Blank line fixes (PEP8 messages E301, E302, E303, W391).

deap/algorithms.py

@@ -29,6 +29,7 @@
 
 import tools
 
+
 def varAnd(population, toolbox, cxpb, mutpb):
     """Part of an evolutionary algorithm applying only the variation part
     (crossover **and** mutation). The modified individuals have their
@@ -79,6 +80,7 @@ def varAnd(population, toolbox, cxpb, mutpb):
 
     return offspring
 
+
 def eaSimple(population, toolbox, cxpb, mutpb, ngen, stats=None,
              halloffame=None, verbose=__debug__):
     """This algorithm reproduce the simplest evolutionary algorithm as
@@ -185,6 +187,7 @@ def eaSimple(population, toolbox, cxpb, mutpb, ngen, stats=None,
 
     return population, logbook
 
+
 def varOr(population, toolbox, lambda_, cxpb, mutpb):
     """Part of an evolutionary algorithm applying only the variation part
     (crossover, mutation **or** reproduction). The modified individuals have
@@ -241,6 +244,7 @@ def varOr(population, toolbox, lambda_, cxpb, mutpb):
 
     return offspring
 
+
 def eaMuPlusLambda(population, toolbox, mu, lambda_, cxpb, mutpb, ngen,
                    stats=None, halloffame=None, verbose=__debug__):
     """This is the :math:`(\mu + \lambda)` evolutionary algorithm.
@@ -332,6 +336,7 @@ def eaMuPlusLambda(population, toolbox, mu, lambda_, cxpb, mutpb, ngen,
 
     return population, logbook
 
+
 def eaMuCommaLambda(population, toolbox, mu, lambda_, cxpb, mutpb, ngen,
                     stats=None, halloffame=None, verbose=__debug__):
     """This is the :math:`(\mu~,~\lambda)` evolutionary algorithm.
@@ -429,10 +434,9 @@ def eaMuCommaLambda(population, toolbox, mu, lambda_, cxpb, mutpb, ngen,
         logbook.record(gen=gen, nevals=len(invalid_ind), **record)
         if verbose:
             print logbook.stream
-
-
     return population, logbook
 
+
 def eaGenerateUpdate(toolbox, ngen, halloffame=None, stats=None,
                      verbose=__debug__):
     """This is algorithm implements the ask-tell model proposed in

deap/base.py

@@ -25,6 +25,7 @@ class used as base class, for the fitness member of any individual. """
 from functools import partial
 from operator import mul, truediv
 
+
 class Toolbox(object):
     """A toolbox for evolution that contains the evolutionary operators. At
     first the toolbox contains a :meth:`~deap.toolbox.clone` method that
@@ -261,4 +262,3 @@ def __repr__(self):
         """Return the Python code to build a copy of the object."""
         return "%s.%s(%r)" % (self.__module__, self.__class__.__name__,
             self.values if self.valid else tuple())
-

deap/cma.py

@@ -26,6 +26,7 @@
 
 import tools
 
+
 class Strategy(object):
     """
     A strategy that will keep track of the basic parameters of the CMA-ES
@@ -154,7 +155,6 @@ def update(self, population):
                 + self.ccovmu * numpy.dot((self.weights * artmp.T), artmp) \
                 / self.sigma ** 2
 
-
         self.sigma *= numpy.exp((numpy.linalg.norm(self.ps) / self.chiN - 1.) \
                                 * self.cs / self.damps)
 
@@ -201,6 +201,7 @@ def computeParams(self, params):
                                             (self.dim + 1.)) - 1.) + self.cs
         self.damps = params.get("damps", self.damps)
 
+
 class StrategyOnePlusLambda(object):
     """
     A CMA-ES strategy that uses the :math:`1 + \lambda` paradigme.
@@ -316,6 +317,7 @@ def update(self, population):
         # to compute covariance matrix inverse in the step-size evolutionary path computation.
         self.A = numpy.linalg.cholesky(self.C)
 
+
 class StrategyMultiObjective(object):
     """Multiobjective CMA-ES strategy based on the paper [Voss2010]_. It
     is used similarly as the standard CMA-ES strategy with a generate-update
@@ -518,7 +520,6 @@ def update(self, population):
                 self.psucc[p_idx] = (1.0 - cp) * self.psucc[p_idx] + cp
                 self.sigmas[p_idx] = self.sigmas[p_idx] * exp((self.psucc[p_idx] - ptarg) / (d * (1.0 - ptarg)))
 
-
         # It is unnecessary to update the entire parameter set for not chosen individuals
         # Their parameters will not make it to the next generation
         for ind in not_chosen:
@@ -529,7 +530,6 @@ def update(self, population):
                 self.psucc[p_idx] = (1.0 - cp) * self.psucc[p_idx]
                 self.sigmas[p_idx] = self.sigmas[p_idx] * exp((self.psucc[p_idx] - ptarg) / (d * (1.0 - ptarg)))
 
-
         # Make a copy of the internal parameters
         # The parameter is in the temporary variable for offspring and in the original one for parents
         self.parents = chosen

deap/creator.py

@@ -72,6 +72,7 @@ def __reduce__(self):
 
     class_replacers[numpy.ndarray] = _numpy_array
 
+
 class _array(array.array):
     @staticmethod
     def __new__(cls, seq=()):
@@ -91,6 +92,7 @@ def __reduce__(self):
         return (self.__class__, (list(self),), self.__dict__)
 class_replacers[array.array] = _array
 
