Updated charts for glucose data and profile chart

pages/4_Dagoverzicht.py

@@ -1,3 +1,5 @@
+from datetime import timedelta
+
 import pandas as pd
 import plotly.graph_objects as go
 import requests
@@ -7,16 +9,17 @@ from plotly.subplots import make_subplots
 from auth import require_auth
 from data_processing import TARGET_HIGH, TARGET_LOW, classify_treatments
 from nightscout_client import NightscoutConfigError
-from reporting import classify_bolus, effective_basal_series, target_glucose_series
+from reporting import BOLUS_CATEGORY_SMB, classify_bolus, daily_stats, effective_basal_series, target_glucose_series
 from ui_common import (
+    MMOL_HOVERTEMPLATE,
     add_basal_area_trace,
     add_bolus_marker_traces,
     add_carb_bars_trace,
     add_target_line_trace,
     add_threshold_lines,
     get_colors,
+    load_day_data,
     load_profile,
-    load_range_data,
     render_completeness_warning,
     select_period_days,
 )
@@ -25,17 +28,48 @@ st.set_page_config(page_title="Glucose dashboard — Dagoverzicht", page_icon="
 require_auth()
 
 st.title("Dagoverzicht")
-st.caption("Eén glucosegrafiek per kalenderdag, met basaal/bolus/koolhydraten-overlay (FR4).")
+st.caption(
+    "Eén dag per keer: boven glucose met koolhydraten/bolus-overlay, onder basaal "
+    "en SMB — apart gehouden omdat één gecombineerde grafiek te veel informatie bevatte."
+)
 
-start, end, days = select_period_days(default_label="14 dagen")
-if days > 31:
-    st.info(
-        "Bij langere periodes wordt de pagina lang en kan laden traag zijn — "
-        "voor het bekijken van individuele dagen is 14 of 30 dagen prettiger."
+# De periode-knop bepaalt alleen het navigeerbare venster (hoe ver terug je kunt
+# bladeren), niet welke data wordt opgehaald — dat gebeurt hieronder voor precies
+# de geselecteerde dag (load_day_data), zodat het wisselen tussen dagen snel blijft.
+window_start, window_end, days = select_period_days(default_label="14 dagen")
+
+state_key = "dagoverzicht_selected_day"
+if state_key not in st.session_state:
+    st.session_state[state_key] = window_end
+if not (window_start <= st.session_state[state_key] <= window_end):
+    st.session_state[state_key] = window_end
+
+selected_day = st.session_state[state_key]
+
+col_prev, col_date, col_next = st.columns([1, 3, 1])
+with col_prev:
+    if st.button("← Vorige dag", disabled=selected_day <= window_start, width="stretch"):
+        selected_day = selected_day - timedelta(days=1)
+        st.session_state[state_key] = selected_day
+with col_next:
+    if st.button("Volgende dag →", disabled=selected_day >= window_end, width="stretch"):
+        selected_day = selected_day + timedelta(days=1)
+        st.session_state[state_key] = selected_day
+with col_date:
+    date_options = [window_end - timedelta(days=i) for i in range(days)]
+    chosen = st.selectbox(
+        "Datum",
+        options=date_options,
+        index=date_options.index(selected_day),
+        format_func=lambda d: d.strftime("%A %d-%m-%Y"),
+        label_visibility="collapsed",
     )
+    if chosen != selected_day:
+        selected_day = chosen
+        st.session_state[state_key] = selected_day
 
 try:
-    glucose, treatments = load_range_data(start, end)
+    glucose, treatments = load_day_data(selected_day)
     profile = load_profile()
 except NightscoutConfigError as exc:
     st.error(str(exc))
@@ -45,132 +79,124 @@ except (requests.RequestException, ValueError) as exc:
     st.stop()
 
 if glucose.empty:
-    st.info("Geen glucosemetingen gevonden in deze periode.")
+    st.info("Geen glucosemetingen gevonden op deze dag.")
     st.stop()
 
