casa::LatticeFit Class Reference

Fit every line of pixels parallel to any axis in a Lattice. More...

#include <LatticeFit.h>

List of all members.

Static Public Member Functions
static uInt	fitProfiles (Lattice< Float > &outImage, Vector< Float > &fittedParameters, LinearFit< Float > &fitter, const Lattice< Float > &inImage, uInt whichAxis, const Vector< Bool > &fitMask, Bool returnResiduals)
	Fit baseline to lattice.
static uInt	fitProfiles (MaskedLattice< Float > *pOutFit, MaskedLattice< Float > *pOutResid, MaskedLattice< Float > &in, Lattice< Float > *pSigma, LinearFit< Float > &fitter, uInt axis, Bool showProgress=False)
	Fit baseline to MaskedLattice.

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Detailed Description

Fit every line of pixels parallel to any axis in a Lattice.

Prerequisite

• LinearFit
• Lattice

Synopsis

For every line in the lattice parallel to axis number whichAxis (often axis number 2, typically the frequency axis in a spectral line cube) independently fit the functions in fitter at the positions where fitMask is true.

Example

Suppose one wanted to subtract a linear polynomial from every spectrum (3d axis) in an image. One could do this as follows:

       Image<Float> myImage("myimage"); // Get the image
       uInt nchan = myImage.shape()(2); // 0 relative axis number
       // Set up the fitter
       Polynomial<AutoDiff<Float> > linear(1);    
       LinearFitSVD<Float> fitter;
       fitter.setFunction(linear);
       Vector<Float> fittedParameters,
   
       // Set up a mask indicating what channels we want to fit over. We want
       // to fit over all channels.
       Vector<Bool> fitMask(nchan); fitMask = True;
   
       // Do the fit. True means subtract the fit from the model. In this case,
       // We overwrite the input with the output.
       fitProfiles (myImage, fittedParameters,fitter, myImage, 2, fitMask, True);

Motivation

Baseline fitting/continuum subtraction are important functions. This function essentially implements the IMLIN algorithm.

To Do

• Save the model parameters in an (optional) other lattice.
• Use logging classes, rather than the raw GlishSysEventSource.
• Allow per-pixel weights.
• Allow non-linear as well as linear LSQ fits.

Definition at line 96 of file LatticeFit.h.

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Member Function Documentation

static uInt casa::LatticeFit::fitProfiles	(	Lattice< Float > &	outImage,
		Vector< Float > &	fittedParameters,
		LinearFit< Float > &	fitter,
		const Lattice< Float > &	inImage,
		uInt	whichAxis,
		const Vector< Bool > &	fitMask,
		Bool	returnResiduals
	)		[static]

Fit baseline to lattice.

Presently the fit parameters, other than the last one(s) in fitter, are lost. If returnResiduals is True, return data-fit, otherwise return the fit. For baseline and continuum subtraction, returnResiduals would normally be True.

static uInt casa::LatticeFit::fitProfiles	(	MaskedLattice< Float > *	pOutFit,
		MaskedLattice< Float > *	pOutResid,
		MaskedLattice< Float > &	in,
		Lattice< Float > *	pSigma,
		LinearFit< Float > &	fitter,
		uInt	axis,
		Bool	showProgress = False
	)		[static]

Fit baseline to MaskedLattice.

Fit and residuals can be optionally written (leave pointers at zero to not write out these lattices) You can optionally specify a weights lattice (1.0 if not given).

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The documentation for this class was generated from the following file:

• casacore/lattices/LatticeMath/LatticeFit.h