def _test_toggle_normalization(self, errorbars_on, plot_kwargs):
fig = plot([self.ws],
spectrum_nums=[1],
errors=errorbars_on,
plot_kwargs=plot_kwargs)
mock_canvas = MagicMock(figure=fig)
fig_manager_mock = MagicMock(canvas=mock_canvas)
fig_interactor = FigureInteraction(fig_manager_mock)
# Earlier versions of matplotlib do not store the data assciated with a
# line with high precision and hence we need to set a lower tolerance
# when making comparisons of this data
if matplotlib.__version__ < "2":
decimal_tol = 1
else:
decimal_tol = 7
ax = fig.axes[0]
fig_interactor._toggle_normalization(ax)
assert_almost_equal(ax.lines[0].get_xdata(), [15, 25])
assert_almost_equal(ax.lines[0].get_ydata(), [0.2, 0.3],
decimal=decimal_tol)
self.assertEqual("Counts ($\\AA$)$^{-1}$", ax.get_ylabel())
fig_interactor._toggle_normalization(ax)
assert_almost_equal(ax.lines[0].get_xdata(), [15, 25])
assert_almost_equal(ax.lines[0].get_ydata(), [2, 3],
decimal=decimal_tol)
self.assertEqual("Counts", ax.get_ylabel())
def test_correct_yunit_label_when_overplotting_after_normaliztion_toggle(
self):
# The earlier version of Matplotlib on RHEL throws an error when performing the second
# plot in this test, if the lines have errorbars. The error occurred when it attempted
# to draw an interactive legend. Plotting without errors still fulfills the purpose of this
# test, so turn them off for old Matplotlib versions.
errors = True
if int(matplotlib.__version__[0]) < 2:
errors = False
fig = plot([self.ws],
spectrum_nums=[1],
errors=errors,
plot_kwargs={'distribution': True})
mock_canvas = MagicMock(figure=fig)
fig_manager_mock = MagicMock(canvas=mock_canvas)
fig_interactor = FigureInteraction(fig_manager_mock)
ax = fig.axes[0]
fig_interactor._toggle_normalization(ax)
self.assertEqual("Counts ($\AA$)$^{-1}$", ax.get_ylabel())
plot([self.ws1],
spectrum_nums=[1],
errors=errors,
overplot=True,
fig=fig)
self.assertEqual("Counts ($\AA$)$^{-1}$", ax.get_ylabel())
def test_log_maintained_when_normalisation_toggled(self):
ws = CreateWorkspace(DataX=[1, 2, 3, 4, 2, 4, 6, 8], DataY=[2] * 8, NSpec=2, OutputWorkspace="ragged_ws")
fig = pcolormesh_from_names([ws])
mock_canvas = MagicMock(figure=fig)
fig_manager_mock = MagicMock(canvas=mock_canvas)
fig_interactor = FigureInteraction(fig_manager_mock)
fig_interactor._change_colorbar_axes(LogNorm)
fig_interactor._toggle_normalization(fig.axes[0])
self.assertTrue(isinstance(fig.axes[0].images[-1].norm, LogNorm))
def test_scale_on_ragged_workspaces_maintained_when_toggling_normalisation(self):
ws = CreateWorkspace(DataX=[1, 2, 3, 4, 2, 4, 6, 8], DataY=[2] * 8, NSpec=2, OutputWorkspace="ragged_ws")
fig = pcolormesh_from_names([ws])
mock_canvas = MagicMock(figure=fig)
fig_manager_mock = MagicMock(canvas=mock_canvas)
fig_interactor = FigureInteraction(fig_manager_mock)
fig_interactor._toggle_normalization(fig.axes[0])
clim = fig.axes[0].images[0].get_clim()
fig_interactor._toggle_normalization(fig.axes[0])
self.assertEqual(clim, fig.axes[0].images[0].get_clim())
self.assertNotEqual((-0.1, 0.1), fig.axes[0].images[0].get_clim())
def test_toggle_normalisation_on_contour_plot_maintains_contour_line_colour(self):
from mantid.plots.legend import convert_color_to_hex
ws = CreateWorkspace(DataX=[1, 2, 3, 4, 2, 4, 6, 8], DataY=[2] * 8, NSpec=2, OutputWorkspace="test_ws")
fig = plot_contour([ws])
for col in fig.get_axes()[0].collections:
col.set_color("#ff9900")
mock_canvas = MagicMock(figure=fig)
fig_manager_mock = MagicMock(canvas=mock_canvas)
fig_interactor = FigureInteraction(fig_manager_mock)
fig_interactor._toggle_normalization(fig.axes[0])
self.assertTrue(all(convert_color_to_hex(col.get_color()[0]) == "#ff9900"
for col in fig.get_axes()[0].collections))
def test_toggle_normalisation_applies_to_all_images_if_one_colorbar(self):
fig = pcolormesh([self.ws, self.ws])
mock_canvas = MagicMock(figure=fig)
fig_manager_mock = MagicMock(canvas=mock_canvas)
fig_interactor = FigureInteraction(fig_manager_mock)
# there should be 3 axes, 2 colorplots and 1 colorbar
self.assertEqual(3, len(fig.axes))
fig.axes[0].tracked_workspaces.values()
self.assertTrue(fig.axes[0].tracked_workspaces['ws'][0].is_normalized)
self.assertTrue(fig.axes[1].tracked_workspaces['ws'][0].is_normalized)
fig_interactor._toggle_normalization(fig.axes[0])
self.assertFalse(fig.axes[0].tracked_workspaces['ws'][0].is_normalized)
self.assertFalse(fig.axes[1].tracked_workspaces['ws'][0].is_normalized)
def test_correct_yunit_label_when_overplotting_after_normaliztion_toggle(
self):
fig = plot([self.ws],
spectrum_nums=[1],
errors=True,
plot_kwargs={'distribution': True})
mock_canvas = MagicMock(figure=fig)
fig_manager_mock = MagicMock(canvas=mock_canvas)
fig_interactor = FigureInteraction(fig_manager_mock)
ax = fig.axes[0]
fig_interactor._toggle_normalization(ax)
self.assertEqual("Counts ($\AA$)$^{-1}$", ax.get_ylabel())
plot([self.ws1],
spectrum_nums=[1],
errors=True,
overplot=True,
fig=fig)
self.assertEqual("Counts ($\AA$)$^{-1}$", ax.get_ylabel())
