1 |
#include <math.h> |
2 |
#include "OOPSEMinimizer.hpp" |
3 |
#include "ShakeMin.hpp" |
4 |
#include "Integrator.cpp" |
5 |
|
6 |
OOPSEMinimizer::OOPSEMinimizer( SimInfo *theInfo, ForceFields* the_ff , |
7 |
MinimizerParameterSet * param) : |
8 |
RealIntegrator(theInfo, the_ff), bShake(true), bVerbose(false) { |
9 |
dumpOut = NULL; |
10 |
statOut = NULL; |
11 |
|
12 |
tStats = new Thermo(info); |
13 |
|
14 |
|
15 |
paramSet = param; |
16 |
|
17 |
calcDim(); |
18 |
|
19 |
curX = getCoor(); |
20 |
curG.resize(ndim); |
21 |
|
22 |
shakeAlgo = new ShakeMinFramework(theInfo); |
23 |
shakeAlgo->doPreConstraint(); |
24 |
} |
25 |
|
26 |
OOPSEMinimizer::~OOPSEMinimizer(){ |
27 |
delete tStats; |
28 |
if(dumpOut) |
29 |
delete dumpOut; |
30 |
if(statOut) |
31 |
delete statOut; |
32 |
delete paramSet; |
33 |
} |
34 |
|
35 |
void OOPSEMinimizer::calcEnergyGradient(vector<double>& x, vector<double>& grad, |
36 |
double& energy, int& status){ |
37 |
|
38 |
DirectionalAtom* dAtom; |
39 |
int index; |
40 |
double force[3]; |
41 |
double dAtomGrad[6]; |
42 |
int shakeStatus; |
43 |
|
44 |
status = 1; |
45 |
|
46 |
setCoor(x); |
47 |
|
48 |
if (bShake){ |
49 |
shakeStatus = shakeAlgo->doShakeR(); |
50 |
if(shakeStatus < 0) |
51 |
status = -1; |
52 |
} |
53 |
|
54 |
calcForce(1, 1); |
55 |
|
56 |
if (bShake){ |
57 |
shakeStatus = shakeAlgo->doShakeF(); |
58 |
if(shakeStatus < 0) |
59 |
status = -1; |
60 |
} |
61 |
|
62 |
x = getCoor(); |
63 |
|
64 |
|
65 |
index = 0; |
66 |
|
67 |
for(int i = 0; i < integrableObjects.size(); i++){ |
68 |
|
69 |
if (integrableObjects[i]->isDirectional()) { |
70 |
|
71 |
integrableObjects[i]->getGrad(dAtomGrad); |
72 |
|
73 |
//gradient is equal to -f |
74 |
grad[index++] = -dAtomGrad[0]; |
75 |
grad[index++] = -dAtomGrad[1]; |
76 |
grad[index++] = -dAtomGrad[2]; |
77 |
grad[index++] = -dAtomGrad[3]; |
78 |
grad[index++] = -dAtomGrad[4]; |
79 |
grad[index++] = -dAtomGrad[5]; |
80 |
|
81 |
} |
82 |
else{ |
83 |
integrableObjects[i]->getFrc(force); |
84 |
|
85 |
grad[index++] = -force[0]; |
86 |
grad[index++] = -force[1]; |
87 |
grad[index++] = -force[2]; |
88 |
|
89 |
} |
90 |
|
91 |
} |
92 |
|
93 |
energy = tStats->getPotential(); |
94 |
|
95 |
} |
96 |
|
97 |
/** |
98 |
* |
99 |
*/ |
100 |
|
101 |
void OOPSEMinimizer::setCoor(vector<double>& x){ |
102 |
|
103 |
DirectionalAtom* dAtom; |
104 |
int index; |
105 |
double position[3]; |
106 |
double eulerAngle[3]; |
107 |
|
108 |
|
109 |
index = 0; |
110 |
|
111 |
for(int i = 0; i < integrableObjects.size(); i++){ |
112 |
|
113 |
position[0] = x[index++]; |
114 |
position[1] = x[index++]; |
115 |
position[2] = x[index++]; |
116 |
|
117 |
integrableObjects[i]->setPos(position); |
118 |
|
119 |
if (integrableObjects[i]->isDirectional()){ |
