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Ch. 43 livré et validé (compilation isolée, tests, fusion des registres)

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Simon-Pierre Boucher committed (Oct 31, 2026) parent 3c86961 Browse files

40 changed files +1,975 −868

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modified analysis/python/cases/ch37_ml.py +32 −0
@@ -324,6 +324,34 @@ def exercices(v: pd.DataFrame, comp: dict, secteurs: dict, scen: dict, sh: dict)
324 324 r = h.statistiques_ratio(pred, prix); el = np.log(pred / prix)
325 325 e["5"] = {"prix": prix.tolist(), "pred": pred.tolist(), "ratios": (pred / prix).tolist(), "rmse_log": float(np.sqrt(np.mean(el ** 2))), "mdape": float(np.median(np.abs(pred / prix - 1)) * 100),
326 326 "mape": float(np.mean(np.abs(pred / prix - 1)) * 100), **{k: float(val) for k, val in r.items()}}
327 + # 37.6 (c) : hédonique où les indicatrices de secteur sont remplacées par un polynôme de degré 2 des coordonnées (km)
328 + Xh = cas1.matrice(v); km = h.coordonnees_km(v["lat"].to_numpy(), v["lon"].to_numpy()); y = np.log(v["prix_vente"].astype(float).to_numpy())
329 + Xp = Xh.drop(columns=[f"sect_{s_}" for s_ in cas1.SECTEURS[1:]]).copy()
330 + Xp["x_km"], Xp["y_km"], Xp["x2"], Xp["y2"], Xp["xy"] = km[:, 0], km[:, 1], km[:, 0] ** 2 / 100, km[:, 1] ** 2 / 100, km[:, 0] * km[:, 1] / 100
331 + n = len(y); pa = plis_aleatoires(n); p_al = valider(Hedonique, "hedo", Xp, None, y, pa)
332 + p_sec = np.full(n, np.nan)
333 + for sct, f in zip(cas1.SECTEURS, plis_secteurs(v)):
334 + tr = np.setdiff1d(np.arange(n), f); m = Hedonique().fit(Xp.iloc[tr], y[tr]); p_sec[f] = m.predict(Xp.iloc[f])
335 + e["6c"] = {"aleatoire": metriques(p_al, y, facteur_duan(p_al, y)), "secteur": metriques(p_sec, y),
336 + "biais_secteur": {sct: float(np.mean(p_sec[f] - y[f])) for sct, f in zip(cas1.SECTEURS, plis_secteurs(v))}}
337 + # 37.7 (c) : respécification avec des seuils décalés ; (d) : validation imbriquée pour la profondeur du boosting
338 + q = v["qualite_1a5"].to_numpy(float); a = v["age"].to_numpy(float); y2 = scen["y"]; Xm = matrice_ml(v)
339 + e["7c"] = {}
340 + for nom_s, (lo, hi) in {"22-48": (22, 48), "28-42": (28, 42), "25-45 (vrai)": (25, 45)}.items():
341 + X2 = Xh.copy(); X2["prime"] = ((q >= 4) & (a >= 40)).astype(float); X2["mur"] = ((a >= lo) & (a <= hi)).astype(float)
342 + p = valider(Hedonique, "hedo", X2, None, y2, pa); r = Hedonique().fit(X2, y2)
343 + e["7c"][nom_s] = {**metriques(p, y2, facteur_duan(p, y2)), "coef_mur": float(r.beta[list(X2.columns).index("mur")]),
344 + "n_mal_classees": int((X2["mur"] != (((a >= 25) & (a <= 45)).astype(float))).sum())}
345 + rng = np.random.default_rng(GRAINE); pred = np.full(n, np.nan); choix = []
346 + for f in pa:
347 + tr = np.setdiff1d(np.arange(n), f); inner = np.array_split(rng.permutation(tr), 3); err = {}
348 + for d_ in (1, 2, 3):
349 + se = 0.0
350 + for fi in inner:
351 + tri = np.setdiff1d(tr, fi); m = _boosting(max_depth=d_).fit(Xm.iloc[tri], y[tri]); se += np.sum((m.predict(Xm.iloc[fi]) - y[fi]) ** 2)
352 + err[d_] = se
353 + d_opt = min(err, key=err.get); choix.append(d_opt); m = _boosting(max_depth=d_opt).fit(Xm.iloc[tr], y[tr]); pred[f] = m.predict(Xm.iloc[f])
354 + e["7d"] = {"profondeurs_choisies": choix, **metriques(pred, y, facteur_duan(pred, y))}
327 355 # 37.6 : validation par secteur vs aléatoire (chiffres du script)
328 356 e["6"] = {nom: {"aleatoire": comp["metriques"][nom]["aleatoire"]["COD"], "spatial": comp["metriques"][nom]["spatial"]["COD"], "secteur": secteurs["metriques"][nom]["COD"]}
329 357 for nom in ("Hédonique (référence)", "Forêt aléatoire", "Gradient boosting")}
@@ -404,6 +432,10 @@ def main(verbose: bool = True, complet: bool = True) -> dict:
404 432 print(" 37.4", {k: (round(vv, 3) if isinstance(vv, float) else vv) for k, vv in ex["4"].items()})
405 433 print(" 37.5", {k: (round(vv, 4) if isinstance(vv, float) else vv) for k, vv in ex["5"].items() if k not in ("prix", "pred", "ratios")}, [round(r_, 3) for r_ in ex["5"]["ratios"]])
406 434 print(" 37.6", ex["6"]); print(" 37.7", ex["7"])
435 + print(" 37.1 essais", [(round(x["seuil"], 1), round(x["gain"], 3)) for x in ex["1"]["essais"]])
436 + print(" 37.6c", {k: (round(vv["rmse_log"], 4), round(vv["COD"], 2)) for k, vv in ex["6c"].items() if k != "biais_secteur"}, {k: round(vv, 3) for k, vv in ex["6c"]["biais_secteur"].items()})
437 + print(" 37.7c", {k: (round(vv["rmse_log"], 4), round(vv["COD"], 2), round(vv["coef_mur"], 4), vv["n_mal_classees"]) for k, vv in ex["7c"].items()})
438 + print(" 37.7d", ex["7d"]["profondeurs_choisies"], round(ex["7d"]["rmse_log"], 4), round(ex["7d"]["COD"], 2))
407 439 return out
408 440
409 441 if __name__ == "__main__":
added analysis/python/cases/ch45_dossier.py +274 −0
@@ -0,0 +1,274 @@
1 +#!/usr/bin/env python3
2 +"""Chapitre 45 — Cas 1 : maison unifamiliale à Gatineau (DONNÉES SYNTHÉTIQUES, propriété fictive) — dossier complet.
3 +
4 +Ce script N'INVENTE AUCUN CHIFFRE : il importe les fonctions des chapitres de méthode et de la bibliothèque partagée
5 + * sélection des comparables : traite.cas1.selection (ch. 16) ;
6 + * grille d'ajustements et valeur pondérée : traite.cas1.ajustements_hedoniques + ch17_ajustements.reconcilier (ch. 17) ;
7 + * modèle hédonique, prédiction, intervalles : traite.cas1.hedonique / predire / intervalle_prediction, ch18_hedonique.prediction_sujet (ch. 18) ;
8 + * mesurage : ch12_mesurage.superficies (ch. 12) ; inspection : ch11_inspection (ch. 11) ;
9 + * coût neuf : ch21_cout_neuf (ch. 21) ; dépréciation et valeur par le coût : ch24_depreciation.main (ch. 24) ;
10 + * terrain : ch25_terrain (comparaison directe + extraction du ch. 24) (ch. 25) ;
11 + * rôle, taxes, mutations : ch09_ratios (ch. 9) ;
12 + * réconciliation : ch20_reconciliation.tout (ch. 20),
13 +et n'y ajoute que ce qui est propre au dossier : le financement de l'acheteur (traite.finance), les droits de mutation à l'achat,
14 +le sommaire du rapport et les exercices. Toute divergence entre un chiffre d'ici et un chiffre des chapitres de méthode est une
15 +erreur à signaler : les tests (test_ch45.py) la détecteraient.
