{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "a62059a5",
   "metadata": {},
   "source": [
    "# 17 — Deux journaux qui enregistrent le rang servi\n",
    "\n",
    "Le [notebook 16](16_exploration_mind.ipynb) s'est terminé sur une exigence plutôt que sur un\n",
    "résultat : il faut un jeu de données qui **enregistre le rang d'affichage**, faute de quoi\n",
    "l'exposition n'est pas identifiable et l'évaluation contrefactuelle d'un réordonnancement est\n",
    "vide par construction.\n",
    "\n",
    "Ce notebook va chercher ces journaux et leur applique les mêmes contrôles. Deux répondent, et\n",
    "pas à la même exigence.\n",
    "\n",
    "**[Baidu-ULTR](https://arxiv.org/abs/2207.03051)** (Zou et al., 2022) enregistre le rang\n",
    "d'affichage de chaque document dans une page de résultats, avec le clic et la session — la\n",
    "structure exacte que MIND avait détruite.\n",
    "\n",
    "**L'[Open Bandit Dataset](https://arxiv.org/abs/2008.07146)** (Saito et al., 2020) publie en\n",
    "plus la **propension vraie** de chaque affichage, et contient un seau où la politique de\n",
    "service est **uniformément aléatoire**. C'est le seul jeu où la condition la plus coûteuse des\n",
    "estimateurs contrefactuels — connaître $\\pi_0$ au lieu de la modéliser — est satisfaite\n",
    "littéralement.\n",
    "\n",
    "**Ce que ce notebook établit :**\n",
    "\n",
    "* Baidu-ULTR **passe le contrôle positif** que MIND avait échoué : $z = -206$, du bon côté —\n",
    "  les clics se concentrent en haut, comme un biais de position l'exige ;\n",
    "* la sévérité y vaut $\\hat\\eta = 1{,}10 \\pm 0{,}09$ par effets fixes de contenu, contre 1,49\n",
    "  par ajustement agrégé : l'écart est le **confondant de qualité**, la plateforme plaçant les\n",
    "  meilleurs documents en tête ;\n",
    "* sur l'Open Bandit Dataset, l'effet de position est **dix fois plus faible** — un bandeau de\n",
    "  trois vignettes horizontales n'est pas une page de résultats verticale, et $\\eta$ est une\n",
    "  propriété de la **surface**, pas une constante ;\n",
    "* l'estimation IPS de la valeur d'une politique **non déployée** tombe à 2,5 % de la valeur\n",
    "  mesurée directement, là où l'estimation naïve se trompe de 32 % — mais la **taille\n",
    "  d'échantillon effective** vaut 1 513 pour 4 millions d'impressions, et c'est le chiffre qui\n",
    "  interdit de crier victoire.\n",
    "\n",
    "Les journaux bruts pèsent 3,1 Go et portent deux licences distinctes : ils ne sont pas\n",
    "versionnés. Ce notebook lit le **condensé** `data/exposure_digest.npz`, qui rend à l'identique\n",
    "tous les chiffres ci-dessous — un test le vérifie — et se reconstruit par\n",
    "`scripts/fetch_exposure.py` puis `scripts/build_exposure_digest.py`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "c568dae1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-23T13:41:03.542663Z",
     "iopub.status.busy": "2026-08-23T13:41:03.542451Z",
     "iopub.status.idle": "2026-08-23T13:41:04.119192Z",
     "shell.execute_reply": "2026-08-23T13:41:04.118718Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Baidu-ULTR : 64200 sessions, 524164 documents servis, taux de clic 0.0843\n",
      "  longueur de session : médiane 8, min 5, max 19\n",
      "  rang servi : de 1 à 20\n",
      "  source (SHA-256) : 3ffee6ef4c644e30168eed8c6533a4346c604a63b5bd89c4ef85fe075726066b\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from ide.exposure import bucket_from_digest, load_digest, obd_click_rates, off_policy_check\n",
