On Sun, Mar 8, 2009 at 3:49 PM, Charles R Harris
wrote:
> So it's off to look at the
> tickets and trying to fix bugs. Urrgh. Oh, and I suppose I should look into
> the argmax/argmin functions and see how they handle nans.
I think they don't at the moment: they have an implementation defined beh
On Sat, Mar 7, 2009 at 11:10 PM, David Cournapeau wrote:
> That's strange - I redid the compilation this morning, and I now get
> the same results as you (modulo the function call - I forced the
> function call because that's how it would work in numpy), that is the
> return value is builtin at
On Sun, Mar 8, 2009 at 4:34 AM, Charles R Harris
wrote:
>
>
> On Sat, Mar 7, 2009 at 11:57 AM, David Cournapeau
> wrote:
>>
>> On Sun, Mar 8, 2009 at 3:20 AM, Charles R Harris
>> wrote:
>>
>> >
>> > The macro is ugly, unneeded, and obfuscating. Why construct a number
>> > from
>> > characters an
On Sat, Mar 7, 2009 at 6:57 PM, Robert Kern wrote:
> On Sat, Mar 7, 2009 at 17:29, wrote:
>> np.random.multinomial looks weird. Are these bugs, or is there
>> something not correct with the explanation.
>
> I would like to know how you are interpreting the documentation.
>
>> Josef
>>
>> from t
On Sat, Mar 7, 2009 at 17:29, wrote:
> np.random.multinomial looks weird. Are these bugs, or is there
> something not correct with the explanation.
I would like to know how you are interpreting the documentation.
> Josef
>
> from the help/ docstring:
>
np.random.multinomial(20, [1/6.]*6,
np.random.multinomial looks weird. Are these bugs, or is there
something not correct with the explanation.
Josef
from the help/ docstring:
>>> np.random.multinomial(20, [1/6.]*6, size=2)
array([[3, 4, 3, 3, 4, 3],
[2, 4, 3, 4, 0, 7]])
For the first run, we threw 3 times 1, 4 times 2, etc
On Sat, Mar 7, 2009 at 11:57 AM, David Cournapeau wrote:
> On Sun, Mar 8, 2009 at 3:20 AM, Charles R Harris
> wrote:
>
> >
> > The macro is ugly, unneeded, and obfuscating. Why construct a number from
> > characters and shifts when you can just *write it down*?
>
> The idea was to replace the 'AB
Hi,
I'm having some difficulty understanding how these work and would be
grateful for any help.
In the simple case, I get what I expect:
In [42]: a = np.zeros((), dtype=[('f1', 'f8'),('f2', 'f8')])
In [43]: a == a
Out[43]: True
If one of the fields is itself an array, and the other is a scalar
On Sun, Mar 8, 2009 at 3:20 AM, Charles R Harris
wrote:
>
> The macro is ugly, unneeded, and obfuscating. Why construct a number from
> characters and shifts when you can just *write it down*?
The idea was to replace the 'ABCD' multi-byte constant. If you think
that writing down the correspondin
On Sat, Mar 7, 2009 at 11:20 AM, Charles R Harris wrote:
>
>
> On Sat, Mar 7, 2009 at 11:02 AM, David Cournapeau wrote:
>
>> On Sun, Mar 8, 2009 at 2:52 AM, Charles R Harris
>> wrote:
>> >
>> >
>> > On Sat, Mar 7, 2009 at 11:41 AM, David Cournapeau
>> > wrote:
>> >>
>> >> On Sat, Mar 7, 2009 at
On Sat, Mar 7, 2009 at 11:02 AM, David Cournapeau wrote:
> On Sun, Mar 8, 2009 at 2:52 AM, Charles R Harris
> wrote:
> >
> >
> > On Sat, Mar 7, 2009 at 11:41 AM, David Cournapeau
> > wrote:
> >>
> >> On Sat, Mar 7, 2009 at 6:01 AM, Charles R Harris
> >> wrote:
> >> > Hi David,
> >> >
> >> > Cur
On Sun, Mar 8, 2009 at 2:52 AM, Charles R Harris
wrote:
>
>
> On Sat, Mar 7, 2009 at 11:41 AM, David Cournapeau
> wrote:
>>
>> On Sat, Mar 7, 2009 at 6:01 AM, Charles R Harris
>> wrote:
>> > Hi David,
>> >
>> > Currently,
>> >
>> > bint.i = __STR2INTCST("ABCD");
>> >
>> > It is probably more por
