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。

docs/calibration-model-contract.zh.md

@@ -121,6 +121,12 @@ runtime.set_calibration_reference({"fn": measured_zero_raw}, reference_id="unloa
 特征定义或单位改变须升级 `feature_version`，配置覆盖后重新计算，不能用配置文件名代替。
 实现由 `calibration_context.build_context` 统一生成，特征版本为 `orisys_hhd_raw/1`。
 
+`hhd_downsample` 是 schema 1/2/3 的兼容例外，允许数值偏差；实际参数、系数和文件指纹不变。
+schema 3 的 `build_context` 运行时上下文仅替换下采样率重算比对签名；
+其余处理参数、几何、展开域、SN 和传感器类型仍须匹配。
+序列化与普通映射仍校验实际指纹。
+验证：`test_calibration_context.py`、`test_calibration.py`。
+
 ## 空间增益模型
 
 `spatial_gain/1` 固定输出 `fn`，使用 `fn_delta_autocal_uv/1`：

src/orisys/calibration.py

@@ -52,7 +52,7 @@ _KNOWN_TOP_KEYS = frozenset(
 #: Filter stages that change **what is measured**: they sit upstream of the
 #: force computation, so two recordings with different values are not comparable.
 #: They belong to the measurement-pipeline identity, for the same reason
-#: ``dis_mode`` and ``hhd_downsample`` do.
+#: ``dis_mode`` does. HHD resolution is retained in provenance but may differ.
 FILTER_MEASUREMENT_KEYS: tuple[str, ...] = ("flow_ema_alpha",)
 #: Filter stages that only smooth the force triple on its way out. They are
 #: recorded so a file explains its own numbers, but a difference between two
@@ -876,7 +876,7 @@ def validate_for_device(
     *,
     pipeline: Mapping[str, Any] | None = None,
 ) -> Calibration:
-    """Reject a calibration for another device or measurement pipeline."""
+    """Reject a different device or pipeline, allowing HHD resolution differences."""
     path = cal.source_path or "<in-memory calibration>"
     if cal.identity.get("sensor_type") != sensor_type or cal.identity.get("sn") != device_id:
         raise CalibrationError(f"calibration identity mismatch: {path}")
@@ -886,7 +886,7 @@ def validate_for_device(
         # Full feature/geometry validation happens when the processor binds its
         # actual context. Device construction only knows this legacy subset.
         if pipeline is not None:
-            for key in ("stitch_resolution", "dis_mode", "hhd_downsample"):
+            for key in ("stitch_resolution", "dis_mode"):
                 if pipeline.get(key) is not None and cal.pipeline.get(key) != pipeline[key]:
                     raise CalibrationError(f"calibration pipeline mismatch ({key}): {path}")
             measurement, _ = filter_mismatches(cal.pipeline.get("filters"), pipeline.get("filters"))
@@ -898,7 +898,7 @@ def validate_for_device(
     if set(CHANNEL_IDS) - cal.channels.keys():
         raise CalibrationError(f"calibration requires FN, FX and FY: {path}")
     if pipeline is not None:
-        for key in ("stitch_resolution", "dis_mode", "hhd_downsample"):
+        for key in ("stitch_resolution", "dis_mode"):
             recorded, current = cal.pipeline.get(key), pipeline.get(key)
             if recorded is not None and current is not None and recorded != current:
                 raise CalibrationError(f"calibration pipeline mismatch ({key}): {path}")

src/orisys/calibration_context.py

@@ -4,6 +4,7 @@ from __future__ import annotations
 
 import hashlib
 import json
+from copy import deepcopy
 from pathlib import Path
 
 import numpy as np
@@ -11,6 +12,29 @@ import numpy as np
 from .calibration import filters_fingerprint
 
 
+def _feature_signature(identity) -> str:
+    encoded = json.dumps(identity, sort_keys=True, separators=(",", ":"), allow_nan=False)
+    return hashlib.sha256(encoded.encode("utf-8")).hexdigest()
+
+
+class CalibrationContext(dict):
+    """Actual pipeline fields plus the runtime inputs needed to compare HHD settings.
+
+    JSON serialization contains only the actual fields. Retaining the signature
+    inputs lets old files differ in downsample without ignoring other hashed settings.
+    """
+
+    def __init__(self, fields, feature_identity):
+        super().__init__(fields)
+        self._feature_identity = deepcopy(feature_identity)
+
+    def signature_for_downsample(self, downsample: int) -> str:
+        """Recompute the runtime identity with only the requested HHD resolution."""
+        identity = deepcopy(self._feature_identity)
+        identity["tracker"]["hhd_downsample"] = downsample
+        return _feature_signature(identity)
+
+
 def sha256_file(path) -> str:
     return hashlib.sha256(Path(path).read_bytes()).hexdigest()
 
@@ -70,6 +94,5 @@ def build_context(config, filters=None, *, geometry_sha256=None, source_scale=No
         "source_scale": source_scale,
         "preprocessing": preprocessing or {},
     }
-    encoded = json.dumps(effective, sort_keys=True, separators=(",", ":"), allow_nan=False)
+    result["feature_signature_sha256"] = _feature_signature(effective)
-    result["feature_signature_sha256"] = hashlib.sha256(encoded.encode("utf-8")).hexdigest()
+    return CalibrationContext(result, effective)
-    return result

src/orisys/calibration_models.py

@@ -209,8 +209,19 @@ class ModelCalibration:
         return deepcopy(self._document)
 
     def validate_for_context(self, pipeline: Mapping[str, Any]) -> None:
+        from .calibration_context import CalibrationContext
+
         for key, value in self.pipeline.items():
-            if key == "filters":
+            if key == "hhd_downsample":
+                # HHD magnitudes are normalized to the full flow grid; resolution
+                # can introduce numerical deviations without changing the force unit.
+                continue
+            if key == "feature_signature_sha256" and isinstance(pipeline, CalibrationContext):
+                _require(
+                    pipeline.signature_for_downsample(self.pipeline["hhd_downsample"]) == value,
+                    "calibration pipeline mismatch: feature_signature_sha256",
+                )
+            elif key == "filters":
                 actual = pipeline.get(key, {})
                 _require(isinstance(actual, Mapping) and actual.get("measurement") == value["measurement"],
                          "calibration pipeline mismatch: filters.measurement")

tests/test_calibration.py

@@ -306,6 +306,18 @@ def test_device_calibration_rejects_wrong_identity_and_pipeline(tmp_path: Path):
         load_for_device(root, "box", "BOX-001", pipeline={"dis_mode": 1})
 
 
+def test_device_calibration_accepts_only_downsample_difference(tmp_path: Path):
+    path = _device_file(tmp_path, "BOX-001")
+    doc = json.loads(path.read_text(encoding="utf-8"))
+    doc["pipeline"] = {"dis_mode": 1, "hhd_downsample": 3}
+    path.write_text(json.dumps(doc), encoding="utf-8")
+    assert load_for_device(
+        tmp_path, "box", "BOX-001", pipeline={"dis_mode": 1, "hhd_downsample": 2},
+    ) is not None
+    with pytest.raises(CalibrationError, match="dis_mode"):
+        load_for_device(tmp_path, "box", "BOX-001", pipeline={"dis_mode": 9, "hhd_downsample": 2})
+
+
 def test_device_calibration_rejects_partial_axes_and_unsafe_id(tmp_path: Path):
     root = tmp_path / "calibrations"
     root.mkdir()

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))