engine+api: plumb life events into the simulator

Until now life events were stored but ignored by the engine — pure
metadata. Now they actually move portfolios.

Engine:
- simulator.simulate() takes optional cashflow_adjustments: a (n_years,)
  real-GBP array applied each year *after* savings + return but
  *before* withdrawal. Positive = inflow, negative = outflow.
- New fire_planner/life_events.py with EventInput dataclass +
  events_to_cashflow_array(events, horizon). Handles ranged deltas,
  one-time amounts, disabled events, year clipping past horizon,
  negative year_start (clipped to 0), and summing multiple events.

API:
- /simulate accepts optional life_events list. Server converts each
  to EventInput, builds cashflow_adjustments, passes to simulate().
- Frontend Run-now on scenario detail now fetches the scenario's
  life events and includes them in the request — projections finally
  reflect "retire at 50, kid born at y3, inheritance at y22".

Tests: 11 events helper + 4 end-to-end engine + 1 API integration =
16 new tests. 188 total (was 172). mypy strict + ruff clean.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

tests/test_api_simulate.py

@@ -113,6 +113,42 @@ async def test_compare_runs_two_scenarios(client: AsyncClient) -> None:
     assert all(len(r["yearly"]) == 20 for r in results)
 
 
+async def test_simulate_with_life_events_changes_outcome(client: AsyncClient) -> None:
+    """Same params with vs without a £500k inheritance at year 5 — the
+    inheritance run must end with strictly more median NW."""
+    base_req = {
+        "jurisdiction": "uk",
+        "strategy": "trinity",
+        "leave_uk_year": 0,
+        "glide_path": "static_60_40",
+        "spending_gbp": "60000",
+        "nw_seed_gbp": "1500000",
+        "horizon_years": 30,
+        "n_paths": 200,
+        "seed": 42,
+    }
+    base = await client.post("/simulate", json=base_req)
+    assert base.status_code == 200, base.text
+
+    enhanced = await client.post(
+        "/simulate",
+        json={
+            **base_req,
+            "life_events": [
+                {
+                    "year_start": 5,
+                    "one_time_amount_gbp": "500000",
+                }
+            ],
+        },
+    )
+    assert enhanced.status_code == 200, enhanced.text
+
+    base_p50 = float(base.json()["p50_ending_gbp"])
+    enhanced_p50 = float(enhanced.json()["p50_ending_gbp"])
+    assert enhanced_p50 > base_p50
+
+
 async def test_compare_rejects_single_scenario(client: AsyncClient) -> None:
     resp = await client.post(
         "/compare",

tests/test_life_events.py

@@ -0,0 +1,107 @@
+"""Tests for the life-events → cashflow-array helper."""
+from __future__ import annotations
+
+import numpy as np
+import pytest
+
+from fire_planner.life_events import EventInput, events_to_cashflow_array
+
+
+def test_empty_events_yield_zero_array() -> None:
+    arr = events_to_cashflow_array([], horizon_years=5)
+    np.testing.assert_array_equal(arr, np.zeros(5))
+
+
+def test_one_time_event_lands_at_year_start() -> None:
+    arr = events_to_cashflow_array(
+        [EventInput(year_start=3, one_time_amount_gbp=250_000)],
+        horizon_years=10,
+    )
+    expected = np.zeros(10)
+    expected[3] = 250_000
+    np.testing.assert_array_equal(arr, expected)
+
+
+def test_ranged_delta_applied_inclusive() -> None:
+    arr = events_to_cashflow_array(
+        [EventInput(year_start=2, year_end=5, delta_gbp_per_year=-10_000)],
+        horizon_years=10,
+    )
+    expected = np.zeros(10)
+    expected[2:6] = -10_000  # 2,3,4,5 inclusive
+    np.testing.assert_array_equal(arr, expected)
+
+
+def test_year_end_none_is_one_time() -> None:
+    """Ranged events default year_end == year_start."""
+    arr = events_to_cashflow_array(
+        [EventInput(year_start=4, year_end=None, delta_gbp_per_year=-5_000)],
+        horizon_years=10,
+    )
+    expected = np.zeros(10)
+    expected[4] = -5_000
+    np.testing.assert_array_equal(arr, expected)
+
+
+def test_disabled_events_skipped() -> None:
+    arr = events_to_cashflow_array(
+        [
+            EventInput(year_start=0, one_time_amount_gbp=1_000_000, enabled=False),
+            EventInput(year_start=1, delta_gbp_per_year=-50_000, year_end=3, enabled=False),
+        ],
+        horizon_years=5,
+    )
+    np.testing.assert_array_equal(arr, np.zeros(5))
+
+
+def test_events_past_horizon_clipped() -> None:
+    """Events starting at or beyond the horizon don't apply at all;
+    ranged events that overlap the horizon get clipped to the last year."""
+    arr = events_to_cashflow_array(
+        [
+            EventInput(year_start=10, one_time_amount_gbp=100_000),
+            EventInput(year_start=8, year_end=15, delta_gbp_per_year=-5_000),
+        ],
+        horizon_years=10,
+    )
+    # First event: year 10 is outside (horizon 0..9), so nothing.
+    # Second event: clipped to years 8..9.
+    expected = np.zeros(10)
+    expected[8] = -5_000
+    expected[9] = -5_000
+    np.testing.assert_array_equal(arr, expected)
+
+
+def test_multiple_events_sum() -> None:
+    arr = events_to_cashflow_array(
+        [
+            EventInput(year_start=0, year_end=4, delta_gbp_per_year=-12_000),
+            EventInput(year_start=2, one_time_amount_gbp=50_000),
+            EventInput(year_start=3, delta_gbp_per_year=20_000, year_end=10),
+        ],
+        horizon_years=10,
+    )
+    expected = np.zeros(10)
+    expected[0:5] += -12_000  # event 1: years 0..4
+    expected[2] += 50_000  # event 2: year 2 lump sum
+    expected[3:10] += 20_000  # event 3: years 3..9 (clipped from 3..10)
+    np.testing.assert_array_equal(arr, expected)
+
+
+def test_negative_year_start_clipped_to_zero() -> None:
+    arr = events_to_cashflow_array(
+        [EventInput(year_start=-2, year_end=2, delta_gbp_per_year=-1_000)],
+        horizon_years=5,
+    )
+    expected = np.zeros(5)
+    expected[0:3] = -1_000  # 0,1,2
+    np.testing.assert_array_equal(arr, expected)
+
+
+@pytest.mark.parametrize("amount", [0, 0.0, None])
+def test_zero_or_none_one_time_amount_skipped(amount: float | None) -> None:
+    arr = events_to_cashflow_array(
+        [EventInput(year_start=2, one_time_amount_gbp=amount)],
+        horizon_years=5,
+    )
+    np.testing.assert_array_equal(arr, np.zeros(5))

