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TQpDataDens.cxx
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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#include "Riostream.h"
44#include "TQpDataDens.h"
45
46////////////////////////////////////////////////////////////////////////////////
47///
48/// \class TQpDataDens
49///
50/// Data for the dense QP formulation
51///
52////////////////////////////////////////////////////////////////////////////////
53
55
56////////////////////////////////////////////////////////////////////////////////
57/// Constructor
58
60: TQpDataBase(nx,my,mz)
61{
65}
66
67
68////////////////////////////////////////////////////////////////////////////////
69/// Constructor
70
72 TVectorD &xlow_in,TVectorD &ixlow_in,
73 TVectorD &xupp_in,TVectorD &ixupp_in,
74 TMatrixD &A_in, TVectorD &bA_in,
75 TMatrixD &C_in,
76 TVectorD &clow_in,TVectorD &iclow_in,
77 TVectorD &cupp_in,TVectorD &icupp_in)
78{
79 fG .ResizeTo(c_in) ; fG = c_in;
80 fBa .ResizeTo(bA_in) ; fBa = bA_in;
81 fXloBound.ResizeTo(xlow_in) ; fXloBound = xlow_in;
82 fXloIndex.ResizeTo(ixlow_in); fXloIndex = ixlow_in;
83 fXupBound.ResizeTo(xupp_in) ; fXupBound = xupp_in;
84 fXupIndex.ResizeTo(ixupp_in); fXupIndex = ixupp_in;
85 fCloBound.ResizeTo(clow_in) ; fCloBound = clow_in;
86 fCloIndex.ResizeTo(iclow_in); fCloIndex = iclow_in;
87 fCupBound.ResizeTo(cupp_in) ; fCupBound = cupp_in;
88 fCupIndex.ResizeTo(icupp_in); fCupIndex = icupp_in;
89
90 fNx = fG.GetNrows();
91 fQ.Use(Q_in);
92
93 if (A_in.GetNrows() > 0) {
94 fA.Use(A_in);
95 fMy = fA.GetNrows();
96 } else
97 fMy = 0;
98
99 if (C_in.GetNrows() > 0) {
100 fC.Use(C_in);
101 fMz = fC.GetNrows();
102 } else
103 fMz = 0;
104}
105
106
107////////////////////////////////////////////////////////////////////////////////
108/// Copy constructor
109
111{
112 *this = another;
113}
114
115
116////////////////////////////////////////////////////////////////////////////////
117/// calculate y = beta*y + alpha*(fQ*x)
118
120{
121 y *= beta;
122 if (fQ.GetNoElements() > 0)
123 y += alpha*(fQ*x);
124}
125
126
127////////////////////////////////////////////////////////////////////////////////
128/// calculate y = beta*y + alpha*(fA*x)
129
131{
132 y *= beta;
133 if (fA.GetNoElements() > 0)
134 y += alpha*(fA*x);
135}
136
137
138////////////////////////////////////////////////////////////////////////////////
139/// calculate y = beta*y + alpha*(fC*x)
140
142{
143 y *= beta;
144 if (fC.GetNoElements() > 0)
145 y += alpha*(fC*x);
146}
147
148
149////////////////////////////////////////////////////////////////////////////////
150/// calculate y = beta*y + alpha*(fA^T*x)
151
153{
154 y *= beta;
155 if (fA.GetNoElements() > 0)
156 y += alpha*(TMatrixD(TMatrixD::kTransposed,fA)*x);
157}
158
159
160////////////////////////////////////////////////////////////////////////////////
161/// calculate y = beta*y + alpha*(fC^T*x)
162
164{
165 y *= beta;
166 if (fC.GetNoElements() > 0)
167 y += alpha*(TMatrixD(TMatrixD::kTransposed,fC)*x);
168}
169
170
171////////////////////////////////////////////////////////////////////////////////
172/// Return the largest component of several vectors in the data class
173
175{
176 Double_t norm = 0.0;
177
178 Double_t componentNorm = fG.NormInf();
179 if (componentNorm > norm) norm = componentNorm;
180
181 TMatrixDSym fQ_abs(fQ);
182 componentNorm = (fQ_abs.Abs()).Max();
183 if (componentNorm > norm) norm = componentNorm;
184
185 componentNorm = fBa.NormInf();
186 if (componentNorm > norm) norm = componentNorm;
187
188 TMatrixD fA_abs(fQ);
189 componentNorm = (fA_abs.Abs()).Max();
190 if (componentNorm > norm) norm = componentNorm;
191
192 TMatrixD fC_abs(fQ);
193 componentNorm = (fC_abs.Abs()).Max();
194 if (componentNorm > norm) norm = componentNorm;
195
197 componentNorm = fXloBound.NormInf();
198 if (componentNorm > norm) norm = componentNorm;
199
201 componentNorm = fXupBound.NormInf();
202 if (componentNorm > norm) norm = componentNorm;
203
205 componentNorm = fCloBound.NormInf();
206 if (componentNorm > norm) norm = componentNorm;
207
