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