On Mon, May 9, 2011 at 6:39 PM, Ondrej Certik <ond...@certik.cz> wrote:
> On Mon, May 9, 2011 at 6:33 PM, Aaron Meurer <asmeu...@gmail.com> wrote:
>> On Mon, May 9, 2011 at 7:30 PM, Ronan Lamy <ronan.l...@gmail.com> wrote:
>>> Le lundi 09 mai 2011 à 17:30 -0700, Luke a écrit :
>>>> Here is a more explicit example of what Gilbert is talking about:
>>>> In [1]: from sympy import *
>>>> In [2]: from pydy import *
>>>> In [3]: x = symbols('x')
>>>> In [4]: N = ReferenceFrame('N')
>>>> In [5]: type(N[1])
>>>> Out[5]: pydy.pydy.UnitVector
>>>> In [9]: test = x*N[1] + x*x*N[2]
>>>> In [10]: type(test)
>>>> Out[10]: sympy.core.add.Add
>>>> In [11]: test2 = Vector(test)
>>>> In [12]: test2
>>>> Out[12]: x*n1> + x**2*n2>
>>>> In [13]: type(test2)
>>>> Out[13]: pydy.pydy.Vector
>>>> In [14]: test3 = x*test2
>>>> In [15]: test3
>>>> Out[15]: x*x*n1> + x**2*n2>
>>>> In [16]: type(test3)
>>>> Out[16]: sympy.core.mul.Mul
>>>>
>>>> As you can see, in Out[15], the multiplication of x and test2 is being
>>>> printed in a way that doesn't make sense, and in Out[16] we can see
>>>> that this multiplication isn't resulting in another Vector object,
>>>> instead it is of type Mul.
>>>>
>>>> Currently, to create a Vector object, you need to explicitly call
>>>> Vector on a sympy expression that is composed from terms that have
>>>> UnitVectors in them, or pass a dictionary with UnitVectors as the keys
>>>> and sympy expressions as the values.
>>>>
>>>> Once you have that Vector object, you might want to multiply it by a
>>>> scalar (sympy expression) and have it return another Vector object.
>>>> This could be done using a somewhat user unfriendly approach:
>>>>
>>>> In [22]: Vector(dict([(k, x*v) for k, v in test2.dict.items()]))
>>>> Out[22]: x**2*n1> + x**3*n2>
>>>>
>>>> This gets the job done, but it isn't very convenient.
>>>>
>>>> So basically, the question is whether
>>>> 1) Is it easy enough in Sympy to make something like x*aVectorObject
>>>> evaluate to another Vector object? Where the x is a "scalar part"
>>>> (probably a sympy Expression) and aVectorObject is of type Vector
>>>> (which currently subclasses from Basic)?
>>>
>>> No, currently, it's not possible to do it correctly. Expr objects don't
>>> expect to be multiplied by non-Expr objects. However, changing this
>>> should be possible: you'd have to add to all relevant __mul__ methods
>>> something like 'if not isinstance(other, Expr): return NotImplemented'.
>>> And then, you'll only have to fight Python's labyrinthine model for
>>> double-dispatch inside your vector classes.
>>
>> Oh, OK, so you were thinking the same thing that I was. Yes, let's do
>> this then. It seems to make the most sense. Expr is supposed to be
>> only mathematical objects, like things that can be part of a Mul, so
>> allowing non-Exprs to multiply Exprs doesn't make much sense.
>
> That'd be great to allow people to extend sympy with their own objects.
>
> So is the proposal to try to coerce an object to an Expr instance, so
> things like Symbol, Python int, etc. would succeed, and if so, Expr
> will take over. Otherwise the other non Expr instance will be given a
> chance to take over the operation (no matter which side you operate on
> the Expr object)? If this can be implemented, that'd be great.
>
> But I thought that exactly this was already implemented using the
> _op_priority, see sympy/core/expr.py, line 22:
>
> # Expr and its sublcasses use _op_priority to determine which object
> # passed to a binary special method (__mul__, etc.) will handle the
> # operation. In general, the 'call_highest_priority' decorator will choose
> # the object with the highest _op_priority to handle the call.
> # Custom subclasses that want to define their own binary special methods
> # should set an _op_priority value that is higher than the default.
> _op_priority = 10.0
>
>
> What am I missing?
For usage, see:
sympy/core/tests/test_priority.py
Ondrej
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