允许 HHD 下采样率不同的标定保持兼容

按实际运行上下文核对其余处理参数，保留文件指纹与设备身份校验。115 项标定及运行时检查通过。

tests/test_calibration_context.py

@@ -1,6 +1,7 @@
 """Feature identities use effective measurement settings, never display metadata."""
 
 from copy import deepcopy
+import json
 
 import numpy as np
 import pytest
@@ -57,3 +58,77 @@ def test_domain_fingerprint_binds_map_content_not_only_dimensions():
         changed[key].flat[0] = not changed[key].flat[0] if key == "valid_mask" else 1
         assert domain_fingerprint(changed) != original
     assert domain_fingerprint({key: value.copy() for key, value in domain.items()}) == original
+
+
+def _model(data):
+    from orisys.calibration import parse
+
+    return parse({
+        "schema_version": 3, "unit": "N",
+        "identity": {"sensor_type": "box", "sn": "A1"},
+        "pipeline": build_context(data),
+        "model": {
+            "type": "global_gain/1", "input_profile": "force_delta/1",
+            "output_frame": "sdk_force/1", "outputs": ["fn"],
+            "params": {"gains_N_per_raw": {"fn": .001}, "valid_force_range_N": [0, 3]},
+        },
+    })
+
+
+@pytest.mark.parametrize("downsample", [1, 2, 4])
+def test_downsample_only_difference_accepts_existing_model_without_rewriting_it(downsample):
+    from orisys.calibration import validate_for_device
+
+    data = config()
+    data["tracker"]["hhd_downsample"] = 3
+    model = _model(data)
+    original = model.to_dict()
+    fingerprint = model.fingerprint
+    data["tracker"]["hhd_downsample"] = downsample
+    actual = build_context(data)
+    assert json.loads(json.dumps(actual)) == actual
+    assert actual["feature_signature_sha256"] != model.pipeline["feature_signature_sha256"]
+    validate_for_device(model, "box", "A1", pipeline=actual)
+    model.validate_for_context(actual)
+    assert model.to_dict() == original
+    assert model.fingerprint == fingerprint
+    assert actual["hhd_downsample"] == downsample
+
+
+def test_runtime_context_binds_a_different_downsample_model_and_predicts():
+    from orisys.force_readout import ForceReadout
+    from orisys.sensor import Sensor
+
+    data = config()
+    data["tracker"]["hhd_downsample"] = 3
+    sensor = Sensor.__new__(Sensor)
+    sensor._config = data
+    sensor.calibration = _model(data)
+    sensor._force_raw = (100.0, 0.0, 0.0)
+    sensor._force_readout = ForceReadout({})
+    sensor._model_readouts = {}
+    sensor._reset_calibration_session()
+    data["tracker"]["hhd_downsample"] = 2
+    sensor.bind_calibration_context(build_context(data))
+    sensor.set_calibration_reference({"fn": 100.0}, reference_id="unloaded")
+    result = sensor.apply_calibration_frame(
+        frame_id=1, timestamp_s=0.1, raw=(120.0, 0.0, 0.0), contact_found=True,
+    )
+    assert result.values_N["fn"] == pytest.approx(.02)
+
+
+@pytest.mark.parametrize("section,key,value", [
+    ("camera", "resolution_raw", [640, 480]),
+    ("tracker", "dis_mode", 1),
+    ("tracker", "flow_iterations", 99),
+    ("contact", "threshold", .9),
+    ("filters", "flow_ema_alpha", .5),
+])
+def test_downsample_tolerance_does_not_hide_other_pipeline_changes(section, key, value):
+    data = config()
+    data["tracker"]["hhd_downsample"] = 3
+    model = _model(data)
+    data["tracker"]["hhd_downsample"] = 2
+    data.setdefault(section, {})[key] = value
+    with pytest.raises(ValueError, match="pipeline mismatch"):
+        model.validate_for_context(build_context(data))