forked from UNN/2026-rff_mp
[2] Add plots generator
This commit is contained in:
parent
1bb67bff28
commit
b335daa881
370
anikinvd/docs/data/2-nd-exercise/plots.py
Normal file
370
anikinvd/docs/data/2-nd-exercise/plots.py
Normal file
|
|
@ -0,0 +1,370 @@
|
|||
import sys
|
||||
import csv
|
||||
from collections import deque
|
||||
import heapq
|
||||
import time
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
|
||||
|
||||
# ---------- Модель ----------
|
||||
class Node:
|
||||
def __init__(self, x, y):
|
||||
self.x = x
|
||||
self.y = y
|
||||
self.wall = False
|
||||
self.start_flag = False
|
||||
self.exit_flag = False
|
||||
|
||||
@property
|
||||
def is_wall(self):
|
||||
return self.wall
|
||||
|
||||
@is_wall.setter
|
||||
def is_wall(self, val):
|
||||
self.wall = val
|
||||
|
||||
@property
|
||||
def is_start(self):
|
||||
return self.start_flag
|
||||
|
||||
@is_start.setter
|
||||
def is_start(self, val):
|
||||
self.start_flag = val
|
||||
|
||||
@property
|
||||
def is_exit(self):
|
||||
return self.exit_flag
|
||||
|
||||
@is_exit.setter
|
||||
def is_exit(self, val):
|
||||
self.exit_flag = val
|
||||
|
||||
def passable(self):
|
||||
return not self.wall
|
||||
|
||||
|
||||
class Grid:
|
||||
def __init__(self, w, h):
|
||||
self.w = w
|
||||
self.h = h
|
||||
self.cells = [[Node(x, y) for x in range(w)] for y in range(h)]
|
||||
self.start_node = None
|
||||
self.exit_node = None
|
||||
|
||||
def get(self, x, y):
|
||||
if 0 <= x < self.w and 0 <= y < self.h:
|
||||
return self.cells[y][x]
|
||||
return None
|
||||
|
||||
def set_type(self, x, y, typ):
|
||||
cell = self.get(x, y)
|
||||
if not cell:
|
||||
return
|
||||
if typ == 'wall':
|
||||
cell.is_wall = True
|
||||
elif typ == 'start':
|
||||
if self.start_node:
|
||||
self.start_node.is_start = False
|
||||
cell.is_start = True
|
||||
cell.is_wall = False
|
||||
self.start_node = cell
|
||||
elif typ == 'exit':
|
||||
if self.exit_node:
|
||||
self.exit_node.is_exit = False
|
||||
cell.is_exit = True
|
||||
cell.is_wall = False
|
||||
self.exit_node = cell
|
||||
elif typ == 'path':
|
||||
cell.is_wall = False
|
||||
|
||||
def neighbors(self, node):
|
||||
res = []
|
||||
dirs = [(0, -1), (0, 1), (-1, 0), (1, 0)]
|
||||
for dx, dy in dirs:
|
||||
nx, ny = node.x + dx, node.y + dy
|
||||
nb = self.get(nx, ny)
|
||||
if nb and nb.passable():
|
||||
res.append(nb)
|
||||
return res
|
||||
|
||||
|
||||
class Loader:
|
||||
def load(self, fname):
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
class TxtLoader(Loader):
|
||||
def load(self, fname):
|
||||
with open(fname, 'r') as f:
|
||||
lines = [line.rstrip('\n') for line in f.readlines()]
|
||||
h = len(lines)
|
||||
w = max(len(line) for line in lines) if h > 0 else 0
|
||||
start_cnt = 0
|
||||
exit_cnt = 0
|
||||
grid = Grid(w, h)
|
||||
|
||||
for y, line in enumerate(lines):
|
||||
for x, ch in enumerate(line):
|
||||
if ch == "#":
|
||||
grid.set_type(x, y, "wall")
|
||||
elif ch == "S":
|
||||
grid.set_type(x, y, "start")
|
||||
start_cnt += 1
|
||||
elif ch == "E":
|
||||
grid.set_type(x, y, "exit")
|
||||
exit_cnt += 1
|
||||
else:
|
||||
grid.set_type(x, y, 'path')
|
||||
|
||||
if start_cnt != 1 or exit_cnt != 1:
|
||||
raise ValueError(f"Bad maze: S={start_cnt}, E={exit_cnt}")
|
||||
return grid
|
||||
|
||||
|
||||
# ---------- Поисковые стратегии ----------
|
||||
class SearchAlgo:
|
||||
def search(self, grid, start, goal):
|
||||
raise NotImplementedError
|
||||
|
||||
def _reconstruct(self, parent, start, goal):
|
||||
path = []
|
||||
cur = goal
|
||||
while cur:
|
||||
path.append(cur)
