Hello everyone, I'm trying to determine the 2 greatest values, in a 3-d array, along one axis.
Here is an approach: # ------------------------------------------------------ # procedure to determine greatest 2 values for 3rd dimension of 3-d array ... import numpy, numpy.ma xcnt, ycnt, zcnt = 2,3,4 # actual case is (1024, 1024, 8) p0 = numpy.empty ((xcnt,ycnt,zcnt)) for z in range (zcnt) : p0[:,:,z] = z*z zaxis = 2 # max values to be determined for 3rd axis p0max = numpy.max (p0, axis=zaxis) # max values for zaxis maxindices = numpy.argmax (p0, axis=zaxis) # indices of max values p1 = p0.copy() # work array to scan for 2nd highest values j, i = numpy.meshgrid (numpy.arange (ycnt), numpy.arange (xcnt)) p1[i,j,maxindices] = numpy.NaN # flag all max values p1 = numpy.ma.masked_where (numpy.isnan (p1), p1) # hide all max values p1max = numpy.max (p1, axis=zaxis) # 2nd highest values for zaxis # additional code to analyze p0max and p1max goes here # ------------------------------------------------------ I would appreciate feedback on a simpler approach -- e.g., one that does not require masked arrays and or use of magic values like NaN. Thanks, -- jv _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
