209 lines
7.8 KiB
Python
209 lines
7.8 KiB
Python
from datetime import timedelta
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import pandas as pd
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import plotly.graph_objects as go
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import requests
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import streamlit as st
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from plotly.subplots import make_subplots
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from auth import require_auth
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from data_processing import TARGET_HIGH, TARGET_LOW, classify_treatments
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from nightscout_client import NightscoutConfigError
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from reporting import (
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BOLUS_CATEGORY_SMB,
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classify_bolus,
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daily_stats,
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effective_basal_series,
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target_glucose_series,
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)
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from ui_common import (
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MMOL_HOVERTEMPLATE,
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add_basal_area_trace,
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add_bolus_marker_traces,
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add_carb_bars_trace,
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add_target_line_trace,
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add_threshold_lines,
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get_colors,
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load_day_data,
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load_profile,
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render_completeness_warning,
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select_period_days,
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)
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st.set_page_config(page_title="Glucose dashboard — Dagoverzicht", page_icon="📊", layout="wide")
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require_auth()
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st.title("Dagoverzicht")
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st.caption(
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"Eén dag per keer: boven glucose met koolhydraten/bolus-overlay, onder basaal "
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"en SMB — apart gehouden omdat één gecombineerde grafiek te veel informatie bevatte."
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)
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# De periode-knop bepaalt alleen het navigeerbare venster (hoe ver terug je kunt
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# bladeren), niet welke data wordt opgehaald — dat gebeurt hieronder voor precies
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# de geselecteerde dag (load_day_data), zodat het wisselen tussen dagen snel blijft.
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window_start, window_end, days = select_period_days(default_label="14 dagen")
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state_key = "dagoverzicht_selected_day"
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if state_key not in st.session_state:
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st.session_state[state_key] = window_end
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if not (window_start <= st.session_state[state_key] <= window_end):
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st.session_state[state_key] = window_end
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selected_day = st.session_state[state_key]
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col_prev, col_date, col_next = st.columns([1, 3, 1])
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with col_prev:
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if st.button("← Vorige dag", disabled=selected_day <= window_start, width="stretch"):
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selected_day = selected_day - timedelta(days=1)
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st.session_state[state_key] = selected_day
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with col_next:
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if st.button("Volgende dag →", disabled=selected_day >= window_end, width="stretch"):
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selected_day = selected_day + timedelta(days=1)
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st.session_state[state_key] = selected_day
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with col_date:
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date_options = [window_end - timedelta(days=i) for i in range(days)]
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chosen = st.selectbox(
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"Datum",
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options=date_options,
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index=date_options.index(selected_day),
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format_func=lambda d: d.strftime("%A %d-%m-%Y"),
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label_visibility="collapsed",
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)
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if chosen != selected_day:
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selected_day = chosen
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st.session_state[state_key] = selected_day
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try:
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glucose, treatments = load_day_data(selected_day)
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profile = load_profile()
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except NightscoutConfigError as exc:
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st.error(str(exc))
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st.stop()
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except (requests.RequestException, ValueError) as exc:
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st.error(f"Kon geen data ophalen van Nightscout: {exc}")
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st.stop()
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if glucose.empty:
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st.info("Geen glucosemetingen gevonden op deze dag.")
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st.stop()
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render_completeness_warning(glucose, selected_day, selected_day)
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colors = get_colors()
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day_start = pd.Timestamp(selected_day)
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day_end = day_start + pd.Timedelta(1, unit="D")
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# treatments bevat een lookback-marge vóór middernacht (zie
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# nightscout_client.fetch_treatments_for_day) zodat een temp basal die al
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# vóór deze dag begon toch meetelt — effective_basal_series() clipt dat
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# zelf aan [day_start, day_end). Voor de koolhydraten/bolus-overlays willen
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# we die marge juist NIET, anders duiken gisteravond se stippen op vandaag op.
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day_treatments = treatments[(treatments["timestamp"] >= day_start) & (treatments["timestamp"] < day_end)]
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carbs_day = classify_treatments(day_treatments)["carbs"]
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bolus_day = classify_bolus(day_treatments)
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basal_day = effective_basal_series(profile, treatments, day_start, day_end)
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target_day = target_glucose_series(profile, day_start, day_end)
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def _close_step_to_day_end(df: pd.DataFrame, value_col: str) -> pd.DataFrame:
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"""Voeg een laatste punt op day_end toe (zelfde waarde als het laatste
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segment) zodat een stapvlak/-lijn de volle dag doortekent i.p.v. te
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stoppen bij het laatste breekpunt."""
