pymchelper.executor.runner module

class pymchelper.executor.runner.OutputDataType

Bases: enum.IntEnum

Output type requested by user plots (i.e .png) or text data

plot = 1

txt = 2

class pymchelper.executor.runner.Runner(jobs=None, keep_workspace_after_run=False, output_directory='.')

Bases: object

Main class responsible for configuring and starting multiple parallel MC simulation processes It can be used to access combined averaged results of the simulation.

clean()

Removes all working directories (if exists)

get_data()

Scans the output directory for location of the working directories (like run_1, run_2). Takes all files from all working directories in output_dir, merges their content to form pymchelper Estimator objects. For each of the output file a single Estimator objects is created, which holds numpy arrays with results. Return dictionary with keys being output filenames, and values being Estimator objects

run(settings)

Execute parallel simulation processes, creating workspace (and working directories) in the output_directory In case of successful execution return True, otherwise return False

class pymchelper.executor.runner.SingleSimulationExecutor

Bases: object

Callable class responsible for execution of the single MC simulation process.

class pymchelper.executor.runner.WorkspaceManager(output_directory='.', keep_workspace_after_run=False)

Bases: object

A workspace consists of multiple working directories (i.e. run_1, run_2), each per one of the parallel simulation run.

clean()

clean the workspace by removing all working directories (only if requested by keep_workspace_after_run flag)

create_working_directories(simulation_input_path, rng_seeds=())

Create working directories and fill self.working_directories_abs_paths