def test_plot_contrast_editor_norm(norm):
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(norm=norm)
ceditor = ImageContrastEditor(s._plot.signal_plot)
if norm == "log":
# test log with negative numbers
s2 = s - 5E3
s2.plot(norm=norm)
_ = ImageContrastEditor(s._plot.signal_plot)
assert ceditor.norm == norm.capitalize()
def test_plot_contrast_editor(gamma, saturated_pixels):
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(gamma=gamma, saturated_pixels=saturated_pixels)
ceditor = ImageContrastEditor(s._plot.signal_plot)
assert ceditor.gamma == gamma
assert ceditor.saturated_pixels == saturated_pixels
return plt.gcf()
def test_plot_contrast_editor_complex():
s = datasets.example_signals.object_hologram()
fft = s.fft(True)
fft.plot(True, vmin=None, vmax=None)
ceditor = ImageContrastEditor(fft._plot.signal_plot)
assert ceditor.bins == 250
np.testing.assert_allclose(ceditor._vmin, fft._plot.signal_plot._vmin)
np.testing.assert_allclose(ceditor._vmax, fft._plot.signal_plot._vmax)
np.testing.assert_allclose(ceditor._vmin, 1.495977361e+3)
np.testing.assert_allclose(ceditor._vmax, 3.568838458887e+17)
def test_plot_contrast_editor(gamma, percentile):
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(gamma=gamma, vmin=percentile[0], vmax=percentile[1])
ceditor = ImageContrastEditor(s._plot.signal_plot)
assert ceditor.gamma == gamma
assert ceditor.vmin_percentile == float(percentile[0].split("th")[0])
assert ceditor.vmax_percentile == float(percentile[1].split("th")[0])
return plt.gcf()
def test_change_navigation_coordinate(self):
s = self.s
s.plot(vmin='10th', vmax='99th')
ceditor = ImageContrastEditor(s._plot.signal_plot)
np.testing.assert_allclose(ceditor._vmin, 9.9)
np.testing.assert_allclose(ceditor._vmax, 98.01)
s.axes_manager.indices = (1, 1)
np.testing.assert_allclose(ceditor._vmin, 409.9)
np.testing.assert_allclose(ceditor._vmax, 498.01)
def test_reset_span_selector(self):
s = self.s
s.plot(vmin='10th', vmax='99th')
ceditor = ImageContrastEditor(s._plot.signal_plot)
ceditor.span_selector.set_initial((20, 90))
try:
ceditor.update_span_selector()
ax_image = s._plot.signal_plot.ax.images[0]
np.testing.assert_allclose(ax_image.norm.vmin, 20)
np.testing.assert_allclose(ax_image.norm.vmax, 90)
ceditor._reset_span_selector()
np.testing.assert_allclose(ax_image.norm.vmin, 9.9)
np.testing.assert_allclose(ax_image.norm.vmax, 98.01)
except TypeError as e:
# Failure sometimes seen with pytest-xdist (parallel tests)
# Message: `TypeError: restore_region() argument 1 must be matplotlib.backends._backend_agg.BufferRegion, not None`
# See e.g. https://github.com/hyperspy/hyperspy/issues/1688
# for a similar issue. Currently unclear what solution is.
pytest.skip(f"Skipping reset_span_selector test due to {e}")
def test_change_navigation_coordinate(self):
s = self.s
s.plot(vmin='10th', vmax='99th')
ceditor = ImageContrastEditor(s._plot.signal_plot)
np.testing.assert_allclose(ceditor._vmin, 9.9)
np.testing.assert_allclose(ceditor._vmax, 98.01)
try:
# Convenience to be able to run test on systems using backends
# supporting blit
s.axes_manager.indices = (1, 1)
except TypeError:
pass
np.testing.assert_allclose(ceditor._vmin, 409.9)
np.testing.assert_allclose(ceditor._vmax, 498.01)
def test_vmin_vmax_changed(self):
s = self.s
s.plot(vmin='0th', vmax='100th')
ceditor = ImageContrastEditor(s._plot.signal_plot)
np.testing.assert_allclose(ceditor._vmin, 0.0)
np.testing.assert_allclose(ceditor._vmax, 99.0)
ceditor._vmin_percentile_changed(0, 10)
ceditor._vmax_percentile_changed(100, 99)
np.testing.assert_allclose(ceditor._vmin, 9.9)
np.testing.assert_allclose(ceditor._vmax, 98.01)
def test_reset_span_selector(self):
s = self.s
s.plot(vmin='10th', vmax='99th')
ceditor = ImageContrastEditor(s._plot.signal_plot)
ceditor.span_selector.extents = (20, 90)
ceditor._update_image_contrast()
ax_image = s._plot.signal_plot.ax.images[0]
np.testing.assert_allclose(ax_image.norm.vmin, 20)
np.testing.assert_allclose(ax_image.norm.vmax, 90)
ceditor._clear_span_selector()
assert not ceditor.span_selector.visible
np.testing.assert_allclose(ax_image.norm.vmin, 20)
np.testing.assert_allclose(ax_image.norm.vmax, 90)
ceditor._update_image_contrast()
np.testing.assert_allclose(ax_image.norm.vmin, 9.9)
np.testing.assert_allclose(ax_image.norm.vmax, 98.01)
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_plot_constrast_editor_reset():
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_image_contrast()
vmin, vmax = 2.1143748173448866, 10988.568946171192
np.testing.assert_allclose(ceditor._vmin, vmin)
np.testing.assert_allclose(ceditor._vmax, vmax)
np.testing.assert_allclose(ceditor._get_current_range(), (3E3, 5E3))
ceditor.reset()
assert not ceditor.span_selector.visible
assert not ceditor._is_selector_visible
np.testing.assert_allclose(ceditor._get_current_range(), (vmin, vmax))
