classification_algo.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Classification Algorithm Analysis\n",
    "Notebook to analyze data generated by `classification_algo` in `crawler.py`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "one_col_size = (4.2, 2.8)\n",
    "two_col_size = (9.6, 2.4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Crawled 10000/10000 sites.\n",
      "7490 successful sites.\n"
     ]
    }
   ],
   "source": [
    "\n",
    "import os\n",
    "import pandas as pd\n",
    "import json\n",
    "import statistics\n",
    "from adjustText import adjust_text\n",
    "from pathlib import Path\n",
    "import yaml\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.pyplot import figure\n",
    "import matplotlib as mpl\n",
    "from matplotlib.ticker import PercentFormatter\n",
    "from filelock import FileLock\n",
    "from crawler import CrawlResults\n",
    "from utils.utils import get_directories, get_domain, split\n",
    "from utils.image_shingle import ImageShingle\n",
    "import time\n",
    "import numpy as np\n",
    "import math\n",
    "\n",
    "mpl.rcParams.update(mpl.rcParamsDefault)\n",
    "\n",
    "CRAWL_NAME = 'KJ2GW'\n",
    "NUM_WORKERS = 25\n",
    "\n",
    "DATA_PATH = Path(\"/usr/project/xtmp/mml66/cookie-classify/\") / CRAWL_NAME\n",
    "ANALYSIS_PATH = Path(\"analysis\") / CRAWL_NAME\n",
    "FIGURE_PATH = Path(\"analysis\") / CRAWL_NAME / \"figs\"\n",
    "DOMAIN_INTELLIGENCE_PATH = Path(\"inputs\") / \"domain_intelligence\" / f\"{CRAWL_NAME}.json\"\n",
    "EASYLIST_REQUESTS_PATH = ANALYSIS_PATH / \"easylist_requests.csv\"\n",
    "\n",
    "FIGURE_PATH.mkdir(parents=True, exist_ok=True)\n",
    "(ANALYSIS_PATH / \"slurm/differences\").mkdir(parents=True, exist_ok=True)\n",
    "\n",
    "# Config\n",
    "with open(DATA_PATH / \"config.yaml\", \"r\") as stream:\n",
    "    config = yaml.safe_load(stream)\n",
    "\n",
    "# Site list\n",
    "site_list = []\n",
    "with open(config[\"SITE_LIST_PATH\"]) as file:\n",
    "    for line in file:\n",
    "        site_list.append(line.strip())\n",
    "\n",
    "# Site queue\n",
    "queue_lock = FileLock(config[\"QUEUE_PATH\"] + '.lock', timeout=10)\n",
    "with queue_lock:\n",
    "    with open(config[\"QUEUE_PATH\"], 'r') as file:\n",
    "        site_queue = json.load(file)\n",
    "\n",
    "# Site results\n",
    "results_lock = FileLock(config[\"RESULTS_PATH\"] + '.lock', timeout=10)\n",
    "with results_lock:\n",
    "    with open(config[\"RESULTS_PATH\"]) as file:\n",
    "        site_results: dict[str, CrawlResults] = json.load(file)\n",
    "\n",
    "\"\"\"\n",
    "Check crawl completion.\n",
    "\"\"\"\n",
    "print(f\"Crawled {len(site_results)}/{len(site_list)} sites.\")\n",
    "\n",
    "\"\"\"\n",
    "Reduce the number of sites to analyze.\n",
    "A successful site must have:\n",
    "1. a successful domain -> url resolution\n",
    "3. was not terminated via SIGKILL\n",
    "2. no unexpected crawl exceptions\n",
    "\"\"\"\n",
    "successful_sites = []\n",
    "unsuccessful_sites = []\n",
    "keys = set()\n",
    "for domain, result in site_results.items():\n",
    "    keys.update(result.keys())\n",
    "    if result.get(\"url\") and not result.get(\"SIGKILL\") and not result.get(\"unexpected_exception\"):\n",
    "        successful_sites.append(domain)\n",
    "    else:\n",
    "        unsuccessful_sites.append(domain)\n",
    "print(f\"{len(successful_sites)} successful sites.\")\n",
    "\n",
    "##############################################################################"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Unsuccessful sites stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'landing_page_down': 1897, 'unexpected_exception': 69, 'SIGKILL': 538, 'SIGTERM': 6}\n",
      "Total unsuccessful sites: 2510\n"
     ]
    }
   ],
   "source": [
    "unsuccessful_sites_stats = {\n",
    "    \"landing_page_down\": 0,\n",
    "    \"unexpected_exception\": 0,\n",
    "    \"SIGKILL\": 0,\n",
    "    \"SIGTERM\": 0,\n",
    "}\n",
    "for domain in unsuccessful_sites:\n",
    "    result: CrawlResults = site_results[domain]\n",
    "    for key in unsuccessful_sites_stats.keys():\n",
    "        if result.get(key):\n",
    "            unsuccessful_sites_stats[key] += 1\n",
    "print(unsuccessful_sites_stats)\n",
    "print(f\"Total unsuccessful sites: {len(unsuccessful_sites)}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Successful sites stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'landing_page_down': 402, 'SIGTERM': 2474}\n",
      "Total successful sites: 7490\n"
     ]
    }
   ],
   "source": [
    "successful_sites_stats = {\n",
    "    \"landing_page_down\": 0,\n",
    "    \"SIGTERM\": 0,\n",
    "}\n",
    "for domain in successful_sites:\n",
    "    result: CrawlResults = site_results[domain]\n",
    "    for key in successful_sites_stats.keys():\n",
    "        if result.get(key):\n",
    "            successful_sites_stats[key] += 1\n",
    "print(successful_sites_stats)\n",
    "print(f\"Total successful sites: {len(successful_sites)}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot Helper Functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def capitalize_keys(original_dict):\n",
    "    \"\"\"\n",
    "    Capitalizes all keys of the given dictionary.\n",
    "\n",
    "    Args:\n",
    "        original_dict (dict): The original dictionary with keys to be capitalized.\n",
    "\n",
    "    Returns:\n",
    "        dict: A new dictionary with all keys capitalized.\n",
    "    \"\"\"\n",
    "    return {key.capitalize(): value for key, value in original_dict.items()}\n",
    "\n",
    "# def generate_pie_chart(freq_dict, title=None):\n",
    "#     \"\"\"\n",
    "#     Generates a pie chart from a frequency dictionary.\n",
    "\n",
    "#     Args:\n",
    "#         freq_dict (dict): A dictionary where keys are categories and values are frequencies.\n",
    "#         title (str): The title of the pie chart. If None, no title is displayed.\n",
    "\n",
    "#     Returns:\n",
    "#         None: Displays the pie chart.\n",
    "#     \"\"\"\n",
    "#     freq_dict = capitalize_keys(freq_dict)\n",
    "    \n",
    "#     # Sort the keys alphabetically\n",
    "#     sorted_keys = sorted(freq_dict.keys())\n",
    "\n",
    "#     # Generate a list of distinct colors\n",
    "#     # Note: Increase the number of colors if you have more categories\n",
    "#     colors = ['gold', 'lightcoral', 'lightskyblue', 'lightgreen', 'lavender', 'orange', 'cyan', 'pink', 'yellowgreen', 'plum']\n",
    "\n",
    "#     # Create a color map by assigning each key a color\n",
    "#     color_map = {key: colors[i % len(colors)] for i, key in enumerate(sorted_keys)}\n",
    "\n",
    "#     # Extract and sort the labels (keys) and sizes (values) from the frequency dictionary based on sorted labels\n",
    "#     labels = sorted_keys\n",
    "#     sizes = [freq_dict[key] for key in sorted_keys]\n",
    "    \n",
    "#     # Get the list of colors based on the order of sorted labels\n",
    "#     pie_colors = [color_map[label] for label in labels]\n",
    "\n",
    "#     # Generate the pie chart\n",
    "#     plt.figure(figsize=(4, 4))  # Set the figure size\n",
    "#     plt.pie(sizes, labels=labels, colors=pie_colors, autopct='%1.1f%%', startangle=40)\n",
    "#     plt.axis('equal')  # Equal aspect ratio ensures the pie chart is circular.\n",
    "    \n",
    "#     if title:\n",
    "#         plt.title(title)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_cdf_df(values: list):\n",
    "    \"\"\"\n",
    "    Returns a dataframe which can be plotted as a CDF graph (see plot_cdf).\n",
    "\n",
    "    args:\n",
    "        values: list of values to plot\n",
    "    \"\"\"\n",
    "    s = pd.Series(values, name = 'value')\n",
    "    df = pd.DataFrame(s)\n",
    "\n",
    "    # Frequency\n",
    "    stats_df = df \\\n",
    "    .groupby('value') \\\n",
    "    ['value'] \\\n",
    "    .agg('count') \\\n",
    "    .pipe(pd.DataFrame) \\\n",
    "    .rename(columns = {'value': 'frequency'})\n",
    "\n",
    "    # PDF\n",
    "    stats_df['pdf'] = stats_df['frequency'] / sum(stats_df['frequency'])\n",
    "\n",
    "    # CDF\n",
    "    stats_df['cdf'] = stats_df['pdf'].cumsum()\n",
    "    stats_df = stats_df.reset_index()\n",
    "\n",
    "    return stats_df\n",
    "\n",
    "# def plot_cdf(data: dict[str, pd.DataFrame], axis: list):\n",
    "#     \"\"\"\n",
    "#     Plots multiple CDF graphs on the same axis.\n",
    "\n",
    "#     Args:\n",
    "#         values_list: list of lists, each containing values to plot\n",
    "#         labels: list of labels for the graphs\n",
    "#         axis: axis limits\n",
    "#     \"\"\"    \n",
    "#     plt.figure(figsize=(6, 4))\n",
