John Hunter schrieb:
Is it desirable that numpy.corrcoef for two arrays returns a 2x2 array
rather than a scalar
In [10]: npy.corrcoef(npy.random.rand(10), npy.random.rand(10))
Out[10]:
array([[ 1., -0.16088728],
[-0.16088728, 1.]])
I always end up extracting
David Cournapeau schrieb:
Well, I think nobody argues that scipy function should crash whatever
input you give :). The problem is more how to treat them. For example,
using numpy.linalg.pinv crashes numpy right now, det and fft do not
work, and norm returns 0. This is seems inconcistent to
Travis Oliphant schrieb:
Sturla Molden wrote:
x = numpy.arange(100).reshape((1,10,10))
x[0,:,numpy.arange(5)].shape
(5, 10)
x[:,:,numpy.arange(5)].shape
(1, 10, 5)
It looks like a bug that needs to be squashed.
These are both correct. See my previous posts about the rule.
Sven Schreiber schrieb:
Tom K. schrieb:
h = zeros((1, 4, 100))
h[0,:,arange(14)].shape
(14, 4)
After reading section 3.4.2.1 of the numpy book, I also still don't
expect this result. So if it's not a bug, I'd be glad if some expert
could explain why not.
To be more specific, I would
Sturla Molden schrieb:
x = numpy.arange(100).reshape((1,10,10))
x[0,:,numpy.arange(5)].shape
(5, 10)
x[:,:,numpy.arange(5)].shape
(1, 10, 5)
It looks like a bug that needs to be squashed.
S.M.
And you already had me convinced ;-)
I'm still curious which one's the bug and
Alex schrieb:
I run VMWare Player and it works fine - easy to setup and easy to
setup a Matlab replacement. I only wonder how to transfer files
between the Windows XP and the Ubuntu VM?
Apart from using usb sticks (AFAIK VMware still has issues with usb 2.0
though) I think the experts usually
Albert Strasheim schrieb:
Hello
On Sun, 27 May 2007, Sven Schreiber wrote:
Hi,
I am wondering whether it's possible to pass (and get back) arrays of
complex floats via ctypes.
To be concrete, I have managed to access lapack's dgges (Fortran)
function using ctypes (thanks to a related
Matthew Brett schrieb:
Can I resurrect this thread then by agreeing with Chris, and my
original post, that it would be better if median had the same behavior
as mean, accepting axis and dtype as inputs?
Well I'm not a developer but I guess there is a backwards-compatibility
issue here. I mean
Charles R Harris wrote:
On 4/3/07, *Travis Oliphant* [EMAIL PROTECTED]
NumPy 1.0.2 was released yesterday (4-02-07). Get it by following the
And thanks for getting it out.
From me too!
-sven
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Travis Oliphant schrieb:
O.K. So, the problem is that when I defined matrix multiplication, I
mistakenly believed that dot always interpreted 1-d arrays as row
vectors which it is now clear it doesn't.
I think this led to the issues.
So, making dot always return arrays seems like the
Tiziano Zito schrieb:
The optional symeig module contains a Python wrapper for the LAPACK
functions to solve the standard and generalized eigenvalue problems
for symmetric (hermitian) positive definite matrices. Those
specialized algorithms give an important speed-up with respect to the
Alan G Isaac schrieb:
What feels wrong: iterating over a container does not give
access to the contained objects. This is not Pythonic.
If you iterate over the rows of the matrix, it feels natural to me to
get the row vectors -- and as you know a 1d-array does not contain the
information
David Koch schrieb:
Hi,
naive question - how do I get an overview over everything to do with
sparse functionality in SciPy 0.5.2 ... I can't find any documentation
anywhere.
First of all I would recommend to start a new and properly named thread
for that
good luck,
sven
Zachary Pincus schrieb:
Hello all,
It seems that the 'eigh' routine from numpy.linalg does not follow
the same convention as numpy.linalg.eig in terms of the order of the
returned eigenvalues. (And thus eigenvectors as well...)
I was told on this list that the ordering should not be
Travis Oliphant schrieb:
I think it's time for the 1.0.2 release of NumPy.
What outstanding issues need to be resolved before we do it?
Hi,
I just used real_if_close for the first time, and promptly discovered
that it turns matrix input into array output:
import numpy as n
Martin Spacek schrieb:
Just a note that I've copied over the 1.0.1 release notes from SourceForge:
http://sourceforge.net/project/shownotes.php?group_id=1369release_id=468153
over to the wiki:
http://scipy.org/ReleaseNotes/NumPy_1.0
Thank you!
Should 1.0.1 get its own page, as
Sven Schreiber schrieb:
Hi,
the kron(a,b) function seems to allow shapes such as (0,x) or (y,0) only
for the second argument b, not for the first argument a. (See below for
examples.)
Maybe it's too harsh to call it a bug because the result is typically
not defined mathematically
Matt Knox schrieb:
I am definitely in favor of the new maskedarray implementation. I've been
working with Pierre on a time series module which is a subclass of the new
masked array implementation, and having it as a subclass of ndarray definitely
has advantages (and no real disadvantages
Vincent Nijs schrieb:
If there is an easy way to read array data + variable names using the csv
module it would be great if that could be added to cookbook/InputOutput. I
couldn't figure out how to do it.
Hi Vincent, of course it depends a little on how exactly your csv file
looks like,
Sven Schreiber schrieb:
Hi Vincent, of course it depends a little on how exactly your csv file
looks like, but if you just have column headers and the actual data, you
might try something like the following:
Ok sorry the previous thing doesn't work, I also stumbled over the
strings. Here's
Vincent Nijs schrieb:
I am tryin to convert some of my time-series code written in Ox to
scipy/numpy (e.g., unit root tests, IRFs, cointegration, etc). Two key
functions I need for this are 'lag' and 'diff'. 'diff' is available but
'lag' is apparently not.
Below is my attempt at a lag
Robert Kern schrieb:
Pierre GM wrote:
Talking about that, what happened to these projects of modular installation
of scipy ? Robert promised us last month to explain what went wrong with his
approach, but never had the time...
I created a module (scipy_subpackages.py, IIRC) next to
Sven Schreiber schrieb:
Keith Goodman schrieb:
There are many numpy functions that will take a matrix as input but
return an array.
The nan functions (nanmin, nanmax, nanargmin, nanargmax, nansum) are an
example.
So that would be a bug IMHO and should be filed as a ticket. I will do
A. M. Archibald schrieb:
On 20/12/06, Alan G Isaac [EMAIL PROTECTED] wrote:
This is my most missed functionality in NumPy.
(For now I feel cannot ask students to install SciPy.)
Although it is a slippery slope, and I definitely do not
want NumPy to slide down it, I would certainly not
Keith Goodman schrieb:
There are many numpy functions that will take a matrix as input but
return an array.
The nan functions (nanmin, nanmax, nanargmin, nanargmax, nansum) are an
example.
So that would be a bug IMHO and should be filed as a ticket. I will do
that eventually if nobody
[you probably should have started a new thread instead of replying to
another one...]
Giorgio Luciano schrieb:
In the old file I created a matrix on the fly. I know that Numpy and
python cannot do that so I found a workaround
I'm not sure what you mean what numpy cannot do, but...
here's
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