This package provides helpful methods and algorithms to handle math computing tasks.
It contains implementations for vector and matrix models, mutliple distributions and random
number generators as well as several generic distance functions.
For more details how...
This package provides common methods used by all other packages especially the most used data structures
of the framework. Additionally it provides implementations for debugging assertions, a weak event model and the logging adapter.
For more details how to use MARS, please...
OpenGL Mathematics (GLM) is a header only C++ mathematics library for graphics software based on the OpenGL Shading Language (GLSL) specifications.
GLM provides classes and functions designed and implemented with the same naming conventions and functionalities than GLSL so that anyone who knows...
mXparser is a super easy, rich, fast and highly flexible math expression parser library (parser and evaluator of mathematical expressions / formulas provided as plain text / string). Software delivers easy to use API for JAVA, Android and C# .NET/MONO (Common Language Specification compliant: F#,...
The core of the C# math rendering engine - CSharpMath.
Can display beautiful math equations and symbols from the LaTeX format.
Needs a front end to function.
Currently, front ends exist for Avalonia, iOS, SkiaSharp and Xamarin.Forms.
A library of various mathematical and statistical functions, as part of a class project. Most functions are stored in nested static classes, each inner class representing a particular branch of the code. Most functions have an extension method form in the namespace MathPlusLib.Extensions. This...
Matheval is a mathematical expressions evaluator library for .NET. Allows to evaluate mathematical, boolean, string and datetime expressions on the fly. Official document and usage examples: https://matheval.org/math-expression-eval-for-c-sharp/
This package uses a Pratt Parser to parse mathematical expresssions in a made-up language. This library takes a string, can convert it into a token stream, parse that stream into a parse tree (returning the root node), and evaluate that into a result.
Basic statistics with some probability library. Includes common distributions (Bernoulli, Binomial, Poisson, Student's and Normal), random number generators from some of the distributions, summary statistics for a sample, Z-Test, Student's T-Test, special functions (Error, Gamma, Beta and...