Flappy Bird/Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2f6d0e6e",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "6241bc34",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import os\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Define the base directory paths\n",
    "base_dirs = ['GPT-3.5', 'GPT-4'] \n",
    "\n",
    "counts = []\n",
    "methods = []\n",
    "\n",
    "# Create variables to store the total count\n",
    "total_count = 0\n",
    "\n",
    "# Iterate over base directories\n",
    "for base_dir in base_dirs:\n",
    "    # Fetch the subfolders (methods)\n",
    "    base_methods = [name for name in os.listdir(base_dir) if os.path.isdir(os.path.join(base_dir, name))]\n",
    "    \n",
    "    # Iterate over methods\n",
    "    for method in base_methods:\n",
    "        # Skip if the method is exactly 'GPT-3.5' or 'GPT-4'\n",
    "        if method == 'GPT-3.5' or method == 'GPT-4':\n",
    "            continue\n",
    "            \n",
    "        method_path = os.path.join(base_dir, method)\n",
    "        count = 0\n",
    "        # Iterate over subfolders of a method\n",
    "        for subdir in os.listdir(method_path):\n",
    "            subdir_path = os.path.join(method_path, subdir)\n",
    "            # If subdir is a directory\n",
    "            if os.path.isdir(subdir_path):\n",
    "                # If \"session\" is part of the subfolder name\n",
    "                if \"session\" in subdir:\n",
    "                    count += 1\n",
    "                # If it contains a file named \"observations.txt\"\n",
    "                elif \"observations.txt\" in os.listdir(subdir_path):\n",
    "                    count += 1\n",
    "        # append method name with the respective base_dir name\n",
    "        methods.append(f\"{method}-{base_dir}\")\n",
    "        counts.append(count)\n",
    "        \n",
    "        \n",
    "        # Increment the total count\n",
    "        total_count += count\n",
    "\n",
    "plt.figure(figsize=(15, 10))\n",
    "# Plotting\n",
    "plt.bar(methods, counts)\n",
    "plt.xticks(rotation=90)  # Rotate labels 45 degrees\n",
    "plt.xlabel('Methods')\n",
    "plt.ylabel('Number of subfolders with \"session\" or \"observations.txt\"')\n",
    "plt.title('Distribution of relevant subfolders')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "05721610",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "35"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "fe178524",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import os\n",
    "import difflib\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "root_dirs = ['GPT-3.5', 'GPT-4']\n",
    "\n",
    "# Get list of all .py files and their reduced names\n",
    "py_files = []\n",
    "reduced_file_names = []\n",
    "for root_dir in root_dirs:\n",
    "    for foldername, subfolders, filenames in os.walk(root_dir):\n",
    "        for filename in filenames:\n",
    "            if filename.endswith('.py'):\n",
    "                filepath = os.path.join(foldername, filename)\n",
    "                py_files.append(filepath)\n",
    "\n",
    "                # Split the file path and keep only the parts you need\n",
    "                path_parts = filepath.split(os.path.sep)\n",
    "                # Add the directory name as postfix\n",
    "                reduced_filepath = \"-\".join(path_parts[1:3]) + '-' + root_dir\n",
    "                reduced_file_names.append(reduced_filepath)\n",
    "\n",
    "# Store contents of each file\n",
    "file_contents = {}\n",
    "\n",
    "for py_file in py_files:\n",
    "    with open(py_file, 'r') as f:\n",
    "        file_contents[py_file] = f.readlines()\n",
    "\n",
    "# Create a 2D list to store the similarity ratios\n",
    "similarity_matrix = np.zeros((len(py_files), len(py_files)))\n",
    "\n",
    "# Compare each file to every other file\n",
    "for i in range(len(py_files)):\n",
    "    for j in range(i + 1, len(py_files)):\n",
    "        file1 = file_contents[py_files[i]]\n",
    "        file2 = file_contents[py_files[j]]\n",
    "        similarity = difflib.SequenceMatcher(None, file1, file2).ratio()\n",
    "        similarity_matrix[i][j] = similarity\n",
    "        similarity_matrix[j][i] = similarity  # Because the matrix is symmetric\n",
    "\n",
    "plt.figure(figsize=(10, 10))\n",
    "# Plot the heatmap\n",
    "plt.imshow(similarity_matrix, cmap='hot', interpolation='nearest')\n",
    "plt.colorbar(label='Similarity')\n",
    "plt.title(\"Similarity Heatmap\")\n",
    "plt.xticks(ticks=range(len(reduced_file_names)), labels=reduced_file_names, rotation='vertical')\n",
    "plt.yticks(ticks=range(len(reduced_file_names)), labels=reduced_file_names)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "49dc5bd4",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-4-d585b1c3315e>:50: ClusterWarning: scipy.cluster: The symmetric non-negative hollow observation matrix looks suspiciously like an uncondensed distance matrix\n",
      "  linkage_matrix = linkage(similarity_df)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936x936 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import os\n",
    "import difflib\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy.cluster.hierarchy import linkage\n",
    "from seaborn import clustermap\n",
    "import pandas as pd\n",
    "\n",
    "root_dirs = ['GPT-3.5', 'GPT-4']\n",
    "\n",
    "# Get list of all .py files and their reduced names\n",
    "py_files = []\n",
    "reduced_file_names = []\n",
    "for root_dir in root_dirs:\n",
    "    for foldername, subfolders, filenames in os.walk(root_dir):\n",
    "        for filename in filenames:\n",
    "            if filename.endswith('.py'):\n",
    "                filepath = os.path.join(foldername, filename)\n",
    "                py_files.append(filepath)\n",
    "\n",
    "                # Split the file path and keep only the parts you need\n",
    "                path_parts = filepath.split(os.path.sep)\n",
    "                # Add the directory name as postfix\n",
    "                reduced_filepath = \"-\".join(path_parts[1:3]) + '-' + root_dir\n",
    "                reduced_file_names.append(reduced_filepath)\n",
    "\n",
    "# Store contents of each file\n",
    "file_contents = {}\n",
    "\n",
    "for py_file in py_files:\n",
    "    with open(py_file, 'r') as f:\n",
    "        file_contents[py_file] = f.readlines()\n",
    "\n",
    "# Create a 2D list to store the similarity ratios\n",
    "similarity_matrix = np.zeros((len(py_files), len(py_files)))\n",
    "\n",
    "# Compare each file to every other file\n",
    "for i in range(len(py_files)):\n",
    "    for j in range(i + 1, len(py_files)):\n",
    "        file1 = file_contents[py_files[i]]\n",
    "        file2 = file_contents[py_files[j]]\n",
    "        similarity = difflib.SequenceMatcher(None, file1, file2).ratio()\n",
    "        similarity_matrix[i][j] = similarity\n",
    "        similarity_matrix[j][i] = similarity  # Because the matrix is symmetric\n",
    "\n",
    "# Convert similarity matrix to DataFrame\n",
    "similarity_df = pd.DataFrame(similarity_matrix, index=reduced_file_names, columns=reduced_file_names)\n",
    "\n",
    "# Generate a linkage matrix\n",
    "linkage_matrix = linkage(similarity_df)\n",
    "\n",
    "# Plot the heatmap with dendrograms\n",
    "clustermap(similarity_df, cmap='hot', linewidths=.5, figsize=(13, 13),\n",
    "            row_linkage=linkage_matrix, col_linkage=linkage_matrix)\n",
