notes/ablation-study.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Ablation study of octave UNet on retinal vessel segmentation\n",
    "\n",
    "---\n",
    "\n",
    "This notbook compares the retinal vessel segmentation performances of various octave UNets with different $\\alpha$, where $\\alpha$ is the hyper-parameter that controls the ratio of low frequency feature components of the model. For example, when the $\\alpha$ is set to 0, an octave UNet degenerats into a vanilla UNet, while an octave UNet with $\\alpha$ of 0.5 will process 50% of low frequency features and 50% of high frequency features. \n",
    "\n",
    "We will first define some helper functions, then layout the configurations of experiments, and finlly compare the experimental results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# setup path environment\n",
    "import os\n",
    "import sys\n",
    "\n",
    "project_dir, _ = os.path.split(os.getcwd())\n",
    "if project_dir not in sys.path:\n",
    "    sys.path.append(project_dir)\n",
    "\n",
    "# import packages for data manipulation and drawing\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import scipy as sp\n",
    "\n",
    "# for ploting inline on the notebook\n",
    "from matplotlib import pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "import seaborn as sns\n",
    "sns.set(style='whitegrid')\n",
    "sns.set_context('paper', font_scale=1.5)\n",
    "\n",
    "from PIL import Image\n",
    "import torch\n",
    "from torch.nn import functional as F\n",
    "from torchvision.transforms import functional as TF\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Configurations of experiments\n",
    "\n",
    "---\n",
    "\n",
    "We performed 4 retinal vessel segmentation experiments on DRIVE dataset with the following models:\n",
    "\n",
    "- UNet ($\\alpha = 0.0$)\n",
    "- Octave UNet ($\\alpha = 0.25$)\n",
    "- Octave UNet ($\\alpha = 0.5$)\n",
    "- Octave UNet ($\\alpha = 0.75$)\n",
    "\n",
    "The only differency between these experiments is the hyper-parameter $\\alpha$ of the model used.\n",
    "\n",
    "These models have the same number of trainable parameters (~16.54M) and are trained with the same procedure. Specifically, they are trained with Adam optimizer for 1000 epoch with batch size of 4, with loss function of weighted binary cross entropy. Please refer to the `run_time_configs.yaml` file under the experiment folder for details of the complete experiment configuration.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# read the last output result after completing training\n",
    "monitor_dir = 'last'\n",
    "\n",
    "# metrics for performance evaluation\n",
    "perf_metrics = ['acc', 'se', 'sp', 'f1', 'auroc', 'ap']\n",
    "\n",
    "# directories of experimental results\n",
    "exp_dirs = ['../exps/ablation-study/alpha_0.0',\n",
    "            '../exps/ablation-study/alpha_0.25',\n",
    "            '../exps/ablation-study/alpha_0.5',\n",
    "            '../exps/ablation-study/alpha_0.75']\n",
    "\n",
    "# names of experiments\n",
    "exp_names=['UNet (α=0.0)',\n",
    "           'Octave UNet (α=0.25)',\n",
    "           'Octave UNet (α=0.5)',\n",
    "           'Octave UNet (α=0.75)']\n",
    "\n",
    "from src.configs.config_node import ConfigNode\n",
    "def get_configs_from_file(configs_file_path):\n",
    "    \"\"\"Read configs.\"\"\"\n",
    "    configs = ConfigNode(new_allowed=True)\n",
    "    configs.merge_from_file(configs_file_path)\n",
    "    return configs\n",
    "\n",
    "exp_configs = [get_configs_from_file(os.path.join(exp_dir, 'run_time_configs.yaml')) for exp_dir in exp_dirs]\n",
    "\n",
    "# uncomment to checkout the details of exp_configs\n",
    "# for exp_config in exp_configs:\n",
    "#     print('===' * 10)\n",
    "#     print(exp_config)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "31c31\r\n",
      "<   DEVICE_IDS: 0\r\n",
      "---\r\n",
      ">   DEVICE_IDS: 2\r\n",
      "39c39\r\n",
      "<   EXP_SUBDIR: alpha_0.0\r\n",
      "---\r\n",
      ">   EXP_SUBDIR: alpha_0.5\r\n",
      "71,74c71,74\r\n",