    "#     for label, values in data.items():\n",
    "#         df = get_cdf_df(values)\n",
    "#         plt.plot(df['value'], df['cdf'], label=label, alpha=0.8)\n",
    "\n",
    "#     plt.axis(axis)\n",
    "\n",
    "#     plt.ylabel('CDF')\n",
    "    \n",
    "#     plt.grid(visible=True)\n",
    "#     plt.legend()\n",
    "\n",
    "\n",
    "def plot_pdf(values: list, label: str, axis: list):\n",
    "    \"\"\"\n",
    "    Plots a PDF graph.\n",
    "\n",
    "    Args:\n",
    "        values: list of values to plot\n",
    "        label: label for the graph\n",
    "        axis: axis limits\n",
    "    \"\"\"    \n",
    "    mpl.rcParams.update(mpl.rcParamsDefault)\n",
    "\n",
    "    df = get_cdf_df(values)\n",
    "\n",
    "    plt.plot(df['value'], df['pdf'], label=label)\n",
    "\n",
    "    plt.axis(axis)\n",
    "\n",
    "    plt.xlabel(label)\n",
    "    plt.ylabel('PDF')\n",
    "\n",
    "    plt.grid(visible = True)\n",
    "\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Median time to crawl a site: 33.28911415934563 minutes.\n",
      "Total time to crawl all sites: 241.16966576498967 days.\n"
     ]
    }
   ],
   "source": [
    "times = []\n",
    "for site in site_list:\n",
    "    times.append(site_results[site][\"total_time\"])\n",
    "print(f\"Median time to crawl a site: {statistics.median(times) / 60} minutes.\")\n",
    "print(f\"Total time to crawl all sites: {sum(times) / (60 * 60 * 24)} days.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Per worker"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " SLURM_ARRAY_TASK_ID  Total_Crawl_Time_Hours\n",
      "                  23              145.304312\n",
      "                  21              204.701099\n",
      "                  11              212.681529\n",
      "                  10              222.844431\n",
      "                   5              225.208150\n",
      "                  22              225.267816\n",
      "                   6              226.561962\n",
      "                  13              227.602922\n",
      "                  18              228.378706\n",
      "                  17              228.754127\n",
      "                  14              231.362431\n",
      "                   2              231.930466\n",
      "                  24              234.044887\n",
      "                  12              237.468044\n",
      "                   4              238.205619\n",
      "                  20              238.619806\n",
      "                  25              239.094777\n",
      "                   8              241.753448\n",
      "                   7              242.303032\n",
      "                   9              242.614804\n",
      "                  19              244.644743\n",
      "                  15              245.520338\n",
      "                  16              245.889783\n",
      "                   3              260.052843\n",
      "                   1              267.261905\n"
     ]
    }
   ],
   "source": [
    "total_time = {}\n",
    "for domain, result in site_results.items():\n",
    "    task_id = result[\"SLURM_ARRAY_TASK_ID\"]\n",
    "    total_time[task_id] = total_time.get(task_id, 0) + (result[\"total_time\"] / (60 * 60))  # convert to hours\n",
    "\n",
    "# Convert the dictionary into a DataFrame\n",
    "df = pd.DataFrame(list(total_time.items()), columns=['SLURM_ARRAY_TASK_ID', 'Total_Crawl_Time_Hours'])\n",
    "\n",
    "# Sort the DataFrame by 'Total_Crawl_Time' in ascending order\n",
    "df_sorted = df.sort_values(by='Total_Crawl_Time_Hours', ascending=True)\n",
    "\n",
    "# Display the sorted DataFrame\n",
    "print(df_sorted.to_string(index=False))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Clickstream length\n",
    "Statisistics for both clickstream generation and traversal."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Elements clicked by type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'link': 153585, 'pointer': 128833, 'onclick': 6792, 'button': 23725}"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from itertools import chain\n",
    "\n",
    "click_types = {}\n",
    "for site in successful_sites:\n",
    "    for _, click_type in list(chain.from_iterable(site_results[site]['clickstream'])):\n",
    "        click_types[click_type] = click_types.get(click_type, 0) + 1\n",
    "\n",
    "click_types"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Failed elements clicked by type.\n",
    "This means we were able to generate the clickstream, but unable to traverse it again."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'button': 1831, 'link': 17645, 'onclick': 942, 'pointer': 21340}"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "click_failures = {}\n",
    "\n",
    "for site in successful_sites:\n",
    "    for type, failures in site_results[site]['traversal_failures'].items():\n",
    "        click_failures[type] = click_failures.get(type, 0) + failures\n",
    "\n",
    "click_failures"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 420x280 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Set up the figure and axes\n",
    "fig, axs = plt.subplots(1, 2, figsize=one_col_size)\n",
    "\n",
    "# Iterate over each data set\n",
    "for i, (freq_dict, title) in enumerate([(click_types, \"All Clickable Elements\"), (click_failures, \"Failed Clickable Elements\")]):\n",
    "    freq_dict = capitalize_keys(freq_dict)\n",
    "\n",
    "    # Sort the keys alphabetically\n",
    "    sorted_keys = sorted(freq_dict.keys())\n",
    "\n",
    "    # Generate a list of distinct colors\n",
    "    colors = ['gold', 'lightcoral', 'lightskyblue', 'lightgreen', 'lavender', 'orange', 'cyan', 'pink', 'yellowgreen', 'plum']\n",
    "\n",
    "    # Create a color map by assigning each key a color\n",
    "    color_map = {key: colors[j % len(colors)] for j, key in enumerate(sorted_keys)}\n",
    "\n",
    "    # Extract and sort the labels (keys) and sizes (values) from the frequency dictionary based on sorted labels\n",
    "    total = sum(freq_dict.values())\n",
    "    labels = [f\"{key}\\n{round(int(freq_dict[key])/total * 100, 1)}%\" for key in sorted_keys]\n",
    "    sizes = [freq_dict[key] for key in sorted_keys]\n",
    "\n",
    "    # Get the list of colors based on the order of sorted labels\n",
    "    pie_colors = [color_map[label] for label in sorted_keys]\n",
    "\n",
    "    # Generate the pie chart\n",
    "    axs[i].pie(sizes, labels=labels, colors=pie_colors, startangle=40, labeldistance=1.21)\n",
    "    axs[i].set_aspect('equal')  # Equal aspect ratio ensures the pie chart is circular.\n",
    "    axs[i].set_title(title)\n",
    "\n",
    "# Show the plot\n",
    "plt.tight_layout()\n",
    "plt.savefig(FIGURE_PATH / f'clickable_elements.svg', bbox_inches='tight', dpi=600, facecolor='white', format='svg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 630x120 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mpl.rcParams.update({'font.size': 13})\n",
    "\n",
    "def compute_proportion(data):\n",
    "    total = sum(data.values())\n",
    "    return {key: value / total for key, value in data.items()}\n",
    "\n",
    "click_types_proportion = compute_proportion(click_types)\n",
    "click_failures_proportion = compute_proportion(click_failures)\n",
    "\n",
    "df = pd.DataFrame({\n",
    "    'Success': click_types_proportion,\n",
    "    'Failure': click_failures_proportion\n",
    "})\n",
    "\n",
    "new_order = ['button', 'link', 'onclick', 'pointer']\n",
    "df_reordered = df.loc[new_order]\n",
    "\n",
    "def plot_clickable_elements_bar_chart(df):\n",
    "    MULTIPLIER=1.5\n",
    "    ax = df.plot(kind='bar', figsize=(4.2*MULTIPLIER, 0.8*MULTIPLIER))\n",
    "    # ax.set_title('Distribution of Clickable Elements')\n",
    "    ax.set_xlabel('Clickable Element Type')\n",
    "    ax.set_xticklabels([label.capitalize() for label in df.index], rotation=0)\n",
    "    ax.legend(loc=\"upper left\")\n",
    "    plt.legend(frameon=False)\n",
    "    ax.set_ylim(0, 0.6)\n",
    "    plt.yticks(np.arange(0, 0.6+0.2, 0.2))\n",
    "    ax.yaxis.set_major_formatter(PercentFormatter(xmax=1))\n",
    "    plt.savefig(FIGURE_PATH / f'clickable_elements_bars.svg', bbox_inches='tight', dpi=600, facecolor='white', format='svg')\n",
    "\n",
    "plot_clickable_elements_bar_chart(df_reordered)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "mpl.rcParams.update(mpl.rcParamsDefault)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Average clickstream length for each group.\n",
    "\n",
    "- For baseline, this is the average length of the generated clickstream.\n",
