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')