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https://github.com/kuhyx/WUT_Computer_Science.git
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357 lines
14 KiB
Python
357 lines
14 KiB
Python
"""
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Write horizontal_line program that solves horizontal_line maze
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using greedy best-first search algorithm.
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The maze is horizontal_line 2D grid
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with empty space, walls, horizontal_line start, and an end position.
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The objective is to find horizontal_line path from start to end position.
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The maze should be loaded from file. horizontal_line step-by-step visualization of the
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algorithm is required. It can be done in the console and an interface may be
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as simple as possible (but of course it does not have to). Example solution:
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https://angeluriot.com/maze_solver/.
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Test multiple heuristics (at least two) h(n) and discuss the differences be-
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tween the obtained results.
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Technical requirements:
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- implemented in Python.
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- adheres to basic standards of lean coding in accordance to PEP8
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- comments in the crucial parts to help with readability and understanding.
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- The clear instruction how to run and test the code should be included.
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Thinks that do not work:
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Does not work if no Start (Should print out NO START FOUND)
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Does not work if no End (Should print out NO END FOUND)
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Does not work if no path (Should print out NO PATH FOUND)
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"""
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import heapq
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import sys
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import time
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import os
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from random import shuffle, randrange, random
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class MazeSolver:
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"""Maze Solver"""
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# self corresponds to "this" in js, it refers to object of MazeSolver class
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def __init__(self, maze, mode):
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# assign read maze 2D array to parameter from class MazeSolver
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self.test = mode
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self.maze = maze
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self.start, self.end = self.find_start_and_end()
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# go through each character in 2D array and find one that corresponds to
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# Start/End character
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def find_start_and_end(self):
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"""Finds start and end points in the maze"""
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start = end = None
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for row_i, row in enumerate(self.maze):
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for col_i, cell in enumerate(row):
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if cell == "S":
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start = (row_i, col_i)
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elif cell == "E":
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end = (row_i, col_i)
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if start is not None and end is not None:
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return start, end
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print(f"DID NOT FOUND START OR END, Start: {start}, End: {end}")
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return start, end
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# Go through each neighbor
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# N
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# N * N
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# N
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# If it is not horizontal_line "wall" (#) add its position to list of neighbors
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def get_neighbors(self, position):
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"""Finds point'maze_data neighbors"""
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row, col = position
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neighbors = []
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if row > 0 and self.maze[row - 1][col] != "#":
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neighbors.append((row - 1, col))
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if col > 0 and self.maze[row][col - 1] != "#":
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neighbors.append((row, col - 1))
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if row < len(self.maze) - 1 and self.maze[row + 1][col] != "#":
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neighbors.append((row + 1, col))
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if col < len(self.maze[row]) - 1 and self.maze[row][col + 1] != "#":
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neighbors.append((row, col + 1))
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return neighbors
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# find path through maze
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def solve_loop(self, queue, visited):
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""" Goes through maze and finds the path """
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heuristic_total_time = 0
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heuristics_called = 0
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while queue:
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# pop first element of heap
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# first value is skipped and we only save current position and path
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# on heap
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_, current, path = heapq.heappop(queue)
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# if we already visited current skip code and go to next iteration
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if current in visited:
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continue
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# if we found the end return path
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if current == self.end:
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break
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visited.add(current)
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for neighbor in self.get_neighbors(current):
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if neighbor not in visited:
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new_path = path + [neighbor]
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heuristic, heuristic_time = self.heuristic_manhattan(neighbor)
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heuristic_total_time += heuristic_time
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heuristics_called += 1
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heapq.heappush(
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queue, (heuristic, neighbor, new_path)
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)
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if not self.test:
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print_maze(self.maze, new_path)
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print()
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return path, heuristic_total_time, heuristics_called
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def solve(self):
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"""Solves the maze"""
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queue = []
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# set means that values inside can not repeat
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visited = set()
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# https://docs.python.org/3/library/heapq.html
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# push onto the queue (which becomes heapq), element containing values
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# we use heapq so the element with lowest heuristic value will always
