shortest_path#

model#

class NetworkCalculator(input_attribute: 'UniformAttribute', output_attribute: 't.Union[CSRAttribute, UniformAttribute]', single_source_entity_resolver: 't.Optional[t.Callable[[], int]]' = None, network: 't.Optional[Network]' = None)#

Bases: object

initialize(network: Network)#
input_attribute: UniformAttribute#
network: Network | None = None#
no_path_found: int | None = None#
output_attribute: CSRAttribute | UniformAttribute#
single_source_entity_resolver: Callable[[], int] | None = None#
source_entity: int | None = None#
update(weights=None)#
class ShortestPathModel(model_config)#

Bases: TrackedModel

calculators: List[NetworkCalculator]#
cost_factor: UniformAttribute#
entity_groups: NetworkEntities#
initialize(**_)#

The initialize method is called when all of the state’s INIT attribute arrays are filled with data. This may be during the model engines initialization phase or during t=0. Data that is required for the model to initialize attribute may be published in another model’s t0-update, and the TrackedModelAdapter can wait for this to happen before calling initialize. When the simulation progresses to t>0 before the model’s INIT attributes have been filled, an Exception is raised, indicating that the model was not ready yet.

Model.initialize may raise NotReady to indicate that it does not have its required input data yet. This is for example useful if a model has a number OPT`ional required attributes of which at least one must be set. The model would check whether this is the case, and raise `NotReady if it is not. Once a model has succesfully run its initialize method, this method will not be called again for the duration of the simulation.

Parameters:

state – The model’s TrackedState object, managed by the TrackedModelAdapter

network: Network | None = None#
no_update_shortest_path: bool = False#
resolve_entity_by_id(entity_id: int) → int#
resolve_entity_by_ref(ref: str) → int#
setup(state: TrackedState, schema: AttributeSchema, **_)#

In setup, a model receives a state object, it’s config and other parameters. The goal of setup is to prepare the state by giving it information of the attributes it needs to track (by subscribing (INIT/SUB/OPT) or publishing (PUB) attributes) from which datasets. These attributes may be grouped together in EntityGroup classes or created directly. The main entry points for registering are:

  • state.add_dataset() for registering a bunch of EntityGroup classes for a certain dataset name at once

  • state.add_entity_group() for registering a single EntityGroup class (or instance) for a dataset name

  • state.register_attribute() for registering a single attribute in a dataset/entity_group combination

During setup there is no data available in the state. These will be downloaded automatically by the TrackedModelAdapter. However, additional datasets may be requested directly through the init_data_handler parameter.

Parameters:

  • state – The model’s TrackedState object, managed by the TrackedModelAdapter

  • settings – global settings

  • schema – The AttributeSchema with all registered attributes

  • init_data_handler – an InitDataHandler that may be used to retrieve additional datasets

  • logger – a logging.Logger instance

setup_calculators(schema: AttributeSchema)#
single_source_entity_resolver(entity_id: int | None, entity_ref: str | None)#
update(**_) → Moment | None#

The update method is called for every update coming from the model engine. However it is only called the first time once all PUB attributes have their arrays filled with data. When the simulation progresses to t>0 before the model’s SUB attributes have been filled, an Exception is raised, indicating that the model was not ready yet.

Parameters:

  • state – The model’s TrackedState object, managed by the TrackedModelAdapter

  • moment – The current simulation Moment

Returns:

an optional Moment indicating the next time a model want to be woken up, as per the model engine’s protocol

class SumCalculator(input_attribute: UniformAttribute, output_attribute: CSRAttribute | UniformAttribute, single_source_entity_resolver: Callable[[], int] | None = None, network: Network | None = None)#

Bases: NetworkCalculator

update(weights=None)#
update_for_all_sources()#
update_for_single_source()#
class WeightedAverageCalculator(input_attribute: UniformAttribute, output_attribute: CSRAttribute | UniformAttribute, single_source_entity_resolver: Callable[[], int] | None = None, network: Network | None = None)#

Bases: NetworkCalculator

update(weights=None)#
update_for_all_sources(weights)#
update_for_single_source(weights)#
convert_v1_v2(config)#

Module contents#

class ShortestPathModel(model_config)#

Bases: TrackedModel

calculators: List[NetworkCalculator]#
cost_factor: UniformAttribute#
entity_groups: NetworkEntities#
initialize(**_)#

The initialize method is called when all of the state’s INIT attribute arrays are filled with data. This may be during the model engines initialization phase or during t=0. Data that is required for the model to initialize attribute may be published in another model’s t0-update, and the TrackedModelAdapter can wait for this to happen before calling initialize. When the simulation progresses to t>0 before the model’s INIT attributes have been filled, an Exception is raised, indicating that the model was not ready yet.

Model.initialize may raise NotReady to indicate that it does not have its required input data yet. This is for example useful if a model has a number OPT`ional required attributes of which at least one must be set. The model would check whether this is the case, and raise `NotReady if it is not. Once a model has succesfully run its initialize method, this method will not be called again for the duration of the simulation.

Parameters:

state – The model’s TrackedState object, managed by the TrackedModelAdapter

network: Network | None = None#
no_update_shortest_path: bool = False#
resolve_entity_by_id(entity_id: int) → int#
resolve_entity_by_ref(ref: str) → int#
setup(state: TrackedState, schema: AttributeSchema, **_)#

In setup, a model receives a state object, it’s config and other parameters. The goal of setup is to prepare the state by giving it information of the attributes it needs to track (by subscribing (INIT/SUB/OPT) or publishing (PUB) attributes) from which datasets. These attributes may be grouped together in EntityGroup classes or created directly. The main entry points for registering are:

  • state.add_dataset() for registering a bunch of EntityGroup classes for a certain dataset name at once

  • state.add_entity_group() for registering a single EntityGroup class (or instance) for a dataset name

  • state.register_attribute() for registering a single attribute in a dataset/entity_group combination

During setup there is no data available in the state. These will be downloaded automatically by the TrackedModelAdapter. However, additional datasets may be requested directly through the init_data_handler parameter.

Parameters:

  • state – The model’s TrackedState object, managed by the TrackedModelAdapter

  • settings – global settings

  • schema – The AttributeSchema with all registered attributes

  • init_data_handler – an InitDataHandler that may be used to retrieve additional datasets

  • logger – a logging.Logger instance

setup_calculators(schema: AttributeSchema)#
single_source_entity_resolver(entity_id: int | None, entity_ref: str | None)#
update(**_) → Moment | None#

The update method is called for every update coming from the model engine. However it is only called the first time once all PUB attributes have their arrays filled with data. When the simulation progresses to t>0 before the model’s SUB attributes have been filled, an Exception is raised, indicating that the model was not ready yet.

Parameters:

  • state – The model’s TrackedState object, managed by the TrackedModelAdapter

  • moment – The current simulation Moment

Returns:

an optional Moment indicating the next time a model want to be woken up, as per the model engine’s protocol