      "<   - 0.0\r\n",
      "<   - 0.0\r\n",
      "<   - 0.0\r\n",
      "<   - 0.0\r\n",
      "---\r\n",
      ">   - 0.5\r\n",
      ">   - 0.5\r\n",
      ">   - 0.5\r\n",
      ">   - 0.5\r\n"
     ]
    }
   ],
   "source": [
    "# the only differences of the experiments is the hyper-parameter alphas \n",
    "# ! diff {exp_dirs[0] + '/run_time_configs.yaml'} {exp_dirs[1] + '/run_time_configs.yaml'}\n",
    "! diff {exp_dirs[0] + '/run_time_configs.yaml'} {exp_dirs[2] + '/run_time_configs.yaml'}\n",
    "# ! diff {exp_dirs[0] + '/run_time_configs.yaml'} {exp_dirs[3] + '/run_time_configs.yaml'}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Experimental results\n",
    "---\n",
    "Experimental results are recorded after finishing the training process, and can be read from the `performances.csv` file, while the model profile (CPU mode) can be read from the `model_summary.csv` file. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_data_frame(exp_dir, exp_name, perf_metrics,\n",
    "                   monitor_dir='last', outputs_dir='outs',\n",
    "                   perf_csv_file='performances.csv',\n",
    "                   summ_csv_file='model_summary.csv'):\n",
    "    \"\"\"Get data frame of an experiment.\"\"\"\n",
    "    perf_csv_path = os.path.join(exp_dir, outputs_dir, monitor_dir, perf_csv_file)\n",
    "    summ_csv_path = os.path.join(exp_dir, summ_csv_file)\n",
    "    perf_df = pd.read_csv(perf_csv_path, index_col=0)\n",
    "    summ_df = pd.read_csv(summ_csv_path, index_col=0)\n",
    "    data_frame = perf_df\n",
    "    data_frame['params (M)'] = round(int(summ_df['params']['total']) / (1000 ** 2), 2)\n",
    "    data_frame['FLOPs (G)'] = round(int(summ_df['FLOPs']['total'].replace(',', '')) / (1000 ** 3), 2)\n",
    "    data_frame['exp_name'] = exp_name\n",
    "    return data_frame\n",
    "\n",
    "# get data frames of experiment results\n",
    "data_frames = []\n",
    "for exp_dir, exp_name in zip(exp_dirs, exp_names):\n",
    "    data_frames.append(get_data_frame(exp_dir, exp_name, perf_metrics, monitor_dir))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Performances on each testing sample"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sample_index</th>\n",
       "      <th>weighted_binary_cross_entropy</th>\n",
       "      <th>acc</th>\n",
       "      <th>se</th>\n",
       "      <th>sp</th>\n",
       "      <th>f1</th>\n",
       "      <th>prc</th>\n",
       "      <th>auroc</th>\n",
       "      <th>ap</th>\n",
       "      <th>params (M)</th>\n",
       "      <th>FLOPs (G)</th>\n",
       "      <th>exp_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0.202904</td>\n",
       "      <td>0.964966</td>\n",
       "      <td>0.885423</td>\n",
       "      <td>0.972739</td>\n",
       "      <td>0.818182</td>\n",
       "      <td>0.760433</td>\n",
       "      <td>0.988403</td>\n",
       "      <td>0.910125</td>\n",
       "      <td>16.54</td>\n",
       "      <td>58.88</td>\n",
       "      <td>Octave UNet (α=0.5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0.191761</td>\n",
       "      <td>0.967873</td>\n",
       "      <td>0.824740</td>\n",
       "      <td>0.984226</td>\n",
       "      <td>0.840371</td>\n",
       "      <td>0.856607</td>\n",
       "      <td>0.988772</td>\n",
       "      <td>0.930139</td>\n",
       "      <td>16.54</td>\n",
       "      <td>58.88</td>\n",
       "      <td>Octave UNet (α=0.5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>0.209033</td>\n",
       "      <td>0.960720</td>\n",
       "      <td>0.794609</td>\n",
       "      <td>0.979043</td>\n",
       "      <td>0.800774</td>\n",
       "      <td>0.807035</td>\n",
       "      <td>0.973354</td>\n",
       "      <td>0.888895</td>\n",
       "      <td>16.54</td>\n",
       "      <td>58.88</td>\n",
       "      <td>Octave UNet (α=0.5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>0.199702</td>\n",
       "      <td>0.968662</td>\n",
       "      <td>0.807193</td>\n",
       "      <td>0.984953</td>\n",
       "      <td>0.825209</td>\n",
       "      <td>0.844048</td>\n",
