Rewrite draw_hyperedges()

[maximelucas]

• rewrites draw_hyperedges using matplotlib's Collections, related to Speed up draw_xgi_nodes and draw_xgi_hyperedges #174 (only slight speedup observed when looking at cleaned up enron). This makes the code shorter, cleaner, a bit faster, more in line with networkx, and allows us to have colorbars (easy colorbar plotting #437). It also makes it more consistent with our draw_nodes() after PR feat: return mappable to allow colorbar #441.
• addresses min/max_val not working in _scalar_arg_to_dict() #442 and Making _scalar_arg_to_dict consistent #410 for this function with a new simpler _parse_color_arg() function
• addresses default settings in draw() ignored if one of them is passed as argument #443 for this function
• new arguments dyad_style, dyad_vmin/max, edge_vmin/max, rescale_sizes.
• new tuto demonstrating all the arguments and their possible formats

Example customisation:

ax, (dyad_collection, edge_collection) = xgi.draw_hyperedges(
    H,
    pos=pos,
    dyad_color=[3, 1, 4],
    edge_fc=H.edges.size,
    dyad_color_cmap="viridis",
    edge_fc_cmap="tab10"
)

plt.colorbar(dyad_collection, label="dyads")
plt.colorbar(edge_collection, label="edges")

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Comparison is base (1b8df54) 91.90% compared to head (4e51373) 92.03%.

Additional details and impacted files

@@            Coverage Diff             @@
##             main     #456      +/-   ##
==========================================
+ Coverage   91.90%   92.03%   +0.12%     
==========================================
  Files          60       60              
  Lines        4375     4392      +17     
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+ Hits         4021     4042      +21     
+ Misses        354      350       -4     

Files	Coverage Δ
xgi/drawing/draw.py	76.32% <98.11%> (+1.99%)	⬆️
xgi/drawing/draw_utils.py	88.61% <83.33%> (-1.91%)	⬇️

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[maximelucas]

Two items required choices:

1. the rewriting of the function made it had to "rescale" the cmap like we used to do to avoid extreme values to be mapped to very light colors. For example, the default cmap was Blues, and the lowest orders would be shown as very very light blue (hardly visible). I chose to have a default cmap that does not start with white ("crest" from Seaborn).
2. the new use of PatchCollection prevents us to use different zorder for different edges (of different sizes) like we used to do. The trick is that it plots the patches in the order that they are given. I reordered the edges so that larger edges are plotted first (below).
3. Related to 1, I'm unsure if we want to keep showing different orders with different colors by default. It looks nice for small hypergraphs, but for larger ones I feel it make things more confused.

I reran the tutorial notebooks so you can go check the new look there.

If we are happy with this implementation, I will update xgi.draw_simplices() to be consistent (this will fix the tutorial notebooks) and add more tests.

[nwlandry]

Great work, @maximelucas, and thanks for implementing such an awesome update to the drawing functionality! I've had a look and I think it is time to merge this. Before you do, though, can you correct the tutorial errors and change the draw_simplices function?

[maximelucas]

I think this is ready now. I updated draw() and draw_simplices() so that they are consistent with draw_hyperedges().

The functions _color_arg_to_dict() and _scalar_arg_to_dict() are not used in the new versions, but are still used in draw_dihypergraph(), draw_multilayer(), and draw_hypergraph_hull(). These functions might need to be updated for consistency. Also the way they handle the kwargs. I think this PR is already big enough so I would l create new issues and leaves this other PRs.

The only thing left: decide if we keep the current default cmap (crest_r) for edges or not.
I managed to create another cmap candidate which is a sequential blue going from not too light to not too dark:

Here are 3 examples of different sizes with different densities and edges sizes with this cmap:

Note how the original cmap is more saturated that what is shown there: that's because we use a default alpha=0.4 when plotting. In any case, I think this cmap might look better for the larger examples, but it looks a bit too light/transparent in the smaller example.

Let me know what you think on the cmap.

[nwlandry]

Looks great, @maximelucas!! Thanks for your hard work on this!