---
title: SVD component scores inconsistent between single-window and trajectory views
date: "2026-05-04"
category: logic-errors
module: analysis
problem_type: logic_error
component: service_object
severity: high
symptoms:
  - "Party position numbers differ between Enkel venster and Tijdtraject views for the same SVD component and window"
  - "Displayed values have opposite signs for flipped components even when underlying data is identical"
root_cause: logic_error
resolution_type: code_fix
tags:
  - svd
  - pca
  - alignment
  - visualization
  - data-consistency
---

# SVD component scores inconsistent between single-window and trajectory views

## Problem

In the parliamentary explorer's "SVD Components" tab, party position numbers differed between the "Enkel venster" (single window) view and the "Tijdtraject" (time trajectory) view for the SAME component and SAME window. Users comparing a specific year across the two views saw inconsistent numerical scores.

## Symptoms

- Selecting component 2, window "2023" in single-window shows a party at +0.42, but the trajectory view at the same point shows that party at a different value (e.g. -0.15)
- Signs invert for certain components when `theme["flip"]` is `True`
- The mismatch occurs even though both views claim to show the same underlying SVD component
- **After initial fixes:** most years aligned, but "Huidig parlement" still showed different values between the two views
- "Huidig parlement" was misspelled as "Huidig parliament" in the window selector label

## What Didn't Work

Initial suspicion that the difference came from Procrustes alignment or data caching issues. Checking whether `load_party_scores_all_windows_aligned()` vs `load_party_scores_all_windows()` was the culprit. However, both views were already using the same alignment path.

The real cause was subtler: the trajectory view was computing PCA over a different set of windows than the single-window view, and then ignoring the flip flag entirely.

## Solution

### Fix 1: Align trajectory PCA computation with single-window computation

In `analysis/explorer_data.py`, function `_get_aligned_trajectory_scores()`:

```python
def _get_aligned_trajectory_scores(
    db_path: str, windows: List[str], n_components: int = 10
) -> Dict[str, Dict[str, List[float]]]:
    from analysis.political_axis import compute_nd_axes

    all_uniform_windows = get_uniform_dim_windows(db_path)
    scores_by_window, _ = compute_nd_axes(
        db_path, window_ids=all_uniform_windows, n_components=n_components
    )
    # ... rest filters to requested windows
```

**Change:** Compute PCA on **all** uniform-dim windows (matching `get_aligned_party_scores`), then filter to the requested windows. Previously, `_get_aligned_trajectory_scores()` passed only a subset of windows (excluding `_current_year`) to `compute_nd_axes()`, which produced different principal components, global mean, and flip signs.

### Fix 2: Apply theme flip in trajectory rendering

In `analysis/tabs/_rendering.py`, function `_render_svd_time_trajectory()`:

```python
    idx = comp_sel - 1
    flip = theme.get("flip", False)
    # ...
    for window in sorted_windows:
        scores_by_party = party_scores_by_window.get(window, {})
        for party in selected_parties:
            scores = scores_by_party.get(party, [])
            if scores and len(scores) > idx:
                try:
                    score = float(scores[idx])
                    if flip:
                        score = -score
                    party_trajectories.setdefault(party, []).append((window, score))
                except (ValueError, TypeError):
                    continue
```

**Change:** Added flip application to negate scores when `theme.get("flip", False)` is `True`. `_render_party_axis_chart_1d()` already did this, but `_render_svd_time_trajectory()` completely ignored the flip flag.

### Fix 3: Filter current_parliament to active MPs in trajectory view

In `analysis/explorer_data.py`, function `_get_aligned_trajectory_scores()`:

```python
    party_map = load_party_map(db_path)
    active_mps = load_active_mps(db_path)

    result: Dict[str, Dict[str, List[float]]] = {}
    for window in windows:
        window_scores = scores_by_window.get(window, {})
        if not window_scores:
            continue

        # For current_parliament, match single-window view by filtering to
        # only MPs who are still seated (active). Historical windows include
        # all MPs present in that window.
        if window == "current_parliament":
            window_scores = {
                mp: sc for mp, sc in window_scores.items() if mp in active_mps
            }

        party_vecs: Dict[str, List[np.ndarray]] = {}
        # ... aggregate by party as before
```

**Change:** Added `active_mps = load_active_mps(db_path)` and filtered `window_scores` to only active MPs when `window == "current_parliament"`. The single-window view (`get_aligned_party_scores()`) already did this filtering, but the trajectory view averaged ALL MPs (including those who had left parliament), producing different party means.

### Fix 4: Correct Dutch spelling of window label

In `analysis/tabs/components.py`:

```python
    def _svd_window_label(w: str) -> str:
        if w == "current_parliament":
            return "Huidig parlement"  # was "Huidig parliament"
        return w
```

**Change:** Fixed misspelling of Dutch word "parlement" (was "parliament").

## Why This Works

1. **Same PCA basis**: `compute_nd_axes()` computes global PCA across all provided windows. When the single-window view used all uniform-dim windows and the trajectory view used a subset, the resulting components, mean centering, and variance explained were different. Passing the same `window_ids` to `compute_nd_axes()` guarantees identical PCA bases.

2. **Same flip handling**: The single-window view negates scores when `flip=True`. The trajectory view now does the same, ensuring both views display numerically identical values for the same (window, component, party) tuple.

3. **Same MP population for current_parliament**: The single-window view filtered `current_parliament` to only active (still-seated) MPs before computing party means. The trajectory view now applies the same filter, so party averages are computed over the identical set of MPs.

## Prevention

- When multiple views display the same underlying SVD/PCA data, ensure they all call `compute_nd_axes()` with the **identical** set of window IDs.
- Never apply visual transformations (like `theme["flip"]` or `active_mps` filtering) in one view but omit them in another — keep rendering logic symmetric across all views for the same data.
- Add a regression test that asserts `get_aligned_party_scores(window, comp)` equals `_get_aligned_trajectory_scores([window], comp)[window]` for sampled windows and components, including `current_parliament`.
- Document that `compute_nd_axes()` is a global operation over its input windows; any subset produces a different coordinate frame.
- When special-casing `current_parliament` (e.g. active-MP filtering), apply the same logic in every code path that processes that window — single-window, trajectory, compass, and exports.

## Related Issues

- `docs/solutions/ui-bugs/svd-axis-pole-labels-incorrect-after-flip.md` — related flip-handling bug in the same SVD Components tab
- `docs/solutions/ui-bugs/svd-compass-components-position-inconsistency.md` — related alignment inconsistency between compass and components tab