scib_metrics.utils.cdist

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scib_metrics.utils.cdist#

scib_metrics.utils.cdist(x, y, metric='euclidean')[source]#

Jax implementation of scipy.spatial.distance.cdist().

Uses euclidean distance by default, cosine distance is also available.

Parameters:

  • x (ndarray) – Array of shape (n_cells_a, n_features)

  • y (ndarray) – Array of shape (n_cells_b, n_features)

  • metric (Literal['euclidean', 'cosine'] (default: 'euclidean')) – The distance metric to use. The distance function can be ‘euclidean’ (default) or ‘cosine’.

Return type:

Array

Returns:

dist Array of shape (n_cells_a, n_cells_b)

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