v3_scale: Checker CS1 r2 — audit verdict_CS1 r2 (tests synthétiques r2) — scripts + agrégats

v3_scale/checker/cs1_r2_audit_1435/make_copy.py

@@ -0,0 +1,21 @@
+# Copie de verdict_CS1.py r2 (fc8f0861…) : SEULS les chemins d'entrée hors runs sont redirigés vers ./synth_inputs (copies) ; logique inchangée.
+import hashlib, os, shutil
+SRC = "/workspace/spira_shared/hashing_gen/code_scale_v1/cs1/verdict_CS1.py"; t = open(SRC).read()
+assert hashlib.sha256(t.encode()).hexdigest() == "fc8f0861aa054f4673f96f9d64e49b46d69118b1469bf30607e85614da931749"
+H = os.path.dirname(os.path.abspath(__file__)); SI = f"{H}/synth_inputs"; os.makedirs(SI, exist_ok=True)
+S = "/workspace/spira_shared"
+for src, dst in [(f"{S}/hashing_gen/m8_v1b/sample/recount64_v1b_sample.json", "rc_ref.json"), (f"{S}/hashing_gen/corpus_v1b/manifest_corpus_diverse_v1b.json", "rc_v1b.json"),
+                 (f"{S}/checker/recount/code_scale_v1_scan/scan64_code_scale_v1.json", "rc_code.json"), (f"{S}/hashing_gen/lever2/verdict_AH1/mask_oldtest_strict.npz", "mask.npz"),
+                 (f"{S}/checker/recount/cs1_mix_1418/recount64_cs1_mix_sample.json", "rc_mix.json")]:
+    shutil.copyfile(src, f"{SI}/{dst}")
+open(f"{SI}/GO_CS1", "w").write("synthetique\n")
+rep = [('RC_REF = f"{B8}/sample/recount64_v1b_sample.json"; RC_MIX = f"{C1}/recount_mix/recount64_cs1_mix_sample.json"',
+        f'RC_REF = "{SI}/rc_ref.json"; RC_MIX = os.environ.get("SYN_RC_MIX", "{SI}/rc_mix.json")'),
+       ('RC_V1B = f"{S}/hashing_gen/corpus_v1b/manifest_corpus_diverse_v1b.json"; RC_CODE = f"{S}/checker/recount/code_scale_v1_scan/scan64_code_scale_v1.json"',
+        f'RC_V1B = "{SI}/rc_v1b.json"; RC_CODE = "{SI}/rc_code.json"'),
+       ('GO = f"{C1}/GO_CS1"; MASKP = f"{S}/hashing_gen/lever2/verdict_AH1/mask_oldtest_strict.npz"', f'GO = "{SI}/GO_CS1"; MASKP = "{SI}/mask.npz"'),
+       ('_ap.add_argument("--runs-ref", default=f"{C1}/runs/v1b"); _ap.add_argument("--runs-cand", default=f"{C1}/runs/mix"); _ap.add_argument("--outdir", default=f"{C1}/verdict")',
+        f'_ap.add_argument("--runs-ref", default="{H}/NONE_ref"); _ap.add_argument("--runs-cand", default="{H}/NONE_cand"); _ap.add_argument("--outdir", default="{H}/NONE_out")')]
+for a, b in rep:
+    assert t.count(a) == 1, a; t = t.replace(a, b)
+open(f"{H}/verdict_CS1_synthcopy.py", "w").write(t); print("ok", hashlib.sha256(t.encode()).hexdigest())

v3_scale/checker/cs1_r2_audit_1435/synth_results.json

@@ -0,0 +1,3090 @@
+{
+ "A_adopte": {
+  "expected": "ADOPTÉ",
+  "got": "ADOPTÉ",
+  "reasons": [],
+  "counts_agree_independent": true,
+  "windows": {
+   "fc2": {
+    "got": [
+     3644,
+     0,
+     734,
+     1.0,
+     1.0
+    ],
+    "indep": [
+     3644,
+     0,
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+     1.0
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+    "rate_in_range_indep": 1.0,
+    "valid": true,
+    "gain": true,
+    "loss": false,
+    "p": 2.2131618651272261e-221,
+    "ci": [
+     18.612936182784587,
+     21.614078101058517
+    ]
+   },
+   "fresh_en": {
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+     1.0
+    ],
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+     0,
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+     1.0
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+    "p": 1.0,
+    "ci": [
+     0.0,
+     0.0
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+   },
+   "fresh_fr": {
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+     1.0
+    ],
+    "indep": [
+     3604,
+     0,
