On Sun, 6 Apr 2008, Charles R Harris wrote:
The boolean algebra is a field and the correct addition is xor, which is
the same as addition modulo 2. This makes all matrices with determinant 1
invertible. This isn't the current convention, however, as it was when
Caratheodory was writing on
On Sun, 6 Apr 2008, Anne Archibald apparently wrote:
I am not aware of any algorithm for finding inverses, or
even determining which matrices are invertible, in the
peculiar Boolean arithmetic we use.
Again, it is *not* peculiar, it is very standard for
boolean matrices. And with this
On Sun, 6 Apr 2008, Charles R Harris apparently wrote:
I prefer the modern usage myself as it is closer to the
accepted logic operations, but applying algebraic
manipulations like powers and matrix inverses in that
context leads to strange results.
I have not really thought much about
On Sun, 6 Apr 2008, Charles R Harris apparently wrote:
You mean as edges in a directed graph?
Yes.
Naturally a boolean matrix is not the most compact
representation of a directed graph, especially a
sparse one. However it can be convenient.
If B is a boolean matrix such that Bij=1 if there
On Fri, 4 Apr 2008, Gael Varoquaux apparently wrote:
I really thing numpy should be as thin as possible, so
that you can really say that it is only an array
manipulation package. This will also make it easier to
sell as a core package for developpers who do not care
about calculator
On Tue, 1 Apr 2008, harryos apparently wrote:
i need to calculate
wk=uk o (L-Psi)
where
uk=a vector of size (1 X N^2)
o =scalar product
l,Psi=vectors of (N^2 X 1)
i have an ndarray U of shape(M X N^2)where uk is one of the rows , and
L of shape (M X N^2) where l.transpose() is one of
On Thu, 27 Mar 2008, lorenzo bolla apparently wrote:
I realized that numpy.loadtxt do not read the last
character of an input file. This is annoying if the input
file do not end with a newline.
I believe Robert fixed this;
update from the SVN repository.
hth,
Alan Isaac
On Wed, Mar 26, 2008 at 5:20 PM, Gabriel J.L. Beckers [EMAIL PROTECTED]
wrote:
Does numpy have something like Matlab's accumarray?
http://www.mathworks.com/access/helpdesk/help/techdoc/ref/accumarray.html
On Wed, 26 Mar 2008, Robert Kern apparently wrote:
No.
But of course you can do
On Sat, 22 Mar 2008, Stéfan van der Walt apparently wrote:
maybe you can post a link as a reminder
URL:http://projects.scipy.org/pipermail/numpy-discussion/2008-February/031548.html
In the matrix world, everything has a minimum dimension of
2, so I don't see how you can contain ndarrays in
On Fri, 21 Mar 2008, Nadav Horesh apparently wrote:
I would like to see a unification of matrices and arrays.
I often do calculation which involve both array processing
and linear algebra, and the current solution of having
function like dot and inv is not aesthetic. Switching
between
On Fri, 21 Mar 2008, Stéfan van der Walt apparently wrote:
The last I remember, we considered adding RowVector,
ColumnVector and letting slices out of a matrix either be
one of those or a matrix itself.
There was a subsequent discussion.
I simply don't see a Matrix as a container of
On Sat, 22 Mar 2008, Nadav Horesh apparently wrote:
A*v
...
ValueError: objects are not aligned
This is just how I want matrices to act!
If A is m׳n, then v should be n׳1
for A*v to be defined. Anything else
is trouble waiting to happen.
But it seems that Charles's proposal would
make
On Tue, 18 Mar 2008, Chris Withers apparently wrote:
Say I have an aribtary number of arrays:
arrays = [array([1,2,3]),array([4,5,6]),array([7,8,9])]
How can I sum these all together?
Try N.sum(arrays,axis=0).
But must they be in a list?
An array of arrays (i.e., 2d array) is easy to sum.
On Tue, 18 Mar 2008, Chris Withers apparently wrote:
Where are the docs for sum?
Again:
http://www.scipy.org/Numpy_Example_List_With_Doc
Really, as a new NumPy user you should just keep
this page open in your browser.