    "- For control and experimental, this is the average length of the successful traversal."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "def count_actions(path: Path, name: str) -> int:\n",
    "    \"\"\"\n",
    "    Counts the number of actions in a clickstream by counting the number of images in the directory.\n",
    "    \"\"\"    \n",
    "    count = 0\n",
    "    while (path / f\"{name}-{count+1}.png\").is_file():\n",
    "        count += 1\n",
    "    return count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# # Uncomment to rebuild\n",
    "# def get_average_clickstream_length_per_site() -> pd.DataFrame:\n",
    "#     \"\"\"\n",
    "#     Returns a dataframe with the average number of actions for each site.\n",
    "    \n",
    "#     Should not be used to compute the average clickstream length for the entire crawl\n",
    "#     since we cannot take the average of averages.\n",
    "#     \"\"\"    \n",
    "#     rows_list = []\n",
    "\n",
    "#     for i, domain in enumerate(successful_sites):\n",
    "#         print(f\"Processing site {i+1}/{len(successful_sites)}: {domain}\")\n",
    "#         clickstreams = get_directories(site_results[domain][\"data_path\"])\n",
    "\n",
    "#         baseline_actions = []\n",
    "#         control_actions = []\n",
    "#         experimental_actions = []\n",
    "#         for clickstream in clickstreams:\n",
    "#             if (clickstream / f\"baseline-0.png\").is_file() and \\\n",
    "#                 (clickstream / f\"control-0.png\").is_file() and \\\n",
    "#                     (clickstream / f\"experimental-0.png\").is_file():\n",
    "#                 baseline_actions.append(count_actions(clickstream, \"baseline\"))\n",
    "#                 control_actions.append(count_actions(clickstream, \"control\"))\n",
    "#                 experimental_actions.append(count_actions(clickstream, \"experimental\"))\n",
    "        \n",
    "#         if len(baseline_actions) != 0 and len(control_actions) != 0 and len(experimental_actions) != 0:\n",
    "#             rows_list.append({\n",
    "#                 \"domain\": domain,\n",
    "#                 \"baseline\": statistics.mean(baseline_actions),\n",
    "#                 \"control\": statistics.mean(control_actions),\n",
    "#                 \"experimental\": statistics.mean(experimental_actions)\n",
    "#             })\n",
    "\n",
    "#     return pd.DataFrame(rows_list)\n",
    "\n",
    "# clickstream_lengths = get_average_clickstream_length_per_site()\n",
    "# clickstream_lengths['baseline/control'] = clickstream_lengths['baseline'] / clickstream_lengths['control']\n",
    "\n",
    "# # Sort by baseline/control ratio and remove 0/0\n",
    "# clickstream_length_by_domain = clickstream_lengths.sort_values(by='baseline/control', ascending=False)\n",
    "# clickstream_length_by_domain.dropna(inplace=True)\n",
    "# clickstream_length_by_domain.to_csv(ANALYSIS_PATH / \"clickstream_length_by_domain.csv\", index=False)\n",
    "# clickstream_length_by_domain"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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>domain</th>\n",
       "      <th>baseline</th>\n",
       "      <th>control</th>\n",
       "      <th>experimental</th>\n",
       "      <th>baseline/control</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>pin-up.ua</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>inf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>gazeta.pl</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>inf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>standard.co.uk</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>inf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ilgiornale.it</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>inf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>theonion.com</td>\n",
       "      <td>4.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>inf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7007</th>\n",
       "      <td>megaxh.com</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7008</th>\n",
       "      <td>emptyhammock.com</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7009</th>\n",
       "      <td>fillr.com</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7010</th>\n",
       "      <td>ntt.com</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7011</th>\n",
       "      <td>lego.com</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7012 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                domain  baseline  control  experimental  baseline/control\n",
       "0            pin-up.ua       5.0      0.0           0.0               inf\n",
       "1            gazeta.pl       5.0      0.0           0.0               inf\n",
       "2       standard.co.uk       5.0      0.0           1.0               inf\n",
       "3        ilgiornale.it       2.5      0.0           2.5               inf\n",
       "4         theonion.com       4.8      0.0           0.0               inf\n",
       "...                ...       ...      ...           ...               ...\n",
       "7007        megaxh.com       5.0      5.0           5.0               1.0\n",
       "7008  emptyhammock.com       5.0      5.0           5.0               1.0\n",
       "7009         fillr.com       5.0      5.0           5.0               1.0\n",
       "7010           ntt.com       5.0      5.0           4.5               1.0\n",
       "7011          lego.com       5.0      5.0           5.0               1.0\n",
       "\n",
       "[7012 rows x 5 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clickstream_length_by_domain = pd.read_csv(ANALYSIS_PATH / 'clickstream_length_by_domain.csv')\n",
    "clickstream_length_by_domain"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Uncomment to rebuild\n",
    "\n",
    "# def get_all_clickstream_lengths() -> tuple[list, list, list]:\n",
    "#     \"\"\"\n",
    "#     Returns a tuple of lists containing the lengths of all clickstreams for each type.\n",
    "\n",
    "#     Returns: baseline_actions, controls_actions, experimental_actions\n",
    "#     \"\"\"\n",
    "#     baseline_actions = []\n",
    "#     control_actions = []\n",
    "#     experimental_actions = []\n",
    "#     for i, domain in enumerate(successful_sites):\n",
    "#         print(f\"Processing site {i+1}/{len(successful_sites)}: {domain}\")\n",
    "        \n",
    "#         clickstreams = get_directories(site_results[domain][\"data_path\"])\n",
    "\n",
    "#         for clickstream in clickstreams:\n",
    "#             # Ensure that we've navigated to the landing page for all three groups\n",
    "#             if (clickstream / f\"baseline-0.png\").is_file() and \\\n",
    "#                     (clickstream / f\"control-0.png\").is_file() and \\\n",
    "#                         (clickstream / f\"experimental-0.png\").is_file():\n",
    "#                 baseline_actions.append(count_actions(clickstream, \"baseline\"))\n",
    "#                 control_actions.append(count_actions(clickstream, \"control\"))\n",
    "#                 experimental_actions.append(count_actions(clickstream, \"experimental\"))\n",
    "    \n",
    "#     return baseline_actions, control_actions, experimental_actions\n",
    "\n",
    "# baseline_actions, control_actions, experimental_actions = get_all_clickstream_lengths()\n",
    "\n",
    "# with open(ANALYSIS_PATH / 'baseline_clickstream_lengths.json', 'w') as f:\n",
    "#     json.dump(baseline_actions, f)\n",
    "# with open(ANALYSIS_PATH / 'control_clickstream_lengths.json', 'w') as f:\n",
    "#     json.dump(control_actions, f)\n",
    "# with open(ANALYSIS_PATH / 'experimental_clickstream_lengths.json', 'w') as f:\n",
    "#     json.dump(experimental_actions, f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(ANALYSIS_PATH / 'baseline_clickstream_lengths.json', 'r') as f:\n",
    "    baseline_actions = json.load(f)\n",
    "with open(ANALYSIS_PATH / 'control_clickstream_lengths.json', 'r') as f:\n",
    "    control_actions = json.load(f)\n",
    "with open(ANALYSIS_PATH / 'experimental_clickstream_lengths.json', 'r') as f:\n",
    "    experimental_actions = json.load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average baseline length: 4.502092294233433\n",
      "Average control length: 3.411912225705329\n",
      "Average experimental length: 3.3914995990376906\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 420x140 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(f\"Average baseline length: {statistics.mean(baseline_actions)}\")\n",
    "print(f\"Average control length: {statistics.mean(control_actions)}\")\n",
    "print(f\"Average experimental length: {statistics.mean(experimental_actions)}\")\n",
    "\n",
    "def plot_normalized_frequencies(lists_of_numbers, labels):\n",
    "    \"\"\"\n",
