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CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

Project Overview

ojAlgo is a pure Java library for mathematics, linear algebra, and optimisation (LP, QP, MIP). Zero external dependencies. Targets Java 11+. Published to Maven Central as org.ojalgo:ojalgo.

Build Commands

./mvnw compile                  # Compile
./mvnw test                     # Run tests (excludes @Tag("slow"), @Tag("unstable"), @Tag("network"))
./mvnw test -Dtest=ClassName    # Run a single test class
./mvnw test -Dtest=ClassName#methodName  # Run a single test method
./mvnw package -DskipTests      # Build JAR without tests

Architecture

All source lives under org.ojalgo with these key packages:

  • structure — Foundational interfaces (Access1D/2D/AnyD, Mutate1D/2D, Structure1D/2D/AnyD, Factory1D/2D) that define how data is accessed, mutated, and structured. Nearly everything implements these.
  • array — Concrete 1D array implementations: dense (ArrayR064, ArrayR032), sparse (SparseArray), off-heap (OffHeapR064), and buffer-backed. Naming convention: R064 = double, R032 = float, C128 = complex, Q128 = rational, H256 = quaternion, Z0xx = integer types.
  • matrix — Matrix types and operations:
    • MatrixR064, MatrixR032, MatrixC128, etc. — user-facing immutable matrix types
    • store/ — mutable matrix storage (R064Store, GenericStore, SparseStore, RawStore) plus logical/virtual stores (transposed, conjugated, sliced, composed)
    • decomposition/ — LU, QR, Cholesky, SVD, Eigenvalue, LDL, Bidiagonal, Hessenberg, Tridiagonal with Dense/Raw/Sparse variants
    • operation/ — low-level BLAS-like primitives
  • optimisation — Mathematical programming:
    • ExpressionsBasedModel — the primary modelling API (variables + expressions/constraints)
    • linear/ — Simplex solvers (primal, dual, phased, revised) with dense and sparse tableaux
    • convex/ — QP solvers
    • integer/ — Branch-and-bound MIP solver
  • scalar — Number types: ComplexNumber, RationalNumber, Quaternion, Quadruple (double-double), BigScalar
  • function — Mathematical functions, aggregators, constants (PrimitiveMath)
  • concurrent — Threading utilities used internally
  • data — Data science utilities (clustering, ANN)

Coding Conventions

  • Performance is paramount. Minimize allocations, prefer primitives over boxed types, avoid streams/Optionals in hot paths. Measure with JMH before/after.
  • Use TestUtils (not JUnit Assertions) for test assertions. Use tolerances for numeric comparisons.
  • Use BasicLogger for diagnostic output, never System.out/System.err.
  • No commented-out code. Use TODO with issue reference if needed.
  • Javadoc style: Keep tidy HTML, avoid unnecessary tags (</p>, </li>, <b>, <i>), avoid HTML entities. Prefer Javadoc on declarations over inline comments.
  • Naming convention for array/matrix types: letter+digits encoding — R064=double, R032=float, C128=complex, Q128=rational, H256=quaternion, Z0xx=integer widths.
  • Binary compatibility: Deprecate before removal. Keep changes small and focused.
  • Ensure exactly one trailing newline in files.
  • For optimisation work, compare with reference solvers (HiGHS, GLOP, CLP, SCIP, CBC, OSQP, CLARABEL).