(x, constraint_values)
| 10 | return 100.*(x[1] - x[0]**2)**2 + (1. - x[0])**2 |
| 11 | |
| 12 | def constraints(x, constraint_values): |
| 13 | # the modeler should throw an exception if the function cannot be evaluated |
| 14 | constraint_values[:] = [x[0]*x[1], x[0] + x[1]**2] |
| 15 | |
| 16 | def objective_gradient(x, gradient): |
| 17 | # the modeler should throw an exception if the function cannot be evaluated |
nothing calls this directly
no outgoing calls
no test coverage detected