class library implementing advanced mathematical algorithms, transforms, and time series manipulations. Implementations favour simplicity and correctness.

v4.2.0↙ 116.0K
MathematicsMatrixVectorIntervalAlgorithm

Dew.Math

Dew.Math is the Windows-optimized high-performance numerical computation library for .NET. It provides a vectorized matrix and vector math environment with native runtime acceleration, multithreaded execution, and extensive algorithm libraries for scientific, engineering, financial, AI/ML and signal processing workloads. Core Numerical Capabilities: - Dense linear algebra (BLAS, LAPACK): SVD, QR, LQ, LU, eigenvalue problems, least-squares, rank reveals - Sparse matrix support: direct solvers (Pardiso, UMFPACK), iterative solvers (CG, BiCG, GMRES), preconditioning strategies, structured sparse formats - Complex number computation with fully vectorized math operations - Polynomial arithmetic, interpolation, splines, rational approximations, Chebyshev basis transforms - Numerical differentiation, root solving, non-linear systems, ODE support for stiff and non-stiff cases - Probability distributions (over 30 families), random number generators, Monte Carlo methods - Special mathematical functions (Airy, Bessel, Gamma-related, elliptic integrals, Legendre, etc.) Optimization and Modeling: - Non-linear curve fitting with Levenberg-Marquardt and trust-region refinements - Direct and constrained optimization (Simplex/Nelder–Mead, BFGS, Conjugate Gradient, LP, dual-phase simplex, Gomory cutting plane) - Vectorized expression parser for dynamic formula construction and symbolic-style evaluation Performance Architecture: - Native accelerated BLAS/LAPACK kernels with automatic CPU dispatch (AVX, AVX2, AVX-512) - Scalable multithreading with a lock-free memory allocator for low-GC overhead - Optional OpenCL GPU offloading for supported device targets Platform Model: - Contains Windows native acceleration binaries - For Linux native acceleration use: Dew.Math.Linux - For a pure managed, portable edition use: Dew.Math.Core Use Dew.Math when you require **maximum numerical performance on Windows** for HPC, simulation, economic modeling, data analytics, or scientific visualization workflows.

v6.3.10↙ 54.8K
dotnetcsharpwindowslinuxmacos

CenterSpace.NMath.Standard.Windows.X86.X64

Foundational classes for financial, engineering, and scientific applications, including complex number classes, general vector and matrix classes, structured sparse matrix classes and factorizations, general sparse matrix classes and factorizations, general matrix decompositions, least squares solutions, random number generators, Fast Fourier Transforms (FFTs), numerical integration and differentiation methods, function minimization, curve fitting, root-finding, linear and nonlinear programming. This package also provides functions for statistical computation and biostatistics, including descriptive statistics, probability distributions, combinatorial functions, multiple linear regression, hypothesis testing, analysis of variance, multivariate statistics, partial least squares, and nonnegative matrix factorization. Built on .NET Standard 2.0. Requires a minimum of .NET Standard 2.0, .NET 5 or .NET Core 2.0. Does not support .NET Framework. Requires Visual Studio 2017 C++ x86 and x64 runtimes. Requires x64 hardware.

v7.1.0.47↙ 178.4K
mathstatisticsnumericsprobabilitylinear

CenterSpace.NMath.Standard.WindowsAndLinux.X64

Foundational classes for financial, engineering, and scientific applications, including complex number classes, general vector and matrix classes, structured sparse matrix classes and factorizations, general sparse matrix classes and factorizations, general matrix decompositions, least squares solutions, random number generators, Fast Fourier Transforms (FFTs), numerical integration and differentiation methods, function minimization, curve fitting, root-finding, linear and nonlinear programming. This package also provides functions for statistical computation and biostatistics, including descriptive statistics, probability distributions, combinatorial functions, multiple linear regression, hypothesis testing, analysis of variance, multivariate statistics, partial least squares, and nonnegative matrix factorization. Built on .NET Standard 2.0. Requires a minimum of .NET Standard 2.0, .NET 5, .NET Core 2.0 or .NET Framework 4.6.1. Requires x64 hardware. On Windows, requires Visual Studio 2017 C++ x64 runtime. On Linux, requires libgcc.