209 componentNorm = fCupBound.NormInf();
210 if (componentNorm > norm) norm = componentNorm;
211
212 return norm;
213}
214
215
216////////////////////////////////////////////////////////////////////////////////
217/// Print all class members
218
219void TQpDataDens::Print(Option_t * /*opt*/) const
220{
221 fQ.Print("Q");
222 fG.Print("c");
223
224 fXloBound.Print("xlow");
225 fXloIndex.Print("ixlow");
226
227 fXupBound.Print("xupp");
228 fXupIndex.Print("ixupp");
229
230 fA.Print("A");
231 fBa.Print("b");
232 fC.Print("C");
233
234 fCloBound.Print("clow");
235 fCloIndex.Print("iclow");
236
237 fCupBound.Print("cupp");
238 fCupIndex.Print("icupp");
239}
240
241
242////////////////////////////////////////////////////////////////////////////////
243/// Insert the Hessian Q into the matrix M at index (row,col) for the fundamental
244/// linear system
245
247{
248 m.SetSub(row,col,fQ);
249}
250
251
252////////////////////////////////////////////////////////////////////////////////
253/// Insert the constraint matrix A into the matrix M at index (row,col) for the fundamental
254/// linear system
255
257{
258 m.SetSub(row,col,fA);
259}
260
261
262////////////////////////////////////////////////////////////////////////////////
263/// Insert the constraint matrix C into the matrix M at index (row,col) for the fundamental
264/// linear system
265
267{
268 m.SetSub(row,col,fC);
269}
270
271
272////////////////////////////////////////////////////////////////////////////////
273/// Return in vector dq the diagonal of matrix fQ (Quadratic part of Objective function)
274
276{
277 const Int_t n = TMath::Min(fQ.GetNrows(),fQ.GetNcols());
278 dq.ResizeTo(n);
279 dq = TMatrixDDiag(fQ);
280}
281
282
283////////////////////////////////////////////////////////////////////////////////
284/// Return value of the objective function
285
287{
288 TVectorD tmp(fG);
289 this->Qmult(1.0,tmp,0.5,vars->fX);
290
291 return tmp*vars->fX;
292}
293
294
295////////////////////////////////////////////////////////////////////////////////
296/// Choose randomly a QP problem
297
299{
300 Double_t ix = 3074.20374;
301
302 TVectorD xdual(fNx);
304 TVectorD sprime(fMz);
306
307 fQ.RandomizePD(0.0,1.0,ix);
308 fA.Randomize(-10.0,10.0,ix);
309 fC.Randomize(-10.0,10.0,ix);
310 y .Randomize(-10.0,10.0,ix);
311
312 fG = xdual;
313 fG -= fQ*x;
314
317
318 fBa = fA*x;
319 s = fC*x;
320
321 // Now compute the real q = s-sprime
322 const TVectorD q = s-sprime;
323
324 // Adjust fCloBound and fCupBound appropriately
325 Add(fCloBound,1.0,q);
326 Add(fCupBound,1.0,q);
327
330}
331
332
333////////////////////////////////////////////////////////////////////////////////
334/// Assignment operator
335
337{
338 if (this != &source) {
340 fQ.ResizeTo(source.fQ); fQ = source.fQ;
341 fA.ResizeTo(source.fA); fA = source.fA;
342 fC.ResizeTo(source.fC); fC = source.fC;
343 }
344 return *this;
345}
double Double_t
Definition: RtypesCore.h:57
const char Option_t
Definition: RtypesCore.h:64
#define ClassImp(name)
Definition: Rtypes.h:361
#define R__ASSERT(e)
Definition: TError.h:96
float * q
Definition: THbookFile.cxx:87
TMatrixTDiag< Double_t > TMatrixDDiag
TMatrixT< Double_t > TMatrixD
Definition: TMatrixDfwd.h:22
virtual TMatrixTBase< Element > & Randomize(Element alpha, Element beta, Double_t &seed)
Randomize matrix element values.
Int_t GetNrows() const
Definition: TMatrixTBase.h:124
void Print(Option_t *name="") const
Print the matrix as a table of elements.
Int_t GetNoElements() const
Definition: TMatrixTBase.h:128
Int_t GetNcols() const
Definition: TMatrixTBase.h:127
virtual TMatrixTBase< Element > & Abs()
Take an absolute value of a matrix, i.e. apply Abs() to each element.
virtual TMatrixTSym< Element > & RandomizePD(Element alpha, Element beta, Double_t &seed)
randomize matrix element values but keep matrix symmetric positive definite
TMatrixTSym< Element > & Use(Int_t row_lwb, Int_t row_upb, Element *data)
virtual TMatrixTBase< Element > & ResizeTo(Int_t nrows, Int_t ncols, Int_t=-1)
Set size of the matrix to nrows x ncols New dynamic elements are created, the overlapping part of the...