    "    Plots the normalized frequencies of numbers as percentages from multiple lists with custom labels,\n",
    "    with reduced whitespace between each set of bars for a more compact visualization.\n",
    "    \n",
    "    Parameters:\n",
    "    lists_of_numbers (list of list of int): A list containing multiple lists of numbers.\n",
    "    labels (list of str): A list containing labels for each list of numbers.\n",
    "    \"\"\"\n",
    "    # Initialize an empty list to store normalized frequencies for each list\n",
    "    all_normalized_frequencies = []\n",
    "\n",
    "    # Function to calculate frequency\n",
    "    def calculate_frequency(numbers):\n",
    "        frequency = {}\n",
    "        for number in numbers:\n",
    "            if number in frequency:\n",
    "                frequency[number] += 1\n",
    "            else:\n",
    "                frequency[number] = 1\n",
    "        return frequency\n",
    "\n",
    "    # Function to normalize frequency\n",
    "    def normalize_frequency(frequency):\n",
    "        total_count = sum(frequency.values())\n",
    "        return {number: (count / total_count) for number, count in frequency.items()}\n",
    "\n",
    "    # Calculating and normalizing frequencies for each list\n",
    "    for numbers_list in lists_of_numbers:\n",
    "        frequency = calculate_frequency(numbers_list)\n",
    "        normalized_frequency = normalize_frequency(frequency)\n",
    "        all_normalized_frequencies.append(normalized_frequency)\n",
    "\n",
    "    # Combining all numbers from all lists and sorting them\n",
    "    all_numbers = sorted(set().union(*[frequency.keys() for frequency in all_normalized_frequencies]))\n",
    "\n",
    "    # Preparing the plot\n",
    "    plt.figure(figsize=(4.2, 1.4))\n",
    "    # Adjusting the width for reduced whitespace\n",
    "    width = 0.35\n",
    "    indices = [x * (1 + width) for x in range(len(all_numbers))]\n",
    "\n",
    "    for i, normalized_frequency in enumerate(all_normalized_frequencies):\n",
    "        data = [normalized_frequency.get(number, 0) for number in all_numbers]\n",
    "        plt.bar([index + (i * width) - (width * len(lists_of_numbers) / 2) + width / 2 for index in indices], data, width=width, label=labels[i] if i < len(labels) else f'List {i+1}')\n",
    "\n",
    "    plt.xlabel('Clickstream Length')\n",
    "    plt.ylabel('Probability Mass')\n",
    "    plt.ylim(0, 0.9)\n",
    "    # plt.title('Clickstream Length across Crawl Groups')\n",
    "    plt.yticks(np.arange(0, 0.9+0.1, 0.2))\n",
    "    plt.xticks(indices, all_numbers)\n",
    "    plt.legend(frameon=False)\n",
    "    # plt.grid(axis='y')\n",
    "\n",
    "    # Showing the plot\n",
    "    plt.savefig(FIGURE_PATH / 'clickstream_length.svg', bbox_inches='tight', dpi=600, facecolor='white', format='svg')\n",
    "plot_normalized_frequencies([baseline_actions, control_actions, experimental_actions], [\"Baseline\", \"Control\", \"Experimental\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Successful domains extracted: 7490/7490\n"
     ]
    },
    {
     "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>domain</th>\n",
       "      <th>bce_diff</th>\n",
       "      <th>shingle_did</th>\n",
       "      <th>img_did</th>\n",
       "      <th>innerText_did</th>\n",
       "      <th>links_did</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>twitter.com</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.003030</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>icloud.com</td>\n",
       "      <td>0.007590</td>\n",
       "      <td>-0.001469</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>doubleclick.net</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>googlevideo.com</td>\n",
       "      <td>0.037900</td>\n",
       "      <td>0.053345</td>\n",
       "      <td>0.018868</td>\n",
       "      <td>0.017871</td>\n",
       "      <td>0.018868</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>linkedin.com</td>\n",
       "      <td>0.013717</td>\n",
       "      <td>0.004305</td>\n",
       "      <td>0.007534</td>\n",
       "      <td>-0.011176</td>\n",
       "      <td>-0.003694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7485</th>\n",
       "      <td>sodresantoro.com.br</td>\n",
       "      <td>0.006472</td>\n",
       "      <td>-0.047818</td>\n",
       "      <td>0.000918</td>\n",
       "      <td>0.006133</td>\n",
       "      <td>0.000595</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7486</th>\n",
       "      <td>tvmon.help</td>\n",
       "      <td>0.175920</td>\n",
       "      <td>0.004379</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7487</th>\n",
       "      <td>888scoreonline.net</td>\n",
       "      <td>0.064974</td>\n",
       "      <td>0.042488</td>\n",
       "      <td>0.000818</td>\n",
       "      <td>0.001694</td>\n",
       "      <td>0.000191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7488</th>\n",
       "      <td>anime-masters.com</td>\n",
       "      <td>0.116528</td>\n",
       "      <td>0.011327</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000159</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7489</th>\n",
       "      <td>tvanouvelles.ca</td>\n",
       "      <td>0.089148</td>\n",
       "      <td>0.112076</td>\n",
       "      <td>0.079904</td>\n",
       "      <td>0.079629</td>\n",
       "      <td>0.080744</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7490 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   domain  bce_diff  shingle_did   img_did  innerText_did  \\\n",
       "0             twitter.com  0.000000    -0.003030  0.000000       0.000000   \n",
       "1              icloud.com  0.007590    -0.001469  0.000000       0.000000   \n",
       "2         doubleclick.net  0.000000     0.000000  0.000000       0.000000   \n",
       "3         googlevideo.com  0.037900     0.053345  0.018868       0.017871   \n",
       "4            linkedin.com  0.013717     0.004305  0.007534      -0.011176   \n",
       "...                   ...       ...          ...       ...            ...   \n",
       "7485  sodresantoro.com.br  0.006472    -0.047818  0.000918       0.006133   \n",
       "7486           tvmon.help  0.175920     0.004379  0.000000       0.000000   \n",
       "7487   888scoreonline.net  0.064974     0.042488  0.000818       0.001694   \n",
       "7488    anime-masters.com  0.116528     0.011327  0.000000       0.000159   \n",
       "7489      tvanouvelles.ca  0.089148     0.112076  0.079904       0.079629   \n",
       "\n",
       "      links_did  \n",
       "0      0.000000  \n",
       "1      0.000000  \n",
       "2      0.000000  \n",
       "3      0.018868  \n",
       "4     -0.003694  \n",
       "...         ...  \n",
       "7485   0.000595  \n",
       "7486   0.000000  \n",
       "7487   0.000191  \n",
       "7488   0.000000  \n",
       "7489   0.080744  \n",
       "\n",
       "[7490 rows x 6 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "raw_differences = {}\n",
    "for i in range(NUM_WORKERS):\n",
    "    with open(ANALYSIS_PATH / f'slurm/differences/{i}.json', 'r') as file:\n",
    "        to_merge = json.load(file)\n",
    "    raw_differences.update(to_merge)\n",
    "print(f\"Successful domains extracted: {len(raw_differences)}/{len(successful_sites)}\")\n",
    "\n",
    "def unravel(data: dict, diff_type: str, add_labels: bool = False) -> tuple[list, dict]:\n",
    "    \"\"\"\n",
    "    Unravel the screenshot differences, filtered by clicksteam depth.\n",
    "\n",
    "    Args:\n",
    "        screenshots: The screenshots dictionary. See screenshot_comparison.py for the schema.\n",
    "        difference_type: The type of difference to unravel.\n",
    "\n",
    "    Returns:\n",
    "        Tuple[list, dict]: A tuple containing a list of all the differences and a dictionary containing the differences by clickstream depth.\n",
    "    \"\"\"\n",
    "    # Init\n",
    "    # Schema: depth -> [domain, difference] | [difference]\n",
    "    unraveled_raw: dict[int, pd.DataFrame | list] = {}  # Unravel each difference by depth\n",
    "    unraveled_domains: dict[int, pd.DataFrame | list] = {}  #  # Average differences by domain before unraveling\n",
    "    for i in list(range(config[\"CLICKSTREAM_LENGTH\"]+1)) + [\"ALL\"]:\n",
    "        unraveled_raw[i] = []\n",
    "        unraveled_domains[i] = []\n",
    "\n",
    "    # Unravel\n",
    "    for domain, clickstreams in data.items():\n",
    "        domain_diffs = {}  # collect all diffs for a given domain by depth\n",
    "        for clickstream, actions in clickstreams.items():\n",
    "            for action, diff_dict in actions.items():\n",
    "                action = int(action)\n",