-render_completeness_warning(glucose, start, end)
+render_completeness_warning(glucose, selected_day, selected_day)
 
 colors = get_colors()
-glucose = glucose.copy()
-glucose["date"] = glucose["timestamp"].dt.date
-glucose["hour"] = glucose["timestamp"].dt.hour + glucose["timestamp"].dt.minute / 60
+day_start = pd.Timestamp(selected_day)
+day_end = day_start + pd.Timedelta(1, unit="D")
 
-carbs_events = classify_treatments(treatments)["carbs"].copy()
-if not carbs_events.empty:
-    carbs_events["date"] = carbs_events["timestamp"].dt.date
-    carbs_events["hour"] = carbs_events["timestamp"].dt.hour + carbs_events["timestamp"].dt.minute / 60
+# treatments bevat een lookback-marge vóór middernacht (zie
+# nightscout_client.fetch_treatments_for_day) zodat een temp basal die al
+# vóór deze dag begon toch meetelt — effective_basal_series() clipt dat
+# zelf aan [day_start, day_end). Voor de koolhydraten/bolus-overlays willen
+# we die marge juist NIET, anders duiken gisteravond se stippen op vandaag op.
+day_treatments = treatments[(treatments["timestamp"] >= day_start) & (treatments["timestamp"] < day_end)]
 
-bolus_events = classify_bolus(treatments)
-if not bolus_events.empty:
-    bolus_events["date"] = bolus_events["timestamp"].dt.date
-    bolus_events["hour"] = bolus_events["timestamp"].dt.hour + bolus_events["timestamp"].dt.minute / 60
+carbs_day = classify_treatments(day_treatments)["carbs"]
+bolus_day = classify_bolus(day_treatments)
+basal_day = effective_basal_series(profile, treatments, day_start, day_end)
+target_day = target_glucose_series(profile, day_start, day_end)
 
 
 def _close_step_to_day_end(df: pd.DataFrame, value_col: str) -> pd.DataFrame:
-    """Voeg een laatste punt op hour=24 toe (zelfde waarde als het laatste
+    """Voeg een laatste punt op day_end toe (zelfde waarde als het laatste
     segment) zodat een stapvlak/-lijn de volle dag doortekent i.p.v. te
     stoppen bij het laatste breekpunt."""
     if df.empty:
         return df
     last_value = df.iloc[-1][value_col]
-    closing_row = pd.DataFrame([{"hour": 24.0, value_col: last_value}])
+    closing_row = pd.DataFrame([{"timestamp": day_end, value_col: last_value}])
     return pd.concat([df, closing_row], ignore_index=True)
 
 
-dates = sorted(glucose["date"].unique())
-row_height = 190
-fig = make_subplots(
-    rows=len(dates),
-    cols=1,
-    shared_xaxes=True,
-    vertical_spacing=min(0.4 / max(len(dates) - 1, 1), 0.05),
-    specs=[[{"secondary_y": True}]] * len(dates),
-)
+basal_day = _close_step_to_day_end(basal_day, "rate")
+target_day = _close_step_to_day_end(target_day, "target")
 
-for i, day in enumerate(dates, start=1):
-    day_df = glucose[glucose["date"] == day]
-    day_start = pd.Timestamp(day)
-    day_end = day_start + pd.Timedelta(1, unit="D")
 
