I too have to agree with Andreas. I have been using Numpy for years in my
work, but am not versed in C so I don't even understand what numpy is doing
under the hood. I too would only be able to contribute to the code at the
python level, or as Andreas said, at improving SciPy packages and other
N
If you are storing objects, then can't you store them in a list and just do:
for obj in objectlist:
obj.attribute = value
Or am I misunderstanding?
On Thu, Apr 5, 2012 at 11:31 AM, Neal Becker wrote:
> I have an array of object.
>
> How can I apply attribute access to each element?
>
> I
aset is so
large that you cannot afford to have several data structures that are
holding it simultanesouly in your code.
On Mon, Mar 12, 2012 at 6:23 PM, Abhishek Pratap wrote:
> Super awesome. I love how the python community in general keeps the
> recordings available for free.
>
> @Adam
Abhi,
One thing I would suggest is to tackle numpy with a particular focus. Once
you've gotten the basics down through tutorials and videos, do you have a
research project in mind to use with numpy?
On Mon, Mar 12, 2012 at 6:08 PM, Skipper Seabold wrote:
> On Mon, Mar 12, 2012 at 6:04 PM, Abhis
Thanks for clearing that up.
On Mon, Feb 20, 2012 at 1:58 PM, Skipper Seabold wrote:
> On Mon, Feb 20, 2012 at 1:35 PM, Brett Olsen
> wrote:
> > On Sat, Feb 18, 2012 at 8:12 PM, Adam Hughes
> wrote:
> >> Hey everyone,
> >>
> >> I have timeseries
x27;s all part of a learning curve. I'll keep in mind that the
period may cause problems later; however, as far as I can tell so far,
there's nothing going wrong when I access the data.
On Mon, Feb 20, 2012 at 1:35 PM, Brett Olsen wrote:
> On Sat, Feb 18, 2012 at 8:12 PM, Adam Hughes
On Feb 19, 2012, at 10:38 AM, Sturla Molden wrote:
Den 19.02.2012 10:52, skrev Mark Wiebe:
C++ removes some of this advantage -- now there is extra code generated by
> the compiler to handle constructors, destructors, operators etc which can
> make a material difference to fast inner loops. S
On Feb 19, 2012, at 2:18 AM, Mark Wiebe wrote:
The suggestion of transitioning the NumPy core code from C to C++ has
sparked a vigorous debate, and I thought I'd start a new thread to give my
perspective on some of the issues raised, and describe how such a
transition could occur.
First, I'd lik
Hey everyone,
I have timeseries data in which the column label is simply a filename from
which the original data was taken. Here's some sample data:
name1.txt name2.txt name3.txt
32 34953
32 03402
I've noticed that the standard genfromtxt() me
Hello,
I get a segfault here:
In [1]: x = np.array([1,2,3], dtype='M')
In [2]: x.searchsorted(2, side='left')
But it's fine here:
In [1]: x = np.array([1,2,3], dtype='M')
In [2]: x.view('i8').searchsorted(2, side='left')
Out[2]: 1
This segfaults again:
x.view('i8').searchsorted(np.datetime64(
build, in setup.py.
Has anyone had this sort of incompatibility on OSX? Suggestions as to
correct way to deal with it?
Thanks,
Adam
On Mon, Dec 19, 2011 at 1:37 PM, mark florisson
wrote:
>
>> On 19 December 2011 00:04, Adam Klein wrote:
>> > Hi all,
>> >
>>
Hi,
Definitely have the sdk installed. In the Developer/SDKs directory I have one
for 10.6 and another for 10.7 - no idea where a second 10.6 would be coming
from =(
Adam.
-Original Message-
From: numpy-discussion-requ...@scipy.org
[mailto:numpy-discussion-requ...@scipy.org]
Sent
27;t quite right with
something. I have placed ** before the lines that appear in red.
