Wes McKinney wrote:
> This still doesn't explain why the buffer interface was slow.
I finally remembered to look at this; there seems to be a problem in
your code:
> def reindexObject(ndarray[object, ndim=1] index,
> ndarray[object, ndim=1] arr,
> dict idxMap):
Wes McKinney wrote:
>
> The general problem here is an indexed array (by dates or strings, for
> example), that you want to conform to a new index. The arrays most of
> the time contain floats but occasionally PyObjects. For some reason
> the access and assignment is slow (this function can be f
I actually got it to work-- the function prototype in the pxi file was
wrong, needed to be:
int PyArray_SETITEM(object obj, void* itemptr, object item)
This still doesn't explain why the buffer interface was slow.
The general problem here is an indexed array (by dates or strings, for
example), t
Wes McKinney wrote:
> I am writing some Cython code and have noted that the buffer interface
> offers very little speedup for PyObject arrays. In trying to rewrite the
> same code using the C API in Cython, I find I can't get PyArray_SETITEM to
> work, in a call like:
>
> PyArray_SETITEM(result, i
Hi Wes,
I do not profess to be an expert, but I have been off loading a fair number
of loops to C from Python code and achieved significant improvements most
have been of the following form (which I have found to be the fastest):
size = *incomingArrayObj->dimensions;
r_dptr = PyArray_DATA(result
Hello,
I am writing some Cython code and have noted that the buffer interface
offers very little speedup for PyObject arrays. In trying to rewrite the
same code using the C API in Cython, I find I can't get PyArray_SETITEM to
work, in a call like:
PyArray_SETITEM(result, iterresult.dataptr, obj)
