{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "# Analyse des dialogues dans l'Avare de Molière"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "## Choix du fichier source\n",
    "\n",
    "*L'Avare* de Molière est disponible dans plusieurs formats différents. \n",
    "Cependant, tous ne se prêtent pas à une analyse sémantique d'une pièce de théâtre. \n",
    "Les formats reposant sur du texte brut (tels que Markdown ou iramuteq, et par extension, les fichiers ne contenant que les prises de parole) compliquent le triage des [didascalies](https://fr.wikipedia.org/wiki/Didascalie_(théâtre)) et autres blocs de texte insérés dans les scènes, et ne relevant pas directement du dialogue. \n",
    "Notre choix devra donc se porter sur un format plus structuré.\n",
    "Nous pourrions tenter l'analyse des fichiers epub ou kindle, mais ce sont des formats destinés à la présentation, ce qui rendrait leur analyse inutilement complexe et coûteuse, alors que de meilleurs formats sont disponibles.\n",
    "\n",
    "Les formats de fichier constituant de meilleurs candidats pour une analyse sémantique sont basés sur XML, qui permet la structuration du contenu : TEI (conçu par le *Text Encoding Initiative Consortium*), TXM (co-développé par l'École normale supérieure de Lyon et l'université de Franche-Comté), et HTML (le langage de balisage du web). \n",
    "\n",
    "Ces trois formats sont basés sur XML, et peuvent donc théoriquement être exploités avec une même API ([XPath](https://fr.wikipedia.org/wiki/XPath)), sans nécessiter de bibliothèque tierce. \n",
    "\n",
    "HTML présente toutefois des avantages considérables : son exploitation par, au minimum, quelques centaines de millions de sites web à travers le monde, et sa gouvernance par un consortium d'entreprises comme Apple, Google ou Mozilla outre-Atlantique, ou encore l'Inria en France. \n",
    "C'est le format qui a créé internet, et il est réutilisé dans des contextes très différents.\n",
    "De plus, en tant que développeur web depuis 30 ans, l'auteur de la présente analyse ne cache pas son intérêt particulier pour ce format, avec lequel il est bien plus familier qu'avec les autres.\n",
    "\n",
    "Nous poursuivrons donc cette étude avec le fichier `moliere_avare.html` [mis à disposition](http://dramacode.github.io/html/moliere_avare.html) par [dramacode](https://dramacode.github.io)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Ouverture du fichier"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Commençons par regrouper les importations, afin d'en avoir une vue d'ensemble."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Parseur XML, requêtes XPath\n",
    "import xml.etree.ElementTree as ET\n",
    "\n",
    "# Analyse\n",
    "import pandas as pd\n",
    "\n",
    "# Utile pour la gestion des caractères accentués\n",
    "import locale\n",
    "\n",
    "# Nous permet de combiner deux listes de longueur indéterminée\n",
    "from itertools import zip_longest\n",
    "\n",
    "# Utilisation d'expressions régulières (regex)\n",
    "import re\n",
    "\n",
    "# Traçage de graphiques\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Permet de définir et d'afficher la colormap des personnages\n",
    "from itertools import cycle\n",
    "import matplotlib.patches as mpatches\n",
    "\n",
    "# Utiles aux calculs effectués pour les graphiques\n",
    "import math\n",
    "import numpy as np\n",
    "\n",
    "# Dépendances pour le graphe final\n",
    "from pathlib import Path\n",
    "from jinja2 import Environment, FileSystemLoader\n",
    "\n",
    "# Pose un certain nombre de problèmes pour l'exportation,\n",
    "# en raison de sa nature dynamique (et écrit en javascript)\n",
    "import pyvis\n",
    "from pyvis.network import Network\n",
    "import matplotlib.colors as mcolors\n",
    "from IPython.display import HTML"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# La définition de la locale nous permettra de gérer correctement les majuscules\n",
    "# accentuées\n",
    "locale.setlocale(locale.LC_COLLATE, \"fr_FR.UTF-8\")  # ou \"fr_FR.UTF-8\", \"fr_FR\" selon le système\n",
    "\n",
    "ns = {\"x\": \"http://www.w3.org/1999/xhtml\"}\n",
    "root = ET.parse(\"moliere_avare.html\").getroot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Outils préliminaires\n",
    "\n",
    "Nous travaillons sur une pièce de théâtre, par définition divisée en actes et en scènes.\n",
    "Nous allons donc nous créer quelques outils pour accéder facilement à ces éléments structurés, que nous complèterons de diverses fonctions utilisées à plusieurs reprises dans notre étude."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Nettoyage des titres\n",
    "def clean_title(el, tag):\n",
    "    return \"\".join(el.find(tag, ns).itertext()).replace(\"§\", \"\").strip()\n",
    "\n",
    "# Actes avec ordre explicite\n",
    "def list_acts():\n",
    "    acts = []\n",
    "\n",
    "    for idx, act in enumerate(root.findall(\".//x:section[@class='div1 act level2']\", ns)):\n",
    "        acts.append({\n",
    "            \"id\": act.get(\"id\"),\n",
    "            \"title\": clean_title(act, \"x:h2\"),\n",
    "            \"node\": act,\n",
    "            \"order\": idx,\n",
    "        })\n",
    "\n",
    "    return acts\n",
    "\n",
    "# Scènes d’un acte donné, avec ordre explicite\n",
    "def list_scenes(act=None, act_id=None):\n",
    "    if act is None:\n",
    "        if act_id is None:\n",
    "            raise ValueError(\"Un élément `act` ou un identifiant doit être spécifié\")\n",
    "\n",
    "        act = root.find(f\".//x:section[@class='div1 act level2'][@id='{act_id}']\", ns)\n",
    "\n",
    "        if act is None:\n",
    "            raise ValueError(f\"Acte introuvable: {act_id}\")\n",
    "\n",
    "    scenes = []\n",
    "\n",
    "    for idx, scene in enumerate(act.findall(\"x:section[@class='div2 scene level3']\", ns)):\n",
    "        scenes.append({\n",
    "            \"id\": scene.get(\"id\"),\n",
    "            \"title\": clean_title(scene, \"x:h3\"),\n",
    "            \"node\": scene,\n",
    "            \"order\": idx,\n",
    "        })\n",
    "\n",
    "    return scenes\n",
    "\n",
    "# On compacte les espaces pour calquer le comptage sur l'OBVIL\n",
    "# Supprime les balises <i> de l'élément HTML soumis.\n",
    "# Cela permet de ne conserver que les noms de personnages extraits des blocs de dialogue,\n",
    "# sans les didascalies.\n",
    "def text_without_i(el):\n",
    "    parts = []\n",
    "\n",
    "    if el.tag != f\"{{{ns['x']}}}i\" and el.text and el.text.strip():\n",
    "        parts.append(el.text.strip())\n",
    "\n",
    "    for child in el:\n",
    "        if child.tag != f\"{{{ns['x']}}}i\":\n",
    "            parts.extend(text_without_i(child))\n",
    "\n",
    "        # on garde toujours le texte suivant, même si le noeud enfant est une balise <i>\n",
    "        if child.tail and child.tail.strip():\n",
    "            parts.append(child.tail.strip())\n",
    "\n",
    "    return parts\n",
    "\n",
    "# Formate le nom d'un acteur extrait d'un dialogue\n",
    "def speaker_name(sp):\n",
    "    name = \" \".join(text_without_i(sp)).strip()\n",
    "\n",
    "    # nettoyage simple de la ponctuation finale\n",
    "    name = name.rstrip(\",;:\").strip()\n",
    "\n",
    "    return name\n",
    "\n",
    "# Résolution d'un nom d'acteur à partir de notre table de correspondance\n",
    "alias_index = {}\n",
    "def resolve_name(name):\n",
    "    return alias_index.get(name, name)\n",
    "\n",
    "# Extrait le texte brut d'un dialogue soumis sous la forme d'un élément HTML\n",
    "def speech_text(sp):\n",
    "    parts = []\n",
    "\n",
    "    for p in sp.findall(\".//x:p[@class='p autofirst']\", ns):\n",
    "        parts.extend(text_without_i(p))\n",
    "\n",
    "    raw = \" \".join(parts)\n",
    "    return \" \".join(raw.split()).strip()\n",
    "\n",
    "# Compte le nombre de mots d'un texte brut.\n",
    "# On utilise ici une regex simple dédiée à cet usage.\n",
    "def word_count(txt):\n",
    "    return len(re.findall(r\"\\b\\w+\\b\", txt, flags=re.UNICODE))\n",
    "\n",
    "# Conversion d'un texte en nombre de lignes (60 caractères par ligne)\n",
    "def line_count(txt, line_length=60):\n",
    "    return len(txt) / line_length if txt else 0\n",
    "\n",
    "# Retourne l'acteur associé à une réplique (<div class=\"sp\">)\n",
    "def speech_actor(sp):\n",
    "    speaker_el = sp.find(\"x:p[@class='speaker']\", ns)\n",
    "\n",
    "    if speaker_el is None:\n",
    "        return \"\"\n",
    "\n",
    "    return resolve_name(speaker_name(speaker_el))\n",
    "\n",
    "# Liste les répliques d'une scène (par noeud ou identifiant) avec texte et nombre de mots\n",
    "def scene_speeches(scene=None, scene_id=None):\n",
    "    if scene is None:\n",
    "        if scene_id is None:\n",
    "            raise ValueError(\"Un élément `scene` ou un identifiant doit être spécifié\")\n",
    "\n",
    "        scene = root.find(f\".//x:section[@class='div2 scene level3'][@id='{scene_id}']\", ns)\n",
    "\n",
    "        if scene is None:\n",
    "            raise ValueError(f\"Scène introuvable: {scene_id}\")\n",
    "\n",
    "    speeches = []\n",
    "\n",
    "    for sp_div in scene.findall(\".//x:div[@class='sp']\", ns):\n",
    "        speaker = speech_actor(sp_div)\n",
    "\n",
    "        if not speaker:\n",
    "            continue\n",
    "\n",
    "        txt = speech_text(sp_div)\n",
    "\n",
    "        speeches.append({\n",
    "            \"speaker\": speaker,\n",
    "            \"text\": txt,\n",
    "            \"word_count\": word_count(txt),\n",
    "            \"node\": sp_div,\n",
    "        })\n",
    "\n",
    "    return speeches\n",
    "\n",
    "# Création d'une colormap associant une couleur à un personnage\n",
    "def create_actors_colormap(personnages):\n",
    "    # Définition d'une palette de couleurs pour les personnages\n",
    "    palette = cycle(plt.cm.tab20.colors)\n",
    "    color_map = {}\n",
    "\n",
    "    for p in personnages:\n",
    "        color_map[p] = next(palette)\n",
    "\n",
    "    return color_map"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Vérifions que nous obtenons bien la liste des actes et des scènes :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Acte I - Scène I01\n",
      "Acte I - Scène I02\n",
      "Acte I - Scène I03\n",
      "Acte I - Scène I04\n",
      "Acte I - Scène I05\n",
      "Acte II - Scène II01\n",
      "Acte II - Scène II02\n",
      "Acte II - Scène II03\n",
      "Acte II - Scène II04\n",
      "Acte II - Scène II05\n",
      "Acte III - Scène III01\n",
      "Acte III - Scène III02\n",
      "Acte III - Scène III03\n",
      "Acte III - Scène III04\n",
      "Acte III - Scène III05\n",
      "Acte III - Scène III06\n",
      "Acte III - Scène III07\n",
      "Acte III - Scène III08\n",
      "Acte III - Scène III09\n",
      "Acte IV - Scène IV01\n",
      "Acte IV - Scène IV02\n",
      "Acte IV - Scène IV03\n",
      "Acte IV - Scène IV04\n",
      "Acte IV - Scène IV05\n",
      "Acte IV - Scène IV06\n",
      "Acte IV - Scène IV07\n",
      "Acte V - Scène V01\n",
      "Acte V - Scène V02\n",
      "Acte V - Scène V03\n",
      "Acte V - Scène V04\n",
      "Acte V - Scène V05\n",
      "Acte V - Scène V06\n"
     ]
    }
   ],
   "source": [
    "for act in list_acts():\n",
    "    for scene in list_scenes(act=act[\"node\"]):\n",
    "        print (\"Acte \" + act[\"id\"] + \" - Scène \" + scene[\"id\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Obtention de la liste des acteurs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "La requête xpath suivante permet d'extraire la liste des acteurs donnée au début du fichier, autrement appelée [_dramatis personae_](https://fr.wikipedia.org/wiki/Dramatis_personæ_(théâtre))."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Personnage</th>\n",
       "      <th>Description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Harpagon</td>\n",
       "      <td>Père de Cléante et d'Élise, et Amoureux de Mar...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cléante</td>\n",
       "      <td>Fils d'Harpagon, Amant de Mariane.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Élise</td>\n",
       "      <td>Fille d'Harpagon, Amante de Valère.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Valère</td>\n",
       "      <td>Fils d'Anselme, et Amant d'Élise.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Mariane</td>\n",
       "      <td>Amante de Cléante, et aimée d'Harpagon.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Anselme</td>\n",
       "      <td>Père de Valère et de Mariane.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Frosine</td>\n",
       "      <td>Femme d'Intrigue.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Maitre Simon</td>\n",
       "      <td>Courtier.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Maitre Jacques</td>\n",
       "      <td>Cuisinier et Cocher d'Harpagon.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>La Flèche</td>\n",
       "      <td>Valet de Cléante.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Dame Claude</td>\n",
       "      <td>Servante d'Harpagon.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Brindavoine</td>\n",
       "      <td>laquais d'Harpagon.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>La Merluche</td>\n",
       "      <td>laquais d'Harpagon.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Le commissaire</td>\n",
       "      <td>et son clerc.</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Personnage                                        Description\n",
       "0         Harpagon  Père de Cléante et d'Élise, et Amoureux de Mar...\n",
       "1          Cléante                 Fils d'Harpagon, Amant de Mariane.\n",
       "2            Élise                Fille d'Harpagon, Amante de Valère.\n",
       "3           Valère                  Fils d'Anselme, et Amant d'Élise.\n",
       "4          Mariane            Amante de Cléante, et aimée d'Harpagon.\n",
       "5          Anselme                      Père de Valère et de Mariane.\n",
       "6          Frosine                                  Femme d'Intrigue.\n",
       "7     Maitre Simon                                          Courtier.\n",
       "8   Maitre Jacques                    Cuisinier et Cocher d'Harpagon.\n",
       "9        La Flèche                                  Valet de Cléante.\n",
       "10     Dame Claude                               Servante d'Harpagon.\n",
       "11     Brindavoine                                laquais d'Harpagon.\n",
       "12     La Merluche                                laquais d'Harpagon.\n",
       "13  Le commissaire                                      et son clerc."