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+     1.0
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+    "loss": false,
+    "p": 1.0,
+    "ci": [
+     0.0,
+     0.0
+    ]
+   },
+   "test20k": {
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+     0,
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+     1.0
+    ],
+    "indep": [
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+     0,
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+    "loss": false,
+    "p": 1.0,
+    "ci": [
+     0.0,
+     0.0
+    ]
+   },
+   "test_v3": {
+    "got": [
+     3607,
+     0,
+     0,
+     1.0,
+     1.0
+    ],
+    "indep": [
+     3607,
+     0,
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+    "loss": false,
+    "p": 1.0,
+    "ci": [
+     0.0,
+     0.0
+    ]
+   },
+   "queries": {
+    "got": [
+     3610,
+     0,
+     0,
+     1.0,
+     1.0
+    ],
+    "indep": [
+     3610,
+     0,
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+    "p": 1.0,
+    "ci": [
+     0.0,
+     0.0
+    ]
+   }
+  },
+  "ok": true
+ },
+ "B1_rejete_perte": {
+  "expected": "REJETÉ",
+  "got": "REJETÉ",
+  "reasons": [
+   "perte(s) significative(s) : fresh_fr"
+  ],
+  "counts_agree_independent": true,
+  "windows": {
+   "fc2": {
+    "got": [
+     3644,
+     0,
+     734,
+     1.0,
+     1.0
+    ],
+    "indep": [
+     3644,
+     0,
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+     1.0
+    ],
+    "rate_in_range_indep": 1.0,
+    "valid": true,
+    "gain": true,
+    "loss": false,
+    "p": 2.2131618651272261e-221,
+    "ci": [
+     18.612936182784587,
+     21.614078101058517
+    ]
+   },
+   "fresh_en": {
+    "got": [
+     3619,
+     0,
+     0,
+     1.0,
+     1.0
+    ],
+    "indep": [
+     3619,
+     0,
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+    "p": 1.0,
+    "ci": [
+     0.0,
+     0.0
+    ]
+   },
+   "fresh_fr": {
+    "got": [
+     3604,
+     715,
+     0,
+     1.0,
+     1.0
+    ],
+    "indep": [
+     3604,
+     715,
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+     1.0,
+     1.0
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+    "valid": true,
+    "gain": false,
+    "loss": true,
+    "p": 1.1603342079438231e-215,
+    "ci": [
+     -21.27174691969445,
+     -18.441457134130808
+    ]
+   },
+   "test20k": {
+    "got": [
+     3586,
+     0,
+     0,
+     1.0,
+     1.0
+    ],
+    "indep": [
+     3586,
+     0,
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+    "p": 1.0,
+    "ci": [
+     0.0,
+     0.0
+    ]
+   },
+   "test_v3": {
+    "got": [
+     3615,
+     0,
+     0,
+     1.0,
+     1.0
+    ],
+    "indep": [
+     3615,
+     0,
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+    "p": 1.0,
+    "ci": [
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+    ]
+   },
+   "queries": {
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+     1.0
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+    "p": 1.0,
+    "ci": [
+     0.0,
+     0.0
+    ]
+   }
+  },
+  "ok": true
+ },
+ "B2_rejete_sans_gain": {
+  "expected": "REJETÉ",
+  "got": "REJETÉ",
+  "reasons": [
+   "aucun gain significatif sur une fenêtre fraîche valide"
+  ],
+  "counts_agree_independent": true,
+  "windows": {
+   "fc2": {
+    "got": [
+     3644,
+     0,
+     0,
+     1.0,
+     1.0
+    ],
+    "indep": [
+     3644,
+     0,
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+    "rate_in_range_indep": 1.0,
+    "valid": true,
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+    "p": 1.0,
