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.add("compulsory","TEMP","temperature");
166 2 : keys.add("compulsory","SELECTOR", "name of the SELECTOR used for rescaling");
167 2 : keys.add("compulsory","MAX_RESCALE","maximum values for rescaling");
168 2 : keys.add("compulsory","NBIN","number of bins for gamma grid");
169 2 : keys.add("compulsory","W0", "initial bias height");
170 2 : keys.add("compulsory","BIASFACTOR", "bias factor");
171 2 : keys.add("compulsory","BSTRIDE", "stride for writing bias");
172 2 : keys.add("compulsory","BFILE", "file name for bias");
173 2 : keys.add("optional","NOT_SHARED", "list of arguments (from 1 to N) not summed across replicas");
174 2 : keys.add("optional","NOT_RESCALED", "these last N arguments will not be scaled");
175 2 : keys.add("optional","MC_STEPS","number of MC steps");
176 2 : keys.add("optional","MC_STRIDE","MC stride");
177 2 : keys.add("optional","PACE", "Pace for adding bias, in MC stride unit");
178 4 : keys.addOutputComponent("igamma", "default","scalar","gamma parameter");
179 4 : keys.addOutputComponent("accgamma","default","scalar","MC acceptance for gamma");
180 4 : keys.addOutputComponent("wtbias", "default","scalar","well-tempered bias");
181 2 : }
182 :
183 0 : Rescale::Rescale(const ActionOptions&ao):
184 : PLUMED_BIAS_INIT(ao),
185 0 : nores_(0), Biaspace_(1), first_bias_(true),
186 0 : MCsteps_(1), MCstride_(1), MCfirst_(-1), MCaccgamma_(0) {
187 : // set up replica stuff
188 0 : if(comm.Get_rank()==0) {
189 0 : nrep_ = multi_sim_comm.Get_size();
190 0 : replica_ = multi_sim_comm.Get_rank();
191 : } else {
192 0 : nrep_ = 0;
193 0 : replica_ = 0;
194 : }
195 0 : comm.Sum(&nrep_,1);
196 0 : comm.Sum(&replica_,1);
197 :
198 : // wt-parameters
199 0 : parse("W0", w0_);
200 0 : parse("BIASFACTOR", biasf_);
201 :
202 : // selector name
203 0 : parse("SELECTOR", selector_);
204 :
205 : // number of bins for gamma ladder
206 : unsigned nbin;
207 0 : parse("NBIN", nbin);
208 :
209 : // number of bias
210 0 : parse("NOT_RESCALED", nores_);
211 0 : if(nores_>0 && nores_!=nbin) {
212 0 : error("The number of non scaled arguments must be equal to either 0 or the number of bins");
213 : }
214 :
215 : // maximum value of rescale
216 : std::vector<double> max_rescale;
217 0 : parseVector("MAX_RESCALE", max_rescale);
218 : // check dimension of max_rescale
219 0 : if(max_rescale.size()!=(getNumberOfArguments()-nores_)) {
220 0 : error("Size of MAX_RESCALE array must be equal to the number of arguments that will to be scaled");
221 : }
222 :
223 : // calculate exponents
224 0 : double igamma_max = static_cast<double>(nbin);
225 0 : for(unsigned i=0; i<max_rescale.size(); ++i) {
226 0 : expo_.push_back(std::log(max_rescale[i])/std::log(igamma_max));
227 : }
228 :
229 : // allocate gamma grid and set bias to zero
230 0 : for(unsigned i=0; i<nbin; ++i) {
231 : // bias grid
232 0 : bias_.push_back(0.0);
233 : // gamma ladder
234 0 : double gamma = std::exp( static_cast<double>(i) / static_cast<double>(nbin-1) * std::log(igamma_max) );
235 0 : gamma_.push_back(gamma);
236 : }
237 : // print bias to file
238 0 : parse("BSTRIDE", Biasstride_);
239 0 : parse("BFILE", Biasfilename_);
240 :
241 : // create vectors of shared arguments
