diff --git a/backend/data_layer/nutrition_interpretation.py b/backend/data_layer/nutrition_interpretation.py
index a014576..4178f8e 100644
--- a/backend/data_layer/nutrition_interpretation.py
+++ b/backend/data_layer/nutrition_interpretation.py
@@ -121,8 +121,7 @@ def build_nutrition_history_kpi_tiles(
"status": "bad",
"verdict": _verdict("bad"),
"hint": (
- f"Es fehlen rund {miss} g Protein pro Tag – bei Kaloriendefizit "
- "steigt das Risiko für Muskelerhalt."
+ f"~{miss} g Protein/Tag fehlen – bei Defizit Muskelerhalt gefährdet."
),
"hoverTop": f"Unterversorgung: {avg_protein}g/Tag (Ziel {pt_low}–{pt_high}g)",
"hoverBody": (
@@ -159,8 +158,8 @@ def build_nutrition_history_kpi_tiles(
"status": "warn",
"verdict": _verdict("warn"),
"hint": (
- f"Viele Kalorien kommen aus KH/Fett; Proteinanteil oft sinnvoll bei 25–35 % "
- f"(aktuell P {prot_pct} % / KH {kh_pct} % / F {fat_pct} %)."
+ f"Protein-Kalorienanteil niedrig (P {prot_pct} % / KH {kh_pct} % / F {fat_pct} %); "
+ "Ziel oft 25–35 %."
),
"hoverTop": f"Protein-Anteil niedrig: {prot_pct}% der Kalorien",
"hoverBody": (
@@ -173,6 +172,37 @@ def build_nutrition_history_kpi_tiles(
return tiles
+def build_energy_availability_kpi_tile(ea: Dict[str, Any]) -> Optional[Dict[str, Any]]:
+ """E5: nur bei caution/warning — gleiche Daten wie /charts/energy-availability-warning."""
+ level = str(ea.get("warning_level") or "none").strip().lower()
+ if level == "none":
+ return None
+ triggers: List[str] = list(ea.get("triggers") or [])
+ msg = str(ea.get("message") or "").strip()
+ st = "bad" if level == "warning" else "warn"
+ first = triggers[0] if triggers else msg
+ if len(first) > 90:
+ first = first[:87] + "…"
+ meta = ea.get("metadata") if isinstance(ea.get("metadata"), dict) else {}
+ note = str(meta.get("note") or "")
+ hover_lines = [msg] + [f"• {t}" for t in triggers]
+ if note:
+ hover_lines.append(note)
+ return {
+ "key": "energy-availability-e5",
+ "category": "Energieverfügbarkeit",
+ "icon": "⚡",
+ "value": "Achtung" if level == "warning" else "Hinweis",
+ "sublabel": first or "Signale prüfen",
+ "status": st,
+ "verdict": _verdict(st),
+ "hint": msg,
+ "hoverTop": "Energieverfügbarkeit (Heuristik)",
+ "hoverBody": "\n".join(hover_lines),
+ "keys": ["nutrition_score"],
+ }
+
+
def build_macro_donut_from_averages(navg: Dict[str, Any]) -> Optional[List[Dict[str, Any]]]:
"""Anteile in % der Makro-kcal + Gramm für Legende."""
p = float(navg.get("protein_avg") or 0)
diff --git a/backend/data_layer/nutrition_metrics.py b/backend/data_layer/nutrition_metrics.py
index 33c844a..b3865d8 100644
--- a/backend/data_layer/nutrition_metrics.py
+++ b/backend/data_layer/nutrition_metrics.py
@@ -699,6 +699,70 @@ def get_weekly_macro_distribution_chart_data(profile_id: str, weeks: int) -> Dic
}
+def get_energy_availability_warning_payload(profile_id: str, days: int = 14) -> Dict:
+ """
+ E5 Energieverfügbarkeit — gleiche Heuristik wie GET /charts/energy-availability-warning.
