{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "db0bcf0c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "C-index: 0.6160477453580901\n"
     ]
    }
   ],
   "source": [
    "#deepseek_c_index kyr 2025-5-5\n",
    "\n",
    "import json\n",
    "import re\n",
    "from lifelines.utils import concordance_index\n",
    "\n",
    "\n",
    "def load_json_data(file_path):\n",
    "    with open(file_path, 'r') as file:\n",
    "        data = json.load(file)\n",
    "    return data\n",
    "\n",
    "def extract_ground_state(ground_truth):\n",
    "    match = re.search(r\"state is ###\\s*(.*?)\\s*###.*?time is ###\\s*(\\d+\\.?\\d*)\\s*###\", ground_truth)\n",
    "    if match:\n",
    "        ground_state = match.group(1).strip()  \n",
    "    else:\n",
    "        raise ValueError(f\"Could not extract ground truth values from: {ground_truth}\")\n",
    "    \n",
    "    return ground_state\n",
    "\n",
    "def extract_ground_time(ground_truth):\n",
    "    match = re.search(r\"state is ###\\s*(.*?)\\s*###.*?time is ###\\s*(\\d+\\.?\\d*)\\s*###\", ground_truth)\n",
    "    if match:\n",
    "        ground_time = float(match.group(2).strip())  \n",
    "    else:\n",
    "        raise ValueError(f\"Could not extract ground truth values from: {ground_truth}\")\n",
    "    \n",
    "    return ground_time\n",
    "\n",
    "def extract_predict_state(predicted_texts):\n",
    "    match = re.search(r\"(?:state|statu)\\s*is\\s*###\\s*(.*?)\\s*###.*?time\\s*is\\s*###\\s*(\\d+\\.?\\d*)\\s*###\", predicted_texts)\n",
    "    if match:\n",
    "        pred_state = match.group(1).strip()  \n",
    "    else:\n",
    "        raise ValueError(f\"Could not extract values from output: {predicted_texts}\")\n",
    "\n",
    "    return pred_state\n",
    "\n",
    "def extract_predict_time(predicted_texts):\n",
    "    match = re.search(r\"(?:state|statu)\\s*is\\s*###\\s*(.*?)\\s*###.*?time\\s*is\\s*###\\s*(\\d+\\.?\\d*)\\s*###\", predicted_texts)\n",
    "    if match:\n",
    "        pred_time = float(match.group(2).strip())  \n",
    "    else:\n",
    "        raise ValueError(f\"Could not extract values from output: {predicted_texts}\")\n",
    "    \n",
    "    return pred_time\n",
    "\n",
    "true_data = load_json_data('/home/kongyiran/work/Dataset/Dataset_0429/Qwen2_5vl/0427_json/DFS/test_DFS_0427.json')  # 真实值文件路径\n",
    "predicted_data = load_json_data('/home/kongyiran/work/deepseek_infer/Deepseek_v1/deepseek_response-kyr-DFS-0407.json')  # 预测值文件路径\n",
    "\n",
    "event_true_state = []\n",
    "event_true_times = []\n",
    "\n",
    "event_predicted_state = []\n",
    "event_predicted_times = []\n",
    "\n",
    "for i in range(len(true_data)):\n",
    "    ground_truth =   true_data[i]['conversations'][1]['value']\n",
    "    predicted_texts =  predicted_data[i]\n",
    "    \n",
    "\n",
    "    if not predicted_texts:\n",
    "        continue\n",
    "    \n",
    "    true_state = extract_ground_state(ground_truth)\n",
    "    true_times = extract_ground_time(ground_truth)\n",
    "    \n",
    "    binary_true_state = 1 if true_state == \"dead\" else 0\n",
    "    \n",
    "    event_true_state.append(binary_true_state)\n",
    "    event_true_times.append(true_times)\n",
    "    \n",
    "    \n",
    "    predicted_state = extract_predict_state(predicted_texts)\n",
    "    predicted_times = extract_predict_time(predicted_texts)\n",
    "    \n",
    "    binary_predicted_state = 1 if true_state == \"dead\" else 0\n",
    "    \n",
    "    event_predicted_state.append(binary_predicted_state)\n",
    "    event_predicted_times.append(predicted_times)\n",
    "    \n",
    "c_index = concordance_index(event_true_times, event_predicted_times , event_true_state)\n",
    "\n",
    "print(\"C-index:\", c_index)\n"
   ]
  }
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