242 : // by default they are all shared
243 0 : for(unsigned i=0; i<getNumberOfArguments(); ++i) {
244 0 : shared_.push_back(1);
245 : }
246 : // share across replicas or not
247 : std::vector<unsigned> not_shared;
248 0 : parseVector("NOT_SHARED", not_shared);
249 : // and change the non-shared
250 0 : for(unsigned i=0; i<not_shared.size(); ++i) {
251 0 : if((not_shared[i]-1)>=(getNumberOfArguments()-nores_) && nrep_>1) {
252 0 : error("NOT_RESCALED args must always be shared when using multiple replicas");
253 : }
254 0 : if((not_shared[i]-1)>=getNumberOfArguments()) {
255 0 : error("NOT_SHARED args should be lower than total number of arguments");
256 : }
257 0 : shared_[not_shared[i]-1] = 0;
258 : }
259 :
260 : // monte carlo stuff
261 0 : parse("MC_STEPS",MCsteps_);
262 0 : parse("MC_STRIDE",MCstride_);
263 : // adjust for multiple-time steps
264 0 : MCstride_ *= getStride();
265 : // read bias deposition pace
266 0 : parse("PACE", Biaspace_);
267 : // multiply by MCstride
268 0 : Biaspace_ *= MCstride_;
269 :
270 : // get temperature
271 0 : kbt_=getkBT();
272 :
273 0 : checkRead();
274 :
275 0 : log.printf(" temperature of the system in energy unit %f\n",kbt_);
276 0 : log.printf(" name of the SELECTOR use for this action %s\n",selector_.c_str());
277 0 : log.printf(" number of bins in grid %u\n",nbin);
278 0 : log.printf(" number of arguments that will not be scaled %u\n",nores_);
279 0 : if(nrep_>1) {
280 0 : log<<" number of arguments that will not be summed across replicas "<<not_shared.size()<<"\n";
281 : }
282 0 : log.printf(" biasfactor %f\n",biasf_);
283 0 : log.printf(" initial hills height %f\n",w0_);
284 0 : log.printf(" stride to write bias to file %u\n",Biasstride_);
285 0 : log.printf(" write bias to file : %s\n",Biasfilename_.c_str());
286 0 : log.printf(" number of replicas %u\n",nrep_);
287 0 : log.printf(" number of MC steps %d\n",MCsteps_);
288 0 : log.printf(" do MC every %d steps\n", MCstride_);
289 0 : log.printf("\n");
290 :
291 0 : log << " Bibliography" << plumed.cite("Bonomi, Camilloni, Bioinformatics, 33, 3999 (2017)") << "\n";
292 :
293 :
294 : // add components
295 0 : addComponent("igamma");
296 0 : componentIsNotPeriodic("igamma");
297 0 : addComponent("accgamma");
298 0 : componentIsNotPeriodic("accgamma");
299 0 : addComponent("wtbias");
300 0 : componentIsNotPeriodic("wtbias");
301 :
302 : // initialize random seed
303 0 : srand (time(NULL));
304 :
305 : // read bias if restarting
306 0 : if(getRestart()) {
307 0 : read_bias();
308 : }
309 0 : }
310 :
311 0 : Rescale::~Rescale() {
312 0 : Biasfile_.close();
313 0 : }
314 :
315 0 : void Rescale::read_bias() {
316 : // open file
317 : auto ifile=Tools::make_unique<IFile>();
318 0 : ifile->link(*this);
319 0 : if(ifile->FileExist(Biasfilename_)) {
320 0 : ifile->open(Biasfilename_);
321 : // read all the lines, store last value of bias
322 : double MDtime;
323 0 : while(ifile->scanField("MD_time",MDtime)) {
324 0 : for(unsigned i=0; i<bias_.size(); ++i) {
325 : // convert i to string
326 0 : std::stringstream ss;
327 : ss << i;
328 : // label
329 0 : std::string label = "b" + ss.str();
330 : // read entry
331 0 : ifile->scanField(label, bias_[i]);
332 0 : }
333 : // new line
