[FIX] Set edgecolors when plotting contours so that they are rendered

[ymzayek]

• Closes [BUG] Contours in plot_3d_map_to_surface_projection examples are not being rendered correctly #3954

[github-actions]

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[codecov]

Codecov Report

Merging #3973 (2e98fbb) into main (93c49f1) will decrease coverage by 0.10%.
Report is 4 commits behind head on main.
The diff coverage is 50.00%.

@@            Coverage Diff             @@
##             main    #3973      +/-   ##
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- Coverage   91.79%   91.69%   -0.10%     
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  Files         134      134              
  Lines       15772    15781       +9     
  Branches     3284     3289       +5     
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- Hits        14478    14471       -7     
- Misses        751      767      +16     
  Partials      543      543              

Flag	Coverage Δ
macos-latest_3.10	91.67% <50.00%> (-0.03%)	⬇️
macos-latest_3.11	91.67% <50.00%> (-0.03%)	⬇️
macos-latest_3.8	91.64% <50.00%> (-0.03%)	⬇️
macos-latest_3.9	91.64% <50.00%> (-0.03%)	⬇️
ubuntu-latest_3.10	91.67% <50.00%> (-0.03%)	⬇️
ubuntu-latest_3.11	91.67% <50.00%> (-0.03%)	⬇️
ubuntu-latest_3.8	?
ubuntu-latest_3.9	?
windows-latest_3.10	91.62% <50.00%> (-0.03%)	⬇️
windows-latest_3.11	91.62% <50.00%> (-0.03%)	⬇️
windows-latest_3.8	91.58% <50.00%> (-0.03%)	⬇️
windows-latest_3.9	91.58% <50.00%> (-0.03%)	⬇️

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Files Changed	Coverage Δ
nilearn/plotting/surf_plotting.py	94.30% <50.00%> (-1.19%)	⬇️

... and 7 files with indirect coverage changes

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[ymzayek]

With this PR, the contours should render correctly again.

Code to test:

from nilearn import datasets
from nilearn import surface
from nilearn import plotting
import numpy as np

motor_images = datasets.fetch_neurovault_motor_task()
stat_img = motor_images.images[0]

fsaverage = datasets.fetch_surf_fsaverage()
texture = surface.vol_to_surf(stat_img, fsaverage.pial_right)

destrieux_atlas = datasets.fetch_atlas_surf_destrieux()
parcellation = destrieux_atlas['map_right']

regions_dict = {b'G_postcentral': 'Postcentral gyrus',
                b'G_precentral': 'Precentral gyrus'}
regions_indices = [
    np.where(np.array(destrieux_atlas['labels']) == region)[0][0]
    for region in regions_dict
]
labels = list(regions_dict.values())

output_file = './plop.pdf'
fig = plotting.plot_surf_stat_map(
    fsaverage.infl_right, texture, hemi='right',
    threshold=1., bg_map=fsaverage.sulc_right,
#    output_file=output_file
)
plotting.show()

output_file = './plop2.pdf'
plotting.plot_surf_contours(
    fsaverage.infl_right, parcellation, labels=labels,
    levels=regions_indices, figure=fig,
    legend=True,
    colors=['g', 'k'],
#    output_file=output_file
)

Uncomment the output_file argument to check rendering in PDF

[ymzayek]

Contours are rendered again: https://output.circle-artifacts.com/output/job/2b6d2712-1278-44a8-bc36-25c8ad1b65a8/artifacts/0/dev/auto_examples/01_plotting/plot_3d_map_to_surface_projection.html#display-outlines-of-the-regions-of-interest-on-top-of-a-statistical-map

vs bug in dev docs: https://nilearn.github.io/dev/auto_examples/01_plotting/plot_3d_map_to_surface_projection.html#display-outlines-of-the-regions-of-interest-on-top-of-a-statistical-map

Side note:
Codecov patch failure is because we don't test mpl version < 3.3.3. In our minimum versions test, mpl 3.5.3 gets installed being the latest version that is compatible with the minimum versions of the other packages we specify. This is separate from this PR but shouldn't we rather also specify mpl version to be the oldest we support for the min test workflow?

[Remi-Gau]

I cannot reproduce with the code snippet you provided but I trust CI more than my own incompetence.

Good to go

[bthirion]

LGTM, thx.