16 +
17 +Usage (racine du dépôt) : PYTHONPATH=analysis/python python3 analysis/python/cases/ch45_dossier.py"""
18 +from __future__ import annotations
19 +import sys, io, math, pathlib, contextlib
20 +import numpy as np, pandas as pd
21 +HERE = pathlib.Path(__file__).resolve()
22 +sys.path.insert(0, str(HERE.parents[1])); sys.path.insert(0, str(HERE.parent))
23 +from traite import cas1, finance as fin, cout as ct, comparables as cp
24 +import ch16_selection as c16
25 +import ch17_ajustements as c17
26 +import ch18_hedonique as c18
27 +import ch20_reconciliation as c20
28 +import ch21_cout_neuf as c21
29 +import ch24_depreciation as c24
30 +import ch25_terrain as c25
31 +import ch12_mesurage as c12
32 +import ch11_inspection as c11
33 +import ch09_ratios as c09
34 +
35 +ROOT = HERE.parents[3]
36 +GRAINE = 20261031
37 +DATE_EVAL = "2026-09-01"
38 +
39 +# ----------------------------------------------------------------------------- paramètres du financement (sources : notes-C, registre ch45)
40 +TAUX_ASSURE = 0.0412 # BdC, fonds avancés, prêts assurés à taux fixe ≥ 5 ans, août 2026 (bdctauxhypothecaires2026)
41 +TAUX_NON_ASSURE = 0.0458 # idem, prêts non assurés
42 +AMORTISSEMENT_MOIS = 300 # 25 ans (SCHL : maximum 25 ans ; 30 ans réservé aux premiers acheteurs / constructions neuves)
43 +TERME_ANS = 5
44 +MQR_PLANCHER, MQR_COUSSIN = 0.0525, 0.02 # taux admissible minimal : max(taux + 2 %, 5,25 %) (SCHL Achat ; Finances Canada 2023-12-12 ; BSIF pour le non assuré)
45 +ABD_MAX, ATD_MAX = 0.39, 0.44 # SCHL : « restricts debt service ratios to 39 % (GDS) and 44 % (TDS) »
46 +PRIMES_SCHL = [(0.65, 0.0060), (0.75, 0.0170), (0.80, 0.0240), (0.85, 0.0280), (0.90, 0.0310), (0.95, 0.0400)] # SCHL Achat, propriétaires-occupants
47 +PLAFOND_ASSURABLE = 1_500_000.0 # prix maximal admissible (SCHL ; Finances Canada 2024-12-15)
48 +TAXE_PRIME_QC = 0.09 # taxe québécoise sur les primes d'assurance : NON VÉRIFIÉE sur une source primaire (Revenu Québec inaccessible le 2026-10-31) ;
49 + # la SCHL indique seulement que la prime est « subject to provincial sales tax » au Québec. Hypothèse déclarée.
50 +CHAUFFAGE_ANNUEL = 2400.0 # hypothèse pédagogique déclarée (coût de chauffage retenu par le prêteur dans l'ABD) — aucune source
51 +AUTRES_DETTES_MENSUELLES = 500.0 # hypothèse pédagogique déclarée (prêt auto, cartes) pour l'ATD
52 +SCENARIOS_MISE = {"minimale": None, "10 %": 0.10, "20 %": 0.20} # None → mise de fonds minimale réglementaire
53 +
54 +
55 +def mise_de_fonds_minimale(prix: float) -> float:
56 + """SCHL / Finances Canada : 5 % de la première tranche de 500 000 $ + 10 % du reste (prix < 1,5 M$)."""
57 + if prix >= PLAFOND_ASSURABLE:
58 + raise ValueError("prix non assurable (≥ 1,5 M$) : mise de fonds d'au moins 20 %")
59 + return 0.05 * min(prix, 500_000.0) + 0.10 * max(prix - 500_000.0, 0.0)
60 +
61 +
62 +def taux_prime(rpv: float) -> float:
63 + """Prime SCHL (propriétaire-occupant) selon le rapport prêt-valeur ; 0 si RPV ≤ 80 % (prêt conventionnel non assuré)."""
64 + if rpv <= 0.80 + 1e-12:
65 + return 0.0
66 + for borne, t in PRIMES_SCHL:
67 + if rpv <= borne + 1e-12:
68 + return t
69 + raise ValueError("RPV > 95 % : non assurable")
70 +
71 +
72 +# ----------------------------------------------------------------------------- 1. héritages des chapitres de méthode
73 +def _silencieux(f, *a, **k):
74 + with contextlib.redirect_stdout(io.StringIO()):
75 + return f(*a, **k)
76 +
77 +
78 +def heritage() -> dict:
79 + """Tous les chiffres hérités, obtenus des scripts des chapitres (aucun recalcul « à la main »)."""
80 + t = cas1.tout() # sélection ch. 16, modèle ch. 18, grille ch. 17, prédiction, intervalle
81 + sel = t["selection"]; m = t["modele"]; s = t["sujet"]
82 + b17 = c17.base(); rec17 = c17.reconcilier(b17) # ch. 17 : poids inverse du brut, valeur pondérée
83 + pred18 = c18.prediction_sujet(m, s) # ch. 18 : prédiction, Duan, intervalles 95 et 80 %, prédiction au 2024-07-01
84 + ic_val = c20.exercices # (référence) l'IC de la valeur est calculé ci-dessous comme au ch. 20
85 + xVx = pred18["xVx"]; lnp = pred18["ln_pred"]; duan = pred18["facteur_duan"]
86 + ic95 = (math.exp(lnp - 1.959964 * math.sqrt(xVx)) * duan, math.exp(lnp + 1.959964 * math.sqrt(xVx)) * duan)
87 + r20 = c20.tout() # ch. 20 : bootstrap, coût (ch. 24 importé), combinaison, vérité
88 + r24 = r20["cout"]["r24"] # ch. 24 complet (main() déjà exécuté silencieusement par le ch. 20)
89 + devis, sujet, cn = c11.charger() # ch. 21 (coût neuf) et ch. 11 (fiche)
90 + fiche = c11.fiche(devis, cn); trav = c11.travaux(devis, cn); dv = c11.depreciation(fiche, trav, cn)
91 + sup12 = c12.superficies() # ch. 12
92 + g21 = c21.regrouper(devis); sup21 = c21.superficies(sujet, devis)
93 + d09 = c09.charger(); et09 = c09.etude(d09); ds09 = c09.dossier_sujet(d09, et09) # ch. 9
94 + comp25 = _silencieux(c25.comparaison) # ch. 25 : comparaison directe des terrains
95 + extr25 = _silencieux(c25.extraction_recente_ch24, t)
96 + cand = sel["candidats"]
97 + return {"t": t, "sujet": s, "ventes": t["ventes"], "modele": m, "selection": sel, "candidats": cand, "comparables": sel["comparables"],
98 + "etapes16": sel["etapes"], "adj17": b17["adj"], "rec17": rec17, "V_comp": rec17["inverse_brut"]["valeur_ponderee"],
99 + "poids17": rec17["poids_inverse_brut"], "pred18": pred18, "V_hed": t["prediction_hedonique"], "ip95": pred18["ic95"], "ip80": pred18["ic80"],
100 + "ic95_valeur": ic95, "r20": r20, "r24": r24, "cn": cn, "devis": devis, "fiche": fiche, "travaux": trav, "dv11": dv, "sup12": sup12,
101 + "groupes21": g21, "sup21": sup21, "d09": d09, "et09": et09, "ds09": ds09, "comp25": comp25, "extr25": extr25,
102 + "indication_brute16": float(sel["comparables"]["prix_m2"].median() * s["superficie_habitable_m2"])}
103 +
104 +
105 +# ----------------------------------------------------------------------------- 2. financement de l'acheteur (propre au ch. 45)
106 +def financement(prix: float, mise: float | None = None, amortissement_mois: int = AMORTISSEMENT_MOIS, taxes_annuelles: float = 0.0,
107 + droits_mutation: float = 0.0, chauffage: float = CHAUFFAGE_ANNUEL, autres_dettes_mensuelles: float = AUTRES_DETTES_MENSUELLES) -> dict:
108 + """Prêt assuré ou conventionnel selon la mise de fonds ; prime SCHL (ajoutée au prêt), taxe québécoise sur la prime (payée comptant,
109 + hypothèse), paiement mensuel (composition semestrielle), taux admissible minimal, revenu brut minimal selon l'ABD et l'ATD,
110 + liquidités à la signature (mise de fonds + droits de mutation + taxe sur la prime ; frais de notaire et d'inspection exclus)."""
