def test_real_single_vector_vector_dot(self):
na = np.array(self.real_veca, dtype=np.float32)
nb = np.array(self.real_vecb, dtype=np.float32)
nc = np.dot(na, nb)
nd = cn.pdot(na, nb)
self.assert_(test.scalars_equal(nc, nd, epsilon=0.05))
def test_complex_single_vector_vector_dot(self):
va = cn.array(self.complex_veca, dtype=cn.complex64)
vb = cn.array(self.complex_vecb, dtype=cn.complex64)
vc = va.dot(vb)
# check we get the same answer as numpy
na = np.array(self.complex_veca, dtype=np.complex64)
nb = np.array(self.complex_vecb, dtype=np.complex64)
nc = np.dot(na, nb)
self.assert_(test.scalars_equal(vc, nc, epsilon=0.05))
def test_real_double_vector_vector_dot(self):
va = cn.array(self.real_veca, dtype=cn.float64)
vb = cn.array(self.real_vecb, dtype=cn.float64)
vc = va.dot(vb)
# check we get the same answer as numpy
na = np.array(self.real_veca, dtype=np.float64)
nb = np.array(self.real_vecb, dtype=np.float64)
nc = np.dot(na,nb)
self.assert_(test.scalars_equal(vc, nc, epsilon=0.0001))
def test_real_single_matrix_product(self):
A_ = cn.array(self.real_mata, dtype=cn.float32)
A = np.array(self.real_mata, dtype=np.float32)
# gpu
s = A_.product()
# cpu
sn = np.product(A)
# XXX this precision doesn't always return true
self.assert_(test.scalars_equal(sn, s, 1E-04))
def test_norm_complex_matrix(self):
A = cn.array(self.complex_mata, dtype=cn.complex64)
# numpy
a = np.array(self.complex_mata, dtype=np.complex64)
self.assert_(test.scalars_equal(lalg.norm(a), A.norm()))
def test_norm_real_matrix(self):
A = cn.array(self.real_mata, dtype=cn.float32)
# numpy
a = np.array(self.real_mata, dtype=np.float32)
self.assert_(test.scalars_equal(lalg.norm(a), A.norm()))
def test_asum_complex_matrix(self):
A = cn.array(self.complex_mata, dtype=cn.complex64)
# numpy
a = np.array(self.complex_mata, dtype=np.complex64)
self.assert_(test.scalars_equal(np.sum(np.abs(a)), A.asum()))
def test_asum_real_matrix(self):
A = cn.array(self.real_mata, dtype=cn.float32)
# numpy
a = np.array(self.real_mata, dtype=np.float32)
self.assert_(test.scalars_equal(np.sum(np.abs(a)), A.asum()))
