def test_add_node(self):
g = Genome(1, 1)
# Test adding nodes
msg = 'Node added incorrectly!'
g.add_connection(0, 1)
g.add_node(0)
self.assertEqual(len(g.get_nodes()), 3, msg)
self.assertEqual(len(g.get_connections()), 3, msg)
self.assertFalse(g.get_connections()[0].expressed, msg)
self.assertTrue(g.get_connections()[1].expressed, msg)
self.assertTrue(g.get_connections()[2].expressed, msg)
self.assertEqual(g.get_connections()[0].weight,
g.get_connections()[1].weight, msg)
self.assertEqual(g.get_connections()[2].weight, 1.0, msg)
self.assertEqual(g.get_nodes()[2].activation,
activations.modified_sigmoid, msg)
g.add_node(1, activation=activations.absolute)
self.assertEqual(len(g.get_nodes()), 4, msg)
self.assertEqual(len(g.get_connections()), 5, msg)
self.assertFalse(g.get_connections()[1].expressed, msg)
self.assertTrue(g.get_connections()[3].expressed, msg)
self.assertTrue(g.get_connections()[4].expressed, msg)
self.assertEqual(g.get_connections()[1].weight,
g.get_connections()[3].weight, msg)
self.assertEqual(g.get_connections()[4].weight, 1.0, msg)
self.assertEqual(g.get_nodes()[3].activation, activations.absolute,
msg)
def test_mutate_shift_weight(self):
g = Genome(1, 1)
steps = [0.1, 0.2, 0.3, 0.4, 0.5, 1.0, 5.0]
error_margin = 0.000000000001
msg = 'Failed to shift weight correctly!'
# Test with one connection
g.add_connection(0, 1, weight=0.0)
for step in steps:
current_weight = g.get_connections()[0].weight
g.mutate_shift_weight(step=step)
self.assertNotEqual(g.get_connections()[0].weight, current_weight,
msg)
self.assertAlmostEqual(abs(g.get_connections()[0].weight -
current_weight),
step,
delta=error_margin)
# Test with multiple connections
g.add_node(0)
for step in steps:
before = [c.weight for c in g.get_connections()]
g.mutate_shift_weight(step=step)
after = [c.weight for c in g.get_connections()]
self.assertNotEqual(before, after, msg)
def test_connections_at_max(self):
g = Genome(2, 2)
msg = 'Connections not at max and should be!'
msg2 = 'Connections at max and shouldn\'t be!'
# Test with no hidden nodes
self.assertFalse(g.connections_at_max(), msg)
g.add_connection(0, 2)
g.add_connection(0, 3)
g.add_connection(1, 2)
self.assertFalse(g.connections_at_max(), msg)
g.add_connection(1, 3)
self.assertTrue(g.connections_at_max(), msg2)
# Test with hidden nodes
g.add_node(0)
self.assertFalse(g.connections_at_max(), msg)
g.add_connection(1, 4)
g.add_connection(4, 3)
self.assertTrue(g.connections_at_max(), msg2)
g.add_node(6)
self.assertFalse(g.connections_at_max(), msg)
g.add_connection(0, 5)
g.add_connection(5, 2)
g.add_connection(5, 3)
self.assertTrue(g.connections_at_max(), msg2)
def test_copy(self):
g = Genome(2, 2)
# Test to make sure the copy is the same as the original
msg = 'Copy is different from the original!'
g.add_connection(0, 2)
g.add_connection(0, 3)
g.add_node(0)
gc = g.copy()
self.assertEqual(len(g.get_nodes()), len(gc.get_nodes()), msg)
self.assertEqual(len(g.get_connections()), len(gc.get_connections()),
msg)
for i in range(len(g.get_connections())):
self.assertEqual(g.get_connections()[i].weight,
gc.get_connections()[i].weight, msg)
# Test to make sure the copy doesn't change when the original does
msg = 'Copy changes when original changes!'
