sparse

Fully interoperable with Gonum's APIs and dense matrix types, allowing seamless integration into existing numerical computing workflows, as demonstrated in the usage examples where sparse matrices can be converted to Gonum mat.Dense.

Implements various sparse matrix formats like DOK, COO, CSR, CSC, and DIA, catering to different access patterns and optimization needs for diverse applications, as listed in the features section.

Provides implementations of standard Sparse BLAS routines, ensuring efficient and optimized operations for sparse data structures, reducing computational overhead in scientific computing scenarios.

Designed to store only non-zero values, significantly reducing memory footprint for large datasets with high sparsity, as emphasized in the project's philosophy for handling text mining and ML applications.