+ """
+ from data_layer.recovery_metrics import calculate_recovery_score_v2, calculate_sleep_quality_7d
+ from data_layer.body_metrics import calculate_lbm_28d_change
+
+ triggers: List[str] = []
+ warning_level = "none"
+
+ energy_data = get_energy_balance_data(profile_id, days)
+ if energy_data.get("energy_balance", 0) < -500:
+ triggers.append("Großes Energiedefizit (>500 kcal/Tag)")
+
+ try:
+ recovery_score = calculate_recovery_score_v2(profile_id)
+ if recovery_score and recovery_score < 50:
+ triggers.append("Recovery Score niedrig (<50)")
+ except Exception:
+ pass
+
+ try:
+ sleep_quality = calculate_sleep_quality_7d(profile_id)
+ if sleep_quality and sleep_quality < 60:
+ triggers.append("Schlafqualität reduziert (<60%)")
+ except Exception:
+ pass
+
+ try:
+ lbm_change = calculate_lbm_28d_change(profile_id)
+ if lbm_change and lbm_change < -1.0:
+ triggers.append("Magermasse sinkt (-{:.1f} kg)".format(abs(lbm_change)))
+ except Exception:
+ pass
+
+ if len(triggers) >= 3:
+ warning_level = "warning"
+ message = (
+ "⚠️ Hinweis auf mögliche Unterversorgung. Mehrere Indikatoren auffällig. "
+ "Erwäge Defizit-Anpassung oder Regenerationswoche."
+ )
+ elif len(triggers) >= 2:
+ warning_level = "caution"
+ message = (
+ "⚡ Beobachte folgende Signale genau. Aktuell noch kein Handlungsbedarf, aber Trend beachten."
+ )
+ elif len(triggers) >= 1:
+ warning_level = "caution"
+ message = "💡 Ein Indikator auffällig. Weiter beobachten."
+ else:
+ message = "✅ Energieverfügbarkeit unauffällig."
+
+ return {
+ "warning_level": warning_level,
+ "triggers": triggers,
+ "message": message,
+ "metadata": {
+ "days_analyzed": days,
+ "trigger_count": len(triggers),
+ "note": "Heuristische Einschätzung, keine medizinische Diagnose",
+ },
+ }
+
+
# ============================================================================
# Calculated Metrics (migrated from calculations/nutrition_metrics.py)
# ============================================================================
diff --git a/backend/data_layer/nutrition_viz.py b/backend/data_layer/nutrition_viz.py
index f05b0a5..8891cf6 100644
--- a/backend/data_layer/nutrition_viz.py
+++ b/backend/data_layer/nutrition_viz.py
@@ -11,11 +11,13 @@ from typing import Any, Dict, List, Optional
from db import get_db, get_cursor, r2d
from data_layer.nutrition_interpretation import (
+ build_energy_availability_kpi_tile,
build_macro_donut_from_averages,
build_nutrition_history_kpi_tiles,
)
from data_layer.nutrition_metrics import (
estimate_tdee_kcal_from_latest_weight,
+ get_energy_availability_warning_payload,
get_energy_balance_data,
get_nutrition_average_data,
get_protein_targets_data,
@@ -184,12 +186,14 @@ def get_nutrition_history_viz_bundle(profile_id: str, days: int) -> Dict[str, An
"tdee_reference_kcal": None,
"energy_balance_meta": {},
"interpretation_tiles": [],
+ "energy_availability_warning": None,
"meta": {"layer_1": "nutrition_metrics", "layer_2b": "nutrition_viz"},
}
all_history = days >= 9999
eff_days = 3650 if all_history else max(7, min(int(days), 3650))
cutoff = _cutoff_sql(days)
+ chart_days_for_pipeline = 90 if all_history else max(7, min(eff_days, 365))
navg = get_nutrition_average_data(profile_id, eff_days, all_history=all_history)
targets = get_protein_targets_data(profile_id)
@@ -223,12 +227,18 @@ def get_nutrition_history_viz_bundle(profile_id: str, days: int) -> Dict[str, An
navg, targets, date_span_label or "—", max(1, n_days)
)
+ ea_days = min(28, max(7, chart_days_for_pipeline))
