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8588daf 46bb905 8588daf 9011070 8588daf d109222 9011070 8588daf | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 | """Tests Sprint 89 β A.II.8b : spΓ©cialisation inter-moteurs.
Couvre :
1. ``compute_specialization_score`` : symΓ©trie, plage [0, 1].
2. ``classify_specialization`` : seuils par dΓ©faut + custom.
3. ``compute_specialization_matrix`` : structure, symΓ©trie, max_pair.
4. ``top_specialized_pairs`` : tri, n, min_score.
5. Vue HTML : adaptive, anti-injection, FR + EN.
6. ComplΓ©tude i18n FR/EN.
"""
from __future__ import annotations
import json
from pathlib import Path
from picarones.evaluation.metrics.specialization import (
DEFAULT_THRESHOLDS,
classify_specialization,
compute_specialization_matrix,
compute_specialization_score,
top_specialized_pairs,
)
from picarones.reports.html.renderers.specialization import (
build_specialization_html,
)
def _load_labels(lang: str) -> dict:
p = (
Path(__file__).parent.parent.parent
/ "picarones" / "reports" / "i18n" / f"{lang}.json"
)
return json.loads(p.read_text(encoding="utf-8"))
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
# 1. compute_specialization_score
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
class TestScore:
def test_identical_profiles_zero(self) -> None:
tax = {"a": 50, "b": 50}
assert compute_specialization_score(tax, tax) < 0.001
def test_disjoint_profiles_one(self) -> None:
tax_a = {"a": 100}
tax_b = {"b": 100}
assert compute_specialization_score(tax_a, tax_b) > 0.95
def test_symmetric(self) -> None:
a = {"x": 70, "y": 30}
b = {"x": 20, "y": 80}
s_ab = compute_specialization_score(a, b)
s_ba = compute_specialization_score(b, a)
assert abs(s_ab - s_ba) < 1e-9
def test_bounded_zero_one(self) -> None:
a = {"x": 1, "y": 0, "z": 0}
b = {"x": 0, "y": 0, "z": 1}
score = compute_specialization_score(a, b)
assert 0.0 <= score <= 1.0
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
# 2. classify_specialization
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
class TestClassify:
def test_below_similar_threshold(self) -> None:
assert classify_specialization(0.05) == "similar"
def test_distinct_band(self) -> None:
assert classify_specialization(0.20) == "distinct"
def test_highly_specialized_above(self) -> None:
assert classify_specialization(0.50) == "highly_specialized"
def test_custom_thresholds(self) -> None:
custom = (("low", 0.5), ("high", 1.01))
assert classify_specialization(0.30, custom) == "low"
assert classify_specialization(0.80, custom) == "high"
def test_default_thresholds_exposed(self) -> None:
assert isinstance(DEFAULT_THRESHOLDS, tuple)
assert len(DEFAULT_THRESHOLDS) >= 2
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
# 3. compute_specialization_matrix
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
class TestMatrix:
def test_returns_none_when_lt_two(self) -> None:
assert compute_specialization_matrix({}) is None
assert compute_specialization_matrix({"a": {"x": 1}}) is None
def test_diagonal_zero(self) -> None:
tax = {
"a": {"x": 1, "y": 0},
"b": {"x": 0, "y": 1},
}
m = compute_specialization_matrix(tax)
for i in range(len(m["engines"])):
assert m["matrix"][i][i] == 0.0
def test_symmetric(self) -> None:
tax = {
"a": {"x": 1, "y": 0},
"b": {"x": 0, "y": 1},
"c": {"x": 1, "y": 1},
}
m = compute_specialization_matrix(tax)
n = len(m["engines"])
for i in range(n):
for j in range(n):
assert m["matrix"][i][j] == m["matrix"][j][i]
def test_max_pair_identifies_most_specialized(self) -> None:
# A vs B totalement disjoints, C similaire Γ A.
tax = {
"a": {"x": 100, "y": 0},
"b": {"x": 0, "y": 100},
"c": {"x": 95, "y": 5},
}
m = compute_specialization_matrix(tax)
# La paire la plus spΓ©cialisΓ©e doit Γͺtre (a, b)
assert set(m["max_pair"]) == {"a", "b"}
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
# 4. top_specialized_pairs
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
class TestTop:
def _matrix(self) -> dict:
return compute_specialization_matrix({
"a": {"x": 100, "y": 0},
"b": {"x": 0, "y": 100},
"c": {"x": 95, "y": 5},
})
def test_sorted_descending(self) -> None:
pairs = top_specialized_pairs(self._matrix(), n=10)
scores = [p["score"] for p in pairs]
assert scores == sorted(scores, reverse=True)
def test_caps_at_n(self) -> None:
pairs = top_specialized_pairs(self._matrix(), n=1)
assert len(pairs) == 1
def test_min_score_filter(self) -> None:
pairs = top_specialized_pairs(
self._matrix(), n=10, min_score=0.99,
)
# Seules les paires (a,b) et Γ©ventuellement (b,c) au-dessus
assert all(p["score"] >= 0.99 for p in pairs)
def test_none_input_returns_empty(self) -> None:
assert top_specialized_pairs(None) == []
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
# 5. Vue HTML
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
class TestRender:
def test_empty_returns_empty(self) -> None:
assert build_specialization_html(None) == ""
assert build_specialization_html({}) == ""
def test_single_engine_returns_empty(self) -> None:
assert build_specialization_html({"a": {"x": 1}}) == ""
def test_renders_table(self) -> None:
tax = {
"tess": {"visual_confusion": 80, "lacuna": 20},
"pero": {"visual_confusion": 5, "lacuna": 95},
}
html = build_specialization_html(tax, _load_labels("fr"))
assert "<table" in html
assert "tess" in html
assert "pero" in html
# CatΓ©gorie traduite
assert "Forte spΓ©cialisation" in html
def test_anti_injection(self) -> None:
tax = {
"<script>alert(1)</script>": {"x": 100},
"pero": {"y": 100},
}
html = build_specialization_html(tax, _load_labels("fr"))
assert "<script>alert" not in html
assert "<script>" in html
def test_renders_in_english(self) -> None:
tax = {
"a": {"x": 100, "y": 0},
"b": {"x": 0, "y": 100},
}
html = build_specialization_html(tax, _load_labels("en"))
assert "Inter-engine specialisation" in html
assert "Highly specialised" in html
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
# 6. ComplΓ©tude i18n
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
_KEYS = {
"specialization_title", "specialization_note",
"specialization_engine_a", "specialization_engine_b",
"specialization_score", "specialization_category",
"specialization_cat_similar", "specialization_cat_distinct",
"specialization_cat_highly_specialized",
}
class TestI18n:
def test_fr(self) -> None:
d = _load_labels("fr")
assert not _KEYS - d.keys()
def test_en(self) -> None:
d = _load_labels("en")
assert not _KEYS - d.keys()
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