Low-level alignment methods.

fmralign.methods: Alignment Methods

Classes

Identity()	Compute no alignment, used as baseline for benchmarks : RX = X.
DetSRM([n_components])	Compute the alignment from one subjects to the shared latent response.
Procrustes([scaling])	Compute a orthogonal mixing matrix R and a scaling sc.
RidgeAlignment([alphas, cv])	Compute a scikit-estimator R using a mixing matrix M s.t Frobenius norm || XM - Y ||^2 + alpha * ||M||^2 is minimized.
OptimalTransport([reg, max_iter, tol, ...])	Compute the optimal coupling between X and Y with entropic regularization, using the pure Python POT (https://pythonot.github.io/) package.
SpectralOT(evecs[, alpha, reg, max_iter, ...])	Compute the optimal coupling between X and Y using an anatomy-aware cost matrix that combines functional and harmonic distances.