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tests_signal_fixpeaks.py
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tests_signal_fixpeaks.py
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# -*- coding: utf-8 -*-
import numpy as np
import numpy.random
import pytest
from neurokit2.signal.signal_fixpeaks import _correct_artifacts, _find_artifacts, signal_fixpeaks
def compute_rmssd(peaks):
rr = np.ediff1d(peaks, to_begin=0)
rr[0] = np.mean(rr[1:])
rmssd = np.sqrt(np.mean(rr ** 2))
return rmssd
@pytest.fixture
def n_peaks():
return 1000
@pytest.fixture
def k_peaks():
return 100
@pytest.fixture
def artifact_idcs(k_peaks, n_peaks):
idcs = np.arange(k_peaks, n_peaks, k_peaks)
return idcs
@pytest.fixture
def peaks_correct(n_peaks):
# Simulate sinusoidally changing heart periods.
rr = np.sin(np.arange(n_peaks))
# Add some noise.
rng = numpy.random.default_rng(42)
rr_noisy = rng.normal(rr, 0.1)
# Scale to range of 250msec and offset by 1000msec. I.e., heart period
# fluctuates in a range of 250msec around 1000msec.
rr_scaled = 1000 + rr_noisy * 125
peaks = np.cumsum(np.rint(rr_scaled)).astype(int)
return peaks
@pytest.fixture
def peaks_misaligned(request, peaks_correct, artifact_idcs):
rmssd = compute_rmssd(peaks_correct)
displacement = request.param * rmssd
peaks_misaligned = peaks_correct.copy()
peaks_misaligned[artifact_idcs] = peaks_misaligned[artifact_idcs] - displacement
return peaks_misaligned
@pytest.fixture
def peaks_missed(peaks_correct, artifact_idcs):
peaks_missed = peaks_correct.copy()
peaks_missed = np.delete(peaks_missed, artifact_idcs)
return peaks_missed
@pytest.fixture
def peaks_extra(peaks_correct, artifact_idcs):
extra_peaks = (peaks_correct[artifact_idcs + 1] - peaks_correct[artifact_idcs]) / 15 + peaks_correct[artifact_idcs]
peaks_extra = peaks_correct.copy()
peaks_extra = np.insert(peaks_extra, artifact_idcs, extra_peaks)
return peaks_extra
@pytest.fixture
def artifacts_misaligned(artifact_idcs):
artifacts = {"ectopic": list(artifact_idcs + 1), "missed": [], "extra": [], "longshort": list(artifact_idcs)}
return artifacts
@pytest.fixture
def artifacts_missed(artifact_idcs):
missed_idcs = [
j - i for i, j in enumerate(artifact_idcs)
] # account for the fact that peak indices are shifted to the left after deletion of peaks
artifacts = {"ectopic": [], "missed": missed_idcs, "extra": [], "longshort": []}
return artifacts
@pytest.fixture
def artifacts_extra(artifact_idcs):
extra_idcs = [
j + (i + 1) for i, j in enumerate(artifact_idcs)
] # account for the fact that peak indices are shifted to the right after insertion of peaks
artifacts = {"ectopic": [], "missed": [], "extra": extra_idcs, "longshort": []}
return artifacts
@pytest.mark.parametrize("peaks_misaligned", [2, 4, 8], indirect=["peaks_misaligned"])
def test_misaligned_detection(peaks_misaligned, artifacts_misaligned):
artifacts, _ = _find_artifacts(peaks_misaligned, sampling_rate=1)
assert artifacts == artifacts_misaligned # check for identical key-value pairs
def test_missed_detection(peaks_missed, artifacts_missed):
artifacts, _ = _find_artifacts(peaks_missed, sampling_rate=1)
assert artifacts == artifacts_missed
def test_extra_detection(peaks_extra, artifacts_extra):
artifacts, _ = _find_artifacts(peaks_extra, sampling_rate=1)
assert artifacts == artifacts_extra
@pytest.mark.parametrize("peaks_misaligned", [2, 4, 8], indirect=["peaks_misaligned"])
def test_misaligned_correction(peaks_misaligned, artifacts_misaligned):
peaks_corrected = _correct_artifacts(artifacts_misaligned, peaks_misaligned)
assert (
np.unique(peaks_corrected).size == peaks_misaligned.size
) # make sure that no peak duplication occurs and that number of peaks doesn't change
