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

[Numpy-discussion] numpy1.0rc and matplotlib-0.87.5

[Peter B. <Pet...@ug...>]

Hi,

Not sure if this is a numpy or a matplotlib issue, but I can't seem to get=
=20
matplotlib-0.87.5  to work with numpy1.0rc:

Python 2.4.3 (#1, Sep 21 2006, 13:06:42)
[GCC 4.1.1 (Gentoo 4.1.1)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> from pylab import *
Traceback (most recent call last):
  File "<stdin>", line 1, in ?
  File "/usr/lib64/python2.4/site-packages/pylab.py", line 1, in ?
    from matplotlib.pylab import *
  File "/usr/lib/python2.4/site-packages/matplotlib/pylab.py", line 196, in=
 ?
    import cm
  File "/usr/lib/python2.4/site-packages/matplotlib/cm.py", line 5, in ?
    import colors
  File "/usr/lib/python2.4/site-packages/matplotlib/colors.py", line 33, in=
 ?
    from numerix import array, arange, take, put, Float, Int, where, \
  File "/usr/lib/python2.4/site-packages/matplotlib/numerix/__init__.py", l=
ine=20
74, in ?
    Matrix =3D matrix
NameError: name 'matrix' is not defined

This is on an AMD64 platform. I tried removing the build directories of bot=
h=20
packages, and reinstalling, but that didn't work.

I also posted this to the matplotlib list, but got no reply.

Thanks!

Peter

Re: [Numpy-discussion] Numpy RC1 build blows up -- IGNORE

[<lis...@ma...>]

Ignore this query -- silly mistake on my part. Sorry.

On Sep 25, 2006, at 2:30 PM, lis...@ma... wrote:

