pages/2_Samenvatting.py

@@ -0,0 +1,76 @@
+import requests
+import streamlit as st
+
+from auth import require_auth
+from nightscout_client import NightscoutConfigError
+from reporting import (
+    gmi_percent,
+    percent_cv,
+    sensor_active_percent,
+    tir_breakdown_5band,
+)
+from ui_common import load_range_data, select_period_days
+
+st.set_page_config(page_title="Glucose dashboard — Samenvatting", page_icon="📊", layout="wide")
+require_auth()
+
+st.title("Samenvatting")
+st.caption("AGP-stijl samenvattingsstatistieken over een gekozen periode (FR2, FR9).")
+
+start, end, days = select_period_days(default_label="90 dagen")
+
+try:
+    glucose, _treatments = load_range_data(start, end)
+except NightscoutConfigError as exc:
+    st.error(str(exc))
+    st.stop()
+except (requests.RequestException, ValueError) as exc:
+    st.error(f"Kon geen data ophalen van Nightscout: {exc}")
+    st.stop()
+
+if glucose.empty:
+    st.info("Geen glucosemetingen gevonden in deze periode.")
+    st.stop()
+
+active_pct = sensor_active_percent(glucose, start, end)
+if active_pct < 70:
+    st.warning(
+        f"Slechts {active_pct:.0f}% sensordekking in deze periode (streefwaarde ≥70%). "
+        "De onderstaande cijfers zijn mogelijk minder betrouwbaar door de vele hiaten."
+    )
+
+mean_mmol = glucose["mmol"].mean()
+gmi = gmi_percent(mean_mmol)
+cv = percent_cv(glucose)
+tir = tir_breakdown_5band(glucose)
+
+st.subheader("Kerncijfers")
+col1, col2, col3, col4 = st.columns(4)
+col1.metric("Sensordekking", f"{active_pct:.0f}%", help="Streefwaarde: ≥70%")
+col2.metric("Gemiddelde glucose", f"{mean_mmol:.1f} mmol/L")
+col3.metric("Geschat HbA1c (GMI)", f"{gmi:.1f}%", help="Bergenstal et al. 2018 — geen labwaarde")
+col4.metric("Variabiliteit (%CV)", f"{cv:.0f}%", help="Streefwaarde: ≤36%")
+
+st.subheader("Tijd in bereik (5 klinische banden)")
+band_labels = {
+    "very_low": "Zeer laag (<3.0)",
+    "low": "Laag (3.0-3.9)",
+    "in_range": "In bereik (3.9-10.0)",
+    "high": "Hoog (10.0-13.9)",
+    "very_high": "Zeer hoog (>13.9)",
+}
+band_targets = {
+    "very_low": "<1%",
+    "low": "<4% (samen met zeer laag)",
+    "in_range": ">70%",
+    "high": "<25% (samen met zeer hoog)",
+    "very_high": "<5%",
+}
+cols = st.columns(5)
+for col, band in zip(cols, band_labels, strict=True):
+    col.metric(band_labels[band], f"{tir[band]:.0f}%", help=f"Streefwaarde: {band_targets[band]}")
+
+st.caption(
+    f"Periode: {start.strftime('%d-%m-%Y')} t/m {end.strftime('%d-%m-%Y')} "
+    f"({len(glucose)} metingen) · streefwaarden volgens Battelino et al. 2019"
+)

