{% extends "base.html" %}

{% block content %}

<div class="callout {{ 'ok' if summary.oos_win_rate and summary.oos_win_rate >= 0.5 else 'warn' }}">
  <strong>样本外结论：</strong>
  {{ summary.windows }} 个滚动窗口中
  <strong>{{ summary.oos_win_windows }}</strong> 个测试期为正
  （胜率 {{ summary.oos_win_rate_s }}）。
  样本外收益均值 {{ summary.oos_total_return_mean_s }}，
  {% if summary.oos_excess_return_mean is not none %}
    相对基准超额 <strong>{{ summary.oos_excess_return_mean_s }}</strong>。
  {% endif %}
  {% if summary.oos_stability is not none and summary.oos_stability < 1 %}
    ⚠ 稳定性指标 {{ summary.oos_stability_s }} 偏低（<1），说明各窗口差异较大，结论需谨慎。
  {% endif %}
</div>

<div class="kpi-grid">
  <div class="kpi"><div class="label">窗口数</div><div class="value">{{ summary.windows }}</div>
    <div class="note">{{ scheme }} · 训练 {{ train_years }} 年 / 测试 {{ test_years }} 年</div></div>
  <div class="kpi"><div class="label">样本外胜率</div>
    <div class="value {{ 'gain' if summary.oos_win_rate and summary.oos_win_rate >= 0.5 else 'loss' }}">{{ summary.oos_win_rate_s }}</div>
    <div class="note">{{ summary.oos_win_windows }} / {{ summary.windows }} 个窗口为正</div></div>
  <div class="kpi"><div class="label">样本外收益均值</div>
    <div class="value {{ 'gain' if summary.oos_total_return_mean and summary.oos_total_return_mean > 0 else 'loss' }}">{{ summary.oos_total_return_mean_s }}</div>
    <div class="note">中位数 {{ summary.oos_total_return_median_s }}</div></div>
  <div class="kpi"><div class="label">最差窗口回撤</div>
    <div class="value loss">{{ summary.oos_max_drawdown_worst_s }}</div>
    <div class="note">样本外最大回撤的最差值</div></div>
  <div class="kpi"><div class="label">超额收益均值</div>
    <div class="value {{ 'gain' if summary.oos_excess_return_mean and summary.oos_excess_return_mean > 0 else 'loss' }}">{{ summary.oos_excess_return_mean_s }}</div>
    <div class="note">相对 {{ benchmark_name }}</div></div>
  <div class="kpi"><div class="label">稳定性</div><div class="value">{{ summary.oos_stability_s }}</div>
    <div class="note">样本外收益均值 / 标准差，越高越可信</div></div>
</div>

<div class="card">
  <h2>样本内 vs 样本外（plan.md §24/§25）</h2>
  <div class="callout">
    训练段用于<strong>校准阈值</strong>（把「历史 P75」转成绝对股息率），
    测试段<strong>冻结</strong>该分布与参数 —— 引擎在代码层面不接受测试期自身数据参与分位计算，
    因此这里不存在「用未来分布判断现在」的隐性未来函数。
  </div>
  <div id="chart-window" class="chart"></div>
</div>

<div class="card">
  <h2>逐窗口明细</h2>
  <div class="table-scroll">
  <table class="data">
    <thead>
      <tr>
        <th>#</th><th>训练区间</th><th>测试区间</th>
        <th>训练收益</th><th>训练回撤</th>
        <th>测试收益</th><th>测试回撤</th><th>测试Sharpe</th>
        <th>测试成交</th><th>绝对买入阈值</th><th>绝对卖出阈值</th>
      </tr>
    </thead>
    <tbody>
      {% for w in windows %}
      <tr>
        <td class="num">{{ w.index }}</td>
        <td class="num">{{ w.train_start }} ~ {{ w.train_end }}</td>
        <td class="num">{{ w.test_start }} ~ {{ w.test_end }}</td>
        <td class="num">{{ w.train_return }}</td>
        <td class="num loss">{{ w.train_dd }}</td>
        <td class="num {{ 'gain' if w.test_positive else 'loss' }}"><strong>{{ w.test_return }}</strong></td>
        <td class="num loss">{{ w.test_dd }}</td>
        <td class="num">{{ w.test_sharpe }}</td>
        <td class="num">{{ w.test_trades }}</td>
        <td class="num">{{ w.abs_entry }}</td>
        <td class="num">{{ w.abs_exit }}</td>
      </tr>
      {% endfor %}
    </tbody>
    <tfoot>
      <tr>
        <td colspan="5">样本外汇总</td>
        <td class="num">{{ summary.oos_total_return_mean_s }}</td>
        <td class="num">{{ summary.oos_max_drawdown_worst_s }}</td>
        <td class="num">{{ summary.oos_sharpe_mean_s }}</td>
        <td colspan="3">均值 / 最差</td>
      </tr>
    </tfoot>
  </table>
  </div>
</div>

