feat(#166): Berührungsgruppen-Aufschlüsselung im Stimmverhalten-Tab
Stimm-Index pro Beruehrungsgruppe (Matrix-Zeilen A-E) zusaetzlich zur bestehenden Werte-Aufschluesselung (Spalten 1-5). Toggle-Buttons in der 3. Sub-Section schalten zwischen Werte/Gruppen. - `aggregate_stimm_index_pro_gruppe()` analog zu `_pro_wert`, aber gruppiert nach `field[0]` (A-E) statt `field[-1]` (1-5). - `_gruppen_score_for_assessment()` Helper. - `GET /api/auswertungen/stimm-index-pro-gruppe`. - UI-Toggle "Pro GWÖ-Wert" / "Pro Berührungsgruppe" mit `setMatrixAxis()`. - 6 neue Tests, Suite jetzt 995 grün. Beruehrungsgruppen-Labels (aus app/models.py:MATRIX_LABELS gekuerzt): - A: Ausgelagerte Betriebe / Lieferant:innen - B: Finanzpartner:innen / Steuerzahler:innen - C: Politische Führung / Verwaltung / Ehrenamt - D: Bürger:innen und Wirtschaft - E: Staat, Gesellschaft und Natur Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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Dotty Dotter
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@ -271,6 +271,16 @@ GWOE_WERTE = {
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"5": "Transparenz & Demokratie",
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}
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# Zeilen der GWOe-Matrix: {field-prefix → Beruehrungsgruppe-Label}. Aus
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# app/models.py:MATRIX_LABELS uebernommen, gekuerzt fuer UI-Spalten.
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GWOE_BERUEHRUNGSGRUPPEN = {
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"A": "Ausgelagerte Betriebe / Lieferant:innen",
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"B": "Finanzpartner:innen / Steuerzahler:innen",
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"C": "Politische Führung / Verwaltung / Ehrenamt",
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"D": "Bürger:innen und Wirtschaft",
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"E": "Staat, Gesellschaft und Natur",
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}
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def _load_assessments_with_votes(
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filter_bl: Optional[str] = None,
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@ -518,6 +528,22 @@ def _wert_score_for_assessment(matrix: list[dict]) -> dict[str, float]:
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return {col: sum(vals) / len(vals) for col, vals in by_col.items()}
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def _gruppen_score_for_assessment(matrix: list[dict]) -> dict[str, float]:
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"""Mittelwert pro Beruehrungsgruppe-Zeile (A..E). Field-Prefix ist die
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Zeile (`field[0]`), z.B. A1..A5 alle in Gruppe A."""
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by_row: defaultdict[str, list[float]] = defaultdict(list)
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for entry in matrix or []:
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if not isinstance(entry, dict):
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continue
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field = entry.get("field") or ""
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rating = entry.get("rating")
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if not field or rating is None:
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continue
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if len(field) >= 2 and field[0] in GWOE_BERUEHRUNGSGRUPPEN:
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by_row[field[0]].append(float(rating))
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return {row: sum(vals) / len(vals) for row, vals in by_row.items()}
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def aggregate_stimm_index_pro_wert(
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filter_bl: Optional[str] = None,
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filter_wp: Optional[str] = None,
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@ -588,6 +614,74 @@ def aggregate_stimm_index_pro_wert(
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}
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def aggregate_stimm_index_pro_gruppe(
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filter_bl: Optional[str] = None,
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filter_wp: Optional[str] = None,
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exclude_antragsteller: bool = True,
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min_n: int = 5,
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db_path: Optional[Path] = None,
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) -> dict:
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"""Pro (Fraktion, Beruehrungsgruppe A-E) ein Stimm-Index analog zu
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pro_wert, aber gegen den Gruppen-Score statt den Wert-Score (#166).
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Gruppen-Score eines Antrags = Ø(rating der gwoe_matrix-Felder mit
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dem entsprechenden Zeilen-Prefix). Domain: -5..+5 pro Gruppe.
