253 lines
8.7 KiB
Python
253 lines
8.7 KiB
Python
"""
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Gedeelde UI-hulpmiddelen voor app.py en alle pages/*.py.
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Elke Streamlit-pagina draait als los script, dus gedeelde constanten/functies
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(kleurenpalet, thema-detectie) horen hier thuis in plaats van gedupliceerd te
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worden per pagina.
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"""
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from __future__ import annotations
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from datetime import date, datetime, timedelta, timezone
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import pandas as pd
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import plotly.graph_objects as go
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import streamlit as st
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from nightscout_client import fetch_entries_range, fetch_treatments_range
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from reporting import (
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HIGH,
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LOW,
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VERY_HIGH,
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VERY_LOW,
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completeness_warning,
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detect_events,
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summarize_events,
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)
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MMOL_HOVERTEMPLATE = "%{x|%d-%m %H:%M} · %{y:.1f} mmol/L<extra></extra>"
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# Periode-opties voor de rapportagepagina's (FR1): elke pagina kiest zijn eigen
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# standaard (90 dagen voor statistiek/TIR, 14 dagen voor recente
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# glucosegrafieken) via `default_label`.
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PERIOD_OPTIONS_DAYS = {"14 dagen": 14, "30 dagen": 30, "90 dagen": 90}
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# Kleuren per rol, licht/donker — categorale kleuren voor identiteit
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# (glucose/insuline/carbs), status-kleuren (vast, nooit hergebruikt) voor
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# te laag/te hoog.
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PALETTE = {
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"light": {
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"glucose": "#2a78d6",
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"insulin": "#1baf7a",
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"carbs": "#eb6834",
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"low": "#d03b3b",
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"very_low": "#d03b3b",
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"high": "#fab219",
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"very_high": "#fab219",
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"band": "rgba(12,163,12,0.08)",
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"grid": "#e1e0d9",
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"muted": "#898781",
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"text": "#52514e",
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"good": "#0ca30c",
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# Losstaand van "low"/"high" hierboven (die blijven gedeeld tussen
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# andere grafieken): de 5-bands TIR-grafiek (gitea #14) heeft juist
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# zichtbaar onderscheid tussen laag/zeer-laag en hoog/zeer-hoog nodig.
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"tir_very_low": "#8b1a1a",
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"tir_low": "#d03b3b",
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"tir_in_range": "#0ca30c",
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"tir_high": "#fab219",
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"tir_very_high": "#c76f0a",
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},
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"dark": {
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"glucose": "#3987e5",
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"insulin": "#199e70",
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"carbs": "#d95926",
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"low": "#d03b3b",
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"very_low": "#d03b3b",
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"high": "#fab219",
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"very_high": "#fab219",
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"band": "rgba(12,163,12,0.15)",
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"grid": "#2c2c2a",
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"muted": "#898781",
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"text": "#c3c2b7",
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"good": "#0ca30c",
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"tir_very_low": "#a32626",
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"tir_low": "#d95d5d",
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"tir_in_range": "#0ca30c",
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"tir_high": "#fab219",
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"tir_very_high": "#d9852e",
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},
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}
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# Klinische drempellijnen (Battelino et al. 2019), gedeeld tussen de AGP- en
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# Dagoverzicht-pagina's (FR3, FR4 — gitea #15) zodat beide grafieken exact
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# dezelfde 4 lijnen op dezelfde manier tonen.
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THRESHOLD_LINES = [
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(VERY_LOW, "3.0"),
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(LOW, "3.9"),
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(HIGH, "10.0"),
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(VERY_HIGH, "13.9"),
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]
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def hex_to_rgba(hex_color: str, alpha: float) -> str:
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"""Zet een '#rrggbb'-kleur om naar een 'rgba(r,g,b,a)'-string voor Plotly-fills."""
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hex_color = hex_color.lstrip("#")
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r, g, b = (int(hex_color[i : i + 2], 16) for i in (0, 2, 4))
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return f"rgba({r},{g},{b},{alpha})"
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def get_colors() -> dict:
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"""Geef de kleurenset terug die past bij het actieve Streamlit-thema."""
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theme_type = "light"
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try:
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theme_type = st.context.theme.type or "light"
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except AttributeError:
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pass
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return PALETTE["dark" if theme_type == "dark" else "light"]
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def select_period_days(default_label: str) -> tuple[date, date, int]:
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"""Periodekiezer voor rapportagepagina's; geeft (start, eind, aantal_dagen) terug."""
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labels = list(PERIOD_OPTIONS_DAYS.keys())
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label = st.radio("Periode", labels, index=labels.index(default_label), horizontal=True)
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days = PERIOD_OPTIONS_DAYS[label]
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end = datetime.now(tz=timezone.utc).date()
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start = end - timedelta(days=days - 1)
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return start, end, days
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@st.cache_data(ttl=3600, show_spinner="Data ophalen van Nightscout...")
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def load_range_data(start: date, end: date):
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"""Gecachete Nightscout-fetch voor een vaste periode.
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Lange TTL (in tegenstelling tot de 60s van de live-pagina): historische
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data van een afgeronde periode verandert niet.
