def test_z_rotation_90(self):
# +90 degree z-rotation
self.rotmat = euler(np.radians(90), 'z')
_powerfit.rotate_image3d(self.image, self.rotmat, self.center,
self.radius, self.out)
self.answer[0, :self.radius, 0] = 1
self.assertTrue(np.allclose(self.answer, self.out))
def test_z_rotation_m90(self):
# -90 degree z-rotation
self.rotmat = euler(np.radians(-90), "z")
_powerfit.rotate_image3d(self.image, self.rotmat, self.center, self.radius, self.out)
self.answer[0, -self.radius + 1 :, 0] = 1
self.answer[0, 0, 0] = 1
self.assertTrue(np.allclose(self.answer, self.out))
def test_euler(self):
# 90 z-rotation
angle = np.radians(90)
out = euler(angle, 'z')
answer = [[0, -1, 0], [1, 0, 0], [0, 0, 1]]
self.assertTrue(np.allclose(answer, out))
# 90 y-rotation
out = euler(angle, 'y')
answer = [[0, 0, 1], [0, 1, 0], [-1, 0, 0]]
self.assertTrue(np.allclose(answer, out))
# 90 x-rotation
out = euler(angle, 'x')
answer = [[1, 0, 0], [0, 0, -1], [0, 1, 0]]
self.assertTrue(np.allclose(answer, out))
def test_euler(self):
# 90 z-rotation
angle = np.radians(90)
out = euler(angle, 'z')
answer = [[0, -1, 0], [1, 0, 0], [0, 0, 1]]
self.assertTrue(np.allclose(answer, out))
# 90 y-rotation
out = euler(angle, 'y')
answer = [[0, 0, 1], [0, 1, 0], [-1, 0, 0]]
self.assertTrue(np.allclose(answer, out))
# 90 x-rotation
out = euler(angle, 'x')
answer = [[1, 0, 0], [0, 0, -1], [0, 1, 0]]
self.assertTrue(np.allclose(answer, out))
def test_near(self):
self.rotmat = euler(np.radians(85), 'z')
_powerfit.rotate_image3d(self.image,
self.rotmat,
self.center,
self.radius,
self.out,
nearest=True)
self.answer[0, :self.radius, 0] = 1
self.assertTrue(np.allclose(self.answer, self.out))
def test_rotate_grids(self):
# identity matrix
rotmat = np.identity(3, dtype=np.float64)
mask = np.ones(self.shape, dtype=np.float64)
template = np.zeros(self.shape, dtype=np.float64)
radius = 3
template[0, 0, 0:radius] = 1
self.corr._template = template
self.corr._mask = mask
self.corr._center = np.asarray([0, 0, 0], dtype=np.float64)
self.corr._rmax = radius
# get clean arrays
self.corr._allocate_arrays(self.shape)
self.corr._rotate_grids(rotmat)
self.assertTrue(np.allclose(self.corr._rot_template, template))
# 90 degree Z-rotation.
rotmat = euler(np.radians(90), 'z')
self.corr._allocate_arrays(self.shape)
self.corr._rotate_grids(rotmat)
answer = np.zeros(self.shape, dtype=np.float64)
answer[0, :radius, 0] = 1
self.assertTrue(np.allclose(self.corr._rot_template, answer))
def test_rotate_grids(self):
# identity matrix
rotmat = np.identity(3, dtype=np.float64)
mask = np.ones(self.shape, dtype=np.float64)
template = np.zeros(self.shape, dtype=np.float64)
radius = 3
template[0, 0, 0: radius] = 1
self.corr._template = template
self.corr._mask = mask
self.corr._center = np.asarray([0, 0, 0], dtype=np.float64)
self.corr._rmax = radius
# get clean arrays
self.corr._allocate_arrays(self.shape)
self.corr._rotate_grids(rotmat)
self.assertTrue(np.allclose(self.corr._rot_template, template))
# 90 degree Z-rotation.
rotmat = euler(np.radians(90), 'z')
self.corr._allocate_arrays(self.shape)
self.corr._rotate_grids(rotmat)
answer = np.zeros(self.shape, dtype=np.float64)
answer[0, :radius, 0] = 1
self.assertTrue(np.allclose(self.corr._rot_template, answer))
def test_near(self):
self.rotmat = euler(np.radians(85), "z")
_powerfit.rotate_image3d(self.image, self.rotmat, self.center, self.radius, self.out, nearest=True)
self.answer[0, : self.radius, 0] = 1
self.assertTrue(np.allclose(self.answer, self.out))