feat(pwa): optimize Mila app icons with safe-zone padding to prevent Android/iOS zoom crop

2026-10-12 08:25:27 +02:00
parent f5b5deaae7
commit 191c8e9143
11 changed files with 316 additions and 3 deletions
@@ -26,6 +26,9 @@ The `datastore` skill is the source of truth for all structured, repetitive, and
   - Searching for beer gardens, playgrounds, stores, or farm stands within a given radius (e.g. 500m or 1km around Grabengasse 7) using native DuckDB spatial distance.
 5. **Catalogs & Entities (`foods`, `recipes`, `places`, `people`):**
   - Upserting and reading reference data.
+6. **Baby Growth & WHO Curves (`growth.measurement`):**
+   - Logging weight (`weight_kg`) and height/length (`height_cm`).
+   - Deterministic WHO child growth standards evaluation (P3, P50 Median, P97) based on exact age in months.

 ---

@@ -139,6 +142,18 @@ uv run /home/node/mop-skills/mop-skills/skills/datastore/scripts/datastore.py pl
 # Nightly Garmin mirror sync
 uv run /home/node/mop-skills/mop-skills/skills/datastore/scripts/garmin_sync.py --days 2

+# Log Mila's weight and height measurement
+uv run /home/node/mop-skills/mop-skills/skills/datastore/scripts/datastore.py add growth.measurement \
+  --subject mila \
+  --actor agent:hebamme \
+  --payload '{"weight_kg": 7.4, "height_cm": 67.5}'
+
+# Retroactively log measurement with date
+uv run /home/node/mop-skills/mop-skills/skills/datastore/scripts/datastore.py add growth.measurement \
+  --subject mila \
+  --date 2026-06-15 \
+  --payload '{"weight_kg": 5.8, "height_cm": 60.0}'
+
 # Render Markdown views & HTML dashboards
 PYTHONPATH=/home/node/mop-skills/mop-skills/skills/datastore/scripts \
 uv run /home/node/mop-skills/mop-skills/skills/datastore/scripts/render_views.py
@@ -30,6 +30,10 @@ from zoneinfo import ZoneInfo

 import duckdb

+SCRIPT_DIR = Path(__file__).resolve().parent
+if str(SCRIPT_DIR) not in sys.path:
+    sys.path.insert(0, str(SCRIPT_DIR))
+
 logger = logging.getLogger("datastore")

 def generate_ulid() -> str:
@@ -225,6 +229,34 @@ class DatastoreEngine:
              restingHeartRate INTEGER,
              raw JSON
            );
+
+            CREATE OR REPLACE VIEW v_growth AS
+            SELECT
+              id,
+              subject,
+              actor,
+              start,
+              start AT TIME ZONE 'Europe/Berlin' AS local_time,
+              CAST(start AT TIME ZONE 'Europe/Berlin' AS DATE) AS log_date,
+              CAST(json_extract(payload, '$.weight_kg') AS DOUBLE) AS weight_kg,
+              CAST(json_extract(payload, '$.height_cm') AS DOUBLE) AS height_cm,
+              CAST(json_extract(payload, '$.head_circ_cm') AS DOUBLE) AS head_circ_cm,
+              note,
+              created_at
+            FROM events
+            WHERE kind = 'growth.measurement' AND deleted_at IS NULL;
+
+            CREATE OR REPLACE VIEW v_growth_daily AS
+            SELECT
+              subject,
+              log_date,
+              ROUND(AVG(weight_kg), 3) AS weight_kg,
+              ROUND(AVG(height_cm), 1) AS height_cm,
+              ROUND(AVG(head_circ_cm), 1) AS head_circ_cm,
+              COUNT(*) AS measurement_count
+            FROM v_growth
+            GROUP BY subject, log_date
+            ORDER BY log_date DESC;
        """)

