# SPDX-FileCopyrightText: Copyright (c) 2023 - 2024 NVIDIA CORPORATION & AFFILIATES. # SPDX-FileCopyrightText: All rights reserved. # SPDX-License-Identifier: Apache-2.0 # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """ This is the datapipe to read OpenFoam files (vtp/vtu/stl) and save them as point clouds in npy format. """ import time, random from collections import defaultdict from pathlib import Path from typing import Any, Iterable, List, Literal, Mapping, Optional, Union, Callable import numpy as np import pandas as pd import pyvista as pv import vtk from torch.utils.data import Dataset import os from vtk.util import numpy_support def get_filenames(filepath: str) -> List[str]: """Function to get filenames from a directory""" if os.path.exists(filepath): filenames = [] for item in os.listdir(filepath): filenames.append(item) return filenames else: FileNotFoundError() def get_node_to_elem(polydata: Any) -> Any: """Function to convert node to elem""" c2p = vtk.vtkPointDataToCellData() c2p.SetInputData(polydata) c2p.Update() cell_data = c2p.GetOutput() return cell_data def get_fields(data, variables): """Function to get fields from VTP/VTU""" fields = [] for array_name in variables: try: array = data.GetArray(array_name) except ValueError: raise ValueError( f"Failed to get array {array_name} from the unstructured grid." ) array_data = numpy_support.vtk_to_numpy(array).reshape( array.GetNumberOfTuples(), array.GetNumberOfComponents() ) fields.append(array_data) return fields class DrivAerAwsPaths: @staticmethod def _get_index(car_dir: Path) -> str: return car_dir.name.removeprefix("run_") @staticmethod def geometry_path(car_dir: Path) -> Path: return car_dir / f"drivaer_{DrivAerAwsPaths._get_index(car_dir)}.stl" @staticmethod def volume_path(car_dir: Path) -> Path: return car_dir / f"volume_{DrivAerAwsPaths._get_index(car_dir)}.vtu" @staticmethod def surface_path(car_dir: Path) -> Path: return car_dir / f"boundary_{DrivAerAwsPaths._get_index(car_dir)}.vtp" class OpenFoamDataset(Dataset): """ Datapipe for converting openfoam dataset to npy """ def __init__( self, data_path: Union[str, Path], surface_variables: Optional[list] = [ "pMean", "wallShearStress", ], volume_variables: Optional[list] = ["UMean", "pMean"], model_type=None, ): if isinstance(data_path, str): data_path = Path(data_path) data_path = data_path.expanduser() self.data_path = data_path self.path_getter = DrivAerAwsPaths assert self.data_path.exists(), f"Path {self.data_path} does not exist" assert self.data_path.is_dir(), f"Path {self.data_path} is not a directory" self.filenames = get_filenames(self.data_path) random.shuffle(self.filenames) self.indices = np.array(len(self.filenames)) self.surface_variables = surface_variables self.volume_variables = volume_variables self.model_type = model_type def __len__(self): return len(self.filenames) def __getitem__(self, idx): cfd_filename = self.filenames[idx] car_dir = self.data_path / cfd_filename if self.model_type == "surface": surface_filepath = self.path_getter.surface_path(car_dir) reader = vtk.vtkXMLPolyDataReader() reader.SetFileName(surface_filepath) reader.Update() polydata = reader.GetOutput() celldata_all = get_node_to_elem(polydata) celldata = celldata_all.GetCellData() surface_fields = get_fields(celldata, self.surface_variables) surface_fields = np.concatenate(surface_fields, axis=-1) mesh = pv.PolyData(polydata) surface_coordinates = np.array(mesh.cell_centers().points) else: surface_fields = None surface_coordinates = None # Add the parameters to the dictionary return { "surface_mesh_centers": np.float32(surface_coordinates), "surface_fields": np.float32(surface_fields), }