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authorJaron Kent-Dobias <jaron@kent-dobias.com>2018-07-10 12:37:02 -0400
committerJaron Kent-Dobias <jaron@kent-dobias.com>2018-07-10 12:37:02 -0400
commite53a4c09eb78e4c5a8365f1328a69ba7f9ff8992 (patch)
tree3c252af9ffafacab8392bf864270dcd034ed07ed /src
parent609fb52b670d8ed74584a988b8c63da82d8d523b (diff)
parent1810103bc9ac4c9a8d432d113f5ca6eae6560fb4 (diff)
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Merge branch 'master' of m5:/srv/git/wolff
Diffstat (limited to 'src')
-rw-r--r--src/wolff_dgm.c247
-rw-r--r--src/wolff_finite.c188
-rw-r--r--src/wolff_heisenberg.cpp77
-rw-r--r--src/wolff_planar.cpp77
-rw-r--r--src/wolff_potts.c485
-rw-r--r--src/wolff_vector.c377
6 files changed, 342 insertions, 1109 deletions
diff --git a/src/wolff_dgm.c b/src/wolff_dgm.c
deleted file mode 100644
index f11b296..0000000
--- a/src/wolff_dgm.c
+++ /dev/null
@@ -1,247 +0,0 @@
-
-#include <getopt.h>
-
-#include <cluster.h>
-
-double identity(h_t x) {
- return -pow(x, 2);
-}
-
-double basic_H(double *H, h_t x) {
- return -H[0] * pow(x, 2);
-}
-
-int main(int argc, char *argv[]) {
-
- L_t L = 128;
- count_t N = (count_t)1e7;
- count_t min_runs = 10;
- count_t n = 3;
- D_t D = 2;
- double T = 2.26918531421;
- double *H = (double *)calloc(MAX_Q, sizeof(double));
- double eps = 0;
- bool silent = false;
- bool record_autocorrelation = false;
- count_t ac_skip = 1;
- count_t W = 10;
-
- int opt;
- q_t H_ind = 0;
-
- while ((opt = getopt(argc, argv, "N:n:D:L:T:H:m:e:saS:W:")) != -1) {
- switch (opt) {
- case 'N':
- N = (count_t)atof(optarg);
- break;
- case 'n':
- n = (count_t)atof(optarg);
- break;
- case 'D':
- D = atoi(optarg);
- break;
- case 'L':
- L = atoi(optarg);
- break;
- case 'T':
- T = atof(optarg);
- break;
- case 'H':
- H[H_ind] = atof(optarg);
- H_ind++;
- break;
- case 'm':
- min_runs = atoi(optarg);
- break;
- case 'e':
- eps = atof(optarg);
- break;
- case 's':
- silent = true;
- break;
- case 'a':
- record_autocorrelation = true;
- break;
- case 'S':
- ac_skip = (count_t)atof(optarg);
- break;
- case 'W':
- W = (count_t)atof(optarg);
- break;
- default:
- exit(EXIT_FAILURE);
- }
- }
-
- gsl_rng *r = gsl_rng_alloc(gsl_rng_mt19937);
- gsl_rng_set(r, rand_seed());
-
- dgm_state_t *s = (dgm_state_t *)calloc(1, sizeof(dgm_state_t));
-
- graph_t *h = graph_create_square(D, L);
- s->g = graph_add_ext(h);
-
- s->spins = (h_t *)calloc(h->nv, sizeof(h_t));
-
- s->H_info = H;
- s->T = T;
- s->H = basic_H;
- s->J = identity;
-
- s->R = (dihinf_t *)calloc(1, sizeof(dihinf_t));
-
- s->M = 0;
- s->E = 0;
-
- double diff = 1e31;
- count_t n_runs = 0;
- count_t n_steps = 0;
-
- meas_t *E, *clust, *M, *dM;
-
- M = (meas_t *)calloc(1, sizeof(meas_t ));
- dM = (meas_t *)calloc(1, sizeof(meas_t ));
-
- E = calloc(1, sizeof(meas_t));
- clust = calloc(1, sizeof(meas_t));
-
- autocorr_t *autocorr;
- if (record_autocorrelation) {
- autocorr = (autocorr_t *)calloc(1, sizeof(autocorr_t));
- autocorr->W = 2 * W + 1;
- autocorr->OO = (double *)calloc(2 * W + 1, sizeof(double));
- }
-
- if (!silent) printf("\n");
- while (((diff > eps || diff != diff) && n_runs < N) || n_runs < min_runs) {
- if (!silent) printf("\033[F\033[JWOLFF: sweep %" PRIu64
- ", dH/H = %.4f, dM/M = %.4f, dC/C = %.4f, dX/X = %.4f, cps: %.1f\n",
- n_runs, fabs(meas_dx(E) / E->x), meas_dx(M) / M->x, meas_dc(E) / meas_c(E), meas_dc(M) / meas_c(M), h->nv / clust->x);
-
- count_t n_flips = 0;
-
- while (n_flips / h->nv < n) {
- v_t v0 = gsl_rng_uniform_int(r, h->nv);
- h_t step = round((((double)s->M) / h->nv) + gsl_ran_gaussian(r, 5));
-
- v_t tmp_flips = flip_cluster_dgm(s, v0, step, r);
- n_flips += tmp_flips;
-
- if (n_runs > 0) {
- n_steps++;
- meas_update(clust, tmp_flips);
- }
-
- if (record_autocorrelation && n_runs > 0) {
- if (n_steps % ac_skip == 0) {
- update_autocorr(autocorr, s->E);
- }
- }
- }
-
- meas_update(M, s->M);
- h_t min_h, max_h;
- min_h = MAX_H;
- max_h = MIN_H;
- for (v_t i = 0; i < h->nv; i++) {
- if (s->spins[i] < min_h) {
- min_h = s->spins[i];
- } else if (s->spins[i] > max_h) {
- max_h = s->spins[i];
- }
- }
- meas_update(dM, max_h - min_h);
- meas_update(E, s->E);
-
- diff = fabs(meas_dc(E) / meas_c(E));
-
- n_runs++;
- }
- if (!silent) {
- printf("\033[F\033[J");
- }
- printf("WOLFF: sweep %" PRIu64
- ", dH/H = %.4f, dM/M = %.4f, dC/C = %.4f, dX/X = %.4f, cps: %.1f\n",
- n_runs, fabs(meas_dx(E) / E->x), meas_dx(M) / M->x, meas_dc(E) / meas_c(E), meas_dc(M) / meas_c(M), h->nv / clust->x);
-
- double tau = 0;
- bool tau_failed = false;
-
- if (record_autocorrelation) {
- double *Gammas = (double *)malloc((W + 1) * sizeof(double));
-
- Gammas[0] = 1 + rho(autocorr, 0);
- for (uint64_t i = 0; i < W; i++) {
- Gammas[1 + i] = rho(autocorr, 2 * i + 1) + rho(autocorr, 2 * i + 2);
