From 1207ff536f12f49f759572c73a89701f29ddfb02 Mon Sep 17 00:00:00 2001 From: willemjan Date: Sun, 26 Jul 2026 20:09:25 +0200 Subject: [PATCH] add Samenvatting and AGP Profiel pages (FR2, FR3, FR9) Wires reporting.py's stats into two new pages: a summary panel (data completeness, GMI, %CV, 5-band time-in-range vs. consensus targets) and the standard AGP percentile chart (5th-95th and 25th-75th bands plus median, aggregated by time-of-day across the selected period). Co-Authored-By: Claude Sonnet 5 --- pages/2_Samenvatting.py | 76 ++++++++++++++++++++++++++++++ pages/3_AGP_Profiel.py | 100 ++++++++++++++++++++++++++++++++++++++++ reporting.py | 24 ++++++++++ tests/test_reporting.py | 30 ++++++++++++ tests/test_ui_common.py | 9 ++++ ui_common.py | 38 +++++++++++++++ 6 files changed, 277 insertions(+) create mode 100644 pages/2_Samenvatting.py create mode 100644 pages/3_AGP_Profiel.py create mode 100644 tests/test_ui_common.py diff --git a/pages/2_Samenvatting.py b/pages/2_Samenvatting.py new file mode 100644 index 0000000..a8c2034 --- /dev/null +++ b/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 โ€” Samenvatting", page_icon="๐Ÿ“Š", 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 โ‰ฅ70%). " + "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: โ‰ฅ70%") +col2.metric("Gemiddelde glucose", f"{mean_mmol:.1f} mmol/L") +col3.metric("Geschat HbA1c (GMI)", f"{gmi:.1f}%", help="Bergenstal et al. 2018 โ€” geen labwaarde") +col4.metric("Variabiliteit (%CV)", f"{cv:.0f}%", help="Streefwaarde: โ‰ค36%") + +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) ยท streefwaarden volgens Battelino et al. 2019" +) diff --git a/pages/3_AGP_Profiel.py b/pages/3_AGP_Profiel.py new file mode 100644 index 0000000..c8caec8 --- /dev/null +++ b/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 โ€” AGP profiel", page_icon="๐Ÿ“Š", layout="wide") +require_auth() + +st.title("AGP profiel") +st.caption( + "Percentielgrafiek over een samengesteld 24-uursbeeld (FR3) โ€” 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 ยท %{y:.1f} mmol/L", + ) +) + +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)" +) diff --git a/reporting.py b/reporting.py index 55fdcf1..a5e0253 100644 --- a/reporting.py +++ b/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 + โ€” 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) diff --git a/tests/test_reporting.py b/tests/test_reporting.py index 5b0faed..c1b7d49 100644 --- a/tests/test_reporting.py +++ b/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) diff --git a/tests/test_ui_common.py b/tests/test_ui_common.py new file mode 100644 index 0000000..8df8981 --- /dev/null +++ b/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)" diff --git a/ui_common.py b/ui_common.py index a8a9a4a..37b31f2 100644 --- a/ui_common.py +++ b/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} ยท %{y:.1f} mmol/L" +# 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 โ€” 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