spectrochempy.basc

basc(dataset, *ranges, **kwargs)[source]

Compute a baseline correction using the BaselineCorrection processor.

2 methods are proposed :

  • sequential (default) = classical polynom fit or spline interpolation with separate fitting of each row (spectrum)

  • multivariate = SVD modeling of baseline, polynomial fit of PC’s and calculation of the modelled baseline spectra.

Parameters

  • dataset (a [NDDataset| instance) – The dataset where to calculate the baseline.

  • *ranges (a variable number of pair-tuples) – The regions taken into account for the manual baseline correction.

  • **kwargs – Optional keyword parameters (see Other Parameters).

Other Parameters

  • dim (str or int, keyword parameter, optional, default=’x’.) – Specify on which dimension to apply the apodization method. If dim is specified as an integer it is equivalent to the usual axis numpy parameter.

  • method (str, keyword parameter, optional, default=’sequential’) – Correction method among [‘multivariate’,’sequential’]

  • interpolation (string, keyword parameter, optional, default=’polynomial’) – Interpolation method for the computation of the baseline, among [‘polynomial’,’pchip’]

  • order (int, keyword parameter, optional, default=6) – If the correction method polynomial, this give the polynomial order to use.

  • npc (int, keyword parameter, optional, default=5) – Number of components to keep for the multivariate method

See also

BaselineCorrection

Manual baseline corrections.

abc

Automatic baseline correction.

Notes

For more flexibility and functionality, it is advised to use the BaselineCorrection processor instead.

Examples

import spectrochempy as scp
nd = scp.read('irdata/nh4y-activation.spg')
ndp = nd[:, 1291.0:5999.0]

ranges=[[5996., 5998.], [1290., 1300.],
        [2205., 2301.], [5380., 5979.],
        [3736., 5125.]]

ndcorr = scp.basc(ndp, *ranges,method='multivariate', interpolation='pchip', npc=8)
ndcorr.plot()
scp.show()

(Source code)