def simulate(self, args):
f_node = args.operandNodes[0]
prior_mean_function = args.operandValues()[1]
prior_covariance_function = args.operandValues()[2]
f_compute = VentureSPRecord(
SP(GPMComputerRequestPSP(f_node), GPMComputerOutputPSP()))
f_emu = VentureSPRecord(GPSP(prior_mean_function, prior_covariance_function))
f_emu.spAux = self.shared_aux
f_compute.spAux = self.shared_aux
return v.pythonListToVentureList([f_compute, f_emu])
def simulate(self, args):
assert len(args.operandValues()) == 6
f_node = args.operandNodes[0]
a, b, c, noisestd, L_ = args.operandValues()[1:6]
L = int(L_)
f_compute = VentureSPRecord(
SP(QuadMComputerRequestPSP(f_node), QuadMComputerOutputPSP()))
f_emu = VentureSPRecord(QuadSP(a, b, c, noisestd, L))
f_emu.spAux = self.shared_aux
f_compute.spAux = self.shared_aux
return t.pythonListToVentureList([f_compute, f_emu])
def simulate(self, args):
f_node = args.operandNodes[0]
prior_covariance_function = args.operandValues[1]
f_compute = VentureSPRecord(
SP(GPMComputerRequestPSP(f_node), GPMComputerOutputPSP()))
# Prior mean is fixed to zero, because the current GP implementation
# assumes this
f_emu = VentureSPRecord(GPSP(zero_function, prior_covariance_function))
f_emu.spAux = self.shared_aux
f_compute.spAux = self.shared_aux
# TODO ways to get_Xseen and get_Yseen? maybe this belongs in the
# inference side
return t.pythonListToVentureList([f_compute, f_emu])