    "from ide.logs import click_rate_by_rank, exchangeability_test, naive_severity_fit\n",
    "from ide.mind import load_digest as load_mind_digest\n",
    "from ide.offpolicy import estimate_position_bias\n",
    "from ide.plotting import PALETTE, save_figure, use_project_style\n",
    "\n",
    "use_project_style()\n",
    "\n",
    "digest = load_digest()\n",
    "baidu = digest.impressions(\"baidu\")\n",
    "lengths = baidu.feed_lengths\n",
    "\n",
    "print(f\"Baidu-ULTR : {baidu.feed_count} sessions, {baidu.served} documents servis, \"\n",
    "      f\"taux de clic {baidu.click_rate:.4f}\")\n",
    "print(f\"  longueur de session : médiane {np.median(lengths):.0f}, min {lengths.min()}, \"\n",
    "      f\"max {lengths.max()}\")\n",
    "print(f\"  rang servi : de {baidu.ranks.min()} à {baidu.ranks.max()}\")\n",
    "print(f\"  source (SHA-256) : {digest.sources['baidu']}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6ae5a293",
   "metadata": {},
   "source": [
    "## 1. Le contrôle positif que MIND avait échoué\n",
    "\n",
    "Le test d'échangeabilité intra-fil demande, à session donnée, si les clics sont répartis\n",
    "indépendamment de la position enregistrée. Sur MIND il ne détectait rien. Il faut vérifier\n",
    "qu'il détecte quelque chose là où il y a quelque chose — sinon son verdict sur MIND ne\n",
    "distinguerait pas un jeu mélangé d'un test aveugle."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c93340ce",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-23T13:41:04.120102Z",
     "iopub.status.busy": "2026-08-23T13:41:04.119967Z",
     "iopub.status.idle": "2026-08-23T13:41:04.359078Z",
     "shell.execute_reply": "2026-08-23T13:41:04.358553Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "journal           fils utiles            z          p   verdict\n",
      "------------------------------------------------------------------------\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MIND                   156965         0.12      0.908   ordre indiscernable d'un mélange\n",
      "Baidu-ULTR              29916      -205.72          0   l'ordre porte le placement\n",
      "\n",
      "Le signe compte autant que l'ampleur : un biais de position concentre les clics en\n",
      "haut, donc la somme des rangs cliqués tombe SOUS son espérance. Un rejet du côté\n",
      "positif signalerait une erreur, pas une découverte.\n"
     ]
    }
   ],
   "source": [
    "mind = load_mind_digest().impressions(\"train\")\n",
    "\n",
    "print(f\"{'journal':16s} {'fils utiles':>12s} {'z':>12s} {'p':>10s}   verdict\")\n",
    "print(\"-\" * 72)\n",
    "verdicts = {}\n",
    "for name, impressions in ((\"MIND\", mind), (\"Baidu-ULTR\", baidu)):\n",
    "    verdict = exchangeability_test(impressions)\n",
    "    verdicts[name] = verdict\n",
    "    reading = (\"ordre indiscernable d'un mélange\" if verdict.exchangeable\n",
    "               else \"l'ordre porte le placement\")\n",
    "    print(f\"{name:16s} {verdict.feeds_used:12d} {verdict.deviation:12.2f} \"\n",
    "          f\"{verdict.p_value:10.3g}   {reading}\")\n",
    "\n",
    "print(\"\\nLe signe compte autant que l'ampleur : un biais de position concentre les clics en\")\n",
    "print(\"haut, donc la somme des rangs cliqués tombe SOUS son espérance. Un rejet du côté\")\n",
    "print(\"positif signalerait une erreur, pas une découverte.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "19646ffb",
   "metadata": {},
   "source": [
    "## 2. La sévérité, mesurée trois fois\n",
    "\n",
