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TQpDataSparse.h
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1// @(#)root/quadp:$Id$
2// Author: Eddy Offermann May 2004
3
4/*************************************************************************
5 * Copyright (C) 1995-2000, Rene Brun and Fons Rademakers. *
6 * All rights reserved. *
7 * *
8 * For the licensing terms see $ROOTSYS/LICENSE. *
9 * For the list of contributors see $ROOTSYS/README/CREDITS. *
10 *************************************************************************/
11
12/*************************************************************************
13 * Parts of this file are copied from the OOQP distribution and *
14 * are subject to the following license: *
15 * *
16 * COPYRIGHT 2001 UNIVERSITY OF CHICAGO *
17 * *
18 * The copyright holder hereby grants you royalty-free rights to use, *
19 * reproduce, prepare derivative works, and to redistribute this software*
20 * to others, provided that any changes are clearly documented. This *
21 * software was authored by: *
22 * *
23 * E. MICHAEL GERTZ gertz@mcs.anl.gov *
24 * Mathematics and Computer Science Division *
25 * Argonne National Laboratory *
26 * 9700 S. Cass Avenue *
27 * Argonne, IL 60439-4844 *
28 * *
29 * STEPHEN J. WRIGHT swright@cs.wisc.edu *
30 * Computer Sciences Department *
31 * University of Wisconsin *
32 * 1210 West Dayton Street *
33 * Madison, WI 53706 FAX: (608)262-9777 *
34 * *
35 * Any questions or comments may be directed to one of the authors. *
36 * *
37 * ARGONNE NATIONAL LABORATORY (ANL), WITH FACILITIES IN THE STATES OF *
38 * ILLINOIS AND IDAHO, IS OWNED BY THE UNITED STATES GOVERNMENT, AND *
39 * OPERATED BY THE UNIVERSITY OF CHICAGO UNDER PROVISION OF A CONTRACT *
40 * WITH THE DEPARTMENT OF ENERGY. *
41 *************************************************************************/
42
43#ifndef ROOT_TQpDataSparse
44#define ROOT_TQpDataSparse
45
46#include "TQpDataBase.h"
47#include "TQpVar.h"
48
49#include "TMatrixDSparse.h"
50
51//////////////////////////////////////////////////////////////////////////
52// //
53// TQpDataSparse //
54// //
55// Data for the dense QP formulation //
56// //
57//////////////////////////////////////////////////////////////////////////
58
60{
61
62protected:
63
64 // these variables will be "Used" not copied
65 TMatrixDSparse fQ; // quadratic part of Objective function
66 TMatrixDSparse fA; // Equality constraints
67 TMatrixDSparse fC; // Inequality constraints
68
69public:
70
72 // data objects of the specified dimensions
74
75 // sets up pointers to the data objects that are passed as arguments
78 TVectorD &iclow,TVectorD &cupp,TVectorD &icupp);
79 TQpDataSparse(const TQpDataSparse &another);
80
81 virtual ~TQpDataSparse() {}
82
83 void SetNonZeros(Int_t nnzQ,Int_t nnzA,Int_t nnzC);
84
85 virtual void PutQIntoAt(TMatrixDBase &M,Int_t row,Int_t col);
86 // insert the Hessian Q into the matrix M for the fundamental
87 // linear system, where M is stored as a TMatrixDSparse
88 virtual void PutAIntoAt(TMatrixDBase &M,Int_t row,Int_t col);
89 // insert the constraint matrix A into the matrix M for the
90 // fundamental linear system, where M is stored as a TMatrixDSparse
91 virtual void PutCIntoAt(TMatrixDBase &M,Int_t row,Int_t col);
92 // insert the constraint matrix C into the matrix M for the
93 // fundamental linear system, where M is stored as a
94 // TMatrixDSparse
95
96 virtual void Qmult (Double_t beta,TVectorD& y,Double_t alpha,const TVectorD& x);
97 // y = beta * y + alpha * Q * x
98 virtual void Amult (Double_t beta,TVectorD& y,Double_t alpha,const TVectorD& x);