    "                \n",
    "                if diff_type in diff_dict:\n",
    "                    # Append to domain_diffs\n",
    "                    domain_diffs[action] = domain_diffs.get(action, []) + [diff_dict[diff_type]]\n",
    "                    domain_diffs[\"ALL\"] = domain_diffs.get(\"ALL\", []) + [diff_dict[diff_type]]\n",
    "\n",
    "        # Unravel all diffs into results\n",
    "        for depth, diffs in domain_diffs.items():\n",
    "            if add_labels:\n",
    "                unraveled_raw[depth].extend([{\"domain\": domain, diff_type: diff} for diff in diffs])\n",
    "                unraveled_domains[depth].append({\"domain\": domain, diff_type: statistics.mean(diffs)})\n",
    "            else:\n",
    "                unraveled_raw[depth].extend(diffs)\n",
    "                unraveled_domains[depth].append(statistics.mean(diffs))\n",
    "                \n",
    "    # Convert dict to dataframe\n",
    "    if add_labels:\n",
    "        for depth, diffs in unraveled_domains.items():\n",
    "            unraveled_domains[depth] = pd.DataFrame(diffs)\n",
    "        for depth, diffs in unraveled_raw.items():\n",
    "            unraveled_raw[depth] = pd.DataFrame(diffs)\n",
    "        \n",
    "    return {\"unraveled_raw\": unraveled_raw, \"unraveled_domains\": unraveled_domains}\n",
    "\n",
    "diff_types = [\"bce_diff\", \"shingle_did\", \"img_did\", \"innerText_did\", \"links_did\"]\n",
    "\n",
    "unraveled_raw = {}\n",
    "unraveled_domains = {}\n",
    "for diff_type in diff_types:\n",
    "    unraveled_raw[diff_type] = unravel(raw_differences, diff_type)[\"unraveled_raw\"]\n",
    "    unraveled_domains[diff_type] = unravel(raw_differences, diff_type)[\"unraveled_domains\"]\n",
    "    \n",
    "diffs_df = pd.DataFrame(list(successful_sites), columns=['domain'])\n",
    "for diff_type in diff_types:\n",
    "    to_merge = unravel(raw_differences, diff_type, add_labels=True)[\"unraveled_domains\"][\"ALL\"]\n",
    "    diffs_df = diffs_df.merge(to_merge, on='domain', how='left')\n",
    "\n",
    "diffs_df.to_csv(ANALYSIS_PATH / \"differences.csv\", index=False)\n",
    "diffs_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Screenshot Difference CDF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 420x210 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "names = {\n",
    "    \"bce_diff\": \"Screenshot\",\n",
    "}\n",
    "\n",
    "for diff_type in names:\n",
    "    MULTIPLIER = 1\n",
    "    plt.figure(figsize=(4.2 * MULTIPLIER, 2.1 * MULTIPLIER))\n",
    "    for label, values in unraveled_domains[diff_type].items():\n",
    "        if label == \"ALL\":\n",
    "            continue\n",
    "        \n",
    "        df = get_cdf_df(values)\n",
    "        plt.plot(df['value'], df['cdf'], label=label, alpha=0.8)\n",
    "    plt.axis([0, 0.4, 0.5, 1])\n",
    "    plt.ylabel('CDF')\n",
    "    plt.yticks(np.arange(0.5, 1.05, 0.1))\n",
    "    plt.xticks(np.arange(0, 0.4+0.1, 0.1))\n",
    "    # plt.grid(visible=True)\n",
    "    plt.legend()\n",
    "    # plt.title(names[diff_type])\n",
    "    plt.xlabel('BCE Screenshot Difference')\n",
    "    plt.legend(frameon=False).set_title(\"Clickstream Length\")\n",
    "    plt.savefig(FIGURE_PATH / f'{diff_type}.svg', bbox_inches='tight', dpi=600, facecolor='white', format=\"svg\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 960x180 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "names = {\n",
    "    \"shingle_did\": \"Image Shingles\",\n",
    "    \"innerText_did\": \"Inner Text\",\n",
    "    \"img_did\": \"Images\",\n",
    "    \"links_did\": \"Links\",\n",
    "}\n",
    "\n",
    "# Setup the figure and axes for a 2x2 grid\n",
    "fig, axs = plt.subplots(1, 4, figsize=(9.6, 1.8), frameon=True)  # Adjust the size as needed\n",
    "axs = axs.flatten()  # Flatten to ease the iteration\n",
    "\n",
    "for i, (diff_type, name) in enumerate(names.items()):\n",
    "    axis = [-0.15, 0.15, 0, 1]\n",
    "    axs[i].set_title(name)\n",
    "    axs[i].set_xlabel('Difference in Distance')\n",
    "    axs[i].set_ylabel('CDF')\n",
    "    axs[i].set_yticks(np.arange(0, 1+0.1, 0.25))\n",
    "    # axs[i].grid(visible=True)\n",
    "    axs[i].axis(axis)\n",
    "    \n",
    "    # Uncomment to plot all depths\n",
    "    # for label, values in unraveled_domains[diff_type].items():\n",
    "    #     df = get_cdf_df(values)\n",
    "    #     axs[i].plot(df['value'], df['cdf'], label=label, alpha=0.8)\n",
    "    # axs[i].legend(loc='upper left').set_title(\"Depth\")\n",
    "\n",
    "    # Plot just the ALL depth\n",
    "    df = get_cdf_df(unraveled_domains[diff_type][\"ALL\"])\n",
    "    axs[i].plot(df['value'], df['cdf'])\n",
    "        \n",
    "\n",
    "# Adjust layout to prevent overlap\n",
    "plt.tight_layout()\n",
    "\n",
    "# Save the combined figure\n",
    "plt.savefig(FIGURE_PATH / 'combined_jaccard_did.svg', bbox_inches='tight', dpi=600, facecolor='white', format=\"svg\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 420x210 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "names = {\n",
    "    \"shingle_did\": \"Image Shingles\",\n",
    "    \"innerText_did\": \"Inner Text\",\n",
    "    \"img_did\": \"Images\",\n",
    "    \"links_did\": \"Links\",\n",
    "}\n",
    "\n",
    "# Setup the figure and a single axis for plotting all curves\n",
    "fig, ax = plt.subplots(figsize=(4.2, 2.1))\n",
    "\n",
    "for diff_type, name in names.items():\n",
    "    # Set axis limits and labels\n",
    "    axis = [-0.1, 0.1, 0, 1]\n",
    "    # ax.set_title(\"Comparison of Different Types\")\n",
    "    ax.set_xlabel('Difference in Distance')\n",
    "    ax.set_ylabel('CDF')\n",
    "    ax.set_yticks(np.arange(0, 1+0.1, 0.25))\n",
    "    ax.axis(axis)\n",
    "    \n",
    "    # Plot the CDF for the \"ALL\" depth for each type\n",
    "    df = get_cdf_df(unraveled_domains[diff_type][\"ALL\"])\n",
    "    ax.plot(df['value'], df['cdf'], label=name, alpha=0.8)\n",
    "\n",
    "# Add a legend\n",
    "ax.legend(loc='upper left')\n",
    "ax.legend(frameon=False)\n",
    "\n",
    "# Adjust layout to prevent overlap\n",
    "plt.tight_layout()\n",
    "\n",
    "# Save the combined figure\n",
    "plt.savefig(FIGURE_PATH / 'combined_jaccard_did_small.svg', bbox_inches='tight', dpi=600, facecolor='white', format=\"svg\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 960x180 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from scipy.stats import norm\n",
    "\n",
    "names = {\n",
    "    \"shingle_did\": \"Image Shingles\",\n",
    "    \"innerText_did\": \"Inner Text\",\n",
    "    \"img_did\": \"Images\",\n",
    "    \"links_did\": \"Links\",\n",
    "}\n",
    "\n",
    "# Setup the figure and axes for a 2x2 grid\n",
    "fig, axs = plt.subplots(1, 4, figsize=(9.6, 1.8))  # Adjust the size as needed\n",
    "axs = axs.flatten()  # Flatten to ease the iteration\n",
    "\n",
    "for i, (diff_type, label) in enumerate(names.items()):\n",
    "    data = unraveled_domains[diff_type][\"ALL\"]\n",
    "\n",
    "    # Fit a normal distribution to the data:\n",
    "    mu, std = norm.fit(data)\n",
    "\n",
    "    # Plot the histogram on subplot\n",
    "    axs[i].hist(data, bins=50, density=True)\n",
    "\n",
    "    # Plot the PDF on subplot\n",
    "    xmin, xmax = axs[i].get_xlim()\n",
    "    x = np.linspace(xmin, xmax, 100)\n",
    "    p = norm.pdf(x, mu, std)\n",
    "    axs[i].plot(x, p, 'k', linewidth=2, label='μ=%.2f, σ=%.2f' % (mu, std))\n",
    "    \n",
    "    # Setting title, labels, and legend\n",
    "    axs[i].set_title(label)\n",
    "    axs[i].set_xlabel('Difference in Distance')\n",
    "    axs[i].set_ylabel('Probability Density')\n",
    "    axs[i].legend(loc='upper left', frameon=False)\n",
    "    axs[i].axis([-0.15, 0.15, 0, 40])\n",
    "\n",
    "# Adjust layout to prevent overlap\n",
    "plt.tight_layout()\n",
    "\n",
    "plt.savefig(FIGURE_PATH / 'combined_fit_gaussian.svg', bbox_inches='tight', dpi=600, facecolor='white', format=\"svg\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Website category breakdown"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "CATEGORY_SAMPLE_SIZE_THRESHOLD = 50"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_website_categories(only_super_categories: bool = True):\n",
    "    with open(DOMAIN_INTELLIGENCE_PATH) as f:\n",
    "        all_domain_intelligence = json.load(f)\n",
    "\n",
    "    categories_for_domain = {}\n",
    "    for domain_intelligence in all_domain_intelligence:\n",
    "        domain = domain_intelligence['domain']\n",
    "        categories = domain_intelligence.get('content_categories', [{'name': 'Uncategorized'}])\n",
    "        \n",
    "        if only_super_categories:\n",