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"""
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rows = _load_assessments_with_votes(filter_bl, filter_wp, db_path)
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gruppen_namen = list(GWOE_BERUEHRUNGSGRUPPEN.values())
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gruppen_keys = list(GWOE_BERUEHRUNGSGRUPPEN.keys())
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ja: defaultdict[tuple[str, str], list[float]] = defaultdict(list)
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nein: defaultdict[tuple[str, str], list[float]] = defaultdict(list)
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parteien_seen: set[str] = set()
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for row in rows:
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gruppen_scores = _gruppen_score_for_assessment(row["gwoe_matrix"])
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if not gruppen_scores:
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continue
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skip = row["antragsteller"] if exclude_antragsteller else set()
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for f in row["ja"] - skip:
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parteien_seen.add(f)
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for row_key, sc in gruppen_scores.items():
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ja[(f, row_key)].append(sc)
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for f in row["nein"] - skip:
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parteien_seen.add(f)
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for row_key, sc in gruppen_scores.items():
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nein[(f, row_key)].append(sc)
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parteien = sorted(parteien_seen)
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cells: dict[str, dict[str, dict]] = {}
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for p in parteien:
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cells[p] = {}
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for row_key, gruppen_name in zip(gruppen_keys, gruppen_namen):
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n_ja = len(ja[(p, row_key)])
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n_nein = len(nein[(p, row_key)])
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avg_ja = _avg(ja[(p, row_key)])
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avg_nein = _avg(nein[(p, row_key)])
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idx = (round(avg_ja - avg_nein, 2)
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if avg_ja is not None and avg_nein is not None else None)
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cells[p][gruppen_name] = {
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"stimm_index": idx,
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"n_ja": n_ja,
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"n_nein": n_nein,
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"ausreichend": n_ja >= min_n and n_nein >= min_n,
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}
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return {
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"fraktionen": parteien,
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"gruppen": gruppen_namen,
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"cells": cells,
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"n_assessments_matched": len({r["drucksache"] for r in rows}),
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"filter": {
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"bundesland": filter_bl,
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"wahlperiode": filter_wp,
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"exclude_antragsteller": exclude_antragsteller,
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"min_n": min_n,
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},
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}
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def aggregate_empfehlungs_konsistenz(
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filter_bl: Optional[str] = None,
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filter_wp: Optional[str] = None,
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17
app/main.py
17
app/main.py
@ -2370,6 +2370,23 @@ async def auswertungen_stimm_index_cross_bl(
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)
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@app.get("/api/auswertungen/stimm-index-pro-gruppe")
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async def auswertungen_stimm_index_pro_gruppe(
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bundesland: Optional[str] = None,
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wahlperiode: Optional[str] = None,
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exclude_antragsteller: bool = True,
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min_n: int = 5,
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):
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"""Stimm-Index pro Beruehrungsgruppe (A-E der GWÖ-Matrix-Zeilen) (#166)."""
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from .auswertungen import aggregate_stimm_index_pro_gruppe
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return aggregate_stimm_index_pro_gruppe(
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filter_bl=bundesland,
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filter_wp=wahlperiode,
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exclude_antragsteller=exclude_antragsteller,
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min_n=min_n,
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)
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@app.get("/api/auswertungen/empfehlungs-konsistenz")
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async def auswertungen_empfehlungs_konsistenz(
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bundesland: Optional[str] = None,
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@ -262,15 +262,33 @@ table.modal-table th { background: var(--ecg-bg-subtle); font-weight: 700; }
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</div>
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<div id="sv-heuchelei-meta" class="meta-line"></div>
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<!-- Sub 3: Pro GWÖ-Wert Heatmap -->
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<!-- Sub 3: Pro GWÖ-Wert / Pro Berührungsgruppe (Toggle) -->
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<h3 style="font-family:var(--font-display);font-size:15px;color:var(--ecg-teal);
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margin:1.5rem 0 0.5rem;">3. Stimm-Index pro GWÖ-Wert</h3>
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margin:1.5rem 0 0.5rem;">3. Stimm-Index pro Matrix-Achse</h3>
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<p style="font-size:11px;font-family:var(--font-mono);opacity:0.7;margin:0 0 0.5rem;">
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Aufschlüsselung nach den fünf GWÖ-Werten (Würde, Solidarität,
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Nachhaltigkeit, Gerechtigkeit, Demokratie). Pro Zelle: Stimm-Index analog
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Aussage 1, aber gegen den Wert-Score statt den Gesamt-Score. Domain
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pro Zelle: −5..+5.
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Aufschlüsselung der Stimm-Indizes pro <strong>GWÖ-Wert</strong>
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(Spalten: Würde, Solidarität, Nachhaltigkeit, Gerechtigkeit,
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Demokratie) oder pro <strong>Berührungsgruppe</strong> (Zeilen A–E:
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Lieferant:innen, Finanzpartner, Politik, Bürger, Staat). Pro Zelle:
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Stimm-Index analog Aussage 1, aber gegen den Achsen-Score statt den
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Gesamt-Score. Domain pro Zelle: −5..+5.