+    "ci": [
+     0.0,
+     0.0
+    ]
+   },
+   "fresh_en": {
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+     0,
+     0,
+     1.0,
+     1.0
+    ],
+    "indep": [
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+     0,
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+     1.0
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+    "rate_in_range_indep": 1.0,
+    "valid": true,
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+    "loss": false,
+    "p": 1.0,
+    "ci": [
+     0.0,
+     0.0
+    ]
+   },
+   "fresh_fr": {
+    "got": [
+     3605,
+     0,
+     0,
+     1.0,
+     1.0
+    ],
+    "indep": [
+     3605,
+     0,
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+    "loss": false,
+    "p": 1.0,
+    "ci": [
+     0.0,
+     0.0
+    ]
+   },
+   "test20k": {
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+     1.0
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+    "p": 1.0,
+    "ci": [
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+    ]
+   },
+   "test_v3": {
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+     0,
+     1.0,
+     1.0
+    ],
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+   },
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+    "p": 1.0,
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+     0.0
+    ]
+   }
+  },
+  "ok": true
+ },
+ "B3_perte_queries_seulement_hors_regle": {
+  "expected": "ADOPTÉ",
+  "got": "ADOPTÉ",
+  "reasons": [],
+  "counts_agree_independent": true,
+  "windows": {
+   "fc2": {
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+     1.0
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+    "valid": true,
+    "gain": true,
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+    "p": 2.2131618651272261e-221,
+    "ci": [
+     18.612936182784587,
+     21.614078101058517
+    ]
+   },
+   "fresh_en": {
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+     1.0
+    ],
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+    "p": 1.0,
+    "ci": [
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+    ]
+   },
+   "fresh_fr": {
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+     0,
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+     1.0
+    ],
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+    "p": 1.0,
+    "ci": [
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+    ]
+   },
+   "test20k": {
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+     0,
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+    "p": 1.0,
+    "ci": [
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+     0.0
+    ]
+   },
+   "test_v3": {
+    "got": [
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+     0,
+     0,
+     1.0,
+     1.0
+    ],
+    "indep": [
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+     0,
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+    "loss": false,
+    "p": 1.0,
+    "ci": [
+     0.0,
+     0.0
+    ]
+   },
+   "queries": {
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+     1.0
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+    "p": 2.121995791e-314,
+    "ci": [
+     -30.067001675041876,
+     -27.730120327265638
+    ]
+   }
+  },
+  "ok": true
+ },
+ "C1_scale_cand_0.12": {
+  "expected": "NON MESURABLE",
+  "got": "NON MESURABLE",
+  "reasons": [
+   "fusion.scale hors [0.03 ; 0.11] : réf 0.07 / cand 0.12"
+  ],
+  "counts_agree_independent": true,
+  "windows": {
+   "fc2": {
+    "got": [
