feat: add Treatment Duration bar chart (Task 9.9)

IMPLEMENTATION_PLAN.md

@@ -431,12 +431,12 @@ Drawer selection → update_drug_selection → app-state store → load_pathway_
 - **Checkpoint**: Heatmap tab renders matrix with correct colour mapping ✓
 
 ### 9.9 Treatment Duration chart (Tab 8)
-- [ ] Create `dash_app/callbacks/duration.py`:
+- [x] Create `dash_app/callbacks/duration.py`:
   - Build horizontal bar chart from `get_treatment_durations()` data
   - Y-axis = drug, X-axis = average days, colour intensity by patient count
   - Directorate filter drives which drugs are shown
-- [ ] Create figure function in `src/visualization/`
+- [x] Create figure function in `src/visualization/`
-- [ ] Wire into tab switching
+- [x] Wire into tab switching
 - **Checkpoint**: Duration tab renders real data, responds to directorate filter
 
 ### 9.10 Final integration + polish

dash_app/callbacks/chart.py

@@ -233,6 +233,34 @@ def _render_heatmap(app_state, title):
     return create_heatmap_figure(data, title, metric="patients")
 
 
+def _render_duration(app_state, title):
+    """Build the treatment duration horizontal bar chart from current filter state."""
+    from dash_app.data.queries import get_treatment_durations
+    from visualization.plotly_generator import create_duration_figure
+
+    filter_id = (app_state or {}).get("date_filter_id", "all_6mo")
+    chart_type = (app_state or {}).get("chart_type", "directory")
+
+    selected_dirs = (app_state or {}).get("selected_directorates") or []
+    directory = selected_dirs[0] if len(selected_dirs) == 1 else None
+
+    selected_trusts = (app_state or {}).get("selected_trusts") or []
+    trust = selected_trusts[0] if len(selected_trusts) == 1 else None
+
+    try:
+        data = get_treatment_durations(filter_id, chart_type, directory, trust)
+    except Exception:
+        log.exception("Failed to load treatment duration data")
+        return _empty_figure("Failed to load treatment duration data.")
+
+    if not data:
+        return _empty_figure("No treatment duration data available.\nTry adjusting your filters.")
+
+    # Show directory breakdown when no specific directory is filtered
+    show_directory = directory is None and chart_type == "indication"
+    return create_duration_figure(data, title, show_directory=show_directory)
+
+
 def register_chart_callbacks(app):
     """Register tab switching, pathway data loading, and chart rendering callbacks."""
 
@@ -364,6 +392,9 @@ def register_chart_callbacks(app):
         elif active_tab == "heatmap":
             fig = _render_heatmap(app_state, title)
 
+        elif active_tab == "duration":
+            fig = _render_duration(app_state, title)
+
         else:
             # Placeholder for charts not yet implemented
             tab_label = dict(TAB_DEFINITIONS).get(active_tab, active_tab)

src/visualization/plotly_generator.py

@@ -1324,3 +1324,152 @@ def create_heatmap_figure(
     )
 
