Line data Source code
1 : /* +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
2 : Copyright (c) 2017-2023 The plumed team
3 : (see the PEOPLE file at the root of the distribution for a list of names)
4 :
5 : See http://www.plumed.org for more information.
6 :
7 : This file is part of plumed, version 2.
8 :
9 : plumed is free software: you can redistribute it and/or modify
10 : it under the terms of the GNU Lesser General Public License as published by
11 : the Free Software Foundation, either version 3 of the License, or
12 : (at your option) any later version.
13 :
14 : plumed is distributed in the hope that it will be useful,
15 : but WITHOUT ANY WARRANTY; without even the implied warranty of
16 : MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
17 : GNU Lesser General Public License for more details.
18 :
19 : You should have received a copy of the GNU Lesser General Public License
20 : along with plumed. If not, see <http://www.gnu.org/licenses/>.
21 : +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ */
22 : /*
23 :
24 : */
25 : #include "bias/Bias.h"
26 : #include "core/ActionRegister.h"
27 : #include "core/PlumedMain.h"
28 : #include "core/Value.h"
29 : #include "tools/File.h"
30 : #include "tools/Random.h"
31 : #include "tools/Communicator.h"
32 : #include <ctime>
33 :
34 : namespace PLMD {
35 : namespace isdb {
36 :
37 : //+PLUMEDOC ISDB_BIAS RESCALE
38 : /*
39 : Scales the value of an another action, being a Collective Variable or a Bias.
40 :
41 : The rescaling factor is determined by a parameter defined on a logarithmic grid of dimension NBIN in the range
42 : from 1 to MAX_RESCALE. The current value of the rescaling parameter is stored and shared across
43 : other actions using a \ref SELECTOR. A Monte Carlo procedure is used to update the value
44 : of the rescaling factor every MC_STRIDE steps of molecular dynamics. Well-tempered metadynamics, defined by the
45 : parameters W0 and BIASFACTOR, is used to enhance the sampling in the space of the rescaling factor.
46 : The well-tempered metadynamics bias potential is written to the file BFILE every BSTRIDE steps and read
47 : when restarting the simulation using the directive \ref RESTART.
48 :
49 : \note
50 : Additional arguments not to be scaled, one for each bin in the rescaling parameter ladder, can be
51 : provided at the end of the ARG list. The number of such arguments is specified by the option NOT_RESCALED.
52 : These arguments will be not be scaled, but they will be
53 : considered as bias potentials and used in the computation of the Metropolis
54 : acceptance probability when proposing a move in the rescaling parameter. See example below.
55 :
56 : \note
57 : If PLUMED is running in a multiple-replica framework (for example using the -multi option in GROMACS),
58 : the arguments will be summed across replicas, unless the NOT_SHARED option is used. Also, the value of the
59 : \ref SELECTOR will be shared and thus will be the same in all replicas.
60 :
61 : \par Examples
62 :
63 : In this example we use \ref RESCALE to implement a simulated-tempering like approach.
64 : The total potential energy of the system is scaled by a parameter defined on a logarithmic grid
65 : of 5 bins in the range from 1 to 1.5.
66 : A well-tempered metadynamics bias potential is used to ensure diffusion in the space of the rescaling
67 : parameter.
68 :
69 : \plumedfile
70 : ene: ENERGY
71 :
72 : SELECTOR NAME=GAMMA VALUE=0
73 :
74 : RESCALE ...
75 : LABEL=res ARG=ene TEMP=300
76 : SELECTOR=GAMMA MAX_RESCALE=1.5 NBIN=5
77 : W0=1000 BIASFACTOR=100.0 BSTRIDE=2000 BFILE=bias.dat
78 : ...
79 :
80 : PRINT FILE=COLVAR ARG=* STRIDE=100
81 : \endplumedfile
82 :
83 : In this second example, we add to the simulated-tempering approach introduced above
84 : one Parallel Bias metadynamics simulation (see \ref PBMETAD) for each value of the rescaling parameter.
85 : At each moment of the simulation, only one of the \ref PBMETAD
86 : actions is activated, based on the current value of the associated \ref SELECTOR.
