test: add trajectory pipeline integration test

tests/test_trajectories_pipeline_integration.py

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+"""Integration test: full trajectory pipeline produces non-empty plot."""
+
+import pytest
+
+from explorer import load_positions, load_party_map, select_trajectory_plot_data
+from explorer_helpers import compute_party_centroids
+
+
+def test_trajectory_pipeline_produces_traces():
+    """Regression: trajectories must produce colored traces, not empty charts."""
+    db_path = "data/motions.db"
+    window_size = "annual"
+
+    # Stage 1: load positions
+    positions_by_window, _ = load_positions(db_path, window_size)
+    assert len(positions_by_window) > 0, "Expected at least one window"
+    total_mps = sum(len(v) for v in positions_by_window.values())
+    assert total_mps > 0, "Expected MPs in windows"
+
+    # Stage 2: load party map
+    party_map = load_party_map(db_path)
+    assert len(party_map) > 0, "Expected party map entries"
+
+    # Stage 3: compute centroids
+    windows = list(positions_by_window.keys())
+    centroids, mp_positions = compute_party_centroids(
+        positions_by_window, party_map, windows
+    )
+    assert len(centroids) > 0, "Expected at least one party centroid"
+
+    # Stage 4: select trajectory plot data (default party selection)
+    # Use the same defaults as build_trajectories_tab: CDA, D66, VVD if available
+    default_parties = [p for p in ["CDA", "D66", "VVD"] if p in centroids]
+    if not default_parties:
+        default_parties = list(centroids.keys())[:3]
+
+    fig, trace_count, banner = select_trajectory_plot_data(
+        positions_by_window,
+        party_map,
+        windows,
+        selected_parties=default_parties,
+        smooth_alpha=0.35,
+    )
+
+    # Assertions
+    assert trace_count > 0, (
+        f"Expected traces but got trace_count={trace_count}, banner={banner}"
+    )
+    assert banner is None, f"Expected no fallback banner but got: {banner}"
+    assert len(fig.data) == trace_count, (
+        f"fig.data ({len(fig.data)}) should equal trace_count ({trace_count})"
+    )
+
+    # Verify traces have real coordinates (not all NaN)
+    for trace in fig.data:
+        assert len(trace.x) > 0, f"Trace {trace.name} has no x values"
+        assert len(trace.y) > 0, f"Trace {trace.name} has no y values"
+        # At least some values should be real (not NaN)
+        import math
+
+        real_x = sum(
+            1 for v in trace.x if not (v is None or (isinstance(v, float) and v != v))
+        )  # v != v is True only for NaN
+        real_y = sum(
+            1 for v in trace.y if not (v is None or (isinstance(v, float) and v != v))
+        )
+        assert real_x > 0, f"Trace {trace.name} has all NaN x values"
+        assert real_y > 0, f"Trace {trace.name} has all NaN y values"
+
+
+def test_trajectory_helper_skips_second_loop():
+    """Regression: when select_trajectory_plot_data succeeds, build_trajectories_tab
+    should NOT add duplicate traces via the fallback loop.
+
+    This test verifies that the helper produces clean output without relying on
+    the second loop in build_trajectories_tab.
+    """
+    db_path = "data/motions.db"
+    window_size = "annual"
+
+    positions_by_window, _ = load_positions(db_path, window_size)
+    party_map = load_party_map(db_path)
+    windows = list(positions_by_window.keys())
+    centroids, _ = compute_party_centroids(positions_by_window, party_map, windows)
+
+    # Use 6 parties like the app's multiselect
+    selected = list(centroids.keys())[:6]
+
+    fig, trace_count, banner = select_trajectory_plot_data(
+        positions_by_window,
+        party_map,
+        windows,
+        selected_parties=selected,
+        smooth_alpha=0.35,
+    )
+
+    # Should produce exactly the number of selected parties (or fewer if some have all-NaN)
+    assert trace_count <= len(selected), (
+        f"trace_count ({trace_count}) should not exceed selected ({len(selected)})"
+    )
+    assert banner is None, "No fallback should be needed with valid data"
+    assert len(fig.data) == trace_count