I appreciate the suggestions,
Thanks again,
Adam.
running build
running config_cc
unifing config_cc, config, build_clib, build_ext, build commands --compiler
options
running config_fc
unifing config_
installer from Python.org so I have no idea whether
Python.h is present or where indeed I would find it or how I would add it to
the search path.
Do I have to install from source or something like that?
Thanks again,
Adam.
-Original Message-
From: McNicol, Adam
Sent: Fri 12/16/2011 1
ot compile 'Python.h'. Perhaps you need to "\
SystemError: Cannot compile 'Python.h'. Perhaps you need to install
python-dev|python-devel.
I have got no idea what to do with this error message. Any help would be much
appreciated.
Kind Regards,
Adam.
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I'm keeping a large number of data points in multiple 2d arrays, for
example:
class c(object):
def __init__(self):
self.a = np.zeros((24, 60))
self.b = np.zeros((24, 60))
...
After processing the data, I'm serializing these to disk for future
reference/post-pro
Ahhh I see this is due to the ABI change, sorry for the noise.
Cheers
Adam
On Mon, Feb 15, 2010 at 21:00, Adam Mercer wrote:
> Hi
>
> According to the NumPy download page
> <http://sourceforge.net/projects/numpy/files/> the latest available
> version is 1.3.0, what happene
Hi
According to the NumPy download page
<http://sourceforge.net/projects/numpy/files/> the latest available
version is 1.3.0, what happened to 1.4.0? Apologies if I've missed
some announcement.
Cheers
Adam
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Hi again, I apologize, the mistake was entirely my own. Sqrt's do the
right thing....
Adam
On Sat, Oct 17, 2009 at 12:17 PM, Adam Ginsburg
wrote:
> My code is actually wrong but I still have the problem I've
> identified that sqrt is leading to precision errors. Sorry abo
My code is actually wrong but I still have the problem I've
identified that sqrt is leading to precision errors. Sorry about the
earlier mistake.
Adam
On Sat, Oct 17, 2009 at 12:08 PM, Adam Ginsburg
wrote:
>
> sqrt(float64(1.034324523462345))
> # 1.0170174646791199
>
I
simply being obtuse?
Thanks,
Adam
Example code:
from scipy.optimize.minpack import fsolve
from numpy import sqrt
sqrt(float64(1.034324523462345))
# 1.0170174646791199
f=lambda x: x**2-float64(1.034324523462345)**2
f(sqrt(float64(1.034324523462345)))
# -0.03550269637326231
fsolve(f,1.01)
# 1.0343
On Wed, Jun 10, 2009 at 15:19, Samir Unni wrote:
> That's odd. You're running Mac OS 10.5.7? Did you install NumPy
> manually or via Fink?
Yep Intel 10.5.7, installed from MacPorts.
Cheers
Adam
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Compiler
--fcompiler=sun Sun or Forte Fortran 95 Compiler
--fcompiler=vast Pacific-Sierra Research Fortran 90 Compiler
For compiler details, run 'config_fc --verbose' setup command.
$
Cheers
Adam
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2): no suitable image found. Did find:
> /Users/srunni/src/pdb2pqr/pdb2pqr/tinker/src/tinker/source/ese.so:
> unknown file type, first eight bytes: 0x80 0xC0 0x4F 0x00 0xEB 0x57
> 0xE0 0x8F
>
> when I attempt to import the generated mod
On Fri, Jun 5, 2009 at 06:09, David Cournapeau wrote:
> Please test it ! I am particularly interested in results for scipy
> binaries on mac os x (do they work on ppc).
Test suite passes on Intel Mac OS X (10.5.7) built from source:
OK (KNOWNFAIL=6, SKIP=21)
Cheers
roughly the behavior I want with 'where':
>>> a
array([1, 1, 1, 5, 5])
>>> numpy.ma.where(a==numpy.ma.max(a))[0]
array([3, 4])
>>> numpy.ma.where(a==numpy.ma.min(a))[0]
array([0, 1, 2])
- Adam J. Oliner
oli...@cs.stanford.edu
On Apr 10, 2009,
, 5, 5])
>>> numpy.ma.argmax(a)
3
>>> numpy.ma.argmin(a)
0
I was expecting to get more than one index for both calls. Am I doing
something wrong or misreading the documentation?
