def test_dtypes(self):
for dtype_op in allowed_types:
for dtype_in in allowed_types:
dtype_out = np.result_type(dtype_op, dtype_in)
matvecs = get_matvecs(self.A)
A = lo.LinearOperator(nargin=matvecs['shape'][1],
nargout=matvecs['shape'][0],
matvec=matvecs['matvec'],
matvec_transp=matvecs['matvec_transp'],
dtype=dtype_op)
x = np.array([1, 1, 1]).astype(dtype_in)
assert_((A * x).dtype == dtype_out)
def test_init(self):
matvecs = get_matvecs(self.A)
A = lo.LinearOperator(nargin=matvecs['shape'][1],
nargout=matvecs['shape'][0],
matvec=matvecs['matvec'])
assert_(hasattr(A, '_matvec'))
assert_(hasattr(A, 'dtype'))
assert_(A.T is None)
assert_(A.H is None)
A = lo.LinearOperator(nargin=matvecs['shape'][1],
nargout=matvecs['shape'][0],
matvec=matvecs['matvec'],
matvec_transp=matvecs['matvec_transp'])
assert_(A.T is not None)
assert_(A.H is A.T)
A = lo.LinearOperator(nargin=matvecs['shape'][1],
nargout=matvecs['shape'][0],
matvec=matvecs['matvec'],
matvec_transp=matvecs['matvec_transp'])
B = lo.LinearOperator(nargin=matvecs['shape'][0],
nargout=matvecs['shape'][1],
matvec=matvecs['matvec_transp'])
x = np.random.random(A.shape[0])
assert_(np.allclose(B * x, A.T * x))
assert_(np.allclose(B * x, A.H * x))
matvecs = get_matvecs(self.D)
D = lo.LinearOperator(nargin=matvecs['shape'][1],
nargout=matvecs['shape'][0],
matvec=matvecs['matvec'],
matvec_transp=matvecs['matvec_transp'],
matvec_adj=matvecs['matvec_adj'],
dtype=self.D.dtype)
assert_(D.T is not None)
assert_(D.H is not None)
E = lo.LinearOperator(nargin=matvecs['shape'][0],
nargout=matvecs['shape'][1],
matvec=matvecs['matvec_transp'],
matvec_transp=matvecs['matvec'],
dtype=self.E.dtype)
x = np.random.random(E.shape[1]) + 1j * np.random.random(E.shape[1])
assert_(np.allclose(E * x, D.T * x))
assert_(E.H is not None) # E.H was inferred.
y = np.random.random(E.shape[0]) + 1j * np.random.random(E.shape[0])
assert_(np.allclose(E.H * y, E.rmatvec(y)))
F = lo.LinearOperator(nargin=matvecs['shape'][0],
nargout=matvecs['shape'][1],
matvec=matvecs['matvec_adj'],
dtype=self.F.dtype)
x = np.random.random(F.shape[1]) + 1j * np.random.random(F.shape[1])
assert_(np.allclose(F * x, D.H * x))
matvecs = get_matvecs(self.G)
G = lo.LinearOperator(nargin=matvecs['shape'][1],
nargout=matvecs['shape'][0],
matvec=matvecs['matvec'],
matvec_transp=matvecs['matvec_transp'],
matvec_adj=matvecs['matvec_adj'],
dtype=self.G.dtype)
x = np.random.random(G.shape[1]) + 1j * np.random.random(G.shape[1])
assert_(np.allclose(G * x, G.H * x))
assert_(np.allclose(G.T.H * x, G.H.T * x))
matvecs = get_matvecs(self.H)
H = lo.LinearOperator(nargin=matvecs['shape'][1],
nargout=matvecs['shape'][0],
matvec=matvecs['matvec'],
matvec_transp=matvecs['matvec_transp'],
matvec_adj=matvecs['matvec_adj'],
dtype=self.H.dtype)
x = np.random.random(H.shape[1]) + 1j * np.random.random(H.shape[1])
assert_(np.allclose(H * x, H.T * x))
assert_(np.allclose(H * x, H.T.T * x))
def test_runtime(self):
matvecs = get_matvecs(self.A)
A = lo.LinearOperator(nargin=matvecs['shape'][1],
nargout=matvecs['shape'][0],
matvec=matvecs['matvec'],
matvec_transp=matvecs['matvec_transp'])
matvecs = get_matvecs(self.B)
B = lo.LinearOperator(nargin=matvecs['shape'][1],
nargout=matvecs['shape'][0],
matvec=matvecs['matvec'],
matvec_transp=matvecs['matvec_transp'])
matvecs = get_matvecs(self.C)
C = lo.LinearOperator(nargin=matvecs['shape'][1],
nargout=matvecs['shape'][0],
matvec=matvecs['matvec'],
matvec_transp=matvecs['matvec_transp'])
u = np.array([1, 1])
v = np.array([1, 1, 1])
assert_equal(A * v, [6, 15])
assert_equal(A._matvec(v), [6, 15])
assert_equal(A.T * u, [5, 7, 9])
assert_equal(A.H * u, [5, 7, 9])
assert_equal((A * 2) * v, A * (2 * v))
assert_equal((A * 2) * v, (2 * A) * v)
assert_equal((A / 2) * v, A * (v / 2))
assert_equal((-A) * v, A * (-v))
assert_equal((A - A) * v, [0, 0])
assert_equal((C**2) * u, [17, 37])
assert_equal((C**2) * u, (C * C) * u)
assert_(isinstance(A + A, lo.LinearOperator))
assert_(isinstance(A - A, lo.LinearOperator))
assert_(isinstance(-A, lo.LinearOperator))
assert_(isinstance(2 * A, lo.LinearOperator))
assert_(isinstance(A * 2, lo.LinearOperator))
assert_(isinstance(A * 0, lo.ZeroOperator))
assert_(isinstance(A / 2, lo.LinearOperator))
assert_(isinstance(C**2, lo.LinearOperator))
assert_(isinstance(C**0, lo.IdentityOperator))
sum_A = lambda x: A + x
assert_raises(ValueError, sum_A, 3)
assert_raises(ValueError, sum_A, v)
assert_raises(ShapeError, sum_A, B)
sub_A = lambda x: A - x
assert_raises(ValueError, sub_A, 3)
assert_raises(ValueError, sub_A, v)
assert_raises(ShapeError, sub_A, B)
mul_A = lambda x: A * x
assert_raises(ValueError, mul_A, u)
assert_raises(ShapeError, mul_A, A)
div_A = lambda x: A / x
assert_raises(ValueError, div_A, B)
assert_raises(ValueError, div_A, u)
assert_raises(ZeroDivisionError, div_A, 0)
pow_A = lambda x: A**x
pow_C = lambda x: C**x
assert_raises(ShapeError, pow_A, 2)
assert_raises(ValueError, pow_C, -2)
assert_raises(ValueError, pow_C, 2.1)