On Tue, May 19, 2015 at 4:41 AM, Carsten Knoll <[email protected]> wrote:
> On 05/19/2015 07:48 AM, Joachim Durchholz wrote:
>>
>> An external dictionary isn't ideal but better than this, at least from
>> the maintainer's perspective.
>>
>>>> Maybe we can give you better help if you describe your use case in some
>>>> more detail.
>>>
>>> At some point I create symbols from which I know, that they are
>>> derivatives and I want to store their order. Using the classes Function
>>> and Derivative is no real option because I want the symbols to behave as
>>> symbols on most occasions.
>>
>> Ah. This sounds like a design problem in Derivative to me that we should
>> fix.
>> Can you post what you did, what you'd have needed to get out, and what
>> SymPy gave you?
>
> I think strongest argument for me was that the string representation of
> the expressions gets too long for Functions and Derivatives. This
> reduces my chance to "see" any structure.
>
> Second argument is that I have a (own) library for modeling differential
> forms which internally uses Symbol and does not straight forwardly work
> with Function instances.
>
> E.g.
>
> x.name -> 'x'
> x(t).name -> AttributeError

That's because x(t) is not really an instance of x. Symbol implements
__call__ so that x(t) returns a Function object (a completely
different class).

Aaron Meurer

>
> However, this discussions make me think, if using Functions would not be
> the better alternative
>
>>
>>> In general, I think there are situations, where it might be useful to
>>> store some algorithm-specific extra information to some symbols.
>>
>> For algorithms of SymPy itself, I think the algorithms should be fixed :-)
>>
>> It would be useful for coding external algorithms, but it does come with
>> ramifications (most importantly the potential for namespace conflicts);
>> from a maintenance perpective, it's far better if such an algorithm does
>> its own data management.
>
> OK. I can perfectly live with this.
>
>
>
>
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