On 11/16/06, Travis Oliphant <[EMAIL PROTECTED]> wrote: > John Hunter wrote: > > >>>>>> "Erin" == Erin Sheldon <[EMAIL PROTECTED]> writes: > >>>>>> > >>>>> > > > > Erin> The question I have been asking myself is "what is the > > Erin> advantage of such an approach?". It would be faster, but by > > > > In the use case that prompted this message, the pull from mysql took > > almost 3 seconds, and the conversion from lists to numpy arrays took > > more that 4 seconds. We have a list of about 500000 2 tuples of > > floats. > > > > Digging in a little bit, we found that numpy is about 3x slower than > > Numeric here > > > > peds-pc311:~> python test.py > > with dtype: 4.25 elapsed seconds > > w/o dtype 5.79 elapsed seconds > > Numeric 1.58 elapsed seconds > > 24.0b2 > > 1.0.1.dev3432 > > > > Hmm... So maybe the question is -- is there some low hanging fruit > > here to get numpy speeds up? > > > > import time > > import numpy > > import numpy.random > > rand = numpy.random.rand > > > > x = [(rand(), rand()) for i in xrange(500000)] > > tnow = time.time() > > y = numpy.array(x, dtype=numpy.float_) > > tdone = time.time() > > print 'with dtype: %1.2f elapsed seconds'%(tdone - tnow) > > > > tnow = time.time() > > y = numpy.array(x) > > tdone = time.time() > > print 'w/o dtype %1.2f elapsed seconds'%(tdone - tnow) > > > > import Numeric > > tnow = time.time() > > y = Numeric.array(x, Numeric.Float) > > tdone = time.time() > > print 'Numeric %1.2f elapsed seconds'%(tdone - tnow) > > > > print Numeric.__version__ > > print numpy.__version__ > > > > > > I just adapted Numarray's version of array (using the fromlist method) > to NumPy. This new change needs some testing as it is called in many, > many ways. But, I think it should be right (all tests of numpy and > scipy pass with it). > With the change I get: > > with dtype: 0.22 elapsed seconds > w/o dtype 5.02 elapsed seconds > Numeric 7.38 elapsed seconds > numarray 0.55 elapsed seconds > 24.2 > 1.0.1.dev3437 > 1.5.1
Hi Travis - That is an impressive speed increase. Why is w/o dtype taking so much longer? Is this just from determining elements sizes and counts? Erin _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
