moscot.base.problems.CompoundProblem.prepare¶
- CompoundProblem.prepare(policy, key, subset=None, reference=None, xy=mappingproxy({}), x=mappingproxy({}), y=mappingproxy({}), xy_callback=None, x_callback=None, y_callback=None, xy_callback_kwargs=mappingproxy({}), x_callback_kwargs=mappingproxy({}), y_callback_kwargs=mappingproxy({}), a=None, b=None, marginal_kwargs=mappingproxy({}))¶
Prepare the individual OT subproblems.
See also
See Subset policy on how to use different policies.
- Parameters:
policy (
Literal
['sequential'
,'star'
,'external_star'
,'explicit'
,'triu'
,'tril'
]) – Rule which defines how to construct the subproblems.key (
Optional
[str
]) – Key inobs
for theSubsetPolicy
.subset (
Optional
[Sequence
[Tuple
[TypeVar
(K
, bound=Hashable
),TypeVar
(K
, bound=Hashable
)]]]) – Subset ofobs['{key}']
for theExplicitPolicy
. Only used whenpolicy = 'explicit'
.reference (
Optional
[Any
]) – Reference for theSubsetPolicy
. Only used whenpolicy = 'star'
.xy (
Mapping
[str
,Any
]) – Data for the linear term.x (
Mapping
[str
,Any
]) – Data for the source quadratic term.y (
Mapping
[str
,Any
]) – Data for the target quadratic term.xy_callback (
Union
[Literal
['local-pca'
],Callable
[[Literal
['xy'
,'x'
,'y'
],AnnData
,Optional
[AnnData
]],Optional
[TaggedArray
]],None
]) – Callback function used to prepare the data in the linear term.x_callback (
Union
[Literal
['local-pca'
],Callable
[[Literal
['xy'
,'x'
,'y'
],AnnData
,Optional
[AnnData
]],Optional
[TaggedArray
]],None
]) – Callback function used to prepare the data in the source quadratic term.y_callback (
Union
[Literal
['local-pca'
],Callable
[[Literal
['xy'
,'x'
,'y'
],AnnData
,Optional
[AnnData
]],Optional
[TaggedArray
]],None
]) – Callback function used to prepare the data in the target quadratic term.xy_callback_kwargs (
Mapping
[str
,Any
]) – Keyword arguments for thexy_callback
.x_callback_kwargs (
Mapping
[str
,Any
]) – Keyword arguments for thex_callback
.y_callback_kwargs (
Mapping
[str
,Any
]) – Keyword arguments for they_callback
.a (
Union
[bool
,str
,ndarray
[Any
,dtype
[float64
]],None
]) –Source marginals. Valid options are:
b (
Union
[bool
,str
,ndarray
[Any
,dtype
[float64
]],None
]) –Target marginals. Valid options are:
marginal_kwargs (
Mapping
[str
,Any
]) – Keyword arguments for theestimate_marginals()
method.
- Return type:
BaseCompoundProblem
[TypeVar
(K
, bound=Hashable
),TypeVar
(B
, bound=OTProblem
)]- Returns:
: Returns self and updates the following fields: