Ajoute page statistiques avec graphiques et onglets de période
- Nouvelle page /stats avec histogrammes de distribution par créneau horaire (entrée/sortie matin et après-midi) - Camemberts animés de conformité aux directives (≤09:00, ≥12:00, ≤14:00, ≥17:00) globale, par slot et par période (mois, sem. N-1) - Onglets Tout / 1 an / 3 mois / 1 mois : filtrage côté client avec recalcul μ, σ, n et conformité en temps réel - Graphique des soldes hebdomadaires (barres animées, toutes semaines sur l'axe X en rotation -45°, semaines partielles distinctes) - Clic sur un graphique → modal plein écran avec axe X détaillé (15 min) - Légende σ / n / directive / moyenne sur chaque histogramme - Journées incomplètes exclues des stats ; heures dues retirées du solde - Lien "Statistiques" dans la nav Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
toto
25
app/main.py
25
app/main.py
@ -1,3 +1,4 @@
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import json
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from datetime import datetime, timedelta
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from itertools import groupby
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@ -11,6 +12,7 @@ from models import (
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toggle_conge, list_all_weeks,
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)
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from calcul import compute_week, minutes_to_hhmm, hhmm_to_minutes, heures_dues
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from stats import compute_all_stats
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app = FastAPI(title="Décompte Horaire")
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templates = Jinja2Templates(directory="templates")
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@ -264,6 +266,29 @@ def save_pointage(
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return _htmx_calc_and_soldes(request, date, d, conges, h_jour)
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@app.get("/stats", response_class=HTMLResponse)
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def stats_page(request: Request):
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stats = compute_all_stats()
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data_json = json.dumps({
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"time_stats": {
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slot: {
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"mean": s["mean"], "sigma": s["sigma"],
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"mean_hhmm": s["mean_hhmm"], "sigma_min": s["sigma_min"],
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"n": s["n"], "dated_values": s["dated_values"],
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} if s else None
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for slot, s in stats["time_stats"].items()
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},
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"compliance": stats["compliance"],
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"weekly_balances": stats["weekly_balances"],
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"today": stats["today"],
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})
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return templates.TemplateResponse("stats.html", {
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"request": request,
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"stats": stats,
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"data_json": data_json,
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})
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@app.post("/conge/{date}/{type_conge}", response_class=HTMLResponse)
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def toggle_conge_route(date: str, type_conge: str, request: Request):
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toggle_conge(date, type_conge)
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191
app/stats.py
Normal file
191
app/stats.py
Normal file
@ -0,0 +1,191 @@
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"""Statistics computation across all recorded weeks."""
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import statistics as _st
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from datetime import datetime, timedelta, date as _date
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from models import load_week_pointages, load_conges, list_all_weeks, load_config
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from calcul import hhmm_to_minutes, minutes_to_hhmm, heures_travaillees, heures_dues
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def _week_dates(year: int, week: int) -> list[str]:
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first = datetime.strptime(f"{year}-W{week:02d}-1", "%G-W%V-%u").date()
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return [(first + timedelta(days=i)).strftime("%Y-%m-%d") for i in range(5)]
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def _to_hhmm(minutes_float: float) -> str:
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m = round(minutes_float)
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return f"{m // 60:02d}:{m % 60:02d}"
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def _day_compliant(p: dict, mc: bool, ac: bool) -> bool | None:
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if mc and ac:
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return None
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matin_ok = mc or (bool(p.get("matin_entree")) and bool(p.get("matin_sortie")))
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aprem_ok = ac or (bool(p.get("aprem_entree")) and bool(p.get("aprem_sortie")))
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if not (matin_ok and aprem_ok):
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return None
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if not mc:
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if p.get("matin_entree") and hhmm_to_minutes(p["matin_entree"]) > 9 * 60:
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return False
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if p.get("matin_sortie") and hhmm_to_minutes(p["matin_sortie"]) < 12 * 60:
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return False
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if not ac:
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if p.get("aprem_entree") and hhmm_to_minutes(p["aprem_entree"]) > 14 * 60:
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return False
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if p.get("aprem_sortie") and hhmm_to_minutes(p["aprem_sortie"]) < 17 * 60:
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return False
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return True
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def _compliance_over(all_days: list[tuple], cg_set: set) -> dict:
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n = n_ok = 0
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for date, p in all_days:
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mc = (date, "matin") in cg_set or (date, "jour") in cg_set
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ac = (date, "aprem") in cg_set or (date, "jour") in cg_set
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result = _day_compliant(p, mc, ac)
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if result is None:
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continue
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n += 1
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if result:
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n_ok += 1
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return {"pct": round(100 * n_ok / n) if n else None, "n": n, "n_ok": n_ok}
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def compute_all_stats() -> dict:
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all_weeks = sorted(list_all_weeks())
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conges = load_conges()
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h_jour = int(float(load_config().get("heures_jour", 7.8)) * 60)
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cg_set = {(c["date"], c["type"]) for c in conges}
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today = _date.today()
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prev_week_date = today - timedelta(weeks=1)
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prev_iso = prev_week_date.isocalendar()
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prev_week_dates = set(_week_dates(prev_iso.year, prev_iso.week))
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current_ym = (today.year, today.month)
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SLOTS = ["matin_entree", "matin_sortie", "aprem_entree", "aprem_sortie"]
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# Store (value, date) pairs per slot
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slot_pairs: dict[str, list[tuple[int, str]]] = {s: [] for s in SLOTS}
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comp_n = {s: 0 for s in SLOTS}
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comp_ok = {s: 0 for s in SLOTS}
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TARGETS = {
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"matin_entree": ("le", 9 * 60),
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"matin_sortie": ("ge", 12 * 60),
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"aprem_entree": ("le", 14 * 60),
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"aprem_sortie": ("ge", 17 * 60),
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}
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weekly_balances = []
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all_days: list[tuple] = []
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month_days: list[tuple] = []
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prev_week_day_list: list[tuple] = []
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for year, week in all_weeks:
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raw = load_week_pointages(year, week)
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if not raw:
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continue
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dates = _week_dates(year, week)
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p_by_date = {p["date"]: p for p in raw}
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week_delta = 0
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week_has_incomplete = False
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for date in dates:
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p = p_by_date.get(date, {
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"date": date, "matin_entree": None, "matin_sortie": None,
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"aprem_entree": None, "aprem_sortie": None,
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})
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mc = (date, "matin") in cg_set or (date, "jour") in cg_set
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ac = (date, "aprem") in cg_set or (date, "jour") in cg_set
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matin_filled = mc or (bool(p.get("matin_entree")) and bool(p.get("matin_sortie")))
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aprem_filled = ac or (bool(p.get("aprem_entree")) and bool(p.get("aprem_sortie")))
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all_days.append((date, p))
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d = datetime.strptime(date, "%Y-%m-%d").date()
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if (d.year, d.month) == current_ym:
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month_days.append((date, p))
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if date in prev_week_dates:
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prev_week_day_list.append((date, p))
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if not (matin_filled and aprem_filled):
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week_has_incomplete = True
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continue
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trav = heures_travaillees(p)
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du = heures_dues(date, conges, h_jour)
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week_delta += trav - du
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if not mc:
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for slot in ("matin_entree", "matin_sortie"):
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if p.get(slot):
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v = hhmm_to_minutes(p[slot])
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slot_pairs[slot].append((v, date))
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op, thr = TARGETS[slot]
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comp_n[slot] += 1
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comp_ok[slot] += 1 if (v <= thr if op == "le" else v >= thr) else 0
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if not ac:
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for slot in ("aprem_entree", "aprem_sortie"):
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if p.get(slot):
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v = hhmm_to_minutes(p[slot])
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slot_pairs[slot].append((v, date))
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op, thr = TARGETS[slot]
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comp_n[slot] += 1
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comp_ok[slot] += 1 if (v <= thr if op == "le" else v >= thr) else 0
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weekly_balances.append({
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"year": year, "week": week,
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"label": f"S{week:02d}",
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"date": dates[0], # Monday — used for period filtering
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"delta_min": week_delta,
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"delta": minutes_to_hhmm(week_delta),
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"partial": week_has_incomplete,
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})
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time_stats = {}
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for slot, pairs in slot_pairs.items():
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if len(pairs) < 2:
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time_stats[slot] = None
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continue
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vals = [v for v, _ in pairs]
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mean = _st.mean(vals)
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sigma = _st.stdev(vals)
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time_stats[slot] = {
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"mean": mean, "sigma": sigma,
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"mean_hhmm": _to_hhmm(mean),
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"sigma_min": round(sigma),
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"n": len(vals),
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"dated_values": [{"v": v, "d": d} for v, d in pairs],
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}
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compliance = {
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slot: (round(100 * comp_ok[slot] / comp_n[slot]) if comp_n[slot] else None)
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for slot in comp_n
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}
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rates = [v for v in compliance.values() if v is not None]
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overall_slot = round(sum(rates) / len(rates)) if rates else None
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n_jours = max(len(slot_pairs["matin_entree"]), len(slot_pairs["aprem_entree"]))
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deltas = [b["delta_min"] for b in weekly_balances]
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avg_delta_min = round(_st.mean(deltas)) if deltas else 0
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comp_globale = _compliance_over(all_days, cg_set)
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comp_mois = _compliance_over(month_days, cg_set)
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comp_sem_n1 = _compliance_over(prev_week_day_list, cg_set)
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return {
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"time_stats": time_stats,
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"compliance": compliance,
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"overall_compliance": overall_slot,
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"weekly_balances": weekly_balances,
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"total_weeks": len(weekly_balances),
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"n_jours": n_jours,
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"avg_delta": minutes_to_hhmm(avg_delta_min),
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"avg_delta_min": avg_delta_min,
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"comp_globale": comp_globale,
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"comp_mois": comp_mois,
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"comp_sem_n1": comp_sem_n1,
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"mois_label": today.strftime("%B %Y"),
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"prev_week_label": f"S{prev_iso.week:02d} / {prev_iso.year}",
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"today": today.strftime("%Y-%m-%d"),
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}
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@ -484,6 +484,350 @@
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}
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.cal-grid .cal-current:hover td { background: rgba(47,95,160,.06); }
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.cal-grid .cal-current:hover td.cal-wn { background: var(--accent); }
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/* ── Stats page ── */
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.stats-head {
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display: flex;
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align-items: flex-start;
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justify-content: space-between;
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gap: 1.5rem;
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border-bottom: 2px solid var(--text);
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padding-bottom: .75rem;
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}
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.stats-title {
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font-family: var(--mono);
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font-size: 1.75rem;
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font-weight: 500;
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letter-spacing: -.02em;
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line-height: 1;
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margin-bottom: .4rem;
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}
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.stats-meta {
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font-size: 12px;
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color: var(--muted);
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font-family: var(--mono);
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}
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.stats-sep { margin: 0 .35em; color: var(--rule); }
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.stat-pos { color: var(--pos); font-weight: 500; }
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.stat-neg { color: var(--neg); font-weight: 500; }
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.stats-overall {
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text-align: center;
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padding: .75rem 1.1rem;
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border: 1.5px solid var(--rule);
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background: var(--surface);
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flex-shrink: 0;
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}
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.stats-overall-num {
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font-family: var(--mono);
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font-size: 2rem;
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font-weight: 500;
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letter-spacing: -.04em;
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line-height: 1;
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}
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.stats-overall-pct { font-size: 1.1rem; font-weight: 300; }
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.stats-overall-label {
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font-size: 9px;
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letter-spacing: .1em;
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text-transform: uppercase;
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color: var(--muted);
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margin-top: .35rem;
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line-height: 1.4;
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}
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.comp-ok { color: var(--pos); border-color: var(--pos) !important; background: var(--pos-bg) !important; }
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.comp-warn { color: #7A5300; border-color: var(--conge-bd) !important; background: var(--conge-bg) !important; }
