Fix IMPA Hall gain sign and synchronize code defaults with vest.yaml (#624, #625)

test/test_impa_mapping.py

@@ -631,3 +631,19 @@ def test_toroidal_hall_channels_declare_a_toroidal_normal_per_the_dd():
     # The normal lies in the horizontal plane, which is what poloidal_angle 0
     # declares; only the toroidal angle distinguishes grad(phi) from grad(R).
     assert IMPA_TOROIDAL_PROBE_POLOIDAL_ANGLE == pytest.approx(0.0)
+
+
+def test_resolve_gain_fallback_is_canonical_negative():
+    from vaft.machine_mapping.impa import _resolve_gain
+
+    # When no gain is present in calibration dictionary, fallback must be -2.0 / 15.0
+    assert _resolve_gain({}, 39204) == pytest.approx(-2.0 / 15.0)
+
+
+def test_window_criteria_matches_vest_yaml_without_max_relative_noise():
+    from vaft.machine_mapping.impa import _window_criteria
+
+    config = resolve_impa_config(39204)
+    criteria = _window_criteria(config)
+    assert not hasattr(criteria, "max_relative_noise")
+    assert "max_relative_noise" not in (config.get("calibration_window") or {})

test/test_impa_processing.py

@@ -227,12 +227,12 @@ def test_calibration_applies_gain_and_baseline_in_the_legacy_order():
     raw = np.vstack([np.full(time.size, 1.5), 1.5 + np.linspace(0.0, 1.0, time.size)])
 
     calibrated = impa_calibrate_signals(
-        raw, gain=2.0 / 15.0, cutoff_hz=250.0, sample_rate=SAMPLE_RATE, baseline="first_sample"
+        raw, gain=-2.0 / 15.0, cutoff_hz=250.0, sample_rate=SAMPLE_RATE, baseline="first_sample"
     )
 
     # A constant input is entirely baseline, so it must vanish.
     assert np.allclose(calibrated[0], 0.0, atol=1e-9)
-    assert calibrated[1, -1] == pytest.approx(2.0 / 15.0, rel=5e-2)
+    assert calibrated[1, -1] == pytest.approx(-2.0 / 15.0, rel=5e-2)
 
 
 def test_unknown_baseline_is_rejected():
@@ -253,7 +253,7 @@ def test_process_impa_reports_valid_for_a_well_behaved_synthetic_array():
     bz = 3.0e-5 * np.sin(2 * np.pi * 3 * time)
     # process_impa filters and gain-calibrates, so hand it volts.
     measured = _synthetic_array(time, i_tf, radii, alpha, bz=bz)
-    raw = measured / (2.0 / 15.0)
+    raw = measured / (-2.0 / 15.0)
 
     result = process_impa(
         time,
@@ -288,7 +288,7 @@ def test_a_toroidal_array_is_rejected_by_the_poloidal_model():
     time = _time()
     i_tf = _tf_ramp(time)
     radii = 0.4 + np.arange(8) * 0.05
-    raw = _synthetic_array(time, i_tf, radii, np.ones(8)) / (2.0 / 15.0)
+    raw = _synthetic_array(time, i_tf, radii, np.ones(8)) / (-2.0 / 15.0)
 
     result = process_impa(
         time, raw, i_tf, r=radii, config=ImpaProcessingConfig(orientation="poloidal")
@@ -304,7 +304,7 @@ def test_a_toroidal_array_is_accepted_by_the_toroidal_model():
     time = _time()
     i_tf = _tf_ramp(time)
     radii = 0.4 + np.arange(8) * 0.05
-    raw = _synthetic_array(time, i_tf, radii, np.ones(8)) / (2.0 / 15.0)
+    raw = _synthetic_array(time, i_tf, radii, np.ones(8)) / (-2.0 / 15.0)
 
     result = process_impa(time, raw, i_tf, r=radii)  # toroidal is the default
 
@@ -317,7 +317,7 @@ def test_a_poloidal_array_is_rejected_by_the_toroidal_model():
     time = _time()
     i_tf = _tf_ramp(time)
     radii = 0.4 + np.arange(8) * 0.05
-    raw = _synthetic_array(time, i_tf, radii, np.full(8, 0.05)) / (2.0 / 15.0)
+    raw = _synthetic_array(time, i_tf, radii, np.full(8, 0.05)) / (-2.0 / 15.0)
 
     result = process_impa(time, raw, i_tf, r=radii)
 