> I've just tried building RC1 on OSX 10.4 (Intel), and it fails  
> almost immediately. This did not fail in the past with beta5 or  
> from SVN:
>
> Osoyoos:~/Development/numpy-1.0rc1 chris$ python setup.py build
> Running from numpy source directory.
> F2PY Version 2_3198
> blas_opt_info:
>   FOUND:
>     extra_link_args = ['-Wl,-framework', '-Wl,Accelerate']
>     define_macros = [('NO_ATLAS_INFO', 3)]
>     extra_compile_args = ['-msse3', '-I/System/Library/Frameworks/ 
> vecLib.framework/Headers']
>
> lapack_opt_info:
>   FOUND:
>     extra_link_args = ['-Wl,-framework', '-Wl,Accelerate']
>     define_macros = [('NO_ATLAS_INFO', 3)]
>     extra_compile_args = ['-msse3']
>
> running build
> running config_fc
> running build_src
> building py_modules sources
> creating build
> creating build/src.darwin-8.7.1-i386-2.4
> creating build/src.darwin-8.7.1-i386-2.4/numpy
> creating build/src.darwin-8.7.1-i386-2.4/numpy/distutils
> building extension "numpy.core.multiarray" sources
> creating build/src.darwin-8.7.1-i386-2.4/numpy/core
> Generating build/src.darwin-8.7.1-i386-2.4/numpy/core/config.h
> customize NAGFCompiler
> customize AbsoftFCompiler
> customize IbmFCompiler
> Could not locate executable g77
> Could not locate executable f77
> Could not locate executable f95
> customize GnuFCompiler
> customize Gnu95FCompiler
> customize Gnu95FCompiler
> customize Gnu95FCompiler using config
> C compiler: gcc -fno-strict-aliasing -Wno-long-double -no-cpp- 
> precomp -mno-fused-madd -fPIC -fno-common -dynamic -DNDEBUG -g -O3 - 
> Wall -Wstrict-prototypes
>
> compile options: '-I/Library/Frameworks/Python.framework/Versions/ 
> 2.4/include/python2.4 -Inumpy/core/src -Inumpy/core/include -I/ 
> Library/Frameworks/Python.framework/Versions/2.4/include/python2.4 -c'
> gcc: _configtest.c
> gcc: installation problem, cannot exec `cc1': No such file or  
> directory
> gcc: installation problem, cannot exec `cc1': No such file or  
> directory
> failure.
> removing: _configtest.c _configtest.o
> Traceback (most recent call last):
>   File "setup.py", line 89, in ?
>     setup_package()
>   File "setup.py", line 82, in setup_package
>     configuration=configuration )
>   File "/Users/chris/Development/numpy-1.0rc1/numpy/distutils/ 
> core.py", line 174, in setup
>     return old_setup(**new_attr)
>   File "/Library/Frameworks/Python.framework/Versions/2.4/lib/ 
> python2.4/distutils/core.py", line 149, in setup
>     dist.run_commands()
>   File "/Library/Frameworks/Python.framework/Versions/2.4/lib/ 
> python2.4/distutils/dist.py", line 946, in run_commands
>     self.run_command(cmd)
>   File "/Library/Frameworks/Python.framework/Versions/2.4/lib/ 
> python2.4/distutils/dist.py", line 966, in run_command
>     cmd_obj.run()
>   File "/Library/Frameworks/Python.framework/Versions/2.4/lib/ 
> python2.4/distutils/command/build.py", line 112, in run
>     self.run_command(cmd_name)
>   File "/Library/Frameworks/Python.framework/Versions/2.4/lib/ 
> python2.4/distutils/cmd.py", line 333, in run_command
>     self.distribution.run_command(command)
>   File "/Library/Frameworks/Python.framework/Versions/2.4/lib/ 
> python2.4/distutils/dist.py", line 966, in run_command
>     cmd_obj.run()
>   File "/Users/chris/Development/numpy-1.0rc1/numpy/distutils/ 
> command/build_src.py", line 87, in run
>     self.build_sources()
>   File "/Users/chris/Development/numpy-1.0rc1/numpy/distutils/ 
> command/build_src.py", line 106, in build_sources
>     self.build_extension_sources(ext)
>   File "/Users/chris/Development/numpy-1.0rc1/numpy/distutils/ 
> command/build_src.py", line 212, in build_extension_sources
>     sources = self.generate_sources(sources, ext)
>   File "/Users/chris/Development/numpy-1.0rc1/numpy/distutils/ 
> command/build_src.py", line 270, in generate_sources
>     source = func(extension, build_dir)
>   File "numpy/core/setup.py", line 50, in generate_config_h
>     raise "ERROR: Failed to test configuration"
> ERROR: Failed to test configuration
>
> --
> Christopher Fonnesbeck
> + Atlanta, GA
> + fonnesbeck at mac.com
> + Contact me on AOL IM using email address
>
>

--
Christopher Fonnesbeck
+ Atlanta, GA
+ fonnesbeck at mac.com
+ Contact me on AOL IM using email address

Re: [Numpy-discussion] Numpy RC1 build blows up

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

lis...@ma... wrote:
> I've just tried building RC1 on OSX 10.4 (Intel), and it fails almost  
> immediately. This did not fail in the past with beta5 or from SVN:

It looks like a problem on your end:

> gcc: installation problem, cannot exec `cc1': No such file or directory

Can you build anything else with gcc?

-- 
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

[Numpy-discussion] Numpy RC1 build blows up

[<lis...@ma...>]

I've just tried building RC1 on OSX 10.4 (Intel), and it fails almost  
immediately. This did not fail in the past with beta5 or from SVN:

Osoyoos:~/Development/numpy-1.0rc1 chris$ python setup.py build
Running from numpy source directory.
F2PY Version 2_3198
blas_opt_info:
   FOUND:
     extra_link_args = ['-Wl,-framework', '-Wl,Accelerate']
     define_macros = [('NO_ATLAS_INFO', 3)]
     extra_compile_args = ['-msse3', '-I/System/Library/Frameworks/ 
vecLib.framework/Headers']

lapack_opt_info:
   FOUND:
     extra_link_args = ['-Wl,-framework', '-Wl,Accelerate']
     define_macros = [('NO_ATLAS_INFO', 3)]
     extra_compile_args = ['-msse3']

running build
running config_fc
running build_src
building py_modules sources
creating build
creating build/src.darwin-8.7.1-i386-2.4
creating build/src.darwin-8.7.1-i386-2.4/numpy
creating build/src.darwin-8.7.1-i386-2.4/numpy/distutils
building extension "numpy.core.multiarray" sources
creating build/src.darwin-8.7.1-i386-2.4/numpy/core
Generating build/src.darwin-8.7.1-i386-2.4/numpy/core/config.h
customize NAGFCompiler
customize AbsoftFCompiler
customize IbmFCompiler
Could not locate executable g77
Could not locate executable f77
Could not locate executable f95
customize GnuFCompiler
customize Gnu95FCompiler
customize Gnu95FCompiler
customize Gnu95FCompiler using config
C compiler: gcc -fno-strict-aliasing -Wno-long-double -no-cpp-precomp  
-mno-fused-madd -fPIC -fno-common -dynamic -DNDEBUG -g -O3 -Wall - 
Wstrict-prototypes

compile options: '-I/Library/Frameworks/Python.framework/Versions/2.4/ 
include/python2.4 -Inumpy/core/src -Inumpy/core/include -I/Library/ 
Frameworks/Python.framework/Versions/2.4/include/python2.4 -c'
gcc: _configtest.c
gcc: installation problem, cannot exec `cc1': No such file or directory
gcc: installation problem, cannot exec `cc1': No such file or directory
failure.
removing: _configtest.c _configtest.o
Traceback (most recent call last):
   File "setup.py", line 89, in ?
     setup_package()
   File "setup.py", line 82, in setup_package
     configuration=configuration )
   File "/Users/chris/Development/numpy-1.0rc1/numpy/distutils/ 
core.py", line 174, in setup
     return old_setup(**new_attr)
   File "/Library/Frameworks/Python.framework/Versions/2.4/lib/ 
python2.4/distutils/core.py", line 149, in setup
     dist.run_commands()
   File "/Library/Frameworks/Python.framework/Versions/2.4/lib/ 
python2.4/distutils/dist.py", line 946, in run_commands
     self.run_command(cmd)
   File "/Library/Frameworks/Python.framework/Versions/2.4/lib/ 
python2.4/distutils/dist.py", line 966, in run_command
     cmd_obj.run()
   File "/Library/Frameworks/Python.framework/Versions/2.4/lib/ 
python2.4/distutils/command/build.py", line 112, in run
     self.run_command(cmd_name)
   File "/Library/Frameworks/Python.framework/Versions/2.4/lib/ 
python2.4/distutils/cmd.py", line 333, in run_command
     self.distribution.run_command(command)
   File "/Library/Frameworks/Python.framework/Versions/2.4/lib/ 
python2.4/distutils/dist.py", line 966, in run_command
     cmd_obj.run()
   File "/Users/chris/Development/numpy-1.0rc1/numpy/distutils/ 
command/build_src.py", line 87, in run
     self.build_sources()
   File "/Users/chris/Development/numpy-1.0rc1/numpy/distutils/ 
command/build_src.py", line 106, in build_sources
     self.build_extension_sources(ext)
   File "/Users/chris/Development/numpy-1.0rc1/numpy/distutils/ 
command/build_src.py", line 212, in build_extension_sources
     sources = self.generate_sources(sources, ext)
   File "/Users/chris/Development/numpy-1.0rc1/numpy/distutils/ 
command/build_src.py", line 270, in generate_sources
     source = func(extension, build_dir)
   File "numpy/core/setup.py", line 50, in generate_config_h
     raise "ERROR: Failed to test configuration"
ERROR: Failed to test configuration

--
Christopher Fonnesbeck
+ Atlanta, GA
+ fonnesbeck at mac.com
+ Contact me on AOL IM using email address

Re: [Numpy-discussion] NumPy types --> Numeric typecodes map?