       "      <td>0.981050</td>\n",
       "      <td>0.907503</td>\n",
       "      <td>16.54</td>\n",
       "      <td>58.88</td>\n",
       "      <td>Octave UNet (α=0.5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>0.204640</td>\n",
       "      <td>0.965477</td>\n",
       "      <td>0.789988</td>\n",
       "      <td>0.983692</td>\n",
       "      <td>0.811450</td>\n",
       "      <td>0.834111</td>\n",
       "      <td>0.979175</td>\n",
       "      <td>0.897061</td>\n",
       "      <td>16.54</td>\n",
       "      <td>58.88</td>\n",
       "      <td>Octave UNet (α=0.5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>0.207282</td>\n",
       "      <td>0.962982</td>\n",
       "      <td>0.772923</td>\n",
       "      <td>0.983480</td>\n",
       "      <td>0.802580</td>\n",
       "      <td>0.834603</td>\n",
       "      <td>0.973403</td>\n",
       "      <td>0.889389</td>\n",
       "      <td>16.54</td>\n",
       "      <td>58.88</td>\n",
       "      <td>Octave UNet (α=0.5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>0.202437</td>\n",
       "      <td>0.967381</td>\n",
       "      <td>0.797159</td>\n",
       "      <td>0.984651</td>\n",
       "      <td>0.818253</td>\n",
       "      <td>0.840494</td>\n",
       "      <td>0.981919</td>\n",
       "      <td>0.903886</td>\n",
       "      <td>16.54</td>\n",
       "      <td>58.88</td>\n",
       "      <td>Octave UNet (α=0.5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>0.207276</td>\n",
       "      <td>0.966808</td>\n",
       "      <td>0.800646</td>\n",
       "      <td>0.982487</td>\n",
       "      <td>0.806192</td>\n",
       "      <td>0.811816</td>\n",
       "      <td>0.977379</td>\n",
       "      <td>0.891484</td>\n",
       "      <td>16.54</td>\n",
       "      <td>58.88</td>\n",
       "      <td>Octave UNet (α=0.5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>0.208113</td>\n",
       "      <td>0.967724</td>\n",
       "      <td>0.832808</td>\n",
       "      <td>0.979626</td>\n",
       "      <td>0.807078</td>\n",
       "      <td>0.782889</td>\n",
       "      <td>0.977367</td>\n",
       "      <td>0.888551</td>\n",
       "      <td>16.54</td>\n",
       "      <td>58.88</td>\n",
       "      <td>Octave UNet (α=0.5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>0.207248</td>\n",
       "      <td>0.965343</td>\n",
       "      <td>0.844981</td>\n",
       "      <td>0.976108</td>\n",
       "      <td>0.800123</td>\n",
       "      <td>0.759788</td>\n",
       "      <td>0.981460</td>\n",
       "      <td>0.893512</td>\n",
       "      <td>16.54</td>\n",
       "      <td>58.88</td>\n",
       "      <td>Octave UNet (α=0.5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10</td>\n",
       "      <td>0.206922</td>\n",
       "      <td>0.963238</td>\n",
       "      <td>0.811506</td>\n",
       "      <td>0.978107</td>\n",
       "      <td>0.797580</td>\n",
       "      <td>0.784124</td>\n",
       "      <td>0.980859</td>\n",
       "      <td>0.890398</td>\n",
       "      <td>16.54</td>\n",
       "      <td>58.88</td>\n",
       "      <td>Octave UNet (α=0.5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>11</td>\n",
       "      <td>0.199582</td>\n",
       "      <td>0.968079</td>\n",
       "      <td>0.858458</td>\n",
       "      <td>0.978414</td>\n",
       "      <td>0.822516</td>\n",
       "      <td>0.789463</td>\n",
       "      <td>0.987365</td>\n",
       "      <td>0.913082</td>\n",
       "      <td>16.54</td>\n",
       "      <td>58.88</td>\n",
       "      <td>Octave UNet (α=0.5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>12</td>\n",
       "      <td>0.201699</td>\n",
       "      <td>0.964554</td>\n",
       "      <td>0.804602</td>\n",
       "      <td>0.981960</td>\n",
       "      <td>0.816697</td>\n",
       "      <td>0.829161</td>\n",
       "      <td>0.981617</td>\n",
       "      <td>0.904888</td>\n",
       "      <td>16.54</td>\n",
       "      <td>58.88</td>\n",
       "      <td>Octave UNet (α=0.5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>13</td>\n",