|
||||
cur = parent.get(cur)
|
||||
path.reverse()
|
||||
return path
|
||||
|
||||
def visited_count(self):
|
||||
return getattr(self, '_visited_num', 0)
|
||||
|
||||
|
||||
class BFSAlgo(SearchAlgo):
|
||||
def search(self, grid, start, goal):
|
||||
q = deque([start])
|
||||
parent = {start: None}
|
||||
seen = {start}
|
||||
|
||||
while q:
|
||||
cur = q.popleft()
|
||||
if cur == goal:
|
||||
self._visited_num = len(seen)
|
||||
return self._reconstruct(parent, start, goal)
|
||||
for nb in grid.neighbors(cur):
|
||||
if nb not in seen:
|
||||
seen.add(nb)
|
||||
parent[nb] = cur
|
||||
q.append(nb)
|
||||
self._visited_num = len(seen)
|
||||
return []
|
||||
|
||||
|
||||
class DFSAlgo(SearchAlgo):
|
||||
def search(self, grid, start, goal):
|
||||
stack = [start]
|
||||
parent = {start: None}
|
||||
seen = {start}
|
||||
|
||||
while stack:
|
||||
cur = stack.pop()
|
||||
if cur == goal:
|
||||
self._visited_num = len(seen)
|
||||
return self._reconstruct(parent, start, goal)
|
||||
for nb in grid.neighbors(cur):
|
||||
if nb not in seen:
|
||||
seen.add(nb)
|
||||
parent[nb] = cur
|
||||
stack.append(nb)
|
||||
self._visited_num = len(seen)
|
||||
return []
|
||||
|
||||
|
||||
class AStarAlgo(SearchAlgo):
|
||||
def _h(self, a, b):
|
||||
return abs(a.x - b.x) + abs(a.y - b.y)
|
||||
|
||||
def search(self, grid, start, goal):
|
||||
heap = []
|
||||
cnt = 0
|
||||
start_f = self._h(start, goal)
|
||||
heapq.heappush(heap, (start_f, cnt, start))
|
||||
cnt += 1
|
||||
|
||||
parent = {}
|
||||
g_score = {start: 0}
|
||||
f_score = {start: start_f}
|
||||
seen = set()
|
||||
|
||||
while heap:
|
||||
cur_f, _, cur = heapq.heappop(heap)
|
||||
seen.add(cur)
|
||||
if cur == goal:
|
||||
self._visited_num = len(seen)
|
||||
return self._reconstruct(parent, start, goal)
|
||||
if cur_f > f_score.get(cur, float('inf')):
|
||||
continue
|
||||
for nb in grid.neighbors(cur):
|
||||
tentative_g = g_score[cur] + 1
|
||||
if tentative_g < g_score.get(nb, float('inf')):
|
||||
parent[nb] = cur
|
||||
g_score[nb] = tentative_g
|
||||
new_f = tentative_g + self._h(nb, goal)
|
||||
f_score[nb] = new_f
|
||||
heapq.heappush(heap, (new_f, cnt, nb))
|
||||
cnt += 1
|
||||
self._visited_num = len(seen)
|
||||
return []
|
||||
|
||||
|
||||
class Solver:
|
||||
def __init__(self, grid):
|
||||
self.grid = grid
|
||||
self.algo = None
|
||||
|
||||
def set_algo(self, algo):
|
||||
self.algo = algo
|
||||
|
||||
def solve(self):
|
||||
if not self.algo:
|
||||
return None
|
||||
t0 = time.perf_counter()
|
||||
path = self.algo.search(self.grid, self.grid.start_node, self.grid.exit_node)
|
||||
t1 = time.perf_counter()
|
||||
elapsed = (t1 - t0) * 1000
|
||||
return {
|
||||
'time_ms': elapsed,
|
||||
'visited_cells': self.algo.visited_count(),
|
||||
'path_length': len(path)
|
||||
}
|
||||
|
||||
|
||||
def experiment(maze_file, algo, runs=5):
|
||||
loader = TxtLoader()
|
||||
grid = loader.load(maze_file)
|
||||
total_t = 0.0
|
||||
total_v = 0
|
||||
total_l = 0
|
||||
for _ in range(runs):
|
||||
s = Solver(grid)
|
||||
s.set_algo(algo)
|
||||
stats = s.solve()
|
||||
if stats:
|
||||
total_t += stats['time_ms']
|
||||
total_v += stats['visited_cells']
|
||||
total_l += stats['path_length']
|
||||
return {
|
||||
'time_ms': total_t / runs,
|
||||
'visited_cells': total_v / runs,
|
||||
'path_length': total_l / runs
|
||||
}
|
||||
|
||||
|
||||
def make_plots(results):
|
||||
mazes = list(set(r['maze'] for r in results))
|
||||
algos = ['BFS', 'DFS', 'AStar']
|
||||
|
||||
fig, axes = plt.subplots(1, 3, figsize=(15, 5))
|
||||
x = np.arange(len(mazes))
