The structure of Meteo2DInterpolator has been brought closer to the structure of DataGenerators. More methods are static.

In order to avoid re-parsing the resampling parameters for every point, the resampling algorithms have been restructured as classes inheriting from an interface class alongside an object factory. This should slightly increase the performances of resampling and clears the way (90% of the work being done) for a per-parameter window size (issue 173).

A useful link has been added to the comments of Sun and some comments improved in DataGenerators

The dataGenerators can now process all parameters (ie including the extra parameters) properly. This makes it possible to create a new parameter by using a COPY followed by *0, +nodata filters and then fill the now empty new parameter with a data generator (very useful to compare generated values with a reference measurement). Moreover the processing overhead should have been reduced by looping over the declared generators instead of over the parameters.

In order to implement an efficient and portable object serialization, it has been decided that all serializable objects would be manually serialized to an std::iostream. Then, the parallelization framework (mpi, popc, etc) can take over this stream and move it to another node. Therefore, the operators "<<" and ">>" are now reserved for serialization (as seems to be standard) and the debug outputs are obtained by printing "object.toString()". This means that all debug code has potentially to be fixed, by replacing "std::cout << object" by "std::cout << object.toString()".

The METEO_TIMSERIES and STATION_TIMESERIES have been renamed in METEO_SET and STATIONS_SET in order to better reflect their content. 

The concept of data generators is introduced. A new section has been created [Generators] to define how to generate data for each parameter when everything else failed. Soon, you will be able to generate ILWR directly by declaring it in your io.ini!