     return fig
+
+
+def create_duration_figure(
+    data: list[dict],
+    title: str = "",
+    show_directory: bool = False,
+) -> go.Figure:
+    """Create horizontal bar chart showing average treatment duration by drug.
+
+    Args:
+        data: List of dicts from get_treatment_durations() with keys:
+              drug, directory, avg_days, patients.
+              Sorted by avg_days desc.
+        title: Chart title suffix (filter description).
+        show_directory: If True, include directory in label (for overview mode).
+
+    Returns:
+        Plotly Figure with horizontal bars coloured by patient count.
+    """
+    if not data:
+        return go.Figure()
+
+    # When not showing directory breakdown, aggregate same drug across directorates
+    if not show_directory:
+        agg = {}
+        for d in data:
+            drug = d["drug"]
+            pts = d["patients"]
+            days = d["avg_days"]
+            if drug not in agg:
+                agg[drug] = {"drug": drug, "total_weighted": 0.0, "total_pts": 0}
+            agg[drug]["total_weighted"] += days * pts
+            agg[drug]["total_pts"] += pts
+        data = []
+        for v in agg.values():
+            if v["total_pts"] > 0:
+                data.append({
+                    "drug": v["drug"],
+                    "avg_days": round(v["total_weighted"] / v["total_pts"], 1),
+                    "patients": v["total_pts"],
+                })
+        data.sort(key=lambda x: -x["avg_days"])
+
+    # Cap at 40 entries for readability (keep top by patient count, then re-sort by days)
+    if len(data) > 40:
+        data.sort(key=lambda x: -x["patients"])
+        data = data[:40]
+        data.sort(key=lambda x: -x["avg_days"])
+
+    # Build labels
+    if show_directory:
+        labels = [f"{d['drug']} ({d['directory']})" for d in data]
+    else:
+        labels = [d["drug"] for d in data]
+
+    days_values = [d["avg_days"] for d in data]
+    patients_list = [d["patients"] for d in data]
+
+    # Colour gradient by patient count: light for few → dark NHS blue for many
+    max_pts = max(patients_list) if patients_list else 1
+    min_pts = min(patients_list) if patients_list else 0
+    pt_range = max_pts - min_pts if max_pts > min_pts else 1
+
+    bar_colours = []
+    for pts in patients_list:
+        t = (pts - min_pts) / pt_range
+        r = int(0x41 + (0x00 - 0x41) * t)
+        g = int(0xB6 + (0x30 - 0xB6) * t)
+        b = int(0xE6 + (0x87 - 0xE6) * t)
+        bar_colours.append(f"rgb({r},{g},{b})")
+
+    hover_texts = []
+    for d in data:
+        years = d["avg_days"] / 365.25
+        hover_texts.append(
+            f"<b>{d['drug']}</b><br>"
+            f"Avg duration: {d['avg_days']:,.0f} days ({years:.1f} years)<br>"
+            f"Patients: {d['patients']:,}"
+        )
+
+    fig = go.Figure()
+
+    fig.add_trace(
+        go.Bar(
+            y=labels,
+            x=days_values,
+            orientation="h",
+            marker=dict(
+                color=bar_colours,
+                line=dict(color="#FFFFFF", width=1),
+            ),
+            hovertemplate="%{customdata}<extra></extra>",
+            customdata=hover_texts,
+            text=[f"{v:,.0f}d" for v in days_values],
+            textposition="outside",
+            textfont=dict(size=10, color="#425563"),
+        )
+    )
+
+    for i, pts in enumerate(patients_list):
+        fig.add_annotation(
+            x=days_values[i],
+            y=labels[i],
+            text=f"n={pts:,}",
+            showarrow=False,
+            xshift=45,
+            font=dict(size=9, color="#768692", family="Source Sans 3"),
+        )
+
+    chart_title = "Treatment Duration by Drug"
+    if title:
+        chart_title += f"<br><span style='font-size:13px;color:#768692'>{title}</span>"
+
+    n_bars = len(data)
+    fig_height = max(400, 40 + n_bars * 28)
+
+    fig.update_layout(
+        title=dict(
+            text=chart_title,
+            font=dict(
+                family="Source Sans 3, system-ui, sans-serif",
+                size=18,
+                color="#003087",
+            ),
+            x=0.5,
+            xanchor="center",
+        ),
+        xaxis=dict(
+            title="Average Duration (days)",
+            titlefont=dict(size=13, color="#425563"),
+            tickfont=dict(size=11, color="#425563"),
+            gridcolor="rgba(0,0,0,0.06)",
+            zeroline=True,
+            zerolinecolor="rgba(0,0,0,0.1)",
+        ),
+        yaxis=dict(
+            title="",
+            tickfont=dict(size=11, color="#425563"),
+            autorange="reversed",
+        ),
+        plot_bgcolor="rgba(0,0,0,0)",
+        paper_bgcolor="rgba(0,0,0,0)",
+        font=dict(family="Source Sans 3, system-ui, sans-serif"),
+        margin=dict(t=60, l=200, r=80, b=50),
+        height=fig_height,
+        showlegend=False,
+    )
+
+    return fig