Note

This page is a reference documentation. It only explains the class signature, and not how to use it. Please refer to the user guide for the big picture.

3.3.6. fmralign.alignment_methods.OptimalTransportAlignment

class fmralign.alignment_methods.OptimalTransportAlignment(metric='euclidean', reg=1, max_iter=1000, tol=0.001)

Compute the optimal coupling between X and Y with entropic regularization using a OTT-JAX as a backend for acceleration.

Parameters:

metricstr(optional)

metric used to create transport cost matrix, see full list in scipy.spatial.distance.cdist doc

regint (optional)

level of entropic regularization

Attributes:

Rjaxlib.xla_extension.Array

Mixing matrix containing the optimal permutation

__init__(metric='euclidean', reg=1, max_iter=1000, tol=0.001)

fit(X, Y)

Parameters:

X: (n_samples, n_features) nd array

source data

Y: (n_samples, n_features) nd array

target data

transform(X)

Transform X using optimal coupling computed during fit.