def matrix_frac(X, P):
if isinstance(P, np.ndarray):
return QuadForm(X, LA.inv(P))
else:
return MatrixFrac(X, P)
def matrix_frac(X, P):
if isinstance(P, np.ndarray):
invP = LA.inv(P)
return QuadForm(X, (invP + np.conj(invP).T) / 2.0)
else:
return MatrixFrac(X, P)
def matrix_frac(X, P):
if isinstance(P, np.ndarray):
invP = np.matrix(LA.inv(P))
return QuadForm(X, (invP + invP.H) / 2.0)
else:
return MatrixFrac(X, P)
def setUp(self):
self.x = Variable(2, name='x')
self.Q = np.eye(2)
self.c = np.array([1, 0.5])
self.qp = Problem(Minimize(QuadForm(self.x, self.Q)), [self.x <= -1])
self.cp = Problem(Minimize(self.c.T * self.x + 1), [self.x >= 0])