def test_eda_eventrelated():
eda = nk.eda_simulate(duration=15, scr_number=3)
eda_signals, info = nk.eda_process(eda, sampling_rate=1000)
epochs = nk.epochs_create(
eda_signals,
events=[5000, 10000, 15000],
sampling_rate=1000,
epochs_start=-0.1,
epochs_end=1.9,
)
eda_eventrelated = nk.eda_eventrelated(epochs)
no_activation = np.where(eda_eventrelated["EDA_SCR"] == 0)[0][0]
assert int(
pd.DataFrame(eda_eventrelated.values[no_activation]).isna().sum()) == 4
assert len(eda_eventrelated["Label"]) == 3
# Test warning on missing columns
with pytest.warns(nk.misc.NeuroKitWarning,
match=r".*does not have an `EDA_Phasic`.*"):
first_epoch_key = list(epochs.keys())[0]
first_epoch_copy = epochs[first_epoch_key].copy()
del first_epoch_copy["EDA_Phasic"]
nk.eda_eventrelated({**epochs, first_epoch_key: first_epoch_copy})
with pytest.warns(nk.misc.NeuroKitWarning,
match=r".*does not have an `SCR_Amplitude`.*"):
first_epoch_key = list(epochs.keys())[0]
first_epoch_copy = epochs[first_epoch_key].copy()
del first_epoch_copy["SCR_Amplitude"]
nk.eda_eventrelated({**epochs, first_epoch_key: first_epoch_copy})
with pytest.warns(nk.misc.NeuroKitWarning,
match=r".*does not have an `SCR_RecoveryTime`.*"):
first_epoch_key = list(epochs.keys())[0]
first_epoch_copy = epochs[first_epoch_key].copy()
del first_epoch_copy["SCR_RecoveryTime"]
nk.eda_eventrelated({**epochs, first_epoch_key: first_epoch_copy})
with pytest.warns(nk.misc.NeuroKitWarning,
match=r".*does not have an `SCR_RiseTime`.*"):
first_epoch_key = list(epochs.keys())[0]
first_epoch_copy = epochs[first_epoch_key].copy()
del first_epoch_copy["SCR_RiseTime"]
nk.eda_eventrelated({**epochs, first_epoch_key: first_epoch_copy})
def test_eda_eventrelated():
eda = nk.eda_simulate(duration=15, scr_number=3)
eda_signals, info = nk.eda_process(eda, sampling_rate=1000)
epochs = nk.epochs_create(eda_signals, events=[5000, 10000, 15000],
sampling_rate=1000,
epochs_start=-0.1, epochs_end=1.9)
eda_eventrelated = nk.eda_eventrelated(epochs)
no_activation = np.where(eda_eventrelated["EDA_SCR"] == 0)[0][0]
assert int(pd.DataFrame(eda_eventrelated.values
[no_activation]).isna().sum()) == 4
assert len(eda_eventrelated["Label"]) == 3
def test_eda_eventrelated():
eda = nk.eda_simulate(duration=15, scr_number=3)
eda_signals, info = nk.eda_process(eda, sampling_rate=1000)
epochs = nk.epochs_create(eda_signals,
events=[5000, 10000, 15000],
sampling_rate=1000,
epochs_start=-0.1,
epochs_end=1.9)
eda_eventrelated = nk.eda_eventrelated(epochs)
no_activation = np.where(eda_eventrelated["EDA_Activation"] == 0)[0][0]
assert int(
pd.DataFrame(eda_eventrelated.values[no_activation]).isna().sum()) == 4
assert len(eda_eventrelated["Label"]) == 3
assert len(eda_eventrelated.columns) == 6
assert all(elem in [
"EDA_Activation", "EDA_Peak_Amplitude", "EDA_Peak_Amplitude_Time",
"EDA_RiseTime", "EDA_RecoveryTime", "Label"
] for elem in np.array(eda_eventrelated.columns.values, dtype=str))