When making extensions, we have a make_model() function which allows us to create a model based on the classes input, which uses the following function:
def as_model(self, model_classes=tuple()):
from autofit.mapper.prior_model.abstract import AbstractPriorModel
return AbstractPriorModel.from_instance(self, model_classes)
The model_classes are created as model components that are fitted for by the NLS. Their priors assume default values based on the json_prior configs.
Could we include an option to pass the results (which are pretty much always available whenever this function is called) and use the results to set up the model priors, instead of the configs? This should be not used by default, but be a bool option of some kind!
When making extensions, we have a make_model() function which allows us to create a model based on the classes input, which uses the following function:
The model_classes are created as model components that are fitted for by the NLS. Their priors assume default values based on the json_prior configs.
Could we include an option to pass the results (which are pretty much always available whenever this function is called) and use the results to set up the model priors, instead of the configs? This should be not used by default, but be a bool option of some kind!