On Fri, Sep 16, 2011 at 2:28 PM, Benjamin Root wrote:
> Came across an oddity when experimenting with the datetime64 and
> timedelta64 objects.
>
> a = np.zeros((10,), dtype='l')
> b = np.datetime64('2010-12-20T14:23:56-0600')
> c = np.datetime64('2010-12-20T21:27:09-0600')
>
> a[0:1] = c - b #
Came across an oddity when experimenting with the datetime64 and timedelta64
objects.
a = np.zeros((10,), dtype='l')
b = np.datetime64('2010-12-20T14:23:56-0600')
c = np.datetime64('2010-12-20T21:27:09-0600')
a[0:1] = c - b # This works fine
a[0] = c - b # This does not
The second assignm
Hi Nicolas,
that looks great.
Could you make this available such that `pip install glumpy` would work?
cheers,
Samuel
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Hi folks,
I am pleased to announce a new release of glumpy, a small python library for
the (very) fast vizualization of numpy arrays, (mainly two dimensional) that
has been designed with efficiency in mind. If you want to draw nice figures for
inclusion in a scientific article, you’d better us
On Fri, Sep 16, 2011 at 11:35 AM, Benjamin Root wrote:
>
>
> On Friday, September 16, 2011, Charles R Harris
> wrote:
> >
> >
> > On Fri, Sep 16, 2011 at 9:11 AM, Benjamin Root wrote:
> >>
> >> Certain numerical types in Python that support accurate fractional
> calculations such as timedelta a
On Friday, September 16, 2011, Charles R Harris
wrote:
>
>
> On Fri, Sep 16, 2011 at 9:11 AM, Benjamin Root wrote:
>>
>> Certain numerical types in Python that support accurate fractional
calculations such as timedelta and Decimal do not allow for multiplication
or division by a floating point nu
On Fri, Sep 16, 2011 at 9:11 AM, Benjamin Root wrote:
> Certain numerical types in Python that support accurate fractional
> calculations such as timedelta and Decimal do not allow for multiplication
> or division by a floating point number, but do allow for use with an
> integer. This can cause
On Fri, Sep 16, 2011 at 10:18 AM, Benjamin Landenberger <
benjamin.landenber...@imtek.uni-freiburg.de> wrote:
> Hello list!
>
> I have an array *mask* of shape (a, b) and another array *intensities*
> of shape (N, a, b), where the values in *mask* range from 0 to N-1. It
> is somehow similar to la
On Friday, September 16, 2011, Benjamin Root wrote:
>
>
> On Friday, September 16, 2011, Benjamin Landenberger <
benjamin.landenber...@imtek.uni-freiburg.de> wrote:
>> Hello list!
>>
>> I have an array *mask* of shape (a, b) and another array *intensities*
>> of shape (N, a, b), where the values i
On Friday, September 16, 2011, Benjamin Landenberger <
benjamin.landenber...@imtek.uni-freiburg.de> wrote:
> Hello list!
>
> I have an array *mask* of shape (a, b) and another array *intensities*
> of shape (N, a, b), where the values in *mask* range from 0 to N-1. It
> is somehow similar to label
Hello list!
I have an array *mask* of shape (a, b) and another array *intensities*
of shape (N, a, b), where the values in *mask* range from 0 to N-1. It
is somehow similar to label arrays in scipy.ndimage.
Now I want to pick those entries from the first dimension of
*intensities* which are given
Certain numerical types in Python that support accurate fractional
calculations such as timedelta and Decimal do not allow for multiplication
or division by a floating point number, but do allow for use with an
integer. This can cause difficulties with some functions such as
np.gradient() which ha
On Thu, Sep 15, 2011 at 11:34 AM, Peter
wrote:
> This may not be the best place to ask, but how should a
> python script (e.g. setup.py) distinguish between real NumPy
> and micronumpy? Or should I instead be looking to distinguish
> PyPy versus another Python implementation?
For anyone intereste
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