atomica.optimization.MaximizeCascadeStage

class atomica.optimization.MaximizeCascadeStage(cascade_name, t, pop_names='all', weight=1.0, cascade_stage=-1)

Bases: Measurable

Methods

eval
get_baseline	Return cached baseline values
get_objective_val	Return objective value

get_baseline(model)

Return cached baseline values

Similar to get_hard_constraint, sometimes a relative Measurable might be desired e.g. ‘Reduce deaths by at least 50%’. In that case, we need to perform a procedure similar to getting a hard constraint, where the Measurable receives an initial Model object and extracts baseline data for subsequent use in get_objective_val.

Thus, the output of this function is paired to its usage in get_objective_val.

Parameters:

model

Returns:

The value to pass back to the Measurable during optimization

get_objective_val(model, baseline)

Return objective value

This method should return the _unweighted_ objective value. Note that further transformation may occur

Parameters:

• model – A Model object after integration

• baseline – The baseline variable returned by this Measurable at the start of optimization

Returns:

A scalar objective value