feat(explorer): harden load_party_axis_scores (close DB, deterministic params)

Plan: docs/superpowers/plans/2026-03-24-svd-tab-redesign.md

explorer.py

@@ -189,16 +189,21 @@ def load_party_axis_scores(db_path: str) -> Dict[str, List[float]]:
     Returns:
         {party_name: [float * k]}  — k = 50 for the canonical 2025 window
     """
+    con = None
     try:
+        # Use a deterministic, ordered list for parameter binding
+        party_list = sorted(CURRENT_PARLIAMENT_PARTIES)
+        if not party_list:
+            return {}
+
         con = duckdb.connect(database=db_path, read_only=True)
-        placeholders = ", ".join("?" for _ in CURRENT_PARLIAMENT_PARTIES)
+        placeholders = ", ".join("?" for _ in party_list)
         rows = con.execute(
             f"SELECT entity_id, vector FROM svd_vectors "
             f"WHERE entity_type='mp' AND window_id='2025' "
             f"AND entity_id IN ({placeholders})",
-            list(CURRENT_PARLIAMENT_PARTIES),
+            party_list,
         ).fetchall()
-        con.close()
         return {
             row[0]: json.loads(row[1]) if isinstance(row[1], str) else list(row[1])
             for row in rows
@@ -206,6 +211,9 @@ def load_party_axis_scores(db_path: str) -> Dict[str, List[float]]:
     except Exception:
         logger.exception("Failed to load party axis scores")
         return {}
+    finally:
+        if con is not None:
+            con.close()
 
 
 @st.cache_data(show_spinner="Moties laden…")
@@ -231,6 +239,97 @@ def load_motions_df(db_path: str) -> pd.DataFrame:
         con.close()
 
 
+def _render_party_axis_chart(
+    party_scores: Dict[str, List[float]], comp_sel: int
+) -> None:
+    """Render a 1D horizontal Plotly scatter of party positions on SVD axis `comp_sel`.
+
+    party_scores: mapping party -> list-like vector (50-dim)
+    comp_sel: 1-based component index
+    """
+    # Validate component selection
+    if not isinstance(comp_sel, int) or comp_sel < 1:
+        st.caption("_Ongeldige SVD-as geselecteerd._")
+        return
+
+    if not party_scores:
+        st.caption("_Partijdata niet beschikbaar_")
+        return
+
+    axis_idx = comp_sel - 1
+
+    parties: List[str] = []
+    xs: List[float] = []
+
+    for party, vec in party_scores.items():
+        # Ensure vec is indexable/sequence-like
+        if not isinstance(vec, (list, tuple, np.ndarray)):
+            # skip malformed entries
+            continue
+        try:
+            raw = vec[axis_idx]
+            # Convert to float safely
+            val = float(raw)
+        except Exception:
+            # skip entries that cannot be indexed or converted
+            continue
+        parties.append(party)
+        xs.append(val)
+
+    if not xs:
+        st.caption("_Partijdata niet beschikbaar_")
+        return
+
+    try:
+        x_min = min(xs)
+        x_max = max(xs)
+    except Exception:
+        st.caption("_Onvoldoende gegevens om asbereik te berekenen_")
+        return
+
+    # If min == max, apply symmetric padding around the value.
+    if x_min == x_max:
+        padding = 0.5 if x_min == 0 else abs(x_min) * 0.1
+        if padding <= 0:
+            padding = 0.5
+        x_min = x_min - padding
+        x_max = x_max + padding
+    else:
+        # Expand range slightly for visual padding
+        x_min = x_min * 1.15
+        x_max = x_max * 1.15
+
+    # Build horizontal scatter: y is constant (0) but offset for label placement
+    ys = [0 for _ in xs]
+
+    fig = go.Figure()
+    fig.add_trace(
+        go.Scatter(
+            x=xs,
+            y=ys,
+            mode="markers+text",
+            text=parties,
+            textposition="top center",
+            marker=dict(
+                size=10, color=[PARTY_COLOURS.get(p, "#9E9E9E") for p in parties]
+            ),
+            hovertemplate="%{text}<br>x: %{x:.3f}<extra></extra>",
+        )
+    )
+
+    fig.update_layout(
+        title=f"Partijposities op SVD-as {comp_sel}",
+        xaxis_title="Negatief ← — → Positief",
+        yaxis=dict(visible=False),
+        xaxis=dict(range=[x_min, x_max]),
+        height=300,
+        margin=dict(t=40, b=40, l=40, r=40),
+        showlegend=False,
+    )
+
+    st.plotly_chart(fig, use_container_width=True)
+
+
 def query_similar(
     db_path: str,
     source_motion_id: int,