import { describe, it, expect } from 'vitest';

import {
  classifyTier,
  computeHeat,
  DEFAULT_RECOMMENDER_SETTINGS,
} from '@/lib/services/berth-recommender.service';

describe('classifyTier', () => {
  it('"A" when there is no interest history at all', () => {
    expect(classifyTier({ activeInterestCount: 0, lostCount: 0, maxActiveStage: 0 })).toBe('A');
  });
  it('"B" when only lost interests exist (no active)', () => {
    expect(classifyTier({ activeInterestCount: 0, lostCount: 2, maxActiveStage: 0 })).toBe('B');
  });
  // L-001 renumber: 7-stage ranks are 1=enquiry, 2=qualified/nurturing,
  // 3=eoi, 4=reservation, 5=deposit_paid, 6=contract. Tier D fires at
  // deposit_paid (5) or later.
  it('"C" when an active interest is in an early stage (eoi)', () => {
    expect(classifyTier({ activeInterestCount: 1, lostCount: 0, maxActiveStage: 3 })).toBe('C');
  });
  it('"C" even when a prior interest was lost, if there is an active one', () => {
    expect(classifyTier({ activeInterestCount: 1, lostCount: 5, maxActiveStage: 2 })).toBe('C');
  });
  it('"D" when an active interest is at deposit or beyond', () => {
    expect(classifyTier({ activeInterestCount: 1, lostCount: 0, maxActiveStage: 5 })).toBe('D');
    expect(classifyTier({ activeInterestCount: 1, lostCount: 0, maxActiveStage: 6 })).toBe('D');
  });
  it('still "C" at reservation (stage 4) - tier D only kicks in at deposit', () => {
    expect(classifyTier({ activeInterestCount: 1, lostCount: 0, maxActiveStage: 4 })).toBe('C');
  });
});

describe('computeHeat', () => {
  const w = DEFAULT_RECOMMENDER_SETTINGS;
  const NOW = new Date('2026-05-05T00:00:00Z');

  it('zero heat when nothing in history', () => {
    const h = computeHeat(
      {
        latestFallthroughAt: null,
        totalInterestCount: 0,
        eoiSignedCount: 0,
        fallthroughMaxStage: 0,
      },
      w,
      NOW,
    );
    expect(h.total).toBe(0);
  });

  it('full recency for a fall-through within the last 30 days', () => {
    const h = computeHeat(
      {
        latestFallthroughAt: new Date('2026-04-25T00:00:00Z'),
        totalInterestCount: 0,
        eoiSignedCount: 0,
        fallthroughMaxStage: 1,
      },
      w,
      NOW,
    );
    // recency component should be the full heat_weight_recency (30)
    expect(h.recency).toBeCloseTo(30, 1);
  });

  it('zero recency for an ancient fall-through (>1 year)', () => {
    const h = computeHeat(
      {
        latestFallthroughAt: new Date('2024-01-01T00:00:00Z'),
        totalInterestCount: 0,
        eoiSignedCount: 0,
        fallthroughMaxStage: 1,
      },
      w,
      NOW,
    );
    expect(h.recency).toBe(0);
  });

  it('full furthest-stage when the fall-through reached deposit', () => {
    const h = computeHeat(
      {
        latestFallthroughAt: null,
        totalInterestCount: 0,
        eoiSignedCount: 0,
        fallthroughMaxStage: 5, // deposit_paid (was deposit_10pct=6 pre-refactor)
      },
      w,
      NOW,
    );
    expect(h.furthestStage).toBeCloseTo(40, 1);
  });

  it('saturates interest-count at 5+', () => {
    const h = computeHeat(
      {
        latestFallthroughAt: null,
        totalInterestCount: 10,
        eoiSignedCount: 0,
        fallthroughMaxStage: 0,
      },
      w,
      NOW,
    );
    expect(h.interestCount).toBeCloseTo(15, 1); // full weight
  });

  it('saturates EOI-count at 3+', () => {
    const h = computeHeat(
      {
        latestFallthroughAt: null,
        totalInterestCount: 0,
        eoiSignedCount: 5,
        fallthroughMaxStage: 0,
      },
      w,
      NOW,
    );
    expect(h.eoiCount).toBeCloseTo(15, 1);
  });

  it('total ≈ 100 when everything is maxed', () => {
    const h = computeHeat(
      {
        latestFallthroughAt: new Date('2026-04-25T00:00:00Z'),
        totalInterestCount: 5,
        eoiSignedCount: 3,
        fallthroughMaxStage: 6,
      },
      w,
      NOW,
    );
    expect(h.total).toBeGreaterThanOrEqual(99);
    expect(h.total).toBeLessThanOrEqual(100);
  });

