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a6bae97 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 | """Rendu HTML « Précision sur séquences numériques » — Sprint 86.
Suite directe ``picarones/core/numerical_sequences.py``
(Sprint 85) + câblage runner Sprint 86.
Pattern identique aux autres rendus : server-side, pas de JS,
anti-injection systématique.
Vue
---
Tableau moteur × catégorie (year / roman / foliation / currency
/ regnal) × score strict ; une ligne par moteur, une cellule
colorée par cellule. Une seconde ligne donne le score ``value``
(en plus petit). Catégorie omise si **aucun** moteur n'a de
GT exploitable pour elle.
Adaptative : ``""`` si aucun moteur n'a de
``aggregated_numerical_sequences``.
"""
from __future__ import annotations
from html import escape as _e
from typing import Optional
from picarones.core.numerical_sequences import CATEGORIES
def _color_for_score(score: float) -> str:
"""Gradient rouge → jaune → vert."""
f = max(0.0, min(1.0, score))
if f < 0.5:
t = f / 0.5
r = 235
g = int(70 + (200 - 70) * t)
b = 70
else:
t = (f - 0.5) / 0.5
r = int(235 + (60 - 235) * t)
g = int(200 + (160 - 200) * t)
b = int(70 + (90 - 70) * t)
return f"#{r:02x}{g:02x}{b:02x}"
def _category_columns_with_signal(rows: list[dict]) -> list[str]:
"""Ne garde que les catégories où ≥ 1 moteur a un n_total > 0."""
visible: list[str] = []
for cat in CATEGORIES:
for r in rows:
agg = r.get("aggregated_numerical_sequences") or {}
cat_data = (agg.get("per_category") or {}).get(cat) or {}
if (cat_data.get("n_total") or 0) > 0:
visible.append(cat)
break
return visible
def build_numerical_sequences_html(
engines: list[dict],
labels: Optional[dict[str, str]] = None,
) -> str:
"""Construit la section HTML séquences numériques.
Returns
-------
str
``""`` si aucun moteur n'a de signal.
"""
rows = [
e for e in engines
if isinstance(e.get("aggregated_numerical_sequences"), dict)
]
if not rows:
return ""
visible_cats = _category_columns_with_signal(rows)
if not visible_cats:
return ""
labels = labels or {}
title = labels.get(
"numseq_title", "Précision sur séquences numériques",
)
note = labels.get(
"numseq_note",
"Score strict (forme préservée) — la valeur entre "
"parenthèses est le score sur la valeur (XIV ↔ 14 "
"accepté). Foliotation : recto/verso non interchangeables.",
)
col_engine = labels.get("numseq_engine", "Moteur")
col_global = labels.get("numseq_global", "Global")
cat_label = {
"year": labels.get("numseq_cat_year", "Année"),
"roman": labels.get("numseq_cat_roman", "Romain"),
"foliation": labels.get("numseq_cat_foliation", "Foliation"),
"currency": labels.get("numseq_cat_currency", "Montant"),
"regnal": labels.get("numseq_cat_regnal", "Régnal"),
}
parts = [
'<div class="numseq-section" style="margin:1rem 0">',
f'<h3 style="margin:0 0 .3rem 0">{_e(title)}</h3>',
f'<div style="font-size:.85rem;opacity:.75;margin-bottom:.5rem">'
f'{_e(note)}</div>',
'<table style="border-collapse:collapse;width:100%;'
'font-size:.9rem">',
'<thead><tr>',
f'<th style="padding:.4rem .6rem;text-align:left;'
f'border-bottom:1px solid #ccc;font-weight:600">'
f'{_e(col_engine)}</th>',
f'<th style="padding:.4rem .6rem;text-align:right;'
f'border-bottom:1px solid #ccc;font-weight:600">'
f'{_e(col_global)}</th>',
]
for cat in visible_cats:
parts.append(
f'<th style="padding:.4rem .6rem;text-align:right;'
f'border-bottom:1px solid #ccc;font-weight:600">'
f'{_e(cat_label.get(cat, cat))}</th>'
)
parts.append("</tr></thead><tbody>")
for engine in rows:
agg = engine["aggregated_numerical_sequences"]
name = engine.get("name") or "?"
per_cat = agg.get("per_category") or {}
global_strict = float(agg.get("global_strict_score") or 0.0)
global_value = float(agg.get("global_value_score") or 0.0)
n_total = int(agg.get("n_total") or 0)
global_color = _color_for_score(global_strict)
parts.append(
f'<tr>'
f'<td style="padding:.4rem .6rem">{_e(str(name))}</td>'
f'<td style="padding:.4rem .6rem;text-align:right;'
f'background:{global_color};font-family:monospace;'
f'font-weight:600">'
f'{global_strict * 100:.1f}%'
f'<span style="font-size:.75rem;font-weight:400;'
f'opacity:.75"> ({global_value * 100:.0f}%, '
f'n={n_total})</span></td>'
)
for cat in visible_cats:
cat_data = per_cat.get(cat) or {}
n = int(cat_data.get("n_total") or 0)
if n == 0:
parts.append(
'<td style="padding:.4rem .6rem;text-align:right;'
'opacity:.4">—</td>'
)
continue
strict = float(cat_data.get("strict_score") or 0.0)
value = float(cat_data.get("value_score") or 0.0)
color = _color_for_score(strict)
parts.append(
f'<td style="padding:.4rem .6rem;text-align:right;'
f'background:{color};font-family:monospace">'
f'{strict * 100:.0f}%'
f'<span style="font-size:.75rem;opacity:.75"> '
f'({value * 100:.0f}%, n={n})</span></td>'
)
parts.append("</tr>")
parts.append("</tbody></table></div>")
return "".join(parts)
__all__ = ["build_numerical_sequences_html"]
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