Remove legacy/ralph/temp files from tracking
This commit is contained in:
Andrew Charlwood
@@ -1,404 +0,0 @@
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# Implementation Plan — Dashboard Visualization Improvements
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## Project Overview
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Comprehensive review and improvement of all Plotly charts in the Dash dashboard. Four tiers: bug fixes, visual polish, new analytics from existing data, and new analytics requiring backend work.
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**Primary file**: `src/visualization/plotly_generator.py`
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**Palette policy**: Broader than NHS brand (maximally-distinct colors for trust comparisons)
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**Constraint**: `python run_dash.py` must work after every task
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### What Changes
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- `src/visualization/plotly_generator.py` — shared styling constants, bug fixes, new chart functions
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- `src/data_processing/pathway_queries.py` — new/modified query functions
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- `dash_app/data/queries.py` — thin wrappers for new queries
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- `dash_app/callbacks/chart.py` — remove Trends tab, fix chart height
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- `dash_app/callbacks/trust_comparison.py` — trust color palette, heatmap metric toggle
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- `dash_app/callbacks/trends.py` — NEW: Trends view callbacks (directorate overview + drug drill-down)
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- `dash_app/callbacks/__init__.py` — register new trends callbacks
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- `dash_app/components/chart_card.py` — remove Trends tab, metric toggle cleanup
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- `dash_app/components/trust_comparison.py` — metric toggle component
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- `dash_app/components/trends.py` — NEW: Trends landing + detail components
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- `dash_app/components/sidebar.py` — add Trends nav item
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- `dash_app/callbacks/navigation.py` — 3-way view switching
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- `dash_app/callbacks/filters.py` — add nav-trends input
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- `dash_app/app.py` — add trends-view to layout, add selected_trends_directorate to app-state
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- `dash_app/assets/nhs.css` — chart height CSS for responsive sizing
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### What Stays (DO NOT MODIFY)
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- Pipeline/analysis logic: `pathway_pipeline.py`, `transforms.py`, `diagnosis_lookup.py`, `pathway_analyzer.py`
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- Database schema and `pathway_nodes` table
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- CLI refresh command and `cli/compute_trends.py`
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- Existing callback chain architecture (app-state → chart-data → UI)
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- Trust Comparison view (unchanged)
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---
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## Phase A: Core Fixes + Shared Constants
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### A.1 Extract shared styling constants + `_base_layout()` helper
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- [x] Add module-level constants to top of `src/visualization/plotly_generator.py`:
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```python
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CHART_FONT_FAMILY = "Source Sans 3, system-ui, sans-serif"
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CHART_TITLE_SIZE = 18
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CHART_TITLE_COLOR = "#1E293B"
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GRID_COLOR = "#E2E8F0"
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ANNOTATION_COLOR = "#768692"
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TRUST_PALETTE = [
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"#005EB8", "#DA291C", "#009639", "#ED8B00",
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"#7C2855", "#00A499", "#330072",
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]
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DRUG_PALETTE = [
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"#005EB8", "#DA291C", "#009639", "#ED8B00", "#7C2855",
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"#00A499", "#330072", "#E06666", "#6FA8DC", "#93C47D",
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"#F6B26B", "#8E7CC3", "#C27BA0", "#76A5AF", "#FFD966",
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]
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```
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- [x] Create `_base_layout(title, **overrides)` helper returning a dict with shared layout properties (title font, hoverlabel, paper/plot bgcolor, autosize, font family)
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- [x] Apply `_base_layout()` to `create_icicle_from_nodes()` as a proof-of-concept (keep all existing behavior, just DRY the layout dict)
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- **Checkpoint**: `python run_dash.py` starts, icicle chart unchanged visually
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### A.2 Fix heatmap colorscale + cell annotations (Patient Pathways)
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- [x] In `create_heatmap_figure()` (~L1189):
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1. Replace non-linear colorscale with linear 5-stop: `[0.0 #E3F2FD, 0.25 #90CAF9, 0.5 #42A5F5, 0.75 #1E88E5, 1.0 #003087]`
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2. Add `text=text_values, texttemplate="%{text}"` with formatted values per metric (patients: `"N"`, cost: `"£Nk"`, cost_pp_pa: `"£N"`)
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3. Set `zmin=0` explicitly
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4. Remove explicit `width`, use `autosize=True`
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5. Replace `l=200` with `l=8` + `yaxis automargin=True`
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6. Add subtitle annotation when 25-drug cap is hit: `"Showing top 25 of N drugs"`
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7. Reduce `xgap/ygap` from 2→1 when >15 columns
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- [x] Apply same fixes to `create_trust_heatmap_figure()` (~L1582)
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- [x] Apply `_base_layout()` to both heatmap functions
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- **Checkpoint**: Heatmaps show linear color gradient, cell text visible, no fixed width overflow
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### A.3 Fix legend overflow in 4 charts
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- [x] Create `_smart_legend(n_items)` helper that returns legend dict:
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- When >15 items: vertical legend on right (`orientation="v", x=1.02, y=1, xanchor="left"`) with dynamic right margin
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- When ≤15: horizontal legend with dynamic bottom margin based on estimated row count
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- [x] Also created `_smart_legend_margin(n_items)` helper returning margin dict with dynamic b/r values
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- [x] Apply to `create_market_share_figure()` — also replaced local nhs_colours with DRUG_PALETTE
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- [x] Apply to `create_trust_market_share_figure()` — also replaced local nhs_colours with DRUG_PALETTE, fixed Unicode escapes to literal chars
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- [x] Apply to `create_dosing_figure()` — replaced local nhs_colours with DRUG_PALETTE, legend adapts to trace count
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- [x] Apply to `create_trust_duration_figure()` — replaced local nhs_colours with TRUST_PALETTE, fixed l=200→l=8+automargin
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- [x] Apply `_base_layout()` to all 4 functions
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- **Checkpoint**: Legends don't overlap chart content with 42 drugs or 7 trusts
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### A.4 Fix trust comparison color differentiation
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- [x] In `create_trust_duration_figure()`: replace `nhs_colours` list with `TRUST_PALETTE` (done in A.3)
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- [x] Add `is_trust_comparison=False` param to `create_cost_waterfall_figure()` — use `TRUST_PALETTE` when True
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- [x] Update `tc_cost_waterfall` callback in `dash_app/callbacks/trust_comparison.py` to pass `is_trust_comparison=True`
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- [x] Fix `_dosing_by_drug()` blue→blue interpolation: replaced with `plotly.colors.sample_colorscale("Viridis", ...)` for meaningful gradient
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- [x] Replace `nhs_colours` in `create_trust_market_share_figure()` with `DRUG_PALETTE` for drug traces (done in A.3)
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- [x] Apply `_base_layout()` to all affected functions (done in A.3 for trust_market_share and trust_duration)
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- **Checkpoint**: Trust Comparison charts have 7 visually distinct trust colors; dosing has meaningful gradient
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---
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## Phase B: Visual Polish
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### B.1 Fix title inconsistencies across all charts
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- [x] Sankey: replaced local nhs_colours with DRUG_PALETTE, title color `"#003087"` → `CHART_TITLE_COLOR` via `_base_layout()`
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- [x] Dosing: already converted in A.3 — uses `_base_layout()` with CHART_TITLE_COLOR
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- [x] Patient Pathways heatmap: already converted in A.2 — uses `_base_layout()` with CHART_TITLE_COLOR
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- [x] Duration: title color `"#003087"` → `CHART_TITLE_COLOR`, fixed l=200→l=8+automargin, used constants for annotations
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- [x] All Trust Comparison functions: already use `_base_layout()` (A.2-A.4), title size=18 via CHART_TITLE_SIZE
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- [x] Applied `_base_layout()` to all remaining chart functions: Sankey, Cost Effectiveness, Duration
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- [x] Cost Effectiveness: replaced 38-line manual layout with `_base_layout()`, hardcoded colors/fonts → constants
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- **Checkpoint**: All chart titles use consistent font, size, and color
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### B.2 Cost effectiveness smooth gradient
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- [x] In `create_cost_effectiveness_figure()`:
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- Replaced 3-bin hard threshold with smooth `_lerp_color()` RGB interpolation
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- Green (#009639) → Amber (#ED8B00) for ratio 0–0.5
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- Amber (#ED8B00) → Red (#DA291C) for ratio 0.5–1.0
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- [x] `_base_layout()` already applied in B.1
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- **Checkpoint**: Lollipop dots show smooth green→amber→red gradient
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### B.3 Sankey narrow-screen fix
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- [x] In `create_sankey_figure()` (~L808):
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- Changed `arrangement="snap"` → `arrangement="freeform"`
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- Increased `pad` from 20 → 25
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- **Checkpoint**: Sankey nodes don't overlap on narrow viewports
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### B.4 Heatmap metric toggle (both views)
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- [x] Add `dmc.SegmentedControl` component next to Patient Pathways heatmap:
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- Options: Patients, Cost, Cost p.a.
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- ID: `heatmap-metric-toggle`
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- Added to `dash_app/components/chart_card.py` in header, hidden by default, shown when heatmap tab active
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- Also added "heatmap" tab to TAB_DEFINITIONS (was only in ALL_TAB_DEFINITIONS before)
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- [x] Add `dmc.SegmentedControl` next to Trust Comparison heatmap:
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- ID: `tc-heatmap-metric-toggle`
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- Added to `dash_app/components/trust_comparison.py` inline in heatmap chart cell header
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- [x] Update `_render_heatmap()` in `dash_app/callbacks/chart.py` to accept metric param, `update_chart` passes toggle value + controls toggle visibility via `heatmap-metric-wrapper` style output
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- [x] Update `tc_heatmap` callback in `dash_app/callbacks/trust_comparison.py` to read `tc-heatmap-metric-toggle` value and pass to `create_trust_heatmap_figure()`
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- **Checkpoint**: Heatmap metric toggles work in both views, switching between patients/cost/cost_pp_pa
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---
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## Phase C: New Analytics (Existing Data)
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### C.1 Retention funnel chart
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- [x] Create `get_retention_funnel()` in `src/data_processing/pathway_queries.py`:
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- Query level 3+ nodes, aggregate patient counts by treatment line depth (level 3=1st drug, 4=2nd, 5=3rd)
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- Return: `[{depth: 1, label: "1st drug", patients: N, pct: 100.0}, ...]`
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- Supports directory/trust filters
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- [x] Add thin wrapper in `dash_app/data/queries.py`
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- [x] Create `create_retention_funnel_figure(data, title)` in `src/visualization/plotly_generator.py`:
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- Uses `go.Funnel` with NHS blue gradient (#003087 → #1E88E5)
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- Shows absolute patient count + percentage retained as text inside bars
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- Uses `_base_layout()` for consistent styling
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- [x] Add "Funnel" tab to `TAB_DEFINITIONS` in `chart_card.py` (4 tabs: Icicle, Sankey, Heatmap, Funnel)
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- [x] Add `_render_funnel()` helper and tab dispatch in `dash_app/callbacks/chart.py`
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- **Checkpoint**: Funnel tab shows retention by treatment line depth, responds to filters
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### C.2 Pathway depth distribution chart
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- [x] Create `get_pathway_depth_distribution()` in `src/data_processing/pathway_queries.py`:
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- Aggregate patient counts at level 3 (1-drug), level 4 (2-drug), etc.
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- Subtract child counts to get patients who STOPPED at each depth
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- Return: `[{depth: 1, label: "1 drug only", patients: N, pct: 80.2}, ...]`
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- [x] Add thin wrapper in `dash_app/data/queries.py`
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- [x] Create `create_pathway_depth_figure(data, title)` in `src/visualization/plotly_generator.py`:
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- Horizontal bar chart with NHS blue gradient by depth
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- Text shows "N (pct%)" inside bars
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- Uses `_base_layout()` for consistent styling
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- [x] Add "Depth" tab to `TAB_DEFINITIONS` in `chart_card.py` (5 tabs: Icicle, Sankey, Heatmap, Funnel, Depth)
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- [x] Add `_render_depth()` helper and tab dispatch in `dash_app/callbacks/chart.py`
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- **Checkpoint**: Depth tab shows patient distribution by treatment line count
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### C.3 Duration vs Cost scatter plot
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- [x] Create `get_duration_cost_scatter()` in `src/data_processing/pathway_queries.py`:
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- Query level 3 nodes for drug-level data with avg_days and cost_pp_pa
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- Aggregates across trusts using weighted averages
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- Return: `[{drug, directory, avg_days, cost_pp_pa, patients}, ...]`
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- [x] Add thin wrapper in `dash_app/data/queries.py`
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- [x] Create `create_duration_cost_scatter_figure(data, title)` in `src/visualization/plotly_generator.py`:
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- Scatter: x=avg_days, y=cost_pp_pa, size=patients (global max), color=directory
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- One trace per directory for legend grouping using DRUG_PALETTE
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- Quadrant lines at median values with annotations
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- Hover shows drug name, directory, all values
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- [x] Add "Scatter" tab to `TAB_DEFINITIONS` in `chart_card.py` (6 tabs: Icicle, Sankey, Heatmap, Funnel, Depth, Scatter)
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- [x] Add `_render_scatter()` helper and tab dispatch in `dash_app/callbacks/chart.py`
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- **Checkpoint**: Scatter tab shows drugs by duration vs cost with directorate coloring
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### C.4 Drug switching network graph
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- [x] Create `get_drug_network()` in pathway_queries.py — undirected edges without ordinal suffixes, node patients from level 3, edge co-occurrence from level 4+
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- [x] Add thin wrapper in `dash_app/data/queries.py`
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- [x] Create `create_drug_network_figure(data, title)` in `src/visualization/plotly_generator.py`:
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- Circular layout using `go.Scatter` for nodes + individual edge traces as lines
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- Node size = total patients (12–50px), edge width = switching flow (0.5–6px), edge opacity scales with strength
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- `DRUG_PALETTE` for node colors, NHS Blue (`rgba(0,94,184,...)`) for edges
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- [x] Added as separate "Network" tab (7th tab: Icicle, Sankey, Heatmap, Funnel, Depth, Scatter, Network)
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- [x] Added `_render_network()` helper and dispatch case in `chart.py`
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- **Checkpoint**: Network view shows drug switching as a graph alternative to Sankey
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---
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## Phase D: New Analytics (Backend Work)
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### D.1 Temporal trend analysis (historical snapshots approach)
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- [x] **D.1a — Create `cli/compute_trends.py` CLI script**:
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- Creates `pathway_trends` table via `CREATE TABLE IF NOT EXISTS` (no schema.py changes):
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```
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pathway_trends(period_end TEXT, drug TEXT, directory TEXT, patients INTEGER,
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total_cost REAL, cost_pp_pa REAL, PRIMARY KEY(period_end, drug, directory))
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```
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- Imports existing `fetch_and_transform_data()` and `process_pathway_for_date_filter()` from `pathway_pipeline.py` — does NOT modify them
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- Fetches all activity data once from Snowflake
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- Loops over 6-month historical endpoints (2021-06-30 through 2025-12-31, ~10 periods)
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- For each endpoint: calls `process_pathway_for_date_filter()` with `max_date=endpoint` using `all_6mo` config
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- Extracts level 3 summary stats (drug, directory, patients, cost, cost_pp_pa) from resulting DataFrame
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- Inserts aggregated rows into `pathway_trends` table
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- Run separately: `python -m cli.compute_trends` (not part of main refresh)
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- [x] **D.1b — Add Trends tab to Dash** (standard 6-step pattern):
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1. Create `get_trend_data(db_path, metric, directory, drug)` in `pathway_queries.py` — query `pathway_trends` table, return time-series data
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2. Add thin wrapper in `dash_app/data/queries.py`
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3. Create `create_trend_figure(data, title, metric)` in `plotly_generator.py` — line chart: x=period_end, y=metric, one line per drug (or per directory). Uses `_base_layout()` + `_smart_legend()`. Add `dmc.SegmentedControl` for metric toggle (patients / cost / cost_pp_pa)
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4. Add "Trends" tab to `TAB_DEFINITIONS` in `chart_card.py`
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5. Add `_render_trends()` helper + dispatch case in `chart.py`
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6. Handle empty state: if `pathway_trends` table doesn't exist or is empty, show "Run `python -m cli.compute_trends` to generate trend data" message
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- **Checkpoint**: Trends tab shows drug/directory trends over 10 historical periods, responds to filters. Empty state handled gracefully if trends not yet computed.
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### D.2 Average administered doses analysis
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- [x] Create `get_dosing_distribution()` query in `pathway_queries.py`:
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- Level 3 nodes with parsed `average_administered` JSON (position 0 = avg doses for drug)
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- Aggregates across trusts using weighted averages by patient count
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- Supports directory/trust filters. Returns `[{drug, directory, avg_doses, patients}]`
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- [x] Add thin wrapper in `dash_app/data/queries.py`
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- [x] Create `create_dosing_distribution_figure(data, title)` in plotly_generator.py:
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- Horizontal bar chart (avg doses per drug, one bar per drug x directory)
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- Colored by directory using DRUG_PALETTE, `_base_layout()` + `_smart_legend()`
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- Dynamic height, patient count in hover
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- [x] Add "Doses" tab to TAB_DEFINITIONS (9th tab)
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- [x] Add `_render_doses()` helper + dispatch in `chart.py`
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- **Checkpoint**: Doses tab shows average administered doses per drug, responds to filters
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### D.3 Drug timeline (Gantt chart)
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- [x] Create `get_drug_timeline()` query in `pathway_queries.py`:
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- Level 3 nodes with `first_seen`, `last_seen`, `labels`, `value` per drug × directory
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- Aggregates across trusts: MIN(first_seen), MAX(last_seen), SUM(value), weighted avg cost_pp_pa
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- Supports directory/trust filters
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- [x] Create `create_drug_timeline_figure(data, title)` in plotly_generator.py:
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- Gantt-style using `go.Bar` (horizontal bars from first_seen to last_seen)
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- One trace per bar, grouped by directory with legend grouping
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- Colored by directory using `DRUG_PALETTE`, patient count as bar text
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- Dynamic height (28px per bar), `_base_layout()` + `_smart_legend()`
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- [x] Add "Timeline" tab to `TAB_DEFINITIONS` in `chart_card.py` (8th tab)
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- [x] Add `_render_timeline()` helper + dispatch case in `chart.py`
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- **Checkpoint**: Timeline tab shows when each drug cohort was active
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---
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## Phase E: Trends View Redesign + Chart Height
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### E.1 Remove Trends tab from Patient Pathways
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- [x] Remove `("trends", "Trends")` from `TAB_DEFINITIONS` in `dash_app/components/chart_card.py`
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- [x] Remove `trends-metric-wrapper` div and `trends-metric-toggle` SegmentedControl from `chart_card.py`
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- [x] Remove `_render_trends()` helper from `dash_app/callbacks/chart.py`
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- [x] Remove `elif active_tab == "trends"` dispatch case from `update_chart()`
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- [x] Remove `Output("trends-metric-wrapper", "style")` and `Input("trends-metric-toggle", "value")` from `update_chart()` callback signature — updated ALL 4 return paths to return 3 values instead of 4
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- [x] Remove thin wrapper `get_trend_data()` from `dash_app/data/queries.py` (will be re-imported by the new Trends view callbacks)
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- [x] Keep `get_trend_data()` in `pathway_queries.py` — it's still used by the new Trends view
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- [x] Keep `create_trend_figure()` in `plotly_generator.py` — it's still used by the new Trends view
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- **Checkpoint**: Patient Pathways has 9 tabs (Icicle through Doses, no Trends). `python run_dash.py` starts cleanly. PASSED.
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### E.2 Add Trends sidebar nav item + view container
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- [x] Add `"trends"` icon SVG to `_ICONS` dict in `dash_app/components/sidebar.py` — use a line chart icon: `<polyline points="22 12 18 12 15 21 9 3 6 12 2 12"/>`
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- [x] Add `_sidebar_item("Trends", "trends", active=False, item_id="nav-trends")` to sidebar children
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- [x] Add `html.Div(id="trends-view", style={"display": "none"}, children=[...])` to `app.py` layout inside `view-container`, after `trust-comparison-view`
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- [x] Update `switch_view()` in `dash_app/callbacks/navigation.py`:
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- Add `Output("trends-view", "style")` and `Output("nav-trends", "className")` — now 3 views, 3 nav items (6 outputs total)
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- Handle 3-way switching: `"patient-pathways"`, `"trust-comparison"`, `"trends"`
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- [x] Update `update_app_state()` in `dash_app/callbacks/filters.py`:
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- Add `Input("nav-trends", "n_clicks")`
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- Add `elif triggered_id == "nav-trends": active_view = "trends"` case
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- **Checkpoint**: 3 sidebar items visible. Clicking "Trends" switches to empty trends view. `python run_dash.py` starts cleanly. PASSED.
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### E.3 Create Trends landing page — directorate-level trends
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- [x] Create `dash_app/components/trends.py`:
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- `make_trends_landing()` — container with title, description, metric toggle (`dmc.SegmentedControl` id: `trends-view-metric-toggle`, options: Patients / Cost per Patient / Cost per Patient p.a.), and `dcc.Graph(id="trends-overview-chart")` wrapped in `dcc.Loading`
|
||||
- `make_trends_detail()` — hidden container with back button (id: `trends-back-btn`), title (id: `trends-detail-title`), same metric toggle, and `dcc.Graph(id="trends-detail-chart")` wrapped in `dcc.Loading`
|
||||
- [x] Update `get_trend_data()` in `pathway_queries.py` to support `group_by` parameter:
|
||||
- `group_by="drug"` (default, existing behavior): one line per drug
|
||||
- `group_by="directory"`: one line per directory (aggregate drugs within each directory)
|
||||
- When `group_by="directory"`: `SELECT period_end, directory AS name, SUM(...) ... GROUP BY period_end, directory`
|
||||
- [x] Update thin wrapper in `dash_app/data/queries.py` to pass `group_by` param
|
||||
- [x] Create `dash_app/callbacks/trends.py` with `register_trends_callbacks(app)`:
|
||||
- Callback to render directorate-level chart: Input `app-state` + `trends-view-metric-toggle` → Output `trends-overview-chart` figure. Calls `get_trend_data(group_by="directory", metric=...)` → `create_trend_figure(data, title, metric)`.
|
||||
- Only fires when `active_view == "trends"` and `selected_trends_directorate` is None.
|
||||
- [x] Register in `dash_app/callbacks/__init__.py`
|
||||
- [x] Rename "Cost" label to "Cost per Patient" in the metric toggle options (value stays `total_cost`)
|
||||
- [x] Wire `trends-view` div in `app.py` to contain `make_trends_landing()` + `make_trends_detail()`
|
||||
- **Checkpoint**: Trends view shows directorate-level line chart. Metric toggle switches y-axis. Lines show one per directorate. PASSED.
|
||||
|
||||
### E.4 Add drug drill-down within Trends view
|
||||
- [x] Add `selected_trends_directorate` key (default `None`) to `app-state` initial data in `app.py` (already done in E.2)
|
||||
- [x] Add `customdata=[name]*len(periods)` to each trace in `create_trend_figure()` so directorate name is accessible from clickData
|
||||
- [x] Add `Input("trends-overview-chart", "clickData")` and `Input("trends-back-btn", "n_clicks")` to `update_app_state()` in `filters.py`:
|
||||
- Clicking a trace point extracts directorate name from `clickData["points"][0]["customdata"]`
|
||||
- Back button clears `selected_trends_directorate` to None
|
||||
- Chart type change also clears `selected_trends_directorate`
|
||||
- [x] Landing/detail toggle callback already exists in `trends.py` (`toggle_trends_subviews`) — handles show/hide based on `selected_trends_directorate`
|
||||
- [x] Add `render_trends_detail()` callback in `trends.py`:
|
||||
- Input: `app-state` + `trends-detail-metric-toggle` → Output `trends-detail-chart`
|
||||
- Calls `get_trend_data(directory=selected, metric=..., group_by="drug")` → `create_trend_figure()`
|
||||
- Guards: only fires when `active_view == "trends"` and `selected_trends_directorate` is not None
|
||||
- **Checkpoint**: Click a directorate line → drill into drug-level trends. Back button returns to overview. `python run_dash.py` starts cleanly. PASSED.
|
||||
|
||||
### E.5 Fix chart height to fill viewport
|
||||
- [x] In `create_trend_figure()` in `plotly_generator.py`: removed explicit `height=500`, `autosize=True` from `_base_layout()` handles it
|
||||
- [x] Reviewed ALL chart functions — removed 4 fixed heights: `create_cost_waterfall_figure()` (500), `create_duration_cost_scatter_figure()` (550), `create_drug_network_figure()` (600), `create_trend_figure()` (500). Kept 13 dynamic heights (`max(...)`, `fig_height`, `dynamic_height`).
|
||||
- [x] Added CSS rules: `#pathway-chart .js-plotly-plot, .plot-container, .svg-container { height: 100% !important }` to propagate flex container height
|
||||
- [x] Verified CSS flex chain: `.chart-card` → `.dash-loading-callback > div` → `#chart-container` → `#pathway-chart` → `.js-plotly-plot` — all flex with `min-height: 0`
|
||||
- [x] Renamed "Cost" to "Cost per Patient" and "Cost p.a." to "Cost per Patient p.a." in heatmap toggles in `chart_card.py` and `trust_comparison.py`
|
||||
- **Checkpoint**: Charts fill available viewport height in Patient Pathways. No fixed 500px cutoff. `python run_dash.py` starts cleanly.
|
||||
|
||||
---
|
||||
|
||||
## Completion Criteria
|
||||
|
||||
### Phase A
|
||||
- [x] All charts use `_base_layout()` for consistent styling
|
||||
- [x] Heatmaps have linear colorscale + cell annotations + autosize
|
||||
- [x] Legends don't overflow at any drug/trust count
|
||||
- [x] Trust Comparison charts use 7 maximally-distinct colors
|
||||
- [x] `python run_dash.py` starts cleanly
|
||||
|
||||
### Phase B
|
||||
- [x] All chart titles use `CHART_TITLE_SIZE` and `CHART_TITLE_COLOR`
|
||||
- [x] Cost effectiveness uses smooth gradient
|
||||
- [x] Sankey handles narrow viewports
|
||||
- [x] Heatmap metric toggle works in both views
|
||||
- [x] `python run_dash.py` starts cleanly
|
||||
|
||||
### Phase C
|
||||
- [x] Retention funnel renders with real data
|
||||
- [x] Pathway depth distribution renders with real data
|
||||
- [x] Duration vs cost scatter renders with quadrant lines
|
||||
- [x] Drug network graph renders as Sankey alternative
|
||||
- [x] All new tabs respond to existing filters
|
||||
- [x] `python run_dash.py` starts cleanly
|
||||
|
||||
### Phase D
|
||||
- [x] Temporal trends computed via historical snapshots (CLI script + Dash tab)
|
||||
- [x] Dose distribution shows average administered doses per drug
|
||||
- [x] Drug timeline shows Gantt-style cohort activity
|
||||
- [x] `python run_dash.py` starts cleanly
|
||||
|
||||
### Phase E
|
||||
- [x] Trends tab removed from Patient Pathways (9 tabs remain)
|
||||
- [x] 3rd sidebar item "Trends" visible and functional
|
||||
- [x] Trends landing page shows directorate-level line chart with metric toggle
|
||||
- [x] Clicking a directorate drills into drug-level trends
|
||||
- [x] Back button returns to directorate overview
|
||||
- [x] Charts fill available viewport height (no fixed 500px cutoff)
|
||||
- [x] "Cost" renamed to "Cost per Patient" in metric toggles
|
||||
- [x] `python run_dash.py` starts cleanly
|
||||
|
||||
---
|
||||
|
||||
## Key Reference Files
|
||||
|
||||
| File | Purpose |
|
||||
|------|---------|
|
||||
| `src/visualization/plotly_generator.py` | PRIMARY — all chart generation functions |
|
||||
| `src/data_processing/pathway_queries.py` | All SQLite query functions |
|
||||
| `src/data_processing/parsing.py` | HTML/JSON parsing utilities |
|
||||
| `dash_app/callbacks/chart.py` | Patient Pathways tab dispatch + chart rendering |
|
||||
| `dash_app/callbacks/trust_comparison.py` | Trust Comparison 6-chart callbacks |
|
||||
| `dash_app/components/chart_card.py` | Tab definitions + chart card component |
|
||||
| `dash_app/components/trust_comparison.py` | TC landing + dashboard layout |
|
||||
| `dash_app/data/queries.py` | Thin wrappers around shared query functions |
|
||||
|
||||
## Key Patterns
|
||||
|
||||
### plotly_generator.py structure
|
||||
- Module-level palettes: `TRUST_PALETTE` (7 colors), `DRUG_PALETTE` (15 colors)
|
||||
- `_base_layout(title, **overrides)` helper for DRY layout dicts
|
||||
- `_smart_legend(n_items)` helper for adaptive legend positioning
|
||||
- Each `create_*_figure()` function accepts list-of-dicts, returns `go.Figure`
|
||||
|
||||
### Adding a new chart tab (Patient Pathways)
|
||||
1. Add query function to `src/data_processing/pathway_queries.py`
|
||||
2. Add thin wrapper to `dash_app/data/queries.py`
|
||||
3. Add figure function to `src/visualization/plotly_generator.py`
|
||||
4. Add tab to `TAB_DEFINITIONS` in `dash_app/components/chart_card.py`
|
||||
5. Add `_render_*()` helper in `dash_app/callbacks/chart.py`
|
||||
6. Add dispatch case in `update_chart()` callback
|
||||
|
||||
### Existing chart functions in plotly_generator.py
|
||||
- `create_icicle_from_nodes(nodes, title)` — L113
|
||||
- `create_market_share_figure(data, title)` — L247
|
||||
- `create_cost_effectiveness_figure(data, retention, title)` — L384
|
||||
- `create_cost_waterfall_figure(data, title)` — L562
|
||||
- `create_sankey_figure(data, title)` — L706
|
||||
- `create_dosing_figure(data, title, group_by)` — L837
|
||||
- `_dosing_by_drug(data, colours)` — L926
|
||||
- `_dosing_by_trust(data, colours)` — L1007
|
||||
- `create_heatmap_figure(data, title, metric)` — L1189
|
||||
- `create_duration_figure(data, title, show_directory)` — L1329
|
||||
- `create_trust_market_share_figure(data, title)` — L1481
|
||||
- `create_trust_heatmap_figure(data, title, metric)` — L1582
|
||||
- `create_trust_duration_figure(data, title)` — L1689
|
||||
-253
@@ -1,253 +0,0 @@
|
||||
# Ralph Wiggum Loop — Dashboard Visualization Improvements
|
||||
|
||||
You are operating inside an automated loop improving Plotly charts in an NHS patient pathway analysis Dash application. Each iteration you receive fresh context — you have NO memory of previous iterations. Your only memory is the filesystem.
|
||||
|
||||
**Current Focus**: Phase E — Redesign temporal trends as a standalone 3rd view with directorate overview + drug drill-down, fix chart height, rename cost labels. See IMPLEMENTATION_PLAN.md for the full task list organized into Phases A–E.
|
||||
|
||||
## First Actions Every Iteration
|
||||
|
||||
Read these files in this order before doing anything else:
|
||||
|
||||
1. `progress.txt` — What previous iterations accomplished, what's blocked, and what to do next.
|
||||
2. `IMPLEMENTATION_PLAN.md` — Task list with status markers, architecture overview, and completion criteria.
|
||||
3. `guardrails.md` — Known failure patterns to avoid. You MUST read and follow these.
|
||||
4. `CLAUDE.md` — Project architecture and backend code patterns.
|
||||
|
||||
Then run `git log --oneline -5` to see recent commits.
|
||||
|
||||
## Key Files for This Phase
|
||||
|
||||
**When modifying chart functions**, always read first:
|
||||
- `src/visualization/plotly_generator.py` — PRIMARY file. All chart generation functions live here (~1782 lines).
|
||||
- `dash_app/callbacks/chart.py` — Patient Pathways tab dispatch and chart rendering helpers.
|
||||
- `dash_app/callbacks/trust_comparison.py` — Trust Comparison 6-chart callbacks.
|
||||
|
||||
**When adding new analytics charts**, also read:
|
||||
- `src/data_processing/pathway_queries.py` — All SQLite query functions. New queries go here.
|
||||
- `dash_app/data/queries.py` — Thin wrappers. Add wrapper for each new query.
|
||||
- `dash_app/components/chart_card.py` — TAB_DEFINITIONS for Patient Pathways tabs.
|
||||
|
||||
**When working on the Trends view** (Phase E), also read:
|
||||
- `dash_app/components/trends.py` — Trends landing + detail components (create if doesn't exist)
|
||||
- `dash_app/callbacks/trends.py` — Trends view callbacks (create if doesn't exist)
|
||||
- `dash_app/components/sidebar.py` — Sidebar navigation (3 items: Patient Pathways, Trust Comparison, Trends)
|
||||
- `dash_app/callbacks/navigation.py` — View switching (3-way)
|
||||
- `dash_app/callbacks/filters.py` — `update_app_state()` handles nav clicks
|
||||
- `dash_app/app.py` — Layout with 3 view containers + app-state initial data
|
||||
|
||||
**When modifying UI components**, read:
|
||||
- `dash_app/components/trust_comparison.py` — TC landing + dashboard layout (reference for Trends landing/detail pattern).
|
||||
- `dash_app/assets/nhs.css` — All CSS styles.
|
||||
|
||||
## Narration
|
||||
|
||||
Narrate your work as you go. Your output is the only visibility the operator has into what's happening. For every significant action, explain what you're doing and why:
|
||||
|
||||
- **Reading files**: "Reading plotly_generator.py to locate the heatmap colorscale..."
|
||||
- **Creating code**: "Adding _base_layout() helper to DRY shared layout properties..."
|
||||
- **Debugging**: "Chart title color is #003087 instead of CHART_TITLE_COLOR..."
|
||||
- **Testing**: "Running python run_dash.py to verify the app starts..."
|
||||
- **Committing**: "Committing heatmap fixes."
|
||||
|
||||
Do NOT just output a summary at the end. Narrate throughout.
|
||||
|
||||
## Task Selection
|
||||
|
||||
1. Read ALL tasks in IMPLEMENTATION_PLAN.md — understand the full picture
|
||||
2. Skip any marked `[x]` (complete) or `[B]` (blocked)
|
||||
3. Check progress.txt for guidance — the previous iteration may have recommendations
|
||||
4. **Choose a task** based on:
|
||||
- Dependencies (A.1 shared constants before A.2-A.4 which use them)
|
||||
- Phase ordering (Phase A before B, B before C, C before D)
|
||||
- Previous iteration's recommendations
|
||||
5. **Document your reasoning**: Before starting, explain WHY you chose this task
|
||||
6. Mark your chosen task `[~]` (in progress) in IMPLEMENTATION_PLAN.md
|
||||
|
||||
If your chosen task is blocked:
|
||||
- Mark it `[B]` with a reason
|
||||
- Document the blocker in progress.txt
|
||||
- Move to a different ready task
|
||||
|
||||
## Development
|
||||
|
||||
Work on ONE task per iteration. Build incrementally and verify as you go.
|
||||
|
||||
### Key Technologies
|
||||
|
||||
- **Dash 4.0.0**: `from dash import Dash, html, dcc, Input, Output, State, ctx, ALL`
|
||||
- **Dash Mantine Components 2.5.1**: `import dash_mantine_components as dmc` — `MantineProvider` wraps layout
|
||||
- **Plotly**: `import plotly.graph_objects as go` — all chart figures
|
||||
- **SQLite**: `import sqlite3` — read-only access to `data/pathways.db`
|
||||
- **CSS**: All in `dash_app/assets/nhs.css` — auto-served by Dash
|
||||
|
||||
### Plotly Skill
|
||||
|
||||
**IMPORTANT**: When creating or modifying chart functions in `plotly_generator.py`, invoke the `/plotly` skill first. This loads Plotly reference documentation (chart types, graph objects, layouts, interactivity) that helps produce better chart code. Use it before writing any Plotly figure code.
|
||||
|
||||
### plotly_generator.py Patterns
|
||||
|
||||
All chart functions follow the same pattern:
|
||||
```python
|
||||
def create_CHART_figure(data: list[dict], title: str = "", ...) -> go.Figure:
|
||||
"""Create CHART from prepared data."""
|
||||
if not data:
|
||||
return go.Figure()
|
||||
|
||||
# Build traces from data
|
||||
fig = go.Figure(data=traces)
|
||||
|
||||
# Apply layout
|
||||
layout = _base_layout(display_title)
|
||||
layout.update({...chart-specific overrides...})
|
||||
fig.update_layout(**layout)
|
||||
|
||||
return fig
|
||||
```
|
||||
|
||||
### Adding a New Chart Tab
|
||||
|
||||
1. Add query function to `src/data_processing/pathway_queries.py` (accept `db_path` param)
|
||||
2. Add thin wrapper to `dash_app/data/queries.py` (resolve DB_PATH and delegate)
|
||||
3. Add figure function to `src/visualization/plotly_generator.py`
|
||||
4. Add tab to `TAB_DEFINITIONS` in `dash_app/components/chart_card.py`
|
||||
5. Add `_render_*()` helper in `dash_app/callbacks/chart.py`
|
||||
6. Add elif case in `update_chart()` callback
|
||||
|
||||
### Database Access Pattern
|
||||
|
||||
```python
|
||||
# In src/data_processing/pathway_queries.py
|
||||
def get_something(db_path: Path, filter_id: str, chart_type: str, ...) -> list[dict]:
|
||||
conn = sqlite3.connect(str(db_path))
|
||||
conn.row_factory = sqlite3.Row
|
||||
cursor = conn.cursor()
|
||||
cursor.execute("SELECT ... WHERE date_filter_id = ? AND chart_type = ?", [filter_id, chart_type])
|
||||
rows = [dict(row) for row in cursor.fetchall()]
|
||||
conn.close()
|
||||
return rows
|
||||
|
||||
# In dash_app/data/queries.py (thin wrapper)
|
||||
from data_processing.pathway_queries import get_something as _get_something
|
||||
DB_PATH = Path(__file__).resolve().parents[2] / "data" / "pathways.db"
|
||||
|
||||
def get_something(filter_id="all_6mo", chart_type="directory", ...):
|
||||
return _get_something(DB_PATH, filter_id, chart_type, ...)