- }
-
- uint64_t n;
- for (n = 0; n < W + 1; n++) {
- if (Gammas[n] <= 0) {
- break;
- }
- }
-
- if (n == W + 1) {
- printf("WARNING: correlation function never hit the noise floor.\n");
- tau_failed = true;
- }
-
- if (n < 2) {
- printf("WARNING: correlation function only has one nonnegative term.\n");
- tau_failed = true;
- }
-
- double *conv_Gamma = get_convex_minorant(n, Gammas);
-
- double ttau = - 0.5;
-
- for (uint64_t i = 0; i < n + 1; i++) {
- ttau += conv_Gamma[i];
- }
-
- free(Gammas);
- free(autocorr->OO);
- while (autocorr->Op != NULL) {
- stack_pop_d(&(autocorr->Op));
- }
- free(autocorr);
-
- tau = ttau * ac_skip * clust->x / h->nv;
- }
-
- if (tau_failed) {
- tau = 0;
- }
-
- FILE *outfile = fopen("out.m", "a");
-
- fprintf(outfile, "<|D->%" PRID ",L->%" PRIL ",T->%.15f", D, L, T);
- fprintf(outfile, ",E->%.15f,\\[Delta]E->%.15f,C->%.15f,\\[Delta]C->%.15f,M->%.15f", E->x / h->nv, meas_dx(E) / h->nv, meas_c(E) / h->nv, meas_dc(E) / h->nv, M->x / h->nv);
- fprintf(outfile, ",\\[Delta]M->%.15f", meas_dx(M) / h->nv);
- fprintf(outfile, ",\\[Chi]->%.15f", meas_c(M) / h->nv);
- fprintf(outfile, ",\\[Delta]\\[Chi]->%.15f", meas_dc(M) / h->nv);
- fprintf(outfile, ",w->%.15f,\\[Delta]w->%.15f,wc->%.15f,\\[Delta]wc->%.15f,Subscript[n,\"clust\"]->%.15f,Subscript[\\[Delta]n,\"clust\"]->%.15f,Subscript[m,\"clust\"]->%.15f,Subscript[\\[Delta]m,\"clust\"]->%.15f,\\[Tau]->%.15f|>\n", dM->x, meas_dx(dM), meas_c(dM), meas_dc(dM), clust->x / h->nv, meas_dx(clust) / h->nv, meas_c(clust) / h->nv, meas_dc(clust) / h->nv,tau);
-
- fclose(outfile);
-
- FILE *image = fopen("out.dat", "a");
- for (v_t i = 0; i < h->nv; i++) {
- fprintf(image, "%" PRIh " ", s->spins[i]);
- }
- fprintf(image, "\n");
- fclose(image);
-
- free(E);
- free(clust);
- free(H);
- free(s->R);
- free(s->spins);
- graph_free(s->g);
- free(s);
- graph_free(h);
- gsl_rng_free(r);
-
- return 0;
-}
-
diff --git a/src/wolff_finite.c b/src/wolff_finite.c
new file mode 100644
index 0000000..9b3e21e
--- /dev/null
+++ b/src/wolff_finite.c
@@ -0,0 +1,188 @@
+
+#include <time.h>
+#include <getopt.h>
+
+#include <initial_finite.h>
+
+int main(int argc, char *argv[]) {
+
+ count_t N = (count_t)1e7;
+
+ finite_model_t model = ISING;
+
+ q_t q = 2;
+ D_t D = 2;
+ L_t L = 128;
+ double T = 2.26918531421;
+ double *J = (double *)calloc(MAX_Q, sizeof(double));
+ J[0] = 1.0;
+ double *H = (double *)calloc(MAX_Q, sizeof(double));
+
+ bool silent = false;
+
+ int opt;
+ q_t J_ind = 0;
+ q_t H_ind = 0;
+
+ while ((opt = getopt(argc, argv, "N:t:q:D:L:T:J:H:s")) != -1) {
+ switch (opt) {
+ case 'N': // number of steps
+ N = (count_t)atof(optarg);
+ break;
+ case 't': // type of simulation
+ model = (finite_model_t)atoi(optarg);
+ break;
+ case 'q': // number of states, if relevant
+ q = atoi(optarg);
+ break;
+ case 'D': // dimension
+ D = atoi(optarg);
+ break;
+ case 'L': // linear size
+ L = atoi(optarg);
+ break;
+ case 'T': // temperature
+ T = atof(optarg);
+ break;
+ case 'J': // couplings, if relevant. nth call couples states i and i + n
+ J[J_ind] = atof(optarg);
+ J_ind++;
+ break;
+ case 'H': // external field. nth call couples to state n
+ H[H_ind] = atof(optarg);
+ H_ind++;
+ break;
+ case 's': // don't print anything during simulation. speeds up slightly
+ silent = true;
+ break;
+ default:
+ exit(EXIT_FAILURE);
+ }
+ }
+
+ state_finite_t *s;
+
+ switch (model) {
+ case ISING:
+ s = initial_finite_prepare_ising(D, L, T, H);
+ break;
+ case POTTS:
+ s = initial_finite_prepare_potts(D, L, q, T, H);
+ break;
+ case CLOCK:
+ s = initial_finite_prepare_clock(D, L, q, T, H);
+ break;
+ case DGM:
+ s = initial_finite_prepare_dgm(D, L, q, T, H);
+ break;
+ default:
+ printf("Not a valid model!\n");
+ free(J);
+ free(H);
+ exit(EXIT_FAILURE);
+ }
+
+ free(J);
+ free(H);
+
+ // initialize random number generator
+ gsl_rng *r = gsl_rng_alloc(gsl_rng_mt19937);
+ gsl_rng_set(r, rand_seed());
+
+ unsigned long timestamp;
+
+ {
+ struct timespec spec;
+ clock_gettime(CLOCK_REALTIME, &spec);
+ timestamp = spec.tv_sec*1000000000LL + spec.tv_nsec;
+ }
+
+ FILE *outfile_info = fopen("wolff_metadata.txt", "a");
+
+ fprintf(outfile_info, "<| \"ID\" -> %lu, \"MODEL\" -> \"%s\", \"q\" -> %" PRIq ", \"D\" -> %" PRID ", \"L\" -> %" PRIL ", \"NV\" -> %" PRIv ", \"NE\" -> %" PRIv ", \"NB\" -> %" PRIq ", \"T\" -> %.15f, \"J\" -> {", timestamp, finite_model_t_strings[model], s->q, D, L, s->nv, s->ne, s->n_bond_types, T);
+
+ for (q_t i = 0; i < s->n_bond_types; i++) {
+ fprintf(outfile_info, "%.15f", s->J[i]);
+ if (i < s->n_bond_types - 1) {
+ fprintf(outfile_info, ", ");
+ }
+ }
+
+ fprintf(outfile_info, "}, \"H\" -> {");
+
+ for (q_t i = 0; i < s->q; i++) {
+ fprintf(outfile_info, "%.15f", s->H[i]);
+ if (i < s->q - 1) {
+ fprintf(outfile_info, ", ");