+ ea_payload = get_energy_availability_warning_payload(profile_id, ea_days)
+ ea_tile = build_energy_availability_kpi_tile(ea_payload)
+ kpi_tiles_out: List[Dict[str, Any]] = list(kpi_tiles)
+ if ea_tile:
+ kpi_tiles_out.append(ea_tile)
+
donut = build_macro_donut_from_averages(navg)
kw_points = _kcal_weight_points_for_window(profile_id, cutoff)
pt_low = round(float(targets.get("protein_target_low") or 0))
- chart_days_for_pipeline = 90 if all_history else max(7, min(eff_days, 365))
weeks_for_weekly = max(4, min(52, (chart_days_for_pipeline + 6) // 7))
weekly_chart = get_weekly_macro_distribution_chart_data(profile_id, weeks_for_weekly)
@@ -255,8 +265,9 @@ def get_nutrition_history_viz_bundle(profile_id: str, days: int) -> Dict[str, An
"protein_target_high": targets.get("protein_target_high"),
"reference_weight_kg": targets.get("current_weight"),
},
- "kpi_tiles": kpi_tiles,
+ "kpi_tiles": kpi_tiles_out,
"interpretation_tiles": [],
+ "energy_availability_warning": ea_payload,
"daily_macros": daily_macros,
"donut_avg_pct": donut,
"protein_reference_line_g": pt_low,
diff --git a/backend/routers/charts.py b/backend/routers/charts.py
index eee336a..fca7c36 100644
--- a/backend/routers/charts.py
+++ b/backend/routers/charts.py
@@ -40,6 +40,7 @@ from data_layer.nutrition_metrics import (
get_macro_consistency_data,
get_energy_balance_data,
get_weekly_macro_distribution_chart_data,
+ get_energy_availability_warning_payload,
)
from data_layer.activity_metrics import (
get_activity_summary_data,
@@ -1026,87 +1027,10 @@ def get_energy_availability_warning(
"""
Energy Availability Warning (E5) - Konzept-konform.
- Heuristic warning for potential undernutrition/overtraining.
-
- Checks:
- - Persistent large deficit
- - Recovery score declining
- - Sleep quality declining
- - LBM declining
-
- Args:
- days: Analysis window (7-28 days, default 14)
- session: Auth session (injected)
-
- Returns:
- {
- "warning_level": "none" | "caution" | "warning",
- "triggers": [...],
- "message": "..."
- }
+ Datenberechnung: data_layer.nutrition_metrics.get_energy_availability_warning_payload
"""
profile_id = session['profile_id']
-
- from db import get_db, get_cursor
- from data_layer.nutrition_metrics import get_energy_balance_data
- from data_layer.recovery_metrics import calculate_recovery_score_v2, calculate_sleep_quality_7d
- from data_layer.body_metrics import calculate_lbm_28d_change
-
- triggers = []
- warning_level = "none"
-
- # Check 1: Large energy deficit
- energy_data = get_energy_balance_data(profile_id, days)
- if energy_data.get('energy_balance', 0) < -500:
- triggers.append("Großes Energiedefizit (>500 kcal/Tag)")
-
- # Check 2: Recovery declining
- try:
- recovery_score = calculate_recovery_score_v2(profile_id)
- if recovery_score and recovery_score < 50:
- triggers.append("Recovery Score niedrig (<50)")
- except:
- pass
-
- # Check 3: Sleep quality
- try:
- sleep_quality = calculate_sleep_quality_7d(profile_id)
- if sleep_quality and sleep_quality < 60:
- triggers.append("Schlafqualität reduziert (<60%)")
- except:
- pass
-
- # Check 4: LBM declining
- try:
- lbm_change = calculate_lbm_28d_change(profile_id)
- if lbm_change and lbm_change < -1.0:
- triggers.append("Magermasse sinkt (-{:.1f} kg)".format(abs(lbm_change)))
- except:
- pass
-
- # Determine warning level
- if len(triggers) >= 3:
- warning_level = "warning"
- message = "⚠️ Hinweis auf mögliche Unterversorgung. Mehrere Indikatoren auffällig. Erwäge Defizit-Anpassung oder Regenerationswoche."
