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AICup/Lectures/Student_lecture 1.ipynb

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{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"collapsed": true,
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"## First Lab\n",
"\n",
"What we are going to do today:\n",
"- read TSP data\n",
"- define euclidean distance function\n",
"- define a ProblemInstance python class \n",
"- store nodes in an instance of the class defined before\n",
"- plot raw data\n",
"- generate naive solution \n",
"- check if the solution is valid\n",
"- evaluate solution!#\n",
"\n",
"NOTE: I've marked all the code that you will have to fill with a `# TODO` comment\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This cell below is simply importing some usefull stuff for later"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import glob\n",
"import numpy as np\n",
"from matplotlib import pyplot as plt"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Read TSP data\n",
"In this Cup you will have to deal with predefined set of problems. These problems are located in the `problems` folder.\n",
"\n",
"First lets get list them out"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ch130.tsp\n",
"d198.tsp\n",
"eil76.tsp\n",
"fl1577.tsp\n",
"kroA100.tsp\n",
"lin318.tsp\n",
"pcb442.tsp\n",
"pr439.tsp\n",
"rat783.tsp\n",
"u1060.tsp\n"
]
}
],
"source": [
"problems = glob.glob('../problems/*.tsp')\n",
"# example_problem = [\"./problems/eil76.tsp\"]\n",
"for prob in problems:\n",
" print(prob[12:])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Checking by hand if all of the 10 problems are in the folder would be a waste of time so we can write a line of code just to check if they are all there"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"True\n"
]
}
],
"source": [
"print(np.all([n[12:] in ['fl1577.tsp','pr439.tsp','ch130.tsp','rat783.tsp','d198.tsp', 'kroA100.tsp','u1060.tsp','lin318.tsp','eil76.tsp','pcb442.tsp'] for n in problems]))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### File format\n",
"All the problems are stored in a `.tsp` (this file is actually a renamed `.txt` file, so you could open them with your favorite text editor)\n",
"\n",
"As we will see in a bit all the problems files are composed of different sections:\n",
"* `NAME`: the shortned name of the problem\n",
"* `COMMENT`: a comment area that can contain the full name of the problem\n",
"* `TYPE`: this defines the type of problem at hand, in our case is always TSP\n",
"* `DIMENSION`: this states the problem dimension\n",
"* `EDGE_WEIGHT_TYPE`: this section states the types of weights applied to edges, in our case it is always EUC_2D or the weights are giveng using the euclidean distance in 2 dimension\n",
"* `BEST_KNOWN`: this states the best known result obtained, note that as the Prof said, it is unlikely to get a better performance than this\n",
"* `NODE_COORD_SECTION`: finally we have the section that states the triplets that defines the problems points. These triplets are (point_number, x,y).\n",
"\n",
"Now that we know all of that, lets print the content of a single problem"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['NAME : eil76', 'COMMENT : 76-city problem (Christofides/Eilon)', 'TYPE : TSP', 'DIMENSION : 76', 'EDGE_WEIGHT_TYPE : EUC_2D', 'BEST_KNOWN : 538', 'NODE_COORD_SECTION', '1 22 22', '2 36 26', '3 21 45', '4 45 35', '5 55 20', '6 33 34', '7 50 50', '8 55 45', '9 26 59', '10 40 66', '11 55 65', '12 35 51', '13 62 35', '14 62 57', '15 62 24', '16 21 36', '17 33 44', '18 9 56', '19 62 48', '20 66 14', '21 44 13', '22 26 13', '23 11 28', '24 7 43', '25 17 64', '26 41 46', '27 55 34', '28 35 16', '29 52 26', '30 43 26', '31 31 76', '32 22 53', '33 26 29', '34 50 40', '35 55 50', '36 54 10', '37 60 15', '38 47 66', '39 30 60', '40 30 50', '41 12 17', '42 15 14', '43 16 19', '44 21 48', '45 50 30', '46 51 42', '47 50 15', '48 48 21', '49 12 38', '50 15 56', '51 29 39', '52 54 38', '53 55 57', '54 67 41', '55 10 70', '56 6 25', '57 65 27', '58 40 60', '59 70 64', '60 64 4', '61 36 6', '62 30 20', '63 20 30', '64 15 5', '65 50 70', '66 57 72', '67 45 42', '68 38 33', '69 50 4', '70 66 8', '71 59 5', '72 35 60', '73 27 24', '74 40 20', '75 40 37', '76 40 40', 'EOF']\n"
]
}
],
"source": [
"example_problem = \"../problems/eil76.tsp\"\n",
"with open(example_problem,\"r\") as exprob:\n",
" print(exprob.read().splitlines())"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Euclidean Distance\n",