99 // y = beta * y + alpha * A * x
100 virtual void Cmult (Double_t beta,TVectorD& y,Double_t alpha,const TVectorD& x);
101 // y = beta * y + alpha * C * x
102 virtual void ATransmult(Double_t beta,TVectorD& y,Double_t alpha,const TVectorD& x);
103 // y = beta * y + alpha * A^T * x
104 virtual void CTransmult(Double_t beta,TVectorD& y,Double_t alpha,const TVectorD& x);
105 // y = beta * y + alpha * C^T * x
106
107 virtual void GetDiagonalOfQ(TVectorD &dQ); // extract the diagonal of Q and put it in the vector dQ
108
109 virtual Double_t DataNorm();
110 virtual void DataRandom(TVectorD &x,TVectorD &y,TVectorD &z,TVectorD &s);
111 // Create a random problem (x,y,z,s)
112 // the solution to the random problem
113 virtual void Print(Option_t *opt="") const;
114
115 virtual Double_t ObjectiveValue(TQpVar *vars);
116
117 TQpDataSparse &operator= (const TQpDataSparse &source);
118
119 ClassDef(TQpDataSparse,1) // Qp Data class for Sparse formulation
120};
121#endif
#define c(i)
Definition: RSha256.hxx:101
int Int_t
Definition: RtypesCore.h:43
double Double_t
Definition: RtypesCore.h:57
const char Option_t
Definition: RtypesCore.h:64
#define ClassDef(name, id)
Definition: Rtypes.h:322
Data for the general QP formulation.
Definition: TQpDataBase.h:61
Data for the sparse QP formulation.
Definition: TQpDataSparse.h:60
virtual void CTransmult(Double_t beta, TVectorD &y, Double_t alpha, const TVectorD &x)
calculate y = beta*y + alpha*(fC^T*x)
virtual void PutCIntoAt(TMatrixDBase &M, Int_t row, Int_t col)
Insert the constraint matrix C into the matrix M at index (row,col) for the fundamental linear system...
virtual void Qmult(Double_t beta, TVectorD &y, Double_t alpha, const TVectorD &x)
calculate y = beta*y + alpha*(fQ*x)
virtual ~TQpDataSparse()
Definition: TQpDataSparse.h:81
virtual void PutAIntoAt(TMatrixDBase &M, Int_t row, Int_t col)
Insert the constraint matrix A into the matrix M at index (row,col) for the fundamental linear system...
virtual void Amult(Double_t beta, TVectorD &y, Double_t alpha, const TVectorD &x)
calculate y = beta*y + alpha*(fA*x)
virtual void PutQIntoAt(TMatrixDBase &M, Int_t row, Int_t col)
Insert the Hessian Q into the matrix M at index (row,col) for the fundamental linear system.
virtual void Cmult(Double_t beta, TVectorD &y, Double_t alpha, const TVectorD &x)
calculate y = beta*y + alpha*(fC*x)
virtual void GetDiagonalOfQ(TVectorD &dQ)
Return in vector dq the diagonal of matrix fQ.
TQpDataSparse & operator=(const TQpDataSparse &source)
Assignment operator.
TMatrixDSparse fC
Definition: TQpDataSparse.h:67
TMatrixDSparse fQ
Definition: TQpDataSparse.h:65
void SetNonZeros(Int_t nnzQ, Int_t nnzA, Int_t nnzC)
Allocate space for the appropriate number of non-zeros in the matrices.
virtual Double_t DataNorm()
Return the largest component of several vectors in the data class.
TMatrixDSparse fA
Definition: TQpDataSparse.h:66
virtual void ATransmult(Double_t beta, TVectorD &y, Double_t alpha, const TVectorD &x)
calculate y = beta*y + alpha*(fA^T*x)
virtual Double_t ObjectiveValue(TQpVar *vars)
Return value of the objective function.
virtual void Print(Option_t *opt="") const
Print class members.
virtual void DataRandom(TVectorD &x, TVectorD &y, TVectorD &z, TVectorD &s)
Choose randomly a QP problem.
Class containing the variables for the general QP formulation.
Definition: TQpVar.h:60
double beta(double x, double y)
Calculates the beta function.
Double_t y[n]
Definition: legend1.C:17
Double_t x[n]
Definition: legend1.C:17
static double Q[]
static double A[]
static double C[]
static constexpr double s