    def _load_all_data(self):
@@ -387,6 +419,13 @@ class DatastoreEngine:
        elif kind.startswith("sleep."):
            if p1.get("type") == p2.get("type"):
                return True
+        elif kind.startswith("growth."):
+            w1, w2 = p1.get("weight_kg"), p2.get("weight_kg")
+            h1, h2 = p1.get("height_cm"), p2.get("height_cm")
+            match_w = (w1 is not None and w2 is not None and abs(float(w1) - float(w2)) < 0.001)
+            match_h = (h1 is not None and h2 is not None and abs(float(h1) - float(h2)) < 0.001)
+            if match_w or match_h:
+                return True
        return False

    def _is_duplicate_event(
@@ -870,6 +909,11 @@ class DatastoreEngine:
        if fee:
            res["feeding"] = fee[0]

+        # 6. Growth latest measurement
+        grw = self.query(f"SELECT * FROM v_growth WHERE subject = '{subject}' ORDER BY start DESC LIMIT 1")
+        if grw:
+            res["growth_latest"] = grw[0]
+
        return res

    def find_places_near(
@@ -952,6 +996,44 @@ class DatastoreEngine:
                    "bottle_count": daily[0],
                    "total_consumed_ml": daily[1],
                }
+        elif kind.startswith("growth"):
+            row = self.con.execute(
+                "SELECT weight_kg, height_cm, head_circ_cm FROM v_growth WHERE subject = ? AND log_date = ? ORDER BY start DESC LIMIT 1",
+                [subject, date_str],
+            ).fetchone()
+            if row:
+                w_kg, h_cm, hc_cm = row[0], row[1], row[2]
+                p_row = self.con.execute("SELECT birthdate FROM people WHERE id = ?", [subject]).fetchone()
+                bdate = p_row[0] if p_row and p_row[0] else datetime.date(2026, 3, 14)
+                if isinstance(bdate, str):
+                    bdate = datetime.date.fromisoformat(bdate)
+                age_days = (target_date - bdate).days
+                age_months = max(0.0, age_days / 30.4375)
+                try:
+                    from who_growth import format_growth_feedback, calculate_percentile
+                    fb_text = format_growth_feedback(w_kg, h_cm, age_months, date_str)
+                    fb_res: Dict[str, Any] = {
+                        "day_total_formatted": fb_text,
+                        "age_months": round(age_months, 2),
+                    }
+                    if w_kg is not None:
+                        pw = calculate_percentile("weight", w_kg, age_months)
+                        fb_res["weight_kg"] = w_kg
+                        fb_res["weight_percentile"] = pw["percentile"]
+                        fb_res["weight_percentile_str"] = pw["percentile_str"]
+                    if h_cm is not None:
+                        ph = calculate_percentile("height", h_cm, age_months)
+                        fb_res["height_cm"] = h_cm
+                        fb_res["height_percentile"] = ph["percentile"]
+                        fb_res["height_percentile_str"] = ph["percentile_str"]
+                    return fb_res
+                except Exception as e:
+                    logger.warning(f"Error computing growth feedback: {e}")
+                    return {
+                        "day_total_formatted": f"Wachstum ({date_str}): Gewicht {w_kg} kg, Größe {h_cm} cm",
+                        "weight_kg": w_kg,
+                        "height_cm": h_cm,
+                    }
        return {}