Also, help(N.sum), of course.
Cheers,
Alan Isaac
On Mon, 17 Mar 2008, Chris Withers apparently wrote:
woefully inadequate state of the currently available free
documentation
1. http://www.scipy.org/Numpy_Example_List_With_Doc
2. write some
Cheers,
Alan Isaac
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Alan suggested:
1. http://www.scipy.org/Numpy_Example_List_With_Doc
On Mon, 17 Mar 2008, Chris Withers apparently wrote:
Yeah, read that, wood, trees, can't tell the...
Oh, then you might want
http://www.scipy.org/Tentative_NumPy_Tutorial
or the other stuff at
On Thu, 13 Mar 2008, Alexander Michael apparently wrote:
I want to format an array of numbers as strings.
To what end?
Note that tofile has a format option.
And for 1d array ``x`` you can always do::
strdata = list( fmt%xi for xi in x)
Nice because the counter name does not bleed into
2008/3/13, Alan G Isaac [EMAIL PROTECTED]:
strdata = list( fmt%xi for xi in x)
Nice because the counter name does not bleed into your program.
On Thu, 13 Mar 2008, David Huard apparently wrote:
['S%03d'%i for i in int_data]
The difference is that the counter bleeds
from the list
On Thu, 13 Mar 2008, Alexander Michael apparently wrote:
I wasn't sure if there was a magic numpy
method to do the loop quickly (as the destination array is created
beforehand) without creating a temporary Python list, but I guess not.
The generator/list-comprehension is likely better than
This is how I would hope ``fromfunction`` would work
and it matches the docs. (See below.) You can fix
the example ...
Cheers,
Alan Isaac
help(N.fromfunction)
Help on function fromfunction in module numpy.core.numeric:
fromfunction(function, shape, **kwargs)
Returns an array constructed
Alan G Isaac wrote:
I never got a response to this:
URL:http://projects.scipy.org/pipermail/scipy-dev/2008-February/008424.html
(Two different types claim to be numpy.int32.)
On Mon, 03 Mar 2008, Travis E. Oliphant apparently wrote:
It's not a bug :-) There are two c-level types
On Wed, 27 Feb 2008, Robert Kern apparently wrote:
Fixed in r4827.
On Wed, Feb 27, 2008 at 6:31 PM, Christopher Barker wrote:
For the record, this is the fixed version:
comment_start = line.find(comments)
if comment_start 0:
line =
On Wed, 27 Feb 2008, Stuart Brorson apparently wrote:
** 0^0: This is problematic.
Accessible discussion:
URL:http://en.wikipedia.org/wiki/Exponentiation#Zero_to_the_zero_power
Cheers,
Alan Isaac
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On Thu, Feb 21, 2008 at 12:08:32PM -0500, Alan G Isaac
wrote:
a matrix behavior that I find bothersome and unnatural::
M = N.mat('1 2;3 4')
M[0]
matrix([[1, 2]])
M[0][0]
matrix([[1, 2]])
On Fri, 22 Feb 2008, Stefan van der Walt apparently wrote:
Could you
On Fri, 22 Feb 2008, Travis E. Oliphant apparently wrote:
The point is that a matrix object is a
matrix object and not a generic container.
I see the point a bit differently:
there are costs and benefits to the abandonment
of a specific and natural behavior of containers.
(The kind of
On Fri, 22 Feb 2008, Travis E. Oliphant apparently wrote:
Do I understand correctly, that by intuitive you mean
based on experience with lists, and NumPy arrays?
Yes.
In particular, array behavior is quite lovely
and almost never surprising, so matrices should
deviate from it only when there
Alan G Isaac wrote:
I propose that the user-friendly question is:
why deviate needlessly from array behavior?
(Needlessly means: no increase in functionality.)
On Fri, 22 Feb 2008, Christopher Barker apparently wrote:
because that's the whole point of a Matrix object in the
first place
On Thu, 21 Feb 2008, Konrad Hinsen apparently wrote:
What I see as more fundamental is the behaviour of Python container
objects (lists, sets, etc.). If you add an object to a container and
then access it as an element of the container, you get the original
object (or something that
On Thu, 21 Feb 2008, Konrad Hinsen apparently wrote:
A float64 array is thus a container of float64 values.
