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-rw-r--r--src/wolff.cpp137
-rw-r--r--src/wolff_dgm.c247
-rw-r--r--src/wolff_vector.c377
3 files changed, 137 insertions, 624 deletions
diff --git a/src/wolff.cpp b/src/wolff.cpp
new file mode 100644
index 0000000..85df357
--- /dev/null
+++ b/src/wolff.cpp
@@ -0,0 +1,137 @@
+
+#include <time.h>
+#include <getopt.h>
+
+#include <cluster.h>
+
+double H_vector(vector_t <2, double> v1, double *H) {
+ vector_t <2, double> H_vec;
+ H_vec.x = H;
+ return dot <2, double> (v1, H_vec);
+}
+
+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);
+ }
+ }
+
+ state_t <orthogonal_t <2, double>, vector_t <2, double>> s(D, L, T, dot <2, double>, std::bind(H_vector, std::placeholders::_1, 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, \"D\" -> %" PRID ", \"L\" -> %" PRIL ", \"NV\" -> %" PRIv ", \"NE\" -> %" PRIv ", \"T\" -> %.15f, \"H\" -> {", timestamp, D, L, s.nv, s.ne, 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);
+
+ char *filename_M = (char *)malloc(255 * sizeof(char));
+ char *filename_E = (char *)malloc(255 * sizeof(char));
+ char *filename_S = (char *)malloc(255 * sizeof(char));
+
+ sprintf(filename_M, "wolff_%lu_M.dat", timestamp);
+ sprintf(filename_E, "wolff_%lu_E.dat", timestamp);
+ sprintf(filename_S, "wolff_%lu_S.dat", timestamp);
+
+ FILE *outfile_M = fopen(filename_M, "wb");
+ FILE *outfile_E = fopen(filename_E, "wb");
+ FILE *outfile_S = fopen(filename_S, "wb");
+
+ free(filename_M);
+ free(filename_E);
+ 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, M_0 = %.2f, S = %" PRIv "\n", steps, N, s.E, s.M.x[0], cluster_size);
+
+ v_t v0 = gsl_rng_uniform_int(r, s.nv);
+
+ orthogonal_t <2, double> step;
+ generate_rotation<2>(r, &step);
+
+ printf("(%g %g) . (%g %g) = %g or %g, H = %g\n\n", s.spins[0].x[0], s.spins[0].x[1], s.spins[1].x[0], s.spins[1].x[1], dot(s.spins[0], s.spins[1]), s.J(s.spins[0],s.spins[1]), s.H(s.spins[0]));
+
+ getchar();
+ cluster_size = flip_cluster <orthogonal_t <2, double>, vector_t <2, double>> (&s, v0, step, r);
+
+ free_spin(step);
+
+ fwrite(&(s.E), sizeof(double), 1, outfile_E);
+ fwrite(s.M.x, sizeof(double), 2, 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, M_0 = %.2f, S = %" PRIv "\n", N, N, s.E, s.M.x[0], cluster_size);
+
+ fclose(outfile_M);
+ fclose(outfile_E);
+ fclose(outfile_S);
+
+ gsl_rng_free(r);
+
+ free(H);
+
+ return 0;
+}
+
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_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;
-}
-