maxfuse.metrics.get_matching_alignment_score

maxfuse.metrics.get_matching_alignment_score(estimated_matching, n_samples, true_matching='identity')[source]

Compute the alignment between the estimated matching and the true_matching according to the metric in https://openproblems.bio/neurips_docs/about_tasks/task2_modality_matching/.

Parameters:

estimated_matching (a list of length three.) – The matched pairs are (matching[0][i], matching[1][i]), and its score (the higher, the better) is matching[2][i].
n_samples (int) – The sample size for the first dataset.
true_matching ('identity' or Iterable of length n_samples, default='identity') – If is a list, then the ground truth matched pairs are (i, true_matching[i]) If is ‘identity’, then true_matching = [0, 1…, n_samples].

Returns:

The alignment score.