Hi,
I am not sure whether this is really useful to other, but anyway: I
release the first version of garnumpy, a system derived from Nick
Moffit's gar system, to build a set of packages from sources.
The idea is to build numpy + scipy automatically with its
dependencies, like a complete
Andrew Straw wrote:
> Perry Greenfield wrote:
>> On Feb 28, 2007, at 7:32 PM, Joe Harrington wrote:
>>
>>
>>> Hi Steve,
>>>
>>> I have taught Astronomical Data Analysis twice at Cornell using IDL,
>>> and I will be teaching it next Fall at UCF using NumPy. Though I've
>>> been active here in th
On 3/1/07, Robert Kern <[EMAIL PROTECTED]> wrote:
Charles R Harris wrote:
> Looks like function call overhead has gone way up or the cost of
> returning a float vs an array has gone way up. The loop overhead is
> about .01 and not significant. So something is definitely wrong here.
> Time to go
Charles R Harris wrote:
> Looks like function call overhead has gone way up or the cost of
> returning a float vs an array has gone way up. The loop overhead is
> about .01 and not significant. So something is definitely wrong here.
> Time to go look in trac ;)
It might have been when Travis put
On 3/1/07, Mark P. Miller <[EMAIL PROTECTED]> wrote:
OK...here goes. This code is going to look goofy, so please bear in
mind that it is only an abstraction of what my real code does (which
happens to provide interesting and meaning insights!).
I've attached saved versions of my interactive py
Alan G Isaac wrote:
> On Tue, 27 Feb 2007, "Steven H. Rogers" apparently wrote:
>
>> I'm doing an informal survey on the use of Array
>> Programming Languages for teaching. If you're using NumPy
>> in this manner I'd like to hear from you. What subject
>> was/is taught, academic level, res
On 3/1/07, Travis Oliphant <[EMAIL PROTECTED]> wrote:
A ticket was posted that emphasizes that the current behavior of NumPy
with regards to scalar coercion is different than numarray's behavior.
If we were pre 1.0, I would probably change the behavior to be in-line
with numarray. But, now I t
Robert Kern wrote:
>Travis Oliphant wrote:
>
>
>
>>So the question is: Do we keep the current behavior or change the
>>behavior to be more consistent with numarray. My current preference is
>>to change the behavior so it is more consistent with numarray (even
>>though it's actually not goin
OK...here goes. This code is going to look goofy, so please bear in
mind that it is only an abstraction of what my real code does (which
happens to provide interesting and meaning insights!).
I've attached saved versions of my interactive python sessions that
document the phenomenon. Again,
Thanks for the quick response!
Please see my in-line comments below.
Pierre GM wrote:
Hello,
The simplest is:
rescaled[rescaled.mask]=clipped_mask[rescaled.mask]
But for this particular kind of operation, I don't think that you need masked
array at all: this could do the trick
rescaled = c
Travis Oliphant wrote:
> So the question is: Do we keep the current behavior or change the
> behavior to be more consistent with numarray. My current preference is
> to change the behavior so it is more consistent with numarray (even
> though it's actually not going to be trivial to do that).
A ticket was posted that emphasizes that the current behavior of NumPy
with regards to scalar coercion is different than numarray's behavior.
