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42 #include "gmx_fatal.h"
44 #include "md_support.h"
45 #include "md_logging.h"
46 #include "types/iteratedconstraints.h"
49 #define CONVERGEITER 0.000000001
50 #define CLOSE_ENOUGH 0.000001000
52 #define CONVERGEITER 0.0001
53 #define CLOSE_ENOUGH 0.0050
56 /* we want to keep track of the close calls. If there are too many, there might be some other issues.
57 so we make sure that it's either less than some predetermined number, or if more than that number,
58 only some small fraction of the total. */
59 #define MAX_NUMBER_CLOSE 50
60 #define FRACTION_CLOSE 0.001
62 /* maximum length of cyclic traps to check, emerging from limited numerical precision */
65 void gmx_iterate_init(gmx_iterate_t *iterate, gmx_bool bSetIterationActive)
70 iterate->bIterationActive = bSetIterationActive;
71 iterate->num_close = 0;
72 for (i = 0; i < MAXITERCONST+2; i++)
74 iterate->allrelerr[i] = 0;
78 gmx_bool done_iterating(const t_commrec *cr, FILE *fplog, int nsteps, gmx_iterate_t *iterate, gmx_bool bFirstIterate, real fom, real *newf)
80 /* monitor convergence, and use a secant search to propose new
83 The secant method computes x_{i+1} = x_{i} - f(x_{i}) * ---------------------
86 The function we are trying to zero is fom-x, where fom is the
87 "figure of merit" which is the pressure (or the veta value) we
88 would get by putting in an old value of the pressure or veta into
89 the incrementor function for the step or half step. I have
90 verified that this gives the same answer as self consistent
91 iteration, usually in many fewer steps, especially for small tau_p.
93 We could possibly eliminate an iteration with proper use
94 of the value from the previous step, but that would take a bit
95 more bookkeeping, especially for veta, since tests indicate the
96 function of veta on the last step is not sufficiently close to
97 guarantee convergence this step. This is
98 good enough for now. On my tests, I could use tau_p down to
99 0.02, which is smaller that would ever be necessary in
100 practice. Generally, 3-5 iterations will be sufficient */
102 real relerr, err, xmin;
109 iterate->f = fom-iterate->x;
116 iterate->f = fom-iterate->x; /* we want to zero this difference */
117 if ((iterate->iter_i > 1) && (iterate->iter_i < MAXITERCONST))
119 if (iterate->f == iterate->fprev)
125 *newf = iterate->x - (iterate->x-iterate->xprev)*(iterate->f)/(iterate->f-iterate->fprev);
130 /* just use self-consistent iteration the first step to initialize, or
131 if it's not converging (which happens occasionally -- need to investigate why) */
135 /* Consider a slight shortcut allowing us to exit one sooner -- we check the
136 difference between the closest of x and xprev to the new
137 value. To be 100% certain, we should check the difference between
138 the last result, and the previous result, or
140 relerr = (fabs((x-xprev)/fom));
142 but this is pretty much never necessary under typical conditions.
143 Checking numerically, it seems to lead to almost exactly the same
144 trajectories, but there are small differences out a few decimal
145 places in the pressure, and eventually in the v_eta, but it could
148 if (fabs(*newf-x) < fabs(*newf - xprev)) { xmin = x;} else { xmin = xprev;}
149 relerr = (fabs((*newf-xmin) / *newf));
152 err = fabs((iterate->f-iterate->fprev));
153 relerr = fabs(err/fom);
155 iterate->allrelerr[iterate->iter_i] = relerr;
157 if (iterate->iter_i > 0)
161 fprintf(debug, "Iterating NPT constraints: %6i %20.12f%14.6g%20.12f\n",
162 iterate->iter_i, fom, relerr, *newf);
165 if ((relerr < CONVERGEITER) || (err < CONVERGEITER) || (fom == 0) || ((iterate->x == iterate->xprev) && iterate->iter_i > 1))
167 iterate->bIterationActive = FALSE;
170 fprintf(debug, "Iterating NPT constraints: CONVERGED\n");
174 if (iterate->iter_i > MAXITERCONST)
176 if (relerr < CLOSE_ENOUGH)
179 for (i = 1; i < CYCLEMAX; i++)
181 if ((iterate->allrelerr[iterate->iter_i-(1+i)] == iterate->allrelerr[iterate->iter_i-1]) &&
182 (iterate->allrelerr[iterate->iter_i-(1+i)] == iterate->allrelerr[iterate->iter_i-(1+2*i)]))
187 fprintf(debug, "Exiting from an NPT iterating cycle of length %d\n", i);
195 /* step 1: trapped in a numerical attractor */
196 /* we are trapped in a numerical attractor, and can't converge any more, and are close to the final result.
197 Better to give up convergence here than have the simulation die.
199 iterate->num_close++;
200 iterate->bIterationActive = FALSE;
205 /* Step #2: test if we are reasonably close for other reasons, then monitor the number. If not, die */
207 /* how many close calls have we had? If less than a few, we're OK */
208 if (iterate->num_close < MAX_NUMBER_CLOSE)
210 md_print_warn(cr, fplog, "Slight numerical convergence deviation with NPT at step %d, relative error only %10.5g, likely not a problem, continuing\n", nsteps, relerr);
211 iterate->num_close++;
212 iterate->bIterationActive = FALSE;
214 /* if more than a few, check the total fraction. If too high, die. */
216 else if (iterate->num_close/(double)nsteps > FRACTION_CLOSE)
218 gmx_fatal(FARGS, "Could not converge NPT constraints, too many exceptions (%d%%\n", iterate->num_close/(double)nsteps);
224 gmx_fatal(FARGS, "Could not converge NPT constraints\n");
229 iterate->xprev = iterate->x;
231 iterate->fprev = iterate->f;