Hi,
Looks like a fun discussion: it's too bad for me I did not join it
earlier. My first try at scipy-cluster was completely in Python. Like
you, I also tried to find the most efficient way to transform the
distance matrix when joining two clusters. Eventually my data sets
became big enough
Robert Kern wrote:
Since there are only 6 places where PyMemData_RENEW is used, all 6
uses should be benchmarked. I would prefer a more targeted benchmark
so we know exactly what we are measuring.
Ok, I started a new branch for aligned allocator:
Hey,
The trunk is in pretty good shape and it is about time that I put out
an official release. So tomorrow (in a little over twelve hours) I am
going to create a 1.1.x branch and the trunk will be officially open
for 1.2 development. If there are no major issues that show up at the
last
2008/5/5 David Cournapeau [EMAIL PROTECTED]:
Basically, what I have in mind is, in a first step (for numpy 1.2):
- define functions to allocate on a given alignement
- make PyMemData_NEW 16 byte aligned by default (to be compatible
with SSE and co).
The problem was, and still is,
Dear Robert,
Thank you. But i am trying to install it in a 32-bit machine only. In that
case, why dose it require 64 bit libraries.
Bala
On Mon, May 5, 2008 at 10:47 PM, Robert Kern [EMAIL PROTECTED] wrote:
On Mon, May 5, 2008 at 6:14 AM, Bala subramanian
[EMAIL PROTECTED] wrote:
Dear
Hello all,
I wanted to fix the formatting problems on the wiki page
http://scipy.org/scipy/numpy/wiki/MaskedArrayApiChanges, so I followed
the instructions on http://scipy.org/scipy/numpy/wiki (which state In
order to edit wiki pages or create and edit tickets, you need to
register first.)
But
Anne Archibald wrote:
How much does this matter? I mean, what if you simply left all the
reallocs as-is? The arrays that resulted from reallocs would not
typically be aligned, but we cannot in any case expect all arrays to
be aligned.
The problem would be the interaction between the aligned
Hello,
I encountered the error Segmentation fault (core dumped) during a rather
standard multiplication, without excessive memory us. This looks likes a
bug to me?
I am using Python 2.5, Numpy 1.0.4 under Ubuntu 7.10.
Here is what I am doing: i have two arrays, points1 and points2.
ti, 2008-05-06 kello 14:15 +0200, Marius Nijhuis kirjoitti:
Hello,
I encountered the error Segmentation fault (core dumped) during a
rather standard multiplication, without excessive memory us. This
looks likes a bug to me?
I am using Python 2.5, Numpy 1.0.4 under Ubuntu 7.10.
Here is
On Tue, 6 May 2008, Jarrod Millman apparently wrote:
open tickets that I would like everyone to take a brief
look at:
http://projects.scipy.org/scipy/numpy/ticket/760
My understanding is that my patch, which would give
a deprecation warning, was rejected in favor of the patch
specified at
Hi nice numpy people
I was wondering if anyone could shed some light on how to distinguish an
empty array of a given shape and an zeros array of the same dimensions.
Thanks
Andy
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On Tue, May 6, 2008 at 9:31 AM, Andy Cheesman [EMAIL PROTECTED]
wrote:
Hi nice numpy people
I was wondering if anyone could shed some light on how to distinguish an
empty array of a given shape and an zeros array of the same dimensions.
An empty array is just uninitialized, while a zeros
I'm trying to design a labeled array class. A labeled array contains a
2d array and two lists. One list labels the rows of the array (e.g.
variable names) and another list labels the columns of the array (e.g.
dates).
You can sum (or multiply, divide, subtract, etc.) two labeled arrays
that have
2008/5/6 Andy Cheesman [EMAIL PROTECTED]:
I was wondering if anyone could shed some light on how to distinguish an
empty array of a given shape and an zeros array of the same dimensions.
An empty array, that is, an array returned by the function empty(),
just means an uninitialized array.
