On May 14, 2009, at 1:37 AM, Cristi Constantin wrote:
> Good day.
> I am trying to obtain MAXIMUM speed for this mappings:
>
> MyString = '\n'.join([ ''.join([j.encode('utf8') for j in i]) for i
> in NdArrayList ])
>
> "NdArrayList" is a list of numpy ndarrays that contain one Unicode
> character and i want to transform it into a string, AS FAST AS
> POSSIBLE.
> For example : NdArrayList can be = [ np.array([u'a', u'\u2588'],
> dtype='<U1'), np.array([u'\u00a9', u'\u00ce', u'\u2022'],
> dtype='<U1') ]
>
> I also want to make MyList = [ ''.join([j.encode('utf8') for j in
> i]) for i in NdArrayList ]. In this case i need a list of united-as-
> string numpy ndarrays.
>
> When i call the codes from Python i get better performance than
> compiling into a Cython function like:
>
> cdef str __Ndarray2String( list TempA ):
> #
> return '\n'.join([ ''.join([j.encode('utf8') for j in i]) for i
> in TempA ])
> #
> def Ndarray2String( v ):
> return __Ndarray2String( v )
>
> Can anyone please sugest a good method?
To go for maximum speed, I would suggest pulling all the data out of
the array first (perhaps using the buffer interface) and using
assignment and/or memcpy to put it into a big string (manually
inserting the newlines). Then call encode to get the whole thing in
utf8.
- Robert
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