789 lines
17 KiB
Python
789 lines
17 KiB
Python
import time
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from collections import deque
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import heapq
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import csv
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import os
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import random
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import matplotlib.pyplot as plt
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# ============================================================
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# ЭТАП 1. МОДЕЛЬ ЛАБИРИНТА
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# ============================================================
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class Cell:
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def __init__(self, x, y, is_wall=False, is_start=False, is_exit=False):
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self.x = x
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self.y = y
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self.is_wall = is_wall
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self.is_start = is_start
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self.is_exit = is_exit
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self.weight = 1
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def isPassable(self):
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return not self.is_wall
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def __repr__(self):
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return f"Cell({self.x},{self.y})"
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def __hash__(self):
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return hash((self.x, self.y))
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def __eq__(self, other):
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return isinstance(other, Cell) and self.x == other.x and self.y == other.y
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class Maze:
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def __init__(self, width, height):
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self.width = width
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self.height = height
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self.cells = []
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self.start = None
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self.exit = None
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def getCell(self, x, y):
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if 0 <= x < self.width and 0 <= y < self.height:
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return self.cells[y][x]
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return None
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def getNeighbors(self, cell):
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neighbors = []
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for dx, dy in [(0, -1), (0, 1), (-1, 0), (1, 0)]:
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nx = cell.x + dx
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ny = cell.y + dy
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neighbor = self.getCell(nx, ny)
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if neighbor and neighbor.isPassable():
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neighbors.append(neighbor)
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return neighbors
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def getWeightedNeighbors(self, cell):
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return [(n, n.weight) for n in self.getNeighbors(cell)]
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# ============================================================
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# ЭТАП 2. BUILDER
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# ============================================================
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class MazeBuilder:
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def buildFromFile(self, filename):
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raise NotImplementedError
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class TextFileMazeBuilder(MazeBuilder):
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def buildFromFile(self, filename):
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with open(filename, 'r', encoding='utf-8') as f:
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lines = [line.rstrip('\n') for line in f]
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height = len(lines)
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width = max(len(line) for line in lines)
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maze = Maze(width, height)
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for y, line in enumerate(lines):
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row = []
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for x, char in enumerate(line):
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if char == '#':
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cell = Cell(x, y, is_wall=True)
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elif char == 'S':
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cell = Cell(x, y, is_start=True)
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maze.start = cell
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elif char == 'E':
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cell = Cell(x, y, is_exit=True)
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maze.exit = cell
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else:
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cell = Cell(x, y)
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row.append(cell)
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while len(row) < width:
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row.append(Cell(len(row), y, is_wall=True))
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maze.cells.append(row)
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if maze.start is None or maze.exit is None:
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raise ValueError("В лабиринте нет S или E")
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return maze
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# ============================================================
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# ВОССТАНОВЛЕНИЕ ПУТИ
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# ============================================================
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def reconstruct_path(parents, end_cell):
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path = []
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current = end_cell
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while current is not None:
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path.append(current)
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current = parents[current]
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path.reverse()
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return path
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# ============================================================
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# ЭТАП 3. STRATEGY
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# ============================================================
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class PathFindingStrategy:
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@property
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def name(self):
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return "Unknown"
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def findPath(self, maze, start, exit):
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raise NotImplementedError
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# ============================================================
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# BFS
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# ============================================================
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class BFSStrategy(PathFindingStrategy):
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@property
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def name(self):
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return "BFS"
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def findPath(self, maze, start, exit):
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queue = deque([start])
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visited = {start}
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parents = {
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start: None
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}
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visited_count = 1
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while queue:
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current = queue.popleft()
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if current == exit:
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path = reconstruct_path(parents, exit)
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return path, visited_count
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for neighbor in maze.getNeighbors(current):
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if neighbor not in visited:
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visited.add(neighbor)
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parents[neighbor] = current
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visited_count += 1
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queue.append(neighbor)
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return [], visited_count
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# ============================================================
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# DFS
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# ============================================================
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class DFSStrategy(PathFindingStrategy):
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@property
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def name(self):
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return "DFS"
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def findPath(self, maze, start, exit):
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stack = [start]
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visited = {start}
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parents = {
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start: None
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}
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visited_count = 1
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while stack:
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current = stack.pop()
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if current == exit:
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path = reconstruct_path(parents, exit)
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return path, visited_count
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for neighbor in maze.getNeighbors(current):
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if neighbor not in visited:
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visited.add(neighbor)
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parents[neighbor] = current
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visited_count += 1
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stack.append(neighbor)
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return [], visited_count
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# ============================================================
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# A*
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# ============================================================
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class AStarStrategy(PathFindingStrategy):
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@property
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def name(self):
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return "A*"
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def heuristic(self, a, b):
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return abs(a.x - b.x) + abs(a.y - b.y)
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def findPath(self, maze, start, exit):
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counter = 0
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open_set = []
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heapq.heappush(open_set, (0, counter, start))
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parents = {
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start: None
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}
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g_score = {
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start: 0
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}
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visited = set()
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visited_count = 0
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while open_set:
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_, _, current = heapq.heappop(open_set)
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if current in visited:
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continue
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visited.add(current)
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visited_count += 1
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if current == exit:
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path = reconstruct_path(parents, exit)
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return path, visited_count
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for neighbor in maze.getNeighbors(current):
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tentative_g = g_score[current] + 1
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if neighbor not in g_score or tentative_g < g_score[neighbor]:
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g_score[neighbor] = tentative_g
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parents[neighbor] = current
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f_score = tentative_g + self.heuristic(neighbor, exit)
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counter += 1
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heapq.heappush(
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open_set,
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(f_score, counter, neighbor)
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)
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return [], visited_count
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# ============================================================
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# DIJKSTRA
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# ============================================================
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class DijkstraStrategy(PathFindingStrategy):
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@property
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def name(self):
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return "Dijkstra"
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def findPath(self, maze, start, exit):
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counter = 0
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queue = []
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heapq.heappush(queue, (0, counter, start))
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distances = {
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start: 0
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}
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parents = {
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start: None
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}
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visited = set()
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visited_count = 0
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while queue:
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dist, _, current = heapq.heappop(queue)
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if current in visited:
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continue
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visited.add(current)
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visited_count += 1
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if current == exit:
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path = reconstruct_path(parents, exit)
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return path, visited_count
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for neighbor, weight in maze.getWeightedNeighbors(current):
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new_dist = dist + weight
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if neighbor not in distances or new_dist < distances[neighbor]:
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distances[neighbor] = new_dist
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parents[neighbor] = current
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counter += 1
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heapq.heappush(
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queue,
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(new_dist, counter, neighbor)
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)
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return [], visited_count
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# ============================================================
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# ЭТАП 4. STATS + SOLVER
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# ============================================================
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class SearchStats:
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def __init__(
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self,
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strategy_name,
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time_ms,
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visited_cells,
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path_length,
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path_found
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):
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self.strategy_name = strategy_name
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self.time_ms = time_ms
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self.visited_cells = visited_cells
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self.path_length = path_length
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self.path_found = path_found
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class MazeSolver:
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def __init__(self, maze, strategy=None):
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self.maze = maze
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self.strategy = strategy
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def setStrategy(self, strategy):
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self.strategy = strategy
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def solve(self):
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if self.strategy is None:
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raise ValueError("Стратегия не выбрана")
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start_time = time.perf_counter()
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path, visited = self.strategy.findPath(
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self.maze,
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self.maze.start,
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self.maze.exit
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)
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end_time = time.perf_counter()
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elapsed_ms = (end_time - start_time) * 1000
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return SearchStats(
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self.strategy.name,
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elapsed_ms,
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visited,
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len(path),
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len(path) > 0
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), path
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# ============================================================
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# ВИЗУАЛИЗАЦИЯ
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# ============================================================
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def render(maze, path=None):
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path_set = set(path) if path else set()
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for y in range(maze.height):
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line = ""
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for x in range(maze.width):
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cell = maze.getCell(x, y)
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if cell == maze.start:
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line += "S"
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elif cell == maze.exit:
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line += "E"
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elif cell in path_set:
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line += "."