120 |
|
121 |
eulerAngle[0] = x[index++]; |
122 |
eulerAngle[1] = x[index++]; |
123 |
eulerAngle[2] = x[index++]; |
124 |
|
125 |
integrableObjects[i]->setEuler(eulerAngle[0], |
126 |
eulerAngle[1], |
127 |
eulerAngle[2]); |
128 |
|
129 |
} |
130 |
|
131 |
} |
132 |
|
133 |
} |
134 |
|
135 |
/** |
136 |
* |
137 |
*/ |
138 |
vector<double> OOPSEMinimizer::getCoor(){ |
139 |
|
140 |
DirectionalAtom* dAtom; |
141 |
int index; |
142 |
double position[3]; |
143 |
double eulerAngle[3]; |
144 |
vector<double> x; |
145 |
|
146 |
x.resize(getDim()); |
147 |
|
148 |
index = 0; |
149 |
|
150 |
for(int i = 0; i < integrableObjects.size(); i++){ |
151 |
integrableObjects[i]->getPos(position); |
152 |
|
153 |
x[index++] = position[0]; |
154 |
x[index++] = position[1]; |
155 |
x[index++] = position[2]; |
156 |
|
157 |
if (integrableObjects[i]->isDirectional()){ |
158 |
|
159 |
integrableObjects[i]->getEulerAngles(eulerAngle); |
160 |
|
161 |
x[index++] = eulerAngle[0]; |
162 |
x[index++] = eulerAngle[1]; |
163 |
x[index++] = eulerAngle[2]; |
164 |
|
165 |
} |
166 |
|
167 |
} |
168 |
|
169 |
return x; |
170 |
|
171 |
} |
172 |
|
173 |
/* |
174 |
int OOPSEMinimizer::shakeR(){ |
175 |
int i, j; |
176 |
int done; |
177 |
double posA[3], posB[3]; |
178 |
double velA[3], velB[3]; |
179 |
double pab[3]; |
180 |
double rab[3]; |
181 |
int a, b, ax, ay, az, bx, by, bz; |
182 |
double rma, rmb; |
183 |
double dx, dy, dz; |
184 |
double rpab; |
185 |
double rabsq, pabsq, rpabsq; |
186 |
double diffsq; |
187 |
double gab; |
188 |
int iteration; |
189 |
|
190 |
for (i = 0; i < nAtoms; i++){ |
191 |
moving[i] = 0; |
192 |
moved[i] = 1; |
193 |
} |
194 |
|
195 |
iteration = 0; |
196 |
done = 0; |
197 |
while (!done && (iteration < maxIteration)){ |
198 |
done = 1; |
199 |
for (i = 0; i < nConstrained; i++){ |
200 |
a = constrainedA[i]; |
201 |
b = constrainedB[i]; |
202 |
|
203 |
ax = (a * 3) + 0; |
204 |
ay = (a * 3) + 1; |
205 |
az = (a * 3) + 2; |
206 |
|
207 |
bx = (b * 3) + 0; |
208 |
by = (b * 3) + 1; |
209 |
bz = (b * 3) + 2; |
210 |
|
211 |
if (moved[a] || moved[b]){ |
212 |
atoms[a]->getPos(posA); |
213 |
atoms[b]->getPos(posB); |
214 |
|
215 |
for (j = 0; j < 3; j++) |
216 |
pab[j] = posA[j] - posB[j]; |
217 |
|
218 |
//periodic boundary condition |
219 |
|
220 |
info->wrapVector(pab); |
221 |
|
222 |
pabsq = pab[0] * pab[0] + pab[1] * pab[1] + pab[2] * pab[2]; |
223 |
|
224 |
rabsq = constrainedDsqr[i]; |
225 |
diffsq = rabsq - pabsq; |
226 |
|
227 |
// the original rattle code from alan tidesley |
228 |
if (fabs(diffsq) > (tol * rabsq * 2)){ |
229 |
rab[0] = oldPos[ax] - oldPos[bx]; |
230 |
rab[1] = oldPos[ay] - oldPos[by]; |
231 |
rab[2] = oldPos[az] - oldPos[bz]; |
232 |
|
233 |
info->wrapVector(rab); |
234 |
|
235 |