    # --------------------------------------------------------------------------
@@ -1013,11 +1095,11 @@ def run_mcp_server():
    TOOLS = [
        {
            "name": "datastore_add_event",
-            "description": "Log an event into the structured datastore (e.g. nutrition.intake, sleep.session, feeding.bottle). Computes all macros and totals deterministically.",
+            "description": "Log an event into the structured datastore (e.g. nutrition.intake, sleep.session, feeding.bottle, growth.measurement). Computes all macros, totals, and WHO percentiles deterministically.",
            "inputSchema": {
                "type": "object",
                "properties": {
-                    "kind": {"type": "string", "description": "e.g. 'nutrition.intake', 'sleep.session', 'feeding.bottle'"},
+                    "kind": {"type": "string", "description": "e.g. 'nutrition.intake', 'sleep.session', 'feeding.bottle', 'growth.measurement'"},
                    "subject": {"type": "string", "description": "'moritz', 'amelie', or 'mila'"},
                    "actor": {"type": "string", "description": "'agent:koch', 'agent:hebamme', 'moritz', 'amelie'"},
                    "payload": {"type": "object", "description": "Detailed payload matching the kind schema"},
@@ -0,0 +1,170 @@
+#!/usr/bin/env python3
+"""
+who_growth.py — WHO Child Growth Standards (Girls 0–24 Months)
+Deterministic percentile and z-score calculations via LMS method
+and reference curve data for Mila's growth tracking.
+"""
+
+from __future__ import annotations
+
+import math
+from typing import Any, Dict, List, Optional, Tuple
+
+# WHO Child Growth Standards (Girls: Birth to 24 Months)
+# Source: World Health Organization (WHO) Multi-centre Growth Reference Study (MGRS)
+# https://www.who.int/tools/child-growth-standards/standards
+WHO_GIRLS_WEIGHT = [
+    {"month": 0, "L": 0.3809, "M": 3.2322, "S": 0.14171, "p3": 2.4, "p50": 3.2, "p97": 4.2},
+    {"month": 1, "L": 0.1714, "M": 4.1873, "S": 0.13724, "p3": 3.2, "p50": 4.2, "p97": 5.4},
+    {"month": 2, "L": 0.0962, "M": 5.1282, "S": 0.13000, "p3": 4.0, "p50": 5.1, "p97": 6.5},
+    {"month": 3, "L": 0.0402, "M": 5.8458, "S": 0.12619, "p3": 4.6, "p50": 5.8, "p97": 7.4},
+    {"month": 4, "L": -0.0050, "M": 6.4237, "S": 0.12402, "p3": 5.1, "p50": 6.4, "p97": 8.1},
+    {"month": 5, "L": -0.0430, "M": 6.8985, "S": 0.12274, "p3": 5.5, "p50": 6.9, "p97": 8.7},
+    {"month": 6, "L": -0.0756, "M": 7.2970, "S": 0.12204, "p3": 5.8, "p50": 7.3, "p97": 9.2},
+    {"month": 7, "L": -0.1039, "M": 7.6422, "S": 0.12178, "p3": 6.1, "p50": 7.6, "p97": 9.6},
+    {"month": 8, "L": -0.1288, "M": 7.9487, "S": 0.12181, "p3": 6.3, "p50": 7.9, "p97": 10.0},
+    {"month": 9, "L": -0.1507, "M": 8.2254, "S": 0.12199, "p3": 6.6, "p50": 8.2, "p97": 10.4},
+    {"month": 10, "L": -0.1700, "M": 8.4800, "S": 0.12223, "p3": 6.8, "p50": 8.5, "p97": 10.7},
+    {"month": 11, "L": -0.1872, "M": 8.7192, "S": 0.12247, "p3": 7.0, "p50": 8.7, "p97": 11.0},
+    {"month": 12, "L": -0.2024, "M": 8.9481, "S": 0.12268, "p3": 7.1, "p50": 8.9, "p97": 11.3},
+    {"month": 13, "L": -0.2158, "M": 9.1699, "S": 0.12283, "p3": 7.3, "p50": 9.2, "p97": 11.6},
+    {"month": 14, "L": -0.2278, "M": 9.3870, "S": 0.12294, "p3": 7.5, "p50": 9.4, "p97": 11.9},
+    {"month": 15, "L": -0.2384, "M": 9.6008, "S": 0.12299, "p3": 7.7, "p50": 9.6, "p97": 12.2},
+    {"month": 16, "L": -0.2478, "M": 9.8124, "S": 0.12303, "p3": 7.8, "p50": 9.8, "p97": 12.5},
