glucose-dashboard/pages/7_Trends.py

import plotly.graph_objects as go
import requests
import streamlit as st

from auth import require_auth
from data_processing import classify_treatments
from nightscout_client import NightscoutConfigError
from reporting import (
    basal_stats,
    bolus_stats,
    day_of_week_pattern,
    gmi_trend,
    overnight_daytime_split,
    site_interval_stats,
)
from ui_common import (
    get_colors,
    hex_to_rgba,
    load_range_data,
    render_completeness_warning,
    select_period_days,
)

st.set_page_config(page_title="Glucose dashboard — Trends", page_icon="📊", layout="wide")
require_auth()

st.title("Trends")
st.caption("Geschat HbA1c (GMI) over tijd en overige statistieken (FR7, FR8).")

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()

render_completeness_warning(glucose, start, end)

colors = get_colors()
events = classify_treatments(treatments)

# --- FR7: geschat HbA1c (GMI) trend ----------------------------------------
st.subheader("Geschat HbA1c (GMI) trend")
trend = gmi_trend(glucose)

if len(trend) >= 2:
    fig = go.Figure()
    fig.add_trace(
        go.Scatter(
            x=trend["date"], y=trend["trend_upper"], mode="lines", line={"width": 0}, showlegend=False,
            hoverinfo="skip",
        )
    )
    fig.add_trace(
        go.Scatter(
            x=trend["date"],
            y=trend["trend_lower"],
            mode="lines",
            line={"width": 0},
            fill="tonexty",
            fillcolor=hex_to_rgba(colors["muted"], 0.2),
            name="95% betrouwbaarheidsband",
            hoverinfo="skip",
        )
    )
    fig.add_trace(
        go.Scatter(
            x=trend["date"],
            y=trend["trend"],
            mode="lines",
            line={"color": colors["muted"], "width": 2, "dash": "dash"},
            name="Trend (lineair)",
        )
    )
    fig.add_trace(
        go.Scatter(
            x=trend["date"],
            y=trend["rolling_avg"],
            mode="lines",
            line={"color": colors["glucose"], "width": 2},
            name="Voortschrijdend gemiddelde (7d)",
        )
    )
    fig.add_trace(
        go.Scatter(
            x=trend["date"],
            y=trend["gmi"],
            mode="markers",
            marker={"color": colors["glucose"], "size": 5, "opacity": 0.5},
            name="Dag-GMI",
        )
    )
    fig.update_layout(
        paper_bgcolor="rgba(0,0,0,0)",
        plot_bgcolor="rgba(0,0,0,0)",
        font_color=colors["text"],
        height=320,
        margin={"l": 10, "r": 10, "t": 10, "b": 10},
        yaxis={"title": "GMI (%)", "gridcolor": colors["grid"]},
        xaxis={"title": "Datum", "gridcolor": colors["grid"]},
        legend={"orientation": "h", "yanchor": "bottom", "y": 1.02, "xanchor": "left", "x": 0},
    )
    st.plotly_chart(fig, width="stretch")
else:
    st.info("Niet genoeg dagen met data voor een trendlijn (minstens 2 nodig).")
st.caption("GMI is een schatting (Bergenstal et al. 2018), geen labwaarde.")

# --- FR8: nacht vs. overdag --------------------------------------------------
st.subheader("Nacht (00:00-06:00) vs. overdag")
split = overnight_daytime_split(glucose)
col1, col2 = st.columns(2)
col1.metric("Tijd in bereik 's nachts", f"{split['overnight']['in_range']:.0f}%")
col2.metric("Tijd in bereik overdag", f"{split['daytime']['in_range']:.0f}%")

# --- FR8: patroon per weekdag -------------------------------------------------
st.subheader("Patroon per weekdag")
weekday_df = day_of_week_pattern(glucose)
weekday_plot = weekday_df.dropna(subset=["mean_mmol"])
if not weekday_plot.empty:
    fig = go.Figure(
        go.Bar(x=weekday_plot["weekday"], y=weekday_plot["mean_mmol"], marker_color=colors["glucose"])
    )
    fig.update_layout(
        paper_bgcolor="rgba(0,0,0,0)",
        plot_bgcolor="rgba(0,0,0,0)",
        font_color=colors["text"],
        height=280,
        margin={"l": 10, "r": 10, "t": 10, "b": 10},
        yaxis={"title": "Gem. glucose (mmol/L)", "gridcolor": colors["grid"]},
        xaxis={"gridcolor": colors["grid"]},
    )
    st.plotly_chart(fig, width="stretch")

# --- FR8: insuline (basaal + bolus-uitsplitsing) ---------------------------
st.subheader("Insuline")
st.caption(
    "Basaal berekend uit Temp Basal-treatments (snelheid x duur), zonder pompprofiel "
    "nodig — een ondergrens bij periodes zonder actieve temp basal. Boluses "
    "opgesplitst naar voeding, handmatige correctie en automatische SMB-microbolus "
    "(gitea #20)."
)
bolus = bolus_stats(treatments)
basal = basal_stats(treatments, days)
total_units = bolus["total_units"] + basal["total_units"]
col1, col2, col3 = st.columns(3)
col1.metric("Totaal insuline", f"{total_units:.1f} E")
col2.metric("Gem. per dag", f"{total_units / days:.1f} E")
col3.metric("Aantal boluses", bolus["count"])

breakdown = {"Basaal": basal["total_units"], **bolus["by_type"]}
if any(breakdown.values()):
    st.table({"Categorie": list(breakdown.keys()), "Eenheden": list(breakdown.values())})

# --- FR8: pompsite-leeftijd vs. glucose/insuline ---------------------------
st.subheader("Pompsite-leeftijd vs. glucose en insuline")
st.caption(
    "Statistieken per interval tussen opeenvolgende pompwissels — een benadering "
    "(zonder basaalinsuline) van of insulinebehoefte samenhangt met de leeftijd "
    "van de pompsite."
)
site_stats = site_interval_stats(glucose, treatments, events["site_changes"])
if site_stats.empty:
    st.info("Geen pompwissels gevonden in deze periode.")
else:
    display = site_stats.copy()
    display["start"] = display["start"].dt.strftime("%d-%m-%Y")
    display["end"] = display["end"].dt.strftime("%d-%m-%Y")
    st.dataframe(display, width="stretch", hide_index=True)

st.caption(f"Periode: {start.strftime('%d-%m-%Y')} t/m {end.strftime('%d-%m-%Y')}")