Datasets:

double-blind-anonymous
/

go-mo-dataset

# GO-MO traffic dataset source code

Here you can find code for several tasks related to the GO-MO traffic dataset:
* Exporting the road network graph to a derived line graph, where the streets/edges are transformed into vertices and 
juntctions/vertices are transformed into edges.
* Exporting the road network graph or the route graph to Pytorch Geometric data format.
* Exporting the road network graph or the route graph to a numpy adjacency matrix.

In the LargeST folder you can find code to:
* Generate data and adjacency matrix compatibles with LargeST benchmark to reproduce benchmarking experiments present in
the GO-MO paper.

	# GO-MO traffic dataset source code

	Here you can find code for several tasks related to the GO-MO traffic dataset:
	* Exporting the road network graph to a derived line graph, where the streets/edges are transformed into vertices and
	juntctions/vertices are transformed into edges.
	* Exporting the road network graph or the route graph to Pytorch Geometric data format.
	* Exporting the road network graph or the route graph to a numpy adjacency matrix.

	In the LargeST folder you can find code to:
	* Generate data and adjacency matrix compatibles with LargeST benchmark to reproduce benchmarking experiments present in
	the GO-MO paper.