alignment_methods

Various methods for aligning microECoG datasets across patients.

Author: Zac Spalding Cogan & Viventi Labs, Duke University

CCAAlign([type, return_space])
JointPCADecomp([n_components, dim_red])

CCA_align(L_a, L_b)	Canonical Correlation Analysis (CCA) alignment between 2 datasets.
CCA_align_by_class(X_a, X_b, y_a, y_b[, ...])	CCA Alignment between 2 datasets with correspondence by averaging within class conditions.
CCA_align_by_trial_subselect(X_a, X_b, y_a, y_b)	CCA Alignment between 2 datasets with correspondence via subselection of trials within shared clases.
extract_latent_dynamics_by_class(X_a, X_b, ...)
extract_latent_dynamics_by_trial_subselect(...)
get_joint_PCA_transforms(features, labels[, ...])	Calculates a shared latent space across features from multiple patients or recording sessions.
parse_return_type(return_space)	Checks the CCA alignment return type is valid.
reshape_latent_dynamics(X_a, X_b, y_a, y_b)
shared_trial_subselect(X_a, X_b, y_a, y_b)