       "      <td>0.202328</td>\n",
       "      <td>0.968330</td>\n",
       "      <td>0.865970</td>\n",
       "      <td>0.977404</td>\n",
       "      <td>0.816620</td>\n",
       "      <td>0.772590</td>\n",
       "      <td>0.987113</td>\n",
       "      <td>0.908875</td>\n",
       "      <td>16.54</td>\n",
       "      <td>58.88</td>\n",
       "      <td>Octave UNet (α=0.5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>14</td>\n",
       "      <td>0.211853</td>\n",
       "      <td>0.968513</td>\n",
       "      <td>0.881972</td>\n",
       "      <td>0.975161</td>\n",
       "      <td>0.799845</td>\n",
       "      <td>0.731709</td>\n",
       "      <td>0.987614</td>\n",
       "      <td>0.893816</td>\n",
       "      <td>16.54</td>\n",
       "      <td>58.88</td>\n",
       "      <td>Octave UNet (α=0.5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>15</td>\n",
       "      <td>0.200457</td>\n",
       "      <td>0.968002</td>\n",
       "      <td>0.843284</td>\n",
       "      <td>0.980380</td>\n",
       "      <td>0.826350</td>\n",
       "      <td>0.810082</td>\n",
       "      <td>0.988283</td>\n",
       "      <td>0.912658</td>\n",
       "      <td>16.54</td>\n",
       "      <td>58.88</td>\n",
       "      <td>Octave UNet (α=0.5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>16</td>\n",
       "      <td>0.207836</td>\n",
       "      <td>0.966000</td>\n",
       "      <td>0.831514</td>\n",
       "      <td>0.978481</td>\n",
       "      <td>0.805973</td>\n",
       "      <td>0.781955</td>\n",
       "      <td>0.985455</td>\n",
       "      <td>0.894407</td>\n",
       "      <td>16.54</td>\n",
       "      <td>58.88</td>\n",
       "      <td>Octave UNet (α=0.5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>17</td>\n",
       "      <td>0.206367</td>\n",
       "      <td>0.967140</td>\n",
       "      <td>0.886354</td>\n",
       "      <td>0.974062</td>\n",
       "      <td>0.809787</td>\n",
       "      <td>0.745396</td>\n",
       "      <td>0.989273</td>\n",
       "      <td>0.905388</td>\n",
       "      <td>16.54</td>\n",
       "      <td>58.88</td>\n",
       "      <td>Octave UNet (α=0.5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>18</td>\n",
       "      <td>0.191230</td>\n",
       "      <td>0.970947</td>\n",
       "      <td>0.913635</td>\n",
       "      <td>0.976152</td>\n",
       "      <td>0.839656</td>\n",
       "      <td>0.776761</td>\n",
       "      <td>0.991478</td>\n",
       "      <td>0.937147</td>\n",
       "      <td>16.54</td>\n",
       "      <td>58.88</td>\n",
       "      <td>Octave UNet (α=0.5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>19</td>\n",
       "      <td>0.214225</td>\n",
       "      <td>0.964451</td>\n",
       "      <td>0.901360</td>\n",
       "      <td>0.969474</td>\n",
       "      <td>0.789024</td>\n",
       "      <td>0.701586</td>\n",
       "      <td>0.988571</td>\n",
       "      <td>0.893993</td>\n",
       "      <td>16.54</td>\n",
       "      <td>58.88</td>\n",
       "      <td>Octave UNet (α=0.5)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    sample_index  weighted_binary_cross_entropy       acc        se        sp  \\\n",
       "0              0                       0.202904  0.964966  0.885423  0.972739   \n",
       "1              1                       0.191761  0.967873  0.824740  0.984226   \n",
       "2              2                       0.209033  0.960720  0.794609  0.979043   \n",
       "3              3                       0.199702  0.968662  0.807193  0.984953   \n",
       "4              4                       0.204640  0.965477  0.789988  0.983692   \n",
       "5              5                       0.207282  0.962982  0.772923  0.983480   \n",
       "6              6                       0.202437  0.967381  0.797159  0.984651   \n",
       "7              7                       0.207276  0.966808  0.800646  0.982487   \n",
       "8              8                       0.208113  0.967724  0.832808  0.979626   \n",
       "9              9                       0.207248  0.965343  0.844981  0.976108   \n",