|
||||
width = 0.25
|
||||
|
||||
# Время
|
||||
for i, algo in enumerate(algos):
|
||||
times = []
|
||||
for m in mazes:
|
||||
val = next((r['time_ms'] for r in results if r['maze'] == m and r['strategy'] == algo), 0)
|
||||
times.append(val)
|
||||
axes[0].bar(x + i * width, times, width, label=algo)
|
||||
axes[0].set_xlabel('Maze')
|
||||
axes[0].set_ylabel('Time (ms)')
|
||||
axes[0].set_title('Execution time')
|
||||
axes[0].set_xticks(x + width)
|
||||
axes[0].set_xticklabels(mazes, rotation=45, ha='right')
|
||||
axes[0].legend()
|
||||
axes[0].grid(True, alpha=0.3)
|
||||
|
||||
# Посещённые клетки
|
||||
for i, algo in enumerate(algos):
|
||||
visited = []
|
||||
for m in mazes:
|
||||
val = next((r['visited_cells'] for r in results if r['maze'] == m and r['strategy'] == algo), 0)
|
||||
visited.append(val)
|
||||
axes[1].bar(x + i * width, visited, width, label=algo)
|
||||
axes[1].set_xlabel('Maze')
|
||||
axes[1].set_ylabel('Visited cells')
|
||||
axes[1].set_title('Visited cells comparison')
|
||||
axes[1].set_xticks(x + width)
|
||||
axes[1].set_xticklabels(mazes, rotation=45, ha='right')
|
||||
axes[1].legend()
|
||||
axes[1].grid(True, alpha=0.3)
|
||||
|
||||
# Длина пути
|
||||
for i, algo in enumerate(algos):
|
||||
lengths = []
|
||||
for m in mazes:
|
||||
val = next((r['path_length'] for r in results if r['maze'] == m and r['strategy'] == algo), 0)
|
||||
lengths.append(val)
|
||||
axes[2].bar(x + i * width, lengths, width, label=algo)
|
||||
axes[2].set_xlabel('Maze')
|
||||
axes[2].set_ylabel('Path length')
|
||||
axes[2].set_title('Path length comparison')
|
||||
axes[2].set_xticks(x + width)
|
||||
axes[2].set_xticklabels(mazes, rotation=45, ha='right')
|
||||
axes[2].legend()
|
||||
axes[2].grid(True, alpha=0.3)
|
||||
|
||||
plt.tight_layout()
|
||||
plt.savefig('performance_plot.png', dpi=150, bbox_inches='tight')
|
||||
plt.show()
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
test_mazes = [
|
||||
("maze1.txt", "Small 10x6"),
|
||||
("maze10x10.txt", "Medium 10x10"),
|
||||
("maze20x20.txt", "Large 20x20"),
|
||||
("maze_empty.txt", "Empty 15x15"),
|
||||
("maze_no_exit.txt", "No exit 10x10")
|
||||
]
|
||||
algorithms = [
|
||||
("BFS", BFSAlgo()),
|
||||
("DFS", DFSAlgo()),
|
||||
("AStar", AStarAlgo())
|
||||
]
|
||||
|
||||
results = []
|
||||
for fname, name in test_mazes:
|
||||
print(f"Benchmarking {name}...")
|
||||
for algo_name, algo in algorithms:
|
||||
try:
|
||||
stat = experiment(fname, algo, runs=3)
|
||||
results.append({
|
||||
'maze': name,
|
||||
'strategy': algo_name,
|
||||
'time_ms': stat['time_ms'],
|
||||
'visited_cells': stat['visited_cells'],
|
||||
'path_length': stat['path_length']
|
||||
})
|
||||
print(f" {algo_name}: time={stat['time_ms']:.3f}ms, visited={stat['visited_cells']:.0f}, length={stat['path_length']:.0f}")
|
||||
except Exception as e:
|
||||
print(f" {algo_name}: failed - {e}")
|
||||
results.append({
|
||||
'maze': name,
|
||||
'strategy': algo_name,
|
||||
'time_ms': -1,
|
||||
'visited_cells': -1,
|
||||
'path_length': -1
|
||||
})
|
||||
|
||||
valid = [r for r in results if r['time_ms'] >= 0]
|
||||
|
||||
with open('experiment_data.csv', 'w', newline='', encoding='utf-8') as f:
|
||||
writer = csv.DictWriter(f, fieldnames=['maze', 'strategy', 'time_ms', 'visited_cells', 'path_length'])
|
||||
writer.writeheader()
|
||||
writer.writerows(valid)
|
||||
|
||||
if valid:
|
||||
make_plots(valid)
|
||||
|
||||
print("\nData saved to experiment_data.csv")
|
||||
print("Plot saved to performance_plot.png")
|
||||
Loading…
Reference in New Issue
Block a user