The reductions listed here are specific to the choice of back end, i.e.,
solver. Currently, we support two types of back ends: conic solvers and
quadratic program solvers. When a problem is solved through the
solve() method, CVXPY attempts to find
the best back end for your problem. The
Dcp2Cone reduction converts DCP-compliant
problems into conic form, while the
Qp2SymbolicQp converts problems with
quadratic, piecewise affine objectives, affine equality constraints, and
piecewise-linear inequality constraints into a form that is closer to what is
accepted by solvers. The problems output by both reductions must be passed
through another sequence of reductions, not documented here, before they are
ready for to be solved.
Reduce DCP problems to a conic form.
This reduction takes as input (minimization) DCP problems and converts them into problems with affine objectives and conic constraints whose arguments are affine.
A problem is accepted if it is a minimization and is DCP.
Converts a DCP problem to a conic form.
Reduces a quadratic problem to a problem that consists of affine expressions and symbolic quadratic forms.
Problems with quadratic, piecewise affine objectives, piecewise-linear constraints inequality constraints, and affine equality constraints are accepted.
Converts a QP to an even more symbolic form.