Code Documentation

wlk(adjs: List[ndarray], labels: List[ndarray], k: int = 4, normalize: bool = False, kernel_fn: Optional[Callable] = None)

Main function implementing the logic for the WLK algorithm.

Parameters

• adjs – List of adjacency matrices

• labels – List of labels which can have any type

• k – number of iterations of the WLK algorithm, must be non-negative

• normalize – whether to normalize the kernel matrix or not

• kernel_fn – Kernel function to use. Default is dot product (if kernel_fn=None) as used in the original paper. Alternative functions can be used to compute the kernel matrix. These have to be provided as callables.

Returns

A symmetric matrix storing the pairwise metric values between graphs. Depending on the kernel function it can be distances or similarities.