On Sat, Mar 7, 2009 at 11:41 AM, David Cournapeau wrote:
> On Sat, Mar 7, 2009 at 6:01 AM, Charles R Harris
> wrote:
> > Hi David,
> >
> > Currently,
> >
> > bint.i = __STR2INTCST("ABCD");
> >
> > It is probably more portable to just initialize the union
> >
> > union {
> > char c[4];
On Sat, Mar 7, 2009 at 6:01 AM, Charles R Harris
wrote:
> Hi David,
>
> Currently,
>
> bint.i = __STR2INTCST("ABCD");
>
> It is probably more portable to just initialize the union
>
> union {
> char c[4];
> npy_uint32 i;
> } bint = {'A','B','C','D'};
>
Ah, tempting, right
On Sun, Feb 22, 2009 at 7:01 PM, Darren Dale wrote:
> On Sun, Feb 22, 2009 at 6:35 PM, Darren Dale wrote:
>
>> On Sun, Feb 22, 2009 at 6:28 PM, Pierre GM wrote:
>>
>>>
>>> On Feb 22, 2009, at 6:21 PM, Eric Firing wrote:
>>>
>>> > Darren Dale wrote:
>>> >> Does anyone know why __array_wrap__ is
On Wed, Mar 4, 2009 at 10:13 PM, David Cournapeau
wrote:
> Is there a rationale for using cblas at all ? Why not using straight
> C functions - it is not like we care about speed for tests, right ? Or
> am I missing something ?
Since nobody reacted, I removed the corresponding cblas calls, an
I was wondering about the behavior of ndarray.astype when passed None.
Currently this defaults to float64, does anyone know why it doesn't default
to the instance's dtype? defaulting to float64 seems too arbitrary.
Thanks,
Darren
___
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On Sat, Mar 7, 2009 at 5:41 AM, Patrick Marsh wrote:
> Greetings,
>
> I am running Windows Vista Ultimate and trying to build numpy from the
> SVN branch using MSVC 2003. I have been able to build previously, but
> with my latest SVN update I am no longer able to build. My CPU is an
> Intel Core
On Sat, Mar 7, 2009 at 5:18 AM, Robert Kern wrote:
> On Sat, Mar 7, 2009 at 04:10, Stéfan van der Walt
> wrote:
> > 2009/3/7 Robert Kern :
> >> In [5]: z = zeros(3, int)
> >>
> >> In [6]: z[1] = 1.5
> >>
> >> In [7]: z
> >> Out[7]: array([0, 1, 0])
> >
> > Blind moment, sorry. So, what is your
2009/3/7 Robert Kern :
> On Sat, Mar 7, 2009 at 04:10, Stéfan van der Walt wrote:
>> 2009/3/7 Robert Kern :
>>> In [5]: z = zeros(3, int)
>>>
>>> In [6]: z[1] = 1.5
>>>
>>> In [7]: z
>>> Out[7]: array([0, 1, 0])
>>
>> Blind moment, sorry. So, what is your take -- should this kind of
>> thing pass
On Sat, Mar 7, 2009 at 04:10, Stéfan van der Walt wrote:
> 2009/3/7 Robert Kern :
>> In [5]: z = zeros(3, int)
>>
>> In [6]: z[1] = 1.5
>>
>> In [7]: z
>> Out[7]: array([0, 1, 0])
>
> Blind moment, sorry. So, what is your take -- should this kind of
> thing pass silently?
Downcasting data is a n
2009/3/7 Robert Kern :
> In [5]: z = zeros(3, int)
>
> In [6]: z[1] = 1.5
>
> In [7]: z
> Out[7]: array([0, 1, 0])
Blind moment, sorry. So, what is your take -- should this kind of
thing pass silently?
Regards
Stéfan
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N
On Sat, Mar 7, 2009 at 03:30, Stéfan van der Walt wrote:
> 2009/3/7 Charles R Harris :
>>> a = np.zeros(6) # real
>>> b= np.arange(6)*(2+3j) # complex
>>> a[1] = b[1] # shouldn't this break?
>>>
>>> What is the rationale behind this behaviour?
>>
>> The same as this:
>>
>> In [1]: a = zeros(2)
>>
2009/3/7 Charles R Harris :
>> a = np.zeros(6) # real
>> b= np.arange(6)*(2+3j) # complex
>> a[1] = b[1] # shouldn't this break?
>>
>> What is the rationale behind this behaviour?
>
> The same as this:
>
> In [1]: a = zeros(2)
>
> In [2]: a[0] = '1'
>
> In [3]: a
> Out[3]: array([ 1., 0.])
This d
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