NumPy Folks,
Sorry for the self-reply, but I have determined that this may have
something to do with an alpha channel being present. When I remove the
alpha channel, things appear to work as I expect. Any discussion on
the matter?
Brady
On Fri, Jul 12, 2013 at 10:00 PM, Brady McCary wrote:
> Nu
NumPy Folks,
I want to load images with PIL and then operate on them with NumPy.
According to the PIL and NumPy documentation, I would expect the
following to work, but it is not.
Python 2.7.4 (default, Apr 19 2013, 18:28:01)
[GCC 4.7.3] on linux2
Type "help", "copyright", "credits" or "license
Hi All,
I've been working on Benjamin's PR, which I took down as he didn't have
time to finish it. I've made the following changes and thought I'd run them
past others before putting up a new pull request.
1. The new functions are consolidated with the old ones inn (new)
numpy/lib/nanfunct
On Fri, Jul 12, 2013 at 12:53 PM, Alan G Isaac wrote:
> The docs for numpy.sign at
> http://docs.scipy.org/doc/numpy/reference/generated/numpy.sign.html
> do not indicate how complex numbers are handled. Currently, np.sign
> appears to return the sign of the real part as a complex value.
> Was t
On Fri, Jul 12, 2013 at 3:35 PM, Frédéric Bastien wrote:
> I also don't like that idea, but I'm not able to come to a good reasoning
> like Benjamin.
>
> I don't see advantage to this change and the reason isn't good enough to
> justify breaking the interface I think.
>
> But I don't think we rely
Am 10.07.2013 17:06, schrieb Matthew Brett:
> Hi,
>
> On Wed, Jul 10, 2013 at 11:02 AM, Andreas Hilboll wrote:
>> Hi,
>>
>> there are np.flipud and np.fliplr methods to flip 2d arrays on the first
>> and second dimension, respectively. What can I do to flip an array on an
>> axis which I don't kn
Hi all,
FYI new free software for knapsack problem (
http://en.wikipedia.org/wiki/Knapsack_problem ) has been made (written in
Python language); it can solve possibly constrained, possibly (with interalg )
nonlinear and multiobjective problems with specifiable accuracy. Along with
interalg lot
I also don't like that idea, but I'm not able to come to a good reasoning
like Benjamin.
I don't see advantage to this change and the reason isn't good enough to
justify breaking the interface I think.
But I don't think we rely on this, so if the change goes in, it probably
won't break stuff or t
The docs for numpy.sign at
http://docs.scipy.org/doc/numpy/reference/generated/numpy.sign.html
do not indicate how complex numbers are handled. Currently, np.sign
appears to return the sign of the real part as a complex value.
Was this an explicit choice? Was x/abs(x) considered (for non-zero ele
On Fri, Jul 12, 2013 at 4:41 PM, Gregorio Bastardo
wrote:
> array.flags.writeable = False
>
> is perfectly fine, but it does not work on ma-s. Moreover, mask
> hardening only protects masked elements, and does not raise error (as
> I'd expect).
You probably have to modify the underlying array and
Hi,
I use masked arrays to mark missing values in data and found it very
convenient, although sometimes counterintuitive.
I'd like to make a pool of masked arrays (shared between several
processing steps) read-only (both data and mask property) to protect
the arrays from accidental modification (
Hi Scott, thanks for your help.
On 12 July 2013 10:02, Scott Sinclair wrote:
>
> Something like the following should work... [...]
>
Your suggestion works like what I already had. The issue is that the .so
created by the Extension is copied to copying
/lib/python2.7/site-packages/
and not to
/lib
I can see where you are getting at, but I would have to disagree. First of
all, when a comparison between two mis-shaped arrays occur, you get back a
bone fide python boolean, not a numpy array of bools. So if any action was
taken on the result of such a comparison assumed that the result was some
Hey,
the array comparisons == and != never raise errors but instead simply
return False for invalid comparisons.
The main example are arrays of non-matching dimensions, and object
arrays with invalid element-wise comparisons:
In [1]: np.array([1,2,3]) == np.array([1,2])
Out[1]: False
In [2]: np
On 10 July 2013 17:50, Jose Gomez-Dans wrote:
> Hi,
> I am building a package that exposes some Fortran libraries through f2py.
> The packages directory looks like this:
> setup.py
> my_pack/
> |
> |-->__init__.py
> |--> some.pyf
> |---> code.f90
>
> I thoughat that
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