       "10            10                       0.206922  0.963238  0.811506  0.978107   \n",
       "11            11                       0.199582  0.968079  0.858458  0.978414   \n",
       "12            12                       0.201699  0.964554  0.804602  0.981960   \n",
       "13            13                       0.202328  0.968330  0.865970  0.977404   \n",
       "14            14                       0.211853  0.968513  0.881972  0.975161   \n",
       "15            15                       0.200457  0.968002  0.843284  0.980380   \n",
       "16            16                       0.207836  0.966000  0.831514  0.978481   \n",
       "17            17                       0.206367  0.967140  0.886354  0.974062   \n",
       "18            18                       0.191230  0.970947  0.913635  0.976152   \n",
       "19            19                       0.214225  0.964451  0.901360  0.969474   \n",
       "\n",
       "          f1       prc     auroc        ap  params (M)  FLOPs (G)  \\\n",
       "0   0.818182  0.760433  0.988403  0.910125       16.54      58.88   \n",
       "1   0.840371  0.856607  0.988772  0.930139       16.54      58.88   \n",
       "2   0.800774  0.807035  0.973354  0.888895       16.54      58.88   \n",
       "3   0.825209  0.844048  0.981050  0.907503       16.54      58.88   \n",
       "4   0.811450  0.834111  0.979175  0.897061       16.54      58.88   \n",
       "5   0.802580  0.834603  0.973403  0.889389       16.54      58.88   \n",
       "6   0.818253  0.840494  0.981919  0.903886       16.54      58.88   \n",
       "7   0.806192  0.811816  0.977379  0.891484       16.54      58.88   \n",
       "8   0.807078  0.782889  0.977367  0.888551       16.54      58.88   \n",
       "9   0.800123  0.759788  0.981460  0.893512       16.54      58.88   \n",
       "10  0.797580  0.784124  0.980859  0.890398       16.54      58.88   \n",
       "11  0.822516  0.789463  0.987365  0.913082       16.54      58.88   \n",
       "12  0.816697  0.829161  0.981617  0.904888       16.54      58.88   \n",
       "13  0.816620  0.772590  0.987113  0.908875       16.54      58.88   \n",
       "14  0.799845  0.731709  0.987614  0.893816       16.54      58.88   \n",
       "15  0.826350  0.810082  0.988283  0.912658       16.54      58.88   \n",
       "16  0.805973  0.781955  0.985455  0.894407       16.54      58.88   \n",
       "17  0.809787  0.745396  0.989273  0.905388       16.54      58.88   \n",
       "18  0.839656  0.776761  0.991478  0.937147       16.54      58.88   \n",
       "19  0.789024  0.701586  0.988571  0.893993       16.54      58.88   \n",
       "\n",
       "               exp_name  \n",
       "0   Octave UNet (α=0.5)  \n",
       "1   Octave UNet (α=0.5)  \n",
       "2   Octave UNet (α=0.5)  \n",
       "3   Octave UNet (α=0.5)  \n",
       "4   Octave UNet (α=0.5)  \n",
       "5   Octave UNet (α=0.5)  \n",
       "6   Octave UNet (α=0.5)  \n",
       "7   Octave UNet (α=0.5)  \n",
       "8   Octave UNet (α=0.5)  \n",
       "9   Octave UNet (α=0.5)  \n",
       "10  Octave UNet (α=0.5)  \n",
       "11  Octave UNet (α=0.5)  \n",
       "12  Octave UNet (α=0.5)  \n",
       "13  Octave UNet (α=0.5)  \n",
       "14  Octave UNet (α=0.5)  \n",
       "15  Octave UNet (α=0.5)  \n",
       "16  Octave UNet (α=0.5)  \n",
       "17  Octave UNet (α=0.5)  \n",
       "18  Octave UNet (α=0.5)  \n",
       "19  Octave UNet (α=0.5)  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# the performance on each testing sample can be retrived \n",
    "data_frames[2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Mean performance comparison of models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>acc</th>\n",
       "      <th>se</th>\n",
       "      <th>sp</th>\n",
       "      <th>f1</th>\n",
       "      <th>auroc</th>\n",
       "      <th>ap</th>\n",
       "      <th>params (M)</th>\n",
       "      <th>FLOPs (G)</th>\n",
       "      <th>exp_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.961670</td>\n",
       "      <td>0.777680</td>\n",
       "      <td>0.979598</td>\n",
