Replace monthly GMI bar chart with daily scatter + rolling avg + linear trend/CI

Adds daily_gmi() and gmi_trend(): per-day GMI as scatter points, a 7-day
rolling average line, and a linear regression trend line with a 95%
confidence band (normal approximation, no scipy dependency, consistent
with the existing preference for a lean container image).

Recomputed from the already-fetched period data on each page load; the
existing 1-hour Streamlit cache on load_range_data() already avoids
repeated Nightscout calls for the same period, so no separate storage
layer is needed at the current max. 90-day report window.

Closes gitea #19.

pages/7_Trends.py

@@ -9,12 +9,13 @@ from reporting import (
     basal_stats,
     bolus_stats,
     day_of_week_pattern,
-    gmi_percent,
+    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,
@@ -46,26 +47,70 @@ render_completeness_warning(glucose, start, end)
 colors = get_colors()
 events = classify_treatments(treatments)
 
-# --- FR7: geschat HbA1c (GMI) per maand ------------------------------------
-st.subheader("Geschat HbA1c (GMI) per maand")
-monthly = glucose.copy()
-monthly["month"] = monthly["timestamp"].dt.to_period("M").astype(str)
-monthly_gmi = monthly.groupby("month")["mmol"].mean().apply(gmi_percent)
+# --- FR7: geschat HbA1c (GMI) trend ----------------------------------------
+st.subheader("Geschat HbA1c (GMI) trend")
+trend = gmi_trend(glucose)
 
-if len(monthly_gmi) >= 1:
-    fig = go.Figure(
-        go.Bar(x=monthly_gmi.index, y=monthly_gmi.to_numpy(), marker_color=colors["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=280,
+        height=320,
         margin={"l": 10, "r": 10, "t": 10, "b": 10},
         yaxis={"title": "GMI (%)", "gridcolor": colors["grid"]},
-        xaxis={"title": "Maand", "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 --------------------------------------------------