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astar_test.py
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astar_test.py
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import pygame
import math
from queue import PriorityQueue
WIDTH = 800
WIN = pygame.display.set_mode((WIDTH, WIDTH))
pygame.display.set_caption("path finding algoriithm")
RED = (255, 0, 0)
GREEN = (0, 255, 0)
YELLOW = (255, 255, 0)
WHITE = (255, 255, 255)
BLACK = (0, 0, 0)
PURPLE = (128, 0, 128)
ORANGE = (255, 165, 0)
GREY = (128, 128, 128)
BLUE = (0, 0, 255)
class Spot:
def __init__(self, row, col, width, total_rows):
self.row = row
self.col = col
self.x = row*width
self.y = col*width
self.color = WHITE
self.neighbors = []
self.width = width
self.total_rows = total_rows
def get_pos(self):
return self.row, self.col
def is_closed(self):
return self.color == RED
def is_open(self):
return self.color == GREEN
def is_obstacle(self):
return self.color == BLACK
def is_start(self):
return self.color == ORANGE
def is_end(self):
return self.color == BLUE
def reset(self):
self.color = WHITE
def make_start(self):
self.color = ORANGE
def make_closed(self):
self.color = RED
def make_open(self):
self.color = GREEN
def make_obstacle(self):
self.color = BLACK
def make_end(self):
self.color = BLUE
def make_path(self):
self.color= PURPLE
def draw(self, win):
pygame.draw.rect(
win, self.color, (self.x, self.y, self.width, self.width))
def update_neighbors(self,grid):
self.neighbors=[]
if self.row<self.total_rows-1 and not grid[self.row+1][self.col].is_obstacle():#bottom neighbor
self.neighbors.append(grid[self.row+1][self.col])
if self.row>0 and not grid[self.row-1][self.col].is_obstacle():#top neighbor
self.neighbors.append(grid[self.row-1][self.col])
if self.col>0 and not grid[self.row][self.col-1].is_obstacle():#left neighbor
self.neighbors.append(grid[self.row][self.col-1])
if self.col<self.total_rows-1 and not grid[self.row][self.col+1].is_obstacle():#right neighbor
self.neighbors.append(grid[self.row][self.col+1])
def __lt__(self, other):
return False
def h(p1, p2):
x1, y1 = p1
x2, y2 = p2
return abs(x1-x2)+abs(y1-y2)
def construct_shortest_path(came_from,current,draw):
while current in came_from:
current=came_from[current]
current.make_path()
draw()
################################### A S T A R Algorithm ##################################
def algorithm(draw, grid,start,end):
count=0
open_set=PriorityQueue()
open_set.put((0,count,start)) # Begin by putting the start node in the open_set
came_from={} # Keeps track of all paths(including the optimal one)
g_score={}
f_score={}
for row in grid: #Making g_score of ALL the nodes infinity
for spot in row:
g_score.update({spot:float("inf")})
g_score[start]=0 #But g_score of the end node is "0"
for row in grid: # Making f_score of ALL the nodes infinity
for spot in row:
f_score.update({spot:float("inf")})
f_score[start]=h(start.get_pos(),end.get_pos()) #But f_score of the end node is "heuristic distance" only
open_set_hash={start} # keeping track of that priorityqueue
while not open_set.empty():
for event in pygame.event.get():
if event.type==pygame.QUIT:
pygame.quit()
current=open_set.get()[2] # Getting the current working node from the open_set to compare with neighbors
open_set_hash.remove(current) # Removing the current working node from the open_set_hash
if current == end: # We have reached to the "goal position"
construct_shortest_path(came_from,end,draw)
end.make_end()
start.make_start()
return True
for neighbor in current.neighbors: # working with ALL the neighbors to get the next optimal node
temp_g_score=g_score[current]+1 # if we go to the next immediate neighbor the g_score increases by 1
if temp_g_score<g_score[neighbor]: #if new temp_g_score is lesser than the previous g_score then update the g_score with the lesser one
came_from[neighbor]=current # Saving the optimal node from where we came at the first place
g_score[neighbor]=temp_g_score # updating the g_score with the lesser one
f_score[neighbor]=temp_g_score+h(neighbor.get_pos(),end.get_pos())
if neighbor not in open_set_hash: # Updating open_set with the optimal neighbor which was not optimal before
count +=1
open_set.put((f_score[neighbor],count,neighbor))
open_set_hash.add(neighbor) # Updating open_set_hash with the optimal neighbor
neighbor.make_open() #if node was NOT optimal before but was neighbor of other optimal node
draw()
if current != start:
pass
current.make_closed() #if node was optimal before
return False
def make_grid(rows, width):
grid = []
spot_width = width // rows
for i in range(rows):
grid.append([]) # making all the rows
for j in range(rows):
spot = Spot(i, j, spot_width, rows)
grid[i].append(spot) # making all the collumns
return grid
def draw_gridline(win, rows, width):
gap = width // rows
for i in range(rows):
pygame.draw.line(win, GREY, (0, i*gap), (width, i*gap))
for j in range(rows):
pygame.draw.line(win, GREY, (j*gap, 0), (j*gap, width))
def draw(win, grid, rows, width):
win.fill(WHITE)
for row in grid:
for spot in row:
spot.draw(win)
draw_gridline(win, rows, width)
pygame.display.update()
def get_clicked_pos(pos, rows, width):
gap = width//rows
x, y = pos
row = x//gap
col = y//gap
return row, col
def main(win, width):
ROWS=10
grid=make_grid(ROWS,width)
start=None
end=None
run=True
started=False
while run:
draw(win,grid,ROWS,width)
for event in pygame.event.get():
if event.type==pygame.QUIT:
run=False
if started:
continue
if pygame.mouse.get_pressed()[0]:
pos=pygame.mouse.get_pos()
row,col=get_clicked_pos(pos,ROWS,width)
spot=grid[row][col]
if not start and spot !=end:
start=spot
start.make_start()
elif not end and spot !=start:
end=spot
end.make_end()
elif spot != end and spot != start:
spot.make_obstacle()
elif pygame.mouse.get_pressed()[1]:
pass
elif pygame.mouse.get_pressed()[2]:
pos=pygame.mouse.get_pos()
row,col=get_clicked_pos(pos,ROWS,width)
spot=grid[row][col]
spot.reset()
if spot == start:
start = None
elif spot ==end:
end = None
if event.type==pygame.KEYDOWN:
if event.key == pygame.K_SPACE and start and end:
for row in grid:
for spot in row:
spot.update_neighbors(grid)
algorithm(lambda:draw(win,grid,ROWS,width),grid,start,end)
if event.key==pygame.K_c :
start=None
end=None
grid=make_grid(ROWS,width)
pygame.quit()
main(WIN,WIDTH)