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.comp-bad { color: var(--neg); border-color: var(--neg) !important; background: var(--neg-bg) !important; }
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/* ── 3 period-compliance cards ── */
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.comp-periods {
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display: grid;
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grid-template-columns: repeat(3, 1fr);
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gap: 1px;
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background: var(--rule);
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border: 1.5px solid var(--rule);
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}
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@media (max-width: 520px) { .comp-periods { grid-template-columns: 1fr; } }
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.comp-period-card {
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background: var(--surface);
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padding: 1rem 1.25rem 1rem;
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display: flex;
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flex-direction: column;
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align-items: center;
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gap: .2rem;
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text-align: center;
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}
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.cp-eyebrow {
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font-family: var(--mono);
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font-size: 9px;
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letter-spacing: .12em;
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text-transform: uppercase;
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color: var(--muted);
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}
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.cp-sub {
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font-family: var(--mono);
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font-size: 10px;
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color: var(--text);
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font-weight: 500;
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margin-bottom: .35rem;
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}
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.cp-donut-wrap { margin: .25rem 0; }
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.cp-donut { display: block; }
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.cp-n {
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font-family: var(--mono);
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font-size: 10px;
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color: var(--muted);
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margin-top: .2rem;
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}
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.cp-n.comp-ok { color: var(--pos); }
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.cp-n.comp-warn { color: #7A5300; }
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.cp-n.comp-bad { color: var(--neg); }
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.cp-nodata { color: var(--rule); }
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/* ── Period tabs ── */
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.period-tabs-wrap {
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display: flex;
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align-items: center;
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gap: 1rem;
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flex-wrap: wrap;
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}
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.period-tabs-label {
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font-family: var(--mono);
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font-size: 9px;
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letter-spacing: .12em;
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text-transform: uppercase;
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color: var(--muted);
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flex-shrink: 0;
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}
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.period-tabs {
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display: flex;
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gap: 1px;
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background: var(--rule);
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border: 1.5px solid var(--rule);
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}
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.ptab {
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padding: .38rem .9rem;
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font-family: var(--mono);
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font-size: 11px;
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background: var(--surface);
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border: none;
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cursor: pointer;
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color: var(--muted);
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letter-spacing: .04em;
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transition: background .12s, color .12s;
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white-space: nowrap;
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}
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.ptab:hover { background: var(--ground); color: var(--text); }
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.ptab.active { background: var(--text); color: var(--ground); }
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.ptab:focus { outline: 2px solid var(--accent); outline-offset: -2px; }
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/* 2×2 grid, 4-in-a-row on wide screens */
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.ts-grid {
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display: grid;
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grid-template-columns: repeat(2, 1fr);
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gap: 1px;
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background: var(--rule);
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border: 1.5px solid var(--rule);
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}
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@media (min-width: 800px) { .ts-grid { grid-template-columns: repeat(4, 1fr); } }
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.ts-card {
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background: var(--surface);
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padding: 1rem 1.2rem .9rem;
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display: flex;
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flex-direction: column;
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gap: .3rem;
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min-width: 0;
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}
