def test_gen_group_power_spectra(): n_spectra = 2 xs, ys = gen_group_power_spectra(n_spectra, *default_group_params()) assert np.all(xs) assert np.all(ys) assert ys.ndim == n_spectra
def test_fg_report(skip_if_no_mpl): """Check that running the top level model method runs.""" n_spectra = 2 xs, ys = gen_group_power_spectra(n_spectra, *default_group_params()) tfg = FOOOFGroup() tfg.report(xs, ys) assert tfg
def test_fit_fooof_group_3d(tfg): n_spectra = 2 xs, ys, _ = gen_group_power_spectra(n_spectra, *default_group_params()) ys = np.stack([ys, ys], axis=0) tfg = FOOOFGroup() fgs = fit_fooof_group_3d(tfg, xs, ys) assert len(fgs) == 2 for fg in fgs: assert fg
def test_fg_fit_par(): """Test FOOOFGroup fit, running in parallel.""" n_spectra = 2 xs, ys = gen_group_power_spectra(n_spectra, *default_group_params()) tfg = FOOOFGroup() tfg.fit(xs, ys, n_jobs=2) out = tfg.get_results() assert out assert len(out) == n_spectra assert isinstance(out[0], FOOOFResult) assert np.all(out[1].background_params)
def test_fg_fit(): """Test FOOOFGroup fit, no knee.""" n_spectra = 2 xs, ys, _ = gen_group_power_spectra(n_spectra, *default_group_params()) tfg = FOOOFGroup(verbose=False) tfg.fit(xs, ys) out = tfg.get_results() assert out assert len(out) == n_spectra assert isinstance(out[0], FOOOFResults) assert np.all(out[1].aperiodic_params)