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"""
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glucose = fetch_entries_range(start, end)
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treatments = fetch_treatments_range(start, end)
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return glucose, treatments
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def add_threshold_lines(fig: go.Figure, colors: dict, row: int | None = None) -> None:
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"""Teken de 4 klinische drempellijnen (3.0/3.9/10.0/13.9 mmol/L) op een grafiek.
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Gedeeld door de AGP- en Dagoverzicht-pagina's (gitea #15). `row` wordt
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doorgegeven aan `add_hline` voor subplot-figuren (Dagoverzicht); voor een
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los-staande figuur (AGP) blijft dit `None`.
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"""
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kwargs = {} if row is None else {"row": row, "col": 1}
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for value, label in THRESHOLD_LINES:
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fig.add_hline(
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y=value,
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line={"color": colors["muted"], "width": 1, "dash": "dot"},
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annotation_text=label,
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annotation_position="right",
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annotation_font={"size": 9, "color": colors["muted"]},
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**kwargs,
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)
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TIR_BAND_ORDER = ["very_low", "low", "in_range", "high", "very_high"]
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TIR_BAND_LABELS = {
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"very_low": "Zeer laag",
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"low": "Laag",
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"in_range": "In bereik",
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"high": "Hoog",
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"very_high": "Zeer hoog",
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}
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def build_tir_stacked_bar_figure(tir: dict, colors: dict) -> go.Figure:
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"""Bouw de 5-bands tijd-in-bereik als één gestapelde staafgrafiek (gitea #14).
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Eén staaf, geen x-as-label, percentage op de y-as; van onder naar boven
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"Zeer laag" -> "Zeer hoog" — dezelfde volgorde als de klinische banden.
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"""
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fig = go.Figure()
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for band in TIR_BAND_ORDER:
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fig.add_trace(
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go.Bar(
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x=[""],
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y=[tir[band]],
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name=TIR_BAND_LABELS[band],
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marker_color=colors[f"tir_{band}"],
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hovertemplate=f"{TIR_BAND_LABELS[band]}: %{{y:.0f}}%<extra></extra>",
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)
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)
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fig.update_layout(
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barmode="stack",
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paper_bgcolor="rgba(0,0,0,0)",
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plot_bgcolor="rgba(0,0,0,0)",
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font_color=colors["text"],
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height=140,
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margin={"l": 10, "r": 10, "t": 10, "b": 10},
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yaxis={"title": "%", "range": [0, 100], "gridcolor": colors["grid"]},
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xaxis={"visible": False},
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legend={"orientation": "h", "yanchor": "bottom", "y": 1.02, "xanchor": "left", "x": 0},
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)
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return fig
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def render_completeness_warning(glucose: pd.DataFrame, start: date, end: date) -> None:
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"""Toon reporting.completeness_warning()'s oordeel als st.warning, indien nodig.
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Gebruikt door elke rapportagepagina, direct na de load_range_data-call.
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De beoordelingslogica zelf staat in reporting.py (pure functie) zodat het
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PDF-rapport (pdf_export.py) exact dezelfde disclaimer kan hergebruiken.
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"""
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message = completeness_warning(glucose, start, end)
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if message:
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st.warning(message)
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def render_event_level(
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glucose: pd.DataFrame,
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threshold: float,
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direction: str,
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level_name: str,
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period_days: int,
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colors: dict,
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) -> None:
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"""Render de metrics/tabel/tijdstip-histogram voor één hypo-/hyperniveau.
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Gedeeld tussen de Hypo Events- en Hyper Events-pagina's (FR5/FR6), die
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elk twee niveaus (Level 1/Level 2) op dezelfde manier tonen.
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"""
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events = detect_events(glucose, threshold, direction)
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summary = summarize_events(events, period_days)
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st.subheader(level_name)
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cols = st.columns(4)
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cols[0].metric("Aantal events", summary["count"])
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cols[1].metric("Gem. duur", f"{summary['avg_duration_minutes']:.0f} min")
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cols[2].metric("Langste event", f"{summary['longest_duration_minutes']:.0f} min")
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cols[3].metric("Events/week", f"{summary['events_per_week']:.1f}")
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if events.empty:
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st.info("Geen events gevonden in deze periode.")
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return
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bar_color = colors["low"] if direction == "below" else colors["high"]
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hours = events["start"].dt.hour
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hour_counts = hours.value_counts().reindex(range(24), fill_value=0).sort_index()
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fig = go.Figure(go.Bar(x=list(hour_counts.index), y=hour_counts.to_numpy(), marker_color=bar_color))
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fig.update_layout(
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paper_bgcolor="rgba(0,0,0,0)",
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plot_bgcolor="rgba(0,0,0,0)",
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font_color=colors["text"],
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height=220,
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margin={"l": 10, "r": 10, "t": 10, "b": 10},
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xaxis={"title": "Uur van de dag", "dtick": 2, "gridcolor": colors["grid"]},
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yaxis={"title": "Aantal events", "gridcolor": colors["grid"]},
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)
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st.plotly_chart(fig, width="stretch")
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display = events.copy()
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display["start"] = display["start"].dt.strftime("%d-%m-%Y %H:%M")
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display["end"] = display["end"].dt.strftime("%d-%m-%Y %H:%M")
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display = display.rename(
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columns={"start": "Start", "end": "Einde", "duration_minutes": "Duur (min)"}
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)
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st.dataframe(display, width="stretch", hide_index=True)
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