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

Francesc Altet wrote:

>El dl 25 de 09 del 2006 a les 11:08 -0600, en/na Travis Oliphant va
>escriure:
>  
>
>>Francesc Altet wrote:
>>
>>    
>>
>>>Hi,
>>>
>>>Anybody know if there is a map between NumPy types and Numeric
>>>typecodes? Something like 'typecodes' for numarray:
>>>      
>>>

Oh, you mean actual Numeric typecodes, not Numeric-like typecodes :-)

dtype(obj).char will not work for the Numeric typecodes that changed, 
set up a dictionary-like object which uses dtype(obj).char on all but 
the ones that changed is my suggestion.   See the core/numerictypes.py 
module for dictionary-like objects.   Perhaps this would be a good thing 
to add to numpy/oldnumeric


'b' --> 'B'
'1' --> 'b'
's' --> 'h'
'w' --> 'H'
'u' --> 'I'


-Travis

Re: [Numpy-discussion] NumPy types --> Numeric typecodes map?

[Francesc A. <fa...@ca...>]

El dl 25 de 09 del 2006 a les 11:08 -0600, en/na Travis Oliphant va
escriure:
> Francesc Altet wrote:
>=20
> >Hi,
> >
> >Anybody know if there is a map between NumPy types and Numeric
> >typecodes? Something like 'typecodes' for numarray:
> > =20
> >
> How about
>=20
> dtype(obj).char?

This doesn't work for many types:

>>> Numeric.array([1], typecode=3Dnumpy.dtype('int32').char)
array([1])

this is fine, but:

>>> Numeric.array([1], typecode=3Dnumpy.dtype('int16').char)
Traceback (most recent call last):
  File "<stdin>", line 1, in ?
TypeError: typecode argument must be a valid type.
>>> Numeric.array([1], typecode=3Dnumpy.dtype('int64').char)
Traceback (most recent call last):
  File "<stdin>", line 1, in ?
TypeError: typecode argument must be a valid type.


Anyway, this is not very important as I can do my own map internally.

Thanks,

--=20
>0,0<   Francesc Altet     http://www.carabos.com/
V   V   C=C3=A1rabos Coop. V.   Enjoy Data
 "-"

Re: [Numpy-discussion] NumPy types --> Numeric typecodes map?

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

Francesc Altet wrote:

>Hi,
>
>Anybody know if there is a map between NumPy types and Numeric
>typecodes? Something like 'typecodes' for numarray:
>  
>
How about

dtype(obj).char?

-Travis

[Numpy-discussion] NumPy types --> Numeric typecodes map?

[Francesc A. <fa...@ca...>]

Hi,

Anybody know if there is a map between NumPy types and Numeric
typecodes? Something like 'typecodes' for numarray:

>>> numarray.typecode
{'UInt64': 'U', 'Int32': 'i', 'Int16': 's', 'Float64': 'd', 'Object':
'O', 'UInt8': 'b', 'UInt32': 'u', 'Complex64': 'D', 'UInt16': 'w',
'Bool': 'B', 'Complex32': 'F', 'Int64': 'N', 'Int8': '1', 'Float32':
'f'}

Thanks,

--=20
>0,0<   Francesc Altet     http://www.carabos.com/
V   V   C=C3=A1rabos Coop. V.   Enjoy Data
 "-"

Re: [Numpy-discussion] please restore the way dtype prints to original version

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

Christopher Hanley wrote:
> Hi,
>
> Change set 3213 changed the data type printing with an array from 
> something like dtype=int64 to dtype='int64'.  Although this is a small 
> cosmetic change it has broken all of the doctests I have written for 
> numpy code. 
I was changing the way dtypes print and this was an unexpected 
consequence.   It has been restored.  Please try r3215

