verbose obj_fun added

Author: Gromwud

epde/globals.py

@@ -97,12 +97,14 @@ class VerboseManager:
     show_iter_idx : bool
     iter_fitness : bool
     iter_stats : bool
-    show_ann_loss : bool    
+    show_ann_loss : bool
     show_warnings : bool
+    candidate_objectives : bool
 
-def init_verbose(plot_DE_solutions : bool = False, show_iter_idx : bool = True, 
-                 show_iter_fitness : bool = False, show_iter_stats : bool = False, 
-                 show_ann_loss : bool = False, show_warnings : bool = False):
+def init_verbose(plot_DE_solutions : bool = False, show_iter_idx : bool = True,
+                 show_iter_fitness : bool = False, show_iter_stats : bool = False,
+                 show_ann_loss : bool = False, show_warnings : bool = False,
+                 candidate_objectives : bool = False):
     """
     Method for initialized of manager for output in text form
 
@@ -121,8 +123,9 @@ def init_verbose(plot_DE_solutions : bool = False, show_iter_idx : bool = True,
     global verbose
     if not show_warnings:
         warnings.filterwarnings("ignore")
-    verbose = VerboseManager(plot_DE_solutions, show_iter_idx, show_iter_fitness, 
-                             show_iter_stats, show_ann_loss, show_warnings)
+    verbose = VerboseManager(plot_DE_solutions, show_iter_idx, show_iter_fitness,
+                             show_iter_stats, show_ann_loss, show_warnings,
+                             candidate_objectives)
 
 def reset_control_nn(n_control: int = 1, ann: torch.nn.Sequential = None, 
                      ctrl_args: list = [(0, [None,]),], device: str = 'cpu'):

epde/operators/multiobjective/moeadd_specific.py

@@ -13,6 +13,7 @@
 
 from epde.optimizers.moeadd.moeadd import ParetoLevels, ObjFunNormalizer
 from epde.operators.utils.template import CompoundOperator, add_base_param_to_operator
+import epde.globals as global_var
 from epde.operators.multiobjective.mutations import get_basic_mutation
 
 from epde.structure.main_structures import SoEq
@@ -447,10 +448,12 @@ def apply(self, objective: ParetoLevels, arguments: dict):
                     self.suboperators['pareto_level_updater'].apply(objective=(temp_offspring, objective),
                                                                     arguments=subop_args['pareto_level_updater'])
                     objective.history.add(system)
-                    print(temp_offspring.obj_fun)
+                    if global_var.verbose.candidate_objectives:
+                        print(temp_offspring.obj_fun)
                     break
                 if replaced == offspring_attempt_limit:
-                    print("Could not generate unique offspring")
+                    if global_var.verbose.candidate_objectives:
+                        print("Could not generate unique offspring")
                     break
                 if attempt == mutation_attempt_limit:
                     temp_offspring.create()
@@ -533,7 +536,8 @@ def apply(self, objective : ParetoLevels, arguments : dict):
                 self.suboperators['chromosome_fitness'].apply(objective=candidate,
                                                               arguments=subop_args['chromosome_fitness'])
                 objective.history.add(system)
-                print(candidate.obj_fun)
+                if global_var.verbose.candidate_objectives:
+                    print(candidate.obj_fun)
             objective.associate_weights()
             objective.initial_placing()
 

epde/structure/main_structures.py

@@ -722,7 +722,7 @@ def add_random_term(self):
                         mandatory_family=None, passed_term=None)
 
         attempt = 0
-        while new_term.term_label in self.terms_labels and attempt < 10:
+        while new_term.term_label in self.terms_labels or attempt < 10:
             new_term.randomize()
             attempt += 1