picos.constraints¶

This package contains the constraint types that are used to express optimization constraints. You do not need to instanciate these constraints directly; it is more convenient to create them by applying Python’s comparison operators to algebraic expressions (see the Cheat Sheet).

Classes¶

 AbsoluteValueConstraint(signedScalar, upperBound) AffineConstraint(lhs, relation, rhs[, …]) An equality or inequality between two affine expressions. Constraint(typeTerm[, customString, printSize]) An abstract base class for optimization constraints. DetRootNConstraint(detRootN, lowerBound) ExpConeConstraint(element[, customString]) An exponential cone constraint stating that fulfills . FlowConstraint(G, f, source, sink, flow_value) GeoMeanConstraint(geoMean, lowerBound) KullbackLeiblerConstraint(divergence, upperBound) LMIConstraint(lhs, relation, rhs[, customString]) An inequality with respect to the positive semidefinite cone, also known as a Linear Matrix Inequality (LMI) or an SDP constraint. LSEConstraint(lse, upperBound) An upper bound on a log-sum-exp expression. LogConstraint(log, lowerBound) A lower bound on a logarithmic expression. MetaConstraint(tmpProblem, typeTerm[, …]) An abstract base class for optimization constraints that are comprised of auxiliary variables and constraints. PNormConstraint(pNorm, relation, rhs) PQNormConstraint(pqNorm, upperBound) QuadConstraint(lowerEqualZero[, customString]) An upper bound on a scalar quadratic expression. RSOCConstraint(normedExpression, …[, …]) A rotated second order cone constraint. SOCConstraint(normedExpression, upperBound) A second order cone (2-norm cone, Lorentz cone) constraint. SumExpConstraint(theSum, upperBound) SumExtremesConstraint(theSum, relation, rhs) SymTruncSimplexConstraint(simplex, element) TracePowConstraint(power, relation, rhs)