How to use the quadprog.problem.quadprogProblem function in quadprog

P = spspa.block_diag((2*D, 2*spspa.eye(k)), format='csc')
            q = np.append(-mu / gamma, np.zeros(k))
            A = spspa.vstack([
                    spspa.hstack([spspa.csc_matrix(np.ones((1, n))),
                                  spspa.csc_matrix((1, k))]),
                    spspa.hstack([F.T, -spspa.eye(k)]),
                    spspa.hstack([spspa.eye(n), spspa.csc_matrix((n, k))])
                ]).tocsc()
            lA = np.hstack([1., np.zeros(k), np.zeros(n)])
            uA = np.hstack([1., np.zeros(k), np.ones(n)])

        else:
            assert False, "Unhandled version"

        # Create a quadprogProblem and store it in a private variable
        self._prob = qp.quadprogProblem(P, q, A, lA, uA)
        # Create an OSQP object and store it in a private variable
        self._osqp = osqp.OSQP(**osqp_opts)
        self._osqp.problem(P, q, A, lA, uA)

uA = np.array([np.inf, np.inf])
        p = qp.quadprogProblem(P, q, A, lA, uA)
    elif example == 'random':
        # Random Example
        n = 30
        m = 50
        # Generate random Matrices
        Pt = sp.randn(n, n)
        P = spspa.csc_matrix(np.dot(Pt.T, Pt))
        q = sp.randn(n)
        A = spspa.csc_matrix(sp.randn(m, n))
        uA = 3 + sp.randn(m)
        # lA = uA
        lA = -3 + sp.randn(m)

        p = qp.quadprogProblem(P, q, A, lA, uA)
    elif example == 'lp':
        # Random Example
        n = 100
        m = 50
        # Generate random Matrices
        P = spspa.csc_matrix(np.zeros((n, n)))
        q = sp.randn(n)
        A = spspa.vstack([spspa.csc_matrix(sp.randn(m, n)), spspa.eye(n)])
        lA = np.append(- 3 + sp.randn(m), - 3 + sp.randn(n))
        uA = np.append(3 + sp.randn(m), 3 + sp.randn(n))
        p = qp.quadprogProblem(P, q, A, lA, uA)
    else:
        assert False, "Unknown example"

    # Solve with CPLEX
    resultsCPLEX = p.solve(solver=CPLEX, verbose=1)

#                   v >= 0
        Im = spspa.eye(m)
        P = spspa.block_diag((spspa.csc_matrix((n, n)), Im,
                              spspa.csc_matrix((m, m))), format='csc')
        q = np.append(np.zeros(m + n), np.ones(m))
        A = spspa.vstack([
                spspa.hstack([A, Im, Im]),
                spspa.hstack([A, -Im, -Im]),
                spspa.hstack([spspa.csc_matrix((m, n)), Im,
                              spspa.csc_matrix((m, m))]),
                spspa.hstack([spspa.csc_matrix((m, n + m)), Im])]).tocsc()
        lA = np.hstack([b, -np.inf*np.ones(m), np.zeros(2*m)])
        uA = np.hstack([np.inf*np.ones(m), b, np.ones(m), np.inf*np.ones(m)])

        # Create a quadprogProblem and store it in a private variable
        self._prob = qp.quadprogProblem(P, q, A, lA, uA)
        # Create an OSQP object and store it in a private variable
        self._osqp = osqp.OSQP(**osqp_opts)
        self._osqp.problem(P, q, A, lA, uA)

# Infeasible example
        # P = spspa.eye(2)
        P = spspa.csc_matrix((2, 2))
        q = np.ones(2)
        A = spspa.csc_matrix(np.array([[1, 0], [0, 1], [1, 1]]))
        lA = np.array([0., 0., -1.])
        uA = np.array([np.inf, np.inf, -1.])
        p = qp.quadprogProblem(P, q, A, lA, uA)
    elif example == 'unbounded':
        # Unbounded example
        P = spspa.csc_matrix((2, 2))
        q = np.array([2, -1])
        A = spspa.eye(2)
        lA = np.array([0., 0.])
        uA = np.array([np.inf, np.inf])
        p = qp.quadprogProblem(P, q, A, lA, uA)
    elif example == 'random':
        # Random Example
        n = 30
        m = 50
        # Generate random Matrices
        Pt = sp.randn(n, n)
        P = spspa.csc_matrix(np.dot(Pt.T, Pt))
        q = sp.randn(n)
        A = spspa.csc_matrix(sp.randn(m, n))
        uA = 3 + sp.randn(m)
        # lA = uA
        lA = -3 + sp.randn(m)

        p = qp.quadprogProblem(P, q, A, lA, uA)
    elif example == 'lp':
        # Random Example

uA = 3 + sp.randn(m)
        # lA = uA
        lA = -3 + sp.randn(m)

        p = qp.quadprogProblem(P, q, A, lA, uA)
    elif example == 'lp':
        # Random Example
        n = 100
        m = 50
        # Generate random Matrices
        P = spspa.csc_matrix(np.zeros((n, n)))
        q = sp.randn(n)
        A = spspa.vstack([spspa.csc_matrix(sp.randn(m, n)), spspa.eye(n)])
        lA = np.append(- 3 + sp.randn(m), - 3 + sp.randn(n))
        uA = np.append(3 + sp.randn(m), 3 + sp.randn(n))
        p = qp.quadprogProblem(P, q, A, lA, uA)
    else:
        assert False, "Unknown example"

    # Solve with CPLEX
    resultsCPLEX = p.solve(solver=CPLEX, verbose=1)

    # Solve with GUROBI
    resultsGUROBI = p.solve(solver=GUROBI, OutputFlag=1)

    # Solve with OSQP. You can pass options to OSQP solver
    resultsOSQP = p.solve(solver=OSQP, max_iter=5000,
                          eps_rel=1e-5,
                          eps_abs=1e-5,
                          alpha=1.6,
                          rho=0.1,
                          scale_steps=3,