utils.scaler

utils.scaler

Classes

Name	Description
TorchStandardScaler	A class for scaling data using standardization with torch tensors.

TorchStandardScaler

utils.scaler.TorchStandardScaler()

A class for scaling data using standardization with torch tensors. This scaler computes the mean and standard deviation on a dataset so that it can later be used to scale the data using the computed mean and standard deviation.

Attributes

Name	Type	Description
mean	torch.Tensor	The mean value computed over the fitted data.
std	torch.Tensor	The standard deviation computed over the fitted data.

Examples

>>> import torch
>>> from spotoptim.utils.scaler import TorchStandardScaler
>>> # Create a sample tensor
>>> tensor = torch.rand((10, 3))  # Random tensor with shape (10, 3)
>>> scaler = TorchStandardScaler()
>>> # Fit the scaler to the data
>>> scaler.fit(tensor)
>>> # Transform the data using the fitted scaler
>>> transformed_tensor = scaler.transform(tensor)
>>> print(transformed_tensor.shape)
torch.Size([10, 3])
>>> # Using fit_transform method to fit and transform in one step
>>> another_tensor = torch.rand((10, 3))
>>> scaled_tensor = scaler.fit_transform(another_tensor)

Methods

Name	Description
fit	Compute the mean and standard deviation of the input tensor.
fit_transform	Fit the scaler to the input tensor and then scale the tensor.
transform	Scale the input tensor using the computed mean and standard deviation.

fit

utils.scaler.TorchStandardScaler.fit(x)

Compute the mean and standard deviation of the input tensor.

Parameters

Name	Type	Description	Default
x	torch.Tensor	The input tensor, expected shape [n_samples, n_features]	required

Raises

Name	Type	Description
	TypeError	If the input is not a torch tensor.

fit_transform

utils.scaler.TorchStandardScaler.fit_transform(x)

Fit the scaler to the input tensor and then scale the tensor.

Parameters

Name	Type	Description	Default
x	torch.Tensor	The input tensor, expected shape [n_samples, n_features]	required

Returns

Name	Type	Description
	torch.Tensor	torch.Tensor: The scaled tensor.

Raises

Name	Type	Description
	TypeError	If the input is not a torch tensor.

transform

utils.scaler.TorchStandardScaler.transform(x)

Scale the input tensor using the computed mean and standard deviation.

Parameters

Name	Type	Description	Default
x	torch.Tensor	The input tensor to be transformed, expected shape [n_samples, n_features]	required

Returns

Name	Type	Description
	torch.Tensor	torch.Tensor: The scaled tensor.

Raises

Name	Type	Description
	TypeError	If the input is not a torch tensor.
	RuntimeError	If the scaler has not been fitted before transforming data.