7.figures/SupplementaryFigure_AllModelEvaluation_Summary.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "2cc4b1ad-4cf5-4332-97b5-1c48b105b974",
   "metadata": {},
   "source": [
    "## Supplementary Figure - All model evalulation\n",
    "\n",
    "- One panel figure showing all model performace"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "b6ed7b80-d6b0-402e-b36b-b294aea229e7",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "“package ‘ggplot2’ was built under R version 4.2.3”\n",
      "Warning message:\n",
      "“package ‘patchwork’ was built under R version 4.2.3”\n"
     ]
    }
   ],
   "source": [
    "suppressPackageStartupMessages(library(dplyr))\n",
    "suppressPackageStartupMessages(library(ggplot2))\n",
    "suppressPackageStartupMessages(library(patchwork))\n",
    "\n",
    "# Load variables important for plotting (e.g., themes, phenotypes, etc.)\n",
    "source(\"themes.r\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "7195ad6e-b409-4f8f-ad2c-9b82adcc3889",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set output file\n",
    "output_fig <- file.path(\"figures\", \"supplementary\", \"all_model_f1_score_performance_barchart.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ae75165f-b8cd-49fb-bfbb-f5b2ea967669",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[1m\u001b[22mNew names:\n",
      "\u001b[36m•\u001b[39m `` -> `...1`\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] 160   8\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A tibble: 6 × 8</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>Phenotypic_Class</th><th scope=col>F1_Score</th><th scope=col>data_split</th><th scope=col>shuffled</th><th scope=col>feature_type</th><th scope=col>balance_type</th><th scope=col>feature_type_with_data_split</th><th scope=col>feature_type_with_balance_type</th></tr>\n",
       "\t<tr><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;fct&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>ADCCM    </td><td>0.7878788</td><td>test</td><td>False</td><td>CP</td><td>balanced</td><td>CPtest</td><td>CellProfiler</td></tr>\n",
       "\t<tr><td>Anaphase </td><td>0.8000000</td><td>test</td><td>False</td><td>CP</td><td>balanced</td><td>CPtest</td><td>CellProfiler</td></tr>\n",
       "\t<tr><td>Apoptosis</td><td>0.7560976</td><td>test</td><td>False</td><td>CP</td><td>balanced</td><td>CPtest</td><td>CellProfiler</td></tr>\n",
       "\t<tr><td>Binuclear</td><td>0.6666667</td><td>test</td><td>False</td><td>CP</td><td>balanced</td><td>CPtest</td><td>CellProfiler</td></tr>\n",
       "\t<tr><td>Elongated</td><td>0.9411765</td><td>test</td><td>False</td><td>CP</td><td>balanced</td><td>CPtest</td><td>CellProfiler</td></tr>\n",
       "\t<tr><td>Grape    </td><td>0.5161290</td><td>test</td><td>False</td><td>CP</td><td>balanced</td><td>CPtest</td><td>CellProfiler</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A tibble: 6 × 8\n",
       "\\begin{tabular}{llllllll}\n",
       " Phenotypic\\_Class & F1\\_Score & data\\_split & shuffled & feature\\_type & balance\\_type & feature\\_type\\_with\\_data\\_split & feature\\_type\\_with\\_balance\\_type\\\\\n",
       " <fct> & <dbl> & <chr> & <chr> & <chr> & <chr> & <chr> & <fct>\\\\\n",
       "\\hline\n",
       "\t ADCCM     & 0.7878788 & test & False & CP & balanced & CPtest & CellProfiler\\\\\n",
       "\t Anaphase  & 0.8000000 & test & False & CP & balanced & CPtest & CellProfiler\\\\\n",
       "\t Apoptosis & 0.7560976 & test & False & CP & balanced & CPtest & CellProfiler\\\\\n",
       "\t Binuclear & 0.6666667 & test & False & CP & balanced & CPtest & CellProfiler\\\\\n",
       "\t Elongated & 0.9411765 & test & False & CP & balanced & CPtest & CellProfiler\\\\\n",
       "\t Grape     & 0.5161290 & test & False & CP & balanced & CPtest & CellProfiler\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A tibble: 6 × 8\n",
       "\n",
       "| Phenotypic_Class &lt;fct&gt; | F1_Score &lt;dbl&gt; | data_split &lt;chr&gt; | shuffled &lt;chr&gt; | feature_type &lt;chr&gt; | balance_type &lt;chr&gt; | feature_type_with_data_split &lt;chr&gt; | feature_type_with_balance_type &lt;fct&gt; |\n",
       "|---|---|---|---|---|---|---|---|\n",
       "| ADCCM     | 0.7878788 | test | False | CP | balanced | CPtest | CellProfiler |\n",
       "| Anaphase  | 0.8000000 | test | False | CP | balanced | CPtest | CellProfiler |\n",
       "| Apoptosis | 0.7560976 | test | False | CP | balanced | CPtest | CellProfiler |\n",
       "| Binuclear | 0.6666667 | test | False | CP | balanced | CPtest | CellProfiler |\n",
       "| Elongated | 0.9411765 | test | False | CP | balanced | CPtest | CellProfiler |\n",
       "| Grape     | 0.5161290 | test | False | CP | balanced | CPtest | CellProfiler |\n",
       "\n"
      ],
      "text/plain": [
       "  Phenotypic_Class F1_Score  data_split shuffled feature_type balance_type\n",
       "1 ADCCM            0.7878788 test       False    CP           balanced    \n",
       "2 Anaphase         0.8000000 test       False    CP           balanced    \n",
       "3 Apoptosis        0.7560976 test       False    CP           balanced    \n",