On Tue, May 6, 2008 at 10:03 AM, Timothy Hochberg [EMAIL PROTECTED] wrote:
Why don't you just roll your own?
def nans(shape, dtype=float):
... a = np.empty(shape, dtype)
... a.fill(np.nan)
... return a
...
nans([3,4])
array([[ NaN, NaN, NaN, NaN],
[ NaN, NaN,
On Tue, May 6, 2008 at 1:00 PM, Keith Goodman [EMAIL PROTECTED] wrote:
I'm trying to design a labeled array class. A labeled array contains a
2d array and two lists. One list labels the rows of the array (e.g.
variable names) and another list labels the columns of the array (e.g.
dates).
Hi all,
I'm currently working on a function that converts a
sympy (http://code.google.com/p/sympy) expression to a lambda-function.
In this lambda-function all sympy builtin functions are replaced by
numpy functions, since they are faster.
Now it may happen that users pass sympy-symbols like pi
What is .T? It looks like an attribute, behaves like a method, and
smells like magic. I'd like to add it to my class but don't no where
to begin.
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On Tue, May 6, 2008 at 12:28 PM, Robert Kern [EMAIL PROTECTED] wrote:
On Tue, May 6, 2008 at 2:22 PM, Keith Goodman [EMAIL PROTECTED] wrote:
What is .T? It looks like an attribute, behaves like a method, and
smells like magic. I'd like to add it to my class but don't no where
to
On Tue, May 6, 2008 at 4:21 AM, Bala subramanian
[EMAIL PROTECTED] wrote:
Dear Robert,
Thank you. But i am trying to install it in a 32-bit machine only. In that
case, why dose it require 64 bit libraries.
Well, judging from the paths on the command line, Python thinks it is
on a 64-bit
On Tue, May 6, 2008 at 4:33 AM, Vincent Noel [EMAIL PROTECTED] wrote:
Hello all,
I wanted to fix the formatting problems on the wiki page
http://scipy.org/scipy/numpy/wiki/MaskedArrayApiChanges, so I followed
the instructions on http://scipy.org/scipy/numpy/wiki (which state In
order to
2008/5/6 Charles R Harris [EMAIL PROTECTED]:
On Tue, May 6, 2008 at 6:40 AM, Alan G Isaac [EMAIL PROTECTED] wrote:
On Tue, 6 May 2008, Jarrod Millman apparently wrote:
open tickets that I would like everyone to take a brief
look at:
http://projects.scipy.org/scipy/numpy/ticket/760
Hi,
I think Ticket 605 (Incorrect behaviour of numpy.histogram) can be closed.
With regards to Ticket 706 (scalar indexing of matrices - deprecation
warning) I think it should not be a blocker now but should apply the
next version. There were many different issues (and threads) raised in
the
a = numpy.array([[1,2,6], [2,2,8], [2,1,7],[1,1,5]])
a
array([[1, 2, 6],
[2, 2, 8],
[2, 1, 7],
[1, 1, 5]])
indices = numpy.lexsort(a.T)
a.T.take(indices,axis=-1).T
array([[1, 1, 5],
[1, 2, 6],
[2, 1, 7],
[2, 2, 8]])
The above does what I want,
2008/5/6 Eleanor [EMAIL PROTECTED]:
a = numpy.array([[1,2,6], [2,2,8], [2,1,7],[1,1,5]])
a
array([[1, 2, 6],
[2, 2, 8],
[2, 1, 7],
[1, 1, 5]])
indices = numpy.lexsort(a.T)
a.T.take(indices,axis=-1).T
array([[1, 1, 5],
[1, 2, 6],
[2, 1, 7],
Anne Archibald peridot.faceted at gmail.com writes:
It appears that lexsort is broken in several ways, and its docstring
is misleading.
First of all, this code is not doing quite what you describe. The
primary key here is the [5,6,7,8] column, followed by the middle and
then by the
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