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elif cell.is_wall:
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line += "#"
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else:
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line += " "
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print(line)
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print()
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# ============================================================
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# ФАЙЛЫ И ПУТИ
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# ============================================================
|
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OUTPUT_DIR = os.path.join("docs", "data")
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PREFIX = "_2lab"
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os.makedirs(OUTPUT_DIR, exist_ok=True)
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def get_path(filename):
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name, ext = os.path.splitext(filename)
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return os.path.join(
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OUTPUT_DIR,
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f"{name}{PREFIX}{ext}"
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)
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# ============================================================
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# СОЗДАНИЕ ЛАБИРИНТА
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# ============================================================
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def create_test_maze(filename, lines):
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with open(filename, 'w', encoding='utf-8') as f:
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for line in lines:
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f.write(line + '\n')
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return filename
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# ============================================================
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# ГЕНЕРАЦИЯ
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# ============================================================
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def generate_maze(width, height, wall_density=0.3):
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grid = [[' ' for _ in range(width)] for _ in range(height)]
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for x in range(width):
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grid[0][x] = '#'
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grid[height - 1][x] = '#'
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for y in range(height):
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grid[y][0] = '#'
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grid[y][width - 1] = '#'
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x, y = 1, 1
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path_cells = {(x, y)}
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while x < width - 2 or y < height - 2:
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if x < width - 2 and random.random() > 0.3:
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x += 1
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elif y < height - 2:
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y += 1
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else:
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x += 1
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path_cells.add((x, y))
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for yy in range(1, height - 1):
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for xx in range(1, width - 1):
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if (xx, yy) not in path_cells:
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if random.random() < wall_density:
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grid[yy][xx] = '#'
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grid[1][1] = 'S'
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grid[height - 2][width - 2] = 'E'
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return [''.join(row) for row in grid]
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|
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|
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def generate_empty_maze(size):
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lines = [" " * size for _ in range(size)]
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lines[0] = "S" + " " * (size - 1)
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|
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lines[size - 1] = " " * (size - 1) + "E"
|
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|
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return lines