rpab = rab[0] * pab[0] + rab[1] * pab[1] + rab[2] * pab[2]; |
236 |
|
237 |
rpabsq = rpab * rpab; |
238 |
|
239 |
|
240 |
if (rpabsq < (rabsq * -diffsq)){ |
241 |
#ifdef IS_MPI |
242 |
a = atoms[a]->getGlobalIndex(); |
243 |
b = atoms[b]->getGlobalIndex(); |
244 |
#endif //is_mpi |
245 |
//cerr << "Waring: constraint failure" << endl; |
246 |
gab = sqrt(rabsq/pabsq); |
247 |
rab[0] = (posA[0] - posB[0])*gab; |
248 |
rab[1]= (posA[1] - posB[1])*gab; |
249 |
rab[2] = (posA[2] - posB[2])*gab; |
250 |
|
251 |
info->wrapVector(rab); |
252 |
|
253 |
rpab = rab[0] * pab[0] + rab[1] * pab[1] + rab[2] * pab[2]; |
254 |
|
255 |
} |
256 |
|
257 |
//rma = 1.0 / atoms[a]->getMass(); |
258 |
//rmb = 1.0 / atoms[b]->getMass(); |
259 |
rma = 1.0; |
260 |
rmb =1.0; |
261 |
|
262 |
gab = diffsq / (2.0 * (rma + rmb) * rpab); |
263 |
|
264 |
dx = rab[0] * gab; |
265 |
dy = rab[1] * gab; |
266 |
dz = rab[2] * gab; |
267 |
|
268 |
posA[0] += rma * dx; |
269 |
posA[1] += rma * dy; |
270 |
posA[2] += rma * dz; |
271 |
|
272 |
atoms[a]->setPos(posA); |
273 |
|
274 |
posB[0] -= rmb * dx; |
275 |
posB[1] -= rmb * dy; |
276 |
posB[2] -= rmb * dz; |
277 |
|
278 |
atoms[b]->setPos(posB); |
279 |
|
280 |
moving[a] = 1; |
281 |
moving[b] = 1; |
282 |
done = 0; |
283 |
} |
284 |
} |
285 |
} |
286 |
|
287 |
for (i = 0; i < nAtoms; i++){ |
288 |
moved[i] = moving[i]; |
289 |
moving[i] = 0; |
290 |
} |
291 |
|
292 |
iteration++; |
293 |
} |
294 |
|
295 |
if (!done){ |
296 |
cerr << "Waring: can not constraint within maxIteration" << endl; |
297 |
return -1; |
298 |
} |
299 |
else |
300 |
return 1; |
301 |
} |
302 |
|
303 |
|
304 |
//remove constraint force along the bond direction |
305 |
int OOPSEMinimizer::shakeF(){ |
306 |
int i, j; |
307 |
int done; |
308 |
double posA[3], posB[3]; |
309 |
double frcA[3], frcB[3]; |
310 |
double rab[3], fpab[3]; |
311 |
int a, b, ax, ay, az, bx, by, bz; |
312 |
double rma, rmb; |
313 |
double rvab; |
314 |
double gab; |
315 |
double rabsq; |
316 |
double rfab; |
317 |
int iteration; |
318 |
|
319 |
for (i = 0; i < nAtoms; i++){ |
320 |
moving[i] = 0; |
321 |
moved[i] = 1; |
322 |
} |
323 |
|
324 |
done = 0; |
325 |
iteration = 0; |
326 |
while (!done && (iteration < maxIteration)){ |
327 |
done = 1; |
328 |
|
329 |
for (i = 0; i < nConstrained; i++){ |
330 |
a = constrainedA[i]; |
331 |
b = constrainedB[i]; |
332 |
|
333 |
ax = (a * 3) + 0; |
334 |
ay = (a * 3) + 1; |
335 |
az = (a * 3) + 2; |
336 |
|
337 |
bx = (b * 3) + 0; |
338 |
by = (b * 3) + 1; |
339 |
bz = (b * 3) + 2; |
340 |
|
341 |
if (moved[a] || moved[b]){ |
342 |
|
343 |
atoms[a]->getPos(posA); |
344 |
atoms[b]->getPos(posB); |
345 |
|
346 |
for (j = 0; j < 3; j++) |
347 |
rab[j] = posA[j] - posB[j]; |
348 |
|
349 |
info->wrapVector(rab); |