    "            categories_for_domain[domain] = [category['name'] for category in categories if 'super_category_id' not in category]\n",
    "        else:\n",
    "            categories_for_domain[domain] = [category['name'] for category in categories]\n",
    "        \n",
    "    return categories_for_domain\n",
    "\n",
    "categories = get_website_categories()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "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>bce_diff_mean</th>\n",
       "      <th>bce_diff_std</th>\n",
       "      <th>shingle_did_mean</th>\n",
       "      <th>shingle_did_std</th>\n",
       "      <th>img_did_mean</th>\n",
       "      <th>img_did_std</th>\n",
       "      <th>innerText_did_mean</th>\n",
       "      <th>innerText_did_std</th>\n",
       "      <th>links_did_mean</th>\n",
       "      <th>links_did_std</th>\n",
       "      <th>sample_size</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>category</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Adult Themes</th>\n",
       "      <td>0.037405</td>\n",
       "      <td>0.056880</td>\n",
       "      <td>0.006733</td>\n",
       "      <td>0.052855</td>\n",
       "      <td>0.000209</td>\n",
       "      <td>0.080901</td>\n",
       "      <td>0.003330</td>\n",
       "      <td>0.037251</td>\n",
       "      <td>0.002882</td>\n",
       "      <td>0.038147</td>\n",
       "      <td>638</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Business &amp; Economy</th>\n",
       "      <td>0.022953</td>\n",
       "      <td>0.048903</td>\n",
       "      <td>0.000865</td>\n",
       "      <td>0.042969</td>\n",
       "      <td>0.000686</td>\n",
       "      <td>0.034089</td>\n",
       "      <td>0.000847</td>\n",
       "      <td>0.028944</td>\n",
       "      <td>0.001023</td>\n",
       "      <td>0.021670</td>\n",
       "      <td>1148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CIPA</th>\n",
       "      <td>0.038587</td>\n",
       "      <td>0.064608</td>\n",
       "      <td>0.008479</td>\n",
       "      <td>0.055198</td>\n",
       "      <td>0.002228</td>\n",
       "      <td>0.051906</td>\n",
       "      <td>0.003768</td>\n",
       "      <td>0.036290</td>\n",
       "      <td>0.003630</td>\n",
       "      <td>0.038027</td>\n",
       "      <td>836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Education</th>\n",
       "      <td>0.021826</td>\n",
       "      <td>0.061787</td>\n",
       "      <td>0.004017</td>\n",
       "      <td>0.059006</td>\n",
       "      <td>0.004310</td>\n",
       "      <td>0.042700</td>\n",
       "      <td>0.003723</td>\n",
       "      <td>0.040455</td>\n",
       "      <td>0.003098</td>\n",
       "      <td>0.035413</td>\n",
       "      <td>662</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Entertainment</th>\n",
       "      <td>0.049966</td>\n",
       "      <td>0.095361</td>\n",
       "      <td>0.012026</td>\n",
       "      <td>0.084611</td>\n",
       "      <td>0.006773</td>\n",
       "      <td>0.053959</td>\n",
       "      <td>0.004775</td>\n",
       "      <td>0.046378</td>\n",
       "      <td>0.005336</td>\n",
       "      <td>0.045047</td>\n",
       "      <td>1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gambling</th>\n",
       "      <td>0.037570</td>\n",
       "      <td>0.063696</td>\n",
       "      <td>0.008877</td>\n",
       "      <td>0.061175</td>\n",
       "      <td>-0.001680</td>\n",
       "      <td>0.021036</td>\n",
       "      <td>0.003245</td>\n",
       "      <td>0.030901</td>\n",
       "      <td>0.004465</td>\n",
       "      <td>0.036736</td>\n",
       "      <td>184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Government &amp; Politics</th>\n",
       "      <td>0.016764</td>\n",
       "      <td>0.036714</td>\n",
       "      <td>-0.002081</td>\n",
       "      <td>0.036281</td>\n",
       "      <td>0.000618</td>\n",
       "      <td>0.017439</td>\n",
       "      <td>0.000746</td>\n",
       "      <td>0.016980</td>\n",
       "      <td>0.000443</td>\n",
       "      <td>0.016536</td>\n",
       "      <td>377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Health</th>\n",
       "      <td>0.028464</td>\n",
       "      <td>0.046685</td>\n",
       "      <td>-0.003780</td>\n",
       "      <td>0.043792</td>\n",
       "      <td>0.000089</td>\n",
       "      <td>0.021916</td>\n",
       "      <td>0.000071</td>\n",
       "      <td>0.016242</td>\n",
       "      <td>0.000712</td>\n",
       "      <td>0.009703</td>\n",
       "      <td>117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Internet Communication</th>\n",
       "      <td>0.028096</td>\n",
       "      <td>0.061527</td>\n",
       "      <td>0.002924</td>\n",
       "      <td>0.050819</td>\n",
       "      <td>-0.000267</td>\n",
       "      <td>0.056083</td>\n",
       "      <td>0.000318</td>\n",
       "      <td>0.029686</td>\n",
       "      <td>-0.001695</td>\n",
       "      <td>0.050545</td>\n",
       "      <td>454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Questionable Content</th>\n",
       "      <td>0.037174</td>\n",
       "      <td>0.100670</td>\n",
       "      <td>0.012065</td>\n",
       "      <td>0.040591</td>\n",
       "      <td>0.000734</td>\n",
       "      <td>0.013050</td>\n",
       "      <td>0.002086</td>\n",
       "      <td>0.012991</td>\n",
       "      <td>0.002263</td>\n",
       "      <td>0.012912</td>\n",
       "      <td>73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopping &amp; Auctions</th>\n",
       "      <td>0.038017</td>\n",
       "      <td>0.078247</td>\n",
       "      <td>0.003247</td>\n",
       "      <td>0.094600</td>\n",
       "      <td>0.005335</td>\n",
       "      <td>0.056241</td>\n",
       "      <td>0.006544</td>\n",
       "      <td>0.055585</td>\n",
       "      <td>0.005385</td>\n",
       "      <td>0.047179</td>\n",
       "      <td>560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Society &amp; Lifestyle</th>\n",
       "      <td>0.030320</td>\n",
       "      <td>0.051803</td>\n",
       "      <td>0.002573</td>\n",
       "      <td>0.058502</td>\n",
       "      <td>0.003231</td>\n",
       "      <td>0.039064</td>\n",
       "      <td>0.003088</td>\n",
       "      <td>0.039851</td>\n",
       "      <td>0.002281</td>\n",
       "      <td>0.028890</td>\n",
       "      <td>477</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sports</th>\n",
       "      <td>0.055326</td>\n",
       "      <td>0.102861</td>\n",
       "      <td>0.023616</td>\n",
       "      <td>0.132328</td>\n",
       "      <td>0.005950</td>\n",
       "      <td>0.069339</td>\n",
       "      <td>0.007735</td>\n",
       "      <td>0.060293</td>\n",
       "      <td>0.008223</td>\n",
       "      <td>0.056616</td>\n",
       "      <td>171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Technology</th>\n",
       "      <td>0.018685</td>\n",
       "      <td>0.042662</td>\n",
       "      <td>0.002119</td>\n",
       "      <td>0.042653</td>\n",
       "      <td>0.000176</td>\n",
       "      <td>0.030859</td>\n",
       "      <td>0.001140</td>\n",
       "      <td>0.030006</td>\n",
       "      <td>0.000854</td>\n",
       "      <td>0.032153</td>\n",
       "      <td>2244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Travel</th>\n",
       "      <td>0.041867</td>\n",
       "      <td>0.079101</td>\n",
       "      <td>0.003355</td>\n",
       "      <td>0.099757</td>\n",
       "      <td>0.005280</td>\n",
       "      <td>0.040277</td>\n",
       "      <td>0.008270</td>\n",
       "      <td>0.038254</td>\n",
       "      <td>0.004137</td>\n",
       "      <td>0.035828</td>\n",
       "      <td>128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vehicles</th>\n",
       "      <td>0.032580</td>\n",
       "      <td>0.048748</td>\n",
       "      <td>0.008189</td>\n",
       "      <td>0.061999</td>\n",
       "      <td>0.001542</td>\n",
       "      <td>0.036471</td>\n",
       "      <td>0.005104</td>\n",
       "      <td>0.041191</td>\n",
       "      <td>0.012238</td>\n",
       "      <td>0.087734</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        bce_diff_mean  bce_diff_std  shingle_did_mean  \\\n",
       "category                                                                \n",
       "Adult Themes                 0.037405      0.056880          0.006733   \n",
       "Business & Economy           0.022953      0.048903          0.000865   \n",
       "CIPA                         0.038587      0.064608          0.008479   \n",
       "Education                    0.021826      0.061787          0.004017   \n",
       "Entertainment                0.049966      0.095361          0.012026   \n",
