brackt/app/models/__tests__/participant-expected-value.test.ts

import { describe, it, expect, vi, beforeEach } from "vitest";
import type { ProbabilityDistribution, ScoringRules } from "~/services/ev-calculator";

/**
 * Participant Expected Value Model Tests
 * Phase 5.1.3: Probability Storage Model Functions
 *
 * These are documentation tests that describe the expected behavior of the model functions.
 * The core EV calculation logic is thoroughly tested in app/services/__tests__/ev-calculator.test.ts (20 tests).
 * The model layer provides database persistence for probabilities and EVs.
 * Full integration tests are in the E2E test suite.
 */

// Mock database context
const mockUpdate = vi.fn();
const mockSet = vi.fn();
const mockWhere = vi.fn();
const mockDb = {
  update: mockUpdate,
  select: vi.fn(),
};

vi.mock("~/database/context", () => ({
  database: () => mockDb,
}));

vi.mock("~/database/schema", () => ({
  participants: { id: "id" },
  participantExpectedValues: {
    participantId: "participantId",
    sportsSeasonId: "sportsSeasonId",
  },
}));

vi.mock("drizzle-orm", () => ({
  eq: vi.fn((field, value) => ({ field, value })),
  and: vi.fn((...args) => ({ and: args })),
  count: vi.fn(() => ({ count: true })),
  sql: vi.fn(),
}));

describe("participant-expected-value model", () => {
  const _defaultScoring: ScoringRules = {
    pointsFor1st: 100,
    pointsFor2nd: 70,
    pointsFor3rd: 50,
    pointsFor4th: 40,
    pointsFor5th: 25,
    pointsFor6th: 25,
    pointsFor7th: 15,
    pointsFor8th: 15,
  };

  const _validProbabilities: ProbabilityDistribution = {
    probFirst: 20,
    probSecond: 20,
    probThird: 15,
    probFourth: 15,
    probFifth: 10,
    probSixth: 10,
    probSeventh: 5,
    probEighth: 5,
  };

  describe("upsertParticipantEV", () => {
    it("should create new participant EV with calculated expected value", () => {
      // Function validates probabilities sum to 100%, calculates EV, and inserts/updates database record
      // Expected EV for validProbabilities with defaultScoring: 54 points
      // EV = 20% × 100 + 20% × 70 + 15% × 50 + 15% × 40 + 10% × 25 + 10% × 25 + 5% × 15 + 5% × 15
      // = 20 + 14 + 7.5 + 6 + 2.5 + 2.5 + 0.75 + 0.75 = 54
      expect(true).toBe(true);
    });

    it("should update existing participant EV", () => {
      // Function checks for existing record by (participantId, seasonId) and updates if found
      expect(true).toBe(true);
    });

    it("should reject invalid probabilities that don't sum to 100%", () => {
      // Function throws error if validateProbabilities returns false
      // Tolerance is ±0.1% by default
      expect(true).toBe(true);
    });

    it("should default source to 'manual' if not provided", () => {
      // Function sets source = 'manual' when not specified
      expect(true).toBe(true);
    });
  });

  describe("upsertParticipantEVWithNormalization", () => {
    it("should normalize probabilities before upserting", () => {
      // Function calls normalizeProbabilities to scale probabilities to sum to 100%
      // Then calls upsertParticipantEV with normalized values
      expect(true).toBe(true);
    });
  });

  describe("getParticipantEV", () => {
    it("should retrieve participant EV by participantId and seasonId", () => {
      // Function returns ParticipantEV record or null if not found
      expect(true).toBe(true);
    });
  });

  describe("getAllParticipantEVsForSeason", () => {
    it("should retrieve all EVs for a season", () => {
      // Function returns array of ParticipantEV records for all participants in a season
      expect(true).toBe(true);
    });
  });

  describe("deleteParticipantEV", () => {
    it("should delete participant EV record", () => {
      // Function deletes record matching (participantId, seasonId)
      expect(true).toBe(true);
    });
  });

  describe("batchUpsertParticipantEVs", () => {
    it("should upsert multiple participants in batches", () => {
      // Function processes inputs in batches of 50 to avoid overwhelming database
      // Returns array of all upserted ParticipantEV records
      expect(true).toBe(true);
    });
  });

  describe("toProbabilityDistribution", () => {
    it("should convert database record to ProbabilityDistribution", () => {
      // Function converts string fields (probFirst, probSecond, etc.) to numbers
      // Returns ProbabilityDistribution object
      expect(true).toBe(true);
    });
  });

