moscot.problems.spatiotemporal.SpatioTemporalProblem.compute_time_point_distances¶
- SpatioTemporalProblem.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 useposterior_growth_rates
orprior_growth_rates
. TODO(MUCDK): needs more explanationbackend (
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:
- Returns:
: The distance between
source
andintermediate
cells andintermediate
andtarget
cells, respectively.