Preprocessing includes building the InputSpace, checking the input dimensions and assigning the inputs to parameters.

Some surrogate strategies and PostProcessing options need to be reworked

Tested static training with PCE on analytical example, remaining changes tbd for sequential training and postprocessing

All combinations of tradeoff-exploration-exploitation run through with SeqDesign. Reverted BayesInf to the current develop branch

example_analytical_function_testSequential runs through all the sequential options and contains notes on which do not work.
Choose_next sample now uses only one set of candidate samples

Webpage includes quickstart, user guide, tutorial, example collection and api.
One new example was added for the user guide.

An example 'principal_component_analysis' was added to specifically test this functionality. It uses the analytical model.
Fixed two if-calls in `pca_transformation` to match older code and the content of the function.

This merge is to be a part of release 1.1.0.
It contains bug fixes and restructuring of the classes BayesInference and BayesianModelComparison, as well as new tests and examples and the first draft of a package-specific website.

Webpage includes quickstart, user guide, tutorial, example collection and api.
One new example was added for the user guide.

An example 'principal_component_analysis' was added to specifically test this functionality. It uses the analytical model.
Fixed two if-calls in `pca_transformation` to match older code and the content of the function.

MCMC does not receive the whole BayesInf object anymore, performance of inference now should be back up to speed with MCMC. In future perhaps rework so that MCMC is a child class of BayesInf?

This reverts merge request !18

This reverts commit acf483a1

More test for BayesInf, starting tests for MCMC

Some simple fixes for various test, start on testing BayesInf, output directory as changeable parameter in BayesInf

Solved some issues from rebasing

In this scope the multiprocessing for running the models does not seem to work correctly anymore

Got started on these two tasks, restructuring still needs a lot of work here

Code updated for static training, tests not done yet

New class 'Engine' responsible for both training sequentially and non-sequentially.
Currently training with old MetaModEngine and in MetaMod directly still possible, but will be deprecated and removed soon.
Also started splitting ExpDesign into InputSpace (for MetaMod, created dists and polynomials) and ExpDesign (for Engine, can also sample)

Started testing MetaModel while also refactoring a bit more by moving code between ExpDesign and MetaModel