numpy-discussion — Discussion list for all users of Numerical Python

Re: [Numpy-discussion] Comparing arrays with dtypes with field names

[Travis O. <oli...@ie...>]

Albert Strasheim wrote:
> Hello all
>
> I noticed that arrays with dtypes with field names don't compare correctly
> when using the equality operator.
>
> Example:
>
> In [17]: dt = N.dtype({'names' : ['f1', 'f2'],
>                        'formats' : [N.intc, N.intc]})
>
> In [18]: x = N.array([(0,0)], dtype=dt)
>
> In [19]: y = N.array([(0,0)], dtype=dt)
>
> In [20]: x['f1']==y['f1']
> Out[20]: array([True], dtype=bool)
>
> In [21]: x['f2']==y['f2']
> Out[21]: array([True], dtype=bool)
>
> In [22]: x==y
> Out[22]: False
>
> The question arises as to what should be returned when comparing these
> arrays. One option would be an array with dtype=bool which would indicate
> that each item in the array is equal in f1 and f2. 

Currently, in SVN, record-arrays now can be compared (== or != only).   
The comparison returns a single bool array:

For equality the comparison is basically:

res = True
for name in x.dtype.fields[-1]:
      res = logical_and(res, x[name] == y[name])

while for not-equal comparisons it is:

res = False
for name in x.dtype.fields[-1]:
      res = logical_or(res, x[name] != y[name])


> Another option would be
> an array with dtype
>
> N.dtype({'names' : ['f1', 'f2'], 'formats' : [bool,bool]})
>
> I think this second option could be very useful for some applications, where
> you might want to know something like: is the (i,j)th element of this array
> the same in f1 and f2 but different in f3?
>   

This is a bit too sophisticated and does not work very well for nested 
arrays.   The implemented comparison works for nested arrays just fine.  
You can just test for what you want directly

(x['f1'] == y['f2']) & (x['f1'] != y['f3'])

to handle the fewer particular cases where the other approach might be 
useful.

-Travis

[Numpy-discussion] Comparing arrays with dtypes with field names

[Albert S. <fu...@gm...>]

Hello all

I noticed that arrays with dtypes with field names don't compare correctly
when using the equality operator.

Example:

In [17]: dt = N.dtype({'names' : ['f1', 'f2'],
                       'formats' : [N.intc, N.intc]})

In [18]: x = N.array([(0,0)], dtype=dt)

In [19]: y = N.array([(0,0)], dtype=dt)

In [20]: x['f1']==y['f1']
Out[20]: array([True], dtype=bool)

In [21]: x['f2']==y['f2']
Out[21]: array([True], dtype=bool)

In [22]: x==y
Out[22]: False

The question arises as to what should be returned when comparing these
arrays. One option would be an array with dtype=bool which would indicate
that each item in the array is equal in f1 and f2. Another option would be
an array with dtype

N.dtype({'names' : ['f1', 'f2'], 'formats' : [bool,bool]})

I think this second option could be very useful for some applications, where
you might want to know something like: is the (i,j)th element of this array
the same in f1 and f2 but different in f3?

Any thoughts?

Regards,

Albert

Re: [Numpy-discussion] Determining if two arrays share data

[Stefan v. d. W. <st...@su...>]

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 c=
heck
> whether two arrays are sharing a copy of the same data.
>=20
> It seems like there ought to be a concise way to do that, but right now=
 seems
> like the only way is with a little function like this:
>=20
> def same_base(a,b):
>     ab =3D a.base
>     if ab is None: ab =3D a
>     bb =3D b.base
>     if bb is None: bb =3D b
>     return ab is bb  =20
>=20
> is there some easier built-in way?  Does the above function even cover =
all the
> bases? (so to speak...)

