On Wed, March 11, 2009 7:50 am, Christopher Barker wrote:
Python does not distinguish between True and
False -- Python makes the distinction between something and nothing.
In that context, NaN is nothing, thus False.
Mathematically speaking, NaN is a quantity with undefined value.
Hi,
For the record, I have just added the following functionalities to
numpy, which may simplify some C code:
- NPY_NAN/NPY_INFINITY/NPY_PZERO/NPY_NZERO: macros to get nan, inf,
positive and negative zeros. Rationale: some code use NAN, _get_nan,
etc... NAN is a GNU C extension, INFINITY
On Wed, Mar 11, 2009 at 3:22 AM, Pauli Virtanen p...@iki.fi wrote:
Tue, 10 Mar 2009 15:27:32 +0900, David Cournapeau wrote:
For the upcoming 1.3.0 release, I would like to distribute the (built)
documentation in some way. But first, I need to be able to build it :)
Yep, buildability would be
There are several possibilities, some of them are listed on
http://en.wikipedia.org/wiki/Automatic_differentiation
== pycppad
http://www.seanet.com/~bradbell/pycppad/index.xml
pycppad is a wrapper of the C++ library CppAD ( http://www.coin-or.org/CppAD/ )
the wrapper can do up to second order
Wed, 11 Mar 2009 16:20:47 +0900, David Cournapeau wrote:
On Wed, Mar 11, 2009 at 3:22 AM, Pauli Virtanen p...@iki.fi wrote:
[clip]
Sphinx 0.5.1 worksforme, and on two different Linux machines (and
Python versions), so I doubt it's somehow specific to my setup.
Yes, it is strange - I can make
Charles R Harris wrote:
It isn't 0 so it should be True. Any disagreement?... Chuck
NaN is not a number equal to 0, so it should be True?
NaN is not a number different from 0, so it should be False?
Also see Pearu's comment.
Why not raise an exception when NaN is evaluated in a boolean
Charles R Harris wrote:
#include math.h
#include stdio.h
int main() {
double nan = sqrt(-1);
printf(%f\n, nan);
printf(%i\n, bool(nan));
return 0;
}
$ ./nan
nan
1
So resolved, it is True.
Unless specified in the ISO C
Pauli Virtanen wrote:
Did you check Pythonpath and egg-overriding-pythonpath issues? There's
also some magic in the autosummary extension, but it's not *too* black,
so I'd be surprised if it was behind these troubles.
I think the problem boils down to building from scratch at once.
Sturla Molden wrote:
Charles R Harris wrote:
#include math.h
#include stdio.h
int main() {
double nan = sqrt(-1);
printf(%f\n, nan);
printf(%i\n, bool(nan));
return 0;
}
$ ./nan
nan
1
So resolved, it is True.
On 10 Mar 2009, at 10:33 AM, Michael S. Gilbert wrote:
On Tue, 10 Mar 2009 17:21:23 +0100, Mark Bakker wrote:
Hello,
I want to convert an array to a string.
I like array2string, but it puts these annoying square brackets
around
the array, like
[[1 2 3],
[3 4 5]]
Anyway we can
--- On Wed, 3/11/09, Bruce Southey bsout...@gmail.com wrote:
From: Bruce Southey bsout...@gmail.com
Subject: Re: [Numpy-discussion] What is the logical value of nan?
To: Discussion of Numerical Python numpy-discussion@scipy.org
Date: Wednesday, March 11, 2009, 10:24 AM
This is one link
On Wed, Mar 11, 2009 at 8:24 AM, Bruce Southey bsout...@gmail.com wrote:
Sturla Molden wrote:
Charles R Harris wrote:
#include math.h
#include stdio.h
int main() {
double nan = sqrt(-1);
printf(%f\n, nan);
printf(%i\n, bool(nan));
On Wed, Mar 11, 2009 at 12:43 AM, David Cournapeau
da...@ar.media.kyoto-u.ac.jp wrote:
Hi,
For the record, I have just added the following functionalities to
numpy, which may simplify some C code:
- NPY_NAN/NPY_INFINITY/NPY_PZERO/NPY_NZERO: macros to get nan, inf,
positive and
Traditionally, Euler's constant is 0.57721 56649 01532 86060 65120 90082
40243 10421 59335 93992... see
wikipediahttp://en.wikipedia.org/wiki/Euler%E2%80%93Mascheroni_constant.
