search
Found 26 packages
Aspose.SVG✓
Aspose.SVG for .NET seamlessly integrates into your .NET Apps to provide processing and rendering of SVG files without installing any 3rd party modeling or rendering software. Aspose.SVG for .NET offers developers to work with its DOM that is fully compatible with the official SVG specifications. Create SVG files from scratch. Perform content navigation via XPath Query or CSS Selectors. High-quality SVG rendering and conversion to various popular formats, including, PDF, XPS, JPEG, PNG, TIFF, and GIF. Ability to fetch information about SVG files, its elements and hierarchy. Merge multiple SVG documents, and vectorize their text elements to retain the high quality. It’s managed C# implementation enables it to be used with any .NET language, such as, C#, VB.NET, etc. You can also create Windows Desktop Apps as well as the ASP.NET web Apps using Aspose.SVG for .NET. It works equally well on any OS that can install .NET Framework (2.0/4.8), Mono (5.4/6.4), .NET Core (2.0/3.1) or use .NET 5, such as, MS Windows (32-bit and 64-bit), macOS (10.12+), and Linux.
v26.2.0
↙ 958.7K / total
.NETCoreFramework.net-core.net-standard
Tsunami
A High Performance C# wrapper that allows you to get the benifts of SIMD Intrinsics on List<T>.
v2.0.2
↙ 1.1K / total
simdperformancecollectionsintrensicsmath
pkg
CloudflareFS.Management
F# clients for Cloudflare Management APIs, including D1, R2, KV, Durable Objects, Queues, Vectorize, Hyperdrive, Workers, Pages, and Analytics. For use in .NET applications to manage Cloudflare resources.
v0.1.0
↙ 458 / total
fsharpcloudflaremanagementapiclient
pkg
CloudflareFS.Runtime
F# and Fable bindings for Cloudflare Workers Runtime APIs, including R2, KV, D1, Durable Objects, Queues, Vectorize, Hyperdrive, and AI. For use with Fable to compile F# to JavaScript.
v0.1.0
↙ 452 / total
fsharpcloudflareworkersfablebindings
Vectorizer.Sdk
Official C# client library for the Hive Vectorizer vector database
v2.2.0
↙ 1.7K / total
Redis.OM.Vectorizers.AllMiniLML6V2
Sentence Vectorizer for Redis OM .NET using all-MiniLM-L6-v2
v1.1.0
↙ 9.7K / total
redisredisearchAIVectors
Redis.OM.Vectorizers
Core Vectorizers for Redis OM .NET.
v1.1.0
↙ 5.9K / total
redisredisearchindexingdatabases
Redis.OM.Vectorizers.Resnet18
Resnet 18 Vectorizers for Redis OM .NET.
v1.1.0
↙ 5.3K / total
redisredisearchindexingdatabases
pkg
AICentral.AzureAISearchVectorizer
Package Description
v0.21.0
↙ 3.2K / total
pkg
VectorizedSpans
A very lightweight library that lets developers enumerate spans with SIMD acceleration
v1.0.0
↙ 339 / total
simdvectorslightweight
Aspose.SVG.Drawing.SkiaSharp✓
Aspose.SVG.Drawing.SkiaSharp is a self-contained build of Aspose.SVG for .NET that uses the SkiaSharp graphics engine instead of GDI+. Simply add the package reference to begin rendering and processing SVG files - no extra configuration code is required. Aspose.SVG seamlessly integrates into your .NET apps to provide processing, DOM manipulation, rendering, and conversion of SVG files without installing any third-party modeling or rendering software. Its DOM implementation is fully compatible with official SVG specifications, allowing you to: • Create SVG files from scratch or merge multiple SVG documents • Navigate content via XPath queries or CSS selectors • Vectorize text elements to keep output crisp at any resolution • Convert or render SVG to PDF, XPS, PNG, JPEG, TIFF, and GIF with SkiaSharp's hardware-accelerated pipeline benefiting from its filters, shaders, and image-processing effects. Written in managed C#, the library works with C#, VB.NET, F#, and any .NET language targeting .NET Standard 2.0. It runs cross-platform on Windows, Linux, macOS, Mono, and all modern .NET (Core/5+/6+/7+) runtimes. Note: This package already contains the full Aspose.SVG API compiled with SkiaSharp. Do not call Aspose.Svg.Configuration.SetExtension(new SkiaModule()); and you do not need a separate Aspose.SVG package.