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+     1.0
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+    "valid": true,
+    "gain": true,
+    "loss": false,
+    "p": 2.2131618651272261e-221,
+    "ci": [
+     18.612936182784587,
+     21.614078101058517
+    ]
+   },
+   "fresh_en": {
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+     1.0
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+    "p": 1.0,
+    "ci": [
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+   },
+   "fresh_fr": {
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+    "p": 1.0,
+    "ci": [
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+   },
+   "test20k": {
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+    "p": 1.0,
+    "ci": [
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+   },
+   "test_v3": {
+    "got": [
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+     1.0
+    ],
+    "indep": [
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+     0,
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+     1.0
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+    "rate_in_range_indep": 1.0,
+    "valid": true,
+    "gain": false,
+    "loss": false,
+    "p": 1.0,
+    "ci": [
+     0.0,
+     0.0
+    ]
+   },
+   "queries": {
+    "got": [
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+    "indep": [
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+    "rate_in_range_indep": 1.0,
+    "valid": true,
+    "gain": false,
+    "loss": false,
+    "p": 1.0,
+    "ci": [
+     0.0,
+     0.0
+    ]
+   }
+  },
+  "ok": true
+ },
+ "C2_scale_ref_0.029": {
+  "expected": "NON MESURABLE",
+  "got": "NON MESURABLE",
+  "reasons": [
+   "fusion.scale hors [0.03 ; 0.11] : réf 0.029 / cand 0.07"
+  ],
+  "counts_agree_independent": true,
+  "windows": {
+   "fc2": {
+    "got": [
+     3644,
+     0,
+     734,
+     1.0,
+     1.0
+    ],
+    "indep": [
+     3644,
+     0,
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+     1.0
+    ],
+    "rate_in_range_indep": 1.0,
+    "valid": true,
+    "gain": true,
+    "loss": false,
+    "p": 2.2131618651272261e-221,
+    "ci": [
+     18.612936182784587,
+     21.614078101058517
+    ]
+   },
+   "fresh_en": {
+    "got": [
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+    ],
+    "indep": [
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+     0,
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+    "valid": true,
+    "gain": false,
+    "loss": false,
+    "p": 1.0,
+    "ci": [
+     0.0,
+     0.0
+    ]
+   },
+   "fresh_fr": {
+    "got": [
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+ "G1_test20k_broad_e89725bb_refuse": {
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+  "detail": [
+   "AssertionError: ref:/workspace/spira_shared/checker/recount/cs1_r2_audit_1435/runs_G1_test20k_broad_e89725bb_refuse/ref/ctl__test20k.npz: window_sha256 e89725bb… (broad_*_test) — interdit en CS1"
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+ "G2_octets_fenetre_differents_refuse": {
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+  "detail": [
+   "AssertionError: fresh_en: octets différents"
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+  "ok": true
+ },
+ "H1_npz_broad_en_plus_sous_dossier_refuse": {
+  "expected": "rc=1",
+  "got": "rc=1",
+  "detail": [
+   "AssertionError: cand:/workspace/spira_shared/checker/recount/cs1_r2_audit_1435/runs_H1_npz_broad_en_plus_sous_dossier_refuse/cand/ckpt_ctl/extra.npz: window_sha256 e89725bb… (broad_*_test) — interdit en CS1"