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Retourne une liste formatée des personnages définis dans la dramatis personae.\n",
    "# Prend en compte les majuscules accentuées.\n",
    "def dramatis_personae():\n",
    "    rows = []\n",
    "\n",
    "    # Requête xpath permettant d'obtenir la liste des balises <li> listant les acteurs\n",
    "    for li in root.findall(\".//x:div[@id='castList']//x:li\", ns):\n",
    "        # L'acteur se trouve dans une balise <span>\n",
    "        span = li.find(\"x:span\", ns)\n",
    "        name = span.text.strip()\n",
    "\n",
    "        # description = texte qui suit le <span> dans la même balise <li>\n",
    "        desc = (span.tail or \"\").strip()\n",
    "\n",
    "        if desc.startswith(\",\"):\n",
    "            desc = desc[1:].strip()\n",
    "\n",
    "        rows.append({\"Personnage\": name, \"Description\": desc})\n",
    "\n",
    "    return pd.DataFrame(rows)\n",
    "\n",
    "dramatis_personae = dramatis_personae()\n",
    "\n",
    "# Affichage de la liste\n",
    "dramatis_personae"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Nous pouvons déjà constater que le commissaire et son clerc sont considérés comme un acteur unique.\n",
    "Nous verrons plus tard si cette information est importante (par exemple, si le clerc s'exprime en son nom propre)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Nous allons confronter cette liste avec la liste des protagonistes mentionnés en introduction de chaque scène, puis avec ceux qui interviennent \"réellement\", c'est-à-dire ceux qui ont une ligne de dialogue.\n",
    "Cette étape devra nous permettre d'identifier des différences d'orthographe subtiles qu'il sera utile de gérer."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Noms des personnages par scène"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Nous allons itérer sur chaque acte, puis chaque scène, afin de consulter la liste des protagonistes. \n",
    "N'oublions pas que ces listes sont facultatives, et ne désignent pas les acteurs dotés d'une réplique.\n",
    "Néanmoins, nous pourrions identifier des éléments potentiellement intéressants, tels que des orthographes différentes ou une anomalie quelconque."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Acte</th>\n",
       "      <th>Scène</th>\n",
       "      <th>Protagonistes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Acte Premier</td>\n",
       "      <td>Scène Première</td>\n",
       "      <td>[Valère, Élise]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Acte Premier</td>\n",
       "      <td>Scène II</td>\n",
       "      <td>[Cléante, Élise]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Acte Premier</td>\n",
       "      <td>Scène III</td>\n",
       "      <td>[Harpagon, La Flèche]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Acte Premier</td>\n",
       "      <td>Scène IV</td>\n",
       "      <td>[Élise, Cléante, Harpagon]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Acte Premier</td>\n",
       "      <td>Scène V</td>\n",
       "      <td>[Valère, Harpagon, Élise]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Acte II</td>\n",
       "      <td>Scène Première</td>\n",
       "      <td>[Cléante, La Flèche]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Acte II</td>\n",
       "      <td>Scène II</td>\n",
       "      <td>[Maître Simon, Harpagon, Cléante, La Flèche]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Acte II</td>\n",
       "      <td>Scène III</td>\n",
       "      <td>[Frosine, Harpagon]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Acte II</td>\n",
       "      <td>Scène IV</td>\n",
       "      <td>[La Flèche, Frosine]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Acte II</td>\n",
       "      <td>Scène V</td>\n",
       "      <td>[Harpagon, Frosine]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Acte III</td>\n",
       "      <td>Scène Première</td>\n",
       "      <td>[Harpagon, Cléante, Élise, Valère, Dame Claude...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Acte III</td>\n",
       "      <td>Scène II</td>\n",
       "      <td>[Maître Jacques, Valère]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Acte III</td>\n",
       "      <td>Scène III</td>\n",
       "      <td>[Frosine, Mariane, Maître Jacques]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Acte III</td>\n",
       "      <td>Scène IV</td>\n",
       "      <td>[Mariane, Frosine]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Acte III</td>\n",
       "      <td>Scène V</td>\n",
       "      <td>[Harpagon, Frosine, Mariane]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Acte III</td>\n",
       "      <td>Scène VI</td>\n",
       "      <td>[Élise, Harpagon, Mariane, Frosine]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Acte III</td>\n",
       "      <td>Scène VII</td>\n",
       "      <td>[Cléante, Harpagon, Élise, Mariane, Frosine]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Acte III</td>\n",
       "      <td>Scène VIII</td>\n",
       "      <td>[Harpagon, Mariane, Frosine, Cléante, Brindavo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Acte III</td>\n",
       "      <td>Scène IX</td>\n",
       "      <td>[Harpagon, Mariane, Cléante, Élise, Frosine, L...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Acte IV</td>\n",
       "      <td>Scène Première</td>\n",
       "      <td>[Cléante, Mariane, Élise, Frosine]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Acte IV</td>\n",
       "      <td>Scène II</td>\n",
       "      <td>[Harpagon, Cléante, Mariane, Élise, Frosine]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Acte IV</td>\n",
       "      <td>Scène III</td>\n",
       "      <td>[Harpagon, Cléante]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Acte IV</td>\n",
       "      <td>Scène IV</td>\n",
       "      <td>[Maître Jacques, Harpagon, Cléante]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Acte IV</td>\n",
       "      <td>Scène V</td>\n",
       "      <td>[Cléante, Harpagon]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Acte IV</td>\n",
       "      <td>Scène VI</td>\n",
       "      <td>[La Flèche, Cléante]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Acte IV</td>\n",
       "      <td>Scène VII</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Acte V</td>\n",
       "      <td>Scène Première</td>\n",
       "      <td>[Harpagon, Le Commissaire, son Clerc]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Acte V</td>\n",
       "      <td>Scène II</td>\n",
       "      <td>[Maître Jacques, Harpagon, Le Commissaire, son...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Acte V</td>\n",
       "      <td>Scène III</td>\n",
       "      <td>[Valère, Harpagon, le Commissaire, son Clerc, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Acte V</td>\n",
       "      <td>Scène IV</td>\n",
       "      <td>[Élise, Mariane, Frosine, Harpagon, Valère, Ma...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Acte V</td>\n",
       "      <td>Scène V</td>\n",
       "      <td>[Anselme, Harpagon, Élise, Mariane, Frosine, V...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Acte V</td>\n",
       "      <td>Scène VI</td>\n",
       "      <td>[Cléante, Valère, Mariane, Élise, Frosine, Har...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Acte           Scène  \\\n",
       "0   Acte Premier  Scène Première   \n",
       "1   Acte Premier        Scène II   \n",
       "2   Acte Premier       Scène III   \n",
       "3   Acte Premier        Scène IV   \n",
       "4   Acte Premier         Scène V   \n",
       "5        Acte II  Scène Première   \n",
       "6        Acte II        Scène II   \n",
       "7        Acte II       Scène III   \n",
       "8        Acte II        Scène IV   \n",
       "9        Acte II         Scène V   \n",
       "10      Acte III  Scène Première   \n",
       "11      Acte III        Scène II   \n",
       "12      Acte III       Scène III   \n",
       "13      Acte III        Scène IV   \n",
       "14      Acte III         Scène V   \n",
       "15      Acte III        Scène VI   \n",
       "16      Acte III       Scène VII   \n",
       "17      Acte III      Scène VIII   \n",
       "18      Acte III        Scène IX   \n",
       "19       Acte IV  Scène Première   \n",
       "20       Acte IV        Scène II   \n",
       "21       Acte IV       Scène III   \n",
       "22       Acte IV        Scène IV   \n",
       "23       Acte IV         Scène V   \n",
       "24       Acte IV        Scène VI   \n",
       "25       Acte IV       Scène VII   \n",
       "26        Acte V  Scène Première   \n",
       "27        Acte V        Scène II   \n",
       "28        Acte V       Scène III   \n",
       "29        Acte V        Scène IV   \n",
       "30        Acte V         Scène V   \n",
       "31        Acte V        Scène VI   \n",
       "\n",
       "                                        Protagonistes  \n",
       "0                                     [Valère, Élise]  \n",
       "1                                    [Cléante, Élise]  \n",
       "2                               [Harpagon, La Flèche]  \n",
       "3                          [Élise, Cléante, Harpagon]  \n",
       "4                           [Valère, Harpagon, Élise]  \n",
       "5                                [Cléante, La Flèche]  \n",
       "6        [Maître Simon, Harpagon, Cléante, La Flèche]  \n",
       "7                                 [Frosine, Harpagon]  \n",
       "8                                [La Flèche, Frosine]  \n",
       "9                                 [Harpagon, Frosine]  \n",
       "10  [Harpagon, Cléante, Élise, Valère, Dame Claude...  \n",
       "11                           [Maître Jacques, Valère]  \n",
       "12                 [Frosine, Mariane, Maître Jacques]  \n",
       "13                                 [Mariane, Frosine]  \n",
       "14                       [Harpagon, Frosine, Mariane]  \n",
       "15                [Élise, Harpagon, Mariane, Frosine]  \n",
       "16       [Cléante, Harpagon, Élise, Mariane, Frosine]  \n",
       "17  [Harpagon, Mariane, Frosine, Cléante, Brindavo...  \n",
       "18  [Harpagon, Mariane, Cléante, Élise, Frosine, L...  \n",
       "19                 [Cléante, Mariane, Élise, Frosine]  \n",
       "20       [Harpagon, Cléante, Mariane, Élise, Frosine]  \n",
       "21                                [Harpagon, Cléante]  \n",
       "22                [Maître Jacques, Harpagon, Cléante]  \n",
       "23                                [Cléante, Harpagon]  \n",
       "24                               [La Flèche, Cléante]  \n",
       "25                                                 []  \n",
       "26              [Harpagon, Le Commissaire, son Clerc]  \n",
       "27  [Maître Jacques, Harpagon, Le Commissaire, son...  \n",
       "28  [Valère, Harpagon, le Commissaire, son Clerc, ...  \n",
       "29  [Élise, Mariane, Frosine, Harpagon, Valère, Ma...  \n",
       "30  [Anselme, Harpagon, Élise, Mariane, Frosine, V...  \n",
       "31  [Cléante, Valère, Mariane, Élise, Frosine, Har...  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def list_scene_protagonists():\n",
    "    rows = []\n",
    "\n",
    "    for act in list_acts():\n",
    "        for scene in list_scenes(act=act[\"node\"]):\n",
    "            stage = scene[\"node\"].find(\"x:div[@class='stage stage']\", ns)\n",
    "\n",
    "            # Si nous trouvons un noeud xpath pour cette requête, c'est un personnage\n",
    "            if stage is not None:\n",
    "                raw = \"\".join(stage.itertext()).strip()\n",
    "                people = [p.strip() for p in raw.split(\",\") if p.strip()]\n",
    "            else:\n",
    "                people = []\n",
    "\n",
    "            rows.append({\n",
    "                \"Acte\": act[\"title\"],\n",
    "                \"Scène\": scene[\"title\"],\n",
    "                \"Protagonistes\": people,\n",
    "            })\n",
    "\n",
    "    return pd.DataFrame(rows)\n",
    "\n",
    "df_scenes = list_scene_protagonists()\n",
    "df_scenes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "Nous voyons ici que la scène VII de l'acte IV ne contient aucun protagoniste déclaré dans la liste attenante[^1], mais nous allons de toute façon la compléter par l'extraction individuelle des interventions concrètes de chaque acteur.\n",
    "\n",
    "[^1]: Cette liste n'est pas obligatoire dans le contexte théâtral. Ici, on peut supposer que son absence est dûe à un monologue par exemple."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Acte</th>\n",
       "      <th>Scène</th>\n",
       "      <th>Intervenants</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Acte Premier</td>\n",
       "      <td>Scène Première</td>\n",
       "      <td>[Valère, Élise]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Acte Premier</td>\n",
       "      <td>Scène II</td>\n",
       "      <td>[Cléante, Élise]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Acte Premier</td>\n",
       "      <td>Scène III</td>\n",
       "      <td>[Harpagon, La Flèche]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Acte Premier</td>\n",
       "      <td>Scène IV</td>\n",
       "      <td>[Harpagon, Cléante, Élise]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Acte Premier</td>\n",
       "      <td>Scène V</td>\n",
       "      <td>[Harpagon, Valère, Élise]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Acte II</td>\n",
       "      <td>Scène Première</td>\n",
       "      <td>[Cléante, La Flèche]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Acte II</td>\n",
       "      <td>Scène II</td>\n",
       "      <td>[Maître simon, Harpagon, La Flèche, Cléante]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Acte II</td>\n",
       "      <td>Scène III</td>\n",
       "      <td>[Frosine, Harpagon]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Acte II</td>\n",
       "      <td>Scène IV</td>\n",
       "      <td>[La Flèche, Frosine]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Acte II</td>\n",
       "      <td>Scène V</td>\n",
       "      <td>[Harpagon, Frosine]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Acte III</td>\n",
       "      <td>Scène Première</td>\n",
       "      <td>[Harpagon, Maître Jacques, La Merluche, Brinda...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Acte III</td>\n",
       "      <td>Scène II</td>\n",
       "      <td>[Valère, Maître Jacques]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Acte III</td>\n",
       "      <td>Scène III</td>\n",
       "      <td>[Frosine, Maître Jacques]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Acte III</td>\n",
       "      <td>Scène IV</td>\n",
       "      <td>[Mariane, Frosine]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Acte III</td>\n",
       "      <td>Scène V</td>\n",
       "      <td>[Harpagon, Frosine]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Acte III</td>\n",
       "      <td>Scène VI</td>\n",