    "plt.title(\"Similarity Heatmap with Dendrogram\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "1a813af4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936x936 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from scipy.spatial.distance import squareform\n",
    "\n",
    "# Convert similarity matrix to a distance matrix\n",
    "distance_matrix = 1.0 - similarity_matrix\n",
    "\n",
    "# Ensure diagonal is zero\n",
    "np.fill_diagonal(distance_matrix, 0)\n",
    "\n",
    "# Convert to a condensed distance matrix\n",
    "condensed_dist_matrix = squareform(distance_matrix)\n",
    "\n",
    "# Generate a linkage matrix\n",
    "linkage_matrix = linkage(condensed_dist_matrix, method='average')\n",
    "\n",
    "# Convert distance matrix to DataFrame\n",
    "distance_df = pd.DataFrame(distance_matrix, index=reduced_file_names, columns=reduced_file_names)\n",
    "\n",
    "# Plot the heatmap with dendrograms\n",
    "clustermap(distance_df, cmap='hot_r', linewidths=.5, figsize=(13, 13),\n",
    "            row_linkage=linkage_matrix, col_linkage=linkage_matrix)\n",
    "plt.title(\"Distance Heatmap with Dendrogram\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "22bae889",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Skipping GPT-3.5/1st method/API/code/code_7.py due to a syntax error.\n",
      "Common classes:\n",
      "Pipe: 28\n",
      "Bird: 20\n",
      "Cloud: 8\n",
      "Base: 4\n",
      "Game: 2\n",
      "FlappyBird: 1\n",
      "\n",
      "Common functions:\n",
      "__init__: 63\n",
      "update: 49\n",
      "draw: 20\n",
      "is_offscreen: 15\n",
      "check_collision: 12\n",
      "load_high_score: 12\n",
      "jump: 12\n",
      "draw_pipes: 12\n",
      "move: 12\n",
      "game_over: 11\n",
      "save_high_score: 11\n",
      "move_pipes: 10\n",
      "flap: 8\n",
      "start_game: 8\n",
      "spawn_pipe: 8\n",
      "collide: 7\n",
      "check_boundaries: 7\n",
      "generate_pipes: 6\n",
      "display_score: 6\n",
      "start_screen: 6\n",
      "draw_bird: 6\n",
      "main: 6\n",
      "create_pipe: 6\n",
      "draw_text: 5\n",
      "update_score: 5\n",
      "game_loop: 5\n",
      "draw_base: 5\n",
      "show_start_screen: 4\n",
      "show_game_over_screen: 4\n",
      "game_over_screen: 4\n",
      "restart_game: 4\n",
      "draw_start_screen: 4\n",
      "draw_game_over_screen: 4\n",
      "show_score: 4\n",
      "display_high_score: 3\n",
      "update_high_score: 3\n",
      "draw_score: 3\n",
      "check_collisions: 3\n",
      "update_highscore: 3\n",
      "move_bird: 2\n",
      "collides_with_bird: 2\n",
      "check_score: 2\n",
      "load_highscore: 2\n",
      "save_highscore: 2\n",
      "draw_background: 2\n",
      "get_mask: 2\n",
      "show_highscore: 2\n",
      "run: 2\n",
      "start: 2\n",
      "get_high_score: 2\n",
      "display_bird: 1\n",
      "display_pipe: 1\n",
      "game: 1\n",
      "has_passed_bird: 1\n",
      "passed_bird: 1\n",
      "reset_game: 1\n",
      "check_passed: 1\n",
      "show_game_over: 1\n",
      "draw_high_score: 1\n",
      "collided: 1\n",
      "chat_with_gpt: 1\n",
      "save_code: 1\n",
      "draw_window: 1\n",
      "draw_objects: 1\n",
      "get_passed: 1\n",
      "bird_flap: 1\n",
      "bird_collision: 1\n",
      "update_pipes: 1\n",
      "collides_with: 1\n",
      "show_high_score: 1\n",
      "is_collision: 1\n",
      "flappy_bird: 1\n",
      "collision_detection: 1\n",
      "draw_pipe: 1\n",
      "new_pipe: 1\n",
      "display_highscore: 1\n",
      "display_game_over: 1\n",
      "updateWalls: 1\n",
      "birdUpdate: 1\n",
      "show_message: 1\n",
      "is_off_screen: 1\n",
      "handle_input: 1\n",
      "set_height: 1\n",
      "set_high_score: 1\n",
      "get_width: 1\n",
      "get_height: 1\n",
      "detect_collision: 1\n",
      "\n",
      "Lines of code:\n",
      "GPT-3.5/2nd method/2nd session/code/Flappy_Bird.py: 257\n",
      "GPT-3.5/5th method/7th session/code/Flappy_Bird.py: 257\n",
      "GPT-4/1st method/5th session-GPT4/code/Flappy_Bird.py: 254\n",
      "GPT-3.5/1st method/API/code/code_7.py: 241\n",
      "GPT-3.5/5th method/5th session/code/Flappy_Bird.py: 240\n",
      "GPT-3.5/1st method/1st session/code/Flappy_Bird.py: 240\n",
      "GPT-3.5/1st method/4th session/code/Flappy_Bird_2.py: 222\n",
      "GPT-3.5/5th method/6th session/code/Flappy_Bird.py: 221\n",
      "GPT-3.5/1st method/2nd session/code/Flappy_Bird.py: 219\n",
      "GPT-3.5/5th method/8th session/code/Flappy_Bird.py: 210\n",
      "GPT-3.5/5th method/3rd session/code/Flappy_Bird.py: 208\n",
      "GPT-3.5/5th method/4th session/code/Flappy_Bird.py: 205\n",
      "GPT-4/5th method/1st session/code/Flappy_Bird.py: 201\n",
      "GPT-3.5/1st method/4th session/code/Flappy_Bird.py: 195\n",
      "GPT-3.5/1st method/5th session/code/Flappy_Bird_3.py: 190\n",
      "GPT-3.5/1st method/6th session/code/Flappy_Bird.py: 190\n",
      "GPT-3.5/1st method/3rd session/code/Flappy_Bird.py: 189\n",
      "GPT-3.5/2nd method/1st session/code/Flappy_Bird.py: 187\n",
      "GPT-3.5/1st method/API/code/code_13.py: 187\n",
      "GPT-3.5/1st method/8th session/code/Flappy_Bird.py: 186\n",
      "GPT-3.5/1st method/5th session/code/Flappy_Bird.py: 186\n",
      "GPT-3.5/3rd method/1st session/code/Flappy_Bird.py: 180\n",
      "GPT-3.5/5th method/1st session/code/Flappy_Bird.py: 179\n",
      "GPT-3.5/3rd method/3rd session/code/Flappy_Bird.py: 174\n",
      "GPT-4/t = 0/1st session/Flappy_Bird_t=0.py: 174\n",
      "GPT-4/1st method/1st session-GPT3.5/code/Flappy_Bird.py: 172\n",
      "GPT-3.5/1st method/API/code/code_2.py: 170\n",
      "GPT-4/3rd method/1st session/code/Flappy_Bird.py: 170\n",
      "GPT-3.5/1st method/API/code/code_10.py: 169\n",
      "GPT-3.5/4th method/1st session/code/Flappy_Bird.py: 169\n",
      "GPT-3.5/2nd method/3rd session/code/Flappy_Bird.py: 168\n",
      "GPT-4/1st method/2nd session-GPT3.5/code/Flappy_Bird.py: 168\n",
      "GPT-3.5/1st method/7th session/code/Flappy_Bird_2.py: 165\n",
      "GPT-3.5/1st method/7th session/code/Flappy_Bird.py: 165\n",
      "GPT-3.5/1st method/API/code/code_14.py: 165\n",
      "GPT-3.5/1st method/API/code/code_6.py: 161\n",
      "GPT-3.5/4th method/2nd session/code/Flappy_Bird.py: 161\n",
      "GPT-4/1st method/4th session-GPT4/code/Flappy_Bird.py: 160\n",
      "GPT-3.5/1st method/API/code/code_4.py: 156\n",
      "GPT-3.5/1st method/API/code/code_12.py: 152\n",
      "GPT-3.5/1st method/API/code/code_3.py: 149\n",
      "GPT-3.5/2nd method/4th session/code/Flappy_Bird.py: 147\n",
      "GPT-3.5/1st method/API/code/code_11.py: 146\n",
      "GPT-3.5/1st method/API/code/code_5.py: 145\n",
      "GPT-4/1st method/3rd session-GPT3.5/code/Flappy_Bird.py: 144\n",
      "GPT-3.5/1st method/API/code/code_1.py: 139\n",
      "GPT-3.5/1st method/API/code/code_0.py: 131\n",
      "GPT-3.5/1st method/API/code/code_8.py: 120\n",
      "GPT-4/3rd method/2nd session/code/Flappy_Bird.py: 113\n",
      "GPT-3.5/1st method/API/code/code_9.py: 100\n",
      "GPT-3.5/left_to_right/1st session/code/Flappy_Bird.py: 78\n",
      "GPT-3.5/3rd method/2nd session/code/Flappy_Bird.py: 77\n",
      "GPT-3.5/5th method/2nd session/code/Flappy_Bird.py: 63\n",
      "GPT-3.5/1st method/API/API.py: 57\n",
      "GPT-4/1st method/1st session-GPT3.5/code/tempCodeRunnerFile.py: 1\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import ast\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "root_dirs = ['GPT-3.5', 'GPT-4']\n",
    "\n",
    "# Get list of all .py files\n",
    "py_files = []\n",
    "for root_dir in root_dirs:\n",
