def test_apply_properties_applies_to_all_images_if_multiple_colorfill_plots_and_one_colorbar(
self):
fig = pcolormesh([self.ws, self.ws])
props = {
'label': 'New Label',
'colormap': 'jet',
'vmin': 0,
'vmax': 2,
'scale': 'Linear',
'interpolation': 'None'
}
if LooseVersion(matplotlib.__version__) > LooseVersion("3.1.3"):
mock_view = Mock(
get_selected_image_name=lambda: 'ws: (0, 0) - child0',
get_properties=lambda: ImageProperties(props))
else:
mock_view = Mock(
get_selected_image_name=lambda: 'ws: (0, 0) - image0',
get_properties=lambda: ImageProperties(props))
presenter = self._generate_presenter(fig=fig, view=mock_view)
presenter.apply_properties()
for ax in range(2):
image = fig.axes[ax].images[0]
if image.colorbar:
self.assertEqual('New Label', image.colorbar.ax.get_ylabel())
self.assertEqual('jet', image.cmap.name)
self.assertEqual(0, image.norm.vmin)
self.assertEqual(2, image.norm.vmax)
self.assertTrue(isinstance(image.norm, Normalize))
def setUpClass(cls):
# Mock axes tab view
mock_axes_view = Mock(
get_selected_ax_name=lambda: '(0, 0)',
get_properties=lambda: AxProperties(new_ax_view_props))
cls.ax_view_patch = patch(AX_VIEW, lambda x: mock_axes_view)
cls.ax_view_mock = cls.ax_view_patch.start()
# Mock curves tab view
cls.curve_view_mock = Mock(
get_selected_curve_name=lambda: 'old label',
get_selected_ax_name=lambda: '(0, 0)',
get_properties=lambda: CurveProperties(new_curve_view_props))
cls.curve_view_patch = patch(CURVE_VIEW, lambda x: cls.curve_view_mock)
cls.curve_view_patch.start()
cls.ax = _run_apply_properties_on_figure_with_curve()
cls.new_curve = cls.ax.containers[0]
# Mock images tab view
cls.img_view_mock = Mock(
get_selected_image_name=lambda: '(0, 0) - old label',
get_properties=lambda: ImageProperties(new_image_props))
cls.img_view_patch = patch(IMAGE_VIEW, lambda x: cls.img_view_mock)
cls.img_view_patch.start()
cls.img_ax = _run_apply_properties_on_figure_with_image()
cls.new_img = cls.img_ax.images[0]
def setUpClass(cls):
# Mock axes tab view
mock_axes_view = Mock(
get_selected_ax_name=lambda: '(0, 0)',
get_properties=lambda: AxProperties(new_ax_view_props))
cls.ax_view_patch = patch(AX_VIEW, lambda x: mock_axes_view)
cls.ax_view_mock = cls.ax_view_patch.start()
# Mock curves tab view
cls.curve_view_mock = Mock(
get_selected_ax_name=lambda: '(0, 0)',
select_curve_list=Mock(selectedItems=lambda: []),
get_properties=lambda: CurveProperties(new_curve_view_props))
cls.curve_view_patch = patch(CURVE_VIEW, lambda x: cls.curve_view_mock)
cls.curve_view_patch.start()
cls.ax = _run_apply_properties_on_figure_with_curve(
cls.curve_view_mock)
cls.new_curve = cls.ax.containers[0]
# Mock images tab view
if LooseVersion(matplotlib.__version__) > LooseVersion("3.1.3"):
cls.img_view_mock = Mock(
get_selected_image_name=lambda: '(0, 0) - child0',
get_properties=lambda: ImageProperties(new_image_props))
else:
cls.img_view_mock = Mock(
get_selected_image_name=lambda: '(0, 0) - image0',
get_properties=lambda: ImageProperties(new_image_props))
cls.img_view_patch = patch(IMAGE_VIEW, lambda x: cls.img_view_mock)
cls.img_view_patch.start()
cls.img_ax = _run_apply_properties_on_figure_with_image()
cls.new_img = cls.img_ax.images[0]
# Mock legend tab view
cls.legend_view_mock = Mock(
get_properties=lambda: LegendProperties(new_legend_props))
cls.legend_view_patch = patch(LEGEND_VIEW,
lambda x: cls.legend_view_mock)
cls.legend_view_patch.start()
cls.legend_ax = _run_apply_properties_on_figure_with_legend(
cls.curve_view_mock)
cls.new_legend = cls.legend_ax.get_legend()
def test_apply_properties_applies_to_all_images_if_mixed_colorfill_plots_and_one_colorbar(
self):
# self.ws does not have common bins and has evenly spaced values on spectrum axis (gives Image)
# Also create ws with common bins, evenly spaced bin edges and uneven values on spectrum axis (gives QuadMesh)
ws = CreateWorkspace(DataX=list([0, 1, 2, 3, 4]) * 4,
