noether.data.datasets.cfd

Submodules

• noether.data.datasets.cfd.caeml
• noether.data.datasets.cfd.dataset
• noether.data.datasets.cfd.drivaernet
• noether.data.datasets.cfd.emmi_wing
• noether.data.datasets.cfd.shapenet_car

Classes

AhmedMLDataset	Dataset implementation for AhmedML CFD simulations.
AhmedMLDefaultSplitIDs	Default split IDs for AhmedML dataset with validation.
DrivAerMLDataset	Dataset implementation for DrivaerML CFD simulations.
DrivAerMLDefaultSplitIDs	Default split IDs for DrivAerML dataset with validation.
DrivAerNetDataset	Dataset implementation for DrivAerNet and DrivAerNet++ dataset.
EmmiWingDataset	Dataset implementation for aerodynamic datasets with volume and surface fields.
ShapeNetCarDataset	Dataset implementation for ShapeNet Car CFD simulations.
ShapeNetCarDefaultSplitIDs	Default split IDs for ShapeNet Car dataset with validation.

Package Contents

class noether.data.datasets.cfd.AhmedMLDataset(dataset_config)

Bases: noether.data.datasets.cfd.caeml.dataset.CAEMLDataset

Dataset implementation for AhmedML CFD simulations.

Parameters:

dataset_config (noether.core.schemas.dataset.DatasetBaseConfig) – Configuration for the dataset.

Initialize the AhmedML dataset.

Parameters:

dataset_config (noether.core.schemas.dataset.DatasetBaseConfig) – Configuration for the dataset.

property get_dataset_splits: noether.core.schemas.dataset.DatasetSplitIDs

Return type:

noether.core.schemas.dataset.DatasetSplitIDs

class noether.data.datasets.cfd.AhmedMLDefaultSplitIDs(/, **data)

Bases: noether.core.schemas.dataset.DatasetSplitIDs

Default split IDs for AhmedML dataset with validation.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Parameters:

data (Any)

EXPECTED_TRAIN_SIZE = 400

EXPECTED_VAL_SIZE = 50

EXPECTED_TEST_SIZE = 50

DATASET_NAME = 'AhmedML'

train: set[int]

val: set[int]

test: set[int]

static create_split()

A helper function to create a random split of the dataset. The default indices were created with seed=42.

class noether.data.datasets.cfd.DrivAerMLDataset(dataset_config)

Bases: noether.data.datasets.cfd.caeml.dataset.CAEMLDataset

Dataset implementation for DrivaerML CFD simulations.

Parameters:

dataset_config (noether.core.schemas.dataset.DatasetBaseConfig) – Configuration for the dataset.

Initialize the DrivaerML dataset.

Parameters:

dataset_config (noether.core.schemas.dataset.DatasetBaseConfig) – Configuration for the dataset.

property get_dataset_splits: noether.core.schemas.dataset.DatasetSplitIDs

Return type:

noether.core.schemas.dataset.DatasetSplitIDs

class noether.data.datasets.cfd.DrivAerMLDefaultSplitIDs(/, **data)

Bases: noether.core.schemas.dataset.DatasetSplitIDs

Default split IDs for DrivAerML dataset with validation.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Parameters:

data (Any)

EXPECTED_TRAIN_SIZE = 400

EXPECTED_VAL_SIZE = 34

EXPECTED_TEST_SIZE = 50

EXPECTED_HIDDEN_TEST_SIZE = 16

DATASET_NAME = 'DrivAerML'

train: set[int]

val: set[int]

test: set[int]

hidden_test: set[int]

static create_split()

A helper function to create a random split of the dataset. The default indices were created with seed=42.

class noether.data.datasets.cfd.DrivAerNetDataset(dataset_config)

Bases: noether.data.datasets.cfd.dataset.AeroDataset

Dataset implementation for DrivAerNet and DrivAerNet++ dataset.