       "      <td>[Mariane, Élise, Harpagon, Frosine]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Acte III</td>\n",
       "      <td>Scène VII</td>\n",
       "      <td>[Cléante, Mariane, Harpagon, Frosine, Valère]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Acte III</td>\n",
       "      <td>Scène VIII</td>\n",
       "      <td>[Brindavoine, Harpagon]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Acte III</td>\n",
       "      <td>Scène IX</td>\n",
       "      <td>[La Merluche, Harpagon, Cléante, Valère]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Acte IV</td>\n",
       "      <td>Scène Première</td>\n",
       "      <td>[Cléante, Élise, Mariane, Frosine]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Acte IV</td>\n",
       "      <td>Scène II</td>\n",
       "      <td>[Harpagon, Élise, Cléante]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Acte IV</td>\n",
       "      <td>Scène III</td>\n",
       "      <td>[Harpagon, Cléante]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Acte IV</td>\n",
       "      <td>Scène IV</td>\n",
       "      <td>[Maître Jacques, Cléante, Harpagon]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Acte IV</td>\n",
       "      <td>Scène V</td>\n",
       "      <td>[Cléante, Harpagon]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Acte IV</td>\n",
       "      <td>Scène VI</td>\n",
       "      <td>[La Flèche, Cléante]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Acte IV</td>\n",
       "      <td>Scène VII</td>\n",
       "      <td>[Harpagon]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Acte V</td>\n",
       "      <td>Scène Première</td>\n",
       "      <td>[Le Commissaire, Harpagon]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Acte V</td>\n",
       "      <td>Scène II</td>\n",
       "      <td>[Maître Jacques, Harpagon, Le Commissaire]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Acte V</td>\n",
       "      <td>Scène III</td>\n",
       "      <td>[Harpagon, Valère, Maître Jacques]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Acte V</td>\n",
       "      <td>Scène IV</td>\n",
       "      <td>[Harpagon, Valère, Élise, Maître Jacques, Fros...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Acte V</td>\n",
       "      <td>Scène V</td>\n",
       "      <td>[Anselme, Harpagon, Valère, Mariane, Maître Ja...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Acte V</td>\n",
       "      <td>Scène VI</td>\n",
       "      <td>[Cléante, Harpagon, Mariane, Anselme, Le Commi...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Acte           Scène  \\\n",
       "0   Acte Premier  Scène Première   \n",
       "1   Acte Premier        Scène II   \n",
       "2   Acte Premier       Scène III   \n",
       "3   Acte Premier        Scène IV   \n",
       "4   Acte Premier         Scène V   \n",
       "5        Acte II  Scène Première   \n",
       "6        Acte II        Scène II   \n",
       "7        Acte II       Scène III   \n",
       "8        Acte II        Scène IV   \n",
       "9        Acte II         Scène V   \n",
       "10      Acte III  Scène Première   \n",
       "11      Acte III        Scène II   \n",
       "12      Acte III       Scène III   \n",
       "13      Acte III        Scène IV   \n",
       "14      Acte III         Scène V   \n",
       "15      Acte III        Scène VI   \n",
       "16      Acte III       Scène VII   \n",
       "17      Acte III      Scène VIII   \n",
       "18      Acte III        Scène IX   \n",
       "19       Acte IV  Scène Première   \n",
       "20       Acte IV        Scène II   \n",
       "21       Acte IV       Scène III   \n",
       "22       Acte IV        Scène IV   \n",
       "23       Acte IV         Scène V   \n",
       "24       Acte IV        Scène VI   \n",
       "25       Acte IV       Scène VII   \n",
       "26        Acte V  Scène Première   \n",
       "27        Acte V        Scène II   \n",
       "28        Acte V       Scène III   \n",
       "29        Acte V        Scène IV   \n",
       "30        Acte V         Scène V   \n",
       "31        Acte V        Scène VI   \n",
       "\n",
       "                                         Intervenants  \n",
       "0                                     [Valère, Élise]  \n",
       "1                                    [Cléante, Élise]  \n",
       "2                               [Harpagon, La Flèche]  \n",
       "3                          [Harpagon, Cléante, Élise]  \n",
       "4                           [Harpagon, Valère, Élise]  \n",
       "5                                [Cléante, La Flèche]  \n",
       "6        [Maître simon, Harpagon, La Flèche, Cléante]  \n",
       "7                                 [Frosine, Harpagon]  \n",
       "8                                [La Flèche, Frosine]  \n",
       "9                                 [Harpagon, Frosine]  \n",
       "10  [Harpagon, Maître Jacques, La Merluche, Brinda...  \n",
       "11                           [Valère, Maître Jacques]  \n",
       "12                          [Frosine, Maître Jacques]  \n",
       "13                                 [Mariane, Frosine]  \n",
       "14                                [Harpagon, Frosine]  \n",
       "15                [Mariane, Élise, Harpagon, Frosine]  \n",
       "16      [Cléante, Mariane, Harpagon, Frosine, Valère]  \n",
       "17                            [Brindavoine, Harpagon]  \n",
       "18           [La Merluche, Harpagon, Cléante, Valère]  \n",
       "19                 [Cléante, Élise, Mariane, Frosine]  \n",
       "20                         [Harpagon, Élise, Cléante]  \n",
       "21                                [Harpagon, Cléante]  \n",
       "22                [Maître Jacques, Cléante, Harpagon]  \n",
       "23                                [Cléante, Harpagon]  \n",
       "24                               [La Flèche, Cléante]  \n",
       "25                                         [Harpagon]  \n",
       "26                         [Le Commissaire, Harpagon]  \n",
       "27         [Maître Jacques, Harpagon, Le Commissaire]  \n",
       "28                 [Harpagon, Valère, Maître Jacques]  \n",
       "29  [Harpagon, Valère, Élise, Maître Jacques, Fros...  \n",
       "30  [Anselme, Harpagon, Valère, Mariane, Maître Ja...  \n",
       "31  [Cléante, Harpagon, Mariane, Anselme, Le Commi...  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def list_scene_speakers():\n",
    "    rows = []\n",
    "\n",
    "    for act in list_acts():\n",
    "        for scene in list_scenes(act=act[\"node\"]):\n",
    "            speakers, seen = [], set()\n",
    "\n",
    "            for sp in scene[\"node\"].findall(\".//x:p[@class='speaker']\", ns):\n",
    "                name = speaker_name(sp)\n",
    "\n",
    "                # On évite d'ajouter à la liste un acteur que l'on a déjà vu passer\n",
    "                if name and name not in seen:\n",
    "                    seen.add(name)\n",
    "                    speakers.append(name)\n",
    "\n",
    "            rows.append({\n",
    "                \"Acte\": act[\"title\"],\n",
    "                \"Scène\": scene[\"title\"],\n",
    "                \"Intervenants\": speakers,\n",
    "            })\n",
    "\n",
    "    return pd.DataFrame(rows)\n",
    "\n",
    "df_speakers = list_scene_speakers()\n",
    "df_speakers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Intervenant</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Anselme</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Brindavoine</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Cléante</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Élise</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Frosine</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Harpagon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>La Flèche</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>La Merluche</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Le Commissaire</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Maître Jacques</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Maître simon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Mariane</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Valère</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Intervenant\n",
       "0          Anselme\n",
       "1      Brindavoine\n",
       "2          Cléante\n",
       "3            Élise\n",
       "4          Frosine\n",
       "5         Harpagon\n",
       "6        La Flèche\n",
       "7      La Merluche\n",
       "8   Le Commissaire\n",
       "9   Maître Jacques\n",
       "10    Maître simon\n",
       "11         Mariane\n",
       "12          Valère"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Tri localisé pour les intervenants et déduplication\n",
    "intervenants_uniques = sorted(\n",
    "    {name for names in df_speakers[\"Intervenants\"] for name in names},\n",
    "    key=locale.strxfrm\n",
    ")\n",
    "\n",
    "intervenants_df = pd.DataFrame({\"Intervenant\": intervenants_uniques})\n",
    "intervenants_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On peut désormais identifier les différences avec la _dramatis personae_, afin de vérifier l'uniformité des orthographes.\n",
    "Par corollaire, on pourra, en même temps, identifier les acteurs sans réplique."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Personnage (en-tête)</th>\n",
       "      <th>Intervenant (répliques)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Dame Claude</td>\n",
       "      <td>Le Commissaire</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Le commissaire</td>\n",
       "      <td>Maître Jacques</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Maitre Jacques</td>\n",
       "      <td>Maître simon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Maitre Simon</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Personnage (en-tête) Intervenant (répliques)\n",
       "0          Dame Claude          Le Commissaire\n",
       "1       Le commissaire          Maître Jacques\n",
       "2       Maitre Jacques            Maître simon\n",
       "3         Maitre Simon                    None"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "acteurs_set = set(dramatis_personae[\"Personnage\"])\n",
    "intervenants_set = set(intervenants_uniques)\n",
    "\n",
    "# On écarte les noms exactement identiques\n",
    "communs = acteurs_set & intervenants_set\n",
    "acteurs_only = sorted(acteurs_set - communs, key=locale.strxfrm)\n",
    "intervenants_only = sorted(intervenants_set - communs, key=locale.strxfrm)\n",
    "\n",
    "df_diff = pd.DataFrame(\n",
    "    list(zip_longest(acteurs_only, intervenants_only)),\n",
    "    columns=[\"Personnage (en-tête)\", \"Intervenant (répliques)\"]\n",
    ")\n",
    "\n",
    "df_diff"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`None` indique simplement un remplissage par `zip_longest` pour que les deux listes aient la même taille."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On identifie bien deux orthographes différentes pour trois acteurs. La liste des personnages initiale omet les accents circonflexes de \"Maître\", \"commissaire\" est écrit en minuscule, et \"Simon\" a perdu sa majuscule."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Enfin, il est clair que Dame Claude n'a aucune réplique (puisqu'on ne la retrouve pas dans la liste des intervenants)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On peut donc créer une table de correspondance, associant un nom correctement orthographié avec les variantes que l'on peut trouver dans le texte initial. Nous utiliserons comme référence la graphie française correcte de \"maître\", et \"Commissaire\" avec une majuscule."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "alias_map = {\n",
    "    \"Maître Jacques\": {\"Maître Jacques\", \"Maitre Jacques\"},\n",
    "    \"Maître Simon\": {\"Maitre Simon\", \"Maître simon\"},\n",
    "    \"Le Commissaire\": {\"Le Commissaire\", \"Le commissaire\"},\n",
    "}\n",
    "\n",
    "alias_index = {alias: canon for canon, aliases in alias_map.items() for alias in aliases}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quantité de parole par acteur\n",
    "\n",
    "Maintenant que nous disposons d'une liste uniformisée des noms des différents acteurs, nous pouvons analyser l'ensemble de la pièce et quantifier le texte prononcé par chaque acteur."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Acte</th>\n",
       "      <th>Scène</th>\n",
       "      <th>Personnage</th>\n",
       "      <th>Mots</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Acte II</td>\n",
       "      <td>Scène II</td>\n",
       "      <td>Cléante</td>\n",
       "      <td>127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Acte II</td>\n",
       "      <td>Scène II</td>\n",
       "      <td>Harpagon</td>\n",
       "      <td>171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Acte II</td>\n",
       "      <td>Scène II</td>\n",
       "      <td>La Flèche</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Acte II</td>\n",
       "      <td>Scène II</td>\n",
       "      <td>Maître Simon</td>\n",
       "      <td>197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Acte II</td>\n",
       "      <td>Scène III</td>\n",
       "      <td>Frosine</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>Acte V</td>\n",
       "      <td>Scène VI</td>\n",
       "      <td>Cléante</td>\n",
       "      <td>130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>Acte V</td>\n",
       "      <td>Scène VI</td>\n",
       "      <td>Harpagon</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>Acte V</td>\n",
       "      <td>Scène VI</td>\n",
       "      <td>Le Commissaire</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>Acte V</td>\n",
       "      <td>Scène VI</td>\n",
       "      <td>Mariane</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>Acte V</td>\n",
       "      <td>Scène VI</td>\n",
       "      <td>Maître Jacques</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>95 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Acte      Scène      Personnage  Mots\n",
       "0   Acte II   Scène II         Cléante   127\n",
       "1   Acte II   Scène II        Harpagon   171\n",
       "2   Acte II   Scène II       La Flèche    12\n",
       "3   Acte II   Scène II    Maître Simon   197\n",
       "4   Acte II  Scène III         Frosine     1\n",
       "..      ...        ...             ...   ...\n",
       "90   Acte V   Scène VI         Cléante   130\n",
       "91   Acte V   Scène VI        Harpagon    89\n",
       "92   Acte V   Scène VI  Le Commissaire    26\n",
       "93   Acte V   Scène VI         Mariane    36\n",
       "94   Acte V   Scène VI  Maître Jacques    23\n",
       "\n",
       "[95 rows x 4 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# TODO : Est-ce que cette fonction est redondante avec\n",
    "# les fonctions utilitaires créées précédemment ?\n",
    "def count_words_by_actor():\n",
