Time table generator

ML/time-table-planning.ipynb

+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "import numpy as np \n",
+    "import pandas as pd\n",
+    "import datetime as dt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "available_times = {\n",
+    "                    \"monday\":[\n",
+    "                        \"04:00-6:00\",\n",
+    "                        \"16:00-21:00\"\n",
+    "                    ],\n",
+    "                    \"tuesday\":[\n",
+    "                        \"04:00-6:00\",\n",
+    "                        \"16:00-21:00\"\n",
+    "                    ],\n",
+    "                    \"wednesday\":[\n",
+    "                        \"04:00-6:00\",\n",
+    "                        \"18:00-21:00\"\n",
+    "                    ],\n",
+    "                    \"thursday\":[\n",
+    "                        \"04:00-6:00\",\n",
+    "                        \"14:00-21:00\"\n",
+    "                    ],\n",
+    "                    \"friday\":[\n",
+    "                        \"04:00-6:00\",\n",
+    "                        \"16:00-21:00\"\n",
+    "                    ],\n",
+    "                    \"saturday\":[\n",
+    "                        \"06:00-18:00\"\n",
+    "                    ],\n",
+    "                    \"sunday\":[\n",
+    "                        \"06:00-18:00\"\n",
+    "                    ]\n",
+    "                    }\n",
+    "\n",
+    "\n",
+    "student_details = [\n",
+    "                    {\n",
+    "                        \"Subject name & PDF\":\"English for academic purpose (EAP)\",\n",
+    "                        \"Credit points\":3,\n",
+    "                        \"Student Level\":\"Easy\",\n",
+    "                        \"Total Chapters\":6,\n",
+    "                        \"Studied Already\":5\n",
+    "                    },\n",
+    "                    {\n",
+    "                        \"Subject name & PDF\":\"Infromation system & data modeling (ISDM)\",\n",
+    "                        \"Credit points\":4,\n",
+    "                        \"Student Level\":\"Easy\",\n",
+    "                        \"Total Chapters\":8,\n",
+    "                        \"Studied Already\":6.75\n",
+    "                    },\n",
+    "                    {\n",
+    "                        \"Subject name & PDF\":\"Internet & web technologies (IWT)\",\n",
+    "                        \"Credit points\":4,\n",
+    "                        \"Student Level\":\"Average\",\n",
+    "                        \"Total Chapters\":9,\n",
+    "                        \"Studied Already\":5\n",
+    "                    },\n",
+    "                    {\n",
+    "                        \"Subject name & PDF\":\"Object oriented concepts (OOC)\",\n",
+    "                        \"Credit points\":4,\n",
+    "                        \"Student Level\":\"Hard\",\n",
+    "                        \"Total Chapters\":7,\n",
+    "                        \"Studied Already\":7\n",
+    "                    },\n",
+    "                    {\n",
+    "                        \"Subject name & PDF\":\"Software process modeling (SPM)\",\n",
+    "                        \"Credit points\":3,\n",
+    "                        \"Student Level\":\"Hard\",\n",
+    "                        \"Total Chapters\":5,\n",
+    "                        \"Studied Already\":3\n",
+    "                    }\n",
+    "                    ]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def find_available_hours_per_week(available_time_dict):\n",
+    "    available_hours = {}\n",
+    "    for day in available_time_dict.keys():\n",
