Module pyprotlinc

class pyprotolinc.RunConfig(state_model_name: str, working_directory: Path = PosixPath('.'), model_name: str = 'GenericMultiState', years_to_simulate: int = 119, steps_per_month: int = 1, portfolio_path: Optional[str] = None, assumptions_path: Optional[str] = None, outfile: str = 'ncf_out_generic.csv', portfolio_cache: Optional[str] = None, profile_out_dir: Optional[str] = None, portfolio_chunk_size: int = 20000, use_multicore: bool = False, kernel_engine: str = 'PY', max_age: int = 119)

The RunConfig object.

Parameters
  • model_name (str) – Name of the model to be used in the run.

  • years_to_simulate (int) – Max. simulation period in years.

  • steps_per_month (int) – Number of steps a month is divided into in the simulation.

  • state_model_name (str) – The name of the the states set.

  • portfolio_path (str) – Path to portfolio file

  • assumptions_path (str) – Path to assumptions config file

  • outfile (str) – Path of the results file.

  • portfolio_cache (str) – Path to the caching directory for portfolios

  • profile_out_dir (str) – Path where to store profiling output.

  • portfolio_chunk_size (int) – Size of the chunks the portfolio is broken into.

  • use_multicore (bool) – Flag to indicate if multiprocessing shall be used.

  • kernel_engine (str) – Use ‘PY’ or ‘C’ to select the Python or C++ engine

  • max_age (int) – Max. age that is used when projecting (only C++)

pyprotolinc.get_config_from_file(config_file: str) RunConfig

Returns a RunConfig object from the file.

Parameters

config_file (str) – Path to the config file to be loaded.

Returns

Configration object.

Return type

RunConfig