snip.h File Reference

Baseline estimation using Statistics-sensitive Non-linear Iterative Peak-clipping(SNIP). More...

#include <stdexcept>
#include <vector>

Go to the source code of this file.

Enumerations
enum class	sablib::SnipPreprocess { None , LL , LLS }
	Preprocessing types for the SNIP algorithm. More...

Functions
const std::vector< double >	sablib::BaselineSnip (const std::vector< double > &y, const unsigned int m, const bool decreasing=true, const SnipPreprocess preprocess=SnipPreprocess::None, const unsigned int loop=1)
	Performs baseline estimation using the Statistics-sensitive Non-linear Iterative Peak-clipping (SNIP) algorithm.

Detailed Description

Baseline estimation using Statistics-sensitive Non-linear Iterative Peak-clipping(SNIP).

Author

Izadori

References:

• Ryan, C. G.; Clayton, E.; Griffin, W. L.; Sie, S. H.; Cousens, D. R. "SNIP, A Statistics-sensitive Background Treatment for the Quantitative Analysis of PIXE Spectra in Geoscience Applications" Nuclear Instruments and Methods in Physics Research, 1988, B34(3), 396-402.
• Caccia, M.; Ebolese, A.; Matteo, M.; Santro, R.; Locatteli, M.; Pieracci, M.; Tintori, C. "Background removal procedure based on the SNIP algorithm for γ−ray spectroscopy with the CAEN Educational Kit" Educational Note ED3163; CAEN S.p.A.: Viareggio, Italy, 2021.

Definition in file snip.h.

Enumeration Type Documentation

SnipPreprocess

enum class sablib::SnipPreprocess

strong

Preprocessing types for the SNIP algorithm.

SNIP often works better when the data is transformed to stabilize the variance or handle high dynamic range peaks.

Enumerator
None	No preprocessing (linear scale).
LL	Log-log transformation: v = log(log(y + 1) + 1). Useful for large dynamic ranges.
LLS	Log-log-sqrt transformation: v = log(log(sqrt(y + 1) + 1) + 1). More aggressive variance stabilization.

Definition at line 25 of file snip.h.

Function Documentation

BaselineSnip()

const std::vector< double > sablib::BaselineSnip	(	const std::vector< double > &	y,
		const unsigned int	m,
		const bool	decreasing = true,
		const SnipPreprocess	preprocess = SnipPreprocess::None,
		const unsigned int	loop = 1 )

Performs baseline estimation using the Statistics-sensitive Non-linear Iterative Peak-clipping (SNIP) algorithm.

Parameters

y	The input data vector (signal to be processed).
m	The maximum half-window size (maximum clipping distance).
decreasing	If true, iterates from m down to 1 (recommended). If false, iterates from 1 up to m.
preprocess	The preprocessing transformation to apply before clipping (None, LL, or LLS).
loop	The number of times to repeat the entire SNIP process (usually 1 is sufficient).

Returns

A vector of the estimated baseline.

Exceptions

std::invalid_argument

One or more parameters are wrong.

Definition at line 17 of file snip.cpp.