  it('respects tunable per-port weights (skewed toward recency)', () => {
    const skewed = {
      heatWeightRecency: 100,
      heatWeightFurthestStage: 0,
      heatWeightInterestCount: 0,
      heatWeightEoiCount: 0,
    };
    const recent = computeHeat(
      {
        latestFallthroughAt: new Date('2026-04-25T00:00:00Z'),
        totalInterestCount: 0,
        eoiSignedCount: 0,
        fallthroughMaxStage: 0,
      },
      skewed,
      NOW,
    );
    expect(recent.total).toBeCloseTo(100, 1);

    const old = computeHeat(
      {
        latestFallthroughAt: new Date('2024-01-01T00:00:00Z'),
        totalInterestCount: 5,
        eoiSignedCount: 3,
        fallthroughMaxStage: 6,
      },
      skewed,
      NOW,
    );
    expect(old.total).toBe(0);
  });

  it('zero-weights guard (no division-by-zero blow-up)', () => {
    const zeros = {
      heatWeightRecency: 0,
      heatWeightFurthestStage: 0,
      heatWeightInterestCount: 0,
      heatWeightEoiCount: 0,
    };
    const h = computeHeat(
      {
        latestFallthroughAt: new Date(),
        totalInterestCount: 5,
        eoiSignedCount: 3,
        fallthroughMaxStage: 6,
      },
      zeros,
      NOW,
    );
    expect(h.total).toBe(0);
  });
});

// ─── W7 snapshot lockfile - locks current tier-ladder boundaries and heat
// ordering so weight-tuning changes can't silently shift outputs. The
// existing toBe / toBeCloseTo tests above cover correctness; these
// inline snapshots are the regression-catching tripwires.

describe('W7 snapshots - tier-ladder boundaries', () => {
  it.each([
    [0, 0, 0],
    [0, 1, 0],
    [0, 5, 0],
    [1, 0, 1],
    [1, 0, 3],
    [1, 0, 4],
    [1, 0, 5],
    [1, 0, 6],
    [1, 5, 6],
    [2, 0, 5],
    [3, 2, 4],
  ])(
    'tier(active=%i, lost=%i, stage=%i) is stable',
    (activeInterestCount, lostCount, maxActiveStage) => {
      expect({
        in: { activeInterestCount, lostCount, maxActiveStage },
        out: classifyTier({ activeInterestCount, lostCount, maxActiveStage }),
      }).toMatchSnapshot();
    },
  );
});

describe('W7 snapshots - heat at canonical inputs', () => {
  const NOW = new Date('2026-05-05T00:00:00Z');
  const w = DEFAULT_RECOMMENDER_SETTINGS;

  it.each([
    // [label, fallthroughDaysAgo|null, totalInterestCount, eoiSignedCount, fallthroughMaxStage]
    ['cold (no history)', null, 0, 0, 0],
    ['recent fallthrough at enquiry stage', 5, 1, 0, 1],
    ['recent fallthrough at eoi stage', 5, 2, 1, 3],
    ['recent fallthrough at deposit stage (deepest hurt)', 5, 5, 3, 5],
    ['old fallthrough at deposit stage (recency decayed)', 120, 5, 3, 5],
    ['no fallthrough but many interests', null, 8, 4, 0],
    ['typical mid-funnel hot lead', 14, 3, 2, 4],
  ])('heat: %s', (_label, daysAgo, totalInterestCount, eoiSignedCount, fallthroughMaxStage) => {
    const latestFallthroughAt =
      daysAgo === null ? null : new Date(NOW.getTime() - daysAgo * 86400 * 1000);
    const h = computeHeat(
      { latestFallthroughAt, totalInterestCount, eoiSignedCount, fallthroughMaxStage },
      w,
      NOW,
    );
    // Snapshot the rounded breakdown - exact float math (toBeCloseTo)
    // is covered above; this locks the relative ordering + magnitude.
    expect({
      total: Math.round(h.total * 1000) / 1000,
      recency: Math.round(h.recency * 1000) / 1000,
      furthestStage: Math.round(h.furthestStage * 1000) / 1000,
      interestCount: Math.round(h.interestCount * 1000) / 1000,
      eoiCount: Math.round(h.eoiCount * 1000) / 1000,
    }).toMatchSnapshot();
  });
});