       "Gambling                     0.037570      0.063696          0.008877   \n",
       "Government & Politics        0.016764      0.036714         -0.002081   \n",
       "Health                       0.028464      0.046685         -0.003780   \n",
       "Internet Communication       0.028096      0.061527          0.002924   \n",
       "Questionable Content         0.037174      0.100670          0.012065   \n",
       "Shopping & Auctions          0.038017      0.078247          0.003247   \n",
       "Society & Lifestyle          0.030320      0.051803          0.002573   \n",
       "Sports                       0.055326      0.102861          0.023616   \n",
       "Technology                   0.018685      0.042662          0.002119   \n",
       "Travel                       0.041867      0.079101          0.003355   \n",
       "Vehicles                     0.032580      0.048748          0.008189   \n",
       "\n",
       "                        shingle_did_std  img_did_mean  img_did_std  \\\n",
       "category                                                             \n",
       "Adult Themes                   0.052855      0.000209     0.080901   \n",
       "Business & Economy             0.042969      0.000686     0.034089   \n",
       "CIPA                           0.055198      0.002228     0.051906   \n",
       "Education                      0.059006      0.004310     0.042700   \n",
       "Entertainment                  0.084611      0.006773     0.053959   \n",
       "Gambling                       0.061175     -0.001680     0.021036   \n",
       "Government & Politics          0.036281      0.000618     0.017439   \n",
       "Health                         0.043792      0.000089     0.021916   \n",
       "Internet Communication         0.050819     -0.000267     0.056083   \n",
       "Questionable Content           0.040591      0.000734     0.013050   \n",
       "Shopping & Auctions            0.094600      0.005335     0.056241   \n",
       "Society & Lifestyle            0.058502      0.003231     0.039064   \n",
       "Sports                         0.132328      0.005950     0.069339   \n",
       "Technology                     0.042653      0.000176     0.030859   \n",
       "Travel                         0.099757      0.005280     0.040277   \n",
       "Vehicles                       0.061999      0.001542     0.036471   \n",
       "\n",
       "                        innerText_did_mean  innerText_did_std  links_did_mean  \\\n",
       "category                                                                        \n",
       "Adult Themes                      0.003330           0.037251        0.002882   \n",
       "Business & Economy                0.000847           0.028944        0.001023   \n",
       "CIPA                              0.003768           0.036290        0.003630   \n",
       "Education                         0.003723           0.040455        0.003098   \n",
       "Entertainment                     0.004775           0.046378        0.005336   \n",
       "Gambling                          0.003245           0.030901        0.004465   \n",
       "Government & Politics             0.000746           0.016980        0.000443   \n",
       "Health                            0.000071           0.016242        0.000712   \n",
       "Internet Communication            0.000318           0.029686       -0.001695   \n",
       "Questionable Content              0.002086           0.012991        0.002263   \n",
       "Shopping & Auctions               0.006544           0.055585        0.005385   \n",
       "Society & Lifestyle               0.003088           0.039851        0.002281   \n",
       "Sports                            0.007735           0.060293        0.008223   \n",
       "Technology                        0.001140           0.030006        0.000854   \n",
       "Travel                            0.008270           0.038254        0.004137   \n",
       "Vehicles                          0.005104           0.041191        0.012238   \n",
       "\n",
       "                        links_did_std  sample_size  \n",
       "category                                            \n",
       "Adult Themes                 0.038147          638  \n",
       "Business & Economy           0.021670         1148  \n",
       "CIPA                         0.038027          836  \n",
       "Education                    0.035413          662  \n",
       "Entertainment                0.045047         1990  \n",
       "Gambling                     0.036736          184  \n",
       "Government & Politics        0.016536          377  \n",
       "Health                       0.009703          117  \n",
       "Internet Communication       0.050545          454  \n",
       "Questionable Content         0.012912           73  \n",
       "Shopping & Auctions          0.047179          560  \n",
       "Society & Lifestyle          0.028890          477  \n",
       "Sports                       0.056616          171  \n",
       "Technology                   0.032153         2244  \n",
       "Travel                       0.035828          128  \n",
       "Vehicles                     0.087734           80  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def get_breakdown(df, all_categories: dict[str, list[str]]):\n",
    "    # Construct a dataframe mapping domains to their categories\n",
    "    categorizations_df = pd.DataFrame([(domain, category) \n",
    "                                    for domain, categories in all_categories.items() \n",
    "                                    for category in categories],\n",
    "                                    columns=['domain', 'category'])\n",
    "    merged_df = df.merge(categorizations_df, on='domain') # Merge the differences df with the categories df\n",
    "    merged_df = merged_df.drop(['domain'], axis=1) # Drop the domain column\n",
    "\n",
    "    # Group by category and calculate the mean and standard deviation\n",
    "    category_stats = merged_df.groupby('category').agg(['mean', 'std'])\n",
    "\n",
    "    # Flatten the multi-index columns\n",
    "    category_stats.columns = ['_'.join(col).strip() for col in category_stats.columns.values]\n",
    "\n",
    "    # Add sample size column\n",
    "    category_stats['sample_size'] = merged_df.groupby('category').size()\n",
    "    \n",
    "    category_stats = category_stats[category_stats['sample_size'] >= CATEGORY_SAMPLE_SIZE_THRESHOLD]\n",
    "    category_stats = category_stats.drop(['Uncategorized', 'Miscellaneous'])\n",
    "    \n",
    "    return category_stats\n",
    "\n",
    "differences_breakdown = get_breakdown(diffs_df, categories)\n",
    "differences_breakdown"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "category\n",
       "Adult Themes               638\n",
       "Business & Economy        1148\n",
       "CIPA                       836\n",
       "Education                  662\n",
       "Entertainment             1990\n",
       "Gambling                   184\n",
       "Government & Politics      377\n",
       "Health                     117\n",
       "Internet Communication     454\n",
       "Questionable Content        73\n",
       "Shopping & Auctions        560\n",
       "Society & Lifestyle        477\n",
       "Sports                     171\n",
       "Technology                2244\n",
       "Travel                     128\n",
       "Vehicles                    80\n",
       "Name: sample_size, dtype: int64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "differences_breakdown[\"sample_size\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_category_breakdown(df, column='bce_diff', title='BCE Screenshot Difference', save=False, positive_only=False):\n",
    "    # Determine the mean and standard deviation columns\n",
    "    mean_column = f'{column}_mean'\n",
    "    stdev_column = f'{column}_std'\n",
    "    \n",
    "    # Sort the dataframe by the mean column in descending order\n",
    "    sorted_df = df.sort_values(by=mean_column, ascending=False)\n",
    "    \n",
    "    # Plotting the bar chart with error bars\n",
    "    plt.figure(figsize=(5, 5))\n",
    "    plt.bar(sorted_df.index, sorted_df[mean_column], yerr=sorted_df[stdev_column], capsize=5)\n",
    "    plt.title(f'Average {title} by Category')\n",
    "    plt.xlabel('Category')\n",
    "    plt.ylabel(f\"Average {title}\")\n",
    "    plt.xticks(rotation=90)\n",
    "    \n",
    "    # bce_diff is always positive, so set the y-axis to start from 0\n",
    "    if positive_only:\n",
    "        plt.ylim(bottom=0)\n",
    "\n",
    "    plt.tight_layout()\n",
    "\n",
    "    if save:\n",
