patch: array_parameter

cad-polito-it · Sep 18, 2024 · 5eb2a5f · 5eb2a5f
1 parent 1c2aff9
commit 5eb2a5f
Show file tree

Hide file tree

Showing 3 changed files with 35 additions and 42 deletions.
diff --git a/examples/classics/onemax.py b/examples/classics/onemax.py
@@ -14,7 +14,7 @@
 
 import byron
 
-NUM_BITS = 50
+NUM_BITS = 16
 
 
 @byron.fitness_function
@@ -26,23 +26,27 @@ def fitness(genotype):
 def main():
     byron.welcome()
 
-    macro = byron.f.macro('{v}', v=byron.f.array_parameter('01', NUM_BITS + 1))
+    macro = byron.f.macro('{v}', v=byron.f.array_parameter('01', NUM_BITS))
     top_frame = byron.f.sequence([macro])
-
-    evaluator = byron.evaluator.PythonEvaluator(fitness, strip_phenotypes=True)
-    # evaluators.append(byron.evaluator.PythonEvaluator(fitness, strip_phenotypes=True, backend='thread_pool'))
-    # evaluators.append(byron.evaluator.PythonEvaluator(fitness, strip_phenotypes=True, backend='joblib'))
-    # evaluators.append(byron.evaluator.ScriptEvaluator('./onemax-shell.sh', args=['-f']))
-    # evaluators.append(byron.evaluator.MakefileEvaluator('genome.dat', required_files=['onemax-shell.sh']))
-
+    evaluator = byron.evaluator.PythonEvaluator(fitness, strip_phenotypes=True, backend=None)
     byron.logger.info("main: Using %s", evaluator)
-    population = byron.ea.vanilla_ea(
+    population = byron.ea.adaptive_ea(
         top_frame, evaluator, max_generation=5_000, lambda_=20, mu=30, max_fitness=NUM_BITS
     )
 
-    print()
+    macro = byron.f.macro('{v}', v=byron.f.array_parameter(range(2), NUM_BITS))
+    top_frame = byron.f.sequence([macro])
+    evaluator = byron.evaluator.PythonEvaluator(fitness, strip_phenotypes=True, backend=None)
+    byron.logger.info("main: Using %s", evaluator)
+    population = byron.ea.adaptive_ea(
+        top_frame, evaluator, max_generation=5_000, lambda_=20, mu=30, max_fitness=NUM_BITS
+    )
 
-    byron.sys.log_operators()
+    # evaluator = byron.evaluator.PythonEvaluator(fitness, strip_phenotypes=True)
+    # evaluators.append(byron.evaluator.PythonEvaluator(fitness, strip_phenotypes=True, backend='thread_pool'))
+    # evaluators.append(byron.evaluator.PythonEvaluator(fitness, strip_phenotypes=True, backend='joblib'))
+    # evaluators.append(byron.evaluator.ScriptEvaluator('./onemax-shell.sh', args=['-f']))
+    # evaluators.append(byron.evaluator.MakefileEvaluator('genome.dat', required_files=['onemax-shell.sh']))
 
 
 if __name__ == "__main__":

diff --git a/src/byron/framework/parameter.py b/src/byron/framework/parameter.py
@@ -188,6 +188,7 @@ class T(ParameterArrayABC):
 
         def __init__(self):
             super().__init__()
+            self._raw_value = None
 
         def is_correct(self, obj: Any) -> bool:
             if len(obj) != length:
@@ -201,10 +202,12 @@ def run_paranoia_checks(self) -> bool:
 
         def mutate(self, strength: float = 1.0) -> None:
             if strength == 1:
-                new_value = [rrandom.choice(symbols) for _ in range(length)]
+                self._raw_value = [rrandom.choice(symbols) for _ in range(length)]
             else:
-                new_value = [rrandom.choice(symbols) if rrandom.boolean(strength) else old for old in self._value]
-            self.value = sep.join(new_value)
+                self._raw_value = [
+                    rrandom.choice(symbols) if rrandom.boolean(strength) else old for old in self._raw_value
+                ]
+            self.value = sep.join(self._raw_value)
 
