"""Engine pins — every number hand-checked before pinning.

RA_benefit = v×(1−rf), RA_cost = v×(1+rf), PV = Σ RA_n/(1.1)^n, initial
undiscounted. The composite reproduction lands within Forrester's own table
rounding of the published Financial Summary (benefits PV $223 low, costs PV
$0.22 low) — pinned both engine-exact (±$1) and against PUBLISHED (±$1,000,
the convention the retired workflow notebooks used).
"""

import pytest

from teicalc import (
    BENEFITS_VERBATIM,
    COSTS_VERBATIM,
    PUBLISHED,
    X_LABELS,
    YEAR_INDEX,
    YEARS,
    by_calendar,
    compute_summary,
    discount_factor,
    money,
    npv,
    payback_label,
    payback_months,
    payback_years,
    roi_pct,
)

# Hand-checked risk-adjusted PVs per row (see module docstring).
ROW_PVS = {
    "ai_contact_resolution": 51_699_826.78,
    "ai_content_sentiment": 11_326_357.54,
    "ai_forecasting_supervision": 19_469_777.37,
    "data_driven_profit_lift": 3_123_065.36,
    "legacy_solution_savings": 16_077_540.50,
    "amazon_connect_usage": 20_819_775.10,
    "implementation_migration": 1_555_794.82,
    "ongoing_management": 607_505.86,
}


@pytest.fixture(scope="module")
def composite():
    return compute_summary(BENEFITS_VERBATIM, COSTS_VERBATIM, 0.10)


def test_calendar_mapping():
    assert YEARS == [2026, 2027, 2028]
    assert YEAR_INDEX == {2026: 1, 2027: 2, 2028: 3}
    assert X_LABELS == ["Initial", "2026", "2027", "2028"]
    assert by_calendar({"1": 10, "2": 20, "3": 30}) == {2026: 10, 2027: 20, 2028: 30}


def test_primitives():
    assert discount_factor(0, 0.10) == 1.0
    assert discount_factor(1, 0.10) == pytest.approx(1 / 1.1)
    assert npv([110], 0.10) == pytest.approx(100)
    assert npv([110], 0.10, initial=-50) == pytest.approx(50)
    assert roi_pct(101_696_791, 22_983_076) == pytest.approx(342.48, abs=0.1)
    assert roi_pct(100, 0) == 0.0
    assert money(78_713_492) == "$78.7M"
    assert money(-250_000) == "-$250K"


def test_payback_edges():
    assert payback_years(0, [100]) == 0.0
    assert payback_years(500, []) is None
    assert payback_years(500, [-100, 200]) is None          # gap widens, never covered
    assert payback_years(300, [-100, 400]) == pytest.approx(2.0)
    assert payback_months(100, [1_200]) == pytest.approx(1.0)
    assert payback_label(None) == "beyond 2028"
    assert payback_label(0.0) == "immediate"
    assert payback_label(0.7178) == "0.7 months (~Jan 2026)"
    assert payback_label(14.2) == "14.2 months (~Mar 2027)"


def test_per_row_pvs(composite):
    rows = composite["rows"]["benefits"] + composite["rows"]["costs"]
    assert len(rows) == 8
    for row in rows:
        assert row["pv"] == pytest.approx(ROW_PVS[row["field_key"]], abs=1)


def test_composite_totals_engine_exact(composite):
    assert composite["benefits_pv"] == pytest.approx(101_696_567.55, abs=1)
    assert composite["costs_pv"] == pytest.approx(22_983_075.78, abs=1)
    assert composite["npv"] == pytest.approx(78_713_491.78, abs=1)
    assert composite["roi_pct"] == pytest.approx(342.4846, abs=0.01)
    assert composite["payback_months"] == pytest.approx(0.7178, abs=0.001)
    assert composite["initial_costs"] == pytest.approx(1_196_250, abs=0.01)


def test_composite_reproduces_published(composite):
    assert composite["benefits_pv"] == pytest.approx(PUBLISHED["benefits_pv"], abs=1_000)
    assert composite["costs_pv"] == pytest.approx(PUBLISHED["costs_pv"], abs=1_000)
    assert composite["npv"] == pytest.approx(PUBLISHED["npv"], abs=1_000)
    assert round(composite["roi_pct"]) == PUBLISHED["roi_pct"]
    assert composite["payback_months"] < PUBLISHED["payback_months_max"]
    assert composite["payback_label"] == "0.7 months (~Jan 2026)"


def test_yearly_schedules(composite):
    assert composite["benefits_by_year"][2026] == pytest.approx(27_279_019.00, abs=0.01)
    assert composite["benefits_by_year"][2027] == pytest.approx(40_333_658.20, abs=0.01)
    assert composite["benefits_by_year"][2028] == pytest.approx(57_983_494.40, abs=0.01)
    assert composite["costs_by_year"][2026] == pytest.approx(7_281_066.70, abs=0.01)
    assert composite["costs_by_year"][2027] == pytest.approx(8_771_168.50, abs=0.01)
    assert composite["costs_by_year"][2028] == pytest.approx(10_539_889.05, abs=0.01)
    assert composite["cumulative_net_by_year"][2028] == pytest.approx(97_807_797.35, abs=0.01)


def test_cross_foots(composite):
    assert composite["npv"] == pytest.approx(
        composite["benefits_pv"] - composite["costs_pv"], abs=0.01)
    for y in YEARS:
        assert composite["net_by_year"][y] == pytest.approx(
            composite["benefits_by_year"][y] - composite["costs_by_year"][y], abs=0.01)
    assert composite["cumulative_net_by_year"][2028] == pytest.approx(
        sum(composite["net_by_year"].values()) - composite["initial_costs"], abs=0.01)
    for table, total in (("benefits", "benefits_pv"), ("costs", "costs_pv")):
        assert sum(r["pv"] for r in composite["rows"][table]) == pytest.approx(
            composite[total], abs=0.01)