brian2tools.plotting.morphology module

Module to plot Brian Morphology objects.

brian2tools.plotting.morphology.plot_dendrogram(morphology, axes=None, **kwds)[source]

Plot a “dendrogram” of a morphology, i.e. an abstract representation which visualizes the branching structure and the length of each section.

Parameters:

  • morphology (Morphology) – The morphology to visualize.

  • axes (Axes, optional) – The Axes instance used for plotting. Defaults to None which means that a new Axes will be created for the plot.

  • **kwds – Any additional keyword arguments are passed to matplotlib’s plot, vlines, and hlines calls. Only arguments accepted by all three functions should be used (e.g. color, alpha, linewidth).

Returns:

axes – The Axes instance that was used for plotting. This object allows to modify the plot further, e.g. by setting the plotted range, the axis labels, the plot title, etc.

Return type:

Axes

brian2tools.plotting.morphology.plot_morphology(morphology, plot_3d=None, show_compartments=False, show_diameter=False, colors=('darkblue', 'darkred'), values=None, value_norm=(None, None), value_colormap='hot', value_colorbar=True, value_unit=None, axes=None)[source]

Plot a given Morphology in 2D or 3D.

Parameters:

  • morphology (Morphology) – The morphology to plot

  • plot_3d (bool, optional) – Whether to plot the morphology in 3D or in 2D. If not set (the default) a morphology where all z values are 0 is plotted in 2D, otherwise it is plot in 3D.

  • show_compartments (bool, optional) – Whether to plot a dot at the center of each compartment. Defaults to False.

  • show_diameter (bool, optional) – Whether to plot the compartments with the diameter given in the morphology. Defaults to False.

  • colors (sequence of color specifications) – A list of colors that is cycled through for each new section. Can be any color specification that matplotlib understands (e.g. a string such as 'darkblue' or a tuple such as (0, 0.7, 0).

  • values (Quantity, optional) – Values to fill compartment patches with a color that corresponds to their given value.

  • value_norm (tuple or callable, optional) – Normalization function to scale the displayed values. Can be a tuple of a minimum and a maximum value (where either of them can be None to denote taking the minimum/maximum from the data) or a function that takes a value and returns the scaled value (e.g. as returned by matplotlib.colors.PowerNorm). For a tuple of values, will use matplotlib.colors.Normalize```(vmin, vmax, clip=True)`` with the given (vmin, vmax) values.

  • value_colormap (str or matplotlib.colors.Colormap, optional) – Desired colormap for plots. Either the name of a standard colormap or a matplotlib.colors.Colormap instance. Defaults to 'hot'. Note that this uses matplotlib color maps even for 3D plots with Mayavi.

  • value_colorbar (bool or dict, optional) – Whether to add a colorbar for the values. Defaults to True, but will be ignored if no values are provided. Can also be a dictionary with the keyword arguments for matplotlib’s colorbar method (2D plot), or for Mayavi’s scalarbar method (3D plot).

  • value_unit (Unit, optional) – A Unit to rescale the values for display in the colorbar. Does not have any visible effect if no colorbar is used. If not specified, will try to determine the “best unit” to itself.

  • axes (Axes or Scene, optional) – A matplotlib Axes (for 2D plots) or mayavi Scene ( for 3D plots) instance, where the plot will be added.

Returns:

axes – The Axes or Scene instance that was used for plotting. This object allows to modify the plot further, e.g. by setting the plotted range, the axis labels, the plot title, etc.

Return type:

Axes or Scene