feat: add axis classifier with party ideology reference data

classify_axes() correlates per-party PCA positions against party_ideologies.csv
to assign honest dynamic labels (Links-Rechts, Coalitie-Oppositie, etc.)
instead of always assuming the first PCA axis is left-right.

tests/test_political_compass.py

@@ -365,3 +365,107 @@ def test_compute_party_discipline_empty_range(monkeypatch):
     )
 
     assert df.empty
+
+
+# ---------------------------------------------------------------------------
+# Tests for analysis.axis_classifier
+# ---------------------------------------------------------------------------
+
+import importlib
+
+
+def _fresh_classifier(monkeypatch):
+    """Import axis_classifier with cleared module-level caches."""
+    import analysis.axis_classifier as _cls
+
+    monkeypatch.setattr(_cls, "_ideology_cache", None)
+    monkeypatch.setattr(_cls, "_coalition_cache", None)
+    return _cls
+
+
+def test_axis_label_left_right(tmp_path, monkeypatch):
+    """Positions that closely correlate with left_right scores → label 'Links–Rechts'."""
+    _cls = _fresh_classifier(monkeypatch)
+
+    (tmp_path / "party_ideologies.csv").write_text(
+        "party,left_right,progressive\n"
+        "VVD,0.65,0.10\n"
+        "PvdA,-0.70,0.75\n"
+        "SP,-0.90,0.50\n"
+        "PVV,0.90,-0.50\n"
+        "D66,-0.10,0.85\n"
+        "CDA,0.25,-0.45\n"
+    )
+    (tmp_path / "coalition_membership.csv").write_text("window_id,party\n")
+
+    # X values are the party's left_right scores — perfect correlation
+    positions_by_window = {
+        "2022": {
+            "VVD": (0.65, 0.10),
+            "PvdA": (-0.70, 0.20),
+            "SP": (-0.90, 0.30),
+            "PVV": (0.90, -0.10),
+            "D66": (-0.10, 0.40),
+            "CDA": (0.25, -0.20),
+        }
+    }
+    axes = {"x_axis": None, "y_axis": None, "method": "pca"}
+
+    result = _cls.classify_axes(positions_by_window, axes, str(tmp_path / "motions.db"))
+
+    assert result["x_label"] == "Links\u2013Rechts"
+    assert result["x_quality"]["2022"] >= 0.65
+
+
+def test_axis_label_coalition_dominant(tmp_path, monkeypatch):
+    """Positions that match coalition pattern but NOT left-right → 'Coalitie–Oppositie'."""
+    _cls = _fresh_classifier(monkeypatch)
+
+    (tmp_path / "party_ideologies.csv").write_text(
+        "party,left_right,progressive\n"
+        "VVD,0.65,0.10\n"
+        "PvdA,-0.70,0.75\n"
+        "SP,-0.90,0.50\n"
+        "PVV,0.90,-0.50\n"
+        "D66,-0.10,0.85\n"
+        "CDA,0.25,-0.45\n"
+    )
+    # 2016: Rutte II coalition = VVD + PvdA
+    (tmp_path / "coalition_membership.csv").write_text(
+        "window_id,party\n2016,VVD\n2016,PvdA\n"
+    )
+
+    # Coalition parties (VVD + PvdA) at x ≈ +1, opposition at x ≈ -1.
+    # VVD (right) and PvdA (left) are both near +1 → low left_right correlation
+    # but high coalition correlation.
+    positions_by_window = {
+        "2016": {
+            "VVD": (0.95, 0.10),
+            "PvdA": (0.90, 0.20),
+            "SP": (-0.85, 0.30),
+            "PVV": (-0.95, -0.10),
+            "D66": (-0.80, 0.40),
+            "CDA": (-0.75, -0.20),
+        }
+    }
+    axes = {"x_axis": None, "y_axis": None, "method": "pca"}
+
+    result = _cls.classify_axes(positions_by_window, axes, str(tmp_path / "motions.db"))
+
+    assert result["x_label"] == "Coalitie\u2013Oppositie"
+    assert "coalitie" in result["x_interpretation"]["2016"].lower()
+
+
+def test_axis_classifier_missing_csv(tmp_path, monkeypatch):
+    """Missing party_ideologies.csv → returns axes dict unchanged, no exception."""
+    _cls = _fresh_classifier(monkeypatch)
+
+    # No CSVs written — directory exists but files do not
+    positions_by_window = {"2022": {"VVD": (1.0, 0.5), "PvdA": (-1.0, 0.3)}}
+    axes = {"x_axis": None, "y_axis": None, "method": "pca"}
+
+    result = _cls.classify_axes(positions_by_window, axes, str(tmp_path / "motions.db"))
+
+    # Must not crash and must return the original axes dict unchanged
+    assert result is axes
+    assert "x_label" not in result