Line data Source code
1 : /* +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
2 : Copyright (c) 2020 of Glen Hocky
3 :
4 : The FISST module is free software: you can redistribute it and/or modify
5 : it under the terms of the GNU Lesser General Public License as published by
6 : the Free Software Foundation, either version 3 of the License, or
7 : (at your option) any later version.
8 :
9 : The FISST module is distributed in the hope that it will be useful,
10 : but WITHOUT ANY WARRANTY; without even the implied warranty of
11 : MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
12 : GNU Lesser General Public License for more details.
13 :
14 : You should have received a copy of the GNU Lesser General Public License
15 : along with plumed. If not, see <http://www.gnu.org/licenses/>.
16 : +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ */
17 : #include "bias/Bias.h"
18 : #include "core/ActionRegister.h"
19 : #include "core/Atoms.h"
20 : #include "core/PlumedMain.h"
21 : #include "tools/File.h"
22 : #include "tools/Matrix.h"
23 : #include "tools/Random.h"
24 : #include "legendre_rule_fast.h"
25 :
26 : #include <iostream>
27 :
28 :
29 : using namespace PLMD;
30 : using namespace bias;
31 :
32 : //namespace is lowercase to match
33 : //module names being all lowercase
34 :
35 : namespace PLMD {
36 : namespace fisst {
37 :
38 : //+PLUMEDOC FISSTMOD_BIAS FISST
39 : /*
40 : Compute and apply the optimal linear force on an observable to enhance sampling of conformational distributions over a range of applied forces.
41 :
42 : This method is described in \cite Hartmann-FISST-2019
43 :
44 : If the system's Hamiltonian is given by:
45 : \f[
46 : H(\vec{p},\vec{q}) = \sum_{j} \frac{p_j^2}{2m_j} + U(\vec{q}),
47 : \f]
48 :
49 : This bias modifies the Hamiltonian to be:
50 : \f[
51 : H'(\vec{p},\vec{q}) = H(\vec{p},\vec{q}) - \bar{F} Q
52 : \f]
53 :
54 : where for CV \f$Q\f$, a coupling constant \f${\bar{F}}\f$ is determined
55 : adaptively according to the FISST algorithm.
56 :
57 : Specifically,
58 : \f[
59 : \bar{F}(Q)=\frac{ \int_{F_{min}}^{F_{max}} e^{\beta F Q(\vec{q})} \omega(F) F dF}{\int_{F_{min}}^{F_{max}} e^{\beta F Q(\vec{q})} \omega(F) dF},
60 : \f]
61 :
62 : where \f$\vec{q}\f$ are the molecular coordinates of the system, and \f$w(F)\f$ is a weighting function that is learned on the fly for each force by the FISST algorithm (starting from an initial weight distribution, uniform by default).
63 :
64 : The target for \f$w(F)=1/Z_q(F)\f$, where
65 : \f[
66 : Z_q(F) \equiv \int d\vec{q} e^{-\beta U(\vec{q}) + \beta F Q(\vec{q})}.
67 : \f]
68 :
69 : FISST also computes and writes Observable Weights \f$W_F(\vec{q}_t)\f$ for a molecular configuration at time \f$t\f$, so that averages of other quantities \f$A(\vec{q})\f$ can be reconstructed later at different force values (over a trajectory with \f$T\f$ samples):
70 : \f[
71 : \langle A \rangle_F = \frac{1}{T} \sum_t W_F(\vec{q}_t) A(\vec{q}_t).
72 : \f]
73 :
74 :
75 : \par Examples
76 :
77 : In the following example, an adaptive restraint is learned to bias the distance between two atoms in a system, for a force range of 0-100 pN.