+  ],
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+  ],
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+     3604,
+     0,
+     0,
+     1.0,
+     1.0
+    ],
+    "indep": [
+     3604,
+     0,
+     0,
+     1.0,
+     1.0
+    ],
+    "rate_in_range_indep": 1.0,
+    "valid": true,
+    "gain": false,
+    "loss": false,
+    "p": 1.0,
+    "ci": [
+     0.0,
+     0.0
+    ]
+   },
+   "test20k": {
+    "got": [
+     3605,
+     0,
+     0,
+     1.0,
+     1.0
+    ],
+    "indep": [
+     3605,
+     0,
+     0,
+     1.0,
+     1.0
+    ],
+    "rate_in_range_indep": 1.0,
+    "valid": true,
+    "gain": false,
+    "loss": false,
+    "p": 1.0,
+    "ci": [
+     0.0,
+     0.0
+    ]
+   },
+   "test_v3": {
+    "got": [
+     3607,
+     0,
+     0,
+     1.0,
+     1.0
+    ],
+    "indep": [
+     3607,
+     0,
+     0,
+     1.0,
+     1.0
+    ],
+    "rate_in_range_indep": 1.0,
+    "valid": true,
+    "gain": false,
+    "loss": false,
+    "p": 1.0,
+    "ci": [
+     0.0,
+     0.0
+    ]
+   },
+   "queries": {
+    "got": [
+     3610,
+     0,
+     0,
+     1.0,
+     1.0
+    ],
+    "indep": [
+     3610,
+     0,
+     0,
+     1.0,
+     1.0
+    ],
+    "rate_in_range_indep": 1.0,
+    "valid": true,
+    "gain": false,
+    "loss": false,
+    "p": 1.0,
+    "ci": [
+     0.0,
+     0.0
+    ]
+   }
+  },
+  "ok": true
+ },
+ "H4_seen_ecart_minime_non_sig": {
+  "expected": "ADOPTÉ",
+  "got": "ADOPTÉ",
+  "reasons": [],
+  "counts_agree_independent": true,
+  "windows": {
+   "fc2": {
+    "got": [
+     3644,
+     0,
+     734,
+     1.0,
+     1.0
+    ],
+    "indep": [
+     3644,
+     0,
+     734,
+     1.0,
+     1.0
+    ],
+    "rate_in_range_indep": 1.0,
+    "valid": true,
+    "gain": true,
+    "loss": false,
+    "p": 2.2131618651272261e-221,
+    "ci": [
+     18.612936182784587,
+     21.614078101058517
+    ]
+   },
+   "fresh_en": {
+    "got": [
+     3619,
+     0,
+     0,
+     1.0,
+     1.0
+    ],
+    "indep": [
+     3619,
+     0,
+     0,
+     1.0,
+     1.0
+    ],
+    "rate_in_range_indep": 1.0,
+    "valid": true,
+    "gain": false,
+    "loss": false,
+    "p": 1.0,
+    "ci": [
+     0.0,
+     0.0
+    ]
+   },
+   "fresh_fr": {
+    "got": [
+     3604,
+     0,
+     0,
+     1.0,
+     1.0
+    ],
+    "indep": [
+     3604,
+     0,
+     0,
+     1.0,
+     1.0
+    ],
+    "rate_in_range_indep": 1.0,
+    "valid": true,
+    "gain": false,
+    "loss": false,
+    "p": 1.0,
+    "ci": [
+     0.0,
+     0.0
+    ]
+   },
+   "test20k": {
+    "got": [
+     3605,
+     0,
+     0,
+     1.0,
+     1.0
+    ],
+    "indep": [
+     3605,
+     0,
+     0,
+     1.0,
+     1.0
+    ],
+    "rate_in_range_indep": 1.0,
+    "valid": true,
+    "gain": false,
+    "loss": false,
+    "p": 1.0,
+    "ci": [
+     0.0,
+     0.0
+    ]
+   },
+   "test_v3": {
+    "got": [
+     3607,
+     0,
+     0,
+     1.0,
+     1.0
+    ],
+    "indep": [
+     3607,
+     0,
+     0,
+     1.0,
+     1.0
+    ],
+    "rate_in_range_indep": 1.0,
+    "valid": true,
+    "gain": false,
+    "loss": false,
+    "p": 1.0,
+    "ci": [
+     0.0,
+     0.0
+    ]
+   },
+   "queries": {
+    "got": [
+     3610,
+     0,
+     0,
+     1.0,
+     1.0
+    ],
+    "indep": [
+     3610,
+     0,
+     0,
+     1.0,
+     1.0
+    ],
+    "rate_in_range_indep": 1.0,
+    "valid": true,
+    "gain": false,
+    "loss": false,
+    "p": 1.0,
+    "ci": [
+     0.0,
+     0.0
+    ]
+   }
+  },
+  "ok": true
+ }
+}