g.add_node(1)
g.get_connections()[0].weight = 50
self.assertNotEqual(len(g.get_nodes()), len(gc.get_nodes()), msg)
self.assertNotEqual(len(g.get_connections()),
len(gc.get_connections()), msg)
self.assertNotEqual(g.get_connections()[0].weight,
gc.get_connections()[0].weight, msg)
def test_adjust_population_fitness(self):
msg = 'Adjusted fitness incorrectly!'
e = Ecosystem(threshold=0.5, dc=1.0, ec=1.0, wc=0.4)
# Create genomes
g = Genome(2, 2)
g2 = Genome(2, 2)
g3 = Genome(2, 2)
# Add connections and/or nodes
g.add_connection(0, 2, weight=1.0)
g.add_connection(0, 3, weight=1.0)
g.add_connection(1, 2, weight=1.0)
g2.add_connection(0, 2, weight=0.9)
g2.add_connection(0, 3, weight=1.0)
g2.add_connection(1, 2, weight=1.0)
g2.add_connection(1, 3, weight=1.0)
g3.add_connection(0, 2, weight=0.1)
g3.add_connection(0, 3, weight=1.0)
g3.add_connection(1, 2, weight=1.0)
g3.add_connection(1, 3, weight=1.0)
g3.add_node(0)
g3.add_node(1)
g3.add_node(2)
g3.add_connection(0, 6, weight=1.0)
g3.add_connection(1, 5, weight=1.0)
g4 = copy.copy(g3)
g4.add_node(3)
# Set genome fitness
g.fitness = 10
g2.fitness = 12
g3.fitness = 22
g4.fitness = 24
# Test to make sure it doesn't change if there are no different genomes
e.add_genome(g)
e.adjust_population_fitness()
self.assertEqual(g.fitness, 10, msg)
e.add_genome(g2)
e.adjust_population_fitness()
self.assertEqual(g.fitness, 10, msg)
self.assertEqual(g2.fitness, 12, msg)
# Test to make sure the fitness does change when there are different genomes
e.add_genome(g3)
e.add_genome(g4)
e.adjust_population_fitness()
self.assertEqual(g.fitness, 5, msg)
self.assertEqual(g2.fitness, 6, msg)
self.assertEqual(g3.fitness, 11, msg)
self.assertEqual(g4.fitness, 12, msg)
def test_mutate_random_weight(self):
g = Genome(1, 1)
msg = 'Failed to set random connection weight!'
# Test with one connection
g.add_connection(0, 1, weight=5)
g.mutate_random_weight()
self.assertNotEqual(g.get_connections()[0].weight, 5, msg)
self.assertTrue(-1.0, g.get_connections()[0].weight <= 1.0)
# Test with multiple connections
g.add_node(0)
before = [c.weight for c in g.get_connections()]
g.mutate_random_weight()
after = [c.weight for c in g.get_connections()]
self.assertNotEqual(before, after, msg)
def test_add_genome(self):
e = Ecosystem()
# Test to make sure it creates a new species if there aren't any
msg = 'Failed to create new species with genome!'
g = Genome(2, 2)
g.add_connection(0, 2, weight=0.4)
g.add_connection(0, 3, weight=0.4)
g.add_connection(1, 2, weight=0.4)
g.add_connection(1, 3, weight=0.4)
self.assertEqual(len(e.species), 0, msg)
e.add_genome(g)
self.assertEqual(len(e.species), 1, msg)
self.assertEqual(e.species[0].representative, g, msg)
self.assertEqual(e.species[0][0], g, msg)
self.assertEqual(len(e.get_population()), 1, msg)
# Test to make sure it adds the genome to the same species if they are close
msg = 'Failed to add genome to species correctly!'
