On Mon, Nov 13, 2006 at 02:29:11PM -0700, Tim Hochberg wrote:
Erin Sheldon wrote:
On 11/13/06, Tim Hochberg [EMAIL PROTECTED] wrote:
Here's one more approach that's marginally faster than the map based
solution and also won't chew up an extra memory since it's based on from
iter:
On Sat, Nov 11, 2006 at 10:40:22AM -0800, Keith Goodman wrote:
I accidentally wrote a unit test using int32 instead of float64 and
ran into this problem:
x = M.matrix([[1, 2, 3]])
x[0,1] = M.nan
x
matrix([[1, 0, 3]]) --- Got 0 instead of NaN
But this, of course, works:
x =
On Sat, Nov 11, 2006 at 06:30:06PM -0300, Lisandro Dalcin wrote:
On 11/11/06, Stefan van der Walt [EMAIL PROTECTED] wrote:
NaN (or inf) is a floating point number, so seeing a zero in integer
representation seems correct:
In [2]: int(N.nan)
Out[2]: 0L
Just to learn myself: Why int
On Sat, Nov 11, 2006 at 01:59:40PM -0800, Keith Goodman wrote:
Would it make sense to upcast instead of downcast?
This upcasts:
x = M.matrix([[1, M.nan, 3]])
x
matrix([[ 1., nan, 3.]])
But this doesn't:
x = M.matrix([[1, 2, 3]])
x[0,1] = M.nan
x
On Thu, Nov 09, 2006 at 03:18:57AM -0500, Colin J. Williams wrote:
import numpy.core as _n
_nt= _n.numerictypes
value=
'[EMAIL PROTECTED]@[EMAIL PROTECTED]@\x00\x00\x00\x00\x00\x00\x18@'
_n.array(value, dtype= _nt.complex128, copy=True)
Traceback (most recent call last):
File
On Wed, Nov 08, 2006 at 05:54:17AM -0800, izak marais wrote:
Hi
Sorry if this is an obvious question, but what is the easiest way to multiply
matrices in numpy? Suppose I want to do A=B*C*D. The ' * ' operator apparently
does element wise multiplication, as does the 'multiply' ufunc. All I
On Mon, Nov 06, 2006 at 02:09:32PM -0600, John Hunter wrote:
A simple import of numpy with the latest svn triggers a ctypes warning
In [1]: import numpy
/usr/lib/python2.4/site-packages/numpy/ctypeslib.py:12: UserWarning:
All features of ctypes interface may not work with ctypes 1.0.1
On Mon, Nov 06, 2006 at 03:10:20PM -0500, Colin J. Williams wrote:
Many thanks. In general, there is sense in the Python dictum about having one
way to do things. Although, in this case [length] vs length for one dimension
doesn't
exercise me greatly. I would be a bit more concerned about
On Mon, Oct 23, 2006 at 11:57:57AM -0400, Scott Ransom wrote:
I believe that ix_() has recently begun modifying the shapes of its
input arrays. For instance:
[...]
This should be fixed in SVN.
Cheers
Stéfan
-
Using
On Mon, Oct 23, 2006 at 05:28:05PM -0600, Travis Oliphant wrote:
Yes it has. Fixed.
I think ctypes 1.0.1 is required for ndpointer to work, so we might consider
some kind of version check + warning on import?
Not sure about that. It worked for me using ctypes 1.0.0.
You have to
On Sun, Oct 22, 2006 at 09:27:39AM +0900, Bill Baxter wrote:
On 10/22/06, Charles R Harris [EMAIL PROTECTED] wrote:
On 10/21/06, Bill Baxter [EMAIL PROTECTED] wrote:
Here's something I've been wondering: is it ok to port Matlab
functions over to python? If so, then it's maybe an
On Fri, Oct 20, 2006 at 11:42:26AM +0200, Sebastien Bardeau wrote:
a = numpy.array((1,2,3))
b = a[:2]
Here you index by a slice.
c = a[2]
Whereas here you index by a scalar.
So you want to do
b = a[[2]]
b += 1
or in the general case
b = a[slice(2,3)]
b += 1
Regards
Stéfan
On Thu, Oct 19, 2006 at 01:59:49PM -0700, Christopher Barker wrote:
Travis Oliphant wrote:
Actually something as simple as
class InfoArray(N.ndarray):
pass
will allow you to add attributes to InfoArray.
Well, sure, but how the heck do you initialize it?