Well ... ok::
x = N.array([1,2],dtype='float')
x0 = x[0]
type(x0)
type 'numpy.float64'
So a float64 value is whatever a numpy.float64 is,
and that is part of
On Thu, Feb 21, 2008 at 12:08:32PM -0500, Alan G Isaac wrote:
a matrix behavior that I find bothersome and unnatural::
M = N.mat('1 2;3 4')
M[0]
matrix([[1, 2]])
M[0][0]
matrix([[1, 2]])
On Fri, 22 Feb 2008, Stefan van der Walt apparently wrote:
This is exactly
On Wed, 20 Feb 2008, John Hunter apparently wrote:
File
/home/titan/johnh/dev/lib/python2.4/site-packages/numpy/lib/function_base.py,
line 155, in histogram
if(any(bins[1:]-bins[:-1] 0)):
NameError: global name 'any' is not defined
``any`` was introduced in Python 2.5, so you
On Fri, 15 Feb 2008, Dinesh B Vadhia apparently wrote:
I upgraded to Python 2.5.2c1 today, and got the following error for:
import numpy
import scipy
Traceback (most recent call last):
File C:\ ... .py, line 19, in module
import scipy
ImportError: No module named scipy
I'm using
Problem also with Windows P3 binaries.
fwiw,
Alan Isaac
Python 2.5.1 (r251:54863, Apr 18 2007, 08:51:08) [MSC v.1310
32 bit (Intel)] on win32
Type help, copyright, credits or license for more information.
import numpy
numpy.__version__
'1.0.4'
A = numpy.array(['a','aa','b'])
B =
On Thu, 31 Jan 2008, dmitrey apparently wrote:
already fixed in more recent versions?
Yes, at least it's fixed in my 1.0.4.
By the way, do you know about the ``A`` attribute of matrices?
Cheers,
Alan Isaac
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On Fri, 4 Jan 2008, Stuart Brorson apparently wrote:
I realize NumPy != Matlab, but I'd wager that most users
would think that this is the natural behavior.
I would not find it natural that elements of my float
array could be assigned complex values. How could it be
a fixed chunk of memory
On Thu, 3 Jan 2008, Charles R Harris apparently wrote:
Isn't it trivially true that all elements of an empty
array are close to any number?
Sure, but might not one expect a ValueError due to
shape mismatch? (Doesn't allclose usually use
normal broadcasting rules?)
Cheers,
Alan Isaac
On Thu, 3 Jan 2008, Charles R Harris apparently wrote:
Isn't it trivially true that all elements of an empty
array are close to any number?
On Thu, 3 Jan 2008, Alan G Isaac apparently wrote:
Sure, but might not one expect a ValueError due to
shape mismatch? (Doesn't allclose usually use
On Wed, 26 Dec 2007, Mathew Yeates apparently wrote:
r1=[dog,cat]
r2=[1,2]
I want to return [[dog,1],[dog,2],[cat,1],[cat,2]]
This is a Cartesian product.
Sage has ``cartesian_product_iterator`` for this.
Also
On Sat, 29 Dec 2007, dikshie apparently wrote:
so import numpy and from numpy import *
are different ?
http://docs.python.org/tut/node8.html
hth,
Alan Isaac
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On Thu, 20 Dec 2007, Jarrod Millman apparently wrote:
If you are having problems with NumPy and SciPy on Pentium III
machines running Windows, please try the newly released binaries:
I used the Python 2.5 binaries (.exe) on my home P3 and all
seems well in use. I got no failures of
On Wed, 12 Dec 2007, Travis E. Oliphant apparently wrote:
2) The matrix object made a C-subclass (for speed).
This will probably be the last chance for such a change,
so I again hope that consideration will be given to *one*
change in the matrix object:
iteration over a matrix should return
This may be a naive question, but just to be sure...
