On Thu, Sep 27, 2012 at 6:08 PM, Sergio Pascual sergio.pa...@gmail.com wrote:
Hello, I'm trying to understand how to work with nditer to do a
reduction, in my case converting a 3d array into a 2d array.
I followed the help here
http://docs.scipy.org/doc/numpy/reference/arrays.nditer.html and
Hi,
Le 28/09/2012 21:02, Neal Becker a écrit :
In [19]: u = np.arange (10)
In [20]: v = np.arange (10)
In [21]: u[v] = u
In [22]: u[v] = np.arange(11)
silence...
I've same behavior with my numpy 1.6.2.
It indeed looks strange that the end of the data vector is dropped in
silence.
Best,
Hi,
On Mon, Oct 1, 2012 at 9:04 AM, Pierre Haessig pierre.haes...@crans.org wrote:
Hi,
Le 28/09/2012 21:02, Neal Becker a écrit :
In [19]: u = np.arange (10)
In [20]: v = np.arange (10)
In [21]: u[v] = u
In [22]: u[v] = np.arange(11)
silence...
I've same behavior with my numpy 1.6.2.
On Sun, Sep 30, 2012 at 8:59 PM, Travis Oliphant tra...@continuum.io wrote:
Hey all,
In a github-discussion with Gael and Nathaniel, we came up with a proposal
for .base that we should put before this list.Traditionally, .base has
always pointed to None for arrays that owned their own
On Sun, Sep 30, 2012 at 7:22 PM, Gael Varoquaux
gael.varoqu...@normalesup.org wrote:
On Sun, Sep 30, 2012 at 07:17:42PM +0100, Nathaniel Smith wrote:
Is there anything better to do than simply revert np.copy() to its
traditional behaviour and accept that np.copy(a) and a.copy() will
continue
On 09/30/2012 03:59 PM, Travis Oliphant wrote:
Hey all,
In a github-discussion with Gael and Nathaniel, we came up with a proposal
for .base that we should put before this list.Traditionally, .base has
always pointed to None for arrays that owned their own memory and to the
most
On Mon, Oct 1, 2012 at 6:20 AM, Nathaniel Smith n...@pobox.com wrote:
On Sun, Sep 30, 2012 at 8:59 PM, Travis Oliphant tra...@continuum.io
wrote:
Hey all,
In a github-discussion with Gael and Nathaniel, we came up with a
proposal for .base that we should put before this list.
On Mon, Oct 1, 2012 at 8:35 AM, Nathaniel Smith n...@pobox.com wrote:
On Sun, Sep 30, 2012 at 7:22 PM, Gael Varoquaux
gael.varoqu...@normalesup.org wrote:
On Sun, Sep 30, 2012 at 07:17:42PM +0100, Nathaniel Smith wrote:
Is there anything better to do than simply revert np.copy() to its
On Mon, Oct 1, 2012 at 8:20 AM, Nathaniel Smith n...@pobox.com wrote:
[...]
How can we discourage people from doing this in the future? Can we
make .base write-only from the Python level (with suitable deprecation
period)? Rename it to ._base (likewise) so that it's still possible to
peek
On Mon, Oct 1, 2012 at 3:40 PM, Thouis (Ray) Jones tho...@gmail.com wrote:
On Mon, Oct 1, 2012 at 8:20 AM, Nathaniel Smith n...@pobox.com wrote:
[...]
How can we discourage people from doing this in the future? Can we
make .base write-only from the Python level (with suitable deprecation
All,
I've submitted the following pull request for NumPy:
https://github.com/numpy/numpy/pull/462
This change allows ufuncs to be registered for structured arrays by using a
new API method PyUFunc_RegisterLoopForStructType. For example, a ufunc
could be registered to take two arrays of type
Hey,
About the imaginary part being ignored for all/any function...
snip
The all method fails also.
In [1]: a = zeros(5, complex)
In [2]: a.imag = 1
In [3]: a.all()
Out[3]: False
Chuck
I believe this diff fixes the issue (also posted on Tracker), I doubt
its the best way to fix
On Mon, Oct 1, 2012 at 10:09 AM, Sebastian Berg
sebast...@sipsolutions.netwrote:
Hey,
About the imaginary part being ignored for all/any function...
snip
The all method fails also.
In [1]: a = zeros(5, complex)
In [2]: a.imag = 1
In [3]: a.all()
Out[3]: False
Chuck
I
On Mon, 2012-10-01 at 10:59 -0600, Charles R Harris wrote:
On Mon, Oct 1, 2012 at 10:09 AM, Sebastian Berg
sebast...@sipsolutions.net wrote:
Hey,
About the imaginary part being ignored for all/any function...
snip
Sounds like I'm not the only one surprised then:
http://projects.scipy.org/numpy/ticket/2220
Matthew Brett wrote:
Hi,
On Mon, Oct 1, 2012 at 9:04 AM, Pierre Haessig pierre.haes...@crans.org
wrote:
Hi,
Le 28/09/2012 21:02, Neal Becker a écrit :
In [19]: u = np.arange (10)
In [20]: v =
Paul,
Nice to see someone working on these issues, but:
I'm not sure the problem you are trying to solve -- accumulating in a
list is pretty efficient anyway -- not a whole lot overhead.
But if you do want to improve that, it may be better to change the
accumulating method, rather than doing
On Fri, Sep 28, 2012 at 3:11 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
If the behaviour is not specified and tested, there is no guarantee that it
will continue.
This is an open-source project - there is no guarantee of ANYTHING.
But that being said, the specification and testing
On Sat, Sep 29, 2012 at 2:16 AM, Gael Varoquaux
gael.varoqu...@normalesup.org wrote:
Next time I see you, I owe you a beer for making you cross :).
If I curse at you, will I get a beer too?
-Chris
--
Christopher Barker, Ph.D.
Oceanographer
Emergency Response Division
NOAA/NOS/ORR
Hi,
One of our kind users pointed out an error when using easy_install to
install our package nipy. I've reproduced it now on a bare package
using numpy distutils and having a trivial extension:
https://github.com/matthew-brett/apkg
To reproduce:
git clone
Hi,
On Mon, Oct 1, 2012 at 9:42 PM, Matthew Brett matthew.br...@gmail.com wrote:
Hi,
One of our kind users pointed out an error when using easy_install to
install our package nipy. I've reproduced it now on a bare package
using numpy distutils and having a trivial extension:
On Mon, Oct 1, 2012 at 2:32 PM, Chris Barker chris.bar...@noaa.gov wrote:
On Sat, Sep 29, 2012 at 2:16 AM, Gael Varoquaux
gael.varoqu...@normalesup.org wrote:
Next time I see you, I owe you a beer for making you cross :).
If I curse at you, will I get a beer too?
Wow! This is taking a
Perhaps sum wasn't the best function for this example. I'm going to
rework the code with other function
Consider a function that operates on an array and returns a number
def myfunc(data):
return data.min() + 2 * data.max()
The function with nditer is:
def nditer_fun(data, axes):
it =
Hello Jay,
Cool idea! I like to see work on structured arrays. Just a couple of
questions:
- Since there are already have ufuncs for primitive dtypes (int, float,
etc), and you are just acting columnwise here, can't you write a single
function which interprets the dtypes, gathers the
On Oct 1, 2012, at 9:11 AM, Jim Bosch wrote:
On 09/30/2012 03:59 PM, Travis Oliphant wrote:
Hey all,
In a github-discussion with Gael and Nathaniel, we came up with a proposal
for .base that we should put before this list.Traditionally, .base has
always pointed to None for arrays
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