moscot.problems.time.TemporalProblem.compute_time_point_distances

TemporalProblem.compute_time_point_distances(source, intermediate, target, posterior_marginals=True, backend='ott', **kwargs)

Compute Wasserstein distance between time points.

See also

• TODO(MUCDK): create an example showing the usage.

Parameters:

• source (TypeVar(K, bound= Hashable)) – Key identifying the source distribution.

• intermediate (TypeVar(K, bound= Hashable)) – Key identifying the intermediate distribution.

• target (TypeVar(K, bound= Hashable)) – Key identifying the target distribution.

• posterior_marginals (bool) – Whether to use posterior_growth_rates or prior_growth_rates. TODO(MUCDK): needs more explanation

• backend (Literal['ott']) – Backend used for the distance computation.

• kwargs (Any) –

  Keyword arguments for the distance function, depending on the backend:

  • 'ott' - sinkhorn_divergence().

Return type:

tuple[float, float]

Returns:

: The distance between source and intermediate cells and intermediate and target cells, respectively.