CubicSplineCorrection#

class chemotools.baseline.CubicSplineCorrection(indices: list | None = None)[source]

Bases: TransformerMixin, OneToOneFeatureMixin, BaseEstimator

A transformer that corrects a baseline by subtracting a cubic spline through the points defined by the indices.

Parameters:

indices (list, optional, default=None) – The indices of the features to use for the baseline correction. If None, the first and last indices will be used.

Variables:

  • n_features_in (int) – The number of features in the input data.

  • indices (list) – The indices of the features used for the baseline correction.

Examples

>>> from chemotools.baseline import CubicSplineCorrection
>>> from chemotools.datasets import load_fermentation_train
>>> # Load sample data
>>> X, _ = load_fermentation_train()
>>> # Instantiate the transformer
>>> transformer = CubicSplineCorrection(indices=[0, 100, 200, 300, 400, 500])
CubicSplineCorrection(indices)
>>> transformer.fit(X)
>>> # Generate baseline-corrected data
>>> X_corrected = transformer.transform(X)
fit(X: ndarray, y=None) → CubicSplineCorrection[source]

Fit the transformer to the input data.

Parameters:

  • X (np.ndarray of shape (n_samples, n_features)) – The input data to fit the transformer to.

  • y (None) – Ignored to align with API.

Returns:

self – The fitted transformer.

Return type:

ConstantBaselineCorrection

transform(X: ndarray, y=None) → ndarray[source]

Transform the input data by subtracting the baseline.

Parameters:

  • X (np.ndarray of shape (n_samples, n_features)) – The input data to transform.

  • y (None) – Ignored to align with API.

Returns:

X_transformed – The transformed data.

Return type:

np.ndarray of shape (n_samples, n_features)

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