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python Programming Glossary: np.linalg.normSpeeding up a closest point on a hyperbolic paraboloid algorithm http://stackoverflow.com/questions/18858448/speeding-up-a-closest-point-on-a-hyperbolic-paraboloid-algorithm the results ''' # Check if c is same as a or b ac c a AC np.linalg.norm ac if AC 0. return c 0. 0. bc c b BC np.linalg.norm bc if BC.. c a AC np.linalg.norm ac if AC 0. return c 0. 0. bc c b BC np.linalg.norm bc if BC 0. return c 0. 1. # See if segment length is 0 ab b.. 0. return c 0. 1. # See if segment length is 0 ab b a AB np.linalg.norm ab if AB 0. return a 0. 0. # Normalize segment and do edge tests..
How to apply numpy.linalg.norm to each row of a matrix? http://stackoverflow.com/questions/7741878/how-to-apply-numpy-linalg-norm-to-each-row-of-a-matrix to find a quicker way Or is it possible to apply np.linalg.norm to each row of a matrix python numpy share improve this question.. perhaps not as convenient In 48 timeit np.apply_along_axis np.linalg.norm 1 x 1000 loops best of 3 208 us per loop In 49 timeit np.sum.. speedups In 55 timeit np.apply_along_axis lambda row np.linalg.norm row ord 1 1 x 1000 loops best of 3 203 us per loop In 54 timeit..
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