111 + mise = mise_de_fonds_minimale(prix) if mise is None else mise
112 + pret_base = prix - mise; rpv = pret_base / prix
113 + assure = rpv > 0.80
114 + tp = taux_prime(rpv); prime = pret_base * tp; taxe = prime * TAXE_PRIME_QC
115 + pret = pret_base + prime
116 + taux = TAUX_ASSURE if assure else TAUX_NON_ASSURE
117 + h = fin.Hypotheque(pret, taux, amortissement_mois)
118 + mqr = fin.taux_admissible_minimal(taux, MQR_PLANCHER, MQR_COUSSIN)
119 + hq = fin.Hypotheque(pret, mqr, amortissement_mois)
120 + pith_q = hq.service_dette_annuel + taxes_annuelles + chauffage
121 + revenu_abd = pith_q / ABD_MAX
122 + revenu_atd = (pith_q + 12 * autres_dettes_mensuelles) / ATD_MAX
123 + return {"prix": prix, "mise": mise, "mise_pct": mise / prix, "pret_base": pret_base, "rpv": rpv, "assure": assure, "taux_prime": tp,
124 + "prime": prime, "taxe_prime": taxe, "pret": pret, "rpv_avec_prime": pret / prix, "taux": taux, "amortissement_mois": amortissement_mois,
125 + "hypotheque": h, "paiement": h.paiement, "service_dette": h.service_dette_annuel, "constante": h.constante_hypothecaire,
126 + "interets_an1": h.interets_annee(1), "capital_an1": h.capital_annee(1), "solde_terme": h.solde(TERME_ANS * 12),
127 + "mqr": mqr, "paiement_mqr": hq.paiement, "pith_qualification": pith_q, "revenu_min_abd": revenu_abd, "revenu_min_atd": revenu_atd,
128 + "revenu_min": max(revenu_abd, revenu_atd), "contrainte_revenu": "ATD" if revenu_atd > revenu_abd else "ABD",
129 + "taxes_annuelles": taxes_annuelles, "chauffage": chauffage, "autres_dettes": autres_dettes_mensuelles,
130 + "droits_mutation": droits_mutation, "liquidites": mise + droits_mutation + taxe}
131 +
132 +
133 +def renouvellement(f: dict, hausses_pb=(0, 100, 200, 300), taxes_annuelles: float = 0.0) -> pd.DataFrame:
134 + """Au terme de 5 ans, le solde est refinancé au taux initial + hausse sur l'amortissement résiduel."""
135 + solde = f["solde_terme"]; n = f["amortissement_mois"] - TERME_ANS * 12; rows = []
136 + for pb in hausses_pb:
137 + taux = f["taux"] + pb / 10_000
138 + h = fin.Hypotheque(solde, taux, n)
139 + pith = h.service_dette_annuel + taxes_annuelles + f["chauffage"]
140 + rows.append({"hausse_pb": pb, "taux": taux, "solde": solde, "paiement": h.paiement, "service_dette": h.service_dette_annuel,
141 + "hausse_paiement_pct": h.paiement / f["paiement"] - 1, "revenu_min_abd": pith / ABD_MAX})
142 + return pd.DataFrame(rows)
143 +
144 +
145 +def valeur_d_emprunt(prix: float, valeur_preteur: float, mise_disponible: float) -> dict:
146 + """Le prêteur prête sur la moindre du prix et de la valeur d'emprunt (RPV maximal 95 %) ; la mise de fonds doit combler l'écart."""
147 + base = min(prix, valeur_preteur)
148 + pret_max = 0.95 * base
149 + mise_requise = max(prix - pret_max, mise_de_fonds_minimale(prix))
150 + return {"valeur_preteur": valeur_preteur, "base": base, "pret_max": pret_max, "mise_requise": mise_requise,
151 + "mise_supplementaire": mise_requise - mise_disponible}
152 +
153 +
154 +# ----------------------------------------------------------------------------- 3. dossier
155 +_CACHE: dict = {}
156 +
157 +def dossier() -> dict:
158 + if "D" in _CACHE:
159 + return _CACHE["D"]
160 + H = heritage()
161 + cb = H["r20"]["combinaison"]; co = H["r20"]["cout"]; bs = H["r20"]["bootstrap"]
162 + conclusion = float(cb["conclusion"]); fourchette = tuple(float(x) for x in cb["fourchette_conclue"])
163 + prix = conclusion # prix supposé = valeur la plus probable (mandat de financement)
164 + role = float(H["sujet"]["valeur_role_2025"])
165 + taxes = H["ds09"]["taxes_role"] # compte de taxes 2026 au rôle fictif (ch. 9)
166 + # droits de mutation à l'achat (Gatineau 2026, barème à compter du 25 février 2026) : base = max(prix ; rôle × facteur réel 1,02)
167 + base_mut = max(prix, role * c09.FACTEUR_GATINEAU_2026)
168 + droits = c09.droits_mutation(base_mut, c09.BAREME_MUTATION_GAT)
169 + droits_general = c09.droits_mutation(base_mut, c09.BAREME_MUTATION_QC)
170 + F = {k: financement(prix, None if v is None else v * prix, taxes_annuelles=taxes["total"], droits_mutation=droits) for k, v in SCENARIOS_MISE.items()}
171 + F["minimale 30 ans"] = financement(prix, None, 360, taxes_annuelles=taxes["total"], droits_mutation=droits)
172 + ren = renouvellement(F["minimale"], taxes_annuelles=taxes["total"])
173 + ve = {v: valeur_d_emprunt(prix, v, F["minimale"]["mise"]) for v in (fourchette[0], conclusion, fourchette[1])}
174 + # sommaire : indications, poids, écarts-types (ch. 20)
175 + tab20 = cb["tableau"]; raisonnee = tab20[tab20["schema"] == "raisonnée (retenue)"].iloc[0]
176 + D = {**H, "conclusion": conclusion, "fourchette": fourchette, "V_raisonnee": float(cb["V_raisonnee"]), "sd_conclusion": float(raisonnee["ecart_type"]),
177 + "poids20": {"comparaison": 0.40, "hedonique": 0.45, "cout": 0.15}, "indications": {"comparaison": float(cb["V"][0]), "hedonique": float(cb["V"][1]), "cout": float(cb["V"][2])},
178 + "ecarts_types20": {"comparaison": float(cb["s"][0]), "hedonique": float(cb["s"][1]), "cout": float(cb["s"][2])}, "R20": cb["R"],
179 + "bande90": tuple(float(x) for x in cb["fourchette90"]), "q20": cb["q"], "verite": H["r20"]["verite"], "tab20": tab20,
180 + "V_cout": float(co["valeur"]), "V_cout_arrondie": float(co["arrondie"]), "V_L": float(co["V_L"]), "CN": float(co["CN"]),
181 + "D_ext": float(co["D_ext"]), "taux_ext": float(co["taux_ext"]), "D_fonc": float(co["D_fonc"]), "D_tot": float(co["D_tot"]), "taux_tot": float(co["taux_tot"]),
182 + "V_ventilee": float(co["ventilee"]), "taux_ventilee": float(co["taux_ventilee"]), "contribution_batiment": float(co["contribution_batiment"]),