v26.2.0
↙ 20.7K / total
AsposeAspose.SVGSkiaSharpSVGDrawing
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 / total
dotnetcsharp
aspose.html.cloud.v143
Aspose HTML SDK for C++ is a programming SDK that allows software developers to manipulate and convert HTML documents from within their own applications. A Wrapper of RESTful APIs, Aspose HTML SDK for C++ speeds up HTML programming and conversion. Aspose Html SDK for C++ is a cross-platform C++ library that enables your applications to perform a great range of html document processing tasks. With Aspose.Html C++ you can load, save and convert html, epub, mhtml, md documents between the following formats: PDF, XPS, DOCX, MD, JPG, GIF, BMP, PDF, TIFF, MHTML. Vectorize images to SVG format.
v22.12.1
↙ 1.4K / total
epubtopdfimagesvg
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 / total
mathnumericalvectormatrixcomplex
pkg
libhat-sharp
C# bindings for libhat, a high-performance game hacking library. Currently only includes the pattern scanner, which uses CPU vectorization features to quickly find patterns.
v0.2.0
↙ 733 / total
libhatvectorizedgame-hackingmoddingpattern-scanning
Dew.Math.Linux
Dew.Math.Linux provides the high-performance numerical computation capabilities of Dew.Math, but with native acceleration binaries compiled for Linux. It is designed for compute clusters, scientific servers, containerized deployment environments, and performance-critical Linux workloads. Core Numerical Capabilities: - Dense linear algebra (BLAS/LAPACK): decomposition and eigenvalue routines optimized for AVX/AVX-512 - Sparse matrix operations with Pardiso and UMFPACK direct solvers and Krylov-based iterative solvers - Complex-valued linear algebra and spectral computations - Polynomial operations, splines, interpolation, approximate function models, and spectral transforms - Probability distributions, stochastic simulation, and random number engines - Special function library suitable for numerical physics, statistics, and differential systems - Optimization algorithms for non-linear fitting, gradient models, linear programming, and statistical inference Performance Architecture: - Linux-native accelerated BLAS/LAPACK libraries - Multithreaded vectorized math with CPU feature dispatch (AVX/AVX2/AVX-512) - Low-overhead memory allocator for stable scaling under parallel workloads - Optional OpenCL GPU integration for Linux compute environments Platform Model: - Contains Linux native runtime binaries - For Windows native acceleration use: Dew.Math - For portable managed-only computation use: Dew.Math.Core Use Dew.Math.Linux for Linux HPC compute nodes, microservice model engines, AI research pipelines, and scalable distributed scientific processing.
