nirs4all.operators.augmentation.random module

class nirs4all.operators.augmentation.random.Random_X_Operation(apply_on='global', random_state=None, *, copy=True, operator_func=<built-in function mul>, operator_range=(0.97, 1.03))[source]

Bases: Augmenter

Class for applying random operation on data augmentation.

Parameters:

  • apply_on (str, optional) – Apply augmentation on “features” or “samples” data. Default is “features”.

  • random_state (int or None, optional) – Random seed for reproducibility. Default is None.

  • copy (bool, optional) – If True, creates a copy of the input data. Default is True.

  • operator_func (function, optional) – Operator function to be applied. Default is operator.mul.

  • operator_range (tuple, optional) – Range for generating random values for the operator. Default is (0.97, 1.03).

augment(X, apply_on='global')[source]

Augment the data by applying random operation.

Parameters:

  • X (ndarray) – Input data to be augmented.

  • apply_on (str, optional) – Apply augmentation on “features” or “samples” data. Default is “features”.

Returns:

Augmented data.

Return type:

ndarray

class nirs4all.operators.augmentation.random.Rotate_Translate(apply_on='samples', random_state=None, *, copy=True, p_range=2, y_factor=3)[source]

Bases: Augmenter

Class for rotating and translating data augmentation.

Vectorized implementation that processes all samples in batch.

Parameters:

  • apply_on (str, optional) – Apply augmentation on “samples” or “global” data. Default is “samples”.

  • random_state (int or None, optional) – Random seed for reproducibility. Default is None.

  • copy (bool, optional) – If True, creates a copy of the input data. Default is True.

  • p_range (int, optional) – Range for generating random slope values. Default is 2.

  • y_factor (int, optional) – Scaling factor for the initial value. Default is 3.

augment(X, apply_on='samples')[source]

Augment the data by rotating and translating the signal.

Vectorized implementation using NumPy broadcasting.

Parameters:

  • X (ndarray) – Input data to be augmented, shape (n_samples, n_features).

  • apply_on (str, optional) – Apply augmentation on “samples” or “global” data. Default is “samples”.

Returns:

Augmented data.

Return type:

ndarray