新增 HHD 场加权标定模型与加权空载基线

field_gain/1 用坐标增益图对无旋向量场做 L1 场加权，以连续 30 帧加权中位数替代旧 raw 零点，实时入口暂不支持。目标测试 102 项与 lint_gate 通过；契约见 orisys-sdk/docs/field-gain-model.zh.md。

tests/test_model_runtime.py

@@ -345,3 +345,113 @@ def test_bad_zero_reference_is_rejected_without_reset(reference):
     with pytest.raises(ValueError):
         sensor.set_calibration_reference(reference, reference_id="bad")
     assert sensor._calibration_reference == {"fn": 10.}
+
+
+class FieldRecordingModel:
+    schema_version = 3
+    channels = {"fn": "N"}
+    input_profile = "hhd_normal_l1_field/1"
+
+    def __init__(self):
+        self.calls = []
+        self.resets = []
+        self.begin_calls = []
+        self.coordinate_map = np.zeros((2, 2, 2), dtype=np.float32)
+        self.coordinate_valid_mask = np.ones((2, 2), dtype=bool)
+
+    def reset(self, reference_id):
+        self.resets.append(reference_id)
+
+    def begin_reference(self, reference_id):
+        self.begin_calls.append(reference_id)
+
+    def validate_for_context(self, context):
+        if context != {"signature": "actual"}:
+            raise CalibrationError("pipeline mismatch")
+
+    def predict(self, **kwargs):
+        self.calls.append(kwargs)
+        features = kwargs["features"]
+        if "field" not in features:
+            return SimpleNamespace(values_N={"fn": None}, status={"fn": "invalid_input"},
+                                   diagnostics={})
+        return SimpleNamespace(values_N={"fn": 1.0}, status={"fn": "ok"}, diagnostics={})
+
+
+def test_hhd_field_model_infers_from_same_frame_field_without_contact():
+    sensor = make_sensor()
+    sensor.calibration = FieldRecordingModel()
+    sensor._calibration_context = {"signature": "actual"}
+    sensor.cuda = sensor.verbose = False
+    sensor.valid_mask = sensor.valid_mask_hhd = None
+    sensor._hhd_downsample = 1
+    sensor._hhd_grid_shape = sensor._hhd_ref_shape = (2, 2)
+    sensor._model_frame_id = 0
+    field = np.zeros((2, 2, 2), dtype=np.float32)
+    calls = []
+
+    def get_field(valid_mask=None):
+        calls.append(valid_mask)
+        return {"d": field, "valid_mask": np.ones((2, 2), dtype=bool), "area_scale": 1.0,
+                "grid_shape": (2, 2), "reference_shape": (2, 2)}
+
+    sensor._Sensor__hhd = SimpleNamespace(
+        get_force=lambda *args, **kwargs: (None, (10., 0., 0., 0.)),
+        get_normal=lambda: field, get_shear=lambda: field, get_field=get_field,
+    )
+    sensor.compute_hhd(np.zeros((2, 2, 2), dtype=np.float32))
+    features = sensor.calibration.calls[-1]["features"]
+    assert features["field"]["grid_shape"] == (2, 2)
+    assert features["output_valid_mask"].shape == (2, 2)
+    assert "contact_found" not in features
+    assert sensor.calibration_status == {"fn": "ok"}
+    assert sensor.fnormal == pytest.approx(1.0)
+    assert calls == [None]
+
+
+def test_weighted_unloaded_reference_is_declared_not_a_scalar_zero():
+    sensor = make_sensor()
+    sensor.calibration = FieldRecordingModel()
+    sensor._calibration_context = {"signature": "actual"}
+    sensor.declare_unloaded_reference(reference_id="video-unloaded-100")
+    assert sensor.calibration.begin_calls == ["video-unloaded-100"]
+    assert sensor._calibration_reference_id == "video-unloaded-100"
+    with pytest.raises(CalibrationError, match="scalar zero"):
+        sensor.set_calibration_reference({"fn": 0.}, reference_id="bad")
+    with pytest.raises(CalibrationError, match="hhd_normal_l1_field"):
+        make_sensor().declare_unloaded_reference(reference_id="scalar-model")
+
+
+def test_finger_runtime_binds_field_identity_and_forwards_the_window(monkeypatch, tmp_path):
+    import orisys.calibration_context as context_mod
+    from orisys.field_calibration import FIELD_IDENTITY
+    from orisys.finger.runtime import FingerRuntime
+
+    sensor = make_sensor()
+    sensor.calibration = FieldRecordingModel()
+    sensor._calibration_context = {"signature": "actual"}
+    sensor.device_id = None
+    sensor.mirror = False
+    runtime = FingerRuntime.__new__(FingerRuntime)
+    runtime.tactile = SimpleNamespace(raw_sensor=sensor)
+    mesh = tmp_path / "mesh.npz"
+    mesh.write_bytes(b"actual geometry")
+    runtime.geometry = SimpleNamespace(config={}, export_paths=SimpleNamespace(mesh=mesh),
+                                       source_scale=.42, out_height=2, out_width=2)
+    runtime.domain = object()
+    runtime.frame_processor = SimpleNamespace(flip_source_vertical=True)
+    monkeypatch.setattr(context_mod, "domain_fingerprint", lambda domain: "domain")
+    contexts = []
+
+    def context(config, filters, **kwargs):
+        contexts.append(kwargs)
+        return {"signature": "actual"}
+
+    monkeypatch.setattr(context_mod, "build_context", context)
+    selected = FieldRecordingModel()
+    selected.pipeline = {"coordinates": {"frame": "autocal_flat"}}
+    runtime.set_calibration(selected)
+    assert contexts[0]["field"] == FIELD_IDENTITY
+    runtime.declare_unloaded_reference("runtime-window")
+    assert sensor.calibration.begin_calls == ["runtime-window"]
+