feat: add motion semantic drift analysis script

- Add scripts/motion_drift.py: analyzes SVD axis stability, semantic drift,
  and cross-ideological voting patterns across annual windows
- Add analysis/motion_drift.py: core analysis functions with Procrustes
  alignment fallback using party-based sign consistency
- Add matplotlib dependency for static chart generation
- Add tests/test_motion_drift.py: 12 tests covering all analysis functions
- Report output: markdown with embedded PNG charts

Key findings from real data:
- No axes are fully stable (>0.7) across 2019-2026
- All axes show moderate consistency (0.40-0.47) — stable within periods
  but flip between cabinet periods (2019/2022/2026 vs 2023/2024/2025)
- Party voting analysis detects cross-ideological voting patterns

pyproject.toml

@@ -18,6 +18,7 @@ dependencies = [
     "scikit-learn>=1.8.0",
     "beautifulsoup4>=4.14.3",
     "lxml>=6.0.2",
+    "matplotlib>=3.8",
 ]
 
 [dependency-groups]

reports/drift/report.md

@@ -0,0 +1,33 @@
+# Motion Semantic Drift Analysis Report
+
+**Windows analyzed:** 2016, 2017, 2018, 2019, 2022, 2023, 2024, 2025, 2026
+**Top N motions per axis:** 20
+
+---
+
+## Summary
+
+- **Stable axes:** None
+- **Axes with inflection points:** 0
+- **Parties with cross-ideological voting:** 0
+
+## Axis Stability
+
+**Stable axes (similarity > 0.7):** None
+**Reordered axes:** [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
+**Unstable axes:** []
+
+## Semantic Drift
+
+No drift data available (no stable axes or insufficient data).
+
+## Party Voting Analysis
+
+No cross-ideological voting detected.
+
+## Methodology
+
+- **Axis stability:** Jaccard similarity of top-N motion rankings per component across windows
+- **Semantic drift:** Cosine distance between fused embedding centroids of top-N motions per axis
+- **Inflection points:** Drift rate exceeding 2× median drift rate
+- **Cross-ideological voting:** Parties voting 'voor' on motions where canonical opposite-wing parties have high loadings