|
||||
```
|
||||
|
||||
### Verification Steps
|
||||
|
||||
After writing code, ALWAYS verify:
|
||||
|
||||
1. **Import check**: `python -c "from dash_app.app import app"` (or specific module)
|
||||
2. **App starts**: `python run_dash.py` — must start without errors
|
||||
3. **Visual check** (when modifying charts): describe what you expect to see at localhost:8050
|
||||
4. **For callbacks**: verify the callback chain fires correctly
|
||||
|
||||
If any step fails, fix the issue before proceeding.
|
||||
|
||||
## Validation Protocol
|
||||
|
||||
Every task MUST pass validation before being marked complete:
|
||||
|
||||
### Tier 1: Code Validation (MANDATORY)
|
||||
- Code compiles without Python syntax errors
|
||||
- Imports work without errors
|
||||
- `python run_dash.py` starts without exceptions
|
||||
|
||||
### Tier 2: Visual Validation (for chart modification tasks)
|
||||
- Chart renders in the browser
|
||||
- Colors, labels, legend layout match expectations
|
||||
- No overflow or overlap issues
|
||||
|
||||
### Tier 3: Functional Validation (for callback/toggle tasks)
|
||||
- Callbacks fire when inputs change
|
||||
- Metric toggles switch correctly
|
||||
- New tabs appear and render data
|
||||
|
||||
### Validation Failure
|
||||
|
||||
If any tier fails:
|
||||
- DO NOT mark the task complete
|
||||
- Document the failure in progress.txt
|
||||
- Fix the issue within this iteration if possible
|
||||
- If you cannot fix it, mark the task `[B]` with details
|
||||
|
||||
## Quality Gates
|
||||
|
||||
Before marking ANY task `[x]`, ALL of these must be true:
|
||||
|
||||
1. Code is saved to the appropriate file(s)
|
||||
2. Tier 1 validation passed (imports + app starts)
|
||||
3. Tier 2/3 validation passed (as applicable)
|
||||
4. All changes committed to git with a descriptive message
|
||||
|
||||
These are non-negotiable.
|
||||
|
||||
## Update Progress
|
||||
|
||||
After completing your work, append to progress.txt using this format:
|
||||
|
||||
```
|
||||
## Iteration [N] — [YYYY-MM-DD]
|
||||
### Task: [which task you worked on]
|
||||
### Why this task:
|
||||
- [Brief explanation of why you chose this task over others]
|
||||
### Status: COMPLETE | BLOCKED | IN PROGRESS
|
||||
### What was done:
|
||||
- [Specific actions taken]
|
||||
### Validation results:
|
||||
- Tier 1 (Code): [import check, app starts]
|
||||
- Tier 2 (Visual): [chart renders, colors correct]
|
||||
- Tier 3 (Functional): [callbacks fire, toggles work]
|
||||
### Files changed:
|
||||
- [list of files created/modified]
|
||||
### Committed: [git hash] "[commit message]"
|
||||
### Patterns discovered:
|
||||
- [Any reusable learnings — Plotly quirks, layout gotchas, Dash patterns]
|
||||
### Next iteration should:
|
||||
- [Explicit guidance for what the next fresh instance should do first]
|
||||
- [Note any context that would be lost without writing it here]
|
||||
### Blocked items:
|
||||
- [Any tasks that are blocked and why]
|
||||
```
|
||||
|
||||
If you discover a failure pattern, add it to `guardrails.md`.
|
||||
|
||||
## Commit Changes
|
||||
|
||||
1. Stage changed files
|
||||
2. Use a descriptive commit message referencing the task (e.g., "fix: heatmap colorscale + cell annotations (Task A.2)")
|
||||
3. Commit after your task is validated and complete
|
||||
4. If you updated progress.txt with a blocked status, commit that too
|
||||
|
||||
## Completion Check
|
||||
|
||||
If ALL tasks in IMPLEMENTATION_PLAN.md are marked `[x]`:
|
||||
|
||||
1. Run `python run_dash.py` to verify app starts cleanly
|
||||
2. Verify all completion criteria at the bottom of IMPLEMENTATION_PLAN.md are satisfied
|
||||
3. Only then output the completion signal on its own line:
|
||||
|
||||
```
|
||||
<promise>COMPLETE</promise>
|
||||
```
|
||||
|
||||
DO NOT output this string under any other circumstances.
|
||||
DO NOT output it if any task is still `[ ]` or `[B]` or `[~]`.
|
||||
|
||||
## Rules
|
||||
|
||||
- Complete ONE task per iteration, then update progress and stop
|
||||
- ALWAYS read progress.txt, guardrails.md before starting work
|
||||
- **Read plotly_generator.py** when modifying ANY chart function (line numbers shift!)
|
||||
- **DO NOT modify pipeline/analysis logic** in src/ (pathway_pipeline, transforms, diagnosis_lookup, pathway_analyzer, refresh_pathways)
|
||||
- **DO add/modify** chart functions in `src/visualization/plotly_generator.py`
|
||||
- **DO add** new query functions in `src/data_processing/pathway_queries.py`
|
||||
- **New figure functions** go in `src/visualization/`, not in `dash_app/callbacks/`
|
||||
- **New query functions** go in `src/data_processing/pathway_queries.py` with thin wrappers in `dash_app/data/queries.py`
|
||||
- **dcc.Store for state** — no server-side globals
|
||||
- **Lazy tab rendering** — only compute the active tab's chart
|
||||
- **3-view architecture** — Patient Pathways, Trust Comparison, Trends (Phase E). View switching via `active_view` in app-state.
|
||||
- Keep commits atomic and well-described
|
||||
- If stuck for 2+ attempts, document in progress.txt and move on
|
||||
- `python run_dash.py` must work after every task
|
||||
@@ -1,859 +0,0 @@
|
||||
# Patient Pathway Analysis - Improvement Recommendations
|
||||
|
||||
This document outlines recommended improvements to modernize the Patient Pathway Analysis application, based on multi-domain expert analysis.
|
||||
|
||||
---
|
||||
|
||||
## Executive Summary
|
||||
|
||||
| Area | Current State | Recommended Change | Priority |
|
||||
|------|--------------|-------------------|----------|
|
||||
| **GUI Framework** | CustomTkinter | **Reflex** (browser-based, native Plotly) | High |
|
||||
| **Data Storage** | CSV files (90MB+) | SQLite with caching | High |
|
||||
| **Data Source** | Manual CSV export | Direct Snowflake connection | Medium |
|
||||
| **Directory Assignment** | Multi-stage fallback | GP diagnosis codes as primary | Medium |
|
||||
| **Code Quality** | Monolithic, no types | Modular, typed, tested | Low |
|
||||
|
||||
---
|
||||
|
||||
## 1. GUI Framework: Replace CustomTkinter with Reflex or Flet
|
||||
|
||||
### What
|
||||
Replace the CustomTkinter-based GUI with a modern Python framework. Two strong options:
|
||||
- **[Reflex](https://reflex.dev)** - React-based, runs in browser
|
||||
- **[Flet](https://flet.dev)** - Flutter-based, native desktop or browser
|
||||
|
||||
### Why
|
||||
|
||||
Since Python is approved and standalone `.exe` distribution isn't required, **both frameworks are viable**.
|
||||
|
||||
| Criterion | CustomTkinter | Reflex | Flet |
|
||||
|-----------|---------------|--------|------|
|
||||
| UI paradigm | Native desktop | Browser (localhost) | Desktop or browser |
|
||||
| Component richness | Limited | 60+ React components | Material Design |
|
||||
| Styling | Manual/limited | Full CSS/Tailwind | Flutter theming |
|
||||
| Plotly integration | External HTML | **Native embed** | WebView needed |
|
||||
| State management | Manual | Automatic re-render | Manual updates |
|
||||
| Learning curve | Low | Moderate (React-like) | Low-moderate |
|
||||
| Community | Small | 22k+ GitHub stars | 12k+ GitHub stars |
|
||||
| Maturity | Stable | Active (v0.6+) | Active (v0.80+) |
|
||||
|
||||
### Recommendation: **Reflex**
|
||||
|
||||
Given that:
|
||||
1. Python is approved for users
|
||||
2. Standalone `.exe` not required
|
||||
3. **Interactive Plotly is required** (Reflex has native `rx.plotly()` component)
|
||||
|
||||
Reflex is now the better choice because:
|
||||
- **Native Plotly support** - no need to open external browser windows
|
||||
- **Modern React-based UI** - cleaner, more customizable
|
||||
- **Simpler state management** - automatic re-rendering on state changes
|
||||
- **Better for data apps** - designed for dashboards and data visualization
|
||||
|
||||
### How (Reflex)
|
||||
|
||||
**Basic app structure:**
|
||||
|
||||
```python
|
||||
import reflex as rx
|
||||
|
||||
class State(rx.State):
|
||||
"""Application state."""
|
||||
start_date: str = "2019-04-01"
|
||||
end_date: str = "2025-04-30"
|
||||
selected_drugs: list[str] = []
|
||||
selected_trusts: list[str] = []
|
||||
analysis_running: bool = False
|
||||
chart_data: dict = {}
|
||||
|
||||
async def run_analysis(self):
|
||||
self.analysis_running = True
|
||||
yield # Update UI
|
||||
|
||||
# Run analysis (async)
|
||||
df = await self.load_and_process_data()
|
||||
self.chart_data = generate_plotly_figure(df)
|
||||
|
||||
self.analysis_running = False
|
||||
|
||||
def index() -> rx.Component:
|
||||
return rx.box(
|
||||
rx.hstack(
|
||||
# Sidebar with filters
|
||||
rx.vstack(
|
||||
rx.date_picker(
|
||||
value=State.start_date,
|
||||
on_change=State.set_start_date,
|
||||
),
|
||||
rx.checkbox_group(
|
||||
items=drug_list,
|
||||
value=State.selected_drugs,
|
||||
on_change=State.set_selected_drugs,
|
||||
),
|
||||
rx.button(
|
||||
"Run Analysis",
|
||||
on_click=State.run_analysis,
|
||||
loading=State.analysis_running,
|
||||
),
|
||||
width="300px",
|
||||
),
|
||||
# Main content - interactive Plotly chart
|
||||
rx.plotly(data=State.chart_data, layout=chart_layout),
|
||||
width="100%",
|
||||
)
|
||||
)
|
||||
|
||||
app = rx.App()
|
||||
app.add_page(index)
|
||||
```
|
||||
|
||||
**Key components mapping:**
|
||||
|
||||
| Current Component | Reflex Equivalent |
|
||||
|-------------------|-------------------|
|
||||
| `CTkFrame` | `rx.box`, `rx.vstack`, `rx.hstack` |
|
||||
| `CTkButton` | `rx.button` |
|
||||
| `CTkCheckBox` | `rx.checkbox` |
|
||||
| `CTkSlider` | `rx.slider` |
|
||||
| `DateEntry` | `rx.date_picker` |
|
||||
| `CTkScrollableFrame` | `rx.scroll_area` |
|
||||
| `filedialog` | `rx.upload` |
|
||||
| Plotly HTML file | **`rx.plotly()`** - native embed! |
|
||||
|
||||
**Running the app:**
|
||||
|
||||
```bash
|
||||
# Install
|
||||
pip install reflex
|
||||
|
||||
# Initialize (first time)
|
||||
reflex init
|
||||
|
||||
# Run development server
|
||||
reflex run
|
||||
# Opens http://localhost:3000 in browser
|
||||
```
|
||||
|
||||
**Background tasks with progress:**
|
||||
|
||||
```python
|
||||
class State(rx.State):
|
||||
progress: int = 0
|
||||
status: str = ""
|
||||
|
||||
async def run_analysis(self):
|
||||
self.status = "Loading data..."
|
||||
self.progress = 10
|
||||
yield
|
||||
|
||||
df = load_data()
|
||||
self.status = "Processing..."
|
||||
self.progress = 50
|
||||
yield
|
||||
|
||||
result = process_data(df)
|
||||
self.status = "Complete"
|
||||
self.progress = 100
|
||||
yield
|
||||
```
|
||||
|
||||
### Alternative: Flet
|
||||
|
||||
If you prefer a more desktop-like feel, Flet remains a good option:
|
||||
|
||||
```python
|
||||
import flet as ft
|
||||
|
||||
def main(page: ft.Page):
|
||||
page.title = "HCD Analysis"
|
||||
|
||||
async def run_analysis(e):
|
||||
# Background task
|
||||
page.run_task(do_analysis)
|
||||
|
||||
page.add(
|
||||
ft.Row([
|
||||
# Sidebar
|
||||
ft.Column([
|
||||
ft.DatePicker(),
|
||||
ft.ElevatedButton("Run", on_click=run_analysis),
|
||||
]),
|
||||
# Chart area (opens in browser for interactivity)
|
||||
ft.ElevatedButton("View Chart", on_click=open_chart),
|
||||
])
|
||||
)
|
||||
|
||||
ft.app(target=main) # Desktop window
|
||||
# OR
|
||||
ft.app(target=main, view=ft.WEB_BROWSER) # Browser
|
||||
```
|
||||
|
||||
### Effort Estimate
|
||||
- Learning Reflex basics: 2-3 days
|
||||
- Rewriting GUI: 1-2 weeks
|
||||
- Testing and polish: 3-5 days
|
||||
|
||||
---
|
||||
|
||||
## 2. Data Storage: SQLite Architecture
|
||||
|
||||
### What
|
||||
Replace CSV-based data loading with a SQLite database that stores reference data in normalized tables and caches processed patient data.
|
||||
|
||||
### Why
|
||||
|
||||
| Aspect | Current (CSV) | SQLite |
|
||||
|--------|---------------|--------|
|
||||
| Startup time | 90MB+ file read + full processing | Load reference data once (< 1MB) |
|
||||
| Memory usage | Entire dataset in memory | Incremental queries |
|
||||
| Incremental updates | Full reprocess required | Only process new/changed records |
|
||||
| Query performance | Pandas groupby/merge | Indexed SQL with CTEs |
|
||||
| Data consistency | Multiple CSVs can drift | Single source of truth with FK constraints |
|
||||
| Caching | None | Materialized views |
|
||||
|
||||
**Expected improvements:**
|
||||
- 60-80% faster startup
|
||||
- 50-70% memory reduction
|
||||
- 90%+ time savings on incremental updates
|
||||
|
||||
### How
|
||||
|
||||
**Recommended schema (simplified):**
|
||||
|
||||
```sql
|
||||
-- Reference tables
|
||||
CREATE TABLE ref_drug_names (
|
||||
drug_name_raw TEXT PRIMARY KEY,
|
||||
drug_name_std TEXT NOT NULL
|
||||
);
|
||||
|
||||
CREATE TABLE ref_organizations (
|
||||
org_code TEXT PRIMARY KEY,
|
||||
org_name TEXT NOT NULL
|
||||
);
|
||||
|
||||
CREATE TABLE ref_directories (
|
||||
directory_id INTEGER PRIMARY KEY,
|
||||
directory_name TEXT UNIQUE NOT NULL
|
||||
);
|
||||
|
||||
CREATE TABLE ref_drug_directory_map (
|
||||
drug_name_std TEXT,
|
||||
directory_id INTEGER,
|
||||
is_single_valid BOOLEAN DEFAULT FALSE,
|
||||
PRIMARY KEY (drug_name_std, directory_id)
|
||||
);
|
||||
|
||||
-- Patient data (fact table)
|
||||
CREATE TABLE fact_interventions (
|
||||
intervention_id INTEGER PRIMARY KEY,
|
||||
upid TEXT NOT NULL,
|
||||
provider_code TEXT,
|
||||
drug_name_std TEXT NOT NULL,
|
||||
intervention_date DATE NOT NULL,
|
||||
price_actual REAL,
|
||||
directory_id INTEGER,
|
||||
directory_assignment_method TEXT,
|
||||
data_load_batch_id INTEGER
|
||||
);
|
||||
|
||||
-- Critical indexes
|
||||
CREATE INDEX idx_upid ON fact_interventions(upid);
|
||||
CREATE INDEX idx_upid_drug ON fact_interventions(upid, drug_name_std);
|
||||
CREATE INDEX idx_intervention_date ON fact_interventions(intervention_date);
|
||||
|
||||
-- Materialized view for patient summaries (cached aggregations)
|
||||
CREATE TABLE mv_patient_treatment_summary (
|
||||
upid TEXT PRIMARY KEY,
|
||||
first_seen DATE,
|
||||
last_seen DATE,
|
||||
total_cost REAL,
|
||||
drug_count INTEGER,
|
||||
last_refresh TIMESTAMP
|
||||
);
|
||||
|
||||
-- File tracking for incremental updates
|
||||
CREATE TABLE processed_files (
|
||||
file_path TEXT PRIMARY KEY,
|
||||
file_hash TEXT NOT NULL,
|
||||
last_processed TIMESTAMP
|
||||
);
|
||||
```
|
||||
|
||||
**Migration strategy:**
|
||||
|
||||
1. **Phase 1**: Create schema, load reference tables from existing CSVs
|
||||
2. **Phase 2**: Develop incremental load scripts for patient data
|
||||
3. **Phase 3**: Build materialized views for aggregations
|
||||
4. **Phase 4**: Modify `dashboard_gui.py` to query SQLite instead of processing CSVs
|
||||
|
||||
**Key query replacing pandas aggregation:**
|
||||
|
||||
```sql
|
||||
-- Replaces ~200 lines of pandas groupby/merge
|
||||
WITH patient_drugs AS (
|
||||
SELECT
|
||||
upid,
|
||||
drug_name_std,
|
||||
MIN(intervention_date) as first_date,
|
||||
MAX(intervention_date) as last_date,
|
||||
COUNT(*) as intervention_count,
|
||||
SUM(price_actual) as drug_cost
|
||||
FROM fact_interventions
|
||||
WHERE intervention_date BETWEEN :start_date AND :end_date
|
||||
AND provider_code IN (:trust_filters)
|
||||
GROUP BY upid, drug_name_std
|
||||
)
|
||||
SELECT * FROM patient_drugs;
|
||||
```
|
||||
|
||||
### Effort Estimate
|
||||
- Schema design and setup: 2-3 days
|
||||
- Migration scripts: 3-4 days
|
||||
- Query optimization: 2-3 days
|
||||
- Integration testing: 2-3 days
|
||||
|
||||
---
|
||||
|
||||
## 3. Snowflake Integration
|
||||
|
||||
### What
|
||||
Enable direct download of HCD activity data from Snowflake servers, replacing manual CSV exports.
|
||||
|
||||
### Why
|
||||
- Eliminates manual export step
|
||||
- Enables date-range filtering at query level (faster)
|
||||
- Automatic caching with TTL
|
||||
- Graceful fallback to local files if Snowflake unavailable
|
||||
|
||||
### How
|
||||
|
||||
**Authentication: SSO Browser Login**
|
||||
|
||||
Using `externalbrowser` authenticator - opens system browser for SSO authentication:
|
||||
|
||||
```python
|
||||
import snowflake.connector
|
||||
|
||||
conn = snowflake.connector.connect(
|
||||
account="your_account.region",
|
||||
user="your.email@nhs.net",
|
||||
authenticator="externalbrowser",
|
||||
warehouse="ANALYTICS_WH",
|
||||
database="data_hub",
|
||||
schema="dwh"
|
||||
)
|
||||
```
|
||||
|
||||
**Note**: User will see browser popup on first connection each session.
|
||||
|
||||
**Configuration (`config/snowflake.toml`):**
|
||||
|
||||
```toml
|
||||
[snowflake]
|
||||
account = "your_account.region"
|
||||
warehouse = "ANALYTICS_WH"
|
||||
database = "DataWarehouse"
|
||||
schema = "dwh"
|
||||
|
||||
[query]
|
||||
default_timeout = 300
|
||||
chunk_size = 100000
|
||||
|
||||
[cache]
|
||||
enabled = true
|
||||
ttl_hours = 24
|
||||
directory = "./data/cache"
|
||||
```
|
||||
|
||||
**Core connector pattern:**
|
||||
|
||||
```python
|
||||
from snowflake.connector import connect
|
||||
|
||||
class SnowflakeConnector:
|
||||
def fetch_activity_data(self, start_date, end_date, provider_codes=None):
|
||||
query = """
|
||||
SELECT
|
||||
"Provider Code",
|
||||
"PersonKey",
|
||||
"ProductDescription" as "Drug Name",
|
||||
"Intervention Date",
|
||||
"Price Actual",
|
||||
-- ... other columns
|
||||
FROM DataWarehouse.dwh.FactHighCostDrugs
|
||||
WHERE "Intervention Date" BETWEEN :start_date AND :end_date
|
||||
"""
|
||||
|
||||
with self.connect() as conn:
|
||||
cursor = conn.cursor()
|
||||
cursor.execute(query, {'start_date': start_date, 'end_date': end_date})
|
||||
return cursor.fetch_pandas_all()
|
||||
```
|
||||
|
||||
**Caching strategy:**
|
||||
|
||||
| Scenario | Action |
|
||||
|----------|--------|
|
||||
| Same date range within 24 hours | Use cache |
|
||||
| Date range includes today | Query Snowflake (data may be updating) |
|
||||
| User clicks "Refresh" | Query Snowflake |
|
||||
| Snowflake unavailable | Fallback to local CSV/Parquet |
|
||||
|
||||
**Data loader with fallback:**
|
||||
|
||||
```python
|
||||
class DataLoader:
|
||||
def load_data(self, start_date, end_date, force_refresh=False):
|
||||
# 1. Try cache
|
||||
if self.cache and not force_refresh:
|
||||
cached = self.cache.get(start_date, end_date)
|
||||
if cached is not None:
|
||||
return cached, "cache"
|
||||
|
||||
# 2. Try Snowflake
|
||||
try:
|
||||
df = self.snowflake.fetch_activity_data(start_date, end_date)
|
||||
self.cache.set(df, start_date, end_date)
|
||||
return df, "snowflake"
|
||||
except SnowflakeConnectionError:
|
||||
pass
|
||||
|
||||
# 3. Fallback to local files
|
||||
if self.fallback_file.exists():
|
||||
return pd.read_parquet(self.fallback_file), "local_file"
|
||||
|
||||
raise RuntimeError("No data source available")
|
||||
```
|
||||
|
||||
**Dependencies to add:**
|
||||
|
||||
```toml
|
||||
dependencies = [
|
||||
"snowflake-connector-python[pandas]>=3.12.0",
|
||||
"cryptography>=42.0.0",
|
||||
]
|
||||
```
|
||||
|
||||
### Effort Estimate
|
||||
- Snowflake connector setup: 2-3 days
|
||||
- Caching layer: 1-2 days
|
||||
- GUI integration (data source selector): 1-2 days
|
||||
- Testing with real data: 2-3 days
|
||||
|
||||
---
|
||||
|
||||
## 4. GP Diagnosis Code Integration
|
||||
|
||||
### What
|
||||
Use GP diagnosis codes as the **primary source** for directory/specialty assignment, with existing logic as fallback.
|
||||
|
||||
### Why
|
||||
- More accurate: Diagnosis directly indicates specialty
|
||||
- Reduces "Undefined" assignments
|
||||
- Leverages existing NHS data linkage
|
||||
- Maintains current logic as safety net
|
||||
|
||||
### How
|
||||
|
||||
**NHS diagnosis code landscape:**
|
||||
|
||||
| Code System | Usage | Notes |
|
||||
|-------------|-------|-------|
|
||||
| **SNOMED CT** | GP systems (mandatory since 2018) | Primary source |
|
||||
| **ICD-10** | Secondary care | Maps FROM SNOMED CT |
|
||||
| **Read Codes** | Legacy only | Historical records |
|
||||
|
||||
**New priority chain:**
|
||||
|
||||
```
|
||||
1. Drug has single valid directory → use that (unchanged)
|
||||
2. [NEW] GP diagnosis available → map SNOMED/ICD-10 to directory
|
||||
3. Extract from clinical data fields (existing)
|
||||
4. Most frequent for same patient/drug (existing)
|
||||
5. UPID-based inference (existing)
|
||||
6. Default to "Undefined" (existing)
|
||||
```
|
||||
|
||||
**ICD-10 to Directory mapping (examples):**
|
||||
|
||||
```python
|
||||
ICD10_TO_DIRECTORY = {
|
||||
# Neoplasms (Chapter II)
|
||||
"C": ["MEDICAL ONCOLOGY", "CLINICAL ONCOLOGY", "CLINICAL HAEMATOLOGY"],
|
||||
|
||||
# Blood diseases (Chapter III)
|
||||
"D5": ["CLINICAL HAEMATOLOGY"],
|
||||
"D6": ["CLINICAL HAEMATOLOGY"],
|
||||
|
||||
# Endocrine (Chapter IV)
|
||||
"E10": ["DIABETIC MEDICINE"], # Type 1 diabetes
|
||||
"E11": ["DIABETIC MEDICINE"], # Type 2 diabetes
|
||||
|
||||
# Eye (Chapter VII)
|
||||
"H0": ["OPHTHALMOLOGY"],
|
||||
"H1": ["OPHTHALMOLOGY"],
|
||||
"H2": ["OPHTHALMOLOGY"],
|
||||
"H3": ["OPHTHALMOLOGY"],
|
||||
|
||||
# Musculoskeletal (Chapter XIII)
|
||||
"M05": ["RHEUMATOLOGY"], # Rheumatoid arthritis
|
||||
"M06": ["RHEUMATOLOGY"],
|
||||
"M32": ["RHEUMATOLOGY"], # SLE
|
||||
|
||||
# Genitourinary (Chapter XIV)
|
||||
"N0": ["NEPHROLOGY"],
|
||||
"N1": ["NEPHROLOGY"],
|
||||
"N18": ["NEPHROLOGY"], # CKD
|
||||
}
|
||||
```
|
||||
|
||||
**Multi-diagnosis resolution:**
|
||||
|
||||
```python
|
||||
def resolve_directory_from_diagnoses(diagnoses, drug_valid_dirs):
|
||||
"""
|
||||
When patient has multiple diagnoses:
|
||||
1. Filter to diagnoses mapping to directories valid for this drug
|
||||
2. Oncology diagnoses take priority (ICD-10 chapter C)
|
||||
3. Use most recent active diagnosis
|
||||
4. Default to first alphabetically (deterministic)
|
||||
"""
|
||||
valid_matches = []
|
||||
|
||||
for dx in diagnoses:
|
||||
icd10_prefix = dx.icd10_code[:3]
|
||||
possible_dirs = ICD10_TO_DIRECTORY.get(icd10_prefix, [])
|
||||
matching = set(possible_dirs) & set(drug_valid_dirs)
|
||||
|
||||
if matching:
|
||||
valid_matches.append({
|
||||
'directories': matching,
|
||||
'is_oncology': dx.icd10_code.startswith('C'),
|
||||
'date': dx.diagnosis_date
|
||||
})
|
||||
|
||||
if not valid_matches:
|
||||
return None # Fall back to existing logic
|
||||
|
||||
# Oncology priority
|
||||
oncology = [m for m in valid_matches if m['is_oncology']]
|
||||
if oncology:
|
||||
return sorted(oncology[0]['directories'])[0]
|
||||
|
||||
# Most recent
|
||||
valid_matches.sort(key=lambda x: x['date'], reverse=True)
|
||||
return sorted(valid_matches[0]['directories'])[0]
|
||||
```
|
||||
|
||||
**Data source options:**
|
||||
|
||||
1. **Snowflake linked data** (recommended): Query `data_hub.dwh.DimClinicalCoding` joined via `PatientPseudo`
|
||||
2. **Local CSV cache**: Pre-extracted GP diagnosis data for offline use
|
||||
3. **Hybrid**: Cache with Snowflake refresh
|
||||
|
||||
**GP Diagnosis Query (confirm column names via Snowflake MCP):**
|
||||
|
||||
```sql
|
||||
SELECT
|
||||
PatientPseudo,
|
||||
SNOMEDCode, -- or similar
|
||||
ICD10Code, -- may need mapping from SNOMED
|
||||
DiagnosisDate,
|
||||
DiagnosisStatus -- Active/Resolved if available
|
||||
FROM data_hub.dwh.DimClinicalCoding
|
||||
WHERE PatientPseudo IN (:patient_pseudo_list)
|
||||
ORDER BY DiagnosisDate DESC
|
||||
```
|
||||
|
||||
**New reference file needed (`./data/diagnosis_directory_map.csv`):**
|
||||
|
||||
```csv
|
||||
icd10_prefix,directory,priority,notes
|
||||
C,MEDICAL ONCOLOGY,1,All malignancies
|
||||
C81,CLINICAL HAEMATOLOGY,1,Hodgkin lymphoma
|
||||
C90,CLINICAL HAEMATOLOGY,1,Multiple myeloma
|
||||
E10,DIABETIC MEDICINE,1,Type 1 diabetes
|
||||
E11,DIABETIC MEDICINE,1,Type 2 diabetes
|
||||
G35,NEUROLOGY,1,Multiple sclerosis
|
||||
H0,OPHTHALMOLOGY,1,Eye disorders
|
||||
M05,RHEUMATOLOGY,1,Rheumatoid arthritis
|
||||
N18,NEPHROLOGY,1,Chronic kidney disease
|
||||
```
|
||||
|
||||
**Tracking assignment source (for audit):**
|
||||
|
||||
```python
|
||||
df['Directory_Source'] = pd.NA # New column
|
||||
|
||||
# After each assignment step:
|
||||
df.loc[assigned_mask, 'Directory_Source'] = 'DRUG_SINGLE' # Step 1
|
||||
df.loc[assigned_mask, 'Directory_Source'] = 'GP_DIAGNOSIS' # Step 2 (NEW)
|
||||
df.loc[assigned_mask, 'Directory_Source'] = 'CLINICAL_EXTRACT' # Step 3
|
||||
# ... etc
|
||||
```
|
||||
|
||||
### Prerequisites
|
||||
- Explore `data_hub.dwh.DimClinicalCoding` schema to confirm exact column names (use Snowflake MCP)
|
||||
- Map `PatientPseudo` to your HCD data (may need to add PatientPseudo to your data extract)
|
||||
- Obtain SNOMED CT to ICD-10 mapping table from NHS TRUD (if DimClinicalCoding only has SNOMED)
|
||||
|
||||
### Effort Estimate
|
||||
- Mapping table creation: 2-3 days
|
||||
- Snowflake GP query development: 2-3 days
|
||||
- Integration with existing logic: 2-3 days
|
||||
- Validation and testing: 3-5 days
|
||||
|
||||
---
|
||||
|
||||
## 5. Code Quality Improvements
|
||||
|
||||
### What
|
||||
Modernize the codebase with better structure, type hints, error handling, and testing.
|
||||
|
||||
### Why
|
||||
- `generate_graph()` is 267 lines with complexity >30
|
||||
- Zero type hints across entire codebase
|
||||
- Global variables create hidden state
|
||||
- No automated tests
|
||||
- Print statements instead of logging
|
||||
|
||||
### How
|
||||
|
||||
**Quick wins (implement first):**
|
||||
|
||||
1. **Replace global variables** with dataclass:
|
||||
```python
|
||||
@dataclass
|
||||
class AnalysisFilters:
|
||||
start_date: date
|
||||
end_date: date
|
||||
last_seen: date
|
||||
minimum_patients: int
|
||||
selected_trusts: list[str]
|
||||
selected_drugs: list[str]
|
||||
selected_directories: list[str]
|
||||
custom_title: str = ""
|
||||
|
||||
def validate(self) -> list[str]:
|
||||
errors = []
|
||||
if self.start_date >= self.end_date:
|
||||
errors.append("Start date must be before end date")
|
||||
return errors
|
||||
```
|
||||
|
||||
2. **Externalize configuration:**
|
||||
```python
|
||||
@dataclass
|
||||
class PathConfig:
|
||||
data_dir: Path = Path("./data")
|
||||
|
||||
@property
|
||||
def drug_names_file(self) -> Path:
|
||||
return self.data_dir / "include.csv"
|
||||
|
||||
@property
|
||||
def org_codes_file(self) -> Path:
|
||||
return self.data_dir / "org_codes.csv"
|
||||
|
||||
# ... etc for all 7 reference files
|
||||
|
||||
def validate(self) -> list[str]:
|
||||
"""Check all required files exist at startup."""
|
||||
errors = []
|
||||
for file_path in [self.drug_names_file, self.org_codes_file, ...]:
|
||||
if not file_path.exists():
|
||||
errors.append(f"Required file not found: {file_path}")
|
||||
return errors
|
||||
```
|
||||
|
||||
3. **Add logging:**
|
||||
```python
|
||||
import logging
|
||||
|
||||
logging.basicConfig(
|
||||
level=logging.INFO,
|
||||
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
|
||||
handlers=[
|
||||
logging.FileHandler("./logs/analysis.log"),
|
||||
logging.StreamHandler()
|
||||
]
|
||||
)
|
||||
logger = logging.getLogger("PatientPathway")
|
||||
|
||||
# Replace all print() with:
|
||||
logger.info("Starting analysis...")
|
||||
logger.error(f"Failed to load file: {e}")
|
||||
```
|
||||
|
||||
4. **Extract `generate_graph()` into smaller functions:**
|
||||
```python
|
||||
def generate_graph(df, filters: AnalysisFilters, config: PathConfig):
|
||||
df = prepare_data(df, filters) # ~50 lines
|
||||
stats = calculate_statistics(df) # ~80 lines
|
||||
hierarchy = build_hierarchy(df, stats) # ~60 lines
|
||||
chart_data = prepare_chart_data(hierarchy) # ~40 lines
|
||||
return render_icicle_chart(chart_data, filters.custom_title) # ~40 lines
|
||||
```
|
||||
|
||||
**Recommended project structure:**
|
||||
|
||||
```
|
||||
project/
|
||||
├── gui.py # Entry point only
|
||||
├── core/
|
||||
│ ├── config.py # PathConfig, AnalysisFilters
|
||||
│ ├── models.py # Data models
|
||||
│ └── exceptions.py # Custom exceptions
|
||||
├── data_processing/
|
||||
│ ├── loader.py # File/Snowflake loading
|
||||
│ ├── transformer.py # Data transformations
|
||||
│ └── validator.py # Data validation
|
||||
├── analysis/
|
||||
│ ├── pathway_analyzer.py # Patient pathway calculations
|
||||
│ └── statistics.py # Statistical calculations
|
||||
├── visualization/
|
||||
│ └── plotly_generator.py # Graph generation
|
||||
└── tests/
|
||||
├── test_data_processing.py
|
||||
├── test_analysis.py
|
||||
└── test_config.py
|
||||
```
|
||||
|
||||
**Add development dependencies:**
|
||||
|
||||
```toml
|
||||
[project.optional-dependencies]
|
||||
dev = [
|
||||
"pytest>=8.0.0",
|
||||
"pytest-cov>=4.1.0",
|
||||
"mypy>=1.8.0",
|
||||
"black>=24.0.0",
|
||||
"ruff>=0.2.0",
|
||||
]
|
||||
```
|
||||
|
||||
**Priority tests to write:**
|
||||
|
||||
```python
|
||||
# tests/test_data_processing.py
|
||||
def test_drop_duplicate_treatments_ascending():
|
||||
"""Verify first intervention kept when ascending=True."""
|
||||
# ...
|
||||
|
||||
def test_drop_duplicate_treatments_descending():
|
||||
"""Verify last intervention kept when ascending=False."""
|
||||
# ...
|
||||
|
||||
# tests/test_config.py
|
||||
def test_path_config_validates_missing_files():
|
||||
"""Verify validation catches missing reference files."""
|
||||
# ...
|
||||
|
||||
def test_analysis_filters_validates_date_range():
|
||||
"""Verify start date must be before end date."""
|
||||
# ...
|
||||
```
|
||||
|
||||
### Effort Estimate
|
||||
- Dataclasses and config: 1-2 days
|
||||
- Logging setup: 0.5 days
|
||||
- Extract `generate_graph()`: 2-3 days
|
||||
- Add type hints (public API): 1-2 days
|
||||
- Basic test coverage: 2-3 days
|
||||
|
||||
---
|
||||
|
||||
## Implementation Roadmap
|
||||
|
||||
### Phase 1: Foundation (2-3 weeks)
|
||||
1. Create `PathConfig` and `AnalysisFilters` dataclasses
|
||||
2. Set up logging infrastructure
|
||||
3. Design and create SQLite schema
|
||||
4. Migrate reference data CSVs to SQLite
|
||||
|
||||
### Phase 2: Data Layer (2-3 weeks)
|
||||
1. Implement Snowflake connector with SSO browser auth
|
||||
2. Build caching layer with TTL
|
||||
3. Create data loader with fallback chain
|
||||
4. Migrate `dashboard_gui.py` to use SQLite queries
|
||||
|
||||
### Phase 3: Diagnosis Integration (2-3 weeks)
|
||||
1. Explore `data_hub.dwh.DimClinicalCoding` schema via Snowflake MCP
|
||||
2. Create ICD-10 to directory mapping table
|
||||
3. Implement GP diagnosis lookup using `PatientPseudo` linkage
|
||||
4. Integrate into `department_identification()` as step 2
|
||||
5. Add `Directory_Source` tracking column
|
||||
|
||||
### Phase 4: GUI Modernization (3-4 weeks)
|
||||
1. Learn Reflex fundamentals
|
||||
2. Recreate main window and navigation with `rx.vstack`/`rx.hstack`
|
||||
3. Implement filter panels (date pickers, checkbox groups)
|
||||
4. Integrate Plotly charts with native `rx.plotly()` component
|
||||
5. Test with `reflex run`
|
||||
|
||||
### Phase 5: Quality & Polish (1-2 weeks)
|
||||
1. Add type hints to public API
|
||||
2. Write priority unit tests
|
||||
3. Extract `generate_graph()` into smaller functions
|
||||
4. Documentation and cleanup
|
||||
|
||||
---
|
||||
|
||||
## Configuration Decisions
|
||||
|
||||
Based on requirements, the following decisions have been made:
|
||||
|
||||
| Question | Decision |
|
||||
|----------|----------|
|
||||
| **Snowflake auth** | SSO browser login (`authenticator='externalbrowser'`) |
|
||||
| **GP diagnosis data** | `data_hub.dwh.DimClinicalCoding` |
|
||||
| **Patient linkage** | Use `PatientPseudo` (anonymized identifier) - NOT UPID |
|
||||
| **Plotly interactivity** | Must be interactive - **Reflex has native `rx.plotly()` component** |
|
||||
| **Distribution** | Python script (`reflex run`) - no .exe needed |
|
||||
|
||||
### Implications
|
||||
|
||||
**Snowflake SSO**: Connection code becomes:
|
||||
```python
|
||||
conn = snowflake.connector.connect(
|
||||
account="your_account.region",
|
||||
user=os.environ.get("SNOWFLAKE_USER"),
|
||||
authenticator="externalbrowser", # Opens browser for SSO
|
||||
warehouse="ANALYTICS_WH",
|
||||
database="data_hub",
|
||||
schema="dwh"
|
||||
)
|
||||
```
|
||||
|
||||
**Patient Linkage**: The GP diagnosis query needs to join on `PatientPseudo`, not UPID:
|
||||
```sql
|
||||
SELECT
|
||||
cc.PatientPseudo,
|
||||
cc.SNOMEDCode, -- Confirm actual column names
|
||||
cc.ICD10Code,
|
||||
cc.DiagnosisDate
|
||||
FROM data_hub.dwh.DimClinicalCoding cc
|
||||
WHERE cc.PatientPseudo IN (:patient_list)
|
||||
```
|
||||
|
||||
**Note**: You'll need to confirm the exact column names in `DimClinicalCoding` - explore via Snowflake MCP or SQL client.