pages/3_AGP_Profiel.py

@@ -0,0 +1,100 @@
+import plotly.graph_objects as go
+import requests
+import streamlit as st
+
+from auth import require_auth
+from data_processing import TARGET_HIGH, TARGET_LOW
+from nightscout_client import NightscoutConfigError
+from reporting import agp_percentile_bands
+from ui_common import get_colors, hex_to_rgba, load_range_data, select_period_days
+
+st.set_page_config(page_title="Glucose dashboard — AGP profiel", page_icon="📊", layout="wide")
+require_auth()
+
+st.title("AGP profiel")
+st.caption(
+    "Percentielgrafiek over een samengesteld 24-uursbeeld (FR3) — de 5e/25e/50e/75e/"
+    "95e percentiel van alle metingen op elk tijdstip van de dag in de gekozen periode."
+)
+
+start, end, days = select_period_days(default_label="90 dagen")
+
+try:
+    glucose, _treatments = load_range_data(start, end)
+except NightscoutConfigError as exc:
+    st.error(str(exc))
+    st.stop()
+except (requests.RequestException, ValueError) as exc:
+    st.error(f"Kon geen data ophalen van Nightscout: {exc}")
+    st.stop()
+
+if glucose.empty:
+    st.info("Geen glucosemetingen gevonden in deze periode.")
+    st.stop()
+
+bands = agp_percentile_bands(glucose, bin_minutes=30)
+colors = get_colors()
+
+hours = bands["minute_of_day"] / 60
+
+fig = go.Figure()
+fig.add_hrect(y0=TARGET_LOW, y1=TARGET_HIGH, fillcolor=colors["band"], line_width=0, layer="below")
+
+# 5e-95e percentiel als brede, lichte band.
+fig.add_trace(
+    go.Scatter(x=hours, y=bands["p95"], mode="lines", line={"width": 0}, showlegend=False, hoverinfo="skip")
+)
+fig.add_trace(
+    go.Scatter(
+        x=hours,
+        y=bands["p5"],
+        mode="lines",
+        line={"width": 0},
+        fill="tonexty",
+        fillcolor=colors["band"],
+        name="5e-95e percentiel",
+        hoverinfo="skip",
+    )
+)
+# 25e-75e percentiel als smallere, donkerdere band.
+fig.add_trace(
+    go.Scatter(x=hours, y=bands["p75"], mode="lines", line={"width": 0}, showlegend=False, hoverinfo="skip")
+)
+fig.add_trace(
+    go.Scatter(
+        x=hours,
+        y=bands["p25"],
+        mode="lines",
+        line={"width": 0},
+        fill="tonexty",
+        fillcolor=hex_to_rgba(colors["glucose"], 0.3),
+        name="25e-75e percentiel",
+        hoverinfo="skip",
+    )
+)
+# Mediaan.
+fig.add_trace(
+    go.Scatter(
+        x=hours,
+        y=bands["p50"],
+        mode="lines",
+        line={"color": colors["glucose"], "width": 2},
+        name="Mediaan",
+        hovertemplate="%{x:.0f}u · %{y:.1f} mmol/L<extra></extra>",
+    )
+)
+
+fig.update_layout(
+    paper_bgcolor="rgba(0,0,0,0)",
+    plot_bgcolor="rgba(0,0,0,0)",
+    font_color=colors["text"],
+    legend={"orientation": "h", "yanchor": "bottom", "y": 1.02, "xanchor": "left", "x": 0},
+    margin={"l": 10, "r": 10, "t": 10, "b": 10},
+    height=480,
+    yaxis={"title": "mmol/L", "gridcolor": colors["grid"], "zeroline": False},
+    xaxis={"title": "Uur van de dag", "gridcolor": colors["grid"], "tickmode": "linear", "dtick": 2},
+)
+st.plotly_chart(fig, width="stretch")
+st.caption(
+    f"Periode: {start.strftime('%d-%m-%Y')} t/m {end.strftime('%d-%m-%Y')} ({len(glucose)} metingen)"
+)

reporting.py

@@ -202,3 +202,27 @@ def summarize_events(events: pd.DataFrame, period_days: float) -> dict[str, floa
         "total_minutes": round(total_minutes, 1),
         "events_per_week": round(len(events) / period_days * 7, 1),
     }
+
+
+AGP_PERCENTILE_COLUMNS = ["minute_of_day", "p5", "p25", "p50", "p75", "p95"]
+
+
+def agp_percentile_bands(glucose: pd.DataFrame, bin_minutes: int = 30) -> pd.DataFrame:
+    """Aggregeer glucosewaarden per tijdstip-van-de-dag naar percentielbanden.
+
+    Groepeert alle metingen in de periode naar hun tijd-van-de-dag (in bins
+    van `bin_minutes`), en berekent per bin de 5e/25e/50e/75e/95e percentiel
+    — de standaard AGP-percentielgrafiek over een samengesteld 24-uursbeeld
+    (Danne et al. 2017, Diabetes Care 40(12):1631-1640).
+    """
+    if glucose.empty:
+        return pd.DataFrame(columns=AGP_PERCENTILE_COLUMNS)
+
+    df = glucose.copy()
+    minute_of_day = df["timestamp"].dt.hour * 60 + df["timestamp"].dt.minute
+    df["bin"] = (minute_of_day // bin_minutes) * bin_minutes
+
+    grouped = df.groupby("bin")["mmol"].quantile([0.05, 0.25, 0.5, 0.75, 0.95]).unstack()
+    grouped.columns = ["p5", "p25", "p50", "p75", "p95"]
+    grouped = grouped.reset_index().rename(columns={"bin": "minute_of_day"})
+    return grouped[AGP_PERCENTILE_COLUMNS].sort_values("minute_of_day").reset_index(drop=True)

tests/test_reporting.py

@@ -2,6 +2,7 @@ import pandas as pd
 import pytest
 
 from reporting import (
+    agp_percentile_bands,
     detect_events,
     gmi_percent,
     minutes_per_day,
@@ -213,6 +214,35 @@ def test_summarize_events_computes_expected_stats():
     assert result["events_per_week"] == pytest.approx(2.0)
 