87 : The \ref PBMETAD bias potentials are not scaled, but just used in the calculation of
88 : the Metropolis acceptance probability when proposing a move in the rescaling parameter.
89 :
90 : \plumedfile
91 : ene: ENERGY
92 : d: DISTANCE ATOMS=1,2
93 :
94 : SELECTOR NAME=GAMMA VALUE=0
95 :
96 : pbmetad0: PBMETAD ARG=d SELECTOR=GAMMA SELECTOR_ID=0 SIGMA=0.1 PACE=500 HEIGHT=1 BIASFACTOR=8 FILE=HILLS.0
97 : pbmetad1: PBMETAD ARG=d SELECTOR=GAMMA SELECTOR_ID=1 SIGMA=0.1 PACE=500 HEIGHT=1 BIASFACTOR=8 FILE=HILLS.1
98 : pbmetad2: PBMETAD ARG=d SELECTOR=GAMMA SELECTOR_ID=2 SIGMA=0.1 PACE=500 HEIGHT=1 BIASFACTOR=8 FILE=HILLS.2
99 : pbmetad3: PBMETAD ARG=d SELECTOR=GAMMA SELECTOR_ID=3 SIGMA=0.1 PACE=500 HEIGHT=1 BIASFACTOR=8 FILE=HILLS.3
100 : pbmetad4: PBMETAD ARG=d SELECTOR=GAMMA SELECTOR_ID=4 SIGMA=0.1 PACE=500 HEIGHT=1 BIASFACTOR=8 FILE=HILLS.4
101 :
102 : RESCALE ...
103 : LABEL=res TEMP=300
104 : ARG=ene,pbmetad0.bias,pbmetad1.bias,pbmetad2.bias,pbmetad3.bias,pbmetad4.bias
105 : SELECTOR=GAMMA MAX_RESCALE=1.5 NOT_RESCALED=5 NBIN=5
106 : W0=1000 BIASFACTOR=100.0 BSTRIDE=2000 BFILE=bias.dat
107 : ...
108 :
109 : PRINT FILE=COLVAR ARG=* STRIDE=100
110 : \endplumedfile
111 :
112 :
113 :
114 : */
115 : //+ENDPLUMEDOC
116 :
117 : class Rescale : public bias::Bias {
118 : // gamma parameter
119 : std::vector<double> gamma_;
120 : double w0_;
121 : double biasf_;
122 : std::vector<double> bias_;
123 : std::vector<double> expo_;
124 : std::vector<unsigned> shared_;
125 : unsigned nores_;
126 : // bias
127 : unsigned int Biasstride_;
128 : unsigned int Biaspace_;
129 : std::string Biasfilename_;
130 : bool first_bias_;
131 : OFile Biasfile_;
132 : // temperature in kbt
133 : double kbt_;
134 : // Monte Carlo stuff
135 : unsigned MCsteps_;
136 : unsigned MCstride_;
137 : long long int MCfirst_;
138 : long long unsigned MCaccgamma_;
139 : // replica stuff
140 : unsigned nrep_;
141 : unsigned replica_;
142 : // selector
143 : std::string selector_;
144 :
145 : // Monte Carlo
146 : void doMonteCarlo(unsigned igamma, double oldE, const std::vector<double> & args, const std::vector<double> & bargs);
147 : unsigned proposeMove(unsigned x, unsigned xmin, unsigned xmax);
148 : bool doAccept(double oldE, double newE);
149 : // read and print bias
150 : void read_bias();
151 : void print_bias(long long int step);
152 :
153 : public:
154 : explicit Rescale(const ActionOptions&);
155 : ~Rescale();
156 : void calculate();
157 : static void registerKeywords(Keywords& keys);
158 : };
159 :
160 :
161 : PLUMED_REGISTER_ACTION(Rescale,"RESCALE")
162 :
163 2 : void Rescale::registerKeywords(Keywords& keys) {
164 2 : Bias::registerKeywords(keys);
165 2 : keys.use("ARG");
166 4 : keys.add("compulsory","TEMP","temperature");
167 4 : keys.add("compulsory","SELECTOR", "name of the SELECTOR used for rescaling");
168 4 : keys.add("compulsory","MAX_RESCALE","maximum values for rescaling");
169 4 : keys.add("compulsory","NBIN","number of bins for gamma grid");
170 4 : keys.add("compulsory","W0", "initial bias height");
171 4 : keys.add("compulsory","BIASFACTOR", "bias factor");
