scipy.optimize.Bounds#
- class scipy.optimize.Bounds(lb, ub, 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, ubarray_like
Lower and upper bounds on independent variables. Each array must have the same size as x or be a scalar, in which case a bound will be the same for all the variables. 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.- keep_feasiblearray_like of bool, optional
Whether to keep the constraint components feasible throughout iterations. A single value set this property for all components. Default is False. Has no effect for equality constraints.