aequilibrae.transit

class aequilibrae.transit.Transit(project)

build_pt_preload(start: int, end: int, inclusion_cond: str = 'start') → DataFrame

Builds a preload vector for the transit network over the specified time period

Arguments:

start (int): The start of the period for which to check pt schedules (seconds from midnight)

end (int): The end of the period for which to check pt schedules, (seconds from midnight)

inclusion_cond (str): Specifies condition with which to include/exclude pt trips from the preload.

Returns:

preloads (pd.DataFrame): A DataFrame of preload from transit vehicles that can be directly used in an assignment

>>> project = create_example(project_path, "coquimbo")

>>> project.network.build_graphs()

>>> start = int(6.5 * 60 * 60) # 6:30 am
>>> end = int(8.5 * 60 * 60)   # 8:30 am

>>> transit = Transit(project)
>>> preload = transit.build_pt_preload(start, end)

>>> project.close()

create_graph(**kwargs) → TransitGraphBuilder

Create a transit graph from an existing GTFS import.

All arguments are forwarded to ‘TransitGraphBuilder’.

A ‘period_id’ may be specified to select a time period. By default, a whole day is used. See ‘project.network.Periods’ for more details.

create_transit_database()

Creates the public transport database

get_table(table_name) → DataFrame

load(period_ids: List[int] = None)

Load the previously saved transit graphs from the ‘public_transport.sqlite’ database. Loading may be filtered by ‘period_id’.

Arguments:

period_ids (int): List of periods of to load. Defaults to all available graph configurations.

new_gtfs_builder(agency, file_path, day='', description='') → GTFSRouteSystemBuilder

Returns a GTFSRouteSystemBuilder object compatible with the project

Arguments:

agency (str): Name for the agency this feed refers to (e.g. ‘CTA’)

file_path (str): Full path to the GTFS feed (e.g. ‘D:/project/my_gtfs_feed.zip’)

day (str, Optional): Service data contained in this field to be imported (e.g. ‘2019-10-04’)

description (str, Optional): Description for this feed (e.g. ‘CTA2019 fixed by John Doe’)

Returns:

gtfs_feed (StaticGTFS): A GTFS feed that can be added to this network

remove_graphs(period_ids: List[int], unload: bool = False)

Remove the previously saved transit graphs from the ‘public_transport.sqlite’ database. Removing may be filtered by ‘period_id’.

Arguments:

period_ids (int): List of periods of to save. unload (bool): Also unload the graph.

save_graphs(period_ids: List[int] = None, force: bool = False)

Save the previously build transit graphs to the ‘public_transport.sqlite’ database. Saving may be filtered by ‘period_id’.

Arguments:

period_ids (int): List of periods of to save. Defaults to

‘project.network.periods.default_period.period_id’.

force (bool): Remove the existing graphs before saving the ‘period_ids’ graphs. Default ‘False’.

default_capacities = {'other': [30, 60], 0: [150, 300], 1: [280, 560], 11: [30, 60], 12: [50, 100], 2: [700, 700], 3: [30, 60], 4: [400, 800], 5: [20, 40]}

default_pces = {'other': 2.0, 0: 5.0, 1: 5.0, 11: 3.0, 3: 4.0, 5: 4.0}

graphs: Dict[str, TransitGraph] = {}

pt_con: Connection

transit = <aequilibrae.utils.python_signal.PythonSignal object>

class aequilibrae.transit.TransitGraphBuilder(project, period_id: int = 1, time_margin: int = 0, projected_crs: str = 'EPSG:3857', num_threads: int = -1, seed: int = None, geometry_noise: bool = None, noise_coef: float = None, with_inner_stop_transfers: bool = False, with_outer_stop_transfers: bool = False, with_walking_edges: bool = True, distance_upper_bound: float = inf, blocking_centroid_flows: bool = True, connector_method: str = 'nearest_neighbour', max_connectors_per_zone: int = -1)

Graph builder for the transit assignment Spiess & Florian algorithm.

