¶

euclidean_distance¶

source

.euclidean_distance(
   distances
)

Computes euclidean distances - norm of vectors

Args

• distances (np.array) : n-dimensional coordinates of points

Returns

• euxlidean_distances (np.array) : array with euclidean distances

pear_correlation¶

source

.pear_correlation(
   distance_matrix, embedding
)

Computes pearson correlation between euclidean distances in different dimensionalities

Args

• distance_matrix (np.array) : n-dimensional distance matrix
• embedding (np.array) : (m < n)-dimensional embedding

Returns

• correlation (float) : pearson correlation

DRM¶

source

.DRM(
   distance_matrix, embedding, inverse_emb
)

Return DRM object from https://github.com/zhangys11/pyDRMetrics

Args

• distance_matrix (np.array) : n-dimensional distance matrix
• embedding (np.array) : (m < n)-dimensional embedding
• inverse_emb (np.array) : reverse fit of model on embeddings

Returns

• DRM : DRM object with quality metrics