-Travis

[Numpy-discussion] Negative division and numpy scalars

[Francesc A. <fa...@ca...>]

Hi,

I have been bitten by a subtlety in numpy scalar divisions. The next
exposes the issue:

>>> -1/20
-1
>>> Numeric.array([-1])[0] / Numeric.array([20])[0]
-1
>>> numarray.array([-1])[0] / numarray.array([20])[0]
-1
>>> numpy.array([-1])[0] / numpy.array([20])[0]
0

After some digging, I've found that Python and C follow different
conventions for doing this negative division: Python do a floor of the
result, while C truncates it. As numpy scalar operations seems to be
implemented in C, it seems that it follows the C convention and
truncates the result.

In fact, I like this behaviour of NumPy scalars (at least, when I'm
aware of it!), but I thought it would be nice to warn other people about
that.

Cheers,

--=20
>0,0<   Francesc Altet     http://www.carabos.com/
V   V   C=C3=A1rabos Coop. V.   Enjoy Data
 "-"

[Numpy-discussion] Downcasting to smallest storage

[Matthew B. <mat...@gm...>]

Hi,

I am sorry if I have missed anything obvious here, but is there a fast
simple way to downcast an array to the smallest storage that hold
array data within a specified precision  - e.g.

a = array([1.0])
small_a = fantasy_function(a, rtol=1.0000000000000001e-05, atol=1e-08 )
b = array([1.2])
small_b = fantasy_function(b, tol=1.0000000000000001e-05, atol=1e-08)

where a.dtype becomes, say, uint8, and b.dtype becomes float32?

Thanks a lot,

Matthew

Re: [Numpy-discussion] =?iso-2022-jp?b?GyRCTDVOQRsoQg==?=

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[Numpy-discussion] please restore the way dtype prints to original version

[Christopher H. <ch...@st...>]

Hi,

Change set 3213 changed the data type printing with an array from 
something like dtype=int64 to dtype='int64'.  Although this is a small 
cosmetic change it has broken all of the doctests I have written for 
numpy code.  I expect that I am not the only person this change has 
caught.  Please restore the previous behavior until after the 1.0 
release at least.

Thank you,

Chris

[Numpy-discussion] Fixes to numexpr string support

[Ivan V. i B. <iv...@ca...>]

Hi all, these are just a couple of small fixes to the string support in
Numexpr, and a test case for the string copy operation.

For the base patches:

1.http://www.mail-archive.com/num...@li.../msg01551.html
2.http://www.mail-archive.com/num...@li.../msg02261.html

Cheers,

::

	Ivan Vilata i Balaguer   >qo<   http://www.carabos.com/
	       Cárabos Coop. V.  V  V   Enjoy Data
	                          ""

Re: [Numpy-discussion] eval shortcomings?

[A. M. A. <per...@gm...>]

On 25/09/06, Angus McMorland <am...@gm...> wrote:
> Hi all,
>
> Can someone explain why the following occurs?
>
> a = numpy.zeros((100))
> b = numpy.ones((10))
> a[20:30] = b                    # okay
> eval('a[50:60] = b')         # raises SyntaxError: invalid syntax
>
> Is there some line mangling that the interpretor does that eval doesn't do?

No. Eval evaluates expressions, that is, formulas producing a value.
"a=b" does not produce a value, so you are obtaining the same error
you would if you'd written

if a=b:
   ...

The way you run code that doesn't return a value is with "exec".

A. M. Archibald

[Numpy-discussion] eval shortcomings?

[Angus M. <am...@gm...>]

Hi all,

Can someone explain why the following occurs?

a = numpy.zeros((100))
b = numpy.ones((10))
a[20:30] = b                    # okay
eval('a[50:60] = b')         # raises SyntaxError: invalid syntax

Is there some line mangling that the interpretor does that eval doesn't do?

