spectrochempy.NormalizeTransformer

class NormalizeTransformer(method='max', dim='x')[source]

Normalization transformer.

Learns the normalization factor along a dimension during fit() and applies it during transform().

Parameters:

  • method (str, optional, default:’max’) – Normalization method:

    • 'max' β€” divide by the maximum absolute value.

    • 'sum' β€” divide by the sum of absolute values.

    • 'vector' β€” divide by the Euclidean (L2) norm.

    • 'minmax' β€” scale linearly to the range [0, 1].

  • dim (str or int, optional, default:’x’) – Dimension along which the normalization is computed.

norm_[source]

Learned norm (for 'max', 'sum', 'vector').

Type:

ndarray

dmin_[source]

Learned minimum (for 'minmax').

Type:

ndarray

dmax_[source]

Learned maximum (for 'minmax').

Type:

ndarray

range_[source]

Learned range (for 'minmax').

Type:

ndarray

Examples

>>> scaler = scp.NormalizeTransformer(method="max", dim="x")
>>> scaler.fit(train)
>>> test_norm = scaler.transform(test)

See also

normalize

Procedural normalization 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.NormalizeTransformer