[Numpy-discussion] numpy all unexpected result (generator)
Dag Sverre Seljebotn
Tue Jan 31 08:14:24 CST 2012
On 01/31/2012 03:07 PM, Robert Kern wrote:
> On Tue, Jan 31, 2012 at 13:26, Neal Becker<email@example.com> wrote:
>> I was just bitten by this unexpected behavior:
>> In : all ([i> 0 for i in xrange (10)])
>> Out: False
>> In : all (i> 0 for i in xrange (10))
>> Out: True
>> Turns out:
>> In : all is numpy.all
>> Out: True
>> So numpy.all doesn't seem to do what I would expect when given a generator.
> Expected behavior. numpy.all(), like nearly all numpy functions,
> converts the input to an array using numpy.asarray(). numpy.asarray()
> knows nothing special about generators and other iterables that are
> not sequences, so it thinks it's a single scalar object. This scalar
> object happens to have a __nonzero__() method that returns True like
> most Python objects that don't override this.
> In order to use generic iterators that are not sequences, you need to
> explicitly use numpy.fromiter() to convert them to ndarrays. asarray()
> and array() can't do it in general because they need to autodiscover
> the shape and dtype all at the same time.
Perhaps np.asarray could specifically check for a generator argument and
raise an exception? I imagine that would save people some time when
running into this...
If you really want
In : x = np.asarray(None)
In : x[()] = (i for i in range(10))
In : x
Out: array(<generator object <genexpr> at 0x4553fa0>, dtype=object)
...then one can type it out?
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