Hi,
I want to know if creating individual documentation for each numpy
routine on the scipy.org wiki would, for some administrative reason
(or other) be frowned upon. Here is an example of what I'd like to do
for all of numpy's routines. http://www.scipy.org/sort.
After each routine is properly
On Fri, Mar 21, 2008 at 3:55 AM, [EMAIL PROTECTED] wrote:
Hi,
I want to know if creating individual documentation for each numpy
routine on the scipy.org wiki would, for some administrative reason
(or other) be frowned upon. Here is an example of what I'd like to do
for all of numpy's
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 array and matrix types (or using .A attribute of a matrix) is
On Thu, Mar 20, 2008 at 9:35 PM, David Cournapeau
[EMAIL PROTECTED] wrote:
numpy 1.0.5 is on the way, and I was wondering about numpy's future. I
myself have some ideas about what could be done; has there been any
discussion behind what is on 1.1 trac's roadmap ? Some of the things I
Hi,
I don't understand why an unification would simplify stuff, it would make
everything so much more difficult :| Instead of dot, you would have a mult()
function to multiply element by element, the same for inv(), so much less
readable when using arrays when arrays are so much more general and
I confirm that the reference count is consistent when trying the exemple
given in the first post of the ticket (Ubuntu 7.10, gcc 4.1.3, Python 2.5.1
).
Matthieu
2008/3/21, Jarrod Millman [EMAIL PROTECTED]:
On Thu, Mar 20, 2008 at 1:27 PM, Pauli Virtanen [EMAIL PROTECTED] wrote:
to,
Hi Dieter
On Fri, Mar 21, 2008 at 9:55 AM, [EMAIL PROTECTED] wrote:
I want to know if creating individual documentation for each numpy
routine on the scipy.org wiki would, for some administrative reason
(or other) be frowned upon. Here is an example of what I'd like to do
for all of
Thank you, Pauli. Tested and applied in r4899.
Regards
Stéfan
On Thu, Mar 20, 2008 at 9:27 PM, Pauli Virtanen [EMAIL PROTECTED] wrote:
to, 2008-03-20 kello 21:09 +0100, Matthieu Brucher kirjoitti:
Well, it is not completely solved. With the patch, the reference count
keeps on raising,
I think the bug was referring to the fact that some types have
duplicate names *explicitly* containing the letter c --
as in
repr(N.intc)
'type 'numpy.int32''
Is this supposed to be consistent naming scheme (i.e. any C type T
is accessible as N.Tc) ?
Then c float-type should consequently be
4. Update the docstring, using the format suggested in
http://projects.scipy.org/scipy/numpy/wiki/CodingStyleGuidelines
I realize this is a bit of a johnny-come-lately comment, but I was
surprised to see that the list of sections does not seem to include the
single most common reason I
On 21 Mar 2008, at 12:29, Sebastian Haase wrote:
... and what does the p stand for in
N.intp
type 'numpy.int32'
It stands for pointer. An intp is an integer large enough to contain
a pointer address.
J.
Disclaimer: http://www.kuleuven.be/cwis/email_disclaimer.htm
read relow...
On Fri, Mar 21, 2008 at 11:21 AM, Stéfan van der Walt [EMAIL PROTECTED] wrote:
Hi Dieter
On Fri, Mar 21, 2008 at 9:55 AM, [EMAIL PROTECTED] wrote:
I want to know if creating individual documentation for each numpy
routine on the scipy.org wiki would, for some administrative
On Fri, Mar 21, 2008 at 8:54 AM, Sebastian Haase [EMAIL PROTECTED] wrote:
read relow...
NumpyDocstrings category on the wiki, and suggest that we organise the
functions underneath it according to their numpy subpackage, e.g.
scipy.org/NumpyDocstrings/core/sort
If you need to
On 21/03/2008, Sebastian Haase [EMAIL PROTECTED] wrote:
Comment: I have read the module- or directory-name core many times
on this list, however: Who really knows where a given functions
belongs ? Isn't that mostly only the numpy svn commiters ?
In other words, using only the python side
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, Mar 21, 2008 at 1:54 PM, Sebastian Haase [EMAIL PROTECTED] wrote:
read relow...
On Fri, Mar 21, 2008 at 11:21 AM, Stéfan van der Walt [EMAIL PROTECTED]
wrote:
Hi Dieter
On Fri, Mar 21, 2008 at 9:55 AM, [EMAIL PROTECTED] wrote:
I want to know if creating individual
Hi Gary
On Fri, Mar 21, 2008 at 12:53 PM, Gary Strangman
[EMAIL PROTECTED] wrote:
4. Update the docstring, using the format suggested in
http://projects.scipy.org/scipy/numpy/wiki/CodingStyleGuidelines
I realize this is a bit of a johnny-come-lately comment, but I was
surprised
On Fri, Mar 21, 2008 at 2:47 PM, Anne Archibald
[EMAIL PROTECTED] wrote:
On 21/03/2008, Sebastian Haase [EMAIL PROTECTED] wrote:
Comment: I have read the module- or directory-name core many times
on this list, however: Who really knows where a given functions
belongs ? Isn't that
On 21/03/2008, Stéfan van der Walt [EMAIL PROTECTED] wrote:
On Fri, Mar 21, 2008 at 2:47 PM, Anne Archibald
[EMAIL PROTECTED] wrote:
Is it perhaps possible to make all numpy functions accessible in
submodules (in addition to in numpy, for backwards compatibility) and
then promote
David Cournapeau wrote:
Hi,
numpy 1.0.5 is on the way, and I was wondering about numpy's future. I
myself have some ideas about what could be done; has there been any
discussion behind what is on 1.1 trac's roadmap ? Some of the things I
would like to see myself:
- a framework
On Fri, Mar 21, 2008 at 5:00 PM, Anne Archibald
[EMAIL PROTECTED] wrote:
On 21/03/2008, Stéfan van der Walt [EMAIL PROTECTED] wrote:
On Fri, Mar 21, 2008 at 2:47 PM, Anne Archibald
[EMAIL PROTECTED] wrote:
Is it perhaps possible to make all numpy functions accessible in
Pierre GM wrote:
This sucks to the point of feeling like a bug :-(
It is not.
