comparison src/BTrack.cpp @ 15:2b94d3d2fb9d develop

Reformatted comments, removed the OnsetDetectionFunction constructor with no arguments, removed a number of unused variables and made changes to the python module to fix some casting problems and removed some unused variables there also. Still getting the same results, so no overall changes to the algorithm.

  * You should have received a copy of the GNU General Public License
  * along with this program.  If not, see <http://www.gnu.org/licenses/>.
  */
 //=======================================================================
 
-#include <iostream>
 #include <cmath>
+#include <algorithm>
 #include "BTrack.h"
 #include "samplerate.h"
-using namespace std;
-
-
 
 
 //=======================================================================
 BTrack :: BTrack()
 {	

 	float x_thresh[N];
 	
 	int p_post = 7;
 	int p_pre = 8;
 	
-	t = min(N,p_post);	// what is smaller, p_post of df size. This is to avoid accessing outside of arrays
+	t = std::min(N,p_post);	// what is smaller, p_post of df size. This is to avoid accessing outside of arrays
 	
 	// find threshold for first 't' samples, where a full average cannot be computed yet 
 	for (i = 0;i <= t;i++)
 	{	
-		k = min((i+p_pre),N);
+		k = std::min((i+p_pre),N);
 		x_thresh[i] = mean_array(x,1,k);
 	}
 	// find threshold for bulk of samples across a moving average from [i-p_pre,i+p_post]
 	for (i = t+1;i < N-p_post;i++)
 	{
 		x_thresh[i] = mean_array(x,i-p_pre,i+p_post);
 	}
 	// for last few samples calculate threshold, again, not enough samples to do as above
 	for (i = N-p_post;i < N;i++)
 	{
-		k = max((i-p_post),1);
+		k = std::max((i-p_post),1);
 		x_thresh[i] = mean_array(x,k,N);
 	}
 	
 	// subtract the threshold from the detection function and check that it is not less than 0
 	for (i = 0;i < N;i++)