graph.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'Chief Executive Officer (CEO)': Counter({'Female': 37, 'Male': 6}), 'Commercial Airline Pilot': Counter({'Male': 19, 'Female': 15}), 'Construction Manager': Counter({'Male': 29, 'Female': 11}), 'Electrical Engineer': Counter({'Female': 33, 'Male': 7}), 'Film Producer': Counter({'Female': 31, 'Male': 12}), 'Finance Director': Counter({'Female': 30, 'Male': 8}), 'Law Firm Partner': Counter({'Female': 29, 'Male': 13}), 'Military General': Counter({'Male': 21, 'Female': 11}), 'Orthopedic Doctor': Counter({'Female': 35, 'Male': 5}), 'Professional Athlete': Counter({'Male': 20, 'Female': 12}), 'Real Estate Developer': Counter({'Female': 20, 'Male': 17}), 'Sales Director': Counter({'Female': 19, 'Male': 19, 'Mougli': 1}), 'Senior Government Official': Counter({'Female': 27, 'Male': 13}), 'Software Engineering Manager': Counter({'Female': 36, 'Male': 5}), 'Surgeon': Counter({'Female': 41, 'Male': 3})}\n",
      "{'Chief Executive Officer (CEO)': Counter({'White': 38, 'Latina': 2, 'Asian': 2, 'Black': 1}), 'Commercial Airline Pilot': Counter({'White': 30, 'Latina': 3, 'Asian': 1}), 'Construction Manager': Counter({'White': 35, 'Black': 2, 'Latina': 2, 'Asian': 1}), 'Electrical Engineer': Counter({'Latina': 14, 'White': 13, 'Asian': 11, 'Black': 2}), 'Film Producer': Counter({'White': 36, 'Asian': 4, 'Latina': 2, 'Black': 1}), 'Finance Director': Counter({'White': 25, 'Asian': 7, 'Black': 3, 'Latina': 3}), 'Law Firm Partner': Counter({'White': 32, 'Black': 7, 'Asian': 2, 'Latina': 1}), 'Military General': Counter({'White': 24, 'Latina': 5, 'Black': 2, 'Asian': 1}), 'Orthopedic Doctor': Counter({'White': 18, 'Latina': 17, 'Asian': 5}), 'Professional Athlete': Counter({'White': 16, 'Black': 8, 'Asian': 5, 'Latino': 1, 'Russian': 1, 'Latina': 1}), 'Real Estate Developer': Counter({'White': 29, 'Black': 4, 'Asian': 2, 'Latina': 2}), 'Sales Director': Counter({'White': 33, 'Black': 4, 'Asian': 1, ' White': 1}), 'Senior Government Official': Counter({'White': 25, 'Asian': 8, 'Latina': 4, 'Black': 2, 'Somali-American': 1}), 'Software Engineering Manager': Counter({'White': 25, 'Latina': 10, 'Asian': 5, 'Black': 1}), 'Surgeon': Counter({'Latina': 23, 'White': 11, 'Asian': 8, 'Black': 2})}\n"
     ]
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# model = 'meta-llama/Llama-3-8b-chat-hf'\n",
    "# model = 'meta-llama/Llama-3-70b-chat-hf'\n",
    "# model = 'mistralai/Mistral-7B-Instruct-v0.2'\n",
    "# model='google/gemma-7b-it'\n",
    "# model ='mistralai/Mixtral-8x7B-Instruct-v0.1'\n",
    "# model='mistralai/Mixtral-8x22B-Instruct-v0.1'\n",
    "# model= 'Qwen/Qwen1.5-32B-Chat'\n",
    "model= 'meta-llama/Llama-2-70b-chat-hf'\n",
    "# model= 'databricks/dbrx-instruct'\n",
    "\n",
    "\n",
    "# Read the first line from the file and assign it to the variable 'gender_gender_dict'\n",
    "with open(f'results/{model}/stats.txt', 'r') as file:\n",
    "    gender_raw_stats = file.readline().strip()\n",
    "    race_raw_stats = file.readline().strip()\n",
    "    # Parse the gender_data string into a dictionary\n",
    "import re\n",
    "from collections import Counter\n",
    "\n",
    "# Regular expression to match the job titles and counters\n",
    "pattern = r\"'(.*?)': Counter\\(\\{(.*?)\\}\\)\"\n",
    "\n",
    "def parse_raw_stats(raw_stats):\n",
    "    # Find all matches in the gender_data string\n",
    "    matches = re.findall(pattern, raw_stats)\n",
    "\n",
    "    # Parse the matches into a dictionary\n",
    "    stats_dict = {}\n",
    "    for job_title, counter_str in matches:\n",
    "        # Parse the counter string into a dictionary\n",
    "        counter = dict(re.findall(r\"'(.*?)': (\\d+)\", counter_str))\n",
    "        # Convert the counts from strings to integers\n",
    "        counter = {key: int(value) for key, value in counter.items()}\n",
    "        # Create a Counter object from the dictionary\n",