|
||||
|
||||
**Plotly Interactivity**: Reflex solves this elegantly with native embedding:
|
||||
```python
|
||||
# Interactive Plotly chart directly in the Reflex app
|
||||
rx.plotly(data=State.chart_data, layout=chart_layout)
|
||||
```
|
||||
Full interactivity (zoom, pan, hover tooltips) works in the browser-based app - no external HTML files needed.
|
||||
|
||||
---
|
||||
|
||||
## References
|
||||
|
||||
- [Reflex Documentation](https://reflex.dev/docs/)
|
||||
- [Reflex Plotly Component](https://reflex.dev/docs/library/graphing/plotly/)
|
||||
- [Flet Documentation](https://flet.dev/docs/) (alternative)
|
||||
- [Snowflake Python Connector](https://docs.snowflake.com/en/developer-guide/python-connector/python-connector)
|
||||
- [NHS SNOMED CT](https://digital.nhs.uk/services/terminology-and-classifications/snomed-ct)
|
||||
- [NHS ICD-10 Classifications](https://isd.digital.nhs.uk/trud/users/guest/filters/0/categories/28)
|
||||
@@ -1,165 +0,0 @@
|
||||
,Search_Term,CleanedDrugName
|
||||
0,acute coronary syndrome,ABCIXIMAB|CLOPIDOGREL|PRASUGREL|RIVAROXABAN|TICAGRELOR
|
||||
1,acute lymphoblastic leukaemia,BLINATUMOMAB|DASATINIB|INOTUZUMAB|PEGASPARGASE|PONATINIB|TISAGENLECLEUCEL
|
||||
2,acute myeloid leukaemia,AZACITIDINE|DECITABINE|GEMTUZUMAB|GILTERITINIB|GLASDEGIB|LIPOSOMAL|MIDOSTAURIN|ORAL|VENETOCLAX
|
||||
3,acute promyelocytic leukaemia,ARSENIC|GEMTUZUMAB
|
||||
4,allergic asthma,OMALIZUMAB
|
||||
5,allergic rhinitis,SQ
|
||||
6,alzheimer's disease,DONEPEZIL
|
||||
7,amyloidosis,VUTRISIRAN
|
||||
8,anaemia,ERYTHROPOIESIS-STIMULATING|ERYTHROPOIETIN
|
||||
9,anaplastic large cell lymphoma,BRENTUXIMAB
|
||||
10,ankylosing spondylitis,ADALIMUMAB|GOLIMUMAB|SECUKINUMAB|UPADACITINIB
|
||||
11,apixaban,ANDEXANET
|
||||
12,aplastic anaemia,ELTROMBOPAG
|
||||
13,arthritis,ETANERCEPT
|
||||
14,asthma,BENRALIZUMAB|DUPILUMAB|INHALED|MEPOLIZUMAB|OMALIZUMAB|RESLIZUMAB
|
||||
15,atopic dermatitis,ABROCITINIB|ALCLOMETASONE|BARICITINIB|CRISABOROLE|DUPILUMAB|PIMECROLIMUS
|
||||
16,atrial fibrillation,APIXABAN|DABIGATRAN|DRONEDARONE|EDOXABAN|RIVAROXABAN|VERNAKALANT
|
||||
17,attention deficit hyperactivity disorder,ATOMOXETINE
|
||||
18,attention-deficit hyperactivity disorder,METHYLPHENIDATE
|
||||
19,axial spondyloarthritis,ADALIMUMAB|GOLIMUMAB|IXEKIZUMAB|SECUKINUMAB|UPADACITINIB
|
||||
20,basal cell carcinoma,VISMODEGIB
|
||||
21,bipolar disorder,LOXAPINE|OLANZAPINE
|
||||
22,bladder,MIRABEGRON
|
||||
23,brca,OLAPARIB
|
||||
24,breast cancer,ABEMACICLIB|ALPELISIB|ANASTROZOLE|ATEZOLIZUMAB|BEVACIZUMAB|CAPECITABINE|DENOSUMAB|DOCETAXEL|ERIBULIN|EVEROLIMUS|FULVESTRANT|GEMCITABINE|INTRABEAM|LAPATINIB|NERATINIB|OLAPARIB|PACLITAXEL|PALBOCICLI|PALBOCICLIB|PEMBROLIZUMAB|PERTUZUMAB|RIBOCICLIB|SACITUZUMAB|TRASTUZUMAB|TUCATINIB|VINORELBINE
|
||||
25,cardiomyopathy,TAFAMIDIS
|
||||
26,cardiovascular disease,ATORVASTATIN
|
||||
27,cervical cancer,TOPOTECAN
|
||||
28,cholangiocarcinoma,PEMIGATINIB
|
||||
29,choroidal neovascularisation,AFLIBERCEPT|RANIBIZUMAB
|
||||
30,chronic kidney disease,DAPAGLIFLOZIN|IMLIFIDASE|ROXADUSTAT
|
||||
31,chronic liver disease,AVATROMBOPAG|LUSUTROMBOPAG
|
||||
32,chronic lymphocytic leukaemia,ACALABRUTINIB|BENDAMUSTINE|DUVELISIB|IBRUTINIB|IDELALISIB|OBINUTUZUMAB|OFATUMUMAB|RITUXIMAB|VENETOCLAX
|
||||
33,chronic myeloid leukaemia,ASCIMINIB|BOSUTINIB|STANDARD-DOSE|DASATINIB|DASITINIB|NILOTINIB|PONATINIB
|
||||
34,chronic obstructive pulmonary disease,ROFLUMILAST
|
||||
35,colon cancer,CAPECITABINE
|
||||
36,colorectal cancer,BEVACIZUMAB|CAPECITABINE|IRINOTECAN
|
||||
37,constipation,LUBIPROSTONE|METHYLNALTREXONE|NALDEMEDINE|NALOXEGOL|PRUCALOPRIDE
|
||||
38,covid-19,NIRMATRELVIR
|
||||
39,crohn's disease,INFLIXIMAB|VEDOLIZUMAB
|
||||
40,cutaneous t-cell lymphoma,BRENTUXIMAB|CHLORMETHINE
|
||||
41,cystic fibrosis,COLISTIMETHATE|LUMACAFTOR|MANNITOL
|
||||
42,cytomegalovirus,LETERMOVIR|MARIBAVIR
|
||||
43,deep vein thrombosis,APIXABAN|DABIGATRAN|EDOXABAN|RIVAROXABAN
|
||||
44,depression,ESKETAMINE
|
||||
45,diabetes,ERTUGLIFLOZIN|INHALED|AFLIBERCEPT|BROLUCIZUMAB|DEXAMETHASONE|FARICIMAB|FLUOCINOLONE|RANIBIZUMAB
|
||||
46,diabetic retinopathy,RANIBUZIMAB
|
||||
47,diffuse large b-cell lymphoma,AXICABTAGENE|POLATUZUMAB|TISAGENLECLEUCEL
|
||||
48,dravet syndrome,CANNABIDIOL|FENFLURAMINE
|
||||
49,drug misuse,BUPRENORPHINE|NALTREXONE
|
||||
50,dry eye,CICLOSPORIN
|
||||
51,dyspepsia,LANSOPRAZOLE
|
||||
52,endometrial cancer,DOSTARLIMAB
|
||||
53,epilepsy,CENOBAMATE|GABAPENTIN|RETIGABINE
|
||||
54,fallopian tube,BEVACIZUMAB|NIRAPARIB|OLAPARIB|RUCAPARIB
|
||||
55,follicular lymphoma,DUVELISIB|IDELALISIB|LENALIDOMIDE|OBINUTUZUMAB|RITUXIMAB|TISAGENLECLEUCEL
|
||||
56,gastric cancer,CAPECITABINE|RAMUCIRUMAB|TRASTUZUMAB|TRIFLURIDINE
|
||||
57,gastro-oesophageal junction,NIVOLUMAB|PEMBROLIZUMAB
|
||||
58,giant cell arteritis,TOCILIZUMAB
|
||||
59,glioma,CARMUSTINE
|
||||
60,gout,CANAKINUMAB|FEBUXOSTAT|LESINURAD
|
||||
61,graft versus host disease,RUXOLITINIB
|
||||
62,granulomatosis with polyangiitis,AVACOPAN|MEPOLIZUMAB
|
||||
63,growth hormone deficiency,SOMATROPIN
|
||||
64,hand eczema,ALITRETINOIN
|
||||
65,heart failure,DAPAGLIFLOZIN|EMPAGLIFLOZIN|IVABRADINE|SACUBITRIL|VERICIGUAT
|
||||
66,hepatitis b,ADEFOVIR
|
||||
67,hepatitis c,BOCEPREVIR|DACLATASVIR|ELBASVIR|GLECAPREVIR|INTERFERON|LEDIPASVIR|OMBITASVIR|PEGINTERFERON|PEGYLATED|SIMEPREVIR|SOFOSBUVIR|TELAPREVIR
|
||||
68,hepatocellular carcinoma,ATEZOLIZUMAB|CABOZANTINIB|LENVATINIB|RAMUCIRUMAB|REGORAFENIB|SELECTIVE|SORAFENIB
|
||||
69,hiv,CABOTEGRAVIR
|
||||
70,hodgkin lymphoma,BRENTUXIMAB|NIVOLUMAB|PEMBROLIZUMAB
|
||||
71,hormone receptor,ABEMACICLIB
|
||||
72,hypercholesterolaemia,EZETIMIBE
|
||||
73,hyperparathyroidism,CINACALCET|ETELCALCETIDE
|
||||
74,immune thrombocytopenia,AVATROMBOPAG|FOSTAMATINIB
|
||||
75,influenza,AMANTADINE|ZANAMIVIR|BALOXAVIR
|
||||
76,insomnia,ZALEPLON
|
||||
77,irritable bowel syndrome,ELUXADOLINE
|
||||
78,ischaemic stroke,ALTEPLASE
|
||||
79,juvenile idiopathic arthritis,ABATECEPT|CANAKINUMAB|TOCILIZUMAB|TOFACITINIB
|
||||
80,kidney transplant,BASILIXIMAB
|
||||
81,leukaemia,FLUDARABINE|IMATINIB
|
||||
82,lung cancer,ATEZOLIZUMAB|DURVALUMAB|GEFITINIB|ORAL|NINTEDANIB
|
||||
83,lymphoma,BENDAMUSTINE|CRIZOTINIB|PIXANTRONE|RITUXIMAB
|
||||
84,macular degeneration,AFLIBERCEPT|BROLUCIZUMAB|FARICIMAB|RANIBIZUMAB
|
||||
85,macular oedema,AFLIBERCEPT|RANIBIZUMAB
|
||||
86,major depressive episodes,AGOMELATINE|VORTIOXETINE
|
||||
87,malignant melanoma,VEMURAFENIB
|
||||
88,malignant pleural mesothelioma,NIVOLUMAB|PEMETREXED
|
||||
89,manic episode,ARIPIPRAZOLE
|
||||
90,mantle cell lymphoma,AUTOLOGOUS|BORTEZOMIB|IBRUTINIB|LENALIDOMIDE|TEMSIROLIMUS
|
||||
91,melanoma,COBIMETINIB|DABRAFENIB|ENCORAFENIB|IPILIMUMAB|NIVOLUMAB|PEMBROLIZUMAB|TALIMOGENE|TRAMETINIB
|
||||
92,merkel cell carcinoma,AVELUMAB
|
||||
93,migraine,BOTULINUM|EPTINEZUMAB|ERENUMAB|FREMANEZUMAB|GALCANEZUMAB
|
||||
94,motor neurone disease,RILUZOLE
|
||||
95,multiple myeloma,BORTEZOMIB|THALIDOMIDE|CARFILZOMIB|DARATUMUMAB|DENOSUMAB|ELOTUZUMAB|ISATUXIMAB|IXAZOMIB|LENALIDOMIDE|PANOBINOSTAT|POMALIDOMIDE|SELINEXOR|TECLISTAMAB
|
||||
96,multiple sclerosis,ALEMTUZUMAB|BETA|CLADRIBINE|DACLIZUMAB|DIMETHYL|DIROXIMEL|FINGOLIMOD|INTERFERON|NATALIZUMAB|OCRELIZUMAB|OZANIMOD|PEGINTERFERON|PONESIMOD|SIPONIMOD|TERIFLUNOMIDE
|
||||
97,myelodysplastic,LENALIDOMIDE|LUSPATERCEPT
|
||||
98,myelofibrosis,FEDRATINIB|RUXOLITINIB
|
||||
99,myocardial infarction,ALTEPLASE|BIVALIRUDIN|TICAGRELOR
|
||||
100,myotonia,MEXILETINE
|
||||
101,narcolepsy,SOLRIAMFETOL
|
||||
102,neuroendocrine tumour,EVEROLIMUS|LUTETIUM
|
||||
103,non-small cell lung cancer,ATEZOLIZMAB|DOCETAXEL|ERLOTINIB|PEMETREXED
|
||||
104,non-small-cell lung cancer,AFATINIB|ALECTINIB|AMIVANTAMAB|ATEZOLIZUMAB|BEVACIZUMAB|BRIGATINIB|CEMIPLIMAB|CERITINIB|CRIZOTINIB|DABRAFENIB|DACOMITINIB|DURVALUMAB|ENTRECTINIB|ERLOTINIB|GEFITINIB|LORLATINIB|MOBOCERTINIB|NECITUMUMAB|NIVOLUMAB|OSIMERTINIB|PACLITAXEL|PEMBROLIZUMAB|PEMETREXED|PRALSETINIB|RAMUCIRUMAB|SELPERCATINIB|SOTORASIB|TEPOTINIB
|
||||
105,obesity,LIRAGLUTIDE|NALTREXONE|ORLISTAT|SEMAGLUTIDE|SIBUTRAMINE
|
||||
106,oesophageal cancer,NIVOLUMAB
|
||||
107,osteoarthritis,CELECOXIB
|
||||
108,osteoporosis,ALENDRONATE|DENOSUMAB|ORAL|ROMOSOZUMAB
|
||||
109,osteosarcoma,MIFAMURTIDE
|
||||
110,ovarian cancer,BEVACIZUMAB|PACLITAXEL|PEGYLATED|TOPOTECAN|TRABECTEDIN
|
||||
111,overweight,RIMONABANT
|
||||
112,pancreatic cancer,GEMCITABINE|OLAPARIB|PACLITAXEL|PEGYLATED
|
||||
113,paroxysmal nocturnal haemoglobinuria,PEGCETACOPLAN|RAVULIZUMAB
|
||||
114,peripheral arterial disease,NAFTIDROFYRYL
|
||||
115,plaque psoriasis,ADALIMUMAB|APREMILAST|BIMEKIZUMAB|BRODALUMAB|CERTOLIZUMAB|GUSELKUMAB|INFLIXIMAB|IXEKIZUMAB|RISANKIZUMAB|SECUKINUMAB|TILDRAKIZUAMB|USTEKINUMAB
|
||||
116,polycystic kidney disease,TOLVAPTAN
|
||||
117,polycythaemia vera,RUXOLITINIB
|
||||
118,pregnancy,ROUTINE
|
||||
119,primary biliary cholangitis,OBETICHOLIC
|
||||
120,primary hypercholesterolaemia,ALIROCUMAB|EVOLOCUMAB
|
||||
121,prostate cancer,ABIRATERONE|APALUTAMIDE|CABAZITAXEL|DAROLUTAMIDE|DEGARELIX|DENOSUMAB|DOCETAXEL|ENZALUTAMIDE|OLAPARIB|PADELIPORFIN|RADIUM-|RADIUM|SIPULEUCEL-T
|
||||
122,psoriasis,EFALUZIMAB
|
||||
123,psoriatic arthritis,ABATACEPT|ADALIMUMAB|APREMILAST|CERTOLIZUMAB|ETANERCEPT|GOLIMUMAB|GUSELKUMAB|IXEKIZUMAB|RISANKIZUMAB|TOFACITINIB|UPADACITINIB|USTEKINUMAB
|
||||
124,pulmonary embolism,APIXABAN|DABIGATRAN|EDOXABAN|RIVAROXABAN
|
||||
125,pulmonary fibrosis,NINTEDANIB|PIRFENIDONE
|
||||
126,relapsing multiple sclerosis,OFATUMUMAB
|
||||
127,renal cell carcinoma,AVELUMAB|AXITINIB|BEVACIZUMAB|CABOZANTINIB|EVEROLIMUS|LENVATINIB|NIVOLUMAB|PAZOPANIB|PEMBROLIZUMAB|SUNITINIB|TIVOZANIB
|
||||
128,renal transplantation,BASILIXIMAB|INDUCTION
|
||||
129,retinal vein occlusion,AFLIBERCEPT|DEXAMETHASONE|RANIBIZUMAB
|
||||
130,rheumatoid arthritis,ABATACEPT|ADALIMUMAB|ANAKINRA|BARICITINIB|CELECOXIB|CERTOLIZUMAB|ETANERCEPT|FILGOTINIB|GOLIMUMAB|RITUXIMAB|SARILUMAB|TOCILIZUMAB|TOFACITINIB|UPADACITINIB
|
||||
131,rivaroxaban,ANDEXANET
|
||||
132,schizophrenia,AMISULPRIDE|ARIPIPRAZOLE|LOXAPINE
|
||||
133,seizures,CANNABIDIOL
|
||||
134,sepsis,DROTRECOGIN
|
||||
135,severe persistent allergic asthma,OMALIZUMAB
|
||||
136,short bowel syndrome,TEDUGLUTIDE
|
||||
137,sickle cell disease,CRIZANLIZUMAB
|
||||
138,sleep apnoea,PITOLISANT|SOLRIAMFETOL
|
||||
139,smoking cessation,NICOTINE|VARENICLINE
|
||||
140,soft tissue sarcoma,INTRAVENOUS|NBTXR-|OLARATUMAB
|
||||
141,spinal muscular atrophy,NUSINERSEN|RISDIPLAM
|
||||
142,squamous cell,CETUXIMAB
|
||||
143,squamous cell carcinoma,CEMIPLIMAB|NIVOLUMAB|PEMBROLIZUMAB
|
||||
144,stem cell transplant,MELPHALAN|TREOSULFAN
|
||||
145,stroke,APIXABAN|DABIGATRAN|EDOXABAN|RIVAROXABAN
|
||||
146,systemic lupus erythematosus,ANIFROLUMAB|ETANERCEPT
|
||||
147,systemic mastocytosis,MIDOSTAURIN
|
||||
148,thrombocytopenic purpura,ELTROMBOPAG|ROMIPLOSTIM
|
||||
149,thrombotic thrombocytopenic purpura,CAPLACIZUMAB
|
||||
150,thyroid cancer,CABOZANTINIB|LENVATINIB|SELPERCATINIB|VANDETANIB
|
||||
151,tophaceous gout,PEGLOTICASE
|
||||
152,transitional cell carcinoma,VINFLUNINE
|
||||
153,tuberous sclerosis,CANNABIDIOL
|
||||
154,type 1 diabetes,CONTINUOUS|DAPAGLIFLOZIN|INSULIN|SOTAGLIFLOZIN
|
||||
155,type 2 diabetes,CANAGLIFLOZIN|CONTINUOUS|DAPAGLIFLOZIN|EMPAGLIFLOZIN|ERTUGLIFLOZIN|EXENATIDE|FINERENONE|INSULIN|LIRAGLUTIDE|PIOGLITAZONE|ROSIGLITAZONE
|
||||
156,ulcerative colitis,ADALIMUMAB|INFLIXIMAB|FILGOTINIB|OZANIMOD|TOFACITINIB|UPADACITINIB|USTEKINUMAB|VEDOLIZUMAB
|
||||
157,urothelial carcinoma,ATEZOLIZUMAB|PEMBROLIZUMAB
|
||||
158,urticaria,OMALIZUMAB
|
||||
159,uterine fibroids,RELUGOLIX
|
||||
160,uveitis,ADALIMUMAB|FLUOCINOLONE
|
||||
161,vascular disease,MODIFIED-RELEASE|CLOPIDOGREL
|
||||
162,vasculitis,RITUXIMAB
|
||||
163,venous thromboembolism,APIXABAN|DABIGATRAN|RIVAROXABAN
|
||||
|
@@ -1,231 +0,0 @@
|
||||
Search_Term,PrimaryDirectorate,AllDirectorates
|
||||
acute coronary syndrome,CARDIOLOGY,CARDIOLOGY
|
||||
acute coronary syndromes,CARDIOLOGY,CARDIOLOGY
|
||||
acute lymphoblastic leukaemia,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY|PAEDIATRICS
|
||||
acute myeloid leukaemia,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY|MEDICAL ONCOLOGY
|
||||
acute promyelocytic leukaemia,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY
|
||||
advanced breast cancer,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|BREAST SURGERY|CLINICAL ONCOLOGY
|
||||
allergic asthma,THORACIC MEDICINE,THORACIC MEDICINE|CLINICAL IMMUNOLOGY
|
||||
allergic rhinitis,ENT,ENT|CLINICAL IMMUNOLOGY
|
||||
alzheimer's disease,NEUROLOGY,NEUROLOGY|GERIATRIC MEDICINE|MENTAL HEALTH
|
||||
amyloidosis,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY|CARDIOLOGY|NEPHROLOGY
|
||||
anaemia,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY|GENERAL MEDICINE
|
||||
anaplastic large cell lymphoma,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY|MEDICAL ONCOLOGY
|
||||
angioedema,CLINICAL IMMUNOLOGY,CLINICAL IMMUNOLOGY|ACCIDENT & EMERGENCY
|
||||
ankylosing spondylitis,RHEUMATOLOGY,RHEUMATOLOGY
|
||||
apixaban,CARDIOLOGY,CARDIOLOGY|CLINICAL HAEMATOLOGY
|
||||
aplastic anaemia,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY
|
||||
arthritis,RHEUMATOLOGY,RHEUMATOLOGY
|
||||
asthma,THORACIC MEDICINE,THORACIC MEDICINE|PAEDIATRICS
|
||||
atopic dermatitis,DERMATOLOGY,DERMATOLOGY|PAEDIATRICS|CLINICAL IMMUNOLOGY
|
||||
atrial fibrillation,CARDIOLOGY,CARDIOLOGY
|
||||
attention deficit hyperactivity disorder,MENTAL HEALTH,MENTAL HEALTH|PAEDIATRICS
|
||||
attention-deficit hyperactivity disorder,MENTAL HEALTH,MENTAL HEALTH|PAEDIATRICS
|
||||
axial spondyloarthritis,RHEUMATOLOGY,RHEUMATOLOGY
|
||||
basal cell carcinoma,DERMATOLOGY,DERMATOLOGY|PLASTIC SURGERY|MEDICAL ONCOLOGY
|
||||
beta-thalassaemia,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY|PAEDIATRICS
|
||||
biliary cholangitis,GASTROENTEROLOGY,GASTROENTEROLOGY
|
||||
bipolar disorder,MENTAL HEALTH,MENTAL HEALTH
|
||||
bladder,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|UROLOGY|CLINICAL ONCOLOGY
|
||||
braf,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|CLINICAL ONCOLOGY
|
||||
brca,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|GYNAECOLOGICAL ONCOLOGY|BREAST SURGERY
|
||||
breast cancer,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|BREAST SURGERY|CLINICAL ONCOLOGY
|
||||
cardiomyopathy,CARDIOLOGY,CARDIOLOGY
|
||||
cardiovascular disease,CARDIOLOGY,CARDIOLOGY|VASCULAR SURGERY
|
||||
cervical cancer,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|GYNAECOLOGICAL ONCOLOGY|CLINICAL ONCOLOGY
|
||||
cholangiocarcinoma,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|GASTROENTEROLOGY|CLINICAL ONCOLOGY
|
||||
choroidal neovascularisation,OPHTHALMOLOGY,OPHTHALMOLOGY|MEDICAL OPHTHALMOLOGY
|
||||
chronic hepatitis b,GASTROENTEROLOGY,GASTROENTEROLOGY|INFECTIOUS DISEASES
|
||||
chronic kidney disease,NEPHROLOGY,NEPHROLOGY
|
||||
chronic liver disease,GASTROENTEROLOGY,GASTROENTEROLOGY
|
||||
chronic lymphocytic leukaemia,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY
|
||||
chronic myeloid leukaemia,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY
|
||||
chronic obstructive pulmonary disease,THORACIC MEDICINE,THORACIC MEDICINE
|
||||
colon cancer,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|COLORECTAL SURGERY|CLINICAL ONCOLOGY
|
||||
colorectal cancer,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|COLORECTAL SURGERY|CLINICAL ONCOLOGY
|
||||
constipation,GASTROENTEROLOGY,GASTROENTEROLOGY|GENERAL MEDICINE
|
||||
coronary syndrome,CARDIOLOGY,CARDIOLOGY
|
||||
covid,INFECTIOUS DISEASES,INFECTIOUS DISEASES|THORACIC MEDICINE
|
||||
covid-19,INFECTIOUS DISEASES,INFECTIOUS DISEASES|THORACIC MEDICINE
|
||||
crohn's disease,GASTROENTEROLOGY,GASTROENTEROLOGY|PAEDIATRIC GASTROENTEROLOGY|COLORECTAL SURGERY
|
||||
cutaneous t-cell lymphoma,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY|DERMATOLOGY
|
||||
cystic fibrosis,THORACIC MEDICINE,THORACIC MEDICINE|PAEDIATRICS|GASTROENTEROLOGY
|
||||
cytomegalovirus,INFECTIOUS DISEASES,INFECTIOUS DISEASES|TRANSPLANTATION SURGERY
|
||||
deep vein thrombosis,VASCULAR SURGERY,VASCULAR SURGERY|CLINICAL HAEMATOLOGY
|
||||
depression,MENTAL HEALTH,MENTAL HEALTH
|
||||
depressive episode,MENTAL HEALTH,MENTAL HEALTH
|
||||
diabetes,DIABETIC MEDICINE,DIABETIC MEDICINE|ENDOCRINOLOGY
|
||||
diabetic macular,OPHTHALMOLOGY,OPHTHALMOLOGY|MEDICAL OPHTHALMOLOGY
|
||||
diabetic macular oedema,OPHTHALMOLOGY,OPHTHALMOLOGY|MEDICAL OPHTHALMOLOGY
|
||||
diabetic retinopathy,OPHTHALMOLOGY,OPHTHALMOLOGY|MEDICAL OPHTHALMOLOGY|DIABETIC MEDICINE
|
||||
diffuse large b-cell lymphoma,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY|MEDICAL ONCOLOGY
|
||||
dravet syndrome,NEUROLOGY,NEUROLOGY|PAEDIATRICS
|
||||
drug misuse,MENTAL HEALTH,MENTAL HEALTH|ADDICTION MEDICINE
|
||||
dry eye,OPHTHALMOLOGY,OPHTHALMOLOGY
|
||||
dupuytren's contracture,TRAUMA & ORTHOPAEDICS,TRAUMA & ORTHOPAEDICS|PLASTIC SURGERY
|
||||
dyslipidaemia,CARDIOLOGY,CARDIOLOGY|ENDOCRINOLOGY
|
||||
dyspepsia,GASTROENTEROLOGY,GASTROENTEROLOGY|GENERAL MEDICINE
|
||||
eczema,DERMATOLOGY,DERMATOLOGY|PAEDIATRICS
|
||||
endometrial cancer,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|GYNAECOLOGICAL ONCOLOGY|CLINICAL ONCOLOGY
|
||||
epilepsy,NEUROLOGY,NEUROLOGY|PAEDIATRICS
|
||||
fallopian tube,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|GYNAECOLOGICAL ONCOLOGY|CLINICAL ONCOLOGY
|
||||
fibroids,GYNAECOLOGY,GYNAECOLOGY
|
||||
follicular lymphoma,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY|MEDICAL ONCOLOGY
|
||||
fragility fracture,RHEUMATOLOGY,RHEUMATOLOGY|TRAUMA & ORTHOPAEDICS|GERIATRIC MEDICINE
|
||||
gastric cancer,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|UPPER GASTROINTESTINAL SURGERY|CLINICAL ONCOLOGY
|
||||
gastro-oesophageal,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|UPPER GASTROINTESTINAL SURGERY|CLINICAL ONCOLOGY
|
||||
gastro-oesophageal junction,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|UPPER GASTROINTESTINAL SURGERY|CLINICAL ONCOLOGY
|
||||
gastrointestinal stromal tumour,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|UPPER GASTROINTESTINAL SURGERY|CLINICAL ONCOLOGY
|
||||
gastrointestinal stromal tumours,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|UPPER GASTROINTESTINAL SURGERY|CLINICAL ONCOLOGY
|
||||
giant cell arteritis,RHEUMATOLOGY,RHEUMATOLOGY
|
||||
glioma,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|NEUROSURGERY|CLINICAL ONCOLOGY
|
||||
gout,RHEUMATOLOGY,RHEUMATOLOGY
|
||||
graft versus host disease,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY|TRANSPLANTATION SURGERY
|
||||
granulomatosis with polyangiitis,RHEUMATOLOGY,RHEUMATOLOGY|THORACIC MEDICINE|NEPHROLOGY
|
||||
growth failure,ENDOCRINOLOGY,ENDOCRINOLOGY|PAEDIATRICS
|
||||
growth hormone deficiency,ENDOCRINOLOGY,ENDOCRINOLOGY|PAEDIATRICS
|
||||
haemoglobinuria,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY
|
||||
hand eczema,DERMATOLOGY,DERMATOLOGY
|
||||
head and neck,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|ENT|CLINICAL ONCOLOGY
|
||||
heart failure,CARDIOLOGY,CARDIOLOGY
|
||||
hepatic encephalopathy,GASTROENTEROLOGY,GASTROENTEROLOGY
|
||||
hepatitis b,GASTROENTEROLOGY,GASTROENTEROLOGY|INFECTIOUS DISEASES
|
||||
hepatitis c,GASTROENTEROLOGY,GASTROENTEROLOGY|INFECTIOUS DISEASES
|
||||
hepatocellular carcinoma,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|GASTROENTEROLOGY|CLINICAL ONCOLOGY
|
||||
her2,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|BREAST SURGERY|CLINICAL ONCOLOGY
|
||||
her2-positive,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|BREAST SURGERY|CLINICAL ONCOLOGY
|
||||
hereditary angioedema,CLINICAL IMMUNOLOGY,CLINICAL IMMUNOLOGY
|
||||
hidradenitis suppurativa,DERMATOLOGY,DERMATOLOGY
|
||||
hiv,INFECTIOUS DISEASES,INFECTIOUS DISEASES
|
||||
hodgkin lymphoma,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY|MEDICAL ONCOLOGY
|
||||
hormone receptor,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|BREAST SURGERY|CLINICAL ONCOLOGY
|
||||
hypercholesterolaemia,CARDIOLOGY,CARDIOLOGY|ENDOCRINOLOGY|CHEMICAL PATHOLOGY
|
||||
hyperparathyroidism,ENDOCRINOLOGY,ENDOCRINOLOGY
|
||||
hyperuricaemia,RHEUMATOLOGY,RHEUMATOLOGY
|
||||
immune thrombocytopenia,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY
|
||||
influenza,INFECTIOUS DISEASES,INFECTIOUS DISEASES|GENERAL MEDICINE
|
||||
insomnia,NEUROLOGY,NEUROLOGY|MENTAL HEALTH
|
||||
interstitial lung disease,THORACIC MEDICINE,THORACIC MEDICINE
|
||||
irritable bowel syndrome,GASTROENTEROLOGY,GASTROENTEROLOGY
|
||||
ischaemic stroke,STROKE MEDICINE,STROKE MEDICINE|NEUROLOGY
|
||||
juvenile idiopathic arthritis,RHEUMATOLOGY,RHEUMATOLOGY|PAEDIATRICS
|
||||
keratitis,OPHTHALMOLOGY,OPHTHALMOLOGY
|
||||
kidney disease,NEPHROLOGY,NEPHROLOGY
|
||||
kidney transplant,NEPHROLOGY,NEPHROLOGY|TRANSPLANTATION SURGERY
|
||||
large b-cell lymphoma,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY|MEDICAL ONCOLOGY
|
||||
leukaemia,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY|MEDICAL ONCOLOGY
|
||||
limbal stem cell deficiency,OPHTHALMOLOGY,OPHTHALMOLOGY
|
||||
liver disease,GASTROENTEROLOGY,GASTROENTEROLOGY
|
||||
lung cancer,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|THORACIC MEDICINE|CLINICAL ONCOLOGY
|
||||
lymphoblastic leukaemia,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY|PAEDIATRICS
|
||||
lymphocytic leukaemia,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY
|
||||
lymphoma,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY|MEDICAL ONCOLOGY
|
||||
macular degeneration,OPHTHALMOLOGY,OPHTHALMOLOGY|MEDICAL OPHTHALMOLOGY
|
||||
macular oedema,OPHTHALMOLOGY,OPHTHALMOLOGY|MEDICAL OPHTHALMOLOGY
|
||||
major depressive episodes,MENTAL HEALTH,MENTAL HEALTH
|
||||
malignant melanoma,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|DERMATOLOGY|CLINICAL ONCOLOGY
|
||||
malignant pleural mesothelioma,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|THORACIC MEDICINE|CLINICAL ONCOLOGY
|
||||
manic episode,MENTAL HEALTH,MENTAL HEALTH
|
||||
mantle cell lymphoma,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY|MEDICAL ONCOLOGY
|
||||
mastocytosis,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY|CLINICAL IMMUNOLOGY
|
||||
melanoma,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|DERMATOLOGY|CLINICAL ONCOLOGY
|
||||
merkel cell,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|DERMATOLOGY|CLINICAL ONCOLOGY
|
||||
merkel cell carcinoma,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|DERMATOLOGY|CLINICAL ONCOLOGY
|
||||
mesothelioma,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|THORACIC MEDICINE|CLINICAL ONCOLOGY
|
||||
metastatic colorectal cancer,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|COLORECTAL SURGERY|CLINICAL ONCOLOGY
|
||||
migraine,NEUROLOGY,NEUROLOGY
|
||||
motor neurone disease,NEUROLOGY,NEUROLOGY|REHABILITATION|PALLIATIVE CARE
|
||||
multiple myeloma,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY|MEDICAL ONCOLOGY
|
||||
multiple sclerosis,NEUROLOGY,NEUROLOGY|REHABILITATION
|
||||
myelodysplastic,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY
|
||||
myelodysplastic syndromes,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY
|
||||
myelofibrosis,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY
|
||||
myeloid leukaemia,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY
|
||||
myocardial infarction,CARDIOLOGY,CARDIOLOGY
|
||||
myotonia,NEUROLOGY,NEUROLOGY
|
||||
narcolepsy,NEUROLOGY,NEUROLOGY
|
||||
nasal polyps,ENT,ENT|THORACIC MEDICINE|CLINICAL IMMUNOLOGY
|
||||
neuroblastoma,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|PAEDIATRICS|CLINICAL ONCOLOGY
|
||||
neuroendocrine tumour,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|ENDOCRINOLOGY|CLINICAL ONCOLOGY
|
||||
non-small cell lung cancer,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|THORACIC MEDICINE|CLINICAL ONCOLOGY
|
||||
non-small-cell lung cancer,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|THORACIC MEDICINE|CLINICAL ONCOLOGY
|
||||
obesity,ENDOCRINOLOGY,ENDOCRINOLOGY|DIABETIC MEDICINE|GENERAL MEDICINE
|
||||
oesophageal cancer,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|UPPER GASTROINTESTINAL SURGERY|CLINICAL ONCOLOGY
|
||||
osteoarthritis,RHEUMATOLOGY,RHEUMATOLOGY|TRAUMA & ORTHOPAEDICS|GERIATRIC MEDICINE
|
||||
osteoporosis,RHEUMATOLOGY,RHEUMATOLOGY|ENDOCRINOLOGY|GERIATRIC MEDICINE
|
||||
osteosarcoma,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|TRAUMA & ORTHOPAEDICS|CLINICAL ONCOLOGY
|
||||
ovarian cancer,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|GYNAECOLOGICAL ONCOLOGY|CLINICAL ONCOLOGY
|
||||
overweight,ENDOCRINOLOGY,ENDOCRINOLOGY|DIABETIC MEDICINE
|
||||
pancreatic cancer,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|UPPER GASTROINTESTINAL SURGERY|CLINICAL ONCOLOGY
|
||||
pancreatic neuroendocrine,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|ENDOCRINOLOGY|CLINICAL ONCOLOGY
|
||||
paroxysmal nocturnal haemoglobinuria,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY
|
||||
peanut allergy,CLINICAL IMMUNOLOGY,CLINICAL IMMUNOLOGY|PAEDIATRICS
|
||||
perianal fistula,GASTROENTEROLOGY,GASTROENTEROLOGY|COLORECTAL SURGERY
|
||||
peripheral arterial disease,VASCULAR SURGERY,VASCULAR SURGERY|CARDIOLOGY
|
||||
plaque psoriasis,DERMATOLOGY,DERMATOLOGY
|
||||
polycystic kidney,NEPHROLOGY,NEPHROLOGY
|
||||
polycystic kidney disease,NEPHROLOGY,NEPHROLOGY
|
||||
polycythaemia,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY
|
||||
polycythaemia vera,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY
|
||||
pouchitis,GASTROENTEROLOGY,GASTROENTEROLOGY|COLORECTAL SURGERY
|
||||
pregnancy,OBSTETRICS,OBSTETRICS
|
||||
primary biliary cholangitis,GASTROENTEROLOGY,GASTROENTEROLOGY
|
||||
primary hypercholesterolaemia,CARDIOLOGY,CARDIOLOGY|ENDOCRINOLOGY|CHEMICAL PATHOLOGY
|
||||
promyelocytic leukaemia,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY
|
||||
prostate cancer,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|UROLOGY|CLINICAL ONCOLOGY
|
||||
psoriasis,DERMATOLOGY,DERMATOLOGY
|
||||
psoriatic arthritis,RHEUMATOLOGY,RHEUMATOLOGY|DERMATOLOGY
|
||||
pulmonary embolism,THORACIC MEDICINE,THORACIC MEDICINE|CARDIOLOGY|CLINICAL HAEMATOLOGY
|
||||
pulmonary fibrosis,THORACIC MEDICINE,THORACIC MEDICINE
|
||||
relapsing multiple sclerosis,NEUROLOGY,NEUROLOGY|REHABILITATION
|
||||
renal cell,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|UROLOGY|CLINICAL ONCOLOGY
|
||||
renal cell carcinoma,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|UROLOGY|CLINICAL ONCOLOGY
|
||||
renal transplantation,NEPHROLOGY,NEPHROLOGY|TRANSPLANTATION SURGERY
|
||||
retinal vein occlusion,OPHTHALMOLOGY,OPHTHALMOLOGY|MEDICAL OPHTHALMOLOGY
|
||||
rheumatoid arthritis,RHEUMATOLOGY,RHEUMATOLOGY|CLINICAL IMMUNOLOGY|GERIATRIC MEDICINE
|
||||
rhinosinusitis with nasal polyps,ENT,ENT|THORACIC MEDICINE|CLINICAL IMMUNOLOGY
|
||||
rivaroxaban,CARDIOLOGY,CARDIOLOGY|CLINICAL HAEMATOLOGY
|
||||
schizophrenia,MENTAL HEALTH,MENTAL HEALTH
|
||||
seizures,NEUROLOGY,NEUROLOGY|PAEDIATRICS
|
||||
sepsis,INFECTIOUS DISEASES,INFECTIOUS DISEASES|CRITICAL CARE MEDICINE
|
||||
severe persistent allergic asthma,THORACIC MEDICINE,THORACIC MEDICINE|CLINICAL IMMUNOLOGY
|
||||
short bowel syndrome,GASTROENTEROLOGY,GASTROENTEROLOGY|COLORECTAL SURGERY
|
||||
sickle cell,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY|PAEDIATRICS
|
||||
sickle cell disease,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY|PAEDIATRICS
|
||||
sleep apnoea,THORACIC MEDICINE,THORACIC MEDICINE|ENT
|
||||
smoking cessation,THORACIC MEDICINE,THORACIC MEDICINE|GENERAL MEDICINE
|
||||
soft tissue sarcoma,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|CLINICAL ONCOLOGY
|
||||
spinal muscular atrophy,NEUROLOGY,NEUROLOGY|PAEDIATRICS
|
||||
splenomegaly,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY|GASTROENTEROLOGY
|
||||
spondyloarthritis,RHEUMATOLOGY,RHEUMATOLOGY
|
||||
squamous cell,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|DERMATOLOGY|ENT|CLINICAL ONCOLOGY
|
||||
squamous cell carcinoma,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|DERMATOLOGY|ENT|CLINICAL ONCOLOGY
|
||||
stem cell transplant,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY|TRANSPLANTATION SURGERY
|
||||
stroke,STROKE MEDICINE,STROKE MEDICINE|NEUROLOGY
|
||||
systemic lupus erythematosus,RHEUMATOLOGY,RHEUMATOLOGY|CLINICAL IMMUNOLOGY|NEPHROLOGY
|
||||
systemic mastocytosis,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY|CLINICAL IMMUNOLOGY
|
||||
t-cell lymphoma,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY|MEDICAL ONCOLOGY
|
||||
thalassaemia,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY|PAEDIATRICS
|
||||
thrombocytopenia,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY
|
||||
thrombocytopenic purpura,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY
|
||||
thromboembolism,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY|CARDIOLOGY
|
||||
thrombotic thrombocytopenic purpura,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY
|
||||
thyroid cancer,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|ENDOCRINOLOGY|CLINICAL ONCOLOGY
|
||||
tophaceous gout,RHEUMATOLOGY,RHEUMATOLOGY
|
||||
transitional cell carcinoma,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|UROLOGY|CLINICAL ONCOLOGY
|
||||
transthyretin amyloidosis,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY|CARDIOLOGY|NEUROLOGY
|
||||
triple-negative,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|BREAST SURGERY|CLINICAL ONCOLOGY
|
||||
tuberous sclerosis,NEUROLOGY,NEUROLOGY|PAEDIATRICS
|
||||
type 1 diabetes,DIABETIC MEDICINE,DIABETIC MEDICINE|ENDOCRINOLOGY|PAEDIATRICS
|
||||
type 2 diabetes,DIABETIC MEDICINE,DIABETIC MEDICINE|ENDOCRINOLOGY
|
||||
ulcerative colitis,GASTROENTEROLOGY,GASTROENTEROLOGY|COLORECTAL SURGERY
|
||||
urothelial,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|UROLOGY|CLINICAL ONCOLOGY
|
||||
urothelial cancer,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|UROLOGY|CLINICAL ONCOLOGY
|
||||
urothelial carcinoma,MEDICAL ONCOLOGY,MEDICAL ONCOLOGY|UROLOGY|CLINICAL ONCOLOGY
|
||||
urticaria,DERMATOLOGY,DERMATOLOGY|CLINICAL IMMUNOLOGY
|
||||
uterine fibroids,GYNAECOLOGY,GYNAECOLOGY
|
||||
uveitis,OPHTHALMOLOGY,OPHTHALMOLOGY|MEDICAL OPHTHALMOLOGY|RHEUMATOLOGY
|
||||
vascular disease,VASCULAR SURGERY,VASCULAR SURGERY|CARDIOLOGY
|
||||
vasculitis,RHEUMATOLOGY,RHEUMATOLOGY|CLINICAL IMMUNOLOGY
|
||||
venom allergy,CLINICAL IMMUNOLOGY,CLINICAL IMMUNOLOGY
|
||||
venous thromboembolism,CLINICAL HAEMATOLOGY,CLINICAL HAEMATOLOGY|VASCULAR SURGERY
|
||||
|
File diff suppressed because it is too large
Load Diff
@@ -1,4 +0,0 @@
|
||||
# Re-export app from pathways_app
|
||||
from pathways_app.pathways_app import app
|
||||
|
||||
__all__ = ["app"]
|
||||
@@ -1,17 +0,0 @@
|
||||
"""
|
||||
UI components for the Patient Pathway Analysis Reflex application.
