Call Special Functions for Operators Like Python

Operators are implemented with specially named methods like in Python. For details see:
http://docs.python.org/reference/datamodel.html#emulating-numeric-types

SIML uses special methods and data attributes that do not exist in Python. Names for these special attributes begin with the string '__siml_'. With this convention there are no accidental clashes with special attributes from Python, and it can also be easily guessed that theses methods (__siml_foo__) are special methods for the Siml language.

- Assignment:
    __siml_assign__(this, other): performs assignments. Special considerations for fundamental types: Unknown second argument 'other' must be possible.

- Boolean operators:
There are special functions for the boolean operators. The 'and' and 'or' operators are not short-circuit operators like in Python, but both arguments are always evaluated.
    __siml_and2__(this, other): 'and' operator
    __siml_or2__(this, other): 'or' operator
    __siml_not__(this): 'not' operator
In the future the complete algorithm detailed in PEP 335 will be implemented, to get short-circuit behavior.
   http://www.python.org/dev/peps/pep-0335/

- String conversion:
    __siml_str__ behaves like __str__, but returns a Siml string instance.

Proposed method:
- Graph creation:
    __siml_graph__ called by the built in graph function, calls built in graph function on Float attributes.
- Differentiation:
    __siml_diff__(this, distribution_domain): return a derivative of the object. There is a global distribution-domain 'time_domain' that denotes time derivatives. This function is a convenience to retrieve the associated differential, and to declare it if it does not already exist. There should be functionality to explicitly associate an existing variable to an other variable as a derivative of it (associate_derivative(variable, derivative, domain)).