Add max_genome_size parameter

pyshgp/gp/estimators.py

@@ -72,6 +72,7 @@ def __init__(self,
                  population_size: int = 300,
                  max_generations: int = 100,
                  initial_genome_size: Tuple[int, int] = (20, 100),
+                 max_genome_size: int = 100,
                  simplification_steps: int = 2000,
                  last_str_from_stdout: bool = False,
                  interpreter: PushInterpreter = "default",
@@ -86,6 +87,7 @@ def __init__(self,
         self.population_size = population_size
         self.max_generations = max_generations
         self.initial_genome_size = initial_genome_size
+        self.max_genome_size = max_genome_size
         self.simplification_steps = simplification_steps
         self.last_str_from_stdout = last_str_from_stdout
         self.parallelism = parallelism
@@ -126,6 +128,7 @@ def _build_search_algo(self):
             population_size=self.population_size,
             max_generations=self.max_generations,
             initial_genome_size=self.initial_genome_size,
+            max_genome_size=self.max_genome_size,
             simplification_steps=self.simplification_steps,
             parallelism=self.parallelism,
             push_config=self.push_config

pyshgp/gp/search.py

@@ -95,6 +95,7 @@ def __init__(self,
                  max_generations: int = 100,
                  error_threshold: float = 0.0,
                  initial_genome_size: Tuple[int, int] = (10, 50),
+                 max_genome_size: int = 100,
                  simplification_steps: int = 2000,
                  parallelism: Union[int, bool] = True,
                  **kwargs):
@@ -105,6 +106,7 @@ def __init__(self,
         self.max_generations = max_generations
         self.error_threshold = error_threshold
         self.initial_genome_size = initial_genome_size
+        self.max_genome_size = max_genome_size
         self.simplification_steps = simplification_steps
         self.ext = kwargs
 
@@ -265,7 +267,7 @@ def _make_child(self) -> Individual:
         op = self.config.get_variation_op()
         selector = self.config.get_selector()
         parent_genomes = [p.genome for p in selector.select(self.population, n=op.num_parents)]
-        child_genome = op.produce(parent_genomes, self.config.spawner)
+        child_genome = op.produce_and_fix(parent_genomes, self.config.spawner, self.config.max_genome_size)
         return Individual(child_genome, self.config.signature)
 
     @tap
@@ -329,9 +331,10 @@ def step(self):
             return
 
         candidate = Individual(
-            self.config.get_variation_op().produce(
+            self.config.get_variation_op().produce_and_fix(
                 [self.population.best().genome],
-                self.config.spawner
+                self.config.spawner,
+                self.config.max_genome_length
             ),
             self.config.signature
         )

pyshgp/gp/variation.py

@@ -67,6 +67,14 @@ def produce(self, parents: Sequence[Genome], spawner: GeneSpawner) -> Genome:
         """
         pass
 
+    def fix(self, child: Genome, max_genome_size: int) -> Genome:
+        if len(child) > max_genome_size:
+            child = child[:max_genome_size]
+        return child
+
+    def produce_and_fix(self, parents: Sequence[Genome], spawner: GeneSpawner, max_genome_size: int) -> Genome:
+        return self.fix(self.produce(parents, spawner), max_genome_size)
+
 
 class VariationStrategy(DiscreteProbDistrib):
     """A collection of VariationOperator and how frequently to use them."""