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-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# 🗺️ k-NN Corse : Version Interactive avec Clic sur Carte\n",
-    "\n",
-    "## 🎮 Mode d'emploi\n",
-    "1. Exécutez toutes les cellules\n",
-    "2. **Cliquez sur la carte** pour choisir un point\n",
-    "3. Ajustez k avec le curseur\n",
-    "4. Observez la classification en temps réel !"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## 📦 Installation"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Installation des bibliothèques\n",
-    "import sys\n",
-    "!{sys.executable} -m pip install ipyleaflet ipywidgets pandas numpy -q"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import pandas as pd\n",
-    "import numpy as np\n",
-    "import math\n",
-    "from collections import Counter\n",
-    "from ipyleaflet import Map, Marker, CircleMarker, Polyline, AwesomeIcon, LayerGroup\n",
-    "from ipywidgets import HTML, VBox, HBox, IntSlider, Output, Label\n",
-    "from IPython.display import display, clear_output"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## 📊 Chargement des données"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Charger les données\n",
-    "df = pd.read_csv('villages_corse.csv', sep='\\t', encoding='utf-8')\n",
-    "\n",
-    "def parse_coordinates(point_geo_str):\n",
-    "    try:\n",
-    "        parts = str(point_geo_str).split(',')\n",
-    "        lat = float(parts[0].strip())\n",
-    "        lon = float(parts[1].strip())\n",
-    "        return lat, lon\n",
-    "    except:\n",
-    "        return None, None\n",
-    "\n",
-    "df[['latitude', 'longitude']] = df['Point_Geo'].apply(\n",
-    "    lambda x: pd.Series(parse_coordinates(x))\n",
-    ")\n",
-    "\n",
-    "df = df.dropna(subset=['latitude', 'longitude'])\n",
-    "df['dept_simple'] = df['Code Département'].apply(lambda x: '2A' if str(x) == '2A' else '2B')\n",
-    "\n",
-    "print(f\"✅ {len(df)} villages chargés\")\n",
-    "print(f\"   - Corse du Sud (2A) : {len(df[df['dept_simple']=='2A'])}\")\n",
-    "print(f\"   - Haute-Corse (2B) : {len(df[df['dept_simple']=='2B'])}\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## 🧮 Fonctions k-NN"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def haversine_distance(lat1, lon1, lat2, lon2):\n",
-    "    \"\"\"Calcule la distance en km entre deux points GPS.\"\"\"\n",
-    "    R = 6371\n",
-    "    lat1_rad = math.radians(lat1)\n",
-    "    lat2_rad = math.radians(lat2)\n",
-    "    delta_lat = math.radians(lat2 - lat1)\n",
-    "    delta_lon = math.radians(lon2 - lon1)\n",
-    "    \n",
-    "    a = math.sin(delta_lat/2)**2 + math.cos(lat1_rad) * math.cos(lat2_rad) * math.sin(delta_lon/2)**2\n",
-    "    c = 2 * math.asin(math.sqrt(a))\n",
-    "    \n",
-    "    return R * c\n",
-    "\n",
-    "def knn_classify(test_lat, test_lon, df, k=5):\n",
-    "    \"\"\"Classifie un point avec k-NN.\"\"\"\n",
-    "    distances = []\n",
-    "    for idx, row in df.iterrows():\n",
-    "        dist = haversine_distance(test_lat, test_lon, row['latitude'], row['longitude'])\n",
-    "        distances.append({\n",
-    "            'village': row['Nom français'],\n",
-    "            'nom_corse': row['Nom corse'],\n",
-    "            'departement': row['dept_simple'],\n",
-    "            'latitude': row['latitude'],\n",
-    "            'longitude': row['longitude'],\n",
-    "            'distance': dist\n",
-    "        })\n",
-    "    \n",
-    "    dist_df = pd.DataFrame(distances).sort_values('distance')\n",
-    "    neighbors = dist_df.head(k)\n",
-    "    votes = Counter(neighbors['departement'])\n",
-    "    prediction = votes.most_common(1)[0][0]\n",
-    "    \n",
-    "    return prediction, neighbors, votes"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## 🗺️ Carte Interactive\n",
-    "\n",
-    "**Instructions :**\n",
-    "- 🖱️ **Cliquez sur la carte** pour placer un point\n",
-    "- 🎚️ **Ajustez k** avec le curseur\n",