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# be at the top of heap
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heuristic = self.heuristic_manhattan(self.start)
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heapq.heappush(
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queue, (heuristic, self.start, [self.start])
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)
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# Go through queue until it'maze_data empty
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# Find neighbor (which is not wall) closest to the
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# END point (based on heuristic)
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# Go there and repeat
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# if cannot find path it starts over but skips the path that lead it to
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# dead end
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return self.solve_loop(queue, visited)
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# This heuristic returns the Manhattan distance between the given position
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# and the maze'maze_data end
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def heuristic_manhattan(self, position):
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"""Heuristic function that uses Manhattan distance"""
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start_time = time.perf_counter()
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heuristic = abs(position[0] - self.end[0]) + abs(position[1] - self.end[1])
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end_time = time.perf_counter()
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heuristic_time = end_time - start_time
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return heuristic, heuristic_time
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# This heuristic returns the Euclidean distance between the given position
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# and the maze'maze_data end
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def heuristic_euclidean(self, position):
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"""Heuristic function that uses Euclidean distance"""
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start_time = time.perf_counter()
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heuristic = (
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abs(position[0] - self.end[0]) ** 2 + abs(position[1] - self.end[1]) ** 2
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) ** 0.5
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end_time = time.perf_counter()
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heuristic_time = end_time - start_time
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return heuristic, heuristic_time
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def heuristic_random(self):
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"""Heuristic function that just returns random value between 0 and 1"""
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start_time = time.perf_counter()
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heuristic = random()
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end_time = time.perf_counter()
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heuristic_time = end_time - start_time
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return heuristic, heuristic_time
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# Open and load text file to array
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def load_maze(maze_file_name):
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"""Loads horizontal_line maze from the specified file"""
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# Open for reading only and save to fileContents
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with open(maze_file_name, "r", encoding="utf8") as file_contents:
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# strip() removes extra white spaces from the beginning and the end of
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# horizontal_line string
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# list() changes string to array of chars
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# Inside of square brackets we will have an array of characters for
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# each line of file
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# After going through every line in horizontal_line file we will have 2D array of arrays
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# of characters of every line
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maze = [list(line.strip()) for line in file_contents]
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return maze
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def print_maze(maze, path=None):
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"""Prints the maze"""
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if path is None:
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path = []
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for row_i, row in enumerate(maze):
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for col_i, cell in enumerate(row):
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if (row_i, col_i) in path:
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print("*", end="")
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else:
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print(cell, end="")
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print()
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def create_maze_folder(solved):
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""" Creates folder for generated or solved mazes"""
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if solved:
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folder_name = "solvedMazes"
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else:
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folder_name = "generatedMazes"
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if not os.path.exists(folder_name):
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os.mkdir(folder_name)
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return folder_name
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def save_maze(maze, solved=True, path=None, saved_file="Maze", iteration=0):
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"""Saves maze from array to txt file"""
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folder_name = create_maze_folder(solved)
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with open(f"{folder_name}/{iteration}{saved_file}", "w", encoding="utf8") as maze_file:
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if path is None:
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path = []
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for row_i, row in enumerate(maze):
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for col_i, cell in enumerate(row):
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if (row_i, col_i) in path:
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maze_file.write("*")
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else:
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maze_file.write(cell)
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if solved:
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maze_file.write("\n")
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if not solved:
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maze_file.write("\n")
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def fill_generated_maze(hor, ver, width):
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""" Fills generated maze array from horizontal and vertical lines """
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maze_data = ""
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for horizontal_line, vertical_line in zip(hor, ver):
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maze_data += "".join(horizontal_line + ["\n"] + vertical_line + ["\n"])
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maze_data_list = list(maze_data)
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maze_data_list[3 * width + 3] = "S"
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maze_data_list[len(maze_data_list) - (3 * width + 6)] = "E"
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maze_data = "".join(maze_data_list)
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return maze_data
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def make_maze(width=16, height=8):
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""" generate maze with given width and height """
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vis = [[0] * width + [1] for _ in range(height)] + [[1] * (width + 1)]
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ver = [["# "] * width + ["#"] for _ in range(height)] + [[]]
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hor = [["###"] * width + ["#"] for _ in range(height + 1)]
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def walk(x_coordinate, y_coordinate):
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vis[y_coordinate][x_coordinate] = 1
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neighbors = [(x_coordinate - 1, y_coordinate),
