Fix CI review R13: preserve NaN-SE contract on degenerate-cohort survey fits

_plugin_se returns NaN when the cohort-recentered IF is empty or
identically zero (documented degenerate-cohort contract — every
variance-eligible group is its own (D_{g,1}, F_g, S_g) singleton).
_survey_se_from_group_if only rejected negative variance, so on the
same panel it computed sqrt(0) = 0.0, suppressed the degenerate-cohort
warning (gated on np.isnan(overall_se)), and exposed a false zero SE.
The bug affected every surface routed through _compute_se — top-level
ATT, joiners/leavers, multi-horizon ATT, placebos, and derived
normalized/cumulated SEs.

Mirror the _plugin_se contract: short-circuit to NaN when U_centered
is empty or sum(U_centered**2) <= 0, before delegating to
compute_survey_if_variance.

Added TestSurveyWithinGroupValidation.test_degenerate_cohort_survey_se_is_nan:
4 groups × 5 periods, each switching at a unique F_g so every cohort
is a singleton; asserts overall_se is NaN (not 0.0) and that the
degenerate-cohort warning fires under the survey path.

All 272 targeted tests pass.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

Author: igerber

diff_diff/chaisemartin_dhaultfoeuille.py

@@ -4874,6 +4874,18 @@ def _survey_se_from_group_if(
     """
     from diff_diff.survey import compute_survey_if_variance
 
+    # Degenerate-cohort contract (mirror _plugin_se): when the centered
+    # IF is empty or every cohort is a singleton (→ recentered IF is
+    # identically zero), the variance is unidentified. Return NaN
+    # rather than sqrt(0)=0 so the fit-time warning fires and
+    # inference stays NaN-consistent across every surface routed
+    # through _compute_se (overall, joiners/leavers, multi-horizon
+    # ATT, placebos, normalized/cumulated, heterogeneity).
+    if U_centered.size == 0:
+        return float("nan")
+    if float((U_centered ** 2).sum()) <= 0:
+        return float("nan")
+
     group_ids = obs_survey_info["group_ids"]
     weights = obs_survey_info["weights"]
     resolved = obs_survey_info["resolved"]

tests/test_survey_dcdh.py

@@ -1117,6 +1117,52 @@ def test_auto_inject_psu_matches_explicit_group_psu(self, base_data):
             == r_explicit.survey_metadata.df_survey
         )
 
+    def test_degenerate_cohort_survey_se_is_nan(self):
+        """When every variance-eligible group is its own singleton
+        cohort (D_{g,1}, F_g, S_g), the cohort-recentered IF is
+        identically zero. The survey SE path must return NaN (not 0.0)
+        so the degenerate-cohort warning fires and inference stays
+        NaN-consistent — matching the _plugin_se contract documented
+        in REGISTRY.md."""
+        # 4 groups × 5 periods, each group switches at a unique F_g so
+        # the (D_{g,1}=0, F_g, S_g=+1) cohort key is unique per group.
+        rows = []
+        for g, f_switch in enumerate([1, 2, 3, 4]):
+            for t in range(5):
+                d = 1 if t >= f_switch else 0
+                y = float(g) + 0.5 * t + float(d)
+                rows.append({
+                    "group": g,
+                    "period": t,
+                    "treatment": d,
+                    "outcome": y,
+                    "pw": 1.0,
+                })
+        df_ = pd.DataFrame(rows)
+        sd = SurveyDesign(weights="pw")
+
+        import warnings as _warnings
+        with _warnings.catch_warnings(record=True) as w:
+            _warnings.simplefilter("always")
+            result = ChaisemartinDHaultfoeuille(seed=1).fit(
+                df_,
+                outcome="outcome", group="group",
+                time="period", treatment="treatment",
+                survey_design=sd,
+            )
+
+        # overall_se must be NaN on degenerate cohorts (not 0.0)
+        assert np.isnan(result.overall_se), (
+            f"Degenerate-cohort survey overall_se must be NaN, "
+            f"got {result.overall_se}"
+        )
+        # Degenerate-cohort warning must fire
+        assert any(
+            "cohort" in str(wi.message).lower()
+            and "identically zero" in str(wi.message).lower()
+            for wi in w
+        ), "Expected degenerate-cohort warning to fire under survey path"
+
     def test_subpopulation_preserves_full_design_df_survey(self, base_data):
         """Under dCDH auto-inject, zero-weighting an entire group must not
         shrink df_survey below what the full-design PSU count would give.