UMAP EFDA Metrics#
Distance metrics for functions and curves in R^n for use with UMAP (lmcinnes/umap)
moduleauthor:: J. Derek Tucker <jdtuck@sandia.gov>
- umap_metric.efda_distance(q1, q2, alpha=0)[source]#
” calculates the distances between two curves, where q2 is aligned to q1. In other words calculates the elastic distances/ This metric is set up for use with UMAP or t-sne from scikit-learn
- Parameters:
q1 – vector of size N
q2 – vector of size N
alpha – weight between phase and amplitude (default = 0, returns amplitude)
- Return type:
scalar
- Return dist:
amplitude distance
- umap_metric.efda_distance_curve(beta1, beta2, closed)[source]#
” calculates the distances between two curves, where beta2 is aligned to beta1. In other words calculates the elastic distance. This metric is set up for use with UMAP or t-sne from scikit-learn
- Parameters:
beta1 – vector of size n*M
beta2 – vector of size n*M
closed –
if open curves and (1) if closed curves
- Return type:
scalar
- Return dist:
shape distance