    "    rows = []\n",
    "\n",
    "    for act in list_acts():\n",
    "        for scene in list_scenes(act=act[\"node\"]):\n",
    "            for order, speech in enumerate(scene_speeches(scene=scene[\"node\"])):\n",
    "                txt = speech[\"text\"]\n",
    "                rows.append({\n",
    "                    \"Acte\": act[\"title\"],\n",
    "                    \"Scène\": scene[\"title\"],\n",
    "                    \"Ordre\": order,\n",
    "                    \"Personnage\": speech[\"speaker\"],\n",
    "                    \"Texte\": txt,\n",
    "                    \"Mots\": speech[\"word_count\"],\n",
    "                    \"Lignes\": line_count(txt),\n",
    "                })\n",
    "\n",
    "    return pd.DataFrame(rows)\n",
    "\n",
    "df_speeches = count_words_by_actor()\n",
    "df_counts = df_speeches.groupby([\"Acte\", \"Scène\", \"Personnage\"], as_index=False)[\"Mots\"].sum()\n",
    "df_counts"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "Le comptage semble s'effectuer correctement, mais un tel tableau n'est pas digeste. \n",
    "On peut noter par exemple que \"Acte Premier\" est dilué au centre du tableau, en raison de la clause `groupby`, qui trie implicitement le tableau, et ignore donc notre tri initial.\n",
    "Nous pouvons toutefois ignorer ce détail ici, et regrouper par personnage : de cette manière, nous aurons un aperçu global du temps de parole de chacun à travers l'oeuvre."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Personnage le plus taciturne : Brindavoine (43 mots)\n",
      "Personnage le plus locace  : Harpagon (6132 mots)\n"
     ]
    }
   ],
   "source": [
    "global_df = df_speeches.groupby([\"Personnage\"])[\"Mots\"].sum()\n",
    "\n",
    "moins_bavard_nom = global_df.idxmin()\n",
    "moins_bavard_mots = global_df.min()\n",
    "\n",
    "plus_bavard_nom = global_df.idxmax()\n",
    "plus_bavard_mots = global_df.max()\n",
    "\n",
    "print(f\"Personnage le plus taciturne : {moins_bavard_nom} ({moins_bavard_mots} mots)\")\n",
    "print(f\"Personnage le plus locace  : {plus_bavard_nom} ({plus_bavard_mots} mots)\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notons que nous avons déjà établi que Dame Claude n'avait aucune réplique, et bien que le Commissaire soit accompagné d'un clerc, ce dernier ne parle jamais non plus."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Montrons la proportion de dialogues par personnage à travers un diagramme circulaire :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "n_small = 5\n",
    "y0, dy = 1.3, 0.05   # Positionnement du bloc des acteurs les moins locaces\n",
    "x_col = -0.5\n",
    "\n",
    "totaux = df_speeches.groupby(\"Personnage\")[\"Mots\"].sum().sort_values(ascending=False)\n",
    "labels = totaux.index\n",
    "values = totaux.values\n",
    "color_map = create_actors_colormap(labels)\n",
    "colors = [color_map[p] for p in labels]\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(7, 7))\n",
    "wedges, _ = ax.pie(values, colors=colors, startangle=90, counterclock=False, normalize=True)\n",
    "\n",
    "small_roles = global_df.sort_values().head(n_small)  # les moins bavards, ordre croissant\n",
    "\n",
    "# Placement de l'étiquette pour les petits rôles\n",
    "for i, (name, val) in enumerate(small_roles.items()):\n",
    "    idx = labels.get_loc(name)\n",
    "    w = wedges[idx]\n",
    "\n",
    "    theta = np.deg2rad((w.theta1 + w.theta2) / 2)\n",
    "    xw, yw = np.cos(theta), np.sin(theta)\n",
    "    xpos, ypos = x_col, y0 - i * dy\n",
    "\n",
    "    ax.annotate(\n",
    "        f\"{name} ({val})\",\n",
    "        xy=(xw, yw), xytext=(xpos, ypos),\n",
    "        ha=\"right\", va=\"center\", fontsize=9,\n",
    "        arrowprops=dict(\n",
    "            arrowstyle=\"-\",\n",
    "            color=colors[idx],\n",
    "            lw=1,\n",
    "            connectionstyle=\"angle,angleA=0,angleB=90\",\n",
    "            shrinkA=0, shrinkB=0,\n",
    "        ),\n",
    "    )\n",
    "\n",
    "# Autres rôles : nom autour + valeur au centre\n",
    "for idx, name in enumerate(labels):\n",
    "    if name in small_roles.index:\n",
    "        continue\n",
    "\n",
    "    w = wedges[idx]\n",
    "    theta = np.deg2rad((w.theta1 + w.theta2) / 2)\n",
    "    r_label, r_value = 1.1, 0.7\n",
    "\n",
    "    ax.text(r_label * np.cos(theta), r_label * np.sin(theta), name, ha=\"center\", va=\"center\", fontsize=9)\n",
    "    ax.text(r_value * np.cos(theta), r_value * np.sin(theta), str(totaux[name]), ha=\"center\", va=\"center\", fontsize=9, color=\"black\")\n",
    "\n",
    "ax.set_title(\"Répartition des mots prononcés par personnage\", pad=50)\n",
    "ax.axis(\"equal\")\n",
    "plt.tight_layout()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Statistiques complémentaires\n",
    "\n",
    "Inspirées des tableaux de l'OBVIL, nous examinons la place de chaque personnage et les relations directes entre interlocuteurs (une ligne = 60 caractères).\n",
    "Commençons par la \"Table des rôles\" :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Rôle</th>\n",
       "      <th>Scènes</th>\n",
       "      <th>Répl.</th>\n",
       "      <th>Répl. moy.</th>\n",
       "      <th>Présence</th>\n",
       "      <th>Texte</th>\n",
       "      <th>Texte % prés.</th>\n",
       "      <th>Texte × pers.</th>\n",
       "      <th>Interlocution</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>[TOUS]</td>\n",
       "      <td>32 sc.</td>\n",
       "      <td>959 répl.</td>\n",
       "      <td>1,8 l.</td>\n",
       "      <td>1 769 l. (100 %)</td>\n",
       "      <td>1 769 l. (100 %)</td>\n",
       "      <td>100 %</td>\n",
       "      <td>5 847 l. (100 %)</td>\n",
       "      <td>3,3 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Harpagon</td>\n",
       "      <td>23 sc.</td>\n",
       "      <td>354 répl.</td>\n",
       "      <td>1,5 l.</td>\n",
       "      <td>1 296 l. (73 %)</td>\n",
       "      <td>514 l. (29 %)</td>\n",
       "      <td>40 %</td>\n",
       "      <td>4 729 l. (81 %)</td>\n",
       "      <td>3,7 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Cléante</td>\n",
       "      <td>14 sc.</td>\n",
       "      <td>161 répl.</td>\n",
       "      <td>1,8 l.</td>\n",
       "      <td>900 l. (51 %)</td>\n",
       "      <td>285 l. (16 %)</td>\n",
       "      <td>32 %</td>\n",
       "      <td>3 486 l. (60 %)</td>\n",
       "      <td>3,9 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Élise</td>\n",
       "      <td>9 sc.</td>\n",
       "      <td>51 répl.</td>\n",
       "      <td>1,8 l.</td>\n",
       "      <td>681 l. (39 %)</td>\n",
       "      <td>92 l. (5 %)</td>\n",
       "      <td>13 %</td>\n",
       "      <td>2 667 l. (46 %)</td>\n",
       "      <td>3,9 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Valère</td>\n",
       "      <td>9 sc.</td>\n",
       "      <td>101 répl.</td>\n",
       "      <td>2,3 l.</td>\n",
       "      <td>695 l. (39 %)</td>\n",
       "      <td>232 l. (13 %)</td>\n",
       "      <td>33 %</td>\n",
       "      <td>3 067 l. (52 %)</td>\n",
       "      <td>4,4 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Mariane</td>\n",
       "      <td>6 sc.</td>\n",
       "      <td>31 répl.</td>\n",
       "      <td>2,5 l.</td>\n",
       "      <td>359 l. (20 %)</td>\n",
       "      <td>79 l. (4 %)</td>\n",
       "      <td>22 %</td>\n",
       "      <td>1 638 l. (28 %)</td>\n",
       "      <td>4,6 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Anselme</td>\n",
       "      <td>2 sc.</td>\n",
       "      <td>20 répl.</td>\n",
       "      <td>2,3 l.</td>\n",
       "      <td>143 l. (8 %)</td>\n",
       "      <td>45 l. (3 %)</td>\n",
       "      <td>32 %</td>\n",
       "      <td>749 l. (13 %)</td>\n",
       "      <td>5,3 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Frosine</td>\n",
       "      <td>10 sc.</td>\n",
       "      <td>60 répl.</td>\n",
       "      <td>3,3 l.</td>\n",
       "      <td>466 l. (26 %)</td>\n",
       "      <td>201 l. (11 %)</td>\n",
       "      <td>43 %</td>\n",
       "      <td>1 465 l. (25 %)</td>\n",
       "      <td>3,1 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Maître Simon</td>\n",
       "      <td>1 sc.</td>\n",
       "      <td>5 répl.</td>\n",
       "      <td>3,2 l.</td>\n",
       "      <td>44 l. (2 %)</td>\n",
       "      <td>16 l. (1 %)</td>\n",
       "      <td>37 %</td>\n",
       "      <td>175 l. (3 %)</td>\n",
       "      <td>4,0 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Maître Jacques</td>\n",
       "      <td>9 sc.</td>\n",
       "      <td>85 répl.</td>\n",
       "      <td>1,6 l.</td>\n",
       "      <td>557 l. (32 %)</td>\n",
       "      <td>140 l. (8 %)</td>\n",
       "      <td>25 %</td>\n",
       "      <td>2 670 l. (46 %)</td>\n",
       "      <td>4,8 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>La Flèche</td>\n",
       "      <td>5 sc.</td>\n",
       "      <td>66 répl.</td>\n",
       "      <td>2,0 l.</td>\n",
       "      <td>255 l. (14 %)</td>\n",
       "      <td>132 l. (7 %)</td>\n",
       "      <td>52 %</td>\n",
       "      <td>598 l. (10 %)</td>\n",
       "      <td>2,3 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Dame Claude</td>\n",
       "      <td>0 sc.</td>\n",
       "      <td>0 répl.</td>\n",
       "      <td>0,0 l.</td>\n",
       "      <td>0 l.</td>\n",
       "      <td>0 l.</td>\n",
       "      <td>0 %</td>\n",
       "      <td>0 l. (0 %)</td>\n",
       "      <td>0,0 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Brindavoine</td>\n",
       "      <td>2 sc.</td>\n",
       "      <td>3 répl.</td>\n",
       "      <td>1,1 l.</td>\n",
       "      <td>166 l. (9 %)</td>\n",
       "      <td>3 l. (0 %)</td>\n",
       "      <td>2 %</td>\n",
       "      <td>1 146 l. (20 %)</td>\n",
       "      <td>6,9 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>La Merluche</td>\n",
       "      <td>2 sc.</td>\n",
       "      <td>5 répl.</td>\n",
       "      <td>0,9 l.</td>\n",
       "      <td>175 l. (10 %)</td>\n",
       "      <td>5 l. (0 %)</td>\n",
       "      <td>3 %</td>\n",
       "      <td>1 189 l. (20 %)</td>\n",
       "      <td>6,8 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Le Commissaire</td>\n",
       "      <td>3 sc.</td>\n",
       "      <td>17 répl.</td>\n",
       "      <td>1,5 l.</td>\n",
       "      <td>110 l. (6 %)</td>\n",
       "      <td>26 l. (1 %)</td>\n",
       "      <td>24 %</td>\n",
       "      <td>418 l. (7 %)</td>\n",
       "      <td>3,8 pers.</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Rôle  Scènes      Répl. Répl. moy.          Présence  \\\n",
       "0           [TOUS]  32 sc.  959 répl.     1,8 l.  1 769 l. (100 %)   \n",
       "1         Harpagon  23 sc.  354 répl.     1,5 l.   1 296 l. (73 %)   \n",
       "2          Cléante  14 sc.  161 répl.     1,8 l.     900 l. (51 %)   \n",
       "3            Élise   9 sc.   51 répl.     1,8 l.     681 l. (39 %)   \n",
       "4           Valère   9 sc.  101 répl.     2,3 l.     695 l. (39 %)   \n",
       "5          Mariane   6 sc.   31 répl.     2,5 l.     359 l. (20 %)   \n",
       "6          Anselme   2 sc.   20 répl.     2,3 l.      143 l. (8 %)   \n",
       "7          Frosine  10 sc.   60 répl.     3,3 l.     466 l. (26 %)   \n",
       "8     Maître Simon   1 sc.    5 répl.     3,2 l.       44 l. (2 %)   \n",
       "9   Maître Jacques   9 sc.   85 répl.     1,6 l.     557 l. (32 %)   \n",
       "10       La Flèche   5 sc.   66 répl.     2,0 l.     255 l. (14 %)   \n",
       "11     Dame Claude   0 sc.    0 répl.     0,0 l.              0 l.   \n",
       "12     Brindavoine   2 sc.    3 répl.     1,1 l.      166 l. (9 %)   \n",
       "13     La Merluche   2 sc.    5 répl.     0,9 l.     175 l. (10 %)   \n",
       "14  Le Commissaire   3 sc.   17 répl.     1,5 l.      110 l. (6 %)   \n",
       "\n",
       "               Texte Texte % prés.     Texte × pers. Interlocution  \n",
       "0   1 769 l. (100 %)         100 %  5 847 l. (100 %)     3,3 pers.  \n",
       "1      514 l. (29 %)          40 %   4 729 l. (81 %)     3,7 pers.  \n",
       "2      285 l. (16 %)          32 %   3 486 l. (60 %)     3,9 pers.  \n",
       "3        92 l. (5 %)          13 %   2 667 l. (46 %)     3,9 pers.  \n",
       "4      232 l. (13 %)          33 %   3 067 l. (52 %)     4,4 pers.  \n",
       "5        79 l. (4 %)          22 %   1 638 l. (28 %)     4,6 pers.  \n",
       "6        45 l. (3 %)          32 %     749 l. (13 %)     5,3 pers.  \n",
       "7      201 l. (11 %)          43 %   1 465 l. (25 %)     3,1 pers.  \n",
       "8        16 l. (1 %)          37 %      175 l. (3 %)     4,0 pers.  \n",
       "9       140 l. (8 %)          25 %   2 670 l. (46 %)     4,8 pers.  \n",
       "10      132 l. (7 %)          52 %     598 l. (10 %)     2,3 pers.  \n",
       "11              0 l.           0 %        0 l. (0 %)     0,0 pers.  \n",
       "12        3 l. (0 %)           2 %   1 146 l. (20 %)     6,9 pers.  \n",
       "13        5 l. (0 %)           3 %   1 189 l. (20 %)     6,8 pers.  \n",
       "14       26 l. (1 %)          24 %      418 l. (7 %)     3,8 pers.  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Agrégats au niveau des scènes\n",
    "scene_totals = (df_speeches.groupby([\"Acte\", \"Scène\"], as_index=False)\n",
    "                .agg(scene_lines=(\"Lignes\", \"sum\"),\n",
    "                     participants=(\"Personnage\", \"nunique\")))\n",
    "scene_totals[\"textexpers\"] = scene_totals[\"scene_lines\"] * scene_totals[\"participants\"]\n",
    "scene_totals[\"SceneKey\"] = scene_totals[\"Acte\"] + \" | \" + scene_totals[\"Scène\"]\n",
    "\n",
    "total_lines_play = scene_totals[\"scene_lines\"].sum()\n",
    "textexpers_total = scene_totals[\"textexpers\"].sum()\n",
    "\n",
    "# Statistiques par personnage\n",
    "speech_stats = df_speeches.groupby(\"Personnage\").agg(\n",
    "    repl=(\"Texte\", \"count\"),\n",
    "    text_lines=(\"Lignes\", \"sum\"),\n",
    ")\n",
    "\n",
    "presence = (df_speeches[[\"Acte\", \"Scène\", \"Personnage\"]]\n",
    "            .drop_duplicates()\n",
    "            .merge(scene_totals[[\"Acte\", \"Scène\", \"scene_lines\", \"textexpers\"]],\n",
    "                   on=[\"Acte\", \"Scène\"], how=\"left\"))\n",
    "\n",
    "presence_stats = presence.groupby(\"Personnage\").agg(\n",
    "    scenes=(\"Scène\", \"count\"),\n",
    "    presence_lines=(\"scene_lines\", \"sum\"),\n",
    "    textexpers=(\"textexpers\", \"sum\"),\n",
    ")\n",
    "\n",
    "roles = speech_stats.join(presence_stats, how=\"outer\").fillna(0)\n",
    "\n",
    "# Ajout des rôles muets (ex : Dame Claude) pour qu'ils apparaissent dans le tableau\n",
    "for name in (resolve_name(p) for p in dramatis_personae[\"Personnage\"]):\n",
    "    if name not in roles.index:\n",
    "        roles.loc[name] = 0\n",
    "\n",
    "roles[\"repl_moy\"] = roles[\"text_lines\"] / roles[\"repl\"]\n",
