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=
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=a/norm(a)
In [4]: b
Out[4]: array([ 0.26726124, 0.53452248, 0.80178373])
Gary R
> bit of a newb question, is t
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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