def _toggle_normalization(self, selected_ax):
if figure_type(self.canvas.figure) == FigureType.Image and len(self.canvas.figure.get_axes()) > 1:
axes = datafunctions.get_axes_from_figure(self.canvas.figure)
else:
axes = [selected_ax]
for ax in axes:
waterfall = isinstance(ax, MantidAxes) and ax.is_waterfall()
if waterfall:
x, y = ax.waterfall_x_offset, ax.waterfall_y_offset
has_fill = ax.waterfall_has_fill()
if has_fill:
line_colour_fill = datafunctions.waterfall_fill_is_line_colour(ax)
if line_colour_fill:
fill_colour = None
else:
fill_colour = datafunctions.get_waterfall_fills(ax)[0].get_facecolor()
ax.update_waterfall(0, 0)
# The colorbar can get screwed up with ragged workspaces and log scales as they go
# through the normalisation toggle.
# Set it to Linear and change it back after if necessary, since there's no reason
# to duplicate the handling.
colorbar_log = False
if ax.images:
colorbar_log = isinstance(ax.images[-1].norm, LogNorm)
if colorbar_log:
self._change_colorbar_axes(Normalize)
self._change_plot_normalization(ax)
if ax.lines: # Relim causes issues with colour plots, which have no lines.
ax.relim()
ax.autoscale()
if ax.images: # Colour bar limits are wrong if workspace is ragged. Set them manually.
colorbar_min = np.nanmin(ax.images[-1].get_array())
colorbar_max = np.nanmax(ax.images[-1].get_array())
for image in ax.images:
image.set_clim(colorbar_min, colorbar_max)
# Update the colorbar label
cb = image.colorbar
if cb:
datafunctions.add_colorbar_label(cb, ax.get_figure().axes)
if colorbar_log: # If it had a log scaled colorbar before, put it back.
self._change_colorbar_axes(LogNorm)
axesfunctions.update_colorplot_datalimits(ax, ax.images)
datafunctions.set_initial_dimensions(ax)
if waterfall:
ax.update_waterfall(x, y)
if has_fill:
ax.set_waterfall_fill(True, fill_colour)
self.canvas.draw()
def test_enabling_fill_with_line_colour_creates_fills_that_match_line_colour(
self):
self.presenter.view.enable_fill_group_box.isChecked.return_value = True
self.presenter.view.use_line_colour_radio_button.isChecked.return_value = True
self.presenter.set_fill_enabled()
self.assertTrue(datafunctions.waterfall_fill_is_line_colour(self.ax))
def _toggle_normalization(self, ax):
waterfall = isinstance(ax, MantidAxes) and ax.is_waterfall()
if waterfall:
x, y = ax.waterfall_x_offset, ax.waterfall_y_offset
has_fill = ax.waterfall_has_fill()
if has_fill:
line_colour_fill = datafunctions.waterfall_fill_is_line_colour(ax)
if line_colour_fill:
fill_colour = None
else:
fill_colour = datafunctions.get_waterfall_fills(ax)[0].get_facecolor()
ax.update_waterfall(0, 0)
is_normalized = self._is_normalized(ax)
for arg_set in ax.creation_args:
if arg_set['workspaces'] in ax.tracked_workspaces:
workspace = ads.retrieve(arg_set['workspaces'])
arg_set['distribution'] = is_normalized
arg_set_copy = copy(arg_set)
[
arg_set_copy.pop(key)
for key in ['function', 'workspaces', 'autoscale_on_update', 'norm']
if key in arg_set_copy.keys()
]
if 'specNum' not in arg_set:
if 'wkspIndex' in arg_set:
arg_set['specNum'] = workspace.getSpectrum(
arg_set.pop('wkspIndex')).getSpectrumNo()
else:
raise RuntimeError("No spectrum number associated with plot of "
"workspace '{}'".format(workspace.name()))
# 2D plots have no spec number so remove it
if figure_type(self.canvas.figure) == FigureType.Image:
arg_set_copy.pop('specNum')
for ws_artist in ax.tracked_workspaces[workspace.name()]:
if ws_artist.spec_num == arg_set.get('specNum'):
ws_artist.is_normalized = not is_normalized
ws_artist.replace_data(workspace, arg_set_copy)
if ax.lines: # Relim causes issues with colour plots, which have no lines.
ax.relim()
if ax.images: # Colour bar limits are wrong if workspace is ragged. Set them manually.
colorbar_min = np.nanmin(ax.images[-1].get_array())
colorbar_max = np.nanmax(ax.images[-1].get_array())
for image in ax.images:
image.set_clim(colorbar_min, colorbar_max)
ax.autoscale()
datafunctions.set_initial_dimensions(ax)
if waterfall:
ax.update_waterfall(x, y)
if has_fill:
ax.set_waterfall_fill(True, fill_colour)
self.canvas.draw()
def _replot_selected_curve(self, plot_kwargs):
"""Replot the selected curve with the given plot kwargs"""
ax = self.get_selected_ax()
curve = self.get_selected_curve()
waterfall = False
if isinstance(ax, MantidAxes):
waterfall = ax.is_waterfall()
