Allow for three model options: Ridge, ARD and BNN.

• Allow for three models using a constructor argument: method_type, which can be "ard", "bnn" or "ridge". By default: "ard".
• ARD prunes the weights, making this more resilient to noise.
• ARD does not accept weighting, but after using the XGM intensity in the model, the weighting is not very helpful anyway, so removed it by default (although still possible here).
• Removed multi output optimization for ARD, since it does not work in this case. Use generic parallelization for ARD and keeping the vectorization of the multi-output meta-estimator only for Ridge.
• Adapted plotting scripts for testing and outputting CSV for plots too, in case we want to do plots offline.
• Check number of peaks in SPEC spectrum. If it is less than 3, exclude it from training. This pre-selects SPEC data to avoid using low-quality data.