neuralop.data.datasets.burgers.Burgers1dTimeDataset

class neuralop.data.datasets.burgers.Burgers1dTimeDataset(root_dir: Path | str, n_train: int, n_tests: list[int], train_resolution: int = 16, test_resolutions: List[int] = [16], batch_size: int = 32, test_batch_sizes: List[int] = 32, temporal_subsample: int | None = None, spatial_subsample: int | None = None, pad: int = 0)[source]

Burgers1dTimeDataset wraps data from the viscous Burger’s equation in 1 spatial dimension. This dataset is not available for download online, but we provide a low-res version on 16 spatial points

Parameters:

root_dirUnion[Path, str]

root at which to download data files

n_trainint

number of train instances

n_testsList[int]

number of test instances per test dataset

batch_sizeint

batch size of training set

test_batch_sizesList[int]

batch size of test sets

train_resolutionint

resolution of data for training set

test_resolutionsList[int], optional

resolution of data for testing sets, by default [16]

temporal_subsampleint, optional

rate at which to subsample the temporal dimension, by default None

spatial_subsampleint, optional

rate at which to subsample along the spatial dimension, by default None

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