Charles R Harris wrote:
>
>
> On Wed, Jan 13, 2010 at 11:34 PM, David Cournapeau
> mailto:da...@silveregg.co.jp>> wrote:
>
> Charles R Harris wrote:
>
> >
> >
> > What is the setup one needs to build the installers? It might be
> well to
> > document that, the depen
On Wed, Jan 13, 2010 at 11:34 PM, David Cournapeau wrote:
> Charles R Harris wrote:
>
> >
> >
> > What is the setup one needs to build the installers? It might be well to
> > document that, the dependencies, and the process.
>
> Right. The top script is:
> http://projects.scipy.org/numpy/browser/t
On Fri, Jan 15, 2010 at 11:59 AM, Pierre GM wrote:
> On Jan 14, 2010, at 8:52 PM, David Cournapeau wrote:
>> Pierre GM wrote:
>>
>>>
>>> Er, no.
>>> np.ma.minimum(a, b) returns the lowest value of a and b element-wsie, or
>>> the the lowest element of a is b is None. The behavior is inherited fro
On Thu, Jan 14, 2010 at 3:49 PM, Warren Weckesser <
warren.weckes...@enthought.com> wrote:
> Yaroslav Halchenko wrote:
> > Dear NumPy People,
> >
> > First I want to apologize if I misbehaved on NumPy Trac by reopening the
> > closed ticket
> > http://projects.scipy.org/numpy/ticket/1362
> > but I
On Jan 14, 2010, at 8:52 PM, David Cournapeau wrote:
> Pierre GM wrote:
>
>>
>> Er, no.
>> np.ma.minimum(a, b) returns the lowest value of a and b element-wsie, or the
>> the lowest element of a is b is None. The behavior is inherited from the
>> very first implementation of maskedarray in nume
Pierre GM wrote:
>
> Er, no.
> np.ma.minimum(a, b) returns the lowest value of a and b element-wsie, or the
> the lowest element of a is b is None. The behavior is inherited from the very
> first implementation of maskedarray in numeric. This itself is unexpected,
> since np.minimum requires a
Hi Warren,
> The "problem" is that the tuple is converted to an array in the
> statement that does the comparison, not in the construction of the
> array. Numpy attempts
> to convert the right hand side of the == operator into an array.
> It then does the comparison using the two arrays.
Thanks
On Thu, 14 Jan 2010, josef.p...@gmail.com wrote:
> It looks difficult to construct an object array with only 1 element,
> since a tuple is interpreted as different array elements.
yeap
> It looks like some convention is necessary for interpreting a tuple in
> the array construction, but it doesn'
On Thu, Jan 14, 2010 at 5:49 PM, Warren Weckesser
wrote:
> Yaroslav Halchenko wrote:
>> Dear NumPy People,
>>
>> First I want to apologize if I misbehaved on NumPy Trac by reopening the
>> closed ticket
>> http://projects.scipy.org/numpy/ticket/1362
>> but I still feel strongly that there is misun
Yaroslav Halchenko wrote:
> Dear NumPy People,
>
> First I want to apologize if I misbehaved on NumPy Trac by reopening the
> closed ticket
> http://projects.scipy.org/numpy/ticket/1362
> but I still feel strongly that there is misunderstanding
> and the bug/defect is valid. I would appreciate if
Dear NumPy People,
First I want to apologize if I misbehaved on NumPy Trac by reopening the
closed ticket
http://projects.scipy.org/numpy/ticket/1362
but I still feel strongly that there is misunderstanding
and the bug/defect is valid. I would appreciate if someone would waste
more of his time t
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Hi,
> It is at least undesirable. It may not be a bug per se as I don't
> think that we guarantee that .isbuiltin is free from false negatives
> (though we do guarantee that it is free from false positives). The
> reason is that we would have to search the builtin dtypes for a match
> every time w
On Thu, Jan 14, 2010 at 07:01, Matthew Brett wrote:
> Hi,
>
> Over on the scipy list, someone pointed out an oddness in the output
> of the matlab reader, which revealed this - to me - unexpected
> behavior in numpy:
>
> In [20]: dt = np.dtype('f8')
>
> In [21]: dt.isbuiltin
> Out[21]: 1
>
> In [2
Hi,
Over on the scipy list, someone pointed out an oddness in the output
of the matlab reader, which revealed this - to me - unexpected
behavior in numpy:
In [20]: dt = np.dtype('f8')
In [21]: dt.isbuiltin
Out[21]: 1
In [22]: ndt = dt.newbyteorder('<')
In [23]: ndt.isbuiltin
Out[23]: 0
I was
On Jan 14, 2010, at 4:53 AM, David Cournapeau wrote:
> Hi,
>
> I encountered a problem in matlab which boils down to a surprising
> behavior of np.ma.minimum:
>
> x = np.random.randn(2, 3)
> mx = np.matrix(x)
>
> np.ma.minimum(x) # smallest item of x
> ret = np.ma.minimum(mx) # flattened version
Hi,
I encountered a problem in matlab which boils down to a surprising
behavior of np.ma.minimum:
x = np.random.randn(2, 3)
mx = np.matrix(x)
np.ma.minimum(x) # smallest item of x
ret = np.ma.minimum(mx) # flattened version of mx, i.e. ret == mx.flatten()
Is this expected ?
cheers,
David
___
I've written a self-contained example that shows that numpy indeed
tries to call the __float__ method.
What is buggy is what happens if calling the __float__ method raises
an Exception.
Then numpy assumes (in this case wrongly) that the object should be
casted to the neutral element.
I'd guess th
Hi,
Thanks all works now! The implicit none only didn't work when defining
dv as a function now its a subroutine it seems to work.
Regards
Jon
On 12/01/2010 13:44, Pearu Peterson wrote:
> Hi,
>
> The problem is that f2py does not support callbacks that
> return arrays. There is easy workaroun
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