model-platform/frontend/app/features/operations/modelData.ts

export const MODEL_CATEGORIES = [
  { id: "std", name: "标准A卡" },
  { id: "bai", name: "白户A卡" },
  { id: "big", name: "大额A卡" },
  { id: "afd", name: "反欺诈评分" },
] as const;

export type ModelCategoryId = (typeof MODEL_CATEGORIES)[number]["id"];
export type ModelGrade = "A" | "B" | "C";
export type AbnormalLevel = "三级" | "二级" | "一级" | "正常";
export type ModelStatus = "正常" | "陪跑" | "陪跑结束" | "下线";
export type RankingStatus = "相符" | "不符" | "—";

export type ModelRecord = {
  bank: string;
  category: ModelCategoryId;
  name: string;
  modelId: string;
  version: string;
  status: ModelStatus;
  iteratedAt: string;
  ranking: RankingStatus;
  ks: number;
  psi: number;
  ksDrop: number;
  secondaryHits: number;
  wuji: boolean;
  processedAt: string | null;
  previousAdvice: string;
  commonModel: string | null;
};

export type MonitoringRow = ModelRecord & {
  monitorMonth: string;
};

export const MONITOR_MONTHS = [
  "2026-02",
  "2026-03",
  "2026-04",
  "2026-05",
  "2026-06",
  "2026-07",
] as const;

// 业务数据全部来自后端。以下空集合仅保留页面类型和计算函数的接口，
// 在真实接口补齐对应字段前不再提供本地样例数据。
export const MODELS: ModelRecord[] = [];
export const FEATURE_METRICS: Array<{
  key: string;
  name: string;
  iv: number;
  ivDrop: number;
  csi: number;
  csiRise: number;
  ksContribution: number;
  psiContribution: number;
}> = [];
export const SORTING_DISTRIBUTION = {
  bins: [] as string[],
  counts: [] as number[],
  badRates: [] as number[],
};
export const BANK_AVERAGE_CYCLE: Record<string, number> = {};

export type ModelLifecycle = {
  onlineAt: string | null;
  escortStartAt: string | null;
  escortEndAt: string | null;
  offlineAt: string | null;
  developer: string;
  developmentKs: number;
  developmentPsi: number;
  maxLift: number;
};

export const MODEL_LIFECYCLE: Record<string, ModelLifecycle> = {};

export function categoryName(category: ModelCategoryId): string {
  return MODEL_CATEGORIES.find((item) => item.id === category)?.name ?? category;
}

export function abnormalLevelOf(model: Pick<ModelRecord, "ranking" | "ks" | "psi" | "ksDrop">): AbnormalLevel {
  const { ranking, ks, psi, ksDrop } = model;
  if (ranking === "—") return "正常";
  if (ranking === "不符" && ks < 40 && psi > 10) return "三级";
  if (ranking === "相符" && ks < 40 && psi > 25) return "三级";
  if (ranking === "不符" && ks >= 40 && psi > 25) return "二级";
  if (ranking === "不符" && ks >= 40 && psi > 10 && psi <= 25 && ksDrop > 20) return "二级";
  if (ranking === "不符" && ks < 40 && psi <= 10) return "二级";
  if (ranking === "相符" && ks < 40 && psi <= 25) return "二级";
  if (ranking === "相符" && ks >= 40 && psi > 25 && ksDrop > 20) return "二级";
  if (ranking === "不符" && ks >= 40 && psi > 10 && psi <= 25 && ksDrop <= 20) return "一级";
  if (ranking === "不符" && ks >= 40 && psi <= 10) return "一级";
  if (ranking === "相符" && ks >= 40 && psi > 25 && ksDrop <= 20) return "一级";
  if (ranking === "相符" && ks >= 40 && psi > 10 && psi <= 25) return "一级";
  if (ranking === "相符" && ks >= 40 && psi <= 10 && ksDrop > 20) return "一级";
  return "正常";
}

export function gradeOf(model: Pick<ModelRecord, "ranking" | "ks" | "psi" | "ksDrop" | "secondaryHits" | "status">): ModelGrade {
  if (model.status === "下线") return "A";
  const abnormal = abnormalLevelOf(model);
  if (abnormal === "三级") return "C";
  if (abnormal === "二级" && model.secondaryHits >= 4) return "C";
  if (abnormal === "正常") return "A";
  return "B";
}