- elif len(triggers) >= 2:
- warning_level = "caution"
- message = "⚡ Beobachte folgende Signale genau. Aktuell noch kein Handlungsbedarf, aber Trend beachten."
- elif len(triggers) >= 1:
- warning_level = "caution"
- message = "💡 Ein Indikator auffällig. Weiter beobachten."
- else:
- message = "✅ Energieverfügbarkeit unauffällig."
-
- return {
- "warning_level": warning_level,
- "triggers": triggers,
- "message": message,
- "metadata": {
- "days_analyzed": days,
- "trigger_count": len(triggers),
- "note": "Heuristische Einschätzung, keine medizinische Diagnose"
- }
- }
+ return get_energy_availability_warning_payload(profile_id, days)
@router.get("/training-volume")
diff --git a/frontend/src/app.css b/frontend/src/app.css
index 9cccb52..f8092ee 100644
--- a/frontend/src/app.css
+++ b/frontend/src/app.css
@@ -350,6 +350,11 @@ body { font-family: var(--font); background: var(--bg); color: var(--text1); -we
font-style: italic;
}
+/* KPI: Kurz-Hinweis max. 2 Zeilen — Details weiter per ℹ */
+.kpi-tiles-card__hint {
+ max-height: 2.8em;
+}
+
/* Verlauf Ernährung: Donut (Ø-Quote) + wöchentliche Makro-Verteilung (E3) */
.nutrition-macro-pair {
display: grid;
diff --git a/frontend/src/components/KpiTilesOverview.jsx b/frontend/src/components/KpiTilesOverview.jsx
index e6fead0..275e8a4 100644
--- a/frontend/src/components/KpiTilesOverview.jsx
+++ b/frontend/src/components/KpiTilesOverview.jsx
@@ -125,14 +125,17 @@ export default function KpiTilesOverview({
{cardHint}
diff --git a/frontend/src/components/NutritionCharts.jsx b/frontend/src/components/NutritionCharts.jsx
index acec389..cd3a7da 100644
--- a/frontend/src/components/NutritionCharts.jsx
+++ b/frontend/src/components/NutritionCharts.jsx
@@ -206,7 +206,12 @@ export function WeeklyMacroDistributionPanel({ macroWeeklyData, loading, error }
/**
* Nutrition Charts (E1–E5). Verlauf: `showWeeklyMacroDistribution={false}` wenn E3 separat (z. B. neben Donut) gerendert wird.
*/
-export default function NutritionCharts({ days = 28, showWeeklyMacroDistribution = true }) {
+export default function NutritionCharts({
+ days = 28,
+ showWeeklyMacroDistribution = true,
+ /** Verlauf: E5-Kachel liegt in nutrition-history-viz KPIs — doppelte Karte ausblenden */
+ hideEnergyAvailabilityCard = false,
+}) {
const [energyData, setEnergyData] = useState(null)
const [proteinData, setProteinData] = useState(null)
const [macroWeeklyData, setMacroWeeklyData] = useState(null)
@@ -221,15 +226,17 @@ export default function NutritionCharts({ days = 28, showWeeklyMacroDistribution
useEffect(() => {
loadCharts()
- }, [days, showWeeklyMacroDistribution])
+ }, [days, showWeeklyMacroDistribution, hideEnergyAvailabilityCard])
const loadCharts = async () => {
const tasks = [
loadEnergyBalance(),
loadProteinAdequacy(),
loadAdherence(),
- loadWarning(),
]
+ if (!hideEnergyAvailabilityCard) {
+ tasks.push(loadWarning())
+ }
if (showWeeklyMacroDistribution) {
tasks.splice(2, 0, loadMacroWeekly())
