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Unit Tests — Active Learning Sampler (backend/active_learning/sampler.py)
No database or HTTP client required.
"""
import pytest
from backend.active_learning.sampler import (
prediction_entropy,
should_queue_for_review,
uncertainty_band,
)
class TestPredictionEntropy:
async def test_entropy_at_maximum_uncertainty(self):
assert prediction_entropy(0.5) == pytest.approx(1.0)
async def test_entropy_at_certain_zero(self):
# p=0 → certain negative → entropy 0
assert prediction_entropy(0.0) == pytest.approx(0.0, abs=1e-6)
async def test_entropy_at_certain_one(self):
# p=1 → certain positive → entropy 0
assert prediction_entropy(1.0) == pytest.approx(0.0, abs=1e-6)
async def test_entropy_symmetric(self):
assert prediction_entropy(0.3) == pytest.approx(prediction_entropy(0.7))
async def test_entropy_monotone_towards_half(self):
# Entropy increases as p approaches 0.5 from 0
assert prediction_entropy(0.1) < prediction_entropy(0.3) < prediction_entropy(0.5)
async def test_entropy_returns_float(self):
result = prediction_entropy(0.4)
assert isinstance(result, float)
async def test_entropy_never_exceeds_one(self):
for p in [0.0, 0.1, 0.25, 0.5, 0.75, 0.9, 1.0]:
assert prediction_entropy(p) <= 1.0 + 1e-9
class TestShouldQueueForReview:
async def test_maximum_uncertainty_queued(self):
assert should_queue_for_review(0.5) is True
async def test_near_maximum_uncertainty_queued(self):
assert should_queue_for_review(0.45) is True
async def test_high_confidence_positive_not_queued(self):
assert should_queue_for_review(0.95) is False
async def test_high_confidence_negative_not_queued(self):
assert should_queue_for_review(0.05) is False
async def test_custom_threshold_lower(self):
# With a very low threshold, even moderately uncertain predictions queue
assert should_queue_for_review(0.4, entropy_threshold=0.5) is True
async def test_custom_threshold_very_high(self):
# With threshold > 1.0, nothing queues (entropy max is 1.0)
assert should_queue_for_review(0.5, entropy_threshold=1.01) is False
class TestUncertaintyBand:
@pytest.mark.parametrize("probability,expected_band", [
(0.95, "CERTAIN"),
(0.05, "CERTAIN"),
(0.75, "CONFIDENT"),
(0.25, "CONFIDENT"),
(0.62, "BORDERLINE"),
(0.38, "BORDERLINE"),
(0.50, "UNCERTAIN"),
])
async def test_uncertainty_band_mapping(self, probability, expected_band):
assert uncertainty_band(probability) == expected_band
async def test_boundary_high_certain(self):
# 0.85 → CERTAIN
assert uncertainty_band(0.85) == "CERTAIN"
async def test_boundary_low_certain(self):
# 0.15 → CERTAIN
assert uncertainty_band(0.15) == "CERTAIN"
async def test_band_returns_string(self):
result = uncertainty_band(0.5)
assert isinstance(result, str)
async def test_all_bands_covered(self):
bands = {uncertainty_band(p) for p in [0.5, 0.62, 0.75, 0.95]}
assert bands == {"UNCERTAIN", "BORDERLINE", "CONFIDENT", "CERTAIN"}
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