beginner with Python here. So I\'m having trouble trying to calculate the resulting binary pairwise hammington distance matrix between the rows of an input matrix using only th
For reasons I do not understand this
(2 * np.inner(a-0.5, 0.5-a) + a.shape[1] / 2)
appears to be much faster than @Psidom's for larger arrays:
a = np.random.randint(0,2,(100,1000))
timeit(lambda: (a[:, None, :] != a).sum(2), number=100)
# 2.297890231013298
timeit(lambda: (2 * np.inner(a-0.5, 0.5-a) + a.shape[1] / 2), number=100)
# 0.10616962902713567
Psidom's is a bit faster for the very small example:
a
# array([[1, 0, 0, 1, 1, 0],
# [1, 0, 0, 0, 0, 0],
# [1, 1, 1, 1, 0, 0]])
timeit(lambda: (a[:, None, :] != a).sum(2), number=100)
# 0.0004370050155557692
timeit(lambda: (2 * np.inner(a-0.5, 0.5-a) + a.shape[1] / 2), number=100)
# 0.00068191799800843
Update
Part of the reason appears to be floats being faster than other dtypes:
timeit(lambda: (0.5 * np.inner(2*a-1, 1-2*a) + a.shape[1] / 2), number=100)
# 0.7315902590053156
timeit(lambda: (0.5 * np.inner(2.0*a-1, 1-2.0*a) + a.shape[1] / 2), number=100)
# 0.12021801102673635