autofit.InitializerPrior#
- class autofit.InitializerPrior[source]#
Bases:
Initializer
The Initializer creates the initial set of samples in non-linear parameter space that can be passed into a NonLinearSearch to define where to begin sampling.
Although most non-linear searches have in-built functionality to do this, some do not cope well with parameter resamples that are raised as FitException’s. Thus, PyAutoFit uses its own initializer to bypass these problems.
The InitializerPrior class generates from the priors, by drawing all values as unit values between 0.0 and 1.0 and mapping them to physical values via the prior.
Methods
figure_of_metric
from_config
Load the Initializer from a non_linear config file.
samples_from_model
Generate the initial points of the non-linear search, by randomly drawing unit values from a uniform distribution between the ball_lower_limit and ball_upper_limit values.
samples_in_test_mode
Generate the initial points of the non-linear search in test mode.