"Since all of our problems are using the euclidean distance between points for the edges weights.\n",
"We will now define a function that computes the euclidean distance. This distance will also be used to build the distance matrix"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"def distance_euc(point_i, point_j): # TODO\n",
" rounding = 0\n",
" # [...]\n",
" return round(distance, rounding)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's test it"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"4.0"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"point_1 = (2, 2)\n",
"point_2 = (5, 5)\n",
"distance_euc(point_1, point_2)\n",
"# Expected output is 4.0 with rounding to 0 "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Reading and storing the data\n",
"We will now define a Class called `ProblemInstance`\n",
"\n",
"in the Constructor of the class (`__init__()`method of a class in Python) you will have to implement the code for:\n",
"* reading the raw data\n",
"* store the metadata\n",
"* read all the point and store them\n",
"* code the method that creates the distance matrix between points\n",
"* \\[optional\\] check if the problem loaded has an optimal and in that case store the optimal solution\n",
"* \\[optional\\] code the plotting method\n"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"from src.utils import distance_euc\n",
"\n",
"class ProblemInstance:\n",
"\n",
" def __init__(self, name_tsp):\n",
" self.exist_opt = False\n",
" self.optimal_tour = None\n",
" self.dist_matrix = None\n",
" \n",
" # read raw data \n",
" # TODO\n",
" # [...]\n",
" self.lines = # here we expect a list of lines of the tsp file\n",
"\n",
" # store metadata set information \n",
" # TODO\n",
" self.name = # here we expect the name of the problem\n",
" self.nPoints = # here the number of pts\n",
" self.best_sol = # here the lenght of the best solution\n",
" \n",
" # read all data points and store them \n",
" # TODO\n",
" self.points = np.zeros((self.nPoints, 3)) # this is the structure where we will store the pts data \n",
" # [...] here you need to fill self.points \n",
" \n",
" self.create_dist_matrix()\n",
" \n",
" # TODO [optional]\n",
" # if the problem is one with a optimal solution, that solution is loaded\n",
" if name_tsp in [\"../problems/eil76.tsp\", \"../problems/kroA100.tsp\"]:\n",
" self.exist_opt = True\n",
" # [...]\n",
"\n",
" # read all data points and store them\n",
" self.optimal_tour = np.zeros(self.nPoints, dtype=np.int)\n",
" # [...]\n",
"\n",
" def print_info(self):\n",
" print(\"\\n#############################\\n\")\n",
" print('name: ' + self.name)\n",
" print('nPoints: ' + str(self.nPoints))\n",
" print('best_sol: ' + str(self.best_sol))\n",
" print('exist optimal: ' + str(self.exist_opt))\n",
"\n",
" def plot_data(self,show_numbers=False): # todo [optional]\n",
" plt.figure(figsize=(8, 8))\n",
" plt.title(self.name)\n",
" plt.scatter(self.points[:, 1], self.points[:, 2])\n",
" if show_numbers:\n",
" for i, txt in enumerate(np.arange(self.nPoints)): # tour_found[:-1]\n",
" plt.annotate(txt, (self.points[i, 1], self.points[i, 2]))\n",
" plt.show()\n",
"\n",
" def create_dist_matrix(self): # TODO\n",
" self.dist_matrix = # [...] define the size of the dist matrix\n",
" \n",
" # now fill it\n",
" # [...]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"------------------------\n",
"Now we can test our Class with an example problem"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"example_problem = \"../problems/eil76.tsp\"\n",
"p_inst=ProblemInstance(example_problem)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"#############################\n",
"\n",
"name: eil76\n",
"nPoints: 76\n",
"best_sol: 538.0\n",
"exist optimal: True\n"
]
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 576x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"p_inst.print_info()\n",
"p_inst.plot_data()\n",
"#Expected output\n",
"\"\"\"\n",
"#############################\n",
"\n",
"name: eil76\n",
"nPoints: 76\n",
"best_sol: 538.0\n",
"exist optimal: True\n",
"\n",
"\"\"\""
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 576x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"p_inst.plot_data(show_numbers=True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"-------------\n",
"### Random solver \n",
"Now we will code the random solver and test it with a class called `SolverTSP` that takes the solvers and the problem instance and act as a framework to compute the solution and gives us some additional information.\n",
