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f559cc0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 | from __future__ import annotations
from dataclasses import dataclass
import sys
from pathlib import Path
ROOT = Path(__file__).resolve().parents[2]
sys.path.insert(0, str(ROOT / "backend"))
sys.path.insert(0, str(ROOT / "backend" / "scripts"))
from analyze_efficientnet_errors import _mistakes, _source_breakdown
@dataclass(frozen=True)
class _Record:
subject_id: str
source: str
image_path: str
def test_source_breakdown_counts_errors_by_source() -> None:
records = [
_Record("s1", "roi_original", "a.jpg"),
_Record("s2", "roi_original", "b.jpg"),
_Record("s3", "palpebral", "c.png"),
]
result = _source_breakdown(
records,
labels=[0, 1, 0],
predictions=[1, 1, 0],
probabilities=[0.8, 0.9, 0.1],
hb_predictions=[10.5, 8.8, 12.4],
hb_targets=[12.6, 9.1, 12.1],
)
assert result["roi_original"]["count"] == 2
assert result["roi_original"]["false_positives"] == 1
assert result["roi_original"]["false_negatives"] == 0
assert result["palpebral"]["errors"] == 0
def test_mistakes_splits_false_positives_and_false_negatives() -> None:
records = [
_Record("s1", "roi_original", "a.jpg"),
_Record("s2", "palpebral", "b.png"),
]
false_positives, false_negatives = _mistakes(
records,
labels=[0, 1],
predictions=[1, 0],
probabilities=[0.91, 0.12],
hb_predictions=[10.2, 12.8],
hb_targets=[13.1, 8.9],
)
assert len(false_positives) == 1
assert false_positives[0]["subject_id"] == "s1"
assert len(false_negatives) == 1
assert false_negatives[0]["subject_id"] == "s2"
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