def test_refine_position_gaussian(self):
signal = self.signal
vector = ipf.find_dumbbell_vector(signal, 4)
position_list = get_atom_positions(signal, separation=13)
atom_lattice = ipf.make_atom_lattice_dumbbell_structure(
signal, position_list, vector)
atom_lattice.refine_position_gaussian()
def test_find_number_of_columns(self):
test_data = MakeTestData(50, 50)
x, y = np.mgrid[5:48:5, 5:48:5]
x, y = x.flatten(), y.flatten()
test_data.add_atom_list(x, y)
peaks = afr.get_atom_positions(test_data.signal, separation=3)
assert len(peaks) == len(x)
def test_simple_running(self):
s = self.s
vector = find_dumbbell_vector(s, 4)
position_list = get_atom_positions(s, 14)
dumbbell_array0, dumbbell_array1 = _get_dumbbell_arrays(
s, position_list, vector)
assert len(dumbbell_array0) == 100
assert len(dumbbell_array1) == 100
def test_simple_running(self):
s = self.s
vector = find_dumbbell_vector(s, 4)
position_list = get_atom_positions(s, separation=13)
atom_lattice = make_atom_lattice_dumbbell_structure(
s, position_list, vector)
assert len(atom_lattice.sublattice_list) == 2
sublattice0 = atom_lattice.sublattice_list[0]
sublattice1 = atom_lattice.sublattice_list[1]
assert len(sublattice0.atom_list) == 100
assert len(sublattice1.atom_list) == 100
def get_polarised_single_sublattice_rotated(image_noise=False, rotation=45):
sublattice = get_polarised_single_sublattice(image_noise=image_noise)
sig = sublattice.signal
sig.map(scipy.ndimage.rotate, angle=rotation, reshape=False)
# sig.plot()
atom_positions = get_atom_positions(sig, separation=7)
rot_sublattice = Sublattice(atom_positions, image=sig.data)
rot_sublattice.find_nearest_neighbors()
rot_sublattice.refine_atom_positions_using_center_of_mass()
# rot_sublattice.plot()
return rot_sublattice
def setup_method(self):
test_data = tt.MakeTestData(520, 520)
x, y = np.mgrid[10:510:20j, 10:510:20j]
x, y = x.flatten(), y.flatten()
test_data.add_atom_list(x, y)
s = test_data.signal
atom_positions = afr.get_atom_positions(
signal=s,
separation=10,
threshold_rel=0.02,
)
sublattice = Sublattice(atom_position_list=atom_positions,
image=s.data)
sublattice.find_nearest_neighbors()
self.sublattice = sublattice
def setup_method(self):
s_adf_filename = os.path.join(my_path, "datasets",
"test_ADF_cropped.hdf5")
peak_separation = 0.15
s_adf = load(s_adf_filename)
s_adf.change_dtype('float64')
s_adf_modified = afr.subtract_average_background(s_adf)
self.s_adf_modified = afr.do_pca_on_signal(s_adf_modified)
self.pixel_size = s_adf.axes_manager[0].scale
self.pixel_separation = peak_separation / self.pixel_size
s_abf_filename = os.path.join(my_path, "datasets",
"test_ABF_cropped.hdf5")
s_abf = load(s_abf_filename)
s_abf.change_dtype('float64')
self.peaks = afr.get_atom_positions(self.s_adf_modified,
self.pixel_separation)
def test_manual_processing(self):
s_adf_filename = os.path.join(my_path, "datasets",
"test_ADF_cropped.hdf5")
s = load(s_adf_filename)
s.change_dtype('float32')
atom_positions = afr.get_atom_positions(
signal=s,
separation=17,
threshold_rel=0.02,
)
sublattice = Sublattice(atom_position_list=atom_positions,
image=s.data)
sublattice.find_nearest_neighbors()
sublattice.refine_atom_positions_using_center_of_mass(
sublattice.image, percent_to_nn=0.4)
sublattice.refine_atom_positions_using_2d_gaussian(sublattice.image,
percent_to_nn=0.4)
Atom_Lattice(image=s.data, sublattice_list=[sublattice])
sublattice.construct_zone_axes()
def find_dumbbell_vector(s, separation):
"""
Find the vector between the atoms in structure with dumbbells.
For example GaAs-(110).
Parameters
----------
s : HyperSpy 2D signal
separation : int
Pixel separation between the atoms in the dumbbells.