+    {"month": 17, "L": -0.2562, "M": 10.0226, "S": 0.12306, "p3": 8.0, "p50": 10.0, "p97": 12.7},
+    {"month": 18, "L": -0.2637, "M": 10.2315, "S": 0.12309, "p3": 8.2, "p50": 10.2, "p97": 13.0},
+    {"month": 19, "L": -0.2703, "M": 10.4393, "S": 0.12315, "p3": 8.3, "p50": 10.4, "p97": 13.3},
+    {"month": 20, "L": -0.2762, "M": 10.6464, "S": 0.12323, "p3": 8.5, "p50": 10.6, "p97": 13.5},
+    {"month": 21, "L": -0.2815, "M": 10.8534, "S": 0.12335, "p3": 8.7, "p50": 10.9, "p97": 13.8},
+    {"month": 22, "L": -0.2862, "M": 11.0608, "S": 0.12350, "p3": 8.8, "p50": 11.1, "p97": 14.1},
+    {"month": 23, "L": -0.2903, "M": 11.2688, "S": 0.12369, "p3": 9.0, "p50": 11.3, "p97": 14.3},
+    {"month": 24, "L": -0.2941, "M": 11.4775, "S": 0.12390, "p3": 9.2, "p50": 11.5, "p97": 14.6},
+]
+
+WHO_GIRLS_HEIGHT = [
+    {"month": 0, "L": 1.0, "M": 49.1477, "S": 0.03790, "p3": 45.6, "p50": 49.1, "p97": 52.7},
+    {"month": 1, "L": 1.0, "M": 53.6872, "S": 0.03640, "p3": 50.0, "p50": 53.7, "p97": 57.4},
+    {"month": 2, "L": 1.0, "M": 57.0673, "S": 0.03568, "p3": 53.2, "p50": 57.1, "p97": 60.9},
+    {"month": 3, "L": 1.0, "M": 59.8029, "S": 0.03520, "p3": 55.8, "p50": 59.8, "p97": 63.8},
+    {"month": 4, "L": 1.0, "M": 62.0899, "S": 0.03486, "p3": 58.0, "p50": 62.1, "p97": 66.2},
+    {"month": 5, "L": 1.0, "M": 64.0301, "S": 0.03463, "p3": 59.9, "p50": 64.0, "p97": 68.2},
+    {"month": 6, "L": 1.0, "M": 65.7311, "S": 0.03448, "p3": 61.5, "p50": 65.7, "p97": 70.0},
+    {"month": 7, "L": 1.0, "M": 67.2873, "S": 0.03441, "p3": 62.9, "p50": 67.3, "p97": 71.6},
+    {"month": 8, "L": 1.0, "M": 68.7498, "S": 0.03440, "p3": 64.3, "p50": 68.7, "p97": 73.2},
+    {"month": 9, "L": 1.0, "M": 70.1435, "S": 0.03444, "p3": 65.6, "p50": 70.1, "p97": 74.7},
+    {"month": 10, "L": 1.0, "M": 71.4818, "S": 0.03452, "p3": 66.8, "p50": 71.5, "p97": 76.1},
+    {"month": 11, "L": 1.0, "M": 72.7710, "S": 0.03464, "p3": 68.0, "p50": 72.8, "p97": 77.5},
+    {"month": 12, "L": 1.0, "M": 74.0150, "S": 0.03479, "p3": 69.2, "p50": 74.0, "p97": 78.9},
+    {"month": 13, "L": 1.0, "M": 75.2176, "S": 0.03496, "p3": 70.3, "p50": 75.2, "p97": 80.2},
+    {"month": 14, "L": 1.0, "M": 76.3817, "S": 0.03514, "p3": 71.3, "p50": 76.4, "p97": 81.4},
+    {"month": 15, "L": 1.0, "M": 77.5099, "S": 0.03534, "p3": 72.4, "p50": 77.5, "p97": 82.7},
+    {"month": 16, "L": 1.0, "M": 78.6055, "S": 0.03555, "p3": 73.3, "p50": 78.6, "p97": 83.9},
+    {"month": 17, "L": 1.0, "M": 79.6710, "S": 0.03576, "p3": 74.3, "p50": 79.7, "p97": 85.0},
+    {"month": 18, "L": 1.0, "M": 80.7079, "S": 0.03598, "p3": 75.2, "p50": 80.7, "p97": 86.2},
+    {"month": 19, "L": 1.0, "M": 81.7182, "S": 0.03620, "p3": 76.2, "p50": 81.7, "p97": 87.3},
+    {"month": 20, "L": 1.0, "M": 82.7036, "S": 0.03643, "p3": 77.0, "p50": 82.7, "p97": 88.4},
+    {"month": 21, "L": 1.0, "M": 83.6654, "S": 0.03666, "p3": 77.9, "p50": 83.7, "p97": 89.4},
+    {"month": 22, "L": 1.0, "M": 84.6040, "S": 0.03688, "p3": 78.7, "p50": 84.6, "p97": 90.5},
+    {"month": 23, "L": 1.0, "M": 85.5202, "S": 0.03711, "p3": 79.6, "p50": 85.5, "p97": 91.5},
+    {"month": 24, "L": 1.0, "M": 86.4153, "S": 0.03734, "p3": 80.3, "p50": 86.4, "p97": 92.5},
+]
+
+
+def _interpolate_lms(table: List[Dict[str, float]], age_months: float) -> Tuple[float, float, float, float, float, float]:
+    """Linearly interpolates L, M, S, p3, p50, p97 for a given age in months."""
