Fix ContinuousDiD fweight TSL scaling and BaconDecomposition empty-cell guard from PR #226 review (round 6)

- ContinuousDiD: rescale IFs by unit-level total survey mass
  (unit_resolved.weights.sum()) instead of hard-coded n_units, so TSL
  SEs are correct for fweight designs where mass != n_units
- BaconDecomposition: add empty-cell guard in _compute_treated_vs_never
  before np.average() to prevent crashes on unbalanced/filtered panels

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

Author: igerber

diff_diff/bacon.py

@@ -822,6 +822,15 @@ def _compute_treated_vs_never(
         never_pre_mask = never_mask & df[time].isin(pre_periods)
         never_post_mask = never_mask & df[time].isin(post_periods)
 
+        # Guard against empty cells (unbalanced/filtered panels)
+        if not (
+            np.any(treated_pre_mask)
+            and np.any(treated_post_mask)
+            and np.any(never_pre_mask)
+            and np.any(never_post_mask)
+        ):
+            return None
+
         treated_pre = np.average(y[treated_pre_mask], weights=w[treated_pre_mask])
         treated_post = np.average(y[treated_post_mask], weights=w[treated_post_mask])
         never_pre = np.average(y[never_pre_mask], weights=w[never_pre_mask])

diff_diff/continuous_did.py

@@ -639,8 +639,9 @@ def fit(
                         # Compute SE: survey-aware TSL or standard sqrt(sum(IF^2))
                         if unit_resolved_es is not None:
                             X_ones_es = np.ones((n_units, 1))
-                            # Rescale IFs from 1/n convention to score scale for TSL
-                            if_es_tsl = if_es * n_units
+                            # Rescale IFs by total survey mass (not n_units) for fweight support
+                            tsl_scale_es = float(unit_resolved_es.weights.sum())
+                            if_es_tsl = if_es * tsl_scale_es
                             vcov_es = compute_survey_vcov(X_ones_es, if_es_tsl, unit_resolved_es)
                             es_se = float(np.sqrt(np.abs(vcov_es[0, 0])))
                         else:
@@ -1198,13 +1199,14 @@ def _compute_analytical_se(
             # Rescale IFs from 1/n convention to score scale for TSL sandwich.
             # The per-unit IFs contain internal 1/n_t, 1/n_c scaling (for the
             # unweighted SE = sqrt(sum(IF^2)) convention). compute_survey_vcov
-            # applies its own (X'WX)^{-1} ≈ 1/n bread, which would double-count.
-            # Multiplying by n_units undoes the internal scaling so TSL gives
-            # the correct variance.
-            if_att_glob_tsl = if_att_glob * n_units
-            if_acrt_glob_tsl = if_acrt_glob * n_units
-            if_att_d_tsl = if_att_d * n_units
-            if_acrt_d_tsl = if_acrt_d * n_units
+            # applies its own (X'WX)^{-1} bread, which would double-count.
+            # Rescale by the unit-level total survey mass (= n_units for
+            # pweight/aweight, but can differ for fweight).
+            tsl_scale = float(unit_resolved.weights.sum())
+            if_att_glob_tsl = if_att_glob * tsl_scale
+            if_acrt_glob_tsl = if_acrt_glob * tsl_scale
+            if_att_d_tsl = if_att_d * tsl_scale
+            if_acrt_d_tsl = if_acrt_d * tsl_scale
 
             # Overall ATT SE via compute_survey_vcov
             vcov_att = compute_survey_vcov(X_ones, if_att_glob_tsl, unit_resolved)