ITDS Linear Systems Documentation

A NumPy/SciPy-backed linear systems library with APIs inspired by the IMSL Fortran Numerical Library “Linear Systems” chapter.

Linear system solvers backed by NumPy & SciPy

ITDS Linear Systems packages direct, iterative, banded, sparse, and least-squares linear system routines from ITDS into a focused library. Install, run a minimal solve example, then dive into the API reference.

Open quick start Browse API reference

40 FunctionsDirect, iterative, banded, sparse, and least-squares solvers.

3 Example ScriptsLSLRG, LSLPB, and LSQRR runnable example scripts shipped with the package.

200+ TestsUnit tests and integration tests shipped with the package.

IMSL-styleFunction families aligned with legacy Fortran engineering workflows.

Direct Solvers

General, SPD, triangular, and banded dense direct solvers with LU, Cholesky, and QR factorizations.

Iterative Solvers

CG, BiCG, GMRES, IC-preconditioned CG, SOR, and sparse system iterative methods.

Least Squares

Standard, non-negative, constrained, bounded, and Tikhonov-regularised least-squares routines.

Recommended path: install the package, run the quick start, then use the examples page to find the closest routine family before dropping into the API reference.

Contents

• Installation
  • Requirements
  • Install from the package directory
  • Verify the installation
  • Build the HTML documentation
• Quick Start
• Examples
  • Example Script Map
• API Reference
  • Data Structures
  • Dense Direct Solvers
  • Factorization-Based Solvers
  • Iterative Solvers
  • Least Squares
  • Matrix Inverse and Utility
  • Norms and Conditioning
  • Banded Matrix Utilities
  • Sparse System Utilities
  • Tridiagonal Solvers
• License
  • Linear Systems Commercial License Agreement
  • 1. Definitions
  • 2. License Grant
  • 3. Restrictions
  • 4. Warranty Disclaimer
  • 5. Governing Law
  • 6. Contact