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])