The constant e is sometimes called Euler's number -- shouldn't that be
Napier or Bernoulli in a pc world -- but I think e
as long as we all agree that e has a value of 2.71828 18284 59045 23536, its
just a matter of semantics.
the constant you reference is indicated by greek lower gamma
Chris
On Wed, Mar 11, 2009 at 11:39 AM, Charles R Harris
charlesr.har...@gmail.com wrote:
Traditionally, Euler's constant is
On Thu, Mar 12, 2009 at 12:39 AM, Charles R Harris
charlesr.har...@gmail.com wrote:
Traditionally, Euler's constant is 0.57721 56649 01532 86060 65120 90082
40243 10421 59335 93992...
You're right, Euler constant is generally gamma. Euler number is not
that great either (euler numbers in
Sturla Molden wrote:
Why not raise an exception when NaN is evaluated in a boolean
context? bool(NaN) has no obvious interpretation, so it should be
considered an error.
+1
Though there is clearly a lot of legacy around this, so maybe it's best
to follow C convention (sigh).
Bruce Southey
On Wed, Mar 11, 2009 at 11:06 AM, Christopher Barker
chris.bar...@noaa.govwrote:
Sturla Molden wrote:
Why not raise an exception when NaN is evaluated in a boolean
context? bool(NaN) has no obvious interpretation, so it should be
considered an error.
+1
Though there is clearly a lot of
Hi,
I noticed the following in numpy/distutils/system_info.py while trying to
get numpy to build against MKL:
if cpu.is_Itanium():
plt = '64'
#l = 'mkl_ipf'
elif cpu.is_Xeon():
plt = 'em64t'
#l = 'mkl_em64t'
Charles R Harris wrote:
Raising exceptions in ufuncs is going to take some work as the inner
loops are void functions without any means of indicating an error.
Exceptions also need to be thread safe. So I am not opposed but it is
something for the future.
I just saw David Cournapeau's
A Wednesday 11 March 2009, Ryan May escrigué:
Hi,
I noticed the following in numpy/distutils/system_info.py while
trying to get numpy to build against MKL:
if cpu.is_Itanium():
plt = '64'
#l = 'mkl_ipf'
elif cpu.is_Xeon():
On Wed, Mar 11, 2009 at 12:19 PM, Sturla Molden stu...@molden.no wrote:
Charles R Harris wrote:
Raising exceptions in ufuncs is going to take some work as the inner
loops are void functions without any means of indicating an error.
Exceptions also need to be thread safe. So I am not
On Thu, Mar 12, 2009 at 3:15 AM, Ryan May rma...@gmail.com wrote:
Hi,
I noticed the following in numpy/distutils/system_info.py while trying to
get numpy to build against MKL:
if cpu.is_Itanium():
plt = '64'
#l = 'mkl_ipf'
elif
On Wed, Mar 11, 2009 at 1:41 PM, David Cournapeau courn...@gmail.comwrote:
On Thu, Mar 12, 2009 at 3:15 AM, Ryan May rma...@gmail.com wrote:
Hi,
I noticed the following in numpy/distutils/system_info.py while trying to
get numpy to build against MKL:
if cpu.is_Itanium():
On Wed, Mar 11, 2009 at 1:34 PM, Francesc Alted fal...@pytables.org wrote:
A Wednesday 11 March 2009, Ryan May escrigué:
Hi,
I noticed the following in numpy/distutils/system_info.py while
trying to get numpy to build against MKL:
if cpu.is_Itanium():
A Wednesday 11 March 2009, Ryan May escrigué:
You know, I knew this sounded familiar. If you regularly build
against MKL, can you send me your site.cfg. I've had a lot more
success getting the build to work using the autodetection than the
blas_opt and lapack_opt sections. Since the
On Wed, Mar 11, 2009 at 2:20 PM, Francesc Alted fal...@pytables.org wrote:
A Wednesday 11 March 2009, Ryan May escrigué:
You know, I knew this sounded familiar. If you regularly build
against MKL, can you send me your site.cfg. I've had a lot more
success getting the build to work using
On Thu, Mar 12, 2009 at 3:36 AM, Charles R Harris
charlesr.har...@gmail.com wrote:
On Wed, Mar 11, 2009 at 12:19 PM, Sturla Molden stu...@molden.no wrote:
Charles R Harris wrote:
Raising exceptions in ufuncs is going to take some work as the inner
loops are void functions without any
Hi,
This is what I'm getting when I try to build scipy HEAD:
building library superlu_src sources
building library arpack sources
building library sc_c_misc sources
building library sc_cephes sources
building library sc_mach sources
building library sc_toms sources
building library sc_amos
On Thu, Mar 12, 2009 at 4:52 AM, Ryan May rma...@gmail.com wrote:
Hi,
This is what I'm getting when I try to build scipy HEAD:
building library superlu_src sources
building library arpack sources
building library sc_c_misc sources
building library sc_cephes sources
building library
Hi,
I was looking at #936, to implement correctly the hashing protocol for
dtypes. Am I right to believe that tp_hash should recursively descend
fields for compound dtypes, and the hash value should depend on the
size/ndim/typenum/byteorder for each atomic dtype + fields name (and
titles) ?
