fire-planner: life-event spending bumps now reflected in fan + auto-

refresh on scenario edits

Two fixes for the user's report that adding a £100k life-event spend
didn't change the chart:

Engine (simulator.py)
- New `extra_outflows` param. cashflow_adjustments still drains the
  portfolio at start-of-year as before, but the simulator now ALSO
  records the spending in `withdrawal_hist[p, y]` so the chart's red
  median-withdrawal trace shows the bump. Without this, the £100k
  silently came out of the portfolio but the user-facing withdrawal
  trace stayed at the strategy's flat 4% draw.
- simulate.py wires extra_outflows = essential + discretionary
  category outflows from life events.

UX (ScenarioDetail.tsx)
- New auto-refresh: when life events / income streams / flex rules
  change for a scenario, the page fires `/simulate` automatically
  with 2,000 paths and uses the result as the primary fan/year-stats
  source. The persisted MC run is only consulted as a fallback for
  scenarios with no overrides.
- Fan chart title gains a "live preview · Xs · Ny" pill while a sim
  is current, and "re-running…" while a fresh one is in flight.
- Removed the now-redundant "Live preview run" duplicate card lower
  down — the main chart IS the live preview.
- Year-stats badge row reads from sim.data when available so changes
  propagate immediately to NW / Δ NW / Spending / Taxes.

247 pytest pass (+1 new); mypy + ruff clean; frontend typecheck/test/
build green.

fire_planner/api/simulate.py

@@ -111,6 +111,7 @@ def _project(req: SimulateRequest, paths: np.ndarray) -> tuple[SimulationResult,
 
     cashflow_adjustments = None
     discretionary_outflows = None
+    extra_outflows = None
     if req.life_events:
         engine_events = [
             EventInput(
@@ -126,6 +127,12 @@ def _project(req: SimulateRequest, paths: np.ndarray) -> tuple[SimulationResult,
         cashflow_adjustments = events_to_cashflow_array(engine_events, req.horizon_years)
         category_outflows = events_to_category_outflows(engine_events, req.horizon_years)
         discretionary_outflows = category_outflows.get("discretionary")
+        # extra_outflows feeds the withdrawal-trace display: total of
+        # essential + discretionary spending events surfaces alongside
+        # the strategy's draw on the chart.
+        essential = category_outflows.get("essential")
+        if essential is not None and discretionary_outflows is not None:
+            extra_outflows = essential + discretionary_outflows
 
     engine_flex = [
         EngineFlexRule(
@@ -175,6 +182,7 @@ def _project(req: SimulateRequest, paths: np.ndarray) -> tuple[SimulationResult,
         income_inflows=income_inflows,
         income_taxable=income_taxable,
         discretionary_outflows=discretionary_outflows,
+        extra_outflows=extra_outflows,
         flex_rules=engine_flex,
     )
     elapsed = time.perf_counter() - started

fire_planner/simulator.py

@@ -188,6 +188,7 @@ def simulate(
     income_inflows: npt.NDArray[np.float64] | None = None,
     income_taxable: npt.NDArray[np.float64] | None = None,
     discretionary_outflows: npt.NDArray[np.float64] | None = None,
+    extra_outflows: npt.NDArray[np.float64] | None = None,
     flex_rules: list[FlexRule] | None = None,
 ) -> SimulationResult:
     """Run the MC simulation. `paths` shape: (n_paths, n_years, 3).
@@ -228,6 +229,8 @@ def simulate(
         income_taxable = np.zeros(n_years, dtype=np.float64)
     if discretionary_outflows is None:
         discretionary_outflows = np.zeros(n_years, dtype=np.float64)
+    if extra_outflows is None:
+        extra_outflows = np.zeros(n_years, dtype=np.float64)
     rules = list(flex_rules) if flex_rules else []
     # Track running ATH per path so we can decide flex cuts each year.
     ath = np.full(n_paths, float(initial_portfolio), dtype=np.float64)
@@ -295,7 +298,13 @@ def simulate(
             # `median_lifetime_tax_gbp` cell while the fan chart and
             # success rate were identical across regimes.
             portfolio[p] = max(0.0, portfolio[p] - w - t)
-            withdrawal_hist[p, y] = w
+            # The chart's "withdrawal" trace shows total spending as a
+            # user would experience it, not just the strategy's draw.
+            # `extra_outflows[y]` is already in cashflow_adjustments[y]
+            # (which drained the portfolio at start-of-year), so we just
+            # *report* it here — no double deduction. Keeps the median
+            # withdrawal line in step with the spending profile chart.
+            withdrawal_hist[p, y] = w + float(extra_outflows[y])
             tax_hist[p, y] = t
             last_withdrawal[p] = w