350 |
|
351 |
atoms[a]->getFrc(frcA); |
352 |
atoms[b]->getFrc(frcB); |
353 |
|
354 |
//rma = 1.0 / atoms[a]->getMass(); |
355 |
//rmb = 1.0 / atoms[b]->getMass(); |
356 |
rma = 1.0; |
357 |
rmb = 1.0; |
358 |
|
359 |
|
360 |
fpab[0] = frcA[0] * rma - frcB[0] * rmb; |
361 |
fpab[1] = frcA[1] * rma - frcB[1] * rmb; |
362 |
fpab[2] = frcA[2] * rma - frcB[2] * rmb; |
363 |
|
364 |
|
365 |
gab=fpab[0] * fpab[0] + fpab[1] * fpab[1] + fpab[2] * fpab[2]; |
366 |
|
367 |
if (gab < 1.0) |
368 |
gab = 1.0; |
369 |
|
370 |
rabsq = rab[0] * rab[0] + rab[1] * rab[1] + rab[2] * rab[2]; |
371 |
rfab = rab[0] * fpab[0] + rab[1] * fpab[1] + rab[2] * fpab[2]; |
372 |
|
373 |
if (fabs(rfab) > sqrt(rabsq*gab) * 0.00001){ |
374 |
|
375 |
gab = -rfab /(rabsq*(rma + rmb)); |
376 |
|
377 |
frcA[0] = rab[0] * gab; |
378 |
frcA[1] = rab[1] * gab; |
379 |
frcA[2] = rab[2] * gab; |
380 |
|
381 |
atoms[a]->addFrc(frcA); |
382 |
|
383 |
|
384 |
frcB[0] = -rab[0] * gab; |
385 |
frcB[1] = -rab[1] * gab; |
386 |
frcB[2] = -rab[2] * gab; |
387 |
|
388 |
atoms[b]->addFrc(frcB); |
389 |
|
390 |
moving[a] = 1; |
391 |
moving[b] = 1; |
392 |
done = 0; |
393 |
} |
394 |
} |
395 |
} |
396 |
|
397 |
for (i = 0; i < nAtoms; i++){ |
398 |
moved[i] = moving[i]; |
399 |
moving[i] = 0; |
400 |
} |
401 |
|
402 |
iteration++; |
403 |
} |
404 |
|
405 |
if (!done){ |
406 |
cerr << "Waring: can not constraint within maxIteration" << endl; |
407 |
return -1; |
408 |
} |
409 |
else |
410 |
return 1; |
411 |
} |
412 |
|
413 |
*/ |
414 |
|
415 |
//calculate the value of object function |
416 |
void OOPSEMinimizer::calcF(){ |
417 |
calcEnergyGradient(curX, curG, curF, egEvalStatus); |
418 |
} |
419 |
|
420 |
void OOPSEMinimizer::calcF(vector<double>& x, double&f, int& status){ |
421 |
vector<double> tempG; |
422 |
tempG.resize(x.size()); |
423 |
|
424 |
calcEnergyGradient(x, tempG, f, status); |
425 |
} |
426 |
|
427 |
//calculate the gradient |
428 |
void OOPSEMinimizer::calcG(){ |
429 |
calcEnergyGradient(curX, curG, curF, egEvalStatus); |
430 |
} |
431 |
|
432 |
void OOPSEMinimizer::calcG(vector<double>& x, vector<double>& g, double& f, int& status){ |
433 |
calcEnergyGradient(x, g, f, status); |
434 |
} |
435 |
|
436 |
void OOPSEMinimizer::calcDim(){ |
437 |
DirectionalAtom* dAtom; |
438 |
|
439 |
ndim = 0; |
440 |
|
441 |
for(int i = 0; i < integrableObjects.size(); i++){ |
442 |
ndim += 3; |
443 |
if (integrableObjects[i]->isDirectional()) |
444 |
ndim += 3; |
445 |
} |
446 |
} |
447 |
|
448 |
void OOPSEMinimizer::setX(vector < double > & x){ |
449 |
|
450 |
if (x.size() != ndim && bVerbose){ |
451 |
//sprintf(painCave.errMsg, |
452 |
// "OOPSEMinimizer Error: dimesion of x and curX does not match\n"); |
453 |
// painCave.isFatal = 1; |
454 |