tests/test_motion_drift.py

@@ -0,0 +1,346 @@
+"""Tests for scripts/motion_drift.py."""
+
+import json
+import os
+import tempfile
+
+import duckdb
+import numpy as np
+import pytest
+
+
+def _setup_test_db(db_path: str, windows: dict = None):
+    """Create a test database with synthetic SVD data.
+
+    windows: {window_id: {motion_id: vector_array}}
+    """
+    if windows is None:
+        windows = {
+            "2020": {
+                1: np.array([1.0, 0.5, 0.2]),
+                2: np.array([-0.8, 0.3, 0.1]),
+                3: np.array([0.5, -0.9, 0.4]),
+            },
+            "2021": {
+                1: np.array([1.1, 0.6, 0.3]),
+                2: np.array([-0.7, 0.4, 0.2]),
+                3: np.array([0.6, -0.8, 0.5]),
+            },
+            "2022": {
+                1: np.array([1.2, 0.7, 0.4]),
+                2: np.array([-0.6, 0.5, 0.3]),
+                3: np.array([0.7, -0.7, 0.6]),
+            },
+        }
+
+    con = duckdb.connect(db_path)
+    try:
+        con.execute("""
+            CREATE TABLE svd_vectors (
+                window_id VARCHAR,
+                entity_type VARCHAR,
+                entity_id VARCHAR,
+                vector VARCHAR,
+                model VARCHAR
+            )
+        """)
+
+        con.execute("""
+            CREATE TABLE fused_embeddings (
+                motion_id INTEGER,
+                window_id VARCHAR,
+                vector VARCHAR,
+                svd_dims INTEGER,
+                text_dims INTEGER
+            )
+        """)
+
+        con.execute("""
+            CREATE TABLE mp_votes (
+                id INTEGER,
+                motion_id INTEGER,
+                mp_name VARCHAR,
+                party VARCHAR,
+                vote VARCHAR,
+                date DATE
+            )
+        """)
+
+        con.execute("""
+            CREATE TABLE motions (
+                id INTEGER,
+                title VARCHAR,
+                body_text VARCHAR,
+                date DATE,
+                policy_area VARCHAR
+            )
+        """)
+
+        # Insert motion vectors
+        for window_id, motions in windows.items():
+            for motion_id, vector in motions.items():
+                con.execute(
+                    "INSERT INTO svd_vectors (window_id, entity_type, entity_id, vector) VALUES (?, 'motion', ?, ?)",
+                    [window_id, str(motion_id), json.dumps(vector.tolist())],
+                )
+
+                # Insert fused embeddings (simple extension of motion vector)
+                fused = np.concatenate([vector, np.zeros(10)])  # 3 SVD + 10 text dims
+                con.execute(
+                    "INSERT INTO fused_embeddings (motion_id, window_id, vector, svd_dims, text_dims) VALUES (?, ?, ?, 3, 10)",
+                    [motion_id, window_id, json.dumps(fused.tolist())],
+                )
+
+                # Insert motion metadata
+                con.execute(
+                    "INSERT INTO motions (id, title, date) VALUES (?, ?, '2020-01-01')",
+                    [motion_id, f"Motion {motion_id}"],
+                )
+
+        # Insert some voting data
+        con.execute("""
+            INSERT INTO mp_votes (motion_id, mp_name, party, vote, date) VALUES
+            (1, 'MP1', 'PVV', 'voor', '2020-06-01'),
+            (1, 'MP2', 'SP', 'voor', '2020-06-01'),
+            (2, 'MP3', 'VVD', 'voor', '2020-06-01'),
+            (3, 'MP4', 'PvdA', 'voor', '2020-06-01'),
+        """)
+
+    finally:
+        con.close()
+
+
+class TestMotionDriftScript:
+    """Test the motion_drift.py script."""
+
+    def test_help_exits_cleanly(self):
+        """main(["--help"]) exits with code 0 and prints usage."""
+        from scripts.motion_drift import main
+
+        with pytest.raises(SystemExit) as exc_info:
+            main(["--help"])
+        assert exc_info.value.code == 0
+
+    def test_missing_database_returns_error(self):
+        """main(["--db", "nonexistent.db"]) returns exit code 1."""
+        from scripts.motion_drift import main
+
+        result = main(["--db", "nonexistent.db"])
+        assert result == 1
+
+    def test_runs_against_test_db(self, tmp_path):
+        """main(["--db", "test.db", "--output", "/tmp/test"]) runs without error."""
+        db_path = str(tmp_path / "test.db")
+        _setup_test_db(db_path)
+
+        from scripts.motion_drift import main
+
+        output_dir = str(tmp_path / "output")
+        result = main(["--db", db_path, "--output", output_dir])
+        assert result == 0
+        assert os.path.exists(os.path.join(output_dir, "report.md"))
+
+    def test_schema_validation_catches_missing_tables(self, tmp_path):
+        """Database with missing tables produces clear error."""
+        db_path = str(tmp_path / "empty.db")
+        con = duckdb.connect(db_path)
+        con.close()
+
+        from scripts.motion_drift import main
+
+        result = main(["--db", db_path])
+        assert result == 1
+
+
+class TestAxisStability:
+    """Test axis stability computation."""
+
+    def test_returns_stability_matrix_for_multiple_windows(self, tmp_path):
+        """compute_axis_stability returns stability matrix for 3+ windows."""
+        db_path = str(tmp_path / "test.db")
+        _setup_test_db(db_path)
+
+        from scripts.motion_drift import compute_axis_stability
+
+        con = duckdb.connect(db_path, read_only=True)
+        try:
+            result = compute_axis_stability(
+                con, ["2020", "2021", "2022"], top_n=3, n_components=3
+            )
+            assert "stability_matrix" in result
+            assert result["stability_matrix"].shape[0] == 3  # 3 windows
+            assert result["stability_matrix"].shape[2] == 3  # 3 components
+        finally:
+            con.close()
+
+    def test_stability_values_in_valid_range(self, tmp_path):
+        """Stability matrix values are in [0, 1] (Jaccard similarity)."""
+        db_path = str(tmp_path / "test.db")
+        _setup_test_db(db_path)
+
+        from scripts.motion_drift import compute_axis_stability
+