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if df.empty:
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return df
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last_value = df.iloc[-1][value_col]
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closing_row = pd.DataFrame([{"timestamp": day_end, value_col: last_value}])
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return pd.concat([df, closing_row], ignore_index=True)
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basal_day = _close_step_to_day_end(basal_day, "rate")
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target_day = _close_step_to_day_end(target_day, "target")
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def build_day_figure(glucose_day, carbs_day, bolus_day, basal_day, target_day, colors) -> go.Figure:
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fig = make_subplots(
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rows=2,
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cols=1,
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shared_xaxes=True,
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row_heights=[0.68, 0.32],
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vertical_spacing=0.08,
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specs=[[{"secondary_y": True}], [{"secondary_y": False}]],
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)
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# Rij 1: glucose + streefwaarde + koolhydraten + voeding-/correctiebolus.
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fig.add_hrect(
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y0=TARGET_LOW, y1=TARGET_HIGH, fillcolor=colors["band"], line_width=0, layer="below", row=1, col=1
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)
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add_target_line_trace(fig, target_day, colors, row=1)
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add_carb_bars_trace(fig, carbs_day, colors, row=1, secondary_y=True)
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top_bolus = bolus_day[bolus_day["category"] != BOLUS_CATEGORY_SMB] if not bolus_day.empty else bolus_day
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lane_y = glucose_day["mmol"].min() - 1.0 if not glucose_day.empty else TARGET_LOW - 1.0
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add_bolus_marker_traces(fig, top_bolus, colors, lane_y, row=1)
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fig.add_trace(
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go.Scatter(
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x=glucose_day["timestamp"],
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y=glucose_day["mmol"],
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mode="lines",
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line={"color": colors["glucose"], "width": 2},
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name="Glucose",
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hovertemplate=MMOL_HOVERTEMPLATE,
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),
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row=1,
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col=1,
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)
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add_threshold_lines(fig, colors, row=1)
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fig.update_yaxes(title_text="mmol/L", gridcolor=colors["grid"], row=1, col=1, secondary_y=False)
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fig.update_yaxes(title_text="Koolhydraten (g)", showgrid=False, row=1, col=1, secondary_y=True)
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# Rij 2: basaal + SMB — apart van rij 1 zodat de glucosegrafiek niet
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# overladen raakt met insulinedetails.
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add_basal_area_trace(fig, basal_day, colors, row=2)
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smb_bolus = bolus_day[bolus_day["category"] == BOLUS_CATEGORY_SMB] if not bolus_day.empty else bolus_day
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smb_lane_y = (basal_day["rate"].max() * 1.15) if not basal_day.empty else 1.0
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add_bolus_marker_traces(fig, smb_bolus, colors, smb_lane_y, row=2)
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fig.update_yaxes(
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title_text="Basaal (E/uur)", gridcolor=colors["grid"], rangemode="tozero", row=2, col=1
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)
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fig.update_xaxes(range=[day_start, day_end], dtick=4 * 3600 * 1000, gridcolor=colors["grid"])
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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=560,
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showlegend=True,
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legend={"orientation": "h", "yanchor": "bottom", "y": 1.02, "xanchor": "left", "x": 0},
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margin={"l": 10, "r": 10, "t": 40, "b": 10},
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)
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return fig
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fig = build_day_figure(glucose, carbs_day, bolus_day, basal_day, target_day, colors)
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st.plotly_chart(fig, width="stretch")
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stats = daily_stats(glucose, day_treatments, profile, day_start, day_end)
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col1, col2, col3, col4 = st.columns(4)
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col1.metric(
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"Glucose (gem./min/max)",
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f"{stats['mean_mmol']:.1f} mmol/L",
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delta=f"{stats['min_mmol']:.1f} - {stats['max_mmol']:.1f}",
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delta_color="off",
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)
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col2.metric("Totale insuline", f"{stats['total_insulin']:.1f} E")
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col3.metric("Basaal / bolus / SMB", f"{stats['basal_insulin']:.1f} / {stats['bolus_insulin']:.1f} / {stats['smb_insulin']:.1f} E")
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col4.metric(
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"Hypo's / hyper's",
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f"{stats['hypo_count']} / {stats['hyper_count']}",
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delta=f"{stats['hypo_duration_minutes']:.0f} / {stats['hyper_duration_minutes']:.0f} min",
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delta_color="off",
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)
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st.caption(
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"Boven: stippen = bolusinsuline (voeding/correctie, grootte naar dosis) · staafjes = koolhydraten · "
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"streepstippellijn = streefwaarde uit pompprofiel. Onder: vlak = basaal · stippen = SMB."
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)
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