    "Trois estimations du même jeu, cette fois sans contradiction — mais pas identiques, et l'écart\n",
    "se lit."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e05ea4d0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-23T13:41:04.359921Z",
     "iopub.status.busy": "2026-08-23T13:41:04.359846Z",
     "iopub.status.idle": "2026-08-23T13:41:04.392713Z",
     "shell.execute_reply": "2026-08-23T13:41:04.392361Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " rang  taux de clic\n",
      "--------------------\n",
      "    1       0.34004\n",
      "    2       0.17235\n",
      "    3       0.08814\n",
      "    5       0.04275\n",
      "    8       0.01931\n",
      "   10       0.00969\n",
      "   12       0.00405\n",
      "\n",
      "ajustement agrégé (rangs 1-10)          : η = 1.494\n",
      "à longueur de session fixée (10 documents) : η = 1.144\n",
      "effets fixes de document                   : η = 1.099 ± 0.089\n",
      "   documents portant l'estimation : 55\n"
     ]
    }
   ],
   "source": [
    "items, ranks, clicks = digest.rows(\"baidu\")\n",
    "fixed_effects = estimate_position_bias(items, ranks, clicks, minimum_impressions=5)\n",
    "aggregate = naive_severity_fit(baidu, maximum_rank=10)\n",
    "at_ten = naive_severity_fit(baidu, maximum_rank=10, feed_length=10)\n",
    "\n",
    "baidu_rates = click_rate_by_rank(baidu, maximum_rank=12)\n",
    "print(f\"{'rang':>5s} {'taux de clic':>13s}\")\n",
    "print(\"-\" * 20)\n",
    "for position in (1, 2, 3, 5, 8, 10, 12):\n",
    "    print(f\"{position:5d} {baidu_rates[position - 1]:13.5f}\")\n",
    "\n",
    "print(f\"\\najustement agrégé (rangs 1-10)          : η = {aggregate:.3f}\")\n",
    "print(f\"à longueur de session fixée (10 documents) : η = {at_ten:.3f}\")\n",
    "print(f\"effets fixes de document                   : η = {fixed_effects.severity:.3f} \"\n",
    "      f\"± {fixed_effects.standard_error:.3f}\")\n",
    "print(f\"   documents portant l'estimation : {fixed_effects.items_with_variation}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2c722b8e",
   "metadata": {},
   "source": [
    "### Pourquoi l'ajustement agrégé surestime\n",
    "\n",
    "Sur MIND, l'écart entre l'ajustement agrégé et les effets fixes venait de la **composition des\n",
    "longueurs**. Ici il vient d'autre chose, et de plus attendu : la plateforme place les\n",
    "**meilleurs documents en tête**. Une partie de la décroissance du taux de clic est donc de la\n",
    "qualité, pas de l'exposition — et c'est exactement ce que les effets fixes de document\n",
    "éliminent, en ne comparant un document qu'à lui-même.\n",
    "\n",
    "Le contrôle par longueur de session ne suffit pas ici : il retire le mélange des longueurs, pas\n",
    "la qualité.\n",
    "\n",
    "!!! warning \"Et la couverture est mince\"\n",
    "    Les effets fixes ne reposent que sur les documents vus à **plusieurs rangs distincts**. Sur\n",
    "    une page de résultats de recherche, une même URL réapparaît rarement : la couverture est\n",
    "    bien plus faible que le nombre de lignes ne le laisse croire."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "dbd66873",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-23T13:41:04.393478Z",
     "iopub.status.busy": "2026-08-23T13:41:04.393408Z",
     "iopub.status.idle": "2026-08-23T13:41:04.396602Z",
     "shell.execute_reply": "2026-08-23T13:41:04.396256Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "documents distincts                        : 444709\n",