If troubles building without SSE2 support on an SSE2
processor are the problem, withould the problem be addressed
by purchasing an old PIII like
Alan G Isaac wrote:
I would think that
multinomial(1,prob,size=ntrials).sum(axis=0)
would be equivalent to
multinomial(ntrials,prob)
but the first gives a surprising result. (See below.)
Explanation?
On Wed, 05 Dec 2007, Robert Kern apparently wrote:
Pretty much anyone who
I would think that
multinomial(1,prob,size=ntrials).sum(axis=0)
would be equivalent to
multinomial(ntrials,prob)
but the first gives a surprising result. (See below.)
Explanation?
Thank you,
Alan Isaac
ntrials = 10
prob = N.arange(100,dtype=N.float32)/4950
On Fri, Nov 23, 2007 at 07:58:13AM -0500, Alan G Isaac wrote:
Specifically, is it not the case that the last line of
a text file is not guaranteed to have a terminator? Does
this not raise the possibility that a digit will be
clipped from the last line?
On Fri, 23 Nov 2007, Gael
On Thu, Nov 22, 2007 at 11:14:07PM -0500, Alan G Isaac wrote:
In numpy.core.numeric.py you will find loadtxt, which uses
the following::
line = line[:line.find(comments)].strip()
On Fri, 23 Nov 2007, Gael Varoquaux apparently wrote:
Unless you are sure that line always ends
In numpy.core.numeric.py you will find loadtxt, which uses
the following::
line = line[:line.find(comments)].strip()
I believe there is a bug here (when a line has no comment).
To illustrate::
line = 12345
comments = #
line[:line.find(comments)]
'1234'
So I propose
On Mon, 12 Nov 2007, D.Hendriks (Dennis) apparently wrote:
All of this makes me doubt the correctness of the formula
you proposed.
It is always a good idea to hesitate before doubting Robert.
1.0**numpy.array([1,2,3])
array([ 1., 1., 1.])
1.0**numpy.mat([1,2,3])
Traceback (most recent call last):
File stdin, line 1, in module
TypeError: unsupported operand type(s) for ** or pow(): 'float' and 'matrix'
Why the restriction for matrices?
Same question for matrices conformable for
It sounds to me like you have something closer to the
following.
class Problem
- initialized with an Input instance and an Analysis instance
- has a ``get_results`` method that asks the Analysis instance to
- call ``get_input`` on Input instance
- run analysis on the provided
On Fri, 12 Oct 2007, Matthieu Brucher apparently wrote:
I'm trying to understand (but perhaps everything is in the
numpy book in which case I'd rather buy the book
immediately) how to use the PyArray_FromAny() function.
This function is discussed in the NumPy Book.
I see perhaps a dozen
On Fri, 12 Oct 2007, Renato Serodio apparently wrote:
The scripts that produce these metrics use Scipy/Numpy
functions that operate on data conveniently converted to
numpy arrays. They're quite specific, and I tend to
produce/tweak a lot of them. So, to fit in this
application someone
On Tue, 2 Oct 2007, David M. Cooke apparently wrote:
Should be fixed now.
The update seems to work for all my students who
were having problems.
Thank you,
Alan Isaac
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Numpy-discussion@scipy.org
On Mon, 8 Oct 2007, Robin apparently wrote:
However in my code (I am converting from MATLAB) it is
important to maintain 2d arrays, and keep the difference
between row and column vectors.
How about using matrices?
help(numpy.mat)
hth,
Alan Isaac
On Fri, 05 Oct 2007, Christopher Barker apparently wrote:
There is a new Python Magazine out there:
http://www.pythonmagazine.com/
Looks useful.
If you think so too, make sure you library subscribes.
Cheers,
Alan Isaac
___
Numpy-discussion
On Tue, 2 Oct 2007, Charles R Harris apparently wrote:
We're avoiding consolidated fields because they behave
badly. ... The main problem with the consolidated fields
is that they are all put together as item lists in
a definition list and moved to the end of the docstring
when it is
Shouldn't x**0 be boolean for a boolean matrix?