    "roles[\"presence_pct\"] = roles[\"presence_lines\"] / total_lines_play\n",
    "roles[\"text_pct\"] = roles[\"text_lines\"] / total_lines_play\n",
    "roles[\"text_presence_pct\"] = roles[\"text_lines\"] / roles[\"presence_lines\"]\n",
    "roles[\"textexpers_pct\"] = roles[\"textexpers\"] / textexpers_total\n",
    "roles[\"interlocution\"] = roles[\"textexpers\"] / roles[\"presence_lines\"]\n",
    "\n",
    "roles = roles.replace([np.inf, -np.inf], 0).fillna(0)\n",
    "\n",
    "# Ordre basé sur la distribution initiale\n",
    "role_order = [name for name in (resolve_name(p) for p in dramatis_personae[\"Personnage\"]) if name in roles.index]\n",
    "role_order += [r for r in roles.index if r not in role_order]\n",
    "\n",
    "roles = roles.loc[role_order]\n",
    "\n",
    "# Ligne globale\n",
    "all_row = pd.Series({\n",
    "    \"scenes\": scene_totals.shape[0],\n",
    "    \"repl\": len(df_speeches),\n",
    "    \"repl_moy\": df_speeches[\"Lignes\"].sum() / len(df_speeches),\n",
    "    \"presence_lines\": total_lines_play,\n",
    "    \"presence_pct\": 1.0,\n",
    "    \"text_lines\": df_speeches[\"Lignes\"].sum(),\n",
    "    \"text_pct\": 1.0,\n",
    "    \"text_presence_pct\": df_speeches[\"Lignes\"].sum() / total_lines_play if total_lines_play else 0,\n",
    "    \"textexpers\": textexpers_total,\n",
    "    \"textexpers_pct\": 1.0,\n",
    "    \"interlocution\": textexpers_total / total_lines_play if total_lines_play else 0,\n",
    "})\n",
    "\n",
    "roles = pd.concat([\n",
    "    pd.DataFrame({\"Personnage\": [\"[TOUS]\"]}).set_index(\"Personnage\").assign(**all_row),\n",
    "    roles\n",
    "])\n",
    "\n",
    "roles.index.name = \"Rôle\"\n",
    "\n",
    "# Quelques utilitaires spécifiques\n",
    "\n",
    "def format_number(value, decimals=0):\n",
    "    fmt = f\"{value:,.{decimals}f}\"\n",
    "    return fmt.replace(\",\", \" \").replace(\".\", \",\")\n",
    "def format_lines(value, decimals=0):\n",
    "    return f\"{format_number(round(value, decimals), decimals)} l.\"\n",
    "def format_percent(value, decimals=0):\n",
    "    return f\"{format_number(value * 100, decimals)} %\"\n",
    "def format_people(value):\n",
    "    return f\"{format_number(value, 1)} pers.\"\n",
    "\n",
    "roles_display = roles.reset_index()\n",
    "roles_display[\"Scènes\"] = roles_display[\"scenes\"].fillna(0).astype(int).astype(str) + \" sc.\"\n",
    "roles_display[\"Répl.\"] = roles_display[\"repl\"].fillna(0).astype(int).astype(str) + \" répl.\"\n",
    "roles_display[\"Répl. moy.\"] = roles_display[\"repl_moy\"].apply(lambda v: format_lines(v, 1))\n",
    "roles_display[\"Présence\"] = roles_display.apply(\n",
    "    lambda r: f\"{format_lines(r['presence_lines'])}\" + (f\" ({format_percent(r['presence_pct'])})\" if r[\"presence_lines\"] else \"\"),\n",
    "    axis=1,\n",
    ")\n",
    "roles_display[\"Texte\"] = roles_display.apply(\n",
    "    lambda r: f\"{format_lines(r['text_lines'])}\" + (f\" ({format_percent(r['text_pct'])})\" if r[\"text_lines\"] else \"\"),\n",
    "    axis=1,\n",
    ")\n",
    "roles_display[\"Texte % prés.\"] = roles_display[\"text_presence_pct\"].apply(lambda v: format_percent(v, 0))\n",
    "roles_display[\"Texte × pers.\"] = roles_display.apply(\n",
    "    lambda r: f\"{format_lines(r['textexpers'])} ({format_percent(r['textexpers_pct'])})\",\n",
    "    axis=1,\n",
    ")\n",
    "roles_display[\"Interlocution\"] = roles_display[\"interlocution\"].apply(format_people)\n",
    "\n",
    "roles_table = roles_display[[\"Rôle\", \"Scènes\", \"Répl.\", \"Répl. moy.\", \"Présence\", \"Texte\", \"Texte % prés.\", \"Texte × pers.\", \"Interlocution\"]]\n",
    "roles_table\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Il existe des différences entre le tableau que nous avons généré et celui de l'OBVIL.\n",
    "Ces différences peuvent être attribuées à :\n",
    "\n",
    "- une méthode de nettoyage des lignes différente (nous avons opté pour un nettoyage agressif des espaces surnuméraires)\n",
    "- une gestion des décimales différentes (est-ce que l'OBVIL arrondi à l'entier supérieur ou inférieur, ou tronque les décimales ?)\n",
    "\n",
    "Ces différences affectent mathématiquement les statistiques qui découlent de ce comptage, notamment l'interlocution."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Statistiques par relation\n",
    "\n",
    "Chaque relation s'appuie sur l'enchaînement de répliques adjacentes entre deux personnages (monologues inclus), ce qui reflète les échanges directs plutôt que la simple coprésence sur scène.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Relation</th>\n",
       "      <th>Détail</th>\n",
       "      <th>Scènes</th>\n",
       "      <th>Texte</th>\n",
       "      <th>Interlocution</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Harpagon</td>\n",
       "      <td>33 l. (100 %) 1 répl. 32,7 l.</td>\n",
       "      <td>1 sc.</td>\n",
       "      <td>33 l. (2 %)</td>\n",
       "      <td>1,0 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cléante / Harpagon</td>\n",
       "      <td>135 l. (49 %) 97 répl. 1,4 l. - 140 l. (51 %) ...</td>\n",
       "      <td>9 sc.</td>\n",
       "      <td>275 l. (16 %)</td>\n",
       "      <td>4,6 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Harpagon / Élise</td>\n",
       "      <td>41 l. (60 %) 28 répl. 1,5 l. - 28 l. (40 %) 28...</td>\n",
       "      <td>6 sc.</td>\n",
       "      <td>69 l. (4 %)</td>\n",
       "      <td>4,7 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Harpagon / Valère</td>\n",
       "      <td>96 l. (44 %) 65 répl. 1,5 l. - 121 l. (56 %) 5...</td>\n",
       "      <td>7 sc.</td>\n",
       "      <td>217 l. (12 %)</td>\n",
       "      <td>4,9 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Harpagon / Mariane</td>\n",
       "      <td>9 l. (39 %) 7 répl. 1,2 l. - 13 l. (61 %) 5 ré...</td>\n",
       "      <td>2 sc.</td>\n",
       "      <td>22 l. (1 %)</td>\n",
       "      <td>4,9 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Anselme / Harpagon</td>\n",
       "      <td>25 l. (71 %) 11 répl. 2,2 l. - 10 l. (29 %) 8 ...</td>\n",
       "      <td>2 sc.</td>\n",
       "      <td>35 l. (2 %)</td>\n",
       "      <td>5,3 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Frosine / Harpagon</td>\n",
       "      <td>128 l. (70 %) 39 répl. 3,3 l. - 56 l. (30 %) 3...</td>\n",
       "      <td>5 sc.</td>\n",
       "      <td>184 l. (10 %)</td>\n",
       "      <td>3,0 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Harpagon / Maître Simon</td>\n",
       "      <td>5 l. (22 %) 3 répl. 1,5 l. - 16 l. (78 %) 4 ré...</td>\n",
       "      <td>1 sc.</td>\n",
       "      <td>20 l. (1 %)</td>\n",
       "      <td>4,0 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Harpagon / Maître Jacques</td>\n",
       "      <td>58 l. (38 %) 49 répl. 1,2 l. - 94 l. (62 %) 51...</td>\n",
       "      <td>7 sc.</td>\n",
       "      <td>153 l. (9 %)</td>\n",
       "      <td>4,9 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Harpagon / La Flèche</td>\n",
       "      <td>35 l. (62 %) 33 répl. 1,1 l. - 22 l. (38 %) 33...</td>\n",
       "      <td>1 sc.</td>\n",
       "      <td>57 l. (3 %)</td>\n",
       "      <td>2,0 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Brindavoine / Harpagon</td>\n",
       "      <td>1 l. (38 %) 2 répl. 0,7 l. - 2 l. (62 %) 2 rép...</td>\n",
       "      <td>2 sc.</td>\n",
       "      <td>4 l. (0 %)</td>\n",
       "      <td>6,9 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Harpagon / La Merluche</td>\n",
       "      <td>1 l. (11 %) 1 répl. 0,6 l. - 5 l. (89 %) 5 rép...</td>\n",
       "      <td>2 sc.</td>\n",
       "      <td>5 l. (0 %)</td>\n",
       "      <td>6,8 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Harpagon / Le Commissaire</td>\n",
       "      <td>11 l. (53 %) 10 répl. 1,1 l. - 10 l. (47 %) 9 ...</td>\n",
       "      <td>3 sc.</td>\n",
       "      <td>21 l. (1 %)</td>\n",
       "      <td>3,8 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Cléante / Élise</td>\n",
       "      <td>66 l. (84 %) 10 répl. 6,6 l. - 13 l. (16 %) 9 ...</td>\n",
       "      <td>2 sc.</td>\n",
       "      <td>78 l. (4 %)</td>\n",
       "      <td>3,0 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Cléante / Mariane</td>\n",
       "      <td>31 l. (60 %) 12 répl. 2,6 l. - 21 l. (40 %) 10...</td>\n",
       "      <td>3 sc.</td>\n",
       "      <td>52 l. (3 %)</td>\n",
       "      <td>4,8 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Cléante / Frosine</td>\n",
       "      <td>3 l. (8 %) 5 répl. 0,6 l. - 37 l. (92 %) 6 rép...</td>\n",
       "      <td>2 sc.</td>\n",
       "      <td>40 l. (2 %)</td>\n",
       "      <td>4,5 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Cléante / Maître Jacques</td>\n",
       "      <td>14 l. (51 %) 8 répl. 1,8 l. - 14 l. (49 %) 8 r...</td>\n",
       "      <td>1 sc.</td>\n",
       "      <td>28 l. (2 %)</td>\n",
       "      <td>3,0 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Cléante / La Flèche</td>\n",
       "      <td>31 l. (27 %) 25 répl. 1,2 l. - 85 l. (73 %) 26...</td>\n",
       "      <td>3 sc.</td>\n",
       "      <td>116 l. (7 %)</td>\n",
       "      <td>2,5 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Valère / Élise</td>\n",
       "      <td>65 l. (59 %) 11 répl. 5,9 l. - 45 l. (41 %) 11...</td>\n",
       "      <td>2 sc.</td>\n",
       "      <td>110 l. (6 %)</td>\n",
       "      <td>2,5 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Mariane / Élise</td>\n",
       "      <td>1 l. (23 %) 2 répl. 0,6 l. - 4 l. (77 %) 1 rép...</td>\n",
       "      <td>2 sc.</td>\n",
       "      <td>6 l. (0 %)</td>\n",
       "      <td>4,0 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Mariane / Valère</td>\n",
       "      <td>3 l. (41 %) 1 répl. 2,6 l. - 4 l. (59 %) 3 rép...</td>\n",
       "      <td>1 sc.</td>\n",
       "      <td>6 l. (0 %)</td>\n",
       "      <td>5,0 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Anselme / Valère</td>\n",
       "      <td>19 l. (47 %) 8 répl. 2,4 l. - 22 l. (53 %) 7 r...</td>\n",
       "      <td>1 sc.</td>\n",
       "      <td>41 l. (2 %)</td>\n",
       "      <td>5,0 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Maître Jacques / Valère</td>\n",
       "      <td>18 l. (49 %) 14 répl. 1,3 l. - 19 l. (51 %) 18...</td>\n",
       "      <td>4 sc.</td>\n",
       "      <td>37 l. (2 %)</td>\n",
       "      <td>5,2 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Frosine / Mariane</td>\n",
       "      <td>18 l. (48 %) 6 répl. 3,0 l. - 20 l. (52 %) 7 r...</td>\n",
       "      <td>4 sc.</td>\n",
       "      <td>38 l. (2 %)</td>\n",
       "      <td>4,1 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Frosine / Maître Jacques</td>\n",
       "      <td>1 l. (42 %) 1 répl. 1,0 l. - 1 l. (58 %) 2 rép...</td>\n",
       "      <td>2 sc.</td>\n",
       "      <td>2 l. (0 %)</td>\n",
       "      <td>4,7 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Frosine / La Flèche</td>\n",
       "      <td>11 l. (42 %) 5 répl. 2,3 l. - 16 l. (58 %) 5 r...</td>\n",
       "      <td>1 sc.</td>\n",
       "      <td>28 l. (2 %)</td>\n",
       "      <td>2,0 pers.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Le Commissaire / Maître Jacques</td>\n",
       "      <td>13 l. (76 %) 7 répl. 1,8 l. - 4 l. (24 %) 5 ré...</td>\n",
       "      <td>1 sc.</td>\n",
       "      <td>17 l. (1 %)</td>\n",
       "      <td>3,0 pers.</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Relation  \\\n",
       "0                          Harpagon   \n",
       "1                Cléante / Harpagon   \n",
       "2                  Harpagon / Élise   \n",
       "3                 Harpagon / Valère   \n",
       "4                Harpagon / Mariane   \n",
       "5                Anselme / Harpagon   \n",
       "6                Frosine / Harpagon   \n",
       "7           Harpagon / Maître Simon   \n",
       "8         Harpagon / Maître Jacques   \n",
       "9              Harpagon / La Flèche   \n",
       "10           Brindavoine / Harpagon   \n",
       "11           Harpagon / La Merluche   \n",
       "12        Harpagon / Le Commissaire   \n",
       "13                  Cléante / Élise   \n",
       "14                Cléante / Mariane   \n",
       "15                Cléante / Frosine   \n",
       "16         Cléante / Maître Jacques   \n",
       "17              Cléante / La Flèche   \n",
       "18                   Valère / Élise   \n",
       "19                  Mariane / Élise   \n",
       "20                 Mariane / Valère   \n",
       "21                 Anselme / Valère   \n",
       "22          Maître Jacques / Valère   \n",
       "23                Frosine / Mariane   \n",
       "24         Frosine / Maître Jacques   \n",
       "25              Frosine / La Flèche   \n",
       "26  Le Commissaire / Maître Jacques   \n",
       "\n",
       "                                               Détail Scènes          Texte  \\\n",
       "0                       33 l. (100 %) 1 répl. 32,7 l.  1 sc.    33 l. (2 %)   \n",
       "1   135 l. (49 %) 97 répl. 1,4 l. - 140 l. (51 %) ...  9 sc.  275 l. (16 %)   \n",
       "2   41 l. (60 %) 28 répl. 1,5 l. - 28 l. (40 %) 28...  6 sc.    69 l. (4 %)   \n",
       "3   96 l. (44 %) 65 répl. 1,5 l. - 121 l. (56 %) 5...  7 sc.  217 l. (12 %)   \n",
       "4   9 l. (39 %) 7 répl. 1,2 l. - 13 l. (61 %) 5 ré...  2 sc.    22 l. (1 %)   \n",
       "5   25 l. (71 %) 11 répl. 2,2 l. - 10 l. (29 %) 8 ...  2 sc.    35 l. (2 %)   \n",
       "6   128 l. (70 %) 39 répl. 3,3 l. - 56 l. (30 %) 3...  5 sc.  184 l. (10 %)   \n",
       "7   5 l. (22 %) 3 répl. 1,5 l. - 16 l. (78 %) 4 ré...  1 sc.    20 l. (1 %)   \n",
       "8   58 l. (38 %) 49 répl. 1,2 l. - 94 l. (62 %) 51...  7 sc.   153 l. (9 %)   \n",
       "9   35 l. (62 %) 33 répl. 1,1 l. - 22 l. (38 %) 33...  1 sc.    57 l. (3 %)   \n",
       "10  1 l. (38 %) 2 répl. 0,7 l. - 2 l. (62 %) 2 rép...  2 sc.     4 l. (0 %)   \n",
       "11  1 l. (11 %) 1 répl. 0,6 l. - 5 l. (89 %) 5 rép...  2 sc.     5 l. (0 %)   \n",
       "12  11 l. (53 %) 10 répl. 1,1 l. - 10 l. (47 %) 9 ...  3 sc.    21 l. (1 %)   \n",
       "13  66 l. (84 %) 10 répl. 6,6 l. - 13 l. (16 %) 9 ...  2 sc.    78 l. (4 %)   \n",
       "14  31 l. (60 %) 12 répl. 2,6 l. - 21 l. (40 %) 10...  3 sc.    52 l. (3 %)   \n",
       "15  3 l. (8 %) 5 répl. 0,6 l. - 37 l. (92 %) 6 rép...  2 sc.    40 l. (2 %)   \n",
       "16  14 l. (51 %) 8 répl. 1,8 l. - 14 l. (49 %) 8 r...  1 sc.    28 l. (2 %)   \n",
       "17  31 l. (27 %) 25 répl. 1,2 l. - 85 l. (73 %) 26...  3 sc.   116 l. (7 %)   \n",
       "18  65 l. (59 %) 11 répl. 5,9 l. - 45 l. (41 %) 11...  2 sc.   110 l. (6 %)   \n",
       "19  1 l. (23 %) 2 répl. 0,6 l. - 4 l. (77 %) 1 rép...  2 sc.     6 l. (0 %)   \n",
       "20  3 l. (41 %) 1 répl. 2,6 l. - 4 l. (59 %) 3 rép...  1 sc.     6 l. (0 %)   \n",
       "21  19 l. (47 %) 8 répl. 2,4 l. - 22 l. (53 %) 7 r...  1 sc.    41 l. (2 %)   \n",