172 4 : keys.add("compulsory","BSTRIDE", "stride for writing bias");
173 4 : keys.add("compulsory","BFILE", "file name for bias");
174 4 : keys.add("optional","NOT_SHARED", "list of arguments (from 1 to N) not summed across replicas");
175 4 : keys.add("optional","NOT_RESCALED", "these last N arguments will not be scaled");
176 4 : keys.add("optional","MC_STEPS","number of MC steps");
177 4 : keys.add("optional","MC_STRIDE","MC stride");
178 4 : keys.add("optional","PACE", "Pace for adding bias, in MC stride unit");
179 4 : keys.addOutputComponent("igamma", "default","gamma parameter");
180 4 : keys.addOutputComponent("accgamma","default","MC acceptance for gamma");
181 4 : keys.addOutputComponent("wtbias", "default","well-tempered bias");
182 2 : }
183 :
184 0 : Rescale::Rescale(const ActionOptions&ao):
185 : PLUMED_BIAS_INIT(ao),
186 0 : nores_(0), Biaspace_(1), first_bias_(true),
187 0 : MCsteps_(1), MCstride_(1), MCfirst_(-1), MCaccgamma_(0) {
188 : // set up replica stuff
189 0 : if(comm.Get_rank()==0) {
190 0 : nrep_ = multi_sim_comm.Get_size();
191 0 : replica_ = multi_sim_comm.Get_rank();
192 : } else {
193 0 : nrep_ = 0;
194 0 : replica_ = 0;
195 : }
196 0 : comm.Sum(&nrep_,1);
197 0 : comm.Sum(&replica_,1);
198 :
199 : // wt-parameters
200 0 : parse("W0", w0_);
201 0 : parse("BIASFACTOR", biasf_);
202 :
203 : // selector name
204 0 : parse("SELECTOR", selector_);
205 :
206 : // number of bins for gamma ladder
207 : unsigned nbin;
208 0 : parse("NBIN", nbin);
209 :
210 : // number of bias
211 0 : parse("NOT_RESCALED", nores_);
212 0 : if(nores_>0 && nores_!=nbin) {
213 0 : error("The number of non scaled arguments must be equal to either 0 or the number of bins");
214 : }
215 :
216 : // maximum value of rescale
217 : std::vector<double> max_rescale;
218 0 : parseVector("MAX_RESCALE", max_rescale);
219 : // check dimension of max_rescale
220 0 : if(max_rescale.size()!=(getNumberOfArguments()-nores_)) {
221 0 : error("Size of MAX_RESCALE array must be equal to the number of arguments that will to be scaled");
222 : }
223 :
224 : // calculate exponents
225 0 : double igamma_max = static_cast<double>(nbin);
226 0 : for(unsigned i=0; i<max_rescale.size(); ++i) {
227 0 : expo_.push_back(std::log(max_rescale[i])/std::log(igamma_max));
228 : }
229 :
230 : // allocate gamma grid and set bias to zero
231 0 : for(unsigned i=0; i<nbin; ++i) {
232 : // bias grid
233 0 : bias_.push_back(0.0);
234 : // gamma ladder
235 0 : double gamma = std::exp( static_cast<double>(i) / static_cast<double>(nbin-1) * std::log(igamma_max) );
236 0 : gamma_.push_back(gamma);
237 : }
238 : // print bias to file
239 0 : parse("BSTRIDE", Biasstride_);
240 0 : parse("BFILE", Biasfilename_);
241 :
242 : // create vectors of shared arguments
243 : // by default they are all shared
244 0 : for(unsigned i=0; i<getNumberOfArguments(); ++i) {
245 0 : shared_.push_back(1);
246 : }
247 : // share across replicas or not
248 : std::vector<unsigned> not_shared;
249 0 : parseVector("NOT_SHARED", not_shared);
250 : // and change the non-shared
251 0 : for(unsigned i=0; i<not_shared.size(); ++i) {
