{% from "_macros.html" import pat, wlabel, pill, tri, popover %}

{% if not rows %}
  <p style="padding: 24px; text-align: center; color: var(--fg-muted); margin: 0;">
    No rows match these filters.
  </p>
{% else %}
<table class="dt">
  <thead>
    <tr>
      <th>Ticker</th>
      <th>Pattern</th>
      <th>Bias</th>
      <th style="text-align:right;">Score
        {% call popover("How to read Score", anchor="enumeration") %}
          <p class="popover-narrative">Final score for the row's top candidate after the coherence multiplier and (optional) LLM blend. Higher = stronger fit. Pair with coherence and right-edge before acting.</p>
        {% endcall %}
      </th>
      <th>Coherence
        {% call popover("How to read Coherence", anchor="coherence") %}
          <p class="popover-narrative">Multi-timeframe agreement on the top count. ✓ = strong, ⚠ = weak, dot = missing timeframe data. The numeric value is the multiplier applied to the engine score.</p>
        {% endcall %}
      </th>
      <th style="text-align:right;">R:R
        {% call popover("How to read R:R", anchor="trade-plan") %}
          <p class="popover-narrative">Reward&#58;risk for the row's trade signal. Targets default to <code>fib_extension</code>; rows without a valid signal show "—".</p>
        {% endcall %}
      </th>
      <th>Entry / Stop / Target</th>
      <th>Right-edge
        {% call popover("How to read Right-edge", anchor="right-edge") %}
          <p class="popover-narrative">Probability the most recent pivot is real and won't be invalidated by a deeper move against it. Trained per degree on real pivots from 2015&ndash;2024. Open the row's deep-dive to see the active model, degree, and calibration.</p>
        {% endcall %}
      </th>
    </tr>
  </thead>
  <tbody>
    {% for r in rows %}
      <tr {% if r.has_error %}style="opacity:0.5;"{% endif %}>
        <td class="tk">
          <a href="/deepdive/{{ r.ticker }}?as_of={{ r.as_of.isoformat() }}">{{ r.ticker }}</a>
        </td>
        <td>{{ pat(r.top_pattern) }}</td>
        <td>
          {% if r.direction == "up" %}{{ pill("LONG", "bull", dot=true) }}
          {% elif r.direction == "down" %}{{ pill("SHORT", "bear", dot=true) }}
          {% else %}{{ pill("—", "muted") }}{% endif %}
        </td>
        <td class="num" style="text-align:right;">
          {% if r.top_score is not none %}
            <span class="scorebar"><span>{{ "%.2f"|format(r.top_score) }}</span><span class="bar"><span style="width: {{ (r.top_score * 100)|round|int }}%"></span></span></span>
          {% else %}—{% endif %}
        </td>
        <td>
          {% if r.coherence is not none %}<span class="num">{{ "%.2f"|format(r.coherence) }}</span>{% else %}—{% endif %}
        </td>
        <td class="num r-pos" style="text-align:right;">
          {{ "%.2f"|format(r.signal_rr|float) if r.signal_rr is not none else "—" }}
        </td>
        <td class="num">
          {% if r.signal_entry %}<span style="color: var(--fg-muted);">{{ r.signal_entry }}</span> /
            <span style="color: var(--bear);">{{ r.signal_stop }}</span> /
            <span style="color: var(--bull);">{{ r.signal_target }}</span>
          {% else %}—{% endif %}
        </td>
        <td class="num">
          {% if r.right_edge_proba is not none %}
            <span style="color: var(--purple);">{{ "%.2f"|format(r.right_edge_proba) }}</span>
          {% else %}—{% endif %}
        </td>
      </tr>
    {% endfor %}
  </tbody>
</table>
{% endif %}