       "4 Binuclear        0.6666667 test       False    CP           balanced    \n",
       "5 Elongated        0.9411765 test       False    CP           balanced    \n",
       "6 Grape            0.5161290 test       False    CP           balanced    \n",
       "  feature_type_with_data_split feature_type_with_balance_type\n",
       "1 CPtest                       CellProfiler                  \n",
       "2 CPtest                       CellProfiler                  \n",
       "3 CPtest                       CellProfiler                  \n",
       "4 CPtest                       CellProfiler                  \n",
       "5 CPtest                       CellProfiler                  \n",
       "6 CPtest                       CellProfiler                  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Load data\n",
    "results_dir <- file.path(\n",
    "    \"..\", \"3.evaluate_model\", \"evaluations\", \"F1_scores\"\n",
    ")\n",
    "results_file <- file.path(results_dir, \"compiled_F1_scores.tsv\")\n",
    "\n",
    "f1_score_df <- readr::read_tsv(\n",
    "    results_file,\n",
    "    col_types = readr::cols(\n",
    "        .default = \"d\",\n",
    "        \"Phenotypic_Class\" = \"c\",\n",
    "        \"data_split\" = \"c\",\n",
    "        \"shuffled\" = \"c\",\n",
    "        \"feature_type\" = \"c\",\n",
    "        \"balance_type\" = \"c\"\n",
    "    )\n",
    ") %>%\n",
    "    dplyr::select(!`...1`) %>%\n",
    "    dplyr::mutate(feature_type_with_data_split = paste0(feature_type, data_split)) %>%\n",
    "    dplyr::mutate(feature_type_with_balance_type = paste0(feature_type, balance_type)) %>%\n",
    "    dplyr::filter(\n",
    "        shuffled == \"False\",\n",
    "        data_split == \"test\"\n",
    "    )\n",
    "\n",
    "f1_score_df$Phenotypic_Class <-\n",
    "    dplyr::recode(f1_score_df$Phenotypic_Class, Weighted = \"OverallPerformance\")\n",
    "\n",
    "# Reverse order of predicted label for plotting\n",
    "front_level <- \"OverallPerformance\"\n",
    "remaining_levels <- setdiff(unique(f1_score_df$Phenotypic_Class), front_level)\n",
    "new_order <- c(rev(remaining_levels), front_level)\n",
    "\n",
    "f1_score_df$Phenotypic_Class <-\n",
    "    factor(f1_score_df$Phenotypic_Class, levels = rev(new_order))\n",
    "\n",
    "f1_score_df$feature_type_with_balance_type <-\n",
    "    factor(\n",
    "        f1_score_df$feature_type_with_balance_type,\n",
    "        levels = c(\n",
    "            \"CPbalanced\",\n",
    "            \"CPunbalanced\",\n",
    "            \"DPbalanced\",\n",
    "            \"DPunbalanced\",\n",
    "            \"CP_and_DPbalanced\",\n",
    "            \"CP_and_DPunbalanced\",\n",
    "            \"CP_zernike_onlybalanced\",\n",
    "            \"CP_zernike_onlyunbalanced\",\n",
    "            \"CP_areashape_onlybalanced\",\n",
    "            \"CP_areashape_onlyunbalanced\"\n",
    "        )\n",
    "    )\n",
    "\n",
    "feature_space_labels <- c(\n",
    "    \"CPbalanced\" = \"CellProfiler\",\n",
    "    \"CPunbalanced\" = \"CellProfiler\",\n",
    "    \"DPbalanced\" = \"DeepProfiler\",\n",
    "    \"DPunbalanced\" = \"DeepProfiler\",\n",
    "    \"CP_and_DPbalanced\" = \"CP and DP\",\n",
    "    \"CP_and_DPunbalanced\" = \"CP and DP\",\n",
    "    \"CP_zernike_onlybalanced\" = \"CP Zernike\",\n",
    "    \"CP_zernike_onlyunbalanced\" = \"CP Zernike\",\n",
    "    \"CP_areashape_onlybalanced\" = \"CP AreaShape\",\n",
    "    \"CP_areashape_onlyunbalanced\" = \"CP AreaShape\"\n",
    ")\n",
    "\n",
    "f1_score_df$feature_type_with_balance_type <-\n",
    "    dplyr::recode_factor(f1_score_df$feature_type_with_balance_type, !!!feature_space_labels)\n",
    "\n",
    "print(dim(f1_score_df))\n",
    "head(f1_score_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "04dfd4d7-765d-4c71-aec9-6d51036a5b03",
   "metadata": {},
   "outputs": [
    {
     "data": {
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57wUvqunbtttuphTeMo3vOlxWJNTXuq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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "focus_bar_gg <- (\n",
    "    ggplot(f1_score_df, aes(x = feature_type_with_balance_type, y = F1_Score))\n",
    "    + geom_bar(aes(fill = balance_type), stat = \"identity\", position = \"dodge\")\n",
    "    + facet_wrap(\"~Phenotypic_Class\", nrow = 4)\n",
    "    + phenotypic_ggplot_theme\n",
    "    + scale_fill_discrete(\"Class weight\")\n",
    "    + theme(\n",
    "        axis.text.x = element_text(angle = 90)\n",
    "    )\n",
    "    + labs(\n",
    "        x = \"Model\",\n",
    "        y = \"F1 score\"\n",
    "    )\n",
    "    + coord_flip()\n",
    ")\n",
    "\n",
    "focus_bar_gg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ce96f81e-e2bb-42d0-9a44-1d3800a611ab",
   "metadata": {},
   "outputs": [],
   "source": [
    "ggsave(output_fig, dpi = 500, height = 8, width = 9.5)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "R [conda env:phenotype_figures] *",
   "language": "R",
   "name": "conda-env-phenotype_figures-r"
  },
  "language_info": {
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