252 0 : if((not_shared[i]-1)>=(getNumberOfArguments()-nores_) && nrep_>1) {
253 0 : error("NOT_RESCALED args must always be shared when using multiple replicas");
254 : }
255 0 : if((not_shared[i]-1)>=getNumberOfArguments()) {
256 0 : error("NOT_SHARED args should be lower than total number of arguments");
257 : }
258 0 : shared_[not_shared[i]-1] = 0;
259 : }
260 :
261 : // monte carlo stuff
262 0 : parse("MC_STEPS",MCsteps_);
263 0 : parse("MC_STRIDE",MCstride_);
264 : // adjust for multiple-time steps
265 0 : MCstride_ *= getStride();
266 : // read bias deposition pace
267 0 : parse("PACE", Biaspace_);
268 : // multiply by MCstride
269 0 : Biaspace_ *= MCstride_;
270 :
271 : // get temperature
272 0 : kbt_=getkBT();
273 :
274 0 : checkRead();
275 :
276 0 : log.printf(" temperature of the system in energy unit %f\n",kbt_);
277 0 : log.printf(" name of the SELECTOR use for this action %s\n",selector_.c_str());
278 0 : log.printf(" number of bins in grid %u\n",nbin);
279 0 : log.printf(" number of arguments that will not be scaled %u\n",nores_);
280 0 : if(nrep_>1) {
281 0 : log<<" number of arguments that will not be summed across replicas "<<not_shared.size()<<"\n";
282 : }
283 0 : log.printf(" biasfactor %f\n",biasf_);
284 0 : log.printf(" initial hills height %f\n",w0_);
285 0 : log.printf(" stride to write bias to file %u\n",Biasstride_);
286 0 : log.printf(" write bias to file : %s\n",Biasfilename_.c_str());
287 0 : log.printf(" number of replicas %u\n",nrep_);
288 0 : log.printf(" number of MC steps %d\n",MCsteps_);
289 0 : log.printf(" do MC every %d steps\n", MCstride_);
290 0 : log.printf("\n");
291 :
292 0 : log << " Bibliography" << plumed.cite("Bonomi, Camilloni, Bioinformatics, 33, 3999 (2017)") << "\n";
293 :
294 :
295 : // add components
296 0 : addComponent("igamma");
297 0 : componentIsNotPeriodic("igamma");
298 0 : addComponent("accgamma");
299 0 : componentIsNotPeriodic("accgamma");
300 0 : addComponent("wtbias");
301 0 : componentIsNotPeriodic("wtbias");
302 :
303 : // initialize random seed
304 0 : srand (time(NULL));
305 :
306 : // read bias if restarting
307 0 : if(getRestart()) {
308 0 : read_bias();
309 : }
310 0 : }
311 :
312 0 : Rescale::~Rescale() {
313 0 : Biasfile_.close();
314 0 : }
315 :
316 0 : void Rescale::read_bias() {
317 : // open file
318 : auto ifile=Tools::make_unique<IFile>();
319 0 : ifile->link(*this);
320 0 : if(ifile->FileExist(Biasfilename_)) {
321 0 : ifile->open(Biasfilename_);
322 : // read all the lines, store last value of bias
323 : double MDtime;
324 0 : while(ifile->scanField("MD_time",MDtime)) {
325 0 : for(unsigned i=0; i<bias_.size(); ++i) {
326 : // convert i to string
327 0 : std::stringstream ss;
328 : ss << i;
329 : // label
330 0 : std::string label = "b" + ss.str();
331 : // read entry
332 0 : ifile->scanField(label, bias_[i]);
333 0 : }
334 : // new line
335 0 : ifile->scanField();
336 : }
337 0 : ifile->close();
338 : } else {
339 0 : error("Cannot find bias file "+Biasfilename_+"\n");
340 : }
341 0 : }
342 :
343 0 : unsigned Rescale::proposeMove(unsigned x, unsigned xmin, unsigned xmax) {
