Hello, What is the fastest way of applying a function on a list of 2D points? More specifically, I have a list of 2D points, and some do not meet some criteria and must be rejected. Even more specifically, the filter only lets through points whose x coordinate satisfies some condition, _and_ whose y coordinates satisfies another condition (maybe is there room for optimization, here?).
Currently, I use points = numpy.apply_along_axis(filter, axis = 1, arr = points) but this creates a bottleneck in my program (array arr may contains 1 million points, for instance). Is there anything that could be faster? Any suggestion would be much appreciated! EOL _______________________________________________ Numpy-discussion mailing list [email protected] http://projects.scipy.org/mailman/listinfo/numpy-discussion
