Module math 

Layer 1g — mathematical special functions (inverse error function, incomplete gamma functions and their inverse). Special mathematical functions used by the thermophysics and statistics kernels.

Ports the OpenFOAM primitives/functions/Math helpers: the inverse error function (erf_inv), the regularised lower/upper incomplete gamma functions and their unnormalised forms (inc_gamma_ratio_p, inc_gamma_ratio_q, inc_gamma_p, inc_gamma_q), and the inverse of the regularised lower incomplete gamma (inv_inc_gamma). All arguments and results are dimensionless f64. It also hosts parallel, the batched root finders — bisection, Brent, bracket-safeguarded Newton, and batched closed-form polynomial roots — each dispatched across crate::compute::ComputeBackend. They live here rather than under polynomial/ because the general case solves a caller-supplied residual such as h(T) - h_target, which is not a polynomial at all, and because this module is already where the crate’s iterative inversions live.

Re-exports

pub use differentiate::derivative;

pub use differentiate::derivative_backend_for;

pub use differentiate::derivative_batch;

pub use differentiate::jacobian;

pub use differentiate::jacobian_batch;

pub use differentiate::jacobian_batch_backend_for;

pub use differentiate::jacobian_column_backend_for;

pub use differentiate::ode_system_jacobian;

pub use differentiate::DerivativeBatch;

pub use differentiate::DerivativeSolution;

pub use differentiate::DiffBatchFailure;

pub use differentiate::DiffScheme;

pub use differentiate::DiffSettings;

pub use differentiate::DiffStatus;

pub use differentiate::JacobianBatch;

pub use differentiate::JacobianSolution;

pub use differentiate::NumericalJacobian;

pub use differentiate::CBRT_EPSILON;

pub use differentiate::DERIVATIVE_BATCH_MIN_POINTS;

pub use differentiate::FIFTH_ROOT_EPSILON;

pub use differentiate::JACOBIAN_BATCH_MIN_PROBLEMS;

pub use differentiate::JACOBIAN_COLUMN_MIN_DIMENSION;

pub use erf_inv::erf_inv;

pub use inc_gamma::inc_gamma_p;

pub use inc_gamma::inc_gamma_q;

pub use inc_gamma::inc_gamma_ratio_p;

pub use inc_gamma::inc_gamma_ratio_q;

pub use inv_inc_gamma::inv_inc_gamma;

pub use minimise::golden_section_batch;

pub use minimise::minimise_backend_for;

pub use minimise::MinBatch;

pub use minimise::MinBatchFailure;

pub use minimise::MinProblem;

pub use minimise::MinSettings;

pub use minimise::MinSolution;

pub use minimise::MinStatus;

pub use minimise::Sense;

pub use minimise::GOLDEN_RATIO;

pub use minimise::MINIMISE_BATCH_MIN_PROBLEMS;

pub use minimise::SQRT_EPSILON;

pub use parallel::cubic_roots_batch;

pub use parallel::linear_roots_batch;

pub use parallel::poly_roots_backend_for;

pub use parallel::quadratic_roots_batch;

pub use parallel::root_batch_backend_for;

pub use parallel::solve_bracketed_batch;

pub use parallel::solve_newton_batch;

pub use parallel::RootBatch;

pub use parallel::RootBatchFailure;

pub use parallel::RootMethod;

pub use parallel::RootProblem;

pub use parallel::RootSettings;

pub use parallel::RootSolution;

pub use parallel::RootStatus;

Modules

differentiate

Numerical differentiation of a supplied function — finite differences, batched derivatives, and batched Jacobians, dispatched across ComputeBackend.

erf_inv

inc_gamma

inv_inc_gamma

minimise

Batched derivative-free 1-D golden-section extremum search on the hybrid execution backend — contract N independent brackets at once, serially or across CPU cores.

parallel

Batched scalar root finding on the hybrid execution backend — solve N independent f(x) = 0 problems at once, serially or across CPU cores.