On Tue, 08 Feb 2011 18:06:48 +, Andrew Jaffe wrote:
> For this shape=(N,3) vector, this is not what you mean: as Robert Kern
> also has it you want axis=1, which produces a shape=(N,) (or the
> [:,newaxis] version which produces shape=(N,1).
>
> But what is the point of the ones(3)? I think
On 08/02/2011 16:44, Ben Gamari wrote:
> I have an array of (say, row) vectors,
>
>v = [ [ a1, a2, a3 ],
> [ b1, b2, b3 ],
> [ c1, c2, c3 ],
> ...
>]
>
> What is the optimal way to compute the norm of each vector,
>norm(v)**2 = [
>[ a1**2 + a2**2 +
On Tue, Feb 8, 2011 at 11:55, Ben Gamari wrote:
> On Tue, 8 Feb 2011 10:46:34 -0600, Robert Kern wrote:
>> (v*v).sum(axis=1)[:,np.newaxis]
>>
>> You can leave off the newaxis bit if you don't really need a column vector.
>>
> Fair enough, I unfortunately neglected to mention that I ultimately wan
On Tue, 8 Feb 2011 10:46:34 -0600, Robert Kern wrote:
> (v*v).sum(axis=1)[:,np.newaxis]
>
> You can leave off the newaxis bit if you don't really need a column vector.
>
Fair enough, I unfortunately neglected to mention that I ultimately want
to normalize these vectors, hence the *ones(3) in my
On Tue, Feb 8, 2011 at 10:44, Ben Gamari wrote:
> I have an array of (say, row) vectors,
>
> v = [ [ a1, a2, a3 ],
> [ b1, b2, b3 ],
> [ c1, c2, c3 ],
> ...
> ]
>
> What is the optimal way to compute the norm of each vector,
> norm(v)**2 = [
> [ a1**2 + a2**2 + a3*
I have an array of (say, row) vectors,
v = [ [ a1, a2, a3 ],
[ b1, b2, b3 ],
[ c1, c2, c3 ],
...
]
What is the optimal way to compute the norm of each vector,
norm(v)**2 = [
[ a1**2 + a2**2 + a3**2 ],
[ b1**2 + b2**2 + b3**2 ],
...
]
It see