v7.1.0.47↙ 142.8K
mathstatisticsnumericsprobabilitylinear

CenterSpace.NMath.Standard.OSX.X64

Foundational classes for financial, engineering, and scientific applications, including complex number classes, general vector and matrix classes, structured sparse matrix classes and factorizations, general sparse matrix classes and factorizations, general matrix decompositions, least squares solutions, random number generators, Fast Fourier Transforms (FFTs), numerical integration and differentiation methods, function minimization, curve fitting, root-finding, linear and nonlinear programming. This package also provides functions for statistical computation and biostatistics, including descriptive statistics, probability distributions, combinatorial functions, multiple linear regression, hypothesis testing, analysis of variance, multivariate statistics, partial least squares, and nonnegative matrix factorization. Built on .NET Standard 2.0. Requires a minimum of .NET Standard 2.0, .NET 5, .NET Core 2.0 or .NET Framework 4.6.1. Requires x64 hardware.

v7.2.0.35↙ 105.9K
mathstatisticsnumericsprobabilitylinear

Dew.Math.Core

Dew.Math.Core is the portable, pure managed edition of the Dew.Math library. It provides the same high-level matrix and vector programming model, expression parser, probability and optimization toolkit, and special function support without linking to any native runtime components. This enables maximum compatibility across platforms and runtime environments. Core Numerical Capabilities (Managed): - Dense matrix and vector operations with operator overloading and method-based APIs - QR, LU, SVD and eigenvalue routines using high-quality managed linear algebra kernels - Complex number and real-valued computation with full vectorization in managed code - Sparse matrix representations with iterative solver support - Probability distributions, histogramming, random generators, Monte Carlo workflows - Nonlinear optimization, curve fitting, regression models, trust-region and gradient methods - Vectorized expression parsing for symbolic-style expression and simulation pipelines - Polynomial and spline interpolation, numerical integration and differentiation - Special function suite including Bessel, Airy, Gamma-related, Legendre and elliptic functions Portability Model: - No native libraries required (zero unmanaged dependencies) - Runs on Windows, Linux, macOS, iOS, Android, MAUI, Uno, WASM, Unity*, cloud functions and plugins - Targets netstandard2.0, net8.0, and net9.0 Use Dew.Math.Core when you need **maximum portability** in libraries, shared simulation engines, tooling, mobile deployments, WebAssembly environments, or plugin architectures.

v6.3.10↙ 14.4K
mathnumericalvectormatrixcomplex

CenterSpace.NMath.Standard.Windows.X86

Foundational classes for financial, engineering, and scientific applications, including complex number classes, general vector and matrix classes, structured sparse matrix classes and factorizations, general sparse matrix classes and factorizations, general matrix decompositions, least squares solutions, random number generators, Fast Fourier Transforms (FFTs), numerical integration and differentiation methods, function minimization, curve fitting, root-finding, linear and nonlinear programming. This package also provides functions for statistical computation and biostatistics, including descriptive statistics, probability distributions, combinatorial functions, multiple linear regression, hypothesis testing, analysis of variance, multivariate statistics, partial least squares, and nonnegative matrix factorization. Built on .NET Standard 2.0. Requires a minimum of .NET Standard 2.0, .NET 5, .NET Core 2.0 or .NET Framework 4.6.1. Requires Visual Studio 2017 C++ x86 runtime.

v7.1.0.47↙ 41.8K
mathstatisticsnumericsprobabilitylinear

Dew.Lab.Studio.Linux

Dew.Lab.Studio.Linux bundles the native-accelerated Linux editions of the Dew libraries: Dew.Math.Linux, Dew.Signal.Linux, and Dew.Stats.Linux. This package is intended for Linux desktops, servers, HPC clusters, and container-based compute environments requiring high numerical throughput and scalable parallel execution. Included Components: - Dew.Math.Linux: dense and sparse linear algebra (BLAS/LAPACK, Pardiso, UMFPACK), complex arithmetic, interpolation and splines, spectral and polynomial transforms, optimization, curve fitting, special function library, numerical integration/differentiation - Dew.Signal.Linux: FIR/IIR filtering, FFT and spectral analysis, convolution/correlation, windowing, resampling, time-frequency transforms, streaming-friendly DSP operations - Dew.Stats.Linux: probability distributions, random sampling, inference tests, regressions, statistical modeling and simulation workflows Performance Architecture: - Native-accelerated BLAS/LAPACK for Linux - CPU feature dispatch (AVX / AVX2 / AVX-512) - Scalable multithreading with low-GC memory allocator - Optional OpenCL GPU acceleration when available Use Dew.Lab.Studio.Linux when you require a unified math + DSP + statistics environment on Linux, with full native acceleration and container/HPC-friendly runtime deployment.

v6.3.10↙ 6.0K
dotnetcsharplinuxnativenative-acceleration