PlanetAlign.algorithms.IsoRank

class IsoRank(alpha: float = 0.4, dtype: dtype = torch.float32)[source]

Bases: BaseModel

Consistency-based method IsoRank for pairwise plain network alignment. IsoRank is proposed by the paper “Global alignment of multiple protein interaction networks with application to functional orthology detection” in PNAS 2008.

Parameters:

  • alpha (float, optional) – The decay factor for the optimization. Default is 0.4.

  • dtype (torch.dtype, optional) – Data type of the tensors, choose from torch.float32 or torch.float64. Default is torch.float32.

test(dataset: Dataset, gids: List[int] | Tuple[int, ...], metrics: tuple[str] | list[str] = None)
Parameters:

  • dataset (Dataset) – The dataset containing the graphs to be aligned and the training/test data.

  • gids (list[int] or tuple[int, ...]) – The indices of the graphs in the dataset to be aligned.

  • metrics (tuple[str] or list[str], optional) – The metrics to be computed after alignment. Default is None, which computes Hits@K (K=1, 10, 30, 50) and MRR metrics.

train(dataset: Dataset, gid1: int, gid2: int, use_attr: bool = False, total_epochs: int = 100, tol: float = 1e-10, save_log: bool = True, verbose: bool = True)[source]
Parameters:

  • dataset (Dataset) – The dataset containing graphs to be aligned and the training/test data.

  • gid1 (int) – The graph id of the first graph to be aligned.

  • gid2 (int) – The graph id of the second graph to be aligned.

  • use_attr (bool, optional) – Flag for using attributes. Must be False for IsoRank. Default is False.

  • total_epochs (int, optional) – Maximum number of training epochs. Default is 100.

  • tol (float, optional) – Tolerance for convergence. Default is 1e-10.

  • save_log (bool, optional) – Flag for saving the logs. Default is True.

  • verbose (bool, optional) – Flag for printing the logs. Default is True.

Returns:

The final similarity matrix S.

Return type:

torch.Tensor