1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
|
/**********************************************************
*
* Solve a quadratic function f(X) = X' A X + b X
* subject to a set of separation constraints cs
*
* Tim Dwyer, 2006
**********************************************************/
#include <math.h>
#include <stdlib.h>
#include <time.h>
#include <stdio.h>
#include <float.h>
#include <cassert>
#include <libvpsc/solve_VPSC.h>
#include <libvpsc/variable.h>
#include <libvpsc/constraint.h>
#include "gradient_projection.h"
#include <iostream>
#include "2geom/isnan.h"
#include "isinf.h"
#include <math.h>
using namespace std;
using namespace vpsc;
//#define CONMAJ_LOGGING 1
static void dumpVPSCException(char const *str, IncSolver* solver) {
cerr<<str<<endl;
unsigned m;
Constraint** cs = solver->getConstraints(m);
for(unsigned i=0;i<m;i++) {
cerr << *cs[i] << endl;
}
}
/*
* Use gradient-projection to solve an instance of
* the Variable Placement with Separation Constraints problem.
* Uses sparse matrix techniques to handle pairs of dummy
* vars.
*/
unsigned GradientProjection::solve(double * b) {
unsigned i,j,counter;
if(max_iterations==0) return 0;
bool converged=false;
IncSolver* solver=NULL;
solver = setupVPSC();
//cerr << "in gradient projection: n=" << n << endl;
for (i=0;i<n;i++) {
assert(!IS_NAN(place[i]));
assert(!isinf(place[i]));
vars[i]->desiredPosition=place[i];
}
try {
solver->satisfy();
} catch (char const *str) {
dumpVPSCException(str,solver);
}
for (i=0;i<n;i++) {
place[i]=vars[i]->position();
}
for (DummyVars::iterator it=dummy_vars.begin();it!=dummy_vars.end();++it){
(*it)->updatePosition();
}
for (counter=0; counter<max_iterations&&!converged; counter++) {
converged=true;
// find steepest descent direction
// g = 2 ( b - Ax )
for (i=0; i<n; i++) {
old_place[i]=place[i];
g[i] = b[i];
for (j=0; j<n; j++) {
g[i] -= A[i][j]*place[j];
}
g[i] *= 2.0;
}
for (DummyVars::iterator it=dummy_vars.begin();it!=dummy_vars.end();++it){
(*it)->computeDescentVector();
}
// compute step size: alpha = ( g' g ) / ( 2 g' A g )
// g terms for dummy vars cancel out so don't consider
double numerator = 0, denominator = 0, r;
for (i=0; i<n; i++) {
numerator += g[i]*g[i];
r=0;
for (j=0; j<n; j++) {
r += A[i][j]*g[j];
}
denominator -= 2.0 * r*g[i];
}
double alpha = numerator/denominator;
// move to new unconstrained position
for (i=0; i<n; i++) {
place[i]-=alpha*g[i];
assert(!IS_NAN(place[i]));
assert(!isinf(place[i]));
vars[i]->desiredPosition=place[i];
}
for (DummyVars::iterator it=dummy_vars.begin();it!=dummy_vars.end();++it){
(*it)->steepestDescent(alpha);
}
//project to constraint boundary
try {
solver->satisfy();
} catch (char const *str) {
dumpVPSCException(str,solver);
}
for (i=0;i<n;i++) {
place[i]=vars[i]->position();
}
for (DummyVars::iterator it=dummy_vars.begin();it!=dummy_vars.end();++it){
(*it)->updatePosition();
}
// compute d, the vector from last pnt to projection pnt
for (i=0; i<n; i++) {
d[i]=place[i]-old_place[i];
}
// now compute beta, optimal step size from last pnt to projection pnt
// beta = ( g' d ) / ( 2 d' A d )
numerator = 0, denominator = 0;
for (i=0; i<n; i++) {
numerator += g[i] * d[i];
r=0;
for (j=0; j<n; j++) {
r += A[i][j] * d[j];
}
denominator += 2.0 * r * d[i];
}
for (DummyVars::iterator it=dummy_vars.begin();it!=dummy_vars.end();++it){
(*it)->betaCalc(numerator,denominator);
}
double beta = numerator/denominator;
// beta > 1.0 takes us back outside the feasible region
// beta < 0 clearly not useful and may happen due to numerical imp.