     T._patch_info(name="Array[" + "".join(str(a) for a in symbols) + f"ｘ{length}]")
     return T
@@ -215,14 +218,13 @@ def _array_parameter_range(min_: int, max_: int, length: int, sep: str) -> type[
     class T(ParameterArrayABC):
         __slots__ = []  # Preventing the automatic creation of __dict__
 
-        MIN = min_
-        MAX = max_
+        RANGE = (min_, max_)
         LENGTH = length
         SEP = sep
 
         def __init__(self):
             super().__init__()
-            self.raw_value = None
+            self._raw_value = None
 
         def is_correct(self, obj: Any) -> bool:
             return all(min_ <= int(e) < max_ for e in obj.split(sep))
@@ -234,14 +236,13 @@ def run_paranoia_checks(self) -> bool:
 
         def mutate(self, strength: float = 1.0) -> None:
             if strength == 1:
-                self.raw_value = [rrandom.random_int(min_, max_) for _ in range(length)]
+                self._raw_value = [rrandom.random_int(min_, max_) for _ in range(length)]
             else:
-                i = rrandom.random_int(0, length)
-                self.raw_value[i] = rrandom.random_int(min_, max_)
-                while rrandom.boolean(strength):
-                    i = rrandom.random_int(0, length)
-                    self.raw_value[i] = rrandom.random_int(min_, max_)
-            self.value = sep.join(str(_) for _ in self.raw_value)
+                self._raw_value = [
+                    rrandom.random_int(min_, max_) if rrandom.boolean(strength) else old for old in self._raw_value
+                ]
+                self.value = sep.join(str(_) for _ in self._raw_value)
+            self.value = sep.join(str(_) for _ in self._raw_value)
 
     T._patch_info(name=f"Array[range({min_}, {max_})]ｘ{length}]")
     return T
@@ -256,9 +257,9 @@ def array_parameter(
     assert check_value_range(int(length), 1)
     if isinstance(symbols, range):
         assert check_value_range(symbols.stop - symbols.start, min_=1)
-        return _array_parameter_range(symbols.start, symbols.stop, int(length), sep=sep)
         if sep is None:
             sep = ' '
+        return _array_parameter_range(symbols.start, symbols.stop, int(length), sep=sep)
     else:
         assert check_valid_type(symbols, Collection)
         assert check_valid_length(symbols, 1)

diff --git a/src/byron/operators/mutations.py b/src/byron/operators/mutations.py
@@ -26,7 +26,7 @@
 
 from collections import Counter
 from copy import deepcopy
-from math import ceil, floor
+from math import floor
 
 from networkx import dfs_preorder_nodes
 
@@ -39,7 +39,7 @@
 
 
 @genetic_operator(num_parents=1)
-def single_parameter_mutation(parent: Individual, strength=1.0) -> list['Individual']:
+def generic_parameter_mutation(parent: Individual, strength=1.0) -> list['Individual']:
     """Mutates a parameter
 
     The function tries at least 100 times to change the parameter by calling `mutate` with the given strength.
@@ -63,26 +63,14 @@ def single_parameter_mutation(parent: Individual, strength=1.0) -> list['Individ
 
 
 @genetic_operator(num_parents=1)
-def single_element_array_parameter_mutation(parent: Individual, strength=1.0) -> list['Individual']:
-    scale = 0.05
-    ext_mutation = 1 / (scale * strength)
+def array_parameter_mutation(parent: Individual, strength=1.0) -> list['Individual']:
     offspring = parent.clone
     candidates = [p for p in offspring.parameters if isinstance(p, ParameterArrayABC)]
     if not candidates:
         raise ByronOperatorFailure
 
     parameter = rrandom.choice(candidates)
-    old_value = list(parameter.value)
-    new_value = list(parameter.value)
-    for _ in range(ceil(len(parameter.value) // ext_mutation)):
-        i = rrandom.random_int(0, len(parameter.value))
-        new_value[i] = rrandom.choice(parameter.DIGITS)
-
-    if strength > 0 and parameter.value == old_value:
-        raise ByronOperatorFailure
-
-    parameter.value = ''.join(new_value)
-
+    parameter.mutate(strength=strength)
     return [offspring]