Arguments:

public_transport_conn (sqlite3.Connection): Connection to the public_transport.sqlite database.

period_id (int): Period id for the period to be used. Preferred over start and end.

time_margin (int): Time margin, extends the start and end times by time_margin ([start, end] becomes [start - time_margin, end + time_margin]), in order to include more trips when computing mean values. Defaults to 0.

projected_crs (str): Projected CRS of the network, intended for more accurate distance calculations. Defaults to EPSG:3857, Spherical Mercator.

num_threads (int): Number of threads to be used where possible. Defaults to -1 (using all available threads).

seed (int): Deprecated. No longer in use.

geometry_noise (bool): Deprecated. No longer in use.

noise_coef (float): Deprecated. No longer in use.

with_inner_stop_transfers (bool): Whether to create transfer edges within parent stations. Defaults to False.

with_outer_stop_transfers (bool): Whether to create transfer edges between parent stations. Defaults to False.

with_walking_edges (bool): Whether to create walking edges between distinct stops of each station. Defaults to True.

distance_upper_bound (float): Upper bound on connector distance. Defaults to np.inf.

blocking_centroid_flows (bool): Whether to block flow through centroids. Defaults to True.

max_connectors_per_zone (int): Maximum connectors per zone. Defaults to -1 for unlimited.

classmethod from_db(project, period_id: int, **kwargs)

Create a SF graph instance from an existing database save.

Assumes the database was constructed with the provided save methods. No checks are performed to see if the provided arguments are compatible with the saved graph.

All arguments are forwarded to the constructor.

Arguments:

project (Project): AequilbraE project to use.

period_id (int): Period ID to use.

classmethod remove(pt_conn: Connection, project_conn: Connection, period_id: int)

static remove_config(conn: Connection, period_id: int)

Remove a transit graph configuration from the project database specified by it’s period_id.

Arguments:

conn (sqlite3.Connection): Connection to the project.sqlite database.

period_id (int): period_id key for the transit_graph_configs table.

static remove_edges(pt_conn: Connection, period_id: int)

Remove a transit graph’s edges from the public transport database specified by it’s period_id.

Arguments:

pt_conn (sqlite3.Connection): Connection to the public_transport.sqlite database.

period_id (int): period_id to remove.

static remove_vertices(pt_conn: Connection, period_id: int)

Remove a transit graph’s vertices from the public transport database specified by it’s period_id.

Arguments:

pt_conn (sqlite3.Connection): Connection to the public_transport.sqlite database.

period_id (int): period_id to remove.

add_zones(zones, from_crs: str = None)

Add zones as ODs.

Arguments:

zones (pd.DataFrame): DataFrame containing the zoning information. Columns must include zone_id and geometry.

from_crs (str): The CRS of the geometry column of zones. If not provided it’s assumed that the geometry is already in self.projected_crs. If provided, the geometry will be projected to self.projected_crs. Defaults to None.

convert_demand_matrix_from_zone_to_node_ids(demand_matrix, o_zone_col='origin_zone_id', d_zone_col='destination_zone', demand_col='demand')

Convert a sparse demand matrix from zone_id’s to the corresponding node_id’s.

create_additional_db_fields(conn: Connection = None)

Create the additional required entries in the tables.

Arguments:

pt_conn (sqlite.Connection): Optional PT connection to use

create_graph()

Create the SF transit graph (vertices and edges).

create_line_geometry(method='direct', graph='w')

Create the LineString for each edge.

The direct method creates a straight line between all points.

The connect project match method uses the existing line geometry within the project to create more accurate line strings. It creates a line string that matches the path between the shortest path between the project nodes closest to either end of the access and egress connectors.

Project graphs must be built for the “connector project match” method.

Arguments:

method (str): Must be either direct or connector project match. If method is direct, graph argument is ignored.

graph (str): Must be a key within project.network.graphs.

create_od_node_mapping()

Build a dataframe mapping the centroid node ids with to transport assignment zone ids.

save(robust=True, pt_conn: Connection = None, project_conn: Connection = None)

Save the current graph to the public transport database.

Arguments:

robust (bool): Deprecated. No longer in use.

pt_conn (sqlite.Connection): Optional PT connection to use

project_conn (sqlite.Connection): Optional project connection to use

save_config(conn: Connection = None)

save_edges(recreate_line_geometry=False, conn: Connection = None)

Save the contents of self.edges to the public transport database.

If no geometry for the edges is present or recreate_line_geometry is True, direct lines will be created.

Arguments:

recreate_line_geometry (bool): Whether to recreate the line strings for the edges as direct lines. Defaults to False.

pt_conn (sqlite.Connection): Optional PT connection to use

save_vertices(robust=None, conn: Connection = None)

Write the vertices DataFrame to the public transport database.

Within the database nodes may not exist at the exact same point in space, provide robust=True to move the nodes slightly.

Arguments:

robust (bool): Deprecated. No longer in use.

pt_conn (sqlite.Connection): Optional PT connection to use

to_transit_graph() → TransitGraph

Create an AequilibraE TransitGraph object from an SF graph builder.

property config

Modules

column_order
constants
date_tools
functions
gtfs_loader
gtfs_writer
lib_gtfs
parse_csv
route_map_matcher
route_system
route_system_reader
transit
transit_elements
transit_graph_builder	Create the graph used by public transport assignment algorithms.