void test_basic(const size_t n, const double data[], const double tol) { gsl_rstat_workspace *rstat_workspace_p = gsl_rstat_alloc(); const double expected_mean = gsl_stats_mean(data, 1, n); const double expected_var = gsl_stats_variance(data, 1, n); const double expected_sd = gsl_stats_sd(data, 1, n); const double expected_sd_mean = expected_sd / sqrt((double) n); const double expected_skew = gsl_stats_skew(data, 1, n); const double expected_kurtosis = gsl_stats_kurtosis(data, 1, n); double expected_rms = 0.0; double mean, var, sd, sd_mean, rms, skew, kurtosis; size_t i, num; int status; /* compute expected rms */ for (i = 0; i < n; ++i) expected_rms += data[i] * data[i]; expected_rms = sqrt(expected_rms / n); /* add data to rstat workspace */ for (i = 0; i < n; ++i) gsl_rstat_add(data[i], rstat_workspace_p); mean = gsl_rstat_mean(rstat_workspace_p); var = gsl_rstat_variance(rstat_workspace_p); sd = gsl_rstat_sd(rstat_workspace_p); sd_mean = gsl_rstat_sd_mean(rstat_workspace_p); rms = gsl_rstat_rms(rstat_workspace_p); skew = gsl_rstat_skew(rstat_workspace_p); kurtosis = gsl_rstat_kurtosis(rstat_workspace_p); num = gsl_rstat_n(rstat_workspace_p); gsl_test_int(num, n, "n n=%zu" , n); gsl_test_rel(mean, expected_mean, tol, "mean n=%zu", n); gsl_test_rel(var, expected_var, tol, "variance n=%zu", n); gsl_test_rel(sd, expected_sd, tol, "stddev n=%zu", n); gsl_test_rel(sd_mean, expected_sd_mean, tol, "stddev_mean n=%zu", n); gsl_test_rel(rms, expected_rms, tol, "rms n=%zu", n); gsl_test_rel(skew, expected_skew, tol, "skew n=%zu", n); gsl_test_rel(kurtosis, expected_kurtosis, tol, "kurtosis n=%zu", n); status = gsl_rstat_reset(rstat_workspace_p); gsl_test_int(status, GSL_SUCCESS, "rstat returned success"); num = gsl_rstat_n(rstat_workspace_p); gsl_test_int(num, 0, "n n=%zu" , n); gsl_rstat_free(rstat_workspace_p); }
int bin2d_add_element_corr(double x, double y, double data1, double data2, bin2d_workspace *w) { int s = 0; size_t binx, biny; double *z1, *z2; size_t n; if (x < w->xmin || x > w->xmax) { fprintf(stderr, "bin_add_element_corr: error: x outside allowed range: %f\n", x); return -1; } else if (y < w->ymin || y > w->ymax) { fprintf(stderr, "bin_add_element_corr: error: y outside allowed range: %f\n", y); return -1; } binx = bin2d_findbin(x, w->xmin, w->xmax, w->nx); biny = bin2d_findbin(y, w->ymin, w->ymax, w->ny); z1 = w->z1[BIN2D_IDX(binx, biny, w)]; z2 = w->z2[BIN2D_IDX(binx, biny, w)]; n = w->n[BIN2D_IDX(binx, biny, w)]; if (n >= MAX_DATA_PER_BIN) { fprintf(stderr, "bin_add_element_corr: MAX_DATA_PER_BIN too small\n"); return -1; } z1[n] = data1; z2[n] = data2; w->n[BIN2D_IDX(binx, biny, w)] = ++n; /* to update 'n' count */ gsl_rstat_add(data1, w->bins[BIN2D_IDX(binx, biny, w)]); return s; } /* bin2d_add_element() */
void test_basic(const size_t n, const double data[], const double tol) { gsl_rstat_workspace *rstat_workspace_p = gsl_rstat_alloc(); const double expected_mean = gsl_stats_mean(data, 1, n); const double expected_var = gsl_stats_variance(data, 1, n); const double expected_sd = gsl_stats_sd(data, 1, n); const double expected_skew = gsl_stats_skew(data, 1, n); const double expected_kurtosis = gsl_stats_kurtosis(data, 1, n); double expected_rms = 0.0; double mean, var, sd, rms, skew, kurtosis; size_t i; /* compute expected rms */ for (i = 0; i < n; ++i) expected_rms += data[i] * data[i]; expected_rms = sqrt(expected_rms / n); /* add data to rstat workspace */ for (i = 0; i < n; ++i) gsl_rstat_add(data[i], rstat_workspace_p); mean = gsl_rstat_mean(rstat_workspace_p); var = gsl_rstat_variance(rstat_workspace_p); sd = gsl_rstat_sd(rstat_workspace_p); rms = gsl_rstat_rms(rstat_workspace_p); skew = gsl_rstat_skew(rstat_workspace_p); kurtosis = gsl_rstat_kurtosis(rstat_workspace_p); gsl_test_rel(mean, expected_mean, tol, "mean n=%zu", n); gsl_test_rel(var, expected_var, tol, "variance n=%zu", n); gsl_test_rel(sd, expected_sd, tol, "stddev n=%zu", n); gsl_test_rel(rms, expected_rms, tol, "rms n=%zu", n); gsl_test_rel(skew, expected_skew, tol, "skew n=%zu", n); gsl_test_rel(kurtosis, expected_kurtosis, tol, "kurtosis n=%zu", n); gsl_rstat_free(rstat_workspace_p); }