// simError(); |
455 |
} |
456 |
|
457 |
curX = x; |
458 |
} |
459 |
|
460 |
void OOPSEMinimizer::setG(vector < double > & g){ |
461 |
|
462 |
if (g.size() != ndim && bVerbose){ |
463 |
//sprintf(painCave.errMsg, |
464 |
// "OOPSEMinimizer Error: dimesion of g and curG does not match\n"); |
465 |
// painCave.isFatal = 1; |
466 |
//simError(); |
467 |
} |
468 |
|
469 |
curG = g; |
470 |
} |
471 |
|
472 |
void OOPSEMinimizer::writeOut(vector<double>& x, double iter){ |
473 |
|
474 |
setX(x); |
475 |
|
476 |
calcG(); |
477 |
|
478 |
dumpOut->writeDump(iter); |
479 |
statOut->writeStat(iter); |
480 |
} |
481 |
|
482 |
|
483 |
void OOPSEMinimizer::printMinimizerInfo(){ |
484 |
cout << "--------------------------------------------------------------------" << endl; |
485 |
cout << minimizerName << endl; |
486 |
cout << "minimization parameter set" << endl; |
487 |
cout << "function tolerance = " << paramSet->getFTol() << endl; |
488 |
cout << "gradient tolerance = " << paramSet->getGTol() << endl; |
489 |
cout << "step tolerance = "<< paramSet->getFTol() << endl; |
490 |
cout << "absolute gradient tolerance = " << endl; |
491 |
cout << "max iteration = " << paramSet->getMaxIteration() << endl; |
492 |
cout << "max line search iteration = " << paramSet->getLineSearchMaxIteration() <<endl; |
493 |
cout << "shake algorithm = " << bShake << endl; |
494 |
cout << "--------------------------------------------------------------------" << endl; |
495 |
|
496 |
} |
497 |
|
498 |
/** |
499 |
* In thoery, we need to find the minimum along the search direction |
500 |
* However, function evaluation is too expensive. |
501 |
* At the very begining of the problem, we check the search direction and make sure |
502 |
* it is a descent direction |
503 |
* we will compare the energy of two end points, |
504 |
* if the right end point has lower energy, we just take it |
505 |
* |
506 |
* |
507 |
* |
508 |
*/ |
509 |
|
510 |
int OOPSEMinimizer::doLineSearch(vector<double>& direction, double stepSize){ |
511 |
vector<double> xa; |
512 |
vector<double> xb; |
513 |
vector<double> xc; |
514 |
vector<double> ga; |
515 |
vector<double> gb; |
516 |
vector<double> gc; |
517 |
double fa; |
518 |
double fb; |
519 |
double fc; |
520 |
double a; |
521 |
double b; |
522 |
double c; |
523 |
int status; |
524 |
double initSlope; |
525 |
double slopeA; |
526 |
double slopeB; |
527 |
double slopeC; |
528 |
bool foundLower; |
529 |
int iter; |
530 |
int maxLSIter; |
531 |
double mu; |
532 |
double eta; |
533 |
double ftol; |
534 |
double lsTol; |
535 |
|
536 |
xa.resize(ndim); |
537 |
xb.resize(ndim); |
538 |
xc.resize(ndim); |
539 |
|
540 |
ga.resize(ndim); |
541 |
gb.resize(ndim); |
542 |
gc.resize(ndim); |
543 |
|
544 |
a = 0.0; |
545 |
fa = curF; |