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|
||
|
||
def generate_no_exit_maze(size):
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|
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lines = generate_maze(size, size, wall_density=0.2)
|
||
|
||
for y, line in enumerate(lines):
|
||
|
||
if 'E' in line:
|
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|
||
x = line.index('E')
|
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|
||
for dy, dx in [(-1, 0), (1, 0), (0, -1), (0, 1)]:
|
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|
||
ny = y + dy
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nx = x + dx
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|
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if 0 <= ny < size and 0 <= nx < size:
|
||
|
||
if lines[ny][nx] == ' ':
|
||
|
||
lines[ny] = (
|
||
lines[ny][:nx]
|
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+ '#'
|
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+ lines[ny][nx + 1:]
|
||
)
|
||
|
||
return lines
|
||
|
||
|
||
# ============================================================
|
||
# ЭКСПЕРИМЕНТЫ
|
||
# ============================================================
|
||
|
||
def run_experiments():
|
||
|
||
mazes = {
|
||
|
||
"small": [
|
||
"##########",
|
||
"#S #",
|
||
"# ###### #",
|
||
"# # # #",
|
||
"# # ## # #",
|
||
"# # ## # #",
|
||
"# # # #",
|
||
"# ###### #",
|
||
"# E#",
|
||
"##########"
|
||
],
|
||
|
||
"medium": generate_maze(50, 50, 0.35),
|
||
|
||
"large": generate_maze(100, 100, 0.4),
|
||
|
||
"empty": generate_empty_maze(20),
|
||
|
||
"no_exit": generate_no_exit_maze(15)
|
||
}
|
||
|
||
strategies = [
|
||
BFSStrategy(),
|
||
DFSStrategy(),
|
||
AStarStrategy(),
|
||
DijkstraStrategy()
|
||
]
|
||
|
||
results = []
|
||
|
||
print("=" * 60)
|
||
print("ЭКСПЕРИМЕНТЫ")
|
||
print("=" * 60)
|
||
|
||
for maze_name, lines in mazes.items():
|
||
|
||
filename = get_path(f"{maze_name}.txt")
|
||
|
||
create_test_maze(filename, lines)
|
||
|
||
maze = TextFileMazeBuilder().buildFromFile(filename)
|
||
|
||
print(f"\nЛабиринт: {maze_name}")
|
||
print("-" * 60)
|
||
|
||
for strategy in strategies:
|
||
|
||
times = []
|
||
visited_values = []
|
||
|
||
final_path_len = 0
|
||
|
||
for _ in range(5):
|
||
|
||
solver = MazeSolver(maze)
|
||
|
||
solver.setStrategy(strategy)
|
||
|
||
stats, path = solver.solve()
|
||
|
||
times.append(stats.time_ms)
|
||
|
||
visited_values.append(stats.visited_cells)
|
||
|
||
final_path_len = stats.path_length
|
||
|
||
avg_time = sum(times) / len(times)
|
||
|
||
avg_visited = sum(visited_values) / len(visited_values)
|
||
|
||
results.append({
|
||
"maze": maze_name,
|
||
"strategy": strategy.name,
|
||
"time_ms": round(avg_time, 4),
|
||
"visited": int(avg_visited),
|
||
"path_length": final_path_len
|
||
})
|
||
|
||
status = "найден" if final_path_len > 0 else "не найден"
|
||
|
||
print(
|
||
f"{strategy.name:<10} | "
|
||
f"{avg_time:>8.4f} мс | "
|
||
f"{int(avg_visited):>5} клеток | "
|
||
f"путь {status}"
|
||
)
|
||
|
||
csv_path = get_path("results.csv")
|
||
|
||
with open(csv_path, "w", newline="", encoding='utf-8') as f:
|
||
|
||
writer = csv.DictWriter(
|
||
f,
|
||
fieldnames=[
|
||
"maze",
|
||
"strategy",
|
||
"time_ms",
|
||
"visited",
|
||
"path_length"
|
||
]
|
||
)
|
||
|
||
writer.writeheader()
|
||
|
||
writer.writerows(results)
|
||
|
||
print(f"\nCSV сохранён: {csv_path}")
|
||
|
||
return results
|
||
|
||
|
||
# ============================================================
|
||
# ГРАФИК
|
||
# ============================================================
|
||
|
||
def build_charts(results):
|
||
|
||
mazes = list(dict.fromkeys(r["maze"] for r in results))
|
||
|
||
strategies = list(dict.fromkeys(r["strategy"] for r in results))
|
||
|
||
fig, ax = plt.subplots(figsize=(12, 6))
|
||
|
||
x = range(len(mazes))
|
||
|
||
width = 0.2
|
||
|
||
colors = {
|
||
'BFS': '#3498db',
|
||
'DFS': '#e74c3c',
|
||
'A*': '#2ecc71',
|
||
'Dijkstra': '#f39c12'
|
||
}
|
||
|
||
for i, strategy in enumerate(strategies):
|
||
|
||
times = [
|
||
r["time_ms"]
|
||
for r in results
|
||
if r["strategy"] == strategy
|
||
]
|
||
|
||
ax.bar(
|
||
[j + i * width for j in x],
|
||
times,
|
||
width,
|
||
label=strategy,
|
||
color=colors.get(strategy, 'gray')
|
||
)
|
||
|
||
ax.set_xlabel("Лабиринт")
|
||
|
||
ax.set_ylabel("Время (мс)")
|
||
|
||
ax.set_title("Сравнение алгоритмов")
|
||
|
||
ax.set_xticks([j + width * 1.5 for j in x])
|
||
|
||
ax.set_xticklabels(mazes)
|
||
|
||
ax.legend()
|
||
|
||
ax.grid(axis='y', alpha=0.3)
|
||
|
||
plt.tight_layout()
|
||
|
||
chart_path = get_path("chart_time.png")
|
||
|
||
plt.savefig(chart_path, dpi=150, bbox_inches='tight')
|
||
|
||
print(f"График сохранён: {chart_path}")
|
||
|
||
plt.show()
|
||
|
||
|
||
# ============================================================
|
||
# MAIN
|
||
# ============================================================
|
||
|
||
def main():
|
||
|
||
results = run_experiments()
|
||
|
||
build_charts(results)
|
||
|
||
|
||
if __name__ == "__main__":
|
||
main() |