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solver-qpoases

A qpOASES wrapper for Python that ships prebuilt binaries. It exposes qpOASES' online active-set solver through a thin, numpy-friendly, MATLAB-quadprog-like interface.

pip install marinholab-solvers-qpoases

Overview

Given a symmetric matrix H, a vector f, and (optionally) inequality and equality constraint matrices, the solver solves the quadratic program

min_x   0.5 * x' H x + f' x
s.t.    A x <= b
        Aeq x = beq

Once a problem has been solved once, subsequent solves on the same Solver instance are warm-started by default (Configuration.use_hotstart = True), which is the main performance benefit of qpOASES for repeated, related QPs.

Quickstart

import numpy as np
from marinholab.solvers import qpoases

solver = qpoases.Solver()

H = np.eye(2)                          # positive definite Hessian
f = np.array([-1.0, -1.0])             # linear term
A = np.array([[1.0, 0.0]])             # x[0] <= 0.2
b = np.array([0.2])

x = solver.solve_quadratic_program(H, f, A, b,
                                   Aeq=np.zeros((1, 2)),
                                   beq=np.zeros((1,)))
# x ≈ [0.2, 1.0]

Omitting constraints

Any of the four constraint arguments (A, b, Aeq, beq) can be None, meaning "no such constraint". The matrix and its right-hand side must be omitted (or provided) together:

# Unconstrained
x = solver.solve_quadratic_program(H, f, None, None, None, None)

# Equality constraints only
x = solver.solve_quadratic_program(H, f, None, None, Aeq, beq)

Active set

solver.get_active_set() reports, for each row of the combined constraint matrix (rows of A followed by rows of Aeq), whether it is:

  • -1 active at its lower bound,
  • 0 inactive,
  • +1 active at its upper bound (equality constraints are always +1, since their bounds coincide).
solver.solve_quadratic_program(H, f, A, b, Aeq, beq)
solver.get_active_set()  # e.g. [ 1.0, 0.0, 0.0]

Configuration

All of qpOASES' Options fields are exposed, plus a few wrapper-specific settings. Create a Configuration, tweak the fields you need, and pass it to the solver:

config = qpoases.Configuration()
config.hessian_type = qpoases.HessianType.HST_SEMIDEF   # H is rank-deficient
config.terminationTolerance = 1.0e-9                    # tighter convergence
solver = qpoases.Solver(config)

The enum types are re-exported for convenience: qpoases.BooleanType, qpoases.HessianType, qpoases.PrintLevel, and qpoases.SubjectToStatus.

Wrapper-specific options

Option Default Type Description
maximum_working_set_recalculations 150 int Max working-set recalculations during the initial homotopy (nWSR passed to init/hotstart). Increase if solves hit the maximum.
use_hotstart True bool Warm-start subsequent solves with hotstart() instead of re-initialising with init().
hessian_type HST_POSDEF HessianType Definiteness assumed for H; given to the underlying SQProblem.

Hessian definiteness (HessianType)

Value Meaning
HST_ZERO Hessian is the zero matrix (LP formulation)
HST_IDENTITY Hessian is the identity matrix
HST_POSDEF Hessian is (strictly) positive definite
HST_POSDEF_NULLSPACE Positive definite on the null space of active bounds/constraints
HST_SEMIDEF Positive semi-definite
HST_INDEF Indefinite
HST_UNKNOWN Unknown

qpOASES options

These map 1:1 onto qpOASES' Options fields. Defaults match qpOASES' own defaults for a double-precision build (see Options::setToDefault()). See the qpOASES manual for a full description of each option.

Booleans (BooleanType: BT_FALSE / BT_TRUE)

Option Default Description
enableRamping BT_TRUE Enables the ramping strategy.
enableFarBounds BT_TRUE Enables the far bounds strategy.
enableFlippingBounds BT_TRUE Allows flipping active bounds between lower and upper values.
enableRegularisation BT_FALSE Regularises H when (semi-)definiteness is detected.
enableFullLITests BT_FALSE Uses the condition-hardened linear-independence (LI) test.
enableNZCTests BT_TRUE Enables the nonzero-curvature test.
enableEqualities BT_FALSE Treats equality constraints as always active.
enableInertiaCorrection BT_TRUE Repairs the working set when negative curvature is found during a hotstart.
enableDropInfeasibles BT_FALSE Whether infeasible constraints may be dropped.

