Ar |
public class ArPLS : ArPLSBase, IBaselineEvaluation, ISingleSpectrumPreprocessor, IEquatable<ArPLS>
The ArPLS type exposes the following members.
Name | Description | |
---|---|---|
Lambda |
Gets or sets the smoothing parameter lambda. The higher lambda is, the smoother the resulting curve will be.
(Inherited from ArPLSBase) | |
MaximumNumberOfIterations |
Gets or sets the maximum number of iterations. The default value is 100.
Usually, the number of iterations is determined by the TerminationRatio, but
with this value, the maximum number of iterations can be limited to a smaller value.
(Inherited from ArPLSBase) | |
Order | (Inherited from ArPLSBase) | |
ScaleLambdaWithXUnits |
If true, lambda is scaled with the x units, so that the effect of baseline estimation is independent on the resolution of the spectrum.
(Inherited from ArPLSBase) | |
TerminationRatio |
Gets or sets the criterion for terminating the iteration (0..1). Default is 0.05.
The iterations stops, if the L2 norm of the differences between actual and previous weights falls below (TerminationRatio x L2 norm of the previous weights).
The lower the value is, the more iterations will be executed.
(Inherited from ArPLSBase) |
Name | Description | |
---|---|---|
Execute(Double, Double, Int32) | Executes the processor. | |
Execute(ReadOnlySpanDouble, ReadOnlySpanDouble, SpanDouble) | (Inherited from ArPLSBase) | |
FillBandMatrixOrder1 | (Inherited from ALSMethodsBase) | |
FillBandMatrixOrder2 | (Inherited from ALSMethodsBase) | |
Finalize | Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object) | |
GetType | Gets the Type of the current instance. (Inherited from Object) | |
MemberwiseClone | Creates a shallow copy of the current Object. (Inherited from Object) | |
UpdateBandMatrixDiagonalOrder1 | (Inherited from ALSMethodsBase) | |
UpdateBandMatrixDiagonalOrder2 | (Inherited from ALSMethodsBase) |
References:
[1] Sung-June Baek et al., Baseline correction using asymmetrically reweighted penalized least squares smoothing, Analyst, 2015, 140, 250-257 doi: 10.1039/C4AN01061B