def test_dlyap(self):
A = array([[-0.6, 0], [-0.1, -0.4]])
Q = array([[1, 0], [0, 1]])
X = dlyap(A, Q)
# print "The solution obtained is ", X
assert_array_almost_equal(dot(A, dot(X, A.T)) - X + Q, zeros((2, 2)))
A = array([[-0.6, 0], [-0.1, -0.4]])
Q = array([[3, 1], [1, 1]])
X = dlyap(A, Q)
# print "The solution obtained is ", X
assert_array_almost_equal(dot(A, dot(X, A.T)) - X + Q, zeros((2, 2)))
def test_dlyap(self):
A = matrix([[-0.6, 0], [-0.1, -0.4]])
Q = matrix([[1, 0], [0, 1]])
X = dlyap(A, Q)
# print("The solution obtained is ", X)
assert_array_almost_equal(A * X * A.T - X + Q, zeros((2, 2)))
A = matrix([[-0.6, 0], [-0.1, -0.4]])
Q = matrix([[3, 1], [1, 1]])
X = dlyap(A, Q)
# print("The solution obtained is ", X)
assert_array_almost_equal(A * X * A.T - X + Q, zeros((2, 2)))
def test_dlyap_g(self):
A = array([[-0.6, 0],[-0.1, -0.4]])
Q = array([[3, 1],[1, 1]])
E = array([[1, 1],[2, 1]])
X = dlyap(A, Q, None, E)
# print("The solution obtained is ", X)
assert_array_almost_equal(A @ X @ A.T - E @ X @ E.T + Q,
zeros((2,2)))
# Make sure that trying to solve with SciPy generates an error
with pytest.raises(ControlArgument, match="'scipy' not valid"):
X = dlyap(A, Q, None, E, method='scipy')
def test_dlyap(self):
A = matrix([[-0.6, 0],[-0.1, -0.4]])
Q = matrix([[1,0],[0,1]])
X = dlyap(A,Q)
# print("The solution obtained is ", X)
assert_array_almost_equal(A * X * A.T - X + Q, zeros((2,2)))
A = matrix([[-0.6, 0],[-0.1, -0.4]])
Q = matrix([[3, 1],[1, 1]])
X = dlyap(A,Q)
# print("The solution obtained is ", X)
assert_array_almost_equal(A * X * A.T - X + Q, zeros((2,2)))
def test_dlyap(self):
A = array([[-0.6, 0],[-0.1, -0.4]])
Q = array([[1,0],[0,1]])
X = dlyap(A,Q)
# print "The solution obtained is ", X
assert_array_almost_equal(dot(A,dot(X,A.T))-X+Q,zeros((2,2)))
A = array([[-0.6, 0],[-0.1, -0.4]])
Q = array([[3, 1],[1, 1]])
X = dlyap(A,Q)
# print "The solution obtained is ", X
assert_array_almost_equal(dot(A,dot(X,A.T))-X+Q,zeros((2,2)))
def test_dlyap_sylvester(self):
A = 5
B = matrix([[4, 3], [4, 3]])
C = matrix([2, 1])
X = dlyap(A, B, C)
# print("The solution obtained is ", X)
assert_array_almost_equal(A * X * B.T - X + C, zeros((1, 2)))
A = matrix([[2, 1], [1, 2]])
B = matrix([[1, 2], [0.5, 0.1]])
C = matrix([[1, 0], [0, 1]])
X = dlyap(A, B, C)
# print("The solution obtained is ", X)
assert_array_almost_equal(A * X * B.T - X + C, zeros((2, 2)))
def test_dlyap_sylvester(self):
A = 5
B = matrix([[4, 3], [4, 3]])
C = matrix([2, 1])
X = dlyap(A,B,C)
# print("The solution obtained is ", X)
assert_array_almost_equal(A * X * B.T - X + C, zeros((1,2)))
A = matrix([[2,1],[1,2]])
B = matrix([[1,2],[0.5,0.1]])
C = matrix([[1,0],[0,1]])
X = dlyap(A,B,C)