@@ -330,7 +330,7 @@ def test_a_reference_shot_calibration_can_be_reused():
     time = _time()
     i_tf = _tf_ramp(time)
     radii = 0.42 + np.arange(8) * 0.05
-    raw = _synthetic_array(time, i_tf, radii, np.ones(8)) / (2.0 / 15.0)
+    raw = _synthetic_array(time, i_tf, radii, np.ones(8)) / (-2.0 / 15.0)
     reference = process_impa(time, raw, i_tf)
 
     # A shot with no clean TF interval of its own still calibrates.
@@ -348,7 +348,7 @@ def test_missing_channels_are_reported_and_never_silently_zero_filled():
     time = _time()
     i_tf = _tf_ramp(time)
     radii = 0.4 + np.arange(8) * 0.05
-    raw = _synthetic_array(time, i_tf, radii, np.full(8, 0.05)) / (2.0 / 15.0)
+    raw = _synthetic_array(time, i_tf, radii, np.full(8, 0.05)) / (-2.0 / 15.0)
     valid = np.ones(8, dtype=bool)
     valid[3] = False
 
@@ -485,7 +485,7 @@ def test_an_inactive_bz_sensor_is_flagged_rather_than_trusted():
     time = _time()
     i_tf = _tf_ramp(time)
     radii = 0.45 + np.arange(2) * 0.05
-    raw = _synthetic_array(time, i_tf, radii, np.ones(2)) / (2.0 / 15.0)
+    raw = _synthetic_array(time, i_tf, radii, np.ones(2)) / (-2.0 / 15.0)
     dead = np.random.default_rng(1).normal(0.0, 1e-5, (2, time.size))
 
     result = process_impa(time, raw, i_tf, r=radii, b_z_raw=dead)
@@ -505,7 +505,7 @@ def test_incident_angle_is_recovered_from_the_rigid_pitch():
     incident = 30.0
     projected = 0.05 * np.cos(np.radians(incident))
     radii = 0.45 + np.arange(8) * projected
-    raw = _synthetic_array(time, i_tf, radii, np.ones(8), noise=0.0) / (2.0 / 15.0)
+    raw = _synthetic_array(time, i_tf, radii, np.ones(8), noise=0.0) / (-2.0 / 15.0)
 
     result = process_impa(time, raw, i_tf, pitch=0.05, fit_pitch=True)
 
@@ -518,7 +518,7 @@ def test_a_radial_insertion_reports_no_incident_angle():
     time = _time()
     i_tf = _tf_ramp(time)
     radii = 0.45 + np.arange(8) * 0.05
-    raw = _synthetic_array(time, i_tf, radii, np.ones(8), noise=0.0) / (2.0 / 15.0)
+    raw = _synthetic_array(time, i_tf, radii, np.ones(8), noise=0.0) / (-2.0 / 15.0)
 
     result = process_impa(time, raw, i_tf, pitch=0.05, fit_pitch=True)
 
