Gist to replicate an error in param checks for nistats.second_level_model.SecondLevelModel.fit()

slice_problem.py

import nilearn
import os
import pandas
from nistats.second_level_model import SecondLevelModel

# 4D images paths
img1 = nilearn.image.load_img(os.path.expanduser('~/nilearn_data/adhd/data/0010128/0010128_rest_tshift_RPI_voreg_mni.nii.gz'))
img2 = nilearn.image.load_img(os.path.expanduser('~/nilearn_data/adhd/data/2497695/2497695_rest_tshift_RPI_voreg_mni.nii.gz'))

# Single 4D image

c = pandas.DataFrame([[1]] * img1.shape[3], columns=['intercept'])
second_level_model = SecondLevelModel(smoothing_fwhm=2.0)
second_level_model.fit(img1, design_matrix=c)

# Single element list with 4D image
c = pandas.DataFrame([[1]] * img1.shape[3], columns=['intercept'])
second_level_model = SecondLevelModel(smoothing_fwhm=2.0)
second_level_model.fit(img1, design_matrix=c)


# Multiple elements list with 4D image
imgs = [img1, img2]
c = pandas.DataFrame([[1]] * len(imgs), columns=['intercept'])
second_level_model = SecondLevelModel(smoothing_fwhm=2.0)
second_level_model.fit(imgs, design_matrix=c)  # This one is caught by the new behaviour I programmed in. List of multiple 4D niimgs fails with a ValueError