def test_array_input(self):
sublattice = am.dummy_data.get_simple_cubic_sublattice()
x, y = sublattice.x_position, sublattice.y_position
i_points0, i_record0, p_record0 = integrate(sublattice.image, x, y)
signal = am.dummy_data.get_simple_cubic_signal()
i_points1, i_record1, p_record1 = integrate(signal, x, y)
assert (i_points0 == i_points1).all()
assert (i_record0.data == i_record1.data).all()
assert (p_record0 == p_record1).all()
def test_sum_2d_random_data(self):
s = hs.signals.Signal2D(np.random.rand(100, 110))
y, x = np.mgrid[5:96:10, 5:96:10]
x, y = x.flatten(), y.flatten()
result = integrate(s, x, y)
assert approx(np.sum(result[0])) == np.sum(s.data)
assert result[2].shape == s.data.shape
def test_3d_data_running(self):
s = dd.get_eels_spectrum_survey_image()
s_eels = dd.get_eels_spectrum_map()
peaks = am.get_atom_positions(s, separation=4)
i_points, i_record, p_record = integrate(
s_eels, peaks[:, 0], peaks[:, 1], max_radius=3)
assert p_record.shape == (100, 100)
assert s_eels.data.shape == i_record.data.shape
def test_two_atoms(self):
test_data = tt.MakeTestData(50, 100)
x, y, A = [25, 25], [25, 75], [5, 10]
test_data.add_atom_list(x=x, y=y, amplitude=A)
s = test_data.signal
i_points, i_record, p_record = integrate(s, x, y, max_radius=500)
assert approx(i_points) == A
assert i_record.axes_manager.signal_shape == (50, 100)
assert (i_record.isig[:, :51].data == i_points[0]).all()
assert (i_record.isig[:, 51:].data == i_points[1]).all()
assert (p_record[:51] == 0).all()
assert (p_record[51:] == 1).all()
def test_max_radius_1(self):
test_data = tt.MakeTestData(60, 100)
x, y, A = [30, 30], [25, 75], [5, 10]
test_data.add_atom_list(
x=x, y=y, amplitude=A, sigma_x=0.1, sigma_y=0.1)
s = test_data.signal
i_points, i_record, p_record = integrate(s, x, y, max_radius=1)
assert (i_points[1] / i_points[0]) == 2.
assert i_record.data[y[0], x[0]] == i_points[0]
assert i_record.data[y[1], x[1]] == i_points[1]
i_record.data[y[0], x[0]] = 0
i_record.data[y[1], x[1]] = 0
assert not i_record.data.any()
def test_four_atoms(self):
test_data = tt.MakeTestData(60, 100)
x, y, A = [20, 20, 40, 40], [25, 75, 25, 75], [5, 10, 15, 20]
test_data.add_atom_list(x=x, y=y, amplitude=A)
s = test_data.signal
i_points, i_record, p_record = integrate(s, x, y, max_radius=500)
assert approx(i_points) == A
assert (i_record.isig[:31, :51].data == i_points[0]).all()
assert (i_record.isig[:31, 51:].data == i_points[1]).all()
assert (i_record.isig[31:, :51].data == i_points[2]).all()
assert (i_record.isig[31:, 51:].data == i_points[3]).all()
assert (p_record[:51, :31] == 0).all()
assert (p_record[51:, :31] == 1).all()
assert (p_record[:51, 31:] == 2).all()
assert (p_record[51:, 31:] == 3).all()
def integrate_column_intensity(self,
method='Voronoi',
max_radius='Auto',
data_to_integrate=None,
show_progressbar=True):
"""Integrate signal around the atoms in the atom lattice.
See temul.external.atomap_devel_012.tools.integrate for more information about the parameters.
Parameters
----------
method : string
Voronoi or Watershed
max_radius : int, optional
data_to_integrate : NumPy array, HyperSpy signal or array-like
Works with 2D, 3D and 4D arrays, so for example an EEL spectrum
image can be used.
Returns
-------
i_points, i_record, p_record
Examples
--------
>>> import temul.external.atomap_devel_012.api as am
>>> al = am.dummy_data.get_simple_atom_lattice_two_sublattices()
>>> i_points, i_record, p_record = al.integrate_column_intensity()
See also
--------
tools.integrate
"""
if data_to_integrate is None:
data_to_integrate = self.image
i_points, i_record, p_record = at.integrate(data_to_integrate,
self.x_position,
self.y_position,
method=method,
max_radius=max_radius)
return (i_points, i_record, p_record)
def test_wrong_method(self):
s = hs.signals.Signal2D(np.zeros((10, 10)))
with pytest.raises(NotImplementedError):
integrate(s, [5, ], [5, ], method='bad_method')
def test_watershed_method_running(self):
test_data = tt.MakeTestData(60, 100)
x, y, A = [20, 20, 40, 40], [25, 75, 25, 75], [5, 10, 15, 20]
test_data.add_atom_list(x=x, y=y, amplitude=A)
s = test_data.signal
i_points, i_record, p_record = integrate(s, x, y, method='Watershed')
def test_too_few_dimensions(self):
s = hs.signals.Signal1D(np.random.rand(110))
y, x = np.mgrid[5:96:10, 5:96:10]
x, y = x.flatten(), y.flatten()
with pytest.raises(ValueError):
integrate(s, x, y)
def test_max_radius_bad_value(self):
s = hs.signals.Signal2D(np.zeros((10, 10)))
with pytest.raises(ValueError):
integrate(s, [5, ], [5, ], max_radius=-1)