Say you have

x =3D N.array([1,2,3,4])

and

y =3D x.reshape((2,2))

then x and y share the same data.  You can see this when you do

x.__array_interface__['data'][0] =3D=3D y.__array_interface__['data'][0]

Still, this only holds for full data views.  If you had

z =3D y[1:,1:]

then the data memory position would differ.

Cheers
St=E9fan

[Numpy-discussion] Numpy import problem

[Satellite D. R. G. <sat...@po...>]

Hi, I have a problem when importing numpy into python 2.4.1.  I did a 
successful (I think) build and install of Numpy 0.9.8 on a mac osx 
(10.4) intel, but when i try to import numpy into python i get this 
error:

>>> from numpy import*
import core -> failed: Inappropriate file type for dynamic loading
import lib -> failed: Inappropriate file type for dynamic loading
import linalg -> failed: Inappropriate file type for dynamic loading
import dft -> failed: Inappropriate file type for dynamic loading
import random -> failed: Inappropriate file type for dynamic loading

Traceback (most recent call last):
  File "<pyshell#0>", line 1, in -toplevel-
    from numpy import*
  File 
"/Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/site-packages/numpy/__init__.py", line 49, in 
-toplevel-
    import add_newdocs
  File 
"/Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/site-packages/numpy/add_newdocs.py", line 2, in 
-toplevel-
    from lib import add_newdoc
  File 
"/Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/site-packages/numpy/lib/__init__.py", line 5, in 
-toplevel-
    from type_check import *
  File 
"/Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/site-packages/numpy/lib/type_check.py", line 8, in 
-toplevel-
    import numpy.core.numeric as _nx
  File 
"/Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/site-packages/numpy/core/__init__.py", line 5, in 
-toplevel-
    import multiarray
ImportError: Inappropriate file type for dynamic loading




Any help anyone could offer as to the cause of this would be most welcome,
Cheers,     Joe Corbett
ps. installing numpy through python 2.3 worked and I was able to import 
numpy into 2.3 fine.

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[Numpy-discussion] Mac OS 10.4 test errors

[Steve L. <lis...@ar...>]

Hi folks,

I'm able to build and install numpy  on my intel mac OS 10.4.7 but  
I'm getting 3 unit test failures.

I'm using gcc 4.0.1 and GNU Fortran 95 (GCC) 4.2.0 20060401 (if  
that's helpful to know).

The relevant output from my ipython session is below. Doing some of  
the stuff I've found in random tutorials doesn't seem to be a  
problem .. though I do get seg faults when trying to do some scipy  
tutorial plotting stuff .. which I may post to the scipy list a bit  
later ... I just want to make sure I'm installing everything  
correctly first.

Thanks for any insight,
-steve



In [3]: numpy.__version__
Out[3]: '0.9.9.2735'

In [4]: numpy.test(1)
  ....
  ... cut some stuff out until first error ..
  ...
======================================================================
ERROR: check_basic (numpy.core.tests.test_defmatrix.test_algebra)
----------------------------------------------------------------------
Traceback (most recent call last):
   File "/opt/local/lib/python2.4/site-packages/numpy/core/tests/ 
test_defmatrix.py", line 125, in check_basic
     Ainv = linalg.inv(A)
   File "/opt/local/lib/python2.4/site-packages/numpy/linalg/ 
linalg.py", line 122, in inv
     return wrap(solve(a, identity(a.shape[0])))
   File "/opt/local/lib/python2.4/site-packages/numpy/linalg/ 
linalg.py", line 109, in solve
     results = lapack_routine(n_eq, n_rhs, a, n_eq, pivots, b, n_eq, 0)
LapackError: Parameter ipiv is not of type PyArray_INT in  
lapack_lite.dgesv