Integers (int_t)

Option Default Description
enableDriftCorrection 1 Frequency of drift corrections (0 = off).
enableCholeskyRefactorisation 0 Frequency of full Cholesky refactorisation of the projected Hessian (0 = rank updates only).
numRegularisationSteps 0 Max successive regularisation steps.
numRefinementSteps 1 Max iterative-refinement steps.
dropBoundPriority 1 Priority used when dropping bounds.
dropEqConPriority 1 Priority used when dropping equality constraints.
dropIneqConPriority 1 Priority used when dropping inequality constraints.

Reals (real_t, double)

Option Default Description
terminationTolerance 5.0e6 * EPS (~1.1e-9) Relative tolerance that stops the homotopy. Smaller = more accurate, more work.
boundTolerance 1.0e6 * EPS Bound tolerance; a constraint whose bounds differ by less is treated as an equality.
boundRelaxation 1.0e4 Offset for relaxing bounds at the start of the initial homotopy (also the initial far-bound value).
epsNum -1.0e3 * EPS Numerator tolerance for the ratio test.
epsDen 1.0e3 * EPS Denominator tolerance for the ratio test.
maxPrimalJump 1.0e8 Max allowed primal jump in nonzero-curvature tests.
maxDualJump 1.0e8 Max allowed dual jump in LI tests.
initialRamping 0.5 Start value of the ramping strategy.
finalRamping 1.0 Final value of the ramping strategy.
initialFarBounds 1.0e6 Initial size of the far bounds.
growFarBounds 1.0e3 Growth factor applied to the far bounds.
epsFlipping 1.0e3 * EPS Tolerance of the squared Cholesky diagonal factor that triggers flipping a bound.
epsRegularisation 1.0e3 * EPS Scaling factor of the identity matrix used for Hessian regularisation.
epsIterRef 1.0e2 * EPS Early-termination tolerance for iterative refinement.
epsLITests 1.0e5 * EPS Tolerance for the linear-independence tests.
epsNZCTests 3.0e3 * EPS Tolerance for the nonzero-curvature tests.
rcondSMin 1.0e-14 Min reciprocal condition number of the Schur complement before a refactorisation is triggered.

Status / print enums

Option Default Type Description
printLevel PL_MEDIUM PrintLevel Verbosity of qpOASES output (PL_NONE, PL_LOW, PL_MEDIUM, PL_HIGH, PL_TABULAR, PL_DEBUG_ITER).
initialStatusBounds ST_LOWER SubjectToStatus Status assumed for all bounds at the first iteration.

Print levels (PrintLevel)

PL_DEBUG_ITER, PL_TABULAR, PL_NONE, PL_LOW, PL_MEDIUM, PL_HIGH.

Bound/constraint statuses (SubjectToStatus)

ST_LOWER, ST_INACTIVE, ST_UPPER, ST_INFEASIBLE_LOWER, ST_INFEASIBLE_UPPER, ST_UNDEFINED.

Examples

  • marinholab/solvers/qpoases/example.py — positive-definite and semi-definite solves, the None-constraint path, and the active set. Run it with qpoases_example (installed as a console script).
  • marinholab/solvers/qpoases/example_kinematics.py — an optional example showing the solver used in a hierarchical (task-priority) controller for a kinematically redundant robot, built on dqrobotics. It requires the optional dependencies dqrobotics and dqrobotics-pyplot (pip install --pre dqrobotics dqrobotics-pyplot).

Building from source

The package builds a C++ extension (via CMake + pybind11) and vendors qpOASES and pybind11 as git submodules.

git clone --recurse-submodules <repo>
pip install .

Prerequisites: a C++23 compiler, CMake, an Eigen3 installation, and Python. On Ubuntu: sudo apt-get install cmake libeigen3-dev.

Type checking

The package ships a type stub (marinholab/solvers/qpoases/_core.pyi) and a py.typed marker, so downstream projects can be checked with Pyright (or Pylance) without extra configuration. Run the project's own check with:

pyright

License

The qpOASES library is LGPLv2.1; the wrapper is under the terms of the included LICENSE file.

Metadata

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Release files / marinholab_solvers_qpoases-26.4.0.42-cp310-cp310-manylinux2014_x86_64.whl

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Release files / marinholab_solvers_qpoases-26.4.0.42-cp310-cp310-macosx_26_0_universal2.whl

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