Merge remote-tracking branch 'origin/development' into development

tpot/base.py

@@ -47,13 +47,12 @@
 from ._version import __version__
 from .operator_utils import TPOTOperatorClassFactory, Operator, ARGType
 from .export_utils import export_pipeline, expr_to_tree, generate_pipeline_code
-#from .decorators import _timeout, _pre_test, TimedOutExc
 from .decorators import _pre_test
 from .built_in_operators import CombineDFs
 
 from .metrics import SCORERS
 from .gp_types import Output_Array
-from .gp_deap import eaMuPlusLambda, mutNodeReplacement, _wrapped_cross_val_score
+from .gp_deap import eaMuPlusLambda, mutNodeReplacement, _wrapped_cross_val_score, cxOnePoint
 
 # hot patch for Windows: solve the problem of crashing python after Ctrl + C in Windows OS
 if sys.platform.startswith('win'):
@@ -747,7 +746,7 @@ def _evaluate_individuals(self, individuals, features, classes, sample_weight =
 
     @_pre_test
     def _mate_operator(self, ind1, ind2):
-        return gp.cxOnePoint(ind1, ind2)
+        return cxOnePoint(ind1, ind2)
 
     @_pre_test
     def _random_mutation_operator(self, individual):
@@ -765,8 +764,6 @@ def _random_mutation_operator(self, individual):
             Returns the individual with one of the mutations applied to it
 
         """
-        # debug usage
-        #print(str(individual))
         mutation_techniques = [
             partial(gp.mutInsert, pset=self._pset),
             partial(mutNodeReplacement, pset=self._pset),

tpot/gp_deap.py

@@ -24,6 +24,7 @@
 from .operator_utils import set_sample_weight
 from sklearn.model_selection import cross_val_score
 from sklearn.base import clone
+from collections import defaultdict
 import warnings
 import threading
 
@@ -200,6 +201,49 @@ def eaMuPlusLambda(population, toolbox, mu, lambda_, cxpb, mutpb, ngen, pbar,
     return population, logbook
 
 
+def cxOnePoint(ind1, ind2):
+    """Randomly select in each individual and exchange each subtree with the
+    point as root between each individual.
+    :param ind1: First tree participating in the crossover.
+    :param ind2: Second tree participating in the crossover.
+    :returns: A tuple of two trees.
+    """
+    # Define the name of type for any types.
+    __type__ = object
+
+    if len(ind1) < 2 or len(ind2) < 2:
+        # No crossover on single node tree
+        return ind1, ind2
+
+    # List all available primitive types in each individual
+    types1 = defaultdict(list)
+    types2 = defaultdict(list)
+    if ind1.root.ret == __type__:
+        # Not STGP optimization
+        types1[__type__] = range(1, len(ind1))
+        types2[__type__] = range(1, len(ind2))
+        common_types = [__type__]
+    else:
+        for idx, node in enumerate(ind1[1:], 1):
+            types1[node.ret].append(idx)
+        for idx, node in enumerate(ind2[1:], 1):
+            types2[node.ret].append(idx)
+
+        common_types = [x for x in types1 if x in types2]
+
+    if len(common_types) > 0:
+        type_ = np.random.choice(common_types)
+
+        index1 = np.random.choice(types1[type_])
+        index2 = np.random.choice(types2[type_])
+
+        slice1 = ind1.searchSubtree(index1)
+        slice2 = ind2.searchSubtree(index2)
+        ind1[slice1], ind2[slice2] = ind2[slice2], ind1[slice1]
+
+    return ind1, ind2
+
+
 # point mutation function
 def mutNodeReplacement(individual, pset):
     """Replaces a randomly chosen primitive from *individual* by a randomly
@@ -283,7 +327,6 @@ def run(self):
                 warnings.simplefilter('ignore')
                 self.result = cross_val_score(*self.args, **self.kwargs)
         except Exception as e:
-            #print(e) # for debug use 
             pass
 
 def _wrapped_cross_val_score(sklearn_pipeline, features, classes,