ramanspy.preprocessing.baseline.IRSQR

class ramanspy.preprocessing.baseline.IRSQR(*, lam=100, quantile=0.05, num_knots=100, spline_degree=3, diff_order=3, max_iter=100, tol=1e-06, weights=None, eps=None)[source]

Baseline correction based on Iterative Reweighted Spline Quantile Regression (IRSQR).

Parameters:: **kwargs – Check original implementation for information about parameters.

Note

Implementation based on pybaselines.

References

Han, Q., et al. Iterative Reweighted Quantile Regression Using Augmented Lagrangian Optimization for Baseline Correction. 2018 5th International Conference on Information Science and Control Engineering (ICISCE), 2018, 280-284.

__init__(*, lam=100, quantile=0.05, num_knots=100, spline_degree=3, diff_order=3, max_iter=100, tol=1e-06, weights=None, eps=None)[source]

Methods

`__init__`(*[, lam, quantile, num_knots, ...])
`apply`(raman_objects)	Applies the defined preprocessing method on the Raman spectroscopic objects provided.