    "    for foldername, subfolders, filenames in os.walk(root_dir):\n",
    "        for filename in filenames:\n",
    "            if filename.endswith('.py'):\n",
    "                filepath = os.path.join(foldername, filename)\n",
    "                py_files.append(filepath)\n",
    "\n",
    "# Analyze each file\n",
    "common_classes = {}\n",
    "common_functions = {}\n",
    "lines_of_code = {}\n",
    "\n",
    "for py_file in py_files:\n",
    "    with open(py_file, 'r') as f:\n",
    "        file_content = f.read()\n",
    "\n",
    "    # Calculate lines of code\n",
    "    lines_of_code[py_file] = len(file_content.split('\\n'))\n",
    "\n",
    "    # Parse the file content to an AST\n",
    "    try:\n",
    "        tree = ast.parse(file_content)\n",
    "\n",
    "        # Iterate over all nodes in the AST, and collect classes and functions\n",
    "        for node in ast.walk(tree):\n",
    "            if isinstance(node, ast.ClassDef):  # Class definition\n",
    "                class_name = node.name\n",
    "                common_classes[class_name] = common_classes.get(class_name, 0) + 1\n",
    "            elif isinstance(node, ast.FunctionDef):  # Function definition\n",
    "                function_name = node.name\n",
    "                common_functions[function_name] = common_functions.get(function_name, 0) + 1\n",
    "    except SyntaxError:\n",
    "        print(f\"Skipping {py_file} due to a syntax error.\")\n",
    "\n",
    "# Print common classes and functions\n",
    "print(\"Common classes:\")\n",
    "for class_name, count in sorted(common_classes.items(), key=lambda x: -x[1]):\n",
    "    print(f\"{class_name}: {count}\")\n",
    "\n",
    "print(\"\\nCommon functions:\")\n",
    "for function_name, count in sorted(common_functions.items(), key=lambda x: -x[1]):\n",
    "    print(f\"{function_name}: {count}\")\n",
    "\n",
    "print(\"\\nLines of code:\")\n",
    "for file, loc in sorted(lines_of_code.items(), key=lambda x: -x[1]):\n",
    "    print(f\"{file}: {loc}\")\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "b52b7fac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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M8up2PzOBJwHXDGoPaL7pHjgYYOPNt1qBl0OSJEmShrYiI1gPVNWs9meoqQ4b0dxq9irgMzz2m++/X1V3VdUDwLeA3dvyW6rqx+3yCcDuVVXAfwIHJtkY2JXm9rkD9qqqbYHnAUe3310y2CVVdWO7vCdwUlUtq6pfAecM1Tm/6V6SJElSV7r4HqwPA+e2yc8raO7INKAG1a3llB8LHAi8ATh1qOuoqurnwO00I1OD+W32kiRJkvqmiwRrI+CX7fJBg9a9KMkTkqxDc/fBgVGrpybZtV1+I3ABQDvS9CvgcJpk6w8keSLNHZluXk5c5wH7J1kzyRbAXivaIUmSJElaFV18D9a/A8cnORz4zqB1lwDfBLYCTqiq+e0dCK8H3tFef3UNj/1ixxOBzarq2kFtndveMn4t4LCqun05cZ0O7N22/38033wvSdKUs/m60zhsh+n9DkOSpoTlJlhV9QfXOlXVPGBeu3wR8Kye1Yf3LP+iqvYdotmlVXXgMLvcHfjyoP3NWF58vTG1zwt453DbSZIkSVLXuhjB6kySy2iuo/rHfsciSZIkSStr1BKsqjoOOG6I8ptobt0+1DY7jVY8kiRJkjTaurjJhSRJkiQJEyxJkiRJ6owJliRJkiR1ZFzd5EKSJHXvtvuXcuSCxf0Ooy+8Pb2kseYIliRJkiR1xARLkiRJkjpigiVJkiRJHTHBkiRJkqSOmGBJkiRJUkdMsCRJkiSpIyZYkiRJktQREyxJkiRJ6ogJliRJkiR1xARLkiRJkjoyrd8BjCebrzuNw3aY3u8wJEmSJE1QjmBJkjSKksxIcl2S45L8NMmJSfZJ8uMkP0uyS5InJPl2koVJfpJkuyRrJLkpycY9bf0syZOSbJbkm0kubX9262MXJUk9HMGSJGn0bQ28FngbcCnwRmB34M+BfwZuARZU1b5J9ga+XlWzkpwBvAo4NskfAzdX1e1J/gv4TFVdkOSpwPeA5/TuMMnBwMEAG2++1Zh0UpJkgiVJ0li4saoWASS5GvhhVVWSRcAM4GnAawCq6pwkmybZEDgF+BfgWOD17XOAfYCZSQba3zDJ+lV170BBVc0F5gJsNXNWjXL/JEktEyxJkkbfQz3Lj/Y8f5TmWPzIMNtdBGydZDNgX+AjbfkawPOr6sHuQ5UkrQ6vwZIkqf/OBw4ASDIHWFxVv62qAk4HPg1cW1V3tfXPBt41sHGSWWMZrCRpeI5gSZLUf0cAX0uyELgfeEvPulNorts6qKfs3cAxbf1pwHnA28ckUknSiEywJEkaRVV1E7Btz/ODhlm37zDbzwcyqGwxsH+ngUqSOuEUQUmSJEnqiAmWJEmSJHXEBEuSJEmSOmKCJUmSJEkd8SYXPW67fylHLlg8au0ftsP0UWtbkiRJUv85giVJkiRJHTHBkiRJkqSOmGBJkiRJUke8BkuSpElu83WneR2wJI0RR7AkSZIkqSMmWJIkSZLUERMsSZIkSeqICZYkSZIkdcQES5IkSZI64l0EJUma5G67fylHLljc7zD6wrsnShprjmBJkiRJUkdMsCRJkiSpIyZYkiRJktQREyxJkiRJ6ogJliRJkiR1xARLkiRJkjpigiVJkiRJHTHBkiRJkqSO9D3BSvKkJP+V5IYklyW5KMmr+h2XJEmSJK2sviZYSQJ8Gzivqp5RVTsBrwe26mdckiRJkrQq+j2CtTfwcFV9aaCgqm6uqs8nmZHk/CSXtz8vAEgyJ8mPkpzRjnodmeSAJJckWZTkj9p6myX5ZpJL25/d+tRHSZIkSVNEvxOs5wKXD7PuDuBFVbUjsD9wVM+67YG3A88B3gQ8q6p2Ab4CvKut8zngM1W1M/Cadp0kSQAkOSLJIX3c/4X92rckafRM63cAvZIcA+wOPAzsAxydZBawDHhWT9VLq+rWdpufA2e35YuAvdrlfYCZzSxEADZMsn5V3TtonwcDBwNsvLkzEyVpKksyraqWjsW+quoFY7EfSdLY6vcI1tXAjgNPquodwAuBzYB/AG6nGa2aDTyuZ7uHepYf7Xn+KL9PGtcAnl9Vs9qfLQcnV+0+51bV7Kqavd4mm3bULUnSeJTk/Ul+muQC4Nlt2bwkn00yH/i7JK9IcnGSBUl+kORJbb1FSTZO464kb27Lv57kRcPs76B2Svu8JD9L8q896+5tH+ckOS/Jd5Jcn+RLSdZo1724vfnT5UlOTbJ+W35kkmuSLEzyyWH2fXCS+Unm37fkru5eREnSiPqdYJ0DrJ3kb3rK1m0fNwJurapHaaYBrrmSbZ/N76cL0o6ESZKmqCQDN1KaBbwM2Lln9ePak22fAi6gOUG3A3Ay8N62zo+B3Wimt98A7NGW7wqMNN1vF5qp6tsBr00ye5g67wJmAn8EvDrJdOBwYJ92uvx84D1JNgVeBTy3qrYDPjLUTj2BKEn90dcpglVVSfYFPpPkvcCdwH3AoTTXZn2zPUP43bZ8ZbwbOCbJQpp+nkdz3ZYkaWraAzi9qu4HSHJmz7pTepa3Ak5JsgXN7Ikb2/LzgT2Bm4EvAgcn2RJYUlUjHaO+X1V3tfv8Fs1U+PmD6lxSVTe0dU5q6zxIk3D9uJ3u/jjgIuDudt1Xk5wFnLXCr4AkadT1/Rqs9lqq1w+zerue5UPb+vOAeT3bz+lZ/t26qlpMc3MMSZKWpzdB+jzw6ao6M8kc4Ii2/DzgHcBTgffTjCLtR5N4jaSW83y4OqFJzt4wuHKSXWim1O8HvJPmrrySpHGg31MEJUkaK+cB+yZZJ8kGwCuGqbcR8Mt2+S0DhVV1CzAdeGY72nQBcEjb7khelOQJSdYB9qWZajjYLkme3l57tX/b9k+A3ZJsDZBkvSTPaq/D2qiq/ofmeuXtl9dxSdLY6fsIliRJY6GqLk9yCnAlzVeBXDpM1SOAU5MsoblW+Ok96y7m99cEnw98jCYZGsklwDdpph6eUFWDpwfSxnI0sDVwLs1UxkeTHASclOTxbb3DgXuAM5KsTTPK9Z7l7F+SNIZMsCRJU0ZVfRT46KDiTw6qcwZwxjDbv6ln+UJWbCbIL6pq3yHaWr/n6W+r6uVD1DmHx96MY8AuK7BfSVIfOEVQkiRJkjriCJYkSaspyZ8CHx9UfGNVvQo4bqRtB9+8SZI0sZlgSZK0mqrqe8D3+h2HJKn/nCIoSZIkSR0xwZIkSZKkjphgSZIkSVJHvAZLkqRJbvN1p3HYDtP7HYYkTQmOYEmSJElSR0ywJEmSJKkjJliSJEmS1BETLEmSJEnqiAmWJEmSJHXEBEuSJEmSOuJt2iVJmuRuu38pRy5Y3O8w+sLb00saayZYPfyeEEmSJEmrwymCkiRJktQREyxJkiRJ6ogJliRJkiR1xARLkiRJkjpigiVJkiRJHTHBkiRJkqSOmGBJkiRJUkdMsCRJkiSpIyZYkiSNkSQX9jsGSdLoMsGSJGmMVNUL+h2DJGl0mWBJkjRGktybZE6Ss3rKjk5yULt8U5KPJbkiyfwkOyb5XpKfJ3l7W2dOkvOSfCfJ9Um+lMTjuSSNE9P6HcB4ctv9SzlyweJ+h7FKDtther9DkCR14/+qalaSzwDHAbsBawNXAV9q6+wCzARuBr4LvBo4bexDlSQN5hkvSZLGlzPbx0XAxVV1T1XdCTyUZON23SVVdUNVLQNOAnYf3EiSg9tRsPn3LblrTAKXJJlgSZI01pby2OPv2oPWP9Q+PtqzPPB8YOZJDdpm8HOqam5Vza6q2ettsulqhCtJWhkmWJIkja2bgZlJHt+OSL1wFdrYJcnT22uv9gcu6DJASdKq8xosSZLGTlXVLUm+QXNN1Y3AglVo51LgaGBr4Fzg9O5ClCStDhMsSZLGQJJNgV8DVNV7gfcOrlNVM3qWj6O5ycVj1iUB+G1VvXwUw5UkrSKnCEqSNMqSPBm4CPhkv2ORJI0uR7AkSRplVfUr4FkdtTUPmNdFW5Kk7jmCJUmSJEkdMcGSJEmSpI6YYEmSJElSR0ywJEmSJKkjJliSJEmS1BETLEmSJEnqiLdplyRpktt83WkctsP0fochSVOCI1iSJEmS1BETLEmSJEnqiAmWJEmSJHXEBEuSJEmSOjIuE6wky5JckeTKJJcneUG/Y5IkSZKk5RmvdxF8oKpmAST5U+BjwJ/0NSJJkiRJWo7xmmD12hBYApBkfeAMYBNgLeDwqjojyXrAN4CtgDWBD1fVKUl2Aj4NrA8sBg6qqlv70AdJkvrmtvuXcuSCxf0Ooy+8Pb2ksTZeE6x1klwBrA1sAezdlj8IvKqqfptkOvCTJGcCLwF+VVV/BpBkoyRrAZ8HXllVdybZH/go8LYx7oskSZKkKWK8Jli9UwR3Bb6eZFsgwL8l2RN4FNgSeBKwCPhUko8DZ1XV+W39bYHvJ4FmZOsPRq+SHAwcDLDx5luNdr8kSZIkTWLjNcH6naq6qB2t2gx4Wfu4U1U9kuQmYO2q+mmSHdv1H0nyQ+B04Oqq2nU57c8F5gJsNXNWjWJXJEmSJE1y4/Iugr2SbEMz+nQXsBFwR5tc7QU8ra3zZOD+qjoB+ASwI3A9sFk7AkaStZI8tx99kCRJkjQ1jNcRrIFrsKCZFviWqlqW5ETgv5MsAuYD17V1ngd8IsmjwCPA31TVw0n2A45KshFNXz8LXD2G/ZAkSZI0hYzLBKuq1hymfDEw1JS/m4DvDVH/CmDPLmOTJEmSpOGM+ymCkiRJkjRRmGBJkiRJUkdMsCRJkiSpIyZYkiRJktQREyxJ0riR5N6O2jkiySEjrJ+XZPYQ5bOTHLWctmckuaqLOCVJk8+4vIugJEn9UFXzab4GZNxKsmZVLet3HJKkoTmCJUkad9L4RJKrkixKsn9bvn6SHya5vC1/Zc8270/y0yQXAM9egd28Nskl7TZ7tG3MSXJWu7xZku8nuTrJV5LcnGR6u+2aSb7crjs7yToj9OXdSa5JsjDJyT39OLbtw8Ikr2nL39CWXZXk4z1t3JvkU0muBHZNcmAb+xVJ/iPJH3y9SZKDk8xPMv++JXetwMshSeqCCZYkaTx6NTAL2B7Yh+bL5LcAHgReVVU7AnsBn2qTsZ2A17fbvAzYeQX2Ma2qdgH+HvjXIdb/K3BOVT0XOA14as+6ZwLHtOt+A7xmhP0cBuxQVdsBb2/LPgDcXVXPa8vPSfJk4OPA3m0/dk6yb1t/PeDiqtoeuAvYH9itqmYBy4ADBu+0quZW1eyqmr3eJpuO9DpIkjpkgiVJGo92B06qqmVVdTvwI5qkKcC/JVkI/ADYEngSsAdwelXdX1W/Bc5cgX18q328DJgxTAwnA1TVd4ElPetubL/MfqTtBywETkxyILC0LdsHOGagQlUtafs3r6rurKqlwInAnm2VZcA32+UXAjsBlya5on3+jBH2L0kaQ16DJUmaSA4ANgN2qqpHktwErL2KbT3UPi5j5Y+HD/UsLwOGnSII/BlNovQK4P1JnreS+wJ4sOe6qwDHV9X7VqEdSdIocwRLkjQenQ/sn2TNJJvRJCiXABsBd7TJ1V7A09r65wH7JlknyQY0yczq+jHwOoAkLwY2WdkGkqwBPKWqzgUObeNfH/g+8I6eepvQ9O9Pkkxvr6l6A83I3WA/BPZL8sR22yckedoQ9SRJfWCCJUkaj06nmVp3JXAO8N6quo1m2tzsJIuANwPXAVTV5cApbf3/BS7tIIYPAi9ub8n+WuA24J6VbGNN4IQ23gXAUVX1G+AjwCbtzSyuBPaqqltprtc6t+3HZVV1xuAGq+oa4HDg7Haq5PeBLValg5Kk7qWq+h3DuLHVzFn1zhN/0O8wVslhO0xffiVJ6oMkl1XVH3zn1HiX5PHAsqpammRX4IvtTSUmnIl8fFtdHh8ljZbhjm9egyVJ0tCeCnyjneb3MPBXfY5HkjQBmGBJkiatJMcAuw0q/lxVHbu8bavqZ8AOY7EvSdLkYYIlSZq0quody6818fYlSRq/vMmFJEmSJHXEEawem687zYthJUmSJK0yR7AkSZIkqSMmWJIkSZLUEacISpI0yTkFXpLGjiNYkiRJktQREyxJkiRJ6ogJliRJkiR1xARLkiRJkjpigiVJkiRJHfEugpIkTXK33b+UIxcs7ncYfeHdEyWNNUewJEmSJKkjJliSJEmS1BGnCPaYylMo+snpG5IkSZosHMGSJEmSpI6YYEmSJElSR0ywJEmSJKkjJliSJEmS1BETLEmSJEnqiAmWJEmSJHXEBEuSJEmSOmKCJUmSJEkdMcGSJE04SY5Lst94aWeIduckOatdPijJ0e3y25O8eYTt/jzJYV3HI0kaO9P6HYAkSVNFVX1pOevPBM4co3AkSaPAESxJ0riX5M1JFia5Msl/tsV7JrkwyQ29o1BJ/inJpW39Dy6njd59fLgd0VpzmBh2bvd3ZZJLkmyQZO0kxyZZlGRBkr2W048jkhzSLr87yTVtTCe3Zb2jXTOSnNOu/2GSp7blxyU5aqi+D9rXwUnmJ5l/35K7Rnx9JUndcQRLkjSuJXkucDjwgqpanOQJwKeBLYDdgW1oRn1OS/Ji4JnALkCAM5PsCdw1RBu9+/gEsAHw1qqqIWJ4HHAKsH9VXZpkQ+AB4O+AqqrnJdkGODvJs1awa4cBT6+qh5JsPMT6zwPHV9XxSd4GHAXs2677g74P3riq5gJzAbaaOesP+iRJGh2OYEmSxru9gVOrajFAVf26Lf92VT1aVdcAT2rLXtz+LAAup0lAnjlCGwAfADaqqrcPlVy1ng3cWlWXttv/tqqW0iQ5J7Rl1wE3AyuaYC0ETkxyILB0iPW7Av/VLv9nu68BQ/VdkjQOmGBJkiaqh3qW0/P4saqa1f5sXVVfXU47lwI7DR7VGgN/BhwD7AhcmmRlZpUM1XdJ0jhggiVJGu/OAV6bZFOA5SRC3wPelmT9tu6WSZ64nDa+CxwJfCfJBsO0ez2wRZKd2+03aBOi84ED2rJnAU9t644oyRrAU6rqXOBQYCNg/UHVLgRe3y4f0O5LkjTOeQ2WJGlcq6qrk3wU+FGSZTTT/4are3aS5wAXJQG4FzhwmDYO6tnu1Da5OjPJy6rqgUHtPpxkf+DzSdahuf5qH+ALwBeTLKKZ5ndQe03V8rq1JnBCko1oRqCOqqrfDNruXcCxSf4JuBN46/IalST1X4afbj71bDVzVr3zxB/0O4wp57Adpvc7BEmjKMllVTW733FMZVP5+OYxRtJoGe745hRBSZIkSerIuEiwkmye5OQkP09yWZL/SfKsJFd11P7vvldEkqSRJDk9yRWDfv6033FJkiaGvl+DlWbC+ek03/Xx+rZse7ztrCSpD6rqVf2OQZI0cY2HEay9gEeq6ksDBVV1JXDLwPMkayc5NsmiJAuS7NWWP2ZkKslZSea0y29N8tMklwC7jVFfJEmSJE1hfR/BArYFLltOnXcAVVXPS7INcHZ7O9whJdkC+CCwE3A3cC4j3HVKkiRJkrowHkawVsTuwAkAVXUdcDMwbIIF/DEwr6rurKqHgVOGq5jk4CTzk8y/b8ldXcYsSZIkaYoZDyNYVwP7reK2S3lskrj2yjZQVXOBudDcxnYV45AkadzafN1p3q5cksbIeBjBOgd4fJKDBwqSbAc8pafO+TTfYk87NfCpwPXATcCsJGskeQqwS1v/YuBPkmyaZC3gtaPeC0mSJElTXt8TrGq+6fhVwD7tbdqvBj4G3NZT7QvAGkkW0Uz3O6iqHgJ+DNwIXAMcBVzetnkrcARwUVvn2rHpjSRJkqSpbDxMEaSqfgW8bohV27brHwTeOsR2RTuyNcS6Y4FjOwxTkiRJkkbU9xEsSZIkSZosTLAkSZIkqSMmWJIkSZLUkXFxDZYkSRo9t92/lCMXLO53GBOOt7aXtCocwZIkSZKkjphgSZIkSVJHTLAkSZIkqSMmWJIkSZLUERMsSZIkSeqICZYkSZIkdcQES5IkSZI6YoIlSZIkSR0xwZIkSZKkjphgSZIkSVJHTLAkSZNakgs7bOu1Sa5Ncm77/KQkC5P8Q1f7kCRNbNP6HYAkSaOpql7QYXN/AfxVVV2QZHNg56raenUaTLJmVS3rJjxJUr85giVJmtSS3Ns+bpHkvCRXJLkqyR4jbPOGJIvaeh9vy/4F2B34apJPAGcDW7bt7ZHk3UmuaUe0Tm63WT/JsW1bC5O8ZiCmJJ9KciWwa5IDk1zStvUfSdZs6704yUVJLk9yapL12/KbknywLV+UZJtRfAklSSvBEawem687jcN2mN7vMCRJo+ONwPeq6qNtArPuUJWSPBn4OLATsAQ4O8m+VfWhJHsDh1TV/CTHAGdV1ax2u1OAp1fVQ0k2bpv7AHB3VT2vrbNJW74ecHFV/WOS5wCHArtV1SNJvgAckOR/gMOBfarqviSHAu8BPtS2sbiqdkzyt8AhwF8O6sfBwMEAG2++1aq/apKklWKCJUmaKi4FvpZkLeDbVXXFMPV2BuZV1Z0ASU4E9gS+vZz2FwInJvl2T919gNcPVKiqJe3iMuCb7fILaZK5S5MArAPcATwfmAn8uC1/HHBRz/6+1T5eBrx6cDBVNReYC7DVzFm1nNglSR1xiqAkaUqoqvNoEqVfAscleXPHu/gz4BhgR5pkaaSTmA/2XHcV4PiqmtX+PLuqjmjLv99TPrOq/qKnjYfax2V4wlSSxg0TLEnSlJDkacDtVfVl4Cs0idBQLgH+JMn0dirhG4AfLaftNYCnVNW5NNP9NgLWB74PvKOn3iZDbP5DYL8kT2zrPKGN9SfAbkm2bsvXS/KsFe6wJKkvTLAkSVPFHODKJAuA/YHPDVWpqm4FDgPOBa4ELquqM5bT9prACUkWAQuAo6rqN8BHgE3am2VcCew1xP6uobnW6uwkC2mSsi3aKYoHASe15RcB3sxCksa5VDkte8Ds2bNr/vz5/Q5DkiaVJJdV1ex+xzGVbTVzVr3zxB/0O4wJxxtfSRrJcMc3R7AkSZIkqSNeFCtJmrKSXAw8flDxm6pqUT/ikSRNfCZYkqQpq6r+uN8xSJImF6cISpIkSVJHTLAkSZIkqSMmWJIkSZLUEa/B6nHb/Us5csHifochaRjeMlmSJI13JliSJE1ym687zRMUkjRGnCIoSZIkSR0xwZIkSZKkjphgSZIkSVJHTLAkSZIkqSMmWJIkSZLUERMsSZIkSeqIt2mXJGmS83sexzdvoS9NLo5gSZIkSVJHTLAkSZIkqSMmWJIkSZLUERMsSZIkSeqICZYkSZIkdcQES5IkSZI6YoIlSZIkSR0xwZIkSZKkjphgSZIkSVJHTLAkSeqDJEckOaTfcUiSujUhEqwky5JckeTKJJcneUFb/uQkp61gG/OSzB7dSCVJWnVJpvU7BknS6pkQCRbwQFXNqqrtgfcBHwOoql9V1X6DK3uAkiSNR0nen+SnSS4Ant2WzUvy2STzgb9L8ookFydZkOQHSZ7U1luUZOM07kry5rb860le1L9eSZJ6TZQEq9eGwBKAJDOSXNUuH5TkzCTnAD9Msk6Sk5Ncm+R0YJ0+xixJmuKS7AS8HpgFvAzYuWf146pqdlV9CrgAeH5V7QCcDLy3rfNjYDfgucANwB5t+a7AhUPs7+Ak85PMv2/JXaPQI0nSUCbKSM86Sa4A1ga2APYept6OwHZV9esk7wHur6rnJNkOuHxsQpUkaUh7AKdX1f0ASc7sWXdKz/JWwClJtgAeB9zYlp8P7AncDHwRODjJlsCSqrpv8M6qai4wF2CrmbOq475IkoYxUUawBqYIbgO8BPh6kgxR7/tV9et2eU/gBICqWggsHKphz/BJksaB3gTp88DRVfU84K9pTi4CnEeTpO0BzAPuBPajSbwkSePEREmwfqeqLgKmA5sNsfoPzuCtQHtz22kZs9fbZNPVjk+SpGGcB+zbTmHfAHjFMPU2An7ZLr9loLCqbqE5/j2zqm6gmUp4SNuuJGmcmHAJVpJtgDWB5Q03nQe8sd1mW2C7UQ5NkqRhVdXlNFMBrwT+F7h0mKpHAKcmuQxYPGjdxcBP2+XzgS1pEi1J0jgx0a7BAgjwlqpaNvQswd/5InBskmuBa4HLRjdESZJGVlUfBT46qPiTg+qcAZwxzPZv6lm+kAl4olSSJrsJkWBV1ZrDlN8EbNsuHwcc17PuAZq7NUmSJEnSmPDMlyRJkiR1xARLkiRJkjpigiVJkiRJHTHBkiRJkqSOmGBJkiRJUkdMsCRJkiSpIyZYkiRJktSRCfE9WJIkadVtvu40Dtther/DkKQpwREsSZIkSeqICZYkSZIkdcQES5IkSZI6YoIlSZIkSR0xwZIkSZKkjphgSZIkSVJHvE27JEmT3G33L+XIBYv7HYakMeRXM/SPI1iSJEmS1BETLEmSJEnqiFMEe/hN95IkSZJWhyNYkiRJktQREyxJkiRJ6ogJliRJkiR1xARLkiRJkjpigiVJkiRJHTHBkiRJkqSOmGBJktRHSW5KMuJ3hCT557GKR5K0ekywJEka/0ywJGmCMMGSJGk1JJmR5Kqe54ckOSLJvCSfS3JFkquS7NKu3zTJ2UmuTvIVID3bfjvJZe26g9uyI4F12nZObMsOTHJJW/YfSdYc215LkoZjgiVJ0uhZt6pmAX8LfK0t+1fggqp6LnA68NSe+m+rqp2A2cC7k2xaVYcBD1TVrKo6IMlzgP2B3dq2lwEHDN5xkoOTzE8y/74ld41W/yRJg0zrdwCSJE1iJwFU1XlJNkyyMbAn8Oq2/DtJlvTUf3eSV7XLTwGeCQzOjl4I7ARcmgRgHeCOwTuuqrnAXICtZs6qrjokSRqZCVaP2+5fypELFvc7DEkaNw7bYcR7L6ixlMfOCFm7Z3lwYjNsopNkDrAPsGtV3Z9k3qC2flcVOL6q3rcqwUqSRpdTBCVJWj23A09sr616PPDynnX7AyTZHbi7qu4GzgPe2Ja/FNikrbsRsKRNrrYBnt/TziNJ1mqXfwjsl+SJbRtPSPK0UeqbJGklOYIlSdJqqKpHknwIuAT4JXBdz+oHkywA1gLe1pZ9EDgpydXAhcD/teXfBd6e5FrgeuAnPe3MBRYmuby9Dutw4OwkawCPAO8Abh6dHkqSVoYJliRJq6mqjgKO6i1rp/idUFV/P6juXcCLh2nqpcO0fyhwaM/zU4BTVj1iSdJocYqgJEmSJHXEESxJkkZBVc3pdwySpLHnCJYkSZIkdcQES5IkSZI6YoIlSZIkSR0xwZIkSZKkjphgSZIkSVJHTLAkSZIkqSPepl2SpElu83WncdgO0/sdhiRNCY5gSZIkSVJHTLAkSZIkqSMmWJIkSZLUERMsSZIkSeqICZYkSZIkdcS7CEqSNMnddv9SjlywuN9hSNK4MZp3Vh33I1hJliW5IslVSU5Nsm6S2UmO6ndskiRJktRr3CdYwANVNauqtgUeBt5eVfOr6t39DkySJEmSek2EBKvX+cDWSeYkOQsgyRFJ/jPJRUl+luSvBion+acklyZZmOSDfYtakiRJ0pQwYa7BSjINeCnw3SFWbwc8H1gPWJDkO8C2wDOBXYAAZybZs6rOG9TuwcDBABtvvtXodUCSJEnSpDcRRrDWSXIFMB/4P+CrQ9Q5o6oeqKrFwLk0SdWL258FwOXANjQJ12NU1dyqml1Vs9fbZNNR6oIkSZKkqWAijGA9UFWzeguSDK5TQzwP8LGq+o/RC02SJEmSfm8ijGCtiFcmWTvJpsAc4FLge8DbkqwPkGTLJE/sY4ySJEmSJrmJMIK1IhbSTA2cDny4qn4F/CrJc4CL2hGve4EDgTv6FqUkSZKkSW3cJ1hVtf4QZfOAeT1FC6vqzUPU+xzwuVELTpIkSZJ6TJYpgpIkSZLUd+N+BGt5quqIfscgSZIkSeAIliRJoy7JhStQ5ytJZrbL/zz6UUmSRoMJliRJo6yqXrACdf6yqq5pn5pgSdIEZYIlSdIoS3Jv+zgnybwkpyW5LsmJaW9125bPTnIksE6SK5KcuBr7PDjJ/CTz71tyV0c9kSQtjwmWJEljawfg74GZwDOA3XpXVtVhwANVNauqDljVnVTV3KqaXVWz19tk09WJV5K0EkywJEkaW5dU1S+q6lHgCmBGf8ORJHXJBEuSpLH1UM/yMibBHX0lSb9ngiVJ0vjzSJK1+h2EJGnlmWBJkjT+zAUWrs5NLiRJ/eG0BEmSRllVrd8+zgPm9ZS/s2d5Ts/yocChYxagJKkzjmBJkiRJUkccwZIkaRUk2RT4YU/RmjQ3rRh4HPDCqlqlL6IaYh8D+2HQPlZrP5Kk7phgSZK0CtpkZtZE34ckqVtOEZQkSZKkjphgSZIkSVJHTLAkSZIkqSNeg9Vj83WncdgO0/sdhiRJnfL4JkljxxEsSZIkSeqICZYkSZIkdcQES5IkSZI6YoIlSZIkSR0xwZIkSZKkjphgSZIkSVJHTLAkSZIkqSMmWJIkSZLUERMsSZIkSeqICZYkSZIkdcQES5IkSZI6YoIlSZIkSR0xwZIkSZKkjphgSZIkSVJHTLAkSZIkqSMmWJIkSZLUkVRVv2MYN5LcA1zf7zjGyHRgcb+DGAP2c3KxnxPT06pqs34HMZVNwuPbZPsbsT/j12TqC9ifrg15fJvWj0jGseurana/gxgLSeZPhb7az8nFfkqrbFId3ybb34j9Gb8mU1/A/owVpwhKkiRJUkdMsCRJkiSpIyZYjzW33wGMoanSV/s5udhPadVMtt8p+zO+Tab+TKa+gP0ZE97kQpIkSZI64giWJEmSJHXEBEuSJEmSOmKC1UrykiTXJ/l/SQ7rdzyjJclNSRYluSLJ/H7H06UkX0tyR5KresqekOT7SX7WPm7Szxi7MEw/j0jyy/Z9vSLJy/oZYxeSPCXJuUmuSXJ1kr9ryyfVezpCPyfde6r+mOjHt8n02T7ZPteSrJ3kkiRXtv35YFv+9CQXt79zpyR5XL9jXRlJ1kyyIMlZ7fMJ25+h/u+bwL9vGyc5Lcl1Sa5Nsut47YsJFs0fEnAM8FJgJvCGJDP7G9Wo2quqZo3H7w1YTccBLxlUdhjww6p6JvDD9vlEdxx/2E+Az7Tv66yq+p8xjmk0LAX+