moscot.base.problems.OTProblem#

class moscot.base.problems.OTProblem(adata, adata_tgt=None, src_obs_mask=None, tgt_obs_mask=None, src_var_mask=None, tgt_var_mask=None, src_key=None, tgt_key=None)[source]#

Base class for all OT problems.

Parameters:

adata (AnnData) – Source annotated data object.
adata_tgt (Optional[AnnData]) – Target annotated data object. If None, use adata.
src_obs_mask (Optional[ndarray[Any, dtype[float64]]]) – Source observation mask that defines adata_src.
tgt_obs_mask (Optional[ndarray[Any, dtype[float64]]]) – Target observation mask that defines adata_tgt.
src_var_mask (Optional[ndarray[Any, dtype[float64]]]) – Source variable mask that defines adata_src.
tgt_var_mask (Optional[ndarray[Any, dtype[float64]]]) – Target variable mask that defines adata_tgt.
src_key (Optional[Any]) – Source key name, usually supplied by the BaseCompoundProblem.
tgt_key (Optional[Any]) – Target key name, usually supplied by the BaseCompoundProblem.

Notes

If source/target mask is specified, adata_src/adata_tgt will be a view.

Methods

`estimate_marginals`(adata, , source, *kwargs)	Estimate the source or target marginals.
`load`(path)	Load the model from a file.
`prepare`(xy, x, y[, a, b])	Prepare the OT problem.
`pull`([data, subset, normalize, split_mass, ...])	Pull data through the `transport_matrix`.
`push`([data, subset, normalize, split_mass, ...])	Push data through the `transport_matrix`.
`save`(path[, overwrite])	Save the problem to a file.
`set_graph_x`(data[, cost, t])	Set a graph for the source quadratic term.
`set_graph_xy`(data[, cost, t])	Set a graph for the linear term for graph based distances.
`set_graph_y`(data[, cost, t])	Set a graph for the target quadratic term.
`set_solution`(solution, *[, overwrite])	Set a `solution` to the OT problem.
`set_x`(data, tag)	Set a cost/kernel matrix for the source quadratic term.
`set_xy`(data, tag)	Set a cost/kernel matrix for the linear term.
`set_y`(data, tag)	Set a cost/kernel matrix for the target quadratic term.
`solve`([backend, device])	Solve the OT problem.

Attributes

`a`	Source marginals.
`adata_src`	Source annotated data object.
`adata_tgt`	Target annotated data object.
`b`	Target marginals.
`problem_kind`	Kind of the underlying problem.
`shape`	Shape of the OT problem.
`solution`	Solution of the OT problem.
`solver`	OT solver.
`stage`	Problem stage.
`x`	Geometry defining the source quadratic term.
`xy`	Geometry defining the linear term.
`y`	Geometry defining the target quadratic term.