334 0 : ifile->scanField();
335 : }
336 0 : ifile->close();
337 : } else {
338 0 : error("Cannot find bias file "+Biasfilename_+"\n");
339 : }
340 0 : }
341 :
342 0 : unsigned Rescale::proposeMove(unsigned x, unsigned xmin, unsigned xmax) {
343 0 : int xmin_i = static_cast<int>(xmin);
344 0 : int xmax_i = static_cast<int>(xmax);
345 : int dx;
346 0 : int r = rand() % 2;
347 0 : if( r % 2 == 0 ) {
348 : dx = +1;
349 : } else {
350 : dx = -1;
351 : }
352 : // new index, integer
353 0 : int x_new = static_cast<int>(x) + dx;
354 : // check boundaries
355 0 : if(x_new >= xmax_i) {
356 0 : x_new = xmax_i-1;
357 : }
358 : if(x_new < xmin_i) {
359 : x_new = xmin_i;
360 : }
361 0 : return static_cast<unsigned>(x_new);
362 : }
363 :
364 0 : bool Rescale::doAccept(double oldE, double newE) {
365 : bool accept = false;
366 : // calculate delta energy
367 0 : double delta = ( newE - oldE ) / kbt_;
368 : // if delta is negative always accept move
369 0 : if( delta < 0.0 ) {
370 : accept = true;
371 : } else {
372 : // otherwise extract random number
373 0 : double s = static_cast<double>(rand()) / RAND_MAX;
374 0 : if( s < std::exp(-delta) ) {
375 : accept = true;
376 : }
377 : }
378 0 : return accept;
379 : }
380 :
381 0 : void Rescale::doMonteCarlo(unsigned igamma, double oldE,
382 : const std::vector<double> & args, const std::vector<double> & bargs) {
383 : double oldB, newB;
384 :
385 : // cycle on MC steps
386 0 : for(unsigned i=0; i<MCsteps_; ++i) {
387 : // propose move in igamma
388 0 : unsigned new_igamma = proposeMove(igamma, 0, gamma_.size());
389 : // calculate new energy
390 : double newE = 0.0;
391 0 : for(unsigned j=0; j<args.size(); ++j) {
392 : // calculate energy term
393 0 : double fact = 1.0/pow(gamma_[new_igamma], expo_[j]) - 1.0;
394 0 : newE += args[j] * fact;
395 : }
396 : // calculate contributions from non-rescaled terms
397 0 : if(bargs.size()>0) {
398 0 : oldB = bias_[igamma]+bargs[igamma];
399 0 : newB = bias_[new_igamma]+bargs[new_igamma];
400 : } else {
401 0 : oldB = bias_[igamma];
402 0 : newB = bias_[new_igamma];
403 : }
404 : // accept or reject
405 0 : bool accept = doAccept(oldE+oldB, newE+newB);
406 0 : if(accept) {
407 0 : igamma = new_igamma;
408 : oldE = newE;
409 0 : MCaccgamma_++;
410 : }
411 : }
412 : // send values of gamma to all replicas
413 0 : if(comm.Get_rank()==0) {
414 0 : if(multi_sim_comm.Get_rank()!=0) {
415 0 : igamma = 0;
416 : }
417 0 : multi_sim_comm.Sum(&igamma, 1);
418 : } else {
419 0 : igamma = 0;
420 : }
421 : // local communication
422 0 : comm.Sum(&igamma, 1);
423 :
424 : // set the value of gamma into passMap
425 0 : plumed.passMap[selector_]=static_cast<double>(igamma);
426 0 : }
427 :
428 0 : void Rescale::print_bias(long long int step) {
429 : // if first time open the file
430 0 : if(first_bias_) {
431 0 : first_bias_ = false;
432 0 : Biasfile_.link(*this);
433 0 : Biasfile_.open(Biasfilename_);
434 : Biasfile_.setHeavyFlush();
435 0 : Biasfile_.fmtField("%30.5f");
436 : }
437 :
438 : // write fields
439 0 : double MDtime = static_cast<double>(step)*getTimeStep();
440 0 : Biasfile_.printField("MD_time", MDtime);
441 0 : for(unsigned i=0; i<bias_.size(); ++i) {
442 : // convert i to string
443 0 : std::stringstream ss;
