piglot.optimisers.botorch.dataset.PCA

class PCA(variance: float)

Bases: object

Principal Component Analysis transformation.

Methods

fit	Fit the PCA transformation to the given data.
to	Move the PCA to a given device.
transform	Transform data to the latent space.
untransform	Transform data back to the original space.

fit(data: Tensor, covariances: Tensor) → None

Fit the PCA transformation to the given data.

Parameters

datatorch.Tensor

Data to fit the PCA transformation to.

covariancestorch.Tensor

Covariances of the data to fit the PCA transformation to.

to(device: str) → PCA

Move the PCA to a given device.

Parameters

devicestr

Device to move the PCA to.

Returns

PCA

The PCA in the new device.

transform(values: torch.Tensor, covariances: torch.Tensor | None = None) → torch.Tensor | Tuple[torch.Tensor, torch.Tensor]

Transform data to the latent space.

Parameters

valuestorch.Tensor

Values to transform.

covariancestorch.Tensor | None

Variances to transform, if any.

Returns

torch.Tensor | Tuple[torch.Tensor, torch.Tensor]

Transformed values and covariances (if any).

untransform(data: Tensor) → Tensor

Transform data back to the original space.

Parameters

datatorch.Tensor

Data to untransform.

Returns

torch.Tensor

Untransformed data.