+    m_clamped = max(0.0, min(float(table[-1]["month"]), float(age_months)))
+    m_low = int(math.floor(m_clamped))
+    m_high = int(math.ceil(m_clamped))
+
+    r_low = table[m_low]
+    if m_low == m_high:
+        return r_low["L"], r_low["M"], r_low["S"], r_low["p3"], r_low["p50"], r_low["p97"]
+
+    r_high = table[m_high]
+    frac = m_clamped - m_low
+
+    L = r_low["L"] + frac * (r_high["L"] - r_low["L"])
+    M = r_low["M"] + frac * (r_high["M"] - r_low["M"])
+    S = r_low["S"] + frac * (r_high["S"] - r_low["S"])
+    p3 = r_low["p3"] + frac * (r_high["p3"] - r_low["p3"])
+    p50 = r_low["p50"] + frac * (r_high["p50"] - r_low["p50"])
+    p97 = r_low["p97"] + frac * (r_high["p97"] - r_low["p97"])
+
+    return L, M, S, p3, p50, p97
+
+
+def calculate_percentile(metric: str, value: float, age_months: float) -> Dict[str, Any]:
+    """
+    Computes exact WHO z-score and percentile using the LMS formula.
+    metric: 'weight' (in kg) or 'height' (in cm)
+    """
+    table = WHO_GIRLS_WEIGHT if metric == "weight" else WHO_GIRLS_HEIGHT
+    L, M, S, p3, p50, p97 = _interpolate_lms(table, age_months)
+
+    if value <= 0 or M <= 0 or S <= 0:
+        return {
+            "value": value,
+            "age_months": round(age_months, 2),
+            "z_score": 0.0,
+            "percentile": 50.0,
+            "percentile_str": "P50",
+            "p3": round(p3, 2),
+            "p50": round(p50, 2),
+            "p97": round(p97, 2),
+            "in_normal_range": True,
+            "status": "normal",
+        }
+
+    # Box-Cox power exponential LMS formula
+    if abs(L) > 1e-6:
+        z = ((value / M) ** L - 1.0) / (L * S)
+    else:
+        z = math.log(value / M) / S
+
+    # Cumulative standard normal distribution
+    p = 0.5 * (1.0 + math.erf(z / math.sqrt(2.0))) * 100.0
+    p_clamped = max(0.1, min(99.9, p))
+
+    in_normal = 3.0 <= p_clamped <= 97.0
+    if p_clamped < 3.0:
+        status = "unter P3"
+    elif p_clamped > 97.0:
+        status = "über P97"
+    else:
+        status = "im WHO-Normbereich"
+
+    return {
+        "value": value,
+        "age_months": round(age_months, 2),
+        "z_score": round(z, 2),
+        "percentile": round(p_clamped, 1),
+        "percentile_str": f"P{int(round(p_clamped))}",
+        "p3": round(p3, 2),
+        "p50": round(p50, 2),
+        "p97": round(p97, 2),
+        "in_normal_range": in_normal,
+        "status": status,
+    }
+
+
+def format_growth_feedback(
+    weight_kg: Optional[float],
+    height_cm: Optional[float],
+    age_months: float,
+    date_str: str,
+) -> str:
+    """Formats clear, comforting feedback for CLI and Hebamme agent responses."""
+    parts = []
+    if weight_kg is not None:
+        pw = calculate_percentile("weight", weight_kg, age_months)
+        parts.append(f"{weight_kg:.2f} kg ({pw['percentile_str']} · WHO Median: {pw['p50']:.1f} kg)")
+
+    if height_cm is not None:
+        ph = calculate_percentile("height", height_cm, age_months)
+        parts.append(f"{height_cm:.1f} cm ({ph['percentile_str']} · WHO Median: {ph['p50']:.1f} cm)")
+
+    if not parts:
+        return f"📏 Messung ({date_str}) ohne Werte geloggt."
+
+    details = " · ".join(parts)
+    return f"📏 Wachstum ({date_str}, ~{age_months:.1f} Mon): {details} [Normbereich: P3–P97]"
@@ -737,5 +737,51 @@ def test_feeding_logging(temp_datastore: DatastoreEngine):
    assert daily[0]["total_consumed_ml"] == 160.0


