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Align task taxonomy and IDs with the updated paper; main evaluation 306
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from __future__ import annotations
import math
import xml.etree.ElementTree as ET
from pathlib import Path
EVAL_DIR = Path(__file__).resolve().parent
STARTER_BRD = next(
(path for path in (EVAL_DIR / "dense.brd", EVAL_DIR / "init_file" / "dense.brd") if path.exists()),
EVAL_DIR / "dense.brd",
)
TARGET_COUNT = 5
def _elements(root: ET.Element) -> list[ET.Element]:
return root.findall(".//elements/element")
def _plain_texts_l25(root: ET.Element) -> list[ET.Element]:
plain = root.find(".//board/plain")
if plain is None:
return []
return [t for t in plain.findall("text") if t.get("layer") == "25"]
def _has_embedded_name(element: ET.Element) -> bool:
return any(attribute.get("name") == "NAME" for attribute in element.findall("attribute"))
def _centroid(elements: list[ET.Element]) -> tuple[float, float]:
xs = [float(e.get("x", "0")) for e in elements]
ys = [float(e.get("y", "0")) for e in elements]
return sum(xs) / len(xs), sum(ys) / len(ys)
def _target_names(elements: list[ET.Element]) -> set[str]:
cx, cy = _centroid(elements)
ranked = sorted(
(e for e in elements if e.get("name")),
key=lambda e: math.hypot(float(e.get("x", "0")) - cx, float(e.get("y", "0")) - cy),
)
return {e.get("name") for e in ranked[:TARGET_COUNT] if e.get("name")}
def evaluate(submission_dir: str) -> bool:
sub = Path(submission_dir).resolve()
target = None
for name in ("labeled.brd",):
p = sub / name
if p.exists():
target = p
break
if target is None or not STARTER_BRD.exists():
return False
try:
starter = ET.parse(STARTER_BRD).getroot()
root = ET.parse(target).getroot()
except Exception:
return False
starter_elems = _elements(starter)
out_elems = _elements(root)
starter_names = {e.get("name") for e in starter_elems if e.get("name")}
out_names = {e.get("name") for e in out_elems if e.get("name")}
if len(out_elems) != len(starter_elems):
return False
if starter_names != out_names:
return False
texts = _plain_texts_l25(root)
labels = [(t.text or "").strip() for t in texts]
chosen = _target_names(starter_elems)
if len(texts) != TARGET_COUNT or set(labels) != chosen or len(labels) != len(set(labels)):
return False
if not all(label in starter_names for label in labels):
return False
starter_by_name = {e.get("name"): e for e in starter_elems if e.get("name")}
output_by_name = {e.get("name"): e for e in out_elems if e.get("name")}
for t in texts:
label = (t.text or "").strip()
ref = starter_by_name.get(label)
if ref is None:
return False
tx = float(t.get("x", "nan"))
ty = float(t.get("y", "nan"))
rx = float(ref.get("x", "nan"))
ry = float(ref.get("y", "nan"))
if math.hypot(tx - rx, ty - ry) > 2.0:
return False
output_element = output_by_name.get(label)
if output_element is None or _has_embedded_name(output_element):
return False
return True
if __name__ == "__main__":
import sys
if len(sys.argv) > 2:
print("usage: python eval.py SUBMISSION_DIR", file=sys.stderr)
sys.exit(2)
submission_dir = sys.argv[1] if len(sys.argv) == 2 else Path(__file__).resolve().parent
print("True" if evaluate(submission_dir) else "False")