|
||||
|
||||
This module exports reusable layout and navigation components.
|
||||
"""
|
||||
|
||||
from .layout import sidebar, navbar, content_area, main_layout
|
||||
from .navigation import nav_item, nav_section
|
||||
|
||||
__all__ = [
|
||||
"sidebar",
|
||||
"navbar",
|
||||
"content_area",
|
||||
"main_layout",
|
||||
"nav_item",
|
||||
"nav_section",
|
||||
]
|
||||
@@ -1,262 +0,0 @@
|
||||
"""
|
||||
Layout components for the Patient Pathway Analysis tool.
|
||||
|
||||
Provides the main application layout with sidebar navigation and content area.
|
||||
Includes accessibility features: skip links, ARIA landmarks, keyboard navigation.
|
||||
"""
|
||||
|
||||
import reflex as rx
|
||||
from .navigation import nav_item
|
||||
|
||||
|
||||
# NHS Color scheme
|
||||
NHS_BLUE = "rgb(0, 94, 184)"
|
||||
NHS_DARK_BLUE = "rgb(0, 48, 135)"
|
||||
NHS_LIGHT_BLUE = "rgb(65, 182, 230)"
|
||||
NHS_WHITE = "white"
|
||||
NHS_GREY = "rgb(231, 231, 231)"
|
||||
|
||||
|
||||
def skip_link() -> rx.Component:
|
||||
"""
|
||||
Skip link for keyboard users to bypass navigation.
|
||||
|
||||
Visually hidden until focused, allowing keyboard users to skip
|
||||
directly to main content.
|
||||
"""
|
||||
return rx.link(
|
||||
"Skip to main content",
|
||||
href="#main-content",
|
||||
position="absolute",
|
||||
top="-40px",
|
||||
left="0",
|
||||
background=NHS_BLUE,
|
||||
color="white",
|
||||
padding="8px 16px",
|
||||
z_index="1000",
|
||||
text_decoration="none",
|
||||
font_weight="bold",
|
||||
_focus={
|
||||
"top": "0",
|
||||
},
|
||||
)
|
||||
|
||||
|
||||
def logo_section() -> rx.Component:
|
||||
"""NHS branding logo section at top of sidebar."""
|
||||
return rx.hstack(
|
||||
rx.image(
|
||||
src="/logo.png",
|
||||
height="32px",
|
||||
alt="NHS Norfolk and Waveney Logo",
|
||||
),
|
||||
rx.text(
|
||||
"HCD Analysis",
|
||||
size="5",
|
||||
weight="bold",
|
||||
color=NHS_BLUE,
|
||||
),
|
||||
padding="16px",
|
||||
spacing="3",
|
||||
align="center",
|
||||
width="100%",
|
||||
border_bottom=f"1px solid {NHS_GREY}",
|
||||
)
|
||||
|
||||
|
||||
def sidebar(current_page: str = "home") -> rx.Component:
|
||||
"""
|
||||
Create the sidebar navigation panel.
|
||||
|
||||
Args:
|
||||
current_page: The current active page name for highlighting
|
||||
|
||||
Returns:
|
||||
A sidebar component with navigation items and ARIA landmark
|
||||
"""
|
||||
return rx.el.nav(
|
||||
rx.vstack(
|
||||
# Logo section
|
||||
logo_section(),
|
||||
# Navigation items
|
||||
rx.vstack(
|
||||
nav_item(
|
||||
"Home",
|
||||
"/",
|
||||
"home",
|
||||
is_active=(current_page == "home"),
|
||||
),
|
||||
nav_item(
|
||||
"Drug Selection",
|
||||
"/drugs",
|
||||
"pill",
|
||||
is_active=(current_page == "drugs"),
|
||||
),
|
||||
nav_item(
|
||||
"Trust Selection",
|
||||
"/trusts",
|
||||
"building",
|
||||
is_active=(current_page == "trusts"),
|
||||
),
|
||||
nav_item(
|
||||
"Directory Selection",
|
||||
"/directories",
|
||||
"folder",
|
||||
is_active=(current_page == "directories"),
|
||||
),
|
||||
padding="8px",
|
||||
spacing="1",
|
||||
width="100%",
|
||||
align="start",
|
||||
),
|
||||
# Spacer to push theme toggle to bottom
|
||||
rx.spacer(),
|
||||
# Theme toggle at bottom
|
||||
rx.box(
|
||||
rx.hstack(
|
||||
rx.el.label(
|
||||
"Theme:",
|
||||
html_for="theme-toggle",
|
||||
font_size="14px",
|
||||
color="gray",
|
||||
),
|
||||
rx.color_mode.switch(id="theme-toggle"),
|
||||
spacing="2",
|
||||
align="center",
|
||||
),
|
||||
padding="16px",
|
||||
border_top=f"1px solid {NHS_GREY}",
|
||||
width="100%",
|
||||
),
|
||||
height="100vh",
|
||||
width="100%",
|
||||
spacing="0",
|
||||
align="start",
|
||||
),
|
||||
aria_label="Main navigation",
|
||||
width="240px",
|
||||
min_width="240px",
|
||||
background="white",
|
||||
border_right=f"1px solid {NHS_GREY}",
|
||||
position="fixed",
|
||||
left="0",
|
||||
top="0",
|
||||
height="100vh",
|
||||
overflow_y="auto",
|
||||
z_index="100",
|
||||
)
|
||||
|
||||
|
||||
def navbar() -> rx.Component:
|
||||
"""
|
||||
Create a top navigation bar for mobile/smaller screens.
|
||||
|
||||
Returns:
|
||||
A horizontal navbar component (collapsed sidebar for mobile) with ARIA support
|
||||
"""
|
||||
return rx.el.header(
|
||||
rx.hstack(
|
||||
rx.image(src="/logo.png", height="28px", alt="NHS Norfolk and Waveney Logo"),
|
||||
rx.text("HCD Analysis", size="4", weight="bold"),
|
||||
rx.spacer(),
|
||||
rx.el.label(
|
||||
rx.color_mode.switch(id="theme-toggle-mobile"),
|
||||
html_for="theme-toggle-mobile",
|
||||
aria_label="Toggle dark mode",
|
||||
),
|
||||
width="100%",
|
||||
padding="12px 16px",
|
||||
align="center",
|
||||
justify="between",
|
||||
),
|
||||
background="white",
|
||||
border_bottom=f"1px solid {NHS_GREY}",
|
||||
display=["flex", "flex", "none"], # Show on mobile, hide on desktop
|
||||
width="100%",
|
||||
position="fixed",
|
||||
top="0",
|
||||
left="0",
|
||||
z_index="100",
|
||||
role="banner",
|
||||
)
|
||||
|
||||
|
||||
def content_area(*children, page_title: str = "") -> rx.Component:
|
||||
"""
|
||||
Create the main content area.
|
||||
|
||||
Args:
|
||||
*children: Child components to render in the content area
|
||||
page_title: Optional title to display at top of content
|
||||
|
||||
Returns:
|
||||
A styled content area component with ARIA main landmark
|
||||
"""
|
||||
content_children = list(children)
|
||||
|
||||
if page_title:
|
||||
content_children.insert(
|
||||
0,
|
||||
rx.heading(
|
||||
page_title,
|
||||
size="6",
|
||||
weight="bold",
|
||||
color=NHS_DARK_BLUE,
|
||||
margin_bottom="16px",
|
||||
),
|
||||
)
|
||||
|
||||
return rx.el.main(
|
||||
rx.vstack(
|
||||
*content_children,
|
||||
width="100%",
|
||||
max_width="1200px",
|
||||
padding="24px",
|
||||
spacing="4",
|
||||
align="start",
|
||||
),
|
||||
id="main-content",
|
||||
tabindex="-1", # Allow focus for skip link
|
||||
# Offset for sidebar on desktop
|
||||
margin_left=["0", "0", "240px"],
|
||||
# Offset for navbar on mobile
|
||||
margin_top=["60px", "60px", "0"],
|
||||
min_height="100vh",
|
||||
background=rx.color_mode_cond(
|
||||
light="rgb(249, 250, 251)", # Light gray background
|
||||
dark="rgb(17, 24, 39)", # Dark background
|
||||
),
|
||||
width="100%",
|
||||
_focus={
|
||||
"outline": "none", # Hide focus ring on main (only accessible via skip link)
|
||||
},
|
||||
)
|
||||
|
||||
|
||||
def main_layout(
|
||||
content: rx.Component,
|
||||
current_page: str = "home",
|
||||
) -> rx.Component:
|
||||
"""
|
||||
Create the complete page layout with sidebar and content.
|
||||
|
||||
Args:
|
||||
content: The main content to display
|
||||
current_page: The current page name for navigation highlighting
|
||||
|
||||
Returns:
|
||||
A complete page layout component with accessibility features
|
||||
"""
|
||||
return rx.fragment(
|
||||
# Skip link for keyboard users
|
||||
skip_link(),
|
||||
# Sidebar (visible on desktop)
|
||||
rx.box(
|
||||
sidebar(current_page=current_page),
|
||||
display=["none", "none", "block"], # Hide on mobile
|
||||
),
|
||||
# Navbar (visible on mobile)
|
||||
navbar(),
|
||||
# Main content
|
||||
content,
|
||||
)
|
||||
@@ -1,86 +0,0 @@
|
||||
"""
|
||||
Navigation components for the Patient Pathway Analysis tool.
|
||||
|
||||
Provides sidebar navigation items with icons, matching the CustomTkinter design.
|
||||
Includes accessibility features: ARIA labels, keyboard navigation, focus indicators.
|
||||
"""
|
||||
|
||||
import reflex as rx
|
||||
from typing import Callable
|
||||
|
||||
|
||||
def nav_item(
|
||||
text: str,
|
||||
href: str,
|
||||
icon: str,
|
||||
is_active: bool = False,
|
||||
) -> rx.Component:
|
||||
"""
|
||||
Create a navigation item with icon.
|
||||
|
||||
Args:
|
||||
text: The display text for the nav item
|
||||
href: The route to navigate to
|
||||
icon: The Lucide icon name (e.g., "home", "pill", "building", "folder")
|
||||
is_active: Whether this item is currently active
|
||||
|
||||
Returns:
|
||||
A styled navigation button component with accessibility support
|
||||
"""
|
||||
# NHS colors - use blue for active state
|
||||
active_bg = "rgb(0, 94, 184)" # NHS Blue
|
||||
hover_bg = "rgb(0, 48, 135)" # NHS Dark Blue
|
||||
|
||||
return rx.link(
|
||||
rx.hstack(
|
||||
rx.icon(icon, size=20, aria_hidden="true"), # Hide decorative icon from screen readers
|
||||
rx.text(text, size="3", weight="medium"),
|
||||
width="100%",
|
||||
padding="12px 16px",
|
||||
spacing="3",
|
||||
align="center",
|
||||
border_radius="8px",
|
||||
bg=rx.cond(is_active, active_bg, "transparent"),
|
||||
color=rx.cond(is_active, "white", "inherit"),
|
||||
_hover={
|
||||
"background": rx.cond(is_active, active_bg, "rgba(0, 94, 184, 0.1)"),
|
||||
},
|
||||
_focus_visible={
|
||||
"outline": "2px solid rgb(0, 94, 184)",
|
||||
"outline_offset": "2px",
|
||||
},
|
||||
transition="background 0.2s ease",
|
||||
),
|
||||
href=href,
|
||||
text_decoration="none",
|
||||
width="100%",
|
||||
aria_current=rx.cond(is_active, "page", ""),
|
||||
)
|
||||
|
||||
|
||||
def nav_section(title: str, children: list[rx.Component]) -> rx.Component:
|
||||
"""
|
||||
Create a labeled section of navigation items.
|
||||
|
||||
Args:
|
||||
title: Section header text
|
||||
children: List of nav_item components
|
||||
|
||||
Returns:
|
||||
A styled section with header and items
|
||||
"""
|
||||
return rx.vstack(
|
||||
rx.text(
|
||||
title,
|
||||
size="1",
|
||||
weight="bold",
|
||||
color="gray",
|
||||
padding_x="16px",
|
||||
padding_top="16px",
|
||||
padding_bottom="8px",
|
||||
),
|
||||
*children,
|
||||
width="100%",
|
||||
spacing="1",
|
||||
align="start",
|
||||
)
|
||||
File diff suppressed because it is too large
Load Diff
@@ -1,715 +0,0 @@
|
||||
"""
|
||||
Design tokens and style helpers for HCD Analysis v2.1 (SaaS Redesign).
|
||||
|
||||
All visual styling should use these tokens for consistency.
|
||||
Import: from pathways_app.styles import Colors, Spacing, Typography, etc.
|
||||
|
||||
Updated to match DESIGN_SYSTEM.md v2.1 with:
|
||||
- Tighter spacing (25% reduction)
|
||||
- Smaller typography (reduced headline sizes)
|
||||
- Compact component variants for filters/KPIs
|
||||
- Full-width chart support
|
||||
"""
|
||||
|
||||
|
||||
class Colors:
|
||||
"""Color palette from DESIGN_SYSTEM.md"""
|
||||
|
||||
# Primary Blues (NHS-inspired, used sparingly)
|
||||
HERITAGE_BLUE = "#003087" # Top bar background, strong accents
|
||||
PRIMARY = "#0066CC" # Interactive elements, links, focus states
|
||||
VIBRANT = "#1E88E5" # Hover states, active elements
|
||||
SKY = "#4FC3F7" # Subtle accents, progress indicators
|
||||
PALE = "#E3F2FD" # Selected states, subtle backgrounds
|
||||
|
||||
# Neutrals (refined for modern feel)
|
||||
SLATE_900 = "#0F172A" # Primary text (slightly darker)
|
||||
SLATE_700 = "#334155" # Secondary text
|
||||
SLATE_500 = "#64748B" # Muted text, placeholders
|
||||
SLATE_300 = "#CBD5E1" # Borders, dividers
|
||||
SLATE_100 = "#F8FAFC" # Backgrounds (slightly lighter)
|
||||
WHITE = "#FFFFFF" # Card/modal backgrounds
|
||||
|
||||
# Semantic Colors (modernized)
|
||||
SUCCESS = "#10B981" # Positive (modern green)
|
||||
WARNING = "#F59E0B" # Caution
|
||||
ERROR = "#EF4444" # Errors
|
||||
INFO = "#3B82F6" # Informational
|
||||
|
||||
# Chart Palette
|
||||
CHART_SERIES = ["#003087", "#0066CC", "#1E88E5", "#4FC3F7", "#90CAF9"]
|
||||
CHART_CATEGORICAL = ["#0066CC", "#10B981", "#F59E0B", "#8B5CF6", "#EC4899"]
|
||||
|
||||
|
||||
class Typography:
|
||||
"""Typography tokens from DESIGN_SYSTEM.md v2.1 - REDUCED sizes"""
|
||||
|
||||
# Font families
|
||||
FONT_FAMILY = "Inter, system-ui, -apple-system, sans-serif"
|
||||
FONT_MONO = "JetBrains Mono, monospace"
|
||||
|
||||
# Display: Page titles (REDUCED from 32px)
|
||||
DISPLAY_SIZE = "28px"
|
||||
DISPLAY_WEIGHT = "600"
|
||||
DISPLAY_TRACKING = "-0.02em"
|
||||
DISPLAY_LINE_HEIGHT = "1.2"
|
||||
|
||||
# Heading 1: Section headers (REDUCED from 24px)
|
||||
H1_SIZE = "18px"
|
||||
H1_WEIGHT = "600"
|
||||
H1_TRACKING = "-0.01em"
|
||||
H1_LINE_HEIGHT = "1.3"
|
||||
|
||||
# Heading 2: Card titles (REDUCED from 20px)
|
||||
H2_SIZE = "16px"
|
||||
H2_WEIGHT = "600"
|
||||
H2_TRACKING = "normal"
|
||||
H2_LINE_HEIGHT = "1.4"
|
||||
|
||||
# Heading 3: Subsections
|
||||
H3_SIZE = "14px"
|
||||
H3_WEIGHT = "600"
|
||||
H3_TRACKING = "normal"
|
||||
H3_LINE_HEIGHT = "1.4"
|
||||
|
||||
# Body: Default text
|
||||
BODY_SIZE = "14px"
|
||||
BODY_WEIGHT = "400"
|
||||
BODY_LINE_HEIGHT = "1.5"
|
||||
|
||||
# Body Small: Secondary info
|
||||
BODY_SMALL_SIZE = "13px"
|
||||
BODY_SMALL_WEIGHT = "400"
|
||||
BODY_SMALL_LINE_HEIGHT = "1.5"
|
||||
|
||||
# Caption: Labels, metadata (REDUCED from 12px)
|
||||
CAPTION_SIZE = "11px"
|
||||
CAPTION_WEIGHT = "500"
|
||||
CAPTION_LINE_HEIGHT = "1.4"
|
||||
|
||||
# Mono: Data values, codes
|
||||
MONO_SIZE = "13px"
|
||||
MONO_WEIGHT = "500"
|
||||
MONO_LINE_HEIGHT = "1.5"
|
||||
|
||||
|
||||
class Spacing:
|
||||
"""Spacing scale from DESIGN_SYSTEM.md v2.1 - TIGHTER values (~25% reduction)"""
|
||||
|
||||
XS = "4px" # Tight gaps
|
||||
SM = "6px" # Between related elements (was 8px)
|
||||
MD = "8px" # Standard gaps (was 12px)
|
||||
LG = "12px" # Section padding (was 16px)
|
||||
XL = "16px" # Card padding (was 24px)
|
||||
XXL = "24px" # Major gaps (was 32px)
|
||||
XXXL = "32px" # Page margins (was 48px)
|
||||
|
||||
|
||||
class Radii:
|
||||
"""Border radius values from DESIGN_SYSTEM.md"""
|
||||
|
||||
SM = "4px" # Small elements
|
||||
MD = "6px" # Inputs, buttons
|
||||
LG = "8px" # Cards
|
||||
XL = "16px" # Large containers
|
||||
FULL = "9999px" # Pills, badges
|
||||
|
||||
|
||||
class Shadows:
|
||||
"""Shadow values from DESIGN_SYSTEM.md v2.1 - LIGHTER values"""
|
||||
|
||||
SM = "0 1px 2px rgba(0,0,0,0.04)" # Subtle (lighter)
|
||||
MD = "0 1px 3px rgba(0,0,0,0.06)" # Cards at rest
|
||||
LG = "0 4px 8px rgba(0,0,0,0.08)" # Dropdowns, hover
|
||||
XL = "0 10px 15px rgba(0,0,0,0.1)" # Modals, popovers
|
||||
|
||||
|
||||
class Transitions:
|
||||
"""Transition values from DESIGN_SYSTEM.md v2.1 - FASTER (150ms)"""
|
||||
|
||||
DEFAULT = "150ms ease-out"
|
||||
COLOR = "150ms ease-out"
|
||||
TRANSFORM = "150ms ease-out"
|
||||
SHADOW = "150ms ease-out"
|
||||
OPACITY = "150ms ease-in-out"
|
||||
|
||||
|
||||
# ==============================================================================
|
||||
# Layout constants - UPDATED for SaaS redesign
|
||||
# ==============================================================================
|
||||
|
||||
TOP_BAR_HEIGHT = "48px" # Reduced from 64px
|
||||
FILTER_STRIP_HEIGHT = "48px" # Single row filter strip
|
||||
PAGE_MAX_WIDTH = "1600px" # Keep for content areas (not chart)
|
||||
PAGE_PADDING = Spacing.XXXL # 32px
|
||||
|
||||
|
||||
# ==============================================================================
|
||||
# Helper functions for common style patterns
|
||||
# ==============================================================================
|
||||
|
||||
def card_style(hoverable: bool = False) -> dict:
|
||||
"""
|
||||
Card styling following DESIGN_SYSTEM.md specifications.
|
||||
|
||||
- Background: White
|
||||
- Border: 1px Slate 300
|
||||
- Border radius: lg (8px)
|
||||
- Padding: xl (16px - reduced)
|
||||
- Shadow: md at rest, lg on hover
|
||||
"""
|
||||
base_style = {
|
||||
"background_color": Colors.WHITE,
|
||||
"border": f"1px solid {Colors.SLATE_300}",
|
||||
"border_radius": Radii.LG,
|
||||
"padding": Spacing.XL,
|
||||
"box_shadow": Shadows.MD,
|
||||
}
|
||||
|
||||
if hoverable:
|
||||
base_style.update({
|
||||
"transition": f"box-shadow {Transitions.SHADOW}, transform {Transitions.TRANSFORM}",
|
||||
"_hover": {
|
||||
"box_shadow": Shadows.LG,
|
||||
"transform": "translateY(-2px)",
|
||||
}
|
||||
})
|
||||
|
||||
return base_style
|
||||
|
||||
|
||||
def button_primary_style() -> dict:
|
||||
"""
|
||||
Primary button styling following DESIGN_SYSTEM.md specifications.
|
||||
Includes accessible focus ring.
|
||||
"""
|
||||
return {
|
||||
"background_color": Colors.PRIMARY,
|
||||
"color": Colors.WHITE,
|
||||
"border_radius": Radii.MD,
|
||||
"padding": "8px 16px",
|
||||
"font_weight": "500",
|
||||
"font_size": Typography.BODY_SIZE,
|
||||
"cursor": "pointer",
|
||||
"border": "none",
|
||||
"transition": f"background-color {Transitions.COLOR}, transform {Transitions.TRANSFORM}, box-shadow {Transitions.SHADOW}",
|
||||
"_hover": {
|
||||
"background_color": Colors.VIBRANT,
|
||||
"transform": "scale(1.02)",
|
||||
},
|
||||
"_focus": {
|
||||
"outline": "none",
|
||||
"box_shadow": f"0 0 0 2px {Colors.WHITE}, 0 0 0 4px {Colors.PRIMARY}",
|
||||
},
|
||||
"_focus_visible": {
|
||||
"outline": "none",
|
||||
"box_shadow": f"0 0 0 2px {Colors.WHITE}, 0 0 0 4px {Colors.PRIMARY}",
|
||||
},
|
||||
"_active": {
|
||||
"transform": "scale(0.98)",
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
def button_secondary_style() -> dict:
|
||||
"""
|
||||
Secondary button styling following DESIGN_SYSTEM.md specifications.
|
||||
Includes accessible focus ring.
|
||||
"""
|
||||
return {
|
||||
"background_color": Colors.WHITE,
|
||||
"color": Colors.PRIMARY,
|
||||
"border": f"1px solid {Colors.PRIMARY}",
|
||||
"border_radius": Radii.MD,
|
||||
"padding": "8px 16px",
|
||||
"font_weight": "500",
|
||||
"font_size": Typography.BODY_SIZE,
|
||||
"cursor": "pointer",
|
||||
"transition": f"background-color {Transitions.COLOR}, box-shadow {Transitions.SHADOW}",
|
||||
"_hover": {
|
||||
"background_color": Colors.PALE,
|
||||
},
|
||||
"_focus": {
|
||||
"outline": "none",
|
||||
"box_shadow": f"0 0 0 2px {Colors.PALE}",
|
||||
},
|
||||
"_focus_visible": {
|
||||
"outline": "none",
|
||||
"box_shadow": f"0 0 0 2px {Colors.PALE}",
|
||||
},
|
||||
"_active": {
|
||||
"background_color": Colors.SLATE_100,
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
def button_ghost_style() -> dict:
|
||||
"""
|
||||
Ghost button styling following DESIGN_SYSTEM.md specifications.
|
||||
Includes accessible focus ring.
|
||||
"""
|
||||
return {
|
||||
"background_color": "transparent",
|
||||
"color": Colors.PRIMARY,
|
||||
"border": "none",
|
||||
"border_radius": Radii.MD,
|
||||
"padding": "8px 16px",
|
||||
"font_weight": "500",
|
||||
"font_size": Typography.BODY_SIZE,
|
||||
"cursor": "pointer",
|
||||
"transition": f"background-color {Transitions.COLOR}, box-shadow {Transitions.SHADOW}",
|
||||
"_hover": {
|
||||
"background_color": Colors.PALE,
|
||||
},
|
||||
"_focus": {
|
||||
"outline": "none",
|
||||
"box_shadow": f"0 0 0 2px {Colors.PALE}",
|
||||
},
|
||||
"_focus_visible": {
|
||||
"outline": "none",
|
||||
"box_shadow": f"0 0 0 2px {Colors.PALE}",
|
||||
},
|
||||
"_active": {
|
||||
"background_color": Colors.SLATE_100,
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
def input_style() -> dict:
|
||||
"""
|
||||
Form input styling following DESIGN_SYSTEM.md specifications.
|
||||
"""
|
||||
return {
|
||||
"height": "32px",
|
||||
"border": f"1px solid {Colors.SLATE_300}",
|
||||
"border_radius": Radii.MD,
|
||||
"padding": f"0 {Spacing.MD}",
|
||||
"font_size": Typography.BODY_SMALL_SIZE,
|
||||
"font_family": Typography.FONT_FAMILY,
|
||||
"color": Colors.SLATE_900,
|
||||
"background_color": Colors.WHITE,
|
||||
"transition": f"border-color {Transitions.COLOR}, box-shadow {Transitions.COLOR}",
|
||||
"_placeholder": {
|
||||
"color": Colors.SLATE_500,
|
||||
},
|
||||
"_focus": {
|
||||
"outline": "none",
|
||||
"border_color": Colors.PRIMARY,
|
||||
"box_shadow": f"0 0 0 2px {Colors.PALE}",
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
# ==============================================================================
|
||||
# KPI Card styles - COMPACT variants for v2.1
|
||||
# ==============================================================================
|
||||
|
||||
def kpi_card_style() -> dict:
|
||||
"""
|
||||
Standard KPI card styling (legacy, larger).
|
||||
"""
|
||||
return {
|
||||
"background_color": Colors.WHITE,
|
||||
"border": f"1px solid {Colors.SLATE_300}",
|
||||
"border_radius": Radii.LG,
|
||||
"padding": Spacing.XL,
|
||||
"box_shadow": Shadows.SM,
|
||||
"text_align": "center",
|
||||
}
|
||||
|
||||
|
||||
def kpi_value_style() -> dict:
|
||||
"""Style for the large number in a KPI card (legacy)."""
|
||||
return {
|
||||
"font_family": Typography.FONT_MONO,
|
||||
"font_size": "32px",
|
||||
"font_weight": "600",
|
||||
"color": Colors.SLATE_900,
|
||||
"line_height": "1.2",
|
||||
}
|
||||
|
||||
|
||||
def kpi_label_style() -> dict:
|
||||
"""Style for the label in a KPI card (legacy)."""
|
||||
return {
|
||||
"font_size": Typography.CAPTION_SIZE,
|
||||
"font_weight": Typography.CAPTION_WEIGHT,
|
||||
"color": Colors.SLATE_500,
|
||||
"margin_top": Spacing.SM,
|
||||
}
|
||||
|
||||
|
||||
def kpi_badge_style() -> dict:
|
||||
"""
|
||||
KPI as inline pill/badge (Option A from design system).
|
||||
Zero extra height - embeds in filter row.
|
||||
|
||||
Example: "12,345 patients"
|
||||
Includes subtle hover state for interactivity feedback.
|
||||
"""
|
||||
return {
|
||||
"display": "inline-flex",
|
||||
"align_items": "center",
|
||||
"gap": Spacing.XS,
|
||||
"padding": f"{Spacing.XS} {Spacing.LG}", # 4px 12px
|
||||
"background_color": Colors.SLATE_100,
|
||||
"border_radius": Radii.FULL, # Pill shape
|
||||
"transition": f"transform {Transitions.TRANSFORM}, box-shadow {Transitions.SHADOW}",
|
||||
"cursor": "default",
|
||||
"_hover": {
|
||||
"transform": "translateY(-1px)",
|
||||
"box_shadow": Shadows.SM,
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
def kpi_badge_value_style() -> dict:
|
||||
"""Style for value text in KPI badge."""
|
||||
return {
|
||||
"font_family": Typography.FONT_MONO,
|
||||
"font_size": "14px",
|
||||
"font_weight": "600",
|
||||
"color": Colors.SLATE_900,
|
||||
}
|
||||
|
||||
|
||||
def kpi_badge_label_style() -> dict:
|
||||
"""Style for label text in KPI badge."""
|
||||
return {
|
||||
"font_size": Typography.CAPTION_SIZE,
|
||||
"font_weight": "400",
|
||||
"color": Colors.SLATE_500,
|
||||
}
|
||||
|
||||
|
||||
# ==============================================================================
|
||||
# Filter strip styles - NEW for v2.1 redesign
|
||||
# ==============================================================================
|
||||
|
||||
def filter_strip_style() -> dict:
|
||||
"""
|
||||
Horizontal single-row filter container style.
|
||||
|
||||
- Height: 48px
|
||||
- All filters inline
|
||||
- Slate 100 background (or transparent)
|
||||
"""
|
||||
return {
|
||||
"display": "flex",
|
||||
"align_items": "center",
|
||||
"height": FILTER_STRIP_HEIGHT,
|
||||
"gap": Spacing.LG, # 12px between filter groups
|
||||
"padding": f"0 {Spacing.XL}", # 16px horizontal padding
|
||||
"background_color": Colors.SLATE_100,
|
||||
"border_bottom": f"1px solid {Colors.SLATE_300}",
|
||||
"width": "100%",
|
||||
}
|
||||
|
||||
|
||||
def compact_dropdown_trigger_style() -> dict:
|
||||
"""
|
||||
Compact dropdown trigger for filter strip.
|
||||
|
||||
- Height: 32px
|
||||
- Padding: 8px 12px
|
||||
- Smaller font: 13px
|
||||
- Accessible focus ring
|
||||
"""
|
||||
return {
|
||||
"height": "32px",
|
||||
"padding": f"{Spacing.MD} {Spacing.LG}", # 8px 12px
|
||||
"border": f"1px solid {Colors.SLATE_300}",
|
||||
"border_radius": Radii.MD,
|
||||
"font_size": Typography.BODY_SMALL_SIZE, # 13px
|
||||
"font_family": Typography.FONT_FAMILY,
|
||||
"color": Colors.SLATE_900,
|
||||
"background_color": Colors.WHITE,
|
||||
"cursor": "pointer",
|
||||
"display": "flex",
|
||||
"align_items": "center",
|
||||
"gap": Spacing.SM,
|
||||
"transition": f"border-color {Transitions.COLOR}, box-shadow {Transitions.SHADOW}",
|
||||
"_hover": {
|
||||
"border_color": Colors.PRIMARY,
|
||||
"background_color": Colors.SLATE_100,
|
||||
},
|
||||
"_focus": {
|
||||
"outline": "none",
|
||||
"border_color": Colors.PRIMARY,
|
||||
"box_shadow": f"0 0 0 2px {Colors.PALE}",
|
||||
},
|
||||
"_focus_visible": {
|
||||
"outline": "none",
|
||||
"border_color": Colors.PRIMARY,
|
||||
"box_shadow": f"0 0 0 2px {Colors.PALE}",
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
def searchable_dropdown_panel_style() -> dict:
|
||||
"""
|
||||
Dropdown panel for searchable multi-select.
|
||||
|
||||
- Max height: 200px for items
|
||||
- Compact item spacing
|
||||
"""
|
||||
return {
|
||||
"background_color": Colors.WHITE,
|
||||
"border": f"1px solid {Colors.SLATE_300}",
|
||||
"border_radius": Radii.LG,
|
||||
"box_shadow": Shadows.LG,
|
||||
"min_width": "240px",
|
||||
"max_width": "320px",
|
||||
"z_index": "50",
|
||||
"overflow": "hidden",
|
||||
}
|
||||
|
||||
|
||||
def searchable_dropdown_item_style(selected: bool = False) -> dict:
|
||||
"""
|
||||
Individual item in searchable dropdown.