+def test_growth_logging(temp_datastore: DatastoreEngine):
+    """Verifies baby growth measurements, WHO percentile feedback, and DuckDB views."""
+    # Ensure Mila is in people table with birthdate
+    temp_datastore.put_entity(
+        collection="people",
+        record={"id": "mila", "name": "Mila Graf", "birthdate": "2026-03-14", "role": "child"},
+    )
+
+    # Log measurement at approx 6.9 months (2026-10-12)
+    res = temp_datastore.add_event(
+        kind="growth.measurement",
+        subject="mila",
+        actor="agent:hebamme",
+        start="2026-10-12T10:00:00+02:00",
+        payload={"weight_kg": 7.4, "height_cm": 67.5},
+        note="U-Untersuchung Vorbereitung",
+    )
+    assert res["status"] == "success"
+    fb = res["feedback"]
+    assert "weight_kg" in fb
+    assert fb["weight_kg"] == 7.4
+    assert fb["height_cm"] == 67.5
+    assert "weight_percentile" in fb
+    assert 30 <= fb["weight_percentile"] <= 60  # around P41
+    assert 45 <= fb["height_percentile"] <= 70  # around P56
+    assert "Normbereich" in fb["day_total_formatted"]
+
+    # Verify DuckDB views
+    growth_rows = temp_datastore.query("SELECT * FROM v_growth WHERE subject = 'mila'")
+    assert len(growth_rows) == 1
+    assert growth_rows[0]["weight_kg"] == 7.4
+    assert growth_rows[0]["height_cm"] == 67.5
+    assert growth_rows[0]["note"] == "U-Untersuchung Vorbereitung"
+
+    daily_rows = temp_datastore.query("SELECT * FROM v_growth_daily WHERE subject = 'mila'")
+    assert len(daily_rows) == 1
+    assert daily_rows[0]["measurement_count"] == 1
+
+    # Verify get_summary returns growth_latest
+    summary = temp_datastore.get_summary(subject="mila", date_str="2026-10-12")
+    assert "growth_latest" in summary
+    assert summary["growth_latest"]["weight_kg"] == 7.4
+    assert summary["growth_latest"]["height_cm"] == 67.5
+
+
+