v3_scale/checker/cs1_r2_audit_1435/synth_tests_r2.py

@@ -0,0 +1,118 @@
+"""Tests synthétiques de verdict_CS1 r2 (harnais Checker 14 h 24 adapté : taux plage commune, E2 attendu ADOPTÉ, + H1-H4) (copie à chemins redirigés). Entrées 100 % synthétiques (runs/ fabriqués ici) ;
+seuls les échantillons v1b_sample.bin / cs1_mix_sample.bin et les fenêtres d'éval sont LUS (sha). Attendus calculés indépendamment."""
+import os, json, hashlib, subprocess, shutil, math, numpy as np
+H = os.path.dirname(os.path.abspath(__file__)); S = "/workspace/spira_shared"; PY = "/workspace/SPIRA-venv/bin/python"
+REF_SHA = "9ea562e44f708adda470c53144dcae748796d77b98039b5fc52ac962d877370b"; CAND_SHA = "85e977700bbfc4ad571d4be15623450eaa4360fdfd1fe9451b0706f81bfc1453"
+SMP = {"ref": f"{S}/hashing_gen/m8_v1b/sample/v1b_sample.bin", "cand": f"{S}/hashing_gen/code_scale_v1/sample/cs1_mix_sample.bin"}
+WF = {"fc2": "broad/freshcode_v2.bin", "fresh_en": "spira_m7/windows/fresh_en.bin", "fresh_fr": "spira_m7/windows/fresh_fr.bin", "test20k": "spira_m7/windows/test20k.bin",
+      "test_v3": "corpus_v3/test.bin", "queries": "spira_m7/windows/queries.bin"}
+WSHA = {w: hashlib.sha256(open(f"{S}/{p}", "rb").read()).hexdigest() for w, p in WF.items()}
+SEENSHA = {x: hashlib.sha256(open(SMP[x], "rb").read(200_000)).hexdigest() for x in SMP}
+N = 4000
+def seg(rng, lens, n=N):   # tokenisation synthétique : n pièces ; renvoie (tgt_start, tgt_len) = pièces 1..n (pièce 0 = contexte), comme train_m8v1b
+    pl = rng.choice(lens, n + 1).astype(np.int64); o2 = np.concatenate([[0], np.cumsum(pl)]); return o2[1:n + 1], pl[1:n + 1]
+def write_arm(d, side, spec, res_over=None):
+    os.makedirs(d, exist_ok=True); recs = []
+    base = {"arm": "ctl", "snn_tokens": 600000, "am_tokens": 1200000, "epochs": 2, "ticks_per_epoch": [600000, 600000], "cal": {"scale": 0.07},
+            "data_sha256": REF_SHA if side == "ref" else CAND_SHA}
+    if res_over: base.update(res_over)
+    for w, (st, ln, iv, hit) in spec.items():
+        np.savez_compressed(f"{d}/ctl__{w}.npz", fused_hit=hit, invocab=iv, tgt_start=st, tgt_len=ln, window_sha256=np.array(WSHA[w] if w != "seen" else SEENSHA[side]))
+        recs.append(dict(base, window=w))
+    open(f"{d}/results.jsonl", "w").write("\n".join(json.dumps(r) for r in recs) + "\n")
+SEENP = {"ref": 0.99, "cand": 0.99}
+def seen_spec(rng, p=0.99):
+    st, ln = seg(rng, [1, 2, 3]); return (st, ln, np.ones(N, bool), rng.random(N) < p)
+def build(name, plan, tok="same", res_ref=None, res_cand=None, seed=0):
+    """plan[w] = (p_ref, p_cand, corr) : probas de hit ; corr=True -> hits identiques sauf fraction contrôlée."""
+    rng = np.random.default_rng(seed); spec = {"ref": {}, "cand": {}}; expect = {}
+    for w in WF:
+        st_a, ln_a = seg(rng, [1, 2, 3, 4])
+        if tok == "same": st_b, ln_b = st_a.copy(), ln_a.copy()
+        elif tok == "diff": st_b, ln_b = seg(np.random.default_rng(seed + 1000 + len(w)), [1, 2, 3, 4])
+        elif tok == "partial":   # mêmes frontières sauf fusions aléatoires de paires de pièces (~30 %)
+            o = np.concatenate([[st_a[0] - 1 if False else 0], st_a, [st_a[-1] + ln_a[-1]]]); keep = np.ones(len(o), bool); r2 = np.random.default_rng(seed + 7)
+            keep[1:-1] = r2.random(len(o) - 2) > 0.3; keep[1] = True; ob = o[keep]; pl = np.diff(ob); st_b, ln_b = ob[1:-1][:N], pl[1:][:N]
+            # complète jusqu'à N avec des pièces de 2 o
+            if len(st_b) < N:
+                e = int(st_b[-1] + ln_b[-1]); k = N - len(st_b); st_b = np.concatenate([st_b, e + 2 * np.arange(k)]); ln_b = np.concatenate([ln_b, np.full(k, 2)])