+ }
+ }
+
+ fprintf(outfile_info, "} |>\n");
+
+ fclose(outfile_info);
+
+ char *filename_M = (char *)malloc(255 * sizeof(char));
+ char *filename_B = (char *)malloc(255 * sizeof(char));
+ char *filename_S = (char *)malloc(255 * sizeof(char));
+
+ sprintf(filename_M, "wolff_%lu_M.dat", timestamp);
+ sprintf(filename_B, "wolff_%lu_B.dat", timestamp);
+ sprintf(filename_S, "wolff_%lu_S.dat", timestamp);
+
+ FILE *outfile_M = fopen(filename_M, "wb");
+ FILE *outfile_B = fopen(filename_B, "wb");
+ FILE *outfile_S = fopen(filename_S, "wb");
+
+ free(filename_M);
+ free(filename_B);
+ free(filename_S);
+
+ v_t cluster_size = 0;
+
+ if (!silent) printf("\n");
+ for (count_t steps = 0; steps < N; steps++) {
+ if (!silent) printf("\033[F\033[JWOLFF: sweep %" PRIu64 " / %" PRIu64 ": E = %.2f, B_0 = %" PRIv ", M_0 = %" PRIv ", S = %" PRIv "\n", steps, N, state_finite_energy(s), s->B[0], s->M[0], cluster_size);
+
+ v_t v0 = gsl_rng_uniform_int(r, s->nv);
+ R_t step;
+
+ bool changed = false;
+ while (!changed) {
+ step = gsl_rng_uniform_int(r, s->n_involutions);
+ if (symmetric_act(s->transformations + s->q * s->involutions[step], s->spins[v0]) != s->spins[v0]) {
+ changed = true;
+ }
+ }
+
+ cluster_size = flip_cluster_finite(s, v0, step, r);
+
+ // v_t is never going to be bigger than 32 bits, but since it's specified
+ // as a fast time many machines will actually have it be 64 bits. we cast
+ // it down here to halve space.
+
+ for (q_t i = 0; i < s->n_bond_types - 1; i++) { // if we know the occupation of all but one state we know the occupation of the last
+ fwrite(&(s->B[i]), sizeof(uint32_t), 1, outfile_B);
+ }
+
+ for (q_t i = 0; i < s->q - 1; i++) { // if we know the occupation of all but one state we know the occupation of the last
+ fwrite(&(s->M[i]), sizeof(uint32_t), 1, outfile_M);
+ }
+
+ fwrite(&cluster_size, sizeof(uint32_t), 1, outfile_S);
+
+ }
+ if (!silent) {
+ printf("\033[F\033[J");
+ }
+ printf("WOLFF: sweep %" PRIu64 " / %" PRIu64 ": E = %.2f, B_0 = %" PRIv ", M_0 = %" PRIv ", S = %" PRIv "\n", N, N, state_finite_energy(s), s->B[0], s->M[0], cluster_size);
+
+ fclose(outfile_M);
+ fclose(outfile_B);
+ fclose(outfile_S);
+
+ state_finite_free(s);
+ gsl_rng_free(r);
+
+ return 0;
+}
+
diff --git a/src/wolff_heisenberg.cpp b/src/wolff_heisenberg.cpp
new file mode 100644
index 0000000..d1ebd48
--- /dev/null
+++ b/src/wolff_heisenberg.cpp
@@ -0,0 +1,77 @@
+
+#include <getopt.h>
+
+#include <wolff.h>
+
+int main(int argc, char *argv[]) {
+
+ count_t N = (count_t)1e7;
+
+ D_t D = 2;
+ L_t L = 128;
+ double T = 2.26918531421;
+ double *H = (double *)calloc(MAX_Q, sizeof(double));
+
+ bool silent = false;
+
+ int opt;
+ q_t J_ind = 0;
+ q_t H_ind = 0;
+
+ while ((opt = getopt(argc, argv, "N:q:D:L:T:J:H:s")) != -1) {
+ switch (opt) {
+ case 'N': // number of steps
+ N = (count_t)atof(optarg);
+ break;
+ case 'D': // dimension
+ D = atoi(optarg);
+ break;
+ case 'L': // linear size
+ L = atoi(optarg);
+ break;
+ case 'T': // temperature
+ T = atof(optarg);
+ break;
+ case 'H': // external field. nth call couples to state n
+ H[H_ind] = atof(optarg);
+ H_ind++;
+ break;
+ case 's': // don't print anything during simulation. speeds up slightly
+ silent = true;
+ break;
+ default:
+ exit(EXIT_FAILURE);
+ }
+ }
+
+ unsigned long timestamp;
+
+ {
+ struct timespec spec;
+ clock_gettime(CLOCK_REALTIME, &spec);
+ timestamp = spec.tv_sec*1000000000LL + spec.tv_nsec;
+ }
+
+ FILE *outfile_info = fopen("wolff_metadata.txt", "a");
+
+ fprintf(outfile_info, "<| \"ID\" -> %lu, \"MODEL\" -> \"HEISENBERG\", q -> \"3\", \"D\" -> %" PRID ", \"L\" -> %" PRIL ", \"NV\" -> %" PRIv ", \"NE\" -> %" PRIv ", \"T\" -> %.15f, \"H\" -> {", timestamp, D, L, L * L, D * L * L, T);
+
+ for (q_t i = 0; i < 2; i++) {
+ fprintf(outfile_info, "%.15f", H[i]);
+ if (i < 2 - 1) {
+ fprintf(outfile_info, ", ");
+ }
+ }
+
+ fprintf(outfile_info, "} |>\n");
+
+ fclose(outfile_info);
+
+
+ wolff <orthogonal_t <3, double>, vector_t <3, double>> (N, D, L, T, dot <3, double>, std::bind(H_vector <3, double>, std::placeholders::_1, H), timestamp, silent);
+
+ free(H);
+
+ return 0;
+}
+
diff --git a/src/wolff_planar.cpp b/src/wolff_planar.cpp
new file mode 100644
index 0000000..02ededc
--- /dev/null
+++ b/src/wolff_planar.cpp
@@ -0,0 +1,77 @@
+
+#include <getopt.h>
+
+#include <wolff.h>
+
+int main(int argc, char *argv[]) {
+
+ count_t N = (count_t)1e7;
+
+ D_t D = 2;
+ L_t L = 128;
+ double T = 2.26918531421;
+ double *H = (double *)calloc(MAX_Q, sizeof(double));
+
+ bool silent = false;
+
+ int opt;
+ q_t J_ind = 0;
+ q_t H_ind = 0;
+
+ while ((opt = getopt(argc, argv, "N:q:D:L:T:J:H:s")) != -1) {
+ switch (opt) {
+ case 'N': // number of steps
+ N = (count_t)atof(optarg);
+ break;
+ case 'D': // dimension
+ D = atoi(optarg);