-    "- 👁️ La classification se met à jour automatiquement"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Créer la carte\n",
-    "m = Map(center=(42.15, 9.05), zoom=9, scroll_wheel_zoom=True)\n",
-    "\n",
-    "# Couches pour les éléments dynamiques\n",
-    "test_point_layer = LayerGroup()\n",
-    "neighbors_layer = LayerGroup()\n",
-    "lines_layer = LayerGroup()\n",
-    "\n",
-    "m.add_layer(test_point_layer)\n",
-    "m.add_layer(neighbors_layer)\n",
-    "m.add_layer(lines_layer)\n",
-    "\n",
-    "# Afficher quelques villages de référence\n",
-    "sample_villages = df.sample(n=min(50, len(df)), random_state=42)\n",
-    "for idx, row in sample_villages.iterrows():\n",
-    "    color = 'red' if row['dept_simple'] == '2A' else 'blue'\n",
-    "    circle = CircleMarker(\n",
-    "        location=(row['latitude'], row['longitude']),\n",
-    "        radius=3,\n",
-    "        color=color,\n",
-    "        fill_color=color,\n",
-    "        fill_opacity=0.4,\n",
-    "        weight=1\n",
-    "    )\n",
-    "    m.add_layer(circle)\n",
-    "\n",
-    "# Widget pour k\n",
-    "k_slider = IntSlider(\n",
-    "    value=5,\n",
-    "    min=1,\n",
-    "    max=20,\n",
-    "    step=1,\n",
-    "    description='k:',\n",
-    "    continuous_update=False\n",
-    ")\n",
-    "\n",
-    "# Zone de résultats\n",
-    "result_output = Output()\n",
-    "info_html = HTML(value=\"<p style='font-size:16px; padding:10px; background:#f0f0f0; border-radius:5px;'>👆 <b>Cliquez sur la carte pour classifier un point</b></p>\")\n",
-    "\n",
-    "# Variable globale pour stocker les coordonnées\n",
-    "current_coords = {'lat': None, 'lon': None}\n",
-    "\n",
-    "def update_classification(lat, lon, k):\n",
-    "    \"\"\"Met à jour la classification et la visualisation.\"\"\"\n",
-    "    # Effacer les couches précédentes\n",
-    "    test_point_layer.clear_layers()\n",
-    "    neighbors_layer.clear_layers()\n",
-    "    lines_layer.clear_layers()\n",
-    "    \n",
-    "    # Classification\n",
-    "    prediction, neighbors, votes = knn_classify(lat, lon, df, k=k)\n",
-    "    \n",
-    "    # Couleur selon prédiction\n",
-    "    color = 'red' if prediction == '2A' else 'blue'\n",
-    "    dept_name = 'Corse du Sud (2A)' if prediction == '2A' else 'Haute-Corse (2B)'\n",
-    "    \n",
-    "    # Marqueur du point test\n",
-    "    icon = AwesomeIcon(\n",
-    "        name='star',\n",
-    "        marker_color='darkred' if prediction == '2A' else 'darkblue',\n",
-    "        icon_color='white'\n",
-    "    )\n",
-    "    test_marker = Marker(location=(lat, lon), icon=icon, draggable=False)\n",
-    "    test_point_layer.add_layer(test_marker)\n",
-    "    \n",
-    "    # Afficher les k plus proches voisins\n",
-    "    for idx, neighbor in neighbors.iterrows():\n",
-    "        n_color = 'red' if neighbor['departement'] == '2A' else 'blue'\n",
-    "        \n",
-    "        # Marqueur du voisin\n",
-    "        n_marker = CircleMarker(\n",
-    "            location=(neighbor['latitude'], neighbor['longitude']),\n",
-    "            radius=8,\n",
-    "            color=n_color,\n",
-    "            fill_color=n_color,\n",
-    "            fill_opacity=0.7,\n",
-    "            weight=2\n",
-    "        )\n",
-    "        neighbors_layer.add_layer(n_marker)\n",
-    "        \n",
-    "        # Ligne vers le voisin\n",
-    "        line = Polyline(\n",
-    "            locations=[\n",
-    "                (lat, lon),\n",
-    "                (neighbor['latitude'], neighbor['longitude'])\n",
-    "            ],\n",
-    "            color=n_color,\n",
-    "            weight=2,\n",
-    "            opacity=0.5\n",
-    "        )\n",
-    "        lines_layer.add_layer(line)\n",
-    "    \n",
-    "    # Afficher les résultats\n",
-    "    with result_output:\n",
-    "        clear_output(wait=True)\n",
-    "        print(f\"📍 Coordonnées : ({lat:.4f}, {lon:.4f})\")\n",