344 0 : int xmin_i = static_cast<int>(xmin);
345 0 : int xmax_i = static_cast<int>(xmax);
346 : int dx;
347 0 : int r = rand() % 2;
348 0 : if( r % 2 == 0 ) {
349 : dx = +1;
350 : } else {
351 : dx = -1;
352 : }
353 : // new index, integer
354 0 : int x_new = static_cast<int>(x) + dx;
355 : // check boundaries
356 0 : if(x_new >= xmax_i) {
357 0 : x_new = xmax_i-1;
358 : }
359 : if(x_new < xmin_i) {
360 : x_new = xmin_i;
361 : }
362 0 : return static_cast<unsigned>(x_new);
363 : }
364 :
365 0 : bool Rescale::doAccept(double oldE, double newE) {
366 : bool accept = false;
367 : // calculate delta energy
368 0 : double delta = ( newE - oldE ) / kbt_;
369 : // if delta is negative always accept move
370 0 : if( delta < 0.0 ) {
371 : accept = true;
372 : } else {
373 : // otherwise extract random number
374 0 : double s = static_cast<double>(rand()) / RAND_MAX;
375 0 : if( s < std::exp(-delta) ) {
376 : accept = true;
377 : }
378 : }
379 0 : return accept;
380 : }
381 :
382 0 : void Rescale::doMonteCarlo(unsigned igamma, double oldE,
383 : const std::vector<double> & args, const std::vector<double> & bargs) {
384 : double oldB, newB;
385 :
386 : // cycle on MC steps
387 0 : for(unsigned i=0; i<MCsteps_; ++i) {
388 : // propose move in igamma
389 0 : unsigned new_igamma = proposeMove(igamma, 0, gamma_.size());
390 : // calculate new energy
391 : double newE = 0.0;
392 0 : for(unsigned j=0; j<args.size(); ++j) {
393 : // calculate energy term
394 0 : double fact = 1.0/pow(gamma_[new_igamma], expo_[j]) - 1.0;
395 0 : newE += args[j] * fact;
396 : }
397 : // calculate contributions from non-rescaled terms
398 0 : if(bargs.size()>0) {
399 0 : oldB = bias_[igamma]+bargs[igamma];
400 0 : newB = bias_[new_igamma]+bargs[new_igamma];
401 : } else {
402 0 : oldB = bias_[igamma];
403 0 : newB = bias_[new_igamma];
404 : }
405 : // accept or reject
406 0 : bool accept = doAccept(oldE+oldB, newE+newB);
407 0 : if(accept) {
408 0 : igamma = new_igamma;
409 : oldE = newE;
410 0 : MCaccgamma_++;
411 : }
412 : }
413 : // send values of gamma to all replicas
414 0 : if(comm.Get_rank()==0) {
415 0 : if(multi_sim_comm.Get_rank()!=0) {
416 0 : igamma = 0;
417 : }
418 0 : multi_sim_comm.Sum(&igamma, 1);
419 : } else {
420 0 : igamma = 0;
421 : }
422 : // local communication
423 0 : comm.Sum(&igamma, 1);
424 :
425 : // set the value of gamma into passMap
426 0 : plumed.passMap[selector_]=static_cast<double>(igamma);
427 0 : }
428 :
429 0 : void Rescale::print_bias(long long int step) {
430 : // if first time open the file
431 0 : if(first_bias_) {
432 0 : first_bias_ = false;
433 0 : Biasfile_.link(*this);
434 0 : Biasfile_.open(Biasfilename_);
435 : Biasfile_.setHeavyFlush();
436 0 : Biasfile_.fmtField("%30.5f");
437 : }
438 :
439 : // write fields
440 0 : double MDtime = static_cast<double>(step)*getTimeStep();
441 0 : Biasfile_.printField("MD_time", MDtime);
442 0 : for(unsigned i=0; i<bias_.size(); ++i) {
443 : // convert i to string
444 0 : std::stringstream ss;
445 : ss << i;
446 : // label
447 0 : std::string label = "b" + ss.str();
448 : // print entry