If we were pre 1.0, I would probably change the behavior to be in-line
with numarray. But, now I think it needs some discussion because we are
changi
On 3/1/07, Mark P. Miller <[EMAIL PROTECTED]> wrote:
One more note (this perhaps may need a separate topic):
I've been using the Enthought python edition that contains python 2.4.3
and numpy 0.9.9.2706. After Robert Kern pointed out that I should try
numpy 1.0.1, I went ahead and installed it
Hello,
The simplest is:
rescaled[rescaled.mask]=clipped_mask[rescaled.mask]
But for this particular kind of operation, I don't think that you need masked
array at all: this could do the trick
>>>rescaled = clipped.copy()
>>>inside = numpy.logical_and(clipped>=123, clipped<=354)
>>>outside = numpy
Mark P. Miller wrote:
> Now however, I'm seeing perhaps a more serious problem: The test
> program that I'm working with went from taking ~80 seconds to run to
> taking over 10 minutes to run. I've rolled back to my old numpy version
> and confirmed that the old version was much faster. I a
One more note (this perhaps may need a separate topic):
I've been using the Enthought python edition that contains python 2.4.3
and numpy 0.9.9.2706. After Robert Kern pointed out that I should try
numpy 1.0.1, I went ahead and installed it (downloaded a few hours ago:
"numpy-1.0.1.win32-py2.4
Mark P. Miller wrote:
>>Ops, this seems a bug with your numpy version:
>>
>>In [46]:array1 = numpy.zeros((10,10),int)
>>In [47]:array1.itemset((5,5),9)
>>In [48]:array1
>>Out[48]:
>>array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
>> [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
>> [0, 0, 0, 0, 0, 0, 0, 0, 0,
Hello all,
I am stuck in my attempts to use masked arrays to combine the contents
of two arrays (please see the masked-arrays.py attachment) such that
missing values in one array are provided by the second array. There are
no ambiguities in the combination operation because each of the two
a
Francesc Altet wrote:
> Ops, this seems a bug with your numpy version:
yup, it's a bug here too:
>>> numpy.__version__
'1.0.1'
this is the dmg for python2.5 on pythonmac.org/packages
--
Christopher Barker, Ph.D.
Oceanographer
Emergency Response Division
NOAA/NOS/OR&R(206) 526-6
On Mar 1, 2007, at 13:33 , Rudolf Sykora wrote:
Hello,
since noone has reacted to my last e-mail yet (for several days), I
feel the need to ask again (since I still do not know a good answer).
Please help me.
>> Hello everybody,
>> I wonder how I could most easily accomplish the following:
On 01/03/07, Francesc Altet <[EMAIL PROTECTED]> wrote:
Hi,
I don't think there is a solution for this, but perhaps anybody may
offer some idea. Given:
In [79]:a=numpy.arange(9,-1,-1)
In [80]:b=numpy.arange(10)
In [81]:numpy.random.shuffle(b)
In [82]:b
Out[82]:array([2, 6, 3, 5, 4, 9, 0, 8, 7, 1
El dj 01 de 03 del 2007 a les 13:40 -0700, en/na Charles R Harris va
escriure:
>
>
> On 3/1/07, Francesc Altet <[EMAIL PROTECTED]> wrote:
> Hi,
>
> I don't think there is a solution for this, but perhaps
> anybody may
> offer some idea. Given:
>
>
On 3/1/07, Francesc Altet <[EMAIL PROTECTED]> wrote:
El dj 01 de 03 del 2007 a les 13:26 -0700, en/na Charles R Harris va
escriure:
>
>
> On 3/1/07, Francesc Altet <[EMAIL PROTECTED]> wrote:
> Hi,
>
> I don't think there is a solution for this, but perhaps
> anybody may
>
El dj 01 de 03 del 2007 a les 13:26 -0700, en/na Charles R Harris va
escriure:
>
>
> On 3/1/07, Francesc Altet <[EMAIL PROTECTED]> wrote:
> Hi,
>
> I don't think there is a solution for this, but perhaps
> anybody may
> offer some idea. Given:
>
>
On 3/1/07, Francesc Altet <[EMAIL PROTECTED]> wrote:
Hi,
I don't think there is a solution for this, but perhaps anybody may
offer some idea. Given:
In [79]:a=numpy.arange(9,-1,-1)
In [80]:b=numpy.arange(10)
In [81]:numpy.random.shuffle(b)
In [82]:b
Out[82]:array([2, 6, 3, 5, 4, 9, 0, 8, 7, 1]
On 3/1/07, Charles R Harris <[EMAIL PROTECTED]> wrote:
On 3/1/07, Francesc Altet <[EMAIL PROTECTED]> wrote:
>
> Hi,
>
> I don't think there is a solution for this, but perhaps anybody may
> offer some idea. Given:
>
> In [79]:a=numpy.arange(9,-1,-1)
> In [80]:b=numpy.arange(10)
> In [81]:numpy
On 3/1/07, Francesc Altet <[EMAIL PROTECTED]> wrote:
Hi,