Ignoring the fill value of masked array feels like a bug to me...
Why is it desirable for it to behave like this?
Because that way, you can compare anything to masked and see whether a value
is masked or not.
Pierre GM wrote:
On Wednesday 19 March 2008 19:47:37 Matt Knox wrote:
1. why am I not getting my NaN's back?
Because they're gone when you create your masked array.
Really? At least one other post has disagreed with that.
And it does seem odd that a value, even if it's a nan, would be
Is it perhaps possible to make all numpy functions accessible in
submodules (in addition to in numpy, for backwards compatibility) and
then promote accessing them that way?
I would caution on breaking functionality out into too many
categories.
It is *very* cumbersome to constantly import
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
Hello,
I have installed numpy-1.0.4.win32-py2.5 on windows machine for python
2.5.1.But when I enter command
import Numeric
I get following error:
Traceback (most recent call last):
File pyshell#16, line 1, in module
import Numeric
ImportError: No module named Numeric
Can anybody please
But asmatrix returns a matrix object and any subsequent operation of it returns
a matrix. What I am thinking about is a convenient way to apply matrix
operation on an array.
BTW, A matrix is just a rank 2 tensor, so matrix (tensor) algebra can be
applied to an arbitrary rank tensor, for
pe, 2008-03-21 kello 07:53 -0400, Gary Strangman kirjoitti:
4. Update the docstring, using the format suggested in
http://projects.scipy.org/scipy/numpy/wiki/CodingStyleGuidelines
I realize this is a bit of a johnny-come-lately comment, but I was
surprised to see that the list of
http://projects.scipy.org/scipy/numpy/wiki/CodingStyleGuidelines
I realize this is a bit of a johnny-come-lately comment, but I was
surprised to see that the list of sections does not seem to include the
single most common reason I usually try to access a doc string ... the
function
Charles R Harris wrote:
On Fri, Mar 21, 2008 at 1:57 PM, Alan G Isaac [EMAIL PROTECTED]
mailto:[EMAIL PROTECTED] wrote:
On Fri, 21 Mar 2008, Nadav Horesh apparently wrote:
But asmatrix returns a matrix object and any subsequent
operation of it returns a matrix. What I am
One problem with the matrix class is that it follows matlab way too much. For
example:
a = arange(9).reshape(3,3)
A = asmatrix(a)
v = arange(3)
dot(a, v)
array([ 5, 14, 23])
A*v
Traceback (most recent call last):
File pyshell#15, line 1, in module
A*v
File
On Friday 21 March 2008 12:52:45 Chris Withers wrote:
Pierre GM wrote:
This sucks to the point of feeling like a bug :-(
It is not.
Ignoring the fill value of masked array feels like a bug to me...
You're right with masked arrays, but here we're talking the masked singleton,
a special
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
Hi All,
Say I have an array like:
measurements = array([100,109,115,117])
What do I do to it to get:
array([9, 6, 2])
Is the following really the best way?
result = []
for i in range(1,len(measurements)):
... result.append(measurements[i]-measurements[i-1])
...
array(result)
numpy.diff
See http://www.scipy.org/Numpy_Example_List
J.
On 22 Mar 2008, at 03:43, Chris Withers wrote:
Hi All,
Say I have an array like:
measurements = array([100,109,115,117])
What do I do to it to get:
array([9, 6, 2])
Is the following really the best way?
result = []
for i
Try
result = A[1:] - A[:-1]
--Hoyt
On Fri, Mar 21, 2008 at 7:43 PM, Chris Withers [EMAIL PROTECTED] wrote:
Hi All,
Say I have an array like:
measurements = array([100,109,115,117])
What do I do to it to get:
array([9, 6, 2])
Is the following really the best way?
result =
On 21 Mar 2008, at 18:22, Joe Harrington wrote:
What you have brought up is really a documentation problem: how do I
find the name of the routine I want?
One way of dealing with this, could be the implementation of a doc()
function in numpy that helps you to find what you want. A (still
Hello all,
Much thanks is deserved by the people who have been chasing down and
fixing reference count problems in NumPy. Two of them are related to
object arrays.
So, if you have been having memory leak problems with object arrays
(vectorize uses object arrays, BTW), you should try out
Travis E. Oliphant wrote:
Hello all,
Much thanks is deserved by the people who have been chasing down and
fixing reference count problems in NumPy. Two of them are related to
object arrays.
So, if you have been having memory leak problems with object arrays
(vectorize uses object
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