AirfRANS_clipped

This dataset is a new version of the dataset originally made available through the library and described in the paper. It has 3 main differences: it is in PLAID format all meshes were clipped in a box [-2, 4] x [-1.5, 1.5] and converted to triangular meshes thanks to Paraview A ML4PhySim_Challenge_train split is provided, corresponding to the training set of the ML4PhySim challenge It has 2 variants: AirfRANS_remeshed AirfRANS_original Tips to access the data: After decompressing the downloaded file: from plaid.containers.dataset import Datasetfrom plaid.problem_definition import ProblemDefinition dataset = Dataset()problem = ProblemDefinition() problem._load_from_dir_(os.path.join(/path/to/data,'problem_definition'))dataset._load_from_dir_(os.path.join(/path/to/data,'dataset'), verbose = True) print("problem =", problem)print("dataset =", dataset) sample = dataset[0]print("sample =", sample) for fn in sample.get_field_names(): print(f"{fn} =", sample.get_field(fn))for sn in sample.get_scalar_names(): print(f"{sn} =", sample.get_scalar(sn)) print("nodes =", sample.get_nodes())print("elements =", sample.get_elements())print("nodal_tags =", sample.get_nodal_tags())