PR_delta.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "24e38858-1adb-4285-8b87-9115db79deb0",
   "metadata": {},
   "outputs": [],
   "source": [
    "########################################\n",
    "#Precision & Recall change scatterplots#\n",
    "#Maintainer: Christopher Chan          #\n",
    "#Version: 0.1.1                        #\n",
    "#Date: 2022-08-06                      #\n",
    "########################################\n",
    "\n",
    "import os, sys, re\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline\n",
    "\n",
    "sns.set_theme(style = \"whitegrid\")\n",
    "\n",
    "depth_wise = pd.read_excel(os.path.join(os.getcwd(), \"Precision_Recall_change.ods\"), sheet_name = \"Depth-wise\")\n",
    "data_wise = pd.read_excel(os.path.join(os.getcwd(), \"Precision_Recall_change.ods\"), sheet_name = \"Dataset-wise\")\n",
    "weight_wise = pd.read_excel(os.path.join(os.getcwd(), \"Precision_Recall_change.ods\"), sheet_name = \"Weights-wise\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "04842b28-e3e1-4a51-96d5-2bb5ea914ef0",
   "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>Architecture</th>\n",
       "      <th>Input dataset</th>\n",
       "      <th>Precision change</th>\n",
       "      <th>Recall change</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4 to 5 layer U-Net (NoIMN)</td>\n",
       "      <td>KBY</td>\n",
       "      <td>0.011</td>\n",
       "      <td>-0.003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4 to 5 layer U-Net (NoIMN)</td>\n",
       "      <td>KBY + DZK + DZKN</td>\n",
       "      <td>0.007</td>\n",
       "      <td>-0.002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>EfficientNet B1 to B2 U-Net (NoIMN)</td>\n",
       "      <td>KBY</td>\n",
       "      <td>-0.003</td>\n",
       "      <td>-0.012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>EfficientNet B1 to B2 U-Net (IMN)</td>\n",
       "      <td>KBY</td>\n",
       "      <td>0.003</td>\n",
       "      <td>-0.006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>EfficientNet B1 to B2 U-Net (NoIMN)</td>\n",
       "      <td>KBY + DZK + DZKN</td>\n",
       "      <td>0.023</td>\n",
       "      <td>0.006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>EfficientNet B1 to B2 U-Net (IMN)</td>\n",
       "      <td>KBY + DZK + DZKN</td>\n",
       "      <td>-0.006</td>\n",
       "      <td>-0.002</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          Architecture     Input dataset  Precision change  \\\n",
       "0           4 to 5 layer U-Net (NoIMN)               KBY             0.011   \n",
       "1           4 to 5 layer U-Net (NoIMN)  KBY + DZK + DZKN             0.007   \n",
       "2  EfficientNet B1 to B2 U-Net (NoIMN)               KBY            -0.003   \n",
       "3    EfficientNet B1 to B2 U-Net (IMN)               KBY             0.003   \n",
       "4  EfficientNet B1 to B2 U-Net (NoIMN)  KBY + DZK + DZKN             0.023   \n",
       "5    EfficientNet B1 to B2 U-Net (IMN)  KBY + DZK + DZKN            -0.006   \n",
       "\n",
       "   Recall change  \n",
       "0         -0.003  \n",
       "1         -0.002  \n",
       "2         -0.012  \n",
       "3         -0.006  \n",
       "4          0.006  \n",
       "5         -0.002  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "depth_wise"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "804f8e7f-14af-4e0e-87e4-3e07d53dbbc9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 598.6x360 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Depth-wise change regplot\n",
    "depth_PS = sns.pairplot(depth_wise, \n",
    "                        x_vars = [\"Precision change\", \"Recall change\"], y_vars = [\"Precision change\", \"Recall change\"],\n",
    "                        hue = \"Architecture\", kind = \"reg\", palette = \"colorblind\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "4fc33e72-435f-4111-bc3a-8345295483f7",
   "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>Input dataset</th>\n",
       "      <th>Architecture</th>\n",
       "      <th>Initialised weights</th>\n",
       "      <th>Precision change</th>\n",
       "      <th>Recall change</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>KBY to ALL</td>\n",
