def test_size(self):
size = 17
peak_array = np.zeros(shape=(3, 2, 3, 2))
s = Diffraction2D(np.zeros(shape=(3, 2, 10, 10)))
mt.add_peak_array_to_signal_as_markers(s, peak_array, size=size)
marker = list(s.metadata.Markers)[0][1]
assert marker.get_data_position("size") == size
def test_color(self):
color = "blue"
peak_array = np.zeros(shape=(3, 2, 3, 2))
s = Diffraction2D(np.zeros(shape=(3, 2, 10, 10)))
mt.add_peak_array_to_signal_as_markers(s, peak_array, color=color)
marker = list(s.metadata.Markers)[0][1]
assert marker.marker_properties["color"] == color
def _add_peak_dicts_to_signal(
signal,
peak_dicts,
color_centre="red",
color_rest="blue",
color_none="cyan",
size=20,
):
"""Visualize the results of peak_dicts through markers in a Signal.
Parameters
----------
signal : HyperSpy Signal2D, PixelatedSTEM
peak_dicts : dicts
color_centre, color_rest, color_none : string, optional
Color of the markers. Default 'red', 'blue', 'cyan'.
size : scalar, optional
Size of the markers. Default 20
Example
-------
>>> peak_dicts = {}
>>> peak_dicts['centre'] = np.random.randint(99, size=(2, 3, 10, 2))
>>> peak_dicts['rest'] = np.random.randint(99, size=(2, 3, 3, 2))
>>> peak_dicts['none'] = np.random.randint(99, size=(2, 3, 2, 2))
>>> s = pxm.signals.Diffraction2D(np.random.random((2, 3, 100, 100)))
>>> import pyxem.utils.cluster_tools as ct
>>> ct._add_peak_dicts_to_signal(s, peak_dicts)
>>> s.plot()
"""
mt.add_peak_array_to_signal_as_markers(signal,
peak_dicts["centre"],
color=color_centre,
size=size)
mt.add_peak_array_to_signal_as_markers(signal,
peak_dicts["rest"],
color=color_rest,
size=size)
mt.add_peak_array_to_signal_as_markers(signal,
peak_dicts["none"],
color=color_none,
size=size)
def test_simple(self):
peak_array = np.zeros(shape=(3, 2, 3, 2))
s = Diffraction2D(np.zeros(shape=(3, 2, 10, 10)))
mt.add_peak_array_to_signal_as_markers(s, peak_array)
assert len(s.metadata.Markers) == 3
