Constraints with arbitrary callables #11
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…tput of ParameterHandler.get_parameter_names_for_type into ParameterHandler.get_parameters_by_name to get both name and value
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Hey Moritz, thanks for this addition to the template fitter and the nice example! I will try to go through your changes today. |
…he model so the model can be pickled.
sognetic
commented
Jan 17, 2023
| self._is_finalized = True | ||
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| def disable_numba_after_finalizing(self): |
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I've added this option to remove numba objects from the model and replace them with python variants. Everything still works but is just a bit slower if you do that. This allows the model to be pickled. Since the finalization of the constraints is the last step in the model setup this shouldn't cause any issues.
…by the pickling process.
…l. As an alternative, the constraint can be saved using the built-in marshal.
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Hi, in this PR I have implemented Gaussian constraints between arbitrary yield parameters. The constraint is passed as a simple lambda function to the model builder which then numba-fies it to get some speedups. I have tested this quite a bit already and it works as expected. I have also added a simple example to demonstrate this capability. The PR already includes PR#10 (as otherwise the fit can take quite a while) so that one should be merged in first.