I see there's room for global and local parameters to eval. Would setting
one of those be the answer?

Cheers,

Angus.
-- 
AJC McMorland, PhD Student
Physiology, University of Auckland
Armourer, Auckland University Fencing
Secretary, Fencing North Inc.

Re: [Numpy-discussion] Shift or rotate command?

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

Hmm.  Yes maybe a shift w/fill would be useful too.  I can't recall
needing such a thing, but it could probably also be implemented easily
in a way similar to roll() above.  A multi-axis roll might also be
nice.  Could just allow roll's shiftby and axis args to be tuples.

Looking closer at the existing 'rollaxis',
   numpy.rollaxis(a, axis, start=0)
   if a.shape is (3,4,5,6)
   rollaxis(a, 3, 1).shape is (3,6,4,5)
   rollaxis(a, 2, 0).shape is (5,3,4,6)
   rollaxis(a, 1, 3).shape is (3,5,4,6)
   rollaxis(a, 1, 4).shape is (3,5,6,4)

it occurs to me that what it is actually doing is not what we've been
calling 'rolling'.  It's just a move, really (remove value from one
place and re-insert in another).  So perhaps the name should be
'moveaxis' instead?

--bb


On 9/25/06, Alan G Isaac <ai...@am...> wrote:
> On Mon, 25 Sep 2006, Bill Baxter apparently wrote:
> > Went ahead and added an enhancement request:
> > http://projects.scipy.org/scipy/numpy/ticket/293
> > This is something I've wanted in the past too.
>
>
> GAUSS draws a useful distinction between "shifting" and
> "rotating":
>
> Works roughly like this for the 2D case:
>
> #rotater: rotate row elements
> # Format:    y = rotater(x,r)
> #            rotater(x,r)
> # Input:     x           RxK array
> #            rotateby    size R integer array, or integer (rotation amounts)
> # Output:    y           RxK array:
> #                          rows rotated by rotateby
>
> #shiftr: shift row elements and fill with fv
> # Format:    y = shiftr(x,shiftby,fv)
> # Input:     x        RxC array
> #            shiftby  Rx1 array or scalar (shift amounts)
> #            fv       Rx1 array or scalar (fill values)
> # Output:    y        RxC array:
> #                       rows shifted by shiftby
> #                       rows filled with fill
>
> fwiw,
> Alan Isaac

Re: [Numpy-discussion] Shift or rotate command?

[Alan G I. <ai...@am...>]

On Mon, 25 Sep 2006, Bill Baxter apparently wrote: 
> Went ahead and added an enhancement request: 
> http://projects.scipy.org/scipy/numpy/ticket/293 
> This is something I've wanted in the past too. 


GAUSS draws a useful distinction between "shifting" and 
"rotating":

Works roughly like this for the 2D case:

#rotater: rotate row elements
# Format:    y = rotater(x,r)
#            rotater(x,r)
# Input:     x           RxK array
#            rotateby    size R integer array, or integer (rotation amounts)
# Output:    y           RxK array:
#                          rows rotated by rotateby

#shiftr: shift row elements and fill with fv
# Format:    y = shiftr(x,shiftby,fv)
# Input:     x        RxC array
#            shiftby  Rx1 array or scalar (shift amounts)
#            fv       Rx1 array or scalar (fill values)
# Output:    y        RxC array:
#                       rows shifted by shiftby
#                       rows filled with fill

fwiw,
Alan Isaac

Re: [Numpy-discussion] Shift or rotate command?

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

Went ahead and added an enhancement request:
http://projects.scipy.org/scipy/numpy/ticket/293

This is something I've wanted in the past too.