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.ts-card.ts-matin { border-top: 3px solid var(--accent); }
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.ts-card.ts-aprem { border-top: 3px solid var(--accent-2); }
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.ts-eyebrow {
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font-family: var(--mono);
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font-size: 9px;
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||||
letter-spacing: .12em;
|
||||
text-transform: uppercase;
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color: var(--muted);
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}
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.ts-mean {
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font-family: var(--mono);
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font-size: 2rem;
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font-weight: 500;
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letter-spacing: -.04em;
|
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line-height: 1;
|
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color: var(--text);
|
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margin-top: .15rem;
|
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}
|
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.ts-mean.ts-empty { color: var(--rule); }
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.ts-sigma {
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font-family: var(--mono);
|
||||
font-size: 10px;
|
||||
color: var(--muted);
|
||||
margin-bottom: .25rem;
|
||||
}
|
||||
|
||||
.ts-mean-row {
|
||||
display: flex;
|
||||
align-items: center;
|
||||
justify-content: space-between;
|
||||
gap: .5rem;
|
||||
}
|
||||
.donut-wrap {
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
align-items: center;
|
||||
gap: .15rem;
|
||||
flex-shrink: 0;
|
||||
}
|
||||
.donut-canvas { display: block; }
|
||||
.donut-label {
|
||||
font-family: var(--mono);
|
||||
font-size: 8px;
|
||||
letter-spacing: .04em;
|
||||
color: var(--muted);
|
||||
text-align: center;
|
||||
}
|
||||
|
||||
.dist-canvas {
|
||||
width: 100%;
|
||||
display: block;
|
||||
margin: .25rem 0 .2rem;
|
||||
background: transparent;
|
||||
}
|
||||
|
||||
.dist-legend {
|
||||
display: flex;
|
||||
flex-wrap: wrap;
|
||||
gap: .5rem .75rem;
|
||||
font-family: var(--mono);
|
||||
font-size: 9px;
|
||||
color: var(--muted);
|
||||
margin-bottom: .35rem;
|
||||
}
|
||||
.dl-item { display: flex; align-items: center; gap: .28rem; white-space: nowrap; }
|
||||
.dl-mean-line {
|
||||
display: inline-block;
|
||||
width: 14px; height: 1.5px;
|
||||
background: var(--text);
|
||||
flex-shrink: 0;
|
||||
}
|
||||
.dl-target-line {
|
||||
display: inline-block;
|
||||
width: 14px; height: 0;
|
||||
border-top: 1.5px dashed;
|
||||
flex-shrink: 0;
|
||||
}
|
||||
.dl-target-line.dl-neg { border-color: var(--neg); }
|
||||
.dl-target-line.dl-pos { border-color: var(--pos); }
|
||||
.dl-band {
|
||||
display: inline-block;
|
||||
width: 10px; height: 10px;
|
||||
flex-shrink: 0;
|
||||
}
|
||||
.dl-band.ts-matin { background: rgba(47,95,160,.12); border: 1px solid rgba(47,95,160,.25); }
|
||||
.dl-band.ts-aprem { background: rgba(184,106,8,.12); border: 1px solid rgba(184,106,8,.25); }
|
||||
.dl-n { color: var(--muted); }
|
||||
|
||||
/* Weekly balance chart */
|
||||
.wkly-section {
|
||||
background: var(--surface);
|
||||
border: 1.5px solid var(--rule);
|
||||
padding: 1rem 1.25rem;
|
||||
}
|
||||
.wkly-eyebrow {
|
||||
font-family: var(--mono);
|
||||
font-size: 9px;
|
||||
letter-spacing: .12em;
|
||||
text-transform: uppercase;
|
||||
color: var(--muted);
|
||||
margin-bottom: .75rem;
|
||||
}
|
||||
.wkly-wrap {
|
||||
overflow-x: auto;
|
||||
-webkit-overflow-scrolling: touch;
|
||||
}
|
||||
#c-weekly { display: block; width: 100%; }
|
||||
.wkly-note { font-weight: 300; color: var(--muted); letter-spacing: 0; text-transform: none; font-size: 9px; }
|
||||
.wkly-legend {
|
||||
margin-top: .5rem;
|
||||
font-size: 10px;
|
||||
color: var(--muted);
|
||||
font-family: var(--mono);
|
||||
display: flex;
|
||||
align-items: center;
|
||||
gap: .4rem;
|
||||
}
|
||||
.legend-dot {
|
||||
width: 10px; height: 10px;
|
||||
display: inline-block;
|
||||
flex-shrink: 0;
|
||||
}
|
||||
.partial-dot { background: repeating-linear-gradient(45deg, var(--muted) 0, var(--muted) 2px, transparent 2px, transparent 4px); }
|
||||
|
||||
/* Zoomable canvas hint */
|
||||
canvas.zoomable { cursor: zoom-in; }
|
||||
|
||||
/* ── Chart zoom modal ── */
|
||||
.chart-modal {
|
||||
position: fixed;
|
||||
inset: 0;
|
||||
z-index: 1000;
|
||||
display: flex;
|
||||
align-items: center;
|
||||
justify-content: center;
|
||||
padding: 1rem;
|
||||
}
|
||||
.chart-modal[hidden] { display: none; }
|
||||
.chart-modal-bd {
|
||||
position: absolute;
|
||||
inset: 0;
|
||||
background: rgba(28,23,18,.55);
|
||||
backdrop-filter: blur(3px);
|
||||
}
|
||||
.chart-modal-inner {
|
||||
position: relative;
|
||||
background: var(--surface);
|
||||
border: 1.5px solid var(--rule);
|
||||
max-width: 92vw;
|
||||
max-height: 90vh;
|
||||
overflow: auto;
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
}
|
||||
.chart-modal-header {
|
||||
display: flex;
|
||||
align-items: center;
|
||||
justify-content: space-between;
|
||||
gap: 1rem;
|
||||
padding: .65rem 1rem;
|
||||
border-bottom: 1px solid var(--rule);
|
||||
background: var(--ground);
|
||||
}
|
||||
.chart-modal-title {
|
||||
font-family: var(--mono);
|
||||
font-size: 10px;
|
||||
letter-spacing: .1em;
|
||||
text-transform: uppercase;
|
||||
color: var(--muted);
|
||||
}
|
||||
.chart-modal-close {
|
||||
background: none;
|
||||
border: 1.5px solid var(--rule);
|
||||
width: 26px; height: 26px;
|
||||
display: flex; align-items: center; justify-content: center;
|
||||
cursor: pointer;
|
||||
font-size: 12px;
|
||||
color: var(--muted);
|
||||
flex-shrink: 0;
|
||||
transition: border-color .15s, color .15s;
|
||||
}
|
||||
.chart-modal-close:hover { border-color: var(--text); color: var(--text); }
|
||||
.chart-modal-close:focus { outline: 2px solid var(--accent); outline-offset: 2px; }
|
||||
.chart-modal-body {
|
||||
padding: 1.25rem;
|
||||
overflow-x: auto;
|
||||
}
|
||||
#chart-modal-canvas { display: block; }
|
||||
</style>
|
||||
</head>
|
||||
<body>
|
||||
@ -491,6 +835,7 @@
|
||||
<a href="/" class="nav-brand"><span class="nav-dot"></span>Décompte Horaire</a>
|
||||
<span class="spacer"></span>
|
||||
<a href="/" class="nav-link">Semaine courante</a>
|
||||
<a href="/stats" class="nav-link">Statistiques</a>
|
||||
</nav>
|
||||
<div class="container">
|
||||
{% block content %}{% endblock %}
|
||||
|
||||
558
app/templates/stats.html
Normal file
558
app/templates/stats.html
Normal file
@ -0,0 +1,558 @@
|
||||
{% extends "base.html" %}
|
||||
{% block content %}
|
||||
|
||||
<div class="stats-head">
|
||||
<div>
|
||||
<div class="stats-title">Statistiques</div>
|
||||
<div class="stats-meta">
|
||||
{{ stats.n_jours }} jours complets analysés
|
||||
<span class="stats-sep">·</span>
|
||||
{{ stats.total_weeks }} semaines
|
||||
{% if stats.avg_delta_min != 0 %}
|
||||
<span class="stats-sep">·</span>
|
||||
solde moyen
|
||||
<span class="{{ 'stat-pos' if stats.avg_delta_min > 0 else 'stat-neg' }}">{{ stats.avg_delta }}/sem</span>
|
||||
{% endif %}
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{# ── 3 période-conformité cards ── #}
|
||||
<div class="comp-periods">
|
||||
{% set periods = [
|
