Has anyone tried mixing numpy with stackless? I am wondering if there
are any obvious reasons why it would not work. I am thinking
specifically of issues that may arise using the stackless microthreads.
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what is the overhead associated with importing a new module (whichever
includes izip)?
I am wondering whether it is actually more efficient for me to put my
aesthetics aside and stick with my ugly but efficient loop
On Sep 15, 2:32 pm, Francesc Alted <[EMAIL PROTECTED]> wrote:
> A Monday 15 Septe
http://www.amazon.com/Eliade-Guide-World-Religions/dp/0060621451/ref=sr_1_1?ie=UTF8&s=books&qid=1221285193&sr=8-1
2008/9/13 Vasile Bouleanu <[EMAIL PROTECTED]>
> Stie cineva despre existenta unei traduceri in engleza a "
> Dictionarului Religiilor " cu autorii Eliade /Culianu ?
>
>Vasile
Hi, can anyone point me in the direction of some example code to use
the norm_gen function in scipy.stats? I know this is the wrong board
but I seem to be at the wrong end of the moderation queue on the scipy
board and have been for a couple of weeks, so my posts over there
don't show up. I'm hop
thank you very much, deliciously satisfying
On Sep 5, 3:33 pm, Zachary Pincus <[EMAIL PROTECTED]> wrote:
> > Hi, probably a basic question, but I'm looking for a neat way to sum
> > all the positive values in an array of floats. I'm currently doing it
> > the hard way, but am hoping there is some
another newb question I suspect, but is there a way to instruct
argsort to sort in descending order or should I just sort and reverse?
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Hi, probably a basic question, but I'm looking for a neat way to sum
all the positive values in an array of floats. I'm currently doing it
the hard way, but am hoping there is some cunning and elegant syntax I
can use instead
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sorry, 1D array
this is perfect, thanks.
On Aug 27, 10:18 pm, Gary Ruben <[EMAIL PROTECTED]> wrote:
> I don't know what you mean by a 1D vector, but for a 3-vector, you can
> do this (also works for N-dimensions)
>
> In [1]: a=r_[1.,2.,3.]
> In [2]: a
> Out[2]: array([ 1., 2., 3.])
> In [3]: b=
bit of a newb question, is there a method for normalising a 1D vector
so it ends up with magnitude 1?
I can do it manually but I was hoping there was a neat numpy - or
scipy - trick. I've been web surfing but nothing really leaps out
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...are they down?
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