+ break;
+ case 'L': // linear size
+ L = atoi(optarg);
+ break;
+ case 'T': // temperature
+ T = atof(optarg);
+ break;
+ case 'H': // external field. nth call couples to state n
+ H[H_ind] = atof(optarg);
+ H_ind++;
+ break;
+ case 's': // don't print anything during simulation. speeds up slightly
+ silent = true;
+ break;
+ default:
+ exit(EXIT_FAILURE);
+ }
+ }
+
+ unsigned long timestamp;
+
+ {
+ struct timespec spec;
+ clock_gettime(CLOCK_REALTIME, &spec);
+ timestamp = spec.tv_sec*1000000000LL + spec.tv_nsec;
+ }
+
+ FILE *outfile_info = fopen("wolff_metadata.txt", "a");
+
+ fprintf(outfile_info, "<| \"ID\" -> %lu, \"MODEL\" -> \"PLANAR\", \"q\" -> 2, \"D\" -> %" PRID ", \"L\" -> %" PRIL ", \"NV\" -> %" PRIv ", \"NE\" -> %" PRIv ", \"T\" -> %.15f, \"H\" -> {", timestamp, D, L, L * L, D * L * L, T);
+
+ for (q_t i = 0; i < 2; i++) {
+ fprintf(outfile_info, "%.15f", H[i]);
+ if (i < 2 - 1) {
+ fprintf(outfile_info, ", ");
+ }
+ }
+
+ fprintf(outfile_info, "} |>\n");
+
+ fclose(outfile_info);
+
+
+ wolff <orthogonal_t <2, double>, vector_t <2, double>> (N, D, L, T, dot <2, double>, std::bind(H_vector <2, double>, std::placeholders::_1, H), timestamp, silent);
+
+ free(H);
+
+ return 0;
+}
+
diff --git a/src/wolff_potts.c b/src/wolff_potts.c
deleted file mode 100644
index b081bec..0000000
--- a/src/wolff_potts.c
+++ /dev/null
@@ -1,485 +0,0 @@
-
-#include <getopt.h>
-
-#include <dihedral.h>
-#include <cluster_finite.h>
-
-int main(int argc, char *argv[]) {
-
- L_t L = 128;
- count_t N = (count_t)1e7;
- count_t min_runs = 10;
- count_t n = 3;
- q_t q = 2;
- D_t D = 2;
- double T = 2.26918531421;
- double *J = (double *)calloc(MAX_Q, sizeof(double));
- J[0] = 1.0;
- double *H = (double *)calloc(MAX_Q, sizeof(double));
- double eps = 0;
- bool pretend_ising = false;
- bool planar_potts = false;
- bool sim_dgm = false;
- bool silent = false;
- bool snapshots = false;
- bool snapshot = false;
- bool record_autocorrelation = false;
- bool record_distribution = false;
- count_t W = 10;
- count_t ac_skip = 1;
-
- int opt;
- q_t J_ind = 0;
- q_t H_ind = 0;
-
- while ((opt = getopt(argc, argv, "N:n:D:L:q:T:J:H:m:e:IpsSPak:W:dr")) != -1) {
- switch (opt) {
- case 'N':
- N = (count_t)atof(optarg);
- break;
- case 'n':
- n = (count_t)atof(optarg);
- break;
- case 'D':
- D = atoi(optarg);
- break;
- case 'L':
- L = atoi(optarg);
- break;
- case 'q':
- q = atoi(optarg);
- break;
- case 'T':
- T = atof(optarg);
- break;
- case 'J':
- J[J_ind] = atof(optarg);
- J_ind++;
- break;
- case 'H':
- H[H_ind] = atof(optarg);
- H_ind++;
- break;
- case 'm':
- min_runs = atoi(optarg);
- break;
- case 'e':
- eps = atof(optarg);
- break;
- case 'I':
- pretend_ising = true;
- break;
- case 'p':
- planar_potts = true;
- break;
- case 's':
- silent = true;
- break;
- case 'S':
- snapshots = true;
- break;
- case 'P':
- snapshot = true;
- break;
- case 'a':
- record_autocorrelation = true;
- break;
- case 'k':
- ac_skip = (count_t)atof(optarg);
- break;
- case 'W':
- W = (count_t)atof(optarg);
- break;
- case 'd':
- record_distribution = true;
- break;
- case 'r':
- sim_dgm = true;
- break;
- default:
- exit(EXIT_FAILURE);
- }
- }
-
- gsl_rng *r = gsl_rng_alloc(gsl_rng_mt19937);
- gsl_rng_set(r, rand_seed());
-
- if (pretend_ising) {
- q = 2;
- H[1] = -H[0];
- J[1] = -J[0];
- }
-
- if (planar_potts) {
- for (q_t i = 0; i < q; i++) {
- J[i] = cos(2 * M_PI * i / ((double)q));
- }
- }
-
- if (sim_dgm) {
- for (q_t i = 0; i < q / 2 + 1; i++) {
- J[i] = -pow(i, 2);
- }
- for (q_t i = 1; i < (q + 1) / 2; i++) {
- J[q - i] = -pow(i, 2);
- }
- }
-
- state_finite_t *s = (state_finite_t *)calloc(1, sizeof(state_finite_t));
-
- graph_t *h = graph_create_square(D, L);
- s->g = graph_add_ext(h);
-
- s->q = q;
- s->n_transformations = q;
- s->transformations = dihedral_gen_transformations(q);
-
- s->T = T;
- s->J = J;
- s->H = H;
-
- s->J_probs = (double *)calloc(pow(q, 2), sizeof(double));
- for (q_t i = 0; i < q; i++) {
- for (q_t j = 0; j < q; j++) {
- s->J_probs[q * i + j] = 1.0 - exp((s->J[i] - s->J[j]) / T);
- }
- }
- s->H_probs = (double *)calloc(pow(q, 2), sizeof(double));
- for (q_t i = 0; i < q; i++) {
- for (q_t j = 0; j < q; j++) {
- s->H_probs[q * i + j] = 1.0 - exp((s->H[i] - s->H[j]) / T);
- }
- }
-
- s->spins = (q_t *)calloc(h->nv, sizeof(q_t)); // everyone starts in state 0
- s->R = (q_t *)malloc(q * sizeof(q_t)); // transformation is the identity, (1 ... q)
-
- for (q_t i = 0; i < q; i++) {
- s->R[i] = i;
- }
-
- // energy is the number of edges times the energy of an aligned edge minus
- // the number of vertices times the energy of a 0-aligned vertex
- s->E = - ((double)h->ne) * s->J[0] - ((double)h->nv) * s->H[0];
- s->M = (v_t *)calloc(q, sizeof(v_t));
- s->M[0] = h->nv; // everyone starts in state 0, remember?