v6.3.10
↙ 37.4K / total
dotnetcsharplinuxnativenative-acceleration
Dew.Stats.Linux
Dew.Stats.Linux is the Linux-native accelerated edition of the Dew.Stats statistical computing library. It provides a comprehensive suite of tools for probability distributions, hypothesis testing, regression, multivariate analysis, experimental design, and time-series modeling, powered by the high-performance vectorized numerical backend in Dew.Math.Linux. This edition is designed for Linux-based compute servers, HPC pipelines, analytics microservices, research clusters, data acquisition systems, and real-time industrial environments. Statistical Capabilities: - Probability distributions (PDF, CDF, inverse CDF) for 36+ discrete and continuous models - Random number generators and parameter estimation - Descriptive statistics, histograms, ogives, quantiles, outlier analysis Hypothesis Testing and Inference: - Parametric tests (t, Z, F, Chi-Squared, Bartlett, Hotelling T²) - Non-parametric tests (Wilcoxon, Sign, Mann–Whitney, Anderson–Darling, Shapiro–Wilk, KS) - Confidence intervals, residual diagnostics, model fitness evaluation Regression and Statistical Modeling: - Linear, multiple linear, logistic, Poisson, ridge and nonlinear regression - ANOVA and ANCOVA - Principal Component Regression and regularization workflows Multivariate and Structural Analysis: - PCA (correlation/covariance) with eigen decomposition - PCA residuals, factor rotation, Bartlett tests, item analysis - Classical Multidimensional Scaling and dimensionality interpretation Time Series Modeling and Forecasting: - ACF and PACF analysis - ARMA, ARIMA and ARAR models - Exponential smoothing (single/double/triple) - Box-Ljung significance testing and forecasting evaluation High-Level Statistical Workflow Components: - TMtxANOVA, TMtxMulLinReg, TMtxNonLinReg, TMtxPCA, TMtxHypothesisTest, TMtxBinaryTest, TMtxMDScaling Platform Characteristics: - Uses **Dew.Math.Linux** for native BLAS/LAPACK acceleration with AVX2/AVX512 dispatch - Highly scalable under multi-threaded workloads - No Windows or WinForms dependencies - Headless execution suitable for batch, service, and compute-node environments Dew.Stats.Linux provides the full analytical capabilities of Dew.Stats, optimized specifically for Linux-based CPU compute environments.
v6.3.10
↙ 8.1K / total
Dew.Signal.Core
Dew.Signal.Core is the cross-platform, managed-only edition of the Dew.Signal DSP library. It provides a comprehensive suite of digital signal processing algorithms and components without requiring native binary acceleration. This maximizes compatibility across platforms including Windows, Linux, macOS, mobile, embedded, and WebAssembly environments. Filter Design and Processing: - IIR filters: Butterworth, Chebyshev I/II, Elliptic, Bessel; analog and discrete design workflows - Frequency transformations in Z- and S-domains, bilinear and matched-Z transforms, pole/zero and state-space forms, group delay analysis, stability filters - FIR filter design: window methods, Remez exchange algorithm, Hilbert transformers, differentiators, integrators, Savitzky–Golay filtering, fast envelope detectors - Multi-rate filtering: half-band multistage FIR designs, zoom-spectrum, decimation, interpolation Nonlinear Processing: - Sample-and-hold, sample-and-decay, and median filtering Spectral Analysis and Estimation: - FFT-based spectral analysis framework - Parametric estimators: Yule–Walker, Burg, Covariance, Modified Covariance - CZT, real and complex cepstrum and inverse cepstrum - Bispectrum, bicoherence, coherence and transfer function estimation - Peak detection, peak interpolation and tracking, phase unwrapping - Advanced spectral statistics: noise floor, SFDR, THD, THDN, SINAD, RMS, SNR Time-Domain Modeling and System Representation: - Conversion between state-space, zero-pole, numerator–denominator transfer models - System zero/pole determination and stability analysis Signal Synthesis, Streaming, and Measurement: - Signal generators using stack-based vectorized function evaluation - Support for multiple noise models: white, pink, brownian, blue, violet - Components for continuous streaming, recording, playback, triggering and monitoring - Scalable FIR and IIR convolution, auto-correlation, cross-correlation, DCT/IDCT Forecasting and Time-Series Modeling: - Spectral forecasting based on user-defined peak selection for interpretable predictive modeling Platform and Integration Notes: - Uses Dew.Math.Core as its numerical foundation (managed vector/matrix computing) - Visualization is optionally provided through Dew.Signal.Tee (Windows-only), not included here - Compatible with cross-platform UI frameworks (MAUI, Uno, Avalonia), compute services, and WASM Dew.Signal.Core is ideal when portability, sandbox safety, or plugin isolation is required.
