spectrochempy.whittaker

whittaker(dataset, lamb=1.0, order=2, dim=-1, **kwargs)[source]

Smooth the data using the Whittaker smoothing algorithm.

This implementation based on the work by Eilers [2003] uses sparse matrices enabling high-speed processing of large input vectors.

Copyright M. H. V. Werts, 2017 (see LICENSES/WITTAKER_SMOOTH_LICENSE.rst)

Parameters:

dataset (NDDataset) – Input dataset to smooth.
lamb (float, optional, default: 1.0) – The smoothing parameter. Larger values make the result smoother.
order (int, optional, default: 2) – The difference order of the penalized least-squares.
dim (int or str, optional, default: -1) – Axis along which to apply the filter. Accepts a dimension name (e.g. "x") or an integer index (e.g. -1 for the last axis).
**kwargs (keyword arguments, optional) – Additional keyword arguments passed to the filter.

Returns:

NDdataset – Smoothed data.

Other Parameters:

log_level (str, optional, default: ‘WARNING’) – The log level for the filter.