sapmAs8H3tH+XU6293S4fsLke081xibJ8e04Js9n+2T7XHsI2LuqtgdmAS9J8nzg4zSfX1sDS4C/6F+Iq+TvgGt7nk/0/gz+v2+i/r59DvhuVW0DbE/zHo3LvphgNXYB/l9V3VBVDwMnA6/sc0xaSVV1HvDrQcWvBI5vl48H9h3LmEbDMP2cdKrq1qq6vF2+h+aDdEsm2Xs6Qj+lLkz449tk+myfbJ9r1bi3fbpW+1PA3sBpbfmE6Q9Akq2APwO+0j4PE7g/w5hwv29JNgL2BL4KUFUPV9VvGKd9McFqbAnc0vP8F0zef3AKODvJZUkO7ncwY+BJVXVru3wb8KR+BjPK3plkYTudZlwMkXclyQxgB+BiJvF7OqifMInfU42ZyXp8m/CfA5Plc62dTncFcAfwfeDnwG+qamlbZaL9zn0WeC/waPt8UyZ2f4b6v28i/r49HbgTOLadvvmVJOsxTvtigjX17F5VO9JMF3lHkj37HdBYqeY7CSbr9xJ8EfgjmikatwKf6ms0HUqyPvBN4O+r6re96ybTezpEPyfteyp1aSJ+Dkymz7WqWlZVs4CtaEZMt+lvRKsuycuBO6rqsn7H0qER/++bQL9v04AdgS9W1Q7AfQyaDjie+mKC1fgl8JSe51u1ZZNOVf2yfbwDOJ3mw3Ayuz3JFgDt4x19jmdUVNXt7UHuUeDLTJL3NclaNP+EnFhV32qLJ917OlQ/J+t7qjE3WY9vE/ZzYLJ+rrXTtc4FdgU2TjKtXTWRfud2A/48yU0002n3prnuZ6L2Z7j/+ybi79svgF9U1cAMj9NoEq5x2RcTrMalwDPbu8Q8Dng9cGafY+pckvWSbDCwDLwYuGrkrSa8M4G3tMtvAc7oYyyjZuDDpfUqJsH72s57/ypwbVV9umfVpHpPh+vnZHxP1ReT9fg2IT8HJtvnWpLNkmzcLq8DvIjmurJzgf3aahOmP1X1vqraqqpm0PytnFNVBzBB+zPC/30T7vetqm4Dbkny7LbohcA1jNO+pBlNU5pbIH8WWBP4WlV9tL8RdS/JM2jOXkAz1Ppfk6mfSU4C5gDTgduBfwW+DXwDeCpwM/C6qprQN4gYpp9zaKaSFXAT8Nc9c5InpCS7A+cDi/j9XPh/prleYdK8pyP08w1MsvdU/THRj2+T6bN9sn2uJdmO5sYCa9KctP9GVX2o/X/jZOAJwALgwKp6qH+Rrrwkc4BDqurlE7U/w/3fl2RTJubv2yyam488DrgBeCvt7x3jrC8mWJIkSZLUEacISpIkSVJHTLAkSZIkqSMmWJIkSZLUERMsSZIkSeqICZYkSZIkdcQES+qzJJsnOTnJz5NcluR/kjyrw/bnJHlBV+1JkrQiPL5pqjLBkvqo/dLJ04F5VfVHVbUT8D7gSR3uZg7gAUiSNGY8vmkqM8GS+msv4JGq+tJAQVVdCVyQ5BNJrkqyKMn+8LuzdWcN1E1ydJKD2uWbknwwyeXtNtskmQG8HfiHJFck2WMsOydJmrI8vmnKmtbvAKQpblvgsiHKXw3MArYHpgOXJjlvBdpbXFU7Jvlbmm+g/8skXwLurapPdhW0JEnL4fFNU5YjWNL4tDtwUlUtq6rbgR8BO6/Adt9qHy8DZoxSbJIkrSqPb5r0TLCk/roa2Gkl6i/lsX+3aw9a/1D7uAxHqCVJ/ePxTVOWCZbUX+cAj09y8EBBku2A3wD7J1kzyWbAnsAlwM3AzCSPT7Ix8MIV2Mc9wAZdBy5J0gg8vmnK8gyA1EdVVUleBXw2yaHAg8BNwN8D6wNXAgW8t6puA0jyDeAq4EZgwQrs5r+B05K8EnhXVZ3fdT8kSerl8U1TWaqq3zFIkiRJ0qTgFEFJkiRJ6ogJliRJkiR1xARLkiRJkjpigiVJkiRJHTHBkiRJkqSOmGBJkiRJUkdMsCRJkiSpI/8ftQyLlhAD4KkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 864x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting\n",
    "# Get top 10 common classes and functions\n",
    "top_classes = sorted(common_classes.items(), key=lambda x: -x[1])[:10]\n",
    "top_functions = sorted(common_functions.items(), key=lambda x: -x[1])[:10]\n",
    "\n",
    "# Separate names and counts\n",
    "class_names, class_counts = zip(*top_classes)\n",
    "function_names, function_counts = zip(*top_functions)\n",
    "\n",
    "plt.figure(figsize=(12, 6))\n",
    "\n",
    "plt.subplot(1, 2, 1)\n",
    "plt.barh(class_names, class_counts, color='skyblue')\n",
    "plt.xlabel('Count')\n",
    "plt.title('Top 10 Common Classes')\n",
    "\n",
    "plt.subplot(1, 2, 2)\n",
    "plt.barh(function_names, function_counts, color='skyblue')\n",
    "plt.xlabel('Count')\n",
    "plt.title('Top 10 Common Functions')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "# Histogram of lines of code\n",
    "plt.figure(figsize=(8, 6))\n",
    "plt.hist(lines_of_code.values(), bins=50, color='skyblue', edgecolor='black')\n",
    "plt.xlabel('Lines of Code')\n",
    "plt.ylabel('Number of Files')\n",
    "plt.title('Histogram of Lines of Code')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "1074a6cc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Skipping GPT-3.5/1st method/API/code/code_7.py due to a syntax error.\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import ast\n",
    "\n",
    "root_dirs = ['GPT-3.5', 'GPT-4']\n",
    "\n",
    "# Get list of all .py files\n",
    "py_files = []\n",
    "for root_dir in root_dirs:\n",
    "    for foldername, subfolders, filenames in os.walk(root_dir):\n",
    "        for filename in filenames:\n",
    "            if filename.endswith('.py'):\n",
    "                filepath = os.path.join(foldername, filename)\n",
    "                py_files.append(filepath)\n",
    "\n",
    "# Class information for PlantUML\n",
    "class_info = {}\n",
    "\n",
    "# Analyze each file\n",
    "for py_file in py_files:\n",
    "    with open(py_file, 'r') as f:\n",
    "        file_content = f.read()\n",
    "\n",
    "    # Parse the file content to an AST\n",
    "    try:\n",
    "        tree = ast.parse(file_content)\n",
    "\n",
    "        # Iterate over all nodes in the AST, and collect classes and functions\n",
    "        for node in ast.walk(tree):\n",
    "            if isinstance(node, ast.ClassDef):  # Class definition\n",
    "                class_name = node.name\n",
    "                methods = [n.name for n in node.body if isinstance(n, ast.FunctionDef)]\n",
    "                class_info[class_name] = methods\n",
    "    except SyntaxError:\n",
    "        print(f\"Skipping {py_file} due to a syntax error.\")\n",
    "\n",
    "# Write to PlantUML file\n",
    "with open('class_diagram.puml', 'w') as f:\n",
    "    f.write('@startuml\\n')\n",
    "    for class_name, methods in class_info.items():\n",
    "        f.write(f'class {class_name} {{\\n')\n",
    "        for method in methods:\n",
    "            f.write(f'  {method}()\\n')\n",
    "        f.write('}\\n')\n",
    "    f.write('@enduml\\n')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "43869801",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import glob\n",
    "\n",
    "def get_all_observation_files(directories):\n",
    "    # This will return a list of all 'observations.txt' files\n",
    "    # in the given directories and their subdirectories.\n",
    "    observation_files = []\n",
    "    for directory in directories:\n",
    "        observation_files.extend(glob.glob(f'{directory}/**/observations.txt', recursive=True))\n",
    "    return observation_files\n",
    "\n",
    "def create_all_observations_file(files, output_file):\n",
    "    with open(output_file, 'w') as outfile:\n",
    "        for file in files:\n",
    "            folder_name = os.path.dirname(file)\n",
    "            outfile.write(f'==== {folder_name} ====\\n\\n')\n",
    "            with open(file, 'r') as infile:\n",
    "                for line in infile:\n",
    "                    outfile.write(line)\n",
    "                outfile.write('\\n\\n')\n",
    "\n",
    "# Set the directories and output file name\n",
    "directories = ['GPT-3.5', 'GPT-4']\n",
    "output_file = 'all_observations.txt'\n",
    "\n",
    "# Get all 'observations.txt' files in the directories and their subdirectories\n",
    "observation_files = get_all_observation_files(directories)\n",
    "\n",
    "# Create the 'all_observations.txt' file\n",
    "create_all_observations_file(observation_files, output_file)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ad3070b0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "          Method Directory  Count\n",
      "0     1st method   GPT-3.5     22\n",
      "1     1st method     GPT-4     44\n",
      "2     2nd method   GPT-3.5     36\n",
      "3     3rd method   GPT-3.5     31\n",
      "4     3rd method     GPT-4     15\n",
      "5     4th method   GPT-3.5      6\n",
      "6     5th method   GPT-3.5      7\n",
      "7     5th method     GPT-4      9\n",
      "8  left_to_right   GPT-3.5      3\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import glob\n",
    "import pandas as pd\n",
    "\n",
    "# Specify the directories you want to search in\n",
    "rootDirs = ['GPT-3.5', 'GPT-4']\n",
    "data = []\n",
    "\n",
    "# Use glob to recursively find all .md files in 'prompt' subfolders of each directory\n",
    "for rootDir in rootDirs:\n",
    "    for filepath in glob.iglob(rootDir + '/**/prompt/*.md', recursive=True):\n",