       "22  18 l. (49 %) 14 répl. 1,3 l. - 19 l. (51 %) 18...  4 sc.    37 l. (2 %)   \n",
       "23  18 l. (48 %) 6 répl. 3,0 l. - 20 l. (52 %) 7 r...  4 sc.    38 l. (2 %)   \n",
       "24  1 l. (42 %) 1 répl. 1,0 l. - 1 l. (58 %) 2 rép...  2 sc.     2 l. (0 %)   \n",
       "25  11 l. (42 %) 5 répl. 2,3 l. - 16 l. (58 %) 5 r...  1 sc.    28 l. (2 %)   \n",
       "26  13 l. (76 %) 7 répl. 1,8 l. - 4 l. (24 %) 5 ré...  1 sc.    17 l. (1 %)   \n",
       "\n",
       "   Interlocution  \n",
       "0      1,0 pers.  \n",
       "1      4,6 pers.  \n",
       "2      4,7 pers.  \n",
       "3      4,9 pers.  \n",
       "4      4,9 pers.  \n",
       "5      5,3 pers.  \n",
       "6      3,0 pers.  \n",
       "7      4,0 pers.  \n",
       "8      4,9 pers.  \n",
       "9      2,0 pers.  \n",
       "10     6,9 pers.  \n",
       "11     6,8 pers.  \n",
       "12     3,8 pers.  \n",
       "13     3,0 pers.  \n",
       "14     4,8 pers.  \n",
       "15     4,5 pers.  \n",
       "16     3,0 pers.  \n",
       "17     2,5 pers.  \n",
       "18     2,5 pers.  \n",
       "19     4,0 pers.  \n",
       "20     5,0 pers.  \n",
       "21     5,0 pers.  \n",
       "22     5,2 pers.  \n",
       "23     4,1 pers.  \n",
       "24     4,7 pers.  \n",
       "25     2,0 pers.  \n",
       "26     3,0 pers.  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from collections import defaultdict\n",
    "\n",
    "# Accumulateur : pour chaque relation (acteur seul - monologues) ou (acteurA, acteurB),\n",
    "# on stocke les lignes, le nombre de répliques, les scènes concernées,\n",
    "# les lignes de présence cumulées et un poids d’interlocution (lignes × nb de participants).\n",
    "relation_stats = defaultdict(lambda: {\n",
    "    \"lines\": defaultdict(float),\n",
    "    \"counts\": defaultdict(int),\n",
    "    \"scenes\": set(),\n",
    "    \"presence_lines\": 0.0,\n",
    "    \"interlocution_weight\": 0.0,\n",
    "})\n",
    "\n",
    "scene_lookup = scene_totals.set_index([\"Acte\", \"Scène\"])[[\"scene_lines\", \"participants\"]]\n",
    "\n",
    "for (act, scene), scene_df in df_speeches.groupby([\"Acte\", \"Scène\"]):\n",
    "    scene_df = scene_df.sort_values(\"Ordre\")\n",
    "    speakers = scene_df[\"Personnage\"].tolist()\n",
    "    lines = scene_df[\"Lignes\"].tolist()\n",
    "    scene_lines = scene_lookup.loc[(act, scene), \"scene_lines\"]\n",
    "    participants = scene_lookup.loc[(act, scene), \"participants\"]\n",
    "    scene_key = f\"{act} | {scene}\"\n",
    "\n",
    "    # Scène à un seul intervenant : on enregistre un monologue\n",
    "    if len(set(speakers)) == 1:\n",
    "        actor = speakers[0]\n",
    "        stats = relation_stats[(actor,)]\n",
    "        stats[\"lines\"][actor] += scene_lines\n",
    "        stats[\"counts\"][actor] += len(speakers)\n",
    "        stats[\"scenes\"].add(scene_key)\n",
    "        stats[\"presence_lines\"] += scene_lines\n",
    "        stats[\"interlocution_weight\"] += scene_lines * participants\n",
    "        continue\n",
    "\n",
    "    relations_here = set()\n",
    "    \n",
    "    # Pour chaque changement d’intervenant, on attribue les lignes du locuteur au duo (ordre ignoré)\n",
    "    for speaker, next_speaker, speaker_lines in zip(speakers, speakers[1:], lines):\n",
    "        if speaker == next_speaker:\n",
    "            continue\n",
    "            \n",
    "        key = tuple(sorted((speaker, next_speaker)))\n",
    "        stats = relation_stats[key]\n",
    "        stats[\"lines\"][speaker] += speaker_lines\n",
    "        stats[\"counts\"][speaker] += 1\n",
    "        stats[\"scenes\"].add(scene_key)\n",
    "        relations_here.add(key)\n",
    "\n",
    "    # On ajoute la présence et l’interlocution une seule fois par scène et par relation\n",
    "    for key in relations_here:\n",
    "        stats = relation_stats[key]\n",
    "        stats[\"presence_lines\"] += scene_lines\n",
    "        stats[\"interlocution_weight\"] += scene_lines * participants\n",
    "\n",
    "role_order_index = {name: idx for idx, name in enumerate(role_order)}\n",
    "\n",
    "def relation_sort_key(rel):\n",
    "    if len(rel) == 1:\n",
    "        return (role_order_index.get(rel[0], len(role_order_index)), -1)\n",
    "    \n",
    "    a, b = rel\n",
    "    \n",
    "    return (\n",
    "        min(role_order_index.get(a, len(role_order_index)), role_order_index.get(b, len(role_order_index))),\n",
    "        max(role_order_index.get(a, len(role_order_index)), role_order_index.get(b, len(role_order_index))),\n",
    "    )\n",
    "\n",
    "relation_rows = []\n",
    "\n",
    "for rel in sorted(relation_stats, key=relation_sort_key):\n",
    "    data = relation_stats[rel]\n",
    "    total_lines = sum(data[\"lines\"].values())\n",
    "\n",
    "    # On ignore les relations sans matière (moins de 2 lignes au total)\n",
    "    if total_lines < 2:\n",
    "        continue\n",
    "        \n",
    "    # On ignore les relations où au moins un protagoniste n’a jamais prononcé de réplique dans ce duo\n",
    "    if len(rel) > 1 and any(data[\"counts\"].get(actor, 0) == 0 for actor in rel):\n",
    "        continue\n",
    "\n",
    "    scenes_count = len(data[\"scenes\"])\n",
    "    interlocution = data[\"interlocution_weight\"] / data[\"presence_lines\"] if data[\"presence_lines\"] else 0\n",
    "\n",
    "    parts = []\n",
    "    \n",
    "    for actor in rel:\n",
    "        actor_lines = data[\"lines\"].get(actor, 0)\n",
    "        actor_repl = data[\"counts\"].get(actor, 0)\n",
    "        avg_lines = actor_lines / actor_repl if actor_repl else 0\n",
    "        share = actor_lines / total_lines if total_lines else 0\n",
    "        \n",
    "        parts.append(\n",
    "            f\"{format_lines(actor_lines)} ({format_percent(share)}) {actor_repl} répl. {format_lines(avg_lines, 1)}\"\n",
    "        )\n",
    "\n",
    "    relation_rows.append({\n",
    "        \"Relation\": \" / \".join(rel),\n",
    "        \"Détail\": \" - \".join(parts),\n",
    "        \"Scènes\": f\"{scenes_count} sc.\",\n",
    "        \"Texte\": f\"{format_lines(total_lines)} ({format_percent(total_lines / total_lines_play)})\",\n",
    "        \"Interlocution\": format_people(interlocution),\n",
    "    })\n",
    "\n",
    "relations_table = pd.DataFrame(relation_rows)\n",
    "relations_table"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Bien que le décompte des lignes diffère toujours de celui de l'OBVIL (comme attendu et pour les mêmes raisons que précédemment), l'interlocution est identique.\n",
    "En effet, les écarts de comptage de lignes n’affectent pas l’interlocution ; seule une différence de liste d’intervenants par scène la ferait varier."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Voyons maintenant si nous parvenons à reproduire le graphique proposé par l'OBVIL :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Ordonnancement des actes et des scènes\n",
    "# On affichera les labels bruts (\"Acte Premier\") mais on utilisera un ordre \"naturel\"\n",
    "scene_order = []\n",
    "\n",
    "for act in list_acts():\n",
    "    for sc in list_scenes(act=act[\"node\"]):\n",
    "        scene_order.append(f\"{act['title']} | {sc['title']}\")\n",
    "\n",
    "# Préparation des données\n",
    "df = df_counts.copy()\n",
    "\n",
    "# Création d'une clé unique pour identifier un couple acte/scène\n",
    "# Cela permet de forcer l'ordre d'affichage, au lieu de suivre un ordre alphabétique\n",
    "# qui noierait \"Acte Premier\" au milieu de la liste, par exemple\n",
    "df[\"SceneKey\"] = pd.Categorical(df[\"Acte\"] + \" | \" + df[\"Scène\"], categories=scene_order, ordered=True)\n",
    "\n",
    "# Obtention du pourcentage que représente un dialogue particulier au sein d'une scène\n",
    "df[\"share\"] = df[\"Mots\"] / df.groupby(\"SceneKey\", observed=False)[\"Mots\"].transform(\"sum\")\n",
    "\n",
    "# Calcul du total de mots pour une scène donnée\n",
    "totals = df.groupby(\"SceneKey\", observed=False)[\"Mots\"].sum()\n",
    "\n",
    "# Paramétrage du graphique\n",
    "gap = 0 # Espace vertical ajouté entre deux scènes\n",
    "label_fs = 8 # Taille de la police des étiquettes\n",
    "min_target = 10  # Hauteur minimale souhaitée\n",
    "\n",
    "# Définition de la hauteur d'une scène.\n",
    "# Nous utilisons ici une fonction racine carré.\n",
    "# Le but de ce calcul est d'éviter que les scènes contenant le moins de mots\n",
    "# se trouvent compressées en une ligne si fine qu'il ne serait pas possible\n",
    "# de distinguer les différents protagonistes.\n",
    "# On sacrifie donc le rapport proportionnel strict au profit d'une meilleure\n",
    "# lisibilité.\n",
    "def scene_height(total):\n",
    "    return max(min_target, math.sqrt(total) * factor)\n",
    "\n",
    "create_actors_colormap(df[\"Personnage\"].unique())\n",
    "\n",
    "# Calcul de l'échelle des scènes : évite qu'une scène courte soit\n",
    "# représentée par une ligne trop fine pour être distinguée\n",
    "min_total = totals.min()\n",
    "factor = min_target / math.log1p(min_total)\n",
    "\n",
    "figure, axis = plt.subplots(figsize=(12, len(scene_order) * 0.5))\n",
    "\n",
    "# Affichage de la colormap des personnages\n",
    "handles = [mpatches.Patch(color=col, label=name) for name, col in color_map.items()]\n",
    "axis.legend(handles=handles, title=\"Personnage\", bbox_to_anchor=(1.25, 1), loc=\"upper left\")\n",
    "\n",
    "y = 0 # \"Curseur\" vertical permettant de positionner les scènes\n",
    "\n",
    "# Traçage des scènes\n",
    "for scene in scene_order:\n",
    "    scene_rows = df[df[\"SceneKey\"] == scene]\n",
    "    h = scene_height(totals.loc[scene])\n",
    "\n",
    "    left = 0\n",
    "\n",
    "    for _, row in scene_rows.iterrows():\n",
    "        # broken_barth est la méthode nous permettant de tracer des barres\n",
    "        # horizontales juxtaposés\n",
    "        axis.broken_barh([(left, row[\"share\"])], (y, h),\n",
    "                       facecolors=color_map[row[\"Personnage\"]],\n",
    "                       edgecolors=\"white\", linewidth=0.5)\n",
    "\n",
    "        # Décalage horizontal de la prochaine barre\n",
    "        left += row[\"share\"]\n",
    "\n",
    "    # Étiquette correspondant à la scène\n",
    "    axis.text(1.01, y + h/2, scene, va=\"center\", fontsize=label_fs)\n",
    "\n",
    "    # Décalage vertical de la prochaine scène\n",
    "    y += h + gap\n",
    "\n",
    "axis.set_xlim(0, 1)\n",
    "axis.set_ylim(0, y)\n",
    "axis.invert_yaxis()  # Acte I en haut\n",
    "axis.set_xlabel(\"% de la scène (largeur) - une ligne par scène\")\n",
    "axis.set_yticks([]) # On masque l'ordonnée à gauche\n",
    "axis.spines[[\"top\", \"right\", \"left\", \"bottom\"]].set_visible(False) # On masque les délimitations du graphique\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "L'ordre des dialogues est respecté sur ce graphique, contrairement au graphique de l'OBVIL.\n",
    "Par exemple, dans la deuxième scène du premier acte, Cléante est bien la première à prendre la parole, et non Élise."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Graphe réseau des dialogues"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "Ici, nous allons représenter les dialogues par un graphe réseau.\n",
    "Nous allons essayer de reproduire le [graphe](https://obtic.huma-num.fr/obvil-web/corpus/moliere/moliere_avare) proposé par l'OBVIL."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<html>\n",
       "    <head>\n",
       "        <meta charset=\"utf-8\">\n",
       "        \n",
       "            <script>function neighbourhoodHighlight(params) {\n",
       "  // console.log(\"in nieghbourhoodhighlight\");\n",
       "  allNodes = nodes.get({ returnType: \"Object\" });\n",
       "  // originalNodes = JSON.parse(JSON.stringify(allNodes));\n",
       "  // if something is selected:\n",
       "  if (params.nodes.length > 0) {\n",
       "    highlightActive = true;\n",
       "    var i, j;\n",
       "    var selectedNode = params.nodes[0];\n",
       "    var degrees = 2;\n",
       "\n",
       "    // mark all nodes as hard to read.\n",
       "    for (let nodeId in allNodes) {\n",
       "      // nodeColors[nodeId] = allNodes[nodeId].color;\n",
       "      allNodes[nodeId].color = \"rgba(200,200,200,0.5)\";\n",
       "      if (allNodes[nodeId].hiddenLabel === undefined) {\n",
       "        allNodes[nodeId].hiddenLabel = allNodes[nodeId].label;\n",
       "        allNodes[nodeId].label = undefined;\n",
       "      }\n",
       "    }\n",
       "    var connectedNodes = network.getConnectedNodes(selectedNode);\n",
       "    var allConnectedNodes = [];\n",
       "\n",
       "    // get the second degree nodes\n",
       "    for (i = 1; i < degrees; i++) {\n",
       "      for (j = 0; j < connectedNodes.length; j++) {\n",
       "        allConnectedNodes = allConnectedNodes.concat(\n",
       "          network.getConnectedNodes(connectedNodes[j])\n",
       "        );\n",
       "      }\n",
       "    }\n",
       "\n",
       "    // all second degree nodes get a different color and their label back\n",
       "    for (i = 0; i < allConnectedNodes.length; i++) {\n",
       "      // allNodes[allConnectedNodes[i]].color = \"pink\";\n",
       "      allNodes[allConnectedNodes[i]].color = \"rgba(150,150,150,0.75)\";\n",
       "      if (allNodes[allConnectedNodes[i]].hiddenLabel !== undefined) {\n",
       "        allNodes[allConnectedNodes[i]].label =\n",
       "          allNodes[allConnectedNodes[i]].hiddenLabel;\n",
       "        allNodes[allConnectedNodes[i]].hiddenLabel = undefined;\n",
       "      }\n",
       "    }\n",
       "\n",
       "    // all first degree nodes get their own color and their label back\n",
       "    for (i = 0; i < connectedNodes.length; i++) {\n",
       "      // allNodes[connectedNodes[i]].color = undefined;\n",
       "      allNodes[connectedNodes[i]].color = nodeColors[connectedNodes[i]];\n",
       "      if (allNodes[connectedNodes[i]].hiddenLabel !== undefined) {\n",
       "        allNodes[connectedNodes[i]].label =\n",
       "          allNodes[connectedNodes[i]].hiddenLabel;\n",
       "        allNodes[connectedNodes[i]].hiddenLabel = undefined;\n",
       "      }\n",
       "    }\n",
       "\n",
       "    // the main node gets its own color and its label back.\n",
       "    // allNodes[selectedNode].color = undefined;\n",
       "    allNodes[selectedNode].color = nodeColors[selectedNode];\n",
       "    if (allNodes[selectedNode].hiddenLabel !== undefined) {\n",
       "      allNodes[selectedNode].label = allNodes[selectedNode].hiddenLabel;\n",
       "      allNodes[selectedNode].hiddenLabel = undefined;\n",
       "    }\n",
       "  } else if (highlightActive === true) {\n",
       "    // console.log(\"highlightActive was true\");\n",
       "    // reset all nodes\n",
       "    for (let nodeId in allNodes) {\n",
       "      // allNodes[nodeId].color = \"purple\";\n",