78 :
79 : \plumedfile
80 : UNITS LENGTH=A TIME=fs ENERGY=kcal/mol
81 :
82 : b1: GROUP ATOMS=1
83 : b2: GROUP ATOMS=12
84 :
85 : dend: DISTANCE ATOMS=b1,b2
86 :
87 : #The conversion factor is 69.4786 pN = 1 kcal/mol/Angstrom
88 :
89 : #0 pN to 100 pN
90 : f: FISST MIN_FORCE=0 MAX_FORCE=1.44 PERIOD=100 NINTERPOLATE=31 ARG=dend OUT_RESTART=pull.restart.txt OUT_OBSERVABLE=pull.observable.txt OBSERVABLE_FREQ=1000
91 :
92 : PRINT ARG=dend,f.dend_fbar,f.bias,f.force2 FILE=pull.colvar.txt STRIDE=1000
93 : \endplumedfile
94 :
95 :
96 : */
97 : //+ENDPLUMEDOC
98 :
99 :
100 : class FISST : public Bias {
101 :
102 :
103 : private:
104 : /*We will get this and store it once, since on-the-fly changing number of CVs will be fatal*/
105 : const unsigned int ncvs_;
106 : std::vector<double> center_;
107 : std::vector<double> current_avg_force_;
108 :
109 : std::vector<double> forces_;
110 : std::vector<double> force_weight_;
111 : std::vector<double> gauss_weight_;
112 : std::vector<double> partition_estimate_;
113 : std::vector<double> observable_weight_;
114 :
115 : std::string in_restart_name_;
116 : std::string out_restart_name_;
117 : std::string out_observable_name_;
118 : std::string fmt_;
119 : std::string initial_weight_dist_;
120 : OFile out_restart_;
121 : OFile out_observable_;
122 : IFile in_restart_;
123 : bool b_freeze_;
124 : bool b_adaptive_;
125 : bool b_restart_;
126 : bool b_write_restart_;
127 : bool b_write_observable_;
128 : bool b_first_restart_sample_;
129 : int period_;
130 : int reset_period_;
131 : int observable_freq_;
132 : int n_interpolation_;
133 : int n_samples_;
134 : double kbt_;
135 : double beta_;
136 : //change min_force and max_force to vectors if going to do more than one cv
137 : double max_force_;
138 : double min_force_;
139 : double initial_weight_rate_;
140 : double threshold_;
141 : Random rand_;
142 :
143 :
144 : Value* value_force2_;
145 : void readInRestart();
146 : void NormalizeForceWeights();
147 : /*setup output restart*/
148 : void setupOutRestart();
149 : void setupOutObservable();
150 : /*write output restart*/
151 : void writeOutRestart();
152 : void writeOutObservable();
153 : void update_statistics();
154 : void update_bias();
155 : void apply_bias();
156 : void compute_observable_weight();
157 :
158 : public:
159 : explicit FISST(const ActionOptions&);
160 : void calculate();
161 : void update();
162 : void turnOnDerivatives();
163 : static void registerKeywords(Keywords& keys);
164 : ~FISST();
165 : };
166 :
167 10423 : PLUMED_REGISTER_ACTION(FISST,"FISST")
168 :
169 3 : void FISST::registerKeywords(Keywords& keys) {
170 3 : Bias::registerKeywords(keys);
171 3 : keys.use("ARG");
172 6 : keys.add("compulsory","PERIOD","Steps corresponding to the learning rate");
173 6 : keys.add("optional","RESET_PERIOD","Reset the learning statistics every time this number of steps comes around.");
174 6 : keys.add("compulsory","NINTERPOLATE","Number of grid points on which to do interpolation.");
175 6 : keys.add("compulsory","MIN_FORCE","Minimum force (per CV) to use for sampling. Units: [Energy]/[CV] (can be negative).");
176 6 : keys.add("compulsory","MAX_FORCE","Maximum force (per CV) to use for sampling.");
177 6 : keys.add("compulsory","CENTER","0","The CV value at which the applied bias energy will be zero");
178 6 : keys.add("optional","KBT","The system temperature in units of KB*T. If not provided will be taken from MD code (if available)");
179 :
180 9 : keys.add("optional","INITIAL_WEIGHT_DIST","Starting distribution for the force weights (options: UNIFORM, EXP, GAUSS).");
181 9 : keys.add("optional","INITIAL_WEIGHT_RATE","Rate of decay for exponential and gaussian distributions. W(F)~exp(-r |F|^d).");
182 :
183 6 : keys.add("optional","RESTART_FMT","the format that should be used to output real numbers in FISST restarts.");
184 6 : keys.add("optional","OUT_RESTART","Output file for all information needed to continue FISST simulation."
