El dc 02 de 11 del 2005 a les 17:16 -0500, en/na Todd Miller va escriure:
I added support for the newcore "array interface" to the numarray C-API and this exception is now gone. The fix/enhancement is checked into CVS. Kick it around some...
Yes. This issue has been solved:
numarray.__version__ '1.4.2' Numeric.__version__ '24.0' num=Numeric.zeros((3,),'f') na=numarray.ones((3,),'f') na[...] = num na array([ 0., 0., 0.], type=Float32)
Now, I've taken the opportunity and tested the Numeric<-->numarray conversion again:
t1_1=timeit.Timer("num=Numeric.array(na,copy=1)","import Numeric;import numarray; na=numarray.arange(10)") t1_1.repeat(3,10000) [0.25493311882019043, 0.25352001190185547, 0.25211095809936523]
and this figures compared with numarray 1.4.1:
t1.repeat(3,10000) [0.59375977516174316, 0.57908082008361816, 0.56574010848999023]
shows that you have accelerated the conversion numarray-->Numeric more than 2x. Now, the Numeric-->numarray:
t3_1=timeit.Timer("na=numarray.array(num,copy=1)","import Numeric;import numarray; num=Numeric.arange(10)") t3_1.repeat(3,10000) [0.40311408042907715, 0.40207314491271973, 0.39954400062561035]
while the 1.4.1 performance was:
t3.repeat(3,10000) [1.3475611209869385, 1.3277668952941895, 1.3417830467224121]
which is a factor 3x of improvement, and almost the same than using the buffer interface. Very nice job, Todd! Now, let's test the conversion for large objects, with data copy and without data copy. For numarray-->Numeric:
t2=timeit.Timer("num=Numeric.array(na,copy=0)","import Numeric;import numarray; na=numarray.arange(100000)") t2.repeat(3,100) [0.0025169849395751953, 0.0025219917297363281, 0.0024950504302978516] t2_copy=timeit.Timer("num=Numeric.array(na,copy=1)","import Numeric;import numarray; na=numarray.arange(100000)") t2_copy.repeat(3,100) [0.50105500221252441, 0.49400091171264648, 0.49266600608825684]
So it seems like if the data copy is taking place. For Numeric-->numarray:
t4=timeit.Timer("na=numarray.array(num,copy=0)","import Numeric;import numarray; num=Numeric.arange(100000)") t4.repeat(3,100) [0.0054900646209716797, 0.0044760704040527344, 0.0048201084136962891] t4_copy=timeit.Timer("na=numarray.array(num,copy=1)","import Numeric;importnumarray; num=Numeric.arange(100000)") t4_copy.repeat(3,100) [0.0063569545745849609, 0.004302978515625, 0.0042738914489746094]
Ooops! the times for conversion with copy and without copy are more or less the same. Perhaps the copy is not done? It seems so:
num=Numeric.arange(10) na=numarray.array(num,copy=0) na_copy=numarray.array(num,copy=1) na.info() ... data pointer: 0x08312280 (DEBUG ONLY) na_copy.info() ... data pointer: 0x08312280 (DEBUG ONLY)
i.e. the same data pointer. So it seems that the Numeric-->numarray is not copying the data even in the case that we are asking to do that. Other minor things (maybe this is just because you are in the middle of refactoring):
na._data array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
while I would expect:
na._data <memory at 0x081e3618 with size:0x00000028 held by object 0x401f06a0 aliasing object 0x00000000>
Also:
na Traceback (most recent call last): File "<stdin>", line 1, in ? File "/usr/lib/python2.4/site-packages/numarray/numarraycore.py", line 930, in __repr__ return array_repr(self) File "/usr/lib/python2.4/site-packages/numarray/numarraycore.py", line 1660, in array_repr lst = arrayprint.array2string( File "/usr/lib/python2.4/site-packages/numarray/arrayprint.py", line 188, in array2string separator, prefix) File "/usr/lib/python2.4/site-packages/numarray/arrayprint.py", line 140, in _array2string data = _gen.ravel(a) File "/usr/lib/python2.4/site-packages/numarray/numarraycore.py", line 918, in copy c = _gen.NDArray.copy(self) File "/usr/lib/python2.4/site-packages/numarray/generic.py", line 724, in copy arr._itemsize) TypeError: NA_maybeLongsFromIntTuple: must be a sequence of integers.
Cheers, --
0,0< Francesc Altet http://www.carabos.com/ V V Cárabos Coop. V. Enjoy Data "-"