[Numpy-discussion] numpy vs numeric benchmarks
RayS
rays at blue-cove.com
Fri Jun 2 09:27:27 CDT 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
# array creation
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)
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