spectrochempy.LogTransformer

class LogTransformer(method='log1p', eps=1e-10)[source]

Logarithmic transform.

This is a stateless transformer: fit() is a no-op and the same transform is applied regardless of the input data. It is provided for API uniformity so that all preprocessing steps can be expressed as transformer objects.

Parameters:

method (str, optional, default:’log1p’) – Transform to apply:
- 'log1p' — compute log(1 + x) (stable for small or zero values).
- 'log' — compute log(x). If the data contain values \(\le 0\), a small offset eps is added automatically.
eps (float, optional, default:1e-10) – Offset added when method='log' and non-positive values are present.

Examples

>>> transformer = scp.LogTransformer(method="log1p")
>>> nd = transformer.fit_transform(dataset)

See also

log_transform: Procedural log transform function.

Methods Summary

`fit`(dataset)	Learn parameters from dataset.
`fit_transform`(dataset)	Fit to dataset, then transform it.
`inverse_transform`(dataset)	Reverse the learned transformation on dataset.
`transform`(dataset)	Apply the learned transformation to dataset.

Methods Documentation

fit(dataset)[source]

Learn parameters from dataset.

Parameters:: dataset (NDDataset) – Training data.
Returns:: self – The fitted instance.

fit_transform(dataset)[source]

Fit to dataset, then transform it.

Equivalent to self.fit(dataset).transform(dataset) but avoids an intermediate copy when possible.

Parameters:: dataset (NDDataset) – Training data.
Returns:: NDDataset – Transformed dataset.

inverse_transform(dataset)[source]

Reverse the learned transformation on dataset.

Parameters:: dataset (NDDataset) – Data to invert.
Returns:: NDDataset – Dataset in the original space.
Raises:: SpectroChemPyError – If fit() has not been called first.

transform(dataset)[source]

Apply the learned transformation to dataset.

Parameters:: dataset (NDDataset) – Data to transform.
Returns:: NDDataset – Transformed dataset.
Raises:: SpectroChemPyError – If fit() has not been called first.

Examples using spectrochempy.LogTransformer