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Kirill Smelkov
cython
Commits
06f75b80
Commit
06f75b80
authored
Nov 09, 2015
by
Robert Bradshaw
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Suggest disabling wraparound rather than unsigned indices.
parent
681da667
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docs/src/tutorial/numpy.rst
docs/src/tutorial/numpy.rst
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docs/src/tutorial/numpy.rst
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06f75b80
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@@ -227,7 +227,8 @@ The array lookups are still slowed down by two factors:
...
cimport cython
@cython.boundscheck(False) # turn of bounds-checking for entire function
@cython.boundscheck(False) # turn off bounds-checking for entire function
@cython.wraparound(False) # turn off negative index wrapping for entire function
def naive_convolve(np.ndarray[DTYPE_t, ndim=2] f, np.ndarray[DTYPE_t, ndim=2] g):
...
...
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@@ -237,32 +238,9 @@ and in the worst case corrupt data). It is possible to switch bounds-checking
mode in many ways, see :ref:`compiler-directives` for more
information.
Negative indices are dealt with by ensuring Cython that the indices will be
positive, by casting the variables to unsigned integer types (if you do have
negative values, then this casting will create a very large positive value
instead and you will attempt to access out-of-bounds values). Casting is done
with a special ``<>``-syntax. The code below is changed to use either
unsigned ints or casting as appropriate::
...
cdef int s, t # changed
cdef unsigned int x, y, v, w # changed
cdef int s_from, s_to, t_from, t_to
cdef DTYPE_t value
for x in range(xmax):
for y in range(ymax):
s_from = max(smid - x, -smid)
s_to = min((xmax - x) - smid, smid + 1)
t_from = max(tmid - y, -tmid)
t_to = min((ymax - y) - tmid, tmid + 1)
value = 0
for s in range(s_from, s_to):
for t in range(t_from, t_to):
v = <unsigned int>(x - smid + s) # changed
w = <unsigned int>(y - tmid + t) # changed
value += g[<unsigned int>(smid - s), <unsigned int>(tmid - t)] * f[v, w] # changed
h[x, y] = value
...
Also, we've disabled the check to wrap negative indices (e.g. g[-1] giving
the last value). As with disabling bounds checking, bad things will happen
if we try to actually use negative indices with this disabled.
The function call overhead now starts to play a role, so we compare the latter
two examples with larger N:
...
...
@@ -310,4 +288,3 @@ There is some speed penalty to this though (as one makes more assumptions
compile-time if the type is set to :obj:`np.ndarray`, specifically it is
assumed that the data is stored in pure strided mode and not in indirect
mode).
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