On Tue, Aug 12, 2008 at 23:27, Kees, Christopher E
<[EMAIL PROTECTED]> wrote:
> Hi, I'm trying to install numpy 1.1.1 into a 4-way universal build of python
> 2.6. It builds fine, but I get an error in install saying I can't install
> when cross-compiling. Does anybody know how to get around this?
Hi, I'm trying to install numpy 1.1.1 into a 4-way universal build of python
2.6. It builds fine, but I get an error in install saying I can't install
when cross-compiling. Does anybody know how to get around this?
Chris
___
Numpy-discussion mailing lis
Hi!
I'm working with a subclass of ndarray and ran into an issue that
seems to be caused by a line in numpy/ma/core.py
The offending line is no. 1837 in version 1.1.0 or 2053 in the latest
SVN version (revision 5635):
r = ndarray.ravel(self._data).view(type(self))
The problem is that my subclass
On Tue, Aug 12, 2008 at 20:12, Charles R Harris
<[EMAIL PROTECTED]> wrote:
>
>
> On Tue, Aug 12, 2008 at 3:21 PM, mark <[EMAIL PROTECTED]> wrote:
>>
>> Hello all -
>>
>> I have been banging my head against the wall.
>>
>> f2py worked fine on windows under 1.0.4 (Python 2.5)
>>
>> After upgrading to
On Tue, Aug 12, 2008 at 19:28, Charles R Harris
<[EMAIL PROTECTED]> wrote:
>
>
> On Tue, Aug 12, 2008 at 5:13 PM, Andrew Dalke <[EMAIL PROTECTED]>
> wrote:
>>
>> On Aug 12, 2008, at 9:54 AM, Anne Archibald wrote:
>> > Er, is this actually a bug? I would instead consider the fact that
>> > np.min([]
On Tue, Aug 12, 2008 at 3:21 PM, mark <[EMAIL PROTECTED]> wrote:
> Hello all -
>
> I have been banging my head against the wall.
>
> f2py worked fine on windows under 1.0.4 (Python 2.5)
>
> After upgrading to numpy 1.1.1, f2py keeps complaining it cannot find
> msvccompiler, yet it is still in the
On Tue, Aug 12, 2008 at 6:28 PM, Charles R Harris <[EMAIL PROTECTED]
> wrote:
>
>
> On Tue, Aug 12, 2008 at 5:13 PM, Andrew Dalke <[EMAIL PROTECTED]>wrote:
>
>> On Aug 12, 2008, at 9:54 AM, Anne Archibald wrote:
>> > Er, is this actually a bug? I would instead consider the fact that
>> > np.min([]
On Tue, Aug 12, 2008 at 5:13 PM, Andrew Dalke <[EMAIL PROTECTED]>wrote:
> On Aug 12, 2008, at 9:54 AM, Anne Archibald wrote:
> > Er, is this actually a bug? I would instead consider the fact that
> > np.min([]) raises an exception a bug of sorts - the identity of min is
> > inf.
>
>
> Personall
On Aug 12, 2008, at 9:54 AM, Anne Archibald wrote:
> Er, is this actually a bug? I would instead consider the fact that
> np.min([]) raises an exception a bug of sorts - the identity of min is
> inf.
That'll break consistency with the normal 'max'
function in Python.
> Really nanmin of an array c
2008/8/12 David Cournapeau <[EMAIL PROTECTED]>:
> On Mon, Aug 11, 2008 at 8:44 AM, Matthieu Brucher
> <[EMAIL PROTECTED]> wrote:
>>
>> Hi David,
>>
>> I recall you propsoed a plugin framework for numpy. Where are you on
>> that matter ? Still waiting for numscons ?
>
> The problem is not so much th
On Tue, Aug 12, 2008 at 10:02 AM, Thomas J. Duck <[EMAIL PROTECTED]> wrote:
>
> It is quite often the case that NaNs are unexpected, so it
> would be helpful to raise an Exception.
from numpy import seterr
seterr(all = 'warn')
Do emit a warning when encountering any kind of floating point er
> It really isn't very hard to replace
> np.sum(A)
> with
> np.sum(A[~isnan(A)])
> if you want to ignore NaNs instead of propagating them. So I don't
> feel a need for special code in sum() that treats NaN as 0.
That's all well and good, until you want to set the axis= keyword.
Then you're stuck w
Hello all -
I have been banging my head against the wall.
f2py worked fine on windows under 1.0.4 (Python 2.5)
After upgrading to numpy 1.1.1, f2py keeps complaining it cannot find
msvccompiler, yet it is still in the same place (under distutils) as
it was under 1.0.4.
Did something change? I r
Hello all -
I have been banging my head against the wall.
f2py worked fine on windows under 1.0.4 (Python 2.5)
After upgrading to numpy 1.1.1, f2py keeps complaining it cannot find
msvccompiler, yet it is still in the same place (under distutils) as
it was under 1.0.4.
Did something change? I r
2008/8/12 Nadav Horesh <[EMAIL PROTECTED]>:
> from numpy import *
>
> a = sqrt(maximum(0, a**2-repeat(b*c, columns).reshape(columns, rows)))
better:
import numpy as np
a = np.sqrt(np.maximum(0.0, a**2-(b*c)[np.newaxis,:]))
This doesn't have to make a temporary the size of a; instead
broadcastin
On Mon, Aug 11, 2008 at 8:44 AM, Matthieu Brucher
<[EMAIL PROTECTED]> wrote:
>
> Hi David,
>
> I recall you propsoed a plugin framework for numpy. Where are you on
> that matter ? Still waiting for numscons ?
The problem is not so much the build part, but the clear separation I
was talking about.
