 		}
 		out_fit_test[1] = shm[0] / double(NROWS_TEST);
 	}
-
-	/*
-	if (tig == 0) {
-		double d = 0;
-		double a = *ls_a;
-		double b = *ls_b;
-		for (int i = 0; i < NROWS_TEST; i++) {
-			double yy = getDataset(NUM_VARIABLE_SYMBOLS, i+NROWS_TRAIN, set);
-			d += ERROR_FUNC(yy, a + b * sem_test[i]);
-		}
-		out_fit_test[1] = d / double(NROWS_TEST);
-	}
-	*/
-}
-
-extern "C" __global__
-void sem_fitness(double *set, double *sem_train, double *sem_test, double *out_fit) {
-	int tig = blockIdx.x * blockDim.x + threadIdx.x;
-	if (tig == 0) {
-		double d = 0;
-		for (int i = 0; i < NROWS_TRAIN; i++) {
-			double yy = getDataset(NUM_VARIABLE_SYMBOLS, i, set);
-			d += ERROR_FUNC(yy, sem_train[i]);
-		}
-		out_fit[0] = d / double(NROWS_TRAIN);
-	} else if (tig == 1) {
-		double d = 0;
-		for (int i = 0; i < NROWS_TEST; i++) {
-			double yy = getDataset(NUM_VARIABLE_SYMBOLS, i+NROWS_TRAIN, set);
-			d += ERROR_FUNC(yy, sem_test[i]);
-		}
-		out_fit[1] = d / double(NROWS_TEST);
-	}
 }
 
 extern "C" __global__

	if (i < NROWS_TOT) {
		double sem_val = eval_arrays(sym, set, tree, 0, i);
		out_sem_tot[i] = sem_val;
		/*
		if (i < NROWS_TRAIN)
			out_sem_train[i] = sem_val;
		else
			out_sem_test[i-NROWS_TRAIN] = sem_val;
		*/
	}
}


extern "C" __global__
void test_kernel(double *out_sem_train, double *out_sem_test) {
	int tig = blockIdx.x * blockDim.x + threadIdx.x;
	if (tig < NROWS_TOT) {
		if (tig < NROWS_TRAIN)
			out_sem_train[tig] = tig;
		else
			out_sem_test[tig-NROWS_TRAIN] = tig;
	}
}


		}
		out_fit_train[0] = shm[0] / double(NROWS_TRAIN);
	}
}

extern "C" __global__