int bin2d_add_element(double x, double y, double data, bin2d_workspace *w) { int s = 0; size_t binx, biny; if (x < w->xmin || x > w->xmax) { fprintf(stderr, "bin_add_element: error: x outside allowed range: %f\n", x); return -1; } else if (y < w->ymin || y > w->ymax) { fprintf(stderr, "bin_add_element: error: y outside allowed range: %f\n", y); return -1; } binx = bin2d_findbin(x, w->xmin, w->xmax, w->nx); biny = bin2d_findbin(y, w->ymin, w->ymax, w->ny); gsl_rstat_add(data, w->bins[BIN2D_IDX(binx, biny, w)]); return s; } /* bin2d_add_element() */
int main() { gsl_rng *r = gsl_rng_alloc(gsl_rng_default); const double tol1 = 1.0e-8; const double tol2 = 1.0e-3; gsl_ieee_env_setup(); { const size_t N = 2000000; double *data = random_data(N, r); double data2[] = { 4.0, 7.0, 13.0, 16.0 }; size_t i; test_basic(2, data, tol1); test_basic(100, data, tol1); test_basic(1000, data, tol1); test_basic(10000, data, tol1); test_basic(50000, data, tol1); test_basic(80000, data, tol1); test_basic(1500000, data, tol1); test_basic(2000000, data, tol1); for (i = 0; i < 4; ++i) data2[i] += 1.0e9; test_basic(4, data2, tol1); free(data); } { /* dataset from Jain and Chlamtac paper */ const size_t n_jain = 20; const double data_jain[] = { 0.02, 0.15, 0.74, 3.39, 0.83, 22.37, 10.15, 15.43, 38.62, 15.92, 34.60, 10.28, 1.47, 0.40, 0.05, 11.39, 0.27, 0.42, 0.09, 11.37 }; double expected_jain = 4.44063435326; test_quantile(0.5, data_jain, n_jain, expected_jain, tol1, "jain"); } { size_t n = 1000000; double *data = malloc(n * sizeof(double)); double *sorted_data = malloc(n * sizeof(double)); gsl_rstat_workspace *rstat_workspace_p = gsl_rstat_alloc(); double p; size_t i; for (i = 0; i < n; ++i) { data[i] = gsl_ran_gaussian_tail(r, 1.3, 1.0); gsl_rstat_add(data[i], rstat_workspace_p); } memcpy(sorted_data, data, n * sizeof(double)); gsl_sort(sorted_data, 1, n); /* test quantile calculation */ for (p = 0.1; p <= 0.9; p += 0.1) { double expected = gsl_stats_quantile_from_sorted_data(sorted_data, 1, n, p); test_quantile(p, data, n, expected, tol2, "gauss"); } /* test mean, variance */ { const double expected_mean = gsl_stats_mean(data, 1, n); const double expected_var = gsl_stats_variance(data, 1, n); const double expected_sd = gsl_stats_sd(data, 1, n); const double expected_skew = gsl_stats_skew(data, 1, n); const double expected_kurtosis = gsl_stats_kurtosis(data, 1, n); const double expected_median = gsl_stats_quantile_from_sorted_data(sorted_data, 1, n, 0.5); const double mean = gsl_rstat_mean(rstat_workspace_p); const double var = gsl_rstat_variance(rstat_workspace_p); const double sd = gsl_rstat_sd(rstat_workspace_p); const double skew = gsl_rstat_skew(rstat_workspace_p); const double kurtosis = gsl_rstat_kurtosis(rstat_workspace_p); const double median = gsl_rstat_median(rstat_workspace_p); gsl_test_rel(mean, expected_mean, tol1, "mean"); gsl_test_rel(var, expected_var, tol1, "variance"); gsl_test_rel(sd, expected_sd, tol1, "stddev"); gsl_test_rel(skew, expected_skew, tol1, "skew"); gsl_test_rel(kurtosis, expected_kurtosis, tol1, "kurtosis"); gsl_test_abs(median, expected_median, tol2, "median"); } free(data); free(sorted_data); gsl_rstat_free(rstat_workspace_p); } gsl_rng_free(r); exit (gsl_test_summary()); }