On Wed, Dec 3, 2014 at 4:02 PM, Stefan van der Walt
wrote:
> Hi Catherine
>
> On 2014-12-04 01:12:30, Moroney, Catherine M (398E) <
> catherine.m.moro...@jpl.nasa.gov> wrote:
> > I have an array "A" of shape (NX, NY, NZ), and then I have a second
> array "B" of shape (NX, NY)
> > that ranges from
Posting in the correct thread now...
A slightly different way to look at it (I don't think it is exactly the
same problem, but the description reminded me of it):
http://mail.scipy.org/pipermail/numpy-discussion/2013-April/066269.html
(and I think there are some things that can be done to make tha
I am sorry, I meant to post this in a different thread...
On Wed, Dec 3, 2014 at 8:32 PM, Benjamin Root wrote:
> A slightly different way to look at it (I don't think it is exactly the
> same problem, but the description reminded me of it):
>
> http://mail.scipy.org/pipermail/numpy-discussion/20
A slightly different way to look at it (I don't think it is exactly the
same problem, but the description reminded me of it):
http://mail.scipy.org/pipermail/numpy-discussion/2013-April/066269.html
(and I think there are some things that can be done to make that faster,
but I don't recall it righ
On 12/3/2014 8:44 AM, Matthew Brett wrote:
> Hi,
>
> I just noticed this using Christophe Gohlke's MKL builds of numpy:
>
import numpy as np
val = 2**63 + 2**62
np.float64(val)
> 1.3835058055282164e+19
np.float64(val).astype(np.uint64)
> 9223372036854775808
>
> In general it see
Hi Catherine
On 2014-12-04 01:12:30, Moroney, Catherine M (398E)
wrote:
> I have an array "A" of shape (NX, NY, NZ), and then I have a second array "B"
> of shape (NX, NY)
> that ranges from 0 to NZ in value.
>
> I want to create a third array "C" of shape (NX, NY) that holds the
> "B"-th slice
Hello,
I'm sure there's a simple solution, but I'm not seeing it so any hints would be
greatly appreciated.
I have an array "A" of shape (NX, NY, NZ), and then I have a second array "B"
of shape (NX, NY)
that ranges from 0 to NZ in value.
I want to create a third array "C" of shape (NX, NY) tha
On Wed, Dec 3, 2014 at 8:44 AM, Matthew Brett
wrote:
> Hi,
>
> I just noticed this using Christophe Gohlke's MKL builds of numpy:
>
> >>> import numpy as np
> >>> val = 2**63 + 2**62
> >>> np.float64(val)
> 1.3835058055282164e+19
> >>> np.float64(val).astype(np.uint64)
> 9223372036854775808
>
I
Hi,
I just noticed this using Christophe Gohlke's MKL builds of numpy:
>>> import numpy as np
>>> val = 2**63 + 2**62
>>> np.float64(val)
1.3835058055282164e+19
>>> np.float64(val).astype(np.uint64)
9223372036854775808
In general it seems that floats get clipped at 2**63 when casting to
uint64.
On 12/03/2014 12:17 PM, Jaime Fernández del Río wrote:
>
>
> The safe way to create 1D object arrays from a list is by preallocating them,
> something like this:
>
> >>> a = [np.random.rand(2, 3), np.random.rand(2, 3)]
> >>> b = np.empty(len(a), dtype=object)
> >>> b[:] = a
> >>> b
> array([ array
On Wed, Dec 3, 2014 at 2:21 AM, Emanuele Olivetti
wrote:
> On 12/03/2014 04:32 AM, Ryan Nelson wrote:
> > Emanuele,
> >
> > This doesn't address your question directly. However, I wonder if you
> > could approach this problem from a different way to get what you want.
> >
> > First of all, create
On 12/03/2014 04:32 AM, Ryan Nelson wrote:
> Emanuele,
>
> This doesn't address your question directly. However, I wonder if you
> could approach this problem from a different way to get what you want.
>
> First of all, create a "index" array and then just vstack all of your
> arrays at once.
>
>
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