      "documents au-dessus du seuil d'impressions : 335\n",
      "documents vus à plusieurs rangs            : 55\n",
      "rangs distincts par document (médiane)     : 1\n",
      "\n",
      "Cinquante-cinq documents portent l'estimation, sur près d'un demi-million. Le\n",
      "chiffre est identifié — l'erreur type le dit — mais la marge est celle-là, pas celle\n",
      "qu'un demi-million de lignes suggérerait.\n"
     ]
    }
   ],
   "source": [
    "coverage = digest.coverage(\"baidu\")\n",
    "print(f\"documents distincts                        : {coverage.items}\")\n",
    "print(f\"documents au-dessus du seuil d'impressions : {coverage.items_above_threshold}\")\n",
    "print(f\"documents vus à plusieurs rangs            : {coverage.items_with_variation}\")\n",
    "print(f\"rangs distincts par document (médiane)     : {coverage.median_distinct_ranks:.0f}\")\n",
    "print(\"\\nCinquante-cinq documents portent l'estimation, sur près d'un demi-million. Le\")\n",
    "print(\"chiffre est identifié — l'erreur type le dit — mais la marge est celle-là, pas celle\")\n",
    "print(\"qu'un demi-million de lignes suggérerait.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fe5b565c",
   "metadata": {},
   "source": [
    "## 3. L'Open Bandit Dataset : la position mesurée sans modèle\n",
    "\n",
    "Le seau **aléatoire** de l'Open Bandit Dataset affecte les contenus aux positions au hasard.\n",
    "L'écart de taux de clic entre positions y est donc un effet **causal** de la position, sans\n",
    "qu'aucun modèle d'examen n'ait à être posé. C'est la mesure la plus propre qu'on puisse faire\n",
    "de $\\eta$ — et elle porte sur une surface toute différente : trois vignettes **horizontales**,\n",
    "de gauche à droite."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "1377896e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-23T13:41:04.397307Z",
     "iopub.status.busy": "2026-08-23T13:41:04.397244Z",
     "iopub.status.idle": "2026-08-23T13:41:04.423559Z",
     "shell.execute_reply": "2026-08-23T13:41:04.423118Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "seau              position  impressions    clics      taux        ±\n",
      "--------------------------------------------------------------------\n",
      "obd_random_all           1       458005     1622   0.00354  0.00009\n",
      "                         2       458158     1590   0.00347  0.00009\n",
      "                         3       458164     1556   0.00340  0.00009\n",
      "obd_random_men           1       150936      812   0.00538  0.00019\n",
      "                         2       151008      792   0.00524  0.00019\n",
      "                         3       151005      717   0.00475  0.00018\n",
      "\n",
      "obd_random_all : η ajusté sur trois positions = 0.037\n",
      "\n",
      "obd_random_men : η ajusté sur trois positions = 0.105\n",
      "\n",
      "Campagne « all » : écart première/dernière vignette = 0.00015, pour des erreurs types de 0.00009.\n",
      "L'effet existe et va dans le bon sens ; à cette taille il n'est pas concluant\n",
      "vignette à vignette.\n"
     ]
    }
   ],
   "source": [
    "print(f\"{'seau':16s} {'position':>9s} {'impressions':>12s} {'clics':>8s} {'taux':>9s} {'±':>8s}\")\n",
    "print(\"-\" * 68)\n",
    "obd_rates = {}\n",
    "for name in (\"obd_random_all\", \"obd_random_men\"):\n",
    "    bucket = bucket_from_digest(digest, name)\n",
    "    obd_rates[name] = obd_click_rates(bucket)\n",
    "    for position, (exposures, successes, rate, error) in sorted(obd_rates[name].items()):\n",