Returns
-------
dumbbell_vector : tuple
Examples
--------
>>> import temul.external.atomap_devel_012.api as am
>>> from temul.external.atomap_devel_012.initial_position_finding import find_dumbbell_vector
>>> s = am.dummy_data.get_dumbbell_signal()
>>> dumbbell_vector = find_dumbbell_vector(s, 4)
"""
position_list = get_atom_positions(s, separation=separation)
test = _get_n_nearest_neighbors(position_list, 10, leafsize=100)
fp = Fingerprinter()
fp.fit(test)
clusters = fp.cluster_centers_
clusters_dist = (clusters[:, 0]**2 + clusters[:, 1]**2)**0.5
sort_zip = zip(list(clusters_dist), clusters[:, 0], clusters[:, 1])
cluster_dist, cluster_x, cluster_y = zip(
*sorted(sort_zip, key=itemgetter(0)))
vec0 = cluster_x[0], cluster_y[0]
vec1 = cluster_x[1], cluster_y[1]
if (abs(vec0[0] + vec1[0]) > 0.1) or (abs(vec0[1] + vec1[1]) > 0.1):
raise ValueError(
"Dumbbell vectors should be antiparallel, but are %r and %r"
% (vec0, vec1))
return(vec0)
def make_atom_lattice_from_image(s_image0,
process_parameter=None,
pixel_separation=None,
s_image1=None,
debug_plot=False):
if s_image0.data.dtype == 'float16':
raise ValueError(
"s_image0 has the dtype float16, which is not supported. "
"Convert it to something else, for example using "
"s_image0.change_dtype('float64')")
image0_filename = _get_signal_name(s_image0)
name = image0_filename
s_image0 = s_image0.deepcopy()
s_image0_modified = run_image_filtering(s_image0)
if process_parameter is None:
process_parameter = pp.GenericStructure()
image0_scale = s_image0.axes_manager[0].scale
if pixel_separation is None:
if process_parameter.peak_separation is None:
raise ValueError("pixel_separation is not set.\
Either set it in the process_parameter.peak_separation\
or pixel_separation parameter")
else:
pixel_separation = process_parameter.peak_separation / image0_scale
initial_atom_position_list = get_atom_positions(
s_image0_modified, separation=pixel_separation)
if s_image1 is not None:
if s_image1.data.dtype == 'float16':
raise ValueError(
"s_image1 has the dtype float16, which is not supported. "
"Convert it to something else, for example using "
"s_image1.change_dtype('float64')")
s_image1 = s_image1.deepcopy()
s_image1.data = 1. / s_image1.data
image1_data = s_image1.data
#################################
image0_data = s_image0.data
image0_data_modified = s_image0_modified.data
atom_lattice = Atom_Lattice(name=name)
atom_lattice._original_filename = image0_filename
atom_lattice.image0 = image0_data
if s_image1 is not None:
atom_lattice.image1 = image1_data
atom_lattice._pixel_separation = pixel_separation
for sublattice_index in range(process_parameter.number_of_sublattices):
sublattice_para = process_parameter.get_sublattice_from_order(
sublattice_index)
if sublattice_para.image_type == 0:
s_image = s_image0
image_data = image0_data
image_data_modified = image0_data_modified
if sublattice_para.image_type == 1:
if s_image1 is not None:
s_image = s_image1
image_data = image1_data
image_data_modified = image1_data
else:
break
if sublattice_para.sublattice_order == 0:
sublattice = Sublattice(initial_atom_position_list,
image_data_modified)
else:
temp_sublattice = atom_lattice.get_sublattice(
sublattice_para.sublattice_position_sublattice)
temp_zone_vector_index = temp_sublattice.get_zone_vector_index(
sublattice_para.sublattice_position_zoneaxis)
zone_vector = temp_sublattice.zones_axis_average_distances[
temp_zone_vector_index]
atom_list = temp_sublattice.find_missing_atoms_from_zone_vector(
zone_vector)
sublattice = Sublattice(atom_list, image_data)
zone_axis_para_list = False
if hasattr(sublattice_para, 'zone_axis_list'):
zone_axis_para_list = sublattice_para.zone_axis_list
sublattice._plot_color = sublattice_para.color
sublattice.name = sublattice_para.name
sublattice.pixel_size = s_image.axes_manager[0].scale
sublattice._pixel_separation = pixel_separation
sublattice.original_image = image_data
atom_lattice.sublattice_list.append(sublattice)
if debug_plot:
sublattice.plot_atom_list_on_image_data(figname=sublattice.name +
"_initial_position.jpg")
for atom in sublattice.atom_list:
atom.sigma_x = sublattice._pixel_separation / 10.
atom.sigma_y = sublattice._pixel_separation / 10.
if not (sublattice_para.sublattice_order == 0):
construct_zone_axes_from_sublattice(
sublattice, zone_axis_para_list=zone_axis_para_list)
atom_subtract_config = sublattice_para.atom_subtract_config
image_data = sublattice.image
for atom_subtract_para in atom_subtract_config:
temp_sublattice = atom_lattice.get_sublattice(
atom_subtract_para['sublattice'])
neighbor_distance = atom_subtract_para['neighbor_distance']
image_data = remove_atoms_from_image_using_2d_gaussian(
image_data,
temp_sublattice,
percent_to_nn=neighbor_distance)
sublattice.image = image_data
sublattice.original_image = image_data
refinement_config = sublattice_para.refinement_config
refinement_neighbor_distance = refinement_config['neighbor_distance']
refinement_steps = refinement_config['config']
for refinement_step in refinement_steps:
if refinement_step[0] == 'image_data':
refinement_step[0] = sublattice.original_image
elif refinement_step[0] == 'image_data_modified':
refinement_step[0] = sublattice.image
else:
refinement_step[0] = sublattice.original_image
refine_sublattice(sublattice, refinement_steps,
refinement_neighbor_distance)
if sublattice_para.sublattice_order == 0:
sublattice.construct_zone_axes(
zone_axis_para_list=zone_axis_para_list)
return (atom_lattice)
def test_too_low_separation(self, separation):
s = dd.get_simple_cubic_signal()
with pytest.raises(ValueError):
afr.get_atom_positions(s, separation)