    "        try:\n",
    "            with open(filepath, 'r', encoding='utf8') as file:\n",
    "                # Read the file\n",
    "                content = file.read()\n",
    "                # Count the occurrences of 'You:'\n",
    "                count = content.count('You:')\n",
    "                # Get the method name from the filepath\n",
    "                method = filepath.split('/')[1]\n",
    "                # Append the filepath, method, and count to the data list\n",
    "                data.append({'Filepath': filepath, 'Method': method, 'Directory': rootDir, 'Count': count})\n",
    "        except UnicodeDecodeError:\n",
    "            # print(f\"Could not read {filepath} due to an encoding issue.\")\n",
    "            continue\n",
    "\n",
    "# Create a DataFrame from the data\n",
    "df = pd.DataFrame(data)\n",
    "\n",
    "# Group by the 'Method' and 'Directory' columns and sum the 'Count' column\n",
    "grouped_df = df.groupby(['Method', 'Directory'])['Count'].sum().reset_index()\n",
    "\n",
    "# Print the grouped DataFrame\n",
    "print(grouped_df)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a7bf8f1e",
   "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>Filepath</th>\n",
       "      <th>Method</th>\n",
       "      <th>Directory</th>\n",
       "      <th>Count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>GPT-3.5/3rd method/2nd session/prompt/ChatGPT-...</td>\n",
       "      <td>3rd method</td>\n",
       "      <td>GPT-3.5</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>GPT-3.5/3rd method/1st session/prompt/ChatGPT-...</td>\n",
       "      <td>3rd method</td>\n",
       "      <td>GPT-3.5</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>GPT-3.5/3rd method/3rd session/prompt/ChatGPT-...</td>\n",
       "      <td>3rd method</td>\n",
       "      <td>GPT-3.5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>GPT-3.5/2nd method/2nd session/prompt/ChatGPT-...</td>\n",
       "      <td>2nd method</td>\n",
       "      <td>GPT-3.5</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>GPT-3.5/2nd method/1st session/prompt/ChatGPT-...</td>\n",
       "      <td>2nd method</td>\n",
       "      <td>GPT-3.5</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>GPT-3.5/2nd method/4th session/prompt/ChatGPT-...</td>\n",
       "      <td>2nd method</td>\n",
       "      <td>GPT-3.5</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>GPT-3.5/2nd method/3rd session/prompt/ChatGPT-...</td>\n",
       "      <td>2nd method</td>\n",
       "      <td>GPT-3.5</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>GPT-3.5/5th method/1st session/prompt/ChatGPT-...</td>\n",
       "      <td>5th method</td>\n",
       "      <td>GPT-3.5</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>GPT-3.5/1st method/2nd session/prompt/ChatGPT-...</td>\n",
       "      <td>1st method</td>\n",
       "      <td>GPT-3.5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>GPT-3.5/1st method/8th session/prompt/ChatGPT-...</td>\n",
       "      <td>1st method</td>\n",
       "      <td>GPT-3.5</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>GPT-3.5/1st method/5th session/prompt/ChatGPT-...</td>\n",
       "      <td>1st method</td>\n",
       "      <td>GPT-3.5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>GPT-3.5/1st method/1st session/prompt/ChatGPT-...</td>\n",
       "      <td>1st method</td>\n",
       "      <td>GPT-3.5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>GPT-3.5/1st method/7th session/prompt/ChatGPT-...</td>\n",
       "      <td>1st method</td>\n",
       "      <td>GPT-3.5</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>GPT-3.5/1st method/6th session/prompt/ChatGPT-...</td>\n",
       "      <td>1st method</td>\n",
       "      <td>GPT-3.5</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>GPT-3.5/1st method/4th session/prompt/ChatGPT-...</td>\n",
       "      <td>1st method</td>\n",
       "      <td>GPT-3.5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>GPT-3.5/1st method/3rd session/prompt/ChatGPT-...</td>\n",
       "      <td>1st method</td>\n",
       "      <td>GPT-3.5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>GPT-3.5/4th method/2nd session/prompt/ChatGPT-...</td>\n",
       "      <td>4th method</td>\n",
       "      <td>GPT-3.5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>GPT-3.5/4th method/1st session/prompt/ChatGPT-...</td>\n",
       "      <td>4th method</td>\n",
       "      <td>GPT-3.5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>GPT-3.5/left_to_right/1st session/prompt/ChatG...</td>\n",
       "      <td>left_to_right</td>\n",
       "      <td>GPT-3.5</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>GPT-4/3rd method/2nd session/prompt/ChatGPT-Fl...</td>\n",
       "      <td>3rd method</td>\n",
       "      <td>GPT-4</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>GPT-4/3rd method/1st session/prompt/ChatGPT-Py...</td>\n",
       "      <td>3rd method</td>\n",
       "      <td>GPT-4</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>GPT-4/5th method/1st session/prompt/ChatGPT-Bi...</td>\n",
       "      <td>5th method</td>\n",
       "      <td>GPT-4</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>GPT-4/1st method/3rd session-GPT3.5/prompt/Cha...</td>\n",
       "      <td>1st method</td>\n",
       "      <td>GPT-4</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>GPT-4/1st method/1st session-GPT3.5/prompt/Cha...</td>\n",
       "      <td>1st method</td>\n",
       "      <td>GPT-4</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>GPT-4/1st method/5th session-GPT4/prompt/ChatG...</td>\n",
       "      <td>1st method</td>\n",
       "      <td>GPT-4</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>GPT-4/1st method/4th session-GPT4/prompt/ChatG...</td>\n",
       "      <td>1st method</td>\n",
       "      <td>GPT-4</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>GPT-4/1st method/2nd session-GPT3.5/prompt/Cha...</td>\n",
       "      <td>1st method</td>\n",
       "      <td>GPT-4</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                             Filepath         Method  \\\n",
       "0   GPT-3.5/3rd method/2nd session/prompt/ChatGPT-...     3rd method   \n",
       "1   GPT-3.5/3rd method/1st session/prompt/ChatGPT-...     3rd method   \n",
       "2   GPT-3.5/3rd method/3rd session/prompt/ChatGPT-...     3rd method   \n",
       "3   GPT-3.5/2nd method/2nd session/prompt/ChatGPT-...     2nd method   \n",
       "4   GPT-3.5/2nd method/1st session/prompt/ChatGPT-...     2nd method   \n",
       "5   GPT-3.5/2nd method/4th session/prompt/ChatGPT-...     2nd method   \n",
       "6   GPT-3.5/2nd method/3rd session/prompt/ChatGPT-...     2nd method   \n",
       "7   GPT-3.5/5th method/1st session/prompt/ChatGPT-...     5th method   \n",
       "8   GPT-3.5/1st method/2nd session/prompt/ChatGPT-...     1st method   \n",
       "9   GPT-3.5/1st method/8th session/prompt/ChatGPT-...     1st method   \n",
       "10  GPT-3.5/1st method/5th session/prompt/ChatGPT-...     1st method   \n",
       "11  GPT-3.5/1st method/1st session/prompt/ChatGPT-...     1st method   \n",
       "12  GPT-3.5/1st method/7th session/prompt/ChatGPT-...     1st method   \n",
       "13  GPT-3.5/1st method/6th session/prompt/ChatGPT-...     1st method   \n",
       "14  GPT-3.5/1st method/4th session/prompt/ChatGPT-...     1st method   \n",
       "15  GPT-3.5/1st method/3rd session/prompt/ChatGPT-...     1st method   \n",
       "16  GPT-3.5/4th method/2nd session/prompt/ChatGPT-...     4th method   \n",