TMatrixT< Element > & Use(Int_t row_lwb, Int_t row_upb, Int_t col_lwb, Int_t col_upb, Element *data)
Use the array data to fill the matrix ([row_lwb..row_upb] x [col_lwb..col_upb])
Definition: TMatrixT.cxx:1056
virtual TMatrixTBase< Element > & ResizeTo(Int_t nrows, Int_t ncols, Int_t=-1)
Set size of the matrix to nrows x ncols New dynamic elements are created, the overlapping part of the...
Definition: TMatrixT.cxx:1213
Data for the general QP formulation.
Definition: TQpDataBase.h:61
TQpDataBase & operator=(const TQpDataBase &source)
Assignment operator.
TVectorD fXupIndex
Definition: TQpDataBase.h:80
TVectorD fXloBound
Definition: TQpDataBase.h:81
TVectorD fCloIndex
Definition: TQpDataBase.h:86
TVectorD fCupIndex
Definition: TQpDataBase.h:84
TVectorD fG
Definition: TQpDataBase.h:77
TVectorD fXupBound
Definition: TQpDataBase.h:79
TVectorD fXloIndex
Definition: TQpDataBase.h:82
TVectorD fCupBound
Definition: TQpDataBase.h:83
TVectorD fCloBound
Definition: TQpDataBase.h:85
TVectorD fBa
Definition: TQpDataBase.h:78
static void RandomlyChooseBoundedVariables(TVectorD &x, TVectorD &dualx, TVectorD &blx, TVectorD &ixlow, TVectorD &bux, TVectorD &ixupp, Double_t &ix, Double_t percentLowerOnly, Double_t percentUpperOnly, Double_t percentBound)
Randomly choose x and its boundaries.
Data for the dense QP formulation.
Definition: TQpDataDens.h:63
virtual void GetDiagonalOfQ(TVectorD &dQ)
Return in vector dq the diagonal of matrix fQ (Quadratic part of Objective function)
virtual void CTransmult(Double_t beta, TVectorD &y, Double_t alpha, const TVectorD &x)
calculate y = beta*y + alpha*(fC^T*x)
virtual Double_t ObjectiveValue(TQpVar *vars)
Return value of the objective function.
virtual void DataRandom(TVectorD &x, TVectorD &y, TVectorD &z, TVectorD &s)
Choose randomly a QP problem.
TMatrixD fC
Definition: TQpDataDens.h:70
virtual Double_t DataNorm()
Return the largest component of several vectors in the data class.
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...
TMatrixDSym fQ
Definition: TQpDataDens.h:68
virtual void Print(Option_t *opt="") const
Print all class members.
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...
TMatrixD fA
Definition: TQpDataDens.h:69
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 ATransmult(Double_t beta, TVectorD &y, Double_t alpha, const TVectorD &x)
calculate y = beta*y + alpha*(fA^T*x)
virtual void Qmult(Double_t beta, TVectorD &y, Double_t alpha, const TVectorD &x)
calculate y = beta*y + alpha*(fQ*x)
TQpDataDens & operator=(const TQpDataDens &source)
Assignment operator.
Class containing the variables for the general QP formulation.
Definition: TQpVar.h:60
TVectorD fX
Definition: TQpVar.h:91
Element NormInf() const
Compute the infinity-norm of the vector MAX{ |v[i]| }.
Definition: TVectorT.cxx:604
Bool_t MatchesNonZeroPattern(const TVectorT< Element > &select)
Check if vector elements as selected through array select are non-zero.
Definition: TVectorT.cxx:1239
TVectorT< Element > & ResizeTo(Int_t lwb, Int_t upb)
Resize the vector to [lwb:upb] .
Definition: TVectorT.cxx:295
Int_t GetNrows() const
Definition: TVectorT.h:75
TVectorT< Element > & SelectNonZeros(const TVectorT< Element > &select)
Keep only element as selected through array select non-zero.
Definition: TVectorT.cxx:545
void Print(Option_t *option="") const
Print the vector as a list of elements.
Definition: TVectorT.cxx:1364
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
const Int_t n
Definition: legend1.C:16
void Add(RHist< DIMENSIONS, PRECISION, STAT_TO... > &to, const RHist< DIMENSIONS, PRECISION, STAT_FROM... > &from)
Add two histograms.
Definition: RHist.hxx:323
static constexpr double s
Short_t Max(Short_t a, Short_t b)
Definition: TMathBase.h:212
Short_t Min(Short_t a, Short_t b)
Definition: TMathBase.h:180
auto * m
Definition: textangle.C:8