{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "924a2a50",
   "metadata": {},
   "source": [
    "## Question 3 (10 marks)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "2b3d1ba2",
   "metadata": {},
   "outputs": [],
   "source": [
    "import math\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "478bad7a",
   "metadata": {},
   "outputs": [],
   "source": [
    "points = np.load('data/points.npy').astype(np.uint8)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c1e442a7",
   "metadata": {},
   "source": [
    "## Method 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e07b0285",
   "metadata": {},
   "outputs": [],
   "source": [
    "def m1_compute_rotation_matrix(points, theta):\n",
    "    \"\"\"\n",
    "    Write a function compute_rotation_matrix(points, theta) to compute the rotation matrix in\n",
    "    homogeneous coordinate system to rotate a shape depicted with 2-dimensional (x,y) coordinates\n",
    "    points with an angle 𝜃 (theta in the definition) in the anticlockwise direction about the centre of the shape.\n",
    "\n",
    "    Parameters:\n",
    "    points: a 2-dimensional numpy array of data type uint8 with shape 𝑘 × 2. Each row\n",
    "    of points is a Cartesian coordinate (x, y).\n",
    "    \n",
    "    theta: a floating-point number denoting the angle of rotation in degree.\n",
    "    \n",
    "    Returns:\n",
    "    The expected output is a 2-dimensional numpy array of data type float64 with shape 3 × 3.\n",
    "    \"\"\"\n",
    "\n",
    "    # Convert theta from degrees to radians\n",
    "    theta_rad = np.radians(theta)\n",
    "\n",
    "    # Calculate the centre of the shape\n",
    "    centre = np.mean(points, axis=0)\n",
    "\n",
    "    # Define the translation matrices to move the centre of the shape to the origin and back\n",
    "    translation_to_origin = np.array([[1, 0, -centre[0]],\n",
    "                                      [0, 1, -centre[1]],\n",
    "                                      [0, 0, 1]], dtype=np.float64)\n",
    "\n",
    "    translation_back = np.array([[1, 0, centre[0]],\n",
    "                                 [0, 1, centre[1]],\n",
    "                                 [0, 0, 1]], dtype=np.float64)\n",
    "\n",
    "    # Define the rotation matrix about the origin\n",
    "    rotation = np.array([[np.cos(theta_rad), -np.sin(theta_rad), 0],\n",
    "                         [np.sin(theta_rad),  np.cos(theta_rad), 0],\n",
    "                         [0,                 0,                1]], dtype=np.float64)\n",
    "\n",
    "    # Combine the translation and rotation into a single transformation matrix\n",
    "    rotation_matrix = np.dot(np.dot(translation_back, rotation), translation_to_origin)\n",
    "    \n",
    "    return rotation_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "16ef4247",
   "metadata": {},
   "outputs": [],
   "source": [
    "m1_rotation_matrices = []\n",
    "\n",
    "for t in range(0, 365, 5):\n",
    "    m1_rotation_matrices.append( m1_compute_rotation_matrix(points, t) )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5554bde0",
   "metadata": {},
   "source": [
    "## Method 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "087b6ac9",
   "metadata": {},
   "outputs": [],
   "source": [
    "def m2_compute_rotation_matrix(points, theta):\n",
    "\n",
    "    # Convert angle to radians\n",
    "    theta_rad = np.deg2rad(theta)\n",
    "    \n",
    "    cos_theta = np.cos(theta_rad)\n",
    "    sin_theta = np.sin(theta_rad)\n",
    "\n",
    "    # Compute center of the shape\n",
    "    center = np.mean(points, axis=0)\n",
    "    \n",
    "    # Construct rotation matrix\n",
    "    rotation_matrix = np.array([\n",
    "        [ cos_theta, -sin_theta, -center[0] * cos_theta + center[1] * sin_theta + center[0] ],\n",
    "        [ sin_theta, cos_theta, -center[0] * sin_theta - center[1] * cos_theta + center[1] ],\n",
    "        [0, 0, 1]\n",
    "    ])\n",
    "    \n",
    "    return rotation_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "02ec3b60",
   "metadata": {},
   "outputs": [],
   "source": [
    "m2_rotation_matrices = []\n",
    "\n",
    "for t in range(0, 365, 5):\n",
    "    m2_rotation_matrices.append( m2_compute_rotation_matrix(points, t) )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a130c201",
   "metadata": {},
   "source": [
    "## Save Output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "23967b5d",
   "metadata": {},
   "outputs": [],
   "source": [
    "np.save('data/question_3_rotation_matrices.npy', m1_rotation_matrices)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a808d8a4",
   "metadata": {},
   "source": [
    "## Put students' implementations here"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "06417b95",
   "metadata": {},
   "source": [
    "This is one common mistake."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b0836f8d",
   "metadata": {},
   "outputs": [],
   "source": [
    "def compute_rotation_matrix(points, theta):\n",
    "\n",
    "    # Convert angle to radians\n",
    "    theta_rad = np.deg2rad(theta)\n",
    "    \n",
    "    # Calculate sine and cosine of the angle\n",
    "    cos_theta = np.cos(theta_rad)\n",
    "    sin_theta = np.sin(theta_rad)\n",
    "    \n",
    "    # Compute center of the shape\n",
    "    center = np.mean(points, axis=0)\n",
    "    \n",
    "    # Translate points to origin\n",
    "    translated_points = points - center\n",
    "    \n",
    "    # Wrong: Construct rotation matrix\n",
    "    rotation_matrix = np.array([[cos_theta, -sin_theta, center[0]],\n",
    "                                 [sin_theta, cos_theta, center[1]],\n",
    "                                 [0, 0, 1]])\n",
    "    \n",
    "    return rotation_matrix"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "73b68192",
   "metadata": {},
   "source": [
    "## Test (Should output ALL PASS)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1c0a88a6",
   "metadata": {},
   "source": [
    "Restart and Run ALL for each submission"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "132d734b",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 PASS\n",
      "Failed\n"
     ]
    },
    {
     "ename": "AssertionError",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mAssertionError\u001b[0m                            Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[9], line 9\u001b[0m\n\u001b[0;32m      6\u001b[0m \u001b[38;5;28mprint\u001b[39m(n_pass, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mPASS\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m      8\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m----> 9\u001b[0m     \u001b[38;5;28;01massert\u001b[39;00m n_pass \u001b[38;5;241m==\u001b[39m \u001b[38;5;28mlen\u001b[39m(m1_rotation_matrices)\n\u001b[0;32m     10\u001b[0m     \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mALL PASS\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m     11\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mAssertionError\u001b[39;00m:\n",
      "\u001b[1;31mAssertionError\u001b[0m: "
     ]
    }
   ],
   "source": [
    "n_pass = 0\n",
    "for t in range(0, 365, 5):\n",
    "    if np.allclose(compute_rotation_matrix(points, t), m1_rotation_matrices[int(t / 5)]):\n",
    "        n_pass = n_pass + 1\n",
    "\n",
    "print(n_pass, \"PASS\")\n",
    "\n",
    "try:\n",
    "    assert n_pass == len(m1_rotation_matrices)\n",
    "    print(\"ALL PASS\")\n",
    "except AssertionError:\n",
    "    print(\"Failed\")\n",
    "    raise"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "03e9c423",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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