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43 #include "gmx_fatal.h"
45 #include "md_support.h"
46 #include "md_logging.h"
47 #include "types/iteratedconstraints.h"
50 #define CONVERGEITER 0.000000001
51 #define CLOSE_ENOUGH 0.000001000
53 #define CONVERGEITER 0.0001
54 #define CLOSE_ENOUGH 0.0050
57 /* we want to keep track of the close calls. If there are too many, there might be some other issues.
58 so we make sure that it's either less than some predetermined number, or if more than that number,
59 only some small fraction of the total. */
60 #define MAX_NUMBER_CLOSE 50
61 #define FRACTION_CLOSE 0.001
63 /* maximum length of cyclic traps to check, emerging from limited numerical precision */
66 void gmx_iterate_init(gmx_iterate_t *iterate, gmx_bool bSetIterationActive)
71 iterate->bIterationActive = bSetIterationActive;
72 iterate->num_close = 0;
73 for (i = 0; i < MAXITERCONST+2; i++)
75 iterate->allrelerr[i] = 0;
79 gmx_bool done_iterating(const t_commrec *cr, FILE *fplog, int nsteps, gmx_iterate_t *iterate, gmx_bool bFirstIterate, real fom, real *newf)
81 /* monitor convergence, and use a secant search to propose new
84 The secant method computes x_{i+1} = x_{i} - f(x_{i}) * ---------------------
87 The function we are trying to zero is fom-x, where fom is the
88 "figure of merit" which is the pressure (or the veta value) we
89 would get by putting in an old value of the pressure or veta into
90 the incrementor function for the step or half step. I have
91 verified that this gives the same answer as self consistent
92 iteration, usually in many fewer steps, especially for small tau_p.
94 We could possibly eliminate an iteration with proper use
95 of the value from the previous step, but that would take a bit
96 more bookkeeping, especially for veta, since tests indicate the
97 function of veta on the last step is not sufficiently close to
98 guarantee convergence this step. This is
99 good enough for now. On my tests, I could use tau_p down to
100 0.02, which is smaller that would ever be necessary in
101 practice. Generally, 3-5 iterations will be sufficient */
103 real relerr, err, xmin;
110 iterate->f = fom-iterate->x;
117 iterate->f = fom-iterate->x; /* we want to zero this difference */
118 if ((iterate->iter_i > 1) && (iterate->iter_i < MAXITERCONST))
120 if (iterate->f == iterate->fprev)
126 *newf = iterate->x - (iterate->x-iterate->xprev)*(iterate->f)/(iterate->f-iterate->fprev);
131 /* just use self-consistent iteration the first step to initialize, or
132 if it's not converging (which happens occasionally -- need to investigate why) */
136 /* Consider a slight shortcut allowing us to exit one sooner -- we check the
137 difference between the closest of x and xprev to the new
138 value. To be 100% certain, we should check the difference between
139 the last result, and the previous result, or
141 relerr = (fabs((x-xprev)/fom));
143 but this is pretty much never necessary under typical conditions.
144 Checking numerically, it seems to lead to almost exactly the same
145 trajectories, but there are small differences out a few decimal
146 places in the pressure, and eventually in the v_eta, but it could
149 if (fabs(*newf-x) < fabs(*newf - xprev)) { xmin = x;} else { xmin = xprev;}
150 relerr = (fabs((*newf-xmin) / *newf));
153 err = fabs((iterate->f-iterate->fprev));
154 relerr = fabs(err/fom);
156 iterate->allrelerr[iterate->iter_i] = relerr;
158 if (iterate->iter_i > 0)
162 fprintf(debug, "Iterating NPT constraints: %6i %20.12f%14.6g%20.12f\n",
163 iterate->iter_i, fom, relerr, *newf);
166 if ((relerr < CONVERGEITER) || (err < CONVERGEITER) || (fom == 0) || ((iterate->x == iterate->xprev) && iterate->iter_i > 1))
168 iterate->bIterationActive = FALSE;
171 fprintf(debug, "Iterating NPT constraints: CONVERGED\n");
175 if (iterate->iter_i > MAXITERCONST)
177 if (relerr < CLOSE_ENOUGH)
180 for (i = 1; i < CYCLEMAX; i++)
182 if ((iterate->allrelerr[iterate->iter_i-(1+i)] == iterate->allrelerr[iterate->iter_i-1]) &&
183 (iterate->allrelerr[iterate->iter_i-(1+i)] == iterate->allrelerr[iterate->iter_i-(1+2*i)]))
188 fprintf(debug, "Exiting from an NPT iterating cycle of length %d\n", i);
196 /* step 1: trapped in a numerical attractor */
197 /* we are trapped in a numerical attractor, and can't converge any more, and are close to the final result.
198 Better to give up convergence here than have the simulation die.
200 iterate->num_close++;
201 iterate->bIterationActive = FALSE;
206 /* Step #2: test if we are reasonably close for other reasons, then monitor the number. If not, die */
208 /* how many close calls have we had? If less than a few, we're OK */
209 if (iterate->num_close < MAX_NUMBER_CLOSE)
211 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);
212 iterate->num_close++;
213 iterate->bIterationActive = FALSE;
215 /* if more than a few, check the total fraction. If too high, die. */
217 else if (iterate->num_close/(double)nsteps > FRACTION_CLOSE)
219 gmx_fatal(FARGS, "Could not converge NPT constraints, too many exceptions (%d%%\n", iterate->num_close/(double)nsteps);
225 gmx_fatal(FARGS, "Could not converge NPT constraints\n");
230 iterate->xprev = iterate->x;
232 iterate->fprev = iterate->f;