Bounds#
- class scipy.optimize.Bounds(lb=-inf, ub=inf, keep_feasible=False)[source]#
- Bounds constraint on the variables. - The constraint has the general inequality form: - lb <= x <= ub - It is possible to use equal bounds to represent an equality constraint or infinite bounds to represent a one-sided constraint. - Parameters:
- lb, ubdense array_like, optional
- Lower and upper bounds on independent variables. lb, ub, and keep_feasible must be the same shape or broadcastable. Set components of lb and ub equal to fix a variable. Use - np.infwith an appropriate sign to disable bounds on all or some variables. Note that you can mix constraints of different types: interval, one-sided or equality, by setting different components of lb and ub as necessary. Defaults to- lb = -np.infand- ub = np.inf(no bounds).
- keep_feasibledense array_like of bool, optional
- Whether to keep the constraint components feasible throughout iterations. Must be broadcastable with lb and ub. Default is False. Has no effect for equality constraints. 
 
 - Methods - residual(x)- Calculate the residual (slack) between the input and the bounds