def inequality_constraint(self, x=None): """Retrieve the inequality constraint values for your function Assumptions: N/A Source: N/A Inputs: x [vector] Outputs: scaled_constraints [vector] Properties Used: None """ self.evaluate(x) aliases = self.optimization_problem.aliases constraints = self.optimization_problem.constraints results = self.results # Setup constraints indices = [] for ii in xrange(0, len(constraints)): if constraints[ii][1] == ('='): indices.append(ii) iqconstraints = np.delete(constraints, indices, axis=0) if iqconstraints == []: scaled_constraints = [] else: constraint_values = help_fun.get_values(self, iqconstraints, aliases) constraint_values[iqconstraints[:, 1] == '<'] = -constraint_values[ iqconstraints[:, 1] == '<'] bnd_constraints = constraint_values - help_fun.scale_const_bnds( iqconstraints) scaled_constraints = help_fun.scale_const_values( iqconstraints, constraint_values) return scaled_constraints
def equality_constraint(self,x = None): """Retrieve the equality constraint values for your function Assumptions: N/A Source: N/A Inputs: x [vector] Outputs: scaled_constraints [vector] Properties Used: None """ self.evaluate(x) aliases = self.optimization_problem.aliases constraints = self.optimization_problem.constraints results = self.results # Setup constraints indices = [] for ii in xrange(0,len(constraints)): if constraints[ii][1]=='>': indices.append(ii) elif constraints[ii][1]=='<': indices.append(ii) eqconstraints = np.delete(constraints,indices,axis=0) if eqconstraints == []: scaled_constraints = [] else: constraint_values = help_fun.get_values(self,eqconstraints,aliases) - help_fun.scale_const_bnds(eqconstraints) scaled_constraints = help_fun.scale_const_values(eqconstraints,constraint_values) return scaled_constraints
def equality_constraint(self,x = None): self.evaluate(x) aliases = self.optimization_problem.aliases constraints = self.optimization_problem.constraints results = self.results # Setup constraints indices = [] for ii in xrange(0,len(constraints)): if constraints[ii][1]=='>': indices.append(ii) elif constraints[ii][1]=='<': indices.append(ii) eqconstraints = np.delete(constraints,indices,axis=0) if eqconstraints == []: scaled_constraints = [] else: constraint_values = help_fun.get_values(self,eqconstraints,aliases) - help_fun.scale_const_bnds(eqconstraints) scaled_constraints = help_fun.scale_const_values(eqconstraints,constraint_values) return scaled_constraints
def equality_constraint(self,x = None): self.evaluate(x) aliases = self.optimization_problem.aliases constraints = self.optimization_problem.constraints results = self.results # Setup constraints indices = [] for ii in xrange(0,len(constraints)): if constraints[ii][1]=='>': indices.append(ii) elif constraints[ii][1]=='<': indices.append(ii) eqconstraints = np.delete(constraints,indices,axis=0) if eqconstraints == []: scaled_constraints = [] else: constraint_values = help_fun.get_values(self,eqconstraints,aliases) - help_fun.scale_const_bnds(eqconstraints) scaled_constraints = help_fun.scale_const_values(eqconstraints,constraint_values) return scaled_constraints