       "      <td>4-layer U-Net (NoIMN)</td>\n",
       "      <td>None</td>\n",
       "      <td>-0.065</td>\n",
       "      <td>-0.016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>KBY to ALL</td>\n",
       "      <td>5-layer U-Net (NoIMN)</td>\n",
       "      <td>None</td>\n",
       "      <td>-0.070</td>\n",
       "      <td>-0.153</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>KBY to ALL</td>\n",
       "      <td>EfficientNet B1 U-Net (NoIMN)</td>\n",
       "      <td>None</td>\n",
       "      <td>-0.124</td>\n",
       "      <td>-0.044</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>KBY to ALL</td>\n",
       "      <td>EfficientNet B1 U-Net (IMN)</td>\n",
       "      <td>ImageNet</td>\n",
       "      <td>-0.119</td>\n",
       "      <td>-0.032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>KBY to ALL</td>\n",
       "      <td>EfficientNet B1 U-Net (OCC)</td>\n",
       "      <td>OCC</td>\n",
       "      <td>-0.002</td>\n",
       "      <td>-0.387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>KBY to ALL</td>\n",
       "      <td>EfficientNet B1 U-Net (OCC transfer-trained)</td>\n",
       "      <td>OCC transfer-trained</td>\n",
       "      <td>-0.125</td>\n",
       "      <td>-0.043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>KBY to ALL</td>\n",
       "      <td>EfficientNet B2 U-Net (NoIMN)</td>\n",
       "      <td>None</td>\n",
       "      <td>-0.099</td>\n",
       "      <td>-0.026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>KBY to ALL</td>\n",
       "      <td>EfficientNet B2 U-Net (IMN)</td>\n",
       "      <td>ImageNet</td>\n",
       "      <td>-0.128</td>\n",
       "      <td>-0.028</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Input dataset                                  Architecture  \\\n",
       "0    KBY to ALL                         4-layer U-Net (NoIMN)   \n",
       "1    KBY to ALL                         5-layer U-Net (NoIMN)   \n",
       "2    KBY to ALL                 EfficientNet B1 U-Net (NoIMN)   \n",
       "3    KBY to ALL                   EfficientNet B1 U-Net (IMN)   \n",
       "4    KBY to ALL                   EfficientNet B1 U-Net (OCC)   \n",
       "5    KBY to ALL  EfficientNet B1 U-Net (OCC transfer-trained)   \n",
       "6    KBY to ALL                 EfficientNet B2 U-Net (NoIMN)   \n",
       "7    KBY to ALL                   EfficientNet B2 U-Net (IMN)   \n",
       "\n",
       "    Initialised weights  Precision change  Recall change  \n",
       "0                  None            -0.065         -0.016  \n",
       "1                  None            -0.070         -0.153  \n",
       "2                  None            -0.124         -0.044  \n",
       "3              ImageNet            -0.119         -0.032  \n",
       "4                   OCC            -0.002         -0.387  \n",
       "5  OCC transfer-trained            -0.125         -0.043  \n",
       "6                  None            -0.099         -0.026  \n",
       "7              ImageNet            -0.128         -0.028  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_wise"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f99eb7a2-f46a-446c-b3b4-6935ce50e246",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 873.975x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Dataset-wise change regplot\n",
    "#data_PS = sns.pairplot(data_wise, \n",
    "#                        x_vars = [\"Precision change\", \"Recall change\"], y_vars = [\"Precision change\", \"Recall change\"],\n",
    "#                        hue = \"Architecture\", kind = \"scatter\", palette = \"colorblind\")\n",
    "\n",
    "data_wise_L = pd.melt(data_wise, id_vars = [\"Input dataset\", \"Architecture\", \"Initialised weights\"])\n",
    "\n",
    "data_wise_L\n",
    "\n",
    "data_SP = sns.catplot(data = data_wise_L, x = \"value\", y = \"Architecture\",\n",
    "                      hue = \"Initialised weights\", col = \"variable\",\n",
    "                      kind = \"strip\", orient = \"h\", jitter = False,\n",
    "                      palette = \"colorblind\", s = 7.5)\n",
    "\n",
    "\n",
    "# Use semantically meaningful titles for the columns\n",
    "titles = [\"Precision change\", \"Recall (TPR) change\"]\n",