+        elif tok == "coarse_tail":   # identique sur les 2000 premières pièces, puis pièces de 4 o (couvre plus loin)
+            st_a = 1 + 2 * np.arange(N); ln_a = np.full(N, 2); st_b = np.concatenate([st_a[:2000], st_a[2000] + 4 * np.arange(N - 2000)]); ln_b = np.concatenate([ln_a[:2000], np.full(N - 2000, 4)])
+        pr, pc = plan.get(w, (0.5, 0.5))
+        ka = {(int(s), int(l)): i for i, (s, l) in enumerate(zip(st_a, ln_a))}; kb = {(int(s), int(l)): i for i, (s, l) in enumerate(zip(st_b, ln_b))}
+        u = rng.random(N + 8000); hit_a = u[:len(st_a)] < pr; iv_a = rng.random(len(st_a)) > 0.05
+        hit_b = np.zeros(len(st_b), bool); iv_b = rng.random(len(st_b)) > 0.05
+        for key, j in kb.items():   # couplage : sur cible commune, cand = ref sauf bascule contrôlée
+            if key in ka:
+                i = ka[key]; base_hit = hit_a[i]
+                if pc > pr: hit_b[j] = True if (base_hit or rng.random() < (pc - pr) / max(1e-9, 1 - pr)) else False
+                elif pc < pr: hit_b[j] = base_hit and rng.random() < pc / pr
+                else: hit_b[j] = base_hit
+            else: hit_b[j] = rng.random() < pc
+        spec["ref"][w] = (st_a, ln_a, iv_a, hit_a); spec["cand"][w] = (st_b, ln_b, iv_b, hit_b)
+        # attendu indépendant : dictionnaire des cibles communes dans la plage commune, in-vocab deux bras
+        END = min(int((st_a + ln_a).max()), int((st_b + ln_b).max())); b = c = n = 0
+        for key, i in ka.items():
+            j = kb.get(key)
+            if j is None or key[0] + key[1] > END or not (iv_a[i] and iv_b[j]): continue
+            n += 1; b += int(hit_a[i] and not hit_b[j]); c += int(hit_b[j] and not hit_a[i])
+        nm = sum(1 for key in ka if key in kb and key[0] + key[1] <= END)
+        expect[w] = {"n_clean": n, "b": b, "c": c, "match_rate": nm / min(len(st_a), len(st_b)),
+                     "rate_in_range": nm / max(1, min(int(((st_a + ln_a) <= END).sum()), int(((st_b + ln_b) <= END).sum())))}
+    spec["ref"]["seen"] = seen_spec(rng, SEENP["ref"]); spec["cand"]["seen"] = seen_spec(rng, SEENP["cand"])
+    D = f"{H}/runs_{name}"; shutil.rmtree(D, ignore_errors=True)
+    write_arm(f"{D}/ref", "ref", spec["ref"], res_ref); write_arm(f"{D}/cand", "cand", spec["cand"], res_cand); return D, expect
+def run(name, D, extra=(), env=None):
+    out = f"{D}/out"; p = subprocess.run([PY, f"{H}/verdict_CS1_synthcopy.py", "--runs-ref", f"{D}/ref", "--runs-cand", f"{D}/cand", "--outdir", out, *extra],
+                                         capture_output=True, text=True, env=dict(os.environ, **(env or {})))
+    if p.returncode: return {"rc": p.returncode, "stderr_tail": p.stderr.strip().splitlines()[-1:]}
+    return dict(json.load(open(f"{out}/verdict_CS1.json")), rc=0)
+R = {}
+def case(name, expected, plan, **kw):
+    extra = kw.pop("extra", ()); env = kw.pop("env", None); mut = kw.pop("mutate", None); D, ex = build(name, plan, **kw)
+    if mut: mut(D)
+    v = run(name, D, extra, env)
+    if v["rc"]: R[name] = {"expected": expected, "got": f"rc={v['rc']}", "detail": v["stderr_tail"], "ok": expected == f"rc={v['rc']}"}; print(name, R[name]); return v, ex
+    pw = v["per_window"]; chk = {w: {"got": [pw[w]["n_clean"], pw[w]["b_ref_only"], pw[w]["c_cand_only"], round(pw[w]["pairing"]["match_rate"], 4), round(pw[w]["pairing"]["match_rate_all_positions_r1_info"], 4)],
+                                     "indep": [ex[w]["n_clean"], ex[w]["b"], ex[w]["c"], round(ex[w]["rate_in_range"], 4), round(ex[w]["match_rate"], 4)], "rate_in_range_indep": round(ex[w]["rate_in_range"], 4),
