def test_compose(self):
s1 = Similarity(self.s, self.r, self.t)
s2 = Similarity(0.75, Rotation.from_rodrigues([-0.5, -0.5, 1.0]),
EigenArray.from_iterable([4, 6.5, 8]))
sim_comp = s1.compose(s2).as_matrix()
mat_comp = numpy.dot(s1.as_matrix(), s2.as_matrix())
print 'sim12 comp:\n', sim_comp
print 'mat comp:\n', mat_comp
print 'sim - mat:\n', sim_comp - mat_comp
nose.tools.assert_almost_equal(
numpy.linalg.norm(sim_comp - mat_comp, 2), 0., 14)
def test_compose_convert(self):
# Composing across types should work
s1 = Similarity(self.s, self.r, self.t)
s2 = Similarity(0.75, Rotation.from_rodrigues([-0.5, -0.5, 1.0]),
EigenArray.from_iterable([4, 6.5, 8]), ctypes.c_float)
sim_comp = s1.compose(s2).as_matrix()
mat_comp = numpy.dot(s1.as_matrix(), s2.as_matrix())
print('sim12 comp:\n', sim_comp)
print('mat comp:\n', mat_comp)
print('sim - mat:\n', sim_comp - mat_comp)
nose.tools.assert_almost_equal(
numpy.linalg.norm(sim_comp - mat_comp, 2), 0., 6)
def test_compose(self):
s1 = Similarity(self.s, self.r, self.t)
s2 = Similarity(0.75,
Rotation.from_rodrigues([-0.5, -0.5, 1.0]),
[4, 6.5, 8])
sim_comp = s1.compose(s2).as_matrix()
mat_comp = numpy.dot(s1.as_matrix(), s2.as_matrix())
print('sim12 comp:\n', sim_comp)
print('mat comp:\n', mat_comp)
print('sim - mat:\n', sim_comp - mat_comp)
nose.tools.assert_almost_equal(
numpy.linalg.norm(sim_comp - mat_comp, 2),
0., 12
)