On Wed, Mar 11, 2009 at 15:06, David Cournapeau courn...@gmail.com wrote:
Hi,
I was looking at #936, to implement correctly the hashing protocol for
dtypes. Am I right to believe that tp_hash should recursively descend
fields for compound dtypes, and the hash value should depend on the
i don't know the correct answer... but i imagine it would be fairly easy to
compile a couple of representative scipts on each compiler and compare their
performance.
On Wed, Mar 11, 2009 at 4:29 PM, Sebastian Haase ha...@msg.ucsf.edu wrote:
Hi,
I was wondering if people could comment on which
there has already been a port of the robotics toolbox for matlab into python
which is built on numpy:
http://code.google.com/p/robotics-toolbox-python/
which contains all the function you are describing.
Chris
On Wed, Mar 4, 2009 at 6:10 PM, Gareth Elston
gareth.elston.fl...@googlemail.com
Hi,
import numpy as np
x = np.arange(30)
x.shape = (2,3,5)
idx = np.array([0,1])
e = x[0,idx,:]
print e.shape
# return (2,5). ok.
idx = np.array([0,1])
e = x[0,:,idx]
print e.shape
#- return (2,3). I think the right answer should be (3,2). Is
# it a bug here? my
You lost me on
x = np.arange(30)
x.shape = (2,3,5)
For me I get:
In [2]: x = np.arange(30)
In [3]: x.shape
Out[3]: (30,)
which is what I would expect. Perhaps I missed something?
Jon.
On Wed, Mar 11, 2009 at 8:55 PM, shuwj5...@163.com shuwj5...@163.com wrote:
Hi,
import numpy as np
x
On Wed, Mar 11, 2009 at 21:51, Jonathan Taylor
jonathan.tay...@utoronto.ca wrote:
You lost me on
x = np.arange(30)
x.shape = (2,3,5)
For me I get:
In [2]: x = np.arange(30)
In [3]: x.shape
Out[3]: (30,)
which is what I would expect. Perhaps I missed something?
He is reshaping x by
On Wed, Mar 11, 2009 at 9:51 PM, Jonathan Taylor
jonathan.tay...@utoronto.ca wrote:
You lost me on
x = np.arange(30)
x.shape = (2,3,5)
For me I get:
In [2]: x = np.arange(30)
In [3]: x.shape
Out[3]: (30,)
which is what I would expect. Perhaps I missed something?
Jon.
- Show quoted
On Wed, Mar 11, 2009 at 19:55, shuwj5...@163.com shuwj5...@163.com wrote:
Hi,
import numpy as np
x = np.arange(30)
x.shape = (2,3,5)
idx = np.array([0,1])
e = x[0,idx,:]
print e.shape
# return (2,5). ok.
idx = np.array([0,1])
e = x[0,:,idx]
print e.shape
#- return (2,3). I
On Thu, Mar 12, 2009 at 5:29 AM, Sebastian Haase ha...@msg.ucsf.edu wrote:
Hi,
I was wondering if people could comment on which compiler produces faster
code,
MS-VS2003 or cygwin g++ ?
I use Python 2.5 and SWIG. I have C/C++ routines for large (maybe
10MB, 100MB or even 1GB (on XP 64bit))
On Thu, Mar 12, 2009 at 12:38 PM, David Cournapeau courn...@gmail.com wrote:
and you can't
cross compile easily.
Of course, this applies to numpy/scipy - you can cross compile your
own extensions relatively easily (at least I don't see why it would
not be possible).
David
On Thu, Mar 12, 2009 at 5:36 AM, Robert Kern robert.k...@gmail.com wrote:
On Wed, Mar 11, 2009 at 15:06, David Cournapeau courn...@gmail.com wrote:
Hi,
I was looking at #936, to implement correctly the hashing protocol for
dtypes. Am I right to believe that tp_hash should recursively descend
On Wed, Mar 11, 2009 at 22:49, David Cournapeau courn...@gmail.com wrote:
On Thu, Mar 12, 2009 at 5:36 AM, Robert Kern robert.k...@gmail.com wrote:
On Wed, Mar 11, 2009 at 15:06, David Cournapeau courn...@gmail.com wrote:
Hi,
I was looking at #936, to implement correctly the hashing protocol
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