def test_plot_constrast_editor_setting_changed():
# Test that changing setting works
np.random.seed(1)
data = np.random.random(size=(100, 100)) * 1000
data += np.arange(100 * 100).reshape((100, 100))
s = signals.Signal2D(data)
s.plot()
ceditor = ImageContrastEditor(s._plot.signal_plot)
ceditor.span_selector.extents = (3E3, 5E3)
ceditor.update_span_selector_traits()
np.testing.assert_allclose(ceditor.ss_left_value, 3E3)
np.testing.assert_allclose(ceditor.ss_right_value, 5E3)
assert ceditor.auto
# Do a cycle to trigger traits changed
ceditor.auto = False
assert not ceditor.auto
ceditor.auto = True # reset and clear span selector
assert ceditor.auto
assert not ceditor.span_selector.visible
assert not ceditor._is_selector_visible
assert not ceditor.line.line.get_visible()
ceditor.span_selector.extents = (3E3, 5E3)
ceditor.span_selector.set_visible(True)
ceditor.update_line()
assert ceditor._is_selector_visible
assert ceditor.line.line.get_visible()
assert ceditor.bins == 24
assert ceditor.line.axis.shape == (ceditor.bins, )
ceditor.bins = 50
assert ceditor.bins == 50
assert ceditor.line.axis.shape == (ceditor.bins, )
# test other parameters
ceditor.linthresh = 0.1
assert ceditor.image.linthresh == 0.1
ceditor.linscale = 0.5
assert ceditor.image.linscale == 0.5
def test_close_vmin_vmax():
data = np.random.random(10 * 10 * 10).reshape([10] * 3)
s = hs.signals.Signal2D(data)
s.plot()
image_plot = s._plot.signal_plot
display_range = (0.6, 0.9)
ceditor = ImageContrastEditor(image_plot)
# Simulate selecting a range on the histogram
ceditor.span_selector.extents = display_range
plt.pause(0.001) # in case, interactive backend is used
ceditor._update_image_contrast()
# Need to use auto=False to pick up the current display when closing
ceditor.auto = False
ceditor.close()
assert (image_plot.vmin, image_plot.vmax) == display_range
def test_plot_constrast_editor_auto_indices_changed():
np.random.seed(1)
data = np.random.random(size=(10, 10, 100, 100)) * 1000
data += np.arange(10 * 10 * 100 * 100).reshape((10, 10, 100, 100))
s = signals.Signal2D(data)
s.plot()
ceditor = ImageContrastEditor(s._plot.signal_plot)
ceditor.span_selector.extents = (3E3, 5E3)
ceditor.update_span_selector_traits()
s.axes_manager.indices = (0, 1)
# auto is None by default, the span selector need to be removed:
assert not ceditor.span_selector.visible
assert not ceditor._is_selector_visible
ref_value = (100045.29840954322, 110988.10581608873)
np.testing.assert_allclose(ceditor._get_current_range(), ref_value)
# Change auto to False
ceditor.auto = False
s.axes_manager.indices = (0, 2)
# vmin, vmax shouldn't have changed
np.testing.assert_allclose(ceditor._get_current_range(), ref_value)
def test_close_vmin_vmax():
data = np.random.random(10*10*10).reshape([10]*3)
s = hs.signals.Signal2D(data)
s.plot()
image_plot = s._plot.signal_plot
display_range = (0.6, 0.9)
ceditor = ImageContrastEditor(image_plot)
# Simulate selecting a range on the histogram
ceditor.span_selector_switch(True)
ceditor.span_selector.set_initial = (0, 1)
ceditor.span_selector.range = display_range
plt.pause(0.001) # in case, interactive backend is used
ceditor.update_span_selector_traits()
# Need to use auto=False to pick up the current display when closing
ceditor.auto = False
ceditor.close()
assert image_plot.vmin == display_range[0]
assert image_plot.vmax == display_range[1]
def test_image_contrast_tool():
s = hs.signals.Signal2D(np.random.random(10000).reshape((100, 100)))
s.plot()
ceditor = ImageContrastEditor(s._plot.signal_plot)
ceditor.gui(**KWARGS)
vmin = 5
ceditor.vmin_percentile = vmin
assert ceditor.vmin_percentile == vmin
vmax = 95
ceditor.vmax_percentile = vmax
assert ceditor.vmax_percentile == vmax
auto = False
ceditor.auto = auto
assert ceditor.auto == auto
for norm in ['Linear', 'Power', 'Log', 'Symlog']:
ceditor.norm = norm
assert ceditor.norm == norm