Draft: Fix #103: Update load surrogates

This MR serves as a replacement for the current interface to TensorFlow, and implements the following features:

• Definition of a new abstract class Transformer, for transforming the input and output. Classes coded according to this interface can transform the data, both in-place and out-of-place, and provide the analytical gradient. Moreover, the object can be saved into an HDF5 file.
• Implementation of MinMaxScaler from scikit-learn into the new interface.
• Implementation of StandardScaler from scikit-learn into the new interface.
• Implementation of PowerTransformer from scikit-learn into the new interface.
• Implementation of a SurrogateModel class, that stores 1 generic surrogate model. It can save and load the model into 2 files, one for the model itself, and the other for the extra data, in HDF5 format. The predict_output() function can apply an arbitrary number of input and output transformations. The predict_jacobian() function provides the analytical gradient using the chain rule.
• Implementation of a TensorFlowModel class, that encapsulates a TensorFlow model.
• Implementation of a SurrogateModelFamily class, that stores several surrogate models and evaluates them in the respective regions of validity.
• Test for 100% coverage.