       "17  GPT-3.5/4th method/1st session/prompt/ChatGPT-...     4th method   \n",
       "18  GPT-3.5/left_to_right/1st session/prompt/ChatG...  left_to_right   \n",
       "19  GPT-4/3rd method/2nd session/prompt/ChatGPT-Fl...     3rd method   \n",
       "20  GPT-4/3rd method/1st session/prompt/ChatGPT-Py...     3rd method   \n",
       "21  GPT-4/5th method/1st session/prompt/ChatGPT-Bi...     5th method   \n",
       "22  GPT-4/1st method/3rd session-GPT3.5/prompt/Cha...     1st method   \n",
       "23  GPT-4/1st method/1st session-GPT3.5/prompt/Cha...     1st method   \n",
       "24  GPT-4/1st method/5th session-GPT4/prompt/ChatG...     1st method   \n",
       "25  GPT-4/1st method/4th session-GPT4/prompt/ChatG...     1st method   \n",
       "26  GPT-4/1st method/2nd session-GPT3.5/prompt/Cha...     1st method   \n",
       "\n",
       "   Directory  Count  \n",
       "0    GPT-3.5      7  \n",
       "1    GPT-3.5     19  \n",
       "2    GPT-3.5      5  \n",
       "3    GPT-3.5      7  \n",
       "4    GPT-3.5      8  \n",
       "5    GPT-3.5     10  \n",
       "6    GPT-3.5     11  \n",
       "7    GPT-3.5      7  \n",
       "8    GPT-3.5      1  \n",
       "9    GPT-3.5      4  \n",
       "10   GPT-3.5      1  \n",
       "11   GPT-3.5      2  \n",
       "12   GPT-3.5      6  \n",
       "13   GPT-3.5      6  \n",
       "14   GPT-3.5      1  \n",
       "15   GPT-3.5      1  \n",
       "16   GPT-3.5      1  \n",
       "17   GPT-3.5      5  \n",
       "18   GPT-3.5      3  \n",
       "19     GPT-4      6  \n",
       "20     GPT-4      9  \n",
       "21     GPT-4      9  \n",
       "22     GPT-4     12  \n",
       "23     GPT-4      9  \n",
       "24     GPT-4     10  \n",
       "25     GPT-4      8  \n",
       "26     GPT-4      5  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "1a817b96",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Get unique methods and directories from the grouped DataFrame\n",
    "methods = grouped_df['Method'].unique()\n",
    "directories = grouped_df['Directory'].unique()\n",
    "\n",
    "# Set the number of rows and columns for the subplots\n",
    "num_rows = (len(methods) + 1) // 2  # Adjust the number of rows based on the number of methods\n",
    "num_cols = 2  # Set the number of columns\n",
    "\n",
    "# Create subplots\n",
    "fig, axes = plt.subplots(num_rows, num_cols, figsize=(12, 8))\n",
    "\n",
    "# Flatten the axes array if needed\n",
    "if num_rows > 1:\n",
    "    axes = axes.flatten()\n",
    "\n",
    "# Iterate over each method and corresponding subplot\n",
    "for i, (method, ax) in enumerate(zip(methods, axes)):\n",
    "    # Filter the DataFrame for the current method and each directory\n",
    "    method_data = [df[(df['Method'] == method) & (df['Directory'] == directory)]['Count'].values\n",
    "                  for directory in directories]\n",
    "    # Generate the boxplot with labels for each directory\n",
    "    ax.boxplot(method_data, labels=directories)\n",
    "    # Set the title for the subplot\n",
    "    ax.set_title(f\"Boxplot for {method}\")\n",
    "    # Set the y-axis label\n",
    "    ax.set_ylabel('User Count')\n",
    "\n",
    "# Remove any extra subplots\n",
    "if len(methods) < len(axes):\n",
    "    for j in range(len(methods), len(axes)):\n",
    "        fig.delaxes(axes[j])\n",
    "\n",
    "# Adjust spacing between subplots\n",
    "fig.tight_layout()\n",
    "\n",
    "# Show the plot\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f5add57e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "c7a56565",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "# Define the base directory paths\n",
    "base_dirs = ['GPT-3.5', 'GPT-4'] \n",
    "\n",
    "mp4_files = []  # Array to store the mp4 file paths\n",
    "\n",
    "# Iterate over base directories\n",
    "for base_dir in base_dirs:\n",
    "    # Fetch the subfolders (methods)\n",
    "    base_methods = [name for name in os.listdir(base_dir) if os.path.isdir(os.path.join(base_dir, name))]\n",
    "    \n",
    "    # Iterate over methods\n",
    "    for method in base_methods:\n",
    "        # Skip if the method is exactly 'GPT-3.5' or 'GPT-4'\n",
    "        if method == 'GPT-3.5' or method == 'GPT-4':\n",
    "            continue\n",
    "            \n",
    "        method_path = os.path.join(base_dir, method)\n",
    "        \n",
    "        # Iterate over subfolders of a method\n",
    "        for subdir in os.listdir(method_path):\n",
    "            subdir_path = os.path.join(method_path, subdir)\n",
    "            # If subdir is a directory\n",
    "            if os.path.isdir(subdir_path):\n",
    "                # Check for mp4 files in the current subdir\n",
    "                for file in os.listdir(subdir_path):\n",
    "                    if file.endswith('.mp4'):\n",
    "                        mp4_files.append(os.path.join(subdir_path, file))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "0911182a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['GPT-3.5/3rd method/2nd session/video.mp4',\n",
       " 'GPT-3.5/3rd method/1st session/video.mp4',\n",
       " 'GPT-3.5/2nd method/2nd session/video.mp4',\n",
       " 'GPT-3.5/2nd method/1st session/video.mp4',\n",
       " 'GPT-3.5/2nd method/4th session/video.mp4',\n",
       " 'GPT-3.5/2nd method/3rd session/video.mp4',\n",
       " 'GPT-3.5/5th method/4th session/video.mp4',\n",
       " 'GPT-3.5/1st method/2nd session/video.mp4',\n",
       " 'GPT-3.5/1st method/8th session/video.mp4',\n",
       " 'GPT-3.5/1st method/5th session/video.mp4',\n",
       " 'GPT-3.5/1st method/1st session/video.mp4',\n",
       " 'GPT-3.5/1st method/7th session/video.mp4',\n",
       " 'GPT-3.5/1st method/6th session/video.mp4',\n",
       " 'GPT-3.5/1st method/4th session/video.mp4',\n",
       " 'GPT-3.5/1st method/3rd session/video.mp4',\n",
       " 'GPT-3.5/4th method/2nd session/video.mp4',\n",
       " 'GPT-3.5/4th method/1st session/video.mp4',\n",
       " 'GPT-3.5/left_to_right/1st session/video.mp4',\n",
       " 'GPT-4/t = 0/1st session/video.mp4']"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mp4_files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "01cced15",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import glob\n",
    "from PIL import Image, ImageDraw, ImageFont\n",
    "\n",
    "# Define the base directory paths\n",
    "base_dirs = ['GPT-3.5', 'GPT-4'] \n",
    "\n",
    "import re\n",
    "\n",
    "def closest_md_file(video_file):\n",
    "    # Split the video file path into parts\n",
    "    parts = video_file.split(os.path.sep)\n",
    "    # Iterate over the parts from longest to shortest\n",
    "    for i in range(len(parts), -1, -1):\n",
    "        # Join the current parts to create a directory path\n",
    "        dir_path = os.path.sep.join(parts[:i])\n",
    "        # Use glob to find .md files in the 'prompt' subfolder of the directory\n",
    "        md_files = glob.glob(dir_path + '/prompt/*.md')\n",
    "        # If any .md files are found, return the path of the first one\n",
    "        if md_files:\n",
    "            with open(md_files[0], 'r', encoding='utf8', errors='ignore') as f:\n",
    "                content = f.read()\n",
    "                # Extract the text between \"#### You:\" and \"#### ChatGPT:\"\n",
    "                match = re.search(r\"#### You:(.*?)#### ChatGPT:\", content, re.DOTALL)\n",
    "                if match:\n",
    "                    return match.group(1) # [:200]  # adjust 200 to control the number of characters\n",