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</p>
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<div style="display:inline-flex;gap:4px;margin-bottom:0.5rem;">
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<button type="button" id="sv-axis-werte" class="sv-axis-btn active"
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onclick="setMatrixAxis('werte')"
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style="font-family:var(--font-mono);font-size:11px;padding:5px 12px;
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border:1px solid var(--ecg-border);border-radius:3px;
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cursor:pointer;background:var(--ecg-teal);color:#fff;">
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Pro GWÖ-Wert
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</button>
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<button type="button" id="sv-axis-gruppen" class="sv-axis-btn"
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onclick="setMatrixAxis('gruppen')"
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style="font-family:var(--font-mono);font-size:11px;padding:5px 12px;
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border:1px solid var(--ecg-border);border-radius:3px;
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cursor:pointer;background:var(--ecg-card-bg);color:var(--ecg-dark);">
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Pro Berührungsgruppe
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</button>
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</div>
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<div id="sv-wert-heatmap" class="matrix-wrap"></div>
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<!-- Sub 4: Empfehlungs-Konsistenz Bar Chart -->
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@ -334,6 +352,36 @@ table.modal-table th { background: var(--ecg-bg-subtle); font-weight: 700; }
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<script>
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let _tabLoaded = { 'bl-partei': false, 'themen': false, 'stimmverhalten': false };
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let _svCharts = { index: null, heuchelei: null, empfehlung: null, crossBl: null };
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let _svMatrixAxis = 'werte'; // 'werte' or 'gruppen'
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function setMatrixAxis(axis) {
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_svMatrixAxis = axis;
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const werteBtn = document.getElementById('sv-axis-werte');
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const gruppenBtn = document.getElementById('sv-axis-gruppen');
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if (axis === 'werte') {
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werteBtn.style.background = 'var(--ecg-teal)';
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werteBtn.style.color = '#fff';
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gruppenBtn.style.background = 'var(--ecg-card-bg)';
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gruppenBtn.style.color = 'var(--ecg-dark)';
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} else {
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gruppenBtn.style.background = 'var(--ecg-teal)';
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gruppenBtn.style.color = '#fff';
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werteBtn.style.background = 'var(--ecg-card-bg)';
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werteBtn.style.color = 'var(--ecg-dark)';
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}
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loadMatrixHeatmap();
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}
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function loadMatrixHeatmap() {
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const blRaw = (window.v2GetGlobalBl && window.v2GetGlobalBl()) || 'ALL';
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const bl = (blRaw === 'ALL') ? '' : blRaw;
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const exclude = document.getElementById('sv-exclude-antragsteller').checked ? '1' : '0';
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if (_svMatrixAxis === 'gruppen') {
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loadStimmIndexProGruppe(bl, exclude);
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} else {
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loadStimmIndexProWert(bl, exclude);
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}
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}
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function switchTab(id, btn) {
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document.querySelectorAll('.auswert-tab').forEach(b => b.classList.remove('active'));
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@ -539,7 +587,7 @@ async function loadStimmverhalten() {
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loadStimmIndex(bl, exclude);
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loadHeuchelei(bl);
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loadStimmIndexProWert(bl, exclude);
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loadMatrixHeatmap();
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loadEmpfehlungsKonsistenz(bl);
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loadStimmIndexCrossBl(exclude);
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}
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@ -739,6 +787,51 @@ async function loadStimmIndexProWert(bl, exclude) {
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}
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}
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async function loadStimmIndexProGruppe(bl, exclude) {
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const wrap = document.getElementById('sv-wert-heatmap');
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let url = `/api/auswertungen/stimm-index-pro-gruppe?exclude_antragsteller=${exclude}&min_n=3`;
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if (bl) url += '&bundesland=' + encodeURIComponent(bl);
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wrap.innerHTML = '<div style="font-family:var(--font-mono);font-size:12px;opacity:0.5;">Lade Heatmap …</div>';
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try {
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const r = await fetch(url);
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const data = await r.json();
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if (!data.fraktionen.length) {
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wrap.innerHTML = '<div style="font-family:var(--font-mono);font-size:12px;opacity:0.5;">Keine Daten für diesen Filter.</div>';
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return;
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}
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let html = '<table class="gwoe-matrix"><thead><tr><th class="row-h">Fraktion</th>';
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for (const g of data.gruppen) html += `<th style="font-size:10px;max-width:120px;white-space:normal;">${g}</th>`;
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html += '</tr></thead><tbody>';
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for (const partei of data.fraktionen) {
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html += `<tr><th class="row-h">${partei}</th>`;
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for (const gruppe of data.gruppen) {
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const cell = (data.cells[partei] || {})[gruppe];
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if (cell && cell.stimm_index != null && cell.ausreichend) {
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const color = wertHeatColor(cell.stimm_index);
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const sign = cell.stimm_index >= 0 ? '+' : '';
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html += `<td style="background:${color};" title="${partei} × ${gruppe}: Index ${sign}${cell.stimm_index} (n_ja=${cell.n_ja}, n_nein=${cell.n_nein})">
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${sign}${cell.stimm_index.toFixed(1)}
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</td>`;
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} else {
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html += '<td class="empty">—</td>';
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}
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}
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html += '</tr>';
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}
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html += '</tbody></table>';
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html += `<div class="meta-line">Datenbasis: ${data.n_assessments_matched} Anträge.
