Hi List,
I have an array, x, with dimensions (K,M,M). I would like to compute a
new array, y ~ (K,M*(M+1)/2), such that
y[k] = numpy.tril(x[k]).flatten() for each k = 0,..,K-1
Is there a way to do this without looping? I was trying with
tril_indices but couldn't quite get the logic right.
Thank
Pierre GM gmail.com> writes:
> On Nov 6, 2010, at 2:22 PM, Damien Moore wrote:
>
> > Hi List,
> >
> > I'm trying to import csv data as a numpy array using genfromtxt.
>
[...]
> Please open a ticket so that I don't forget about it. T
In reply to my own question, the trivial, but massively inefficient solution
is:
s=StringIO.StringIO('q1,2\nq3,4')
a=numpy.genfromtxt(s,delimiter=',',converters={0:lambda s:float(s[1:])})
a1 = numpy.array(a.tolist())
But what I really want to do is have genfromtxt do the conversion for me.
Specif
Hi List,
I'm trying to import csv data as a numpy array using genfromtxt. The csv
file contains mixed data, some floating point, others string codes and dates
that I want to convert to floating point. The strange thing is that when I
use the 'converters' argument to convert a subset of the columns
Emanuelle,
perfect! thanks.
> (assuming "import numpy as np", which is considered as a better practice
> as "from numpy import *")
actually I normally just "import numpy" but I guess np is nicer to
type and read...
cheers,
Damien
___
NumPy-Discussion
ugh... I goofed. The code snippet should have read
from numpy import *
A=array([[1,2],[2,3],[3,4]])
B=array([[2,2],[3,3]])
C=zeros(A.shape)
for i in xrange(len(A)):
C[i]=(A[i]**B).sum(0)
print C
On Wed, Nov 18, 2009 at 2:17 PM, Damien Moore wrote:
> The title of this e-mail is proba
The title of this e-mail is probably misleading so let me just show some code:
from numpy import *
A=array([[1,2],[2,3],[3,4]])
B=array([[2,2],[3,3]])
C=zeros(A.shape)
for i in xrange(len(A)):
C[i]=sum(A[i]**B)
print C
What I want to do is eliminate the for loop and rely on numpy
internals, but