np.testing.assert_allclose(ceditor.image._vmin, vmin)
np.testing.assert_allclose(ceditor.image._vmax, vmax)
def test_reset_vmin_vmax(self):
s = self.s
s.plot(vmin='10th', vmax='99th')
ceditor = ImageContrastEditor(s._plot.signal_plot)
np.testing.assert_allclose(ceditor._vmin, 9.9)
np.testing.assert_allclose(ceditor._vmax, 98.01)
ceditor._vmin = 20
ceditor._vmax = 90
ceditor._reset_original_settings()
np.testing.assert_allclose(ceditor._vmin, 9.9)
np.testing.assert_allclose(ceditor._vmax, 98.01)
def test_reset_span_selector(self):
s = self.s
s.plot(vmin='10th', vmax='99th')
ceditor = ImageContrastEditor(s._plot.signal_plot)
ceditor.span_selector.set_initial((20, 90))
ceditor.update_span_selector()
ax_image = s._plot.signal_plot.ax.images[0]
assert_allclose(ax_image.norm.vmin, 20)
assert_allclose(ax_image.norm.vmax, 90)
ceditor._reset_span_selector()
assert_allclose(ax_image.norm.vmin, 9.9)
assert_allclose(ax_image.norm.vmax, 98.01)
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
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_apply():
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_image_contrast()
image_vmin_vmax = ceditor.image._vmin, ceditor.image._vmax
ceditor.apply()
assert not ceditor.span_selector.visible
assert not ceditor._is_selector_visible
np.testing.assert_allclose(
(ceditor.image._vmin, ceditor.image._vmax),
image_vmin_vmax,
)
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_vmin_vmax_changed(self):
s = self.s
s.plot(vmin='0th', vmax='100th')
ceditor = ImageContrastEditor(s._plot.signal_plot)
np.testing.assert_allclose(ceditor._vmin, 0.0)
np.testing.assert_allclose(ceditor._vmax, 99.0)
try:
# Convenience to be able to run test on systems using backends
# supporting blit
ceditor._vmin_percentile_changed(0, 10)
except TypeError:
pass
try:
# Convenience to be able to run test on systems using backends
# supporting blit
ceditor._vmax_percentile_changed(100, 99)
except TypeError:
pass
np.testing.assert_allclose(ceditor._vmin, 9.9)
np.testing.assert_allclose(ceditor._vmax, 98.01)
def gui_adjust_contrast(self, display=True, toolkit=None):
ceditor = ImageContrastEditor(self)
return ceditor.gui(display=display, toolkit=toolkit)
def gui_adjust_contrast(self, display=True, toolkit=None):
if self._is_rgb:
raise NotImplementedError(
"Constrast adjustment of RGB images is not implemented")
ceditor = ImageContrastEditor(self)
return ceditor.gui(display=display, toolkit=toolkit)
def test_constrast_editor(self):
# To get this test to work, matplotlib backend needs to set to 'Agg'
np.random.seed(1)
im = hs.signals.Signal2D(np.random.random((32, 32)))
im.plot()
ceditor = ImageContrastEditor(im._plot.signal_plot)
ceditor.ax.figure.canvas.draw_idle()
wd = ceditor.gui(**KWARGS)["ipywidgets"]["wdict"]
assert wd["linthresh"].layout.display == "none" # not visible
assert wd["linscale"].layout.display == "none" # not visible
assert wd["gamma"].layout.display == "none" # not visible
wd["bins"].value = 50
assert ceditor.bins == 50
wd["norm"].value = 'Log'
assert ceditor.norm == 'Log'
assert wd["linthresh"].layout.display == "none" # not visible
assert wd["linscale"].layout.display == "none" # not visible
wd["norm"].value = 'Symlog'
assert ceditor.norm == 'Symlog'
assert wd["linthresh"].layout.display == "" # visible
assert wd["linscale"].layout.display == "" # visible
assert wd["linthresh"].value == 0.01 # default value
assert wd["linscale"].value == 0.1 # default value
wd["linthresh"].value = 0.1
assert ceditor.linthresh == 0.1
wd["linscale"].value = 0.2
assert ceditor.linscale == 0.2
wd["norm"].value = 'Linear'
percentile = [1.0, 99.0]
wd["percentile"].value = percentile
assert ceditor.vmin_percentile == percentile[0]
assert ceditor.vmax_percentile == percentile[1]
assert im._plot.signal_plot.vmin == f'{percentile[0]}th'
assert im._plot.signal_plot.vmax == f'{percentile[1]}th'
wd["norm"].value = 'Power'
assert ceditor.norm == 'Power'
assert wd["gamma"].layout.display == "" # visible
assert wd["gamma"].value == 1.0 # default value
wd["gamma"].value = 0.1
assert ceditor.gamma == 0.1
assert wd["auto"].value is True # default value
wd["auto"].value = False
assert ceditor.auto is False
wd["left"].value = 0.2
assert ceditor.ss_left_value == 0.2
wd["right"].value = 0.5
assert ceditor.ss_right_value == 0.5
# Setting the span selector programmatically from the widgets will
# need to be implemented properly
wd["apply_button"]._click_handlers(wd["apply_button"]) # Trigger it
# assert im._plot.signal_plot.vmin == 0.2
# assert im._plot.signal_plot.vmax == 0.5
# Reset to default values
wd["reset_button"]._click_handlers(wd["reset_button"]) # Trigger it
assert im._plot.signal_plot.vmin == '0.0th'
assert im._plot.signal_plot.vmax == '100.0th'
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