       "      <td>0.779517</td>\n",
       "      <td>0.954292</td>\n",
       "      <td>0.823837</td>\n",
       "      <td>16.53</td>\n",
       "      <td>133.93</td>\n",
       "      <td>UNet (α=0.0)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.965915</td>\n",
       "      <td>0.848298</td>\n",
       "      <td>0.977495</td>\n",
       "      <td>0.812628</td>\n",
       "      <td>0.984886</td>\n",
       "      <td>0.904298</td>\n",
       "      <td>16.54</td>\n",
       "      <td>90.25</td>\n",
       "      <td>Octave UNet (α=0.25)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.966360</td>\n",
       "      <td>0.837456</td>\n",
       "      <td>0.979030</td>\n",
       "      <td>0.812713</td>\n",
       "      <td>0.983496</td>\n",
       "      <td>0.902760</td>\n",
       "      <td>16.54</td>\n",
       "      <td>58.88</td>\n",
       "      <td>Octave UNet (α=0.5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.962806</td>\n",
       "      <td>0.846524</td>\n",
       "      <td>0.974247</td>\n",
       "      <td>0.798507</td>\n",
       "      <td>0.980310</td>\n",
       "      <td>0.891372</td>\n",
       "      <td>16.54</td>\n",
       "      <td>39.97</td>\n",
       "      <td>Octave UNet (α=0.75)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        acc        se        sp        f1     auroc        ap  params (M)  \\\n",
       "0  0.961670  0.777680  0.979598  0.779517  0.954292  0.823837       16.53   \n",
       "1  0.965915  0.848298  0.977495  0.812628  0.984886  0.904298       16.54   \n",
       "2  0.966360  0.837456  0.979030  0.812713  0.983496  0.902760       16.54   \n",
       "3  0.962806  0.846524  0.974247  0.798507  0.980310  0.891372       16.54   \n",
       "\n",
       "   FLOPs (G)              exp_name  \n",
       "0     133.93          UNet (α=0.0)  \n",
       "1      90.25  Octave UNet (α=0.25)  \n",
       "2      58.88   Octave UNet (α=0.5)  \n",
       "3      39.97  Octave UNet (α=0.75)  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def get_data_frame_mean(data_frame, exp_name, perf_metrics):\n",
    "    \"\"\"Get mean of data frame.\"\"\"\n",
    "    metrics = perf_metrics + ['params (M)', 'FLOPs (G)']\n",
    "    data_frame = pd.DataFrame.from_dict(data_frame[metrics].mean()).T\n",
    "    data_frame['exp_name'] = exp_name\n",
    "    return data_frame\n",
    "\n",
    "def compare_data_frames_with_mean(data_frames, exp_names, perf_metrics):\n",
    "    \"\"\"Compare experiments with mean of performance.\"\"\"\n",
    "    assert len(data_frames) == len(exp_names)\n",
    "    data_frames_mean = []\n",
    "    for data_frame, exp_name in zip(data_frames, exp_names):\n",
    "        data_frame_mean = get_data_frame_mean(data_frame, exp_name, perf_metrics)\n",
    "        data_frames_mean.append(data_frame_mean)\n",
    "    data_frames = pd.concat(data_frames_mean, ignore_index=True)\n",
    "    return data_frames\n",
    "\n",
    "compare_data_frames_with_mean(data_frames, exp_names, perf_metrics)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Stander deviation comparison of models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": false
   },
   "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>acc</th>\n",
       "      <th>se</th>\n",
       "      <th>sp</th>\n",
       "      <th>f1</th>\n",
       "      <th>auroc</th>\n",
       "      <th>ap</th>\n",
       "      <th>exp_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.002940</td>\n",
       "      <td>0.042671</td>\n",
       "      <td>0.003628</td>\n",
       "      <td>0.017234</td>\n",
       "      <td>0.011075</td>\n",
       "      <td>0.018565</td>\n",
       "      <td>UNet (α=0.0)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.002276</td>\n",
       "      <td>0.039949</td>\n",
       "      <td>0.004251</td>\n",
       "      <td>0.013852</td>\n",
       "      <td>0.004550</td>\n",
       "      <td>0.012998</td>\n",
       "      <td>Octave UNet (α=0.25)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.002409</td>\n",
       "      <td>0.041055</td>\n",
