torch_geometric.datasets.NeuroGraphDataset

class NeuroGraphDataset(root: str, name: str, transform: Optional[Callable] = None, pre_transform: Optional[Callable] = None, pre_filter: Optional[Callable] = None, force_reload: bool = False)[source]

Bases: InMemoryDataset

The NeuroGraph benchmark datasets from the “NeuroGraph: Benchmarks for Graph Machine Learning in Brain Connectomics” paper. NeuroGraphDataset holds a collection of five neuroimaging graph learning datasets that span multiple categories of demographics, mental states, and cognitive traits. See the documentation and the Github for more details.

Dataset

#Graphs

Task

HCPActivity

7,443

Graph Classification

HCPGender

1,078

Graph Classification

HCPAge

1,065

Graph Classification

HCPFI

1,071

Graph Regression

HCPWM

1,078

Graph Regression
Parameters:

  • root (str) – Root directory where the dataset should be saved.

  • name (str) – The name of the dataset (one of "HCPGender", "HCPActivity", "HCPAge", "HCPFI", "HCPWM").

  • transform (callable, optional) – A function/transform that takes in an torch_geometric.data.Data object and returns a transformed version. The data object will be transformed before every access. (default: None)

  • pre_transform (callable, optional) – A function/transform that takes in an torch_geometric.data.Data object and returns a transformed version. The data object will be transformed before being saved to disk. (default: None)

  • pre_filter (callable, optional) – A function that takes in an torch_geometric.data.Data object and returns a boolean value, indicating whether the data object should be included in the final dataset. (default: None)

  • force_reload (bool, optional) – Whether to re-process the dataset. (default: False)