mathematics

Math.NET Numerics

Math.NET Numerics is a mathematics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Math.NET Numerics rather than just read about it. In short: Math.NET Numerics is an open-source numerical library for .NET and Mono, written in C# and F#. It features functionality similar to BLAS and LAPACK.

Key takeaways

Math.NET Numerics belongs to mathematics; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Math.NET Numerics to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Math.NET Numerics from memory before moving on to harder problems.

Reference excerpt

Math.NET Numerics is an open-source numerical library for .NET and Mono, written in C# and F#. It features functionality similar to BLAS and LAPACK.

History Math.NET Numerics started 2009 by merging code and teams of dnAnalytics with Math.NET Iridium. It is influenced by ALGLIB, JAMA and Boost, among others, and has accepted numerous code contributions. It is part of the Math.NET initiative to build and maintain open mathematical toolkits for the .NET platform since 2002. Math.NET is used by several open source libraries and research projects, like MyMediaLite, FermiSim and LightField Retrieval, and various theses and papers.

Features The software library provides facilities for:

Probability distributions: discrete, continuous and multivariate. Pseudo-random number generation, including Mersenne Twister MT19937. Real and complex linear algebra types and solvers with support for sparse matrices and vectors. LU, QR, SVD, EVD, and Cholesky decompositions. Matrix IO classes that read and write matrices from/to Matlab and delimited files. Complex number arithmetic and trigonometry. “Special” routines including the Gamma, Beta, Erf, modified Bessel and Struve functions. Interpolation routines, including Barycentric, Floater-Hormann. Linear Regression/Curve Fitting routines. Numerical Quadrature/Integration. Root finding methods, including Brent, Robust Newton-Raphson and Broyden. Descriptive Statistics, Order Statistics, Histogram, and Pearson Correlation Coefficient. Markov chain Monte Carlo sampling. Basic financial statistics. Fourier and Hartley transforms (FFT). Overloaded mathematical operators to simplify complex expressions. Runs under Microsoft Windows and platforms that support Mono. Optional support for Intel Math Kernel Library (Microsoft Windows and Linux) Optional F# extensions for more idiomatic usage.

See also List of numerical analysis software List of numerical libraries List of open-source mathematical libraries

References

External links Math.NET Numerics Website Math.NET Initiative

Worked examples

Example 1 — a first encounter with Math.NET Numerics

Start with the simplest possible case. Write down what Math.NET Numerics claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In mathematics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Math.NET Numerics before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Math.NET Numerics ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Math.NET Numerics

In research: Math.NET Numerics appears in mathematics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Math.NET Numerics in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Math.NET Numerics is common in secondary-school and first-year university syllabi. It links to neighbouring topics C Sharp libraries, Numerical software, so understanding it makes those chapters shorter.
In everyday life: Look for Math.NET Numerics outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

Affiliate

Preply — study more efficiently by working with a personal tutor. 50% off.

How to study Math.NET Numerics in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Math.NET Numerics means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Math.NET Numerics out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Math.NET Numerics in simple terms?

Math.NET Numerics is an open-source numerical library for .NET and Mono, written in C# and F#. It features functionality similar to BLAS and LAPACK.

Why does Math.NET Numerics matter?

Because it connects several mathematics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Math.NET Numerics?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Math.NET Numerics.