g2 = Genome(2, 2)
g2.add_connection(0, 2, weight=0.3)
g2.add_connection(0, 3, weight=0.4)
g2.add_connection(1, 2, weight=0.4)
g2.add_connection(1, 3, weight=0.4)
e.add_genome(g2)
self.assertEqual(len(e.species), 1, msg)
self.assertEqual(e.species[0].representative, g, msg)
self.assertEqual(e.species[0][1], g2, msg)
self.assertEqual(len(e.get_population()), 2, msg)
# Test to make sure a new species is created if the genome is distant from the current species
msg = 'Failed to create new species with genome!'
g3 = Genome(2, 2)
g3.add_connection(0, 2, weight=0.3)
g3.add_connection(0, 3, weight=0.4)
g3.add_connection(1, 2, weight=0.4)
g3.add_connection(1, 3, weight=0.4)
g3.add_node(0)
g3.add_node(1)
g3.add_node(2)
g3.add_node(3)
e.add_genome(g3)
self.assertEqual(len(e.species), 2, msg)
self.assertEqual(e.species[1].representative, g3, msg)
self.assertEqual(e.species[1][0], g3, msg)
self.assertEqual(len(e.get_population()), 3, msg)
def test_mutate_toggle_connection(self):
g = Genome(1, 1)
msg = 'Failed to toggle connection!'
# Test with one connection
g.add_connection(0, 1)
g.mutate_toggle_connection()
self.assertFalse(g.get_connections()[0].expressed, msg)
g.mutate_toggle_connection()
self.assertTrue(g.get_connections()[0].expressed, msg)
# Test with multiple connections
g.add_node(0)
before = [c.expressed for c in g.get_connections()]
g.mutate_toggle_connection()
after = [c.expressed for c in g.get_connections()]
self.assertNotEqual(before, after, msg)
def test_get_node_max_distance(self):
g = Genome(2, 2)
# Test to make sure empty genomes return the correct values for output nodes
msg = 'Disconnected output node returned invalid value!'
self.assertEqual(g.get_node_max_distance(g.get_node(2).id), -1, msg)
self.assertEqual(g.get_node_max_distance(g.get_node(3).id), -1, msg)
# Add nodes and connections
g.add_connection(0, 2, weight=-0.7)
g.add_connection(0, 3, weight=-0.1)
g.add_connection(1, 2, weight=0.5)
g.add_connection(1, 3, weight=0.9)
g.add_node(0)
g.add_node(2)
g.add_connection(4, 5, 0.5)
msg = 'Incorrect node max distance!'
# Test the values of each node distance to make sure they are correct
correct_distances = [0, 0, 3, 1, 1, 2]
for node, distance in zip(g.get_nodes(), correct_distances):
self.assertEqual(g.get_node_max_distance(node.id), distance, msg)
# Add a node and test again
g.add_node(8)
correct_distances = [0, 0, 4, 1, 1, 3, 2]
for node, distance in zip(g.get_nodes(), correct_distances):
self.assertEqual(g.get_node_max_distance(node.id), distance, msg)
# Add connection and test again
g.add_connection(6, 3)
correct_distances = [0, 0, 4, 3, 1, 3, 2]
for node, distance in zip(g.get_nodes(), correct_distances):
self.assertEqual(g.get_node_max_distance(node.id), distance, msg)
# Test genome with connection loop
msg = 'Genome failed to handle connection loop!'
g2 = Genome(1, 1)
g2.add_connection(0, 1)
g2.add_node(0)
g2.add_node(0)
g2.add_node(1)
g2.add_connection(3, 2)
g2.add_connection(4, 3)
correct_distances = [0, 4, 3, 3, 3]
for node, distance in zip(g2.get_nodes(), correct_distances):
self.assertEqual(g2.get_node_max_distance(node.id), distance, msg)
def test_add_connection(self):
g = Genome(2, 2)
# Test connecting input and output nodes
msg = 'Failed connection to output node!'
