On 2-Feb-09, at 9:21 AM, Hrvoje Niksic wrote:
>
> It turns out that an even faster method of creating an array is by
> using the fromstring() method. fromstring() requires an actual
> string, not a buffer, so in C++ I created an std::vector<double>
> with a contiguous array of doubles, passed that array to
> PyString_FromStringAndSize, and called array.fromstring with the
> resulting string. Despite all the unnecessary copying, the result
> was much faster than either of the previous versions.
>
>
> Would it be possible for the array module to define a C interface
> for the most frequent operations on array objects, such as appending
> an item, and getting/setting an item? Failing that, could we at
> least make fromstring() accept an arbitrary read buffer, not just an
> actual string?
Do you need to append, or are you just looking to create/manipulate an
array with a bunch of c-float values? I find As{Write/Read}Buffer
sufficient for most of these tasks. I've included some example pyrex
code that populates a new array.array at c speed. (Note that you can
get the size of the resulting c array more easily than you are by
using PyObject_Length). Of course, this still leaves difficult
appending to an already-created array.
def calcW0(W1, colTotal):
""" Calculate a W0 array from a W1 array.
@param W1: array.array of doubles
@param colTotal: value to which each column should sum
@return W0 = [colTotal] * NA - W1
"""
cdef int NA
NA = len(W1)
W0 = array('d', [colTotal]) * NA
cdef double *cW1, *cW0
cdef int i
cdef Py_ssize_t dummy
PyObject_AsReadBuffer(W1, <void**>&cW1, &dummy)
PyObject_AsWriteBuffer(W0, <void**>&cW0, &dummy)
for i from 0 <= i < NA:
cW0[i] = cW0[i] - cW1[i]
return W0
regards,
-Mike
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