546 |
xa = curX; |
547 |
ga = curG; |
548 |
c = a + stepSize; |
549 |
ftol = paramSet->getFTol(); |
550 |
lsTol = paramSet->getLineSearchTol(); |
551 |
|
552 |
//calculate the derivative at a = 0 |
553 |
slopeA = 0; |
554 |
for (size_t i = 0; i < ndim; i++) |
555 |
slopeA += curG[i]*direction[i]; |
556 |
|
557 |
initSlope = slopeA; |
558 |
|
559 |
// if going uphill, use negative gradient as searching direction |
560 |
if (slopeA > 0) { |
561 |
|
562 |
if (bVerbose){ |
563 |
cout << "LineSearch Warning: initial searching direction is not a descent searching direction, " |
564 |
<< " use negative gradient instead. Therefore, finding a smaller vaule of function " |
565 |
<< " is guaranteed" |
566 |
<< endl; |
567 |
} |
568 |
|
569 |
for (size_t i = 0; i < ndim; i++) |
570 |
direction[i] = -curG[i]; |
571 |
|
572 |
for (size_t i = 0; i < ndim; i++) |
573 |
slopeA += curG[i]*direction[i]; |
574 |
|
575 |
initSlope = slopeA; |
576 |
} |
577 |
|
578 |
// Take a trial step |
579 |
for(size_t i = 0; i < ndim; i++) |
580 |
xc[i] = curX[i] + direction[i] * c; |
581 |
|
582 |
calcG(xc, gc, fc, status); |
583 |
|
584 |
if (status < 0){ |
585 |
if (bVerbose) |
586 |
cerr << "Function Evaluation Error" << endl; |
587 |
} |
588 |
|
589 |
//calculate the derivative at c |
590 |
slopeC = 0; |
591 |
for (size_t i = 0; i < ndim; i++) |
592 |
slopeC += gc[i]*direction[i]; |
593 |
|
594 |
// found a lower point |
595 |
if (fc < fa) { |
596 |
curX = xc; |
597 |
curG = gc; |
598 |
curF = fc; |
599 |
return LS_SUCCEED; |
600 |
} |
601 |
else { |
602 |
|
603 |
if (slopeC > 0) |
604 |
stepSize *= 0.618034; |
605 |
} |
606 |
|
607 |
maxLSIter = paramSet->getLineSearchMaxIteration(); |
608 |
|
609 |
iter = 0; |
610 |
|
611 |
do { |
612 |
// Select a new trial point. |
613 |
// If the derivatives at points a & c have different sign we use cubic interpolate |
614 |
//if (slopeC > 0){ |
615 |
eta = 3 *(fa -fc) /(c - a) + slopeA + slopeC; |
616 |
mu = sqrt(eta * eta - slopeA * slopeC); |
617 |
b = a + (c - a) * (1 - (slopeC + mu - eta) /(slopeC - slopeA + 2 * mu)); |
618 |
|
619 |
if (b < lsTol){ |
620 |
if (bVerbose) |
621 |
cout << "stepSize is less than line search tolerance" << endl; |
622 |
break; |
623 |
} |
624 |
//} |
625 |
|
626 |
// Take a trial step to this new point - new coords in xb |
627 |
for(size_t i = 0; i < ndim; i++) |
628 |
xb[i] = curX[i] + direction[i] * b; |
629 |
|
630 |
//function evaluation |
631 |
calcG(xb, gb, fb, status); |
632 |
|
633 |
if (status < 0){ |
634 |
if (bVerbose) |
635 |
cerr << "Function Evaluation Error" << endl; |
636 |
} |
637 |
|
638 |
//calculate the derivative at c |
639 |
slopeB = 0; |
640 |
for (size_t i = 0; i < ndim; i++) |
641 |
slopeB += gb[i]*direction[i]; |
642 |
|
643 |
