plot#

GeometricalKikuchiPatternSimulation.plot(index: int | tuple | None = None, coordinates: str = 'detector', pattern: ndarray | None = None, lines: bool = True, zone_axes: bool = True, zone_axes_labels: bool = True, pc: bool = True, pattern_kwargs: dict | None = None, lines_kwargs: dict | None = None, zone_axes_kwargs: dict | None = None, zone_axes_labels_kwargs: dict | None = None, pc_kwargs: dict | None = None, return_figure: bool = False) → Figure[source]#

Plot a single simulation on the detector.

Parameters:

index: Index of the simulation to plot. If not given, this is the first simulation. If navigation_shape is 2D, and index is passed, it must be a 2-tuple.
coordinates: The coordinates of the plot axes, either "detector" (default) or "gnomonic".
pattern: A pattern to plot the simulation onto. If not given, the simulation is plotted on a gray background.
lines: Whether to show Kikuchi lines. Default is True.
zone_axes: Whether to show zone axes. Default is True.
zone_axes_labels: Whether to show zone axes labels. Default is True.
pc: Whether to show the projection/pattern centre (PC). Default is True.
pattern_kwargs: Keyword arguments passed to matplotlib.axes.Axes.imshow() if pattern is given.
lines_kwargs: Keyword arguments passed to matplotlib.collections.LineCollection to format Kikuchi lines if lines=True.
zone_axes_kwargs: Keyword arguments passed to matplotlib.collections.PathCollection to format zone axes if zone_axes=True.
zone_axes_labels_kwargs: Keyword arguments passed to matplotlib.text.Text to format zone axes labels if zone_axes_labels=True.
pc_kwargs: Keyword arguments passed to matplotlib.axes.Axes.scatter() to format the PC if pc=True.
return_figure: Whether to return the figure. Default is False.

Returns:

fig: Returned if return_figure=True.