g.add_connection(0, 2)
self.assertEqual(len(g.get_connections()), 1, msg)
self.assertEqual(g.get_connections()[0].in_node, 0, msg)
self.assertEqual(g.get_connections()[0].out_node, 2, msg)
g.add_connection(0, 3)
self.assertEqual(len(g.get_connections()), 2, msg)
self.assertEqual(g.get_connections()[1].in_node, 0, msg)
self.assertEqual(g.get_connections()[1].out_node, 3, msg)
g.add_connection(1, 2)
self.assertEqual(len(g.get_connections()), 3, msg)
self.assertEqual(g.get_connections()[2].in_node, 1, msg)
self.assertEqual(g.get_connections()[2].out_node, 2, msg)
g.add_connection(1, 3, 0.5)
self.assertEqual(len(g.get_connections()), 4, msg)
self.assertEqual(g.get_connections()[3].in_node, 1, msg)
self.assertEqual(g.get_connections()[3].out_node, 3, msg)
self.assertEqual(g.get_connections()[3].weight, 0.5, msg)
# # Test connecting to hidden nodes
msg = 'Failed connection to hidden node!'
g.add_node(0)
g.add_connection(1, 4, 0.7)
self.assertEqual(len(g.get_connections()), 7, msg)
self.assertEqual(g.get_connections()[6].in_node, 1, msg)
self.assertEqual(g.get_connections()[6].out_node, 4, msg)
self.assertEqual(g.get_connections()[6].weight, 0.7, msg)
g.add_node(2)
g.add_connection(4, 5, 0.9)
self.assertEqual(len(g.get_connections()), 10, msg)
self.assertEqual(g.get_connections()[9].in_node, 4, msg)
self.assertEqual(g.get_connections()[9].out_node, 5, msg)
self.assertEqual(g.get_connections()[9].weight, 0.9, msg)
# Test to make sure it catches invalid parameters
msg = 'Invalid parameters not caught!'
# Nodes that don't exist
invalid_nodes = range(10, 15)
for n1 in invalid_nodes:
for n2 in invalid_nodes:
with self.assertRaises(AssertionError, msg=msg):
g.add_connection(n1, n2)
# Duplicate connections
for conn in g.get_connections():
with self.assertRaises(AssertionError, msg=msg):
g.add_connection(conn.in_node, conn.out_node)
# Input to input, output to output, and self to self connections
conns = [(0, 1), (3, 2), (5, 5)]
for n1, n2 in conns:
with self.assertRaises(AssertionError, msg=msg):
g.add_connection(n1, n2)
def test_forward(self):
error_margin = 0.000000000001
g = Genome(2, 2)
x = np.array([0.5, 0.5])
msg = 'Invalid genome output!'
# No connections
y = g(x)
self.assertEqual(y[0], 0.0, msg=msg)
self.assertEqual(y[1], 0.0, msg=msg)
# No hidden nodes, modified sigmoid activation
g.add_connection(0, 2, weight=-0.7)
g.add_connection(0, 3, weight=-0.1)
g.add_connection(1, 2, weight=0.5)
g.add_connection(1, 3, weight=0.9)
y = g(x)
self.assertAlmostEqual(y[0],
0.3798935676569099,
msg=msg,
delta=error_margin)
self.assertAlmostEqual(y[1],
0.8765329524347759,
msg=msg,
delta=error_margin)
# Different activation
for n in g.get_nodes():
if n.type != 'input':
g.set_activation(n.id, activations.absolute)
y = g(x)
self.assertAlmostEqual(y[0], 0.1, msg=msg, delta=error_margin)
self.assertAlmostEqual(y[1], 0.4, msg=msg, delta=error_margin)