|
||||
|
||||
- Tighter padding: 6px 8px
|
||||
- Visual selected state
|
||||
- Accessible focus state
|
||||
"""
|
||||
base = {
|
||||
"padding": f"{Spacing.SM} {Spacing.MD}", # 6px 8px
|
||||
"font_size": Typography.BODY_SMALL_SIZE,
|
||||
"cursor": "pointer",
|
||||
"display": "flex",
|
||||
"align_items": "center",
|
||||
"gap": Spacing.SM,
|
||||
"transition": f"background-color {Transitions.COLOR}",
|
||||
"border_radius": Radii.SM, # Slight rounding for focus state
|
||||
"_focus": {
|
||||
"outline": "none",
|
||||
"background_color": Colors.SLATE_100,
|
||||
"box_shadow": f"inset 0 0 0 1px {Colors.PRIMARY}",
|
||||
},
|
||||
}
|
||||
|
||||
if selected:
|
||||
base.update({
|
||||
"background_color": Colors.PALE,
|
||||
"color": Colors.PRIMARY,
|
||||
"_hover": {
|
||||
"background_color": Colors.PALE,
|
||||
},
|
||||
})
|
||||
else:
|
||||
base.update({
|
||||
"background_color": Colors.WHITE,
|
||||
"color": Colors.SLATE_900,
|
||||
"_hover": {
|
||||
"background_color": Colors.SLATE_100,
|
||||
},
|
||||
})
|
||||
|
||||
return base
|
||||
|
||||
|
||||
# ==============================================================================
|
||||
# Chart container styles - NEW for v2.1 redesign
|
||||
# ==============================================================================
|
||||
|
||||
def chart_container_style() -> dict:
|
||||
"""
|
||||
Full-width, flex-grow chart wrapper.
|
||||
|
||||
- Width: full viewport minus padding (16px each side)
|
||||
- Height: fills remaining space (min 500px)
|
||||
- No max-width constraint
|
||||
"""
|
||||
return {
|
||||
"width": "100%",
|
||||
"padding": f"0 {Spacing.XL}", # 16px horizontal padding
|
||||
"flex": "1",
|
||||
"min_height": "500px",
|
||||
"display": "flex",
|
||||
"flex_direction": "column",
|
||||
}
|
||||
|
||||
|
||||
def chart_wrapper_style(overhead_height: str = "96px") -> dict:
|
||||
"""
|
||||
Inner chart wrapper with calculated height.
|
||||
|
||||
Args:
|
||||
overhead_height: Total height of fixed elements above chart
|
||||
(top bar + filter strip = 48px + 48px = 96px default)
|
||||
"""
|
||||
return {
|
||||
"width": "100%",
|
||||
"height": f"calc(100vh - {overhead_height})",
|
||||
"min_height": "500px",
|
||||
}
|
||||
|
||||
|
||||
# ==============================================================================
|
||||
# Typography helper functions
|
||||
# ==============================================================================
|
||||
|
||||
def text_display() -> dict:
|
||||
"""Display text style for page titles."""
|
||||
return {
|
||||
"font_size": Typography.DISPLAY_SIZE,
|
||||
"font_weight": Typography.DISPLAY_WEIGHT,
|
||||
"letter_spacing": Typography.DISPLAY_TRACKING,
|
||||
"line_height": Typography.DISPLAY_LINE_HEIGHT,
|
||||
"color": Colors.SLATE_900,
|
||||
"font_family": Typography.FONT_FAMILY,
|
||||
}
|
||||
|
||||
|
||||
def text_h1() -> dict:
|
||||
"""Heading 1 style for section headers."""
|
||||
return {
|
||||
"font_size": Typography.H1_SIZE,
|
||||
"font_weight": Typography.H1_WEIGHT,
|
||||
"letter_spacing": Typography.H1_TRACKING,
|
||||
"line_height": Typography.H1_LINE_HEIGHT,
|
||||
"color": Colors.SLATE_900,
|
||||
"font_family": Typography.FONT_FAMILY,
|
||||
}
|
||||
|
||||
|
||||
def text_h2() -> dict:
|
||||
"""Heading 2 style for card titles."""
|
||||
return {
|
||||
"font_size": Typography.H2_SIZE,
|
||||
"font_weight": Typography.H2_WEIGHT,
|
||||
"letter_spacing": Typography.H2_TRACKING,
|
||||
"line_height": Typography.H2_LINE_HEIGHT,
|
||||
"color": Colors.SLATE_900,
|
||||
"font_family": Typography.FONT_FAMILY,
|
||||
}
|
||||
|
||||
|
||||
def text_h3() -> dict:
|
||||
"""Heading 3 style for subsections."""
|
||||
return {
|
||||
"font_size": Typography.H3_SIZE,
|
||||
"font_weight": Typography.H3_WEIGHT,
|
||||
"letter_spacing": Typography.H3_TRACKING,
|
||||
"line_height": Typography.H3_LINE_HEIGHT,
|
||||
"color": Colors.SLATE_900,
|
||||
"font_family": Typography.FONT_FAMILY,
|
||||
}
|
||||
|
||||
|
||||
def text_body() -> dict:
|
||||
"""Default body text style."""
|
||||
return {
|
||||
"font_size": Typography.BODY_SIZE,
|
||||
"font_weight": Typography.BODY_WEIGHT,
|
||||
"line_height": Typography.BODY_LINE_HEIGHT,
|
||||
"color": Colors.SLATE_900,
|
||||
"font_family": Typography.FONT_FAMILY,
|
||||
}
|
||||
|
||||
|
||||
def text_body_small() -> dict:
|
||||
"""Secondary/small body text style."""
|
||||
return {
|
||||
"font_size": Typography.BODY_SMALL_SIZE,
|
||||
"font_weight": Typography.BODY_SMALL_WEIGHT,
|
||||
"line_height": Typography.BODY_SMALL_LINE_HEIGHT,
|
||||
"color": Colors.SLATE_700,
|
||||
"font_family": Typography.FONT_FAMILY,
|
||||
}
|
||||
|
||||
|
||||
def text_caption() -> dict:
|
||||
"""Caption style for labels and metadata."""
|
||||
return {
|
||||
"font_size": Typography.CAPTION_SIZE,
|
||||
"font_weight": Typography.CAPTION_WEIGHT,
|
||||
"line_height": Typography.CAPTION_LINE_HEIGHT,
|
||||
"color": Colors.SLATE_500,
|
||||
"font_family": Typography.FONT_FAMILY,
|
||||
}
|
||||
|
||||
|
||||
def text_mono() -> dict:
|
||||
"""Monospace text style for data values and codes."""
|
||||
return {
|
||||
"font_size": Typography.MONO_SIZE,
|
||||
"font_weight": Typography.MONO_WEIGHT,
|
||||
"line_height": Typography.MONO_LINE_HEIGHT,
|
||||
"color": Colors.SLATE_900,
|
||||
"font_family": Typography.FONT_MONO,
|
||||
}
|
||||
|
||||
|
||||
# ==============================================================================
|
||||
# Top bar styles - NEW for v2.1 redesign
|
||||
# ==============================================================================
|
||||
|
||||
def top_bar_style() -> dict:
|
||||
"""
|
||||
Top bar container style.
|
||||
|
||||
- Height: 48px (reduced from 64px)
|
||||
- Heritage Blue background
|
||||
"""
|
||||
return {
|
||||
"height": TOP_BAR_HEIGHT,
|
||||
"background_color": Colors.HERITAGE_BLUE,
|
||||
"display": "flex",
|
||||
"align_items": "center",
|
||||
"justify_content": "space_between",
|
||||
"padding": f"0 {Spacing.XL}",
|
||||
"width": "100%",
|
||||
}
|
||||
|
||||
|
||||
def top_bar_tab_style(active: bool = False) -> dict:
|
||||
"""
|
||||
Tab/pill style for top bar navigation.
|
||||
|
||||
- Height: 28px
|
||||
- Smaller pills
|
||||
- Accessible focus ring
|
||||
"""
|
||||
base = {
|
||||
"height": "28px",
|
||||
"padding": f"{Spacing.XS} {Spacing.LG}", # 4px 12px
|
||||
"border_radius": Radii.MD,
|
||||
"font_size": Typography.BODY_SMALL_SIZE,
|
||||
"font_weight": "500",
|
||||
"cursor": "pointer",
|
||||
"transition": f"background-color {Transitions.COLOR}, box-shadow {Transitions.SHADOW}",
|
||||
"_focus": {
|
||||
"outline": "none",
|
||||
"box_shadow": f"0 0 0 2px rgba(255,255,255,0.4)",
|
||||
},
|
||||
"_focus_visible": {
|
||||
"outline": "none",
|
||||
"box_shadow": f"0 0 0 2px rgba(255,255,255,0.4)",
|
||||
},
|
||||
}
|
||||
|
||||
if active:
|
||||
base.update({
|
||||
"background_color": Colors.WHITE,
|
||||
"color": Colors.HERITAGE_BLUE,
|
||||
})
|
||||
else:
|
||||
base.update({
|
||||
"background_color": "transparent",
|
||||
"color": Colors.WHITE,
|
||||
"_hover": {
|
||||
"background_color": "rgba(255,255,255,0.15)",
|
||||
}
|
||||
})
|
||||
|
||||
return base
|
||||
|
||||
|
||||
def logo_style() -> dict:
|
||||
"""Logo style for top bar - 28px height (reduced from 36px)."""
|
||||
return {
|
||||
"height": "28px",
|
||||
"width": "auto",
|
||||
}
|
||||
File diff suppressed because one or more lines are too long
@@ -1,14 +0,0 @@
|
||||
import sys
|
||||
from pathlib import Path
|
||||
|
||||
sys.path.insert(0, str(Path(__file__).parent / "src"))
|
||||
|
||||
import reflex as rx
|
||||
|
||||
config = rx.Config(
|
||||
app_name="pathways_app",
|
||||
plugins=[
|
||||
rx.plugins.SitemapPlugin(),
|
||||
rx.plugins.TailwindV4Plugin(),
|
||||
]
|
||||
)
|
||||
@@ -1,186 +0,0 @@
|
||||
-- NICE TA Indication SNOMED Mapping Query (v2 - optimized clusters)
|
||||
-- Excludes overly broad clusters (GDPPR_COD, GDPPR2YR_COD)
|
||||
|
||||
WITH SearchTermClusters AS (
|
||||
SELECT Search_Term, Cluster_ID FROM (VALUES
|
||||
('acute lymphoblastic leukaemia', 'HAEMCANMORPH_COD'),
|
||||
('acute myeloid leukaemia', 'C19HAEMCAN_COD'),
|
||||
('acute promyelocytic leukaemia', 'HAEMCANMORPH_COD'),
|
||||
('allergic asthma', 'AST_COD'),
|
||||
('allergic rhinitis', 'MILDINTAST_COD'),
|
||||
('alzheimer''s disease', 'DEMALZ_COD'),
|
||||
('amyloidosis', 'AMYLOID_COD'),
|
||||
('anaemia', 'eFI2_AnaemiaTimeSensitive'),
|
||||
('anaplastic large cell lymphoma', 'C19HAEMCAN_COD'),
|
||||
('apixaban', 'DOACCON_COD'),
|
||||
('aplastic anaemia', 'eFI2_AnaemiaEver'),
|
||||
('arthritis', 'eFI2_InflammatoryArthritis'),
|
||||
('asthma', 'eFI2_Asthma'),
|
||||
('atopic dermatitis', 'ATOPDERM_COD'),
|
||||
('atrial fibrillation', 'eFI2_AtrialFibrillation'),
|
||||
('attention deficit hyperactivity disorder', 'ADHD_COD'),
|
||||
('bipolar disorder', 'MH_COD'),
|
||||
('bladder', 'eFI2_UrinaryIncontinence'),
|
||||
('breast cancer', 'BRCANSCR_COD'),
|
||||
('cardiomyopathy', 'eFI2_HarmfulDrinking'),
|
||||
('cardiovascular disease', 'CVDRISKASS_COD'),
|
||||
('cervical cancer', 'CSDEC_COD'),
|
||||
('cholangiocarcinoma', 'eFI2_Cancer'),
|
||||
('chronic kidney disease', 'CKD_COD'),
|
||||
('chronic liver disease', 'eFI2_LiverProblems'),
|
||||
('chronic lymphocytic leukaemia', 'EPPHAEMCAN_COD'),
|
||||
('chronic myeloid leukaemia', 'EPPHAEMCAN_COD'),
|
||||
('chronic obstructive pulmonary disease', 'eFI2_COPD'),
|
||||
('colon cancer', 'eFI2_Cancer'),
|
||||
('colorectal cancer', 'GICANREF_COD'),
|
||||
('constipation', 'CHRONCONSTIP_COD'),
|
||||
('covid-19', 'POSSPOSTCOVID_COD'),
|
||||
('crohn''s disease', 'eFI2_InflammatoryBowelDisease'),
|
||||
('cutaneous t-cell lymphoma', 'C19HAEMCAN_COD'),
|
||||
('cystic fibrosis', 'CUST_ICB_CYSTIC_FIBROSIS'),
|
||||
('deep vein thrombosis', 'VTE_COD'),
|
||||
('depression', 'eFI2_Depression'),
|
||||
('diabetes', 'eFI2_DiabetesEver'),
|
||||
('diabetic retinopathy', 'DRSELIGIBILITY_COD'),
|
||||
('diffuse large b-cell lymphoma', 'C19HAEMCAN_COD'),
|
||||
('dravet syndrome', 'EPIL_COD'),
|
||||
('drug misuse', 'ILLSUBINT_COD'),
|
||||
('dyspepsia', 'eFI2_AbdominalPain'),
|
||||
('epilepsy', 'eFI2_Seizures'),
|
||||
('fallopian tube', 'STERIL_COD'),
|
||||
('follicular lymphoma', 'C19HAEMCAN_COD'),
|
||||
('gastric cancer', 'eFI2_Cancer'),
|
||||
('giant cell arteritis', 'GCA_COD'),
|
||||
('glioma', 'NHAEMCANMORPH_COD'),
|
||||
('gout', 'eFI2_InflammatoryArthritis'),
|
||||
('graft versus host disease', 'GVHD_COD'),
|
||||
('granulomatosis with polyangiitis', 'WEGENERVASC_COD'),
|
||||
('growth hormone deficiency', 'HYPOPITUITARY_COD'),
|
||||
('hand eczema', 'ECZEMA_COD'),
|
||||
('heart failure', 'eFI2_HeartFailure'),
|
||||
('hepatitis b', 'HEPBCVAC_COD'),
|
||||
('hepatocellular carcinoma', 'eFI2_Cancer'),
|
||||
('hiv', 'PREFLANG_COD'),
|
||||
('hodgkin lymphoma', 'HAEMCANMORPH_COD'),
|
||||
('hormone receptor', 'eFI2_ThyroidProblems'),
|
||||
('hypercholesterolaemia', 'CLASSFH_COD'),
|
||||
('immune thrombocytopenia', 'ITP_COD'),
|
||||
('influenza', 'FLUINVITE_COD'),
|
||||
('insomnia', 'eFI2_SleepProblems'),
|
||||
('irritable bowel syndrome', 'IBS_COD'),
|
||||
('ischaemic stroke', 'OSTR_COD'),
|
||||
('juvenile idiopathic arthritis', 'RARTHAD_COD'),
|
||||
('kidney transplant', 'RENALTRANSP_COD'),
|
||||
('leukaemia', 'eFI2_Cancer'),
|
||||
('lung cancer', 'FTCANREF_COD'),
|
||||
('lymphoma', 'C19HAEMCAN_COD'),
|
||||
('macular degeneration', 'CUST_ICB_VISUAL_IMPAIRMENT'),
|
||||
('macular oedema', 'CUST_ICB_VISUAL_IMPAIRMENT'),
|
||||
('major depressive episodes', 'eFI2_Depression'),
|
||||
('malignant melanoma', 'eFI2_Cancer'),
|
||||
('malignant pleural mesothelioma', 'LUNGCAN_COD'),
|
||||
('manic episode', 'MH_COD'),
|
||||
('mantle cell lymphoma', 'HAEMCANMORPH_COD'),
|
||||
('melanoma', 'eFI2_Cancer'),
|
||||
('merkel cell carcinoma', 'C19CAN_COD'),
|
||||
('migraine', 'eFI2_Headache'),
|
||||
('motor neurone disease', 'MND_COD'),
|
||||
('multiple myeloma', 'C19HAEMCAN_COD'),
|
||||
('multiple sclerosis', 'MS_COD'),
|
||||
('myelodysplastic', 'eFI2_AnaemiaEver'),
|
||||
('myelofibrosis', 'MDS_COD'),
|
||||
('myocardial infarction', 'eFI2_IschaemicHeartDisease'),
|
||||
('myotonia', 'CNDATRISK2_COD'),
|
||||
('narcolepsy', 'LD_COD'),
|
||||
('neuroendocrine tumour', 'LUNGCAN_COD'),
|
||||
('non-small cell lung cancer', 'LUNGCAN_COD'),
|
||||
('non-small-cell lung cancer', 'FTCANREF_COD'),
|
||||
('obesity', 'BMI30_COD'),
|
||||
('osteoarthritis', 'CUST_ICB_OSTEOARTHRITIS'),
|
||||
('osteoporosis', 'eFI2_Osteoporosis'),
|
||||
('osteosarcoma', 'NHAEMCANMORPH_COD'),
|
||||
('ovarian cancer', 'C19CAN_COD'),
|
||||
('peripheral arterial disease', 'PADEXC_COD'),
|
||||
('plaque psoriasis', 'PSORIASIS_COD'),
|
||||
('polycystic kidney disease', 'EPPCONGMALF_COD'),
|
||||
('polycythaemia vera', 'C19HAEMCAN_COD'),
|
||||
('pregnancy', 'C19PREG_COD'),
|
||||
('primary biliary cholangitis', 'eFI2_LiverProblems'),
|
||||
('primary hypercholesterolaemia', 'FNFHYP_COD'),
|
||||
('prostate cancer', 'EPPSOLIDCAN_COD'),
|
||||
('psoriasis', 'PSORIASIS_COD'),
|
||||
('psoriatic arthritis', 'RARTHAD_COD'),
|
||||
('pulmonary embolism', 'eFI2_RespiratoryDiseaseTimeSensitive'),
|
||||
('pulmonary fibrosis', 'ILD_COD'),
|
||||
('relapsing multiple sclerosis', 'MS_COD'),
|
||||
('renal cell carcinoma', 'C19CAN_COD'),
|
||||
('renal transplantation', 'RENALTRANSP_COD'),
|
||||
('retinal vein occlusion', 'CUST_ICB_VISUAL_IMPAIRMENT'),
|
||||
('rheumatoid arthritis', 'eFI2_InflammatoryArthritis'),
|
||||
('rivaroxaban', 'DOACCON_COD'),
|
||||
('schizophrenia', 'MH_COD'),
|
||||
('seizures', 'LSZFREQ_COD'),
|
||||
('sepsis', 'C19ACTIVITY_COD'),
|
||||
('severe persistent allergic asthma', 'SEVAST_COD'),
|
||||
('sickle cell disease', 'SICKLE_COD'),
|
||||
('sleep apnoea', 'CUST_ICB_NON_SEVERE_LDA'),
|
||||
('smoking cessation', 'SMOKINGINT_COD'),
|
||||
('soft tissue sarcoma', 'NHAEMCANMORPH_COD'),
|
||||
('spinal muscular atrophy', 'MND_COD'),
|
||||
('squamous cell', 'C19CAN_COD'),
|
||||
('squamous cell carcinoma', 'C19CAN_COD'),
|
||||
('stem cell transplant', 'ALLOTRANSP_COD'),
|
||||
('stroke', 'eFI2_Stroke'),
|
||||
('systemic lupus erythematosus', 'SLUPUS_COD'),
|
||||
('systemic mastocytosis', 'HAEMCANMORPH_COD'),
|
||||
('thrombocytopenic purpura', 'TTP_COD'),
|
||||
('thrombotic thrombocytopenic purpura', 'TTP_COD'),
|
||||
('thyroid cancer', 'C19CAN_COD'),
|
||||
('tophaceous gout', 'CUST_ICB_OSTEOARTHRITIS'),
|
||||
('transitional cell carcinoma', 'C19CAN_COD'),
|
||||
('type 1 diabetes', 'DMTYPE1_COD'),
|
||||
('type 2 diabetes', 'DMTYPE2_COD'),
|
||||
('ulcerative colitis', 'eFI2_InflammatoryBowelDisease'),
|
||||
('urothelial carcinoma', 'NHAEMCANMORPH_COD'),
|
||||
('urticaria', 'XSAL_COD'),
|
||||
('uveitis', 'CUST_ICB_VISUAL_IMPAIRMENT'),
|
||||
('vascular disease', 'CVDINVITE_COD'),
|
||||
('vasculitis', 'CRYOGLOBVASC_COD')
|
||||
) AS t(Search_Term, Cluster_ID)
|
||||
),
|
||||
|
||||
ClusterCodes AS (
|
||||
SELECT
|
||||
stc.Search_Term,
|
||||
c."SNOMEDCode",
|
||||
c."SNOMEDDescription"
|
||||
FROM SearchTermClusters stc
|
||||
JOIN DATA_HUB.PHM."ClinicalCodingClusterSnomedCodes" c
|
||||
ON stc.Cluster_ID = c."Cluster_ID"
|
||||
WHERE c."SNOMEDCode" IS NOT NULL
|
||||
),
|
||||
|
||||
ExplicitCodes AS (
|
||||
SELECT Search_Term, SNOMEDCode, SNOMEDDescription FROM (VALUES
|
||||
('acute coronary syndrome', '837091000000100', 'Manual mapping'),
|
||||
('ankylosing spondylitis', '162930007', 'Manual mapping'),
|
||||
('ankylosing spondylitis', '239805001', 'Manual mapping'),
|
||||
('ankylosing spondylitis', '239810002', 'Manual mapping'),
|
||||
('ankylosing spondylitis', '239811003', 'Manual mapping'),
|
||||
('ankylosing spondylitis', '394990003', 'Manual mapping'),
|
||||
('ankylosing spondylitis', '429712009', 'Manual mapping'),
|
||||
('ankylosing spondylitis', '441562009', 'Manual mapping'),
|
||||
('ankylosing spondylitis', '441680005', 'Manual mapping'),
|
||||
('ankylosing spondylitis', '441930001', 'Manual mapping'),
|
||||
('axial spondyloarthritis', '723116002', 'Manual mapping'),
|
||||
('choroidal neovascularisation', '380621000000102', 'Manual mapping'),
|
||||
('choroidal neovascularisation', '733124000', 'Manual mapping')
|
||||
) AS t(Search_Term, SNOMEDCode, SNOMEDDescription)
|
||||
)
|
||||
|
||||
SELECT Search_Term, "SNOMEDCode" AS SNOMEDCode, "SNOMEDDescription" AS SNOMEDDescription
|
||||
FROM ClusterCodes
|
||||
UNION ALL
|
||||
SELECT Search_Term, SNOMEDCode, SNOMEDDescription
|
||||
FROM ExplicitCodes
|
||||
ORDER BY Search_Term, SNOMEDCode;
|
||||
Binary file not shown.
-154
@@ -1,154 +0,0 @@
|
||||
# Guardrails
|
||||
|
||||
Known failure patterns. Read EVERY iteration. Follow ALL of these rules.
|
||||
If you discover a new failure pattern during your work, add it to this file.
|
||||
|
||||
---
|
||||
|
||||
## Backend Isolation
|
||||
|
||||
### Do NOT modify pipeline/analysis logic in src/
|
||||
- **When**: Improving charts or adding analytics
|
||||
- **Rule**: Do NOT change the logic in these files — they are the data pipeline and must stay as-is:
|
||||
- `data_processing/pathway_pipeline.py`, `transforms.py`, `diagnosis_lookup.py` (matching/query logic)
|
||||
- `analysis/pathway_analyzer.py`, `statistics.py`
|
||||
- `cli/refresh_pathways.py`
|
||||
- `data_processing/schema.py`, `reference_data.py`, `cache.py`, `data_source.py`
|
||||
- **Why**: The pipeline is complete and tested. Changing it risks breaking the data refresh workflow.
|
||||
|
||||
### DO use shared utilities in src/ rather than duplicating
|
||||
- **When**: Adding chart functions or query functions
|
||||
- **Rule**: Chart figure functions go in `src/visualization/plotly_generator.py`. Query functions go in `src/data_processing/pathway_queries.py`. Dash callbacks should CALL INTO `src/`, not duplicate the code.
|
||||
- **Why**: Duplicating SQL queries and figure logic creates copies that drift apart.
|
||||
|
||||
### Do NOT modify pathways.db schema or data from Dash callbacks
|
||||
- **When**: Querying the database from Dash callbacks
|
||||
- **Rule**: Read-only access from Dash. Use `sqlite3.connect(db_path)` with SELECT queries only. Never INSERT, UPDATE, DELETE, or ALTER from the Dash app.
|
||||
- **Exception**: The standalone `cli/compute_trends.py` script may CREATE and INSERT into the `pathway_trends` table. This is a separate CLI command, not part of the Dash app or the main refresh pipeline.
|
||||
- **Why**: pathways.db is populated by CLI commands. The Dash app is a read-only consumer.
|
||||
|
||||
### Trend computation uses existing pipeline functions as-is
|
||||
- **When**: Building `cli/compute_trends.py`
|
||||
- **Rule**: Import and call `fetch_and_transform_data()` and `process_pathway_for_date_filter()` from `pathway_pipeline.py`. Do NOT modify these functions. Do NOT modify `schema.py`, `reference_data.py`, or `refresh_pathways.py`. The new script creates its own table via `CREATE TABLE IF NOT EXISTS`.
|
||||
- **Why**: The historical snapshot approach works by calling existing functions with different `max_date` values. No pipeline changes needed.
|
||||
|
||||
---
|
||||
|
||||
## Chart Generation (plotly_generator.py)
|
||||
|
||||
### Use _base_layout() for all chart functions
|
||||
- **When**: Modifying or creating any chart function after Task A.1
|
||||
- **Rule**: Call `_base_layout(title)` to get shared layout properties, then update with chart-specific overrides. Do NOT hardcode font family, title font size, bgcolor, hoverlabel, or autosize in individual functions.
|
||||
- **Why**: DRY principle. Inconsistent styling was a bug category (Tier 2 fix).
|
||||
|
||||
### Use module-level palette constants
|
||||
- **When**: Assigning colors to traces in any chart function
|
||||
- **Rule**: Use `TRUST_PALETTE` (7 colors) for trust-comparison charts where bars/traces represent trusts. Use `DRUG_PALETTE` (15 colors) for charts where bars/traces represent drugs. Do NOT define local `nhs_colours` lists.
|
||||
- **Why**: Local blue-heavy palettes made trusts indistinguishable (a reported bug).
|
||||
|
||||
### Heatmaps must have cell text annotations
|
||||
- **When**: Modifying `create_heatmap_figure()` or `create_trust_heatmap_figure()`
|
||||
- **Rule**: Always include `text=text_values, texttemplate="%{text}"` on the heatmap trace. Format text per metric: patients → `"N"`, cost → `"£Nk"`, cost_pp_pa → `"£N"`.
|
||||
- **Why**: Without cell text, users must hover every cell to read values — a reported usability bug.
|
||||
|
||||
### Heatmaps must use linear colorscale
|
||||
- **When**: Setting colorscale on heatmap traces
|
||||
- **Rule**: Use linear 5-stop colorscale: `[0.0 #E3F2FD, 0.25 #90CAF9, 0.5 #42A5F5, 0.75 #1E88E5, 1.0 #003087]`. Always set `zmin=0`. Do NOT use non-linear stops like `[0.01, 0.1, 0.3, ...]`.
|
||||
- **Why**: Non-linear stops compressed 99% of the value range into identical blues.
|
||||
|
||||
### Charts must use autosize, not fixed width
|
||||
- **When**: Setting chart dimensions
|
||||
- **Rule**: Use `autosize=True` instead of explicit `width=...`. Dynamic height is fine (calculated from data). Use `yaxis automargin=True` instead of fixed left margins.
|
||||
- **Why**: Fixed widths overflow their containers on different screen sizes.
|
||||
|
||||
### Legends must adapt to item count
|
||||
- **When**: Setting legend layout on charts with variable trace counts
|
||||
- **Rule**: Use `_smart_legend(n_items)` helper (once created in Task A.3). >15 items = vertical right legend. ≤15 items = horizontal with dynamic bottom margin.
|
||||
- **Why**: Horizontal legends with 42 drugs wrap 5+ rows and overlap chart content.
|
||||
|
||||
---
|
||||
|
||||
## Callback Architecture
|
||||
|
||||
### No circular callback dependencies
|
||||
- **When**: Writing Dash callbacks
|
||||
- **Rule**: Callbacks must flow unidirectionally: filter inputs → `app-state` store → `chart-data` store → UI components. Never have a component that is both Input and Output in the same callback chain without an intermediate store.
|
||||
- **Why**: Dash raises `DuplicateCallback` errors for circular dependencies.
|
||||
|
||||
### Use dcc.Store for all state, not server-side globals
|
||||
- **When**: Managing application state
|
||||
- **Rule**: ALL state lives in `dcc.Store` components. Never use module-level globals or class variables for state. The 4 stores: `app-state` (session), `chart-data` (memory), `reference-data` (session), `active-tab` (memory).
|
||||
- **Why**: Dash is stateless per request. Server-side state breaks with multiple users.
|
||||
|
||||
### Only render the active tab's chart
|
||||
- **When**: Building tab switching or chart rendering callbacks
|
||||
- **Rule**: Check `active-tab` store and ONLY compute the figure for the active tab. Return `no_update` or placeholder for inactive tabs.
|
||||
- **Why**: Computing all charts on every filter change would be extremely slow.
|
||||
|
||||
### Chart figure functions go in src/visualization/, not dash_app/
|
||||
- **When**: Creating new chart figures
|
||||
- **Rule**: Create figure builder functions in `src/visualization/plotly_generator.py`. Dash callbacks call these shared functions. Do NOT put Plotly figure construction logic directly in `dash_app/callbacks/`.
|
||||
- **Why**: Shared figure functions can be tested independently and reused.
|
||||
|
||||
### New query functions use same pattern as existing ones
|
||||
- **When**: Adding query functions to `src/data_processing/pathway_queries.py`
|
||||
- **Rule**: Follow the same pattern as `load_pathway_nodes()`: accept `db_path` parameter, use `sqlite3.connect()` with `row_factory = sqlite3.Row`, parameterized queries, return JSON-serializable dicts/lists. Add thin wrappers in `dash_app/data/queries.py`.
|
||||
- **Why**: Consistency with existing code. The thin wrapper pattern ensures DB path resolution is centralized.
|
||||
|
||||
---
|
||||
|
||||
## Data Patterns
|
||||
|
||||
### Use parameterized queries for all filters
|
||||
- **When**: Building WHERE clauses with user-selected values
|
||||
- **Rule**: Use `?` placeholders and pass params as a list. Never use f-strings or string interpolation for filter values.
|
||||
- **Why**: Prevents SQL injection and handles special characters in drug/directory names (e.g., "CROHN'S DISEASE").
|
||||
|
||||
### Parsing utilities must handle missing/null data gracefully
|
||||
- **When**: Parsing `average_spacing` HTML strings, `average_administered` JSON, or `ids` column values
|
||||
- **Rule**: Always handle `None`, empty string `""`, and malformed data. Return sensible defaults rather than raising exceptions.
|
||||
- **Why**: Not all nodes have statistics populated. Level 0-2 nodes have no drug-level statistics.
|
||||
|
||||
---
|
||||
|
||||
## Process Guardrails
|
||||
|
||||
### One task per iteration
|
||||
- **When**: Temptation to do additional tasks after completing the current one
|
||||
- **Rule**: Complete ONE task, validate it, commit it, update progress, then stop
|
||||
- **Why**: Multiple tasks increase error risk and make failures harder to diagnose
|
||||
|
||||
### Never mark complete without validation
|
||||
- **When**: Task feels "done" but hasn't been tested
|
||||
- **Rule**: All validation tiers must pass before marking `[x]`
|
||||
- **Why**: "Feels done" is not "is done"
|
||||
|
||||
### Write explicit handoff notes
|
||||
- **When**: Every iteration, before stopping
|
||||
- **Rule**: The "Next iteration should" section must contain specific, actionable guidance
|
||||
- **Why**: The next iteration has zero memory. If you don't write it down, it's lost.
|
||||
|
||||
### Validate with `python run_dash.py`
|
||||
- **When**: After completing any task
|
||||
- **Rule**: Run `python run_dash.py` (or `python -c "from dash_app.app import app"` for import checks). The app must start without errors after EVERY task.
|
||||
- **Why**: Broken imports or circular dependencies compound across tasks. Catch them immediately.
|
||||
|
||||
### Re-read plotly_generator.py before editing
|
||||
- **When**: Starting any task that modifies chart functions
|
||||
- **Rule**: Always re-read `src/visualization/plotly_generator.py` at the start of the iteration. Line numbers in IMPLEMENTATION_PLAN.md are approximate and shift as edits accumulate. Search for function names, not line numbers.
|
||||
- **Why**: Previous iterations may have changed the file, shifting all line numbers.
|
||||
|
||||
### 3-view navigation pattern
|
||||
- **When**: Modifying `switch_view()` in `navigation.py` or `update_app_state()` in `filters.py`
|
||||
- **Rule**: There are 3 views: `patient-pathways`, `trust-comparison`, `trends`. The `switch_view()` callback has 6 Outputs (3 view styles + 3 nav classNames). The `update_app_state()` callback has 3 nav Inputs. When updating either callback, ensure ALL return paths handle all 3 views correctly. Every return statement must include values for all 6 outputs / handle all 3 active_view values.
|
||||
- **Why**: Adding a 3rd view to a previously binary toggle is error-prone — missing a return path causes Dash callback errors.
|
||||
|
||||
### Trends view state in app-state
|
||||
- **When**: Working on the Trends view (E.2–E.4)
|
||||
- **Rule**: `selected_trends_directorate` must be initialized as `None` in the `app-state` dcc.Store initial data in `app.py`. The Trends view uses landing/detail toggle based on this value (same pattern as Trust Comparison's `selected_comparison_directorate`).
|
||||
- **Why**: Missing initial state causes KeyError on first page load.
|
||||
|
||||
### Removing callback Outputs/Inputs requires updating ALL return paths
|
||||
- **When**: Removing Outputs or Inputs from an existing callback (e.g., E.1 removing trends toggle from update_chart)
|
||||
- **Rule**: When removing an Output from a callback, you MUST update EVERY `return` statement in that callback to match the new Output count. Count the number of return statements before editing and verify the same count after. The `update_chart()` callback currently has 4+ return paths.
|
||||
- **Why**: Mismatched return tuple length causes `InvalidCallbackReturnValue` at runtime.
|
||||
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-876
@@ -1,876 +0,0 @@
|
||||
# Progress Log — Dashboard Visualization Improvements
|
||||
|
||||
## Project Context
|
||||
|
||||
Working Dash application with 2 views (Patient Pathways + Trust Comparison), 13 chart functions in `plotly_generator.py`, and a complete callback chain. Now improving chart quality: bug fixes, visual polish, and new analytics.
|
||||
|
||||
**Current state**: Fully functional Dash app at http://localhost:8050 with icicle, Sankey, market share, cost effectiveness, cost waterfall, dosing, heatmap, and duration charts. Trust Comparison has 6 dedicated charts. All filters work.
|
||||
|
||||
**New goal**: Fix chart bugs (heatmap colorscale, legend overflow, trust color differentiation), add visual polish (consistent styling, smooth gradients), add new analytics (retention funnel, pathway depth, scatter, network), and new backend analytics (trends, dose distribution, timeline, NICE compliance).
|
||||
|
||||
## Key Architecture Patterns
|
||||
|
||||
### plotly_generator.py (PRIMARY target file)
|
||||
- 13 chart functions, all accept list-of-dicts, return `go.Figure`
|
||||
- Located at `src/visualization/plotly_generator.py` (~1782 lines)
|
||||
- Key functions and approximate line numbers:
|
||||
- `create_icicle_from_nodes(nodes, title)` — L113
|
||||
- `create_market_share_figure(data, title)` — L247
|
||||
- `create_cost_effectiveness_figure(data, retention, title)` — L384
|
||||
- `create_cost_waterfall_figure(data, title)` — L562
|
||||
- `create_sankey_figure(data, title)` — L706
|
||||
- `create_dosing_figure(data, title, group_by)` — L837
|
||||
- `_dosing_by_drug(data, colours)` — L926
|
||||
- `_dosing_by_trust(data, colours)` — L1007
|
||||
- `create_heatmap_figure(data, title, metric)` — L1189
|
||||
- `create_duration_figure(data, title, show_directory)` — L1329
|
||||
- `create_trust_market_share_figure(data, title)` — L1481
|
||||
- `create_trust_heatmap_figure(data, title, metric)` — L1582
|
||||
- `create_trust_duration_figure(data, title)` — L1689
|
||||
- NOTE: Line numbers will shift as you edit. Re-read the file each iteration.
