[Numpy-discussion] How to copy data from a C array to a numpy array efficiently?

Dag Sverre Seljebotn d.s.seljebotn@astro.uio...
Sun Oct 7 01:48:10 CDT 2012


On 10/07/2012 08:41 AM, Jianbao Tao wrote:
> Hi,
>
> I am developing a Python wrapper of the NASA CDF C library in Cython. I
> have got a working version of it now, but it is slower than the
> counterpart in IDL. For loading the same file, mine takes about 400 ms,
> whereas the IDL version takes about 290 ms.
>
> The main overhead in my code is caused by a for-loop of
> element-by-element copying. Here is the relevant code in cython:
> #-------------------------------- code
> -----------------------------------------------------
>      #-- double
>          realData = numpy.zeros(lenData, np_dtype)
>
>          dblEntry = <double *>malloc(lenData * sizeof(double))
>          status = CDFlib(
>                         SELECT_, zVAR_RECCOUNT_, numRecs,
>                         NULL_)
>          status = CDFlib(
>                         GET_, zVAR_HYPERDATA_, dblEntry,
>                         NULL_)
> for ii in range(lenData):
>              realData[ii] = dblEntry[ii]
>          realData.shape = np_shape
>          free(dblEntry)

You don't say what np_dtype is here (or the Cython variable declaration 
for it).

Assuming it is np.double and "cdef np.ndarray[double] realData", what 
you should do is simple pass the buffer of realData to the CDFlib function:

status = CDFlib(GET_, ..., &realData[0], NULL)

Then there's no need for copying.

This is really what you should do anyway, then if the dtype is different 
leave it to the "astype" function (but then comparisons with IDL should 
take into account the dtype conversion).

Dag Sverre


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