       "      allNodes[nodeId].color = nodeColors[nodeId];\n",
       "      // delete allNodes[nodeId].color;\n",
       "      if (allNodes[nodeId].hiddenLabel !== undefined) {\n",
       "        allNodes[nodeId].label = allNodes[nodeId].hiddenLabel;\n",
       "        allNodes[nodeId].hiddenLabel = undefined;\n",
       "      }\n",
       "    }\n",
       "    highlightActive = false;\n",
       "  }\n",
       "\n",
       "  // transform the object into an array\n",
       "  var updateArray = [];\n",
       "  if (params.nodes.length > 0) {\n",
       "    for (let nodeId in allNodes) {\n",
       "      if (allNodes.hasOwnProperty(nodeId)) {\n",
       "        // console.log(allNodes[nodeId]);\n",
       "        updateArray.push(allNodes[nodeId]);\n",
       "      }\n",
       "    }\n",
       "    nodes.update(updateArray);\n",
       "  } else {\n",
       "    // console.log(\"Nothing was selected\");\n",
       "    for (let nodeId in allNodes) {\n",
       "      if (allNodes.hasOwnProperty(nodeId)) {\n",
       "        // console.log(allNodes[nodeId]);\n",
       "        // allNodes[nodeId].color = {};\n",
       "        updateArray.push(allNodes[nodeId]);\n",
       "      }\n",
       "    }\n",
       "    nodes.update(updateArray);\n",
       "  }\n",
       "}\n",
       "\n",
       "function filterHighlight(params) {\n",
       "  allNodes = nodes.get({ returnType: \"Object\" });\n",
       "  // if something is selected:\n",
       "  if (params.nodes.length > 0) {\n",
       "    filterActive = true;\n",
       "    let selectedNodes = params.nodes;\n",
       "\n",
       "    // hiding all nodes and saving the label\n",
       "    for (let nodeId in allNodes) {\n",
       "      allNodes[nodeId].hidden = true;\n",
       "      if (allNodes[nodeId].savedLabel === undefined) {\n",
       "        allNodes[nodeId].savedLabel = allNodes[nodeId].label;\n",
       "        allNodes[nodeId].label = undefined;\n",
       "      }\n",
       "    }\n",
       "\n",
       "    for (let i=0; i < selectedNodes.length; i++) {\n",
       "      allNodes[selectedNodes[i]].hidden = false;\n",
       "      if (allNodes[selectedNodes[i]].savedLabel !== undefined) {\n",
       "        allNodes[selectedNodes[i]].label = allNodes[selectedNodes[i]].savedLabel;\n",
       "        allNodes[selectedNodes[i]].savedLabel = undefined;\n",
       "      }\n",
       "    }\n",
       "\n",
       "  } else if (filterActive === true) {\n",
       "    // reset all nodes\n",
       "    for (let nodeId in allNodes) {\n",
       "      allNodes[nodeId].hidden = false;\n",
       "      if (allNodes[nodeId].savedLabel !== undefined) {\n",
       "        allNodes[nodeId].label = allNodes[nodeId].savedLabel;\n",
       "        allNodes[nodeId].savedLabel = undefined;\n",
       "      }\n",
       "    }\n",
       "    filterActive = false;\n",
       "  }\n",
       "\n",
       "  // transform the object into an array\n",
       "  var updateArray = [];\n",
       "  if (params.nodes.length > 0) {\n",
       "    for (let nodeId in allNodes) {\n",
       "      if (allNodes.hasOwnProperty(nodeId)) {\n",
       "        updateArray.push(allNodes[nodeId]);\n",
       "      }\n",
       "    }\n",
       "    nodes.update(updateArray);\n",
       "  } else {\n",
       "    for (let nodeId in allNodes) {\n",
       "      if (allNodes.hasOwnProperty(nodeId)) {\n",
       "        updateArray.push(allNodes[nodeId]);\n",
       "      }\n",
       "    }\n",
       "    nodes.update(updateArray);\n",
       "  }\n",
       "}\n",
       "\n",
       "function selectNode(nodes) {\n",
       "  network.selectNodes(nodes);\n",
       "  neighbourhoodHighlight({ nodes: nodes });\n",
       "  return nodes;\n",
       "}\n",
       "\n",
       "function selectNodes(nodes) {\n",
       "  network.selectNodes(nodes);\n",
       "  filterHighlight({nodes: nodes});\n",
       "  return nodes;\n",
       "}\n",
       "\n",
       "function highlightFilter(filter) {\n",
       "  let selectedNodes = []\n",
       "  let selectedProp = filter['property']\n",
       "  if (filter['item'] === 'node') {\n",
       "    let allNodes = nodes.get({ returnType: \"Object\" });\n",
       "    for (let nodeId in allNodes) {\n",
       "      if (allNodes[nodeId][selectedProp] && filter['value'].includes((allNodes[nodeId][selectedProp]).toString())) {\n",
       "        selectedNodes.push(nodeId)\n",
       "      }\n",
       "    }\n",
       "  }\n",
       "  else if (filter['item'] === 'edge'){\n",
       "    let allEdges = edges.get({returnType: 'object'});\n",
       "    // check if the selected property exists for selected edge and select the nodes connected to the edge\n",
       "    for (let edge in allEdges) {\n",
       "      if (allEdges[edge][selectedProp] && filter['value'].includes((allEdges[edge][selectedProp]).toString())) {\n",
       "        selectedNodes.push(allEdges[edge]['from'])\n",
       "        selectedNodes.push(allEdges[edge]['to'])\n",
       "      }\n",
       "    }\n",
       "  }\n",
       "  selectNodes(selectedNodes)\n",
       "}</script>\n",
       "            <link rel=\"stylesheet\" href=\"https://cdnjs.cloudflare.com/ajax/libs/vis-network/9.1.2/dist/dist/vis-network.min.css\" integrity=\"sha512-WgxfT5LWjfszlPHXRmBWHkV2eceiWTOBvrKCNbdgDYTHrT2AeLCGbF4sZlZw3UMN3WtL0tGUoIAKsu8mllg/XA==\" crossorigin=\"anonymous\" referrerpolicy=\"no-referrer\" />\n",
       "            <script src=\"https://cdnjs.cloudflare.com/ajax/libs/vis-network/9.1.2/dist/vis-network.min.js\" integrity=\"sha512-LnvoEWDFrqGHlHmDD2101OrLcbsfkrzoSpvtSQtxK3RMnRV0eOkhhBN2dXHKRrUU8p2DGRTk35n4O8nWSVe1mQ==\" crossorigin=\"anonymous\" referrerpolicy=\"no-referrer\"></script>\n",
       "            \n",
       "            \n",
       "            \n",
       "            \n",
       "            \n",
       "            \n",
       "\n",
       "        \n",
       "<center>\n",
       "<h1></h1>\n",
       "</center>\n",
       "\n",
       "<!-- <link rel=\"stylesheet\" href=\"../node_modules/vis/dist/vis.min.css\" type=\"text/css\" />\n",
       "<script type=\"text/javascript\" src=\"../node_modules/vis/dist/vis.js\"> </script>-->\n",
       "        <link\n",
       "          href=\"https://cdn.jsdelivr.net/npm/bootstrap@5.0.0-beta3/dist/css/bootstrap.min.css\"\n",
       "          rel=\"stylesheet\"\n",
       "          integrity=\"sha384-eOJMYsd53ii+scO/bJGFsiCZc+5NDVN2yr8+0RDqr0Ql0h+rP48ckxlpbzKgwra6\"\n",
       "          crossorigin=\"anonymous\"\n",
       "        />\n",
       "        <script\n",
       "          src=\"https://cdn.jsdelivr.net/npm/bootstrap@5.0.0-beta3/dist/js/bootstrap.bundle.min.js\"\n",
       "          integrity=\"sha384-JEW9xMcG8R+pH31jmWH6WWP0WintQrMb4s7ZOdauHnUtxwoG2vI5DkLtS3qm9Ekf\"\n",
       "          crossorigin=\"anonymous\"\n",
       "        ></script>\n",
       "\n",
       "\n",
       "        <center>\n",
       "          <h1></h1>\n",
       "        </center>\n",
       "        <style type=\"text/css\">\n",
       "\n",
       "             #mynetwork {\n",
       "                 width: 100%;\n",
       "                 height: 700px;\n",
       "                 background-color: #f8f8f8;\n",
       "                 border: 1px solid lightgray;\n",
       "                 position: relative;\n",
       "                 float: left;\n",
       "             }\n",
       "\n",
       "             \n",
       "\n",
       "             \n",
       "\n",
       "             \n",
       "        </style>\n",
       "    </head>\n",
       "\n",
       "\n",
       "    <body>\n",
       "        <div class=\"card\" style=\"width: 100%\">\n",
       "            \n",
       "            \n",
       "            <div id=\"mynetwork\" class=\"card-body\"></div>\n",
       "        </div>\n",
       "\n",
       "        \n",
       "        \n",
       "\n",
       "        <script type=\"text/javascript\">\n",
       "\n",
       "              // initialize global variables.\n",
       "              var edges;\n",
       "              var nodes;\n",
       "              var allNodes;\n",
       "              var allEdges;\n",
       "              var nodeColors;\n",
       "              var originalNodes;\n",
       "              var network;\n",
       "              var container;\n",
       "              var options, data;\n",
       "              var filter = {\n",
       "                  item : '',\n",
       "                  property : '',\n",
       "                  value : []\n",
       "              };\n",
       "\n",
       "              \n",
       "\n",
       "              \n",
       "\n",
       "              // This method is responsible for drawing the graph, returns the drawn network\n",
       "              function drawGraph() {\n",
       "                  var container = document.getElementById('mynetwork');\n",
       "\n",
       "                  \n",
       "\n",
       "                  // parsing and collecting nodes and edges from the python\n",
       "                  nodes = new vis.DataSet([{\"color\": \"#9467bd\", \"font\": {\"align\": \"center\", \"color\": \"#111\", \"size\": 18}, \"id\": \"Anselme\", \"label\": \"Anselme\", \"shape\": \"dot\", \"size\": 21.642580401082487, \"title\": \"517 mots\"}, {\"color\": \"#e377c2\", \"font\": {\"align\": \"center\", \"color\": \"#111\", \"size\": 18}, \"id\": \"Brindavoine\", \"label\": \"Brindavoine\", \"shape\": \"dot\", \"size\": 11.9344631145812, \"title\": \"43 mots\"}, {\"color\": \"#aec7e8\", \"font\": {\"align\": \"center\", \"color\": \"#111\", \"size\": 18}, \"id\": \"Cl\\u00e9ante\", \"label\": \"Cl\\u00e9ante\", \"shape\": \"dot\", \"size\": 42.68083043988422, \"title\": \"3341 mots\"}, {\"color\": \"#ffbb78\", \"font\": {\"align\": \"center\", \"color\": \"#111\", \"size\": 18}, \"id\": \"Frosine\", \"label\": \"Frosine\", \"shape\": \"dot\", \"size\": 37.01792549442499, \"title\": \"2339 mots\"}, {\"color\": \"#1f77b4\", \"font\": {\"align\": \"center\", \"color\": \"#111\", \"size\": 18}, \"id\": \"Harpagon\", \"label\": \"Harpagon\", \"shape\": \"dot\", \"size\": 54.98425268108454, \"title\": \"6132 mots\"}, {\"color\": \"#98df8a\", \"font\": {\"align\": \"center\", \"color\": \"#111\", \"size\": 18}, \"id\": \"La Fl\\u00e8che\", \"label\": \"La Fl\\u00e8che\", \"shape\": \"dot\", \"size\": 31.330666514268298, \"title\": \"1512 mots\"}, {\"color\": \"#c49c94\", \"font\": {\"align\": \"center\", \"color\": \"#111\", \"size\": 18}, \"id\": \"La Merluche\", \"label\": \"La Merluche\", \"shape\": \"dot\", \"size\": 12.113392760240625, \"title\": \"47 mots\"}, {\"color\": \"#c5b0d5\", \"font\": {\"align\": \"center\", \"color\": \"#111\", \"size\": 18}, \"id\": \"Le Commissaire\", \"label\": \"Le Commissaire\", \"shape\": \"dot\", \"size\": 18.287856919689347, \"title\": \"294 mots\"}, {\"color\": \"#ff9896\", \"font\": {\"align\": \"center\", \"color\": \"#111\", \"size\": 18}, \"id\": \"Mariane\", \"label\": \"Mariane\", \"shape\": \"dot\", \"size\": 26.18900766946894, \"title\": \"919 mots\"}, {\"color\": \"#2ca02c\", \"font\": {\"align\": \"center\", \"color\": \"#111\", \"size\": 18}, \"id\": \"Ma\\u00eetre Jacques\", \"label\": \"Ma\\u00eetre Jacques\", \"shape\": \"dot\", \"size\": 32.53405796031305, \"title\": \"1672 mots\"}, {\"color\": \"#8c564b\", \"font\": {\"align\": \"center\", \"color\": \"#111\", \"size\": 18}, \"id\": \"Ma\\u00eetre Simon\", \"label\": \"Ma\\u00eetre Simon\", \"shape\": \"dot\", \"size\": 16.42140130857092, \"title\": \"197 mots\"}, {\"color\": \"#ff7f0e\", \"font\": {\"align\": \"center\", \"color\": \"#111\", \"size\": 18}, \"id\": \"Val\\u00e8re\", \"label\": \"Val\\u00e8re\", \"shape\": \"dot\", \"size\": 39.309423501559394, \"title\": \"2723 mots\"}, {\"color\": \"#d62728\", \"font\": {\"align\": \"center\", \"color\": \"#111\", \"size\": 18}, \"id\": \"\\u00c9lise\", \"label\": \"\\u00c9lise\", \"shape\": \"dot\", \"size\": 27.59897956527329, \"title\": \"1067 mots\"}]);\n",
       "                  edges = new vis.DataSet([{\"arrows\": \"to\", \"color\": \"#9467bd\", \"from\": \"Anselme\", \"title\": \"293 mots\", \"to\": \"Harpagon\", \"value\": 5.683579767338681}, {\"arrows\": \"to\", \"color\": \"#9467bd\", \"from\": \"Anselme\", \"title\": \"13 mots\", \"to\": \"Le Commissaire\", \"value\": 2.639057329615259}, {\"arrows\": \"to\", \"color\": \"#9467bd\", \"from\": \"Anselme\", \"title\": \"211 mots\", \"to\": \"Val\\u00e8re\", \"value\": 5.356586274672012}, {\"arrows\": \"to\", \"color\": \"#e377c2\", \"from\": \"Brindavoine\", \"title\": \"20 mots\", \"to\": \"Harpagon\", \"value\": 3.044522437723423}, {\"arrows\": \"to\", \"color\": \"#e377c2\", \"from\": \"Brindavoine\", \"title\": \"23 mots\", \"to\": \"La Merluche\", \"value\": 3.1780538303479458}, {\"arrows\": \"to\", \"color\": \"#aec7e8\", \"from\": \"Cl\\u00e9ante\", \"title\": \"32 mots\", \"to\": \"Frosine\", \"value\": 3.4965075614664802}, {\"arrows\": \"to\", \"color\": \"#aec7e8\", \"from\": \"Cl\\u00e9ante\", \"title\": \"1587 mots\", \"to\": \"Harpagon\", \"value\": 7.370230641807081}, {\"arrows\": \"to\", \"color\": \"#aec7e8\", \"from\": \"Cl\\u00e9ante\", \"title\": \"385 mots\", \"to\": \"La Fl\\u00e8che\", \"value\": 5.955837369464831}, {\"arrows\": \"to\", \"color\": \"#aec7e8\", \"from\": \"Cl\\u00e9ante\", \"title\": \"350 mots\", \"to\": \"Mariane\", \"value\": 5.860786223465865}, {\"arrows\": \"to\", \"color\": \"#aec7e8\", \"from\": \"Cl\\u00e9ante\", \"title\": \"170 mots\", \"to\": \"Ma\\u00eetre Jacques\", \"value\": 5.14166355650266}, {\"arrows\": \"to\", \"color\": \"#aec7e8\", \"from\": \"Cl\\u00e9ante\", \"title\": \"13 mots\", \"to\": \"Ma\\u00eetre Simon\", \"value\": 2.639057329615259}, {\"arrows\": \"to\", \"color\": \"#aec7e8\", \"from\": \"Cl\\u00e9ante\", \"title\": \"758 mots\", \"to\": \"\\u00c9lise\", \"value\": 6.6320017773956295}, {\"arrows\": \"to\", \"color\": \"#ffbb78\", \"from\": \"Frosine\", \"title\": \"436 mots\", \"to\": \"Cl\\u00e9ante\", \"value\": 6.07993319509559}, {\"arrows\": \"to\", \"color\": \"#ffbb78\", \"from\": \"Frosine\", \"title\": \"1498 mots\", \"to\": \"Harpagon\", \"value\": 7.312553498102598}, {\"arrows\": \"to\", \"color\": \"#ffbb78\", \"from\": \"Frosine\", \"title\": \"130 mots\", \"to\": \"La Fl\\u00e8che\", \"value\": 4.875197323201151}, {\"arrows\": \"to\", \"color\": \"#ffbb78\", \"from\": \"Frosine\", \"title\": \"203 mots\", \"to\": \"Mariane\", \"value\": 5.318119993844216}, {\"arrows\": \"to\", \"color\": \"#ffbb78\", \"from\": \"Frosine\", \"title\": \"10 mots\", \"to\": \"Ma\\u00eetre Jacques\", \"value\": 2.3978952727983707}, {\"arrows\": \"to\", \"color\": \"#1f77b4\", \"from\": \"Harpagon\", \"title\": \"120 mots\", \"to\": \"Anselme\", \"value\": 4.795790545596741}, {\"arrows\": \"to\", \"color\": \"#1f77b4\", \"from\": \"Harpagon\", \"title\": \"27 mots\", \"to\": \"Brindavoine\", \"value\": 3.332204510175204}, {\"arrows\": \"to\", \"color\": \"#1f77b4\", \"from\": \"Harpagon\", \"title\": \"1661 mots\", \"to\": \"Cl\\u00e9ante\", \"value\": 