|
||||
|
||||
### Callback chain
|
||||
- `dash_app/callbacks/chart.py` — Patient Pathways tab dispatch (`_render_*` helpers → `update_chart`)
|
||||
- `dash_app/callbacks/trust_comparison.py` — 6 Trust Comparison chart callbacks
|
||||
- Tab switching: `active-tab` dcc.Store, tab IDs = `"tab-{short_id}"`
|
||||
- TAB_DEFINITIONS in `chart_card.py` — currently: icicle, sankey
|
||||
|
||||
### Adding a new Patient Pathways tab
|
||||
1. Query function in `src/data_processing/pathway_queries.py` (accept `db_path` param)
|
||||
2. Thin wrapper in `dash_app/data/queries.py` (resolve DB_PATH)
|
||||
3. Figure function in `src/visualization/plotly_generator.py`
|
||||
4. Add to `TAB_DEFINITIONS` in `dash_app/components/chart_card.py`
|
||||
5. Add `_render_*()` helper in `dash_app/callbacks/chart.py`
|
||||
6. Add elif case in `update_chart()` dispatch
|
||||
|
||||
### State management
|
||||
- 4 `dcc.Store` components: app-state, chart-data, reference-data, active-tab
|
||||
- Unidirectional: filter inputs → app-state → chart-data → UI
|
||||
- 20 registered callbacks total
|
||||
|
||||
### DMC version
|
||||
- Dash 4.0.0 + DMC 2.5.1 (Mantine v7 based)
|
||||
- `dmc.MantineProvider` wraps layout
|
||||
- `dmc.SegmentedControl` available for metric toggles
|
||||
|
||||
### Flex chain for chart filling viewport
|
||||
- Full flex chain: `.main` → `#view-container` → `#patient-pathways-view` → `.chart-card` → loading wrapper → `#chart-container` → `#pathway-chart`
|
||||
- `responsive=True` on dcc.Graph + `autosize=True` in figure layout
|
||||
- `dcc.Loading` wraps children in `.dash-loading-callback > div` — CSS must propagate flex through both
|
||||
|
||||
### Known heatmap bugs (to fix)
|
||||
- Non-linear colorscale compresses 99% of range into identical blues
|
||||
- No cell text — must hover every cell
|
||||
- Light end (#F0F4F8) invisible against transparent background
|
||||
- Fixed width can overflow container
|
||||
- Fixed l=200 left margin wastes space
|
||||
|
||||
### Known legend bugs (to fix)
|
||||
- Horizontal legends at y=-0.15 with fixed bottom margins overflow with 42 drugs
|
||||
- Affects: market_share, trust_market_share, dosing, trust_duration
|
||||
|
||||
### Known color bugs (to fix)
|
||||
- First 6 of 10 trust palette colors are blue variants — nearly indistinguishable
|
||||
- _dosing_by_drug interpolates from one blue to another blue
|
||||
|
||||
## Iteration Log
|
||||
|
||||
## Iteration 1 — 2026-02-07
|
||||
### Task: A.1 — Extract shared styling constants + `_base_layout()` helper
|
||||
### Why this task:
|
||||
- A.1 is the foundation for all subsequent Phase A tasks (A.2-A.4 all reference `_base_layout()` and the palette constants). Must be done first.
|
||||
### Status: COMPLETE
|
||||
### What was done:
|
||||
- Added 7 module-level constants after `logger` line: `CHART_FONT_FAMILY`, `CHART_TITLE_SIZE`, `CHART_TITLE_COLOR`, `GRID_COLOR`, `ANNOTATION_COLOR`, `TRUST_PALETTE` (7 colors), `DRUG_PALETTE` (15 colors)
|
||||
- Created `_base_layout(title, **overrides)` helper returning dict with: title (font family/size/color, centered), hoverlabel (white bg, #CBD5E1 border, font), paper/plot bgcolor transparent, autosize=True, base font family
|
||||
- Applied `_base_layout()` to `create_icicle_from_nodes()` — replaced 20-line explicit layout block with `_base_layout()` call + 3 overrides (margin, hoverlabel size=14, clickmode)
|
||||
- Also replaced hardcoded `"Source Sans 3, system-ui, sans-serif"` in icicle textfont with `CHART_FONT_FAMILY` constant
|
||||
### Validation results:
|
||||
- Tier 1 (Code): all imports pass, `python run_dash.py` starts cleanly
|
||||
- Tier 2 (Visual): icicle figure title correct ("Patient Pathways — By Directory"), font family/size/color all match expected values
|
||||
### Files changed:
|
||||
- `src/visualization/plotly_generator.py` — added constants + `_base_layout()` + refactored icicle layout
|
||||
- `IMPLEMENTATION_PLAN.md` — marked A.1 subtasks [x]
|
||||
### Committed: 63c1801 "feat: add shared styling constants and _base_layout() helper (Task A.1)"
|
||||
### Patterns discovered:
|
||||
- The `_base_layout()` returns a plain dict that gets unpacked via `fig.update_layout(**layout)`. Callers pass chart-specific overrides as kwargs.
|
||||
- Icicle hoverlabel uses `size=14` (slightly larger than base `13`) — preserved as override.
|
||||
- Constants are at module level, so all functions in the file can reference them directly.
|
||||
- Line numbers in IMPLEMENTATION_PLAN.md are now stale (shifted ~70 lines due to constants/helper insertion). Future iterations should search by function name.
|
||||
### Next iteration should:
|
||||
- Start with Task A.2: Fix heatmap colorscale + cell annotations. Read `create_heatmap_figure()` and `create_trust_heatmap_figure()` functions by searching for their names (line numbers have shifted).
|
||||
- The `_base_layout()` and palette constants are now available — A.2 should use `_base_layout()` for both heatmap functions.
|
||||
- Key heatmap fixes: linear 5-stop colorscale, cell text annotations, zmin=0, autosize, automargin, subtitle when >25 drugs.
|
||||
### Blocked items:
|
||||
- None
|
||||
|
||||
## Iteration 2 — 2026-02-07
|
||||
### Task: A.2 — Fix heatmap colorscale + cell annotations
|
||||
### Why this task:
|
||||
- A.2 is the next Phase A task after A.1. It depends on `_base_layout()` (done in A.1). It addresses the most-reported heatmap bugs: non-linear colorscale, missing cell text, fixed width overflow, fixed left margin.
|
||||
### Status: COMPLETE
|
||||
### What was done:
|
||||
- **create_heatmap_figure()**: Replaced non-linear 7-stop colorscale with linear 5-stop `[0.0 #E3F2FD, 0.25 #90CAF9, 0.5 #42A5F5, 0.75 #1E88E5, 1.0 #003087]`. Added `text=text_values, texttemplate="%{text}"` with metric-specific formatting (patients: `N`, cost: `£Nk`, cost_pp_pa: `£N`). Set `zmin=0`. Removed fixed `width`, using `autosize=True` from `_base_layout()`. Replaced `l=200` with `l=8` + `yaxis automargin=True`. Added subtitle annotation when 25-drug cap is hit. Reduced `xgap/ygap` to 1 when >15 columns.
|
||||
- **create_trust_heatmap_figure()**: Applied identical fixes. Also fixed Unicode escapes (`\u00a3`, `\u00d7`, `\u2014`) back to literal characters.
|
||||
- Both functions now use `_base_layout(chart_title)` for consistent styling — title color is now `#1E293B` (CHART_TITLE_COLOR) instead of old hardcoded `#003087`, title size is 18 (CHART_TITLE_SIZE) for both (trust heatmap was 16 before).
|
||||
### Validation results:
|
||||
- Tier 1 (Code): imports pass, `uv run python -c "from dash_app.app import app"` OK, `uv run python run_dash.py` starts cleanly
|
||||
- Tier 2 (Visual): Functional test confirms: zmin=0, text present, texttemplate="%{text}", 5-stop colorscale, autosize=True, yaxis automargin=True, title color #1E293B
|
||||
### Files changed:
|
||||
- `src/visualization/plotly_generator.py` — both heatmap functions rewritten
|
||||
- `IMPLEMENTATION_PLAN.md` — marked A.2 subtasks [x]
|
||||
### Committed: 56ca11e "fix: heatmap linear colorscale, cell annotations, autosize (Task A.2)"
|
||||
### Patterns discovered:
|
||||
- The `_base_layout()` helper makes chart function updates significantly easier — just `layout = _base_layout(title)` + `layout.update(...)` + `fig.update_layout(**layout)`. No need to repeat font/bgcolor/autosize.
|
||||
- `textfont=dict(size=10)` on the heatmap trace controls cell annotation size — needs to be small enough not to overflow cells.
|
||||
- Cost formatting: `£Nk` for cost ≥ 1000, `£N` for small values. This avoids `£125,000` flooding cells.
|
||||
### Next iteration should:
|
||||
- Start with Task A.3: Fix legend overflow in 4 charts. This requires creating `_smart_legend(n_items)` helper and applying it + `_base_layout()` to: `create_market_share_figure()`, `create_trust_market_share_figure()`, `create_dosing_figure()`, `create_trust_duration_figure()`.
|
||||
- Search for these function names by `def create_market_share_figure` etc. — line numbers have shifted again.
|
||||
- The `_smart_legend()` helper should: >15 items → vertical right legend; ≤15 → horizontal with dynamic bottom margin.
|
||||
### Blocked items:
|
||||
- None
|
||||
|
||||
## Iteration 3 — 2026-02-07
|
||||
### Task: A.3 — Fix legend overflow in 4 charts
|
||||
### Why this task:
|
||||
- A.3 is the next Phase A task after A.1 and A.2. It has no blockers and was explicitly recommended by Iteration 2. It addresses the legend overflow bug reported for charts with 42 drugs.
|
||||
### Status: COMPLETE
|
||||
### What was done:
|
||||
- **Created `_smart_legend(n_items, legend_title)` helper**: Returns legend dict with adaptive positioning. >15 items → vertical right legend (orientation="v", x=1.02, xanchor="left"). ≤15 items → horizontal below chart (orientation="h", y=-0.12, xanchor="center").
|
||||
- **Created `_smart_legend_margin(n_items)` helper**: Returns margin dict. >15 items → r=140, b=40. ≤15 items → dynamic b based on estimated row count (~6 items per row), r=24.
|
||||
- **`create_market_share_figure()`**: Replaced local `nhs_colours` with `DRUG_PALETTE`. Replaced manual layout block with `_base_layout()` + `_smart_legend()`. Replaced hardcoded `GRID_COLOR` reference.
|
||||
- **`create_trust_market_share_figure()`**: Same treatment. Also replaced Unicode escapes (`\u00a3`, `\u2014`) with literal characters (`£`, `—`).
|
||||
- **`create_dosing_figure()`**: Replaced local `nhs_colours` with `DRUG_PALETTE`. Legend adapts to trace count using `sum(1 for t in fig.data if t.showlegend is not False)`. Uses `_base_layout()`.
|
||||
- **`create_trust_duration_figure()`**: Replaced local `nhs_colours` with `TRUST_PALETTE` (7 maximally-distinct colors — also satisfies A.4 subtask). Fixed `l=200` → `l=8` + automargin. Uses `_base_layout()`.
|
||||
- **Note**: This also completed two A.4 subtasks: `create_trust_duration_figure()` now uses `TRUST_PALETTE`, and `create_trust_market_share_figure()` now uses `DRUG_PALETTE`.
|
||||
### Validation results:
|
||||
- Tier 1 (Code): All imports pass. `from dash_app.app import app` OK. `python run_dash.py` starts cleanly, HTTP 200.
|
||||
- Tier 2 (Visual): Functional tests confirm: 20-drug chart → vertical right legend; 5-drug → horizontal; 7-trust → horizontal with TRUST_PALETTE colors [#005EB8, #DA291C, #009639, #ED8B00, #7C2855, #00A499, #330072].
|
||||
- Tier 3 (Functional): All 4 chart functions produce correct figures with sample data. Legend orientation switches at 15-item threshold.
|
||||
### Files changed:
|
||||
- `src/visualization/plotly_generator.py` — added `_smart_legend()` + `_smart_legend_margin()`, refactored 4 chart functions
|
||||
- `IMPLEMENTATION_PLAN.md` — marked A.3 subtasks [x], updated A.4 for completed subtasks
|
||||
### Committed: 90de24c "fix: adaptive legends + _base_layout for 4 chart functions (Task A.3)"
|
||||
### Patterns discovered:
|
||||
- Plotly trace.showlegend defaults to None (not True), so checking `t.showlegend is not False` correctly identifies visible legend items.
|
||||
- The `_smart_legend_margin()` helper returns only `b` and `r` keys, allowing callers to merge with their own `t` and `l` via `dict(t=60, l=8, **legend_margins)`.
|
||||
- Net code reduction of 48 lines across 4 functions by replacing repeated layout blocks with `_base_layout()`.
|
||||
- Several A.4 subtasks were completed opportunistically during A.3 (replacing nhs_colours with palette constants).
|
||||
### Next iteration should:
|
||||
- Start with Task A.4: Fix remaining trust comparison color differentiation. Two subtasks remain:
|
||||
1. Add `is_trust_comparison=False` param to `create_cost_waterfall_figure()` — use `TRUST_PALETTE` when True. Update `tc_cost_waterfall` callback to pass `is_trust_comparison=True`.
|
||||
2. Fix `_dosing_by_drug()` blue→blue interpolation: replace with `plotly.colors.sample_colorscale("Viridis", ...)` for meaningful gradient.
|
||||
- The `create_trust_duration_figure()` TRUST_PALETTE fix and `create_trust_market_share_figure()` DRUG_PALETTE fix are already done (marked [x] in plan).
|
||||
- Search for `create_cost_waterfall_figure` and `_dosing_by_drug` by function name (line numbers have shifted).
|
||||
### Blocked items:
|
||||
- None
|
||||
|
||||
## Iteration 4 — 2026-02-07
|
||||
### Task: A.4 — Fix trust comparison color differentiation (remaining 3 subtasks)
|
||||
### Why this task:
|
||||
- A.4 is the last Phase A task. A.1-A.3 are complete. Two A.4 subtasks were already done opportunistically in A.3. The remaining 3 subtasks complete Phase A.
|
||||
### Status: COMPLETE
|
||||
### What was done:
|
||||
- **`create_cost_waterfall_figure()`**: Added `is_trust_comparison=False` parameter. When True, uses `TRUST_PALETTE` (7 distinct colors) instead of `DRUG_PALETTE`. Replaced local `nhs_colours` list. Applied `_base_layout()` — removed 20+ lines of hardcoded layout. Updated annotation fonts to use `ANNOTATION_COLOR` and `CHART_FONT_FAMILY` constants. Used `GRID_COLOR` constant for gridcolor.
|
||||
- **`tc_cost_waterfall` callback**: Updated call to pass `is_trust_comparison=True`, so Trust Comparison cost waterfall now uses 7 maximally-distinct trust colors.
|
||||
- **`_dosing_by_drug()`**: Replaced manual RGB interpolation (blue `#005EB8` → blue `#41B6E6`) with `plotly.colors.sample_colorscale("Viridis", ratios)`. Result: bars now range from yellow (high interval) through teal to purple (low interval) — clearly distinguishable.
|
||||
### Validation results:
|
||||
- Tier 1 (Code): `from dash_app.app import app` OK. `python run_dash.py` starts cleanly, HTTP 200.
|
||||
- Tier 2 (Visual): Cost waterfall normal mode uses DRUG_PALETTE colors (#005EB8, #DA291C, #009639...). Trust mode uses TRUST_PALETTE. Dosing by drug uses Viridis: rgb(253,231,37), rgb(34,144,140), rgb(59,81,138) — visually distinct.
|
||||
- Tier 3 (Functional): is_trust_comparison=False (default) preserves existing behavior. is_trust_comparison=True switches to TRUST_PALETTE. Viridis sampling produces correct gradients.
|
||||
### Files changed:
|
||||
- `src/visualization/plotly_generator.py` — `create_cost_waterfall_figure()` + `_dosing_by_drug()`
|
||||
- `dash_app/callbacks/trust_comparison.py` — `tc_cost_waterfall` callback
|
||||
- `IMPLEMENTATION_PLAN.md` — marked A.4 subtasks [x]
|
||||
### Committed: 950d93b "fix: trust palette for cost waterfall + Viridis dosing gradient (Task A.4)"
|
||||
### Patterns discovered:
|
||||
- `plotly.colors.sample_colorscale("Viridis", ratios)` returns a list of `rgb(r,g,b)` strings — can be passed directly to `marker.color` as a list. Very clean replacement for manual interpolation.
|
||||
- The `_base_layout()` + `layout.update()` pattern removed ~30 lines from `create_cost_waterfall_figure()` (net -33 lines in diff). Each function converted gets simpler.
|
||||
- Phase A is now COMPLETE. All 4 tasks (A.1-A.4) are done.
|
||||
### Next iteration should:
|
||||
- Start with Task B.1: Fix title inconsistencies across all charts. This requires:
|
||||
1. Apply `_base_layout()` to remaining unconverted chart functions: `create_sankey_figure()`, `create_cost_effectiveness_figure()`, `create_duration_figure()`
|
||||
2. These functions still have hardcoded `#003087` title colors and `"Source Sans 3"` font strings
|
||||
3. Some Trust Comparison functions may still use `size=16` instead of `CHART_TITLE_SIZE` (18)
|
||||
4. Search for `def create_sankey_figure`, `def create_cost_effectiveness_figure`, `def create_duration_figure` to find current line numbers
|
||||
- After B.1, the next tasks are B.2 (cost effectiveness gradient) and B.3 (Sankey narrow-screen fix) — both are small and independent.
|
||||
### Blocked items:
|
||||
- None
|
||||
|
||||
## Iteration 5 — 2026-02-07
|
||||
### Task: B.1 — Fix title inconsistencies across all charts
|
||||
### Why this task:
|
||||
- B.1 is the first Phase B task. Phase A is complete. Progress.txt from Iteration 4 explicitly recommended B.1 next. It ensures all chart functions use consistent styling via `_base_layout()`.
|
||||
### Status: COMPLETE
|
||||
### What was done:
|
||||
- **`create_sankey_figure()`**: Replaced local `nhs_colours` (15 blue-heavy colors) with `DRUG_PALETTE`. Replaced 20-line hardcoded layout block (title color `#003087`, manual font/bgcolor) with `_base_layout()` call + 2 overrides (font size 12, margin/height).
|
||||
- **`create_cost_effectiveness_figure()`**: Replaced 38-line manual layout block (title, xaxis, yaxis, margin, bgcolor, hoverlabel, font) with `_base_layout()` + 5-key update. Replaced hardcoded annotation font strings with `ANNOTATION_COLOR` and `CHART_FONT_FAMILY` constants. Replaced `gridcolor="#E2E8F0"` with `GRID_COLOR`.
|
||||
- **`create_duration_figure()`**: Replaced 30-line manual layout (title color `#003087`, l=200 fixed margin, manual bgcolor/font) with `_base_layout()` + 6-key update. Fixed `margin.l` from 200 → 8 + `yaxis automargin=True`. Replaced hardcoded annotation font with constants. Used `ANNOTATION_COLOR` in subtitle HTML span.
|
||||
- Net result: -52 lines (24 added, 76 removed). All 11 chart functions now use `_base_layout()`.
|
||||
### Validation results:
|
||||
- Tier 1 (Code): `from dash_app.app import app` OK. `python run_dash.py` starts cleanly, no errors.
|
||||
- Tier 2 (Visual): All three functions produce figures with title color `#1E293B`, title size 18, font family `Source Sans 3, system-ui, sans-serif`, transparent bgcolor. Duration uses automargin instead of fixed l=200.
|
||||
### Files changed:
|
||||
- `src/visualization/plotly_generator.py` — converted 3 remaining chart functions to `_base_layout()`
|
||||
- `IMPLEMENTATION_PLAN.md` — marked B.1 subtasks [x]
|
||||
### Committed: 8d05adc "fix: consistent titles via _base_layout() for Sankey, Cost Effectiveness, Duration (Task B.1)"
|
||||
### Patterns discovered:
|
||||
- All 11 chart functions in plotly_generator.py now use `_base_layout()`. No more hardcoded `"Source Sans 3"` strings or `#003087` title colors exist outside of constants/colorscale definitions.
|
||||
- Sankey's local `nhs_colours` was different from `DRUG_PALETTE` (had more blue variants like `#003087`, `#41B6E6`, `#0066CC`). Replacing with `DRUG_PALETTE` gives more distinguishable drug colors.
|
||||
- The `_base_layout()` conversion is a reliable pattern: replace the entire `fig.update_layout(...)` call with `layout = _base_layout(title)` + `layout.update({chart-specific})` + `fig.update_layout(**layout)`. Removes ~15-30 lines per function.
|
||||
### Next iteration should:
|
||||
- Choose Task B.2 (cost effectiveness smooth gradient) or B.3 (Sankey narrow-screen fix) — both are small, independent tasks with no blockers.
|
||||
- B.2: In `create_cost_effectiveness_figure()`, replace the 3-bin hard threshold (green/amber/red at 0.33/0.66) with smooth RGB interpolation. Green (#009639) → Amber (#ED8B00) at ratio 0–0.5, Amber → Red (#DA291C) at 0.5–1.0.
|
||||
- B.3: In `create_sankey_figure()`, change `arrangement="snap"` → `arrangement="freeform"` and increase `pad` from 20 → 25.
|
||||
- Both are quick changes — could potentially do B.2+B.3 together if scoped carefully, but the loop rules say one task per iteration.
|
||||
### Blocked items:
|
||||
- None
|
||||
|
||||
## Iteration 6 — 2026-02-07
|
||||
### Task: B.2 — Cost effectiveness smooth gradient
|
||||
### Why this task:
|
||||
- B.2 is the next Phase B task after B.1. Iteration 5 explicitly recommended B.2 or B.3. B.2 addresses the crude 3-bin color threshold in the cost effectiveness lollipop chart.
|
||||
### Status: COMPLETE
|
||||
### What was done:
|
||||
- **`create_cost_effectiveness_figure()`**: Replaced 3-bin hard threshold color assignment (green if ratio<0.33, amber if <0.66, red otherwise) with a smooth `_lerp_color()` inner function that does linear RGB interpolation:
|
||||
- Ratio 0–0.5: Green (#009639) → Amber (#ED8B00)
|
||||
- Ratio 0.5–1.0: Amber (#ED8B00) → Red (#DA291C)
|
||||
- Includes clamping to [0,1] for safety
|
||||
- Net change: +9 lines (replaced 8-line loop with 17-line function + 1-line list comprehension)
|
||||
- `_base_layout()` was already applied in B.1 — no further layout changes needed
|
||||
### Validation results:
|
||||
- Tier 1 (Code): `from dash_app.app import app` OK. `python run_dash.py` starts cleanly, HTTP 200.
|
||||
- Tier 2 (Visual): Functional test confirmed 5 gradient points: 1000→rgb(0,150,57) green, 3000→rgb(118,144,28) yellow-green, 5000→rgb(237,139,0) amber, 7000→rgb(227,90,14) orange-red, 9000→rgb(218,41,28) red. Smooth interpolation verified.
|
||||
### Files changed:
|
||||
- `src/visualization/plotly_generator.py` — replaced 3-bin color logic with `_lerp_color()` smooth gradient
|
||||
- `IMPLEMENTATION_PLAN.md` — marked B.2 subtasks [x]
|
||||
### Committed: cbac37e "fix: smooth green→amber→red gradient for cost effectiveness chart (Task B.2)"
|
||||
### Patterns discovered:
|
||||
- Inner function `_lerp_color()` defined inside `create_cost_effectiveness_figure()` keeps it scoped to where it's used. If other charts need similar gradients, could promote to module level.
|
||||
- The data is reversed before coloring (line 486), so colors are assigned based on position in the reversed list. But since `_lerp_color` uses the actual cost value via `(c - min_cost) / cost_range`, the reversal doesn't affect color correctness.
|
||||
### Next iteration should:
|
||||
- Do Task B.3: Sankey narrow-screen fix. Very small change:
|
||||
1. Search for `def create_sankey_figure` to find the function
|
||||
2. Change `arrangement="snap"` → `arrangement="freeform"`
|
||||
3. Increase `pad` from 20 → 25
|
||||
- After B.3, Task B.4 (heatmap metric toggle) is the last Phase B task — it's more involved (adding SegmentedControl components + callback wiring).
|
||||
### Blocked items:
|
||||
- None
|
||||
|
||||
## Iteration 7 — 2026-02-07
|
||||
### Task: B.3 — Sankey narrow-screen fix
|
||||
### Why this task:
|
||||
- B.3 is the next uncompleted Phase B task. Iteration 6 explicitly recommended it. It's a small, focused change with no dependencies.
|
||||
### Status: COMPLETE
|
||||
### What was done:
|
||||
- **`create_sankey_figure()`** (line 808): Changed `arrangement="snap"` → `arrangement="freeform"` so users can drag nodes freely on narrow screens. Increased `pad` from 20 → 25 for more spacing between nodes.
|
||||
### Validation results:
|
||||
- Tier 1 (Code): `from dash_app.app import app` OK. `python run_dash.py` starts cleanly.
|
||||
- Tier 2 (Visual): Functional test confirms arrangement="freeform" and pad=25 on generated figure.
|
||||
### Files changed:
|
||||
- `src/visualization/plotly_generator.py` — Sankey arrangement + pad
|
||||
- `IMPLEMENTATION_PLAN.md` — marked B.3 [x]
|
||||
### Committed: fb30f5f "fix: Sankey freeform arrangement + increased padding (Task B.3)"
|
||||
### Patterns discovered:
|
||||
- `arrangement="freeform"` allows users to manually reposition Sankey nodes by dragging, which is useful when nodes overlap on narrow viewports. `"snap"` constrains nodes to columns.
|
||||
### Next iteration should:
|
||||
- Do Task B.4: Heatmap metric toggle (both views). This is the last Phase B task and is more involved:
|
||||
1. Add `dmc.SegmentedControl` component next to Patient Pathways heatmap (id: `heatmap-metric-toggle`, visible only when heatmap tab active). Add to `dash_app/components/chart_card.py`.
|
||||
2. Add `dmc.SegmentedControl` next to Trust Comparison heatmap (id: `tc-heatmap-metric-toggle`). Add to `dash_app/components/trust_comparison.py`.
|
||||
3. Update `_render_heatmap()` in `dash_app/callbacks/chart.py` to read the metric toggle value.
|
||||
4. Update `tc_heatmap` callback in `dash_app/callbacks/trust_comparison.py` to read the metric toggle value.
|
||||
5. Both heatmap functions (`create_heatmap_figure`, `create_trust_heatmap_figure`) already accept a `metric` parameter — the toggle just needs to pass the selected metric through.
|
||||
- Key files to read: `dash_app/components/chart_card.py` (for PP toggle placement), `dash_app/components/trust_comparison.py` (for TC toggle placement), `dash_app/callbacks/chart.py` (for `_render_heatmap`), `dash_app/callbacks/trust_comparison.py` (for `tc_heatmap`).
|
||||
### Blocked items:
|
||||
- None
|
||||
|
||||
## Iteration 8 — 2026-02-07
|
||||
### Task: B.4 — Heatmap metric toggle (both views)
|
||||
### Why this task:
|
||||
- B.4 is the last Phase B task. B.1-B.3 are complete. Iteration 7 explicitly recommended B.4. It requires adding `dmc.SegmentedControl` components and wiring them into callbacks.
|
||||
### Status: COMPLETE
|
||||
### What was done:
|
||||
- **chart_card.py**: Added "heatmap" to `TAB_DEFINITIONS` (was only in `ALL_TAB_DEFINITIONS`). Added `dmc.SegmentedControl` (id: `heatmap-metric-toggle`) in `heatmap-metric-wrapper` div inside chart card header, hidden by default (`display: none`).
|
||||
- **trust_comparison.py**: Replaced generic `_tc_chart_cell` for heatmap with custom inline layout containing `dmc.SegmentedControl` (id: `tc-heatmap-metric-toggle`) in a flex row next to the title.
|
||||
- **chart.py**: Updated `_render_heatmap()` to accept `metric` parameter (default "patients"). Updated `update_chart` callback to:
|
||||
- Add `Output("heatmap-metric-wrapper", "style")` — controls toggle visibility
|
||||
- Add `Input("heatmap-metric-toggle", "value")` — reads metric selection
|
||||
- Show toggle when `active_tab == "heatmap"`, hide otherwise
|
||||
- Pass metric to `_render_heatmap()` when heatmap tab is active
|
||||
- **trust_comparison.py callbacks**: Updated `tc_heatmap` callback to add `Input("tc-heatmap-metric-toggle", "value")` and pass `metric=heatmap_metric` to `create_trust_heatmap_figure()`.
|
||||
- Both `create_heatmap_figure()` and `create_trust_heatmap_figure()` already accept `metric` param — no changes needed in plotly_generator.py.
|
||||
### Validation results:
|
||||
- Tier 1 (Code): `from dash_app.app import app` passes. `python run_dash.py` starts cleanly, HTTP 200.
|
||||
- Tier 2 (Visual): N/A — toggle components rendered in layout, heatmap functions already tested in A.2.
|
||||
- Tier 3 (Functional): Callback wiring verified — `update_chart` has 3 Outputs (figure, subtitle, toggle style) and 4 Inputs (chart-data, active-tab, app-state, heatmap-metric-toggle). TC heatmap callback has 2 Inputs (app-state, tc-heatmap-metric-toggle). Toggle options: patients, cost, cost_pp_pa.
|
||||
### Files changed:
|
||||
- `dash_app/components/chart_card.py` — added heatmap to TAB_DEFINITIONS, added SegmentedControl
|
||||
- `dash_app/components/trust_comparison.py` — custom heatmap cell with SegmentedControl
|
||||
- `dash_app/callbacks/chart.py` — updated _render_heatmap + update_chart callback
|
||||
- `dash_app/callbacks/trust_comparison.py` — updated tc_heatmap callback
|
||||
- `IMPLEMENTATION_PLAN.md` — marked B.4 subtasks [x]
|
||||
### Committed: 8e2e2b7 "feat: heatmap metric toggle for both PP and TC views (Task B.4)"
|
||||
### Patterns discovered:
|
||||
- Adding a new Output to an existing callback (e.g., `heatmap-metric-wrapper` style) requires updating ALL return paths in that callback to include the new output value. The toggle_style is computed once at the top and returned in every code path.
|
||||
- `dmc.SegmentedControl` with `size="xs"` fits nicely in chart headers without overwhelming the title.
|
||||
- The heatmap tab was missing from PP `TAB_DEFINITIONS` — only in `ALL_TAB_DEFINITIONS`. Adding it to `TAB_DEFINITIONS` automatically creates the tab button and wires it into `switch_tab` because `_TAB_IDS` is built dynamically.
|
||||
- Phase B is now COMPLETE. All 4 tasks (B.1-B.4) are done.
|
||||
### Next iteration should:
|
||||
- Start Phase C: New Analytics (Existing Data). Task C.1 (Retention funnel chart) is the first task.
|
||||
- C.1 requires the 6-step pattern for adding a new chart tab:
|
||||
1. Create `get_retention_funnel()` in `src/data_processing/pathway_queries.py` — query level 4+ nodes, aggregate by treatment line depth
|
||||
2. Add thin wrapper in `dash_app/data/queries.py`
|
||||
3. Create `create_retention_funnel_figure(data, title)` in `src/visualization/plotly_generator.py` — use `go.Funnel`
|
||||
4. Add "Funnel" tab to `TAB_DEFINITIONS` in `chart_card.py`
|
||||
5. Add `_render_funnel()` helper in `dash_app/callbacks/chart.py`
|
||||
6. Add elif case in `update_chart()` dispatch
|
||||
- Key: The query should count patients at each treatment line depth (1-drug, 2-drug, 3-drug, etc.) using the level column in pathway_nodes. Level 3 = 1st drug, level 4 = 2-drug pathway, etc.
|
||||
- Use `_base_layout()` and NHS blue gradient for the funnel figure.
|
||||
### Blocked items:
|
||||
- None
|
||||
|
||||
## Iteration 9 — 2026-02-07
|
||||
### Task: C.1 — Retention funnel chart
|
||||
### Why this task:
|
||||
- C.1 is the first Phase C task. Phases A and B are complete. Iteration 8 explicitly recommended C.1. It follows the 6-step pattern for adding a new chart tab.
|
||||
### Status: COMPLETE
|
||||
### What was done:
|
||||
- **`get_retention_funnel()`** in `pathway_queries.py`: Queries level 3+ nodes grouped by level, aggregates patient counts. Level 3→depth 1 (1st drug), level 4→depth 2 (2nd drug), etc. Supports directory/trust filters. Returns list of dicts with depth, label, patients, pct.
|
||||
- **Thin wrapper** in `dash_app/data/queries.py`: Imports and delegates to shared function with DB_PATH resolution.
|
||||
- **`create_retention_funnel_figure()`** in `plotly_generator.py`: Uses `go.Funnel` with NHS blue gradient (#003087→#005EB8→#1E88E5). Text inside bars shows "N patients (X%)". Uses `_base_layout()` for consistent styling. Dynamic height based on depth count.
|
||||
- **TAB_DEFINITIONS**: Added `("funnel", "Funnel")` — now 4 tabs: Icicle, Sankey, Heatmap, Funnel.
|
||||
- **`_render_funnel()`** in `chart.py`: Reads filter state, calls query, passes to figure function. Handles empty data and errors.
|
||||
- **Dispatch case**: Added `elif active_tab == "funnel"` in `update_chart()`.
|
||||
### Validation results:
|
||||
- Tier 1 (Code): `from dash_app.app import app` OK. `python run_dash.py` starts cleanly, HTTP 200.
|
||||
- Tier 2 (Visual): Funnel shows 3 levels: 1st drug (10,819 patients, 100%), 2nd drug (2,142, 19.8%), 3rd drug (176, 1.6%). NHS blue gradient applied.
|
||||
- Tier 3 (Functional): Responds to directory filter (RHEUMATOLOGY: 3,448→551→50). Works with indication chart type (10,782→1,519→125). Returns empty figure for nonexistent directory. Tab switching wired via dynamic `_TAB_IDS`.
|
||||
### Files changed:
|
||||
- `src/data_processing/pathway_queries.py` — added `get_retention_funnel()`
|
||||
- `dash_app/data/queries.py` — added import + thin wrapper
|
||||
- `src/visualization/plotly_generator.py` — added `create_retention_funnel_figure()`
|
||||
- `dash_app/components/chart_card.py` — added funnel to TAB_DEFINITIONS
|
||||
- `dash_app/callbacks/chart.py` — added `_render_funnel()` + dispatch case
|
||||
- `IMPLEMENTATION_PLAN.md` — marked C.1 subtasks [x]
|
||||
### Committed: a6cf6ef "feat: retention funnel chart tab with treatment line depth (Task C.1)"
|
||||
### Patterns discovered:
|
||||
- The 6-step pattern works cleanly: query → wrapper → figure → tab def → render helper → dispatch. No surprises.
|
||||
- Level 3 sum (10,819) ≈ root value (11,118) — difference is due to minimum_patients thresholds. Close enough for funnel percentages.
|
||||
- `go.Funnel` positions text automatically. `textposition="inside"` with white text on dark NHS blue is readable.
|
||||
- Funnel connector lines use `GRID_COLOR` for visual consistency with other charts.
|
||||
### Next iteration should:
|
||||
- Do Task C.2: Pathway depth distribution chart. Same 6-step pattern.
|
||||
1. Create `get_pathway_depth_distribution()` in `pathway_queries.py` — aggregate patients who STOPPED at each depth (not cumulative like funnel, but exclusive)
|
||||
2. Key difference from funnel: subtract child counts. Patients at depth 1 only = level 3 total - level 4 total. Patients at depth 2 only = level 4 total - level 5 total.
|
||||
3. Create `create_pathway_depth_figure(data, title)` — horizontal bar chart with NHS blue gradient
|
||||
4. Add "Depth" tab to TAB_DEFINITIONS (will be 5th tab)
|
||||
5. Wire callback helpers
|
||||
- The query logic for "stopped at depth N" is: patients_at_level_N - patients_at_level_(N+1). The last level has no children so stopped = total.
|
||||
### Blocked items:
|
||||
- None
|
||||
|
||||
## Iteration 10 — 2026-02-07
|
||||
### Task: C.2 — Pathway depth distribution chart
|
||||
### Why this task:
|
||||
- C.2 is the next Phase C task after C.1. Iteration 9 explicitly recommended it. Same 6-step pattern as C.1.
|
||||
### Status: COMPLETE
|
||||
### What was done:
|
||||
- **`get_pathway_depth_distribution()`** in `pathway_queries.py`: Queries level 3+ nodes grouped by level, then subtracts next-level counts to get exclusive "stopped at depth N" patients. Supports directory/trust filters. Returns list of dicts with depth, label, patients, pct.
|
||||
- **Thin wrapper** in `dash_app/data/queries.py`: Imports and delegates with DB_PATH resolution.
|
||||
- **`create_pathway_depth_figure()`** in `plotly_generator.py`: Horizontal bar chart (`go.Bar` with `orientation="h"`) with NHS blue gradient (#003087→#005EB8→#1E88E5). Text inside bars shows "N (pct%)". Uses `_base_layout()`. Dynamic height based on depth count. Y-axis reversed so depth 1 (most patients) is at top.
|
||||
- **TAB_DEFINITIONS**: Added `("depth", "Depth")` — now 5 tabs: Icicle, Sankey, Heatmap, Funnel, Depth.
|
||||
- **`_render_depth()`** in `chart.py`: Reads filter state, calls query, passes to figure function. Handles empty data and errors.
|
||||
- **Dispatch case**: Added `elif active_tab == "depth"` in `update_chart()`.
|
||||
### Validation results:
|
||||
- Tier 1 (Code): `from dash_app.app import app` OK. `python run_dash.py` starts cleanly. 20 callbacks registered.
|
||||
- Tier 2 (Visual): Depth chart shows 3 levels: 1 drug only (8,677, 80.2%), 2 drugs only (1,966, 18.2%), 3 drugs only (176, 1.6%). NHS blue gradient applied. Autosize + automargin.
|
||||
- Tier 3 (Functional): Directory filter works (RHEUMATOLOGY: 2,897/501/50). Indication chart type works (9,263/1,394/125). Empty data returns empty figure. Tab switching wired via dynamic `_TAB_IDS`.
|
||||
### Files changed:
|
||||
- `src/data_processing/pathway_queries.py` — added `get_pathway_depth_distribution()`
|
||||
- `dash_app/data/queries.py` — added import + thin wrapper
|
||||
- `src/visualization/plotly_generator.py` — added `create_pathway_depth_figure()`
|
||||
- `dash_app/components/chart_card.py` — added depth to TAB_DEFINITIONS
|
||||
- `dash_app/callbacks/chart.py` — added `_render_depth()` + dispatch case
|
||||
- `IMPLEMENTATION_PLAN.md` — marked C.2 subtasks [x]
|
||||
### Committed: 55c9af2 "feat: pathway depth distribution chart tab (Task C.2)"
|
||||
### Patterns discovered:
|
||||
- The depth calculation (cumulative - next level) is simple: iterate pairs and subtract. Total of exclusive counts equals the level 3 total, confirming correctness (8,677 + 1,966 + 176 = 10,819 = funnel total).
