Redesign C++ code to be more generic

[BerndDoser]

The first version of PINK was written basically in C-style and we have duplicated code for CPU and GPU execution. Therefore, for PINK version 2 we would like to rewrite the code to get a more generic structure to avoid the CPU/GPU code duplication and to enable the implementation of an python interface, so that the C++ functions can be called directly in python.

The development will be performed in the branch https://github.com/HITS-AIN/PINK/tree/redesign.

The basic idea is to separate data and algorithm classes and to formulate the SOM, neurons and training objects as LayoutTypes. We start with the two LayoutTypes Cartesian<dim, T> and Hexagonal<T>, where dim is the dimension of the cartesian grid and T the data type, e.g. float. A image has then the type Cartesian<2, float>. The type of a 2-dimensional, cartesian SOM would be Cartesian<2, Cartesian<2, float>> or Hexagonal<Cartesian<2, float>> for a hexagonal SOM.

The SOM training and mapping algorithms are formulated as Functors, where the call operator gets the SOM and the training data object:

struct Trainer {
    template <typename SOMType>
    void operator () (SOMType& som, typename SOMType::NeuronType const& image) const;
};

The new design makes it also easier to add new SOM types and training algorithms.

Discussions and suggestions are always welcome.