Generate constrained random values

Author: ahmedfgad

example.py

@@ -0,0 +1,28 @@
+import pygad
+import numpy
+
+function_inputs = [4,-2,3.5,5,-11,-4.7]
+desired_output = 44
+
+def fitness_func(ga_instance, solution, solution_idx):
+    output = numpy.sum(solution*function_inputs)
+    fitness = 1.0 / (numpy.abs(output - desired_output) + 0.000001)
+    return fitness
+
+num_genes = len(function_inputs)
+
+ga_instance = pygad.GA(num_generations=100,
+                       num_parents_mating=10,
+                       sol_per_pop=20,
+                       num_genes=num_genes,
+                       mutation_num_genes=6,
+                       fitness_func=fitness_func,
+                       # suppress_warnings=True,
+                       random_mutation_min_val=4,
+                       random_mutation_max_val=10,
+                       mutation_by_replacement=True,
+                       gene_type=int,
+                       # mutation_probability=0.4,
+                       gene_constraint=[lambda x: x[0]>=8,None,None,None,None,None])
+
+ga_instance.run()

pygad/__pycache__/__init__.cpython-310.pyc

@@ -316,7 +316,6 @@ def unique_genes_by_space(self,
         # Update the list of duplicate indices after each iteration.
         _, unique_gene_indices = numpy.unique(new_solution, return_index=True)
         not_unique_indices = set(range(len(new_solution))) - set(unique_gene_indices)
-        # self.logger.info("not_unique_indices INSIDE", not_unique_indices)        
 
         return new_solution, not_unique_indices, num_unsolved_duplicates
 
@@ -551,7 +550,7 @@ def find_two_duplicates(self,
         # This means there is no way to solve the duplicates between the genes.
         # Because the space of the duplicates genes only has a single value and there is no alternatives.
         return None, gene
-    
+
     def unpack_gene_space(self, 
                           range_min,
                           range_max,

pygad/__pycache__/pygad.cpython-310.pyc

@@ -564,24 +564,30 @@ def __init__(self,
             # Validate that gene_constraint is a list or tuple and every element inside it is either None or callable.
             if gene_constraint:
                 if type(gene_constraint) in [list, tuple]:
-                    for constraint_idx, item in enumerate(gene_constraint):
-                        # Check whether the element is None or a callable.
-                        if item and callable(item):
-                            if item.__code__.co_argcount == 1:
-                                # Every callable is valid if it receives a single argument.
-                                # This argument represents the solution.
+                    if len(gene_constraint) == self.num_genes:
+                        for constraint_idx, item in enumerate(gene_constraint):
+                            # Check whether the element is None or a callable.
+                            if item is None:
                                 pass
+                            elif item and callable(item):
+                                if item.__code__.co_argcount == 1:
+                                    # Every callable is valid if it receives a single argument.
+                                    # This argument represents the solution.
+                                    pass
+                                else:
+                                    self.valid_parameters = False
+                                    raise ValueError(f"Every callable inside the gene_constraint parameter must accept a single argument representing the solution/chromosome. But the callable at index {constraint_idx} named '{item.__code__.co_name}' accepts {item.__code__.co_argcount} argument(s).")
                             else:
                                 self.valid_parameters = False
-                                raise ValueError(f"Every callable inside the gene_constraint parameter must accept a single argument representing the solution/chromosome. But the callable at index {constraint_idx} named '{item.__code__.co_name}' accepts {item.__code__.co_argcount} argument(s).")
-                        else:
-                            self.valid_parameters = False
-                            raise TypeError(f"The expected type of an element in the 'gene_constraint' parameter is None or a callable (e.g. function). But {item} at index {constraint_idx} of type {type(item)} found.")
+                                raise TypeError(f"The expected type of an element in the 'gene_constraint' parameter is None or a callable (e.g. function). But {item} at index {constraint_idx} of type {type(item)} found.")
+                    else:
+                        self.valid_parameters = False
+                        raise ValueError(f"The number of constrains ({len(gene_constraint)}) in the 'gene_constraint' parameter must be equal to the number of genes ({self.num_genes}).")
                 else:
                     self.valid_parameters = False
-                    raise TypeError(f"The expected type of the 'gene_constraint' parameter is either list or tuple. But the value {gene_constraint} of type {type(gene_constraint)} found.")
+                    raise TypeError(f"The expected type of the 'gene_constraint' parameter is either a list or tuple. But the value {gene_constraint} of type {type(gene_constraint)} found.")
             else:
-                # It is None.
+                # gene_constraint is None and not used.
                 pass
 
             self.gene_constraint = gene_constraint