Looks like
x =
On Thu, Oct 19, 2006 at 09:45:02AM -0600, Travis Oliphant wrote:
Stefan van der Walt wrote:
If I understand correctly, the following should work:
import numpy as N
class InfoArray(N.ndarray):
def __new__(info_arr_cls,arr,info={}):
info_arr_cls.info = info
return
On Tue, Oct 17, 2006 at 10:01:51AM -0600, Travis Oliphant wrote:
Charles R Harris wrote:
Travis,
I note that
a = arange(6).reshape(2,3,order='F')
a
array([[0, 1, 2],
[3, 4, 5]])
Shouldn't that be 3x2? Or maybe [[0,2,4],[1,3,5]]? Reshape is making a
copy, but
Hi all,
Some of you may have seen the interesting thread on Fortran-ordering
earlier. I thought it might be fun to set up a short quiz which tests
your knowledge on the topic.
If you're up for the challenge, take a look at
http://mentat.za.net/numpy/quiz
I won't be held liable for any
On Wed, Oct 18, 2006 at 10:30:26AM +0900, Bill Baxter wrote:
I think the answer to #3 is wrong.
From 1.0rc2 I get:
array([1,2,3,4,5,6],order='C').reshape((2,3),order='F')
array([[1, 2, 3],
[4, 5, 6]])
But the quiz wants me to answer something different.
This recently changed.
I've summarised this thread at
http://www.scipy.org/NegativeSquareRoot
Feel free to make adjustments, in case I missed something.
Regards
Stefan
-
Using Tomcat but need to do more? Need to support web services, security?
On Thu, Oct 12, 2006 at 12:38:51AM -0600, Travis Oliphant wrote:
I made some fixes to the asbuffer code which let me feel better about
exposing it in NumPy (where it is now named int_asbuffer).
This code takes a Python integer and a size and returns a buffer object
that points to that
On Thu, Oct 12, 2006 at 08:58:21AM -0500, Greg Willden wrote:
On 10/11/06, Bill Baxter [EMAIL PROTECTED] wrote:
On 10/12/06, Greg Willden [EMAIL PROTECTED] wrote:
Speed should not take precedence over correctness.
Unless your goal is speed. Then speed should take precedence
On Thu, Oct 12, 2006 at 10:53:12AM -0400, Alan G Isaac wrote:
On Thu, 12 Oct 2006, Stefan van der Walt apparently wrote:
I tried to explain the argument at
http://www.scipy.org/NegativeSquareRoot
Helpful. But you start off by saying:
In mathematics, the above assumption
On Wed, Oct 11, 2006 at 05:21:44PM -0600, Travis Oliphant wrote:
Stefan van der Walt wrote:
I agree with Fernando on this one.
Further, if I understand correctly, changing sqrt and power to give
the right answer by default will slow things down somewhat. But is it
worth sacrificing
On Wed, Oct 11, 2006 at 08:24:01PM -0400, A. M. Archibald wrote:
What is the desired behaviour of sqrt?
[...]
Should it return a complex array only when any entry in its input is
negative? This will be even *more* surprising when a negative (perhaps
even -0) value appears in their matrix
On Wed, Oct 04, 2006 at 01:37:55AM -0400, A. M. Archibald wrote:
Would it be useful for me to contribute the tiny script I wrote to
trigger it as a regression test?
A. M. Archibald
from numpy import vectorize, zeros
vt = vectorize(lambda *args: args)
# Removing either of the following
Hi all,
Currently, the power function returns '0' for negative powers of
integers:
In [1]: N.power(3,-2)
Out[1]: 0
(or, more confusingly)
In [1]: N.power(a,b)
Out[1]: 0
which is almost certainly not the answer you want. Two possible
solutions may be to upcast the input to float before
On Thu, Sep 21, 2006 at 08:35:02PM -0400, P GM wrote:
Folks,
I'm running into the following problem with putmask on take.
import numpy
x = N.arange(12.)
m = [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1]
i = N.nonzero (m)[0]
w = N.array([-1, -2, -3, -4.])
x.putmask(w,m)
You can also use
On Fri, Sep 22, 2006 at 02:17:57AM -0500, Robert Kern wrote:
Stefan van der Walt wrote:
Hi P.,
On Thu, Sep 21, 2006 at 07:40:39PM -0400, PGM wrote:
I'm running into the following problem with putmask on take.
import numpy
x = N.arange(12.)
m = [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0
Hi,
Would anyone object if I changed the signature of
unique1d(ar1, retindx=False)
to
unique1d(ar1, return_index=False)?
