Timer unit: 6.98413e-08 s

Total time: 0.186524 s
File: avgcol2.py
Function: test_v5 at line 112

Line #      Hits         Time  Per Hit   % Time  Line Contents
==============================================================
   112                                           @profile
   113                                           def test_v5(frame, labels, stats):
   114         4        369.0     92.2      0.0      flat_labels = labels.ravel()
   115         4        154.0     38.5      0.0      c = stats[...,-1]
   116         4      99829.0  24957.2      3.7      flat_green = frame[...,1].ravel()
   117         4    1244370.0 311092.5     46.6      cn1 = np.bincount(flat_labels, flat_green)
   118         4     104271.0  26067.8      3.9      flat_red = frame[...,2].ravel()
   119         4    1219137.0 304784.2     45.6      cn2 = np.bincount(flat_labels, flat_red)
   120         4       2227.0    556.8      0.1      measurements = (cn2-cn1)/c
   121         4        327.0     81.8      0.0      return measurements[1:]

Total time: 0.230549 s
File: avgcol2.py
Function: test_v9 at line 189

Line #      Hits         Time  Per Hit   % Time  Line Contents
==============================================================
   189                                           @profile
   190                                           def test_v9(frame, labels, stats):
   191                                               global L
   192         4     995086.0 248771.5     30.1      data = frame[...,1:].ravel()
   193         4    2303369.0 575842.2     69.8      p = np.bincount(L,data)
   194         4       2581.0    645.2      0.1      return (p[res+1:]-p[1:res])/stats[1:,-1]

Total time: 0.234597 s
File: avgcol2.py
Function: test_v10 at line 198

Line #      Hits         Time  Per Hit   % Time  Line Contents
==============================================================
   198                                           @profile
   199                                           def test_v10(frame, labels, stats):
   200                                               global L2
   201         4        302.0     75.5      0.0      data = frame.ravel()
   202         4    3356064.0 839016.0     99.9      p = np.bincount(L2,data)
   203         4       2643.0    660.8      0.1      return (p[res*2+1:]-p[res+1:res*2])/stats[1:,-1]