On Tue, Jun 19, 2007 at 05:06:42PM +0900, David Cournapeau wrote:
Robert Kern wrote:
Stefan van der Walt wrote:
On Fri, Jun 15, 2007 at 03:44:37PM -0400, David M. Cooke wrote:
I meet a problem when I installed numpy. I installed numpy by the command
python setup.py install. Then I tested
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
On 6/19/2007 12:19 PM, Sven Schreiber wrote:
To be more specific, I would expect shape==(4,14).
h = numpy.zeros((1,4,14))
h[0,:,numpy.arange(14)].shape
(14, 4)
h[0,:,:].shape
(4, 14)
h[0,:,numpy.arange(14)] is a case of sdvanced indexing. You can also
see that
On 6/19/2007 12:14 PM, Sturla Molden wrote:
h[0,:,numpy.arange(14)] is a case of sdvanced indexing. You can also
see that
h[0,:,[0,1,2,3,4,5,6,7,8,9,10,11,12,13]].shape
(14, 4)
Another way to explain this is that numpy.arange(14) and
[0,1,2,3,4,5,6,7,8,9,10,11,12,13] is a sequence
On Tue, Jun 19, 2007 at 12:35:05PM +0200, Sturla Molden wrote:
On 6/19/2007 12:14 PM, Sturla Molden wrote:
h[0,:,numpy.arange(14)] is a case of sdvanced indexing. You can also
see that
h[0,:,[0,1,2,3,4,5,6,7,8,9,10,11,12,13]].shape
(14, 4)
Another way to explain this is that
On 6/19/2007 1:28 PM, Stefan van der Walt wrote:
x = N.arange(100).reshape((10,10))
x[:,N.arange(5)].shape
should be (5, 10), while in reality it is (10, 5).
y = numpy.arange(100).reshape((10,10))
y[:,numpy.arange(5)].shape
(10,5)
x = numpy.arange(100).reshape((1,10,10))
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
Stefan van der Walt schrieb:
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Dear numpy experts,
I see from the docs that there seem to be 3 sorting algorithms for array
data (quicksort, mergesort and heapsort). After hearing a rumour about
radix sorts and floats I google'd and now I'm wondering about a radix
sort for numpy (and Numeric) scalars? See:
On 6/19/07, Jon Wright [EMAIL PROTECTED] wrote:
Dear numpy experts,
I see from the docs that there seem to be 3 sorting algorithms for array
data (quicksort, mergesort and heapsort). After hearing a rumour about
radix sorts and floats I google'd and now I'm wondering about a radix
sort for
Bug
===
In [8]: N.info(N.ones(3))
class: ndarray
shape: (3,)
strides: (8,)
itemsize: 8
aligned: True
contiguous: True
fortran: True
---
TypeError Traceback (most recent call last)
Fernando Perez wrote:
Question
any objection if I commit this? Since I don't really touch the
codebase often, I'd rather ask the real core people. I also don't
know if it's really the right thing to do, I just tabbed into the
object and picked what seemed to be the most
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