       "      <td>0.004289</td>\n",
       "      <td>0.013592</td>\n",
       "      <td>0.005468</td>\n",
       "      <td>0.013497</td>\n",
       "      <td>Octave UNet (α=0.5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.002395</td>\n",
       "      <td>0.038830</td>\n",
       "      <td>0.005096</td>\n",
       "      <td>0.017140</td>\n",
       "      <td>0.005682</td>\n",
       "      <td>0.015139</td>\n",
       "      <td>Octave UNet (α=0.75)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        acc        se        sp        f1     auroc        ap  \\\n",
       "0  0.002940  0.042671  0.003628  0.017234  0.011075  0.018565   \n",
       "1  0.002276  0.039949  0.004251  0.013852  0.004550  0.012998   \n",
       "2  0.002409  0.041055  0.004289  0.013592  0.005468  0.013497   \n",
       "3  0.002395  0.038830  0.005096  0.017140  0.005682  0.015139   \n",
       "\n",
       "               exp_name  \n",
       "0          UNet (α=0.0)  \n",
       "1  Octave UNet (α=0.25)  \n",
       "2   Octave UNet (α=0.5)  \n",
       "3  Octave UNet (α=0.75)  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def get_data_frame_std(data_frame, exp_name, perf_metrics):\n",
    "    \"\"\"Get stander diviation of data frame.\"\"\"\n",
    "    metrics = perf_metrics\n",
    "    data_frame = pd.DataFrame.from_dict(data_frame[metrics].std()).T\n",
    "    data_frame['exp_name'] = exp_name\n",
    "    return data_frame\n",
    "\n",
    "def compare_data_frames_with_std(data_frames, exp_names, perf_metrics):\n",
    "    \"\"\"Compare experiments with stander diviation of performance.\"\"\"\n",
    "    assert len(data_frames) == len(exp_names)\n",
    "    data_frames_mean = []\n",
    "    for data_frame, exp_name in zip(data_frames, exp_names):\n",
    "        data_frame_mean = get_data_frame_std(data_frame, exp_name, perf_metrics)\n",
    "        data_frames_mean.append(data_frame_mean)\n",
    "    data_frames = pd.concat(data_frames_mean, ignore_index=True)\n",
    "    return data_frames\n",
    "\n",
    "compare_data_frames_with_std(data_frames, exp_names, perf_metrics)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualizing performances differences"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x540 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def compare_data_frames_with_barplot(data_frames, exp_names, perf_metrics, \n",
    "                                     save_fig=False, figsize=(15, 7.5), \n",
    "                                     ylim=(0.7, 1), font_scale=2):\n",
    "    \"\"\"Compare experiment performance with barplot.\"\"\"\n",
    "    assert len(data_frames) == len(exp_names)\n",
    "    data_frames = pd.concat(data_frames, ignore_index=True)\n",
    "    data_frames = data_frames.melt(id_vars=['exp_name'], value_vars=perf_metrics, \n",
    "                                   var_name='metric', value_name='value', col_level=None)\n",
    "    sns.set(style='whitegrid', font_scale=font_scale)\n",
    "    fig, axis = plt.subplots(1, 1, figsize=figsize)\n",
    "    box_plot = sns.barplot(x='metric', y='value', hue='exp_name', \n",
    "                           data=data_frames, palette='tab10', ax=axis)\n",
    "    box_plot.set_ylim(ylim)\n",
    "    box_plot.legend(loc='lower right', ncol=2)\n",
    "    fig.tight_layout()\n",
    "    if save_fig:\n",
    "        try:\n",
    "            os.mkdir('ablation')\n",
    "        except:\n",
    "            pass\n",
    "        fig.savefig('ablation/ablation-barplot.pdf')\n",
    "    plt.show()\n",
    "    sns.set(style='whitegrid')\n",
    "    sns.set_context('paper', font_scale=1.5)\n",
    "\n",
    "compare_data_frames_with_barplot(data_frames, exp_names, perf_metrics, save_fig=False)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x540 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def compare_data_frames_with_boxplot(data_frames, exp_names, perf_metrics, \n",
    "                                     save_fig=False, figsize=(15, 7.5), \n",
    "                                     font_scale=2, framealpha=0.2, \n",
    "                                     ylim=(0.66, 1),\n",
