Changeset 1194 for framspy/evolalg/base/experiment_abc.py

Timestamp:

01/30/23 00:27:10 (15 months ago)

Author:

Maciej Komosinski

Message:

make_new_population() targets the desired popsize instead of preserving the input (current) population size

File:

• framspy/evolalg/base/experiment_abc.py (modified) (2 diffs)

framspy/evolalg/base/experiment_abc.py

@@ -40 +40 @@
         new_individual = Individual()
         new_individual.set_and_evaluate(genotype, self.evaluate)
-        if new_individual.fitness is not BAD_FITNESS:  # this is how we defined BAD_FITNESS in evaluate()
+        if new_individual.fitness is not BAD_FITNESS:
             ind_list.append(new_individual)
 
@@ -46 +46 @@
         """'individuals' is the input population (a list of individuals).
         Assumptions: all genotypes in 'individuals' are valid and evaluated (have fitness set).
-        Returns: a new population of the same size as 'individuals' with prob_mut mutants, prob_xov offspring, and the remainder of clones."""
+        Returns: a new population of size 'self.popsize' with prob_mut mutants, prob_xov offspring, and the remainder of clones."""
 
         newpop = []
-        N = len(individuals)
-        expected_mut = int(N * prob_mut)
-        expected_xov = int(N * prob_xov)
-        assert expected_mut + \
-            expected_xov <= N, "If probabilities of mutation (%g) and crossover (%g) added together exceed 1.0, then the population would grow every generation..." % (
-                prob_mut, prob_xov)
-        ris = RandomIndexSequence(N)
+        expected_mut = int(self.popsize * prob_mut)
+        expected_xov = int(self.popsize * prob_xov)
+        assert expected_mut + expected_xov <= self.popsize, "If probabilities of mutation (%g) and crossover (%g) added together exceed 1.0, then the population would grow every generation..." % (prob_mut, prob_xov)
+        ris = RandomIndexSequence(len(individuals))
 
         # adding valid mutants of selected individuals...
         while len(newpop) < expected_mut:
-            ind = self.select(
-                individuals, tournament_size=tournament_size, random_index_sequence=ris)
+            ind = self.select(individuals, tournament_size=tournament_size, random_index_sequence=ris)
             self.addGenotypeIfValid(newpop, self.mutate(ind.genotype))
 
         # adding valid crossovers of selected individuals...
         while len(newpop) < expected_mut + expected_xov:
-            ind1 = self.select(
-                individuals, tournament_size=tournament_size, random_index_sequence=ris)
-            ind2 = self.select(
-                individuals, tournament_size=tournament_size, random_index_sequence=ris)
-            self.addGenotypeIfValid(
-                newpop, self.cross_over(ind1.genotype, ind2.genotype))
+            ind1 = self.select(individuals, tournament_size=tournament_size, random_index_sequence=ris)
+            ind2 = self.select(individuals, tournament_size=tournament_size, random_index_sequence=ris)
+            self.addGenotypeIfValid(newpop, self.cross_over(ind1.genotype, ind2.genotype))
 
         # select clones to fill up the new population until we reach the same size as the input population
-        while len(newpop) < len(individuals):
-            ind = self.select(
-                individuals, tournament_size=tournament_size, random_index_sequence=ris)
+        while len(newpop) < self.popsize:
+            ind = self.select(individuals, tournament_size=tournament_size, random_index_sequence=ris)
             newpop.append(Individual().copyFrom(ind))