export function abnormalReasonOf(model: ModelRecord | MonitoringRow): string {
  const abnormal = abnormalLevelOf(model);
  if (abnormal === "正常") return "各项指标均在阈值内";

  const reasons: string[] = [];
  if (model.ranking === "不符") reasons.push("排序性不符");
  if (model.ks < 40) reasons.push("KS 低于 40%");
  if (model.psi > 25) reasons.push("PSI 高于 25%");
  else if (model.psi > 10) reasons.push("PSI 处于 10%–25%");
  if (model.ksDrop > 20) reasons.push("KS 环比降幅高于 20%");

  if (abnormal === "二级") {
    const result = model.secondaryHits >= 4 ? "，已触发监控结果升级为 C" : "，未达到累计升级条件";
    return `${reasons.join("、")}；近 6 个月累计 ${model.secondaryHits} 次二级异常${result}`;
  }
  return reasons.join("、");
}

export function modelTrend(
  _model: ModelRecord,
  _metric: "ks" | "psi",
  _months: readonly string[] = MONITOR_MONTHS,
): number[] {
  return [];
}

export function monitoringRows(_source: ModelRecord[] = MODELS): MonitoringRow[] {
  return [];
}

export function monthsBetween(from: string, to: string): string[] {
  const [fromYear, fromMonth] = from.split("-").map(Number);
  const [toYear, toMonth] = to.split("-").map(Number);
  if (!fromYear || !fromMonth || !toYear || !toMonth) return [...MONITOR_MONTHS];
  const start = fromYear * 12 + fromMonth - 1;
  const end = toYear * 12 + toMonth - 1;
  if (start > end || end - start > 23) return [...MONITOR_MONTHS];
  return Array.from({ length: end - start + 1 }, (_, index) => {
    const value = start + index;
    const year = Math.floor(value / 12);
    const month = value % 12 + 1;
    return `${year}-${String(month).padStart(2, "0")}`;
  });
}

export function average(values: number[]): number {
  return values.length ? values.reduce((sum, value) => sum + value, 0) / values.length : 0;
}

export function categoryTrend(
  _category: ModelCategoryId,
  _metric: "ks" | "psi",
  _months: string[],
  _source: ModelRecord[] = MODELS,
): number[] {
  return [];
}

export function bankTrend(
  _bank: string,
  _metric: "ks" | "psi",
  _months: string[],
  _source: ModelRecord[] = MODELS,
): number[] {
  return [];
}

export function modelsTrend(
  _models: ModelRecord[],
  _metric: "ks" | "psi",
  _months: string[],
): number[] {
  return [];
}

export function latestIterationDate(models: ModelRecord[]): string {
  return models.map((model) => model.iteratedAt).filter(Boolean).sort().at(-1) ?? "—";
}

export function modelIterationCycleMonths(model: ModelRecord): number | null {
  const lifecycle = MODEL_LIFECYCLE[model.modelId];
  const start = lifecycle?.onlineAt ?? lifecycle?.escortStartAt;
  if (!start || !model.iteratedAt) return null;
  const [startYear, startMonth] = start.slice(0, 7).split("-").map(Number);
  const [endYear, endMonth] = model.iteratedAt.slice(0, 7).split("-").map(Number);
  if (![startYear, startMonth, endYear, endMonth].every(Number.isFinite)) return null;
  return Math.max(0, (endYear * 12 + endMonth) - (startYear * 12 + startMonth));
}

export function averageIterationCycle(models: ModelRecord[]): number | null {
  const values = models.map(modelIterationCycleMonths).filter((value): value is number => value !== null);
  return values.length ? Number(average(values).toFixed(1)) : null;
}

export function averageIterationMonths(models: ModelRecord[]): number {
  const months = models
    .filter((model) => model.status !== "下线")
    .map((model) => {
      const [year, month] = model.iteratedAt.slice(0, 7).split("-").map(Number);
      return (2026 * 12 + 7) - (year * 12 + month);
    })
    .filter(Number.isFinite);
  return Number(average(months).toFixed(1));
}