- Adam J. Oliner
oli...@cs.stanford.edu
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version on many OS (mac
> os X 10.4 I believe, RHEL for sure, open solaris).
Mac OS X 10.4 uses python-2.3, 10.5 uses python-2.5.
Cheers
Adam
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;t seem to be going to the
> right places when I re-examined them.
I think I answered my own question: if I'd used zeros() instead of
ones() it would have worked fine. I don't know why I tried to use
ones().
Adam
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.net/):
In [85]: bi = (f.bolo_indices[np.newaxis,:]+ones([7751,1])).astype('int')
In [86]: whc = (whscan[:,np.newaxis] + ones([1,107])).astype('int')
In [87]: array2d[whc,bi] = temp2d
I thought this had worked, but the values didn't seem to be going to the
right place
numpy 1.2 is not buildable with python 2.6. You will have to wait
> for a later version, most probably 1.3,
>
Ok thanks David, guess I will have to wait till I can leverage the new
IEEE 754 support in python 2.6
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Please add numpy 1.2.0 win32 package for python 2.6
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don't
> have to specify anything.
Thanks for the clarification.
Cheers
Adam
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Hi
If I specify a fortran compiler when building numpy, does that have
any effect on what is installed? In other words, must I build numpy
against a fortran compiler in order to successfully build and use
extension written in fortran - such as scipy?
Cheers
Adam
t
the page doesn't exist, however the scipy home page, i.e.
http://www.scipy.org, now appears to be the planet aggregator is this
just a temporary DNS issue?
Cheers
Adam
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gt; Total Time with list: 0.0469707035741
>
>
>
> Hope this helps,
That is helpful, I thought that using arrays would be much faster but
its clearly not in this case.
Thanks
Adam
st wondering if there was a
better way to do it.
Cheers
Adam
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need for the list, as the array object doesn't
seem to have an append() method?
Cheers
Adam
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On 08/10/2007, Robert Kern <[EMAIL PROTECTED]> wrote:
> Use sep=' '. As the docstring says, if sep is empty, then the string is
> interpreted as binary data. If it is not empty, then the string is interpreted
> as ASCII.
Thanks, got it the wrong way round. That
6 1.18295070e-076 ...,
5.45168074e-067 2.11101912e-052 6.58519056e-260]
where using
values = array(wavearray.split()).astype(float)
print values
results in the correct
[ 0.e+00 0.e+00 0.e+00 ...,
4.22233200e-23 3.86799900e-23 3.48452000
On 07/10/2007, Gary Ruben <[EMAIL PROTECTED]> wrote:
> Try using astype. This works:
>
> values = array(wavearray.split()).astype(float)
Thanks Gary, that does the trick.
Cheers
Adam
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array element with a sequence.
Cheers
Adam
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why i need to loop over a large number of single-trial events,
rather than just replacing the loop with a large number of trials in one single
multinomial pick (annoying, as that's so much quicker!).
Thanks for any help,
Adam
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Travis Oliphant ieee.org> writes:
>
> Adam Jenkins wrote:
> > I just tried it, and it does solve the problem for the
> > mathematical operators like + and -, but doesn't seem to work for
> > the comparison operators. That is, if I write
> >
> > lhs
y_priority__. Is this intentional that the comparison operators
ignore __array_priority__, or just a bug in ndarray? Thanks again.
Adam
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ay involves transferring all the array data to the python
process. For various reasons, for my application it's preferable that I
handle binary operators with mixed numpy/myarray operand types myself,
rather than converting the myarray object to a numpy.ndarray.
T
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