Meta.Numerics A Mono library for numerical and scientific programming
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programming library Mono .NET library numerical programming scientific programming

Meta.Numerics Description

A Mono library for numerical and scientific programming Meta.Numerics is a Mono-compatible .NET library for numerical and scientific programming.It includes functions for matrix algebra (including the computation of eigenvalues and eigenvectors for non-symmetric matrices), special functions of real and complex numbers (including Bessel functions and the complex error function), and statistics (including contingency table analysis and fitting to non-linear models). Here are some key features of "Meta.Numerics": Complex Numbers: · The library not only defines a complex number class and associated arithmetic operations, but also provides a full array of basic functions of complex numbers (corresponding to those offered by the System.Math class for real numbers). The library can also compute several advanced functions of complex arguments. Matrix Algebra: · The library defines a number of matrix classes and operations on them. Advanced Functions Library: · The advanced functions library defines a large number of advanced mathematical function on real numbers, Complex numbers, and integers. · Functions of integers include Factorials, Binomial coefficients, greatest common denominators (GCD) and least common multiples (LCM). · Library routines support root finding, maximum and minimum finding, and the integration of arbitrary user-supplied functions. Statistics and Data Analysis: The statistics library provides specialized classes for working with various types of data, including: · Univariate Samples · Multivariate Samples · Experimental Data with Error Bars · Contingency Tables · For each kind of data, methods allow you to evaluate descriptive statistics, fit models, and perform appropriate statisical tests. All fits produce not just a best-fit parameter set, but also error bars, a covariance matrix, and a goodness-of-fit test. Testing: · The library has undergone extensive testing. We test more than 600 mathematical relationships, most for scores of different arguments ranging over many orders of magnitude. If there is a relationship in Abromiwitz and Stegun expressible using our library functions, we have probably tested it. Our test cases achieve code coverage in excess of 80%. Requirements: · Mono Project What's New in This Release: · New features in this release include Clebsch-Gordon coefficients, the Lambert W function, Zernike R polynomials, the Kuiper test (an alternative to the Kolmogorov-Smirnov test) and its associated distribution, the Logistic distribution, and more tutorials with sample code.

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