# With hidden nodes and different activations (sigmoid for the new ones)
g.add_node(0, activation=activations.sigmoid)
g.add_node(2, activation=activations.sigmoid)
g.add_connection(4, 5, 0.5)
y = g(x)
self.assertAlmostEqual(y[0],
0.08953579350695234,
msg=msg,
delta=error_margin)
self.assertAlmostEqual(y[1], 0.4, msg=msg, delta=error_margin)
# Test with many hidden nodes in a line
g2 = Genome(2, 2)
g2.add_connection(0, 2, -0.3)
g2.add_node(0)
g2.add_node(2)
g2.add_node(4)
g2.add_node(6)
g2.add_connection(1, 7, 0.7)
g2.add_connection(4, 3, -0.2)
y = g2(x)
self.assertAlmostEqual(y[0],
0.18866305913528142,
msg=msg,
delta=error_margin)
self.assertAlmostEqual(y[1],
0.2743863603871294,
msg=msg,
delta=error_margin)
# Test with recursive loop
g3 = Genome(1, 1)
x = np.array([0.5])
g3.add_connection(0, 1, 0.5)
g3.add_node(0)
g3.add_node(0)
g3.add_node(1)
g3.add_connection(3, 2, 0.5)
g3.add_connection(4, 3, 0.5)
y = g3(x)
self.assertAlmostEqual(y[0],
0.9907948306148218,
msg=msg,
delta=error_margin)
def test_kill_percentage(self):
e = Ecosystem(dc=1.0, ec=1.0, wc=0.4)
# Create genomes
g = Genome(2, 2, ecosystem=e)
g2 = Genome(2, 2, ecosystem=e)
g3 = Genome(2, 2, ecosystem=e)
# Add connections and/or nodes
g.add_connection(0, 2, weight=1.0)
g.add_connection(0, 3, weight=1.0)
g.add_connection(1, 2, weight=1.0)
g2.add_connection(0, 2, weight=0.9)
g2.add_connection(0, 3, weight=1.0)
g2.add_connection(1, 2, weight=1.0)
g2.add_connection(1, 3, weight=1.0)
g3.add_connection(0, 2, weight=0.1)
g3.add_connection(0, 3, weight=1.0)
g3.add_connection(1, 2, weight=1.0)
g3.add_connection(1, 3, weight=1.0)
g3.add_node(0)
g3.add_node(1)
g3.add_node(2)
g3.add_connection(0, 6, weight=1.0)
g3.add_connection(1, 5, weight=1.0)
g.add_node(1)
# Test to make sure the correct amount are killed
msg = 'Incorrect percentage killed!'
for i in range(10):
g_copy = g.copy()
g2_copy = g2.copy()
g3_copy = g3.copy()
g_copy.fitness = random.randrange(0, 200)
g2_copy.fitness = random.randrange(0, 200)
g3_copy.fitness = random.randrange(0, 200)
e.add_genome(g_copy)
e.add_genome(g2_copy)
e.add_genome(g3_copy)
e.kill_percentage(50)
for s in e.species:
self.assertAlmostEqual(len(s), 5, msg=msg, delta=1)
self.assertAlmostEqual(len(e.get_population()), 15, msg=msg, delta=1)
for i in range(5):
g_copy = g.copy()
g2_copy = g2.copy()
g3_copy = g3.copy()
g_copy.fitness = random.randrange(0, 200)
g2_copy.fitness = random.randrange(0, 200)
g3_copy.fitness = random.randrange(0, 200)
e.add_genome(g_copy)
e.add_genome(g2_copy)
e.add_genome(g3_copy)
e.kill_percentage(25)
for s in e.species:
self.assertAlmostEqual(len(s), 8, msg=msg, delta=1)
self.assertAlmostEqual(len(e.get_population()), 24, msg=msg, delta=1)
for i in range(2):
g_copy = g.copy()
g2_copy = g2.copy()
g3_copy = g3.copy()
g_copy.fitness = random.randrange(0, 200)
g2_copy.fitness = random.randrange(0, 200)
g3_copy.fitness = random.randrange(0, 200)
e.add_genome(g_copy)
e.add_genome(g2_copy)
e.add_genome(g3_copy)
e.kill_percentage(75)
