pybaselines.morphological.jbcd

pybaselines.morphological.jbcd(data, half_window=None, alpha=0.1, beta=10.0, gamma=1.0, beta_mult=1.1, gamma_mult=0.909, diff_order=1, max_iter=20, tol=0.01, tol_2=0.001, robust_opening=True, x_data=None, window_kwargs=None, **kwargs)

Joint Baseline Correction and Denoising (jbcd) Algorithm.

Parameters:

dataarray_like, shape (N,)

The y-values of the measured data, with N data points.

half_windowint, optional

The half-window used for the morphology functions. If a value is input, then that value will be used. Default is None, which will optimize the half-window size using optimize_window() and window_kwargs.

alphafloat, optional

The regularization parameter that controls how close the baseline must fit the calculated morphological opening. Larger values make the fit more constrained to the opening and can make the baseline less smooth. Default is 0.1.

betafloat, optional

The regularization parameter that controls how smooth the baseline is. Larger values produce smoother baselines. Default is 1e1.

gammafloat, optional

The regularization parameter that controls how smooth the signal is. Larger values produce smoother baselines. Default is 1.

beta_multfloat, optional

The value that beta is multiplied by each iteration. Default is 1.1.

gamma_multfloat, optional

The value that gamma is multiplied by each iteration. Default is 0.909.

diff_orderint, optional

The order of the differential matrix. Must be greater than 0. Default is 1 (first order differential matrix). Typical values are 2 or 1.

max_iterint, optional

The maximum number of iterations. Default is 20.

tolfloat, optional

The exit criteria for the change in the calculated signal. Default is 1e-2.

tol_2float, optional

The exit criteria for the change in the calculated baseline. Default is 1e-2.

robust_openingbool, optional

If True (default), the opening used to represent the initial baseline is the element-wise minimum between the morphological opening and the average of the morphological erosion and dilation of the opening, similar to mor(). If False, the opening is just the morphological opening, as used in the reference. The robust opening typically represents the baseline better.

x_dataarray_like, optional

The x-values. Not used by this function, but input is allowed for consistency with other functions.

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 (N,)

The calculated baseline.

paramsdict

A dictionary with the following items:

• 'half_window': int

  The half window used for the morphological calculations.

• 'tol_history': numpy.ndarray, shape (K, 2)

  An array containing the calculated tolerance values for each iteration. Index 0 are the tolerence values for the relative change in the signal, and index 1 are the tolerance values for the relative change in the baseline. The length of the array is the number of iterations completed, K. If the last values in the array are greater than the input tol or tol_2 values, then the function did not converge.

• 'signal': numpy.ndarray, shape (N,)

  The pure signal portion of the input data without noise or the baseline.

References

Liu, H., et al. Joint Baseline-Correction and Denoising for Raman Spectra. Applied Spectroscopy, 2015, 69(9), 1013-1022.