mappymatch.constructs.road

mappymatch.constructs.road#

Classes

Road(road_id, geom[, metadata])

Represents a road segment in the road network that can be matched to GPS trajectories.

RoadId(start, end, key)

class mappymatch.constructs.road.RoadId(start, end, key)[source]#
start: int | str | None#

Alias for field number 0

end: int | str | None#

Alias for field number 1

key: int | str | None#

Alias for field number 2

to_string() → str[source]#
to_json() → Dict[str, Any][source]#
classmethod from_string(s: str) → RoadId[source]#
classmethod from_json(json: Dict[str, Any]) → RoadId[source]#
class mappymatch.constructs.road.Road(road_id: RoadId, geom: LineString, metadata: dict | None = None)[source]#

Represents a road segment in the road network that can be matched to GPS trajectories.

A Road is an immutable object representing a directional edge in a road network graph. Roads have a unique identifier (composed of start/end junctions and a key), a geometry (typically a LineString), and optional metadata for storing additional attributes like speed limits, road names, etc.

Attributes:

road_id: A RoadId tuple uniquely identifying this road segment (start, end, key) geom: The Shapely LineString geometry representing the road's path metadata: An optional dictionary for storing additional road attributes such as speed limits, road names, surface type, etc.

road_id: RoadId#

Alias for field number 0

geom: LineString#

Alias for field number 1

metadata: dict | None#

Alias for field number 2

to_dict() → Dict[str, Any][source]#

Convert the road to a dictionary representation.

This creates a dictionary with all road attributes, extracting the origin and destination junction IDs from the road_id for convenience.

Returns:

A dictionary containing the road's attributes with separate keys for origin_junction_id, destination_junction_id, and road_key

to_flat_dict() → Dict[str, Any][source]#

Convert the road to a flat dictionary with metadata unpacked.

This method creates a single-level dictionary by unpacking the metadata dictionary and merging it with the road's other attributes. This is useful for creating DataFrames or exporting to formats that don't support nested structures.

Returns:

A flat dictionary with all road attributes and metadata fields at the top level. The 'metadata' key itself is removed.

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