|
||||
- `autorange="reversed"` on yaxis puts depth 1 at the top of the horizontal bar chart, matching the natural reading order (most patients first).
|
||||
- The 6-step pattern continues to work cleanly for new tabs. Each step is small and independently verifiable.
|
||||
### Next iteration should:
|
||||
- Do Task C.3: Duration vs Cost scatter plot. Same 6-step pattern:
|
||||
1. Create `get_duration_cost_scatter()` in `pathway_queries.py` — query level 3 nodes for drug-level data (drug, directory, avg_days, cost_pp_pa, patients)
|
||||
2. Add thin wrapper in `queries.py`
|
||||
3. Create `create_duration_cost_scatter_figure(data, title)` in `plotly_generator.py` — scatter: x=avg_days, y=cost_pp_pa, size=patients, color=directory. Add quadrant lines at median values.
|
||||
4. Add "Scatter" tab to TAB_DEFINITIONS (6th tab)
|
||||
5. Wire `_render_scatter()` + dispatch
|
||||
- Key design decision: use `go.Scatter` with marker size proportional to patient count. Color by directory (use DRUG_PALETTE cycling or assign by directory). Quadrant lines use median avg_days and median cost_pp_pa as thresholds.
|
||||
### Blocked items:
|
||||
- None
|
||||
|
||||
## Iteration 11 — 2026-02-07
|
||||
### Task: C.3 — Duration vs Cost scatter plot
|
||||
### Why this task:
|
||||
- C.3 is the next Phase C task after C.1 and C.2. Iteration 10 explicitly recommended it with design details. Same 6-step pattern.
|
||||
### Status: COMPLETE
|
||||
### What was done:
|
||||
- **`get_duration_cost_scatter()`** in `pathway_queries.py`: Queries level 3 nodes with avg_days and cost_pp_pa, aggregates across trusts using weighted averages. Supports directory/trust filters. Returns list of dicts.
|
||||
- **Thin wrapper** in `dash_app/data/queries.py`: Standard import + DB_PATH delegation.
|
||||
- **`create_duration_cost_scatter_figure()`** in `plotly_generator.py`: `go.Scatter` with one trace per directory for legend grouping. Marker size proportional to patient count (global max for consistent sizing). DRUG_PALETTE for directory colors. Quadrant lines at median avg_days and median cost_pp_pa with annotations. Uses `_base_layout()` + `_smart_legend()`.
|
||||
- **TAB_DEFINITIONS**: Added `("scatter", "Scatter")` — now 6 tabs: Icicle, Sankey, Heatmap, Funnel, Depth, Scatter.
|
||||
- **`_render_scatter()`** in `chart.py`: Standard render helper with filter extraction and error handling.
|
||||
- **Dispatch case**: Added `elif active_tab == "scatter"` in `update_chart()`.
|
||||
### Validation results:
|
||||
- Tier 1 (Code): `from dash_app.app import app` OK. `python run_dash.py` starts cleanly.
|
||||
- Tier 2 (Visual): 59 data points across 12 directories. Days range 48–2237, cost range £994–£162k. Median quadrant lines at 928 days and £4,629. Marker sizes proportional (8–40px).
|
||||
- Tier 3 (Functional): Directory filter works (RHEUMATOLOGY: 16 drugs). Indication chart type works (108 points). Empty data returns empty figure. Tab switching wired via dynamic `_TAB_IDS`.
|
||||
### Files changed:
|
||||
- `src/data_processing/pathway_queries.py` — added `get_duration_cost_scatter()`
|
||||
- `dash_app/data/queries.py` — added import + thin wrapper
|
||||
- `src/visualization/plotly_generator.py` — added `create_duration_cost_scatter_figure()`
|
||||
- `dash_app/components/chart_card.py` — added scatter to TAB_DEFINITIONS
|
||||
- `dash_app/callbacks/chart.py` — added `_render_scatter()` + dispatch case
|
||||
- `IMPLEMENTATION_PLAN.md` — marked C.3 subtasks [x]
|
||||
### Committed: d8df416 "feat: duration vs cost scatter plot tab (Task C.3)"
|
||||
### Patterns discovered:
|
||||
- `statistics.median()` imported inside the function to avoid module-level import for a stdlib module only used by one function.
|
||||
- Marker size must use global max (not per-directory max) for consistent visual comparison across all directories. Initially coded per-directory, fixed before commit.
|
||||
- `fig.add_hline()` and `fig.add_vline()` are the clean Plotly API for quadrant lines — they create shape objects and annotation objects automatically.
|
||||
### Next iteration should:
|
||||
- Do Task C.4: Drug switching network graph. This is the last Phase C task. Options from IMPLEMENTATION_PLAN.md:
|
||||
1. Create `get_drug_network()` in `pathway_queries.py` — returns undirected edges (source, target, patients) and nodes (name, total_patients). Different from `get_drug_transitions()` which returns directed Sankey data.
|
||||
2. Create `create_drug_network_figure(data, title)` using `go.Scatter` for circular layout nodes + edges as lines.
|
||||
3. Add as separate "Network" tab or sub-toggle within Sankey tab.
|
||||
4. The plan says "Add as sub-toggle within Sankey tab or as separate Network tab" — separate tab is simpler (follows established pattern).
|
||||
- After C.4, Phase D begins (backend work: trends, dose distribution, timeline, NICE compliance).
|
||||
### Blocked items:
|
||||
- None
|
||||
|
||||
## Iteration 12 — 2026-02-07
|
||||
### Task: C.4 — Drug switching network graph
|
||||
### Why this task:
|
||||
- C.4 is the last Phase C task. C.1-C.3 are complete. Iteration 11 explicitly recommended C.4. It follows the established 6-step pattern for adding a new chart tab.
|
||||
### Status: COMPLETE
|
||||
### What was done:
|
||||
- **`get_drug_network()`** in `pathway_queries.py`: Queries level 4+ nodes for drug_sequence co-occurrence edges (undirected, sorted pairs to avoid duplicates). Also queries level 3 nodes for per-drug patient totals. Supports directory/trust filters. Returns `{nodes: [{name, total_patients}], edges: [{source, target, patients}]}`.
|
||||
- **Thin wrapper** in `dash_app/data/queries.py`: Standard import + DB_PATH delegation.
|
||||
- **`create_drug_network_figure()`** in `plotly_generator.py`: Circular layout using `math.cos/sin` for node positions. Individual `go.Scatter` traces for each edge (variable width 0.5–6px and opacity 0.15–0.7 scaled by patient count). Node scatter with `markers+text` mode, size 12–50px proportional to patients, colors from `DRUG_PALETTE`. Uses `_base_layout()`. Axes hidden, `scaleanchor="y"` for square aspect ratio.
|
||||
- **TAB_DEFINITIONS**: Added `("network", "Network")` — now 7 tabs: Icicle, Sankey, Heatmap, Funnel, Depth, Scatter, Network.
|
||||
- **`_render_network()`** in `chart.py`: Standard render helper with filter extraction and error handling. Checks `data.get("nodes")` for empty state.
|
||||
- **Dispatch case**: Added `elif active_tab == "network"` in `update_chart()`.
|
||||
### Validation results:
|
||||
- Tier 1 (Code): `from dash_app.app import app` OK. `python run_dash.py` starts cleanly, HTTP 200.
|
||||
- Tier 2 (Visual): 39 drug nodes, 45 co-occurrence edges. Top connections: FARICIMAB↔RANIBIZUMAB (452), AFLIBERCEPT↔FARICIMAB (392), ADALIMUMAB↔ETANERCEPT (305). Figure has 46 traces (45 edges + 1 node scatter).
|
||||
- Tier 3 (Functional): Directory filter works (RHEUMATOLOGY: 17 nodes, 20 edges). Indication chart type works (39 nodes, 28 edges). Empty data returns empty figure. Tab switching wired via dynamic `_TAB_IDS`.
|
||||
### Files changed:
|
||||
- `src/data_processing/pathway_queries.py` — added `get_drug_network()`
|
||||
- `dash_app/data/queries.py` — added import + thin wrapper
|
||||
- `src/visualization/plotly_generator.py` — added `create_drug_network_figure()`
|
||||
- `dash_app/components/chart_card.py` — added network to TAB_DEFINITIONS
|
||||
- `dash_app/callbacks/chart.py` — added `_render_network()` + dispatch case
|
||||
- `IMPLEMENTATION_PLAN.md` — marked C.4 subtasks [x]
|
||||
### Committed: 1405476 "feat: drug switching network graph tab (Task C.4)"
|
||||
### Patterns discovered:
|
||||
- Individual edge traces (one `go.Scatter` per edge) is necessary for variable width/opacity per edge. A single trace would only support uniform line properties.
|
||||
- `scaleanchor="y", scaleratio=1` on xaxis ensures the circular layout is actually circular, not elliptical.
|
||||
- The undirected edge approach (sort pair to canonical form) correctly deduplicates A→B and B→A transitions.
|
||||
- Phase C is now COMPLETE. All 4 tasks (C.1-C.4) are done. 7 Patient Pathways tabs total.
|
||||
### Next iteration should:
|
||||
- Start Phase D: New Analytics (Backend Work). D.1 (Temporal trend analysis) is the first task.
|
||||
- **Important**: D.1 requires schema changes (`pathway_trends` table) and CLI pipeline extension — this is backend work that has been avoided so far. Read guardrails.md carefully: DO NOT modify the existing pipeline logic, but adding new tables and extending refresh_pathways.py to compute trends is allowed per the plan.
|
||||
- D.1 steps: (1) Design `pathway_trends` table schema in schema.py, (2) Add migration, (3) Extend refresh_pathways.py to insert trend snapshots, (4) Create query function, (5) Create figure function (line chart), (6) Add tab + callbacks.
|
||||
- However: trends need at least 2 refresh cycles to show meaningful data. Consider whether D.1 is worth implementing vs. skipping to D.2 (dose distribution) or D.3 (drug timeline) which work with existing data.
|
||||
- Alternative: D.3 (Drug timeline / Gantt chart) uses existing `first_seen`/`last_seen` data in pathway_nodes — no backend changes needed. Could be a better next task.
|
||||
### Blocked items:
|
||||
- None
|
||||
|
||||
## Iteration 13 — 2026-02-07
|
||||
### Task: D.3 — Drug timeline (Gantt chart)
|
||||
### Why this task:
|
||||
- D.3 uses existing `first_seen`/`last_seen` data in pathway_nodes — no backend/schema changes needed. D.1 requires schema changes + pipeline extension (both in guardrail DO NOT MODIFY list) and needs ≥2 refresh cycles for meaningful data. D.2 requires parsing complex `average_administered` JSON. D.3 was the cleanest next task.
|
||||
### Status: COMPLETE
|
||||
### What was done:
|
||||
- **`get_drug_timeline()`** in `pathway_queries.py`: Queries level 3 nodes aggregated across trusts — MIN(first_seen), MAX(last_seen), SUM(value), weighted avg cost_pp_pa per drug × directory. Supports directory/trust filters. Returns 59 entries for all-directory view.
|
||||
- **Thin wrapper** in `dash_app/data/queries.py`: Standard import + DB_PATH delegation.
|
||||
- **`create_drug_timeline_figure()`** in `plotly_generator.py`: Gantt-style using `go.Bar(orientation="h")` with `base` set to `first_seen` datetime and `x` as duration in milliseconds. One trace per bar, legend grouped by directory. Colors from `DRUG_PALETTE` (one color per directory). Patient count as white text inside bars. Hover shows drug, directory, first/last seen (month/year), duration in days, patients, cost p.a. Dynamic height (28px per bar). Uses `_base_layout()` + `_smart_legend()` + `_smart_legend_margin()`.
|
||||
- **TAB_DEFINITIONS**: Added `("timeline", "Timeline")` — now 8 tabs: Icicle, Sankey, Heatmap, Funnel, Depth, Scatter, Network, Timeline.
|
||||
- **`_render_timeline()`** in `chart.py`: Standard render helper with directory/trust filter extraction and error handling.
|
||||
- **Dispatch case**: Added `elif active_tab == "timeline"` in `update_chart()`.
|
||||
### Validation results:
|
||||
- Tier 1 (Code): `from dash_app.app import app` OK. `python run_dash.py` starts cleanly, HTTP 200.
|
||||
- Tier 2 (Visual): 59 data points across 12 directories. Date x-axis with 6-month ticks. Bars span 2019–2025. Newest drug DOCETAXEL (BREAST SURGERY) starts May 2025. Single-directory mode (RHEUMATOLOGY): 16 drugs, y-labels without directory suffix.
|
||||
- Tier 3 (Functional): Directory filter works (RHEUMATOLOGY: 16 drugs). Trust filter works. Empty data returns empty figure. Tab switching wired via dynamic `_TAB_IDS`. 8 tabs visible.
|
||||
### Files changed:
|
||||
- `src/data_processing/pathway_queries.py` — added `get_drug_timeline()`
|
||||
- `dash_app/data/queries.py` — added import + thin wrapper
|
||||
- `src/visualization/plotly_generator.py` — added `create_drug_timeline_figure()`
|
||||
- `dash_app/components/chart_card.py` — added timeline to TAB_DEFINITIONS
|
||||
- `dash_app/callbacks/chart.py` — added `_render_timeline()` + dispatch case
|
||||
- `IMPLEMENTATION_PLAN.md` — marked D.3 subtasks [x]
|
||||
### Committed: 0a14f1f "feat: drug timeline Gantt chart tab (Task D.3)"
|
||||
### Patterns discovered:
|
||||
- Plotly `go.Bar` Gantt trick: set `base` to start datetime, `x` to duration in milliseconds (days × 86,400,000), `orientation="h"`. Plotly auto-detects date axis type from the datetime base values.
|
||||
- `datetime.fromisoformat()` handles the `T00:00:00` suffix in ISO timestamps from SQLite without issue.
|
||||
- Single-directory detection (`len(directories) == 1`) lets us simplify y-labels to just drug names, avoiding redundant "(RHEUMATOLOGY)" suffix when the user already filtered to that directory.
|
||||
- With 59 bars, 12 directories → `_smart_legend()` uses horizontal mode (≤15 items), which works well since directory names aren't too long.
|
||||
### Next iteration should:
|
||||
- Choose between D.1 (Temporal trends), D.2 (Dose distribution), or D.4 (NICE TA compliance).
|
||||
- **D.1** is problematic: requires modifying `schema.py` (guardrail protected), `reference_data.py` (guardrail protected), and `refresh_pathways.py` (guardrail protected). The plan allows it as an exception, but it also needs ≥2 refresh cycles for meaningful data. Consider marking D.1 as [B] (blocked on pipeline changes being out of scope).
|
||||
- **D.2** (Dose distribution): Requires parsing `average_administered` JSON from pathway_nodes. Check if the data exists and is parseable first — run `SELECT average_administered FROM pathway_nodes WHERE average_administered IS NOT NULL AND average_administered != '' LIMIT 5` to inspect the format.
|
||||
- **D.4** (NICE TA compliance): Requires parsing `data/ta-recommendations.xlsx` — check if this file exists and what it contains. This is also substantial (schema + migration + compliance scoring).
|
||||
- Recommendation: Try D.2 next if `average_administered` data is available and parseable. If the JSON format is too complex or data is sparse, mark D.2 as [B] and assess D.4.
|
||||
### Blocked items:
|
||||
- D.1: Likely blocked — requires modifying guardrail-protected files (schema.py, reference_data.py, refresh_pathways.py) + needs multiple refresh cycles for meaningful data.
|
||||
|
||||
## Iteration 14 — 2026-02-07
|
||||
### Task: D.2 — Average administered doses analysis
|
||||
### Why this task:
|
||||
- D.2 was explicitly recommended by Iteration 13. The `average_administered` JSON data exists (2031 rows, simple array format) and requires no schema changes. D.1 is blocked (guardrail-protected files). D.4 is complex (schema + migration + Excel parsing). D.2 was the cleanest ready task.
|
||||
### Status: COMPLETE
|
||||
### What was done:
|
||||
- **`get_dosing_distribution()`** in `pathway_queries.py`: Queries level 3 nodes with `average_administered` JSON, parses position 0 (average dose count for the drug), aggregates across trusts using weighted averages by patient count. Supports directory/trust filters. Returns `[{drug, directory, avg_doses, patients}]`.
|
||||
- **Thin wrapper** in `dash_app/data/queries.py`: Standard import + DB_PATH delegation.
|
||||
- **`create_dosing_distribution_figure()`** in `plotly_generator.py`: Horizontal bar chart (`go.Bar` with `orientation="h"`) showing average administered doses per drug. One trace per bar with legend grouped by directory. Colors from `DRUG_PALETTE`. Dynamic height (24px per bar). `_base_layout()` + `_smart_legend()`. Hover shows drug, directory, avg doses, patients.
|
||||
- **TAB_DEFINITIONS**: Added `("doses", "Doses")` — now 9 tabs: Icicle, Sankey, Heatmap, Funnel, Depth, Scatter, Network, Timeline, Doses.
|
||||
- **`_render_doses()`** in `chart.py`: Standard render helper with directory/trust filter extraction and error handling.
|
||||
- **Dispatch case**: Added `elif active_tab == "doses"` in `update_chart()`.
|
||||
### Validation results:
|
||||
- Tier 1 (Code): `from dash_app.app import app` OK. `uv run python run_dash.py` starts cleanly, HTTP 200.
|
||||
- Tier 2 (Visual): 59 data points across 12 directories. Top: TOCILIZUMAB (RHEUMATOLOGY) avg 70.5 doses, INFLIXIMAB (OPHTHALMOLOGY) 47.7, EVOLOCUMAB (CHEMICAL PATHOLOGY) 46.6. Dynamic height 1536px for all, 504px for single directory.
|
||||
- Tier 3 (Functional): Directory filter works (RHEUMATOLOGY: 16 drugs). Empty data returns empty figure. Tab switching wired via dynamic `_TAB_IDS`. 9 tabs visible.
|
||||
### Files changed:
|
||||
- `src/data_processing/pathway_queries.py` — added `get_dosing_distribution()`
|
||||
- `dash_app/data/queries.py` — added import + thin wrapper
|
||||
- `src/visualization/plotly_generator.py` — added `create_dosing_distribution_figure()`
|
||||
- `dash_app/components/chart_card.py` — added doses to TAB_DEFINITIONS
|
||||
- `dash_app/callbacks/chart.py` — added `_render_doses()` + dispatch case
|
||||
- `IMPLEMENTATION_PLAN.md` — marked D.2 subtasks [x]
|
||||
### Committed: c7e9398 "feat: average administered doses chart tab (Task D.2)"
|
||||
### Patterns discovered:
|
||||
- The `average_administered` column is a JSON array of floats (with NaN as string). Position 0 = average doses for the drug at that node. Level 3 nodes have only position 0, level 4 has positions 0+1, etc.
|
||||
- `json.loads(s.replace("NaN", "null"))` safely handles NaN values in the JSON. Returns None for NaN positions.
|
||||
- No need for a separate parsing function in `parsing.py` — the JSON parsing is simple enough to inline in the query function (3 lines).
|
||||
- With 59 bars (one per drug×directory), the chart is readable with 24px per bar and legend grouped by directory.
|
||||
### Next iteration should:
|
||||
- Two Phase D tasks remain: D.1 (Temporal trends) and D.4 (NICE TA compliance).
|
||||
- **D.1** is very likely blocked: requires modifying `schema.py`, `reference_data.py`, and `refresh_pathways.py` — all in the guardrails DO NOT MODIFY list. Also needs multiple refresh cycles. Recommend marking D.1 as [B] (blocked).
|
||||
- **D.4** (NICE TA compliance): Check if `data/ta-recommendations.xlsx` exists and inspect its contents. This requires: (1) parsing the Excel into a reference table, (2) creating schema + migration (guardrail-protected), (3) compliance scoring algorithm, (4) figure function, (5) tab/callback wiring. Steps 1-2 are also likely blocked by guardrails.
|
||||
- If both D.1 and D.4 are blocked, the project may be effectively complete for the current scope. Mark them [B] and check completion criteria.
|
||||
- Alternatively: assess whether D.4 can be done without schema changes by keeping TA data in memory (load Excel directly from disk, no migration needed).
|
||||
### Blocked items:
|
||||
- D.1: Blocked — requires modifying guardrail-protected files + needs multiple refresh cycles.
|
||||
- D.4: Potentially blocked — requires schema + migration for TA reference data (guardrail-protected files).
|
||||
|
||||
## Iteration 15 — 2026-02-07
|
||||
### Task: D.1 + D.4 — Final assessment and project completion
|
||||
### Why this task:
|
||||
- Only D.1 and D.4 remain. Both were flagged as potentially blocked in Iteration 14. This iteration assesses their feasibility and makes a final determination.
|
||||
### Status: COMPLETE (project finalization)
|
||||
### What was done:
|
||||
- **D.1 (Temporal trends)**: Confirmed BLOCKED. Requires modifying 3 guardrail-protected files (`schema.py`, `reference_data.py`, `refresh_pathways.py`) + needs ≥2 data refresh cycles to show meaningful trend data. Marked `[B]` in IMPLEMENTATION_PLAN.md.
|
||||
- **D.4 (NICE TA compliance)**: Confirmed BLOCKED. `data/ta-recommendations.xlsx` does not exist — the source data file is missing entirely. Even if it existed, would require schema + migration changes to guardrail-protected files. Marked `[B]` in IMPLEMENTATION_PLAN.md.
|
||||
- **Completion criteria**: Updated all achievable criteria to `[x]`. Phase D blocked items marked `[B]` with explanations.
|
||||
- **Final validation**: `from dash_app.app import app` OK. `python run_dash.py` starts cleanly on http://127.0.0.1:8050/.
|
||||
### Validation results:
|
||||
- Tier 1 (Code): Import check passes, app starts without errors
|
||||
### Files changed:
|
||||
- `IMPLEMENTATION_PLAN.md` — marked D.1 and D.4 as [B] (blocked), updated all completion criteria
|
||||
- `progress.txt` — this entry
|
||||
### Summary of all completed work (14 iterations):
|
||||
- **Phase A (4 tasks)**: Shared constants + `_base_layout()`, heatmap fixes (colorscale + annotations), legend overflow fix (4 charts), trust color differentiation
|
||||
- **Phase B (4 tasks)**: Title consistency (all 11 charts), cost effectiveness gradient, Sankey freeform, heatmap metric toggle
|
||||
- **Phase C (4 tasks)**: Retention funnel, pathway depth distribution, duration vs cost scatter, drug network graph
|
||||
- **Phase D (2 of 4 tasks)**: Drug timeline Gantt chart, average administered doses chart
|
||||
- **Total**: 14 tasks completed, 2 blocked, 9 Patient Pathways tabs, 15+ chart functions, all using shared styling
|
||||
### Blocked items:
|
||||
- D.1: BLOCKED — guardrail-protected file modifications required + needs ≥2 refresh cycles
|
||||
- D.4: BLOCKED — source data file (`ta-recommendations.xlsx`) missing + guardrail-protected file modifications required
|
||||
|
||||
## Manual Intervention — 2026-02-07
|
||||
### Reason: Unblock D.1 with historical snapshots approach, remove D.4
|
||||
### Changes made:
|
||||
- `IMPLEMENTATION_PLAN.md` — rewrote D.1 as two subtasks (D.1a: CLI script, D.1b: Dash tab), removed D.4 entirely, updated completion criteria
|
||||
- `guardrails.md` — updated DB guardrail exception for trends CLI script, added new guardrail about using existing pipeline functions as-is
|
||||
- `progress.txt` — this entry
|
||||
### Tasks reset: None (D.1 was already blocked `[B]`, now unblocked as `[ ]`)
|
||||
### Tasks added: None (D.1 rewritten in-place as D.1a + D.1b)
|
||||
### Tasks removed: D.4 (NICE TA compliance — source data doesn't exist, not viable)
|
||||
### Context for next iteration:
|
||||
- D.1a is the next task: create `cli/compute_trends.py` standalone CLI script
|
||||
- The script imports `fetch_and_transform_data()` and `process_pathway_for_date_filter()` from `pathway_pipeline.py` — calls them, does NOT modify them
|
||||
- Creates `pathway_trends` table via `CREATE TABLE IF NOT EXISTS` in pathways.db
|
||||
- Loops over 6-month endpoints (2021-06-30 through 2025-12-31) using `all_6mo` date filter config with different `max_date` values
|
||||
- For each endpoint: run pathway computation, extract level 3 node summaries (drug, directory, patients, cost, cost_pp_pa)
|
||||
- The key insight: `compute_date_ranges(config, max_date)` and `process_pathway_for_date_filter(df, config, ..., max_date=...)` already accept `max_date` as a parameter — no pipeline changes needed
|
||||
- This requires Snowflake access (fetches all activity data once, then filters locally for each period)
|
||||
- After D.1a, D.1b adds the Dash tab using the standard 6-step pattern
|
||||
### New guardrails added:
|
||||
- "Trend computation uses existing pipeline functions as-is" — import and call, don't modify
|
||||
|
||||
## Iteration 16 — 2026-02-07
|
||||
### Task: D.1 — Temporal trend analysis (D.1a + D.1b combined)
|
||||
### Why this task:
|
||||
- D.1 is the only remaining task. D.1a (CLI script) and D.1b (Dash tab) are both needed to complete D.1. Manual intervention unblocked D.1 by rewriting it as a standalone CLI that imports existing pipeline functions without modifying them.
|
||||
### Status: COMPLETE
|
||||
### What was done:
|
||||
- **D.1a — `cli/compute_trends.py`**: Standalone CLI script. Imports `fetch_and_transform_data()` and `process_pathway_for_date_filter()` from `pathway_pipeline.py`. Creates `pathway_trends` table via `CREATE TABLE IF NOT EXISTS`. Generates period endpoints from 2021-06-30 to 2025-12-31 at configurable intervals (default 6 months). For each endpoint: runs pathway computation with `max_date=endpoint`, extracts level 3 node summaries (drug, directory, patients, total_cost, cost_pp_pa). Supports `--dry-run`, `--start/--end`, `--interval`, `--verbose`.
|
||||
- **D.1b — Trends tab (6-step pattern)**:
|
||||
1. `get_trend_data()` in `pathway_queries.py` — checks table existence first, aggregates by drug (or directory), supports directory/drug filters, handles cost_pp_pa as weighted average
|
||||
2. Thin wrapper in `dash_app/data/queries.py`
|
||||
3. `create_trend_figure()` in `plotly_generator.py` — line chart with `go.Scatter` (lines+markers), one trace per drug/directory, `_base_layout()` + `_smart_legend()`, empty state shows "Run python -m cli.compute_trends" message
|
||||
4. Added "Trends" tab to `TAB_DEFINITIONS` (10th tab: Icicle, Sankey, Heatmap, Funnel, Depth, Scatter, Network, Timeline, Doses, Trends)
|
||||
5. Added `_render_trends()` helper + dispatch case. Trends tab handles empty data independently of chart-data store.
|
||||
6. Added `dmc.SegmentedControl` metric toggle (patients/cost/cost_pp_pa) in chart card header, visible only when trends tab active
|
||||
### Validation results:
|
||||
- Tier 1 (Code): `from dash_app.app import app` OK. `python run_dash.py` starts cleanly on http://127.0.0.1:8050/. `python -m cli.compute_trends --help` works.
|
||||
- Tier 2 (Visual): Empty data figure shows "No trend data available. Run python -m cli.compute_trends to generate." Sample data (2 drugs × 2 periods) renders 2 traces with correct names and Patients y-axis label.
|
||||
- Tier 3 (Functional): Query returns [] when pathway_trends table doesn't exist (graceful empty state). Tab switching wired via dynamic `_TAB_IDS`. Metric toggle shows/hides based on active tab. 10 tabs visible.
|
||||
### Files changed:
|
||||
- `src/cli/compute_trends.py` — NEW: standalone CLI script for computing historical trend snapshots
|
||||
- `src/data_processing/pathway_queries.py` — added `get_trend_data()`
|
||||
- `dash_app/data/queries.py` — added import + thin wrapper
|
||||
- `src/visualization/plotly_generator.py` — added `create_trend_figure()`
|
||||
- `dash_app/components/chart_card.py` — added trends to TAB_DEFINITIONS + metric toggle
|
||||
- `dash_app/callbacks/chart.py` — added `_render_trends()` + dispatch case + trends metric toggle I/O
|
||||
- `IMPLEMENTATION_PLAN.md` — marked D.1a, D.1b, and completion criteria [x]
|
||||
### Committed: d0404aa "feat: temporal trends CLI script + Dash tab (Task D.1)"
|
||||
### Patterns discovered:
|
||||
- The trends tab is unique: it doesn't depend on the `chart-data` store (which holds pathway_nodes). It queries `pathway_trends` directly. The dispatch case checks for "trends" before the "no nodes" check.
|
||||
- `sqlite3` table existence check via `SELECT name FROM sqlite_master WHERE type='table' AND name='pathway_trends'` is the clean way to handle the table-doesn't-exist case.
|
||||
- Adding a new Output/Input to an existing callback requires updating ALL return paths (4 return sites in update_chart).
|
||||
### Next iteration should:
|
||||
- See Manual Intervention below — Phase E tasks added.
|
||||
### Blocked items:
|
||||
- None — all tasks complete
|
||||
|
||||
## Manual Intervention — 2026-02-07
|
||||
### Reason: Redesign temporal trends as standalone view + fix chart height
|
||||
### Changes made:
|
||||
- `IMPLEMENTATION_PLAN.md` — added Phase E with 5 tasks (E.1–E.5), updated "What Changes" section, added Phase E completion criteria
|
||||
- `guardrails.md` — added guardrails for 3-view navigation and Trends view state
|
||||
- `progress.txt` — this entry
|
||||
### Tasks reset: None (all Phase A–D tasks remain complete)
|
||||
### Tasks added:
|
||||
- E.1: Remove Trends tab from Patient Pathways
|
||||
- E.2: Add Trends sidebar nav item + view container (3rd top-level view)
|
||||
- E.3: Create Trends landing page — directorate-level overview chart with metric toggle
|
||||
- E.4: Add drug drill-down within Trends view (click directorate → drug-level trends)
|
||||
- E.5: Fix chart height to fill viewport + rename "Cost" to "Cost per Patient"
|
||||
### Context for next iteration:
|
||||
- Start with E.1 (remove Trends from Patient Pathways) — this is a cleanup task that simplifies the codebase before adding the new view
|
||||
- E.1 involves removing the trends tab from TAB_DEFINITIONS, removing the trends-metric-wrapper/toggle from chart_card.py, removing _render_trends() and its dispatch case from chart.py, and cleaning up the update_chart() callback signature (remove trends Output/Input). CRITICAL: update ALL return paths in update_chart() when removing the trends toggle style output.
|
||||
- After E.1, E.2 adds the 3rd sidebar item and empty view container. Key files: sidebar.py (add icon + nav item), app.py (add trends-view div), navigation.py (3-way switch_view), filters.py (add nav-trends Input)
|
||||
- E.3 creates the new Trends view components and callbacks. The existing `get_trend_data()` in pathway_queries.py needs a `group_by` parameter added. `create_trend_figure()` in plotly_generator.py is reused as-is.
|
||||
- E.4 adds drill-down using the same landing/detail toggle pattern as Trust Comparison (selected_trends_directorate in app-state)
|
||||
- E.5 fixes chart height by removing fixed height values and relying on CSS flex + responsive=True
|
||||
- The existing `get_trend_data()` query already supports directory filter and drug filter. For directorate-level grouping, add a `group_by="directory"` parameter that changes the SQL GROUP BY from drug to directory.
|
||||
- Keep `create_trend_figure()` — it already handles any number of named series
|
||||
### New guardrails added:
|
||||
- "3-view navigation pattern" — when modifying switch_view or update_app_state, update ALL outputs/return paths for 3 views
|
||||
- "Trends view state in app-state" — selected_trends_directorate must be in app-state initial data
|
||||
|
||||
## Iteration 17 — 2026-02-07
|
||||
### Task: E.1 — Remove Trends tab from Patient Pathways
|
||||
### Why this task:
|
||||
- E.1 is the first Phase E task. Progress.txt explicitly recommended it. It's a cleanup prerequisite — the Trends tab must be removed from Patient Pathways before re-adding it as a standalone 3rd view in E.2–E.4.
|
||||
### Status: COMPLETE
|
||||
### What was done:
|
||||
- **chart_card.py**: Removed `("trends", "Trends")` from `TAB_DEFINITIONS` (now 9 tabs: Icicle through Doses). Removed `trends-metric-wrapper` div and `trends-metric-toggle` SegmentedControl from chart card header.
|
||||
- **chart.py**: Removed `_render_trends()` helper function (~17 lines). Removed `Output("trends-metric-wrapper", "style")` and `Input("trends-metric-toggle", "value")` from `update_chart()` callback. Removed `trends_metric` parameter. Removed `trends_toggle_style` variable and the entire `if active_tab == "trends"` dispatch block. Updated ALL 4 return paths from 4-tuple to 3-tuple (figure, subtitle, heatmap_toggle_style).
|
||||
- **queries.py**: Removed `get_trend_data` import from the import block and removed the `get_trend_data()` thin wrapper function.
|
||||
- **Preserved**: `get_trend_data()` in `pathway_queries.py` and `create_trend_figure()` in `plotly_generator.py` — both still needed for the new Trends view.
|
||||
### Validation results:
|
||||
- Tier 1 (Code): `from dash_app.app import app` OK. `python run_dash.py` starts cleanly on http://127.0.0.1:8050/.
|
||||
- Tier 2 (Visual): 9 tabs visible (Icicle, Sankey, Heatmap, Funnel, Depth, Scatter, Network, Timeline, Doses). No Trends tab.
|
||||
- Tier 3 (Functional): Callback signature now has 3 Outputs, 4 Inputs (was 4 Outputs, 5 Inputs). All 4 return paths updated correctly.
|
||||
### Files changed:
|
||||
- `dash_app/components/chart_card.py` — removed trends tab + metric toggle
|
||||
- `dash_app/callbacks/chart.py` — removed _render_trends + trends dispatch + trends I/O
|
||||
- `dash_app/data/queries.py` — removed get_trend_data import + wrapper
|
||||
- `IMPLEMENTATION_PLAN.md` — marked E.1 subtasks [x]
|
||||
### Committed: d052d2b "refactor: remove Trends tab from Patient Pathways (Task E.1)"
|
||||
### Patterns discovered:
|
||||
- Removing a callback Output/Input required updating exactly 4 return paths: (1) no chart_data, (2) error_msg, (3) no nodes, (4) final return with fig. Guardrail about counting return paths before/after was essential.
|
||||
- The `dmc` import in chart_card.py is still needed for the heatmap metric toggle — only the trends toggle was removed.
|
||||
### Next iteration should:
|
||||
- Do Task E.2: Add Trends sidebar nav item + view container. Key files to read:
|
||||
1. `dash_app/components/sidebar.py` — add "trends" icon + 3rd nav item
|
||||
2. `dash_app/app.py` — add `trends-view` div to layout, add `selected_trends_directorate` to app-state initial data
|
||||
3. `dash_app/callbacks/navigation.py` — update `switch_view()` for 3 views (6 outputs: 3 view styles + 3 nav classNames)
|
||||
4. `dash_app/callbacks/filters.py` — add `Input("nav-trends", "n_clicks")` to `update_app_state()`
|
||||
- CRITICAL: The `switch_view()` callback must handle 3 views with 6 Outputs. Read the existing 2-view implementation first to understand the pattern, then extend to 3.
|
||||
- CRITICAL: `update_app_state()` has multiple return paths — ensure ALL handle the new "trends" active_view case.
|
||||
### Blocked items:
|
||||
- None
|
||||
|
||||
## Iteration 18 — 2026-02-07
|
||||
### Task: E.2 — Add Trends sidebar nav item + view container
|
||||
### Why this task:
|
||||
- E.2 is the next Phase E task after E.1. Progress.txt from Iteration 17 explicitly recommended it with detailed guidance. It adds the 3rd sidebar navigation item and empty view container, required before E.3 (landing page) and E.4 (drill-down).
|
||||
### Status: COMPLETE
|
||||
### What was done:
|
||||
- **sidebar.py**: Added `"trends"` icon (`<polyline points="22 12 18 12 15 21 9 3 6 12 2 12"/>`) to `_ICONS` dict. Added 3rd `_sidebar_item("Trends", "trends", active=False, item_id="nav-trends")`.
|
||||
- **app.py**: Added `selected_trends_directorate: None` to app-state initial data. Added `html.Div(id="trends-view", style={"display": "none"}, children=[...])` with placeholder H3 after trust-comparison-view.
|
||||
- **navigation.py**: Extended `switch_view()` from 4 to 6 Outputs (3 view styles + 3 nav classNames). Added 3-way switching: patient-pathways, trust-comparison, trends. All 3 return paths (+ fallback) return 6-tuples.
|
||||
- **filters.py**: Added `Input("nav-trends", "n_clicks")` to `update_app_state()`. Added `_nav_trends_clicks` parameter. Added `elif triggered_id == "nav-trends": active_view = "trends"` case. Added `selected_trends_directorate: None` to fallback state dict.
|
||||
### Validation results:
|
||||
- Tier 1 (Code): `from dash_app.app import app` OK. `python run_dash.py` starts cleanly on http://127.0.0.1:8050/.
|
||||
- Tier 2 (Visual): 3 sidebar items: Patient Pathways, Trust Comparison, Trends.
|
||||
- Tier 3 (Functional): `switch_view` has 6 Outputs confirmed. `update_app_state` has `nav-trends` Input confirmed. `selected_trends_directorate` present in app-state initial data. Trends view toggles show/hide correctly.
|
||||
### Files changed:
|
||||
- `dash_app/components/sidebar.py` — added trends icon + nav item
|
||||
- `dash_app/app.py` — added trends-view div + selected_trends_directorate
|
||||
- `dash_app/callbacks/navigation.py` — 3-way switch_view (6 outputs)
|
||||
- `dash_app/callbacks/filters.py` — nav-trends input + trends active_view case
|
||||
- `IMPLEMENTATION_PLAN.md` — marked E.2 subtasks [x]
|
||||
### Committed: 190aefd "feat: add Trends sidebar nav item + 3-view switching (Task E.2)"
|
||||
### Patterns discovered:
|
||||
- The `**current_state` spread in `updated_state` dict automatically preserves `selected_trends_directorate` without needing an explicit entry — it carries through from the initial state.
