NetworkSettings

settings activitysim.core.configuration.NetworkSettings

Network level of service and skims settings

The input for these settings is typically stored in one YAML file, usually called network_los.yaml.

Fields:

• TVPB_SETTINGS (Any)

• demographic_segments (Any)

• maz (str)

• maz_to_maz (activitysim.core.configuration.network.MazToMazSettings | None)

• maz_to_tap (dict[str, typing.Any])

• name (str)

• network_cache_dir (str)

• read_skim_cache (bool)

• rebuild_tvpb_cache (bool)

• skim_dict_factory (Literal['NumpyArraySkimFactory', 'MemMapSkimFactory'])

• skim_time_periods (activitysim.core.configuration.network.TimeSettings)

• source_file_paths (list[pathlib.Path])

• tap (str)

• tap_lines (str)

• tap_skims (Union[str, list[str]])

• taz_skims (Union[str, list[str], activitysim.core.configuration.network.TAZ_Settings])

• trace_tvpb_cache_as_csv (bool)

• write_skim_cache (bool)

• zone_system (int)

field TVPB_SETTINGS: Any = None

field demographic_segments: Any = None

field maz: str = None

Filename for the MAZ data file.

This file should contain the MAZ ID, TAZ, and land use and other MAZ attributes

field maz_to_maz: activitysim.core.configuration.network.MazToMazSettings | None = None

Settings to manage maz-to-maz level of service in 2- and 3-zone models.

field maz_to_tap: dict[str, Any] = None

Settings to manage maz-to-tap level of service in 3-zone models.

field name: str = None

Name of this network, not used for anything?

field network_cache_dir: str = None

alternate dir to read/write cache files (defaults to output_dir)

field read_skim_cache: bool = False

Read cached skims (using numpy memmap) from output directory.

Reading from memmap is much faster than omx, but the memmap is a huge uncompressed file.

field rebuild_tvpb_cache: bool = True

rebuild and overwrite existing pre-computed TAP to TAP utilities cache

field skim_dict_factory: Literal['NumpyArraySkimFactory', 'MemMapSkimFactory'] = 'NumpyArraySkimFactory'

The skim dict factory to use.

The MemMapSkimFactory is strictly experimental.

field skim_time_periods: TimeSettings [Required]

How to discretize time in this model.

field source_file_paths: list[Path] = None

A list of source files from which these settings were loaded.

This value should not be set by the user within the YAML settings files, instead it is populated as those files are loaded. It is primarily provided for debugging purposes, and does not actually affect the operation of the model.

field tap: str = None

Filename for the TAP data file.

This file should contain the MAZ ID, TAZ, and land use and other MAZ attributes

field tap_lines: str = None

TAP lines filename.

field tap_skims: Union[str, list[str]] = None

field taz_skims: Union[str, list[str], TAZ_Settings] = None

Instructions for how to load and pre-process skim matrices.

If given as a string or a list of strings, it is interpreted as the location for OMX file(s), either as a single file or as a glob-matching pattern for multiple files. The time period for the matrix must be represented at the end of the matrix name and be seperated by a double_underscore (e.g. BUS_IVT__AM indicates base skim BUS_IVT with a time period of AM.

Alternatively, this can be given as a nested dictionary defined via the TAZ_Settings class, which allows for ZARR transformation and pre-processing.

field trace_tvpb_cache_as_csv: bool = False

Write a CSV version of TVPB cache for tracing

Not currently implemented.

field write_skim_cache: bool = False

Write memmapped cached skims to output directory.

This is needed if you want to use the cached skims to speed up subsequent runs.

field zone_system: int [Required]

Which zone system type is used.

• 1 - TAZ only.

• 2 - MAZ and TAZ.

• 3 - MAZ, TAZ, and TAP