On Friday, April 21, 2017 at 3:46:03 PM UTC+1, David Roe wrote:
>
> Quick guess (don't have time to look at this soon): the issue could be in
> the action discovery code, which may try creating elements of numpy.float32
> using weird inputs. This could cause a difference between right and left
> multiplication. One way to check if this is the source is to try converting
> each of the polynomials from RR['x'].some_elements() into numpy.float32 and
> see if you get the same error.
>
no, this does not give anything that looks like the error in question (no
errors on degree 0 terms,
"ValueError: setting an array element with a sequence." on degree >0 terms)
>
> On Apr 21, 2017 05:10, "Dima Pasechnik" <dim...@gmail.com <javascript:>>
> wrote:
>
> On Friday, April 21, 2017 at 9:11:37 AM UTC+1, Marc Mezzarobba wrote:
>>
>> Dima Pasechnik wrote:
>> > but it looks as if it might be a coercion problem.
>> > Any ideas where to look?
>>
>> Not really, but it does look like the common parent
>> discovered by the coercion system is incorrect:
>>
>> sage: import numpy as np
>> sage: a = np.float('1.5')
>> sage: b = np.float32('1.5')
>>
>
>
>> sage: get_coercion_model().common_parent(b, polygen(RR))
>> Univariate Polynomial Ring in x over Real Field with 53 bits of
>> precision
>>
>> sage: RR.coerce(a)
>> 1.50000000000000
>>
>> sage: RR.coerce(b)
>> ...
>> TypeError: no canonical coercion from <type 'numpy.float32'> to Real
>> Field with 53 bits of precision
>>
>> sage: get_coercion_model().common_parent(b, RR)
>> <type 'numpy.float32'>
>>
>
> This does not look like this is the root cause of the problem.
> Namely, note that also
>
> sage: a128 = np.float128('1.5')
> sage: RR.coerce(a128)
> # throws the same as above TypeError, but
> sage: a128*x
> # does not print the numpy warning.
>
> what is also somewhat puzzling is
> that while
> sage: np.float32('1.5')*x
> # does print the numpy warning
>
> sage: x*np.float32('1.5')
> # just works (i.e. does not print the numpy warning)
>
> So this is a subtle combination of an apparent bug in numpy (or in clang)
> with
> some Sage coercion weirdness.
> Apparently numpy's floats are coerced into RDF for the purpose of
> dealing with polynomials, see py_scalar_to_element in
> structure/coerce.pyx, but apparently this only happens
> for
> x*np.float32('1.5'), and not for np.float32('1.5')*x ?
>
> Dima
>
>
>
>> --
>> Marc
>>
>> --
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