@@ -559,11 +559,37 @@ def test_process_impa_rejects_a_reference_with_a_different_channel_count():
     time = _time()
     i_tf = _tf_ramp(time)
     reference_radii = 0.4 + np.arange(7) * 0.05
-    reference_raw = _synthetic_array(time, i_tf, reference_radii, np.ones(7)) / (2.0 / 15.0)
+    reference_raw = _synthetic_array(time, i_tf, reference_radii, np.ones(7)) / (-2.0 / 15.0)
     reference = process_impa(time, reference_raw, i_tf, r=reference_radii)
 
     target_radii = 0.4 + np.arange(8) * 0.05
-    target_raw = _synthetic_array(time, i_tf, target_radii, np.ones(8)) / (2.0 / 15.0)
+    target_raw = _synthetic_array(time, i_tf, target_radii, np.ones(8)) / (-2.0 / 15.0)
 
     with pytest.raises(ValueError, match="7 channels but this shot has 8"):
         process_impa(time, target_raw, i_tf, reference=reference)
+
+
+def test_impa_code_defaults_match_canonical_values():
+    """Verify code defaults agree with hardware specs and vest.yaml (#624, #625)."""
+    config = ImpaProcessingConfig()
+    assert config.gain == pytest.approx(-2.0 / 15.0)
+
+    # TfWindowCriteria no longer defines unread max_relative_noise
+    criteria = TfWindowCriteria()
+    assert not hasattr(criteria, "max_relative_noise")
+
+
+def test_process_impa_defaults_agree_with_vest_yaml():
+    """Verify process_impa defaults bz_radial_offset=0.01 and max_normalized_rmse=0.15."""
+    time = _time()
+    i_tf = _tf_ramp(time)
+    radii = 0.4 + np.arange(8) * 0.05
+    raw = _synthetic_array(time, i_tf, radii, np.ones(8)) / (-2.0 / 15.0)
+    bz_raw = np.zeros((8, time.size))
+
+    # Without passing explicit config or bz_radial_offset, the defaults apply
+    result = process_impa(time, raw, i_tf, r=radii, b_z_raw=bz_raw)
+
+    assert result.bz_r is not None
+    np.testing.assert_allclose(result.bz_r, radii + 0.01)
+    assert result.provenance["gain"] == pytest.approx(-2.0 / 15.0)

vaft/machine_mapping/impa.py

@@ -145,7 +145,7 @@ def _channel_specs(config: Mapping[str, Any], shot: int) -> list[dict[str, Any]]
 
 def _resolve_gain(calibration: Mapping[str, Any], shot: int) -> float:
     """Return the Hall gain for ``shot``, honouring verified shot-era ranges."""
-    gain = float(calibration.get("gain", 2.0 / 15.0))
+    gain = float(calibration.get("gain", -2.0 / 15.0))
     for era in calibration.get("shot_era_overrides") or ():
         if int(era.get("min_shot", 0)) <= int(shot) <= int(era.get("max_shot", 0)):
             return float(era.get("gain", gain))
@@ -202,7 +202,6 @@ def _window_criteria(config: Mapping[str, Any]) -> TfWindowCriteria:
         pf_current_max=float(window.get("pf_current_max", defaults.pf_current_max)),
         min_duration=float(window.get("min_duration", defaults.min_duration)),
         tf_dynamic_range_min=float(window.get("tf_dynamic_range_min", defaults.tf_dynamic_range_min)),
-        max_relative_noise=float(window.get("max_relative_noise", defaults.max_relative_noise)),
         smoothing_samples=int(window.get("smoothing_samples", defaults.smoothing_samples)),
     )
 
@@ -439,15 +438,15 @@ def process_impa_shot(
         pitch=float(geometry.get("radial_pitch", 0.05)),
         r_bounds=(float(min(r_bounds)), float(max(r_bounds))),
         r0_initial=float(geometry.get("r0_initial", 0.4)),
-        max_normalized_rmse=float(quality.get("max_normalized_rmse", 0.1)),
+        max_normalized_rmse=float(quality.get("max_normalized_rmse", 0.15)),
         reference=reference,
         b_z_raw=inputs["bz_raw"],
         bz_channel_valid=inputs["bz_channel_valid"],
         fit_pitch=bool(geometry.get("fit_pitch", False)),
         max_crosstalk_angle_deg=float(crosstalk_config.get("max_angle_deg", 30.0)),
         min_crosstalk_r_squared=float(crosstalk_config.get("min_r_squared", 0.8)),
         bz_gain=config.get("calibration", {}).get("bz_gain"),
-        bz_radial_offset=float(geometry.get("bz_radial_offset", 0.0)),
+        bz_radial_offset=float(geometry.get("bz_radial_offset", 0.01)),
     )
     object.__setattr__(result, "provenance", {**result.provenance, "shot": int(shot)})
     return result, inputs

