pybaselines.Baseline2D.rolling_ball

Baseline2D.rolling_ball(data, half_window=None, smooth_half_window=None, pad_kwargs=None, window_kwargs=None, **kwargs)

The rolling ball baseline algorithm.

Applies a minimum and then maximum moving window, and subsequently smooths the result, giving a baseline that resembles rolling a ball across the data.

Parameters:

dataarray_like, shape (M, N)

The y-values of the measured data.

half_windowint or sequence[int, int], optional

The half-window used for the rows and columns, respectively, for the morphology functions. If a single value is given, rows and columns will use the same value. Default is None, which will optimize the half-window size using optimize_window() and window_kwargs.

smooth_half_windowint, optional

The half-window to use for smoothing the data after performing the morphological operation. Default is None, which will use the same value as used for the morphological operation.

pad_kwargsdict, optional

A dictionary of keyword arguments to pass to pad_edges() for padding the edges of the data to prevent edge effects from the moving average.

window_kwargsdict, optional

A dictionary of keyword arguments to pass to optimize_window() for estimating the half window if half_window is None. Default is None.

**kwargs

Deprecated since version 1.2.0: Passing additional keyword arguments is deprecated and will be removed in version 1.4.0. Pass keyword arguments using window_kwargs.

Returns:

baselinenumpy.ndarray, shape (M, N)

The calculated baseline.

dict

A dictionary with the following items:

• 'half_window': np.ndarray[int, int]

  The half windows used for the morphological calculations.

References

Kneen, M.A., et al. Algorithm for fitting XRF, SEM and PIXE X-ray spectra backgrounds. Nuclear Instruments and Methods in Physics Research B, 1996, 109, 209-213.

Liland, K., et al. Optimal Choice of Baseline Correction for Multivariate Calibration of Spectra. Applied Spectroscopy, 2010, 64(9), 1007-1016.