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@kchawla-pi
Last active September 11, 2018 14:24
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Gist to replicate an error in param checks for nistats.second_level_model.SecondLevelModel.fit()
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
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