for s in e.species:
self.assertAlmostEqual(len(s), 3, msg=msg, delta=1)
self.assertAlmostEqual(len(e.get_population()), 9, msg=msg, delta=1)
e.kill_percentage(12)
for s in e.species:
self.assertAlmostEqual(len(s), 3, msg=msg, delta=1)
self.assertAlmostEqual(len(e.get_population()), 9, msg=msg, delta=1)
# Test with a larger population
e.create_initial_population(100, parent_genome=g)
e.add_genome(g2.copy())
e.add_genome(g3.copy())
e.kill_percentage(90)
self.assertAlmostEqual(len(e.get_population()), 12, msg=msg, delta=3)
def test_get_distance(self):
error_margin = 0.000000000001
e = Ecosystem(dc=1.0, ec=1.0, wc=0.4)
# Create genomes
g = Genome(2, 2, ecosystem=e)
g2 = Genome(2, 2, ecosystem=e)
g3 = Genome(2, 2, ecosystem=e)
# Add connections and/or nodes
g.add_connection(0, 2, weight=1.0)
g.add_connection(0, 3, weight=1.0)
g.add_connection(1, 2, weight=1.0)
g2.add_connection(0, 2, weight=0.9)
g2.add_connection(0, 3, weight=1.0)
g2.add_connection(1, 2, weight=1.0)
g2.add_connection(1, 3, weight=1.0)
g3.add_connection(0, 2, weight=0.1)
g3.add_connection(0, 3, weight=1.0)
g3.add_connection(1, 2, weight=1.0)
g3.add_connection(1, 3, weight=1.0)
g3.add_node(0)
g3.add_node(1)
g3.add_node(2)
g3.add_connection(0, 6, weight=1.0)
g3.add_connection(1, 5, weight=1.0)
g.add_node(1)
# Test distance results to make sure they are approximately correct
msg = 'Invalid distance result!'
self.assertAlmostEqual(e.get_distance(g, g2),
0.6133333333333334,
msg=msg,
delta=error_margin)
self.assertAlmostEqual(e.get_distance(g2, g),
0.6133333333333334,
msg=msg,
delta=error_margin)
self.assertAlmostEqual(e.get_distance(g, g3),
0.84,
msg=msg,
delta=error_margin)
self.assertAlmostEqual(e.get_distance(g3, g),
0.84,
msg=msg,
delta=error_margin)
self.assertAlmostEqual(e.get_distance(g2, g3),
0.7466666666666666,
msg=msg,
delta=error_margin)
self.assertAlmostEqual(e.get_distance(g3, g2),
0.7466666666666666,
msg=msg,
delta=error_margin)
# Test to make sure the same genome returns zero when tested against node_to_itself
msg = 'Distance between same genomes is not zero!'
self.assertEqual(e.get_distance(g, g), 0.0, msg)
self.assertEqual(e.get_distance(g2, g2), 0.0, msg)
self.assertEqual(e.get_distance(g3, g3), 0.0, msg)
def test_cross(self):
e = Ecosystem()
# Create genomes
g = Genome(2, 2, ecosystem=e)
g2 = Genome(2, 2, ecosystem=e)
# Cross the genomes
child = e.cross(g, g2)
# Test child connections
msg = 'Child connection doesn\'t exist within either parent!'
for c in child.get_connections():
self.assertTrue(
g.get_connection(c.innovation_number) is not None
or g2.get_connection(c.innovation_number) is not None, msg)
# Test to make sure the child has the same amount of connections as the fitter parent
msg = 'Child missing fitter parent connection(s)!'
self.assertEqual(len(child.get_connections()),
len(g.get_connections()), msg)
# Test child nodes
msg = 'Child node doesn\'t exist within either parent!'
