Fix Parameter Generator
The generation of parameters for the Lorenz example was presenting issues:
- Parameters are always the same, the
iter_param_set
was not actually iterating; - Active learning, which requires on the fly change of the parameter was not easily feasible.
This MR introduces a ParameterGenerator
class that exposes a draw_parameters
function that can work with iterators and be changed on-the-fly for active learning. The server only call the draw_parameters
that can be directly instanciated as for HeatPDE
or interfaced with a ParameterGenerator
class as done now in the Lorenz
example.