||||
(stats.comp_globale, "Conformité globale", "Toutes périodes"),
|
||||
(stats.comp_mois, "Ce mois", stats.mois_label),
|
||||
(stats.comp_sem_n1, "Semaine précédente", stats.prev_week_label),
|
||||
] %}
|
||||
{% for comp, title, sub in periods %}
|
||||
{% set pct = comp.pct %}
|
||||
{% set cls = 'comp-ok' if pct is not none and pct >= 95 else ('comp-warn' if pct is not none and pct >= 80 else 'comp-bad') %}
|
||||
<div class="comp-period-card">
|
||||
<div class="cp-eyebrow">{{ title }}</div>
|
||||
<div class="cp-sub">{{ sub }}</div>
|
||||
<div class="cp-donut-wrap">
|
||||
<canvas class="cp-donut" id="cpd-{{ loop.index }}" width="90" height="90"
|
||||
data-pct="{{ pct if pct is not none else 0 }}"
|
||||
data-has-data="{{ 'true' if pct is not none else 'false' }}"
|
||||
aria-label="{{ pct }}%"></canvas>
|
||||
</div>
|
||||
<div class="cp-n {{ cls if pct is not none }}">
|
||||
{% if pct is not none %}{{ comp.n_ok }}/{{ comp.n }} jours conformes
|
||||
{% else %}<span class="cp-nodata">pas de données</span>{% endif %}
|
||||
</div>
|
||||
</div>
|
||||
{% endfor %}
|
||||
</div>
|
||||
|
||||
{# ── Onglets de période ── #}
|
||||
<div class="period-tabs-wrap">
|
||||
<span class="period-tabs-label">Période d'analyse</span>
|
||||
<div class="period-tabs" role="tablist">
|
||||
<button class="ptab active" data-period="all" role="tab" aria-selected="true">Tout</button>
|
||||
<button class="ptab" data-period="1y" role="tab">1 an</button>
|
||||
<button class="ptab" data-period="3m" role="tab">3 mois</button>
|
||||
<button class="ptab" data-period="1m" role="tab">1 mois</button>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{# ── 4 time-slot cards ── #}
|
||||
<div class="ts-grid">
|
||||
{% set slot_meta = [
|
||||
("matin_entree", "Entrée matin", "≤ 09:00", "le", "matin"),
|
||||
("matin_sortie", "Sortie matin", "≥ 12:00", "ge", "matin"),
|
||||
("aprem_entree", "Entrée après-midi","≤ 14:00", "le", "aprem"),
|
||||
("aprem_sortie", "Sortie après-midi","≥ 17:00", "ge", "aprem"),
|
||||
] %}
|
||||
{% for slot, label, constraint, op, half in slot_meta %}
|
||||
{% set ts = stats.time_stats[slot] %}
|
||||
{% set comp = stats.compliance[slot] %}
|
||||
<div class="ts-card ts-{{ half }}">
|
||||
<div class="ts-eyebrow">{{ label }}</div>
|
||||
{% if ts %}
|
||||
<div class="ts-mean-row">
|
||||
<div class="ts-mean" id="ts-mean-{{ slot }}">{{ ts.mean_hhmm }}</div>
|
||||
{% if comp is not none %}
|
||||
<div class="donut-wrap">
|
||||
<canvas id="donut-{{ slot }}" class="donut-canvas" width="60" height="60"
|
||||
data-pct="{{ comp }}" data-op="{{ op }}"
|
||||
aria-label="{{ comp }}% {{ constraint }}"></canvas>
|
||||
<div class="donut-label" id="donut-label-{{ slot }}">{{ constraint }}</div>
|
||||
</div>
|
||||
{% endif %}
|
||||
</div>
|
||||
<div class="ts-sigma" id="ts-sigma-{{ slot }}">σ = {{ ts.sigma_min }} min · n = {{ ts.n }}</div>
|
||||
<canvas class="dist-canvas zoomable" id="dist-{{ slot }}" width="1" height="76"
|
||||
data-chart-type="dist" data-chart-slot="{{ slot }}"
|
||||
data-chart-title="{{ label }}"
|
||||
aria-label="Distribution {{ label }}"></canvas>
|
||||
<div class="dist-legend">
|
||||
<span class="dl-item"><span class="dl-mean-line"></span>μ = <span id="dl-mean-{{ slot }}">{{ ts.mean_hhmm }}</span></span>
|
||||
<span class="dl-item"><span class="dl-target-line {{ 'dl-neg' if op == 'le' else 'dl-pos' }}"></span>{{ constraint }}</span>
|
||||
<span class="dl-item"><span class="dl-band ts-{{ half }}"></span>±1σ (<span id="dl-sigma-{{ slot }}">{{ ts.sigma_min }}</span> min)</span>
|
||||
<span class="dl-item dl-n">n = <span id="dl-n-{{ slot }}">{{ ts.n }}</span> jours</span>
|
||||
</div>
|
||||
{% else %}
|
||||
<div class="ts-mean ts-empty">—</div>
|
||||
<div class="ts-sigma">pas de données</div>
|
||||
{% endif %}
|
||||
</div>
|
||||
{% endfor %}
|
||||
</div>
|
||||
|
||||
{# ── Weekly balance chart ── #}
|
||||
{% if stats.weekly_balances %}
|
||||
<div class="wkly-section">
|
||||
<div class="wkly-eyebrow">Soldes hebdomadaires <span class="wkly-note">(jours incomplets exclus)</span></div>
|
||||
<div class="wkly-wrap">
|
||||
<canvas id="c-weekly" class="zoomable" height="180"
|
||||
data-chart-type="weekly" data-chart-title="Soldes hebdomadaires"
|
||||
aria-label="Soldes hebdomadaires"></canvas>
|
||||
</div>
|
||||
{% set has_partial = stats.weekly_balances | selectattr("partial") | list %}
|
||||
{% if has_partial %}
|
||||
<div class="wkly-legend">
|
||||
<span class="legend-dot partial-dot"></span> semaine avec jours non renseignés
|
||||
</div>
|
||||
{% endif %}
|
||||
</div>
|
||||
{% endif %}
|
||||
|
||||
{# ── Zoom modal ── #}
|
||||
<div id="chart-modal" class="chart-modal" hidden aria-modal="true" role="dialog" aria-labelledby="chart-modal-title">
|
||||
<div class="chart-modal-bd" id="chart-modal-bd"></div>
|
||||
<div class="chart-modal-inner">
|
||||
<div class="chart-modal-header">
|
||||
<span id="chart-modal-title" class="chart-modal-title"></span>
|
||||
<button class="chart-modal-close" id="chart-modal-close" aria-label="Fermer">✕</button>
|
||||
</div>
|
||||
<div class="chart-modal-body">
|
||||
<canvas id="chart-modal-canvas"></canvas>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<script>
|
||||
(function () {
|
||||
const DATA = {{ data_json | safe }};
|
||||
|
||||
const C = {
|
||||
pos: '#2A5E42', neg: '#9B3528',
|
||||
accent: '#2F5FA0', accent2: '#B86A08', warn: '#B86A08',
|
||||
rule: '#D8D0C0', ruleL: '#EAE5DA',
|
||||
text: '#1C1712', muted: '#6B6152',
|
||||
ground: '#F4F0E8', surface: '#FDFAF4',
|
||||
};
|
||||
const MONO = "'DM Mono', 'Cascadia Code', ui-monospace, monospace";
|
||||
const SLOTS = ['matin_entree', 'matin_sortie', 'aprem_entree', 'aprem_sortie'];
|
||||
const SLOT_COLOR = { matin_entree: C.accent, matin_sortie: C.accent, aprem_entree: C.accent2, aprem_sortie: C.accent2 };
|
||||
const SLOT_TARGET = { matin_entree: [9*60,'le'], matin_sortie: [12*60,'ge'], aprem_entree: [14*60,'le'], aprem_sortie: [17*60,'ge'] };
|
||||
|
||||
let currentPeriod = 'all';
|
||||
|
||||
/* ─── Period filtering ─── */
|
||||
function getCutoff(period) {
|
||||
if (period === 'all') return null;
|
||||
const d = new Date(DATA.today);
|
||||
if (period === '1m') d.setMonth(d.getMonth() - 1);
|
||||
else if (period === '3m') d.setMonth(d.getMonth() - 3);
|
||||
else if (period === '1y') d.setFullYear(d.getFullYear() - 1);
|
||||
return d;
|
||||
}
|
||||
|
||||
function filterVals(slot, period) {
|
||||
const dv = DATA.time_stats[slot]?.dated_values;
|
||||
if (!dv) return [];
|
||||
const cutoff = getCutoff(period);
|
||||
return cutoff
|
||||
? dv.filter(x => new Date(x.d) >= cutoff).map(x => x.v)
|
||||
: dv.map(x => x.v);
|
||||
}
|
||||
|
||||
function filterWeekly(period) {
|
||||
const cutoff = getCutoff(period);
|
||||
if (!cutoff) return DATA.weekly_balances;
|
||||
return DATA.weekly_balances.filter(b => new Date(b.date) >= cutoff);
|
||||
}
|
||||
|
||||
/* ─── Stats helpers ─── */
|
||||
function _mean(arr) { return arr.length ? arr.reduce((a,b) => a+b,0) / arr.length : 0; }
|
||||
function _sigma(arr) {
|
||||
if (arr.length < 2) return 0;
|
||||
const m = _mean(arr);
|
||||
return Math.sqrt(arr.reduce((a,b) => a+(b-m)**2, 0) / (arr.length-1));
|
||||
}
|
||||
function _fmtMin(m) {
|
||||
const h = Math.floor(m/60), mm = m%60;
|
||||
return `${h.toString().padStart(2,'0')}:${mm.toString().padStart(2,'0')}`;
|
||||
}
|
||||
function _compPct(vals, target, op) {
|
||||
if (!vals.length) return null;
|
||||