    "        label = name if position == 1 else \"\"\n",
    "        print(f\"{label:16s} {position:9d} {exposures:12d} {successes:8d} {rate:9.5f} \"\n",
    "              f\"{error:8.5f}\")\n",
    "\n",
    "for name, bucket_rates in obd_rates.items():\n",
    "    positions = np.array(sorted(bucket_rates))\n",
    "    values = np.array([bucket_rates[p][2] for p in positions])\n",
    "    slope = np.polyfit(np.log(positions), np.log(values), 1)[0]\n",
    "    print(f\"\\n{name} : η ajusté sur trois positions = {-slope:.3f}\")\n",
    "\n",
    "first, last = obd_rates[\"obd_random_all\"][1], obd_rates[\"obd_random_all\"][3]\n",
    "gap = first[2] - last[2]\n",
    "print(f\"\\nCampagne « all » : écart première/dernière vignette = {gap:.5f}, \"\n",
    "      f\"pour des erreurs types de {first[3]:.5f}.\")\n",
    "print(\"L'effet existe et va dans le bon sens ; à cette taille il n'est pas concluant\")\n",
    "print(\"vignette à vignette.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3ef9f15f",
   "metadata": {},
   "source": [
    "!!! danger \"$\\eta$ n'est pas une constante, c'est une propriété de la surface\"\n",
    "    Une page de résultats verticale décroît en $R^{-1{,}1}$ ; un bandeau de trois vignettes\n",
    "    horizontales décroît en $R^{-0{,}04}$ à $R^{-0{,}11}$ selon la campagne. Un ordre de\n",
    "    grandeur sépare les deux.\n",
    "\n",
    "    Le [notebook 15](15_rang_adverse_et_severite.ipynb) avait chiffré ce que coûte un $\\eta$\n",
    "    posé de travers : jusqu'à +179 % sur le chiffre publié. Transporter la valeur d'une page de\n",
    "    résultats vers un bandeau — ou l'inverse — est précisément une erreur de cette taille.\n",
    "\n",
    "## 4. La confrontation : une estimation contrefactuelle jugée contre la vérité\n",
    "\n",
    "L'Open Bandit Dataset contient deux seaux servis **en parallèle** par deux politiques\n",
    "différentes. On peut donc faire ce qu'aucun autre jeu de ce dépôt ne permet : estimer la valeur\n",
    "de la politique uniforme **à partir des seules données d'une autre politique**, puis la\n",
    "comparer à sa valeur mesurée directement là où elle a réellement servi."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "810a8c79",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-23T13:41:04.424298Z",
     "iopub.status.busy": "2026-08-23T13:41:04.424231Z",
     "iopub.status.idle": "2026-08-23T13:41:04.588666Z",
     "shell.execute_reply": "2026-08-23T13:41:04.588280Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "vérité terrain (politique uniforme, mesurée) : 0.005124 ± 0.000106\n",
      "journal d'enregistrement (Bernoulli TS)      : 4077727 impressions\n",
      "\n",
      "estimateur                       valeur   écart à la vérité\n",
      "------------------------------------------------------------\n",
      "naïf (taux de clic observé)    0.006743               31.6 %\n",
      "IPS                            0.005253                2.5 %\n",
      "SNIPS                          0.004768               -7.0 %\n",
      "IPS plafonné à 10              0.004473              -12.7 %\n",
      "IPS plafonné à 100             0.005238                2.2 %\n",
      "IPS plafonné à 1000            0.005253                2.5 %\n",
      "\n",
      "taille d'échantillon effective : 1513 sur 4077727 (0.037 %)\n"
     ]
    }
   ],
   "source": [
    "check = off_policy_check(\n",
    "    bucket_from_digest(digest, \"obd_random_men\"),\n",
    "    bucket_from_digest(digest, \"obd_bts_men\"),\n",
    ")\n",