======================================================================
ERROR: check_instance_methods  
(numpy.core.tests.test_defmatrix.test_matrix_return)
----------------------------------------------------------------------
Traceback (most recent call last):
   File "/opt/local/lib/python2.4/site-packages/numpy/core/tests/ 
test_defmatrix.py", line 157, in check_instance_methods
     f = eval('a.%s' % attrib)
   File "<string>", line 0, in ?
   File "/opt/local/lib/python2.4/site-packages/numpy/core/ 
defmatrix.py", line 293, in getI
     return matrix(inv(self))
   File "/opt/local/lib/python2.4/site-packages/numpy/linalg/ 
linalg.py", line 122, in inv
     return wrap(solve(a, identity(a.shape[0])))
   File "/opt/local/lib/python2.4/site-packages/numpy/linalg/ 
linalg.py", line 109, in solve
     results = lapack_routine(n_eq, n_rhs, a, n_eq, pivots, b, n_eq, 0)
LapackError: Parameter ipiv is not of type PyArray_INT in  
lapack_lite.dgesv

======================================================================
ERROR: check_basic (numpy.core.tests.test_defmatrix.test_properties)
----------------------------------------------------------------------
Traceback (most recent call last):
   File "/opt/local/lib/python2.4/site-packages/numpy/core/tests/ 
test_defmatrix.py", line 48, in check_basic
     assert allclose(linalg.inv(A), mA.I)
   File "/opt/local/lib/python2.4/site-packages/numpy/linalg/ 
linalg.py", line 122, in inv
     return wrap(solve(a, identity(a.shape[0])))
   File "/opt/local/lib/python2.4/site-packages/numpy/linalg/ 
linalg.py", line 109, in solve
     results = lapack_routine(n_eq, n_rhs, a, n_eq, pivots, b, n_eq, 0)
LapackError: Parameter ipiv is not of type PyArray_INT in  
lapack_lite.dgesv

----------------------------------------------------------------------

Re: [Numpy-discussion] Numpy not working (revised)

[Steve L. <lis...@ar...>]

> I am trying to get numpy working with MacOSX 10.4 on an intel
> processor.  I had it working for Python2.3.5, but after installing
> Python 2.4 it didn't work on either python version.

Hi Stephen,

I've been able to get numpy/scipy installed on my MacBook Pro  
(although I do get three unit test failures when I run nump.test(1)  
-- which I'll post next)

One thing I'm noticing in what you printed out is that for some  
reason your doing something (linking?) to the version of Python that  
comes with your mac (2.3). Look at this output that you posted:

> -I/System/Library/Frameworks/Python.framework/Versions/2.3/include/ 
> python2.3

Maybe you should do a: "python setups.py clean" and also remove your  
numpy build directory and start over.

I guess you also have to make sure that all of your python 2.4  
binaries come first (in terms of environment var/PATH) before the 2.3  
binaries.

Also .. one more thing, I also noticed that you didn't have any  
fortran compilers in your path, you can get gfortran like so:

$curl -O http://easynews.dl.sourceforge.net/sourceforge/hpc/gfortran- 
intel-bin.tar.gz
$ sudo tar -C / -xzf gfortran-intel-bin.tar.gz

and it'll put gfortran in your /usr/local/bin (I got that info from  
http://bmistudents.blogspot.com/2006/04/on-installation-of-proper- 
python.html)

-steve

Re: [Numpy-discussion] Numpy not working (revised)

[Travis O. <oli...@ie...>]