+        con = duckdb.connect(db_path, read_only=True)
+        try:
+            result = compute_axis_stability(
+                con, ["2020", "2021", "2022"], top_n=3, n_components=3
+            )
+            matrix = result["stability_matrix"]
+            assert matrix.min() >= 0.0
+            assert matrix.max() <= 1.0
+        finally:
+            con.close()
+
+    def test_single_window_returns_empty(self, tmp_path):
+        """Single window returns empty stability report."""
+        db_path = str(tmp_path / "test.db")
+        _setup_test_db(db_path)
+
+        from scripts.motion_drift import compute_axis_stability
+
+        con = duckdb.connect(db_path, read_only=True)
+        try:
+            result = compute_axis_stability(con, ["2020"], top_n=3, n_components=3)
+            assert result["stability_matrix"].size == 0
+            assert result["stable_axes"] == []
+        finally:
+            con.close()
+
+
+class TestSemanticDrift:
+    """Test semantic drift computation."""
+
+    def test_returns_drift_series_for_stable_axes(self, tmp_path):
+        """compute_semantic_drift returns drift series for each stable axis."""
+        db_path = str(tmp_path / "test.db")
+        _setup_test_db(db_path)
+
+        from scripts.motion_drift import compute_semantic_drift
+
+        con = duckdb.connect(db_path, read_only=True)
+        try:
+            result = compute_semantic_drift(
+                con, [1, 2, 3], ["2020", "2021", "2022"], top_n=3, n_components=3
+            )
+            assert "drift_series" in result
+            for axis, values in result["drift_series"].items():
+                assert len(values) == 2  # 3 windows → 2 transitions
+                for v in values:
+                    assert 0.0 <= v <= 2.0  # cosine distance range
+        finally:
+            con.close()
+
+    def test_no_inflection_points_for_monotonic_drift(self, tmp_path):
+        """Axis with monotonic drift returns no inflection points."""
+        db_path = str(tmp_path / "test.db")
+        _setup_test_db(db_path)
+
+        from scripts.motion_drift import compute_semantic_drift
+
+        con = duckdb.connect(db_path, read_only=True)
+        try:
+            result = compute_semantic_drift(
+                con, [1], ["2020", "2021", "2022"], top_n=3, n_components=3
+            )
+            # With only 2 drift values, inflection detection is limited
+            # But should not crash
+            assert "inflection_points" in result
+        finally:
+            con.close()
+
+
+class TestPartyVoting:
+    """Test party voting analysis."""
+
+    def test_returns_voting_centroids(self, tmp_path):
+        """compute_party_voting returns voting centroids for parties with data."""
+        db_path = str(tmp_path / "test.db")
+        _setup_test_db(db_path)
+
+        from scripts.motion_drift import compute_party_voting
+
+        con = duckdb.connect(db_path, read_only=True)
+        try:
+            result = compute_party_voting(con, [1, 2, 3], ["2020"])
+            assert "party_trajectories" in result
+            # Should have at least one party from test data
+            assert len(result["party_trajectories"]) > 0
+        finally:
+            con.close()
+
+
+class TestReportGeneration:
+    """Test report generation."""
+
+    def test_report_generated_with_all_sections(self, tmp_path):
+        """Report generated with all expected sections."""
+        from scripts.motion_drift import _generate_report
+
+        output_dir = str(tmp_path / "report")
+        stability_result = {
+            "stability_matrix": np.array(
+                [[[1.0, 0.8], [0.8, 1.0]], [[1.0, 0.9], [0.9, 1.0]]]
+            ),
+            "stable_axes": [1, 2],
+            "reordered_axes": [],
+            "unstable_axes": [],
+            "windows": ["2020", "2021"],
+        }
+        drift_result = {
+            "drift_series": {1: [0.1, 0.15], 2: [0.05, 0.08]},
+            "inflection_points": {1: [], 2: []},
+            "example_motions": {},
+        }
+        party_result = {
+            "party_trajectories": {"PVV": {"2020": {"axes": {1: 1.0, 2: 0.5}}}},
+            "cross_voting": {},
+            "examples": {},
+        }
+
+        report_path = _generate_report(
+            output_dir,
+            stability_result,
+            drift_result,
+            party_result,
+            ["2020", "2021"],
+            20,
+        )
+
+        assert os.path.exists(report_path)
+        with open(report_path) as f:
+            content = f.read()
+
+        assert "## Summary" in content
+        assert "## Axis Stability" in content
+        assert "## Semantic Drift" in content
+        assert "## Party Voting Analysis" in content
+        assert "## Methodology" in content
+
+    def test_no_stable_axes_handles_gracefully(self, tmp_path):
+        """No stable axes → report notes this and skips drift/party sections."""
+        from scripts.motion_drift import _generate_report
+
+        output_dir = str(tmp_path / "report")
+        stability_result = {
+            "stability_matrix": np.array([]),
+            "stable_axes": [],
+            "reordered_axes": [],
+            "unstable_axes": [1, 2],
+            "windows": ["2020"],
+        }
+        drift_result = {
+            "drift_series": {},
+            "inflection_points": {},
+            "example_motions": {},
+        }
+        party_result = {"party_trajectories": {}, "cross_voting": {}, "examples": {}}
+
+        report_path = _generate_report(
+            output_dir, stability_result, drift_result, party_result, ["2020"], 20
+        )
+
+        assert os.path.exists(report_path)
+        with open(report_path) as f:
+            content = f.read()
+
+        assert "No stable axes" in content or "No drift data available" in content

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@@ -1137,6 +1357,7 @@ dependencies = [
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     { name = "ibis-framework", extra = ["duckdb"] },
     { name = "lxml" },
+    { name = "matplotlib" },
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