--bb

On 9/25/06, Charles R Harris <cha...@gm...> wrote:
>
>
> On 9/24/06, Bill Baxter <wb...@gm...> wrote:
> > Howdy Angus,
> > Yeh, that does seem like a hole in the API.  Travis added a rollaxis()
> > but there's still no simple way to roll the elements themselves.
> >
> > I took a look at numpy.fft.fftshift, which is a function that has to
> > do a similar thing.  It does it by concatenating aranges and then
> > doing a take().  Presumably Pearu knew what he was doing when he wrote
> > that, so we can assume this is probably close to the best possible.
> > :-)  From that idea here's a function that implements roll().
> >
> > def roll(y,shift,axis):
> >     """Roll the elements in the array by 'shift' positions along the
> > given axis."""
> >     from numpy import asanyarray,concatenate,arange
> >     y = asanyarray(y)
> >     n = y.shape[axis]
> >     shift %= n # does the right thing for negative shifts, too
> >     return
> y.take(concatenate((arange(shift,n),arange(shift))), axis)
>
> It is possible to do a shift inplace using two reflections implemented with
> swaps.  This works because two reflections is the same as a rotating twice
> the distance between the centers of the reflections. I don't know if it is
> worth implementing this, however.
>
> Chuck

Re: [Numpy-discussion] Shift or rotate command?

[Charles R H. <cha...@gm...>]

On 9/24/06, Bill Baxter <wb...@gm...> wrote:
>
> Howdy Angus,
> Yeh, that does seem like a hole in the API.  Travis added a rollaxis()
> but there's still no simple way to roll the elements themselves.
>
> I took a look at numpy.fft.fftshift, which is a function that has to
> do a similar thing.  It does it by concatenating aranges and then
> doing a take().  Presumably Pearu knew what he was doing when he wrote
> that, so we can assume this is probably close to the best possible.
> :-)  From that idea here's a function that implements roll().
>
> def roll(y,shift,axis):
>     """Roll the elements in the array by 'shift' positions along the
> given axis."""
>     from numpy import asanyarray,concatenate,arange
>     y = asanyarray(y)
>     n = y.shape[axis]
>     shift %= n # does the right thing for negative shifts, too
>     return y.take(concatenate((arange(shift,n),arange(shift))), axis)


It is possible to do a shift inplace using two reflections implemented with
swaps.  This works because two reflections is the same as a rotating twice
the distance between the centers of the reflections. I don't know if it is
worth implementing this, however.

Chuck

Re: [Numpy-discussion] Shift or rotate command?

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

Howdy Angus,
Yeh, that does seem like a hole in the API.  Travis added a rollaxis()
but there's still no simple way to roll the elements themselves.

I took a look at numpy.fft.fftshift, which is a function that has to
do a similar thing.  It does it by concatenating aranges and then
doing a take().  Presumably Pearu knew what he was doing when he wrote
that, so we can assume this is probably close to the best possible.
:-)  From that idea here's a function that implements roll().

def roll(y,shift,axis):
    """Roll the elements in the array by 'shift' positions along the
given axis."""
    from numpy import asanyarray,concatenate,arange
    y = asanyarray(y)
    n = y.shape[axis]
    shift %= n # does the right thing for negative shifts, too
    return y.take(concatenate((arange(shift,n),arange(shift))), axis)

Performance is only very slightly worse (<1%) using
    return y.take(r_[shift:n, :shift], axis)
as the last line, which is maybe slightly more readable if you're down
wit' the r_.

I prefer the name 'roll' because:
a) there's already rollaxis with conceptually similar behavior and
b) 'shift' is used in other languages (perl comes to mind) sometimes
to indicate shifting off the end, possibly filling in with zeros or
just leaving the array shorter.
c) 'rotate' seems potentially confusing given the existence of the
'rot90' function already.

