neuralop.data.datasets.darcy.DarcyDataset

class neuralop.data.datasets.darcy.DarcyDataset(root_dir: Path | str, n_train: int, n_tests: List[int], batch_size: int, test_batch_sizes: List[int], train_resolution: int, test_resolutions: int = [16, 32], encode_input: bool = False, encode_output: bool = True, encoding='channel-wise', channel_dim=1, subsampling_rate=None, download: bool = True)[source]

DarcyDataset stores data generated according to Darcy’s Law. Input is a coefficient function and outputs describe flow.

Data source: https://zenodo.org/records/10994262

Attributes:

train_db: torch.utils.data.Dataset of training examples

test_db: “” of test examples

data_processor: neuralop.data.transforms.DataProcessor to process data examples

optional, default is None