185 : "If you have the RESTART directive set (global or for FISST), this file will be appended to."
186 : "Note that the header will be printed again if appending.");
187 6 : keys.add("optional","IN_RESTART","Read this file to continue an FISST simulation. "
188 : "If same as OUT_RESTART and you have not set the RESTART directive, the file will be backed-up and overwritten with new output."
189 : "If you do have the RESTART flag set and it is the same name as OUT_RESTART, this file will be appended.");
190 6 : keys.add("optional","OUT_OBSERVABLE","Output file putting weights needed to compute observables at different force values."
191 : "If you have the RESTART directive set (global or for FISST), this file will be appended to. "
192 : "Note that the header will be printed again if appending.");
193 6 : keys.add("optional","OBSERVABLE_FREQ","How often to write out observable weights (default=period).");
194 6 : keys.addFlag("FREEZE",false,"Fix bias weights at current level (only used for restarting).");
195 3 : keys.use("RESTART");
196 6 : keys.addOutputComponent("force2","default","squared value of force from the bias.");
197 6 : keys.addOutputComponent("_fbar","default", "For each named CV biased, there will be a corresponding output CV_fbar storing the current linear bias prefactor.");
198 3 : }
199 :
200 2 : FISST::FISST(const ActionOptions&ao):
201 : PLUMED_BIAS_INIT(ao),
202 2 : ncvs_(getNumberOfArguments()),
203 0 : current_avg_force_(ncvs_,0.0),
204 2 : center_(ncvs_,0.0),
205 : //change min_force and max_force to vectors if going to do more than one cv
206 2 : min_force_(0.0),
207 2 : max_force_(0.0),
208 2 : in_restart_name_(""),
209 2 : out_restart_name_(""),
210 2 : out_observable_name_(""),
211 2 : fmt_("%e"),
212 2 : b_freeze_(false),
213 2 : b_restart_(false),
214 2 : b_write_restart_(false),
215 2 : b_write_observable_(false),
216 2 : b_first_restart_sample_(true),
217 2 : n_interpolation_(0),
218 2 : n_samples_(0),
219 2 : initial_weight_rate_(0),
220 2 : initial_weight_dist_("UNIFORM"),
221 2 : period_(0),
222 2 : reset_period_(0),
223 2 : observable_freq_(0),
224 2 : kbt_(0.0),
225 6 : value_force2_(NULL)
226 : {
227 2 : if(ncvs_==0)
228 0 : error("Must specify at least one CV with ARG");
229 :
230 : //temporary
231 2 : if(ncvs_>1)
232 0 : error("FISST only supports using one CV right now");
233 :
234 2 : addComponent("force2");
235 2 : componentIsNotPeriodic("force2");
236 2 : value_force2_ = getPntrToComponent("force2");
237 :
238 4 : for(unsigned int i = 0; i<ncvs_; i++) {
239 2 : std::string comp = getPntrToArgument(i)->getName() + "_fbar";
240 2 : addComponent(comp);
241 2 : componentIsNotPeriodic(comp);
242 : }
243 :
244 2 : parseVector("CENTER",center_);
245 : //change min_force and max_force to vectors if going to do more than one cv
246 2 : parse("MIN_FORCE",min_force_);
247 2 : parse("MAX_FORCE",max_force_);
248 2 : parse("PERIOD",period_);
249 2 : parse("RESET_PERIOD",reset_period_);
250 2 : parse("INITIAL_WEIGHT_DIST",initial_weight_dist_);
251 2 : parse("INITIAL_WEIGHT_RATE",initial_weight_rate_);