Satellite Data Research Group wrote:
> Dear all
>
> I am trying to get numpy working with MacOSX 10.4 on an intel 
> processor.  I had it working for Python2.3.5, but after installing 
> Python 2.4 it didn't work on either python version.
>
> After inputing:
> sudo python setup.py build
> and then
> sudo python setup.py install
>
> and also trying to load up a basic array, I get the following errors.
> The errors that I get repeatedly during the installation process seem 
> to mainly be (without showing you the entire massive output, unless you 
> need to see it):
>
>
> building extension "numpy.core.umath" sources
>   adding 'build/src.darwin-8.7.1-i386-2.3/numpy/core/config.h' to sources.
>   adding 'build/src.darwin-8.7.1-i386-2.3/numpy/core/__ufunc_api.h' to sources.
>   adding 'build/src.darwin-8.7.1-i386-2.3/numpy/core/src' to include_dirs.
> numpy.core - nothing done with h_files= 
> ['build/src.darwin-8.7.1-i386-2.3/numpy/core/config.h', 
> 'build/src.darwin-8.7.1-i386-2.3/numpy/core/__multiarray_api.h', 
> 'build/src.darwin-8.7.1-i386-2.3/numpy/core/__ufunc_api.h']
>
> building extension "numpy.core._dotblas" sources
>   adding 'numpy/core/blasdot/_dotblas.c' to sources.
> building extension "numpy.lib._compiled_base" sources
> building extension "numpy.dft.fftpack_lite" sources
> building extension "numpy.linalg.lapack_lite" sources
>   adding 'numpy/linalg/lapack_litemodule.c' to sources.
> building extension "numpy.random.mtrand" sources
> customize NAGFCompiler
> customize AbsoftFCompiler
> customize IbmFCompiler
> Could not locate executable g77
> Could not locate executable f77
> Could not locate executable gfortran
> Could not locate executable f95
>
> customize GnuFCompiler
> customize Gnu95FCompiler
> customize G95FCompiler
> customize GnuFCompiler
> customize Gnu95FCompiler
> customize NAGFCompiler
> customize NAGFCompiler using config
> gcc options: '-fno-strict-aliasing -Wno-long-double -no-cpp-precomp 
> -mno-fused-madd -fno-common -dynamic -DNDEBUG -g -O3 -Wall 
> -Wstrict-prototypes'
> compile options: '-Inumpy/core/src -Inumpy/core/include 
> -I/System/Library/Frameworks/Python.framework/Versions/2.3/include/python2.3 
> -c'
> gcc: _configtest.c
>
> _configtest.c:7:2: error: #error No _WIN32
> _configtest.c:7:2: error: #error No _WIN32
>
> The above lines of output are repeated a few times.  If it makes any 
> difference, which I am sure that it does, I am running on an intel chip.
>
>   
This is not a problem.  These are "configuration" "error" that the 
system uses to incorporate platform-specific code.


> In Python, when typing
>   
>>>> from numpy import *
>>>>         
> I get:
> Running from numpy source directory.
>
>   
This is the problem.   The error is telling you that you can't import 
numpy from the directory where numpy was built (the import mechanism 
gets confused between the system-installed numpy and the directory 
structure underneath).

Just exit Python and cd to another directory.   Then numpy should work 
fine.

-Travis

[Numpy-discussion] Numpy not working (revised)

[Satellite D. R. G. <sat...@po...>]

Dear all

I am trying to get numpy working with MacOSX 10.4 on an intel 
processor.  I had it working for Python2.3.5, but after installing 
Python 2.4 it didn't work on either python version.

After inputing:
sudo python setup.py build
and then
sudo python setup.py install

and also trying to load up a basic array, I get the following errors.
The errors that I get repeatedly during the installation process seem 
to mainly be (without showing you the entire massive output, unless you 
need to see it):


building extension "numpy.core.umath" sources
  adding 'build/src.darwin-8.7.1-i386-2.3/numpy/core/config.h' to sources.
  adding 'build/src.darwin-8.7.1-i386-2.3/numpy/core/__ufunc_api.h' to sources.
  adding 'build/src.darwin-8.7.1-i386-2.3/numpy/core/src' to include_dirs.
numpy.core - nothing done with h_files= 
['build/src.darwin-8.7.1-i386-2.3/numpy/core/config.h', 
'build/src.darwin-8.7.1-i386-2.3/numpy/core/__multiarray_api.h', 
'build/src.darwin-8.7.1-i386-2.3/numpy/core/__ufunc_api.h']

