pybaselines.two_d

pybaselines.two_d provides the following algorithms for baseline correcting 2D data.

  • Polynomial methods (pybaselines.two_d.polynomial)

    • poly (Regular Polynomial)

    • modpoly (Modified Polynomial)

    • imodpoly (Improved Modified Polynomial)

    • penalized_poly (Penalized Polynomial)

    • quant_reg (Quantile Regression)

  • Whittaker-smoothing-based methods (pybaselines.two_d.whittaker)

    • asls (Asymmetric Least Squares)

    • iasls (Improved Asymmetric Least Squares)

    • airpls (Adaptive Iteratively Reweighted Penalized Least Squares)

    • arpls (Asymmetrically Reweighted Penalized Least Squares)

    • drpls (Doubly Reweighted Penalized Least Squares)

    • iarpls (Improved Asymmetrically Reweighted Penalized Least Squares)

    • aspls (Adaptive Smoothness Penalized Least Squares)

    • psalsa (Peaked Signal's Asymmetric Least Squares Algorithm)

  • Morphological methods (pybaselines.two_d.morphological)

    • mor (Morphological)

    • imor (Improved Morphological)

    • rolling_ball (Rolling Ball Baseline)

    • tophat (Top-hat Transformation)

  • Spline methods (pybaselines.two_d.spline)

    • mixture_model (Mixture Model)

    • irsqr (Iterative Reweighted Spline Quantile Regression)

    • pspline_asls (Penalized Spline Version of asls)

    • pspline_iasls (Penalized Spline Version of iasls)

    • pspline_airpls (Penalized Spline Version of airpls)

    • pspline_arpls (Penalized Spline Version of arpls)

    • pspline_iarpls (Penalized Spline Version of iarpls)

    • pspline_psalsa (Penalized Spline Version of psalsa)

  • Smoothing-based methods (pybaselines.two_d.smooth)

    • noise_median (Noise Median method)

  • Optimizers (pybaselines.two_d.optimizers)

    • collab_pls (Collaborative Penalized Least Squares)

    • adaptive_minmax (Adaptive MinMax)

    • individual_axes (1D Baseline Correction Along Individual Axes)

@author: Donald Erb Created on January 15, 2024

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