[Numpy-discussion] numpy vs numeric benchmarks (original) (raw)

RayS rays at blue-cove.com
Fri Jun 2 10:27:27 EDT 2006

favorable numpy creates arrays much faster, fft seems a tad faster a useful metric, I think, for O-scope and ADC apps

I get 0.0039054614015815738 0.0019759541205486885

0.023268623246481726 0.0023570392204637913 from the below on a PIII 600...

from time import * n=4096 r = range(n)

#numpy import numpy arr = numpy.array

array creation

t0 = clock() for i in r: a = arr(r)

(clock()-t0)/float(n) #fft of n fftn = numpy.fft t0 = clock() for i in r: f = fftn(a)

(clock()-t0)/float(n)

#Numeric import Numeric arr = Numeric.array

t0 = clock() for i in r: a = arr(r)

(clock()-t0)/float(n) #fft of n from FFT import * t0 = clock() for i in r: f = fft(a)

(clock()-t0)/float(n)