casacore
LinearFitSVD.h
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1 //# LinearFitSVD.h: Linear fit using Singular Value Decomposition method.
2 //#
3 //# Copyright (C) 1995,1999,2000,2001,2002,2004
4 //# Associated Universities, Inc. Washington DC, USA.
5 //#
6 //# This library is free software; you can redistribute it and/or modify it
7 //# under the terms of the GNU Library General Public License as published by
8 //# the Free Software Foundation; either version 2 of the License, or (at your
9 //# option) any later version.
10 //#
11 //# This library is distributed in the hope that it will be useful, but WITHOUT
12 //# ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
13 //# FITNESS FOR A PARTICULAR PURPOSE. See the GNU Library General Public
14 //# License for more details.
15 //#
16 //# You should have received a copy of the GNU Library General Public License
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18 //# Inc., 675 Massachusetts Ave, Cambridge, MA 02139, USA.
19 //#
20 //# Correspondence concerning AIPS++ should be addressed as follows:
21 //# Internet email: aips2-request@nrao.edu.
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26 //#
27 //# $Id$
28 
29 #ifndef SCIMATH_LINEARFITSVD_H
30 #define SCIMATH_LINEARFITSVD_H
31 
32 #include <casacore/casa/aips.h>
33 #include <casacore/scimath/Fitting/LinearFit.h>
34 
35 namespace casacore { //# NAMESPACE CASACORE - BEGIN
36 
37 // <summary>
38 // Linear least-squares fit using Singular Value Decomposition method.
39 // </summary>
40 //
41 // <reviewed reviewer="wbrouw" date="2004/06/15" tests="tLinearFitSVD.cc"
42 // demos="">
43 // </reviewed>
44 //
45 // <prerequisite>
46 // <li> <linkto class="LinearFit">LinearFit</linkto>
47 // <li> <linkto module="Fitting">Fitting</linkto>
48 // </prerequisite>
49 //
50 // <etymology>
51 // Solves the linear least-squares fit problem using the singular value
52 // decomposition method.
53 // </etymology>
54 //
55 // <synopsis>
56 // The operation, calls and results are identical to those for the
57 // LinearFit class. The only difference is a collinearity default of 1e-8
58 // rather than 0. The actual calculations do a singular value
59 // decomposition solution. A method exists to get the constraints
60 // used in solving for missing rank.
61 //
62 // </synopsis>
63 //
64 // <motivation>
65 // The creation of this class was driven by the need to provide users with
66 // a reliable least-squares fit method. "Numerical Recipes" recommends that
67 // singular value decomposition (SVD) method be always used for linear
68 // least-squares problems, because of its robustness.
69 // Not everybody agrees with this.
70 // </motivation>
71 
72 template<class T> class LinearFitSVD: public LinearFit<T>
73 {
74 public:
75  //# Constructors
76  // Create a fitter: the normal way to generate a fitter object. Necessary
77  // data will be deduced from the Functional provided with
78  // <src>setFunction()</src>
80  // Copy constructor (deep copy)
81  LinearFitSVD(const LinearFitSVD &other);
82  // Assignment (deep copy)
84 
85  // Destructor
86  virtual ~LinearFitSVD();
87 
88 protected:
89  //# Make members of parent classes known.
90  using LinearFit<T>::svd_p;
92 };
93 
94 
95 } //# NAMESPACE CASACORE - END
96 
97 #ifndef CASACORE_NO_AUTO_TEMPLATES
98 #include <casacore/scimath/Fitting/LinearFitSVD.tcc>
99 #endif //# CASACORE_NO_AUTO_TEMPLATES
100 #endif
virtual ~LinearFitSVD()
Destructor.
LinearFitSVD(const LinearFitSVD &other)
Copy constructor (deep copy)
LinearFitSVD()
Create a fitter: the normal way to generate a fitter object.
LinearFitSVD & operator=(const LinearFitSVD &other)
Assignment (deep copy)
this file contains all the compiler specific defines
Definition: mainpage.dox:28