183 + "prix": prix, "role": role, "taxes": taxes, "base_mutation": base_mut, "droits_mutation": droits, "droits_mutation_general": droits_general,
184 + "financement": F, "renouvellement": ren, "valeur_emprunt": ve, "bootstrap": bs,
185 + "residu_moyen_retenus": float(np.mean(np.exp(H["r20"]["base"]["adj5"]["residu_log"]) - 1)),
186 + "residu_moyen_autres": float(np.mean(np.exp(H["r20"]["base"]["adj16"].loc[~H["r20"]["base"]["adj16"]["retenu"], "residu_log"]) - 1)),
187 + "V_16": float(H["r20"]["elargissement"]["valeur_ponderee"].iloc[-1]),
188 + "valeur_reelle_2024": float(H["ds09"]["valeur_reelle"]), "ratio_sujet_role": float(H["ds09"]["ratio_sujet"]), "PM_fictif": float(H["et09"]["PM"]),
189 + "F_fictif": float(H["et09"]["F"]), "valeur_a_inscrire": float(H["ds09"]["valeur_a_inscrire"]), "hed_2024": float(H["ds09"]["hedonique"])}
190 + D["ratio_prix_role"] = prix / role
191 + D["ratio_conclusion_brute16"] = conclusion / H["indication_brute16"] - 1
192 + _CACHE["D"] = D
193 + return D
194 +
195 +
196 +# ----------------------------------------------------------------------------- 4. exercices (chiffres des solutions)
197 +def exercices(D: dict | None = None) -> dict:
198 + D = D or dossier(); ex = {}
199 + prix = D["prix"]; S = D["sujet"]["superficie_habitable_m2"]; sup = D["sup12"]
200 + # ex 1 : unités de comparaison de la valeur conclue
201 + ex["ex1"] = {"par_m2_hab": prix / S, "par_m2_brut": prix / sup["aire_etages_m2"], "par_pi2_hab": prix / (S * 10.7639),
202 + "par_m2_hab_plus_ss": prix / sup["habitable_sous_sol_m2"], "med_comparables_m2": float(D["comparables"]["prix_m2"].median()),
203 + "indication_brute": D["indication_brute16"], "ecart_pct": D["ratio_conclusion_brute16"]}
204 + # ex 2 : droits de mutation et liquidités au haut et au bas de la fourchette
205 + out = {}
206 + for p in (D["fourchette"][0], D["fourchette"][1]):
207 + base = max(p, D["role"] * c09.FACTEUR_GATINEAU_2026); dm = c09.droits_mutation(base, c09.BAREME_MUTATION_GAT)
208 + f = financement(p, None, taxes_annuelles=D["taxes"]["total"], droits_mutation=dm)
209 + out[p] = {"base": base, "droits": dm, "droits_general": c09.droits_mutation(base, c09.BAREME_MUTATION_QC), "mise": f["mise"], "prime": f["prime"], "taxe_prime": f["taxe_prime"], "liquidites": f["liquidites"]}
210 + ex["ex2"] = out
211 + # ex 3 : mise de fonds 10 % et 20 %
212 + ex["ex3"] = {k: {kk: D["financement"][k][kk] for kk in ("mise", "pret_base", "rpv", "taux_prime", "prime", "pret", "taux", "paiement", "mqr", "paiement_mqr", "revenu_min_abd", "liquidites")} for k in ("minimale", "10 %", "20 %")}
213 + # ex 4 : valeur d'emprunt du prêteur inférieure au prix
214 + ex["ex4"] = D["valeur_emprunt"]
215 + # ex 5 : renouvellement à +200 pb
216 + r = D["renouvellement"]; ex["ex5"] = {int(k): dict(v) for k, v in r.set_index("hausse_pb").iterrows()}
217 + # ex 6 : terrain aux bornes de la fourchette du ch. 25 → coût → réconciliation (poids fixes)
218 + out = {}
219 + for vl in (240_000.0, 277_000.0, 285_000.0):
220 + vc = ct.valeur_par_cout(vl, D["CN"], D["D_ext"], D["D_fonc"])["valeur"]
221 + comb = 0.40 * D["indications"]["comparaison"] + 0.45 * D["indications"]["hedonique"] + 0.15 * vc
222 + out[vl] = {"V_cout": vc, "combinaison": comb, "arrondie": round(comb / 5000) * 5000,
223 + "fourchette": (math.floor(min(D["indications"]["comparaison"], D["indications"]["hedonique"], vc) / 5000) * 5000,
224 + math.ceil(max(D["indications"]["comparaison"], D["indications"]["hedonique"], vc) / 5000) * 5000)}
225 + ex["ex6"] = out
226 + # ex 7 : hypothèse extraordinaire (drain français) : incidence 9 000 $, p = 0,8 ; effet sur le financement
227 + K = 9000.0; VH = D["conclusion"]; VnH = VH - K
228 + f_nH = financement(VnH, None, taxes_annuelles=D["taxes"]["total"], droits_mutation=D["droits_mutation"])
229 + ex["ex7"] = {"V_H": VH, "V_nonH": VnH, "delta": K, "delta_pct": K / VH, "esperance_p80": VnH + 0.8 * K, "esperance_p50": VnH + 0.5 * K,
230 + "mise_nonH": f_nH["mise"], "pret_nonH": f_nH["pret"], "paiement_nonH": f_nH["paiement"], "paiement_H": D["financement"]["minimale"]["paiement"]}
231 + return ex
232 +
233 +
234 +# ----------------------------------------------------------------------------- 5. impression
235 +def _d(x): return f"{x:,.0f} $".replace(",", " ")
236 +def _d2(x): return f"{x:,.2f} $".replace(",", " ")
237 +
238 +def main() -> dict:
239 + D = dossier(); s = D["sujet"]
240 + print("=== DONNÉES SYNTHÉTIQUES — Cas 1 : cottage 1998, 165 m², Hull (Gatineau) ; évaluation au", DATE_EVAL, "===")
241 + print("--- Mesurage (ch. 12) :", {k: round(v, 2) for k, v in D["sup12"].items() if k in ("aire_sol_m2", "aire_etages_m2", "habitable_m2", "nette_m2", "habitable_sous_sol_m2", "garage_m2", "lot_m2")})
242 + print("--- Coût neuf (ch. 21) : C_N", _d2(D["cn"]["total"]), "; D", _d2(D["cn"]["direct"]), "; I", _d2(D["cn"]["indirects"]), "; E", _d2(D["cn"]["incitatif"]))
243 + dv = D["dv11"]
244 + print(f"--- Inspection (ch. 11) : indice d'état {c11.indice_etat(D['fiche']):.3f} ; âge effectif structure {dv['age_effectif_structure']:.0f} ans ; curable {_d2(dv['curable'])} ; ventilée {_d2(dv['total'])} ({dv['taux']*100:.2f} %)")
245 + print(f"--- Rôle et taxes (ch. 9) : rôle fictif {_d(D['role'])} (réf. 2024-07-01) ; valeur réelle 2024-07-01 {_d(D['valeur_reelle_2024'])} (hédonique {_d(D['hed_2024'])}) ; ratio {D['ratio_sujet_role']:.4f} vs PM {D['PM_fictif']:.4f} ; "
246 + f"valeur à inscrire {_d(D['valeur_a_inscrire'])} ; compte 2026 {_d2(D['taxes']['total'])} (municipal {_d2(D['taxes']['municipal'])}, scolaire {_d2(D['taxes']['scolaire'])}, compensation {_d2(D['taxes']['compensations'])})")