    "\n",
    "print(f\"vérité terrain (politique uniforme, mesurée) : {check.truth:.6f} ± {check.truth_error:.6f}\")\n",
    "print(f\"journal d'enregistrement (Bernoulli TS)      : {check.logged_size} impressions\\n\")\n",
    "print(f\"{'estimateur':28s} {'valeur':>10s} {'écart à la vérité':>19s}\")\n",
    "print(\"-\" * 60)\n",
    "estimates = [(\"naïf (taux de clic observé)\", check.naive),\n",
    "             (\"IPS\", check.importance_sampling),\n",
    "             (\"SNIPS\", check.self_normalised)]\n",
    "estimates += [(f\"IPS plafonné à {cap:.0f}\", value) for cap, value in check.clipped.items()]\n",
    "for label, value in estimates:\n",
    "    print(f\"{label:28s} {value:10.6f} {100 * check.relative_error(value):18.1f} %\")\n",
    "\n",
    "print(f\"\\ntaille d'échantillon effective : {check.effective_size:.0f} sur {check.logged_size} \"\n",
    "      f\"({100 * check.effective_share:.3f} %)\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "74f23085",
   "metadata": {},
   "source": [
    "### Ce que ce tableau dit, et ce qu'il ne dit pas\n",
    "\n",
    "**Il dit que la correction fonctionne.** L'estimation naïve — le taux de clic observé sous la\n",
    "politique d'enregistrement, c'est-à-dire ce que mesure un *replay* — se trompe de **+32 %**.\n",
    "L'IPS, qui repondère chaque observation par l'inverse de sa propension, tombe à **2,5 %** de la\n",
    "valeur vraie. C'est la première fois dans ce dépôt qu'un estimateur contrefactuel est jugé\n",
    "contre la grandeur qu'il prétend estimer, et non contre une simulation.\n",
    "\n",
    "**Il ne dit pas que l'estimation est précise.** La taille d'échantillon effective vaut **1 513**\n",
    "pour 4 077 727 impressions, soit 0,04 %. L'estimation sans biais repose sur l'équivalent de\n",
    "mille cinq cents observations : à un taux de clic de 0,005, cela laisse une marge de l'ordre de\n",
    "la moitié du chiffre. Que l'écart tombe à 2,5 % tient donc autant à la chance qu'à la méthode.\n",
    "\n",
    "C'est exactement le diagnostic que `ide.offpolicy` impose de publier à côté du chiffre, et\n",
    "voici le cas réel qui montre pourquoi : sans lui, on croirait tenir une mesure sur quatre\n",
    "millions de lignes.\n",
    "\n",
    "**Et le plafonnement n'est pas gratuit.** Plafonner les poids à 10 ramène l'estimation à\n",
    "$-12{,}7$ % : le biais échangé contre de la variance est du même ordre que l'erreur qu'on\n",
    "cherchait à corriger. Le plafond doit être publié avec le chiffre, faute de quoi le choix du\n",
    "plafond suffit à déplacer le résultat.\n",
    "\n",
    "## 5. La figure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "0303df98",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-23T13:41:04.589493Z",
     "iopub.status.busy": "2026-08-23T13:41:04.589425Z",
     "iopub.status.idle": "2026-08-23T13:41:05.079714Z",
     "shell.execute_reply": "2026-08-23T13:41:05.079322Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1488x1032 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure, axes = plt.subplots(2, 2, figsize=(12.4, 8.6))\n",
    "\n",
    "# (a) le rang enregistré fait ou ne fait pas la courbe\n",
    "ax = axes[0, 0]\n",
    "positions = np.arange(1, 13)\n",
    "mind_rates = click_rate_by_rank(mind, maximum_rank=12, feed_length=30)\n",
    "ax.plot(positions, baidu_rates[:12], \"o-\", color=PALETTE[\"order\"], markersize=4,\n",
    "        label=f\"Baidu-ULTR — rang servi (η = {fixed_effects.severity:.2f})\")\n",
    "ax.plot(positions, mind_rates, \"o-\", color=PALETTE[\"disorder\"], markersize=4,\n",
