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board_color.py
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board_color.py
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#!/usr/bin/python3
import copy
import heapq
import json
from timeit import default_timer as timer
import os
import psutil
## Helper Classes and variables
stats = {}
## ---> Profiling functions and decorator
def get_process_memory():
process = psutil.Process(os.getpid())
return process.memory_info().rss
def profile(store):
def prof_stor(func):
def wrapper(*args, **kwargs):
mem_before = get_process_memory()
visited = set()
itr = [0,0]
start = timer()
try:
result = func(*args, visited, itr, **kwargs)
except Exception as e:
print(e)
result = None
elapsed_time = timer() - start
mem_after = get_process_memory()
if result and store:
print('Final ', end='')
result.print_state()
stats[store]= {
'elapsed_time' : elapsed_time,
# 'memory' : mem_after - mem_before,
'iters' : itr[0],
'path_length': itr[1],
}
else:
print('No Soluton found !')
stats[store]= {
'elapsed_time' : elapsed_time,
# 'memory' : mem_after - mem_before,
'iters' : 0,
'path_length': 0,
}
return result
return wrapper
return prof_stor
## ^^ Simple decorator to make tracking execution time and other statistics easy
class Board:
def __init__(self, n: int):
self.size = n
self.state = []
def __eq__(self, other):
return self.h() == other.h()
def __lt__(self, other):
return self.h() < other.h()
def is_goal_state(self):
# determine if the board is in the goal state currently
return self.h() == 0
def h(self):
dist = 0
val = 0
for i in range(0, self.size):
for j in range(0, self.size):
dir_x = [1,0,-1,0]
dir_y = [0,1,0,-1]
for k in range(0, 4):
new_x = i+dir_x[k]
new_y = j+dir_y[k]
if new_x >=0 and new_x <self.size and new_y >=0 and new_y < self.size:
if self.state[new_x][new_y] == self.state[i][j]:
dist+=1
return dist
def input_state(self):
n = self.size
print('Enter the colour Board state as {0}x{0} matrix, elements separated by a {1}:'.format(n, '","'))
for i in range(0, n):
row = input().split(',')
self.state.append(row)
self.validate_input()
def validate_input(self):
vals = []
for i in range(0, self.size):
# print(self.state[i])
if len(self.state[i]) != self.size:
raise AssertionError('Board specified is not square')
for i in range(0, self.size):
for j in range(0, self.size):
if str(self.state[i][j]).strip() not in ['R','G','B','Y']:
raise AssertionError('Invalid Colour')
else:
self.state[i][j] = str(self.state[i][j]).strip()
def print_state(self):
n = self.size
print('Board state: ')
for i in range(0, n):
print(self.state[i])
def generate_states(self):
n = self.size
new_states = []
for i in range(0, n):
for j in range(0, n):
dir_x = [1,0,-1,0]
dir_y = [0,1,0,-1]
bad = False
for k in range(0, 4):
new_x = i+dir_x[k]
new_y = j+dir_y[k]
if new_x >=0 and new_x <self.size and new_y >=0 and new_y < self.size:
if self.state[new_x][new_y] == self.state[i][j]:
bad = True
if not bad:
continue
for k in range(0, 4):
new_x = i+dir_x[k]
new_y = j+dir_y[k]
if new_x >=0 and new_x <self.size and new_y >=0 and new_y < self.size:
if self.state[new_x][new_y] != self.state[i][j]:
nboard = Board(n)
nboard.state = copy.deepcopy(self.state)
nboard.state[new_x][new_y], nboard.state[i][j] = nboard.state[i][j], nboard.state[new_x][new_y]
new_states.append(nboard)
return new_states
########################
## Search Algorithms ##
########################
## BFS Algorithm
@profile(store='bfs')
def bfs(cur_state, visited, itr):
print('BFS Initial ', end='')
cur_state.print_state()
qu = []
qu.append((cur_state, 0))
# parent = {}
while(len(qu) != 0):
itr[0]+=1
cst, depth = qu.pop(0)
if cst.is_goal_state():
itr[1] = depth
return cst
for state in cst.generate_states():
y = repr(state.state)
if y not in visited:
visited.add(y)
# parent[y] = cst
qu.append((state, depth+1))
return None
# def print_path(parents, goal, initial):
# # print(parents)
# temp = goal
# while repr(temp.state) in parents.keys() and repr(temp.state) != repr(initial.state):
# temp.print_state()
# temp = parents[repr(temp.state)]
# temp.print_state()
## A* Algorithm
@profile(store='A*')
def a_star(cur_state, visited, itr):
print('A* Initial ', end='')
cur_state.print_state()
hp = []
heapq.heappush(hp, (0+cur_state.h(), 0, cur_state))
# parent = {}
while(len(hp) != 0):
itr[0]+=1
top_ele = heapq.heappop(hp)
cst = top_ele[2]
if cst.is_goal_state():
itr[1] = top_ele[1]
# print_path(parent, cst, cur_state)
return cst
cur_steps = top_ele[1]
for state in cst.generate_states():
y = repr(state.state)
if y not in visited:
visited.add(y)
# parent[y] = cst
cost = cur_steps+1+state.h()
heapq.heappush(hp, (cost, cur_steps+1, state))
return None
## Main Functions and Input/Output routines
board = Board(int(input('Enter Board Size: ')))
board.input_state()
# print(board.h())
# for state in board.generate_states():
# state.print_state()
bfs(board)
a_star(board)
print(json.dumps(stats, indent = 4))