DataY=range(20),
NSpec=4,
OutputWorkspace='test_ws',
VerticalAxisUnit='TOF',
VerticalAxisValues=[1, 2, 4, 10])
fig = pcolormesh([self.ws, ws])
self.assertTrue(
isinstance(fig.axes[0].images[0], matplotlib.image.AxesImage))
self.assertTrue(
isinstance(fig.axes[1].collections[0],
matplotlib.collections.QuadMesh))
props = {
'label': 'New Label',
'colormap': 'jet',
'vmin': 0,
'vmax': 2,
'scale': 'Linear',
'interpolation': 'None'
}
if LooseVersion(matplotlib.__version__) > LooseVersion("3.1.3"):
mock_view = Mock(
get_selected_image_name=lambda: 'ws: (0, 0) - child0',
get_properties=lambda: ImageProperties(props))
else:
mock_view = Mock(
get_selected_image_name=lambda: 'ws: (0, 0) - image0',
get_properties=lambda: ImageProperties(props))
presenter = self._generate_presenter(fig=fig, view=mock_view)
presenter.apply_properties()
images = datafunctions.get_images_from_figure(fig)
for image in images:
if image.colorbar:
self.assertEqual('New Label', image.colorbar.ax.get_ylabel())
self.assertEqual('jet', image.cmap.name)
self.assertEqual(0, image.norm.vmin)
self.assertEqual(2, image.norm.vmax)
self.assertTrue(isinstance(image.norm, Normalize))
def update_view(self):
# self.view.update(ImageProperties.from_image(self.get_selected_image()))
img_props = ImageProperties.from_image(self.get_selected_image())
self.view.set_label(img_props.label)
self.view.set_colormap(img_props.colormap)
self.view.set_min_value(img_props.vmin)
self.view.set_max_value(img_props.vmax)
if img_props.interpolation:
self.view.enable_interpolation(True)
self.view.set_interpolation(img_props.interpolation)
else:
self.view.set_interpolation('None')
self.view.enable_interpolation(False)
self.view.set_scale(img_props.scale)
def update_view(self):
img_props = ImageProperties.from_image(self.get_selected_image())
self.view.label_line_edit.setEnabled(bool(get_colorbars_from_fig(self.fig)))
self.view.set_label(img_props.label)
self.view.set_colormap(img_props.colormap)
self.view.set_reverse_colormap(img_props.reverse_colormap)
self.view.set_min_value(img_props.vmin)
self.view.set_max_value(img_props.vmax)
if img_props.interpolation:
self.view.enable_interpolation(True)
self.view.set_interpolation(img_props.interpolation)
else:
self.view.set_interpolation('None')
self.view.enable_interpolation(False)
self.view.set_scale(img_props.scale)
def test_apply_properties_log_scale_with_zero_vmin(self):
fig = figure()
ax = fig.add_subplot(111)
img = ax.imshow([[0, 2], [2, 0]], label='img label')
props = {'title': '(0, 0) - img label',
'label': 'New Label',
'colormap': 'jet',
'vmin': 0,
'vmax': 4,
'scale': 'Logarithmic',
'interpolation': 'Hanning'}
mock_view = Mock(get_selected_image_name=lambda: '(0, 0) - img label',
get_properties=lambda: ImageProperties(props))
presenter = self._generate_presenter(fig=fig, view=mock_view)
presenter.apply_properties()
self.assertEqual("New Label", img.get_label())
self.assertEqual('jet', img.cmap.name)
self.assertEqual(1e-6, img.norm.vmin)
self.assertEqual(4, img.norm.vmax)
self.assertTrue(isinstance(img.norm, LogNorm))
def test_apply_properties_sets_properties(self):
fig = figure()
ax = fig.add_subplot(111)
img = ax.imshow([[0, 2], [2, 0]], label='img label')
props = {'title': '(0, 0) - img label',
'label': 'New Label',
'colormap': 'jet',
'vmin': 0,
'vmax': 2,
'scale': 'Linear',
'interpolation': 'None'}
mock_view = Mock(get_selected_image_name=lambda: '(0, 0) - img label',
get_properties=lambda: ImageProperties(props))
presenter = self._generate_presenter(fig=fig, view=mock_view)
presenter.apply_properties()
self.assertEqual("New Label", img.get_label())
self.assertEqual('jet', img.cmap.name)
self.assertEqual(0, img.norm.vmin)
self.assertEqual(2, img.norm.vmax)
self.assertTrue(isinstance(img.norm, Normalize))
def get_properties(self):
return ImageProperties.from_view(self)
