immuneML.workflows.instructions.ligo_simulation package

Submodules

immuneML.workflows.instructions.ligo_simulation.LigoSimInstruction module

class immuneML.workflows.instructions.ligo_simulation.LigoSimInstruction.LigoSimInstruction(simulation: SimConfig, signals: List[Signal], name: str, sequence_batch_size: int, max_iterations: int, number_of_processes: int, export_p_gens: bool = None)[source]

Bases: Instruction

LIgO simulation instruction creates a synthetic dataset from scratch based on the generative model and a set of signals provided by the user.

Specification arguments:

  • simulation (str): a name of a simulation object containing a list of SimConfigItem as specified under definitions key; defines how to combine signals with simulated data; specified under definitions

  • sequence_batch_size (int): how many sequences to generate at once using the generative model before checking for signals and filtering

  • max_iterations (int): how many iterations are allowed when creating sequences

  • export_p_gens (bool): whether to compute generation probabilities (if supported by the generative model) for sequences and include them as part of output

  • number_of_processes (int): determines how many simulation items can be simulated in parallel

YAML specification:

instructions:
    my_simulation_instruction: # user-defined name of the instruction
        type: LIgOSim # which instruction to execute
        simulation: sim1
        sequence_batch_size: 1000
        max_iterations: 1000
        export_p_gens: False
        number_of_processes: 4
MIN_RANGE_PROBABILITY = 1e-05
property annotation_fields
property custom_fields
run(result_path: Path)[source]
property sequence_type: SequenceType

Module contents