failures to generate reports with several atlases

[Remi-Gau]

it turns out that we get failures to generate reports with several atlases.

• fetch_atlas_destrieux_2009
• fetch_atlas_aal
• fetch_atlas_basc_multiscale_2015
• fetch_atlas_yeo_2011

  File "/home/remi/github/nilearn/nilearn/../tmp.py", line 80, in main
    report = masker.generate_report()
             ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/remi/github/nilearn/nilearn/nilearn/maskers/nifti_labels_masker.py", line 350, in generate_report
    return generate_report(self)
           ^^^^^^^^^^^^^^^^^^^^^
  File "/home/remi/github/nilearn/nilearn/nilearn/reporting/html_report.py", line 236, in generate_report
    return _create_report(estimator, data)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/remi/github/nilearn/nilearn/nilearn/reporting/html_report.py", line 241, in _create_report
    overlay, image = _define_overlay(estimator)
                     ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/remi/github/nilearn/nilearn/nilearn/reporting/html_report.py", line 164, in _define_overlay
    displays = estimator._reporting()
               ^^^^^^^^^^^^^^^^^^^^^^
  File "/home/remi/github/nilearn/nilearn/nilearn/maskers/nifti_labels_masker.py", line 387, in _reporting
    self._check_mismatch_labels_regions(label_values, tolerant=False)
  File "/home/remi/github/nilearn/nilearn/nilearn/maskers/nifti_labels_masker.py", line 333, in _check_mismatch_labels_regions
    raise ValueError(msg)
ValueError: Mismatch between the number of provided labels (151) and the number of regions in provided label image (149).

Originally posted by @Remi-Gau in #4289 (comment)

[Remi-Gau]

Code to reproduce:

"""Test atlases masking."""

import numpy as np
from rich import print

from nilearn import datasets
from nilearn.datasets import (
    fetch_atlas_aal,
    fetch_atlas_basc_multiscale_2015,
    fetch_atlas_destrieux_2009,
    fetch_atlas_harvard_oxford,
    fetch_atlas_juelich,
    fetch_atlas_schaefer_2018,
    fetch_atlas_talairach,
    fetch_atlas_yeo_2011,
)
from nilearn.maskers import NiftiLabelsMasker

functions = {
    fetch_atlas_destrieux_2009: None,
    fetch_atlas_harvard_oxford: ["cort-maxprob-thr0-1mm"],
    fetch_atlas_juelich: ["maxprob-thr0-1mm"],
    fetch_atlas_talairach: ["gyrus"],
    fetch_atlas_aal: None,
    fetch_atlas_schaefer_2018: None,
    fetch_atlas_basc_multiscale_2015: [None, None, True, 1, 64, "sym"],
    fetch_atlas_yeo_2011: None,
}

failing_atlas = []


def main():
    """Test atlases masking."""
    dataset = datasets.fetch_development_fmri(n_subjects=1)
    func_filename = dataset.func[0]

    for f, args in functions.items():
        print(f)

        atlas = f(*args) if args else f()

        if "labels" in atlas:
            labels = atlas.labels
        elif "rsn_indices" in atlas:
            labels = atlas.rsn_indices
        elif f == fetch_atlas_basc_multiscale_2015:
            labels = range(64)
        elif f == fetch_atlas_yeo_2011:
            labels = range(17)

        if f == fetch_atlas_schaefer_2018:
            labels = np.insert(labels, 0, "Background")

        labels_img = atlas["thick_17"] if f == fetch_atlas_yeo_2011 else atlas.maps

        resampling_target = "data"
        # resampling_target="labels"

        masker = NiftiLabelsMasker(
            labels_img=labels_img,
            labels=labels,
            standardize="zscore_sample",
            resampling_target=resampling_target,
        )

        masker.fit_transform(func_filename)
        
        try:
            report = masker.generate_report()
            report.save_as_html("foo.html")
        except ValueError:
            print("\n[red]" + "Could not generate report".upper() + "\n")
            failing_atlas.append(f)

    print(failing_atlas)

if __name__ == "__main__":
    exit(main())

[Remi-Gau]

• Should be fixed by Standardize "nilearn" atlases #4329