7.415776975415394}, {\"arrows\": \"to\", \"color\": \"#1f77b4\", \"from\": \"Harpagon\", \"title\": \"678 mots\", \"to\": \"Frosine\", \"value\": 6.520621127558696}, {\"arrows\": \"to\", \"color\": \"#1f77b4\", \"from\": \"Harpagon\", \"title\": \"434 mots\", \"to\": \"La Fl\\u00e8che\", \"value\": 6.075346031088684}, {\"arrows\": \"to\", \"color\": \"#1f77b4\", \"from\": \"Harpagon\", \"title\": \"6 mots\", \"to\": \"La Merluche\", \"value\": 1.9459101490553132}, {\"arrows\": \"to\", \"color\": \"#1f77b4\", \"from\": \"Harpagon\", \"title\": \"135 mots\", \"to\": \"Le Commissaire\", \"value\": 4.912654885736052}, {\"arrows\": \"to\", \"color\": \"#1f77b4\", \"from\": \"Harpagon\", \"title\": \"94 mots\", \"to\": \"Mariane\", \"value\": 4.553876891600541}, {\"arrows\": \"to\", \"color\": \"#1f77b4\", \"from\": \"Harpagon\", \"title\": \"677 mots\", \"to\": \"Ma\\u00eetre Jacques\", \"value\": 6.519147287940395}, {\"arrows\": \"to\", \"color\": \"#1f77b4\", \"from\": \"Harpagon\", \"title\": \"51 mots\", \"to\": \"Ma\\u00eetre Simon\", \"value\": 3.9512437185814275}, {\"arrows\": \"to\", \"color\": \"#1f77b4\", \"from\": \"Harpagon\", \"title\": \"1129 mots\", \"to\": \"Val\\u00e8re\", \"value\": 7.029972911706386}, {\"arrows\": \"to\", \"color\": \"#1f77b4\", \"from\": \"Harpagon\", \"title\": \"506 mots\", \"to\": \"\\u00c9lise\", \"value\": 6.2285110035911835}, {\"arrows\": \"to\", \"color\": \"#98df8a\", \"from\": \"La Fl\\u00e8che\", \"title\": \"953 mots\", \"to\": \"Cl\\u00e9ante\", \"value\": 6.860663671448287}, {\"arrows\": \"to\", \"color\": \"#98df8a\", \"from\": \"La Fl\\u00e8che\", \"title\": \"196 mots\", \"to\": \"Frosine\", \"value\": 5.2832037287379885}, {\"arrows\": \"to\", \"color\": \"#98df8a\", \"from\": \"La Fl\\u00e8che\", \"title\": \"258 mots\", \"to\": \"Harpagon\", \"value\": 5.556828061699537}, {\"arrows\": \"to\", \"color\": \"#c49c94\", \"from\": \"La Merluche\", \"title\": \"47 mots\", \"to\": \"Harpagon\", \"value\": 3.8712010109078907}, {\"arrows\": \"to\", \"color\": \"#c5b0d5\", \"from\": \"Le Commissaire\", \"title\": \"113 mots\", \"to\": \"Harpagon\", \"value\": 4.736198448394496}, {\"arrows\": \"to\", \"color\": \"#c5b0d5\", \"from\": \"Le Commissaire\", \"title\": \"148 mots\", \"to\": \"Ma\\u00eetre Jacques\", \"value\": 5.003946305945459}, {\"arrows\": \"to\", \"color\": \"#ff9896\", \"from\": \"Mariane\", \"title\": \"199 mots\", \"to\": \"Anselme\", \"value\": 5.298317366548036}, {\"arrows\": \"to\", \"color\": \"#ff9896\", \"from\": \"Mariane\", \"title\": \"245 mots\", \"to\": \"Cl\\u00e9ante\", \"value\": 5.5053315359323625}, {\"arrows\": \"to\", \"color\": \"#ff9896\", \"from\": \"Mariane\", \"title\": \"231 mots\", \"to\": \"Frosine\", \"value\": 5.44673737166631}, {\"arrows\": \"to\", \"color\": \"#ff9896\", \"from\": \"Mariane\", \"title\": \"163 mots\", \"to\": \"Harpagon\", \"value\": 5.099866427824199}, {\"arrows\": \"to\", \"color\": \"#ff9896\", \"from\": \"Mariane\", \"title\": \"29 mots\", \"to\": \"Val\\u00e8re\", \"value\": 3.4011973816621555}, {\"arrows\": \"to\", \"color\": \"#ff9896\", \"from\": \"Mariane\", \"title\": \"14 mots\", \"to\": \"\\u00c9lise\", \"value\": 2.70805020110221}, {\"arrows\": \"to\", \"color\": \"#2ca02c\", \"from\": \"Ma\\u00eetre Jacques\", \"title\": \"23 mots\", \"to\": \"Anselme\", \"value\": 3.1780538303479458}, {\"arrows\": \"to\", \"color\": \"#2ca02c\", \"from\": \"Ma\\u00eetre Jacques\", \"title\": \"154 mots\", \"to\": \"Cl\\u00e9ante\", \"value\": 5.043425116919247}, {\"arrows\": \"to\", \"color\": \"#2ca02c\", \"from\": \"Ma\\u00eetre Jacques\", \"title\": \"18 mots\", \"to\": \"Frosine\", \"value\": 2.9444389791664403}, {\"arrows\": \"to\", \"color\": \"#2ca02c\", \"from\": \"Ma\\u00eetre Jacques\", \"title\": \"1132 mots\", \"to\": \"Harpagon\", \"value\": 7.0326242610280065}, {\"arrows\": \"to\", \"color\": \"#2ca02c\", \"from\": \"Ma\\u00eetre Jacques\", \"title\": \"8 mots\", \"to\": \"La Merluche\", \"value\": 2.1972245773362196}, {\"arrows\": \"to\", \"color\": \"#2ca02c\", \"from\": \"Ma\\u00eetre Jacques\", \"title\": \"48 mots\", \"to\": \"Le Commissaire\", \"value\": 3.8918202981106265}, {\"arrows\": \"to\", \"color\": \"#2ca02c\", \"from\": \"Ma\\u00eetre Jacques\", \"title\": \"218 mots\", \"to\": \"Val\\u00e8re\", \"value\": 5.389071729816501}, {\"arrows\": \"to\", \"color\": \"#8c564b\", \"from\": \"Ma\\u00eetre Simon\", \"title\": \"194 mots\", \"to\": \"Harpagon\", \"value\": 5.272999558563747}, {\"arrows\": \"to\", \"color\": \"#8c564b\", \"from\": \"Ma\\u00eetre Simon\", \"title\": \"3 mots\", \"to\": \"La Fl\\u00e8che\", \"value\": 1.3862943611198906}, {\"arrows\": \"to\", \"color\": \"#ff7f0e\", \"from\": \"Val\\u00e8re\", \"title\": \"262 mots\", \"to\": \"Anselme\", \"value\": 5.572154032177765}, {\"arrows\": \"to\", \"color\": \"#ff7f0e\", \"from\": \"Val\\u00e8re\", \"title\": \"5 mots\", \"to\": \"Cl\\u00e9ante\", \"value\": 1.791759469228055}, {\"arrows\": \"to\", \"color\": \"#ff7f0e\", \"from\": \"Val\\u00e8re\", \"title\": \"1432 mots\", \"to\": \"Harpagon\", \"value\": 7.267525427828172}, {\"arrows\": \"to\", \"color\": \"#ff7f0e\", \"from\": \"Val\\u00e8re\", \"title\": \"4 mots\", \"to\": \"La Merluche\", \"value\": 1.6094379124341003}, {\"arrows\": \"to\", \"color\": \"#ff7f0e\", \"from\": \"Val\\u00e8re\", \"title\": \"43 mots\", \"to\": \"Mariane\", \"value\": 3.784189633918261}, {\"arrows\": \"to\", \"color\": \"#ff7f0e\", \"from\": \"Val\\u00e8re\", \"title\": \"218 mots\", \"to\": \"Ma\\u00eetre Jacques\", \"value\": 5.389071729816501}, {\"arrows\": \"to\", \"color\": \"#ff7f0e\", \"from\": \"Val\\u00e8re\", \"title\": \"742 mots\", \"to\": \"\\u00c9lise\", \"value\": 6.610696044717759}, {\"arrows\": \"to\", \"color\": \"#d62728\", \"from\": \"\\u00c9lise\", \"title\": \"154 mots\", \"to\": \"Cl\\u00e9ante\", \"value\": 5.043425116919247}, {\"arrows\": \"to\", \"color\": \"#d62728\", \"from\": \"\\u00c9lise\", \"title\": \"10 mots\", \"to\": \"Frosine\", \"value\": 2.3978952727983707}, {\"arrows\": \"to\", \"color\": \"#d62728\", \"from\": \"\\u00c9lise\", \"title\": \"328 mots\", \"to\": \"Harpagon\", \"value\": 5.796057750765372}, {\"arrows\": \"to\", \"color\": \"#d62728\", \"from\": \"\\u00c9lise\", \"title\": \"48 mots\", \"to\": \"Mariane\", \"value\": 3.8918202981106265}, {\"arrows\": \"to\", \"color\": \"#d62728\", \"from\": \"\\u00c9lise\", \"title\": \"514 mots\", \"to\": \"Val\\u00e8re\", \"value\": 6.244166900663736}]);\n",
       "\n",
       "                  nodeColors = {};\n",
       "                  allNodes = nodes.get({ returnType: \"Object\" });\n",
       "                  for (nodeId in allNodes) {\n",
       "                    nodeColors[nodeId] = allNodes[nodeId].color;\n",
       "                  }\n",
       "                  allEdges = edges.get({ returnType: \"Object\" });\n",
       "                  // adding nodes and edges to the graph\n",
       "                  data = {nodes: nodes, edges: edges};\n",
       "\n",
       "                  var options = {\"physics\": {\"solver\": \"repulsion\", \"repulsion\": {\"nodeDistance\": 240, \"springLength\": 180, \"springConstant\": 0.05, \"damping\": 0.12}}, \"edges\": {\"arrows\": {\"to\": {\"enabled\": true}}, \"smooth\": {\"type\": \"dynamic\"}}, \"nodes\": {\"shape\": \"dot\", \"borderWidth\": 1.2}};\n",
       "\n",
       "                  \n",
       "\n",
       "\n",
       "                  \n",
       "\n",
       "                  network = new vis.Network(container, data, options);\n",
       "\n",
       "                  \n",
       "\n",
       "                  \n",
       "\n",
       "                  \n",
       "\n",
       "\n",
       "                  \n",
       "\n",
       "                  return network;\n",
       "\n",
       "              }\n",
       "              drawGraph();\n",
       "        </script>\n",
       "    </body>\n",
       "</html>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Arêtes directionnelles source -> cible : succession des locuteurs par scène\n",
    "def interlocution_edges(df_speeches):\n",
    "    df = df_speeches.copy()\n",
    "    df[\"SceneKey\"] = df[\"Acte\"] + \" | \" + df[\"Scène\"]\n",
    "    df[\"order\"] = range(len(df))\n",
    "    df = df.sort_values([\"SceneKey\", \"order\"])\n",
    "    df[\"next\"] = df.groupby(\"SceneKey\")[\"Personnage\"].shift(-1)\n",
    "\n",
    "    return (df.dropna(subset=[\"next\"])\n",
    "              .groupby([\"Personnage\", \"next\"], as_index=False)[\"Mots\"]\n",
    "              .sum()\n",
    "              .rename(columns={\"Personnage\": \"source\", \"next\": \"target\", \"Mots\": \"weight\"}))\n",
    "\n",
    "# Données\n",
    "totaux = df_speeches.groupby(\"Personnage\")[\"Mots\"].sum()\n",
    "edges_dir = interlocution_edges(df_speeches)\n",
    "\n",
    "# Template + ressources inline (vis.js embarqué)\n",
    "tpl_dir = Path(pyvis.__file__).with_name(\"templates\")\n",
    "env = Environment(loader=FileSystemLoader(tpl_dir))\n",
    "\n",
    "net = Network(\n",
    "    height=\"700px\",\n",
    "    width=\"100%\",\n",
    "    bgcolor=\"#f8f8f8\",\n",
    "    notebook=True,\n",
    "    directed=True,\n",
    "    cdn_resources=\"remote\",\n",
    ")\n",
    "net.template = env.get_template(\"template.html\")\n",
    "\n",
    "# Réglage vis.js : on « écarte » les nœuds avec le solver repulsion\n",
    "# On importe exceptionnellement json ici pour pouvoir travailler les options\n",
    "# directement dans ce format\n",
    "import json\n",
    "\n",
    "options = {\n",
    "    \"physics\": {\n",
    "        \"solver\": \"repulsion\",\n",
    "        \"repulsion\": {\n",
    "            \"nodeDistance\": 240,\n",
    "            \"springLength\": 180,\n",
    "            \"springConstant\": 0.05,\n",
    "            \"damping\": 0.12,\n",
    "        },\n",
    "    },\n",
    "    \"edges\": {\n",
    "        \"arrows\": {\"to\": {\"enabled\": True}},\n",
    "        \"smooth\": {\"type\": \"dynamic\"},\n",
    "    },\n",
    "    \"nodes\": {\n",
    "        \"shape\": \"dot\",\n",
    "        \"borderWidth\": 1.2,\n",
    "    },\n",
    "}\n",
    "\n",
    "net.set_options(json.dumps(options))\n",
    "\n",
    "# Noeuds : label centré dans la bulle (font align center)\n",
    "for n, mots in totaux.items():\n",
    "    net.add_node(\n",
    "        n,\n",
    "        label=n,\n",
    "        title=f\"{mots} mots\",\n",
    "        shape=\"dot\",\n",
    "        size=8 + 0.6 * np.sqrt(mots),\n",
    "        color=mcolors.to_hex(color_map.get(n)) if color_map.get(n) else None,\n",
    "        font={\"size\": 18, \"align\": \"center\", \"color\": \"#111\"},\n",
    "    )\n",
    "\n",
    "# Arêtes : poids log1p, couleur héritée de la source\n",
    "for _, r in edges_dir.iterrows():\n",
    "    if r[\"source\"] == r[\"target\"]:\n",
    "        continue\n",
    "    net.add_edge(\n",
    "        r[\"source\"],\n",
    "        r[\"target\"],\n",
    "        value=np.log1p(r[\"weight\"]),\n",
    "        title=f\"{r['weight']} mots\",\n",
    "        color=net.get_node(r[\"source\"])[\"color\"],\n",
    "    )\n",
    "\n",
    "# On évite l'iframe qui poserait un problème de sécurité (Content Security Policy)\n",
    "html = net.generate_html(notebook=True)\n",
    "HTML(html)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "Ce graphique 3D interactif permet de cliquer sur un nom et de le déplacer afin de faire apparaître toutes les relations. En outre, le survol d'un nom ou de la flèche représentant une relation donnera le nombre de mots associés.\n",
    "\n",
    "La pile logicielle employée par l'OBVIL pour son propre graphique repose sur Sigma et ForceAtlas2, des modules `nodejs` que je ne souhaitais pas exploiter dans ce notebook."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Dans le cas où ce graphique interactif ne s'afficherait pas (si la bibliothèque `pyvis` n'est pas disponible), en voici une capture d'écran :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.display import Image, display\n",
    "\n",
    "display(Image(filename=\"graphe_interlocutions.png\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "## Conclusion\n",
    "\n",
    "Cette étude a révélé que malgré tout le soin que l'on peut apporter au traitement d'un sujet spécifique, il est possible d'introduire involontairement des \"artefacts\" dans les données sur lesquelles on travaille. \n",
    "Ici, il s'agit de différences d'orthographes mineures, invisibles lors d'une lecture par un humain, mais qui peuvent rendre une étude assistée par l'informatique plus complexe, voire sujette aux erreurs.\n",
    "On le répète assez souvent en informatique (et particulièrement en développement web) : on ne doit jamais avoir confiance dans les entrées...\n",
    "Cela a nécessité un travail assez important en amont, et il faut préciser que ce n'est pas infaillible.\n",
    "\n",
    "Une autre source potentielle d'erreur, que ce soit au niveau de l'analyse ou de l'interprétation, consiste en des définitions ou des méthodologies différentes.\n",
    "Ici, nous avons calculé des statistiques divergentes de celles de l'OBVIL, probablement en raison d'une définition différente de ce qu'est une \"ligne\".\n",
    "Pour notre étude, nous considérons qu'une ligne est une suite de 60 caractères, dont les espaces surnuméraires ont été supprimés (incluant les sauts de lignes).\n",
    "\n",
    "Or, ce n'est qu'après une inspection plus poussée du dépôt de l'outil [dramagraph](https://github.com/dramacode/dramagraph/tree/gh-pages) de l'OBLIV révèle la méthode : après \"nettoyage\" des fichiers TEI source par l'emploi d'une [feuille de style XSL](https://github.com/dramacode/dramagraph/blob/gh-pages/naked.xsl), [un autre fichier XSL](https://github.com/dramacode/dramagraph/blob/gh-pages/drama2csv.xsl#L517) est en charge, notamment, du formatage des paragraphes (séparés par des retours de ligne), de la [gestion des accents](https://github.com/dramacode/dramagraph/blob/gh-pages/drama2csv.xsl#L14) et de [la casse](https://github.com/dramacode/dramagraph/blob/gh-pages/drama2csv.xsl#L524), et enfin de la production [des compteurs](https://github.com/dramacode/dramagraph/blob/gh-pages/drama2csv.xsl#L490).\n",
    "\n",
    "Par conséquent, pour retrouver des statistiques identiques à l'OBVIL, il aurait fallut passer par le même _pipeline_.\n",
    "On aurait du choisir d'utiliser le TEI comme fichier source et lui appliquer les mêmes fichiers XSL, ce qui nous aurait donné directement accès aux statistiques, sans avoir besoin de les recalculer nous-même, réduisant considérablement la taille de ce notebook.\n",
    "\n",
    "On en déduit finalement que :\n",
    "\n",
    "- l'enthousiasme est parfois un ennemi ! J'aurai du prendre davantage de temps pour examiner comment l'OBVIL a produit ses statistiques, avant de me lancer dans une étude personnelle\n",
    "- bien que structuré, HTML est un \"produit transformé\" : les fichiers TEI ont manifestement servi comme base à tous les autres formats proposés par l'OBVIL ; j'aurai du l'identifier comme source idéale"
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