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 pcolormesh(workspaces,
fig=None,
color_norm=None,
normalize_by_bin_width=None):
"""
Create a figure containing pcolor subplots
:param workspaces: A list of workspace handles
:param fig: An optional figure to contain the new plots. Its current contents will be cleared
:param normalize_by_bin_width: Optional and only to be used in the event that the function is being called as part
of a plot restore
:returns: The figure containing the plots
"""
# check inputs
_validate_pcolormesh_inputs(workspaces)
workspaces = [ws for ws in workspaces if isinstance(ws, MatrixWorkspace)]
# create a subplot of the appropriate number of dimensions
# extend in number of columns if the number of plottables is not a square number
workspaces_len = len(workspaces)
fig, axes, nrows, ncols = create_subplots(workspaces_len, fig=fig)
plots = []
row_idx, col_idx = 0, 0
for subplot_idx in range(nrows * ncols):
ax = axes[row_idx][col_idx]
if subplot_idx < workspaces_len:
ws = workspaces[subplot_idx]
pcm = pcolormesh_on_axis(ax, ws, color_norm,
normalize_by_bin_width)
plots.append(pcm)
if col_idx < ncols - 1:
col_idx += 1
else:
row_idx += 1
col_idx = 0
if ConfigService.getString("plots.ShowMinorTicks").lower() == "on":
ax.minorticks_on()
ax.show_minor_gridlines = ConfigService.getString(
"plots.ShowMinorGridlines").lower() == "on"
else:
# nothing here
ax.axis('off')
# If there are multiple plots limits are the min and max of all the plots
colorbar_min = min(pt.norm.vmin for pt in plots)
colorbar_max = max(pt.norm.vmax for pt in plots)
for pt in plots:
pt.set_clim(colorbar_min, colorbar_max)
# Adjust locations to ensure the plots don't overlap
fig.subplots_adjust(wspace=SUBPLOT_WSPACE, hspace=SUBPLOT_HSPACE)
axes = axes.ravel()
colorbar = fig.colorbar(pcm, ax=axes.tolist(), pad=0.06)
add_colorbar_label(colorbar, axes)
if fig.canvas.manager is not None:
fig.canvas.manager.set_window_title(
figure_title(workspaces, fig.number))
# assert a minimum size, otherwise we can lose axis labels
size = fig.get_size_inches()
if (size[0] <= COLORPLOT_MIN_WIDTH) or (size[1] <= COLORPLOT_MIN_HEIGHT):
fig.set_size_inches(COLORPLOT_MIN_WIDTH,
COLORPLOT_MIN_HEIGHT,
forward=True)
fig.canvas.draw()
fig.show()
return fig
