3_benchmark_results_complete.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rcParams[\"figure.figsize\"] = (10, 8)\n",
    "plt.rcParams.update({'font.size': 20})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "quality_name_map = {\n",
    "    \"crowdlab\": \"CROWDLAB\",\n",
    "    \"label_quality_score\": \"Label Quality Score\",\n",
    "    \"agreement\": \"Agreement\",\n",
    "    \"active_label_cleaning\": \"Active Label Cleaning\",\n",
    "    \"empirical_bayes\": \"Empirical Bayes\",\n",
    "    \"no_perannotator_weights\": \"No Perannotator Weights\",\n",
    "    \"dawid_skene\": \"Dawid-Skene\",\n",
    "    \"glad\": \"GLAD\",\n",
    "    \"dawid_skene_with_model\": \"Dawid-Skene with Model\",\n",
    "    \"glad_with_model\": \"GLAD with Model\"\n",
    "}\n",
    "\n",
    "consensus_name_map = {\n",
    "    \"majority\": \"Majority Vote (Agreement)\",\n",
    "    \"dawid_skene\": \"Dawid-Skene\",\n",
    "    \"glad\": \"GLAD\",\n",
    "    \"dawid_skene_with_model\": \"Dawid-Skene with Model\",\n",
    "    \"glad_with_model\": \"GLAD with Model\",\n",
    "    \"crowdlab\": \"CROWDLAB\"\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "results = pd.read_csv(\"benchmark_results/results_complete.csv\")\n",
    "\n",
    "results_qual_score = results[(results[\"consensus_method\"] != \"crowdlab\") & (results[\"quality_method\"] != \"no_perannotator_weights\")][\n",
    "        [\n",
    "            \"dataset\",\n",
    "            \"model\",\n",
    "            \"quality_method\",\n",
    "            \"consensus_quality_auroc\",\n",
    "            \"consensus_quality_auprc\", \n",
    "            \"annotator_quality_spearman_corr\"\n",
    "        ]\n",
    "    ]\n",
    "\n",
    "results_accuracy = results[\n",
    "        [\n",
    "            \"dataset\",\n",
    "            \"model\",\n",
    "            \"consensus_method\",\n",
    "            \"consensus_labels_accuracy\",\n",
    "        ]\n",
    "    ].drop_duplicates(ignore_index=True)\n",
    "\n",
    "results_qual_score[\"quality_method\"] = results_qual_score[\"quality_method\"].apply(lambda s: quality_name_map[s])\n",
    "results_accuracy[\"consensus_method\"] = results_accuracy[\"consensus_method\"].apply(lambda s: consensus_name_map[s])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "qual_score_order = {\n",
    "    \"Agreement\": 0,\n",
    "    \"Dawid-Skene\": 1,\n",
    "    \"GLAD\": 2,\n",
    "    \"Dawid-Skene with Model\": 3,\n",
    "    \"GLAD with Model\": 4,\n",
    "    \"Empirical Bayes\": 5,\n",
    "    \"Active Label Cleaning\": 6,\n",
    "    \"Label Quality Score\": 7,\n",
    "    \"CROWDLAB\": 8\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "resnet_qual_score = results_qual_score[results_qual_score[\"model\"] == \"resnet18\"].sort_values(\"quality_method\", key=lambda s: s.map(qual_score_order))\n",
    "swin_qual_score = results_qual_score[results_qual_score[\"model\"] == \"swin\"].sort_values(\"quality_method\", key=lambda s: s.map(qual_score_order))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.arange(len(resnet_qual_score[\"quality_method\"]) - 1, -1, -1)\n",
    "width = 0.4 # the width of the bars\n",
    "\n",
    "plt.barh(x + width/2, resnet_qual_score[\"consensus_quality_auroc\"], width, label=\"ResNet-18\") \n",
    "plt.barh(x - width/2, swin_qual_score[\"consensus_quality_auroc\"], width, label=\"Swin\") \n",
    "\n",
    "plt.xlim(np.min(swin_qual_score[\"consensus_quality_auroc\"]) - 0.03, min(np.max(swin_qual_score[\"consensus_quality_auroc\"]) + 0.03, 1))\n",
    "plt.yticks(x, resnet_qual_score[\"quality_method\"])\n",
    "plt.title(\"AUROC for Consensus Quality Score\")\n",
    "\n",
    "plt.savefig('benchmark_graphs/auroc_complete.png', bbox_inches = \"tight\")  \n",
    "plt.savefig('benchmark_graphs/auroc_complete.pdf', bbox_inches = \"tight\")  \n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.arange(len(resnet_qual_score[\"quality_method\"]) - 1, -1, -1)\n",
    "width = 0.4 # the width of the bars\n",
    "\n",
    "plt.barh(x + width/2, resnet_qual_score[\"consensus_quality_auprc\"], width, label=\"ResNet-18\") \n",
    "plt.barh(x - width/2, swin_qual_score[\"consensus_quality_auprc\"], width, label=\"Swin\") \n",