+    "        available_hour_per_day = 0\n",
+    "        for time in available_time_dict[day]:\n",
+    "            start_time = time.split('-')[0]\n",
+    "            end_time = time.split('-')[1]\n",
+    "            start_time = dt.datetime.strptime(start_time, '%H:%M')\n",
+    "            end_time = dt.datetime.strptime(end_time, '%H:%M')\n",
+    "            available_hour_per_day += (end_time - start_time).seconds/3600\n",
+    "\n",
+    "        available_hours[day] = available_hour_per_day\n",
+    "    return available_hours\n",
+    "\n",
+    "def map_time_slot(duration):\n",
+    "    # map each half hour to a number, so a day should have 0 - 48 \n",
+    "    # eg : duration - '06:00-18:00'\n",
+    "\n",
+    "    start_time = duration.split('-')[0]\n",
+    "    end_time = duration.split('-')[1]\n",
+    "\n",
+    "    start_time = dt.datetime.strptime(start_time, '%H:%M')\n",
+    "    end_time = dt.datetime.strptime(end_time, '%H:%M')\n",
+    "\n",
+    "    time_starter = dt.datetime.strptime('00:00', '%H:%M')\n",
+    "    idx_tracker = []\n",
+    "\n",
+    "    idx = 0\n",
+    "    while True:\n",
+    "        if time_starter >= start_time and time_starter < end_time:\n",
+    "            idx_tracker.append(idx)\n",
+    "        time_starter += dt.timedelta(minutes=30)\n",
+    "        idx += 1\n",
+    "        if time_starter >= dt.datetime.strptime('23:59', '%H:%M'):\n",
+    "            break\n",
+    "\n",
+    "    return idx_tracker\n",
+    "\n",
+    "def map_idx_to_time(idx):\n",
+    "    time_starter = dt.datetime.strptime('00:00', '%H:%M')\n",
+    "    for i in range(idx):\n",
+    "        time_starter += dt.timedelta(minutes=30)\n",
+    "    start_time = time_starter.strftime('%H:%M')\n",
+    "    end_time = (time_starter + dt.timedelta(minutes=30)).strftime('%H:%M')\n",
+    "    return f\"{start_time}-{end_time}\"\n",
+    "\n",
+    "def find_available_slots_per_week(available_time_dict):\n",
+    "    available_slots = {}\n",
+    "    for day in available_time_dict.keys():\n",
+    "        available_slots_per_day = []\n",
+    "        for time in available_time_dict[day]:\n",
+    "            available_slots_per_day += map_time_slot(time)\n",
+    "        available_slots[day] = available_slots_per_day\n",
+    "    return available_slots\n",
+    "\n",
+    "def extract_all_slots(available_times):\n",
+    "    slot_dict = find_available_slots_per_week(available_times)\n",
+    "    all_slots = []\n",
+    "    for dat, slots in slot_dict.items():\n",
+    "        for slot in slots:\n",
+    "            all_slots.append(f\"{dat}_{slot}\")\n",
+    "    return all_slots\n",
+    "\n",
+    "def reward_per_module(\n",
+    "                    student_details,\n",
+    "                    level_mapping = {\n",
+    "                        'Easy': 0,\n",
+    "                        'Average': 1,\n",
+    "                        'Hard': 2\n",
+    "                    }):\n",
+    "    df = pd.DataFrame(student_details)\n",
+    "    df['Student Level'] = df['Student Level'].map(level_mapping)\n",
+    "\n",
+    "    CreditPoints = df['Credit points'].values\n",
+    "    StudentLevel = df['Student Level'].values\n",
+    "    StudentLevel = [int(i) + 1 for i in StudentLevel]\n",
+    "\n",
+    "    TotalChapters = df['Total Chapters'].values\n",
+    "    StudiedAlready = df['Studied Already'].values\n",
+    "\n",
+    "    ChapterScore = (TotalChapters - StudiedAlready) / TotalChapters\n",
+    "\n",
+    "    reward = (CreditPoints * StudentLevel) * ChapterScore\n",
+    "    reward = reward / np.sum(reward)\n",
