# scipy.optimize.Bounds

class scipy.optimize.Bounds(lb, ub, keep_feasible=False)

  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, ub array_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.inf` with 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_feasible array_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.

scipy.optimize.LinearConstraint scipy.optimize.BFGS