const ok = vals.filter(v => op === 'le' ? v <= target : v >= target).length;
|
||||
return Math.round(100 * ok / vals.length);
|
||||
}
|
||||
|
||||
/* ─── Donut ─── */
|
||||
function drawDonut(canvas, pct, op, progress) {
|
||||
const W = canvas.width, H = canvas.height;
|
||||
const ctx = canvas.getContext('2d');
|
||||
ctx.clearRect(0, 0, W, H);
|
||||
const cx = W/2, cy = H/2;
|
||||
const outerR = Math.min(W,H)/2 - 2;
|
||||
const lw = outerR * 0.38;
|
||||
const r = outerR - lw/2;
|
||||
ctx.beginPath(); ctx.arc(cx, cy, r, 0, 2*Math.PI);
|
||||
ctx.strokeStyle = C.ruleL; ctx.lineWidth = lw; ctx.stroke();
|
||||
if (pct === null) {
|
||||
ctx.fillStyle = C.muted; ctx.font = `400 ${Math.round(W*0.19)}px ${MONO}`;
|
||||
ctx.textAlign = 'center'; ctx.textBaseline = 'middle'; ctx.fillText('—', cx, cy);
|
||||
return;
|
||||
}
|
||||
const color = pct >= 95 ? C.pos : (pct >= 80 ? C.warn : C.neg);
|
||||
ctx.beginPath(); ctx.arc(cx, cy, r, -Math.PI/2, -Math.PI/2 + 2*Math.PI*(pct/100)*progress);
|
||||
ctx.strokeStyle = color; ctx.lineWidth = lw; ctx.lineCap = 'butt'; ctx.stroke();
|
||||
if (progress >= 1) {
|
||||
ctx.fillStyle = color;
|
||||
ctx.font = `500 ${Math.round(W*0.19)}px ${MONO}`;
|
||||
ctx.textAlign = 'center'; ctx.textBaseline = 'middle';
|
||||
ctx.fillText(pct + '%', cx, cy);
|
||||
}
|
||||
}
|
||||
|
||||
function animateDonut(canvas, pct, op) {
|
||||
if (pct === null) { drawDonut(canvas, null, op, 1); return; }
|
||||
if (window.matchMedia('(prefers-reduced-motion: reduce)').matches) { drawDonut(canvas, pct, op, 1); return; }
|
||||
const DUR = 600; let t0 = null;
|
||||
function step(ts) {
|
||||
if (!t0) t0 = ts;
|
||||
const p = Math.min((ts-t0)/DUR, 1);
|
||||
drawDonut(canvas, pct, op, 1-Math.pow(1-p,3));
|
||||
if (p < 1) requestAnimationFrame(step);
|
||||
}
|
||||
requestAnimationFrame(step);
|
||||
}
|
||||
|
||||
/* ─── Distribution core ─── */
|
||||
function _drawDistVals(canvas, vals, mean, sigma, target, op, color, enlarged) {
|
||||
if (!vals || !vals.length) return;
|
||||
const W = canvas.width, H = canvas.height;
|
||||
const ctx = canvas.getContext('2d');
|
||||
ctx.clearRect(0, 0, W, H);
|
||||
|
||||
const lo = Math.min(...vals, target) - 15;
|
||||
const hi = Math.max(...vals, target) + 15;
|
||||
const range = hi - lo || 1;
|
||||
const toX = v => ((v - lo) / range) * W;
|
||||
const PAD_T = 4, PAD_B = H > 60 ? 20 : 4, chartH = H - PAD_T - PAD_B;
|
||||
const targetColor = op === 'le' ? C.neg : C.pos;
|
||||
|
||||
const binSize = 5;
|
||||
const nBins = Math.ceil((hi-lo)/binSize) + 1;
|
||||
const bins = new Array(nBins).fill(0);
|
||||
vals.forEach(v => { const b = Math.min(Math.floor((v-lo)/binSize), nBins-1); bins[b]++; });
|
||||
const maxBin = Math.max(...bins, 1);
|
||||
|
||||
// σ band
|
||||
ctx.fillStyle = color === C.accent ? 'rgba(47,95,160,.09)' : 'rgba(184,106,8,.09)';
|
||||
const sLo = Math.max(0, toX(mean-sigma)), sHi = Math.min(W, toX(mean+sigma));
|
||||
ctx.fillRect(sLo, 0, sHi-sLo, PAD_T+chartH);
|
||||
|
||||
// Bars
|
||||
const bw = Math.max(1, (W/nBins) - 0.5);
|
||||
bins.forEach((count, i) => {
|
||||
if (!count) return;
|
||||
const x = (i/nBins)*W, bh = (count/maxBin)*chartH;
|
||||
ctx.fillStyle = color + 'BB';
|
||||
ctx.fillRect(x, PAD_T+chartH-bh, bw, bh);
|
||||
});
|
||||
|
||||
// Baseline
|
||||
ctx.strokeStyle = C.rule; ctx.lineWidth = 0.5;
|
||||
ctx.beginPath(); ctx.moveTo(0, PAD_T+chartH); ctx.lineTo(W, PAD_T+chartH); ctx.stroke();
|
||||
|
||||
// Target line
|
||||
const tx = toX(target);
|
||||
if (tx >= 0 && tx <= W) {
|
||||
ctx.save(); ctx.strokeStyle = targetColor; ctx.lineWidth = 1.5; ctx.setLineDash([3,3]);
|
||||
ctx.beginPath(); ctx.moveTo(tx, PAD_T); ctx.lineTo(tx, PAD_T+chartH); ctx.stroke(); ctx.restore();
|
||||
}
|
||||
|
||||
// Mean line
|
||||
ctx.strokeStyle = C.text; ctx.lineWidth = 1.5;
|
||||
ctx.beginPath(); ctx.moveTo(toX(mean), PAD_T); ctx.lineTo(toX(mean), PAD_T+chartH); ctx.stroke();
|
||||
|
||||
// X axis labels
|
||||
if (PAD_B > 10) {
|
||||
const tickStep = enlarged ? 15 : 30;
|
||||
const firstTick = Math.ceil(lo/tickStep)*tickStep;
|
||||
const labelY = PAD_T+chartH+5;
|
||||
const fs = Math.max(7, Math.min(9, Math.floor(W/28)));
|
||||
ctx.textBaseline = 'top';
|
||||
|
||||
let ticks;
|
||||
if (enlarged) {
|
||||
ticks = new Set();
|
||||
for (let t = firstTick; t <= hi; t += tickStep) {
|
||||
if (toX(t) >= 2 && toX(t) <= W-2) ticks.add(t);
|
||||
}
|
||||
} else {
|
||||
ticks = new Set([Math.round(target/tickStep)*tickStep]);
|
||||
let lastX = -999;
|
||||
for (let t = firstTick; t <= hi; t += tickStep) {
|
||||
const x = toX(t);
|
||||
if (x >= 4 && x <= W-4 && x-lastX >= 30) { ticks.add(t); lastX = x; }
|
||||
}
|
||||
}
|
||||
|
||||
ticks.forEach(t => {
|
||||
const x = toX(t);
|
||||
if (x < 0 || x > W) return;
|
||||
const isTarget = (t === target);
|
||||
const isMean = !isTarget && Math.abs(t - Math.round(mean/tickStep)*tickStep) < 2;
|
||||
ctx.textAlign = x < 16 ? 'left' : (x > W-16 ? 'right' : 'center');
|
||||
ctx.fillStyle = isTarget ? targetColor : (isMean ? C.text : C.muted);
|
||||
ctx.font = `${isTarget||isMean?'500':'400'} ${fs}px ${MONO}`;
|
||||
ctx.strokeStyle = isTarget ? targetColor : C.rule;
|
||||
ctx.lineWidth = isTarget ? 1 : 0.5;
|
||||
ctx.beginPath(); ctx.moveTo(x, PAD_T+chartH); ctx.lineTo(x, PAD_T+chartH+3); ctx.stroke();
|
||||
ctx.fillText(_fmtMin(t), x, labelY);
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
function _drawDist(canvas, slot, enlarged) {
|
||||
const stat = DATA.time_stats[slot];
|
||||
if (!stat) return;
|
||||
const vals = filterVals(slot, currentPeriod);
|
||||
if (!vals.length) return;
|
||||
const mean = _mean(vals), sigma = _sigma(vals);
|
||||
const [target, op] = SLOT_TARGET[slot];
|
||||
_drawDistVals(canvas, vals, mean, sigma, target, op, SLOT_COLOR[slot], enlarged);
|
||||
}
|
||||
|
||||
function drawDist(slot) {
|
||||
const c = document.getElementById('dist-'+slot);
|
||||
if (!c) return;
|
||||
c.width = c.parentElement.clientWidth || 240;
|
||||
_drawDist(c, slot, false);
|
||||
}
|
||||
|
||||
/* ─── Weekly bars ─── */
|
||||
function _drawWeekly(canvas, balances) {
|
||||
if (!balances || !balances.length) return;
|
||||
const W = canvas.width, H = canvas.height;
|
||||
const ctx = canvas.getContext('2d');
|
||||
ctx.clearRect(0, 0, W, H);
|
||||
|
||||
const PAD_L = 42, PAD_R = 12, PAD_T = 12, PAD_B = 42;
|
||||
const chartW = W-PAD_L-PAD_R, chartH = H-PAD_T-PAD_B;
|
||||
const midY = PAD_T+chartH/2;
|
||||
const maxAbs = Math.max(...balances.map(b => Math.abs(b.delta_min)), 1);
|
||||
const axisMax = Math.ceil(maxAbs/30)*30;
|
||||
const toY = v => midY - (v/axisMax)*(chartH/2);
|
||||
const barSlot = chartW/balances.length;
|
||||
const barW = Math.max(4, Math.min(32, barSlot-3));
|
||||
|
||||
ctx.fillStyle = C.surface; ctx.fillRect(PAD_L, PAD_T, chartW, chartH);
|
||||
|
||||
ctx.strokeStyle = C.ruleL; ctx.lineWidth = 0.5;
|
||||
for (let v = 30; v <= axisMax; v += 30) {
|
||||
[toY(v), toY(-v)].forEach(y => {
|
||||
ctx.beginPath(); ctx.moveTo(PAD_L,y); ctx.lineTo(PAD_L+chartW,y); ctx.stroke();
|
||||
});
|
||||
}
|
||||
ctx.strokeStyle = C.rule; ctx.lineWidth = 1;
|
||||
ctx.beginPath(); ctx.moveTo(PAD_L,midY); ctx.lineTo(PAD_L+chartW,midY); ctx.stroke();
|
||||
|
||||
ctx.fillStyle = C.muted; ctx.font = `9px ${MONO}`; ctx.textAlign = 'right';
|
||||
for (let v = 60; v <= axisMax; v += 60) {
|
||||
const h = Math.floor(v/60);
|
||||
ctx.fillText(`+${h}h`, PAD_L-5, toY(v)+3);
|
||||
ctx.fillText(`-${h}h`, PAD_L-5, toY(-v)+3);
|
||||
}
|
||||