+    "\n",
+    "    modules = df['Subject name & PDF'].values\n",
+    "    return dict(zip(modules, reward))\n",
+    "\n",
+    "def q_learning():\n",
+    "    Q = np.zeros([7, 48])\n",
+    "\n",
+    "    gamma = 0.8\n",
+    "    alpha = 0.9\n",
+    "\n",
+    "    num_episodes = 1000\n",
+    "\n",
+    "    for i in range(num_episodes):\n",
+    "        s = 0\n",
+    "\n",
+    "        while s < 6:\n",
+    "            a = np.argmax(Q[s, :] + np.random.randn(1, 48) * (1. / (i + 1)))\n",
+    "\n",
+    "            s_prime = s + 1\n",
+    "            r = 1\n",
+    "\n",
+    "            Q[s, a] = Q[s, a] + alpha * (r + gamma * np.max(Q[s_prime, :]) - Q[s, a])\n",
+    "            s = s_prime\n",
+    "\n",
+    "    return Q\n",
+    "\n",
+    "def assign_slots_per_week(available_times, student_details):\n",
+    "    module_weights = reward_per_module(student_details)\n",
+    "    all_slots = extract_all_slots(available_times)\n",
+    "    module_weights = {k : int(v * len(all_slots)) for k, v in module_weights.items()}\n",
+    "    # sort the modules based on weights\n",
+    "    module_weights = {k: v for k, v in sorted(module_weights.items(), key=lambda item: item[1], reverse=True)}\n",
+    "    module_weights[list(module_weights.keys())[-1]] = (len(all_slots) - sum(module_weights.values())) + module_weights[list(module_weights.keys())[-1]]\n",
+    "\n",
+    "    all_slots_cp = all_slots.copy()\n",
+    "    all_slots_cp = np.array(all_slots_cp)\n",
+    "\n",
+    "    assign_slots = {}\n",
+    "    for module, weight in module_weights.items():\n",
+    "        Q = q_learning()\n",
+    "        rand_idxs = np.random.choice(len(all_slots_cp), weight, replace=False)\n",
+    "        module_json = {}\n",
+    "        for idx in rand_idxs:\n",
+    "            slopt_details = all_slots_cp[idx]\n",
+    "            day, splot_id = slopt_details.split('_')\n",
+    "            if day not in module_json.keys():\n",
+    "                module_json[day] = []\n",
+    "            module_json[day].append(int(splot_id))\n",
+    "            \n",
+    "        all_slots_cp = np.delete(all_slots_cp, rand_idxs)\n",
+    "        assign_slots[module] = module_json\n",
+    "\n",
+    "    for module, slots in assign_slots.items():\n",
+    "        for day, slot_ids in slots.items():\n",
+    "            # sort the slot ids in ascending order\n",
+    "            slot_ids = sorted(slot_ids)\n",
+    "            assign_slots[module][day] = slot_ids\n",
+    "            assign_slots[module][day] = [map_idx_to_time(i) for i in slot_ids]\n",
+    "\n",
+    "    return assign_slots"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# find_available_hours_per_week(available_times)\n",
+    "# find_available_slots_per_week(available_times)\n",
+    "# extract_all_slots(available_times)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'Internet & web technologies (IWT)': {'wednesday': ['05:00-05:30',\n",
+       "   '05:30-06:00',\n",
+       "   '18:00-18:30',\n",
+       "   '18:30-19:00',\n",
+       "   '19:00-19:30',\n",
+       "   '20:00-20:30',\n",
+       "   '20:30-21:00'],\n",
+       "  'sunday': ['07:00-07:30',\n",
+       "   '07:30-08:00',\n",
+       "   '08:00-08:30',\n",
+       "   '08:30-09:00',\n",
+       "   '09:30-10:00',\n",
+       "   '10:30-11:00',\n",
+       "   '11:00-11:30',\n",
+       "   '13:00-13:30',\n",
+       "   '13:30-14:00',\n",
+       "   '14:00-14:30',\n",
+       "   '15:30-16:00',\n",
+       "   '16:30-17:00'],\n",
+       "  'thursday': ['04:00-04:30',\n",
+       "   '04:30-05:00',\n",
+       "   '05:00-05:30',\n",
