File size: 2,492 Bytes
694a26f | 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 63 | """The boundary-condition rule is stable within a sensor, and it is data-driven.
Two properties, both of which were violated by an earlier version of the rule
and neither of which a figure would have shown:
1. STABLE. The choice must not vary frame to frame inside one dataset. The
first rule decided from the contact's anchor region, so on FEATS it chose
the free boundary on 20% of frames and the clamped one on 80% — two
height conventions inside one feature table, worth -0.044 rho on the LUT.
It is now decided from the REFERENCE frame, which is constant per sensor.
2. DATA-DRIVEN. It must actually be reading the gel, not a dataset name.
Marker gel -> clamped, markerless -> free, asserted per dataset.
python -m scripts.test_boundary_rule
"""
from __future__ import annotations
import numpy as np
import sys as _sys
from pathlib import Path as _Path
# repo root, so `force_recovery` / `twm` / `react_toolbox` import however
# this file is invoked. Six scripts lacked this and failed at import; all
# six sat in validate_all's "slow" skip list, so nothing ran them.
_sys.path.insert(0, str(_Path(__file__).resolve().parents[1]))
from force_recovery import debug_gallery as dg
from force_recovery.poisson import free_boundary_ok
# (loader, expect_free_boundary). FEATS is the marker gel.
DATASETS = (("cnc_mini_26", "load_glowtact", True),
("cnc", "load_cnc", True),
("feats", "load_feats", False))
N = 12
def main() -> int:
bad = []
for name, loader, expect in DATASETS:
try:
rows, get = getattr(dg, loader)()
except Exception as exc: # noqa: BLE001
bad.append(f"{name}: could not load ({exc}) — NOT reporting a pass")
continue
rng = np.random.default_rng(0)
sel = [rows[i] for i in rng.permutation(len(rows))[:N]]
got = {free_boundary_ok(get(fr)[1]) for fr in sel}
print(f" {name:12s} free boundary: {sorted(got)} (expected {expect})")
if len(got) != 1:
bad.append(f"{name}: the rule flips inside one dataset {got} — "
f"two height conventions in one feature table")
elif got.pop() is not expect:
bad.append(f"{name}: expected free={expect}")
for b in bad:
print(f" FAIL: {b}")
print(f"boundary-rule: {len(bad)} problem(s)")
return 1 if bad else 0
if __name__ == "__main__":
raise SystemExit(main())
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