444 : ss << i;
445 : // label
446 0 : std::string label = "b" + ss.str();
447 : // print entry
448 0 : Biasfile_.printField(label, bias_[i]);
449 0 : }
450 0 : Biasfile_.printField();
451 0 : }
452 :
453 0 : void Rescale::calculate() {
454 : // get the current value of the selector
455 0 : unsigned igamma = static_cast<unsigned>(plumed.passMap[selector_]);
456 :
457 : // collect data from other replicas
458 0 : std::vector<double> all_args(getNumberOfArguments(), 0.0);
459 : // first calculate arguments
460 0 : for(unsigned i=0; i<all_args.size(); ++i) {
461 0 : double arg = getArgument(i);
462 : // sum shared arguments across replicas
463 0 : if(shared_[i]==1) {
464 0 : if(comm.Get_rank()==0) {
465 0 : multi_sim_comm.Sum(arg);
466 : } else {
467 0 : arg = 0.0;
468 : }
469 0 : if(comm.Get_size()>1) {
470 0 : comm.Sum(arg);
471 : }
472 : }
473 : // put into all_args
474 0 : all_args[i] = arg;
475 : }
476 :
477 : // now separate terms that should be rescaled
478 : std::vector<double> args;
479 0 : if(getNumberOfArguments()-nores_>0) {
480 0 : args.resize(getNumberOfArguments()-nores_);
481 : }
482 0 : for(unsigned i=0; i<args.size(); ++i) {
483 0 : args[i] = all_args[i];
484 : }
485 : // and terms that should not
486 : std::vector<double> bargs;
487 0 : if(nores_>0) {
488 0 : bargs.resize(nores_);
489 : }
490 0 : for(unsigned i=0; i<bargs.size(); ++i) {
491 0 : bargs[i] = all_args[i+args.size()];
492 : }
493 :
494 : // calculate energy and forces, only on rescaled terms
495 : double ene = 0.0;
496 0 : for(unsigned i=0; i<args.size(); ++i) {
497 : // calculate energy term
498 0 : double fact = 1.0/pow(gamma_[igamma], expo_[i]) - 1.0;
499 0 : ene += args[i] * fact;
500 : // add force
501 0 : setOutputForce(i, -fact);
502 : }
503 :
504 : // set to zero on the others
505 0 : for(unsigned i=0; i<bargs.size(); ++i) {
506 0 : setOutputForce(i+args.size(), 0.0);
507 : }
508 :
509 : // set value of the bias
510 0 : setBias(ene);
511 : // set value of the wt-bias
512 0 : getPntrToComponent("wtbias")->set(bias_[igamma]);
513 : // set values of gamma
514 0 : getPntrToComponent("igamma")->set(igamma);
515 : // get time step
516 0 : long long int step = getStep();
517 0 : if(MCfirst_==-1) {
518 0 : MCfirst_=step;
519 : }
520 : // calculate gamma acceptance
521 0 : double MCtrials = std::floor(static_cast<double>(step-MCfirst_) / static_cast<double>(MCstride_))+1.0;
522 0 : double accgamma = static_cast<double>(MCaccgamma_) / static_cast<double>(MCsteps_) / MCtrials;
523 0 : getPntrToComponent("accgamma")->set(accgamma);
524 :
525 : // do MC at the right time step
526 0 : if(step%MCstride_==0&&!getExchangeStep()) {
527 0 : doMonteCarlo(igamma, ene, args, bargs);
528 : }
529 :
530 : // add well-tempered like bias
531 0 : if(step%Biaspace_==0) {
532 : // get updated igamma
533 0 : unsigned igamma = static_cast<unsigned>(plumed.passMap[selector_]);
534 : // add "Gaussian"
535 0 : double kbDT = kbt_ * ( biasf_ - 1.0 );
536 0 : bias_[igamma] += w0_ * std::exp(-bias_[igamma] / kbDT);
537 : }
538 :
539 : // print bias
540 0 : if(step%Biasstride_==0) {
541 0 : print_bias(step);
542 : }
543 :
544 0 : }
545 :
546 :
547 : }
548 : }
549 :
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