//! Model-order reduction: POD-Galerkin projection with ECSW hyper-reduction.
//!
//! The pipeline, all offline steps verified by their own invariants:
//!
//! 1. Collect full-order solution snapshots (the caller's job — typically a
//!    parameter or load sweep of [`crate::analysis::NonlinearStaticAnalysis`]).
//! 2. [`pod::pod_basis`] — orthonormal basis by SVD, truncated at an energy
//!    criterion.
//! 3. [`ecsw::train_ecsw`] — nonnegative element weights so that a small
//!    element subset reproduces the reduced internal force over the
//!    training set ([`nnls`] with an early stop; sparsity comes from the
//!    stopping tolerance).
//! 4. [`reduced::ReducedNonlinearModel`] — Newton in reduced coordinates,
//!    assembling only the sampled elements.
//!
//! Scope: homogeneous Dirichlet data; the basis is over the free DOFs
//! only (lifting for inhomogeneous boundary values is not implemented).
//! Kinematics are selected per [`reduced::Formulation`]: the original
//! small-strain scope (geometrically linear, materially nonlinear), or
//! total-Lagrangian Saint Venant–Kirchhoff matching
//! `NonlinearDynamicAnalysis::with_total_lagrangian` — required when the
//! snapshots come from a total-Lagrangian trajectory (the FSI flag).

pub mod dynamic;
pub mod ecsw;
pub mod nnls;
pub mod pod;
pub mod reduced;

pub use dynamic::{ReducedNewmark, ReducedState};
pub use ecsw::{EcswModel, ecsw_residual, train_ecsw, train_ecsw_formulated};
pub use nnls::nnls;
pub use pod::pod_basis;
pub use reduced::{Formulation, ReducedNonlinearModel};