UMAP EFDA Metrics¶
Distance metrics for functions and curves in R^n for use with UMAP (https://github.com/lmcinnes/umap)
moduleauthor:: J. Derek Tucker <jdtuck@sandia.gov>
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umap_metric.
efda_distance
[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
Return type: scalar
Return dist: amplitude distance
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umap_metric.
efda_distance_curve
[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