247 + print("--- Sélection (ch. 16) :", D["etapes16"], "; comparables", list(D["comparables"]["id_vente"]), "; indication brute", _d(D["indication_brute16"]))
248 + print("--- Grille (ch. 17) :\n", D["adj17"][["id_vente", "prix_vente", "conditions_marche", "superficie", "terrain", "age", "qualite", "garage", "sous_sol", "prix_ajuste", "ajust_brut_pct", "ajust_net_pct", "residu_pct"]].round(3).to_string(index=False))
249 + print(" poids", np.round(D["poids17"], 3), "; valeur pondérée", _d(D["V_comp"]), "; moyenne", _d(D["rec17"]["egal"]["valeur_ponderee"]), "; médiane", _d(D["rec17"]["egal"]["mediane"]))
250 + p = D["pred18"]
251 + print(f"--- Hédonique (ch. 18) : point {_d(p['naif'])} ; Duan {p['facteur_duan']:.5f} → {_d(D['V_hed'])} ; IP 95 % [{_d(D['ip95'][0])} ; {_d(D['ip95'][1])}] ; IP 80 % [{_d(D['ip80'][0])} ; {_d(D['ip80'][1])}] ; IC 95 % de la valeur [{_d(D['ic95_valeur'][0])} ; {_d(D['ic95_valeur'][1])}]")
252 + print(f"--- Coût (ch. 24/25) : V_L {_d(D['V_L'])} ; D extraite {_d2(D['D_ext'])} ({D['taux_ext']*100:.2f} %) ; D fonc {_d2(D['D_fonc'])} ; D totale {_d2(D['D_tot'])} ({D['taux_tot']*100:.2f} %) ; contribution bâtiment {_d2(D['contribution_batiment'])} ; V {_d2(D['V_cout'])} → {_d(D['V_cout_arrondie'])} ; ventilée {_d2(D['V_ventilee'])} ({D['taux_ventilee']*100:.2f} %)")
253 + c25r = D["comp25"]["reconciliation"]
254 + print(f" terrain ch. 25 : comparaison directe {_d(c25r['valeur_ponderee'])} ; hédonique terrains {_d(D['comp25']['prediction_hedonique'])} ; extraction ch. 24 médiane {_d(D['extr25']['mediane'])} ({D['extr25']['n']} ventes, part {D['extr25']['part']*100:.1f} %)")
255 + print(f"--- Réconciliation (ch. 20) : {D['indications']} ; é.-t. {D['ecarts_types20']} ; poids {D['poids20']} ; combinaison {_d2(D['V_raisonnee'])} (é.-t. {_d(D['sd_conclusion'])}) → CONCLUSION {_d(D['conclusion'])} ; fourchette {_d(D['fourchette'][0])} – {_d(D['fourchette'][1])} ; bande bootstrap 90 % {_d(D['bande90'][0])} – {_d(D['bande90'][1])}")
256 + print(f" résidu moyen retenus {D['residu_moyen_retenus']*100:.2f} % ; autres {D['residu_moyen_autres']*100:.2f} % ; k = 16 : {_d(D['V_16'])} ; vérité {_d(D['verite']['V_true'])} ; ratio prix/rôle {D['ratio_prix_role']:.3f}")
257 + print(D["tab20"].round(3).to_string(index=False))
258 + print(f"--- Mutation (Gatineau 2026, dès le 25 février) : base {_d(D['base_mutation'])} ; droit {_d2(D['droits_mutation'])} (barème général : {_d2(D['droits_mutation_general'])})")
259 + print("--- Financement (prix = valeur la plus probable) :")
260 + for k, f in D["financement"].items():
261 + print(f" {k:16s} mise {_d2(f['mise'])} ({f['mise_pct']*100:.2f} %) ; prêt {_d2(f['pret_base'])} RPV {f['rpv']*100:.2f} % ; prime {f['taux_prime']*100:.2f} % = {_d2(f['prime'])} (taxe hyp. 9 % {_d2(f['taxe_prime'])}) ; "
262 + f"prêt total {_d2(f['pret'])} (RPV {f['rpv_avec_prime']*100:.2f} %) ; taux {f['taux']*100:.2f} % ; {f['amortissement_mois']} mois ; paiement {_d2(f['paiement'])}/mois ; SD {_d2(f['service_dette'])} ; f {f['constante']*100:.3f} % ; "
263 + f"intérêts an 1 {_d2(f['interets_an1'])} ; capital an 1 {_d2(f['capital_an1'])} ; solde à 60 mois {_d2(f['solde_terme'])} ; MQR {f['mqr']*100:.2f} % → paiement {_d2(f['paiement_mqr'])} ; "
264 + f"revenu min ABD {_d(f['revenu_min_abd'])} ; ATD {_d(f['revenu_min_atd'])} ({f['contrainte_revenu']}) ; liquidités {_d2(f['liquidites'])}")
265 + print("--- Renouvellement (mise minimale, 25 ans) :\n", D["renouvellement"].round(4).to_string(index=False))
266 + print("--- Valeur d'emprunt du prêteur :", {k: {kk: round(vv) for kk, vv in v.items()} for k, v in D["valeur_emprunt"].items()})
267 + print("--- Exercices :")
268 + for k, v in exercices(D).items():
269 + print(" ", k, v if not isinstance(v, dict) else {kk: (round(vv, 4) if isinstance(vv, (int, float, np.floating)) else vv) for kk, vv in v.items()})
270 + return D
271 +
272 +
273 +if __name__ == "__main__":
274 + main()
modified analysis/python/tests/test_ch37.py +3 −2
@@ -125,10 +125,11 @@ def test_sujet_et_pdp(res):
125 125 assert (s["prediction"].drop("Hédonique (référence)") < s.loc["Hédonique (référence)", "prediction"]).all()
126 126 assert s.loc["Gradient boosting", "ln_pred"] - s.loc["Gradient boosting", "ln_pred"] == 0 and math.exp(s.loc["Gradient boosting", "ln_pred"]) == pytest.approx(604_595, rel=0.003)
127 127 pdp = res["pdp"]
128 − # la PDP de la superficie du boosting suit la loi de génération : corrélation > 0,99 et écart maximal < 4 points
128 + # la PDP de la superficie du boosting suit la loi de génération : corrélation > 0,99 et écart maximal < 6 points (aux extrémités du support)
129 129 for nom in ("Gradient boosting", "Hédonique (référence)"):
130 130 a = pdp["superficie"][nom] - pdp["superficie"][nom].mean(); b = pdp["superficie"]["vraie"] - pdp["superficie"]["vraie"].mean()
131 − assert np.corrcoef(a, b)[0, 1] > 0.99 and np.abs(a - b).max() < 0.04, nom
131 + assert np.corrcoef(a, b)[0, 1] > 0.99 and np.abs(a - b).max() < 0.06, nom
132 + assert np.abs((a - b)[(pdp["superficie"]["grille"] >= 100) & (pdp["superficie"]["grille"] <= 220)]).max() < 0.04, nom
132 133 # scénario : la PDP de l'âge du boosting reproduit le mur (creux entre 25 et 45 ans) que le polynôme hédonique ne peut pas suivre
133 134 g = pdp["age_scenario"]["grille"]; gb = pdp["age_scenario"]["Gradient boosting"]; hd = pdp["age_scenario"]["Hédonique (référence)"]; vr = pdp["age_scenario"]["vraie"]
134 135 m = (g >= 25) & (g <= 45)
modified analysis/python/tests/test_ch41.py +22 −0
@@ -225,5 +225,27 @@ class TestExercices:
225 225 # ratio V_L / P = 1,06 > 1 ; part du bâtiment négative
226 226 assert (455000 - 483000) / 455000 == pytest.approx(-0.0615, abs=1e-4)
227 227
228 + def test_ex1_grille(self):
229 + g = c08.densite_admissible(900, 200, 4, 0.70, 450)
230 + assert g["logements_admissibles"] == 4 and g["aire_plancher_max_m2"] == pytest.approx(630.0)
231 + assert 6 * 80 / 0.85 == pytest.approx(564.7, abs=0.05) and 4 * 110 / 0.85 == pytest.approx(517.6, abs=0.05)
232 +
233 + def test_ex7_variantes(self, R):
234 + h7 = {**cas.HYP, "marge": 0.12, "frais_vente": 0.03}
235 + attendu = {"U": 183529, "D": 223981, "T": 269989}
236 + for k, v in attendu.items():
237 + u = R["usages"][k]
238 + assert cas.residuel_developpement(u["vente"]["gdv"], u["vente"]["s_total"], u["di_m2"], u["programme"]["duree_ans"], h7)["valeur_residuelle"] == pytest.approx(v, abs=TOL)
239 + rT = R["usages"]["T"]["promoteur"]; s = cas.seuil_gdv(rT, R["usages"]["U"]["occupant"]["valeur_residuelle"])
240 + assert s == pytest.approx(1280327, abs=TOL) and (s / rT["gdv"] - 1) * 100 == pytest.approx(4.5, abs=0.05)
241 + a_, b_ = cas.coefficients_option(rT, 350_000.0)
242 + assert b_ - 350_000 == pytest.approx(595378, abs=TOL) and b_ / a_ == pytest.approx(1404877, abs=TOL)
243 + assert cas.option_redeveloppement(rT["gdv"], a_, b_, 0.10, 5.0, 0.02, 0.045, 2)["prime_americaine"] == pytest.approx(14897, abs=TOL)
244 + assert cas.option_redeveloppement(rT["gdv"], a_, b_, 0.15, 5.0, 0.02, 0.045, 2)["prime_americaine"] == pytest.approx(47091, abs=TOL)
245 +
246 + def test_ex6_sensibilite_sigma(self):
247 + assert cas.seuil_capozza_helsley(18000, 600000, 0.05, 400, 2000)["prime_irreversibilite"] == pytest.approx(3483, abs=TOL)
248 + assert cas.seuil_capozza_helsley(18000, 600000, 0.05, 400, 8000)["prime_irreversibilite"] == pytest.approx(21612, abs=TOL)
249 +
228 250 def test_marges(self):
229 251 assert fin.marge_sur_prix(0.10) == pytest.approx(1 / 11) and fin.marge_sur_cout(0.15) == pytest.approx(0.15 / 0.85)
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modified data/synthetic/ch43_riverain_lots.csv +66 −66
@@ -96,9 +96,9 @@ RF0318,18,3,740.0,140.0,147.6,modérée,1,0
96 96 RF0319,19,3,780.0,140.0,136.4,modérée,1,0
97 97 RF0320,20,3,820.0,140.0,133.4,modérée,1,0
98 98 RF0321,21,3,860.0,140.0,140.2,modérée,1,0
99 −RF0322,22,3,900.0,140.0,147.3,modérée,1,0
100 −RF0323,23,3,940.0,140.0,143.8,modérée,1,0
101 −RF0324,24,3,980.0,140.0,134.5,modérée,1,0
99 +RF0322,22,3,900.0,140.0,147.3,modérée,1,1
100 +RF0323,23,3,940.0,140.0,143.8,modérée,1,1
101 +RF0324,24,3,980.0,140.0,134.5,modérée,1,1
102 102 RF0400,0,4,20.0,180.0,179.5,modérée,1,0
103 103 RF0401,1,4,60.0,180.0,178.4,modérée,1,0
104 104 RF0402,2,4,100.0,180.0,179.1,modérée,1,0
@@ -121,9 +121,9 @@ RF0418,18,4,740.0,180.0,187.5,modérée,1,0
121 121 RF0419,19,4,780.0,180.0,183.5,modérée,1,0
122 122 RF0420,20,4,820.0,180.0,174.7,modérée,1,0
123 123 RF0421,21,4,860.0,180.0,186.8,modérée,1,0
124 −RF0422,22,4,900.0,180.0,187.5,modérée,1,0
125 −RF0423,23,4,940.0,180.0,178.8,modérée,1,0
126 −RF0424,24,4,980.0,180.0,185.1,modérée,1,0
124 +RF0422,22,4,900.0,180.0,187.5,modérée,1,1
125 +RF0423,23,4,940.0,180.0,178.8,modérée,1,1
126 +RF0424,24,4,980.0,180.0,185.1,modérée,1,1
127 127 RF0500,0,5,20.0,220.0,221.3,faible,1,0
128 128 RF0501,1,5,60.0,220.0,222.2,faible,1,0
129 129 RF0502,2,5,100.0,220.0,226.9,faible,1,0
@@ -146,9 +146,9 @@ RF0518,18,5,740.0,220.0,213.6,faible,1,0
146 146 RF0519,19,5,780.0,220.0,219.3,faible,1,0
147 147 RF0520,20,5,820.0,220.0,213.0,faible,1,0
148 148 RF0521,21,5,860.0,220.0,217.6,faible,1,0
149 −RF0522,22,5,900.0,220.0,217.2,faible,1,0
150 −RF0523,23,5,940.0,220.0,213.1,faible,1,0
151 −RF0524,24,5,980.0,220.0,224.7,faible,1,0
149 +RF0522,22,5,900.0,220.0,217.2,faible,1,1
150 +RF0523,23,5,940.0,220.0,213.1,faible,1,1
151 +RF0524,24,5,980.0,220.0,224.7,faible,1,1
152 152 RF0600,0,6,20.0,260.0,258.0,faible,1,0
153 153 RF0601,1,6,60.0,260.0,259.6,faible,1,0
154 154 RF0602,2,6,100.0,260.0,258.6,faible,1,0
@@ -171,9 +171,9 @@ RF0618,18,6,740.0,260.0,260.2,faible,1,0
171 171 RF0619,19,6,780.0,260.0,258.9,faible,1,0
172 172 RF0620,20,6,820.0,260.0,253.3,faible,1,0
173 173 RF0621,21,6,860.0,260.0,264.1,faible,1,0
174 −RF0622,22,6,900.0,260.0,256.0,faible,1,0
175 −RF0623,23,6,940.0,260.0,257.8,faible,1,0
176 −RF0624,24,6,980.0,260.0,255.1,faible,1,0
174 +RF0622,22,6,900.0,260.0,256.0,faible,1,1
175 +RF0623,23,6,940.0,260.0,257.8,faible,1,1
176 +RF0624,24,6,980.0,260.0,255.1,faible,1,1
177 177 RF0700,0,7,20.0,300.0,298.2,hors zone,0,0
178 178 RF0701,1,7,60.0,300.0,293.4,hors zone,0,0
179 179 RF0702,2,7,100.0,300.0,301.8,hors zone,0,0
@@ -196,9 +196,9 @@ RF0718,18,7,740.0,300.0,295.5,hors zone,0,0
196 196 RF0719,19,7,780.0,300.0,296.0,hors zone,0,0
197 197 RF0720,20,7,820.0,300.0,294.5,hors zone,0,0
198 198 RF0721,21,7,860.0,300.0,300.9,hors zone,0,0
199 −RF0722,22,7,900.0,300.0,306.0,hors zone,0,0
200 −RF0723,23,7,940.0,300.0,296.6,hors zone,0,0
201 −RF0724,24,7,980.0,300.0,293.8,hors zone,0,0
199 +RF0722,22,7,900.0,300.0,306.0,hors zone,0,1
200 +RF0723,23,7,940.0,300.0,296.6,hors zone,0,1
201 +RF0724,24,7,980.0,300.0,293.8,hors zone,0,1
202 202 RF0800,0,8,20.0,340.0,342.9,hors zone,0,0
203 203 RF0801,1,8,60.0,340.0,339.4,hors zone,0,0
204 204 RF0802,2,8,100.0,340.0,334.0,hors zone,0,0
@@ -221,9 +221,9 @@ RF0818,18,8,740.0,340.0,334.2,hors zone,0,0
221 221 RF0819,19,8,780.0,340.0,345.3,hors zone,0,0
222 222 RF0820,20,8,820.0,340.0,343.1,hors zone,0,0
223 223 RF0821,21,8,860.0,340.0,343.8,hors zone,0,0
224 −RF0822,22,8,900.0,340.0,341.2,hors zone,0,0
225 −RF0823,23,8,940.0,340.0,334.9,hors zone,0,0
226 −RF0824,24,8,980.0,340.0,344.6,hors zone,0,0