Cheers,
Alan Isaac
import numpy
numpy.__version__
'1.0.3.1'
x = numpy.mat('1 1;1 0',dtype='bool')
x**0
matrix([[ 1., 0.],
[ 0., 1.]])
x**1
matrix([[ True, True],
[ True, False]], dtype=bool)
x**2
matrix([[ True, True],
To help me understand, might someone offer some examples of
NumPy names that really should be changed?
Thank you,
Alan Isaac
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Numpy-discussion@scipy.org
http://projects.scipy.org/mailman/listinfo/numpy-discussion
On Tue, 02 Oct 2007, Pearu Peterson apparently wrote:
1. The printed '0' traces to an undesirable print statement.
(I've reported this before.)
Travis seemed to fix this about two weeks ago.
Sorry for the noise.
2. The 'False report is on a Pentium M. Should that not be
True?
Here is the processor information using the Intel utility.
Cheers,
Alan Isaac
Intel(R) Processor Identification Utility
Version: 3.7.20070907
Time Stamp: 2007/10/02 14:21:29
Number of processors in system: 1
Current processor: #1
Cores per processor: 1
Disabled cores per processor: 0
Processor
On Tue, 2 Oct 2007, Pierre GM apparently wrote:
is there any kind of standard to describe the attributes
of a class, a la :IVariables: in epydoc ?
I thought it was ... :IVariables:
i.e., I thought the standard was reST as handled by epydoc.
On Sat, 22 Sep 2007, Charles R Harris apparently wrote:
an array view is returned, and the data is updated in the
loop ... I think your range fix is the way to go.
Got it. Thanks!
Alan
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On Fri, 21 Sep 2007, Stephen McInerney apparently wrote:
The pure Pythonic solution is a list comprehension involving multiple
sequences:
x = range(0,n)
y = x
z = x
t = [(xx,yy,zz) for xx in x for yy in y for zz in z]
Different question ...
Cheers,
Alan Isaac
Suppose I import cpuinfo on a Win32 platform::
Python 2.5.1 (r251:54863, Apr 18 2007, 08:51:08) [MSC
v.1310 32 bit (Intel)] on win32
Type help, copyright, credits or license for more information.
import numpy
numpy.__version__
'1.0.3.1'
from numpy.distutils import
On Wed, 29 Aug 2007, Peter apparently wrote:
I would like to know if there is a preferred form for
citing the old
Numeric library
I'll attach text from the first two pages of *Numerical
Python* below.
Cheers,
Alan Isaac
-
An Open
On Fri, 24 Aug 2007, Ryan Krauss apparently wrote:
I helped a couple of my students install on Vista. It was
enough to right click on the exe and choose Run as
Administrator. A pop-up window then comes up asking you
if you trust the file or something and you have to chose
an option that
On Thu, 16 Aug 2007, Geoffrey Zhu apparently wrote:
K=numpy.array(o[2]/1000.0 for o in opts)
It does not work.
K=numpy.fromiter((o[2]/1000.0 for o in opts),'float')
hth,
Alan Isaac
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On Tue, 07 Aug 2007, Nils Wagner apparently wrote:
I have a list of integer numbers. The entries can vary between 0 and 19.
How can I count the occurrence of any number. Consider
data
[9, 6, 9, 6, 7, 9, 9, 10, 7, 9, 9, 6, 7, 9, 8, 8, 11, 9, 6, 7, 10, 9, 7, 9,
7, 8, 9, 8, 7, 9]
Is there
On Fri, 03 Aug 2007, [EMAIL PROTECTED] apparently wrote:
I appear to be having a problem with the random.multinomial function. For
some
reason if i attempt to loop over a large number of single-trial multinomial
picks then the function begins to ignore some non-zero entries in my 1-D
On Tue, 17 Jul 2007, Stefan van der Walt apparently wrote:
var1 :
Description.
breaks. This can be fixed either by omitting the colon after
'var1' in the second case, or by slightly modifying epydoc's output.
It breaks semantically too, no?
(The colon is a separator,
I found Gael's presentation rather puzzling for two reasons.
