diff --git a/tests/testRandom.c b/tests/testRandom.c index 4e1b714586aa12f2d28500b55d10bbd63a0d21bc..417d8a3dea2d8daa18e45f9f6b2b22c2e38cc907 100644 --- a/tests/testRandom.c +++ b/tests/testRandom.c @@ -41,8 +41,6 @@ int main(int argc, char* argv[]) { message("Seed = %d", seed); srand(seed); - - /* Time-step size */ const int time_bin = 29; @@ -54,11 +52,6 @@ int main(int argc, char* argv[]) { const long long idoffset = id + 2; message("Testing id=%lld time_bin=%d", id, time_bin); - //char buffer[32]; - //snprintf(buffer, sizeof(char)*32, "fileII%i.txt", i); - - //FILE *fp; - //fp = fopen(buffer,"w"); double total = 0., total2 = 0.; int count = 0; @@ -71,8 +64,6 @@ int main(int argc, char* argv[]) { double pearsonIDs = 0.; double totalID = 0.; double total2ID = 0.; - - //message("Max nr timesteps = %lld",max_nr_timesteps); /* Check that the numbers are uniform over the full-range of useful * time-steps */ @@ -90,8 +81,6 @@ int main(int argc, char* argv[]) { total += r; total2 += r * r; count++; - //const unsigned int test = 127LL*(ti_current - 1LL) + 124429LL; - //fprintf(fp, "%f %lld %lld\n", r, (test) % 1514917LL, ti_current ); /* For the pearson correlation of time i and i-1 */ sum_previous_current += r * previous; @@ -101,17 +90,14 @@ int main(int argc, char* argv[]) { pearsonIDs += r * r_2ndid; totalID += r_2ndid; total2ID += r_2ndid * r_2ndid; - } - //fclose(fp); const double mean = total / (double)count; const double var = total2 / (double)count - mean * mean; /* Pearson correlation calculation for different times */ const double mean_xy = sum_previous_current / ( (double)count -1.f); const double correlation = (mean_xy-mean*mean)/var; - message("Correlation = %f", correlation); /* Pearson correlation for different IDs */ const double meanID = totalID / (double)count; @@ -120,9 +106,6 @@ int main(int argc, char* argv[]) { const double meanID_xy = pearsonIDs / (double)count; const double correlationID = (meanID_xy - mean*meanID) / pow(var * varID, .5f); - message("Correlation ID = %f", correlationID); - - /* Verify that the mean and variance match the expected values for a uniform * distribution */ if ((fabs(mean - 0.5) / 0.5 > 2e-4) ||