mirror of
https://github.com/TheAlgorithms/Python.git
synced 2024-11-27 15:01:08 +00:00
267 lines
6.5 KiB
Python
267 lines
6.5 KiB
Python
from __future__ import print_function
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import heapq
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import numpy as np
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try:
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xrange # Python 2
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except NameError:
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xrange = range # Python 3
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class PriorityQueue:
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def __init__(self):
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self.elements = []
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self.set = set()
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def minkey(self):
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if not self.empty():
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return self.elements[0][0]
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else:
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return float('inf')
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def empty(self):
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return len(self.elements) == 0
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def put(self, item, priority):
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if item not in self.set:
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heapq.heappush(self.elements, (priority, item))
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self.set.add(item)
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else:
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# update
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# print("update", item)
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temp = []
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(pri, x) = heapq.heappop(self.elements)
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while x != item:
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temp.append((pri, x))
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(pri, x) = heapq.heappop(self.elements)
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temp.append((priority, item))
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for (pro, xxx) in temp:
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heapq.heappush(self.elements, (pro, xxx))
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def remove_element(self, item):
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if item in self.set:
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self.set.remove(item)
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temp = []
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(pro, x) = heapq.heappop(self.elements)
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while x != item:
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temp.append((pro, x))
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(pro, x) = heapq.heappop(self.elements)
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for (prito, yyy) in temp:
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heapq.heappush(self.elements, (prito, yyy))
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def top_show(self):
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return self.elements[0][1]
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def get(self):
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(priority, item) = heapq.heappop(self.elements)
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self.set.remove(item)
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return (priority, item)
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def consistent_hueristic(P, goal):
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# euclidean distance
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a = np.array(P)
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b = np.array(goal)
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return np.linalg.norm(a - b)
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def hueristic_2(P, goal):
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# integer division by time variable
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return consistent_hueristic(P, goal) // t
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def hueristic_1(P, goal):
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# manhattan distance
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return abs(P[0] - goal[0]) + abs(P[1] - goal[1])
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def key(start, i, goal, g_function):
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ans = g_function[start] + W1 * hueristics[i](start, goal)
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return ans
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def do_something(back_pointer, goal, start):
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grid = np.chararray((n, n))
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for i in range(n):
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for j in range(n):
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grid[i][j] = '*'
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for i in range(n):
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for j in range(n):
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if (j, (n-1)-i) in blocks:
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grid[i][j] = "#"
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grid[0][(n-1)] = "-"
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x = back_pointer[goal]
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while x != start:
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(x_c, y_c) = x
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# print(x)
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grid[(n-1)-y_c][x_c] = "-"
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x = back_pointer[x]
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grid[(n-1)][0] = "-"
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for i in xrange(n):
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for j in range(n):
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if (i, j) == (0, n-1):
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print(grid[i][j], end=' ')
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print("<-- End position", end=' ')
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else:
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print(grid[i][j], end=' ')
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print()
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print("^")
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print("Start position")
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print()
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print("# is an obstacle")
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print("- is the path taken by algorithm")
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print("PATH TAKEN BY THE ALGORITHM IS:-")
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x = back_pointer[goal]
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while x != start:
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print(x, end=' ')
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x = back_pointer[x]
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print(x)
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quit()
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def valid(p):
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if p[0] < 0 or p[0] > n-1:
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return False
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if p[1] < 0 or p[1] > n-1:
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return False
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return True
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def expand_state(s, j, visited, g_function, close_list_anchor, close_list_inad, open_list, back_pointer):
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for itera in range(n_hueristic):
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open_list[itera].remove_element(s)
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# print("s", s)
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# print("j", j)
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(x, y) = s
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left = (x-1, y)
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right = (x+1, y)
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up = (x, y+1)
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down = (x, y-1)
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for neighbours in [left, right, up, down]:
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if neighbours not in blocks:
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if valid(neighbours) and neighbours not in visited:
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# print("neighbour", neighbours)
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visited.add(neighbours)
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back_pointer[neighbours] = -1
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g_function[neighbours] = float('inf')
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if valid(neighbours) and g_function[neighbours] > g_function[s] + 1:
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g_function[neighbours] = g_function[s] + 1
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back_pointer[neighbours] = s
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if neighbours not in close_list_anchor:
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open_list[0].put(neighbours, key(neighbours, 0, goal, g_function))
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if neighbours not in close_list_inad:
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for var in range(1,n_hueristic):
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if key(neighbours, var, goal, g_function) <= W2 * key(neighbours, 0, goal, g_function):
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# print("why not plssssssssss")
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open_list[j].put(neighbours, key(neighbours, var, goal, g_function))
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# print
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def make_common_ground():
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some_list = []
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# block 1
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for x in range(1, 5):
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for y in range(1, 6):
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some_list.append((x, y))
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# line
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for x in range(15, 20):
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some_list.append((x, 17))
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# block 2 big
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for x in range(10, 19):
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for y in range(1, 15):
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some_list.append((x, y))
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# L block
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for x in range(1, 4):
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for y in range(12, 19):
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some_list.append((x, y))
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for x in range(3, 13):
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for y in range(16, 19):
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some_list.append((x, y))
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return some_list
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hueristics = {0: consistent_hueristic, 1: hueristic_1, 2: hueristic_2}
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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)]
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blocks_no = []
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blocks_all = make_common_ground()
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blocks = blocks_blk
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# hyper parameters
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W1 = 1
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W2 = 1
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n = 20
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n_hueristic = 3 # one consistent and two other inconsistent
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# start and end destination
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start = (0, 0)
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goal = (n-1, n-1)
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t = 1
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def multi_a_star(start, goal, n_hueristic):
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g_function = {start: 0, goal: float('inf')}
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back_pointer = {start:-1, goal:-1}
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open_list = []
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visited = set()
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for i in range(n_hueristic):
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open_list.append(PriorityQueue())
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open_list[i].put(start, key(start, i, goal, g_function))
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close_list_anchor = []
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close_list_inad = []
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while open_list[0].minkey() < float('inf'):
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for i in range(1, n_hueristic):
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# print("i", i)
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# print(open_list[0].minkey(), open_list[i].minkey())
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if open_list[i].minkey() <= W2 * open_list[0].minkey():
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global t
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t += 1
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# print("less prio")
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if g_function[goal] <= open_list[i].minkey():
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if g_function[goal] < float('inf'):
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do_something(back_pointer, goal, start)
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else:
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_, get_s = open_list[i].top_show()
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visited.add(get_s)
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expand_state(get_s, i, visited, g_function, close_list_anchor, close_list_inad, open_list, back_pointer)
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close_list_inad.append(get_s)
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else:
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# print("more prio")
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if g_function[goal] <= open_list[0].minkey():
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if g_function[goal] < float('inf'):
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do_something(back_pointer, goal, start)
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else:
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# print("hoolla")
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get_s = open_list[0].top_show()
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visited.add(get_s)
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expand_state(get_s, 0, visited, g_function, close_list_anchor, close_list_inad, open_list, back_pointer)
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close_list_anchor.append(get_s)
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print("No path found to goal")
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print()
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for i in range(n-1,-1, -1):
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for j in range(n):
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if (j, i) in blocks:
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print('#', end=' ')
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elif (j, i) in back_pointer:
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if (j, i) == (n-1, n-1):
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print('*', end=' ')
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else:
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print('-', end=' ')
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else:
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print('*', end=' ')
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if (j, i) == (n-1, n-1):
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print('<-- End position', end=' ')
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print()
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print("^")
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print("Start position")
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print()
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print("# is an obstacle")
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print("- is the path taken by algorithm")
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multi_a_star(start, goal, n_hueristic)
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