//Amijo Rule to stop the line search |
644 |
if (fb <= curF + initSlope * ftol * b) { |
645 |
curF = fb; |
646 |
curX = xb; |
647 |
curG = gb; |
648 |
return LS_SUCCEED; |
649 |
} |
650 |
|
651 |
if (slopeB <0 && fb < fa) { |
652 |
//replace a by b |
653 |
fa = fb; |
654 |
a = b; |
655 |
slopeA = slopeB; |
656 |
|
657 |
// swap coord a/b |
658 |
std::swap(xa, xb); |
659 |
std::swap(ga, gb); |
660 |
} |
661 |
else { |
662 |
//replace c by b |
663 |
fc = fb; |
664 |
c = b; |
665 |
slopeC = slopeB; |
666 |
|
667 |
// swap coord b/c |
668 |
std::swap(gb, gc); |
669 |
std::swap(xb, xc); |
670 |
} |
671 |
|
672 |
|
673 |
iter++; |
674 |
} while((fb > fa || fb > fc) && (iter < maxLSIter)); |
675 |
|
676 |
if(fb < curF || iter >= maxLSIter) { |
677 |
//could not find a lower value, we might just go uphill. |
678 |
return LS_ERROR; |
679 |
} |
680 |
|
681 |
//select the end point |
682 |
|
683 |
if (fa <= fc) { |
684 |
curX = xa; |
685 |
curG = ga; |
686 |
curF = fa; |
687 |
} |
688 |
else { |
689 |
curX = xc; |
690 |
curG = gc; |
691 |
curF = fc; |
692 |
} |
693 |
|
694 |
return LS_SUCCEED; |
695 |
|
696 |
} |
697 |
|
698 |
void OOPSEMinimizer::minimize(){ |
699 |
|
700 |
int convgStatus; |
701 |
int stepStatus; |
702 |
int maxIter; |
703 |
//int resetFrq; |
704 |
//int nextResetIter; |
705 |
int writeFrq; |
706 |
int nextWriteIter; |
707 |
|
708 |
if (bVerbose) |
709 |
printMinimizerInfo(); |
710 |
|
711 |
dumpOut = new DumpWriter(info); |
712 |
statOut = new StatWriter(info); |
713 |
|
714 |
init(); |
715 |
|
716 |
//resetFrq = paramSet->getResetFrq(); |
717 |
//nextResetIter = resetFrq; |
718 |
|
719 |
writeFrq = paramSet->getWriteFrq(); |
720 |
nextWriteIter = writeFrq; |
721 |
|
722 |
maxIter = paramSet->getMaxIteration(); |
723 |
|
724 |
for (curIter = 1; curIter <= maxIter; curIter++){ |
725 |
|
726 |
stepStatus = step(); |
727 |
|
728 |
if (bShake) |
729 |
shakeAlgo->doPreConstraint(); |
730 |
|
731 |
if (stepStatus < 0){ |
732 |
saveResult(); |
733 |
minStatus = MIN_LSERROR; |
734 |
cerr << "OOPSEMinimizer Error: line search error, please try a small stepsize" << endl; |
735 |
return; |
736 |
} |
737 |
|
738 |
if (curIter == nextWriteIter){ |
739 |
nextWriteIter += writeFrq; |
740 |
writeOut(curX, curIter); |
741 |
} |
742 |
|
743 |
convgStatus = checkConvg(); |
744 |
|
745 |
if (convgStatus > 0){ |
746 |
saveResult(); |
747 |
minStatus = MIN_CONVERGE; |
748 |
return; |
749 |
} |
750 |
|
751 |
prepareStep(); |
752 |
|
753 |
} |
754 |
|
755 |
|
756 |
if (bVerbose) { |
757 |
cout << "OOPSEMinimizer Warning: " |
758 |
<< minimizerName << " algorithm did not converge within " |
759 |
<< maxIter << " iteration" << endl; |
760 |
} |
761 |
minStatus = MIN_MAXITER; |
762 |
saveResult(); |
763 |
|
764 |
} |