    "    # If no .md file was found, return None\n",
    "    return None\n",
    "\n",
    "\n",
    "mp4_files = []  # Array to store the mp4 file paths\n",
    "\n",
    "# Iterate over base directories\n",
    "for base_dir in base_dirs:\n",
    "    # Fetch the subfolders (methods)\n",
    "    base_methods = [name for name in os.listdir(base_dir) if os.path.isdir(os.path.join(base_dir, name))]\n",
    "    \n",
    "    # Iterate over methods\n",
    "    for method in base_methods:\n",
    "        # Skip if the method is exactly 'GPT-3.5' or 'GPT-4'\n",
    "        if method == 'GPT-3.5' or method == 'GPT-4':\n",
    "            continue\n",
    "            \n",
    "        method_path = os.path.join(base_dir, method)\n",
    "        \n",
    "        # Iterate over subfolders of a method\n",
    "        for subdir in os.listdir(method_path):\n",
    "            subdir_path = os.path.join(method_path, subdir)\n",
    "            # If subdir is a directory\n",
    "            if os.path.isdir(subdir_path):\n",
    "                # Check for mp4 files in the current subdir\n",
    "                for file in os.listdir(subdir_path):\n",
    "                    if file.endswith('.mp4'):\n",
    "                        mp4_files.append(os.path.join(subdir_path, file))\n",
    "\n",
    "# Define the final video file\n",
    "final_video = 'final_video.mp4'\n",
    "\n",
    "# Define the intermediate files list\n",
    "intermediate_files = []\n",
    "\n",
    "\n",
    "# Function to create a multiline image for a given text\n",
    "def create_multiline_image(text):\n",
    "    img_width = 436 # 1920\n",
    "    img_height = 816 # 1080\n",
    "    font_size = 15\n",
    "    max_text_width = img_width - 20\n",
    "\n",
    "    # Create a new image with white background\n",
    "    img = Image.new('RGB', (img_width, img_height), color=(255, 255, 255))\n",
    "\n",
    "    # Get a drawing context\n",
    "    d = ImageDraw.Draw(img)\n",
    "    \n",
    "    # Load the font\n",
    "    font = ImageFont.truetype('/usr/share/fonts/google-carlito-fonts/Carlito-Regular.ttf', font_size)\n",
    "\n",
    "    # Split the text into words\n",
    "    words = text.split()\n",
    "\n",
    "    # Initialize variables for multiline text drawing\n",
    "    lines = []\n",
    "    current_line = \"\"\n",
    "    for word in words:\n",
    "        # Check if the current line plus the next word exceed the image width\n",
    "        if d.textsize(current_line + word, font=font)[0] > max_text_width:\n",
    "            lines.append(current_line)\n",
    "            current_line = word + \" \"\n",
    "        else:\n",
    "            current_line += word + \" \"\n",
    "    lines.append(current_line + \"\\n\")  # Add the last line\n",
    "    \n",
    "    # Calculate the total text height\n",
    "    total_text_height = sum(d.textsize(line, font=font)[1] for line in lines)\n",
    "    \n",
    "    # Calculate the starting position to center the text vertically\n",
    "    start_y = (img_height - total_text_height) // 2\n",
    "\n",
    "    # Draw the multiline text, center-aligned\n",
    "    for line in lines:\n",
    "        text_width, text_height = d.textsize(line, font=font)\n",
    "        start_x = (img_width - text_width) // 2\n",
    "        d.text((start_x, start_y), line, font=font, fill=(0, 0, 0, 128))\n",
    "        start_y += text_height\n",
    "\n",
    "    return img\n",
    "\n",
    "# Open the bash script file in write mode\n",
    "with open('concatenate_videos.sh', 'w') as f:\n",
    "    f.write('#!/bin/bash\\n\\n')\n",
    "\n",
    "    # Initialize list to store the typing effect videos\n",
    "    typing_videos = []\n",
    "\n",
    "    # Initialize list to store the intermediate video files\n",
    "    intermediate_files = []\n",
    "    \n",
    "    import random\n",
    "\n",
    "    # Assuming you have the list of mp4 files named mp4_files\n",
    "    random.shuffle(mp4_files)\n",
    "\n",
    "    # Iterate over mp4 files\n",
    "    for i, mp4_file in enumerate(mp4_files):\n",
    "        # Get the closest .md file text\n",
    "        md_text = closest_md_file(mp4_file)\n",
    "\n",
    "        # If md_text is None, use the filename as the text\n",
    "        if md_text is None:\n",
    "            md_text = mp4_file\n",
    "\n",
    "        # Generate a frame file name\n",
    "        frame_file = f\"frame{i}.png\"\n",
    "\n",
    "        # Create a new multiline image\n",
    "        img = create_multiline_image(md_text)\n",
    "\n",
    "        # Save the frame\n",
    "        img.save(frame_file)\n",
    "\n",
    "        # Add the frame file to the typing effect video list\n",
    "        typing_videos.append(frame_file)\n",
    "\n",
    "        # Add commands to the bash script to generate a 1 sec black screen video with the text\n",
    "        # f.write(f'ffmpeg -y -framerate 30 -i \"{frame_file}\" -c:v libx264 -r 30 -pix_fmt yuv420p text_typing{i}.mp4\\n')\n",
    "        f.write(f'ffmpeg -loop 1 -i \"{frame_file}\" -c:v libx264 -t 2 -pix_fmt yuv420p -r 30 text_typing{i}.mp4\\n')\n",
    "\n",
    "        # Add the typing effect video to the intermediate files list\n",
    "        intermediate_files.append(f'text_typing{i}.mp4')\n",
    "\n",
    "        # Add commands to the bash script to generate a 1 sec black screen video with the text\n",
    "        f.write(f'ffmpeg -y -i \"{mp4_file}\" -c copy output{i}.mp4\\n')\n",
    "        \n",
    "        # Add the output file to the intermediate files list\n",
    "        intermediate_files.append(f'output{i}.mp4')\n",
    "\n",
    "\n",
    "# Add commands to the bash script to create list file for ffmpeg\n",
    "# with open('concatenate_videos.sh', 'a') as f:\n",
    "#     f.write(\"echo -e \\\"\" + \"\\\\n\".join(intermediate_files) + \"\\\" > ffmpeg_concat.txt\\n\")\n",
    "with open('concatenate_videos.sh', 'a') as f:\n",
    "    f.write(\"echo -e \\\"\") \n",
    "    for intermediate_file in intermediate_files:\n",
    "        f.write(\"file \\\"\" + intermediate_file + \"\\\"\" + \"\\\\n\")\n",
    "    f.write(\"\\\" > ffmpeg_concat.txt\\n\")\n",
    "    \n",
    "# Add commands to the bash script to concatenate all intermediate files into the final video\n",
    "with open('concatenate_videos.sh', 'a') as f:\n",
    "    f.write(f\"ffmpeg -y -f concat -safe 0 -i ffmpeg_concat.txt -c copy final_video.mp4\\n\")\n",
    "    \n",
    "\n",
    "with open('playlist.m3u', 'w') as f:\n",
    "    for intermediate_file in intermediate_files:\n",
    "        if \"output\" in intermediate_file:\n",
    "            f.write('/home/mathieuacher/Documents/INPROGRESS/enduserprogrammingLLM/Flappy Bird/' + intermediate_file + '\\n')\n",
    "\n",
    "# Add commands to the bash script to remove all intermediate files\n",
    "# with open('concatenate_videos.sh', 'a') as f:\n",
    "#    for file in intermediate_files:\n",
    "#        f.write(f\"rm \\\"{file}\\\"\\n\")\n",
    "        \n",
    "# Remove list file\n",
    "# with open('concatenate_videos.sh', 'a') as f:\n",
    "#    f.write(\"rm ffmpeg_concat.txt\\n\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a25f71f7",
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   "outputs": [],
   "source": []
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  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f157329f",
   "metadata": {},
   "outputs": [],
   "source": []
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