    "        label=\"MIND — rang mélangé (η = 0,00)\")\n",
    "ax.set_yscale(\"log\")\n",
    "ax.set_xlabel(\"rang enregistré\")\n",
    "ax.set_ylabel(\"taux de clic (échelle log)\")\n",
    "ax.set_title(\"(a) ce qu'un rang réellement servi fait à la courbe\")\n",
    "ax.set_xticks([1, 3, 6, 9, 12])\n",
    "ax.legend(loc=\"lower left\", fontsize=8)\n",
    "\n",
    "# (b) le test d'échangeabilité sur les deux journaux\n",
    "ax = axes[0, 1]\n",
    "names = [\"MIND\\n(156 965 fils)\", \"Baidu-ULTR\\n(29 916 sessions)\"]\n",
    "deviations = [verdicts[\"MIND\"].deviation, verdicts[\"Baidu-ULTR\"].deviation]\n",
    "colours = [PALETTE[\"disorder\"], PALETTE[\"order\"]]\n",
    "ax.set_xscale(\"symlog\", linthresh=1)\n",
    "for index, (value, colour) in enumerate(zip(deviations, colours, strict=True)):\n",
    "    ax.plot([0, value], [index, index], color=colour, linewidth=2.5, alpha=0.85)\n",
    "    ax.plot([value], [index], \"o\", color=colour, markersize=9)\n",
    "    ax.annotate(f\"z = {value:+.2f}\", xy=(value, index), xytext=(0, 12),\n",
    "                textcoords=\"offset points\", ha=\"center\", fontsize=9, color=colour)\n",
    "ax.axvline(-1.96, color=PALETTE[\"neutral\"], linestyle=\":\", linewidth=1.2)\n",
    "ax.text(-1.96, 1.62, \"rejet à 5 %\", fontsize=8, color=PALETTE[\"neutral\"], ha=\"center\")\n",
    "ax.axvline(0.0, color=PALETTE[\"neutral\"], linewidth=0.8)\n",
    "ax.set_yticks([0, 1])\n",
    "ax.set_yticklabels(names, fontsize=8)\n",
    "ax.set_ylim(1.75, -0.6)\n",
    "ax.set_xlim(-600, 30)\n",
    "ax.set_xlabel(\"écart réduit $z$ (symlog) — négatif = les clics sont en haut\")\n",
    "ax.set_title(\"(b) le contrôle qui distingue un ordre d'un mélange\")\n",
    "\n",
    "# (c) trois vignettes horizontales : l'effet est ténu\n",
    "ax = axes[1, 0]\n",
    "for name, colour, label in ((\"obd_random_all\", PALETTE[\"remedy\"], \"campagne « all » (1,4 M)\"),\n",
    "                            (\"obd_random_men\", PALETTE[\"field\"], \"campagne « men » (0,45 M)\")):\n",
    "    slots = np.array(sorted(obd_rates[name]))\n",
    "    values = np.array([obd_rates[name][s][2] for s in slots])\n",
    "    errors = np.array([obd_rates[name][s][3] for s in slots])\n",
    "    ax.errorbar(slots, 100 * values, yerr=100 * 1.96 * errors, fmt=\"o-\", color=colour,\n",
    "                markersize=5, capsize=4, label=label)\n",
    "ax.set_xticks([1, 2, 3])\n",
    "ax.set_xticklabels([\"gauche\", \"centre\", \"droite\"])\n",
    "ax.set_xlabel(\"position dans le bandeau (allocation aléatoire)\")\n",
    "ax.set_ylabel(\"taux de clic (%)\")\n",
    "ax.set_title(\"(c) Open Bandit Dataset : l'effet de position, mesuré sans modèle\")\n",
    "ax.legend(loc=\"lower left\", fontsize=8)\n",
    "\n",
    "# (d) la confrontation\n",
    "ax = axes[1, 1]\n",
    "labels = [\"naïf\", \"IPS\", \"SNIPS\", \"plafond 10\", \"plafond 100\"]\n",
    "values = [check.naive, check.importance_sampling, check.self_normalised,\n",
    "          check.clipped[10.0], check.clipped[100.0]]\n",
    "bar_colours = [PALETTE[\"disorder\"], PALETTE[\"remedy\"], PALETTE[\"field\"],\n",
    "               PALETTE[\"neutral\"], PALETTE[\"neutral\"]]\n",
    "ax.bar(labels, [1000 * value for value in values], color=bar_colours, alpha=0.85, width=0.6)\n",
    "ax.axhline(1000 * check.truth, color=PALETTE[\"order\"], linewidth=1.6)\n",
    "ax.axhspan(1000 * (check.truth - 1.96 * check.truth_error),\n",
    "           1000 * (check.truth + 1.96 * check.truth_error),\n",
