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)