QUIZ_week2_processing.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "608c7b2a",
   "metadata": {},
   "source": [
    "# QUIZ WEEK 2 PROCESSING"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3b557041",
   "metadata": {},
   "outputs": [],
   "source": [
    "import quizzes_helper as qh\n",
    "import matplotlib.pyplot as plt\n",
    "import shutil\n",
    "\n",
    "folder = '_SUBMISSIONS/'\n",
    "zipfile = 'Week 2 quiz submission Download 21 February, 2024 1220 PM.zip'\n",
    "week_nr = zipfile.split()[1]  \n",
    "\n",
    "unpacked = folder + 'Week' + week_nr + '_unpacked'\n",
    "shutil.unpack_archive(folder + zipfile, folder + 'Week' + week_nr + '_unpacked') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "0e378d67",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of processed submissions: 23\n",
      "Number of submissions throwing errors: 0\n"
     ]
    }
   ],
   "source": [
    "fixed = folder + 'Week' + week_nr + '_fixed'\n",
    "tasks = {\n",
    "    'radius_mean_varying': [23.92 - 1, 23.92 + 1],\n",
    "    'number_fibers': [2291 - 250, 2291 + 250],\n",
    "    'fiber_radius_mean': [4.21 - 1.5, 4.21 + 1.5],\n",
    "    }\n",
    "\n",
    "results = qh.read_all_files(fixed, tasks)\n",
    "summary = qh.process_results(results, tasks)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "610083a1",
   "metadata": {},
   "source": [
    "## Task 1: What is mean radius of the black blobs in the test image?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "94626178",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "qh.plot_task_results(results, tasks, i=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "2a02dd88",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RSM                            JuliusKokholm                  Caroline                      \n",
      "s184009                        Anonymous_Duck                 askefandersen                 \n",
      "Delfin                         CassandraD                     HannahNielsen                 \n",
      "EmilRamovic                    Louis Kamp                     Ida Puggaard                  \n",
      "ngre98                         J5gbqp                         NielsPeter                    \n",
      "HelenaJensen                   Ingi                           Denitsa                       \n",
      "AstridVesterbrandt             Olczixo                        Nojus                         \n"
     ]
    }
   ],
   "source": [
    "qh.print_winners(summary, i=0)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "843175e6",
   "metadata": {},
   "source": [
    "## Task 2: What is the number of fibers detected in the CT slice?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "32e0c554",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "qh.plot_task_results(results, tasks, i=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "27f3048e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RSM                            JuliusKokholm                  Caroline                      \n",
      "Anonymous_Duck                 askefandersen                  Delfin                        \n",
      "CassandraD                     HannahNielsen                  EmilRamovic                   \n",
      "Ida Puggaard                   ngre98                         J5gbqp                        \n",
      "ET_Phone_Home                  NielsPeter                     Ingi                          \n",
      "Denitsa                        AstridVesterbrandt             Olczixo                       \n",
      "Nojus                         \n"
     ]
    }
   ],
   "source": [
    "qh.print_winners(summary, i=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b70b145b",
   "metadata": {},
   "source": [
    "## Task 3: What is the mean radius of the blobs from the CT slice?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "94b1d764",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ASKEhBgAAAAAAgJBCQwwAAAAAAAAhhYYYAAAAAAAAQsr/Ay0GIWW1JmmAAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "qh.plot_task_results(results, tasks, i=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "449e58f3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RSM                            JuliusKokholm                  Caroline                      \n",
      "s184009                        Anonymous_Duck                 SeverinH                      \n",
      "askefandersen                  Delfin                         CassandraD                    \n",
      "HannahNielsen                  Louis Kamp                     ngre98                        \n",
      "J5gbqp                         ET_Phone_Home                  NielsPeter                    \n",
      "HelenaJensen                   Ingi                           AstridVesterbrandt            \n",
      "Olczixo                        Nojus                         \n"
     ]
    }
   ],
   "source": [
    "qh.print_winners(summary, i=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e987fa32",
   "metadata": {},
   "source": [
    "## Week 2 final score\n",
    "Following students answered all three questions correctly. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "c39a411c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RSM                            JuliusKokholm                  Caroline                      \n",
      "Anonymous_Duck                 askefandersen                  Delfin                        \n",
      "CassandraD                     HannahNielsen                  ngre98                        \n",
      "J5gbqp                         NielsPeter                     Ingi                          \n",
      "AstridVesterbrandt             Olczixo                        Nojus                         \n"
     ]
    }
   ],
   "source": [
    "qh.print_winners(summary)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a0d98b67",
   "metadata": {},
   "outputs": [],
   "source": [
    "summary.to_csv(folder +'Week' + week_nr + '.csv')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "aia2023",
   "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": "3.9.13"
  },
  "vscode": {
   "interpreter": {
    "hash": "864c54ae2c00d287136c49aec72343cc9457da9cff5129afc5c16bdd0f87f600"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}