Dew.Lab.Studio
Dew Lab Studio bundles the Dew.Math, Dew.Signal, and Dew.Stats libraries into a unified package suitable for scientific, engineering, financial, and real-time signal-processing applications. It includes full numerical computation, vectorized signal analysis and filtering, statistical modeling, probability distributions, spectral transforms, optimization, and advanced data workflows. This package also integrates visualization via Dew.Math.TeePro, Dew.Signal.Tee, and Dew.Stats.Tee, which extend TeeChart for high-performance plotting of large datasets, spectrograms, signal traces, matrices, probability distributions, and live streaming data. No hard WinForms linking is introduced into your own code; the visualization libraries depend on WinForms internally while allowing you to use WinForms, WPF, Avalonia, or custom UI frameworks. Included Components: - Dew.Math (Windows native-accelerated numerical computation) - Dew.Signal (real-time DSP, filtering, transforms, spectral and streaming signal analysis) - Dew.Stats (probability distributions, statistical modeling, hypothesis testing, inference) - Dew.Math.TeePro (high-speed charting extensions for numerical data) - Dew.Signal.Tee (spectral / time-frequency / oscilloscope plotting extensions) - Dew.Stats.Tee (statistical visualization and histogramming helpers) Usage Model: - Use Dew Lab Studio for Windows desktop and server applications requiring interactive visualization, scientific and engineering debugging workflows, data interpretation, or real-time signal monitoring. - For Linux HPC systems: use Dew.Lab.Studio.Linux (accelerated native Linux builds). - For maximum cross-platform portability: use Dew.Lab.Studio.Core (managed-only .Core builds). Platform Notes: - Dew.*.Tee packages depend on WinForms internally. Therefore, projects targeting net8.0-windows or net9.0-windows must enable the Windows Desktop framework (WinForms).
v6.3.10
↙ 6.4K / total
dotnetcsharp
Dew.Signal
Dew.Signal is a high-performance digital signal processing library built on top of Dew.Math, providing a comprehensive suite of optimized algorithms for real-time signal analysis, filtering, spectral estimation, modeling, and streaming signal workflows. The library is designed for scientific, engineering, audio, RF, vibration, instrumentation, control, and monitoring applications requiring both numerical accuracy and hardware-level performance on multi-core CPUs with AVX2/AVX512 support. Filter Design and Processing: - IIR filter design (Butterworth, Chebyshev I/II, Elliptic, Bessel), analog and digital domains - Order estimation, frequency transformations, bilinear and matched-Z transforms - State-space and zero-pole-numerator-domain modeling with group delay and stability analysis - FIR filter design using window methods and Remez exchange algorithm - FIR/Hilbert/differentiator/integrator design, Savitzky–Golay filtering, envelope detectors - Multi-rate filtering: half-band polyphase filters, decimation, interpolation, zoom-spectrum analysis Nonlinear and Adaptive Filters: - Sample-and-hold, sample-and-decay, and median filtering - High-quality rate conversion with 160dB stopband attenuation at high speed Spectral and Frequency-Domain Analysis: - FFT-based spectrum analyzer components with real-time UI integration support - Parametric spectral estimation: Yule–Walker, Burg, Covariance, Modified Covariance - Chirp-Z transform, bispectrum, bicoherence, transfer function, coherence estimation - Peak interpolation and peak-tracking enhancements, phase unwrapping - Real and complex cepstrum, inverse cepstrum - Spectral statistics: noise floor, SFDR, THD, THDN, SINAD, RMS, SNR measurements Signal Synthesis, Streaming, and Measurement: - Signal generators with stack-based vectorized function evaluation - Audio capture/playback with monitoring and triggering support - Data streaming and file format components for continuous acquisition and logging Forecasting and Time-Series Modeling: - Spectral forecasting based on controlled peak selection, enabling clear component-based prediction Integration and Extensions: - Works seamlessly with Dew.Math numeric structures (vectors/matrices) - Optional high-performance charting available via a separate Dew.Signal.Tee package (Windows visualization) - Part of the Dew Lab Studio ecosystem for unified math, DSP, and statistical analysis workflows Designed for reproducibility, determinism, and stable numerical behavior in long-running or real-time environments.
page 1next →