Roadmap.

Numra is pre-1.0. This page describes the directions we're actively working on. It's deliberately silent on dates — the single-maintainer release cadence makes calendar promises unreliable, and a vague schedule is worse than none. For the most current signal of where work is happening, see the open issues and the CHANGELOG.

Active directions

Expand DAE capabilities

Today Numra's stiff solvers (Radau5, BDF) handle index-1 differential-algebraic equations with constant mass matrices. The infrastructure for higher-index DAEs — Pantelides structural analysis, symbolic differentiation, and consistent initialisation — already ships, but it's not yet wired into the solver call path. The work here is to close that gap so higher-index problems are practical to solve, with sparse Jacobian support and constraint stabilisation as related extensions.

Expand PDE capabilities

Method of lines on 1D, 2D, and 3D grids is solid today — parabolic problems (heat, diffusion, reaction-diffusion, advection-diffusion) work with all four boundary-condition types via the second-order stencils that ship in the MOL pipeline. The growth areas are multi-component / coupled-PDE systems (so hyperbolic and wave equations become first-class), an elliptic static solver path, wiring the existing fourth-order stencil helpers through the MOL assemblers, and more discretisation choices beyond finite differences.

Build numra-plot

Numerical results without a comfortable plotting story are half-finished. numra-plot will be a Numra-native plotting crate aimed at the equation-class-aware visualisations Numra users actually need — phase portraits, time-series with confidence bands, method-of-lines surface plots, convergence diagrams — without forcing a Python detour.

Numra-native linear algebra; remove the faer dependency

Iterative Krylov solvers (CG, GMRES, BiCGSTAB, MINRES) and preconditioners (Jacobi, ILU, SSOR) are already native code in numra-linalg. The dense direct path — LU, QR, Cholesky, SVD, eigendecomposition — is currently a wrapper around faer. The long-term goal is for Numra to own its complete linear-algebra surface. This is the largest item on this list and is intentionally framed as a direction, not a milestone — the work spans BLAS-equivalent primitives, dense factorisations, and refactors across every downstream crate that uses linalg trait bounds.

What you can rely on today

  • Stability commitments. See /stability for MSRV, semver, and deprecation windows.
  • Solver behaviour in any released version. Covered by the regression suite documented in docs/audit/correctness-test-map.md.
  • License terms. Free for non-commercial academic and research use; commercial use requires a separate license. See /license.

How to influence the direction