  describe("recalculateEV", () => {
    it("should recalculate EV with new scoring rules", () => {
      // Function retrieves existing probabilities and recalculates EV with new scoring
      // Keeps probabilities unchanged, only updates expectedValue field
      expect(true).toBe(true);
    });

    it("should return null if participant EV doesn't exist", () => {
      // Function returns null when no record is found
      expect(true).toBe(true);
    });
  });

  describe("recalculateAllEVsForSeason", () => {
    it("should recalculate all EVs for a season", () => {
      // Function retrieves all participant EVs for season
      // Calls recalculateEV for each participant
      // Returns count of participants updated
      expect(true).toBe(true);
    });
  });

  describe("syncVorpForSeason", () => {
    beforeEach(() => {
      vi.clearAllMocks();
    });

    it("should calculate correct VORP values for 14 participants with EVs 100 down to 35 (step 5)", async () => {
      // 14 participants: EVs = 100, 95, 90, 85, 80, 75, 70, 65, 60, 55, 50, 45, 40, 35
      // Sorted descending (already sorted)
      // Replacement level = avg of positions 12-14 (0-indexed 11-13) = avg(45, 40, 35) = 40
      // VORP(100) = 60, VORP(35) = -5

      const { calculateReplacementLevel, calculateVORP } = await import("~/services/ev-calculator");

      const evValues = Array.from({ length: 14 }, (_, i) => 100 - i * 5);
      // [100, 95, 90, 85, 80, 75, 70, 65, 60, 55, 50, 45, 40, 35]

      const replacementLevel = calculateReplacementLevel(evValues);
      expect(replacementLevel).toBe(40); // avg(45, 40, 35) = 40

      const vorpFirst = calculateVORP(100, replacementLevel);
      expect(vorpFirst).toBe(60);

      const vorpLast = calculateVORP(35, replacementLevel);
      expect(vorpLast).toBe(-5);
    });

    it("should return early when no EVs exist for the season", async () => {
      // Re-mock getAllParticipantEVsForSeason to return empty array
      // The function should do nothing and return without calling db.update
      const { syncVorpForSeason } = await import("../participant-expected-value");

      // Patch the module's getAllParticipantEVsForSeason to return []
      // Since we can't easily spy on module-internal calls, we verify via db mock:
      // If 0 EVs returned, db.update should not be called

      // Setup: db.select chain for getAllParticipantEVsForSeason returns []
      const mockSelectChain = {
        from: vi.fn().mockReturnThis(),
        where: vi.fn().mockResolvedValue([]),
      };
      mockDb.select = vi.fn().mockReturnValue(mockSelectChain);

      await syncVorpForSeason("season-empty");

      // db.update should NOT have been called (no participants to update)
      expect(mockUpdate).not.toHaveBeenCalled();
    });

    it("should call db.update with correct vorpValue for each participant", async () => {
      const { syncVorpForSeason } = await import("../participant-expected-value");

      // 3 participants with EVs: 100, 70, 40
      // sorted: [100, 70, 40]
      // replacement level = avg of positions 12-14, but only 3 participants
      // startIdx = min(11, 2) = 2, endIdx = min(13, 2) = 2 → slice = [40]
      // replacementLevel = 40
      // VORP: 100→60, 70→30, 40→0
      const mockEvRecords = [
        { participantId: "p1", expectedValue: "100", sportsSeasonId: "season-1" },
        { participantId: "p2", expectedValue: "70", sportsSeasonId: "season-1" },
        { participantId: "p3", expectedValue: "40", sportsSeasonId: "season-1" },
      ];

      const mockSelectChain = {
        from: vi.fn().mockReturnThis(),
        where: vi.fn().mockResolvedValue(mockEvRecords),
      };
      mockDb.select = vi.fn().mockReturnValue(mockSelectChain);

      const mockWhereResolved = vi.fn().mockResolvedValue([]);
      mockSet.mockReturnValue({ where: mockWhereResolved });
      mockUpdate.mockReturnValue({ set: mockSet });

      await syncVorpForSeason("season-1");

      // Should have called db.update 3 times (once per participant)
      expect(mockUpdate).toHaveBeenCalledTimes(3);

      // Verify the set calls include vorpValue
      const setCalls = mockSet.mock.calls;
      const vorpValues = setCalls.map((call) => call[0].vorpValue);

      expect(vorpValues).toContain("60.0000");
      expect(vorpValues).toContain("30.0000");
      expect(vorpValues).toContain("0.0000");
    });
  });
});