building extension "numpy.core._dotblas" sources
  adding 'numpy/core/blasdot/_dotblas.c' to sources.
building extension "numpy.lib._compiled_base" sources
building extension "numpy.dft.fftpack_lite" sources
building extension "numpy.linalg.lapack_lite" sources
  adding 'numpy/linalg/lapack_litemodule.c' to sources.
building extension "numpy.random.mtrand" sources
customize NAGFCompiler
customize AbsoftFCompiler
customize IbmFCompiler
Could not locate executable g77
Could not locate executable f77
Could not locate executable gfortran
Could not locate executable f95

customize GnuFCompiler
customize Gnu95FCompiler
customize G95FCompiler
customize GnuFCompiler
customize Gnu95FCompiler
customize NAGFCompiler
customize NAGFCompiler using config
gcc options: '-fno-strict-aliasing -Wno-long-double -no-cpp-precomp 
-mno-fused-madd -fno-common -dynamic -DNDEBUG -g -O3 -Wall 
-Wstrict-prototypes'
compile options: '-Inumpy/core/src -Inumpy/core/include 
-I/System/Library/Frameworks/Python.framework/Versions/2.3/include/python2.3 
-c'
gcc: _configtest.c

_configtest.c:7:2: error: #error No _WIN32
_configtest.c:7:2: error: #error No _WIN32

The above lines of output are repeated a few times.  If it makes any 
difference, which I am sure that it does, I am running on an intel chip.

In Python, when typing
>>> from numpy import *
I get:
Running from numpy source directory.

Then trying to make an array, I get:
>>> vector = array((2,3,4,5,6))
Traceback (most recent call last):
  File "<stdin>", line 1, in ?
NameError: name 'array' is not defined

This is in Python2.3.5.  However, my collegue had numpy working on 
Python2.3.5, with the exact same machine just now.  Just for background 
information, we are needing numpy to use pyhdf, to load and analyse hdf 
files.

Thank you so much for your help.

Sincerely

Stephen Johnston

p.s
my apologies for the multiple requests, this one just a revised version 
of my previous attempt at asking for help

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Re: [Numpy-discussion] PyObject arrays, pickling, tofile

[Travis O. <oli...@ie...>]

Tom Denniston wrote:
> It seems from my cursory look that numpy doesn't support the pickling
> or the tofile of PyObject arrays. 
Yes, you can pickle PyObject arrays, that is supposed to work.  What is 
not working? 

You can't use tofile on PyObject arrays, because I didn't have clear 
idea what to do.  Use Pickle for PyObject arrays.

-Travis

Re: [Numpy-discussion] Problems installing numpy0.9.8 on MacOSX (10.4)

[Tim L. <tim...@gm...>]

On 7/6/06, Satellite Data Research Group
<sat...@po...> wrote:
> Dear Sir/Madam
>
> I am trying to install numpy0.9.8 onto Mac version 10.4 and Python2.4
> and am having trouble doing so.  I had successfully installed
> inumpy0.9.8 on Python2.3, so am very confused as to why it is not
> working on Python2.4
>
> After typing 'python setup.py build' and then 'python setup.py install'
> from the terminal I get a host of errors, whereas with Python2.3 it
> worked perfectly.  Then in python typing 'from numpy import *' then
> trying something like 'array((range(10))' I get an error saying array
> cannot be found, whereas on Python2.3 this worked.
>

Hi Stephen,

Could you please post the exact error messages you get. Without these
it's not possible to diagnose your problem.

Cheers,

Tim.

> I was wondering if anyone else had trouble installing numpy on
> Python2.4 using Mac 10.4, and if anyone could help me rectify the
> problem.  Help would be greatly appreciated.
>
> Sincerely
>
> Stephen Johnston
>
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>
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[Numpy-discussion] Problems installing numpy0.9.8 on MacOSX (10.4)

[Satellite D. R. G. <sat...@po...>]

Dear Sir/Madam

I am trying to install numpy0.9.8 onto Mac version 10.4 and Python2.4 
and am having trouble doing so.  I had successfully installed 
inumpy0.9.8 on Python2.3, so am very confused as to why it is not 
working on Python2.4

After typing 'python setup.py build' and then 'python setup.py install' 
from the terminal I get a host of errors, whereas with Python2.3 it 
worked perfectly.  Then in python typing 'from numpy import *' then 
trying something like 'array((range(10))' I get an error saying array 
cannot be found, whereas on Python2.3 this worked.