"We will also need to code the `evaluate_solution` method of the the `SolverTSP` class"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"def random_method(instance_): # TODO\n",
" return solution\n",
"available_methods = {\"random\": random_method} # this is here because the SolverTSP will check for the available methods"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"from time import time as t\n",
"\n",
"class SolverTSP:\n",
" def __init__(self, algorithm_name, problem_instance):\n",
" self.duration = np.inf\n",
" self.found_length = np.inf\n",
" self.algorithm_name = algorithm_name\n",
" self.name_method = \"initialized with \" + algorithm_name\n",
" self.solved = False\n",
" self.problem_instance = problem_instance\n",
" self.solution = None\n",
"\n",
" def compute_solution(self, verbose=True, return_value=True):\n",
" self.solved = False\n",
" if verbose:\n",
" print(f\"### solving with {self.algorithm_name} ####\")\n",
" start_time = t()\n",
" self.solution = available_methods[self.algorithm_name](self.problem_instance)\n",
" assert self.check_if_solution_is_valid(self.solution), \"Error the solution is not valid\"\n",
" end_time = t()\n",
" self.duration = np.around(end_time - start_time, 3)\n",
" if verbose:\n",
" print(f\"### solved ####\")\n",
" self.solved = True\n",
" self.evaluate_solution()\n",
" self._gap()\n",
" if return_value:\n",
" return self.solution\n",
"\n",
" def plot_solution(self):\n",
" assert self.solved, \"You can't plot the solution, you need to compute it first!\"\n",
" plt.figure(figsize=(8, 8))\n",
" self._gap()\n",
" plt.title(f\"{self.problem_instance.name} solved with {self.name_method} solver, gap {self.gap}\")\n",
" ordered_points = self.problem_instance.points[self.solution]\n",
" plt.plot(ordered_points[:, 1], ordered_points[:, 2], 'b-')\n",
" plt.show()\n",
"\n",
" def check_if_solution_is_valid(self, solution):\n",
" rights_values = np.sum([self.check_validation(i, solution) for i in np.arange(self.problem_instance.nPoints)])\n",
" if rights_values == self.problem_instance.nPoints:\n",
" return True\n",
" else:\n",
" return False \n",
" def check_validation(self, node , solution):\n",
" if np.sum(solution == node) == 1:\n",
" return 1\n",
" else:\n",
" return 0\n",
"\n",
" def evaluate_solution(self, return_value=False):\n",
" total_length = 0\n",
" from_node = self.solution[0] # starting_node\n",
" # TODO\n",
" # [...] compute total_lenght of the solution \n",
" self.found_length = total_length\n",
" if return_value:\n",
" return total_length\n",
"\n",
" def _gap(self):\n",
" self.evaluate_solution(return_value=False)\n",
" self.gap = np.round(\n",
" ((self.found_length - self.problem_instance.best_sol) / self.problem_instance.best_sol) * 100, 2)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"----------------------------\n",
"Now we will test our code"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"### solving with random ####\n",
"### solved ####\n",
"the total length for the solution found is 2424.0\n",
"while the optimal length is 538.0\n",
"the gap is 350.56%\n",
"the solution is found in 0.0 seconds\n"
]
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 576x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"solver_name=\"random\"\n",
"# here I'm repeating this two lines just to remind you which problem we are using\n",
"example_problem = \"../problems/eil76.tsp\"\n",
"p_inst = ProblemInstance(example_problem)\n",
"\n",
"# TODO\n",
"# create an instance of SolverTSP\n",
"# compute a solution\n",
"# print the information as for the output\n",
"# plot the solution\n",
"\n",
"# this is the output expected and after that the solution's plot\n",
"\"\"\"\n",
"### solving with random ####\n",
"### solved ####\n",
"the total length for the solution found is 2424.0\n",
"while the optimal length is 538.0\n",
"the gap is 350.56%\n",
"the solution is found in 0.0 seconds\n",
"\"\"\""
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"--------------------\n",
"Finally since our example problem has an optimal solution we can plot it"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 576x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"solver = SolverTSP(\"optimal\", p_inst)\n",
"solver.solved = True\n",
"solver.solution = np.concatenate([p_inst.optimal_tour, [p_inst.optimal_tour[0]]])\n",
"solver.plot_solution()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "PyCharm (AI2020BsC)",
"language": "python",
"name": "pycharm-61970693"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.3"
}
},
"nbformat": 4,
"nbformat_minor": 1
}