def __init__(self,
length=None,
fitness_fn=None,
maximize=True,
crossover=None,
mutator=None):
if (fitness_fn is None) and (length is None):
raise Exception("fitness_fn or length must be specified.")
if length is None:
length = len(fitness_fn.weights)
self.length = length
if fitness_fn is None:
fitness_fn = FlipFlop()
self.max_val = 2
crossover = OnePointCrossOver(self) if crossover is None else crossover
mutator = ChangeOneMutator(self) if mutator is None else mutator
super().__init__(length, fitness_fn, maximize, 2, crossover, mutator)
state = np.random.randint(2, size=self.length)
self.set_state(state)
def __init__(self, length=None, fitness_fn=None, maximize=True, max_val=2,
weights=None, values=None, max_weight_pct=0.35,
crossover=None, mutator=None,
multiply_by_max_item_count=False):
if (fitness_fn is None) and (weights is None and values is None):
raise Exception("""fitness_fn or both weights and"""
+ """ values must be specified.""")
if length is None:
if weights is not None:
length = len(weights)
elif values is not None:
length = len(values)
elif fitness_fn is not None:
length = len(fitness_fn.weights)
self.length = length
if fitness_fn is None:
fitness_fn = Knapsack(weights=weights, values=values,
max_weight_pct=max_weight_pct,
max_item_count=max_val,
multiply_by_max_item_count=multiply_by_max_item_count)
self.max_val = max_val
crossover = UniformCrossOver(self) if crossover is None else crossover
mutator = ChangeOneMutator(self) if mutator is None else mutator
super().__init__(length, fitness_fn, maximize, max_val, crossover, mutator)
def __init__(self,
length=None,
fitness_fn=None,
maximize=False,
crossover=None,
mutator=None):
if (fitness_fn is None) and (length is None):
raise Exception("fitness_fn or length must be specified.")
if length is None:
length = len(fitness_fn.weights)
self.length = length
if fitness_fn is None:
fitness_fn = Queens()
self.max_val = length
crossover = UniformCrossOver(self) if crossover is None else crossover
mutator = ChangeOneMutator(self) if mutator is None else mutator
super().__init__(length, fitness_fn, maximize, length, crossover,
mutator)
state = np.random.randint(self.length, size=self.length)
np.random.shuffle(state)
self.set_state(state)
def __init__(self,
edges=None,
length=None,
fitness_fn=None,
maximize=False,
max_colors=None,
crossover=None,
mutator=None):
if (fitness_fn is None) and (edges is None):
raise Exception("fitness_fn or edges must be specified.")
if length is None:
if fitness_fn is None:
length = len(edges)
else:
length = len(fitness_fn.weights)
self.length = length
if fitness_fn is None:
fitness_fn = MaxKColor(edges)
# set up initial state (everything painted one color)
g = nx.Graph()
g.add_edges_from(edges)
fitness_fn.set_graph(g)
# if none is provided, make a reasonable starting guess.
# the max val is going to be the one plus the maximum number of neighbors of any one node.
if max_colors is None:
max_colors = 1 + max(
[len([*g.neighbors(n)]) for n in range(length)])
self.max_val = max_colors
crossover = UniformCrossOver(self) if crossover is None else crossover
mutator = ChangeOneMutator(self) if mutator is None else mutator
super().__init__(length, fitness_fn, maximize, max_colors, crossover,
mutator)
# state = [len([*g.neighbors(n)]) for n in range(length)]
state = np.random.randint(max_colors, size=self.length)
np.random.shuffle(state)
# state = [0] * length
self.set_state(state)