if(beta>0&&beta<1.0) {
for (i=0; i<n; i++) {
place[i]=old_place[i]+beta*d[i];
}
for (DummyVars::iterator it=dummy_vars.begin();it!=dummy_vars.end();++it){
(*it)->feasibleDescent(beta);
}
}
double test=0;
for (i=0; i<n; i++) {
test += fabs(place[i]-old_place[i]);
}
for (DummyVars::iterator it=dummy_vars.begin();it!=dummy_vars.end();++it){
test += (*it)->absoluteDisplacement();
}
if(test>tolerance) {
converged=false;
}
}
destroyVPSC(solver);
return counter;
}
// Setup an instance of the Variable Placement with Separation Constraints
// for one iteration.
// Generate transient local constraints --- such as non-overlap constraints
// --- that are only relevant to one iteration, and merge these with the
// global constraint list (including alignment constraints,
// dir-edge constraints, containment constraints, etc).
IncSolver* GradientProjection::setupVPSC() {
Constraint **cs;
//assert(lcs.size()==0);
for(DummyVars::iterator dit=dummy_vars.begin();
dit!=dummy_vars.end(); ++dit) {
(*dit)->setupVPSC(vars,lcs);
}
Variable** vs = new Variable*[vars.size()];
for(unsigned i=0;i<vars.size();i++) {
vs[i]=vars[i];
}
if(nonOverlapConstraints) {
Constraint** tmp_cs=NULL;
unsigned m=0;
if(k==HORIZONTAL) {
Rectangle::setXBorder(0.0001);
m=generateXConstraints(n,rs,vs,tmp_cs,true);
Rectangle::setXBorder(0);
} else {
m=generateYConstraints(n,rs,vs,tmp_cs);
}
for(unsigned i=0;i<m;i++) {
lcs.push_back(tmp_cs[i]);
}
}
cs = new Constraint*[lcs.size() + gcs.size()];
unsigned m = 0 ;
for(vector<Constraint*>::iterator ci = lcs.begin();ci!=lcs.end();++ci) {
cs[m++] = *ci;
}
for(vector<Constraint*>::iterator ci = gcs.begin();ci!=gcs.end();++ci) {
cs[m++] = *ci;
}
return new IncSolver(vars.size(),vs,m,cs);
}
void GradientProjection::clearDummyVars() {
for(DummyVars::iterator i=dummy_vars.begin();i!=dummy_vars.end();++i) {
delete *i;
}
dummy_vars.clear();
}
void GradientProjection::destroyVPSC(IncSolver *vpsc) {
if(acs) {
for(AlignmentConstraints::iterator ac=acs->begin(); ac!=acs->end();++ac) {
(*ac)->updatePosition();
}
}
unsigned m,n;
Constraint** cs = vpsc->getConstraints(m);
const Variable* const* vs = vpsc->getVariables(n);
delete vpsc;
delete [] cs;
delete [] vs;
for(vector<Constraint*>::iterator i=lcs.begin();i!=lcs.end();i++) {
delete *i;
}
lcs.clear();
//cout << " Vars count = " << vars.size() << " Dummy vars cnt=" << dummy_vars.size() << endl;
vars.resize(vars.size()-dummy_vars.size()*2);
for(DummyVars::iterator i=dummy_vars.begin();i!=dummy_vars.end();++i) {
DummyVarPair* p = *i;
delete p->left;
delete p->right;
}
}
// vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=4:softtabstop=4 :
|
