Files
tono/tests/node_tests/drift_correction.py
2026-04-03 22:09:19 -07:00

54 lines
1.8 KiB
Python

import numpy as np
import pytest
from tests.node_tests._shared import make_field
def test_drift_correction_flat():
from backend.nodes.drift_correction import DriftCorrection
node = DriftCorrection()
field = make_field(data=np.zeros((32, 32)))
result, = node.process(field, "previous_row", "horizontal")
assert result.data.shape == (32, 32)
assert np.allclose(result.data, 0.0, atol=1e-10)
def test_drift_correction_preserves_shape():
from backend.nodes.drift_correction import DriftCorrection
node = DriftCorrection()
field = make_field(shape=(48, 64))
for ref in ("previous_row", "mean_row"):
for direction in ("horizontal", "vertical"):
result, = node.process(field, ref, direction)
assert result.data.shape == (48, 64)
def test_drift_correction_reduces_drift():
"""A field with artificial row-by-row drift should have less variance after correction."""
from backend.nodes.drift_correction import DriftCorrection
node = DriftCorrection()
rng = np.random.default_rng(42)
base = rng.standard_normal((32, 64))
# Add artificial drift: shift each row by cumulative offset
drifted = base.copy()
for i in range(1, 32):
drifted[i] = np.roll(base[i], i)
field = make_field(data=drifted)
result, = node.process(field, "previous_row", "horizontal")
# The corrected field should have lower inter-row variance
row_means_before = np.var(np.diff(drifted, axis=0))
row_means_after = np.var(np.diff(result.data, axis=0))
assert row_means_after <= row_means_before
def test_drift_correction_mean_row_reference():
from backend.nodes.drift_correction import DriftCorrection
node = DriftCorrection()
field = make_field(shape=(32, 32))
result, = node.process(field, "mean_row", "horizontal")
assert result.data.shape == (32, 32)