I find retindx both harder to read and to type than return_index.
Thanks.
Stéfan
-
Take Surveys.
On Tue, Aug 29, 2006 at 10:49:58AM -0600, Travis Oliphant wrote:
Matt Knox wrote:
is the following behaviour expected? or is this a bug with
numpy.object_ ? I'm using numpy 1.0b1
print numpy.array([],numpy.float64).size
0
print numpy.array([],numpy.object_).size
1
On Wed, Aug 30, 2006 at 12:04:22PM +0100, Andrew Jaffe wrote:
the current implementation of fftfreq (which is meant to return the
appropriate frequencies for an FFT) does the following:
k = range(0,(n-1)/2+1)+range(-(n/2),0)
return array(k,'d')/(n*d)
I have tried this with very
On Thu, Aug 24, 2006 at 11:10:24PM -0400, Sasha wrote:
I would welcome an effort to make the glossary more novice friendly,
but not at the expense of oversimplifying things.
BTW, do you think Rank ... (2) number of orthogonal dimensions of a
matrix is clear? Considering that matrix is
On Fri, Aug 18, 2006 at 01:54:44PM +0900, David Cournapeau wrote:
import numpy as N
from ctypes import cdll, POINTER, c_int, c_uint
_hello = cdll.LoadLibrary('libhello.so')
_hello.sum.restype= c_int
_hello.sum.artype = [POINTER(c_int), c_uint]
def sum(data):
return
On Fri, Aug 18, 2006 at 04:45:03PM +0200, Stefan van der Walt wrote:
Hi Norbert
On Fri, Aug 18, 2006 at 03:36:47PM +0200, Norbert Nemec wrote:
in numpy-1.0b2 the logic in setup.py is slightly off. The attached patch
fixes the issue.
Please file a ticket so that we don't lose track
On Wed, Jul 19, 2006 at 03:06:00PM -0700, Webb Sprague wrote:
I am not sure where to look for this, sorry if it is RTFM or JPS
(just plain stupid):
Is there a way to set a default to print the entire array, rather than
an ellipses version of it? If not, why doesn't
Hi Tamaryn
On Wed, Jul 12, 2006 at 11:57:48AM +0100, Tamaryn Menneer wrote:
Hi
I'm running Python 2.4 on Windows XP. I've installed NumPy, and run the
simple test of import numeric but I get the error ImportError: No module
named numeric in return. The module numeric is located in
On Tue, Jul 11, 2006 at 11:32:48AM +0200, Emanuele Olivetti wrote:
Hi,
I don't understand how to use argsort results. I have a 2D matrix and
I want to sort values in each row and obtain the index array of that
sorting. Argsort(1) is what I need, but the problem is how to use its
result in
On Thu, Jul 06, 2006 at 10:26:12PM -0600, Travis Oliphant wrote:
1) .T Have some kind of .T attribute
-1, since the expected behaviour of .T is different depending on
problem context.
a) .T == .swapaxes(-2,-1)
The fact that this was proposed just demonstrates the fact. If you
have a
On Fri, Jul 07, 2006 at 07:06:58PM -0600, Fernando Perez wrote:
On 7/7/06, Travis Oliphant [EMAIL PROTECTED] wrote:
I just committed a big change to the NumPy SVN (r2773-r2777) which adds
the prefix npy_ or NPY_ to all names not otherwise pre-fixed.
There is also a noprefix.h header that
On Thu, Jul 06, 2006 at 11:39:19AM +0900, Bill Baxter wrote:
Often when I'm doing interactive prototyping I find myself wanting to check
whether two arrays are sharing a copy of the same data.
It seems like there ought to be a concise way to do that, but right now seems
like the only way is
Hi Tim
On Wed, Jun 21, 2006 at 12:02:27PM -0700, Tim Hochberg wrote:
Numexpr can now handle broadcasting. As an example, check out this
implementation of the distance-in-a-bunch-of-dimenstions function that's
been going around. This is 80% faster than the most recent one posted on
my box
I filed this as ticket #135:
http://projects.scipy.org/scipy/numpy/ticket/135
Regards
Stéfan
On Wed, May 31, 2006 at 05:47:25PM +0200, Nils Wagner wrote:
test_wrap (numpy.core.tests.test_umath.test_special_methods) ... ok
check_types (numpy.core.tests.test_scalarmath.test_types)*** glibc
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