1. It appears to contain a `+` vs. `*` confusion.
See http://en.wikipedia.org/wiki/Two-element_Boolean_algebra
2. MUCH more importantly:
In implementations of TWO, we interpret `-` as unary
complementation (not e.g. as additive
On Mon, 9 Jul 2007, Timothy Hochberg apparently wrote:
x*y and x**2 are already decoupled for arrays and matrices. What if x*y was
simply defined to do a boolean matrix multiply when the arguments are
boolean matrices?
I don't care about this that much though, so I'll let it drop.
So if
Hi Gael,
More important is the following.
On Tue, 10 Jul 2007, Alan G Isaac apparently wrote:
N.array([False])-N.array([True])
array([True], dtype=bool)
N.array([False])+(-N.array([True]))
array([False], dtype=bool)
The second answer is the right one, in this context.
I would call
On Wed, 04 Jul 2007, dmitrey apparently wrote:
cumproduct(x, axis=None, dtype=None, out=None)
Sum the array over the given axis.
Docstring bug.
But it behaves right.
Cheers,
Alan Isaac
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On Wed, 16 May 2007, Anne Archibald apparently wrote:
numpy.max(-1.3,2,7)
-1.3
Is that new behavior?
I get a TypeError on the last argument.
(As expected.)
Cheers,
Alan Isaac
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Gary Ruben wrote:
In you post, is your numpy/doc reference referring to the
file HOWTO_DOCUMENT.txt?
I notice that this is not the same as the one here
http://scipy.org/DocstringStandard
which I think may be the preferred standard. If someone can confirm
this, it should probably
On 5/15/07, Alan G Isaac [EMAIL PROTECTED] wrote:
Just to add a bit more specificity, I believe that the
HOWTO_DOCUMENT.txt document at
http://svn.scipy.org/svn/numpy/trunk/numpy/doc/HOWTO_DOCUMENT.txt
summarizes a substantial discussion and broad agreement.
I.e., it is currently
On Tue, 15 May 2007, Charles R Harris apparently wrote:
It also causes the headings to be set in large bold type. Ugly.
Well I agree.
But again this is just a style issue.
All font decisions (and *much* else) can be set in a CSS file.
I think reST is great, and properly used we get good
On Tue, May 15, 2007 at 01:15:12PM -0400, Alan G Isaac wrote:
Bullets in consolidated lists:
if you don't like them, don't use them.
Use a definition list instead.
(I like this much better myself.)
On Tue, 15 May 2007, Gael Varoquaux apparently wrote:
Can't this be fixed
On Tue, 15 May 2007, Charles R Harris apparently wrote:
If a CSS can set all the font styles, item spacing, and
treatment of explanatory text, that would be the more
flexible route.
I'm not sure what treatment meams here,
but if it is a matter of font decisions or spacing,
the answer should
On Tue, 15 May 2007, Charles R Harris apparently wrote:
Looks like the font used for section headings can be
specified, but there is nothing in the epydoc.css file
that looks like it affects the consolidated lists or the
movement of a section heading to the top of the output.
I think the
On Tue, 15 May 2007, Charles R Harris apparently wrote:
The item in a consolidated list is divided into three
parts: name, type, explanation. I see no way in the CSS to
control the display of those parts, although it might be
an undocumented feature. I basically want it to look like
a
On Tue, 15 May 2007, Charles R Harris apparently wrote:
What I would like it to look like, except for the type
stuff, is attached.
Ooof!
Aside from obviously agreeing with the location of notes
and examples, I have to say, the readability of your
example is greatly reduced from the epydoc
On Wed, 02 May 2007, Rob De Almeida apparently wrote:
http://cheeseshop.python.org/pypi/pupynere/
I do not think you were shameless enough.
Pupynere is a PUre PYthon NEtcdf REader. It allows
read-access to netCDF files using the same syntax as
the
On Thu, 5 Apr 2007, Gael Varoquaux apparently wrote:
Actually I do it the other way around nowadays.
Except in the tutorial?
But anyway, I'm willing to try anything that gets them moving.
It is true that avoiding the appearance of complexity can
sometimes add complexity.
Cheers,
Alan Isaac
On Wed, 04 Apr 2007, Eric Firing apparently wrote:
Key point: properties work with new-style classes but fail
silently and mysteriously with classic classes.