}
@@ -474,7 +481,7 @@ export default function NutritionCharts({ days = 28, showWeeklyMacroDistribution
)}
{!loading.adherence && !errors.adherence && renderAdherence()}
- {!loading.warning && !errors.warning && renderWarning()}
+ {!hideEnergyAvailabilityCard && !loading.warning && !errors.warning && renderWarning()}
)
}
diff --git a/frontend/src/pages/History.jsx b/frontend/src/pages/History.jsx
index 99be26c..c6f4591 100644
--- a/frontend/src/pages/History.jsx
+++ b/frontend/src/pages/History.jsx
@@ -700,6 +700,26 @@ function BodySection({ profile, insights, onRequest, loadingSlug, filterActiveSl
)
}
+/** TDEE-Linie muss in der kcal-Y-Domain liegen (sonst unsichtbar trotz Legende). */
+function kcalVsWeightKcalDomain(points, tdeeRef) {
+ const vals = (points || [])
+ .map(d => Number(d.kcal_avg))
+ .filter(v => !Number.isNaN(v))
+ if (!vals.length) return ['auto', 'auto']
+ let lo = Math.min(...vals)
+ let hi = Math.max(...vals)
+ const t = tdeeRef != null ? Number(tdeeRef) : NaN
+ if (!Number.isNaN(t)) {
+ lo = Math.min(lo, t)
+ hi = Math.max(hi, t)
+ }
+ const span = hi - lo || 400
+ const pad = Math.max(100, span * 0.1)
+ return [Math.max(0, Math.floor(lo - pad)), Math.ceil(hi + pad)]
+}
+
+const TDEE_REF_LINE_COLOR = '#475569'
+
/** Legende unter dem Chart: Linien + ggf. TDEE-Referenz (gestrichelt). */
function KcalVsWeightLegend({ showTdee }) {
const line = (color) => ({
@@ -753,7 +773,7 @@ function KcalVsWeightLegend({ showTdee }) {
height: 0,
verticalAlign: 'middle',
marginRight: 6,
- borderTop: '2px dashed #EA580C',
+ borderTop: `2px dashed ${TDEE_REF_LINE_COLOR}`,
opacity: 0.95,
}}
/>
@@ -774,6 +794,7 @@ function KcalVsWeightChart({ vizKcalWeight, corrData: corrRows, profile, cutoffD
}))
const n = vizKcalWeight.common_days_count ?? kcalVsW.length
const tdeeLabel = tdee != null && tdee > 0 ? Math.round(tdee) : null
+ const kcalDomain = kcalVsWeightKcalDomain(kcalVsW, tdeeLabel)
return (
@@ -786,14 +807,21 @@ function KcalVsWeightChart({ vizKcalWeight, corrData: corrRows, profile, cutoffD
-
+
[`${Math.round(v)} ${n === 'weight' ? 'kg' : 'kcal'}`, n === 'kcal_avg' ? 'Ø Kalorien' : 'Gewicht']}
/>
{tdeeLabel != null && (
-
+
)}
@@ -823,6 +851,7 @@ function KcalVsWeightChart({ vizKcalWeight, corrData: corrRows, profile, cutoffD
const bmr = sex === 'm' ? 10 * latestW + 6.25 * height - 5 * age + 5 : 10 * latestW + 6.25 * height - 5 * age - 161
const tdee = Math.round(bmr * 1.4)
const kcalVsW = rollingAvg(raw.map(d => ({ ...d, date: fmtDate(d.date) })), 'kcal')
+ const kcalDomainFb = kcalVsWeightKcalDomain(kcalVsW, tdee)
return (
@@ -836,13 +865,20 @@ function KcalVsWeightChart({ vizKcalWeight, corrData: corrRows, profile, cutoffD
-
+
[`${Math.round(v)} ${n === 'weight' ? 'kg' : 'kcal'}`, n === 'kcal_avg' ? 'Ø Kalorien' : 'Gewicht']}
/>
-
+
@@ -1054,7 +1090,7 @@ function NutritionSection({ profile, insights, onRequest, loadingSlug, filterAct
Zeitverläufe (Energie & Protein)
-
+