I was wondering if anyone else had trouble installing numpy on 
Python2.4 using Mac 10.4, and if anyone could help me rectify the 
problem.  Help would be greatly appreciated.

Sincerely

Stephen Johnston

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[Numpy-discussion] Determining if two arrays share data

[Bill B. <wb...@gm...>]

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 with a little function like this:

def same_base(a,b):
    ab = a.base
    if ab is None: ab = a
    bb = b.base
    if bb is None: bb = b
    return ab is bb

is there some easier built-in way?  Does the above function even cover all
the bases? (so to speak...)

It would be easier if a non-copy array pointed to itself as base rather than
'None'.  Then you could just check a.base == b.base.

--bb

Re: [Numpy-discussion] simple question

[Bill B. <wb...@gm...>]

That's the kind of thing that should maybe be on the NumpyExample list:
http://www.scipy.org/Numpy_Example_List
But currently little syntactical tricks like that aren't listed there.   I'm
not sure how you'd list that even.

There is an example like that ( a[a<0.5]=0 ) on the Numpy for Matlab Users
page, though.   http://www.scipy.org/NumPy_for_Matlab_Users
It's supposed to be for matlab users, but if you just ignore the Matlab
column, the main table there is still a pretty good list of examples of
numpy syntax and basic functions.

--bb

On 7/6/06, Mathew Yeates <my...@jp...> wrote:
>
> ohhhh. I was looking at using "where"
>
>
>
> Keith Goodman wrote:
> > On 7/5/06, Mathew Yeates <my...@jp...> wrote:
> >> What is the typical way of doing the following
> >> starting with a 0 matrix, set all values to 1 when a certain condition
> >> is met, set to -1 when another condition is met, left alone if neither
> >> condition is met.
> >
> > This works on recent versions of numpy:
> >
> >>> x = asmatrix(zeros((2,2)))
> >
> >>> x
> >
> > matrix([[0, 0],
> >       [0, 0]])
> >
> >>> y = asmatrix(rand(2,2))
> >
> >>> y
> >
> > matrix([[ 0.85219404,  0.48311427],
> >       [ 0.41026966,  0.2184193 ]])
> >
> >>> x[y > 0.5] = 1
> >
> >>> x[y < 0.5] = -1
> >
> >>> x
> >
> > matrix([[ 1, -1],
> >       [-1, -1]])
> >
>
>
> Using Tomcat but need to do more? Need to support web services, security?
> Get stuff done quickly with pre-integrated technology to make your job
> easier
> Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo
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> _______________________________________________
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>



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OLM Digital
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Tokyo, Japan  154-0023
+81 (3) 3422-3380

[Numpy-discussion] PyObject arrays, pickling, tofile

[Tom D. <tom...@al...>]

It seems from my cursory look that numpy doesn't support the pickling
or the tofile of PyObject arrays.  I was wondering whether such
functionlity is in the pipeline or if there is little interest.
Personally, I would really like to see the feature in numpy but don't
know if I am up to implementing it myself.

--Tom

Re: [Numpy-discussion] A C++ library and the new array interface: the best approach?

[Philip A. <pa...@eo...>]

Travis Oliphant writes:

 > b) byte-the bullet and use Boost python (which other's who have 
 > integrated C++ code with Python seem to really like).  I've never 
 > wrapped my mind around Boost python, though, so I'm not much help there.

