On Thu, Jul 4, 2013 at 8:01 PM, David Schaich wrote:
> Hi all,
>
> I recently adopted python, and am in the process of replacing my old
> analysis tools. For simple (e.g., linear) interpolations and
> extrapolations, in the past I used gnuplot. Today I set up the
> equivalent with polyfit in numpy
Hi all,
I recently adopted python, and am in the process of replacing my old
analysis tools. For simple (e.g., linear) interpolations and
extrapolations, in the past I used gnuplot. Today I set up the
equivalent with polyfit in numpy v1.7.1, first running a simple test to
reproduce the gnuplot
round() does not consistently preserve subtype of the ndarray,
is this known behaviour or should I file a bug for it?
Python 2.7.3 (default, Sep 26 2012, 21:51:14)
[GCC 4.7.2] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import numpy as np
>>> np.version.v
On Thu, Jul 4, 2013 at 9:12 AM, sebastian wrote:
> On 2013-07-04 15:06, Thomas Robitaille wrote:
> > Hi everyone,
> >
> > The following example:
> >
> > import numpy as np
> >
> > class SimpleArray(np.ndarray):
> >
> > __array_priority__ = 1
> >
> > def __new__(cls, inp
On 2013-07-04 15:06, Thomas Robitaille wrote:
> Hi everyone,
>
> The following example:
>
> import numpy as np
>
> class SimpleArray(np.ndarray):
>
> __array_priority__ = 1
>
> def __new__(cls, input_array, info=None):
> return np.asarray(input_array).vi
Hi,
__array__priority wasn't checked for ==, !=, <, <=, >, >= operation. I
added it in the development version and someone else back-ported it to the
1.7.X branch.
So this will work with the next release of numpy.
I don't know of a workaround until the next release.
Fred
On Thu, Jul 4, 2013 a
Hi everyone,
The following example:
import numpy as np
class SimpleArray(np.ndarray):
__array_priority__ = 1
def __new__(cls, input_array, info=None):
return np.asarray(input_array).view(cls)
def __eq__(self, other):
return False
