- PenaltyModelCache.retrieve(samples_like, graph_like, *, linear_bound: Tuple[float, float] = (- 2, 2), quadratic_bound: Tuple[float, float] = (- 1, 1), min_classical_gap: float = 2) Tuple[dimod.binary.binary_quadratic_model.BinaryQuadraticModel, float] ¶
Retrieve a penalty model from the database.
The set of feasible states that form the ground states of the generated binary quadratic model.
Defines the structure of the desired binary quadratic model. Each node in the graph represents a variable and each edge defines an interaction between two variables. Can be given as a
int, or as a sequence of variable labels.
If given as a sequence of labels, the structure will be fully-connected, with the variables labelled according to the sequence.
If given as an int, the structure will be fully-connected with the variables labelled
The nodes of the graph must be a superset of the labels of
If not provided, defaults to a fully connected graph with nodes that are the variables of
linear_bound – The range allowed for the linear biases of the binary quadratic model.
quadratic_bound – The range allowed for the quadratic biases of the binary quadratic model.
min_classical_gap – This is a threshold value for the classical gap. It describes the minimum energy gap between the highest feasible state and the lowest infeasible state.
A 2-tuple of the binary quadratic model and the classical gap. Note that the binary quadratic model always has vartype