SolveSpec

class cubie.batchsolving.solveresult.SolveSpec(dt: float | None, dt_min: float, dt_max: float, save_every: float | None, summarise_every: float | None, sample_summaries_every: float | None, atol: float | None, rtol: float | None, duration: float, warmup: float, t0: float, algorithm: str, saved_states: List[str] | None, saved_observables: List[str] | None, summarised_states: List[str] | None, summarised_observables: List[str] | None, output_types: List[str] | None, precision: type[float16] | type[float32] | type[float64] | dtype[float16] | dtype[float32] | dtype[float64])

Bases: object

Describe the configuration of a solver run.

dt_min

Minimum time step size.

Type:

float

dt_max

Maximum time step size.

Type:

float

save_every

Interval at which state values are stored.

Type:

float | None

summarise_every

Interval for computing summary outputs.

Type:

float | None

sample_summaries_every

Interval for sampling summary metric updates.

Type:

float | None

atol

Absolute error tolerance when configured.

Type:

float | None

rtol

Relative error tolerance when configured.

Type:

float | None

duration

Total integration time.

Type:

float

warmup

Initial warm-up period prior to recording outputs.

Type:

float

t0

Initial integration time supplied to the solver.

Type:

float

algorithm

Name of the integration algorithm.

Type:

str

saved_states

Labels of states saved verbatim or None when disabled.

Type:

List[str] | None

saved_observables

Labels of observables saved verbatim or None when disabled.

Type:

List[str] | None

summarised_states

Labels of states with summaries computed or None when disabled.

Type:

List[str] | None

summarised_observables

Labels of observables with summaries computed or None when disabled.

Type:

List[str] | None

output_types

Types of output arrays generated during the run or None.

Type:

List[str] | None

precision

Floating-point precision factory used for host conversions.

Type:

type[numpy.float16] | type[numpy.float32] | type[numpy.float64] | numpy.dtype[numpy.float16] | numpy.dtype[numpy.float32] | numpy.dtype[numpy.float64]

algorithm: str

atol: float | None

dt: float | None

dt_max: float

dt_min: float

duration: float

output_types: List[str] | None

precision: type[float16] | type[float32] | type[float64] | dtype[float16] | dtype[float32] | dtype[float64]

rtol: float | None

sample_summaries_every: float | None

save_every: float | None

saved_observables: List[str] | None

saved_states: List[str] | None

summarise_every: float | None

summarised_observables: List[str] | None

summarised_states: List[str] | None

t0: float

warmup: float