+def build_day_figure(glucose_day, carbs_day, bolus_day, basal_day, target_day, colors) -> go.Figure:
+    fig = make_subplots(
+        rows=2,
+        cols=1,
+        shared_xaxes=True,
+        row_heights=[0.68, 0.32],
+        vertical_spacing=0.08,
+        specs=[[{"secondary_y": True}], [{"secondary_y": False}]],
+    )
+
+    # Rij 1: glucose + streefwaarde + koolhydraten + voeding-/correctiebolus.
     fig.add_hrect(
-        y0=TARGET_LOW, y1=TARGET_HIGH, fillcolor=colors["band"], line_width=0, layer="below", row=i, col=1
-    )
-    # Handmatige titel-annotatie t.o.v. het domein van déze rij i.p.v.
-    # make_subplots' subplot_titles (die t.o.v. de hele figuur positioneert en
-    # daardoor bij veel dagen de gedeelde legenda bovenaan kan overlappen).
-    fig.add_annotation(
-        text=day.strftime("%A %d-%m-%Y"),
-        xref="x domain",
-        yref="y domain",
-        x=0.0,
-        y=1.15,
-        xanchor="left",
-        yanchor="bottom",
-        showarrow=False,
-        font={"size": 13, "color": colors["text"]},
-        row=i,
-        col=1,
+        y0=TARGET_LOW, y1=TARGET_HIGH, fillcolor=colors["band"], line_width=0, layer="below", row=1, col=1
     )
+    add_target_line_trace(fig, target_day, colors, row=1)
+    add_carb_bars_trace(fig, carbs_day, colors, row=1, secondary_y=True)
 
-    basal_day = effective_basal_series(profile, treatments, day_start, day_end)
-    if not basal_day.empty:
-        basal_day["hour"] = (basal_day["timestamp"] - day_start).dt.total_seconds() / 3600
-        basal_day = _close_step_to_day_end(basal_day, "rate")
-    add_basal_area_trace(fig, basal_day, colors, row=i, secondary_y=True, x_col="hour")
-
-    target_day = target_glucose_series(profile, day_start, day_end)
-    if not target_day.empty:
-        target_day["hour"] = (target_day["timestamp"] - day_start).dt.total_seconds() / 3600
-        target_day = _close_step_to_day_end(target_day, "target")
-    add_target_line_trace(fig, target_day, colors, row=i, x_col="hour")
-
-    add_carb_bars_trace(fig, carbs_events[carbs_events["date"] == day], colors, row=i, secondary_y=True, x_col="hour")
-
-    lane_y = day_df["mmol"].min() - 1.0 if not day_df.empty else TARGET_LOW - 1.0
-    add_bolus_marker_traces(fig, bolus_events[bolus_events["date"] == day], colors, lane_y, row=i, x_col="hour")
+    top_bolus = bolus_day[bolus_day["category"] != BOLUS_CATEGORY_SMB] if not bolus_day.empty else bolus_day
+    lane_y = glucose_day["mmol"].min() - 1.0 if not glucose_day.empty else TARGET_LOW - 1.0
+    add_bolus_marker_traces(fig, top_bolus, colors, lane_y, row=1)
 
     fig.add_trace(
         go.Scatter(
-            x=day_df["hour"],
-            y=day_df["mmol"],
+            x=glucose_day["timestamp"],
+            y=glucose_day["mmol"],
             mode="lines",
             line={"color": colors["glucose"], "width": 2},
             name="Glucose",
-            hovertemplate="%{y:.1f} mmol/L<extra></extra>",
+            hovertemplate=MMOL_HOVERTEMPLATE,
         ),
-        row=i,
+        row=1,
         col=1,
-        secondary_y=False,
     )
-    fig.update_yaxes(title_text="mmol/L", gridcolor=colors["grid"], row=i, col=1, secondary_y=False)
+    add_threshold_lines(fig, colors, row=1)
+    fig.update_yaxes(title_text="mmol/L", gridcolor=colors["grid"], row=1, col=1, secondary_y=False)
+    fig.update_yaxes(title_text="Koolhydraten (g)", showgrid=False, row=1, col=1, secondary_y=True)
+
+    # Rij 2: basaal + SMB — apart van rij 1 zodat de glucosegrafiek niet
+    # overladen raakt met insulinedetails.
+    add_basal_area_trace(fig, basal_day, colors, row=2)
+    smb_bolus = bolus_day[bolus_day["category"] == BOLUS_CATEGORY_SMB] if not bolus_day.empty else bolus_day
+    smb_lane_y = (basal_day["rate"].max() * 1.15) if not basal_day.empty else 1.0
+    add_bolus_marker_traces(fig, smb_bolus, colors, smb_lane_y, row=2)
     fig.update_yaxes(
-        title_text="Basaal (E/uur) · KH (g)", showgrid=False, row=i, col=1, secondary_y=True
+        title_text="Basaal (E/uur)", gridcolor=colors["grid"], rangemode="tozero", row=2, col=1
     )
-    add_threshold_lines(fig, colors, row=i)
 