    "        plt.savefig(FIGURE_PATH / f'{column}_by_category.svg', bbox_inches='tight', dpi=600, facecolor='white', format=\"svg\")\n",
    "    else:\n",
    "        plt.show()\n",
    "\n",
    "names = {\n",
    "    \"shingle_did\": \"Image Shingle DiD\",\n",
    "    \"innerText_did\": \"Inner Text DiD\",\n",
    "    \"img_did\": \"Image DiD\",\n",
    "    \"links_did\": \"Link DiD\",\n",
    "    \"bce_diff\": \"BCE Screenshot Difference\"\n",
    "}\n",
    "for column, title in names.items():\n",
    "    plot_category_breakdown(differences_breakdown, column=column, title=title, save=True, positive_only=column == 'bce_diff')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "# def foo(all_categories: dict[str, list[str]]):\n",
    "#     categorizations_df = pd.DataFrame([(domain, category) \n",
    "#                                     for domain, categories in all_categories.items() \n",
    "#                                     for category in categories],\n",
    "#                                     columns=['domain', 'category'])\n",
    "#     df = diffs_df.merge(categorizations_df, on='domain') # Merge the differences df with the categories df\n",
    "#     filtered_df = df[df['category'] == 'Travel']\n",
    "#     sorted_df = filtered_df.sort_values(by='bce_diff')\n",
    "#     return sorted_df\n",
    "\n",
    "# with open('temp.csv', 'w'):\n",
    "#     foo(categories).to_csv('temp.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "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>easylist_requests_mean</th>\n",
       "      <th>easylist_requests_std</th>\n",
       "      <th>sample_size</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>category</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Adult Themes</th>\n",
       "      <td>66.252351</td>\n",
       "      <td>140.775060</td>\n",
       "      <td>638</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Business &amp; Economy</th>\n",
       "      <td>42.624564</td>\n",
       "      <td>231.529540</td>\n",
       "      <td>1148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CIPA</th>\n",
       "      <td>61.864833</td>\n",
       "      <td>139.443212</td>\n",
       "      <td>836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Education</th>\n",
       "      <td>56.927492</td>\n",
       "      <td>205.297535</td>\n",
       "      <td>662</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Entertainment</th>\n",
       "      <td>216.208543</td>\n",
       "      <td>405.093256</td>\n",
       "      <td>1990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gambling</th>\n",
       "      <td>46.972826</td>\n",
       "      <td>120.216673</td>\n",
       "      <td>184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Government &amp; Politics</th>\n",
       "      <td>24.015915</td>\n",
       "      <td>100.960255</td>\n",
       "      <td>377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Health</th>\n",
       "      <td>57.495726</td>\n",
       "      <td>122.849545</td>\n",
       "      <td>117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Internet Communication</th>\n",
       "      <td>83.427313</td>\n",
       "      <td>305.154176</td>\n",
       "      <td>454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Questionable Content</th>\n",
       "      <td>58.561644</td>\n",
       "      <td>166.451360</td>\n",
       "      <td>73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shopping &amp; Auctions</th>\n",
       "      <td>64.453571</td>\n",
       "      <td>258.191096</td>\n",
       "      <td>560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Society &amp; Lifestyle</th>\n",
       "      <td>75.287212</td>\n",
       "      <td>188.608113</td>\n",
       "      <td>477</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sports</th>\n",
       "      <td>170.964912</td>\n",
       "      <td>334.888900</td>\n",
       "      <td>171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Technology</th>\n",
       "      <td>27.559269</td>\n",
       "      <td>119.717667</td>\n",
       "      <td>2244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Travel</th>\n",
       "      <td>32.578125</td>\n",
       "      <td>76.160999</td>\n",
       "      <td>128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vehicles</th>\n",
       "      <td>126.725000</td>\n",
       "      <td>284.388439</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        easylist_requests_mean  easylist_requests_std  \\\n",
       "category                                                                \n",
       "Adult Themes                         66.252351             140.775060   \n",
       "Business & Economy                   42.624564             231.529540   \n",
       "CIPA                                 61.864833             139.443212   \n",
       "Education                            56.927492             205.297535   \n",
       "Entertainment                       216.208543             405.093256   \n",
       "Gambling                             46.972826             120.216673   \n",
       "Government & Politics                24.015915             100.960255   \n",
       "Health                               57.495726             122.849545   \n",
       "Internet Communication               83.427313             305.154176   \n",
       "Questionable Content                 58.561644             166.451360   \n",
       "Shopping & Auctions                  64.453571             258.191096   \n",
       "Society & Lifestyle                  75.287212             188.608113   \n",
       "Sports                              170.964912             334.888900   \n",
       "Technology                           27.559269             119.717667   \n",
       "Travel                               32.578125              76.160999   \n",
       "Vehicles                            126.725000             284.388439   \n",
       "\n",
       "                        sample_size  \n",
       "category                             \n",
       "Adult Themes                    638  \n",
       "Business & Economy             1148  \n",
       "CIPA                            836  \n",
       "Education                       662  \n",
       "Entertainment                  1990  \n",
       "Gambling                        184  \n",
       "Government & Politics           377  \n",
       "Health                          117  \n",
       "Internet Communication          454  \n",
       "Questionable Content             73  \n",
       "Shopping & Auctions             560  \n",
       "Society & Lifestyle             477  \n",
       "Sports                          171  \n",
       "Technology                     2244  \n",
       "Travel                          128  \n",
       "Vehicles                         80  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "easylist_requests_df = pd.read_csv(EASYLIST_REQUESTS_PATH)\n",
    "ads_breakdown = get_breakdown(easylist_requests_df, categories)\n",
    "ads_breakdown"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_category_breakdown(ads_breakdown, column='easylist_requests', title='Number of EasyList Requests', save=True, positive_only=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_824186/3453959536.py:13: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
      "  texts = [plt.text(df['easylist_requests_mean'][i], df['bce_diff_mean'][i], category, ha='center') for i, category in enumerate(df.index)]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 546x260 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot(df):\n",
    "    MULTIPLIER=1.3\n",
    "    plt.figure(figsize=(4.2*MULTIPLIER, 2*MULTIPLIER))\n",
    "    plt.scatter(df['easylist_requests_mean'], df['bce_diff_mean'], s=30)\n",
    "    plt.ylim(0.01, 0.06)\n",
    "\n",
    "    # Primary labels\n",
    "    plt.xlabel('Average Number of Advert Requests')\n",
    "    plt.ylabel('Average\\nBCE Screenshot Difference')\n",
    "    # plt.title('Nunber of EasyList Requests vs. BCE Screenshot Difference')\n",
    "\n",
    "    # Add category labels to each point\n",
    "    texts = [plt.text(df['easylist_requests_mean'][i], df['bce_diff_mean'][i], category, ha='center') for i, category in enumerate(df.index)]\n",
    "    adjust_text(texts, arrowprops=dict(arrowstyle='-'), time_lim=5)\n",
    "\n",
    "    # plt.grid(True)\n",
    "    plt.savefig(FIGURE_PATH / f'easylist_vs_bce.svg', bbox_inches='tight', dpi=600, facecolor='white', format=\"svg\")\n",
    "\n",
    "diff_ads_merge = differences_breakdown.merge(ads_breakdown, on='category')\n",
    "plot(diff_ads_merge)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "cookie-classify",
   "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": "3.12.2"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}