Scheduler

class Scheduler[ValueType]

A Finite Memory Scheduler

Template arguments:

• ValueType (type)

Available specializations:

• Scheduler[float]

• Scheduler[stormpy.numbers.Rational]

• Scheduler[stormpy.numbers.Interval]

• Scheduler[stormpy.numbers.RationalInterval]

• Scheduler[stormpy.numbers.RationalFunction]

Construction

The default specialization is Scheduler[float].

Members

Scheduler.compute_action_support(

self: stormpy.models.Scheduler[ValueType],

nondeterministic_choice_indices: collections.abc.Sequence[SupportsInt | SupportsIndex],

) → stormpy.datastructures.BitVector

property Scheduler.deterministic

Is the scheduler deterministic?

Scheduler.get_choice(

self: stormpy.models.Scheduler[ValueType],

state_index: SupportsInt | SupportsIndex,

memory_index: SupportsInt | SupportsIndex = 0,

)

Scheduler.get_memoryless_scheduler_for_memory_state(

self: stormpy.models.Scheduler[ValueType],

memory_state: SupportsInt | SupportsIndex = 0,

) → stormpy.models.Scheduler[ValueType]

Get the memoryless scheduler corresponding to the given memory state

property Scheduler.memory_size

How much memory does the scheduler take?

property Scheduler.memoryless

Is the scheduler memoryless?

property Scheduler.partial

Is the scheduler partial?

Scheduler.set_choice(

self: stormpy.models.Scheduler[ValueType],

choice,

state: SupportsInt | SupportsIndex,

memory_index: SupportsInt | SupportsIndex = 0,

) → None

Scheduler.to_json_str(

self: stormpy.models.Scheduler[ValueType],

model: stormpy.models.SparseModel[ValueType],

skip_unique_choices: bool = False,

skip_dont_care_states: bool = False,

) → str

Scheduler.to_str(

self: stormpy.models.Scheduler[ValueType],

model: stormpy.models.SparseModel[ValueType] = None,

skip_unique_choices: bool = False,

skip_dont_care_states: bool = False,

) → str

Scheduler.to_value_type(

self: stormpy.models.Scheduler,

value_type: type = float,

) → stormpy.models.Scheduler

Convert a scheduler’s choice probabilities to another value type.

Parameters:

value_type – Target numeric type, such as float or stormpy.Rational.

Returns:

A new scheduler using the requested numeric type.

Raises:

TypeError – If conversion between the selected types is unsupported.