-# Elke dag herhaalt dezelfde spoornamen (Glucose/Basaal/Koolhydraten/...) — zonder
-# deduplicatie zou de legenda 7x "Glucose" etc. tonen. Alleen de eerste keer per
-# naam blijft in de legenda staan.
-seen_names = set()
-for trace in fig.data:
-    if trace.name in seen_names:
-        trace.showlegend = False
-    else:
-        seen_names.add(trace.name)
+    fig.update_xaxes(range=[day_start, day_end], dtick=4 * 3600 * 1000, gridcolor=colors["grid"])
+    fig.update_layout(
+        paper_bgcolor="rgba(0,0,0,0)",
+        plot_bgcolor="rgba(0,0,0,0)",
+        font_color=colors["text"],
+        height=560,
+        showlegend=True,
+        legend={"orientation": "h", "yanchor": "bottom", "y": 1.02, "xanchor": "left", "x": 0},
+        margin={"l": 10, "r": 10, "t": 40, "b": 10},
+    )
+    return fig
 
-fig.update_xaxes(title_text="Uur van de dag", range=[0, 24], dtick=4, gridcolor=colors["grid"])
-fig.update_layout(
-    paper_bgcolor="rgba(0,0,0,0)",
-    plot_bgcolor="rgba(0,0,0,0)",
-    font_color=colors["text"],
-    height=row_height * len(dates) + 40,
-    showlegend=True,
-    legend={"orientation": "h", "yanchor": "bottom", "y": 1.0, "xanchor": "left", "x": 0},
-    margin={"l": 10, "r": 10, "t": 40, "b": 10},
-)
+
+fig = build_day_figure(glucose, carbs_day, bolus_day, basal_day, target_day, colors)
 st.plotly_chart(fig, width="stretch")
+
+stats = daily_stats(glucose, day_treatments, profile, day_start, day_end)
+col1, col2, col3, col4 = st.columns(4)
+col1.metric(
+    "Glucose (gem./min/max)",
+    f"{stats['mean_mmol']:.1f} mmol/L",
+    delta=f"{stats['min_mmol']:.1f} - {stats['max_mmol']:.1f}",
+    delta_color="off",
+)
+col2.metric("Totale insuline", f"{stats['total_insulin']:.1f} E")
+col3.metric("Basaal / bolus / SMB", f"{stats['basal_insulin']:.1f} / {stats['bolus_insulin']:.1f} / {stats['smb_insulin']:.1f} E")
+col4.metric(
+    "Hypo's / hyper's",
+    f"{stats['hypo_count']} / {stats['hyper_count']}",
+    delta=f"{stats['hypo_duration_minutes']:.0f} / {stats['hyper_duration_minutes']:.0f} min",
+    delta_color="off",
+)
+
 st.caption(
-    f"{len(dates)} dagen · {len(glucose)} metingen · stippen = bolusinsuline "
-    "(voeding/correctie/SMB, grootte naar dosis) · vlak = basaal · staafjes = koolhydraten · "
-    "streepstippellijn = streefwaarde uit pompprofiel"
+    "Boven: stippen = bolusinsuline (voeding/correctie, grootte naar dosis) · staafjes = koolhydraten · "
+    "streepstippellijn = streefwaarde uit pompprofiel. Onder: vlak = basaal · stippen = SMB."
 )