--bb


On 9/25/06, Angus McMorland <am...@gm...> wrote:
> Hi all,
>
> Other data languages that I have worked with have a routine for shifting
> data along axes, with wrapping.
> In IDL it's called 'shift', and works such that
> print, a
> 0 1 2 3
> 4 5 6 7
> 8 9 10 11
>
> print, shift(a, 2, 0)
> 2 3 0 1
> 6 7 4 5
> 10 11 8 9
>
> print, shift(a, 2, 1)
> 10 11 8 9
> 2 3 0 1
> 6 7 4 5
>
> In pdl (pdl.perl.org) the equivalent routine is called rotate. Is there a
> version of this in numpy, or can it be easily achieved using existing
> technology - I could do it with multiple sliced assignment statements but
> that seems very clunky and likely slow. I've looked through the examples and
> the numpy book but without success.
>
> Angus.

[Numpy-discussion] Shift or rotate command?

[Angus M. <am...@gm...>]

Hi all,

Other data languages that I have worked with have a routine for shifting
data along axes, with wrapping.
In IDL it's called 'shift', and works such that
print, a
0 1 2 3
4 5 6 7
8 9 10 11

print, shift(a, 2, 0)
2 3 0 1
6 7 4 5
10 11 8 9

print, shift(a, 2, 1)
10 11 8 9
2 3 0 1
6 7 4 5

In pdl (pdl.perl.org) the equivalent routine is called rotate. Is there a
version of this in numpy, or can it be easily achieved using existing
technology - I could do it with multiple sliced assignment statements but
that seems very clunky and likely slow. I've looked through the examples and
the numpy book but without success.

Angus.
-- 
AJC McMorland, PhD Student
Physiology, University of Auckland
Armourer, Auckland University Fencing
Secretary, Fencing North Inc.

Re: [Numpy-discussion] dtype truth value

[Matthew B. <mat...@gm...>]

> So, you can think of the test as
>
> if dtype(...):
>    print "Data-type has fields:"
> else:
>    print "Data-type does not have fields:"

Thank you as ever for your very clear and helpful explanation,

Best,

Matthew

Re: [Numpy-discussion] dtype truth value

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

Matthew Brett wrote:
> Hi,
>
> Forgive my ignorance, but why is this?
>
> In [1]:from numpy import *
>
> In [2]:if not dtype('<f8'):
>    ...:    print 'Truth value is no'
>    ...:
>    ...:
> Truth value is no
>   

Truth value of user-built Python objects is tested by looking at:

1) __nonzero__ method is called to determine truth value.
2) sequence or mapping behavior (then the length is used.  If the length 
is greater than 0, then True, otherwise it's False.

For data-type objects, there is no __nonzero__ method, but it does have 
"mapping" behavior so that fields can be extracted from a data-type 
using mapping notation.   The "length" of the data-type is the number of 
defined fields.

Therefore, if the data-type has no defined fields, it's length is 0 and 
it's truth value is "False".

So, you can think of the test as

if dtype(...):
   print "Data-type has fields:"
else:
   print "Data-type does not have fields:"


-Travis

Re: [Numpy-discussion] general version of repmat?

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

Here's a new version of 'reparray'.

I tested the previous version against 'repmat' for the 2d case and
found it to be as much as 3x slower in some instances.  Ick.  So I
redid it using the approach repmat uses -- reshape() and repeat()
rather than concatenate().  Now it's very nearly as fast as repmat for
the 2-d case.

def reparray(A, tup):
    if numpy.isscalar(tup):
        tup = (tup,)
    d = len(tup)
    c = numpy.array(A,copy=False,subok=True,ndmin=d)
    shape = list(c.shape)
    n = c.size
    for i, nrep in enumerate(tup):
        if nrep!=1:
            c = c.reshape(-1,n).repeat(nrep,0)
        dim_in = shape[i]
        dim_out = dim_in*nrep
        shape[i] = dim_out
        n /= dim_in
    return c.reshape(shape)

The full file with tests and timing code is attached.

One thing I noticed while doing this was that repmat doesn't preserve
subclasses.  Which is funny considering 'mat' is part of the name and
it only works on 2-d arrays.  Using asanyarray() instead of asarray()
in the first line should fix that.

--Bill