vaft/machine_mapping/vest.yaml

@@ -644,7 +644,6 @@
         pf_current_max: 500.0
         min_duration: 0.005
         tf_dynamic_range_min: 0.02
-        max_relative_noise: 0.5
         smoothing_samples: 25       # 1 ms: Ip/PF quiet must be sustained
       quality:
         # Set from the verified 2022-04-23 alignment shots, whose rigid-array

vaft/process/impa.py

@@ -166,7 +166,7 @@ class ImpaProcessingConfig:
     #: as a separate stage because the two legacy routines genuinely differ.
     position_lowpass_hz: float = 2_500.0
     #: Hall calibration factor [T/V] in the canonical VAFT sign convention.
-    gain: float = 2.0 / 15.0
+    gain: float = -2.0 / 15.0
     baseline: str = "first_sample"
     baseline_samples: int = 2_500
     tf_turns: int = 24
@@ -210,8 +210,6 @@ class TfWindowCriteria:
     #: Relative TF spread ``(max-min)/max|I_TF|`` below which the interval is
     #: usable but reported as poorly conditioned for a slope fit.
     tf_dynamic_range_min: float = 0.02
-    #: Per-channel sample-to-sample noise relative to the in-window spread.
-    max_relative_noise: float = 0.5
     #: Median-filter width applied to |Ip| and the PF peak before thresholding.
     #: "No plasma" is a sustained condition, so isolated noise spikes must not
     #: fragment an otherwise clean interval.  25 samples is 1 ms at 25 kHz.
@@ -616,7 +614,6 @@ def fit_impa_geometry(
     i_tf = np.asarray(i_tf, dtype=float)
     idx = np.asarray(window.indices, dtype=int)
     n_channels = b_measured.shape[0]
-    offsets = np.arange(n_channels) * float(pitch)
     observed = b_measured[:, idx]
     lower, upper = float(min(r_bounds)), float(max(r_bounds))
 
@@ -627,7 +624,6 @@ def fit_impa_geometry(
     if not usable.any():
         raise ValueError("No IMPA channel has finite samples inside the calibration window")
     fitted = observed[usable]
-    fitted_offsets = offsets[usable]
 
     # The array is rigid, so the physical spacing is fixed; a probe inserted at
     # an angle to the midplane projects it onto a shorter radial step, and the
@@ -975,7 +971,7 @@ def grade_impa_quality(
     coupling: ImpaCouplingFit | None,
     *,
     expected_channels: int = IMPA_CHANNEL_COUNT,
-    max_normalized_rmse: float = 0.1,
+    max_normalized_rmse: float = 0.15,
     r_bounds: Sequence[float] = (0.1, 0.9),
     pitch_tolerance: float = 0.01,
     window_reasons: Sequence[str] = (),
@@ -1177,15 +1173,15 @@ def process_impa(
     pitch: float = 0.05,
     r_bounds: Sequence[float] = (0.1, 0.9),
     r0_initial: float = 0.4,
-    max_normalized_rmse: float = 0.1,
+    max_normalized_rmse: float = 0.15,
     reference: ImpaResult | None = None,
     b_z_raw: np.ndarray | None = None,
     bz_channel_valid: np.ndarray | None = None,
     fit_pitch: bool = False,
     max_crosstalk_angle_deg: float = 30.0,
     min_crosstalk_r_squared: float = 0.8,
     bz_gain: float | None = None,
-    bz_radial_offset: float = 0.0,
+    bz_radial_offset: float = 0.01,
 ) -> ImpaResult:
     """Run the full single-shot IMPA pipeline.