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The report outlines a collection of .NET libraries designed for various numerical and statistical tasks.

March 26, 2026Open Access

INAF.Libraries.Net.Math TECHNICAL REPORT

Key Points

The report outlines a collection of .NET libraries designed for various numerical and statistical tasks.
Developed reusable class libraries for numerical processing and statistical analysis
Included utility libraries for extension methods and controlled parallel execution
Organized codebase into modular structures by domain areas like Fit, Stats, and Clustering
Targeted .NET framework version net10.0 and utilized nullable reference types
Provided algorithms for fitting, smoothing, clustering, and contour extraction
Enabled efficient parallel execution for better performance in numerical tasks
Facilitated statistical analysis through easy-to-use methods and models

Abstract

This solution is a set of reusable .NET class libraries centered on numerical processing, scientific data handling, and parallel execution support. The main project, `INAF.Libraries.Net.Math`, provides algorithms and models for fitting, smoothing, clustering, contour extraction, and statistical analysis. It is supported by two utility libraries: `INAF.Libraries.Net.Extensions` for general-purpose extension methods and `INAF.Libraries.Net.Parallelization` for controlled parallel execution.The codebase targets `net10.0`, uses nullable reference types, and follows a modular structure organized by domain areas such as `Fit`, `Stats`, `Smoothing`, `Models`, and `Clustering`.

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