Or making the same point a little more generally,
descriptors only work for new-style classes:
Is either NumPy or SciPy substantially supported
by an identifiable and actual non-profit organization?
I ask because I think both fit under
http://www.mellon.org/grant_programs/programs/copy_of_research
item 4.
Here is the announcement:
http://matc.mellon.org/
Note that universities are among
On Tue, 27 Mar 2007, Zachary Pincus apparently wrote:
Now, Bill offers up a different suggestion: indexing
M yields neither a matrix nor an array, but a class that
operates more or less like an array, except insofar as it
interacts with other matrix objects, or other objects of
similar
On Tue, 27 Mar 2007, Bill Baxter apparently wrote:
xformedPt = someComplicatedNonLinearThing(pt)
I do stuff like the above quite frequently in my code,
although with arrays rather than matrices.
Exactly: that was one other thing I found artificial.
Surely the points will then be wanted as
Hi Zachary,
I think your response highlights very well
the apparent design flaw.
Here is your response to my request for a use case where
iteration over a matrix should yield matrices:
do not iterate!
Does some part of you not find that just a little bizarre?!
As for offering as a use
Hi Zach,
The use case I requested was for iteration over a
matrix where it is desirable that matrices are yielded.
That is not what you offered.
The context for this request is my own experience:
whenever I have needed to iterate over matrices,
I have always wanted the arrays. So I am simply
On Tue, 27 Mar 2007, Robert Kern apparently wrote:
Gram-Schmidt orthogonalization
I take it from context that you consider it desirable
to end up with a list of matrices?
I guess I would find it more natural to work with the
arrays, but perhaps that starts just being taste.
Thank you,
Alan
On Tue, 27 Mar 2007, Robert Kern apparently wrote:
Gram-Schmidt orthogonalization
Alan G Isaac wrote:
I take it from context that you consider it desirable
to end up with a list of matrices?
Robert wrote:
Honestly, I don't care. You asked about iteration, and
I gave you
On Mon, 26 Mar 2007, Colin J. Williams apparently wrote:
Perhaps things would be clearer if we thought of the
constituent groups of data in a matrix as being themselves
matrices.
This thinking of is what you have suggested before.
You need to explain why it is not begging the question.
Alan G Isaac schrieb:
X[1]
array([3,4])
X[1,:]
matrix([[3, 4]])
But again the point is:
indexing for submatrices should produce matrices.
Normal Python indexing should access the constituent arrays.
On Mon, 26 Mar 2007, Sven Schreiber apparently wrote:
I think
Alan G Isaac schrieb:
What feels wrong: iterating over a container does not give
access to the contained objects. This is not Pythonic.
On Mon, 26 Mar 2007, Sven Schreiber apparently wrote:
If you iterate over the rows of the matrix, it feels
natural to me to get the row vectors
On Mon, 26 Mar 2007, Sebastian Haase apparently wrote:
A matrix is an object that you expect a certain
(mathematical !) behavior from. If some object behaves
intuitively right -- that's ultimately pythonic!
The problem is, as I am not the only one to point out,
this particular behavior is
On Mon, 26 Mar 2007, Colin J. Williams apparently wrote:
One would expect the iteration over A to return row
vectors, represented by (1, n) matrices.
On 3/26/07, Alan G Isaac [EMAIL PROTECTED] wrote:
This is again simple assertion.
**Why** would one expect this?
Some people clearly
One thing keeps bugging me when I use numpy.matrix.
All this is fine::
x=N.mat('1 1;1 0')
x
matrix([[1, 1],
[1, 0]])
x[1,:]
matrix([[1, 0]])
But it seems to me that I should be able
to extract a matrix row as an array.
So this ::
x[1]
matrix([[1,
Em Dom, 2007-03-25 às 13:07 -0400, Alan G Isaac escreveu:
x[1]
matrix([[1, 0]])
feels wrong. (Similarly when iterating across rows.)
On Sun, 25 Mar 2007, Paulo Jose da Silva e Silva apparently wrote:
I think the point here is that if you are using matrices,
then all you should
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