-
- double diff = 1e31;
- count_t n_runs = 0;
- count_t n_steps = 0;
-
- meas_t *E, *clust, **M, **sE, ***sM;
-
- M = (meas_t **)malloc(q * sizeof(meas_t *));
- for (q_t i = 0; i < q; i++) {
- M[i] = (meas_t *)calloc(1, sizeof(meas_t));
- }
-
- E = calloc(1, sizeof(meas_t));
- clust = calloc(1, sizeof(meas_t));
-
- sE = (meas_t **)malloc(q * sizeof(meas_t *));
- sM = (meas_t ***)malloc(q * sizeof(meas_t **));
-
- for (q_t i = 0; i < q; i++) {
- sE[i] = (meas_t *)calloc(1, sizeof(meas_t));
- sM[i] = (meas_t **)malloc(q * sizeof(meas_t *));
- for (q_t j = 0; j < q; j++) {
- sM[i][j] = (meas_t *)calloc(1, sizeof(meas_t));
- }
- }
-
- count_t *freqs = (count_t *)calloc(q, sizeof(count_t));
- q_t cur_M = 0;
-
- autocorr_t *autocorr;
- if (record_autocorrelation) {
- autocorr = (autocorr_t *)calloc(1, sizeof(autocorr_t));
- autocorr->W = 2 * W + 1;
- autocorr->OO = (double *)calloc(2 * W + 1, sizeof(double));
- }
-
- count_t *mag_dist;
- if (record_distribution) {
- mag_dist = (count_t *)calloc(h->nv + 1, sizeof(count_t));
- }
-
- if (!silent) printf("\n");
- while (((diff > eps || diff != diff) && n_runs < N) || n_runs < min_runs) {
- if (!silent) printf("\033[F\033[JWOLFF: sweep %" PRIu64
- ", dH/H = %.4f, dM/M = %.4f, dC/C = %.4f, dX/X = %.4f, cps: %.1f\n",
- n_runs, fabs(meas_dx(E) / E->x), meas_dx(M[0]) / M[0]->x, meas_dc(E) / meas_c(E), meas_dc(M[0]) / meas_c(M[0]), h->nv / clust->x);
-
- count_t n_flips = 0;
-
- while (n_flips / h->nv < n) {
- v_t v0 = gsl_rng_uniform_int(r, h->nv);
- R_t step;
-
- bool changed = false;
- while (!changed) {
- step = gsl_rng_uniform_int(r, s->n_transformations);
- if (symmetric_act(s->transformations + q * step, s->spins[v0]) != s->spins[v0]) {
- changed = true;
- }
- }
-
- v_t tmp_flips = flip_cluster_finite(s, v0, step, r);
- n_flips += tmp_flips;
-
- if (n_runs > 0) {
- n_steps++;
- meas_update(clust, tmp_flips);
-
- if (record_autocorrelation && n_steps % ac_skip == 0) {
- update_autocorr(autocorr, s->E);
- }
-
- }
-
- }
-
- for (q_t i = 0; i < q; i++) {
- meas_update(M[i], s->M[i]);
- }
- meas_update(E, s->E);
-
- q_t n_at_max = 0;
- q_t max_M_i = 0;
- v_t max_M = 0;
-
- for (q_t i = 0; i < q; i++) {
- if (s->M[i] > max_M) {
- n_at_max = 1;
- max_M_i = i;
- max_M = s->M[i];
- } else if (s->M[i] == max_M) {
- n_at_max++;
- }
- }
-
- if (record_distribution) {
- mag_dist[s->M[0]]++;
- }
-
- if (n_at_max == 1) {
- for (q_t i = 0; i < q; i++) {
- meas_update(sM[max_M_i][i], s->M[i]);
- }
- meas_update(sE[max_M_i], s->E);
- freqs[max_M_i]++;
- }
-
- diff = fabs(meas_dx(clust) / clust->x);
-
- n_runs++;
- }
- if (!silent) {
- printf("\033[F\033[J");
- }
- printf("WOLFF: sweep %" PRIu64
- ", dH/H = %.4f, dM/M = %.4f, dC/C = %.4f, dX/X = %.4f, cps: %.1f\n",
- n_runs, fabs(meas_dx(E) / E->x), meas_dx(M[0]) / M[0]->x, meas_dc(E) / meas_c(E), meas_dc(M[0]) / meas_c(M[0]), h->nv / clust->x);
-
- if (snapshots) {
- FILE *snapfile = fopen("snapshots.m", "a");
- fprintf(snapfile, "\n");
- }
-
- if (snapshot) {
- q_t *R_inv = symmetric_invert(q, s->R);
- FILE *snapfile = fopen("snapshot.m", "a");
- fprintf(snapfile, "{{");
- for (L_t i = 0; i < L; i++) {
- fprintf(snapfile, "{");
- for (L_t j = 0; j < L; j++) {
- fprintf(snapfile, "%" PRIq, symmetric_act(R_inv, s->spins[L * i + j]));
- if (j != L - 1) {
- fprintf(snapfile, ",");
- }
- }
- fprintf(snapfile, "}");
- if (i != L - 1) {
- fprintf(snapfile, ",");
- }
- }
- fprintf(snapfile, "}}\n");
- fclose(snapfile);
- }
-
- double tau = 0;
- int tau_failed = 0;
-
- if (record_autocorrelation) {
- double *Gammas = (double *)malloc((W + 1) * sizeof(double));
-
- Gammas[0] = 1 + rho(autocorr, 0);
- for (uint64_t i = 0; i < W; i++) {
- Gammas[1 + i] = rho(autocorr, 2 * i + 1) + rho(autocorr, 2 * i + 2);
- }
-
- uint64_t n;
- for (n = 0; n < W + 1; n++) {
- if (Gammas[n] <= 0) {
- break;
- }
- }
-
- if (n == W + 1) {
- printf("WARNING: correlation function never hit the noise floor.\n");
- tau_failed = 1;
- }
-
- if (n < 2) {
- printf("WARNING: correlation function only has one nonnegative term.\n");
- tau_failed = 2;
- }
-
