def test_rsp_eventrelated():
rsp, info = nk.rsp_process(nk.rsp_simulate(duration=30, random_state=42))
epochs = nk.epochs_create(rsp,
events=[5000, 10000, 15000],
epochs_start=-0.1,
epochs_end=1.9)
rsp_eventrelated = nk.rsp_eventrelated(epochs)
# Test rate features
assert np.alltrue(
np.array(rsp_eventrelated["RSP_Rate_Min"]) < np.array(
rsp_eventrelated["RSP_Rate_Mean"]))
assert np.alltrue(
np.array(rsp_eventrelated["RSP_Rate_Mean"]) < np.array(
rsp_eventrelated["RSP_Rate_Max"]))
# Test amplitude features
assert np.alltrue(
np.array(rsp_eventrelated["RSP_Amplitude_Min"]) < np.array(
rsp_eventrelated["RSP_Amplitude_Mean"]))
assert np.alltrue(
np.array(rsp_eventrelated["RSP_Amplitude_Mean"]) < np.array(
rsp_eventrelated["RSP_Amplitude_Max"]))
assert len(rsp_eventrelated["Label"]) == 3
def test_rsp_eventrelated():
rsp, info = nk.rsp_process(nk.rsp_simulate(duration=20))
epochs = nk.epochs_create(rsp,
events=[5000, 10000, 15000],
epochs_start=-0.1,
epochs_end=1.9)
rsp_eventrelated = nk.rsp_eventrelated(epochs)
# Test rate features
assert np.alltrue(
np.array(rsp_eventrelated["RSP_Rate_Min"]) < np.array(
rsp_eventrelated["RSP_Rate_Mean"]))
assert np.alltrue(
np.array(rsp_eventrelated["RSP_Rate_Mean"]) < np.array(
rsp_eventrelated["RSP_Rate_Max"]))
# Test amplitude features
assert np.alltrue(
np.array(rsp_eventrelated["RSP_Amplitude_Min"]) < np.array(
rsp_eventrelated["RSP_Amplitude_Mean"]))
assert np.alltrue(
np.array(rsp_eventrelated["RSP_Amplitude_Mean"]) < np.array(
rsp_eventrelated["RSP_Amplitude_Max"]))
assert all(elem in [
"RSP_Rate_Max", "RSP_Rate_Min", "RSP_Rate_Mean", "RSP_Rate_Max_Time",
"RSP_Rate_Min_Time", "RSP_Amplitude_Max", "RSP_Amplitude_Min",
"RSP_Amplitude_Mean", "RSP_Phase", "RSP_PhaseCompletion", "Label"
] for elem in np.array(rsp_eventrelated.columns.values, dtype=str))
def test_rsp_eventrelated():
rsp, info = nk.rsp_process(nk.rsp_simulate(duration=30, random_state=42))
epochs = nk.epochs_create(rsp,
events=[5000, 10000, 15000],
epochs_start=-0.1,
epochs_end=1.9)
rsp_eventrelated = nk.rsp_eventrelated(epochs)
# Test rate features
assert np.alltrue(
np.array(rsp_eventrelated["RSP_Rate_Min"]) < np.array(
rsp_eventrelated["RSP_Rate_Mean"]))
assert np.alltrue(
np.array(rsp_eventrelated["RSP_Rate_Mean"]) < np.array(
rsp_eventrelated["RSP_Rate_Max"]))
# Test amplitude features
assert np.alltrue(
np.array(rsp_eventrelated["RSP_Amplitude_Min"]) < np.array(
rsp_eventrelated["RSP_Amplitude_Mean"]))
assert np.alltrue(
np.array(rsp_eventrelated["RSP_Amplitude_Mean"]) < np.array(
rsp_eventrelated["RSP_Amplitude_Max"]))
assert len(rsp_eventrelated["Label"]) == 3
# Test warning on missing columns
with pytest.warns(nk.misc.NeuroKitWarning,
match=r".*does not have an `RSP_Amplitude`.*"):
first_epoch_key = list(epochs.keys())[0]
first_epoch_copy = epochs[first_epoch_key].copy()
del first_epoch_copy["RSP_Amplitude"]
nk.rsp_eventrelated({**epochs, first_epoch_key: first_epoch_copy})
with pytest.warns(nk.misc.NeuroKitWarning,
match=r".*does not have an `RSP_Phase`.*"):
first_epoch_key = list(epochs.keys())[0]
first_epoch_copy = epochs[first_epoch_key].copy()
del first_epoch_copy["RSP_Phase"]
nk.rsp_eventrelated({**epochs, first_epoch_key: first_epoch_copy})
