We really ought to have a special page for all of Robert's little gems!
DG
On Tue, Oct 29, 2013 at 10:00 AM, wrote:
>
> -Message: 5
> Date: Tue, 29 Oct 2013 17:02:33 +
> From: Robert Kern
> Subject: Re: [Numpy-discussion] getting the equivalent complex dtype
>
On Tue, Oct 29, 2013 at 4:55 PM, Julian Taylor <
jtaylor.deb...@googlemail.com> wrote:
> On 29.10.2013 21:00, Charles R Harris wrote:
> >
> >
> >
> > On Tue, Oct 29, 2013 at 1:57 PM, Charles R Harris
> > mailto:charlesr.har...@gmail.com>> wrote:
> >
> > Hi All,
> >
> > I'm going to tag 1.7
On 29.10.2013 21:00, Charles R Harris wrote:
>
>
>
> On Tue, Oct 29, 2013 at 1:57 PM, Charles R Harris
> mailto:charlesr.har...@gmail.com>> wrote:
>
> Hi All,
>
> I'm going to tag 1.7.2 soon. That is, unless someone else would like
> the experience of making a release. Any voluntee
On Tue, Oct 29, 2013 at 1:57 PM, Charles R Harris wrote:
> Hi All,
>
> I'm going to tag 1.7.2 soon. That is, unless someone else would like the
> experience of making a release. Any volunteers?
>
>
Make that 1.7.2rc1.
Chuck
___
NumPy-Discussion mailing
Hi All,
I'm going to tag 1.7.2 soon. That is, unless someone else would like the
experience of making a release. Any volunteers?
Chuck
___
NumPy-Discussion mailing list
NumPy-Discussion@scipy.org
http://mail.scipy.org/mailman/listinfo/numpy-discussion
On Tue, 2013-10-29 at 16:47 +, Henry Gomersall wrote:
> Is there a way to extract the size of array that would be created by
> doing 1j*array?
>
There is np.result_type. It does the handling of scalars as normal,
dtypes will be handled like arrays (scalars are allowed to lose
precision).
-
On 29/10/13 17:02, Robert Kern wrote:
>
> Quick and dirty:
>
> # Get a tiny array from `a` to test the dtype of its output when
> multiplied
> # by a complex float. It must be an array rather than a scalar since the
> # casting rules are different for array*scalar and scalar*scalar.
> dt = (a.flat
On Tue, Oct 29, 2013 at 5:02 PM, Ao Liu wrote:
>
> Hi,
>
> I've been using np.random.uniform and mpi4py.
>
> I found that the random number each processor (or rank) generated are the
same, so I was wondering how random.uniform chose its seeds. Theoretically,
those ranks shouldn't have anything to
On Tue, Oct 29, 2013 at 4:47 PM, Henry Gomersall wrote:
>
> Is there a way to extract the size of array that would be created by
> doing 1j*array?
>
> The problem I'm having is in creating an empty array to fill with
> complex values without knowing a priori what the input data type is.
>
> For ex
Hi,
I've been using np.random.uniform and mpi4py.
I found that the random number each processor (or rank) generated are the
same, so I was wondering how random.uniform chose its seeds. Theoretically,
those ranks shouldn't have anything to do with others. The only possibility
that I can think of i
On 29/10/13 16:47, Henry Gomersall wrote:
> Is there a way to extract the size of array that would be created by
> doing 1j*array?
Of course, I mean dtype of the array.
Henry
___
NumPy-Discussion mailing list
NumPy-Discussion@scipy.org
http://mail.scipy.
Is there a way to extract the size of array that would be created by
doing 1j*array?
The problem I'm having is in creating an empty array to fill with
complex values without knowing a priori what the input data type is.
For example, I have a real or int array `a`.
I want to create an array `b`
Le 29/10/2013 11:37, Pierre Haessig a écrit :
> def compare(point, other):
> delta = point - other
> argmax = np.abs(delta).argmax()
> delta_max = delta[argmax]
> if delta_max > 0:
> return 1
> elif delta_max < 0:
> return -1
> else:
> return 0
>
> Th
Hi Freddie,
Le 29/10/2013 10:21, Freddie Witherden a écrit :
> The order itself does not need to satisfy any specific properties.
I can't agree with you : if there is no specific property, then keeping
the list *unchanged* would be a fine solution (and very fast and very
very robust) ;-)
what abo
-BEGIN PGP SIGNED MESSAGE-
Hash: SHA1
On 28/10/2013 12:44, Pierre Haessig wrote:
> Hi,
>
> Le 27/10/2013 19:28, Freddie Witherden a écrit :
>> I wish to sort these points into a canonical order in a fashion
>> which is robust against small perturbations. In other words
>> changing any co
15 matches
Mail list logo