def test_constraints(self):
"""
In this test, we build a body generator with a maximum
number of inputs / outputs that is already satisfied
by the root component, and ensure no further generation
is done.
:return:
"""
# Seed so we can reproduce if this goes wrong
seed = random.randint(0, 10000)
random.seed(seed)
gen = BodyGenerator(
body_spec,
root_parts=["Core"],
attach_parts=["2Params"],
max_inputs=2,
max_outputs=10,
max_parts=100,
fix_num_parts=True
)
body = gen.generate()
self.assertEquals("Core", body.root.type,
"Root type should be 'Core' (seed %d)." % seed)
self.assertEquals(0, len(body.root.child),
"Too many inputs were generated (seed %d)." % seed)
gen.max_inputs = 100
gen.max_outputs = 2
body = gen.generate()
self.assertEquals(0, len(body.root.child),
"Too many outputs were generated (seed %d)." % seed)
# This leaves enough room for a 2Params child, but not enough for a SomePart child
gen.max_outputs = 4
body = gen.generate()
self.assertEquals(_count_parts(body.root), 1,
"One child part should be present (seed %d)." % seed)
self.assertEquals("2Params", body.root.child[0].part.type,
"Child part should be of type 2Params (seed %d)." % seed)
gen.max_inputs = gen.max_outputs = 100
gen.max_parts = 1
body = gen.generate()
self.assertEquals(0, _count_parts(body.root),
"No child parts should be present (seed %d)." % seed)
def test_constraints(self):
"""
In this test, we build a body generator with a maximum
number of inputs / outputs that is already satisfied
by the root component, and ensure no further generation
is done.
:return:
"""
# Seed so we can reproduce if this goes wrong
seed = random.randint(0, 10000)
random.seed(seed)
gen = BodyGenerator(
body_spec,
root_parts=["Core"],
attach_parts=["2Params"],
max_inputs=2,
max_outputs=10,
max_parts=100,
fix_num_parts=True
)
body = gen.generate()
self.assertEquals("Core", body.root.type, "Root type should be 'Core' (seed %d)." % seed)
self.assertEquals(0, len(body.root.child), "Too many inputs were generated (seed %d)." % seed)
gen.max_inputs = 100
gen.max_outputs = 2
body = gen.generate()
self.assertEquals(0, len(body.root.child), "Too many outputs were generated (seed %d)." % seed)
# This leaves enough room for a 2Params child, but not enough for a SomePart child
gen.max_outputs = 4
body = gen.generate()
self.assertEquals(_count_parts(body.root), 1,
"One child part should be present (seed %d)." % seed)
self.assertEquals("2Params", body.root.child[0].part.type,
"Child part should be of type 2Params (seed %d)." % seed)
gen.max_inputs = gen.max_outputs = 100
gen.max_parts = 1
body = gen.generate()
self.assertEquals(0, _count_parts(body.root),
"No child parts should be present (seed %d)." % seed)
def test_valid(self):
"""
Generates a body and ensures it is completely initialized.
:return:
"""
# Seed so we can reproduce if this goes wrong
seed = random.randint(0, 10000)
random.seed(seed)
gen = BodyGenerator(
body_spec,
root_parts=["Core"],
attach_parts=["2Params"],
max_inputs=100,
max_outputs=100,
max_parts=10,
fix_num_parts=True
)
body = gen.generate()
self.assertTrue(body.IsInitialized(), "Incomplete body (seed %d)." % seed)
# For the brain, we use the default neural network
brain_spec = default_neural_net()
# Specify a body generator for the specification
body_gen = BodyGenerator(
body_spec,
# List all parts that can serve as the robot root
root_parts=["Core"],
# List all parts that can be attached
attach_parts=["Wheel", "Hinge"],
# Set the maximum number of used parts. The
# actual number will be determined by a
# random pick and some input / output constraints.
max_parts=15,
# The maximum number of input (i.e. sensory) values
# our robot may have.
max_inputs=8,
# The maximum number ouf output (i.e. motory) values
# our robot may have.
max_outputs=12)
# Also get a brain generator
brain_gen = NeuralNetworkGenerator(brain_spec, max_hidden=10)
# Create a builder to convert the protobuf to SDF