Hi, All,
I am using ipython with --pylab flag. ipython loads the numpy into the
workspace, so I do not know abs is from python or numpy. The weird thing is if
I execute the code line by line, I do not have any speed problem. But when I
combine them together into one command, it slowdonws the computer significantly.
>From my understanding, using the modulename.functionname will slow down the
>python performance. For a big simulation, it may not be a good idear.
Are there any suggestion for the matlab uses who want to use numpy/scipy how to
setup their working environment?
Thanks
Frank> Date: Wed, 24 Sep 2008 15:37:03 -0700> From: [EMAIL PROTECTED]> To:
numpy-discussion@scipy.org> Subject: Re: [Numpy-discussion] performance of the
numpy> > Nadav Horesh wrote:> > You should use absolute (a ufunc) and not abs
(internal python function):> > > >>>> plot(absolute(fft(b)))> > another reason
why "import *" is a bad idea:> > import numpy as np> import pylab as plot
#(what is the convention for this now?)> > pylab.plot(np.absolute(np.fft(b)))>
> yes, it's more typing, but you'll never get confused as to what module >
functions come from.> > -Chris> > -- > Christopher Barker, Ph.D.>
Oceanographer> > NOAA/OR&R/HAZMAT (206) 526-6959 voice> 7600 Sand Point Way NE
(206) 526-6329 fax> Seattle, WA 98115 (206) 526-6317 main reception>
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