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Mindest-N pro Zelle: 3. Skala −5..+5 (Gruppen-Score-Differenz Ja minus Nein).</div>`;
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wrap.innerHTML = html;
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} catch (e) {
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wrap.innerHTML = `<div style="color:#c00;font-family:var(--font-mono);font-size:12px;">Fehler: ${e}</div>`;
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}
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}
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async function loadEmpfehlungsKonsistenz(bl) {
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const meta = document.getElementById('sv-empfehlung-meta');
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@ -17,8 +17,10 @@ from app.auswertungen import (
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aggregate_heuchelei,
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aggregate_stimm_index,
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aggregate_stimm_index_cross_bl,
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aggregate_stimm_index_pro_gruppe,
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aggregate_stimm_index_pro_wert,
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export_stimmverhalten_csv,
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_gruppen_score_for_assessment,
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_wert_score_for_assessment,
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)
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@ -377,6 +379,65 @@ class TestAggregateProWert:
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assert "ausreichend" in cell
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# ─────────────────────────────────────────────────────────────────────────────
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# aggregate_stimm_index_pro_gruppe (#166)
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# ─────────────────────────────────────────────────────────────────────────────
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class TestGruppenScoreHelper:
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def test_extracts_per_row(self):
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matrix = [
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{"field": "A1", "rating": 3},
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{"field": "A3", "rating": 5},
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{"field": "B2", "rating": 4},
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]
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result = _gruppen_score_for_assessment(matrix)
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# Zeile A: A1=3 + A3=5 → Ø=4
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assert result["A"] == 4.0
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# Zeile B: B2=4 → Ø=4
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assert result["B"] == 4.0
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def test_empty_matrix(self):
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assert _gruppen_score_for_assessment([]) == {}
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def test_invalid_entries_skipped(self):
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matrix = [
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{"field": "A1", "rating": 3},
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{"field": "X9", "rating": 2}, # invalid row prefix
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{"field": "", "rating": 5},
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]
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result = _gruppen_score_for_assessment(matrix)
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assert result == {"A": 3.0}
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class TestAggregateProGruppe:
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def test_structure(self, sample_db):
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out = aggregate_stimm_index_pro_gruppe(db_path=sample_db, min_n=1)
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# 5 Berührungsgruppen-Labels
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assert len(out["gruppen"]) == 5
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assert "cells" in out
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def test_cell_format(self, sample_db):
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out = aggregate_stimm_index_pro_gruppe(db_path=sample_db, min_n=1)
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if not out["fraktionen"]:
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pytest.skip("no parteien — DB empty")
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first_partei = out["fraktionen"][0]
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# Pick first gruppe
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first_gruppe = out["gruppen"][0]
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cell = out["cells"][first_partei][first_gruppe]
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assert "stimm_index" in cell
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assert "n_ja" in cell
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assert "n_nein" in cell
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assert "ausreichend" in cell
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def test_independent_from_pro_wert(self, sample_db):
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"""Pro-Gruppe-Aggregation soll andere Achse als Pro-Wert haben."""
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wert_out = aggregate_stimm_index_pro_wert(db_path=sample_db, min_n=1)
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gruppe_out = aggregate_stimm_index_pro_gruppe(db_path=sample_db, min_n=1)
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# Werte und Gruppen-Labels müssen disjunkt sein
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assert set(wert_out["werte"]).isdisjoint(set(gruppe_out["gruppen"]))
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# ─────────────────────────────────────────────────────────────────────────────
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# aggregate_stimm_index_cross_bl
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# ─────────────────────────────────────────────────────────────────────────────
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