As always as i clicked send i realized my error
it is indeed not commutative and that makes sense
but i'm not sure the case:
numpy.ma.masked_equal(1,a)
should have worked, since we don't really know how to do this
comparison, the only thing that could make sense would be commutation
but i thinks
Hi I'm using 1.1.1
and found that numpy.ma.masked_equal is not commutative!
I would expect it to be in this case. Or raise an error for uncompatible
shape in the first case, no ?
>>> a = numpy.ma.arange(100)
>>> a.shape=(10,10)
>>> b=numpy.ma.masked_equal(1,a)
>>> b
Traceback (most recent cal
thank you, Nadav
Shawn
-Original Message-
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Nadav Horesh
Sent: Tuesday, August 12, 2008 11:58 AM
To: Discussion of Numerical Python
Subject: RE: [Numpy-discussion] non-linear array manipulation
from numpy import *
a = sqrt(max
Stefan,
The changes look reasonable, and if the old tests still pass (I'm
assuming your new ones will), then I'm happy.
There is one "style" issue: the (int* is_new_object) argument always
appears last in those helper functions where it is used.
Thanks
On Aug 12, 2008, at 2:16 AM, Stéfan va
from numpy import *
a = sqrt(maximum(0, a**2-repeat(b*c, columns).reshape(rows, columns)))
Nadav
-הודעה מקורית-
מאת: [EMAIL PROTECTED] בשם Gong, Shawn (Contractor)
נשלח: ג 12-אוגוסט-08 17:37
אל: Discussion of Numerical Python
נושא: [Numpy-discussion] non-linear array manipulation
hi
from numpy import *
a = sqrt(maximum(0, a**2-repeat(b*c, columns).reshape(columns, rows)))
Nadav.
-הודעה מקורית-
מאת: [EMAIL PROTECTED] בשם Gong, Shawn (Contractor)
נשלח: ג 12-אוגוסט-08 17:37
אל: Discussion of Numerical Python
נושא: [Numpy-discussion] non-linear array manipulation
hi
Christopher Barker wrote:
> well, it's not a bug because the result if there is a NaN is
> undefined.
> However, it sure could trip people up. If you know there is likely
> to be
> a NaN in there, then you could use nanmin() or masked arrays. The
> problem comes up when you have no idea there
hi list,
The following array manipulation takes long time because I can't find
ways to do in row/column, and have to do cell by cell. Would you check
to see if there is a nicer/faster way for this non-linear operation?
for i in range(rows):
for j in range(columns):
a[i][j] = math.sqrt(
Anne Archibald wrote:
> 2008/8/12 Joe Harrington <[EMAIL PROTECTED]>:
>
>
>> So, I endorse extending min() and all other statistical routines to
>> handle NaNs, possibly with a switch to turn it on if a suitably fast
>> algorithm cannot be found (which is competitor IDL's solution).
>> Certainly
2008/8/12 Barry Wark <[EMAIL PROTECTED]>:
> Stefan,
>
> I'm sorry I dropped the ball on this one. I didn't have time to get
> things working again before I left town for a month and, obviously,
> there it sat. Again, sorry.
No worries, Barry. That machine was troublesome, and I didn't want to
bot
On Tue, Aug 12, 2008 at 1:46 AM, Andrew Dalke <[EMAIL PROTECTED]>wrote:
> Here's the implementation, from lib/function_base.py
>
> def nanmin(a, axis=None):
> """Find the minimium over the given axis, ignoring NaNs.
> """
> y = array(a,subok=True)
> if not issubclass(y.dtype.type,
Stefan,
I'm sorry I dropped the ball on this one. I didn't have time to get
things working again before I left town for a month and, obviously,
there it sat. Again, sorry.
Barry
On Mon, Aug 11, 2008 at 3:11 PM, Stéfan van der Walt <[EMAIL PROTECTED]> wrote:
> Hi all,
>
> Due to hardware failure,
2008/8/12 Joe Harrington <[EMAIL PROTECTED]>:
> So, I endorse extending min() and all other statistical routines to
> handle NaNs, possibly with a switch to turn it on if a suitably fast
> algorithm cannot be found (which is competitor IDL's solution).
> Certainly without a switch the default beha
2008/8/12 Stéfan van der Walt <[EMAIL PROTECTED]>:
> Hi Andrew
>
> 2008/8/12 Andrew Dalke <[EMAIL PROTECTED]>:
>> This is buggy for the case of a list containing only NaNs.
>>
>> >>> import numpy as np
>> >>> np.NAN
>> nan
>> >>> np.min([np.NAN])
>> nan
>> >>> np.nanmin([np.NAN])
>> inf
>> >>>
I am pushing back the beta release for another day. Stefan is looking
into one thing I would like to get into the beta.
Cheers,
On Sun, Aug 10, 2008 at 6:48 PM, Jarrod Millman <[EMAIL PROTECTED]> wrote:
> Hello,
>
> The C-API change was committed in revision 5626:
> http://scipy.org/scipy/numpy/c
Masked arrays are a bit clunky for something as simple and standard as
NaN handling. They also have the inverse of the standard truth sense,
at least as used in my field. 1 (or True) usually means the item is
allowed, not denied, so that you can multiply the mask by the data to
zero all bad value
Hi Andrew
2008/8/12 Andrew Dalke <[EMAIL PROTECTED]>:
> This is buggy for the case of a list containing only NaNs.
>
> >>> import numpy as np
> >>> np.NAN
> nan
> >>> np.min([np.NAN])
> nan
> >>> np.nanmin([np.NAN])
> inf
> >>>
Thanks for the report. This should be fixed in r5630.
Regards
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