Thank you very much Oliver,
> It did not occurred to me that this can be done so simple with size
>of original array itself!
>Thanks a lot.
>with best regards,
>Sudheer
>From: Olivier Delalleau
>To: Discussion of Numerical Python
>Sent: Monday, 27 May 2013 3:22 AM
>Subject: Re: [Numpy-
Your array doesn't seem strange, it looks like a perfectly normal (11 x 5)
matrix of dtype float64.
>>> x = np.load('csum.npy')
>>> np.vstack((np.zeros((1, x.shape[1])), x))
array([[ 0.,0.,0.,0.,
0.],
[ 31.82571459, 29.0629995 , 27.
On Fri, May 24, 2013 at 1:09 PM, Christoph Gohlke wrote:
> This patch works for me:
>
> diff --git a/numpy/random/mtrand/mtrand.pyx
> b/numpy/random/mtrand/mtrand.pyx
> index b0de560..233ff52 100644
> --- a/numpy/random/mtrand/mtrand.pyx
> +++ b/numpy/random/mtrand/mtrand.pyx
> @@ -4156,7 +4156
Thank you Aronne for the helping hand,
I tried the transpose as a check when I
could not get it correct other way. I could do it with test arrays, but it
appears some thing strange happens when I do the cumsum. So I am attaching here
the csum as csum.npy arr
On Sun, May 26, 2013 at 4:30 AM, Sudheer Joseph wrote:
> Dear Brian,
> I even tried below but no luck!
> In [138]: xx=np.zeros(11)
> In [139]: xx
> Out[139]: array([ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])
>
> In [147]: xx.shape
> Out[147]: (11,)
> In [140]: xx=np.ar
Hi David,
On 25 May 2013 15:23, David Cournapeau wrote:
> As some of you may know, Stéfan and me will present a tutorial on
> NumPy C code, so if we do our job correctly, we should have a few new
> people ready to help out during the sprints.
>
Is there any chance you'll be repeating this at Eu