check_line_colour = False
# If the plot is a waterfall plot and the user has set it so the area under each line is filled, and the fill
# colour for each line is set as the line colour, after the curve is updated we need to check if its colour has
# changed so the fill can be updated accordingly.
if waterfall and ax.waterfall_has_fill(
) and datafunctions.waterfall_fill_is_line_colour(ax):
check_line_colour = True
if isinstance(curve, Line2D):
curve_index = ax.get_lines().index(curve)
errorbar = False
else:
curve_index = ax.get_lines().index(curve[0])
errorbar = True
new_curve = FigureErrorsManager.replot_curve(ax, curve, plot_kwargs)
self.curve_names_dict[self.view.get_selected_curve_name()] = new_curve
if isinstance(ax, MantidAxes):
errorbar_cap_lines = datafunctions.remove_and_return_errorbar_cap_lines(
ax)
else:
errorbar_cap_lines = []
# When a curve is redrawn it is moved to the back of the list of curves so here it is moved back to its previous
# position. This is so that the correct offset is applied to the curve if the plot is a waterfall plot, but it
# also just makes sense for the curve order to remain unchanged.
ax.lines.insert(curve_index, ax.lines.pop())
if waterfall:
if check_line_colour:
# curve can be either a Line2D or an ErrorContainer and the colour is accessed differently for each.
if not errorbar:
# if the line colour hasn't changed then the fill colour doesn't need to be updated.
update_fill = curve.get_color() != new_curve[0].get_color()
else:
update_fill = curve[0].get_color(
) != new_curve[0].get_color()
datafunctions.convert_single_line_to_waterfall(
ax, curve_index, need_to_update_fill=update_fill)
else:
# the curve has been reset to its original position so for a waterfall plot it needs to be re-offset.
datafunctions.convert_single_line_to_waterfall(ax, curve_index)
datafunctions.set_waterfall_fill_visible(ax, curve_index)
ax.lines += errorbar_cap_lines
def init_view(self):
# This function sets the correct values in the menu when it is first opened.
if self.ax.waterfall_has_fill():
self.view.enable_fill_group_box.setChecked(True)
if datafunctions.waterfall_fill_is_line_colour(self.ax):
self.view.use_line_colour_radio_button.setChecked(True)
else:
self.view.use_solid_colour_radio_button.setChecked(True)
poly = next(poly_collection for poly_collection in self.ax.collections
if isinstance(poly_collection, PolyCollection))
self.view.colour_selector_widget.set_color(convert_color_to_hex(poly.get_facecolor().tolist()[0]))
def _replot_current_curve(self, plot_kwargs):
"""Replot the selected curve with the given plot kwargs"""
ax = self.get_selected_ax()
curve = self.get_current_curve()
waterfall = False
if isinstance(ax, MantidAxes):
waterfall = ax.is_waterfall()
check_line_colour = False
# If the plot is a waterfall plot and the user has set it so the area under each line is filled, and the fill
# colour for each line is set as the line colour, after the curve is updated we need to check if its colour has
# changed so the fill can be updated accordingly.
if waterfall and ax.waterfall_has_fill() and datafunctions.waterfall_fill_is_line_colour(ax):
check_line_colour = True
if isinstance(curve, Line2D):
curve_index = ax.get_lines().index(curve)
errorbar = False
else:
curve_index = ax.get_lines().index(curve[0])
errorbar = True
# When you remove the curve on a waterfall plot, the remaining curves are repositioned so that they are
# equally spaced apart. However since the curve is being replotted we don't want that to happen, so here
# the waterfall offsets are set to 0 so the plot appears to be non-waterfall. The offsets are then re-set
# after the curve is replotted.
if waterfall:
x_offset, y_offset = ax.waterfall_x_offset, ax.waterfall_y_offset
ax.waterfall_x_offset = ax.waterfall_y_offset = 0
new_curve = FigureErrorsManager.replot_curve(ax, curve, plot_kwargs)
self.curve_names_dict[self.view.get_current_curve_name()] = new_curve
if isinstance(ax, MantidAxes):
errorbar_cap_lines = datafunctions.remove_and_return_errorbar_cap_lines(ax)
else:
errorbar_cap_lines = []
# TODO: Accessing the ax.lines property is deprecated in mpl 3.5. It must be removed by mpl 3.7.
with warnings.catch_warnings():
warnings.simplefilter("ignore")
# When a curve is redrawn it is moved to the back of the list of curves so here it is moved back to its previous
# position. This is so that the correct offset is applied to the curve if the plot is a waterfall plot, but it
# also just makes sense for the curve order to remain unchanged.
ax.lines.insert(curve_index, ax.lines.pop())
if waterfall:
# Set the waterfall offsets to what they were previously.
ax.waterfall_x_offset, ax.waterfall_y_offset = x_offset, y_offset
if check_line_colour:
# curve can be either a Line2D or an ErrorContainer and the colour is accessed differently for each.
if not errorbar:
# if the line colour hasn't changed then the fill colour doesn't need to be updated.
update_fill = curve.get_color() != new_curve[0].get_color()
else:
update_fill = curve[0].get_color() != new_curve[0].get_color()
datafunctions.convert_single_line_to_waterfall(ax, curve_index, need_to_update_fill=update_fill)
else:
# the curve has been reset to its original position so for a waterfall plot it needs to be re-offset.
datafunctions.convert_single_line_to_waterfall(ax, curve_index)
datafunctions.set_waterfall_fill_visible(ax, curve_index)
for cap in errorbar_cap_lines:
ax.add_line(cap)