    "\n",
    "plt.xlim(np.min(swin_qual_score[\"consensus_quality_auprc\"]) - 0.03, min(np.max(swin_qual_score[\"consensus_quality_auprc\"]) + 0.03, 1))\n",
    "plt.yticks(x, resnet_qual_score[\"quality_method\"])\n",
    "plt.title(\"AUPRC for Consensus Quality Score\")\n",
    "\n",
    "plt.savefig('benchmark_graphs/auprc_complete.png', bbox_inches = \"tight\")  \n",
    "plt.savefig('benchmark_graphs/auprc_complete.pdf', bbox_inches = \"tight\") \n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "resnet_qual_score = resnet_qual_score[(resnet_qual_score[\"quality_method\"] != \"Active Label Cleaning\") & (resnet_qual_score[\"quality_method\"] != \"Empirical Bayes\")]\n",
    "swin_qual_score = swin_qual_score[(swin_qual_score[\"quality_method\"] != \"Active Label Cleaning\") & (swin_qual_score[\"quality_method\"] != \"Empirical Bayes\")]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.arange(len(resnet_qual_score[\"quality_method\"]) - 1, -1, -1)\n",
    "width = 0.4 # the width of the bars\n",
    "\n",
    "plt.barh(x + width/2, resnet_qual_score[\"annotator_quality_spearman_corr\"], width, label=\"ResNet-18\") \n",
    "plt.barh(x - width/2, swin_qual_score[\"annotator_quality_spearman_corr\"], width, label=\"Swin\") \n",
    "\n",
    "plt.xlim(np.min(resnet_qual_score[\"annotator_quality_spearman_corr\"]) - 0.03, min(np.max(swin_qual_score[\"annotator_quality_spearman_corr\"]) + 0.03, 1))\n",
    "plt.yticks(x, resnet_qual_score[\"quality_method\"])\n",
    "plt.title(\"Spearman Correlation for Annotator Quality\")\n",
    "\n",
    "plt.savefig('benchmark_graphs/spearman_complete.png', bbox_inches = \"tight\")  \n",
    "plt.savefig('benchmark_graphs/spearman_complete.pdf', bbox_inches = \"tight\")  \n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "accuracy_order = {\n",
    "    \"Majority Vote (Agreement)\": 0,\n",
    "    \"Dawid-Skene\": 1,\n",
    "    \"GLAD\": 2,\n",
    "    \"Dawid-Skene with Model\": 3,\n",
    "    \"GLAD with Model\": 4,\n",
    "    \"CROWDLAB\": 5\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "resnet_accuracy = results_accuracy[results_accuracy[\"model\"] == \"resnet18\"].sort_values(\"consensus_method\", key=lambda s: s.map(accuracy_order))\n",
    "swin_accuracy = results_accuracy[results_accuracy[\"model\"] == \"swin\"].sort_values(\"consensus_method\", key=lambda s: s.map(accuracy_order))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.arange(len(resnet_accuracy[\"consensus_method\"]) - 1, -1, -1)\n",
    "width = 0.4 # the width of the bars\n",
    "\n",
    "plt.barh(x + width/2, resnet_accuracy[\"consensus_labels_accuracy\"], width, label=\"ResNet-18\") \n",
    "plt.barh(x - width/2, swin_accuracy[\"consensus_labels_accuracy\"], width, label=\"Swin\") \n",
    "\n",
    "plt.xlim(np.min(resnet_accuracy[\"consensus_labels_accuracy\"]) - 0.005, min(np.max(swin_accuracy[\"consensus_labels_accuracy\"]) + 0.005, 1))\n",
    "plt.yticks(x, resnet_accuracy[\"consensus_method\"])\n",
    "plt.title(\"Consensus Label Accuracy\")\n",
    "\n",
    "plt.savefig('benchmark_graphs/accuracy_complete.png', bbox_inches = \"tight\")  \n",
    "plt.savefig('benchmark_graphs/accuracy_complete.pdf', bbox_inches = \"tight\")  \n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%capture \n",
    "\n",
    "fig = plt.figure(\"Line plot\")\n",
    "legend_fig = plt.figure(\"Legend plot\")\n",
    "ax = fig.add_subplot()\n",
    "\n",
    "resnet = ax.barh(x + width/2, resnet_accuracy[\"consensus_labels_accuracy\"], width) \n",
    "swin = ax.barh(x - width/2, swin_accuracy[\"consensus_labels_accuracy\"], width) \n",
    "\n",
    "legend_fig.legend([resnet, swin], [\"ResNet-18\", \"Swin Transformer\"], loc=\"center\", ncol=2)\n",
    "\n",
    "legend_fig.set_size_inches(8, 0.75)\n",
    "legend_fig.savefig(\"benchmark_graphs/legend_complete_wide.pdf\")\n",
    "legend_fig.savefig(\"benchmark_graphs/legend_complete_wide.png\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.10.6 ('cl-dev')",
   "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": "3.10.6"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "1b7ac7a092e8f679e0c6d6ca9f3df454c820f76db2a859208803bf085fb9eeb3"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}