# print("The solution obtained is ", X)
assert_array_almost_equal(A * X * B.T - X + C, zeros((2,2)))
def test_dlyap_sylvester(self):
A = 5
B = array([[4, 3], [4, 3]])
C = array([2, 1])
X = dlyap(A, B, C)
# print "The solution obtained is ", X
assert_array_almost_equal(dot(A, dot(X, B.T)) - X + C, zeros((1, 2)))
A = array([[2, 1], [1, 2]])
B = array([[1, 2], [0.5, 0.1]])
C = array([[1, 0], [0, 1]])
X = dlyap(A, B, C)
# print "The solution obtained is ", X
assert_array_almost_equal(dot(A, dot(X, B.T)) - X + C, zeros((2, 2)))
def test_dlyap_sylvester(self):
A = 5
B = array([[4, 3], [4, 3]])
C = array([2, 1])
X = dlyap(A,B,C)
# print "The solution obtained is ", X
assert_array_almost_equal(dot(A,dot(X,B.T))-X+C,zeros((1,2)))
A = array([[2,1],[1,2]])
B = array([[1,2],[0.5,0.1]])
C = array([[1,0],[0,1]])
X = dlyap(A,B,C)
# print "The solution obtained is ", X
assert_array_almost_equal(dot(A,dot(X,B.T))-X+C,zeros((2,2)))
def test_dlyap_g(self):
A = matrix([[-0.6, 0], [-0.1, -0.4]])
Q = matrix([[3, 1], [1, 1]])
E = matrix([[1, 1], [2, 1]])
X = dlyap(A, Q, None, E)
# print("The solution obtained is ", X)
assert_array_almost_equal(A * X * A.T - E * X * E.T + Q, zeros((2, 2)))
def test_dlyap_g(self):
A = matrix([[-0.6, 0],[-0.1, -0.4]])
Q = matrix([[3, 1],[1, 1]])
E = matrix([[1, 1],[2, 1]])
X = dlyap(A,Q,None,E)
# print("The solution obtained is ", X)
assert_array_almost_equal(A * X * A.T - E * X * E.T + Q, zeros((2,2)))
def test_dlyap_g(self):
A = array([[-0.6, 0], [-0.1, -0.4]])
Q = array([[3, 1], [1, 1]])
E = array([[1, 1], [2, 1]])
X = dlyap(A, Q, None, E)
# print("The solution obtained is ", X)
assert_array_almost_equal(
A.dot(X).dot(A.T) - E.dot(X).dot(E.T) + Q, zeros((2, 2)))
def test_dlyap_g(self):
A = array([[-0.6, 0], [-0.1, -0.4]])
Q = array([[3, 1], [1, 1]])
E = array([[1, 1], [2, 1]])
X = dlyap(A, Q, None, E)
# print "The solution obtained is ", X
assert_array_almost_equal(dot(A,dot(X,A.T))-dot(E,dot(X,E.T))+Q, \
zeros((2,2)))
def test_dlyap_g(self):
A = array([[-0.6, 0],[-0.1, -0.4]])
Q = array([[3, 1],[1, 1]])
E = array([[1, 1],[2, 1]])
X = dlyap(A,Q,None,E)
# print "The solution obtained is ", X
assert_array_almost_equal(dot(A,dot(X,A.T))-dot(E,dot(X,E.T))+Q, \
zeros((2,2)))
def test_dlyap_sylvester(self):
A = 5
B = array([[4, 3], [4, 3]])
C = array([2, 1])
X = dlyap(A,B,C)
# print("The solution obtained is ", X)
assert_array_almost_equal(A * X @ B.T - X + C, zeros((1,2)))
A = array([[2, 1], [1, 2]])
B = array([[1, 2], [0.5, 0.1]])
C = array([[1, 0], [0, 1]])
X = dlyap(A, B, C)
# print("The solution obtained is ", X)
assert_array_almost_equal(A @ X @ B.T - X + C, zeros((2,2)))
# Make sure that trying to solve with SciPy generates an error
with pytest.raises(ControlArgument, match="'scipy' not valid"):
X = dlyap(A, B, C, method='scipy')
