volume_creation_module

class ModelBasedAdapter(global_settings: Settings)[source]

Bases: VolumeCreationAdapterBase

The model-based volume creator uses a set of rules how to generate structures to create a simulation volume. These structures are added to the dictionary and later combined by the algorithm:

# Initialise settings dictionaries
simulation_settings = Settings()
all_structures = Settings()
structure = Settings()

# Definition of en example structure.
# The concrete structure parameters will change depending on the
# structure type
structure[Tags.PRIORITY] = 1
structure[Tags.STRUCTURE_START_MM] = [0, 0, 0]
structure[Tags.STRUCTURE_END_MM] = [0, 0, 100]
structure[Tags.MOLECULE_COMPOSITION] = TISSUE_LIBRARY.muscle()
structure[Tags.CONSIDER_PARTIAL_VOLUME] = True
structure[Tags.ADHERE_TO_DEFORMATION] = True
structure[Tags.STRUCTURE_TYPE] = Tags.HORIZONTAL_LAYER_STRUCTURE

all_structures["arbitrary_identifier"] = structure

simulation_settings[Tags.STRUCTURES] = all_structures

# ...
# Define further simulation settings
# ...

simulate(simulation_settings)

Parameters:: global_settings (Settings) – The SIMPA settings dictionary

create_simulation_volume() → dict[source]

This method creates an in silico representation of a tissue as described in the settings file that is given.

Returns:: A dictionary containing optical and acoustic properties as well as other characteristics of the simulated volume such as oxygenation, and a segmentation mask. All of these are given as 3d numpy arrays.
Return type:: dict

class SegmentationBasedAdapter(global_settings: Settings)[source]

Bases: VolumeCreationAdapterBase

This volume creator expects a np.ndarray to be in the settings under the Tags.INPUT_SEGMENTATION_VOLUME tag and uses this array together with a SegmentationClass mapping which is a dict defined in the settings under Tags.SEGMENTATION_CLASS_MAPPING.

With this, an even greater utility is warranted.

Parameters:: global_settings (Settings) – The SIMPA settings dictionary

create_simulation_volume() → dict[source]

This method creates an in silico representation of a tissue as described in the settings file that is given.

Returns:: A dictionary containing optical and acoustic properties as well as other characteristics of the simulated volume such as oxygenation, and a segmentation mask. All of these are given as 3d numpy arrays.
Return type:: dict

class VolumeCreationAdapterBase(global_settings: Settings)[source]

Bases: SimulationModuleBase

Use this class to define your own volume creation adapter.

Parameters:: global_settings (Settings) – The SIMPA settings dictionary

create_empty_volumes()[source]

abstract create_simulation_volume() → dict[source]

This method creates an in silico representation of a tissue as described in the settings file that is given.

Returns:: A dictionary containing optical and acoustic properties as well as other characteristics of the simulated volume such as oxygenation, and a segmentation mask. All of these are given as 3d numpy arrays.
Return type:: dict

load_component_settings() → Settings[source]

Implements abstract method to serve volume creation settings as component settings

Returns:: Settings: volume creation component settings

run(device)[source]

Executes the respective simulation module

Parameters:: digital_device_twin – The digital twin that can be used by the digital device_twin.