- double *conv_Gamma = get_convex_minorant(n, Gammas);
-
- double ttau = - 0.5;
-
- for (uint64_t i = 0; i < n + 1; i++) {
- ttau += conv_Gamma[i];
- }
-
- tau = ttau * ac_skip * clust->x / h->nv;
-
- free(Gammas);
- free(autocorr->OO);
- while (autocorr->Op != NULL) {
- stack_pop_d(&(autocorr->Op));
- }
- free(autocorr);
- }
-
- if (tau_failed) {
- //tau = 0;
- }
-
- FILE *outfile = fopen("out.m", "a");
-
- fprintf(outfile, "<|N->%" PRIcount ",n->%" PRIcount ",D->%" PRID ",L->%" PRIL ",q->%" PRIq ",T->%.15f,J->{", N, n, D, L, q, T);
- for (q_t i = 0; i < q; i++) {
- fprintf(outfile, "%.15f", J[i]);
- if (i != q-1) {
- fprintf(outfile, ",");
- }
- }
- fprintf(outfile, "},H->{");
- for (q_t i = 0; i < q; i++) {
- fprintf(outfile, "%.15f", H[i]);
- if (i != q-1) {
- fprintf(outfile, ",");
- }
- }
- fprintf(outfile, "},E->%.15f,\\[Delta]E->%.15f,C->%.15f,\\[Delta]C->%.15f,M->{", E->x / h->nv, meas_dx(E) / h->nv, meas_c(E) / h->nv, meas_dc(E) / h->nv);
- for (q_t i = 0; i < q; i++) {
- fprintf(outfile, "%.15f", M[i]->x / h->nv);
- if (i != q-1) {
- fprintf(outfile, ",");
- }
- }
- fprintf(outfile, "},\\[Delta]M->{");
- for (q_t i = 0; i < q; i++) {
- fprintf(outfile, "%.15f", meas_dx(M[i]) / h->nv);
- if (i != q-1) {
- fprintf(outfile, ",");
- }
- }
- fprintf(outfile, "},\\[Chi]->{");
- for (q_t i = 0; i < q; i++) {
- fprintf(outfile, "%.15f", meas_c(M[i]) / h->nv);
- if (i != q-1) {
- fprintf(outfile, ",");
- }
- }
- fprintf(outfile, "},\\[Delta]\\[Chi]->{");
- for (q_t i = 0; i < q; i++) {
- fprintf(outfile, "%.15f", meas_dc(M[i]) / h->nv);
- if (i != q-1) {
- fprintf(outfile, ",");
- }
- }
- for (q_t i = 0; i < q; i++) {
- fprintf(outfile, "},Subscript[E,%" PRIq "]->%.15f,Subscript[\\[Delta]E,%" PRIq "]->%.15f,Subscript[C,%" PRIq "]->%.15f,Subscript[\\[Delta]C,%" PRIq "]->%.15f,Subscript[M,%" PRIq "]->{", i, sE[i]->x / h->nv, i, meas_dx(sE[i]) / h->nv, i, meas_c(sE[i]) / h->nv, i, meas_dc(sE[i]) / h->nv, i);
- for (q_t j = 0; j < q; j++) {
- fprintf(outfile, "%.15f", sM[i][j]->x / h->nv);
- if (j != q-1) {
- fprintf(outfile, ",");
- }
- }
- fprintf(outfile, "},Subscript[\\[Delta]M,%" PRIq "]->{", i);
- for (q_t j = 0; j < q; j++) {
- fprintf(outfile, "%.15f", meas_dx(sM[i][j]) / h->nv);
- if (j != q-1) {
- fprintf(outfile, ",");
- }
- }
- fprintf(outfile, "},Subscript[\\[Chi],%" PRIq "]->{", i);
- for (q_t j = 0; j < q; j++) {
- fprintf(outfile, "%.15f", meas_c(sM[i][j]) / h->nv);
- if (j != q-1) {
- fprintf(outfile, ",");
- }
- }
- fprintf(outfile, "},Subscript[\\[Delta]\\[Chi],%" PRIq "]->{", i);
- for (q_t j = 0; j < q; j++) {
- fprintf(outfile, "%.15f", meas_dc(sM[i][j]) / h->nv);
- if (j != q-1) {
- fprintf(outfile, ",");
- }
- }
- }
- fprintf(outfile,"}");
- for (q_t i = 0; i < q; i++) {
- fprintf(outfile, ",Subscript[f,%" PRIq "]->%.15f,Subscript[\\[Delta]f,%" PRIq "]->%.15f", i, (double)freqs[i] / (double)n_runs, i, sqrt(freqs[i]) / (double)n_runs);
- }
- fprintf(outfile, ",Subscript[n,\"clust\"]->%.15f,Subscript[\\[Delta]n,\"clust\"]->%.15f,Subscript[m,\"clust\"]->%.15f,Subscript[\\[Delta]m,\"clust\"]->%.15f,\\[Tau]->%.15f,\\[Tau]s->%d", clust->x / h->nv, meas_dx(clust) / h->nv, meas_c(clust) / h->nv, meas_dc(clust) / h->nv,tau,tau_failed);
- if (record_distribution) {
- fprintf(outfile, ",S->{");
- for (v_t i = 0; i < h->nv + 1; i++) {
- fprintf(outfile, "%" PRIcount, mag_dist[i]);
- if (i != h->nv) {
- fprintf(outfile, ",");
- }
- }
- fprintf(outfile, "}");
- free(mag_dist);
- }
- fprintf(outfile, "|>\n");
-
- fclose(outfile);
-
- free(E);
- free(clust);
- for (q_t i = 0; i < q; i++) {
- free(M[i]);
- for (q_t j = 0; j < q; j++) {
- free(sM[i][j]);
- }
- free(sM[i]);
- }
- free(M);
- free(sM);
- for (q_t i = 0; i < q; i++) {
- free(sE[i]);
- }
- free(freqs);
- free(sE);
- free(s->H_probs);
- free(s->J_probs);
- free(s->M);
- free(s->spins);
- free(s->R);
- free(s->transformations);
- graph_free(s->g);
- free(s);
- free(H);
- free(J);
- graph_free(h);
- gsl_rng_free(r);
-
- return 0;
-}
-
diff --git a/src/wolff_vector.c b/src/wolff_vector.c
deleted file mode 100644
index c5ebcb5..0000000
--- a/src/wolff_vector.c
+++ /dev/null
