feat: add voting discipline section below political compass

tests/test_political_compass.py

@@ -237,3 +237,131 @@ def test_pca_axis_orientation(monkeypatch):
     assert prog_y > cons_y, (
         f"Expected progressive parties (y={prog_y:.3f}) > conservative parties (y={cons_y:.3f}) on Y-axis"
     )
+
+
+# ---------------------------------------------------------------------------
+# Tests for compute_party_discipline
+# ---------------------------------------------------------------------------
+
+
+def _make_mp_votes_db():
+    """Create an in-memory DuckDB with mp_votes fixture data.
+
+    6 motions, 2 parties (SP, VVD), each with 4 MPs.
+    SP is perfectly disciplined (all 4 vote the same each time).
+    VVD has 1 dissident on 2 of 6 motions → Rice index = (4+4+4+4+3+3)/6/4 ≈ 0.917.
+    Dates span 2023-01-01 to 2023-12-31.
+    """
+    import duckdb
+
+    conn = duckdb.connect(":memory:")
+    conn.execute("""
+        CREATE TABLE mp_votes (
+            id INTEGER,
+            motion_id VARCHAR,
+            mp_name VARCHAR,
+            party VARCHAR,
+            vote VARCHAR,
+            date DATE,
+            created_at TIMESTAMP
+        )
+    """)
+    rows = []
+    dates = [
+        "2023-01-10",
+        "2023-03-15",
+        "2023-05-20",
+        "2023-07-25",
+        "2023-09-30",
+        "2023-11-05",
+    ]
+    sp_mps = ["Janssen, A.", "Pietersen, B.", "Willemsen, C.", "Hendriksen, D."]
+    vvd_mps = ["Adams, E.", "Bakker, F.", "Claassen, G.", "Dekker, H."]
+    for i, date in enumerate(dates, start=1):
+        m_id = f"M{i:03d}"
+        for mp in sp_mps:
+            rows.append((i * 10 + 1, m_id, mp, "SP", "voor", date, "2023-01-01"))
+        if i <= 4:
+            for mp in vvd_mps:
+                rows.append((i * 10 + 2, m_id, mp, "VVD", "voor", date, "2023-01-01"))
+        else:
+            for mp in vvd_mps[:3]:
+                rows.append((i * 10 + 2, m_id, mp, "VVD", "voor", date, "2023-01-01"))
+            rows.append(
+                (i * 10 + 3, m_id, vvd_mps[3], "VVD", "tegen", date, "2023-01-01")
+            )
+    conn.executemany("INSERT INTO mp_votes VALUES (?, ?, ?, ?, ?, ?, ?)", rows)
+    return conn
+
+
+def test_compute_party_discipline_basic(monkeypatch):
+    """compute_party_discipline returns correct Rice index for fixture data."""
+    import duckdb as _duckdb
+
+    fixture_conn = _make_mp_votes_db()
+
+    monkeypatch.setattr(_duckdb, "connect", lambda path, **kw: fixture_conn)
+
+    import importlib
+    import sys
+
+    if "streamlit" not in sys.modules:
+        import types
+
+        st_stub = types.ModuleType("streamlit")
+        st_stub.cache_data = lambda **kw: lambda f: f
+        sys.modules["streamlit"] = st_stub
+
+    import explorer as _explorer
+
+    importlib.reload(_explorer)
+
+    df = _explorer.compute_party_discipline(
+        db_path="dummy",
+        start_date="2023-01-01",
+        end_date="2023-12-31",
+    )
+
+    assert not df.empty
+    assert set(df.columns) >= {"party", "n_motions", "discipline"}
+
+    sp_row = df[df["party"] == "SP"].iloc[0]
+    vvd_row = df[df["party"] == "VVD"].iloc[0]
+
+    assert sp_row["n_motions"] == 6
+    assert sp_row["discipline"] == pytest.approx(1.0, abs=1e-6)
+
+    assert vvd_row["n_motions"] == 6
+    expected_vvd = (4 * 1.0 + 2 * 0.75) / 6
+    assert vvd_row["discipline"] == pytest.approx(expected_vvd, abs=1e-4)
+
+    assert (df["discipline"] >= 0).all() and (df["discipline"] <= 1).all()
+
+
+def test_compute_party_discipline_empty_range(monkeypatch):
+    """Returns empty DataFrame when no motions fall in the date range."""
+    import duckdb as _duckdb
+
+    fixture_conn = _make_mp_votes_db()
+    monkeypatch.setattr(_duckdb, "connect", lambda path, **kw: fixture_conn)
+
+    import importlib, sys
+
+    if "streamlit" not in sys.modules:
+        import types
+
+        st_stub = types.ModuleType("streamlit")
+        st_stub.cache_data = lambda **kw: lambda f: f
+        sys.modules["streamlit"] = st_stub
+
+    import explorer as _explorer
+
+    importlib.reload(_explorer)
+
+    df = _explorer.compute_party_discipline(
+        db_path="dummy",
+        start_date="2000-01-01",
+        end_date="2000-12-31",
+    )
+
+    assert df.empty