    "\n",
    "data_SP.despine(bottom = True)\n",
    "\n",
    "for ax, title in zip(data_SP.axes.flat, titles):\n",
    "\n",
    "    # Set a different title for each axes\n",
    "    ax.set(title = title)\n",
    "    \n",
    "    for label in ax.axes.get_yticklabels(which = 'major'):\n",
    "        label.set(rotation=30, horizontalalignment = 'right')\n",
    "\n",
    "    # Make the grid horizontal instead of vertical\n",
    "    ax.xaxis.grid(True)\n",
    "    ax.yaxis.grid(True)\n",
    "    ax.set_xlabel(\"\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c33b5e8f-bf25-45c4-b285-6d3df2e312e5",
   "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>Architecture</th>\n",
       "      <th>Weights change</th>\n",
       "      <th>Input dataset</th>\n",
       "      <th>Precision change</th>\n",
       "      <th>Recall change</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>EfficientNet B1 U-Net (NoIMN to IMN)</td>\n",
       "      <td>None to ImageNet</td>\n",
       "      <td>KBY</td>\n",
       "      <td>0.003</td>\n",
       "      <td>0.0080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>EfficientNet B1 U-Net (NoIMN to IMN)</td>\n",
       "      <td>None to ImageNet</td>\n",
       "      <td>KBY + DZK + DZKN</td>\n",
       "      <td>0.009</td>\n",
       "      <td>0.0197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>EfficientNet B1 U-Net (OCC to OCC transfer-tra...</td>\n",
       "      <td>OCC to OCC transfer-trained</td>\n",
       "      <td>KBY</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.3060</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>EfficientNet B1 U-Net (OCC to OCC transfer-tra...</td>\n",
       "      <td>OCC to OCC transfer-trained</td>\n",
       "      <td>KBY + DZK + DZKN</td>\n",
       "      <td>-0.122</td>\n",
       "      <td>0.6490</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>EfficientNet B2 U-Net (NoIMN to IMN)</td>\n",
       "      <td>None to ImageNet</td>\n",
       "      <td>KBY</td>\n",
       "      <td>0.009</td>\n",
       "      <td>0.0140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>EfficientNet B2 U-Net (NoIMN to IMN)</td>\n",
       "      <td>None to ImageNet</td>\n",
       "      <td>KBY + DZK + DZKN</td>\n",
       "      <td>-0.020</td>\n",
       "      <td>0.0120</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        Architecture  \\\n",
       "0               EfficientNet B1 U-Net (NoIMN to IMN)   \n",
       "1               EfficientNet B1 U-Net (NoIMN to IMN)   \n",
       "2  EfficientNet B1 U-Net (OCC to OCC transfer-tra...   \n",
       "3  EfficientNet B1 U-Net (OCC to OCC transfer-tra...   \n",
       "4               EfficientNet B2 U-Net (NoIMN to IMN)   \n",
       "5               EfficientNet B2 U-Net (NoIMN to IMN)   \n",
       "\n",
       "                Weights change     Input dataset  Precision change  \\\n",
       "0             None to ImageNet               KBY             0.003   \n",
       "1             None to ImageNet  KBY + DZK + DZKN             0.009   \n",
       "2  OCC to OCC transfer-trained               KBY             0.000   \n",
       "3  OCC to OCC transfer-trained  KBY + DZK + DZKN            -0.122   \n",
       "4             None to ImageNet               KBY             0.009   \n",
       "5             None to ImageNet  KBY + DZK + DZKN            -0.020   \n",
       "\n",
       "   Recall change  \n",
       "0         0.0080  \n",
       "1         0.0197  \n",
       "2         0.3060  \n",
       "3         0.6490  \n",
       "4         0.0140  \n",
       "5         0.0120  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weight_wise"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "078790d0-4b94-4587-aa05-448938bde57d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 686.35x360 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Dataset-wise change regplot\n",
    "weight_PS = sns.pairplot(weight_wise, \n",
    "                         x_vars = [\"Precision change\", \"Recall change\"], y_vars = [\"Precision change\", \"Recall change\"],\n",
    "                         hue = \"Architecture\", kind = \"reg\", palette = \"colorblind\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}