Hi All, I am tryin to "vectorize" 3 nested for loops but I am not having much success. Here is the code I use: import numpy import numpy.ma as masked grid = numpy.zeros((nx, ny), dtype=numpy.float32) xOut = numpy.zeros((nx, ny), dtype=numpy.float32) yOut = numpy.zeros((nx, ny), dtype=numpy.float32) z = GetCentroids() # Some vector z values prop = GetValue() # Some other vector values NaN = numpy.NaN for I in xrange(1, nx+1): for J in xrange(1, ny+1): theSum = [] for K in xrange(1, nz+1): cellPos = I-1 + nx*(J-1) + nx*ny*(K-1) centroid = z[cellPos] if low <= centroid <= high and actnum[cellPos] > 0: theSum.append(prop[cellPos]) if theSum: grid[I-1, J-1] = sum(theSum)/len(theSum) else: grid[I-1, J-1] = NaN xOut[I-1, J-1], yOut[I-1, J-1] = x[cellPos], y[cellPos] grid = masked.masked_where(numpy.isnan(grid), grid) Some explanation: 1) "z" is a vector of nx*ny*nz components, where nx = 100, ny = 73, nz = 23, which represents 3D hexahedron cell centroids; 2) "prop" is a vector like z, with the same shape, with some floating point values in it; 3) "actnum" is a vector of integers (0 or 1) with the same shape as z, and indicates if a cell should be considered in the loop or not; 4) low and high are 2 floating point values with low < high: if the cell centroid fall between low and high and the cell is active (as stated in "actnum"), then I take the value of "prop" in that cell and I append it to the "theSum" list; 5) At the end of the K loop, I just take an arithmetic mean of the values in "theSum" list. I think I may be able to figure out how to vectorize the part regarding the "grid" variable, but I have no idea on what to do for the xOut and yOut variables, and I need them because I use them in a later call to matplotlib.contourf. If you could drop some hint on how to proceed, ot would be very appreciated. Thank you for your suggestions. Andrea. "Imagination Is The Only Weapon In The War Against Reality." http://xoomer.alice.it/infinity77/