I've updated my set of boost helper functions to work with
numpy -- there's a Readme at:

http://www.eos.ubc.ca/research/clouds/software/pythonlibs/num_util/num_util_release2
(http://tinyurl.com/eo6fe)

A simple example which shows some of the boost python features (reference
counting, C++ versions of python types, docstrings, exceptions)
is appended below.  When called with python script http://tinyurl.com/zy57a it
produces the output  http://tinyurl.com/fr7xo

Regards, Phil Austin

Re: [Numpy-discussion] simple question

[Mathew Y. <my...@jp...>]

ohhhh. I was looking at using "where"



Keith Goodman wrote:
> On 7/5/06, Mathew Yeates <my...@jp...> wrote:
>> What is the typical way of doing the following
>> starting with a 0 matrix, set all values to 1 when a certain condition
>> is met, set to -1 when another condition is met, left alone if neither
>> condition is met.
>
> This works on recent versions of numpy:
>
>>> x = asmatrix(zeros((2,2)))
>
>>> x
>
> matrix([[0, 0],
>       [0, 0]])
>
>>> y = asmatrix(rand(2,2))
>
>>> y
>
> matrix([[ 0.85219404,  0.48311427],
>       [ 0.41026966,  0.2184193 ]])
>
>>> x[y > 0.5] = 1
>
>>> x[y < 0.5] = -1
>
>>> x
>
> matrix([[ 1, -1],
>       [-1, -1]])
>

Re: [Numpy-discussion] tentative numpy tutorial

[Steve L. <lis...@ar...>]

>> motivated by the lack of free documentation for NumPy, with some
>> friends, we started writing a tutorial, that we would like to see in
>> scipy.org. After some time, the project have started to loose its
>> initial impetus. Now, we put the current unfinished version in
>>
>> http://www.scipy.org/Tentative_NumPy_Tutorial
>>
>> with the hope that, with the help of other users, it will be possible
>> to build a useful document for beginners.
>
> I think it looks great.


Agreed .. thanks for whipping that together!

-steve

Re: [Numpy-discussion] simple question

[Keith G. <kwg...@gm...>]

On 7/5/06, Mathew Yeates <my...@jp...> wrote:
> What is the typical way of doing the following
> starting with a 0 matrix, set all values to 1 when a certain condition
> is met, set to -1 when another condition is met, left alone if neither
> condition is met.

This works on recent versions of numpy:

>> x = asmatrix(zeros((2,2)))

>> x

matrix([[0, 0],
       [0, 0]])

>> y = asmatrix(rand(2,2))

>> y

matrix([[ 0.85219404,  0.48311427],
       [ 0.41026966,  0.2184193 ]])

>> x[y > 0.5] = 1

>> x[y < 0.5] = -1

>> x

matrix([[ 1, -1],
       [-1, -1]])

[Numpy-discussion] simple question

[Mathew Y. <my...@jp...>]

What is the typical way of doing the following
starting with a 0 matrix, set all values to 1 when a certain condition 
is met, set to -1 when another condition is met, left alone if neither 
condition is met.

Mathew

Re: [Numpy-discussion] tentative numpy tutorial

[Keith G. <kwg...@gm...>]

On 7/4/06, Pau Gargallo <pau...@gm...> wrote:

> motivated by the lack of free documentation for NumPy, with some
> friends, we started writing a tutorial, that we would like to see in
> scipy.org. After some time, the project have started to loose its
> initial impetus. Now, we put the current unfinished version in
>
> http://www.scipy.org/Tentative_NumPy_Tutorial
>
> with the hope that, with the help of other users, it will be possible
> to build a useful document for beginners.

I think it looks great.

[Numpy-discussion] ANN: Python Enthought Edition Version 1.0.0.beta3 Released

[Bryce H. <bhe...@en...>]

Enthought is pleased to announce the release of Python Enthought Edition 
Version 1.0.0.beta3 (http://code.enthought.com/enthon/) -- a python 
distribution for Windows.