tests/test_simulator_events.py

@@ -0,0 +1,73 @@
+"""End-to-end: cashflow_adjustments make portfolios bigger or smaller."""
+from __future__ import annotations
+
+import numpy as np
+
+from fire_planner.glide_path import static
+from fire_planner.life_events import EventInput, events_to_cashflow_array
+from fire_planner.simulator import simulate
+from fire_planner.strategies.trinity import TrinityStrategy
+from fire_planner.tax.malaysia import MalaysiaTaxRegime
+from tests.test_simulator import fixed_paths
+
+
+def _baseline_kwargs() -> dict[str, object]:
+    """0% real returns, 25y, Trinity 4%, no taxes (Malaysia) — predictable."""
+    paths = fixed_paths(n_paths=1, n_years=25, stock_ret=0.0, bond_ret=0.0, cpi=0.0)
+    return dict(
+        paths=paths,
+        initial_portfolio=1_000_000.0,
+        spending_target=40_000.0,
+        glide=static(0.6),
+        strategy=TrinityStrategy(initial_rate=0.04),
+        regime=MalaysiaTaxRegime(),
+    )
+
+
+def test_no_adjustments_matches_baseline() -> None:
+    base = simulate(**_baseline_kwargs())  # type: ignore[arg-type]
+    with_zero = simulate(**_baseline_kwargs(), cashflow_adjustments=np.zeros(25))  # type: ignore[arg-type]
+    np.testing.assert_allclose(base.portfolio_real, with_zero.portfolio_real)
+
+
+def test_one_time_inheritance_lifts_portfolio() -> None:
+    kwargs = _baseline_kwargs()
+    adj = events_to_cashflow_array(
+        [EventInput(year_start=10, one_time_amount_gbp=250_000)],
+        horizon_years=25,
+    )
+    base = simulate(**kwargs)  # type: ignore[arg-type]
+    enhanced = simulate(**kwargs, cashflow_adjustments=adj)  # type: ignore[arg-type]
+    # Year 11 onward should be exactly £250k higher under 0% returns +
+    # constant Trinity withdrawal.
+    delta = enhanced.portfolio_real[0, 11:] - base.portfolio_real[0, 11:]
+    assert np.all(delta > 0)
+    # Year 11 specifically: +£250k landed at end of year 10, withdrawn
+    # nothing extra in y10. By y11 just propagated forward.
+    assert enhanced.portfolio_real[0, 11] - base.portfolio_real[0, 11] == 250_000
+
+
+def test_ongoing_expense_drains_portfolio() -> None:
+    kwargs = _baseline_kwargs()
+    adj = events_to_cashflow_array(
+        [EventInput(year_start=0, year_end=5, delta_gbp_per_year=-20_000)],
+        horizon_years=25,
+    )
+    base = simulate(**kwargs)  # type: ignore[arg-type]
+    drained = simulate(**kwargs, cashflow_adjustments=adj)  # type: ignore[arg-type]
+    # 6 years × £20k expense = £120k less by end of year 6, 0% growth.
+    delta = base.portfolio_real[0, 6] - drained.portfolio_real[0, 6]
+    assert delta == 120_000
+
+
+def test_event_can_force_failure() -> None:
+    """A massive expense early on can ruin an otherwise-successful run."""
+    kwargs = _baseline_kwargs()
+    adj = events_to_cashflow_array(
+        [EventInput(year_start=2, one_time_amount_gbp=-1_500_000)],
+        horizon_years=25,
+    )
+    base = simulate(**kwargs)  # type: ignore[arg-type]
+    ruined = simulate(**kwargs, cashflow_adjustments=adj)  # type: ignore[arg-type]
+    assert base.success_rate == 1.0
+    assert ruined.success_rate == 0.0