def test_init(self):
v = np.arange(6)
A = lo.linop_from_ndarray(np.outer(v, v), symmetric=True)
R = lo.SymmetricallyReducedLinearOperator(A, [1, 2, 3])
self.assertTrue(R.symmetric)
self.assertTrue(R.hermitian)
A = lo.linop_from_ndarray(np.outer(v, v))
R = lo.SymmetricallyReducedLinearOperator(A, [1, 2, 3])
self.assertFalse(R.symmetric)
self.assert_(R.shape == (3, 3))
def test_init(self):
v = np.arange(6)
A = lo.linop_from_ndarray(np.outer(v, v), symmetric=True)
R = lo.SymmetricallyReducedLinearOperator(A, [1, 2, 3])
self.assertTrue(R.symmetric)
self.assertTrue(R.hermitian)
A = lo.linop_from_ndarray(np.outer(v, v))
R = lo.SymmetricallyReducedLinearOperator(A, [1, 2, 3])
self.assertFalse(R.symmetric)
self.assert_(R.shape == (3, 3))
def test_linop_from_ndarray():
A = np.array([[1, 2, 3], [4, 5, 6]])
A_as_op = lo.linop_from_ndarray(A)
assert_(isinstance(A_as_op, lo.LinearOperator))
x = np.array([1, 1, 1])
assert_equal(A_as_op * x, A.dot(x))
x = np.array([1, 1])
assert_equal(A_as_op.T * x, A.T.dot(x))
assert_equal(A_as_op.H * x, A.T.dot(x))
init_Aop = lambda s, h: lo.linop_from_ndarray(A, symmetric=s, hermitian=h)
assert_raises(ValueError, init_Aop, True, False)
def test_linop_from_ndarray():
A = np.array([[1, 2, 3],
[4, 5, 6]])
A_as_op = lo.linop_from_ndarray(A)
assert_(isinstance(A_as_op, lo.LinearOperator))
x = np.array([1, 1, 1])
assert_equal(A_as_op * x, A.dot(x))
x = np.array([1, 1])
assert_equal(A_as_op.T * x, A.T.dot(x))
assert_equal(A_as_op.H * x, A.T.dot(x))
init_Aop = lambda s, h: lo.linop_from_ndarray(A, symmetric=s, hermitian=h)
assert_raises(ValueError, init_Aop, True, False)
def test_runtime(self):
v = np.arange(6)
A_mat = np.outer(v, v)
A = lo.linop_from_ndarray(A_mat)
sym_idx = [1, 2, 3]
R = lo.SymmetricallyReducedLinearOperator(A, sym_idx)
vmask = np.zeros(v.size); vmask[sym_idx] = 1
assert_equal(R * v[sym_idx], A_mat.dot(v * vmask)[sym_idx])
def test_runtime(self):
v = np.arange(6)
A_mat = np.outer(v, v)
A = lo.linop_from_ndarray(A_mat)
row_idx = [2, 4]
col_idx = [1, 2, 3]
R = lo.ReducedLinearOperator(A, row_idx, col_idx)
vmask = np.zeros(v.size); vmask[col_idx] = 1
assert_equal(R * v[col_idx], A_mat.dot(v * vmask)[row_idx])
def test_runtime(self):
v = np.arange(6)
A_mat = np.outer(v, v)
A = lo.linop_from_ndarray(A_mat)
sym_idx = [1, 2, 3]
R = lo.SymmetricallyReducedLinearOperator(A, sym_idx)
vmask = np.zeros(v.size)
vmask[sym_idx] = 1
assert_equal(R * v[sym_idx], A_mat.dot(v * vmask)[sym_idx])
def test_runtime(self):
v = np.arange(6)
A_mat = np.outer(v, v)
A = lo.linop_from_ndarray(A_mat)
row_idx = [2, 4]
col_idx = [1, 2, 3]
R = lo.ReducedLinearOperator(A, row_idx, col_idx)
vmask = np.zeros(v.size)
vmask[col_idx] = 1
assert_equal(R * v[col_idx], A_mat.dot(v * vmask)[row_idx])
def setUp(self):
self.A = lo.IdentityOperator(2)
self.B = lo.linop_from_ndarray(np.arange(1, 7).reshape([2, 3]))
self.C = lo.DiagonalOperator(np.arange(3))
self.D = lo.linop_from_ndarray(np.arange(6, 0, -1).reshape([3, 2]))
def test_init(self):
v = np.arange(6)
A = lo.linop_from_ndarray(np.outer(v, v))
R = lo.ReducedLinearOperator(A, [1, 2, 3], [4, 5])
self.assertFalse(R.symmetric)
self.assert_(R.shape == (3, 2))
def setUp(self):
self.A = lo.IdentityOperator(2)
self.B = lo.linop_from_ndarray(np.arange(1, 7).reshape([2, 3]))
self.C = lo.DiagonalOperator(np.arange(3))
self.D = lo.linop_from_ndarray(np.arange(6, 0, -1).reshape([3, 2]))
def test_init(self):
v = np.arange(6)
A = lo.linop_from_ndarray(np.outer(v, v))
R = lo.ReducedLinearOperator(A, [1, 2, 3], [4, 5])
self.assertFalse(R.symmetric)
self.assert_(R.shape == (3, 2))