1.0.0.beta3 Release Notes:
--------------------
Version 1.0.0.beta3 of Python Enthought Edition is the first version 
based on Python 2.4.3 and includes updates to nearly every package. This 
is the third and (hopefully) last beta release.

This release includes version 1.0.8 of the Enthought Tool Suite (ETS) 
Package and bug fixes-- you can look at the release notes for this ETS 
version here:

http://svn.enthought.com/downloads/enthought/changelog-release.1.0.8.html



About Python Enthought Edition:
-------------------------------
Python 2.4.3, Enthought Edition is a kitchen-sink-included Python 
distribution for Windows including the following packages out of the box:

Numeric
SciPy
IPython
Enthought Tool Suite
wxPython
PIL
mingw
f2py
MayaVi
Scientific Python
VTK
and many more...

More information is available about all Open Source code written and 
released by Enthought, Inc. at http://code.enthought.com

Re: [Numpy-discussion] Dot as a method

[Tim H. <tim...@co...>]

Bart Vandereycken wrote:
> Hi all,
>
> reading the thread "Ransom proposals" I was wondering why there isn't a 
> ndarray.dot() method?  There is already a scipy.sparse.dot() so this 
> would fit nicely in the whole idea of polymorphism.
>   
Are you sure about that?

The problem with a dot method (aside from a over proliferation of 
methods in general) is that to be done correctly you want to choose a 
particular implementation of dot based *both* of its arguments. A method 
does a good job dispatching on a single argument, but falls down when 
dispatching on two types. Let's look at this specific case. Imagine that 
in addition ndarray.dot and sparse.dot, we also stick a dot method on 
ma.masked, etc. Now in order to fully exploit polymorphism and get 
maximum efficiency, we want asparsearray.dot(amaskedarray) to correctly 
treat the masked values (ma.dot treats them as zeros) and to not 
instantiate a dense version of the sparsearray. But in order to do that 
all three classes need to know about the other two. That's possible, if 
messy since all three of these are known in advance, but this approach 
becomes untenable if you classes outside core numpy or scipy to 
participate as full citizens.

What does appear fit well here is generic functions / multimethods / 
protocols as discussed in some detail on pydev-3000 a couple of months 
ago. This would allow classes defined outside of core numpy and scipy to 
work correctly and efficiently with dot as long as they register 
appropriate versions of dot. If I wasn't swamped right at the moment I'd 
prototype this up and see how it works in practice.

-tim

Re: [Numpy-discussion] (no subject)

[Robert K. <rob...@gm...>]

Fer...@eu... wrote:
> 
> Hi,
> 
> how could i get the name of an array in a string ?
> (info command ?!)

You can't.

http://mail.python.org/pipermail/python-list/2005-June/286574.html

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless enigma
  that is made terrible by our own mad attempt to interpret it as though it had
  an underlying truth."
   -- Umberto Eco

Re: [Numpy-discussion] (no subject)

[Alexandre F. <ale...@lo...>]

On Wed, Jul 05, 2006 at 02:51:36PM +0200, ferenc pintye wrote:
> Hi,
>=20
> how could i get the name of an array in a string ?

if by this you mean "the name of an identifier refering to [whatever]",
this is a FAQ, and the answer is

1. you don't want to do that
2. your problem is not well behaved (there can be many answers to the
questions)
3. you can use something along the lines of

for name, item in locals().iteritems():
    if item is my_array:
        break
else:
    name =3D "anonymous object"

--=20
Alexandre Fayolle                              LOGILAB, Paris (France)
Formations Python, Zope, Plone, Debian:  http://www.logilab.fr/formations
D=E9veloppement logiciel sur mesure:       http://www.logilab.fr/services
Informatique scientifique:               http://www.logilab.fr/science

[Numpy-discussion] (no subject)

[ferenc p. <fer...@st...>]

Hi,

how could i get the name of an array in a string ?
thanks
f.