seemps.analysis.cross.cross_maxvol#
- seemps.analysis.cross.cross_maxvol(black_box: BlackBox, initial_points: ndarray[tuple[Any, ...], dtype[_ScalarT]] | None = None, cross_strategy: CrossStrategyMaxvol = CrossStrategyMaxvol()) CrossResults[source]#
Computes the MPS representation of a black-box function using the tensor cross-approximation (TCI) algorithm based on one-site optimizations using the rectangular maxvol decomposition. The black-box function can represent several different structures. See black_box for usage examples.
- Parameters:
- black_box
BlackBox The black box to approximate as a MPS.
- initial_points
Optional[Matrix], default=None A collection of initial points used to initialize the algorithm. If None, the point at origin is used.
- cross_strategy
CrossStrategyMaxvol=CrossStrategyMaxvol() A dataclass containing the parameters of the algorithm.
- black_box
- Returns:
CrossResultsA dataclass containing the MPS representation of the black-box function, among other useful information.