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(x_coordinate, y_coordinate + 1),
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(x_coordinate + 1, y_coordinate),
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(x_coordinate, y_coordinate - 1)]
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shuffle(neighbors)
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for x_coordinate_neighbor, y_coordinate_neighbor in neighbors:
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if vis[y_coordinate_neighbor][x_coordinate_neighbor]:
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continue
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if x_coordinate_neighbor == x_coordinate:
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hor[max(y_coordinate, y_coordinate_neighbor)][x_coordinate] = "# "
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if y_coordinate_neighbor == y_coordinate:
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ver[y_coordinate][max(x_coordinate, x_coordinate_neighbor)] = " "
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walk(x_coordinate_neighbor, y_coordinate_neighbor)
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walk(randrange(width), randrange(height))
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return fill_generated_maze(hor, ver, width)
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def print_help():
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"""prints help"""
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print(
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"""python main.py - run the script against default maze file
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(any file named maze.txt in the code directory)
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python main.py filename.txt - run the script against filename.txt file
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python main.py -h --help print this prompt
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python main.py -t --test non interactive (does not print steps) for testing
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different heuristics, goes through entire generatedMazes folder and
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compares heuristic speed and path length
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python main.py -t --test [FOLDER] non interactive (does not print steps) for testing
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different heuristics, goes through entire [FOLDER] folder and
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compares heuristic speed and path length
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python main.py -g --generate [NUMBER] - generates as many mazes as entered in
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Number parameter and puts it in the generatedMazes folder"""
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)
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def test_mode():
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""" Loads and solves multiple mazes in order to compare heuristics """
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create_maze_folder(False)
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sum_of_paths = 0
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files_amount = 0
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sum_of_time = 0
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heuristic_total_total_time = 0
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all_heuristic_called = 0
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for filename in os.listdir(FOLDER_NAME):
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filename_directory = os.path.join(FOLDER_NAME, filename)
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# Open and load text file to array
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loaded_maze = load_maze(filename_directory)
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# Initialize MazeSolver object with maze as parameter
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solver_test = MazeSolver(loaded_maze, TEST_MODE)
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# Find path using MazeSolver solve method
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start_time = time.perf_counter()
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solved_path, heuristic_total_time, heuristics_called = solver_test.solve()
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heuristic_total_total_time += heuristic_total_time
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all_heuristic_called += heuristics_called
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end_time = time.perf_counter()
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sum_of_time += end_time - start_time
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sum_of_paths += len(solved_path)
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save_maze(loaded_maze, True, solved_path, filename, 0)
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files_amount += 1
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if files_amount == 0:
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print("no mazes found! Generate some using python main.py -g [NUMBER]")
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sys.exit()
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average_path = sum_of_paths / files_amount
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average_time = sum_of_time / files_amount
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print(f"""For: {files_amount} files,
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sum of path lengths = {sum_of_paths},
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average path length = {average_path},
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sum_of_time = {sum_of_time},
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average time to solve: {average_time},
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heuristic_total_total_time: {heuristic_total_total_time},
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all_heuristic_called: {all_heuristic_called},
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average_heuristic_time: {heuristic_total_total_time / all_heuristic_called}""")
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def default():
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""" Runs default operation - reads, solves and prints single maze from file """
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# Open and load text file to array
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loaded_maze = load_maze(FILE_NAME)
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# Initialize MazeSolver object with maze as parameter
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solver = MazeSolver(loaded_maze, TEST_MODE)
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# Find path using MazeSolver solve method
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solved_path = solver.solve()
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print_maze(loaded_maze, solved_path)
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save_maze(loaded_maze, True, solved_path, FILE_NAME, 0)
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# Ran first in the code
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if __name__ == "__main__":
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# print(sys.argv)
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FILE_NAME = "maze.txt"
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TEST_MODE = False
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FOLDER_NAME = ""
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GENERATE_AMOUNT = 0
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if len(sys.argv) > 1:
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if sys.argv[1] == "-h" or sys.argv[1] == "--help":
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print_help()
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sys.exit()
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if sys.argv[1] == "-t" or sys.argv[1] == "--test":
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TEST_MODE = True
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FILE_NAME = "maze.txt"
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FOLDER_NAME = "generatedMazes"
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if len(sys.argv) > 2:
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FOLDER_NAME = sys.argv[2]
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test_mode()
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sys.exit()
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if sys.argv[1] == '-g' or sys.argv[1] == '--generate':
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if len(sys.argv) > 2:
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GENERATE_AMOUNT = int(sys.argv[2])
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for n in range(GENERATE_AMOUNT):
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GENERATED_MAZE = make_maze()
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save_maze(GENERATED_MAZE, False, None, f'generated{n}.txt')
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sys.exit()
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FILE_NAME = sys.argv[1]
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default()
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