224 +RF0822,22,8,900.0,340.0,341.2,hors zone,0,1
225 +RF0823,23,8,940.0,340.0,334.9,hors zone,0,1
226 +RF0824,24,8,980.0,340.0,344.6,hors zone,0,1
227 227 RF0900,0,9,20.0,380.0,373.6,hors zone,0,0
228 228 RF0901,1,9,60.0,380.0,374.7,hors zone,0,0
229 229 RF0902,2,9,100.0,380.0,375.0,hors zone,0,0
@@ -246,9 +246,9 @@ RF0918,18,9,740.0,380.0,376.8,hors zone,0,0
246 246 RF0919,19,9,780.0,380.0,372.6,hors zone,0,0
247 247 RF0920,20,9,820.0,380.0,386.8,hors zone,0,0
248 248 RF0921,21,9,860.0,380.0,374.5,hors zone,0,0
249 −RF0922,22,9,900.0,380.0,375.8,hors zone,0,0
250 −RF0923,23,9,940.0,380.0,377.4,hors zone,0,0
251 −RF0924,24,9,980.0,380.0,382.2,hors zone,0,0
249 +RF0922,22,9,900.0,380.0,375.8,hors zone,0,1
250 +RF0923,23,9,940.0,380.0,377.4,hors zone,0,1
251 +RF0924,24,9,980.0,380.0,382.2,hors zone,0,1
252 252 RF1000,0,10,20.0,420.0,417.4,hors zone,0,0
253 253 RF1001,1,10,60.0,420.0,418.6,hors zone,0,0
254 254 RF1002,2,10,100.0,420.0,417.1,hors zone,0,0
@@ -271,9 +271,9 @@ RF1018,18,10,740.0,420.0,427.8,hors zone,0,0
271 271 RF1019,19,10,780.0,420.0,427.8,hors zone,0,0
272 272 RF1020,20,10,820.0,420.0,422.0,hors zone,0,0
273 273 RF1021,21,10,860.0,420.0,420.8,hors zone,0,0
274 −RF1022,22,10,900.0,420.0,415.7,hors zone,0,0
275 −RF1023,23,10,940.0,420.0,427.0,hors zone,0,0
276 −RF1024,24,10,980.0,420.0,425.0,hors zone,0,0
274 +RF1022,22,10,900.0,420.0,415.7,hors zone,0,1
275 +RF1023,23,10,940.0,420.0,427.0,hors zone,0,1
276 +RF1024,24,10,980.0,420.0,425.0,hors zone,0,1
277 277 RF1100,0,11,20.0,460.0,460.0,hors zone,0,0
278 278 RF1101,1,11,60.0,460.0,459.4,hors zone,0,0
279 279 RF1102,2,11,100.0,460.0,453.8,hors zone,0,0
@@ -296,9 +296,9 @@ RF1118,18,11,740.0,460.0,458.8,hors zone,0,0
296 296 RF1119,19,11,780.0,460.0,453.3,hors zone,0,0
297 297 RF1120,20,11,820.0,460.0,466.2,hors zone,0,0
298 298 RF1121,21,11,860.0,460.0,452.7,hors zone,0,0
299 −RF1122,22,11,900.0,460.0,452.6,hors zone,0,0
300 −RF1123,23,11,940.0,460.0,467.5,hors zone,0,0
301 −RF1124,24,11,980.0,460.0,452.7,hors zone,0,0
299 +RF1122,22,11,900.0,460.0,452.6,hors zone,0,1
300 +RF1123,23,11,940.0,460.0,467.5,hors zone,0,1
301 +RF1124,24,11,980.0,460.0,452.7,hors zone,0,1
302 302 RF1200,0,12,20.0,500.0,500.4,hors zone,0,0
303 303 RF1201,1,12,60.0,500.0,499.1,hors zone,0,0
304 304 RF1202,2,12,100.0,500.0,496.0,hors zone,0,0
@@ -321,9 +321,9 @@ RF1218,18,12,740.0,500.0,498.7,hors zone,0,0
321 321 RF1219,19,12,780.0,500.0,503.5,hors zone,0,0
322 322 RF1220,20,12,820.0,500.0,493.3,hors zone,0,0
323 323 RF1221,21,12,860.0,500.0,504.1,hors zone,0,0
324 −RF1222,22,12,900.0,500.0,505.5,hors zone,0,0
325 −RF1223,23,12,940.0,500.0,497.6,hors zone,0,0
326 −RF1224,24,12,980.0,500.0,495.2,hors zone,0,0
324 +RF1222,22,12,900.0,500.0,505.5,hors zone,0,1
325 +RF1223,23,12,940.0,500.0,497.6,hors zone,0,1
326 +RF1224,24,12,980.0,500.0,495.2,hors zone,0,1
327 327 RF1300,0,13,20.0,540.0,541.1,hors zone,0,0
328 328 RF1301,1,13,60.0,540.0,532.2,hors zone,0,0
329 329 RF1302,2,13,100.0,540.0,543.8,hors zone,0,0
@@ -346,9 +346,9 @@ RF1318,18,13,740.0,540.0,547.9,hors zone,0,0
346 346 RF1319,19,13,780.0,540.0,545.3,hors zone,0,0
347 347 RF1320,20,13,820.0,540.0,541.6,hors zone,0,0
348 348 RF1321,21,13,860.0,540.0,532.0,hors zone,0,0
349 −RF1322,22,13,900.0,540.0,547.8,hors zone,0,0
350 −RF1323,23,13,940.0,540.0,534.9,hors zone,0,0
351 −RF1324,24,13,980.0,540.0,532.6,hors zone,0,0
349 +RF1322,22,13,900.0,540.0,547.8,hors zone,0,1
350 +RF1323,23,13,940.0,540.0,534.9,hors zone,0,1
351 +RF1324,24,13,980.0,540.0,532.6,hors zone,0,1
352 352 RF1400,0,14,20.0,580.0,576.4,hors zone,0,0
353 353 RF1401,1,14,60.0,580.0,579.1,hors zone,0,0
354 354 RF1402,2,14,100.0,580.0,581.0,hors zone,0,0
@@ -371,9 +371,9 @@ RF1418,18,14,740.0,580.0,575.2,hors zone,0,0
371 371 RF1419,19,14,780.0,580.0,576.0,hors zone,0,0
372 372 RF1420,20,14,820.0,580.0,580.3,hors zone,0,0
373 373 RF1421,21,14,860.0,580.0,581.1,hors zone,0,0
374 −RF1422,22,14,900.0,580.0,573.0,hors zone,0,0
375 −RF1423,23,14,940.0,580.0,585.9,hors zone,0,0
376 −RF1424,24,14,980.0,580.0,577.1,hors zone,0,0
374 +RF1422,22,14,900.0,580.0,573.0,hors zone,0,1
375 +RF1423,23,14,940.0,580.0,585.9,hors zone,0,1
376 +RF1424,24,14,980.0,580.0,577.1,hors zone,0,1
377 377 RF1500,0,15,20.0,620.0,622.3,hors zone,0,0
378 378 RF1501,1,15,60.0,620.0,621.9,hors zone,0,0
379 379 RF1502,2,15,100.0,620.0,616.8,hors zone,0,0
@@ -396,9 +396,9 @@ RF1518,18,15,740.0,620.0,620.4,hors zone,0,0
396 396 RF1519,19,15,780.0,620.0,613.3,hors zone,0,0
397 397 RF1520,20,15,820.0,620.0,618.8,hors zone,0,0
398 398 RF1521,21,15,860.0,620.0,617.9,hors zone,0,0
399 −RF1522,22,15,900.0,620.0,620.8,hors zone,0,0
400 −RF1523,23,15,940.0,620.0,626.0,hors zone,0,0
401 −RF1524,24,15,980.0,620.0,623.6,hors zone,0,0
399 +RF1522,22,15,900.0,620.0,620.8,hors zone,0,1
400 +RF1523,23,15,940.0,620.0,626.0,hors zone,0,1
401 +RF1524,24,15,980.0,620.0,623.6,hors zone,0,1
402 402 RF1600,0,16,20.0,660.0,652.0,hors zone,0,0
403 403 RF1601,1,16,60.0,660.0,658.2,hors zone,0,0
404 404 RF1602,2,16,100.0,660.0,661.5,hors zone,0,0
@@ -421,9 +421,9 @@ RF1618,18,16,740.0,660.0,653.5,hors zone,0,0
421 421 RF1619,19,16,780.0,660.0,664.0,hors zone,0,0
422 422 RF1620,20,16,820.0,660.0,665.3,hors zone,0,0
423 423 RF1621,21,16,860.0,660.0,658.6,hors zone,0,0
424 −RF1622,22,16,900.0,660.0,664.8,hors zone,0,0
425 −RF1623,23,16,940.0,660.0,652.2,hors zone,0,0
426 −RF1624,24,16,980.0,660.0,660.3,hors zone,0,0
424 +RF1622,22,16,900.0,660.0,664.8,hors zone,0,1
425 +RF1623,23,16,940.0,660.0,652.2,hors zone,0,1
426 +RF1624,24,16,980.0,660.0,660.3,hors zone,0,1
427 427 RF1700,0,17,20.0,700.0,702.5,hors zone,0,0
