def run(self,x0,x1,autoInit=True,threshold=1e-3,**kwargs):
if autoInit:
_,_,T = self.buildInitGuess(x0,x1)
if 'horizon' not in self.options:
if 'additionalOptions' not in kwargs: kwargs['additionalOptions'] = ''
kwargs['additionalOptions'] += ' --horizon=%.4f' % T[-1]
AcadoRunner.run(self,states=self.stateDict(x0,x1), **kwargs)
# # Run may raise an error but always return True.
return self.checkResult(True,x0,x1,threshold=threshold)
def __init__(self,path="/home/nmansard/src/pinocchio/pycado/build/unittest/connect_pendulum",
model=None,data=None,datadir='/tmp/'):
AcadoRunner.__init__(self,path)
self.options['istate'] = datadir+'guess.stx'
self.options['icontrol'] = datadir+'guess.ctl'
self.options['ocontrol'] = datadir+'mpc.ctl'
self.options['ostate'] = datadir+'mpc.stx'
self.options['oparam'] = datadir+'mpc.prm'
self.withRunningCost = False # The problem is Mayer cost.
self.guess = InitGuessBuilder(model,data)
def run_async(self,x0,x1,autoInit=True,jobid=None, **kwargs):
# We have to pre-book to know where the init-guess should be stored.
if jobid is None: jobid = self.book_async()
if autoInit:
_,_,T = self.buildInitGuess(x0,x1,jobid=jobid)
if 'horizon' not in self.options:
if 'additionalOptions' not in kwargs: kwargs['additionalOptions'] = ''
kwargs['additionalOptions'] += ' --horizon=%.4f' % T[-1]
return AcadoRunner.run_async(self,
states = self.stateDict(x0,x1),
jobid = jobid, **kwargs)
def join(self,jobid,x1=None,x2=None,threshold=1e-3,**kwargs):
'''Join the solver process and check if the result satisfies the constraints'''
ret = AcadoRunner.join(self,jobid,**kwargs)
return self.checkResult(ret,x1,x2,jobid,threshold)
def rerun(self): return AcadoRunner.run(self) # DEPREC???
# --- ASYNC --------------------------------------------------------------------------
# --- ASYNC --------------------------------------------------------------------------
# --- ASYNC --------------------------------------------------------------------------
def run_async(self,x0,x1,autoInit=True,jobid=None, **kwargs):
def initrun(self,x0,x1,iterations=100,autoInit = True,**kwargs):
if autoInit: self.buildInitGuess(x0,x1)
AcadoRunner.initrun(self,
states=self.stateDict(x0,x1),
iterations=iterations)
return self.checkResult(True,x0,x1)
x, reward = env.step(u)
env.render()
time.sleep(1e-1)
rsum += reward
if verbose: print 'Lasted ', i, ' timestep -- total reward:', rsum
signal.signal(signal.SIGTSTP,
lambda x, y: rendertrial()) # Roll-out when CTRL-Z is pressed
env.NDT = 1
env.modulo = False
from acado_runner import AcadoRunner
acado = AcadoRunner()
acado.options['horizon'] = NSTEPS * env.DT
acado.options['steps'] = NSTEPS
acado.options['shift'] = 0
acado.options['iter'] = 20
acado.options['friction'] = env.Kf
acado.options['decay'] = DECAY_RATE
acado.options['icontrol'] = '/tmp/guess.ctl'
del acado.options['istate']
def policyOptim(x0):
'''
Rollout the net to get a warmstart, then run Acado to optimize the warmstart
Return the policy and the value at input state.
'''
mod = round(env.x[0, 0] / 2 / np.pi)
dx = -mod * 2 * np.pi
X[:, 0] += dx
return X, U
x0 = np.matrix([2., .2]).T
#X,U=rollout(x0)
env.NDT = 10
x0 = np.matrix([0.30459664, -7.20891078]).T
NNODES = 16
FNODES = NSTEPS / NNODES
from acado_runner import AcadoRunner
acado = AcadoRunner(
"/home/nmansard/src/pinocchio/pycado/build/unittest/pendulum2o")
acado.options['horizon'] = NSTEPS * env.DT
acado.options['steps'] = NNODES
acado.options['shift'] = 0
acado.options['iter'] = 10 # 100
acado.options['friction'] = env.Kf
#acado.options['decay'] = 0 # DECAY_RATE
#del acado.options['istate']
def policyOptim(x0=None):
X, U = rollout(x0)
guess = np.hstack([
np.matrix(np.arange(0, (NSTEPS + 1) * env.DT, env.DT)).T, X, U,
zero(NSTEPS + 1),