    "           color=PALETTE[\"order\"], alpha=0.15)\n",
    "ax.text(-0.42, 1000 * check.truth + 0.18, \"vérité mesurée\", fontsize=8,\n",
    "        color=PALETTE[\"order\"], ha=\"left\")\n",
    "for index, value in enumerate(values):\n",
    "    ax.text(index, 1000 * value + 0.1, f\"{100 * check.relative_error(value):+.0f} %\",\n",
    "            ha=\"center\", fontsize=8)\n",
    "ax.set_ylabel(\"valeur estimée de la politique uniforme (‰)\")\n",
    "ax.set_title(\"(d) l'estimateur jugé contre la valeur qu'il estime\")\n",
    "ax.tick_params(axis=\"x\", labelsize=8)\n",
    "ax.set_ylim(0, 1000 * max(values) * 1.25)\n",
    "ax.text(0.98, 0.97, f\"taille effective : {check.effective_size:.0f} / {check.logged_size:,}\"\n",
    "        .replace(\",\", \" \"), transform=ax.transAxes, fontsize=8, color=PALETTE[\"disorder\"],\n",
    "        ha=\"right\", va=\"top\")\n",
    "\n",
    "save_figure(figure, \"fig17_rang_servi\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9d24279",
   "metadata": {},
   "source": [
    "## 6. Ce que ces deux journaux règlent, et ce qu'ils ne règlent pas\n",
    "\n",
    "**Réglé : le critère de choix d'un jeu de données.** Il ne s'agit ni de la taille ni de la\n",
    "présence d'étiquettes éditoriales, mais de l'enregistrement du rang servi — et cela se\n",
    "**vérifie** en une ligne, par le test d'échangeabilité, avant toute mesure.\n",
    "\n",
    "**Réglé : la sévérité n'a plus à être posée.** Elle vaut 1,10 ± 0,09 sur une page de résultats\n",
    "de recherche et un dixième de cela sur un bandeau de trois vignettes. Les deux chiffres sont\n",
    "mesurés ; ce qui reste interdit est de transporter l'un vers l'autre surface.\n",
    "\n",
    "**Réglé : les estimateurs contrefactuels tiennent devant une vérité terrain** — à 2,5 %, quand\n",
    "le naïf se trompe de 32 %. Avec la réserve, chiffrée, que leur précision effective est bien\n",
    "moindre que le nombre de lignes ne le suggère.\n",
    "\n",
    "**Non réglé : aucun de ces jeux ne permet d'évaluer l'ADE.** Il y faudrait le rang servi **et**\n",
    "une étiquette de point de vue interprétable. MIND porte des catégories éditoriales mais pas le\n",
    "rang. Baidu-ULTR porte le rang mais ses documents n'ont aucune étiquette exploitable — requêtes\n",
    "et titres y sont des identifiants numériques. L'Open Bandit Dataset porte le rang, la propension\n",
    "et trois attributs catégoriels par article — mais **anonymisés** : on peut calculer une\n",
    "diversité sur des hachages, on ne peut pas déclarer le catalogue de référence qu'exige l'IDE, et\n",
    "une diversité sur des catégories dont personne ne sait ce qu'elles désignent est exactement le\n",
    "genre de mesure que ce dépôt refuse.\n",
    "\n",
    "C'est donc le troisième résultat négatif de cette série, et il faut le dire aussi nettement que\n",
    "les deux autres : **le jeu de données qui permettrait l'évaluation annoncée n'existe pas\n",
    "publiquement.** Ce qui reste possible se dit en trois lignes, et c'est la [feuille de\n",
    "route](../docs/feuille-de-route.md) qui en hérite :\n",
    "\n",
    "1. mesurer sur MIND ce qui ne dépend pas de l'exposition, en le disant ;\n",
    "2. mesurer sur Baidu-ULTR et l'Open Bandit Dataset ce qui ne dépend pas des points de vue ;\n",
    "3. pour le reste, demander la donnée — ce qui, sous l'article 40 du DSA, est une démarche\n",
    "   prévue, et non un vœu."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.14"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}