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.
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 :None:None:`lb` and :None:None:`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 :None:None:`lb` and :None:None:`ub` as necessary.
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.
Bounds constraint on the variables.
The following pages refer to to this document either explicitly or contain code examples using this.
scipy.optimize._minimize._remove_from_bounds
scipy.optimize._differentialevolution.DifferentialEvolutionSolver
scipy.optimize._optimize._minimize_neldermead
scipy.optimize._minimize.minimize
scipy.optimize._differentialevolution.differential_evolution
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