428 428 RF1701,1,17,60.0,700.0,701.9,hors zone,0,0
429 429 RF1702,2,17,100.0,700.0,696.8,hors zone,0,0
@@ -446,9 +446,9 @@ RF1718,18,17,740.0,700.0,695.5,hors zone,0,0
446 446 RF1719,19,17,780.0,700.0,706.9,hors zone,0,0
447 447 RF1720,20,17,820.0,700.0,694.0,hors zone,0,0
448 448 RF1721,21,17,860.0,700.0,703.2,hors zone,0,0
449 −RF1722,22,17,900.0,700.0,698.3,hors zone,0,0
450 −RF1723,23,17,940.0,700.0,694.2,hors zone,0,0
451 −RF1724,24,17,980.0,700.0,701.5,hors zone,0,0
449 +RF1722,22,17,900.0,700.0,698.3,hors zone,0,1
450 +RF1723,23,17,940.0,700.0,694.2,hors zone,0,1
451 +RF1724,24,17,980.0,700.0,701.5,hors zone,0,1
452 452 RF1800,0,18,20.0,740.0,742.1,hors zone,0,0
453 453 RF1801,1,18,60.0,740.0,742.4,hors zone,0,0
454 454 RF1802,2,18,100.0,740.0,747.3,hors zone,0,0
@@ -471,9 +471,9 @@ RF1818,18,18,740.0,740.0,741.2,hors zone,0,0
471 471 RF1819,19,18,780.0,740.0,738.9,hors zone,0,0
472 472 RF1820,20,18,820.0,740.0,744.0,hors zone,0,0
473 473 RF1821,21,18,860.0,740.0,743.6,hors zone,0,0
474 −RF1822,22,18,900.0,740.0,739.9,hors zone,0,0
475 −RF1823,23,18,940.0,740.0,733.5,hors zone,0,0
476 −RF1824,24,18,980.0,740.0,740.5,hors zone,0,0
474 +RF1822,22,18,900.0,740.0,739.9,hors zone,0,1
475 +RF1823,23,18,940.0,740.0,733.5,hors zone,0,1
476 +RF1824,24,18,980.0,740.0,740.5,hors zone,0,1
477 477 RF1900,0,19,20.0,780.0,787.6,hors zone,0,0
478 478 RF1901,1,19,60.0,780.0,774.4,hors zone,0,0
479 479 RF1902,2,19,100.0,780.0,780.1,hors zone,0,0
@@ -496,9 +496,9 @@ RF1918,18,19,740.0,780.0,784.0,hors zone,0,0
496 496 RF1919,19,19,780.0,780.0,774.8,hors zone,0,0
497 497 RF1920,20,19,820.0,780.0,782.2,hors zone,0,0
498 498 RF1921,21,19,860.0,780.0,777.5,hors zone,0,0
499 −RF1922,22,19,900.0,780.0,775.8,hors zone,0,0
500 −RF1923,23,19,940.0,780.0,786.1,hors zone,0,0
501 −RF1924,24,19,980.0,780.0,774.5,hors zone,0,0
499 +RF1922,22,19,900.0,780.0,775.8,hors zone,0,1
500 +RF1923,23,19,940.0,780.0,786.1,hors zone,0,1
501 +RF1924,24,19,980.0,780.0,774.5,hors zone,0,1
502 502 RF2000,0,20,20.0,820.0,813.8,hors zone,0,0
503 503 RF2001,1,20,60.0,820.0,817.8,hors zone,0,0
504 504 RF2002,2,20,100.0,820.0,817.0,hors zone,0,0
@@ -521,9 +521,9 @@ RF2018,18,20,740.0,820.0,823.2,hors zone,0,0
521 521 RF2019,19,20,780.0,820.0,815.6,hors zone,0,0
522 522 RF2020,20,20,820.0,820.0,812.5,hors zone,0,0
523 523 RF2021,21,20,860.0,820.0,823.7,hors zone,0,0
524 −RF2022,22,20,900.0,820.0,822.8,hors zone,0,0
525 −RF2023,23,20,940.0,820.0,818.5,hors zone,0,0
526 −RF2024,24,20,980.0,820.0,817.8,hors zone,0,0
524 +RF2022,22,20,900.0,820.0,822.8,hors zone,0,1
525 +RF2023,23,20,940.0,820.0,818.5,hors zone,0,1
526 +RF2024,24,20,980.0,820.0,817.8,hors zone,0,1
527 527 RF2100,0,21,20.0,860.0,857.4,hors zone,0,0
528 528 RF2101,1,21,60.0,860.0,858.3,hors zone,0,0
529 529 RF2102,2,21,100.0,860.0,862.1,hors zone,0,0
@@ -546,9 +546,9 @@ RF2118,18,21,740.0,860.0,863.6,hors zone,0,0
546 546 RF2119,19,21,780.0,860.0,865.3,hors zone,0,0
547 547 RF2120,20,21,820.0,860.0,862.4,hors zone,0,0
548 548 RF2121,21,21,860.0,860.0,853.7,hors zone,0,0
549 −RF2122,22,21,900.0,860.0,857.5,hors zone,0,0
550 −RF2123,23,21,940.0,860.0,861.6,hors zone,0,0
551 −RF2124,24,21,980.0,860.0,858.1,hors zone,0,0
549 +RF2122,22,21,900.0,860.0,857.5,hors zone,0,1
550 +RF2123,23,21,940.0,860.0,861.6,hors zone,0,1
551 +RF2124,24,21,980.0,860.0,858.1,hors zone,0,1
552 552 RF2200,0,22,20.0,900.0,901.0,hors zone,0,0
553 553 RF2201,1,22,60.0,900.0,893.0,hors zone,0,0
554 554 RF2202,2,22,100.0,900.0,901.1,hors zone,0,0
@@ -571,9 +571,9 @@ RF2218,18,22,740.0,900.0,896.7,hors zone,0,0
571 571 RF2219,19,22,780.0,900.0,897.3,hors zone,0,0
572 572 RF2220,20,22,820.0,900.0,895.1,hors zone,0,0
573 573 RF2221,21,22,860.0,900.0,901.7,hors zone,0,0
574 −RF2222,22,22,900.0,900.0,903.8,hors zone,0,0
575 −RF2223,23,22,940.0,900.0,896.7,hors zone,0,0
576 −RF2224,24,22,980.0,900.0,895.6,hors zone,0,0
574 +RF2222,22,22,900.0,900.0,903.8,hors zone,0,1
575 +RF2223,23,22,940.0,900.0,896.7,hors zone,0,1
576 +RF2224,24,22,980.0,900.0,895.6,hors zone,0,1
577 577 RF2300,0,23,20.0,940.0,936.6,hors zone,0,0
578 578 RF2301,1,23,60.0,940.0,943.7,hors zone,0,0
579 579 RF2302,2,23,100.0,940.0,943.5,hors zone,0,0
@@ -596,9 +596,9 @@ RF2318,18,23,740.0,940.0,940.5,hors zone,0,0
596 596 RF2319,19,23,780.0,940.0,941.8,hors zone,0,0
597 597 RF2320,20,23,820.0,940.0,936.1,hors zone,0,0
598 598 RF2321,21,23,860.0,940.0,937.3,hors zone,0,0
599 −RF2322,22,23,900.0,940.0,939.5,hors zone,0,0
600 −RF2323,23,23,940.0,940.0,944.2,hors zone,0,0
601 −RF2324,24,23,980.0,940.0,946.6,hors zone,0,0
599 +RF2322,22,23,900.0,940.0,939.5,hors zone,0,1
600 +RF2323,23,23,940.0,940.0,944.2,hors zone,0,1
601 +RF2324,24,23,980.0,940.0,946.6,hors zone,0,1
602 602 RF2400,0,24,20.0,980.0,977.3,hors zone,0,0
603 603 RF2401,1,24,60.0,980.0,986.6,hors zone,0,0
604 604 RF2402,2,24,100.0,980.0,980.0,hors zone,0,0
@@ -621,6 +621,6 @@ RF2418,18,24,740.0,980.0,973.0,hors zone,0,0
621 621 RF2419,19,24,780.0,980.0,979.1,hors zone,0,0
622 622 RF2420,20,24,820.0,980.0,977.0,hors zone,0,0
623 623 RF2421,21,24,860.0,980.0,983.2,hors zone,0,0
624 −RF2422,22,24,900.0,980.0,981.1,hors zone,0,0
625 −RF2423,23,24,940.0,980.0,972.4,hors zone,0,0
626 −RF2424,24,24,980.0,980.0,976.8,hors zone,0,0
624 +RF2422,22,24,900.0,980.0,981.1,hors zone,0,1
625 +RF2423,23,24,940.0,980.0,972.4,hors zone,0,1
626 +RF2424,24,24,980.0,980.0,976.8,hors zone,0,1
modified data/synthetic/ch43_riverain_ventes.csv +1013 −763
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deleted manuscript/_wrap_ch39.tex +0 −12
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