Updated charts for glucose data and profile chart

pdf_export.py

@@ -230,7 +230,7 @@ def _insulin_profile_figure_png(profile: dict) -> bytes:
     if bars:
         hours = [b["hour"] for b in bars]
         values = [b["value"] for b in bars]
-        ax.step(hours, values, where="post", color=_BASAL_COLOR, linewidth=1.5)
+        ax.step(hours, values, where="post", color=_BASAL_COLOR, linewidth=1.5, alpha=0.8)
         ax.fill_between(hours, values, step="post", color=_BASAL_COLOR, alpha=0.3)
     ax.set_xlim(0, 24)
     ax.set_xticks(range(0, 25, 2))
@@ -261,9 +261,8 @@ def _add_carbs_overlay(ax2, day_treatments: pd.DataFrame, day_start) -> None:
     ax2.bar(hours, carbs["carbs"], width=0.25, color=_CARBS_COLOR, alpha=0.55, label="Koolhydraten")
 
 
-def _add_bolus_overlay(ax, day_treatments: pd.DataFrame, day_start, lane_y: float) -> None:
-    bolus = classify_bolus(day_treatments)
-    for category in (BOLUS_CATEGORY_SMB, BOLUS_CATEGORY_CORRECTION, BOLUS_CATEGORY_FOOD):
+def _add_bolus_overlay(ax, bolus: pd.DataFrame, day_start, lane_y: float, categories: tuple[str, ...]) -> None:
+    for category in categories:
         subset = bolus[bolus["category"] == category] if not bolus.empty else bolus
         if subset.empty:
             continue
@@ -291,35 +290,56 @@ def _add_target_overlay(ax, profile: dict | None, day_start, day_end) -> None:
 def _daily_figure_png(
     day_df: pd.DataFrame, day_treatments: pd.DataFrame, profile: dict | None, day_label: str, day_start, day_end
 ) -> bytes:
-    """Eén dag als grafiek: glucoselijn + basaal/bolus/koolhydraten/streefwaarde-overlay."""
+    """Eén dag als twee gestapelde grafieken (gedeelde tijdas, één gedeelde legenda):
+    boven glucose + streefwaarde + koolhydraten + voeding/correctiebolus, onder
+    basaal + SMB — gescheiden omdat één gecombineerde grafiek te veel informatie
+    bevatte om nog leesbaar te zijn."""
     hours = day_df["timestamp"].dt.hour + day_df["timestamp"].dt.minute / 60
-    fig, ax = plt.subplots(figsize=(11, 3.8))
+    fig, (ax, ax_basal) = plt.subplots(2, 1, figsize=(11, 5.2), sharex=True, height_ratios=[2.2, 1])
     ax2 = ax.twinx()
 
-    basal = effective_basal_series(profile, day_treatments, day_start, day_end)
-    _add_basal_overlay(ax2, basal, day_start)
+    bolus = classify_bolus(day_treatments)
     _add_carbs_overlay(ax2, day_treatments, day_start)
-
     lane_y = (day_df["mmol"].min() - 1.0) if not day_df.empty else LOW - 1.0
-    _add_bolus_overlay(ax, day_treatments, day_start, lane_y)
+    _add_bolus_overlay(ax, bolus, day_start, lane_y, categories=(BOLUS_CATEGORY_CORRECTION, BOLUS_CATEGORY_FOOD))
     _add_target_overlay(ax, profile, day_start, day_end)
 
     ax.plot(hours, day_df["mmol"], color="#2a78d6", linewidth=1.4, label="Glucose", zorder=6)
     _add_threshold_lines(ax)
-    ax.set_xlim(0, 24)
-    ax.set_xticks(range(0, 25, 2))
     ax.set_ylabel("mmol/L", fontsize=9)
-    ax2.set_ylabel("Basaal (E/uur) · KH (g)", fontsize=9)
+    ax2.set_ylabel("Koolhydraten (g)", fontsize=9)
     ax.set_title(day_label, fontsize=11, loc="left")
     ax.tick_params(labelsize=8)
     ax2.tick_params(labelsize=8)
 
+    basal = effective_basal_series(profile, day_treatments, day_start, day_end)
+    _add_basal_overlay(ax_basal, basal, day_start)
+    smb_lane_y = (basal["rate"].max() * 1.15) if not basal.empty else 1.0
+    _add_bolus_overlay(ax_basal, bolus, day_start, smb_lane_y, categories=(BOLUS_CATEGORY_SMB,))
+    ax_basal.set_xlim(0, 24)
+    ax_basal.set_xticks(range(0, 25, 2))
+    ax_basal.set_xlabel(_HOUR_OF_DAY_LABEL)
+    ax_basal.set_ylabel("Basaal (E/uur)", fontsize=9)
+    ax_basal.tick_params(labelsize=8)
+
     lines1, labels1 = ax.get_legend_handles_labels()
     lines2, labels2 = ax2.get_legend_handles_labels()
-    ax.legend(
-        lines1 + lines2, labels1 + labels2, loc="upper center", bbox_to_anchor=(0.5, -0.2), ncol=6, fontsize=7, frameon=False
+    lines3, labels3 = ax_basal.get_legend_handles_labels()
+    ax_basal.legend(
+        lines1 + lines2 + lines3,
+        labels1 + labels2 + labels3,
+        loc="upper center",
+        bbox_to_anchor=(0.5, -0.35),
+        ncol=6,
+        fontsize=7,
+        frameon=False,
     )
-    fig.tight_layout()
+    # fig.tight_layout() introspecteert elke as se bounding box om marges te
+    # berekenen, en matplotlib ondersteunt dat niet betrouwbaar zodra er twee
+    # hoofd-assen (ax/ax_basal) plus een twinx (ax2) tegelijk in de figuur
+    # zitten (waarschuwing "Axes ... not compatible with tight_layout").
+    # subplots_adjust() met vaste marges omzeilt die introspectie.
+    fig.subplots_adjust(left=0.06, right=0.94, top=0.93, bottom=0.24, hspace=0.35)
     return _fig_to_png(fig)