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)