252 2 : parse("OBSERVABLE_FREQ",observable_freq_);
253 2 : parse("NINTERPOLATE",n_interpolation_);
254 2 : parseFlag("FREEZE",b_freeze_);
255 2 : parse("KBT",kbt_);
256 2 : parse("RESTART_FMT", fmt_);
257 2 : fmt_ = " " + fmt_;//add space since parse strips them
258 2 : parse("OUT_RESTART",out_restart_name_);
259 2 : parse("OUT_OBSERVABLE",out_observable_name_);
260 2 : parse("IN_RESTART",in_restart_name_);
261 2 : checkRead();
262 :
263 2 : if(center_.size() != ncvs_)
264 0 : error("Must have same number of CENTER arguments as ARG arguments");
265 :
266 2 : if(in_restart_name_ != "") {
267 0 : b_restart_ = true;
268 0 : log.printf(" reading simulation information from file: %s\n",in_restart_name_.c_str());
269 0 : readInRestart();
270 : } else {
271 :
272 2 : if(! kbt_ > 0.0)
273 2 : kbt_ = plumed.getAtoms().getKbT();
274 :
275 : //in driver, this results in kbt of 0
276 2 : if(kbt_ == 0) {
277 0 : error(" Unable to determine valid kBT. "
278 : "Could be because you are runnning from driver or MD didn't give temperature.\n"
279 : "Consider setting temperature manually with the KBT keyword.");
280 : }
281 :
282 2 : log.printf(" kBT = %f\n",kbt_);
283 2 : log.printf(" Updating with a time scale of %i steps\n",period_);
284 :
285 2 : log.printf(" Using centers for CVs of:");
286 4 : for(unsigned int i = 0; i< ncvs_; i++) {
287 2 : log.printf(" %f ",center_[i]);
288 : }
289 2 : log.printf("\n");
290 2 : observable_weight_.resize(n_interpolation_);
291 64 : for(unsigned int i = 0; i<n_interpolation_; i++) observable_weight_[i] = 1.0;
292 :
293 2 : forces_.resize(n_interpolation_);
294 2 : force_weight_.resize(n_interpolation_);
295 : //using code from the MIST project
296 2 : gauss_weight_.resize(n_interpolation_);
297 2 : legendre_compute_glr(n_interpolation_, &forces_[0], &gauss_weight_[0]);
298 2 : rescale(min_force_, max_force_, n_interpolation_, &forces_[0], &gauss_weight_[0]);
299 :
300 2 : log.printf("Using weight distribution %s with rate %f\n",initial_weight_dist_.c_str(),initial_weight_rate_);
301 2 : if(initial_weight_dist_ == "UNIFORM" ) {
302 32 : for(unsigned int i = 0; i<n_interpolation_; i++) force_weight_[i] = 1.0;
303 : }
304 1 : else if (initial_weight_dist_ == "EXP" ) {
305 32 : for(unsigned int i = 0; i<n_interpolation_; i++) force_weight_[i] = exp(-fabs(forces_[i])*initial_weight_rate_);
306 : }
307 0 : else if (initial_weight_dist_ == "GAUSS" ) {
308 0 : for(unsigned int i = 0; i<n_interpolation_; i++) force_weight_[i] = exp(-pow(forces_[i],2)*initial_weight_rate_);
309 : }
310 : else {
311 0 : error(" Specified weight distribution is not from the allowed list.");
312 :
313 : }
314 :
315 2 : partition_estimate_.resize(n_interpolation_);
316 2 : NormalizeForceWeights();
317 : double sum = 0.0;
318 64 : for(unsigned int i = 0; i<n_interpolation_; i++) {
319 : //setting partition estimate as 1/w_i
320 62 : partition_estimate_[i] = 1/force_weight_[i];
321 62 : log.printf("force/gauss weight/force_weight: %i %f %f %f\n",i,forces_[i],gauss_weight_[i],force_weight_[i]);
322 62 : sum+=gauss_weight_[i]*force_weight_[i];
323 : }
