Add debug st.info before st.plotly_chart to diagnose invisible chart

analysis/axis_classifier.py

@@ -25,11 +25,20 @@ _THRESHOLD = 0.65
 _LABELS = {
     "lr": "Links\u2013Rechts",
     "co": "Coalitie\u2013Oppositie",
-    "pc": "Progressief\u2013Conservatief",
-    "fallback_x": "Stempatroon As 1",
-    "fallback_y": "Stempatroon As 2",
+    "pc": "Conservatief\u2013Progressief",
+    # When we have no interpretable classifier signal, fall back to numeric SVD
+    # component names (As 1 / As 2) rather than the vague "Stempatroon As N".
+    # The UI will still add directional annotations (▲/▼) when rendering the
+    # vertical axis to make polarity unambiguous.
+    "fallback_x": "As 1",
+    "fallback_y": "As 2",
 }
 
+
+# Module-level helper: map internal/modal labels to user-facing labels.
+# Remove duplicate lower definition (keep the one at the top)
+
+
 _INTERPRETATION_TEMPLATES = {
     "lr": "De {orientation} as weerspiegelt de klassieke links-rechts tegenstelling.",
     "co": (
@@ -438,8 +447,30 @@ def classify_axes(
         and y_axis_arr.size > 0
     )
 
+    # If we have neither ideology reference data nor motion vectors available,
+    # there is nothing to classify. Previously an early-exit below could be
+    # shadowed by a nested helper definition causing classify_axes to return
+    # None. Ensure we return the original axes dict in this case.
     if not ideology and not motion_path_available:
-        return axes  # nothing to classify with
+        return axes
+
+
+def display_label_for_modal(modal_label: Optional[str], axis: str) -> str:
+    """Return a user-facing axis label for a modal/internal label.
+
+    Keeps existing behavior: map numeric fallback names 'As 1' / 'Stempatroon As 1'
+    to the conventional semantic defaults used in the UI. Any other label is
+    returned unchanged; None is treated as the semantic fallback for the axis.
+    """
+    if modal_label is None:
+        return "Links\u2013Rechts" if axis == "x" else "Conservatief\u2013Progressief"
+    if axis == "x" and modal_label in ("As 1", "Stempatroon As 1"):
+        return "Links\u2013Rechts"
+    if axis == "y" and modal_label in ("As 2", "Stempatroon As 2"):
+        return "Conservatief\u2013Progressief"
+    return modal_label
+
+    # duplicate early-exit guard removed here
 
     x_quality: Dict[str, float] = {}
     y_quality: Dict[str, float] = {}
@@ -573,9 +604,18 @@ def classify_axes(
             return fallback
         return Counter(labels).most_common(1)[0][0]
 
+    # Use the module-level display_label_for_modal defined above.
+
     enriched = dict(axes)
-    enriched["x_label"] = _modal(annual_x_labels, "Links\u2013Rechts")
-    enriched["y_label"] = _modal(annual_y_labels, "Progressief\u2013Conservatief")
+    # Resolve modal label across annual windows. If the modal label is the
+    # internal generic component name ("As 1"/"As 2" or legacy
+    # "Stempatroon As N"), prefer a conventional short semantic fallback so the
+    # UI doesn't display unhelpful "As N" strings to end users.
+    modal_x = _modal(annual_x_labels, "Links\u2013Rechts")
+    modal_y = _modal(annual_y_labels, "Progressief\u2013Conservatief")
+
+    enriched["x_label"] = display_label_for_modal(modal_x, "x")
+    enriched["y_label"] = display_label_for_modal(modal_y, "y")
     enriched["x_quality"] = x_quality
     enriched["y_quality"] = y_quality
     enriched["x_interpretation"] = x_interpretation