449 0 : Biasfile_.printField(label, bias_[i]);
450 0 : }
451 0 : Biasfile_.printField();
452 0 : }
453 :
454 0 : void Rescale::calculate() {
455 : // get the current value of the selector
456 0 : unsigned igamma = static_cast<unsigned>(plumed.passMap[selector_]);
457 :
458 : // collect data from other replicas
459 0 : std::vector<double> all_args(getNumberOfArguments(), 0.0);
460 : // first calculate arguments
461 0 : for(unsigned i=0; i<all_args.size(); ++i) {
462 0 : double arg = getArgument(i);
463 : // sum shared arguments across replicas
464 0 : if(shared_[i]==1) {
465 0 : if(comm.Get_rank()==0) {
466 0 : multi_sim_comm.Sum(arg);
467 : } else {
468 0 : arg = 0.0;
469 : }
470 0 : if(comm.Get_size()>1) {
471 0 : comm.Sum(arg);
472 : }
473 : }
474 : // put into all_args
475 0 : all_args[i] = arg;
476 : }
477 :
478 : // now separate terms that should be rescaled
479 : std::vector<double> args;
480 0 : if(getNumberOfArguments()-nores_>0) {
481 0 : args.resize(getNumberOfArguments()-nores_);
482 : }
483 0 : for(unsigned i=0; i<args.size(); ++i) {
484 0 : args[i] = all_args[i];
485 : }
486 : // and terms that should not
487 : std::vector<double> bargs;
488 0 : if(nores_>0) {
489 0 : bargs.resize(nores_);
490 : }
491 0 : for(unsigned i=0; i<bargs.size(); ++i) {
492 0 : bargs[i] = all_args[i+args.size()];
493 : }
494 :
495 : // calculate energy and forces, only on rescaled terms
496 : double ene = 0.0;
497 0 : for(unsigned i=0; i<args.size(); ++i) {
498 : // calculate energy term
499 0 : double fact = 1.0/pow(gamma_[igamma], expo_[i]) - 1.0;
500 0 : ene += args[i] * fact;
501 : // add force
502 0 : setOutputForce(i, -fact);
503 : }
504 :
505 : // set to zero on the others
506 0 : for(unsigned i=0; i<bargs.size(); ++i) {
507 0 : setOutputForce(i+args.size(), 0.0);
508 : }
509 :
510 : // set value of the bias
511 0 : setBias(ene);
512 : // set value of the wt-bias
513 0 : getPntrToComponent("wtbias")->set(bias_[igamma]);
514 : // set values of gamma
515 0 : getPntrToComponent("igamma")->set(igamma);
516 : // get time step
517 0 : long long int step = getStep();
518 0 : if(MCfirst_==-1) {
519 0 : MCfirst_=step;
520 : }
521 : // calculate gamma acceptance
522 0 : double MCtrials = std::floor(static_cast<double>(step-MCfirst_) / static_cast<double>(MCstride_))+1.0;
523 0 : double accgamma = static_cast<double>(MCaccgamma_) / static_cast<double>(MCsteps_) / MCtrials;
524 0 : getPntrToComponent("accgamma")->set(accgamma);
525 :
526 : // do MC at the right time step
527 0 : if(step%MCstride_==0&&!getExchangeStep()) {
528 0 : doMonteCarlo(igamma, ene, args, bargs);
529 : }
530 :
531 : // add well-tempered like bias
532 0 : if(step%Biaspace_==0) {
533 : // get updated igamma
534 0 : unsigned igamma = static_cast<unsigned>(plumed.passMap[selector_]);
535 : // add "Gaussian"
536 0 : double kbDT = kbt_ * ( biasf_ - 1.0 );
537 0 : bias_[igamma] += w0_ * std::exp(-bias_[igamma] / kbDT);
538 : }
539 :
540 : // print bias
541 0 : if(step%Biasstride_==0) {
542 0 : print_bias(step);
543 : }
544 :
545 0 : }
546 :
547 :
548 : }
549 : }
550 :
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