def test_ALESubtraction_smoke_lowmem(testdata_cbma, tmp_path_factory):
"""Smoke test for ALESubtraction with low memory settings."""
tmpdir = tmp_path_factory.mktemp("test_ALESubtraction_smoke_lowmem")
out_file = os.path.join(tmpdir, "file.pkl.gz")
sub_meta = ale.ALESubtraction(n_iters=10, memory_limit="1gb")
sub_meta.fit(testdata_cbma, testdata_cbma)
assert isinstance(sub_meta.results, nimare.results.MetaResult)
assert "z_desc-group1MinusGroup2" in sub_meta.results.maps.keys()
assert isinstance(
sub_meta.results.get_map("z_desc-group1MinusGroup2", return_type="image"), nib.Nifti1Image
)
assert isinstance(
sub_meta.results.get_map("z_desc-group1MinusGroup2", return_type="array"), np.ndarray
)
sub_meta.save(out_file)
assert os.path.isfile(out_file)
def test_ALESubtraction_ma_map_reuse(testdata_cbma, tmp_path_factory, caplog):
"""Test that MA maps are re-used when appropriate."""
from nimare.meta import kernel
tmpdir = tmp_path_factory.mktemp("test_ALESubtraction_ma_map_reuse")
testdata_cbma.update_path(tmpdir)
# ALEKernel cannot extract sample_size from a Dataset,
# so we need to set it for this kernel and for the later meta-analyses.
kern = kernel.ALEKernel(sample_size=20)
dset = kern.transform(testdata_cbma, return_type="dataset")
# The Dataset without the images will generate them from scratch.
sub_meta = ale.ALESubtraction(n_iters=10, kernel__sample_size=20)
with caplog.at_level(logging.DEBUG, logger="nimare.meta.cbma.base"):
sub_meta.fit(testdata_cbma, testdata_cbma)
assert "Loading pre-generated MA maps" not in caplog.text
# The Dataset with the images will re-use them,
# as evidenced by the logger message.
with caplog.at_level(logging.DEBUG, logger="nimare.meta.cbma.base"):
sub_meta.fit(dset, dset)
assert "Loading pre-generated MA maps" in caplog.text