324 2 : log.printf("--Sum_i w_i g_i: %f\n",sum);
325 :
326 : }
327 :
328 : //set inverse temperature
329 2 : beta_ = 1/kbt_;
330 :
331 2 : if(b_freeze_ && b_restart_) {
332 0 : log.printf(" freezing weights read in from the restart file\n");
333 : }
334 :
335 2 : if(out_restart_name_.length()>0) {
336 2 : log.printf(" writing restart information every %i steps to file %s with format %s\n",abs(period_),out_restart_name_.c_str(), fmt_.c_str());
337 2 : b_write_restart_ = true;
338 2 : setupOutRestart();
339 : }
340 2 : if(out_observable_name_.length()>0) {
341 2 : if(observable_freq_==0) observable_freq_ = period_;
342 2 : log.printf(" writing observable information every %i steps to file %s with format %s\n",observable_freq_,out_observable_name_.c_str(), fmt_.c_str());
343 2 : b_write_observable_ = true;
344 2 : setupOutObservable();
345 : }
346 :
347 : //add citation later:
348 : //log<<" Bibliography "<<plumed.cite("")<<"\n";
349 2 : }
350 :
351 12 : void FISST::NormalizeForceWeights() {
352 : double denom = 0.0;
353 :
354 384 : for(unsigned i=0; i<n_interpolation_; i++)
355 372 : denom += gauss_weight_[i] * force_weight_[i];
356 :
357 384 : for(unsigned i=0; i<n_interpolation_; i++)
358 372 : force_weight_[i] /= denom;
359 12 : }
360 :
361 0 : void FISST::readInRestart() {
362 0 : in_restart_.open(in_restart_name_);
363 :
364 0 : if(in_restart_.FieldExist("kbt")) {
365 0 : in_restart_.scanField("kbt",kbt_);
366 0 : } else { error("No field 'kbt' in restart file"); }
367 0 : log.printf(" with kBT = %f\n",kbt_);
368 :
369 0 : if(in_restart_.FieldExist("period")) {
370 0 : in_restart_.scanField("period",period_);
371 0 : } else { error("No field 'period' in restart file"); }
372 0 : log.printf(" Updating every %i steps\n",period_);
373 :
374 : //this one can be optional
375 0 : if(in_restart_.FieldExist("reset_period")) {
376 0 : in_restart_.scanField("reset_period",reset_period_);
377 : }
378 0 : log.printf(" Resetting statistics every %i steps\n",reset_period_);
379 :
380 0 : if(in_restart_.FieldExist("n_interpolation")) {
381 0 : in_restart_.scanField("n_interpolation",n_interpolation_);
382 0 : } else { error("No field 'n_interpolation' in restart file"); }
383 :
384 0 : if(in_restart_.FieldExist("min_force")) {
385 0 : in_restart_.scanField("min_force",min_force_);
386 0 : } else { error("No field 'min_force' in restart file"); }
387 0 : if(in_restart_.FieldExist("max_force")) {
388 0 : in_restart_.scanField("max_force",max_force_);
389 0 : } else { error("No field 'max_force' in restart file"); }
390 0 : log.printf(" with forces from min_force=%e to max_force=%e over %i bins\n",min_force_,max_force_,n_interpolation_);
391 :
392 : unsigned int N = 0;
393 : std::string cv_name;
394 : double tmp, time;
395 :
396 0 : while(in_restart_.scanField("time",time)) {
397 0 : in_restart_.scanField("nsamples",n_samples_);
398 :
399 0 : observable_weight_.resize(n_interpolation_);
400 0 : partition_estimate_.resize(n_interpolation_);
401 0 : force_weight_.resize(n_interpolation_);
402 0 : gauss_weight_.resize(n_interpolation_);
