Hi all, (sorry for missing the debate, I don't often check my
numpy-list folder.)
I agree that an "official" numpy solution to this problem is
premature, but at the same time I think the failure to approach
anything remotely resembling a consensus on how to deal with lazy
evaluation is really gumm
It is unfortunate that this was committed to master. This should be backed out
and is a blocker for 1.7. Can someone help me identify which commit made the
change?
This is a rather significant change and changes the documented behavior of
NumPy substantially. This should definitely not o
#! /usr/bin/env python3.2
import numpy
for t in (numpy.float16, numpy.float32, numpy.float64, numpy.float128):
two = t(2)
print(t, two, two ** two, numpy.power(two, two))
"""
I use up-to-date debian testing (wheezy), amd64 architecture. The python
package is python3, version 3.2.3~rc1
Something that we just ran into trying to merge a scipy PR:
With 1.5.1:
>>> np.arange(10)[np.array([0,1,0,1,2,3]) > 0]
array([1, 3, 4, 5])
With current master:
In [1]: np.arange(10)[np.array([0,1,0,1,2,3]) > 0]
---
ValueError
On Sun, Jun 10, 2012 at 2:17 AM, Travis Oliphant wrote:
>
> On Jun 9, 2012, at 4:45 PM, josef.p...@gmail.com wrote:
>
>> Is there a way to convert an array to string elements in numpy,
>> without knowing the string length?
>
> Not really. In the next release of NumPy you should be able to do.
>