I don't think there is a solution for this, but perhaps anybody may
offer some idea. Given:
In [79]:a=numpy.arange(9,-1,-1)
In [80]:b=numpy.arange(10)
In [81]:numpy.random.shuffle(b)
In [82]:b
Out[82]:array([2, 6, 3, 5, 4, 9, 0, 8, 7, 1]
Hi,
I don't think there is a solution for this, but perhaps anybody may
offer some idea. Given:
In [79]:a=numpy.arange(9,-1,-1)
In [80]:b=numpy.arange(10)
In [81]:numpy.random.shuffle(b)
In [82]:b
Out[82]:array([2, 6, 3, 5, 4, 9, 0, 8, 7, 1])
In [83]:a=a[b]
In [84]:a
Out[84]:array([7, 3, 6, 4, 5,
>>
>
> Ops, this seems a bug with your numpy version:
>
> In [46]:array1 = numpy.zeros((10,10),int)
> In [47]:array1.itemset((5,5),9)
> In [48]:array1
> Out[48]:
> array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
>[0,
El dj 01 de 03 del 2007 a les 12:47 -0700, en/na Mark P. Miller va
escriure:
> > try with
> >
> array1.itemset((5,5),9)
>
>
> Yep...tried that. But I don't get it!
>
> >>> import numpy
> >>> array1 = numpy.zeros((10,10),int)
> >>> array1
> array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
>
> try with
>
array1.itemset((5,5),9)
Yep...tried that. But I don't get it!
>>> import numpy
>>> array1 = numpy.zeros((10,10),int)
>>> array1
array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0
There are binaries of 1.0.1 here:
http://pythonmac.org/packages/py24-fat/index.html
and here:
http://pythonmac.org/packages/py25-fat/index.html
-Chris
--
Christopher Barker, Ph.D.
Oceanographer
Emergency Response Division
NOAA/NOS/OR&R(206) 526-6959 voice
7600 Sand Point Way N
El dj 01 de 03 del 2007 a les 12:03 -0700, en/na Mark P. Miller va
escriure:
> Sorry to pester, but is this the intended behavior of itemset?
>
> >>> array1=numpy.zeros((10,10),int)
> >>> array1
> array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
> [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
> [0, 0, 0
Sorry to pester, but is this the intended behavior of itemset?
>>> array1=numpy.zeros((10,10),int)
>>> array1
array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0,
Hello,
since noone has reacted to my last e-mail yet (for several days), I feel the
need to ask again (since I still do not know a good answer).
Please help me.
Hello everybody,
I wonder how I could most easily accomplish the following:
Say I have sth like:
a = array( [1, 2] )
and I want to us
Mark P. Miller wrote:
> Travis: Can you clarify this for me. The book doesn't have much detail
> here and seems to differ from your notation (which gives me errors).
> numpy 0.9.9.2706
This is the problem. You will need to upgrade to 1.0.1.
--
Robert Kern
"I have come to believe that the wh
Travis: Can you clarify this for me. The book doesn't have much detail
here and seems to differ from your notation (which gives me errors).
>> Getting single indices like this is a bit slower for NumPy then for
>> lists because of all the possibilities that must be distinguished for
>> array
>> ##imports
>> import numpy as NP
>>from numpy.random import randint
>> #numpy array code
>> array1 = NP.zeros((50,50), int)
>>
>> def random1():
>> c = array1(randint(10), randint(10))
>>
>>
> Is this a bug? You can't "call" an array. Did you mean,
> array1[randint(10), randint(10)]?
On 3/1/07, Mark P. Miller <[EMAIL PROTECTED]> wrote:
I've been using Numpy arrays for some work recently. Just for fun, I
compared some "representative" code using Numpy arrays and an object
comprised of nested lists to represent my arrays. To my surprise, the
array of nested lists outperforme
Mark P. Miller wrote:
>I've been using Numpy arrays for some work recently. Just for fun, I
>compared some "representative" code using Numpy arrays and an object
>comprised of nested lists to represent my arrays. To my surprise, the
>array of nested lists outperformed Numpy in this particular
Mark P. Miller wrote:
>I've been using Numpy arrays for some work recently. Just for fun, I
>compared some "representative" code using Numpy arrays and an object
>comprised of nested lists to represent my arrays. To my surprise, the
>array of nested lists outperformed Numpy in this particular
Hi -- the last dmg distribution was for numpy version 0.9.6. Is there
any chance of having dmg distributions posted for the current version
please?
