Remove the '🔍 Wat bepaalt deze assen?' expander that showed individual
motion titles (➕/➖) with axis labels and variance explanation. Only the
Stemdiscipline analyse (Rice index) section remains. Also removes the
now-unused _render_axis_motions() helper function.
Two related bugs fixed:
1. Label alignment: Removed static left_pole/right_pole from SVD_THEMES
entries. These labels assumed a fixed flip direction but could mismatch
with runtime flip computation, causing right-wing parties to appear on
the wrong side. Labels are now always derived from positive_pole,
negative_pole, and the runtime flip direction.
2. Score mismatch: Changed tijdtraject view for components 3-10 from
load_party_scores_all_windows_aligned() to load_party_scores_all_windows().
Procrustes alignment rotates the full 50-dim vector space to align
components 1-2, but this also transforms components 3-10, making their
scores incomparable with the single-window view. Per-window flip
computation already handles orientation alignment for these components.
Also updated svd_labels.py to prefer analysis.config as the canonical
source for SVD_THEMES, falling back to explorer only when config is
unavailable.
The component captures voting unity of the right-wing coalition vs left
opposition, NOT semantic content like 'defense' or 'EU integration'.
Motions about elderly care (Dobbe) appear because the left votes for them
while the right coalition votes against - this is coalition-opposition
polarization, not policy domain.
- Add Dutch paragraph explaining Rice index and party discipline patterns
- Analysis covers high discipline parties (PVV, SGP) vs lower discipline parties
- Explains what discipline reveals about party dynamics
- Add _load_mp_vectors_by_party_for_window() to load SVD vectors for specific windows
- Add load_party_axis_scores_for_window() cached function
- Add year selector UI for components 3-10 similar to components 1-2
- Uses get_uniform_dim_windows() to get available windows
- Changed _render_party_axis_chart_1d from horizontal bar chart to scatter plot
- Same format as components 1-2: markers on horizontal line with axis arrows- Axis labels now show correct direction with arrows (← left | right →)
- Ensures consistent visualization across all SVD components
Previously the st.plotly_chart call was wrapped in 'except Exception: pass'
which silently swallowed all rendering errors. The user would see no chart
and no error message.
Now:
- Exception message is shown via st.error()
- Diagnostics JSON is shown when debug is enabled (EXPLORER_DEBUG_TRAJECTORIES=1
or UI checkbox), even when trace_count > 0
This reveals the actual root cause when the chart fails to render.
- Lock x_label/y_label to Links-Rechts / Progressief-Conservatief after
classify_axes; Procrustes sign-fixing in compute_2d_axes already ensures
the correct orientation so the heuristic _should_swap_axes call is removed
- Remove visual error bars from party axis chart; 95% CI is now shown in
hover text (party: score, N=n, 95%-BI: [low, high]) to keep the 1D
scatter clean
- Remove show_ci checkbox and parameter — CI is always accessible on hover
- Update tests to match new hover format and absence of error_x
- Extract shared helper that both load_party_axis_scores and
load_party_mp_vectors delegate to, eliminating ~40 lines of
duplicated DB query + vector parsing code
- Remove dead code in load_party_axis_scores that queried mp_metadata
twice (first without ORDER BY, then again with ORDER BY, overwriting)
- Fix _cached_bootstrap_cis parameter: remove _ prefix so Streamlit
actually hashes the input dict instead of caching with no key
- Add load_party_mp_vectors() to return raw per-MP SVD vectors by party
- Extract _build_party_axis_figure() as pure function for testability
- Modify _render_party_axis_chart to accept bootstrap_data and delegate
to the new builder
- When bootstrap_data present: show error_x bars, diamond markers for
N=1 parties, and N=count in hover text
- Wire up bootstrap computation in build_svd_components_tab via cached
_cached_bootstrap_cis wrapper
- Add 6 tests covering figure construction, bootstrap rendering, flip