403 0 : forces_.resize(n_interpolation_);
404 :
405 0 : for(unsigned int i = 0; i<ncvs_; ++i) {
406 : cv_name = getPntrToArgument(i)->getName();
407 0 : in_restart_.scanField(cv_name,tmp);
408 0 : for(unsigned int j =0; j<n_interpolation_; ++j) {
409 0 : in_restart_.scanField(cv_name + "_f"+std::to_string(j),forces_[j]);
410 0 : in_restart_.scanField(cv_name + "_g"+std::to_string(j),gauss_weight_[j]);
411 0 : in_restart_.scanField(cv_name + "_w"+std::to_string(j),force_weight_[j]);
412 0 : in_restart_.scanField(cv_name + "_z"+std::to_string(j),partition_estimate_[j]);
413 : }
414 : }
415 : N++;
416 :
417 0 : in_restart_.scanField();
418 : }
419 :
420 : double sum = 0.0;
421 0 : for(unsigned int j =0; j<n_interpolation_; ++j) {
422 : //clear observable weight, which will be set later
423 0 : observable_weight_[j] = 1.0;
424 :
425 : //setting partition estimate as 1/w_i
426 0 : log.printf("force/gauss weight/force_weight: %i %e %e %e\n",j,forces_[j],gauss_weight_[j],force_weight_[j]);
427 0 : sum+=gauss_weight_[j]*force_weight_[j];
428 : }
429 0 : log.printf("--Sum_i w_i g_i: %f\n",sum);
430 :
431 0 : in_restart_.close();
432 0 : }
433 :
434 2 : void FISST::setupOutObservable() {
435 2 : out_observable_.link(*this);
436 2 : out_observable_.fmtField(fmt_);
437 2 : out_observable_.open(out_observable_name_);
438 : out_observable_.setHeavyFlush();
439 :
440 4 : out_observable_.addConstantField("kbt").printField("kbt",kbt_);
441 4 : out_observable_.addConstantField("n_interpolation").printField("n_interpolation",n_interpolation_);
442 4 : out_observable_.addConstantField("period").printField("period",period_);
443 4 : out_observable_.addConstantField("min_force").printField("min_force",min_force_);
444 4 : out_observable_.addConstantField("max_force").printField("max_force",max_force_);
445 2 : }
446 :
447 2 : void FISST::setupOutRestart() {
448 2 : out_restart_.link(*this);
449 2 : out_restart_.fmtField(fmt_);
450 2 : out_restart_.open(out_restart_name_);
451 : out_restart_.setHeavyFlush();
452 :
453 4 : out_restart_.addConstantField("kbt").printField("kbt",kbt_);
454 4 : out_restart_.addConstantField("n_interpolation").printField("n_interpolation",n_interpolation_);
455 4 : out_restart_.addConstantField("period").printField("period",period_);
456 2 : if(reset_period_>0) out_restart_.addConstantField("reset_period").printField("reset_period",reset_period_);
457 4 : out_restart_.addConstantField("min_force").printField("min_force",min_force_);
458 4 : out_restart_.addConstantField("max_force").printField("max_force",max_force_);
459 2 : }
460 :
461 10 : void FISST::writeOutRestart() {
462 : std::string cv_name;
463 10 : out_restart_.printField("time",getTimeStep()*getStep());
464 10 : out_restart_.printField("nsamples",n_samples_);
465 :
466 20 : for(unsigned int i = 0; i<ncvs_; ++i) {
467 : cv_name = getPntrToArgument(i)->getName();
468 10 : double Q_i = difference(i, center_[i], getArgument(i));
469 10 : out_restart_.printField(cv_name,Q_i);
470 320 : for(int j = 0; j < n_interpolation_; j++ ) {
471 : //have to update this for multiple cvs