ctx.fillText('0', PAD_L-5, midY+3);
|
||||
|
||||
balances.forEach((b, i) => {
|
||||
const x = PAD_L+i*barSlot+(barSlot-barW)/2;
|
||||
const hPx = (Math.abs(b.delta_min)/axisMax)*(chartH/2);
|
||||
const baseColor = b.delta_min >= 0 ? C.pos : C.neg;
|
||||
const alpha = b.partial ? '55' : 'CC';
|
||||
if (b.delta_min >= 0) {
|
||||
const g = ctx.createLinearGradient(x, midY-hPx, x, midY);
|
||||
g.addColorStop(0, baseColor+alpha); g.addColorStop(1, baseColor+(b.partial?'33':'88'));
|
||||
ctx.fillStyle = g; ctx.fillRect(x, midY-hPx, barW, hPx);
|
||||
} else {
|
||||
const g = ctx.createLinearGradient(x, midY, x, midY+hPx);
|
||||
g.addColorStop(0, baseColor+(b.partial?'33':'88')); g.addColorStop(1, baseColor+alpha);
|
||||
ctx.fillStyle = g; ctx.fillRect(x, midY, barW, hPx);
|
||||
}
|
||||
if (b.partial && hPx > 2) {
|
||||
const yEdge = b.delta_min >= 0 ? midY-hPx : midY+hPx;
|
||||
ctx.save(); ctx.strokeStyle = baseColor+'88'; ctx.lineWidth=1; ctx.setLineDash([2,2]);
|
||||
ctx.beginPath(); ctx.moveTo(x,yEdge); ctx.lineTo(x+barW,yEdge); ctx.stroke(); ctx.restore();
|
||||
}
|
||||
});
|
||||
|
||||
ctx.font = `9px ${MONO}`; ctx.fillStyle = C.muted;
|
||||
ctx.textAlign = 'right'; ctx.textBaseline = 'middle';
|
||||
balances.forEach((b, i) => {
|
||||
const x = PAD_L+i*barSlot+barSlot/2, y = PAD_T+chartH+8;
|
||||
ctx.save(); ctx.translate(x,y); ctx.rotate(-Math.PI/4); ctx.fillText(b.label,0,0); ctx.restore();
|
||||
});
|
||||
|
||||
ctx.strokeStyle = C.rule; ctx.lineWidth = 1;
|
||||
ctx.strokeRect(PAD_L, PAD_T, chartW, chartH);
|
||||
}
|
||||
|
||||
function drawWeekly() {
|
||||
const c = document.getElementById('c-weekly');
|
||||
if (!c) return;
|
||||
c.width = c.parentElement.clientWidth || 800;
|
||||
const balances = filterWeekly(currentPeriod);
|
||||
if (window.matchMedia('(prefers-reduced-motion: reduce)').matches) {
|
||||
_drawWeekly(c, balances); return;
|
||||
}
|
||||
const DUR = 500; let t0 = null;
|
||||
function step(ts) {
|
||||
if (!t0) t0 = ts;
|
||||
const p = Math.min((ts-t0)/DUR, 1);
|
||||
const ease = 1-Math.pow(1-p,3);
|
||||
// Animate bar heights by scaling delta_min
|
||||
const scaled = balances.map(b => ({...b, delta_min: b.delta_min * ease}));
|
||||
_drawWeekly(c, scaled);
|
||||
if (p < 1) requestAnimationFrame(step);
|
||||
}
|
||||
requestAnimationFrame(step);
|
||||
}
|
||||
|
||||
/* ─── Update everything for a period ─── */
|
||||
function updateForPeriod(period) {
|
||||
currentPeriod = period;
|
||||
|
||||
SLOTS.forEach(slot => {
|
||||
if (!DATA.time_stats[slot]) return;
|
||||
const vals = filterVals(slot, period);
|
||||
const [target, op] = SLOT_TARGET[slot];
|
||||
|
||||
if (!vals.length) {
|
||||
const meanEl = document.getElementById('ts-mean-'+slot);
|
||||
if (meanEl) meanEl.textContent = '—';
|
||||
const sigmaEl = document.getElementById('ts-sigma-'+slot);
|
||||
if (sigmaEl) sigmaEl.textContent = 'pas de données pour cette période';
|
||||
const donutEl = document.getElementById('donut-'+slot);
|
||||
if (donutEl) drawDonut(donutEl, null, op, 1);
|
||||
return;
|
||||
}
|
||||
|
||||
const m = _mean(vals), s = _sigma(vals);
|
||||
const pct = _compPct(vals, target, op);
|
||||
|
||||
// Update text
|
||||
const meanEl = document.getElementById('ts-mean-'+slot);
|
||||
if (meanEl) meanEl.textContent = _fmtMin(Math.round(m));
|
||||
const sigmaEl = document.getElementById('ts-sigma-'+slot);
|
||||
if (sigmaEl) sigmaEl.textContent = `σ = ${Math.round(s)} min · n = ${vals.length}`;
|
||||
|
||||
// Update legend
|
||||
const dlMean = document.getElementById('dl-mean-'+slot);
|
||||
if (dlMean) dlMean.textContent = _fmtMin(Math.round(m));
|
||||
const dlSigma = document.getElementById('dl-sigma-'+slot);
|
||||
if (dlSigma) dlSigma.textContent = Math.round(s);
|
||||
const dlN = document.getElementById('dl-n-'+slot);
|
||||
if (dlN) dlN.textContent = vals.length;
|
||||
|
||||
// Redraw distribution
|
||||
const c = document.getElementById('dist-'+slot);
|
||||
if (c) {
|
||||
c.width = c.parentElement.clientWidth || 240;
|
||||
_drawDistVals(c, vals, m, s, target, op, SLOT_COLOR[slot], false);
|
||||
}
|
||||
|
||||
// Redraw donut
|
||||
const donutEl = document.getElementById('donut-'+slot);
|
||||
if (donutEl) drawDonut(donutEl, pct, op, 1);
|
||||
});
|
||||
|
||||
drawWeekly();
|
||||
}
|
||||
|
||||
/* ─── Zoom modal ─── */
|
||||
function openModal(sourceCanvas) {
|
||||
const type = sourceCanvas.dataset.chartType;
|
||||
const slot = sourceCanvas.dataset.chartSlot;
|
||||
const title = sourceCanvas.dataset.chartTitle || '';
|
||||
const mc = document.getElementById('chart-modal-canvas');
|
||||
const maxW = Math.floor(Math.min(window.innerWidth*0.88, 1050));
|
||||
|
||||
document.getElementById('chart-modal-title').textContent = title;
|
||||
|
||||
if (type === 'dist') {
|
||||
mc.width = maxW; mc.height = 180;
|
||||
_drawDist(mc, slot, true);
|
||||
} else if (type === 'weekly') {
|
||||
mc.width = maxW; mc.height = 300;
|
||||
_drawWeekly(mc, filterWeekly(currentPeriod));
|
||||
}
|
||||
|
||||
document.getElementById('chart-modal').removeAttribute('hidden');
|
||||
document.body.style.overflow = 'hidden';
|
||||
document.getElementById('chart-modal-close').focus();
|
||||
}
|
||||
|
||||
function closeModal() {
|
||||
document.getElementById('chart-modal').setAttribute('hidden', '');
|
||||
document.body.style.overflow = '';
|
||||
}
|
||||
|
||||
/* ─── Init ─── */
|
||||
function init() {
|
||||
[1,2,3].forEach(i => {
|
||||
const el = document.getElementById('cpd-'+i);
|
||||
if (!el) return;
|
||||
el.dataset.hasData === 'true'
|
||||
? animateDonut(el, parseInt(el.dataset.pct), 'day')
|
||||
: (function(){
|
||||
const ctx = el.getContext('2d');
|
||||
const W=el.width,H=el.height,cx=W/2,cy=H/2;
|
||||
const r=(Math.min(W,H)/2-2)*0.69;
|
||||
ctx.beginPath(); ctx.arc(cx,cy,r,0,2*Math.PI);
|
||||
ctx.strokeStyle=C.ruleL; ctx.lineWidth=(Math.min(W,H)/2-2)*0.38; ctx.stroke();
|
||||
ctx.fillStyle=C.muted; ctx.font=`400 13px ${MONO}`;
|
||||
ctx.textAlign='center'; ctx.textBaseline='middle'; ctx.fillText('—',cx,cy);
|
||||
})();
|
||||
});
|
||||
|
||||
SLOTS.forEach(slot => {
|
||||
drawDist(slot);
|
||||
const el = document.getElementById('donut-'+slot);
|
||||
if (el) animateDonut(el, parseInt(el.dataset.pct), el.dataset.op);
|
||||
});
|
||||
drawWeekly();
|
||||
}
|
||||
|
||||
if (document.readyState === 'loading') {
|
||||
document.addEventListener('DOMContentLoaded', init);
|
||||
} else { init(); }
|
||||
|
||||
// Tabs
|
||||
document.querySelectorAll('.ptab').forEach(btn => {
|
||||
btn.addEventListener('click', () => {
|
||||
document.querySelectorAll('.ptab').forEach(b => {
|
||||
b.classList.remove('active'); b.setAttribute('aria-selected','false');
|
||||
});
|
||||
btn.classList.add('active'); btn.setAttribute('aria-selected','true');
|
||||
updateForPeriod(btn.dataset.period);
|
||||
});
|
||||
});
|
||||
|
||||
// Zoom
|
||||
document.addEventListener('click', e => { const c = e.target.closest('canvas.zoomable'); if (c) openModal(c); });
|
||||
document.getElementById('chart-modal-close').addEventListener('click', closeModal);
|
||||
document.getElementById('chart-modal-bd').addEventListener('click', closeModal);
|
||||
document.addEventListener('keydown', e => { if (e.key === 'Escape') closeModal(); });
|
||||
|
||||
let resizeTimer;
|
||||
window.addEventListener('resize', () => { clearTimeout(resizeTimer); resizeTimer = setTimeout(init, 120); });
|
||||
})();
|
||||
</script>
|
||||
|
||||
{% endblock %}
|
||||
Reference in New Issue
Block a user