""" =================== Drawing fancy boxes =================== The following examples show how to plot boxes with different visual properties. """ import matplotlib.pyplot as plt import matplotlib.transforms as mtransforms import matplotlib.patches as mpatch from matplotlib.patches import FancyBboxPatch ############################################################################### # First we'll show some sample boxes with fancybox. styles = mpatch.BoxStyle.get_styles() spacing = 1.2 figheight = (spacing * len(styles) + .5) fig = plt.figure(figsize=(4 / 1.5, figheight / 1.5)) fontsize = 0.3 * 72 for i, stylename in enumerate(sorted(styles)): fig.text(0.5, (spacing * (len(styles) - i) - 0.5) / figheight, stylename, ha="center", size=fontsize, bbox=dict(boxstyle=stylename, fc="w", ec="k")) ############################################################################### # Next we'll show off multiple fancy boxes at once. def add_fancy_patch_around(ax, bb, **kwargs): fancy = FancyBboxPatch((bb.xmin, bb.ymin), bb.width, bb.height, fc=(1, 0.8, 1, 0.5), ec=(1, 0.5, 1, 0.5), **kwargs) ax.add_patch(fancy) return fancy def draw_control_points_for_patches(ax): for patch in ax.patches: patch.axes.plot(*patch.get_path().vertices.T, ".", c=patch.get_edgecolor()) fig, axs = plt.subplots(2, 2, figsize=(8, 8)) # Bbox object around which the fancy box will be drawn. bb = mtransforms.Bbox([[0.3, 0.4], [0.7, 0.6]]) ax = axs[0, 0] # a fancy box with round corners. pad=0.1 fancy = add_fancy_patch_around(ax, bb, boxstyle="round,pad=0.1") ax.set(xlim=(0, 1), ylim=(0, 1), aspect=1, title='boxstyle="round,pad=0.1"') ax = axs[0, 1] # bbox=round has two optional arguments: pad and rounding_size. # They can be set during the initialization. fancy = add_fancy_patch_around(ax, bb, boxstyle="round,pad=0.1") # The boxstyle and its argument can be later modified with set_boxstyle(). # Note that the old attributes are simply forgotten even if the boxstyle name # is same. fancy.set_boxstyle("round,pad=0.1,rounding_size=0.2") # or: fancy.set_boxstyle("round", pad=0.1, rounding_size=0.2) ax.set(xlim=(0, 1), ylim=(0, 1), aspect=1, title='boxstyle="round,pad=0.1,rounding_size=0.2"') ax = axs[1, 0] # mutation_scale determines the overall scale of the mutation, i.e. both pad # and rounding_size is scaled according to this value. fancy = add_fancy_patch_around( ax, bb, boxstyle="round,pad=0.1", mutation_scale=2) ax.set(xlim=(0, 1), ylim=(0, 1), aspect=1, title='boxstyle="round,pad=0.1"\n mutation_scale=2') ax = axs[1, 1] # When the aspect ratio of the axes is not 1, the fancy box may not be what you # expected (green). fancy = add_fancy_patch_around(ax, bb, boxstyle="round,pad=0.2") fancy.set(facecolor="none", edgecolor="green") # You can compensate this by setting the mutation_aspect (pink). fancy = add_fancy_patch_around( ax, bb, boxstyle="round,pad=0.3", mutation_aspect=0.5) ax.set(xlim=(-.5, 1.5), ylim=(0, 1), aspect=2, title='boxstyle="round,pad=0.3"\nmutation_aspect=.5') for ax in axs.flat: draw_control_points_for_patches(ax) # Draw the original bbox (using boxstyle=square with pad=0). fancy = add_fancy_patch_around(ax, bb, boxstyle="square,pad=0") fancy.set(edgecolor="black", facecolor="none", zorder=10) fig.tight_layout() plt.show() ############################################################################# # # ------------ # # References # """""""""" # # The use of the following functions, methods, classes and modules is shown # in this example: import matplotlib matplotlib.patches matplotlib.patches.FancyBboxPatch matplotlib.patches.BoxStyle matplotlib.patches.BoxStyle.get_styles matplotlib.transforms.Bbox matplotlib.figure.Figure.text matplotlib.axes.Axes.text