def test_convolve_regressors():
# tests for convolve_regressors helper function
conditions = ['c0', 'c1']
onsets = [20, 40]
paradigm = pd.DataFrame({'name': conditions, 'onset': onsets})
# names not passed -> default names
frame_times = np.arange(100)
f, names = _convolve_regressors(paradigm, 'canonical', frame_times)
assert_equal(names, ['c0', 'c1'])
def test_convolve_regressors():
# tests for convolve_regressors helper function
conditions = ["c0", "c1"]
onsets = [20, 40]
paradigm = pd.DataFrame({"name": conditions, "onset": onsets})
# names not passed -> default names
frame_times = np.arange(100)
f, names = _convolve_regressors(paradigm, "glover", frame_times)
assert_equal(names, ["c0", "c1"])
def test_convolve_regressors():
# tests for convolve_regressors helper function
conditions = ['c0', 'c1']
onsets = [20, 40]
paradigm = pd.DataFrame({'name': conditions,
'onset': onsets})
# names not passed -> default names
frame_times = np.arange(100)
f, names = _convolve_regressors(paradigm, 'canonical', frame_times)
assert_equal(names, ['c0', 'c1'])
def test_convolve_regressors():
# tests for convolve_regressors helper function
conditions = ['c0', 'c1']
onsets = [20, 40]
duration = [1, 1]
events = pd.DataFrame(
{'trial_type': conditions, 'onset': onsets, 'duration': duration})
# names not passed -> default names
frame_times = np.arange(100)
f, names = _convolve_regressors(events, 'glover', frame_times)
assert_equal(names, ['c0', 'c1'])
