feat: add Directorate × Drug Heatmap chart (Task 9.8)

2026-02-06 20:04:19 +00:00
parent c1e11a6dd7
commit 0af76e68e0
3 changed files with 170 additions and 4 deletions
@@ -421,14 +421,14 @@ Drawer selection → update_drug_selection → app-state store → load_pathway_
 - **Checkpoint**: Dosing tab renders real data with parsed interval numbers ✓

 ### 9.8 Directorate × Drug Heatmap chart (Tab 7)
- [ ] Create `dash_app/callbacks/heatmap.py`:
+- [x] Create `dash_app/callbacks/heatmap.py`:
  - Build Plotly heatmap from `get_drug_directory_matrix()` data
  - Rows = directorates (sorted by total patients), columns = drugs (sorted by frequency)
  - Cell colour = patient count or cost, hover shows details
  - Toggle between patient count / cost / cost_pp_pa colouring (additional control in tab)
- [ ] Create figure function in `src/visualization/`
- [ ] Wire into tab switching
- **Checkpoint**: Heatmap tab renders matrix with correct colour mapping
+- [x] Create figure function in `src/visualization/`
+- [x] Wire into tab switching
+- **Checkpoint**: Heatmap tab renders matrix with correct colour mapping ✓

 ### 9.9 Treatment Duration chart (Tab 8)
 - [ ] Create `dash_app/callbacks/duration.py`:
@@ -210,6 +210,29 @@ def _render_dosing(app_state, title):
    return create_dosing_figure(data, title, group_by)


+def _render_heatmap(app_state, title):
+    """Build the directorate × drug heatmap from current filter state."""
+    from dash_app.data.queries import get_drug_directory_matrix
+    from visualization.plotly_generator import create_heatmap_figure
+
+    filter_id = (app_state or {}).get("date_filter_id", "all_6mo")
+    chart_type = (app_state or {}).get("chart_type", "directory")
+
+    selected_trusts = (app_state or {}).get("selected_trusts") or []
+    trust = selected_trusts[0] if len(selected_trusts) == 1 else None
+
+    try:
+        data = get_drug_directory_matrix(filter_id, chart_type, trust)
+    except Exception:
+        log.exception("Failed to load heatmap data")
+        return _empty_figure("Failed to load heatmap data.")
+
+    if not data.get("directories") or not data.get("drugs"):
+        return _empty_figure("No heatmap data available.\nTry adjusting your filters.")
+
+    return create_heatmap_figure(data, title, metric="patients")
+
+
 def register_chart_callbacks(app):
    """Register tab switching, pathway data loading, and chart rendering callbacks."""

@@ -338,6 +361,9 @@ def register_chart_callbacks(app):
        elif active_tab == "dosing":
            fig = _render_dosing(app_state, title)

+        elif active_tab == "heatmap":
+            fig = _render_heatmap(app_state, title)
+
        else:
            # Placeholder for charts not yet implemented
            tab_label = dict(TAB_DEFINITIONS).get(active_tab, active_tab)
@@ -1184,3 +1184,143 @@ def figure_legacy(ice_df: pd.DataFrame, dir_string: str, save_dir: str) -> None:
    fig.write_html(filepath)
    logger.info(f"Success! File saved to {filepath}")
    webbrowser.open_new_tab("file:///" + filepath)
+
+
+def create_heatmap_figure(
+    data: dict,
+    title: str = "",
+    metric: str = "patients",
+) -> go.Figure:
+    """Create a directorate × drug heatmap chart.
+
+    Args:
+        data: Dict from get_drug_directory_matrix() with keys:
+              directories (list), drugs (list),
+              matrix ({dir: {drug: {patients, cost, cost_pp_pa}}}).
+        title: Chart title suffix (filter description).
+        metric: Colour metric — "patients", "cost", or "cost_pp_pa".
+
+    Returns:
+        Plotly Figure with annotated heatmap.
+    """
+    directories = data.get("directories", [])
+    drugs = data.get("drugs", [])
+    matrix = data.get("matrix", {})
+
+    if not directories or not drugs:
+        return go.Figure()
+
+    # Cap columns to top 25 drugs for readability
+    max_drugs = 25
+    drugs = drugs[:max_drugs]
+
+    metric_labels = {
+        "patients": "Patients",
+        "cost": "Total Cost (£)",
+        "cost_pp_pa": "Cost per Patient p.a. (£)",
+    }
+    metric_label = metric_labels.get(metric, "Patients")
+
+    # Build 2D arrays for z-values and hover text
+    z_values = []
+    hover_texts = []
+
+    for d in directories:
+        row_z = []
+        row_hover = []
+        dir_data = matrix.get(d, {})
+        for drug in drugs:
+            cell = dir_data.get(drug)
+            if cell:
+                val = cell.get(metric, cell.get("patients", 0))
+                patients = cell.get("patients", 0)
+                cost = cell.get("cost", 0)
+                cpp = cell.get("cost_pp_pa", 0)
+                row_z.append(val if val else 0)
+                row_hover.append(
+                    f"<b>{drug}</b><br>"
+                    f"{d}<br>"
+                    f"Patients: {patients:,}<br>"
+                    f"Total cost: £{cost:,.0f}<br>"
+                    f"Cost p.a.: £{cpp:,.0f}"
+                )
+            else:
+                row_z.append(0)
+                row_hover.append(
+                    f"<b>{drug}</b><br>{d}<br>No patients"
+                )
+        z_values.append(row_z)
+        hover_texts.append(row_hover)
+
+    # NHS blue colorscale for the heatmap
+    colorscale = [
+        [0.0, "#F0F4F8"],
+        [0.01, "#E3F2FD"],
+        [0.1, "#90CAF9"],
+        [0.3, "#42A5F5"],
+        [0.5, "#1E88E5"],
+        [0.7, "#0066CC"],
+        [1.0, "#003087"],
+    ]
+
+    fig = go.Figure(
+        data=go.Heatmap(
+            z=z_values,
+            x=drugs,
+            y=directories,
+            colorscale=colorscale,
+            hovertext=hover_texts,
+            hovertemplate="%{hovertext}<extra></extra>",
+            colorbar=dict(
+                title=dict(
+                    text=metric_label,
+                    font=dict(size=12, color="#425563"),
+                ),
+                thickness=15,
+                len=0.8,
+            ),
+            xgap=2,
+            ygap=2,
+        )
+    )
+
+    chart_title = f"Directorate × Drug — {metric_label}"
+    if title:
+        chart_title = f"{chart_title} — {title}"
+
+    n_drugs = len(drugs)
+    n_dirs = len(directories)
+    fig_width = max(700, 80 + n_drugs * 55)
+    fig_height = max(400, 80 + n_dirs * 40)
+
+    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="",
+            tickfont=dict(size=11, color="#425563"),
+            tickangle=-45,
+            side="bottom",
+        ),
+        yaxis=dict(
+            title="",
+            tickfont=dict(size=12, 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=120),
+        width=fig_width,
+        height=fig_height,
+    )
+
+    return fig