behavior, and importability
- PC2: rename 'maatschappelijke verantwoordelijkheid' to 'institutioneel
progressivisme' (less normatively loaded), rewrite explanation with actual
party scores (CU=-59, SGP=-25, VVD=-15 — all strongly negative, not
'near the middle'), update pole descriptions
- PC3: remove speculative motivation claim about PVV, state factual
observation that PVV/SP/PvdD/GL-PvdA vote alike despite opposing PC1
- PC7-PC10: add '(indicatief)' to labels — these axes explain <4% EVR
and may be below noise level
- PC7: add explicit fragility warning in explanation
- PC8: clarify DENK/SP negative scores mean active opposition voting,
not lack of focus; note Volt N=1 unreliability
- Scree plot: soften claim that later axes are 'meaningful'
- Re-ran generate_svd_json.py for current_parliament window (100 rows, 10 components)
- Computed party centroid scores per axis from 150 matched MPs
- Updated all 10 SVD_THEMES entries with accurate labels, Dutch explanations
and correct positive/negative pole party attributions
- Key findings: PC1=rechts-links, PC2=populistisch nationalisme vs mainstream,
PC3=verzorgingsstaat vs bezuinigingen, PC6=klimaat & energie,
PC8=Europese defensie-integratie
- Added axis_analysis_data.json and party_svd_scores.json as analysis artifacts
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'.
Replace hardcoded 'Links-Rechts' / 'Progressief-Conservatief' axis labels
with values from classify_axes(). Add per-year interpretation caption when
axis quality score is below the 0.65 correlation threshold.
- Rename app to 'Motief: de stematlas' in Home.py
- Remove PCA variance caption from compass tab
- Hardcode db_path and window_size; remove sidebar inputs
- Change trajectories default to [CDA, D66, VVD]
- Move quiz to pages/1_Stemwijzer.py; wrap in st.form
- Remove quiz tab from main explorer
- Add pytest dev dep + fix test fixtures (_load_mp_vectors_for_window)
- Add test_pca_axis_orientation with proper PCA variance dominance
The mp_votes table contains both party-aggregate rows (e.g. 'PVV', 'NSC')
and individual MP rows (e.g. 'Aardema, M.'). Running SVD on both together
creates a block-diagonal vote matrix where party codes and individual MPs
occupy disjoint SVD dimensions — causing dim 0 to be zero for all 421 MPs.
Fix: _build_expanded_rows() converts every party-level vote to individual
MP votes using mp_metadata date ranges (active MPs on motion date). Motions
that already have individual MP records are kept as-is. A party name mapping
handles NSC/Nieuw Sociaal Contract and other canonical name variants.
Results for current_parliament: 517 individual MPs, all 8732 motions covered,
dim 0 std=23.1 (was 0.0 for all MPs). PVV/NSC/BBB on positive end, SP/GL/PvdD
on negative end — matches expected left-right political axis.
All 11 annual windows (2016-2026) re-run with the new pipeline.
- load_party_axis_scores now loads individual MP vectors and averages
per party (same data source as the political compass), so SVD axis
rankings are consistent between the two tabs. Previously it used
party-aggregate rows which gave structurally 0 signal on dim 3.
- Re-add component 4 (dim 3) to SVD_THEMES and revert comp_options
filter — with individual MPs averaged, dim 3 now shows real party
separation (the 'publieke voorzieningen vs marktwerking' axis).
- Scree plot y-axis now shows percentage of total variance instead of
raw L2-norms; hover also updated to show '% van totaal'.
Dim 3 captures within-party individual disagreement (MPs splitting
from party lines). Party-aggregate votes are structurally 0 on this
dimension, so the axis chart showed all parties at ~0 with no
discrimination. Confirmed via dry-run: identical to existing data.
Also filter comp_options to only show components with a defined theme,
so component 4 is hidden from the selectbox entirely.
current_parliament has two separate SVD data spaces mixed together.
Party vectors (entity_id without comma) carry the between-party signal
in dims 0-15. Individual MP vectors only have signal in dim 3 and
dims 16-49 (within-party variance). The axis chart uses party vectors,
so the scree must too.
