{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c24846e6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Préparation commune des TP Python\n",
    "# Le notebook utilise uniquement les ressources fournies dans le dossier codes/.\n",
    "from pathlib import Path\n",
    "import importlib.util\n",
    "import subprocess\n",
    "import sys\n",
    "\n",
    "REQUIRED_PACKAGES = {'numpy': 'numpy', 'pandas': 'pandas', 'matplotlib': 'matplotlib'}\n",
    "missing = [package for module, package in REQUIRED_PACKAGES.items()\n",
    "           if importlib.util.find_spec(module) is None]\n",
    "if missing:\n",
    "    print(\"Installation des paquets manquants :\", \", \".join(missing))\n",
    "    subprocess.check_call([sys.executable, \"-m\", \"pip\", \"install\", *missing])\n",
    "\n",
    "WORKDIR = Path.cwd().resolve()\n",
    "CODES_DIR = WORKDIR.parent if WORKDIR.name == \"correction\" else WORKDIR\n",
    "TOOLBOX_DIR = CODES_DIR / \"toolbox\"\n",
    "DATA_DIR = CODES_DIR / \"data\"\n",
    "if not CODES_DIR.is_dir():\n",
    "    raise FileNotFoundError(\"Exécutez le notebook depuis le dossier codes/.\" )\n",
    "if TOOLBOX_DIR.is_dir():\n",
    "    sys.path.insert(0, str(TOOLBOX_DIR))\n",
    "\n",
    "DICE_FILE = TOOLBOX_DIR / \"DICE.py\"\n",
    "if not DICE_FILE.is_file():\n",
    "    raise FileNotFoundError(\n",
    "        f\"Module du cours introuvable : {DICE_FILE}. \"\n",
    "        \"Téléchargez le dossier codes complet, avec toolbox/.\"\n",
    "    )\n",
    "\n",
    "DATA_FILE = DATA_DIR / \"SSP_scenarios.csv\"\n",
    "if not DATA_FILE.is_file():\n",
    "    raise FileNotFoundError(\n",
    "        f\"Donnée du cours introuvable : {DATA_FILE}. \"\n",
    "        \"Téléchargez le dossier codes complet, avec data/.\"\n",
    "    )\n",
    "\n",
    "print(\"Environnement prêt :\", CODES_DIR)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "85d582d0",
   "metadata": {},
   "source": [
    "# TP3 — Génération de scénarios physiques SSP\n",
    "\n",
    "**Date de la séance :** mercredi 9 septembre 2026, 08:30–10:30\n",
    "\n",
    "**Objectifs**\n",
    "- Manipuler les scénarios SSP (Shared Socioeconomic Pathways)\n",
    "- Simuler plusieurs scénarios physiques avec DICE\n",
    "- Calculer des probabilités de dépassement de seuils de température\n",
    "- Identifier les années de dépassement de +1,5°C et +2°C selon le scénario\n",
    "\n",
    "**Prérequis** : TP2 (prise en main de DICE)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4e7d84fd",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np, pandas as pd, matplotlib.pyplot as plt\n",
    "import DICE"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0f274179",
   "metadata": {},
   "source": [
    "## Partie 1 — Scénarios SSP"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a5fc8975",
   "metadata": {},
   "source": [
    "**Question 1.** Chargez le fichier SSP_scenarios.csv. Affichez les premières lignes et les colonnes disponibles."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "97aebfaa",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_ssp = pd.read_csv(DATA_DIR / \"SSP_scenarios.csv\")\n",
    "# YOUR CODE HERE to display"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7ec0acd9",
   "metadata": {},
   "source": [
    "## Partie 2 — Simulation des scénarios SSP avec DICE"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "797fa27c",
   "metadata": {},
   "source": [
    "**Question 2.** Simulez trois scénarios avec DICE en faisant varier les paramètres :\n",
    "- SSP1 (soutenabilité) : `gA=0.04`, `Linf=8500`, `gsig=0.025`\n",
    "- SSP2 (référence) : paramètres par défaut\n",
    "- SSP5 (fossile) : `gA=0.10`, `Linf=12000`, `gsig=0.008`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ac0c3d60",
   "metadata": {},
   "outputs": [],
   "source": [
    "ssp_params = {\n",
    "    'SSP1': dict(gA=0.04, Linf=8500, gsig=0.025),\n",
    "    'SSP2': dict(),  # default\n",
    "    'SSP5': dict(gA=0.10, Linf=12000, gsig=0.008)\n",
    "}\n",
    "ssp_paths = {}\n",
    "for name, kwargs in ssp_params.items():\n",
    "    p = DICE.Params(**kwargs)\n",
    "    path = DICE.init_states(p)\n",
    "    timevec = range(1, p.nT)\n",
    "    path[1:, p.i_mu] = 0.03\n",
    "    path = DICE.update_path(path, timevec, p)\n",
    "    ssp_paths[name] = (p, path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "82c2d78f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# YOUR CODE HERE: tracez les trajectoires T_AT pour SSP1, SSP2, SSP5"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a0d8ddb8",
   "metadata": {},
   "source": [
    "**Question 3.** Calculez la probabilité de dépasser +1,5°C, +2°C et +3°C en 2100 pour chaque scénario (à ce stade, avec 3 scénarios déterministes, la 'probabilité' est 0 ou 1 — discutez pourquoi une vraie distribution nécessite Monte Carlo)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6c0e80d8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# YOUR CODE HERE"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f5633ee8",
   "metadata": {},
   "source": [
    "## Partie 3 — Analyse des risques chroniques et aigus"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c81fe562",
   "metadata": {},
   "source": [
    "**Question 4.** Pour chaque scénario, calculez la première année de dépassement de +1,5°C et de +2°C. Présentez les résultats dans un tableau."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d3e91833",
   "metadata": {},
   "outputs": [],
   "source": [
    "# YOUR CODE HERE"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7bb11508",
   "metadata": {},
   "source": [
    "## Interprétation"
   ]
  }
 ],
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