+                                     "valid": pw[w]["valid"], "gain": pw[w]["sig_gain"], "loss": pw[w]["sig_loss"], "p": pw[w]["mcnemar_p"], "ci": pw[w]["boot_ci95_delta_pct"]} for w in pw}
+    agree = all(c["got"] == c["indep"] for c in chk.values())
+    R[name] = {"expected": expected, "got": v["decision"], "reasons": v["reasons"], "counts_agree_independent": agree, "windows": chk,
+               "ok": v["decision"] == expected and agree}
+    print(name, expected, v["decision"], agree, v["reasons"]); return v, ex
+G = {"fc2": (0.40, 0.60)}
+case("A_adopte", "ADOPTÉ", G)
+case("B1_rejete_perte", "REJETÉ", {"fc2": (0.40, 0.60), "fresh_fr": (0.60, 0.40)})
+case("B2_rejete_sans_gain", "REJETÉ", {})
+case("B3_perte_queries_seulement_hors_regle", "ADOPTÉ", {"fc2": (0.40, 0.60), "queries": (0.6, 0.3)})
+case("C1_scale_cand_0.12", "NON MESURABLE", G, res_cand={"cal": {"scale": 0.12}})
+case("C2_scale_ref_0.029", "NON MESURABLE", G, res_ref={"cal": {"scale": 0.029}})
+case("C3_scale_bornes_incluses_0.03_0.11", "ADOPTÉ", G, res_ref={"cal": {"scale": 0.03}}, res_cand={"cal": {"scale": 0.11}})
+case("C4_scale_absente", "NON MESURABLE", G, res_cand={"cal": {}})
+case("C5_scale_NaN", "NON MESURABLE", G, res_cand={"cal": {"scale": float("nan")}})
+case("C6_tentative_surcharge_--scale-hi", "rc=2", G, extra=("--scale-hi", "2.0"))
+case("D1_budget_snn_inegal", "NON MESURABLE", G, res_cand={"snn_tokens": 500000, "ticks_per_epoch": [500000, 500000]})
+case("D2_passe_snn_incomplete", "NON MESURABLE", G, res_cand={"ticks_per_epoch": [600000, 3000]}, res_ref={"ticks_per_epoch": [600000, 3000]})
+case("D3_am_inegal", "NON MESURABLE", G, res_cand={"am_tokens": 1000000})
+case("D4_data_sha_cand_egal_ref", "NON MESURABLE", G, res_cand={"data_sha256": REF_SHA})
+case("E1_tokenisations_differentes_aleatoires", "NON MESURABLE", G, tok="diff")
+case("E2_tokenisations_partielles_gain_r2_plage_commune", "ADOPTÉ", G, tok="partial")
+case("E3_coarse_tail_taux_0.5_accepte", "ADOPTÉ", G, tok="coarse_tail")
+case("F1_recompte_mix_absent", "NON MESURABLE", G, env={"SYN_RC_MIX": f"{H}/synth_inputs/ABSENT.json"})
+BROAD = "e89725bb94d9f167ffad1f68ae372343a14a1957ae0a1f0a67167aa974ec75a9"
+def put_broad(D):
+    for side in ("ref", "cand"):
+        f = f"{D}/{side}/ctl__test20k.npz"; z = dict(np.load(f)); z["window_sha256"] = np.array(BROAD); np.savez_compressed(f, **z)
+case("G1_test20k_broad_e89725bb_refuse", "rc=1", G, mutate=put_broad)
+def put_diffwin(D):
+    f = f"{D}/cand/ctl__fresh_en.npz"; z = dict(np.load(f)); z["window_sha256"] = np.array(WSHA["fresh_fr"]); np.savez_compressed(f, **z)
+case("G2_octets_fenetre_differents_refuse", "rc=1", G, mutate=put_diffwin)
+def put_extra_broad(D):
+    z = dict(np.load(f"{D}/cand/ctl__fc2.npz")); z["window_sha256"] = np.array(BROAD); os.makedirs(f"{D}/cand/ckpt_ctl", exist_ok=True); np.savez_compressed(f"{D}/cand/ckpt_ctl/extra.npz", **z)
+case("H1_npz_broad_en_plus_sous_dossier_refuse", "rc=1", G, mutate=put_extra_broad)
+case("H2_cand_arm_cm_refuse", "rc=2", G, extra=("--cand-arm", "cm"))
+SEENP.update(ref=0.99, cand=0.90); case("H3_perte_seen_fisher_avec_gain", "REJETÉ", G)
+SEENP.update(ref=0.99, cand=0.985); case("H4_seen_ecart_minime_non_sig", "ADOPTÉ", G)
+SEENP.update(ref=0.99, cand=0.99)
+json.dump(R, open(f"{H}/synth_results.json", "w"), indent=1, ensure_ascii=False, default=str)
+print("ALL_OK", all(r["ok"] for r in R.values()), {k: r["ok"] for k, r in R.items()})