feat: add Treatment Duration bar chart (Task 9.9)
This commit is contained in:
Andrew Charlwood
@@ -431,12 +431,12 @@ Drawer selection → update_drug_selection → app-state store → load_pathway_
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- **Checkpoint**: Heatmap tab renders matrix with correct colour mapping ✓
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### 9.9 Treatment Duration chart (Tab 8)
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- [ ] Create `dash_app/callbacks/duration.py`:
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- [x] Create `dash_app/callbacks/duration.py`:
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- Build horizontal bar chart from `get_treatment_durations()` data
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- Y-axis = drug, X-axis = average days, colour intensity by patient count
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- Directorate filter drives which drugs are shown
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- [ ] Create figure function in `src/visualization/`
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- [ ] Wire into tab switching
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- [x] Create figure function in `src/visualization/`
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- [x] Wire into tab switching
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- **Checkpoint**: Duration tab renders real data, responds to directorate filter
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### 9.10 Final integration + polish
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@@ -233,6 +233,34 @@ def _render_heatmap(app_state, title):
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return create_heatmap_figure(data, title, metric="patients")
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def _render_duration(app_state, title):
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"""Build the treatment duration horizontal bar chart from current filter state."""
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from dash_app.data.queries import get_treatment_durations
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from visualization.plotly_generator import create_duration_figure
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filter_id = (app_state or {}).get("date_filter_id", "all_6mo")
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chart_type = (app_state or {}).get("chart_type", "directory")
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selected_dirs = (app_state or {}).get("selected_directorates") or []
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directory = selected_dirs[0] if len(selected_dirs) == 1 else None
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selected_trusts = (app_state or {}).get("selected_trusts") or []
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trust = selected_trusts[0] if len(selected_trusts) == 1 else None
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try:
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data = get_treatment_durations(filter_id, chart_type, directory, trust)
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except Exception:
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log.exception("Failed to load treatment duration data")
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return _empty_figure("Failed to load treatment duration data.")
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if not data:
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return _empty_figure("No treatment duration data available.\nTry adjusting your filters.")
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# Show directory breakdown when no specific directory is filtered
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show_directory = directory is None and chart_type == "indication"
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return create_duration_figure(data, title, show_directory=show_directory)
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def register_chart_callbacks(app):
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"""Register tab switching, pathway data loading, and chart rendering callbacks."""
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@@ -364,6 +392,9 @@ def register_chart_callbacks(app):
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elif active_tab == "heatmap":
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fig = _render_heatmap(app_state, title)
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elif active_tab == "duration":
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fig = _render_duration(app_state, title)
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else:
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# Placeholder for charts not yet implemented
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tab_label = dict(TAB_DEFINITIONS).get(active_tab, active_tab)
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@@ -1324,3 +1324,152 @@ def create_heatmap_figure(
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)
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return fig
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def create_duration_figure(
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data: list[dict],
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title: str = "",
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show_directory: bool = False,
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) -> go.Figure:
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"""Create horizontal bar chart showing average treatment duration by drug.
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Args:
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data: List of dicts from get_treatment_durations() with keys:
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drug, directory, avg_days, patients.
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Sorted by avg_days desc.
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title: Chart title suffix (filter description).
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show_directory: If True, include directory in label (for overview mode).
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Returns:
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Plotly Figure with horizontal bars coloured by patient count.
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"""
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if not data:
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return go.Figure()
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# When not showing directory breakdown, aggregate same drug across directorates
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if not show_directory:
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agg = {}
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for d in data:
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drug = d["drug"]
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pts = d["patients"]
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days = d["avg_days"]
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if drug not in agg:
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agg[drug] = {"drug": drug, "total_weighted": 0.0, "total_pts": 0}
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agg[drug]["total_weighted"] += days * pts
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agg[drug]["total_pts"] += pts
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data = []
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for v in agg.values():
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if v["total_pts"] > 0:
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data.append({
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"drug": v["drug"],
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"avg_days": round(v["total_weighted"] / v["total_pts"], 1),
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"patients": v["total_pts"],
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})
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data.sort(key=lambda x: -x["avg_days"])
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# Cap at 40 entries for readability (keep top by patient count, then re-sort by days)
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if len(data) > 40:
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data.sort(key=lambda x: -x["patients"])
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data = data[:40]
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data.sort(key=lambda x: -x["avg_days"])
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# Build labels
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if show_directory:
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labels = [f"{d['drug']} ({d['directory']})" for d in data]
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else:
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labels = [d["drug"] for d in data]
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days_values = [d["avg_days"] for d in data]
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patients_list = [d["patients"] for d in data]
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# Colour gradient by patient count: light for few → dark NHS blue for many
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max_pts = max(patients_list) if patients_list else 1
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min_pts = min(patients_list) if patients_list else 0
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pt_range = max_pts - min_pts if max_pts > min_pts else 1
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bar_colours = []
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for pts in patients_list:
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t = (pts - min_pts) / pt_range
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r = int(0x41 + (0x00 - 0x41) * t)
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g = int(0xB6 + (0x30 - 0xB6) * t)
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b = int(0xE6 + (0x87 - 0xE6) * t)
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bar_colours.append(f"rgb({r},{g},{b})")
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hover_texts = []
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for d in data:
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years = d["avg_days"] / 365.25
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hover_texts.append(
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f"<b>{d['drug']}</b><br>"
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f"Avg duration: {d['avg_days']:,.0f} days ({years:.1f} years)<br>"
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f"Patients: {d['patients']:,}"
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)
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fig = go.Figure()
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fig.add_trace(
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go.Bar(
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y=labels,
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x=days_values,
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orientation="h",
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marker=dict(
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color=bar_colours,
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line=dict(color="#FFFFFF", width=1),
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),
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hovertemplate="%{customdata}<extra></extra>",
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customdata=hover_texts,
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text=[f"{v:,.0f}d" for v in days_values],
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textposition="outside",
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textfont=dict(size=10, color="#425563"),
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)
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)
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for i, pts in enumerate(patients_list):
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fig.add_annotation(
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x=days_values[i],
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y=labels[i],
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text=f"n={pts:,}",
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showarrow=False,
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xshift=45,
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font=dict(size=9, color="#768692", family="Source Sans 3"),
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)
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chart_title = "Treatment Duration by Drug"
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if title:
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chart_title += f"<br><span style='font-size:13px;color:#768692'>{title}</span>"
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n_bars = len(data)
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fig_height = max(400, 40 + n_bars * 28)
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fig.update_layout(
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title=dict(
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text=chart_title,
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font=dict(
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family="Source Sans 3, system-ui, sans-serif",
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size=18,
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color="#003087",
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),
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x=0.5,
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xanchor="center",
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),
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xaxis=dict(
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title="Average Duration (days)",
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titlefont=dict(size=13, color="#425563"),
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tickfont=dict(size=11, color="#425563"),
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gridcolor="rgba(0,0,0,0.06)",
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zeroline=True,
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zerolinecolor="rgba(0,0,0,0.1)",
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),
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yaxis=dict(
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title="",
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tickfont=dict(size=11, color="#425563"),
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autorange="reversed",
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),
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plot_bgcolor="rgba(0,0,0,0)",
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paper_bgcolor="rgba(0,0,0,0)",
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font=dict(family="Source Sans 3, system-ui, sans-serif"),
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margin=dict(t=60, l=200, r=80, b=50),
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height=fig_height,
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showlegend=False,
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)
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return fig
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