def test_refines_multiple_peaks_bad_annotations_numpy_arrays(self):
time = np.linspace(0, 4 * np.pi, 200)
signal = np.sin(time)
res = signals.refine_signal_peaks(
time, signal, [np.array([[25]]), 50,
np.array([75]), 125, 150])
exp = [
{
'peak_value': 1.0,
'peak_index': 25,
'peak_start_index': 0,
'peak_end_index': 68,
'total_wave_time': 4.29,
},
{
'peak_value': 1.0,
'peak_index': 125,
'peak_start_index': 81,
'peak_end_index': 167,
'total_wave_time': 5.43,
},
]
assert len(res) == len(exp)
for res_stats, exp_stats in zip(res, exp):
for key, val in exp_stats.items():
assert round(res_stats[key], 2) == round(exp_stats[key],
2), key
def test_refines_empty_list(self):
time = np.linspace(0, 2 * np.pi, 100)
signal = np.sin(time)
res = signals.refine_signal_peaks(time, signal, [])
assert res == []
def test_refines_single_peak_bad_annotation(self):
time = np.linspace(0, 2 * np.pi, 100)
signal = np.sin(time)
res = signals.refine_signal_peaks(time, signal, [25, 50])
assert len(res) == 1
res = res[0]
exp = {
'peak_value': 1.0,
'peak_index': 25,
'peak_start_index': 0,
'peak_end_index': 68,
'total_wave_time': 4.32,
}
for key, val in exp.items():
assert round(res[key], 2) == round(exp[key], 2), key