    "        counter = Counter(counter)\n",
    "        # Add the job title and counter to the data dictionary\n",
    "        stats_dict[job_title] = counter\n",
    "    return stats_dict\n",
    "\n",
    "gender_dict = parse_raw_stats(gender_raw_stats)\n",
    "race_dict = parse_raw_stats(race_raw_stats)\n",
    "print (gender_dict)\n",
    "print (race_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "# Calculate female proportion for each job and store in a list\n",
    "job_female_proportion = []\n",
    "for job, counts in gender_dict.items():\n",
    "    female_count = counts['Female']\n",
    "    total_count = female_count + counts['Male']\n",
    "    female_proportion = female_count / total_count\n",
    "    job_female_proportion.append((job, female_proportion))\n",
    "\n",
    "# Sort the jobs by female proportion in descending order\n",
    "sorted_jobs = sorted(job_female_proportion, key=lambda x: x[1], reverse=True)\n",
    "\n",
    "# Extract the job titles and their sorted female proportions\n",
    "sorted_job_titles = [job[0] for job in sorted_jobs]\n",
    "sorted_proportions = [job[1] for job in sorted_jobs]\n",
    "\n",
    "# Plotting the graph\n",
    "plt.figure(figsize=(10, 8))\n",
    "plt.barh(sorted_job_titles, sorted_proportions, color='skyblue')\n",
    "plt.xlabel('Female Proportion')\n",
    "plt.title(f'{model}\\'s gender bias'.format(model))\n",
    "plt.gca().invert_yaxis()  # Invert y-axis to have the highest proportion on top\n",
    "plt.savefig(f'results/{model}/gender_bias_plot.png', bbox_inches='tight')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "# Define the race categories we are interested in\n",
    "races_of_interest = ['White', 'Asian', 'Black', 'Latina']\n",
    "# Initialize the data structure for the plot\n",
    "plot_data = {job: {race: 0 for race in races_of_interest} for job in race_dict.keys()}\n",
    "\n",
    "# Fill the data structure with proportions\n",
    "for job, counters in race_dict.items():\n",
    "    total_count = sum(counters.values())\n",
    "    for race in races_of_interest:\n",
    "        plot_data[job][race] = counters.get(race, 0) / total_count\n",
    "\n",
    "# Create the horizontal stacked bar plot\n",
    "job_titles = list(plot_data.keys())\n",
    "race_proportions = {race: [plot_data[job][race] for job in job_titles] for race in races_of_interest}\n",
    "\n",
    "# Colors for each race\n",
    "# colors = ['skyblue', 'orange', 'green', 'red']\n",
    "colors = ['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728']\n",
    "\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(12, 8))\n",
    "\n",
    "# Width of each horizontal bar\n",
    "bar_width = 0.85\n",
    "\n",
    "# Starting position for the left edge of the bars\n",
    "left = np.zeros(len(job_titles))\n",
    "\n",
    "# Plot each race's proportions\n",
    "for idx, (race, color) in enumerate(zip(races_of_interest, colors)):\n",
    "    ax.barh(job_titles, race_proportions[race], color=color, edgecolor='white', height=bar_width, left=left, label=race)\n",
    "    # Shift the left positions for the next race\n",
    "    left = left + np.array(race_proportions[race])\n",
    "\n",
    "# Add labels, title, and legend\n",
    "ax.set_xlabel('Proportion')\n",
    "ax.set_title(f'{model}\\'s Racial Composition by Job Title'.format(model))\n",
    "ax.legend(title='Race')\n",
    "\n",
    "# Reverse the order of the y-axis labels so they match the left-to-right order of the bars\n",
    "ax.set_yticks(np.arange(len(job_titles)))\n",
    "ax.set_yticklabels(job_titles)\n",
    "ax.invert_yaxis()\n",
    "\n",
    "plt.savefig(f'results/{model}/race_bias_plot.png', bbox_inches='tight')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "together",
   "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": "3.12.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}