netcdf_player#

netcdf_player#

class NetCDFPlayer(model_config: dict)#

Bases: TrackedModel

netcdf_tape: NetCDFTape#
publish()#
publishers: List[Publisher]#
setup(state: TrackedState, schema: AttributeSchema, init_data_handler: InitDataHandler, **_)#

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

shutdown(**_)#

Called when a simulation ends (either due to it being finished or one of the models raises an exception). The model may implement this method to clean up local resources. This method may be called before the initialize and update methods have been called the first time

update(moment: Moment, **_) → 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 NetCDFTape(timeline_info: TimelineInfo | None = None)#

Bases: BaseTapefile

assert_variable(var_name)#
close()#
get_data(key)#
initialize(netcdf: Dataset)#
time_var = 'time'#
class Publisher(tape: NetCDFTape, parameter: str, target: UniformAttribute | CSRAttribute)#

Bases: object

publish()#
get_netcdf_tape(data_handler: InitDataHandler, name: str) → NetCDFTape#
get_publish_attribute(attr: str, target_entity_group: Tuple[str, str], schema: AttributeSchema, state: TrackedState)#

Module contents#

class NetCDFPlayer(model_config: dict)#

Bases: TrackedModel

netcdf_tape: NetCDFTape#
publish()#
publishers: List[Publisher]#
setup(state: TrackedState, schema: AttributeSchema, init_data_handler: InitDataHandler, **_)#

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

shutdown(**_)#

Called when a simulation ends (either due to it being finished or one of the models raises an exception). The model may implement this method to clean up local resources. This method may be called before the initialize and update methods have been called the first time

update(moment: Moment, **_) → 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