def conventional_xc(self, square_size, disc_radius, upsample_factor):
"""Refines the peaks using (phase) cross correlation.
Parameters
----------
square_size : int
Length (in pixels) of one side of a square the contains the peak to
be refined.
disc_radius: int
Radius (in pixels) of the discs that you seek to refine
upsample_factor: int
Factor by which to upsample the patterns
Returns
-------
vector_out: DiffractionVectors
DiffractionVectors containing the refined vectors in calibrated
units with the same navigation shape as the diffraction patterns.
"""
def _conventional_xc_map(
dp, vectors, sim_disc, upsample_factor, center, calibration
):
shifts = np.zeros_like(vectors, dtype=np.float64)
for i, vector in enumerate(vectors):
expt_disc = get_experimental_square(dp, vector, square_size)
shifts[i] = _conventional_xc(expt_disc, sim_disc, upsample_factor)
return ((vectors + shifts) - center) * calibration
sim_disc = get_simulated_disc(square_size, disc_radius)
self.vectors_out = self.dp.map(
_conventional_xc_map,
vectors=self.vector_pixels,
sim_disc=sim_disc,
upsample_factor=upsample_factor,
center=self.center,
calibration=self.calibration,
inplace=False,
)
self.vectors_out.set_signal_type("diffraction_vectors")
self.last_method = "conventional_xc"
return self.vectors_out
def conventional_xc(self, square_size, disc_radius, upsample_factor):
"""Refines the peaks using (phase) cross correlation.
Parameters
----------
square_size : int
Length (in pixels) of one side of a square the contains the peak to
be refined.
disc_radius: int
Radius (in pixels) of the discs that you seek to refine
upsample_factor: int
Factor by which to upsample the patterns
Returns
-------
vector_out: np.array()
array containing the refined vectors in calibrated units
"""
self.vectors_out = np.zeros(
(self.dp.data.shape[0],
self.dp.data.shape[1],
self.vectors_init.shape[0],
self.vectors_init.shape[1]))
sim_disc = get_simulated_disc(square_size, disc_radius)
for i in np.arange(0, len(self.vectors_init)):
vect = self.vectors_pixels[i]
expt_disc = self.dp.map(
get_experimental_square,
vector=vect,
square_size=square_size,
inplace=False)
shifts = expt_disc.map(
_conventional_xc,
sim_disc=sim_disc,
upsample_factor=upsample_factor,
inplace=False)
self.vectors_out[:, :, i, :] = (((vect + shifts.data) - self.center) * self.calibration)
self.last_method = "conventional_xc"
return self.vectors_out
def test_failure_for_non_even_entry_to_get_simulated_disc():
disc = get_simulated_disc(61, 5)
def test_failure_for_non_even_entry_to_get_simulated_disc():
with pytest.raises(ValueError,
match="'square_size' must be an even number"):
disc = get_simulated_disc(61, 5)
def test_non_even_errors_get_simulated_disc():
disc = get_simulated_disc(61, 5)
def sim_disc():
return get_simulated_disc(60, 5)