@@ -1,377 +0,0 @@
-
-#include <getopt.h>
-
-#include <cluster.h>
-
-double identity(double x) {
- return x;
-}
-
-double zero(q_t n, double *H, double *x) {
- return 0.0;
-}
-
-double dot(q_t n, double *H, double *x) {
- double total = 0;
- for (q_t i = 0; i < n; i++) {
- total += H[i] * x[i];
- }
- return total;
-}
-
-double theta(double x, double y) {
- double val = atan(y / x);
-
- if (x < 0.0 && y > 0.0) {
- return M_PI + val;
- } else if ( x < 0.0 && y < 0.0 ) {
- return - M_PI + val;
- } else {
- return val;
- }
-}
-
-double modulated(q_t n, double *H_info, double *x) {
- return H_info[0] * cos(H_info[1] * theta(x[0], x[1]));
-}
-
-double cubic(q_t n, double *H_info, double *x) {
- double v_sum = 0;
-
- for (q_t i = 0; i < n; i++) {
- v_sum += pow(x[i], 4);
- }
-
- return - H_info[0] * v_sum;
-}
-
-double quadratic(q_t n, double *H_info, double *x) {
- double tmp = 0;
-
- tmp += pow(x[0], 2);
-
- for (q_t i = 1; i < n; i++) {
- tmp += - 1.0 / (n - 1.0) * pow(x[i], 2);
- }
-
- return - 0.5 * H_info[0] * tmp;
-}
-
-int main(int argc, char *argv[]) {
-
- L_t L = 128;
- count_t N = (count_t)1e7;
- count_t min_runs = 10;
- count_t n = 3;
- q_t q = 2;
- D_t D = 2;
- double T = 2.26918531421;
- double *H = (double *)calloc(MAX_Q, sizeof(double));
- double eps = 0;
- bool silent = false;
- bool record_autocorrelation = false;
- vector_field_t H_type = VECTOR;
- count_t ac_skip = 1;
- count_t W = 10;
-
- int opt;
- q_t H_ind = 0;
-
- while ((opt = getopt(argc, argv, "N:n:D:L:q:T:H:m:e:saS:W:f:")) != -1) {
- switch (opt) {
- case 'N':
- N = (count_t)atof(optarg);
- break;
- case 'n':
- n = (count_t)atof(optarg);
- break;
- case 'D':
- D = atoi(optarg);
- break;
- case 'L':
- L = atoi(optarg);
- break;
- case 'q':
- q = atoi(optarg);
- break;
- case 'T':
- T = atof(optarg);
- break;
- case 'H':
- H[H_ind] = atof(optarg);
- H_ind++;
- break;
- case 'm':
- min_runs = atoi(optarg);
- break;
- case 'e':
- eps = atof(optarg);
- break;
- case 's':
- silent = true;
- break;
- case 'a':
- record_autocorrelation = true;
- break;
- case 'S':
- ac_skip = (count_t)atof(optarg);
- break;
- case 'W':
- W = (count_t)atof(optarg);
- break;
- case 'f':
- switch (atoi(optarg)) {
- case 0:
- H_type = VECTOR;
- break;
- case 1:
- H_type = MODULATED;
- break;
- case 2:
- H_type = CUBIC;
- break;
- case 3:
- H_type = QUADRATIC;
- break;
- }
- break;
- default:
- exit(EXIT_FAILURE);
- }
- }
-
- gsl_rng *r = gsl_rng_alloc(gsl_rng_mt19937);
- gsl_rng_set(r, rand_seed());
-
- vector_state_t *s = (vector_state_t *)calloc(1, sizeof(vector_state_t));
-
- graph_t *h = graph_create_square(D, L);
- s->g = graph_add_ext(h);
-
- s->n = q;
-
- s->spins = (double *)calloc(n * h->nv, sizeof(double));
-
- for (v_t i = 0; i < h->nv; i++) {
- s->spins[q * i] = 1.0;
- }
-
- s->H_info = H;
- s->T = T;
- switch (H_type) {
- case VECTOR:
- s->H = dot;
- break;
- case MODULATED:
- s->H = modulated;
- break;
- case CUBIC:
- s->H = cubic;
- break;
- case QUADRATIC:
- s->H = quadratic;
- break;
- }
- s->J = identity;
-
- s->R = (double *)calloc(q * q, sizeof(double));
-
- for (q_t i = 0; i < q; i++) {
- s->R[q * i + i] = 1.0;
- }
-
- s->M = (double *)calloc(q, sizeof(double));
- s->M[0] = 1.0;
- s->E = - ((double)h->ne) * s->J(1.0) - (double)h->nv * s->H(s->n, s->H_info, s->M);
- s->M[0] *= (double)h->nv;
-
- double diff = 1e31;
- count_t n_runs = 0;
- count_t n_steps = 0;
-
- meas_t *E, *clust, **M, *aM;
-
- M = (meas_t **)malloc(q * sizeof(meas_t *));
- aM = (meas_t *)calloc(q, sizeof(meas_t ));
- for (q_t i = 0; i < q; i++) {
- M[i] = (meas_t *)calloc(1, sizeof(meas_t));
- }
-
- E = calloc(1, sizeof(meas_t));
- clust = calloc(1, sizeof(meas_t));
-
- autocorr_t *autocorr;
- if (record_autocorrelation) {
- autocorr = (autocorr_t *)calloc(1, sizeof(autocorr_t));
- autocorr->W = 2 * W + 1;
- autocorr->OO = (double *)calloc(2 * W + 1, sizeof(double));
- }
-
- if (!silent) printf("\n");
- while (((diff > eps || diff != diff) && n_runs < N) || n_runs < min_runs) {
- if (!silent) printf("\033[F\033[JWOLFF: sweep %" PRIu64
- ", dH/H = %.4f, dM/M = %.4f, dC/C = %.4f, dX/X = %.4f, cps: %.1f\n",