 
+def test_agp_percentile_bands_groups_by_time_of_day_across_days():
+    # zelfde tijdstip (08:00) op twee verschillende dagen, met bekende waarden
+    glucose = _series(
+        [
+            ("2026-01-01 08:00", 6.0),
+            ("2026-01-02 08:00", 8.0),
+            ("2026-01-01 20:00", 10.0),
+            ("2026-01-02 20:00", 10.0),
+        ]
+    )
+    result = agp_percentile_bands(glucose, bin_minutes=30)
+    assert list(result.columns) == ["minute_of_day", "p5", "p25", "p50", "p75", "p95"]
+
+    morning_bin = 8 * 60
+    row = result[result["minute_of_day"] == morning_bin].iloc[0]
+    assert row["p50"] == pytest.approx(7.0)  # mediaan van 6.0 en 8.0
+
+    evening_bin = 20 * 60
+    evening_row = result[result["minute_of_day"] == evening_bin].iloc[0]
+    assert evening_row["p50"] == pytest.approx(10.0)
+
+
+def test_agp_percentile_bands_handles_empty_input():
+    empty = pd.DataFrame(columns=["timestamp", "mmol"])
+    result = agp_percentile_bands(empty)
+    assert result.empty
+    assert list(result.columns) == ["minute_of_day", "p5", "p25", "p50", "p75", "p95"]
+
+
 def test_summarize_events_handles_empty_input():
     empty = pd.DataFrame(columns=["start", "end", "duration_minutes"])
     result = summarize_events(empty, period_days=14)

tests/test_ui_common.py

@@ -0,0 +1,9 @@
+from ui_common import hex_to_rgba
+
+
+def test_hex_to_rgba_converts_correctly():
+    assert hex_to_rgba("#2a78d6", 0.3) == "rgba(42,120,214,0.3)"
+
+
+def test_hex_to_rgba_handles_hash_optional():
+    assert hex_to_rgba("2a78d6", 0.3) == "rgba(42,120,214,0.3)"

ui_common.py

@@ -8,10 +8,19 @@ worden per pagina.
 
 from __future__ import annotations
 
+from datetime import date, datetime, timedelta, timezone
+
 import streamlit as st
 
+from nightscout_client import fetch_entries_range, fetch_treatments_range
+
 MMOL_HOVERTEMPLATE = "%{x|%d-%m %H:%M} · %{y:.1f} mmol/L<extra></extra>"
 
+# Periode-opties voor de rapportagepagina's (FR1): elke pagina kiest zijn eigen
+# standaard (90 dagen voor statistiek/TIR, 14 dagen voor recente
+# glucosegrafieken) via `default_label`.
+PERIOD_OPTIONS_DAYS = {"14 dagen": 14, "30 dagen": 30, "90 dagen": 90}
+
 # Kleuren per rol, licht/donker — categorale kleuren voor identiteit
 # (glucose/insuline/carbs), status-kleuren (vast, nooit hergebruikt) voor
 # te laag/te hoog.
@@ -47,6 +56,13 @@ PALETTE = {
 }
 
 
+def hex_to_rgba(hex_color: str, alpha: float) -> str:
+    """Zet een '#rrggbb'-kleur om naar een 'rgba(r,g,b,a)'-string voor Plotly-fills."""
+    hex_color = hex_color.lstrip("#")
+    r, g, b = (int(hex_color[i : i + 2], 16) for i in (0, 2, 4))
+    return f"rgba({r},{g},{b},{alpha})"
+
+
 def get_colors() -> dict:
     """Geef de kleurenset terug die past bij het actieve Streamlit-thema."""
     theme_type = "light"
@@ -55,3 +71,25 @@ def get_colors() -> dict:
     except AttributeError:
         pass
     return PALETTE["dark" if theme_type == "dark" else "light"]
+
+
+def select_period_days(default_label: str) -> tuple[date, date, int]:
+    """Periodekiezer voor rapportagepagina's; geeft (start, eind, aantal_dagen) terug."""
+    labels = list(PERIOD_OPTIONS_DAYS.keys())
+    label = st.radio("Periode", labels, index=labels.index(default_label), horizontal=True)
+    days = PERIOD_OPTIONS_DAYS[label]
+    end = datetime.now(tz=timezone.utc).date()
+    start = end - timedelta(days=days - 1)
+    return start, end, days
+
+
+@st.cache_data(ttl=3600, show_spinner="Data ophalen van Nightscout...")
+def load_range_data(start: date, end: date):
+    """Gecachete Nightscout-fetch voor een vaste periode.
+
+    Lange TTL (in tegenstelling tot de 60s van de live-pagina): historische
+    data van een afgeronde periode verandert niet.
+    """
+    glucose = fetch_entries_range(start, end)
+    treatments = fetch_treatments_range(start, end)
+    return glucose, treatments