___
Numpy-discussion mailing list
Numpy-discussion@scipy.org
http://projects.scipy.org/mailman/listinfo/nu
Steven H. Rogers wrote:
>Travis Oliphant wrote:
>
>
>>I just wanted to point people to the online version of the PEP. I'm
>>still looking for comments and suggestions. The current version is here:
>>
>>http://projects.scipy.org/scipy/numpy/browser/trunk/numpy/doc/pep_buffer.txt
>>
>>-Travis
Perry Greenfield wrote:
> On Feb 28, 2007, at 7:32 PM, Joe Harrington wrote:
>
>
>> Hi Steve,
>>
>> I have taught Astronomical Data Analysis twice at Cornell using IDL,
>> and I will be teaching it next Fall at UCF using NumPy. Though I've
>> been active here in the recent past, I'm actually no
Interesting...
I also tried the following and got similar results (using a 1,000 x
1,000 arrays). The time required to initialize the nested list array
was much higher (but nonetheless small in the context of the overall
time that my programs will run). But array element access is always
fas
On Mar 1, 2007, at 11:03 AM, Mark P. Miller wrote:
> I've been using Numpy arrays for some work recently. Just for fun, I
> compared some "representative" code using Numpy arrays and an object
> comprised of nested lists to represent my arrays. To my surprise, the
> array of nested lists outper
Hi all,
I'm posting this message to announce the availability of the *second
alpha release of PyTables 2.0*, the new and shiny major version of
PyTables.
This release settles the file format used in this major version,
removing the need to use pickled objects in order to store system
attributes,
On Feb 28, 2007, at 7:32 PM, Joe Harrington wrote:
> Hi Steve,
>
> I have taught Astronomical Data Analysis twice at Cornell using IDL,
> and I will be teaching it next Fall at UCF using NumPy. Though I've
> been active here in the recent past, I'm actually not a regular NumPy
> user myself yet
I've been using Numpy arrays for some work recently. Just for fun, I
compared some "representative" code using Numpy arrays and an object
comprised of nested lists to represent my arrays. To my surprise, the
array of nested lists outperformed Numpy in this particular application
(in my actual
On Tue, 27 Feb 2007, "Steven H. Rogers" apparently wrote:
> I'm doing an informal survey on the use of Array
> Programming Languages for teaching. If you're using NumPy
> in this manner I'd like to hear from you. What subject
> was/is taught, academic level, results, lessons learned,
> etc.
Thanks Mike:
Michael Williams wrote:
> On Tue, Feb 27, 2007 at 09:05:58PM -0700, Steven H. Rogers wrote:
>
>> I'm doing an informal survey on the use of Array Programming Languages
>> for teaching. If you're using NumPy in this manner I'd like to hear
>> from you. What subject was/is taught
Travis Oliphant wrote:
> I just wanted to point people to the online version of the PEP. I'm
> still looking for comments and suggestions. The current version is here:
>
> http://projects.scipy.org/scipy/numpy/browser/trunk/numpy/doc/pep_buffer.txt
>
> -Travis
>
Hi Travis:
I'd like to help,
On Tue, Feb 27, 2007 at 09:05:58PM -0700, Steven H. Rogers wrote:
> I'm doing an informal survey on the use of Array Programming Languages
> for teaching. If you're using NumPy in this manner I'd like to hear
> from you. What subject was/is taught, academic level, results, lessons
> learned, e
El dc 28 de 02 del 2007 a les 14:03 -0700, en/na Travis Oliphant va
escriure:
> I took the opportunity to go to PyCon this year and met several people
> there. I had a really good time although I would have liked to stay
> longer. If you want to see the slides for my talk they are here:
>
> h
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