On Mon, Mar 5, 2012 at 11:52 AM, Benjamin Root <ben.r...@ou.edu> wrote:
> Another issue to watch out for is if the array is empty. Technically
> speaking, that should be True, but some of the solutions offered so far
> would fail in this case.
Good point.
For fun, here's the speed of a simple cython allclose:
I[2] a = np.ones(100000)
I[3] timeit a.min() == a.max()
10000 loops, best of 3: 106 us per loop
I[4] timeit allequal(a)
10000 loops, best of 3: 68.9 us per loop
I[5] a[1] = 9
I[6] timeit a.min() == a.max()
10000 loops, best of 3: 102 us per loop
I[7] timeit allequal(a)
1000000 loops, best of 3: 269 ns per loop
where
@cython.boundscheck(False)
@cython.wraparound(False)
def allequal(np.ndarray[np.float64_t, ndim=1] a):
cdef:
np.float64_t a0
Py_ssize_t i, n=a.size
a0 = a[0]
for i in range(n):
if a[i] != a0:
return False
return True
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