Move rng initialization before the party loop so each party gets a
unique segment of the random stream instead of identical sequences.
Replace Python bootstrap loop with vectorized numpy indexing.
Pure numpy function that computes bootstrap confidence intervals for
party centroid vectors. Handles N>=2 (bootstrap), N=1 (degenerate CI),
and N=0 (excluded) cases. Uses np.random.default_rng for reproducibility.
Both _load_window_ids and _load_mp_vectors_for_window only read from the DB.
Opening without read_only=True caused an IOException when Streamlit already held
a read-only lock, silently returning an empty scree plot.
Previously load_scree_data computed L2-norms per dimension on current_parliament
vectors only, giving ~11% for PC1. This was inconsistent with the compass which
uses all windows + Procrustes alignment and gets PC1=24.1%.
Added compute_svd_spectrum() helper to political_axis.py that reuses the same
alignment pipeline. load_scree_data now delegates to it. _render_scree_plot
no longer re-normalizes (inputs are already EVR percentages). Hover label
updated to 'verklaarde variantie'.
Quarterly windows (29 of 41 total) diluted PC1 explained variance ratio
from ~20% down to ~14.6%. The fix splits the vector collection loop into:
- pca_vecs: annual windows only (re.match r'^\d{4}$') -> M_pca used for SVD
- all_vecs: every window -> M used for projections onto derived axes
Centering for SVD and global_mean for projection both now use M_pca.mean(axis=0)
so axes are consistent. Falls back to all windows if no annual windows exist.
The global PCA X-axis flip uses centroids averaged across all windows,
which can leave individual windows with left/right inverted (e.g. PvdA
appearing right of VVD in 2020). Mirror the existing per-window Y-axis
correction to also check and flip X values per window.
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.
The global orientation check using party centroids averaged across all
windows was insufficient — individual windows (notably 2023) could still
have conservative parties above progressive ones on the Y-axis.
Added a per-window flip in compute_2d_axes (PCA branch) that checks
prog_avg_y vs cons_avg_y for each window independently and negates all
Y values in that window when cons > prog. Flipped window IDs are stored
in axis_def['y_flipped_windows'] for diagnostics.
Moved the canonical party set definitions outside the orientation try-
block so they are always in scope for the per-window correction.
Added test_per_window_y_orientation to cover the case where one window
is globally fine but locally inverted.
SVD sign/rotation is arbitrary per window. Without alignment, drift was
dominated by basis flips (~1.9/step max=2.0) rather than real political movement.
- _procrustes_align_windows(): aligns each window to the previous using
orthogonal Procrustes on common entities (scipy, falls back gracefully)
- compute_trajectories(): builds aligned window dict before per-MP drift calc,
adds normalize=True (L2-normalise) to remove cross-window magnitude differences
caused by varying numbers of motions per quarter
- Results now in sensible range: NSC=2.28, DENK=1.90, ... PVV=0.82, FVD=0.70
- NSC large late jump (1.39 in Q4→Q1 2026) matches its parliamentary fracture
- Add outputs/trajectories_party_aligned.html with cleaned-up drift chart
- fetch_mp_metadata: use real OData URL with pagination (1200 records, 5 pages)
uses Fractie.Afkorting not NaamNL for abbreviation matching
skips Verwijderd=true records
- upsert_mp_metadata: keep most recent membership (prefer active over ended,
then higher Van date) so current party affiliations are not overwritten by historical
- compute_anchor_axis: anchor directly on party-level SVD entities (GroenLinks-PvdA etc)
before falling back to mp_metadata individual MP lookup
- test_fetch_mp_metadata: fix mock for timeout kwarg + pagination + Afkorting field
- Generated anchor axis HTML for 2025-Q2 through 2026-Q1 in outputs/
