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Matrix compatibility and interdependent components (#201)

* Any valid Expr or MatrixExpr that is not a Parameter is now a valid variable

* Added variabletuple to replace namedtuple

* Treat derivatives wrt parameters as Variables in their own right.

This means that they are considered as Variables when using seperate_symbols, and are replaced by a Variable upon printing to a python callable.

* Added matrix methods to the printer.

* Update objectives to the notation that not all model vars are dependent vars: explicitely use self.model.dependent_vars where needed.

* A minimizers called with a symfit model will now also accept that, not wrap it twice as before by accident.

* BaseModel now supports the notation of interdependent_vars: Variables shared between components.

* Fixed #84, models are now printed to resemble a list, which they always are even when scalar.

* connectivity_mapping added for numerical models.

* eval_components now uses the topological order to eval components.

* Introduce BaseGradientModel for Models which have a derivative

* Numerical models now also use the connectivity_mapping to create python callables for analytical components.

* Massive cleanup of Model: removed all references to chi_squared, and hessians and jacobians are now seperate models.

* Added methods to build the jacobian, hessian and least-squares from a model.

* Massive cleanup on Constraint: most of the special needs for constraints have been eliminated.

They now only differ from Model in that they have a type (e.g. Eq), and they always have all parameters of the model present.

* Updated the analytical fit models and TaylorModel to the new paradigm.

* Updated HasCovarianceMatrix.

* Removed some fossil code

* Made ODEModel compatible with the new paradigm, though they do not support interdependent components. (yet?)

* Constraints can be initiated with parameters directly.

* Updated test to the fact t... (continued)

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Source Files on job 677.2