- n_runs, fabs(meas_dx(E) / E->x), meas_dx(aM) / aM->x, meas_dc(E) / meas_c(E), meas_dc(aM) / meas_c(aM), h->nv / clust->x);
-
- count_t n_flips = 0;
-
- while (n_flips / h->nv < n) {
- v_t v0 = gsl_rng_uniform_int(r, h->nv);
- double *step = gen_rot(r, q);
-
- v_t tmp_flips = flip_cluster_vector(s, v0, step, r);
- free(step);
- n_flips += tmp_flips;
-
- if (n_runs > 0) {
- n_steps++;
- meas_update(clust, tmp_flips);
-
- if (record_autocorrelation && n_steps % ac_skip == 0) {
- update_autocorr(autocorr, s->E);
- }
- }
- }
-
- double aM_val = 0;
-
- for (q_t i = 0; i < q; i++) {
- meas_update(M[i], s->M[i]);
- aM_val += s->M[i] * s->M[i];
- }
-
- meas_update(aM, sqrt(aM_val));
- meas_update(E, s->E);
-
- diff = fabs(meas_dx(clust) / clust->x);
-
- n_runs++;
- }
-
- if (!silent) {
- printf("\033[F\033[J");
- }
- printf("WOLFF: sweep %" PRIu64
- ", dH/H = %.4f, dM/M = %.4f, dC/C = %.4f, dX/X = %.4f, cps: %.1f\n",
- n_runs, fabs(meas_dx(E) / E->x), meas_dx(M[0]) / M[0]->x, meas_dc(E) / meas_c(E), meas_dc(M[0]) / meas_c(M[0]), h->nv / clust->x);
-
- double tau = 0;
- bool tau_failed = false;
-
- if (record_autocorrelation) {
- double *Gammas = (double *)malloc((W + 1) * sizeof(double));
-
- Gammas[0] = 1 + rho(autocorr, 0);
- for (uint64_t i = 0; i < W; i++) {
- Gammas[1 + i] = rho(autocorr, 2 * i + 1) + rho(autocorr, 2 * i + 2);
- }
-
- uint64_t n;
- for (n = 0; n < W + 1; n++) {
- if (Gammas[n] <= 0) {
- break;
- }
- }
-
- if (n == W + 1) {
- printf("WARNING: correlation function never hit the noise floor.\n");
- tau_failed = true;
- }
-
- if (n < 2) {
- printf("WARNING: correlation function only has one nonnegative term.\n");
- tau_failed = true;
- }
-
- double *conv_Gamma = get_convex_minorant(n, Gammas);
-
- double ttau = - 0.5;
-
- for (uint64_t i = 0; i < n + 1; i++) {
- ttau += conv_Gamma[i];
- }
-
- FILE *autocorr_file = fopen("autocorr.dat", "a");
-
- printf("%g %g\n", Gammas[0], conv_Gamma[0]);
-
- for (count_t i = 0; i < n+1; i++) {
- fprintf(autocorr_file, "%g ", conv_Gamma[i]);
- }
- fprintf(autocorr_file, "\n");
-
- fclose(autocorr_file);
-
- free(Gammas);
- free(autocorr->OO);
- while (autocorr->Op != NULL) {
- stack_pop_d(&(autocorr->Op));
- }
- free(autocorr);
-
- tau = ttau * ac_skip * clust->x / h->nv;
- }
-
- if (tau_failed) {
- tau = 0;
- }
-
- FILE *outfile = fopen("out.m", "a");
-
- fprintf(outfile, "<|N->%" PRIcount ",n->%" PRIcount ",D->%" PRID ",L->%" PRIL ",q->%" PRIq ",T->%.15f,H->{", N, n, D, L, q, T);
- for (q_t i = 0; i < q; i++) {
- fprintf(outfile, "%.15f", H[i]);
- if (i != q-1) {
- fprintf(outfile, ",");
- }
- }
- fprintf(outfile, "},E->%.15f,\\[Delta]E->%.15f,C->%.15f,\\[Delta]C->%.15f,M->{", E->x / h->nv, meas_dx(E) / h->nv, meas_c(E) / h->nv, meas_dc(E) / h->nv);
- for (q_t i = 0; i < q; i++) {
- fprintf(outfile, "%.15f", M[i]->x / h->nv);
- if (i != q-1) {
- fprintf(outfile, ",");
- }
- }
- fprintf(outfile, "},\\[Delta]M->{");
- for (q_t i = 0; i < q; i++) {
- fprintf(outfile, "%.15f", meas_dx(M[i]) / h->nv);
- if (i != q-1) {
- fprintf(outfile, ",");
- }
- }
- fprintf(outfile, "},\\[Chi]->{");
- for (q_t i = 0; i < q; i++) {
- fprintf(outfile, "%.15f", meas_c(M[i]) / h->nv);
- if (i != q-1) {
- fprintf(outfile, ",");
- }
- }
- fprintf(outfile, "},\\[Delta]\\[Chi]->{");
- for (q_t i = 0; i < q; i++) {
- fprintf(outfile, "%.15f", meas_dc(M[i]) / h->nv);
- if (i != q-1) {
- fprintf(outfile, ",");
- }
- }
- fprintf(outfile, "},aM->%.15f,\\[Delta]aM->%.15f,a\\[Chi]->%.15f,\\[Delta]a\\[Chi]->%.15f,Subscript[n,\"clust\"]->%.15f,Subscript[\\[Delta]n,\"clust\"]->%.15f,Subscript[m,\"clust\"]->%.15f,Subscript[\\[Delta]m,\"clust\"]->%.15f,\\[Tau]->%.15f|>\n", aM->x / h->nv, meas_dx(aM) / h->nv, meas_c(aM) / h->nv, meas_dc(aM) / h->nv, clust->x / h->nv, meas_dx(clust) / h->nv, meas_c(clust) / h->nv, meas_dc(clust) / h->nv,tau);
-
- fclose(outfile);
-
- free(E);
- free(clust);
- for (q_t i = 0; i < q; i++) {
- free(M[i]);
- }
- free(M);
- free(H);
- free(s->M);
- free(s->R);
- free(s->spins);
- graph_free(s->g);
- free(s);
- graph_free(h);
- gsl_rng_free(r);
-
- return 0;
-}
-