+       "   '05:30-06:00',\n",
+       "   '16:00-16:30',\n",
+       "   '17:00-17:30',\n",
+       "   '17:30-18:00',\n",
+       "   '18:30-19:00',\n",
+       "   '19:00-19:30',\n",
+       "   '19:30-20:00',\n",
+       "   '20:00-20:30',\n",
+       "   '20:30-21:00'],\n",
+       "  'friday': ['04:30-05:00',\n",
+       "   '16:00-16:30',\n",
+       "   '16:30-17:00',\n",
+       "   '17:00-17:30',\n",
+       "   '19:00-19:30',\n",
+       "   '19:30-20:00',\n",
+       "   '20:30-21:00'],\n",
+       "  'monday': ['04:00-04:30',\n",
+       "   '04:30-05:00',\n",
+       "   '05:00-05:30',\n",
+       "   '16:00-16:30',\n",
+       "   '16:30-17:00',\n",
+       "   '17:00-17:30',\n",
+       "   '17:30-18:00',\n",
+       "   '18:30-19:00',\n",
+       "   '19:00-19:30',\n",
+       "   '19:30-20:00',\n",
+       "   '20:00-20:30',\n",
+       "   '20:30-21:00'],\n",
+       "  'tuesday': ['04:00-04:30',\n",
+       "   '05:30-06:00',\n",
+       "   '17:30-18:00',\n",
+       "   '19:00-19:30',\n",
+       "   '19:30-20:00',\n",
+       "   '20:00-20:30',\n",
+       "   '20:30-21:00'],\n",
+       "  'saturday': ['06:00-06:30',\n",
+       "   '06:30-07:00',\n",
+       "   '07:30-08:00',\n",
+       "   '08:00-08:30',\n",
+       "   '08:30-09:00',\n",
+       "   '09:00-09:30',\n",
+       "   '09:30-10:00',\n",
+       "   '10:30-11:00',\n",
+       "   '11:30-12:00',\n",
+       "   '13:00-13:30',\n",
+       "   '14:30-15:00',\n",
+       "   '15:30-16:00',\n",
+       "   '16:00-16:30',\n",
+       "   '17:30-18:00']},\n",
+       " 'Software process modeling (SPM)': {'tuesday': ['05:00-05:30',\n",
+       "   '16:00-16:30',\n",
+       "   '16:30-17:00',\n",
+       "   '17:00-17:30',\n",
+       "   '18:30-19:00'],\n",
+       "  'saturday': ['12:30-13:00', '14:00-14:30', '16:30-17:00', '17:00-17:30'],\n",
+       "  'sunday': ['06:30-07:00',\n",
+       "   '09:00-09:30',\n",
+       "   '10:00-10:30',\n",
+       "   '11:30-12:00',\n",
+       "   '12:00-12:30',\n",
+       "   '12:30-13:00',\n",
+       "   '14:30-15:00',\n",
+       "   '16:00-16:30',\n",
+       "   '17:00-17:30'],\n",
+       "  'wednesday': ['04:30-05:00'],\n",
+       "  'thursday': ['14:00-14:30', '16:30-17:00'],\n",
+       "  'friday': ['05:30-06:00', '18:30-19:00', '20:00-20:30']},\n",
+       " 'Infromation system & data modeling (ISDM)': {'friday': ['05:00-05:30',\n",
+       "   '18:00-18:30'],\n",
+       "  'sunday': ['06:00-06:30', '15:00-15:30'],\n",
+       "  'tuesday': ['04:30-05:00', '18:00-18:30'],\n",
+       "  'saturday': ['10:00-10:30', '13:30-14:00', '15:00-15:30'],\n",
+       "  'wednesday': ['04:00-04:30', '19:30-20:00'],\n",
+       "  'thursday': ['18:00-18:30']},\n",
+       " 'English for academic purpose (EAP)': {'thursday': ['14:30-15:00',\n",
+       "   '15:00-15:30',\n",
+       "   '15:30-16:00'],\n",
+       "  'friday': ['04:00-04:30', '17:30-18:00'],\n",
+       "  'saturday': ['07:00-07:30', '11:00-11:30', '12:00-12:30'],\n",
+       "  'monday': ['18:00-18:30'],\n",
+       "  'sunday': ['17:30-18:00']},\n",
+       " 'Object oriented concepts (OOC)': {'monday': ['05:30-06:00']}}"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "assign_slots_per_week(available_times, student_details)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "tf210",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
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+   "mimetype": "text/x-python",
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+   "version": "3.8.16"
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+ },
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+}