dimod.Initialized.parse_initial_states#

Initialized.parse_initial_states(bqm: BinaryQuadraticModel, initial_states: Sequence[float | floating | integer] | Mapping[Hashable, float | floating | integer] | Tuple[Sequence[float | floating | integer], Sequence[Hashable]] | Tuple[ndarray, Sequence[Hashable]] | ndarray | Sequence[Sequence[float | floating | integer]] | Tuple[Sequence[Sequence[float | floating | integer]], Sequence[Hashable]] | Sequence[Sequence[float | floating | integer] | Mapping[Hashable, float | floating | integer] | Tuple[Sequence[float | floating | integer], Sequence[Hashable]] | Tuple[ndarray, Sequence[Hashable]] | ndarray] | Iterator[Sequence[float | floating | integer] | Mapping[Hashable, float | floating | integer] | Tuple[Sequence[float | floating | integer], Sequence[Hashable]] | Tuple[ndarray, Sequence[Hashable]] | ndarray] | None = None, initial_states_generator: Literal['none', 'tile', 'random'] = 'random', num_reads: int | None = None, seed: int | None = None, copy_always: bool = False) ParsedInputs[source]#

Parse or generate initial states for an initialized sampler.

Parameters:
  • bqm – Binary quadratic model.

  • initial_states (samples-like) – One or more samples, each defining an initial state for all the problem variables. Initial states are given one per read, but if fewer than num_reads initial states are defined, additional values are generated as specified by initial_states_generator. See func:dimod.as_samples for a description of “samples-like”.

  • initial_states_generator

    Defines the expansion of initial_states if fewer than num_reads are specified:

    • ”none”:

      If the number of initial states specified is smaller than num_reads, raises ValueError.

    • ”tile”:

      Reuses the specified initial states if fewer than num_reads or truncates if greater.

    • ”random”:

      Expands the specified initial states with randomly generated states if fewer than num_reads or truncates if greater.

  • num_reads – Number of reads. Defaults to the number of initial states, if initial_states is specified, or to 1, if not.

  • seed – 32-bit unsigned integer seed to use for the PRNG. Specifying a particular seed with a constant set of parameters produces identical results. If not provided, a random seed is chosen.

  • copy_always – If True, initial_states is always copied; otherwise it is copied only if necessary.

Returns:

A named tuple with ['initial_states', 'initial_states_generator', 'num_reads', 'seed'] as generated by this function.