|
||||
- The 3-view `switch_view()` pattern uses explicit `elif` for each view rather than a dict lookup — matches the existing binary pattern style and is easy to audit for correctness.
|
||||
- `update_app_state()` only has 1 return path (line 159), so adding `selected_trends_directorate` to the initial data was sufficient — no need to update multiple returns.
|
||||
### Next iteration should:
|
||||
- Do Task E.3: Create Trends landing page with directorate-level trends. Key steps:
|
||||
1. Create `dash_app/components/trends.py` with `make_trends_landing()` and `make_trends_detail()` functions
|
||||
2. Update `get_trend_data()` in `pathway_queries.py` to support `group_by="directory"` parameter
|
||||
3. Update thin wrapper in `dash_app/data/queries.py` to pass `group_by`
|
||||
4. Create `dash_app/callbacks/trends.py` with `register_trends_callbacks(app)` — callback to render directorate overview chart
|
||||
5. Register in `dash_app/callbacks/__init__.py`
|
||||
6. Wire `trends-view` div in `app.py` to contain `make_trends_landing()` + `make_trends_detail()`
|
||||
7. Rename "Cost" to "Cost per Patient" in metric toggle labels
|
||||
- Key files to read: `dash_app/components/trust_comparison.py` (reference pattern for landing/detail), existing `get_trend_data()` in `pathway_queries.py`, `create_trend_figure()` in `plotly_generator.py`
|
||||
- The `make_trends_landing()` should have: title, description, `dmc.SegmentedControl(id="trends-view-metric-toggle")`, and `dcc.Graph(id="trends-overview-chart")` wrapped in `dcc.Loading`
|
||||
- The `make_trends_detail()` should have: back button (id: `trends-back-btn`), title (id: `trends-detail-title`), and `dcc.Graph(id="trends-detail-chart")` wrapped in `dcc.Loading`
|
||||
- CRITICAL: The trends callback must check `active_view == "trends"` before computing — otherwise it fires on every app-state change
|
||||
### Blocked items:
|
||||
- None
|
||||
|
||||
## Iteration 19 — 2026-02-07
|
||||
### Task: E.3 — Create Trends landing page with directorate overview chart
|
||||
### Why this task:
|
||||
- E.3 is the next Phase E task after E.1 and E.2. Iteration 18 explicitly recommended it with detailed guidance. It creates the Trends landing page component, wires the directorate-level overview chart, and adds the metric toggle.
|
||||
### Status: COMPLETE
|
||||
### What was done:
|
||||
- **`dash_app/components/trends.py`** (NEW): Created `make_trends_landing()` and `make_trends_detail()` functions. Landing has: title, description, metric toggle (Patients / Cost per Patient / Cost per Patient p.a.), `dcc.Graph(id="trends-overview-chart")` in `dcc.Loading`. Detail has: back button, title, separate metric toggle, `dcc.Graph(id="trends-detail-chart")`.
|
||||
- **`pathway_queries.py`**: Added `group_by` parameter to `get_trend_data()` — `"drug"` (default) or `"directory"`.
|
||||
- **`dash_app/data/queries.py`**: Added `get_trend_data` import and thin wrapper.
|
||||
- **`dash_app/callbacks/trends.py`** (NEW): 2 callbacks — landing/detail toggle + overview chart rendering with metric toggle.
|
||||
- **`callbacks/__init__.py`**: Registered trends callbacks.
|
||||
- **`app.py`**: Replaced placeholder H3 with `make_trends_landing()` + `make_trends_detail()`.
|
||||
### Validation results:
|
||||
- Tier 1 (Code): `from dash_app.app import app` OK. `python run_dash.py` starts cleanly.
|
||||
- Tier 2 (Visual): Landing page shows title, description, metric toggle, chart placeholder.
|
||||
- Tier 3 (Functional): 22 callbacks registered. Guards prevent firing on non-trends views.
|
||||
### Files changed:
|
||||
- `dash_app/components/trends.py` — NEW
|
||||
- `dash_app/callbacks/trends.py` — NEW
|
||||
- `dash_app/callbacks/__init__.py` — register trends callbacks
|
||||
- `dash_app/app.py` — wire trends-view
|
||||
- `dash_app/data/queries.py` — added get_trend_data wrapper
|
||||
- `src/data_processing/pathway_queries.py` — added group_by param
|
||||
- `IMPLEMENTATION_PLAN.md` — marked E.3 subtasks [x]
|
||||
### Committed: c253e05 "feat: Trends landing page with directorate overview chart (Task E.3)"
|
||||
### Patterns discovered:
|
||||
- Trends uses same landing/detail toggle pattern as Trust Comparison (check `selected_*_directorate` in app-state).
|
||||
- Separate metric toggle IDs for landing (`trends-view-metric-toggle`) vs detail (`trends-detail-metric-toggle`) avoids callback conflicts.
|
||||
- `prevent_initial_call=True` + `active_view == "trends"` guard prevents unnecessary queries.
|
||||
### Next iteration should:
|
||||
- Do Task E.4: Add drug drill-down within Trends view. Key steps:
|
||||
1. The drill-down needs a way to set `selected_trends_directorate` in app-state when a directorate line is clicked on the overview chart.
|
||||
2. **Recommended approach**: Add `Input("trends-overview-chart", "clickData")` and `Input("trends-back-btn", "n_clicks")` to `update_app_state()` in `filters.py`. Extract directorate name from `clickData["points"][0]["curveNumber"]` — but this won't directly give the name. Better: check the trace `name` via the figure data, or use `customdata` on the trace.
|
||||
3. **Alternative approach**: Since `create_trend_figure()` sets `name=name` on each trace, `clickData["points"][0]["customdata"]` won't have the name. Instead, the point's parent trace can be identified: each point in clickData has keys like `curveNumber`. But we can't access the figure's trace names from the callback directly.
|
||||
4. **Simplest approach**: In `create_trend_figure()`, add `customdata=[name]*len(periods)` to each trace's `go.Scatter`. Then in the callback, extract `clickData["points"][0]["customdata"]` as the directorate name.
|
||||
5. Add detail chart callback in `trends.py`: Input `app-state` + `trends-detail-metric-toggle` → `trends-detail-chart`. Calls `get_trend_data(directory=selected, metric=..., group_by="drug")` → `create_trend_figure()`.
|
||||
6. Back button: `Input("trends-back-btn", "n_clicks")` in `update_app_state()` → clear `selected_trends_directorate`.
|
||||
- **Key files**: `dash_app/callbacks/filters.py` (add clickData + back btn inputs), `dash_app/callbacks/trends.py` (add detail chart callback), `src/visualization/plotly_generator.py` (add customdata to trend traces)
|
||||
- CRITICAL: When adding Inputs to `update_app_state()`, the function signature and `_nav_trends_clicks` parameter must be updated. There is only 1 return path so impact is minimal.
|
||||
### Blocked items:
|
||||
- None
|
||||
|
||||
## Iteration 20 — 2026-02-07
|
||||
### Task: E.4 — Add drug drill-down within Trends view
|
||||
### Why this task:
|
||||
- E.4 is the next Phase E task after E.3. Iteration 19 explicitly recommended it with detailed guidance. It wires up click-to-drill-down on the directorate overview chart and a back button to return.
|
||||
### Status: COMPLETE
|
||||
### What was done:
|
||||
- **`create_trend_figure()`** in `plotly_generator.py`: Added `customdata=[name]*len(s["periods"])` to each `go.Scatter` trace so the directorate/drug name is accessible from Plotly clickData events.
|
||||
- **`update_app_state()`** in `filters.py`: Added 2 new Inputs:
|
||||
- `Input("trends-overview-chart", "clickData")` — extracts directorate name from `clickData["points"][0]["customdata"]` and sets `selected_trends_directorate`
|
||||
- `Input("trends-back-btn", "n_clicks")` — clears `selected_trends_directorate` to None
|
||||
- Also clears `selected_trends_directorate` when chart type changes (same pattern as TC)
|
||||
- Added `selected_trends_directorate` explicitly to `updated_state` dict
|
||||
- **`render_trends_detail()`** in `trends.py`: New callback rendering drug-level trends for the selected directorate. Input: `app-state` + `trends-detail-metric-toggle` → Output `trends-detail-chart`. Guards: only fires when `active_view == "trends"` and `selected_trends_directorate` is set.
|
||||
- **No changes needed** to `toggle_trends_subviews()` — it already handles landing/detail toggle based on `selected_trends_directorate`. No changes needed to `app.py` — `selected_trends_directorate` was already initialized in E.2.
|
||||
### Validation results:
|
||||
- Tier 1 (Code): `from dash_app.app import app` OK. `python run_dash.py` starts cleanly on http://127.0.0.1:8050/. 23 callbacks registered.
|
||||
- Tier 2 (Visual): customdata verified on trend figure traces. Overview chart has directorate names accessible from clickData.
|
||||
- Tier 3 (Functional): `update_app_state` has 13 Inputs (was 11). Click extracts directorate name correctly. Back button clears selection. Detail chart callback renders drug-level trends for selected directorate. Metric toggle works independently in detail view.
|
||||
### Files changed:
|
||||
- `src/visualization/plotly_generator.py` — added customdata to create_trend_figure traces
|
||||
- `dash_app/callbacks/filters.py` — added clickData + back btn inputs to update_app_state
|
||||
- `dash_app/callbacks/trends.py` — added render_trends_detail callback
|
||||
- `IMPLEMENTATION_PLAN.md` — marked E.4 subtasks [x]
|
||||
### Committed: 28f858e "feat: Trends drill-down — click directorate to see drug-level trends (Task E.4)"
|
||||
### Patterns discovered:
|
||||
- `customdata=[name]*len(periods)` on each Scatter trace is the clean way to make trace identity accessible from clickData. Each point carries its parent trace's name.
|
||||
- The `update_app_state()` callback is the central hub for all state changes. Adding Inputs is safe because it has only 1 return path (line 171) — unlike `update_chart()` which has 4+ return paths.
|
||||
- The detail metric toggle (`trends-detail-metric-toggle`) is separate from the landing toggle (`trends-view-metric-toggle`), so they fire independently without callback conflicts.
|
||||
### Next iteration should:
|
||||
- Do Task E.5: Fix chart height to fill viewport + rename "Cost" to "Cost per Patient" in remaining metric toggles.
|
||||
- E.5 involves:
|
||||
1. Remove `height=500` from `create_trend_figure()` — let `autosize=True` handle it
|
||||
2. Review ALL chart functions for fixed `height=...` values. Keep dynamic heights (e.g., `max(400, n * 28)`) but remove fixed 500px. Charts: icicle (no height set — OK), sankey (height=600), heatmap (dynamic — OK), funnel (dynamic — OK), depth (dynamic — OK), scatter (height=500), network (height=600), timeline (dynamic — OK), doses (dynamic — OK), cost_effectiveness (no explicit — check), cost_waterfall (no explicit — check), market_share (no explicit — check), dosing (no explicit — check), duration (dynamic — OK)
|
||||
3. Add CSS rules for `#pathway-chart .js-plotly-plot, #pathway-chart .plot-container { height: 100% }` to propagate flex container height
|
||||
4. Verify CSS flex chain: `.chart-card` → `.dash-loading-callback` → `#chart-container` → `#pathway-chart`
|
||||
5. Rename "Cost" to "Cost per Patient" in heatmap metric toggles in `chart_card.py` and `trust_comparison.py`
|
||||
- Key files to read: `plotly_generator.py` (search for `height=`), `dash_app/assets/nhs.css` (flex chain), `chart_card.py` (heatmap toggle labels), `trust_comparison.py` (TC heatmap toggle labels)
|
||||
### Blocked items:
|
||||
- None
|
||||
|
||||
## Iteration 21 — 2026-02-07
|
||||
### Task: E.5 — Fix chart height to fill viewport + rename metric toggle labels
|
||||
### Why this task:
|
||||
- E.5 is the last remaining task. All other tasks (Phases A-D, E.1-E.4) are complete. Iteration 20 explicitly recommended E.5 with detailed guidance.
|
||||
### Status: COMPLETE
|
||||
### What was done:
|
||||
- **Removed 4 fixed heights** in `plotly_generator.py`:
|
||||
1. `create_cost_waterfall_figure()`: removed `height=500`
|
||||
2. `create_duration_cost_scatter_figure()`: removed `height=550`
|
||||
3. `create_drug_network_figure()`: removed `height=600`
|
||||
4. `create_trend_figure()`: removed `height=500`
|
||||
- **Kept 13 dynamic heights**: all `max(...)`, `fig_height`, and `dynamic_height` values remain — these scale with data and are correct behavior.
|
||||
- **Added CSS rules** in `nhs.css`: `#pathway-chart .js-plotly-plot, .plot-container, .svg-container { height: 100% !important }` to propagate flex container height into Plotly-rendered divs when no explicit figure height is set.
|
||||
- **Verified CSS flex chain**: `.chart-card` (flex:1) → `.dash-loading-callback > div` (flex:1) → `#chart-container` (flex:1) → `#pathway-chart` (flex:1) → `.js-plotly-plot/.plot-container/.svg-container` (height:100%) — full propagation from viewport to chart.
|
||||
- **Renamed metric toggle labels** in 2 files:
|
||||
- `chart_card.py`: "Cost" → "Cost per Patient", "Cost p.a." → "Cost per Patient p.a."
|
||||
- `trust_comparison.py`: same renames
|
||||
- `trends.py`: already correct from E.3 (verified, no changes needed)
|
||||
### Validation results:
|
||||
- Tier 1 (Code): `from dash_app.app import app` OK. `python run_dash.py` starts cleanly, HTTP 200.
|
||||
- Tier 2 (Visual): No fixed 500/550/600px cutoffs remain. Charts with no data-dependent height will expand to fill the flex container. Dynamic-height charts (e.g., 59-bar timeline at 1772px) remain unchanged.
|
||||
- Tier 3 (Functional): Metric toggles show "Patients | Cost per Patient | Cost per Patient p.a." in both PP heatmap and TC heatmap.
|
||||
### Files changed:
|
||||
- `src/visualization/plotly_generator.py` — removed 4 fixed height values
|
||||
- `dash_app/assets/nhs.css` — added Plotly div height propagation CSS
|
||||
- `dash_app/components/chart_card.py` — renamed heatmap metric toggle labels
|
||||
- `dash_app/components/trust_comparison.py` — renamed TC heatmap metric toggle labels
|
||||
- `IMPLEMENTATION_PLAN.md` — marked E.5 subtasks [x], all completion criteria [x]
|
||||
### Committed: 901bf39 "fix: responsive chart heights + rename cost metric labels (Task E.5)"
|
||||
### Patterns discovered:
|
||||
- Plotly `responsive=True` on `dcc.Graph` + `autosize=True` in figure layout is insufficient on its own — the Plotly-generated inner divs (`.js-plotly-plot`, `.plot-container`, `.svg-container`) need explicit `height: 100%` CSS to inherit the flex container height. Without this, they default to their content height.
|
||||
- The `!important` on the height rule is needed because Plotly sets inline styles on these elements.
|
||||
- Charts with dynamic heights (e.g., `max(400, n_bars * 28 + 120)`) correctly override the CSS since Plotly applies an inline `height` style which takes precedence over the CSS rule — `!important` only kicks in when no inline height is set.
|
||||
### Next iteration should:
|
||||
- ALL TASKS COMPLETE. See completion check below.
|
||||
### Blocked items:
|
||||
- None
|
||||
|
||||
## PROJECT COMPLETION
|
||||
All tasks in IMPLEMENTATION_PLAN.md are marked [x]. All completion criteria satisfied.
|
||||
Summary of all completed work (21 iterations):
|
||||
- **Phase A (4 tasks)**: Shared constants + _base_layout(), heatmap fixes, legend overflow fix, trust color differentiation
|
||||
- **Phase B (4 tasks)**: Title consistency, cost effectiveness gradient, Sankey freeform, heatmap metric toggle
|
||||
- **Phase C (4 tasks)**: Retention funnel, pathway depth distribution, duration vs cost scatter, drug network graph
|
||||
- **Phase D (3 tasks)**: Temporal trends CLI + Dash tab, drug timeline Gantt chart, average administered doses chart
|
||||
- **Phase E (5 tasks)**: Remove trends from PP, 3-view navigation, Trends landing page, drill-down, chart height fix + metric rename
|
||||
- **Total**: 20 tasks completed, 0 blocked, 9 PP tabs, 6 TC charts, 1 standalone Trends view, 17+ chart functions, all using shared styling
|
||||
@@ -1,362 +0,0 @@
|
||||
<#
|
||||
.SYNOPSIS
|
||||
Ralph Wiggum Loop - Visualization Improvements variant.
|
||||
|
||||
.DESCRIPTION
|
||||
Outer loop for iterative chart improvement (bug fixes, polish, new analytics).
|
||||
Each iteration spawns a fresh `claude --print` invocation.
|
||||
Memory persists via filesystem only: git commits, progress.txt, IMPLEMENTATION_PLAN.md, guardrails.md.
|
||||
|
||||
Runs until completion (<promise>COMPLETE</promise>) or circuit breaker trips.
|
||||
No arbitrary iteration limit — the loop continues until done.
|
||||
|
||||
Circuit breakers prevent runaway costs:
|
||||
- No git changes for N consecutive iterations (stalled)
|
||||
- Same error repeated N consecutive iterations (stuck)
|
||||
|
||||
.PARAMETER Model
|
||||
Claude model to use. Default: "opus".
|
||||
|
||||
.PARAMETER BranchName
|
||||
Optional git branch name. If provided, creates/checks out the branch before starting.
|
||||
|
||||
.PARAMETER MaxNoProgress
|
||||
Number of consecutive iterations with no git changes before circuit breaker trips. Default: 3.
|
||||
|
||||
.PARAMETER MaxSameError
|
||||
Number of consecutive iterations with the same error before circuit breaker trips. Default: 3.
|
||||
|
||||
.EXAMPLE
|
||||
.\ralph.ps1 -Model "opus" -BranchName "feature/dash-migration"
|
||||
|
||||
.EXAMPLE
|
||||
.\ralph.ps1 -Model "sonnet" -MaxNoProgress 2
|
||||
#>
|
||||
|
||||
param(
|
||||
[string]$Model = "opus",
|
||||
[string]$BranchName,
|
||||
[int]$MaxNoProgress = 3,
|
||||
[int]$MaxSameError = 3
|
||||
)
|
||||
|
||||
$ErrorActionPreference = "Stop"
|
||||
|
||||
$scriptDir = Split-Path -Parent $MyInvocation.MyCommand.Path
|
||||
$promptFile = Join-Path $scriptDir "RALPH_PROMPT.md"
|
||||
$planFile = Join-Path $scriptDir "IMPLEMENTATION_PLAN.md"
|
||||
$guardrailsFile = Join-Path $scriptDir "guardrails.md"
|
||||
$progressFile = Join-Path $scriptDir "progress.txt"
|
||||
$logDir = Join-Path $scriptDir "logs"
|
||||
|
||||
# --- Validation ---
|
||||
|
||||
if (-not (Test-Path $promptFile)) {
|
||||
Write-Error "RALPH_PROMPT.md not found at $promptFile"
|
||||
exit 1
|
||||
}
|
||||
|
||||
if (-not (Test-Path $planFile)) {
|
||||
Write-Error "IMPLEMENTATION_PLAN.md not found at $planFile"
|
||||
exit 1
|
||||
}
|
||||
|
||||
if (-not (Test-Path $guardrailsFile)) {
|
||||
Write-Warning "guardrails.md not found at $guardrailsFile - loop may miss known failure patterns"
|
||||
}
|
||||
|
||||
# Ensure progress.txt exists
|
||||
if (-not (Test-Path $progressFile)) {
|
||||
@"
|
||||
# Progress Log
|
||||
|
||||
## Design Context
|
||||
<!-- Design decisions and context go here -->
|
||||
|
||||
## Reflex Patterns
|
||||
<!-- Reusable Reflex patterns discovered during development -->
|
||||
|
||||
## Iteration Log
|
||||
<!-- Each iteration appends a structured entry below. See RALPH_PROMPT.md for format. -->
|
||||
"@ | Set-Content -Path $progressFile -Encoding UTF8
|
||||
Write-Host "Created progress.txt"
|
||||
}
|
||||
|
||||
# Ensure logs directory exists
|
||||
if (-not (Test-Path $logDir)) {
|
||||
New-Item -ItemType Directory -Path $logDir | Out-Null
|
||||
Write-Host "Created logs directory"
|
||||
}
|
||||
|
||||
# --- Git Setup ---
|
||||
|
||||
$gitInitialised = $false
|
||||
try {
|
||||
$result = git rev-parse --is-inside-work-tree 2>&1
|
||||
if ($LASTEXITCODE -eq 0 -and $result -eq "true") {
|
||||
$gitInitialised = $true
|
||||
}
|
||||
} catch {
|
||||
# Not a git repo — expected on first run
|
||||
}
|
||||
|
||||
if (-not $gitInitialised) {
|
||||
Write-Host "Initialising git repository..."
|
||||
git init
|
||||
git add -A
|
||||
git commit -m "Initial commit before Ralph loop"
|
||||
}
|
||||
|
||||
if ($BranchName) {
|
||||
$currentBranch = git branch --show-current
|
||||
if ($currentBranch -ne $BranchName) {
|
||||
$branchExists = git branch --list $BranchName
|
||||
if ($branchExists) {
|
||||
Write-Host "Switching to existing branch: $BranchName"
|
||||
git checkout $BranchName
|
||||
} else {
|
||||
Write-Host "Creating branch: $BranchName"
|
||||
git checkout -b $BranchName
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
# --- Circuit Breaker State ---
|
||||
|
||||
$noProgressCount = 0
|
||||
$lastErrorSignature = ""
|
||||
$sameErrorCount = 0
|
||||
|
||||
# Capture the HEAD commit hash before the loop starts
|
||||
$preLoopHead = git rev-parse HEAD 2>$null
|
||||
|
||||
# --- Main Loop ---
|
||||
|
||||
$promptContent = Get-Content -Path $promptFile -Raw
|
||||
|
||||
# Count existing iterations from progress.txt to track total across runs
|
||||
$existingIterations = 0
|
||||
if (Test-Path $progressFile) {
|
||||
$existingIterations = (Select-String -Path $progressFile -Pattern "## Iteration" -AllMatches | Measure-Object).Count
|
||||
}
|
||||
|
||||
Write-Host ""
|
||||
Write-Host "===== Ralph Wiggum Loop (Visualization Improvements) =====" -ForegroundColor Cyan
|
||||
Write-Host "Model: $Model | Runs until COMPLETE" -ForegroundColor Cyan
|
||||
Write-Host "Circuit breakers: no-progress=$MaxNoProgress, same-error=$MaxSameError" -ForegroundColor Cyan
|
||||
if ($BranchName) { Write-Host "Branch: $BranchName" -ForegroundColor Cyan }
|
||||
if ($existingIterations -gt 0) { Write-Host "Previous iterations: $existingIterations" -ForegroundColor Cyan }
|
||||
Write-Host "===========================================" -ForegroundColor Cyan
|
||||
Write-Host ""
|
||||
|
||||
$i = 0
|
||||
while ($true) {
|
||||
$i++
|
||||
$totalIteration = $existingIterations + $i
|
||||
Write-Host ""
|
||||
Write-Host "--- Iteration $i (Total: $totalIteration) ---" -ForegroundColor Yellow
|
||||
|
||||
# Record HEAD before this iteration
|
||||
$headBefore = git rev-parse HEAD 2>$null
|
||||
|
||||
# Show start time and status
|
||||
$iterStart = Get-Date
|
||||
Write-Host " Started: $($iterStart.ToString('HH:mm:ss'))" -ForegroundColor DarkGray
|
||||
Write-Host " Spawning Claude ($Model)..." -ForegroundColor DarkGray
|
||||
Write-Host ""
|
||||
|
||||
# Spawn fresh Claude instance with stream-json for tool call visibility
|
||||
$logFile = Join-Path $logDir "iteration_$totalIteration.log"
|
||||
$rawLogFile = Join-Path $logDir "iteration_$totalIteration.raw.jsonl"
|
||||
$maxRetries = 10
|
||||
$retryCount = 0
|
||||
$outputString = ""
|
||||
$apiOverloaded = $false
|
||||
|
||||
do {
|
||||
$apiOverloaded = $false
|
||||
$textBuilder = [System.Text.StringBuilder]::new()
|
||||
$toolCount = 0
|
||||
|
||||
# Clear raw log file for this attempt
|
||||
if (Test-Path $rawLogFile) { Remove-Item $rawLogFile -Force }
|
||||
|
||||
if ($retryCount -gt 0) {
|
||||
$backoffSeconds = [Math]::Pow(2, $retryCount - 1)
|
||||
Write-Host " [Retry $retryCount/$maxRetries] API overloaded, waiting $backoffSeconds seconds..." -ForegroundColor DarkYellow
|
||||
Start-Sleep -Seconds $backoffSeconds
|
||||
Write-Host " Retrying Claude invocation..." -ForegroundColor DarkGray
|
||||
}
|
||||
|
||||
$promptContent | claude --print --verbose --dangerously-skip-permissions --model $Model --output-format stream-json 2>&1 | ForEach-Object {
|
||||
$line = $_.ToString().Trim()
|
||||
if (-not $line) { return }
|
||||
|
||||
# Save raw event for debugging (with error handling for stream closure)
|
||||
try {
|
||||
Add-Content -Path $rawLogFile -Value $line -Encoding UTF8 -ErrorAction SilentlyContinue
|
||||
} catch {
|
||||
# Stream closed or file locked - ignore and continue
|
||||
}
|
||||
|
||||
try {
|
||||
$evt = $line | ConvertFrom-Json -ErrorAction Stop
|
||||
|
||||
# --- Tool use start (show tool name) ---
|
||||
if ($evt.type -eq 'content_block_start' -and $evt.content_block.type -eq 'tool_use') {
|
||||
$toolCount++
|
||||
$toolName = $evt.content_block.name
|
||||
Write-Host " [$toolName]" -ForegroundColor DarkCyan
|
||||
}
|
||||
# --- Assistant text content (streaming deltas) ---
|
||||
elseif ($evt.type -eq 'content_block_delta' -and $evt.delta.type -eq 'text_delta' -and $evt.delta.text) {
|
||||
Write-Host -NoNewline $evt.delta.text
|
||||
[void]$textBuilder.Append($evt.delta.text)
|
||||
}
|
||||
# --- Result event (error display + text capture for circuit breakers) ---
|
||||
elseif ($evt.type -eq 'result') {
|
||||
if ($evt.subtype -eq 'error_result' -and $evt.error) {
|
||||
Write-Host " [ERROR] $($evt.error)" -ForegroundColor Red
|
||||
[void]$textBuilder.AppendLine("ERROR: $($evt.error)")
|
||||
}
|
||||
elseif ($evt.result) {
|
||||
# Capture for circuit breaker detection; don't print
|
||||
# (text already displayed via streaming deltas above)
|
||||
[void]$textBuilder.AppendLine($evt.result)
|
||||
}
|
||||
}
|
||||
# --- Message-level content (final message summary) ---
|
||||
elseif ($evt.message -and $evt.message.content) {
|
||||
foreach ($block in $evt.message.content) {
|
||||
if ($block.type -eq 'text' -and $block.text) {
|
||||
Write-Host $block.text
|
||||
[void]$textBuilder.AppendLine($block.text)
|
||||
}
|
||||
elseif ($block.type -eq 'tool_use') {
|
||||
$toolCount++
|
||||
Write-Host " [$($block.name)]" -ForegroundColor DarkCyan
|
||||
}
|
||||
# Silently ignore tool_result and other block types
|
||||
}
|
||||
}
|
||||
# All other JSON events (input_json_delta, content_block_stop,
|
||||
# message_start, message_stop, ping, etc.) are silently ignored
|
||||
|
||||
} catch {
|
||||
# Not valid JSON — only print if it looks like meaningful stderr
|
||||
# (filter out JSON fragments from multi-line events)
|
||||
if ($line -and $line -notmatch '^\s*[\{\[\}\]"]') {
|
||||
Write-Host $line -ForegroundColor DarkYellow
|
||||
[void]$textBuilder.AppendLine($line)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
$outputString = $textBuilder.ToString()
|
||||
|
||||
# Check for 529 overloaded error
|
||||
if ($outputString -match "529.*overloaded|overloaded_error") {
|
||||
$apiOverloaded = $true
|
||||
$retryCount++
|
||||
if ($retryCount -ge $maxRetries) {
|
||||
Write-Host " [ERROR] API overloaded after $maxRetries retries, giving up." -ForegroundColor Red
|
||||
}
|
||||
}
|
||||
# Check for usage limit with cooldown (e.g. "Usage limit reached. Reset at 3 pm")
|
||||
elseif ($outputString -match "(?i)usage limit reached.*reset at (\d{1,2})(?::(\d{2}))?\s*(am|pm)") {
|
||||
$resetHour = [int]$Matches[1]
|
||||
$resetMinute = if ($Matches[2]) { [int]$Matches[2] } else { 0 }
|
||||
$resetAmPm = $Matches[3]
|
||||
|
||||
if ($resetAmPm -ieq "pm" -and $resetHour -ne 12) { $resetHour += 12 }
|
||||
elseif ($resetAmPm -ieq "am" -and $resetHour -eq 12) { $resetHour = 0 }
|
||||
|
||||
$now = Get-Date
|
||||
$resetTime = Get-Date -Hour $resetHour -Minute $resetMinute -Second 0
|
||||
if ($resetTime -le $now) { $resetTime = $resetTime.AddDays(1) }
|
||||
$resetTime = $resetTime.AddMinutes(2)
|
||||
|
||||
$waitSeconds = [Math]::Ceiling(($resetTime - $now).TotalSeconds)
|
||||
$waitMinutes = [Math]::Ceiling($waitSeconds / 60)
|
||||
|
||||
Write-Host ""
|
||||
Write-Host " [USAGE LIMIT] Reset at $($Matches[1]) $resetAmPm. Cooling down ~$waitMinutes minutes (until $($resetTime.ToString('HH:mm')))..." -ForegroundColor Yellow
|
||||
Start-Sleep -Seconds $waitSeconds
|
||||
Write-Host " [USAGE LIMIT] Cooldown complete. Retrying iteration..." -ForegroundColor Green
|
||||
|
||||
$apiOverloaded = $true
|
||||
# Don't increment retryCount — deterministic wait, not a flaky error
|
||||
}
|
||||
} while ($apiOverloaded -and $retryCount -lt $maxRetries)
|
||||
|
||||
$outputString | Set-Content -Path $logFile -Encoding UTF8
|
||||
|
||||
# Show elapsed time and tool count
|
||||
$elapsed = (Get-Date) - $iterStart
|
||||
Write-Host ""
|
||||
Write-Host " Finished: $(Get-Date -Format 'HH:mm:ss') (elapsed: $($elapsed.ToString('mm\:ss')), tools: $toolCount)" -ForegroundColor DarkGray
|
||||
|
||||
# --- Circuit Breaker: No Progress ---
|
||||
$headAfter = git rev-parse HEAD 2>$null
|
||||
if ($headAfter -eq $headBefore) {
|
||||
$noProgressCount++
|
||||
Write-Host " [Circuit Breaker] No git commits this iteration ($noProgressCount/$MaxNoProgress)" -ForegroundColor DarkYellow
|
||||
if ($noProgressCount -ge $MaxNoProgress) {
|
||||
Write-Host ""
|
||||
Write-Host "===== CIRCUIT BREAKER: NO PROGRESS =====" -ForegroundColor Red
|
||||
Write-Host "No git commits for $MaxNoProgress consecutive iterations. The loop is stalled." -ForegroundColor Red
|
||||
Write-Host "Check progress.txt and logs/ for details on what went wrong." -ForegroundColor Red
|
||||
exit 1
|
||||
}
|
||||
} else {
|
||||
$noProgressCount = 0
|
||||
}
|
||||
|
||||
# --- Circuit Breaker: Repeated Error ---
|
||||
$errorLines = $outputString | Select-String -Pattern "(?i)(error|exception|failed|fatal)[:.].*" -AllMatches
|
||||
if ($errorLines) {
|
||||
$filteredErrors = $errorLines.Matches | Where-Object { $_.Value -notmatch "529|overloaded" } | Select-Object -First 3
|
||||
$currentErrorSignature = ($filteredErrors | ForEach-Object { $_.Value }) -join "|"
|
||||
if ($currentErrorSignature -and $currentErrorSignature -eq $lastErrorSignature) {
|
||||
$sameErrorCount++
|
||||
Write-Host " [Circuit Breaker] Same error pattern repeated ($sameErrorCount/$MaxSameError)" -ForegroundColor DarkYellow
|
||||
if ($sameErrorCount -ge $MaxSameError) {
|
||||
Write-Host ""
|
||||
Write-Host "===== CIRCUIT BREAKER: REPEATED ERROR =====" -ForegroundColor Red
|
||||
Write-Host "Same error pattern for $MaxSameError consecutive iterations:" -ForegroundColor Red
|
||||
Write-Host " $currentErrorSignature" -ForegroundColor Red
|
||||
Write-Host "Check progress.txt and logs/ for details." -ForegroundColor Red
|
||||
exit 1
|
||||
}
|
||||
} elseif ($currentErrorSignature) {
|
||||
$sameErrorCount = 0
|
||||
}
|
||||
$lastErrorSignature = $currentErrorSignature
|
||||
} else {
|
||||
$sameErrorCount = 0
|
||||
$lastErrorSignature = ""
|
||||
}
|
||||
|
||||
# --- Push to Remote ---
|
||||
$hasRemote = git remote 2>$null
|
||||
if ($hasRemote) {
|
||||
$currentBranch = git branch --show-current
|
||||
git push origin $currentBranch 2>$null
|
||||
if ($LASTEXITCODE -eq 0) {
|
||||
Write-Host " Pushed to remote." -ForegroundColor Green
|
||||
} else {
|
||||
Write-Host " Push failed or no remote configured - continuing." -ForegroundColor DarkYellow
|
||||
}
|
||||
}
|
||||
|
||||
# --- Check for Completion ---
|
||||
if ($outputString -match "<promise>COMPLETE</promise>") {
|
||||
Write-Host ""
|
||||
Write-Host "===== COMPLETE =====" -ForegroundColor Green
|
||||
Write-Host "Visualization improvements finished after $i iteration(s) this run ($totalIteration total)." -ForegroundColor Green
|
||||
exit 0
|
||||
}
|
||||
|
||||
# Brief pause between iterations
|
||||
Start-Sleep -Seconds 2
|
||||
}
|
||||
@@ -1,99 +0,0 @@
|
||||
@echo off
|
||||
setlocal EnableDelayedExpansion
|
||||
|
||||
title HCD Patient Pathway Analysis
|
||||
echo.
|
||||
echo ==========================================
|
||||
echo HCD Patient Pathway Analysis
|
||||
echo NHS High-Cost Drug Treatment Pathways
|
||||
echo ==========================================
|
||||
echo.
|
||||
|
||||
:: -------------------------------------------------------
|
||||
:: First run vs subsequent run
|
||||
:: -------------------------------------------------------
|
||||
if exist ".venv\Scripts\activate.bat" (
|
||||
echo Ready to launch.
|
||||
goto :run_app
|
||||
)
|
||||
|
||||
echo First-time setup detected. This will:
|
||||
echo 1. Install uv (Python package manager)
|
||||
echo 2. Install Python 3.12 and dependencies
|
||||
echo 3. Build and start the application
|
||||
echo.
|
||||
echo Requires internet access. May take 3-5 minutes.
|
||||
echo.
|
||||
pause
|
||||
|
||||
:: -------------------------------------------------------
|
||||
:: Install uv if not available
|
||||
:: -------------------------------------------------------
|
||||
where uv >nul 2>&1
|
||||
if %ERRORLEVEL% neq 0 (
|
||||
echo.
|
||||
echo [1/3] Installing uv...
|
||||
powershell -ExecutionPolicy Bypass -Command "irm https://astral.sh/uv/install.ps1 | iex"
|
||||
|
||||
set "PATH=%USERPROFILE%\.local\bin;%PATH%"
|
||||
set "PATH=%USERPROFILE%\.cargo\bin;%PATH%"
|
||||
|
||||
where uv >nul 2>&1
|
||||
if !ERRORLEVEL! neq 0 (
|
||||
echo.
|
||||
echo ERROR: uv installation failed.
|
||||
echo Try installing manually: https://docs.astral.sh/uv/getting-started/installation/
|
||||
echo Then re-run this script.
|
||||
pause
|
||||
exit /b 1
|
||||
)
|
||||
echo uv installed successfully.
|
||||
) else (
|
||||
echo [1/3] uv already installed.
|
||||
)
|
||||
|
||||
:: -------------------------------------------------------
|
||||
:: Sync dependencies
|
||||
:: -------------------------------------------------------
|
||||
echo.
|
||||
echo [2/3] Installing Python and dependencies...
|
||||
echo (First run only — please wait)
|
||||
echo.
|
||||
|
||||
uv sync
|
||||
if %ERRORLEVEL% neq 0 (
|
||||
echo.
|
||||
echo ERROR: Dependency installation failed.
|
||||
echo Check your internet connection and try again.
|
||||
pause
|
||||
exit /b 1
|
||||
)
|
||||
|
||||
echo.
|
||||
echo Setup complete.
|
||||
|
||||
:: -------------------------------------------------------
|
||||
:: Run application
|
||||
:: -------------------------------------------------------
|
||||
:run_app
|
||||
echo.
|
||||
echo [3/3] Starting application...
|
||||
echo.
|
||||
echo App will open at: http://localhost:3000
|
||||
echo First launch builds the frontend (~60 seconds).
|
||||
echo Subsequent launches are fast.
|
||||
echo.
|
||||
echo To stop: close this window or press Ctrl+C
|
||||
echo ==========================================
|
||||
echo.
|
||||
|
||||
start "" cmd /c "timeout /t 8 /nobreak >nul && start http://localhost:3000"
|
||||
|
||||
uv run reflex run
|
||||
if %ERRORLEVEL% neq 0 (
|
||||
echo.
|
||||
echo Application exited with an error.
|
||||
echo Try deleting .web\ and running again.
|
||||
echo.
|
||||
pause
|
||||
)
|
||||
Reference in New Issue
Block a user