472 620 : out_restart_.printField(cv_name + "_f"+std::to_string(j),forces_[j]);
473 620 : out_restart_.printField(cv_name + "_g"+std::to_string(j),gauss_weight_[j]);
474 620 : out_restart_.printField(cv_name + "_w"+std::to_string(j),force_weight_[j]);
475 620 : out_restart_.printField(cv_name + "_z"+std::to_string(j),partition_estimate_[j]);
476 : }
477 : }
478 10 : out_restart_.printField();
479 10 : }
480 :
481 10 : void FISST::writeOutObservable() {
482 : std::string cv_name;
483 10 : out_observable_.printField("time",getTimeStep()*getStep());
484 10 : out_observable_.printField("nsamples",n_samples_);
485 :
486 20 : for(unsigned int i = 0; i<ncvs_; ++i) {
487 : cv_name = getPntrToArgument(i)->getName();
488 10 : double Q_i = difference(i, center_[i], getArgument(i));
489 10 : out_observable_.printField(cv_name,Q_i);
490 10 : out_observable_.printField(cv_name + "_fbar",current_avg_force_[i]);
491 320 : for(int j = 0; j < n_interpolation_; j++ ) {
492 : //have to update this for multiple cvs
493 620 : out_observable_.printField(cv_name + "_f"+std::to_string(j),forces_[j]);
494 620 : out_observable_.printField(cv_name + "_ow"+std::to_string(j),observable_weight_[j]);
495 : }
496 : }
497 10 : out_observable_.printField();
498 10 : }
499 :
500 :
501 10 : void FISST::calculate() {
502 10 : if(getStep() == 0 ) {
503 2 : if(b_write_restart_) writeOutRestart();
504 2 : if(b_write_observable_) writeOutObservable();
505 : }
506 :
507 10 : if(! b_freeze_) {
508 10 : if(b_restart_ && b_first_restart_sample_) {
509 : //dont' update statistics if restarting and first sample
510 0 : b_first_restart_sample_ = false;
511 : }
512 : else {
513 10 : update_statistics();
514 : }
515 : }
516 10 : update_bias();
517 10 : apply_bias();
518 :
519 : //check about writing restart file
520 10 : if(getStep()>0 && getStep()%period_==0) {
521 8 : if(b_write_restart_) writeOutRestart();
522 : }
523 10 : if(getStep()>0 && getStep()%observable_freq_==0) {
524 8 : if(b_write_observable_) {
525 8 : compute_observable_weight();
526 8 : writeOutObservable();
527 : }
528 : }
529 10 : }
530 :
531 :
532 10 : void FISST::apply_bias() {
533 : //Compute linear force as in "restraint"
534 : double ene = 0, totf2 = 0, cv, m, f;
535 :
536 20 : for(unsigned int i = 0; i < ncvs_; ++i) {
537 10 : cv = difference(i, center_[i], getArgument(i));
538 10 : double fbar = current_avg_force_[i];
539 10 : ene -= fbar*cv;
540 : setOutputForce(i,fbar);
541 10 : totf2 += fbar*fbar;
542 :
543 10 : std::string fbar_name_ = getPntrToArgument(i)->getName() + "_fbar";
544 10 : Value* fbar_ = getPntrToComponent(fbar_name_);
545 : fbar_->set(fbar);
546 : };
547 :
548 : setBias(ene);
549 10 : value_force2_->set(totf2);
550 : //log.flush();
551 10 : }
552 :
553 10 : void FISST::update_statistics() {
554 : //get stride is for multiple time stepping
555 10 : double dt=getTimeStep()*getStride();
556 10 : double h = dt/(period_*getTimeStep());
557 : double fbar_denum_integral = 0.0;
558 :
559 10 : int step = getStep();
560 10 : if(reset_period_>0 && step>0 && step%reset_period_==0) {
561 0 : n_samples_=1;
562 : }
