Initialize From Data#
This Initializer is intended to initialize a model from a user defined data source. This data source may take the form of a pre-saved json file or a user provided dict-like data structure. This Initializer loads variable values from the data provided and checks that the resulting values satisfy all constraints in the model.
Note
When initializing from a json format, only the values of unfixed variables will be loaded. Any other information stored in the json format (e.g., whether a variable is fixed or any information regarding constraints) will be ignored.
FromDataInitializer Class#
- class idaes.core.initialization.initialize_from_data.FromDataInitializer(**kwargs)[source]#
This is a general purpose Initializer object which attempts to initialize a model from user provided data.
Data can be provided in either json format or as a dict-like structure. The loaded solution is then checked to ensure that it satisfies all constraints in the model.
- constraint_tolerance
Tolerance for checking constraint convergence
- output_level
Set output level for logging messages
- initialize(model, initial_guesses=None, json_file=None, output_level=None, exclude_unused_vars=False)#
Execute full initialization routine.
- Parameters:
model (Block) – Pyomo model to be initialized.
initial_guesses (dict) – dict of initial guesses to load.
json_file (str) – file name of json file to load initial guesses from as str.
output_level – (optional) output level to use during initialization run (overrides global setting).
exclude_unused_vars (bool) – whether to ignore unused variables when doing post-initialization checks.
Note - can only provide one of initial_guesses or json_file.