Is there a PyPlot construct that allows one to configure a portable canvas that does not exist in PyPlot's global workspace? - matplotlib

Question

I will use the term canvas to mean some kind of renderable and complete sub-component/object so I don't confuse anyone by overloading PyPlot terminology.
I am looking for a canvas-like construct that I can pass around in collections and through pipelines and back to PyPlot for rendering. The motivation here is to create reusable functions for generic rendering tasks. The approaches I have tried so far always end up falling back on the PyPlot global space/object at some point before the plots are ready to be rendered.
E.g., I could create a plot as follows:
import matplotlib.pyplot as plt
x_axis = ['value_1', 'value_2', 'value_3', ...]
y_axis = ['value_1', 'value_2', 'value_3', ...]
plt.plot(x_axis, y_axis)
plt.title('title name')
plt.xlabel('x_axis name')
plt.ylabel('y_axis name')
plt.show()
but the "canvas" lives in PyPlot. For example, is there a way to build outside or export the canvas for future rendering? E.g. ()
import matplotlib.pyplot as plt
...
plt.plot(x_axis, y_axis)
...
canvas = plt.export()
... do things ...
plt.show(canvas)
More specifically, for example, I wrote the following code to render an array of images. Is there a way to generalize this code by replacing PlotProperties.image with a generic container that can hold an image, scatterplot, or similar graph.?
#dataclass
class PlotProperties:
image: np.array
caption: str
color_mode: ColorMode
def render_image_card(plots: List[PlotProperties], title: str, gallery_columns: int = 3, font_size: int = 10) -> None:
matplotlib.rcParams.update({'font.size': f'{font_size}'})
plt.figure(0, figsize=(5 + gallery_columns, 4)) # width / height
grid_size = (2, gallery_columns + 2) # height / width
ax = plt.subplot2grid(grid_size, (0, 0), rowspan=2, colspan=2)
poster = plots.pop(0)
colormapping = 'gray' if poster.color_mode == ColorMode.GRAYSCALE else 'viridis'
ax.imshow(poster.image, cmap=colormapping)
plt.title(poster.caption)
for index, plot in enumerate(plots):
x = index % gallery_columns
y = index // gallery_columns
ax_inner = plt.subplot2grid(grid_size, (0 + y, 2 + x))
colormapping = 'gray' if poster.color_mode == ColorMode.GRAYSCALE else 'viridis'
ax_inner.imshow(plot.image, cmap=colormapping)
plt.title(plot.caption)
forceAspect(ax, aspect=1)
plt.suptitle(title)
hide_tick_labels(plt.gcf())
I have tried using figures, but I always have a problem where I need to go back to plt to deal with specific formatting. What am I missing?