def validator(self,NEAT_file):
""" Validate a single run.
Args:
NEAT_File: file for the NEAT genome
"""
global man, quadruped
# Initialize the manager to be unique to the process.
man = ODEManager(near_callback, stepsize=self.dt/self.n, log_data=self.log_frames, run_num=self.run_num)
# Initialize the quadruped
quadruped = Quadruped(man=man)
# If logging the output, tell manager to write the body type, dimensions, and position to the logging file.
if self.log_frames:
man.log_world_setup(self.eval_time,ind_num=self.run_num)
# Load in the best performing NEAT genome
genome = NEAT.Genome(NEAT_file)
self.current_network = NEAT.NeuralNetwork()
if not self.hyperNEAT:
genome.BuildPhenotype(self.current_network)
else:
genome.BuildHyperNEATPhenotype(self.current_network,self.substrate)
fit = self.physics_only_simulation_validator()
print(fit)
def validator(self, NEAT_file):
""" Validate a single run.
Args:
NEAT_File: file for the NEAT genome
"""
global man, quadruped
# Initialize the manager to be unique to the process.
man = ODEManager(near_callback,
stepsize=self.dt / self.n,
log_data=self.log_frames,
run_num=self.run_num)
# Initialize the quadruped
quadruped = Quadruped(man=man)
# If logging the output, tell manager to write the body type, dimensions, and position to the logging file.
if self.log_frames:
man.log_world_setup(self.eval_time, ind_num=self.run_num)
# Load in the best performing NEAT genome
genome = NEAT.Genome(NEAT_file)
self.current_network = NEAT.NeuralNetwork()
if not self.hyperNEAT:
genome.BuildPhenotype(self.current_network)
else:
genome.BuildHyperNEATPhenotype(self.current_network,
self.substrate)
fit = self.physics_only_simulation_validator()
print(fit)
def debug_validator(self):
""" Validate a single run. """
global man, worm
if self.aquatic:
grav = 0
fluid_dyn = 1
else:
grav = -9.81
fluid_dyn = 0
# Initialize the manager to be unique to the process.
man = ODEManager(near_callback,
stepsize=self.dt / self.n,
log_data=self.log_frames,
run_num=self.run_num,
gravity=grav,
fluid_dynamics=fluid_dyn)
# Initialize the worm
worm = Worm(man=man, num_joints=self._num_joints)
# If logging the output, tell manager to write the body type, dimensions, and position to the logging file.
if self.log_frames:
man.log_world_setup(self.eval_time, ind_num=self.run_num)
fit = self.physics_only_simulation_validator()
print(fit)
def validator(self):
""" Validate a single run.
Args:
NEAT_File: file for the NEAT genome
"""
global man, test_setup
# Initialize the manager to be unique to the process.
man = ODEManager(near_callback,
gravity=0,
stepsize=self.dt / self.n,
log_data=self.log_frames,
run_num=self.run_num)
# Initialize the quadruped
test_setup = Test_Setup(man=man)
# If logging the output, tell manager to write the body type, dimensions, and position to the logging file.
if self.log_frames:
man.log_world_setup(self.eval_time, ind_num=self.run_num)
fit = self.physics_only_simulation_validator()
print(fit)
def debug_validator(self):
""" Validate a single run. """
global man, quadruped
# Initialize the manager to be unique to the process.
man = ODEManager(near_callback, stepsize=self.dt/self.n, log_data=self.log_frames, run_num=self.run_num)
# Initialize the quadruped
quadruped = Quadruped(man=man)
# If logging the output, tell manager to write the body type, dimensions, and position to the logging file.
if self.log_frames:
man.log_world_setup(self.eval_time,ind_num=self.run_num)
fit = self.physics_only_simulation_validator()
print(fit)
def debug_validator(self):
""" Validate a single run. """
global man, quadruped
# Initialize the manager to be unique to the process.
man = ODEManager(near_callback, stepsize=self.dt/self.n, log_data=self.log_frames, run_num=self.run_num)
# Initialize the quadruped
quadruped = Quadruped(man=man)
# If logging the output, tell manager to write the body type, dimensions, and position to the logging file.
if self.log_frames:
man.log_world_setup(self.eval_time,ind_num=self.run_num)
fit = self.physics_only_simulation_validator()
print(fit)
def validator(self,NEAT_file,Morph_file):
""" Validate a single run.
Args:
NEAT_File: file for the NEAT genome
Morph_file: file for the morphology components
"""
global man, quadruped
self.validating = True
# Initialize the manager to be unique to the process.
man = ODEManager(near_callback, stepsize=self.dt/self.n, log_data=self.log_frames, run_num=self.run_num,erp=0.5,cfm=1E-2)
genome = [0,{}]
if NEAT_file:
# Load in the best performing NEAT genome
genome[0] = NEAT.Genome(NEAT_file)
self.current_network = NEAT.NeuralNetwork()
if not self.hyperNEAT:
genome[0].BuildPhenotype(self.current_network)
else:
genome[0].BuildHyperNEATPhenotype(self.current_network,self.substrate)
if Morph_file:
with open(Morph_file,"r") as f:
line = f.readline()
line = line.strip().split(',')
genome[1]['erp'] = float(line[0])
genome[1]['cfm'] = float(line[1])
# Initialize the quadruped
quadruped = Quadruped(man=man,morphology_genome={'erp':genome[1]['erp'],'cfm':genome[1]['cfm']})
# If logging the output, tell manager to write the body type, dimensions, and position to the logging file.
# Must be placed after creating the quadruped.
if self.log_frames:
man.log_world_setup(self.eval_time,ind_num=self.run_num)
fit = self.physics_only_simulation_validator()
return self.ann_activations,self.joint_feedback