563 : else {
564 10 : n_samples_++;
565 : }
566 10 : double d_n_samples = (double)n_samples_;
567 :
568 20 : for(unsigned int i = 0; i < ncvs_; ++i) {
569 10 : double Q_i = difference(i, center_[i], getArgument(i));
570 320 : for(unsigned int j=0; j<n_interpolation_; j++)
571 : {
572 : //if multiple cvs, these need to be updated to have 2 columns
573 310 : double f_j = forces_[j];
574 310 : double w_j = force_weight_[j];
575 310 : double g_j = gauss_weight_[j];
576 :
577 310 : fbar_denum_integral += g_j * w_j * exp(beta_*f_j * Q_i);
578 : }
579 :
580 320 : for(unsigned int j=0; j<n_interpolation_; j++)
581 : {
582 310 : double f_j = forces_[j];
583 310 : double sample_weight = exp(beta_*f_j * Q_i) / fbar_denum_integral;
584 :
585 310 : partition_estimate_[j] = sample_weight/d_n_samples + partition_estimate_[j]*(d_n_samples-1)/(d_n_samples);
586 :
587 310 : double w_jn = force_weight_[j];
588 310 : double z_jn = partition_estimate_[j];
589 :
590 310 : double w_jp1 = (1.0 - h) * w_jn + h / z_jn;
591 310 : force_weight_[j] = w_jp1;
592 : }
593 : }
594 :
595 : // make sure that the weights are normalised
596 10 : NormalizeForceWeights();
597 10 : }
598 :
599 :
600 10 : void FISST::update_bias()
601 : {
602 20 : for(unsigned int i = 0; i < ncvs_; ++i) {
603 10 : double Q_i = difference(i, center_[i], getArgument(i));
604 : double fbar_num_integral = 0.0;
605 : double fbar_denum_integral = 0.0;
606 :
607 320 : for(unsigned int j=0; j<n_interpolation_; j++ ) {
608 310 : double f_j = forces_[j];
609 310 : double w_j = force_weight_[j];
610 310 : double g_j = gauss_weight_[j];
611 :
612 310 : fbar_num_integral += g_j * f_j * w_j * exp(beta_*f_j*Q_i);
613 310 : fbar_denum_integral += g_j * w_j * exp(beta_*f_j*Q_i);
614 : }
615 :
616 10 : current_avg_force_[i] = fbar_num_integral/fbar_denum_integral;
617 : }
618 10 : }
619 :
620 8 : void FISST::compute_observable_weight() {
621 8 : double obs_num = (max_force_ - min_force_);
622 :
623 16 : for(unsigned int i = 0; i < ncvs_; ++i) {
624 8 : double Q_i = difference(i, center_[i], getArgument(i));
625 :
626 256 : for(unsigned int j=0; j<n_interpolation_; j++ ) {
627 248 : double z_j = partition_estimate_[j];
628 248 : double f_j = forces_[j];
629 : double denum_integral = 0.0;
630 :
631 7936 : for( unsigned int k=0; k<n_interpolation_; k++ ) {
632 7688 : double f_k = forces_[k];
633 7688 : double w_k = force_weight_[k];
634 7688 : double g_k = gauss_weight_[k];
635 :
636 7688 : denum_integral += g_k * w_k * exp(beta_*(f_k-f_j)*Q_i);
637 : }
638 248 : observable_weight_[j] = obs_num/(denum_integral*z_j);
639 : }
640 : }
641 8 : }
642 :
643 :
644 :
645 10 : void FISST::update() {
646 : //pass
647 10 : }
648 :
649 4 : FISST::~FISST() {
650 2 : out_restart_.close();
651 2 : out_observable_.close();
652 6 : }
653 :
654 0 : void FISST::turnOnDerivatives() {
655 : // do nothing
656 : // this is to avoid errors triggered when a bias is used as a CV
657 : // (This is done in ExtendedLagrangian.cpp)
658 0 : }
659 :
660 :
661 : }
662 : }//close the 2 namespaces
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