for n in child.get_nodes():
self.assertTrue(
g.get_node(n.id) is not None or g2.get_node(n.id) is not None,
msg)
# Test to make sure the child has the same amount of nodes as the fitter parent
msg = 'Child is missing fitter parent node(s)!'
self.assertEqual(len(child.get_nodes()), len(g.get_nodes()), msg)
# Test preference for fit parents
msg = 'Child connection preferred less fit parent!'
for c in child.get_connections():
in_both = g.get_connection(
c.innovation_number) is not None and g2.get_connection(
c.innovation_number) is not None
in_fit_parent = g.get_connection(
c.innovation_number) is not None and g2.get_connection(
c.innovation_number) is None
self.assertTrue(in_both or in_fit_parent, msg)
# Add connections and nodes
g.add_connection(0, 2)
g.add_connection(0, 3)
g.add_connection(1, 2)
g.add_connection(1, 3)
g.add_node(0)
g.get_connections()[5].weight = 0.4
g2.add_connection(0, 2)
g2.add_connection(0, 3)
g2.add_connection(1, 2)
g2.add_connection(1, 3)
g2.add_node(1)
g.add_node(2)
# Assign fitness to genomes
g.fitness = 10
g2.fitness = 5
# Cross the genomes
child = e.cross(g, g2)
# Test child connections
msg = 'Child connection doesn\'t exist within either parent!'
for c in child.get_connections():
self.assertTrue(
g.get_connection(c.innovation_number) is not None
or g2.get_connection(c.innovation_number) is not None, msg)
# Test to make sure the child has the same amount of connections as the fitter parent
msg = 'Child missing fitter parent connection(s)!'
self.assertEqual(len(child.get_connections()),
len(g.get_connections()), msg)
# Test child nodes
msg = 'Child node doesn\'t exist within either parent!'
for n in child.get_nodes():
self.assertTrue(
g.get_node(n.id) is not None or g2.get_node(n.id) is not None,
msg)
# Test to make sure the child has the same amount of nodes as the fitter parent
msg = 'Child is missing fitter parent node(s)!'
self.assertEqual(len(child.get_nodes()), len(g.get_nodes()), msg)
# Test preference for fit parents
msg = 'Child connection preferred less fit parent!'
for c in child.get_connections():
in_both = g.get_connection(
c.innovation_number) is not None and g2.get_connection(
c.innovation_number) is not None
in_fit_parent = g.get_connection(
c.innovation_number) is not None and g2.get_connection(
c.innovation_number) is None
self.assertTrue(in_both or in_fit_parent, msg)
# Swap the fitness and test again
g.fitness = 5
g2.fitness = 10
# Cross the genomes
child = e.cross(g, g2)
# Test child connections
msg = 'Child connection doesn\'t exist within either parent!'
for c in child.get_connections():
self.assertTrue(
g.get_connection(c.innovation_number) is not None
or g2.get_connection(c.innovation_number) is not None, msg)
# Test to make sure the child has the same amount of connections as the fitter parent
msg = 'Child missing fitter parent connection(s)!'
self.assertEqual(len(child.get_connections()),
len(g2.get_connections()), msg)
# Test child nodes
msg = 'Child node doesn\'t exist within either parent!'
for n in child.get_nodes():
self.assertTrue(
g.get_node(n.id) is not None or g2.get_node(n.id) is not None,
msg)
# Test to make sure the child has the same amount of nodes as the fitter parent
msg = 'Child is missing fitter parent node(s)!'
self.assertEqual(len(child.get_nodes()), len(g2.get_nodes()), msg)
# Test preference for fit parents
msg = 'Child connection preferred less fit parent!'
for c in child.get_connections():
in_both = g.get_connection(
c.innovation_number) is not None and g2.get_connection(
c.innovation_number) is not None
in_fit_parent = g.get_connection(
c.innovation_number) is None and g2.get_connection(
c.innovation_number) is not None
self.assertTrue(in_both or in_fit_parent, msg)