+
 def create(name, base, **kargs):
     """Creates a new class named *name* inheriting from *base* in the
     :mod:`~deap.creator` module. The new class can have attributes defined by

deap/gp.py

@@ -40,6 +40,7 @@
 # Define the name of type for any types.
 __type__ = object
 
+
 class PrimitiveTree(list):
     """Tree specifically formatted for optimization of genetic
     programming operations. The tree is represented with a
@@ -189,6 +190,7 @@ class Primitive(object):
         'mul(1, 2)'
     """
     __slots__ = ('name', 'arity', 'args', 'ret', 'seq')
+
     def __init__(self, name, args, ret):
         self.name = name
         self.arity = len(args)
@@ -207,11 +209,13 @@ def __eq__(self, other):
         else:
             return NotImplemented
 
+
 class Terminal(object):
     """Class that encapsulates terminal primitive in expression. Terminals can
     be values or 0-arity functions.
     """
     __slots__ = ('name', 'value', 'ret', 'conv_fct')
+
     def __init__(self, terminal, symbolic, ret):
         self.ret = ret
         self.value = terminal
@@ -232,6 +236,7 @@ def __eq__(self, other):
         else:
             return NotImplemented
 
+
 class Ephemeral(Terminal):
     """Class that encapsulates a terminal which value is set when the
     object is created. To mutate the value, a new object has to be
@@ -247,6 +252,7 @@ def func():
         """
         raise NotImplementedError
 
+
 class PrimitiveSetTyped(object):
     """Class that contains the primitives that can be used to solve a
     Strongly Typed GP problem. The set also defined the researched
@@ -417,6 +423,7 @@ def terminalRatio(self):
         """
         return self.terms_count / float(self.terms_count + self.prims_count)
 
+
 class PrimitiveSet(PrimitiveSetTyped):
     """Class same as :class:`~deap.gp.PrimitiveSetTyped`, except there is no
     definition of type.
@@ -473,6 +480,7 @@ def compile(expr, pset):
         "operators. See the DEAP documentation for more information. "
         "DEAP will now abort."), traceback
 
+
 def compileADF(expr, psets):
     """Compile the expression represented by a list of trees. The first
     element of the list is the main tree, and the following elements are
@@ -498,6 +506,7 @@ def compileADF(expr, psets):
         adfdict.update({pset.name: func})
     return func
 
+
 ######################################
 # GP Program generation functions    #
 ######################################
@@ -518,6 +527,7 @@ def condition(height, depth):
         return depth == height
     return generate(pset, min_, max_, condition, type_)
 
+
 def genGrow(pset, min_, max_, type_=None):
     """Generate an expression where each leaf might have a different depth
     between *min* and *max*.
@@ -538,6 +548,7 @@ def condition(height, depth):
                (depth >= min_ and random.random() < pset.terminalRatio)
     return generate(pset, min_, max_, condition, type_)
 
+
 def genHalfAndHalf(pset, min_, max_, type_=None):
     """Generate an expression with a PrimitiveSet *pset*.
     Half the time, the expression is generated with :func:`~deap.gp.genGrow`,
@@ -554,6 +565,7 @@ def genHalfAndHalf(pset, min_, max_, type_=None):
     method = random.choice((genGrow, genFull))
     return method(pset, min_, max_, type_)
 
+
 def genRamped(pset, min_, max_, type_=None):
     """
     .. deprecated:: 1.0
@@ -563,6 +575,7 @@ def genRamped(pset, min_, max_, type_=None):
                   FutureWarning)
     return genHalfAndHalf(pset, min_, max_, type_)
 
+
 def generate(pset, min_, max_, condition, type_=None):
     """Generate a Tree as a list of list. The tree is build
     from the root to the leaves, and it stop growing when the
@@ -756,6 +769,7 @@ def mutNodeReplacement(individual, pset):
 
     return individual,
 
+
 def mutEphemeral(individual, mode):
     """This operator works on the constants of the tree *individual*. In
     *mode* ``"one"``, it will change the value of one of the individual
@@ -783,6 +797,7 @@ def mutEphemeral(individual, mode):
 
     return individual,
 
+
 def mutInsert(individual, pset):
     """Inserts a new branch at a random position in *individual*. The subtree
     at the chosen position is used as child node of the created subtree, in
@@ -822,6 +837,7 @@ def mutInsert(individual, pset):
     individual[slice_] = new_subtree
     return individual,
 
+
 def mutShrink(individual):
     """This operator shrinks the *individual* by chosing randomly a branch and
     replacing it with one of the branch's arguments (also randomly chosen).
@@ -856,6 +872,7 @@ def mutShrink(individual):
 # GP bloat control decorators        #
 ######################################
 
+
 def staticLimit(key, max_value):
     """Implement a static limit on some measurement on a GP tree, as defined
     by Koza in [Koza1989]. It may be used to decorate both crossover and
@@ -1007,7 +1024,6 @@ def _genpop(n, pickfrom=[], acceptfunc=lambda s: True, producesizes=False):
         else:
             return producedpop
 
-
     halflifefunc = lambda x: (x * float(alpha) + beta)
     if nbrindsmodel == -1:
         nbrindsmodel = max(2000, len(population))