Parameters:

• dataset_config (noether.core.schemas.dataset.StandardDatasetConfig) – Configuration for the dataset. See DatasetBaseConfig for available options.

• filemap – FileMap object defining the mapping of data properties to filenames. See FileMap for details.

FILEMAP

source_root

design_ids

class noether.data.datasets.cfd.EmmiWingDataset(dataset_config)

Bases: noether.data.datasets.cfd.dataset.AeroDataset

Dataset implementation for aerodynamic datasets with volume and surface fields. This unified dataset class provides an interface for aerodynamics dataset with volume and surface fields. The dataset behavior such as the dataset choice, train/val/test split IDs, etc. is configured through constructor parameters, allowing for easy extension to new datasets.

Parameters:

• dataset_config (noether.core.schemas.dataset.StandardDatasetConfig) – Configuration for the dataset. See DatasetBaseConfig for available options.

• filemap – FileMap object defining the mapping of data properties to filenames. See FileMap for details.

split

source_root

sample_info(idx)

Get information about a sample such as its local path, run name, etc.

Parameters:

idx (int)

Return type:

dict[str, str | int | None]

property get_dataset_splits: noether.core.schemas.dataset.DatasetSplitIDs

Return type:

noether.core.schemas.dataset.DatasetSplitIDs

property supported_splits: set[str]

Return type:

set[str]

getitem_geometry_design_parameters(idx)

Retrieves geometry design parameters as a single tensor.

Returns:

Geometry design parameters tensor of shape (1, num_geometry_parameters)

Return type:

torch.Tensor

Parameters:

idx (int)

getitem_inflow_design_parameters(idx)

Retrieves inflow design parameters as a single tensor.

Returns:

Inflow design parameters tensor of shape (1, num_inflow_parameters)

Return type:

torch.Tensor

Parameters:

idx (int)

class noether.data.datasets.cfd.ShapeNetCarDataset(dataset_config)

Bases: noether.data.datasets.cfd.dataset.AeroDataset

Dataset implementation for ShapeNet Car CFD simulations.

This dataset provides access to: - Surface properties: positions, pressure, normals - Volume properties: positions, velocity, normals, signed distance field (SDF)

The dataset is split by parameter configurations: - Test: param0 (100 samples) - Validation: no validation split defined - Train: param1-8 (789 samples)

Download link to the raw dataset: http://www.nobuyuki-umetani.com/publication/mlcfd_data.zip

Expected directory structure:

root/

preprocessed/

param0/

<simulation_id>/

surface_points.pt surface_pressure.pt surface_normals.pt volume_velocity.pt volume_points.pt volume_sdf.pt volume_normals.pt

param1/

…

… param8/

Initialize the ShapeNet Car dataset.

Parameters:

dataset_config (noether.core.schemas.dataset.StandardDatasetConfig) – Configuration for the dataset.

Raises:

• ValueError – If configuration is invalid or split is unknown

• FileNotFoundError – If data directory does not exist

split

source_root: pathlib.Path

property get_dataset_splits: noether.core.schemas.dataset.DatasetSplitIDs

Return type:

noether.core.schemas.dataset.DatasetSplitIDs

sample_info(idx)

Get information about a sample such as its local path, run name, etc.

Parameters:

idx (int)

Return type:

dict[str, str | int | None]

class noether.data.datasets.cfd.ShapeNetCarDefaultSplitIDs(/, **data)

Bases: noether.core.schemas.dataset.DatasetSplitIDs

Default split IDs for ShapeNet Car dataset with validation.

Following the Transolver paper convention:

• param0 is used for test/validation set

• param1-8 are used for training set

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Parameters:

data (Any)

EXPECTED_TRAIN_SIZE = 789

EXPECTED_VAL_SIZE = 0

EXPECTED_TEST_SIZE = 100

DATASET_NAME = 'ShapeNet-Car'

train: set[str]

val: set[str]

test: set[str]