def test_missed_correction(peaks_missed, artifacts_missed):
peaks_corrected = _correct_artifacts(artifacts_missed, peaks_missed)
assert np.unique(peaks_corrected).size == (peaks_missed.size + len(artifacts_missed["missed"]))
def test_extra_correction(peaks_extra, artifacts_extra):
peaks_corrected = _correct_artifacts(artifacts_extra, peaks_extra)
assert np.unique(peaks_corrected).size == (peaks_extra.size - len(artifacts_extra["extra"]))
def idfn(val):
if isinstance(val, bool):
return f"iterative_{val}"
@pytest.mark.parametrize(
"peaks_misaligned, iterative, rmssd_diff",
[(2, True, 34), (2, False, 27), (4, True, 133), (4, False, 113), (8, True, 466), (8, False, 444)],
indirect=["peaks_misaligned"],
ids=idfn,
)
def test_misaligned_correction_wrapper(peaks_correct, peaks_misaligned, iterative, rmssd_diff):
_, peaks_corrected = signal_fixpeaks(peaks_misaligned, sampling_rate=1, iterative=iterative)
rmssd_correct = compute_rmssd(peaks_correct)
rmssd_corrected = compute_rmssd(peaks_corrected)
rmssd_uncorrected = compute_rmssd(peaks_misaligned)
# Assert that correction does not produce peaks that exceed the temporal
# bounds of the original peaks.
assert peaks_correct[0] <= peaks_corrected[0]
assert peaks_correct[-1] >= peaks_corrected[-1]
# Assert that after artifact correction, the difference in RMSSD to the
# undistorted signal decreases. This also implicitely tests if the peak
# distortion affects the RMSSD (manipulation check).
rmssd_diff_uncorrected = np.abs(rmssd_correct - rmssd_uncorrected)
rmssd_diff_corrected = np.abs(rmssd_correct - rmssd_corrected)
assert int(rmssd_diff_uncorrected - rmssd_diff_corrected) == rmssd_diff
@pytest.mark.parametrize("iterative, rmssd_diff", [(True, 3), (False, 3)], ids=idfn)
def test_extra_correction_wrapper(peaks_correct, peaks_extra, iterative, rmssd_diff):
_, peaks_corrected = signal_fixpeaks(peaks_extra, sampling_rate=1, iterative=iterative)
rmssd_correct = compute_rmssd(peaks_correct)
rmssd_corrected = compute_rmssd(peaks_corrected)
rmssd_uncorrected = compute_rmssd(peaks_extra)
# Assert that correction does not produce peaks that exceed the temporal
# bounds of the original peaks.
assert peaks_correct[0] <= peaks_corrected[0]
assert peaks_correct[-1] >= peaks_corrected[-1]
# Assert that after artifact correction, the difference in RMSSD to the
# undistorted signal decreases. This also implicitely tests if the peak
# distortion affects the RMSSD (manipulation check).
rmssd_diff_uncorrected = np.abs(rmssd_correct - rmssd_uncorrected)
rmssd_diff_corrected = np.abs(rmssd_correct - rmssd_corrected)
assert int(rmssd_diff_uncorrected - rmssd_diff_corrected) == rmssd_diff
@pytest.mark.parametrize("iterative, rmssd_diff", [(True, 13), (False, 13)], ids=idfn)
def test_missed_correction_wrapper(peaks_correct, peaks_missed, iterative, rmssd_diff):
_, peaks_corrected = signal_fixpeaks(peaks_missed, sampling_rate=1, iterative=iterative)
rmssd_correct = compute_rmssd(peaks_correct)
rmssd_corrected = compute_rmssd(peaks_corrected)
rmssd_uncorrected = compute_rmssd(peaks_missed)
# Assert that correction does not produce peaks that exceed the temporal
# bounds of the original peaks.
assert peaks_correct[0] <= peaks_corrected[0]
assert peaks_correct[-1] >= peaks_corrected[-1]
# Assert that after artifact correction, the difference in RMSSD to the
# undistorted signal decreases. This also implicitely tests if the peak
# distortion affects the RMSSD (manipulation check).
rmssd_diff_uncorrected = np.abs(rmssd_correct - rmssd_uncorrected)
rmssd_diff_corrected = np.abs(rmssd_correct - rmssd_corrected)
assert int(rmssd_diff_uncorrected - rmssd_diff_corrected) == rmssd_diff