{% if frozen_rows %}
<div class="card">
  <h2>校准出的绝对阈值（阈值稳定性）</h2>
  <div class="callout">
    若各窗口校准出的绝对股息率阈值<strong>差异很大</strong>，说明「历史 P75」这一相对口径
    在不同时期对应的绝对水平不稳定，策略的市场环境依赖性较强。
  </div>
  <div id="chart-frozen" class="chart short"></div>
  <div class="table-scroll">
  <table class="data">
    <thead><tr><th>#</th><th>校准窗口</th><th>买入阈值(绝对股息率)</th><th>卖出阈值</th><th>样本观测数</th><th>中位股息率</th></tr></thead>
    <tbody>
      {% for f in frozen_rows %}
      <tr>
        <td class="num">{{ f.index }}</td>
        <td class="num">{{ f.window }}</td>
        <td class="num">{{ f.entry }}</td>
        <td class="num">{{ f.exit }}</td>
        <td class="num">{{ f.obs }}</td>
        <td class="num">{{ f.median }}</td>
      </tr>
      {% endfor %}
    </tbody>
  </table>
  </div>
</div>
{% endif %}

<div class="card">
  <h2>可复现性</h2>
  <div class="table-scroll">
  <table class="data">
    <thead><tr><th style="text-align:left">项</th><th style="text-align:left">值</th></tr></thead>
    <tbody>
      <tr><td style="text-align:left">Walk-forward ID</td><td style="text-align:left" class="mono">{{ wf_id }}</td></tr>
      <tr><td style="text-align:left">策略</td><td style="text-align:left" class="mono">{{ strategy_id }} v{{ strategy_version }}</td></tr>
      <tr><td style="text-align:left">配置指纹</td><td style="text-align:left" class="mono">{{ config_hash }}</td></tr>
      <tr><td style="text-align:left">数据版本</td><td style="text-align:left" class="mono">{{ data_version }}</td></tr>
      <tr><td style="text-align:left">窗口方案</td><td style="text-align:left">{{ scheme }} · 训练 {{ train_years }} 年 · 测试 {{ test_years }} 年 · 步进 {{ step_months }} 月</td></tr>
      <tr><td style="text-align:left">测试期冻结参数</td><td style="text-align:left">{{ freeze }}</td></tr>
    </tbody>
  </table>
  </div>
</div>

{% endblock %}

{% block scripts %}
<script>
(function () {
  if (typeof echarts === 'undefined') return;
  var C = {{ chart_colors | json }};

  var el = document.getElementById('chart-window');
  if (el) {
    var d = {{ window_chart | json }};
    var c = echarts.init(el);
    c.setOption({
      color: C,
      grid: { left: 66, right: 30, top: 44, bottom: 50 },
      tooltip: { trigger: 'axis',
                 valueFormatter: function (v) { return v == null ? '—' : (v * 100).toFixed(2) + '%'; } },
      legend: { top: 0, textStyle: { color: '#64748B' } },
      xAxis: { type: 'category', data: d.labels, axisLabel: { color: '#64748B' } },
      yAxis: { type: 'value', name: '收益', axisLabel: { color: '#64748B',
               formatter: function (v) { return (v * 100).toFixed(0) + '%'; } },
               splitLine: { lineStyle: { color: '#E9EEF6' } } },
      series: [
        { name: '样本内(训练)', type: 'bar', data: d.train,
          itemStyle: { color: '#94A3B8' }, barMaxWidth: 26 },
        { name: '样本外(测试)', type: 'bar', data: d.test.map(function (v) {
            return { value: v, itemStyle: { color: v >= 0 ? '#DC2626' : '#059669' } };
          }), barMaxWidth: 26 },
        { name: '基准(测试期)', type: 'line', data: d.bench, showSymbol: true,
          symbolSize: 6, lineStyle: { color: C[1], type: 'dashed', width: 1.4 } }
      ]
    });
    window.addEventListener('resize', function () { c.resize(); });
  }

  var fel = document.getElementById('chart-frozen');
  if (fel) {
    var f = {{ frozen_chart | json }};
    var c2 = echarts.init(fel);
    c2.setOption({
      color: C,
      grid: { left: 66, right: 30, top: 36, bottom: 44 },
      tooltip: { trigger: 'axis',
                 valueFormatter: function (v) { return (v * 100).toFixed(2) + '%'; } },
      legend: { top: 0, textStyle: { color: '#64748B' } },
      xAxis: { type: 'category', data: f.labels, axisLabel: { color: '#64748B' } },
      yAxis: { type: 'value', name: '绝对股息率', axisLabel: { color: '#64748B',
               formatter: function (v) { return (v * 100).toFixed(0) + '%'; } },
               splitLine: { lineStyle: { color: '#E9EEF6' } } },
      series: [
        { name: '买入阈值', type: 'line', data: f.entry, showSymbol: true, symbolSize: 7,
          lineStyle: { color: C[4], width: 2 } },
        { name: '卖出阈值', type: 'line', data: f.exit, showSymbol: true, symbolSize: 7,
          lineStyle: { color: C[3], width: 2 } }
      ]
    });
    window.addEventListener('resize', function () { c2.resize(); });
  }
})();
</script>
{% endblock %}