def test_SampleSizeBasedLikelihood_reml(testdata_ibma):
"""
Smoke test for SampleSizeBasedLikelihood with REML.
"""
meta = ibma.SampleSizeBasedLikelihood(method="reml")
res = meta.fit(testdata_ibma)
assert isinstance(meta.results, nimare.results.MetaResult)
assert isinstance(res, nimare.results.MetaResult)
def test_jackknife_with_custom_masker_smoke(testdata_ibma):
"""Ensure that Jackknife will work with NiftiLabelsMaskers.
CBMAs don't work with NiftiLabelsMaskers and VarianceBasedLikelihood takes ~1 minute,
which is too long for a single test, so I'm just using SampleSizeBasedLikelihood.
"""
atlas = op.join(get_test_data_path(), "test_pain_dataset", "atlas.nii.gz")
masker = NiftiLabelsMasker(atlas)
meta = ibma.SampleSizeBasedLikelihood(mask=masker)
res = meta.fit(testdata_ibma)
jackknife = Jackknife(target_image="z", voxel_thresh=0.5)
cluster_table, labeled_img = jackknife.transform(res)
assert cluster_table.shape[0] == len(meta.inputs_["id"]) + 1
# A Jackknife with a target_image that isn't present in the MetaResult raises a ValueError.
with pytest.raises(ValueError):
jackknife = Jackknife(target_image="doggy", voxel_thresh=0.5)
jackknife.transform(res)