-    "        print(f\"🔢 k = {k}\")\n",
-    "        print(f\"\\n🎯 Prédiction : {dept_name}\")\n",
-    "        print(f\"📊 Votes : 2A={votes.get('2A', 0)}, 2B={votes.get('2B', 0)}\")\n",
-    "        print(f\"\\n🏘️ Les {k} plus proches villages :\")\n",
-    "        print(neighbors[['village', 'nom_corse', 'departement', 'distance']].to_string(index=False))\n",
-    "    \n",
-    "    # Mettre à jour l'info\n",
-    "    info_html.value = f\"<div style='font-size:16px; padding:10px; background:{'#ffebee' if prediction=='2A' else '#e3f2fd'}; border-radius:5px; border-left: 4px solid {color};'><b>Classification : {dept_name}</b><br>Votes : 2A={votes.get('2A', 0)}, 2B={votes.get('2B', 0)}</div>\"\n",
-    "\n",
-    "def handle_click(**kwargs):\n",
-    "    \"\"\"Gestionnaire de clic sur la carte.\"\"\"\n",
-    "    if kwargs.get('type') == 'click':\n",
-    "        coords = kwargs.get('coordinates')\n",
-    "        lat, lon = coords\n",
-    "        current_coords['lat'] = lat\n",
-    "        current_coords['lon'] = lon\n",
-    "        update_classification(lat, lon, k_slider.value)\n",
-    "\n",
-    "def on_k_change(change):\n",
-    "    \"\"\"Gestionnaire de changement de k.\"\"\"\n",
-    "    if current_coords['lat'] is not None:\n",
-    "        update_classification(current_coords['lat'], current_coords['lon'], change['new'])\n",
-    "\n",
-    "# Connecter les événements\n",
-    "m.on_interaction(handle_click)\n",
-    "k_slider.observe(on_k_change, names='value')\n",
-    "\n",
-    "# Afficher l'interface\n",
-    "display(VBox([\n",
-    "    info_html,\n",
-    "    HBox([Label('Nombre de voisins (k):'), k_slider]),\n",
-    "    m,\n",
-    "    result_output\n",
-    "]))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## 🎯 Points d'intérêt à tester\n",
-    "\n",
-    "Essayez de cliquer sur ces zones :\n",
-    "\n",
-    "- **Ajaccio** : (41.9267, 8.7369) - Capitale 2A\n",
-    "- **Bastia** : (42.7028, 9.4500) - Préfecture 2B\n",
-    "- **Corte** : (42.3062, 9.1509) - Centre de la Corse\n",
-    "- **Frontière approximative** : Zone entre 42.0 et 42.3 latitude\n",
-    "\n",
-    "### Questions à explorer :\n",
-    "1. 🤔 Où se situe la \"frontière\" k-NN entre les deux départements ?\n",
-    "2. 📊 Comment k influence-t-il la classification près de cette frontière ?\n",
-    "3. 🏔️ Y a-t-il des zones ambiguës où le résultat change souvent ?"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## 💡 Mode manuel (si la carte ne fonctionne pas)\n",
-    "\n",
-    "Si le clic sur carte ne fonctionne pas, utilisez cette cellule :"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Mode manuel : entrez les coordonnées\n",
-    "test_lat = 42.3  # Modifiez ici\n",
-    "test_lon = 9.15  # Modifiez ici\n",
-    "k = 5\n",
-    "\n",
-    "prediction, neighbors, votes = knn_classify(test_lat, test_lon, df, k=k)\n",
-    "dept_name = 'Corse du Sud (2A)' if prediction == '2A' else 'Haute-Corse (2B)'\n",
-    "\n",
-    "print(f\"📍 Point : ({test_lat}, {test_lon})\")\n",
-    "print(f\"🎯 Prédiction : {dept_name}\")\n",
-    "print(f\"📊 Votes : {dict(votes)}\")\n",
-    "print(f\"\\n🏘️ Les {k} plus proches villages :\")\n",
-    "print(neighbors[['village', 'nom_corse', 'departement', 'distance']].to_string(index=False))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## 📝 Notes techniques\n",
-    "\n",
-    "Cette version utilise **ipyleaflet** qui offre une vraie interactivité bidirectionnelle entre Python et JavaScript dans Jupyter.\n",
-    "\n",
-    "**Avantages :**\n",
-    "- ✅ Clic directement sur la carte\n",
-    "- ✅ Mise à jour en temps réel\n",
-    "- ✅ Curseur interactif pour k\n",
-    "- ✅ Pas besoin de recharger\n",
-    "\n",
-    "**Prérequis :**\n",
-    "- Jupyter Notebook ou JupyterLab\n",
-    "- Extension widgets activée : `jupyter nbextension enable --py widgetsnbextension`"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.8.0"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}