    "                                     showmeans=False):\n",
    "    \"\"\"Compare experiment performance with boxplot.\"\"\"\n",
    "    assert len(data_frames) == len(exp_names)\n",
    "    for data_frame, exp_name in zip(data_frames, exp_names):\n",
    "        data_frame['exp_name'] = exp_name\n",
    "    data_frames = pd.concat(data_frames, ignore_index=True)\n",
    "    data_frames = data_frames.melt(id_vars=['exp_name'], value_vars=perf_metrics, \n",
    "                                   var_name='metric', value_name='value', col_level=None)\n",
    "    sns.set(style='whitegrid', font_scale=font_scale)\n",
    "    fig, axis = plt.subplots(1, 1, figsize=figsize)\n",
    "    box_plot = sns.boxplot(x='metric', y='value', hue='exp_name', \n",
    "                           data=data_frames, palette='tab10',\n",
    "                           showmeans=showmeans, ax=axis)\n",
    "    l = box_plot.legend(loc='lower right', ncol=2, framealpha=framealpha)\n",
    "    box_plot.set_ylim(ylim)\n",
    "    fig.tight_layout()\n",
    "    if save_fig:\n",
    "        try:\n",
    "            os.mkdir('ablation')\n",
    "        except:\n",
    "            pass\n",
    "        fig.savefig('ablation/ablation-boxplot.pdf')\n",
    "    plt.show()\n",
    "    sns.set(style='whitegrid')\n",
    "    sns.set_context('paper', font_scale=1.5)\n",
    "\n",
    "compare_data_frames_with_boxplot(data_frames, \n",
    "                                 exp_names=['            UNet (α=0.0)', # to avoid overlapping :( \n",
    "                                            'Octave UNet (α=0.25)',\n",
    "                                            'Octave UNet (α=0.5)',\n",
    "                                            'Octave UNet (α=0.75)'],\n",
    "                                 perf_metrics=perf_metrics,\n",
    "                                 save_fig=False, font_scale=2.5)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 3240x1080 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def compare_data_frames_with_paretoplot(data_frames, exp_names, perf_metrics, \n",
    "                                        save_fig=False, invert_xaxis=True, font_scale=3):\n",
    "    \"\"\"Compare experiment performance with pareto plot.\"\"\"\n",
    "    sns.set(style='whitegrid', font_scale=font_scale)\n",
    "    assert len(data_frames) == len(exp_names)\n",
    "    data_frames = pd.concat(data_frames, ignore_index=True)\n",
    "    rows = int(len(perf_metrics) ** 0.5)\n",
    "    cols = int(np.ceil(len(perf_metrics) / int(len(perf_metrics) ** 0.5)))\n",
    "    fig, axes = plt.subplots(rows, cols, figsize=(cols*15, rows*7.5))\n",
    "    axes = axes.ravel()\n",
    "    for idx, metric in enumerate(perf_metrics):\n",
    "        g = sns.pointplot(x='FLOPs (G)', y=metric, data=data_frames, ci=None, \n",
    "                          markers=['.', '^', 'o', '*'], linestyles='--', dodge=True, color='k',\n",
    "                          scale=2.5, capsize=0.1, ax=axes[idx])\n",
    "        g = sns.pointplot(x='FLOPs (G)', y=metric, hue='exp_name', data=data_frames, \n",
    "                          markers=['P', '^', 'o', '*'], linestyles='-', dodge=True, \n",
    "                          scale=5, capsize=0.1, ax=axes[idx], font_scale=5)\n",
    "        if idx == len(perf_metrics) - 1:\n",
    "            g.legend(loc='best')\n",
    "        else:\n",
    "            g._remove_legend(g.get_legend())\n",
    "        if invert_xaxis:\n",
    "            g.invert_xaxis()\n",
    "    plt.tight_layout()\n",
    "    if save_fig:\n",
    "        try:\n",
    "            os.mkdir('ablation')\n",
    "        except:\n",
    "            pass\n",
    "        fig.savefig('ablation/pareto.pdf')\n",
    "    plt.show()\n",
    "    sns.set(style='whitegrid')\n",
    "    sns.set_context('paper', font_scale=1.5)\n",
    "\n",
    "compare_data_frames_with_paretoplot(data_frames, exp_names, perf_metrics, \n",
    "                                    save_fig=False, font_scale=3.3)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}