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Multi_Hueristic_Astar.py
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Multi_Hueristic_Astar.py
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from __future__ import print_function
import heapq
import numpy as np
import math
import copy
try:
xrange # Python 2
except NameError:
xrange = range # Python 3
class PriorityQueue:
def __init__(self):
self.elements = []
self.set = set()
def minkey(self):
if not self.empty():
return self.elements[0][0]
else:
return float('inf')
def empty(self):
return len(self.elements) == 0
def put(self, item, priority):
if item not in self.set:
heapq.heappush(self.elements, (priority, item))
self.set.add(item)
else:
# update
# print("update", item)
temp = []
(pri, x) = heapq.heappop(self.elements)
while x != item:
temp.append((pri, x))
(pri, x) = heapq.heappop(self.elements)
temp.append((priority, item))
for (pro, xxx) in temp:
heapq.heappush(self.elements, (pro, xxx))
def remove_element(self, item):
if item in self.set:
self.set.remove(item)
temp = []
(pro, x) = heapq.heappop(self.elements)
while x != item:
temp.append((pro, x))
(pro, x) = heapq.heappop(self.elements)
for (prito, yyy) in temp:
heapq.heappush(self.elements, (prito, yyy))
def top_show(self):
return self.elements[0][1]
def get(self):
(priority, item) = heapq.heappop(self.elements)
self.set.remove(item)
return (priority, item)
def consistent_hueristic(P, goal):
# euclidean distance
a = np.array(P)
b = np.array(goal)
return np.linalg.norm(a - b)
def hueristic_2(P, goal):
# integer division by time variable
return consistent_hueristic(P, goal) // t
def hueristic_1(P, goal):
# manhattan distance
return abs(P[0] - goal[0]) + abs(P[1] - goal[1])
def key(start, i, goal, g_function):
ans = g_function[start] + W1 * hueristics[i](start, goal)
return ans
def do_something(back_pointer, goal, start):
grid = np.chararray((n, n))
for i in range(n):
for j in range(n):
grid[i][j] = '*'
for i in range(n):
for j in range(n):
if (j, (n-1)-i) in blocks:
grid[i][j] = "#"
grid[0][(n-1)] = "-"
x = back_pointer[goal]
while x != start:
(x_c, y_c) = x
# print(x)
grid[(n-1)-y_c][x_c] = "-"
x = back_pointer[x]
grid[(n-1)][0] = "-"
for i in xrange(n):
for j in range(n):
if (i, j) == (0, n-1):
print(grid[i][j], end=' ')
print("<-- End position", end=' ')
else:
print(grid[i][j], end=' ')
print()
print("^")
print("Start position")
print()
print("# is an obstacle")
print("- is the path taken by algorithm")
print("PATH TAKEN BY THE ALGORITHM IS:-")
x = back_pointer[goal]
while x != start:
print(x, end=' ')
x = back_pointer[x]
print(x)
quit()
def valid(p):
if p[0] < 0 or p[0] > n-1:
return False
if p[1] < 0 or p[1] > n-1:
return False
return True
def expand_state(s, j, visited, g_function, close_list_anchor, close_list_inad, open_list, back_pointer):
for itera in range(n_hueristic):
open_list[itera].remove_element(s)
# print("s", s)
# print("j", j)
(x, y) = s
left = (x-1, y)
right = (x+1, y)
up = (x, y+1)
down = (x, y-1)
for neighbours in [left, right, up, down]:
if neighbours not in blocks:
if valid(neighbours) and neighbours not in visited:
# print("neighbour", neighbours)
visited.add(neighbours)
back_pointer[neighbours] = -1
g_function[neighbours] = float('inf')
if valid(neighbours) and g_function[neighbours] > g_function[s] + 1:
g_function[neighbours] = g_function[s] + 1
back_pointer[neighbours] = s
if neighbours not in close_list_anchor:
open_list[0].put(neighbours, key(neighbours, 0, goal, g_function))
if neighbours not in close_list_inad:
for var in range(1,n_hueristic):
if key(neighbours, var, goal, g_function) <= W2 * key(neighbours, 0, goal, g_function):
# print("why not plssssssssss")
open_list[j].put(neighbours, key(neighbours, var, goal, g_function))
# print
def make_common_ground():
some_list = []
# block 1
for x in range(1, 5):
for y in range(1, 6):
some_list.append((x, y))
# line
for x in range(15, 20):
some_list.append((x, 17))
# block 2 big
for x in range(10, 19):
for y in range(1, 15):
some_list.append((x, y))
# L block
for x in range(1, 4):
for y in range(12, 19):
some_list.append((x, y))
for x in range(3, 13):
for y in range(16, 19):
some_list.append((x, y))
return some_list
hueristics = {0: consistent_hueristic, 1: hueristic_1, 2: hueristic_2}
blocks_blk = [(0, 1),(1, 1),(2, 1),(3, 1),(4, 1),(5, 1),(6, 1),(7, 1),(8, 1),(9, 1),(10, 1),(11, 1),(12, 1),(13, 1),(14, 1),(15, 1),(16, 1),(17, 1),(18, 1), (19, 1)]
blocks_no = []
blocks_all = make_common_ground()
blocks = blocks_blk
# hyper parameters
W1 = 1
W2 = 1
n = 20
n_hueristic = 3 # one consistent and two other inconsistent
# start and end destination
start = (0, 0)
goal = (n-1, n-1)
t = 1
def multi_a_star(start, goal, n_hueristic):
g_function = {start: 0, goal: float('inf')}
back_pointer = {start:-1, goal:-1}
open_list = []
visited = set()
for i in range(n_hueristic):
open_list.append(PriorityQueue())
open_list[i].put(start, key(start, i, goal, g_function))
close_list_anchor = []
close_list_inad = []
while open_list[0].minkey() < float('inf'):
for i in range(1, n_hueristic):
# print("i", i)
# print(open_list[0].minkey(), open_list[i].minkey())
if open_list[i].minkey() <= W2 * open_list[0].minkey():
global t
t += 1
# print("less prio")
if g_function[goal] <= open_list[i].minkey():
if g_function[goal] < float('inf'):
do_something(back_pointer, goal, start)
else:
_, get_s = open_list[i].top_show()
visited.add(get_s)
expand_state(get_s, i, visited, g_function, close_list_anchor, close_list_inad, open_list, back_pointer)
close_list_inad.append(get_s)
else:
# print("more prio")
if g_function[goal] <= open_list[0].minkey():
if g_function[goal] < float('inf'):
do_something(back_pointer, goal, start)
else:
# print("hoolla")
get_s = open_list[0].top_show()
visited.add(get_s)
expand_state(get_s, 0, visited, g_function, close_list_anchor, close_list_inad, open_list, back_pointer)
close_list_anchor.append(get_s)
print("No path found to goal")
print()
for i in range(n-1,-1, -1):
for j in range(n):
if (j, i) in blocks:
print('#', end=' ')
elif (j, i) in back_pointer:
if (j, i) == (n-1, n-1):
print('*', end=' ')
else:
print('-', end=' ')
else:
print('*', end=' ')
if (j, i) == (n-1, n-1):
print('<-- End position', end=' ')
print()
print("^")
print("Start position")
print()
print("# is an obstacle")
print("- is the path taken by algorithm")
multi_a_star(start, goal, n_hueristic)