aequilibrae.paths.traffic_class

Classes

TrafficClass(name, graph, matrix)	Traffic class for equilibrium traffic assignment
TransitClass(name, graph, matrix)
TransportClassBase(name, graph, matrix)

class aequilibrae.paths.traffic_class.TrafficClass(name: str, graph: Graph, matrix: AequilibraeMatrix)

Traffic class for equilibrium traffic assignment

>>> from aequilibrae.paths import TrafficClass

>>> project = create_example(project_path)
>>> project.network.build_graphs()

>>> graph = project.network.graphs['c'] # we grab the graph for cars
>>> graph.set_graph('free_flow_time') # let's say we want to minimize time
>>> graph.set_skimming(['free_flow_time', 'distance']) # And will skim time and distance
>>> graph.set_blocked_centroid_flows(False)

>>> proj_matrices = project.matrices

>>> demand = proj_matrices.get_matrix("demand_omx")
>>> demand.computational_view()

>>> tc = TrafficClass("car", graph, demand)
>>> tc.set_pce(1.3)

>>> project.close()

set_fixed_cost(field_name: str, multiplier=1)

Sets value of time

Arguments:

field_name (str): Name of the graph field with fixed costs for this class

multiplier (Union[float, int]): Multiplier for the fixed cost. Defaults to 1 if not set

set_pce(pce: float | int) → None

Sets Passenger Car equivalent

Arguments:

pce (Union[float, int]): PCE. Defaults to 1 if not set

set_select_links(links: Dict[str, List[Tuple[int, int]]])

Set the selected links. Checks if the links and directions are valid. Translates link_id and direction into unique link id used in compact graph. Supply links=None to disable select link analysis.

Arguments:

links (Union[None, Dict[str, List[Tuple[int, int]]]]): name of link set and Link IDs and directions to be used in select link analysis

set_vot(value_of_time: float) → None

Sets value of time

Arguments:

value_of_time (Union[float, int]): Value of time. Defaults to 1 if not set

skim_congested(skim_fields=None)

Skims the congested network. The user can add a list of skims to be computed, which will be added to the congested time and the assignment cost from the last iteration of the assignment.

Arguments:

skim_fields (Union[None, str]): Name of the skims to use. If None, uses default only

property info: dict

class aequilibrae.paths.traffic_class.TransitClass(name: str, graph: TransitGraph, matrix: AequilibraeMatrix)

set_demand_matrix_core(core: str)

Set the matrix core to use for demand.

Arguments:

core (str):

property info: dict

class aequilibrae.paths.traffic_class.TransportClassBase(name: str, graph: GraphBase, matrix: AequilibraeMatrix)

property info: dict