This solution provides a set of reusable .NET libraries for scientific and numeric data processing, with a focus on multidimensional data structures, matrix-oriented transformations, and parallel execution helpers. The codebase is organized into small libraries with separated responsibilities:- `INAF.Libraries.Net.Data`: domain types and low-level data access for matrices, qubes, headers, and typed result containers.- `INAF.Libraries.Net.Data.Helpers`: higher-level helper APIs for building arrays and matrices, and for converting `Qube` data into analysis-ready `Matrix` instances.- `INAF.Libraries.Net.Parallelization`: reusable parallel iteration and processor allocation helpers used by the other libraries.The solution is suitable as a foundation for data-analysis pipelines that need to read structured scientific datasets, transform them into matrix form, and execute CPU-bound operations efficiently
Francesco Carraro (Tue,) studied this question.