def resources(tmpdir_factory):
"""Set up."""
r = namedtuple("resources", "data_path")
r.features = rois[:3]
r.regression_features = [
"Age",
"summary_gm_median",
"spacing_x",
"summary_gm_p95",
"cnr",
"size_x",
"cjv",
"summary_wm_mean",
"icvs_gm",
"wm2max",
]
r.covariates = ["Gender", "scanner", "Age"]
r.eliminate_variance = ["scanner"]
r.original_data = fetch_sample()
exclude_vars = r.original_data.columns[
r.original_data.isna().sum() != 0].to_list()
r.original_data = r.original_data[[
var for var in r.original_data.columns if var not in exclude_vars
]]
r.original_data = r.original_data[~r.original_data[r.covariates].isna().
any(axis=1)]
r.original_data.Age = r.original_data.Age.astype(int)
scanners = r.original_data.scanner.unique()
train_bool = r.original_data.scanner.isin(scanners[1:])
test_bool = r.original_data.scanner.isin(scanners[:1])
r.X_train_split = r.original_data[train_bool]
r.X_train_split = exclude_single_subject_groups(r.X_train_split,
r.covariates)
r.X_test_split = r.original_data[test_bool]
r.n_scanners = len(r.original_data.scanner.unique())
return r
def test_fetch_sample():
data = collect_tools.fetch_sample()
assert isinstance(data, NDFrame)
def test_fetch_model():
"""Test a trained model can be retrained."""
neuroharmony = fetch_trained_model()
X = fetch_sample()
neuroharmony.transform(X)
assert isinstance(neuroharmony.coverage_, NDFrame)