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A* Searching Algorithm Added #11737
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# Python program for A* Search Algorithm | ||
import math | ||
import heapq | ||
from typing import List, Tuple | ||
Check failure on line 4 in searches/A_star_search.py
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# Define the Cell class | ||
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class Cell: | ||
def __init__(self)->None: | ||
# Parent cell's row index | ||
self.parent_i = 0 | ||
# Parent cell's column index | ||
self.parent_j = 0 | ||
# Total cost of the cell (g + h) | ||
self.f = float("inf") | ||
# Cost from start to this cell | ||
self.g = float("inf") | ||
# Heuristic cost from this cell to destination | ||
self.h = 0 | ||
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# Define the size of the grid | ||
ROW = 9 | ||
COL = 10 | ||
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# Check if a cell is valid (within the grid) | ||
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def is_valid(row: int, col: int) -> bool: | ||
return (row >= 0) and (row < ROW) and (col >= 0) and (col < COL) | ||
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# Check if a cell is unblocked | ||
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def is_unblocked(grid: List[List[int]], row: int, col: int) -> bool: | ||
Check failure on line 37 in searches/A_star_search.py
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return grid[row][col] == 1 | ||
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# Check if a cell is the destination | ||
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def is_destination(row: int, col: int, dest: Tuple[int, int]) -> bool: | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. As there is no test file in this pull request nor any test function or class in the file |
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return row == dest[0] and col == dest[1] | ||
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# Calculate the heuristic value of a cell (Euclidean distance to destination) | ||
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def calculate_h_value(row: int, col: int, dest: Tuple[int, int]) -> float: | ||
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return ((row - dest[0]) ** 2 + (col - dest[1]) ** 2) ** 0.5 | ||
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# Trace the path from source to destination | ||
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def trace_path(cell_details: List[List[Cell]], dest: Tuple[int, int]) -> None: | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. As there is no test file in this pull request nor any test function or class in the file |
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print("The Path is ") | ||
path = [] | ||
row = dest[0] | ||
col = dest[1] | ||
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# Trace the path from destination to source using parent cells | ||
while not ( | ||
cell_details[row][col].parent_i == row | ||
and cell_details[row][col].parent_j == col | ||
): | ||
path.append((row, col)) | ||
temp_row = cell_details[row][col].parent_i | ||
temp_col = cell_details[row][col].parent_j | ||
row = temp_row | ||
col = temp_col | ||
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# Add the source cell to the path | ||
path.append((row, col)) | ||
# Reverse the path to get the path from source to destination | ||
path.reverse() | ||
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# Print the path | ||
for i in path: | ||
print("->", i, end=" ") | ||
print() | ||
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# Implement the A* search algorithm | ||
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def a_star_search(grid: List[List[int]], src: Tuple[int, int], dest: Tuple[int, int]) -> None: | ||
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# Check if the source and destination are valid | ||
if not is_valid(src[0], src[1]) or not is_valid(dest[0], dest[1]): | ||
print("Source or destination is invalid") | ||
return | ||
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# Check if the source and destination are unblocked | ||
if not is_unblocked(grid, src[0], src[1]) or not is_unblocked( | ||
grid, dest[0], dest[1] | ||
): | ||
print("Source or the destination is blocked") | ||
return | ||
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# Check if we are already at the destination | ||
if is_destination(src[0], src[1], dest): | ||
print("We are already at the destination") | ||
return | ||
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# Initialize the closed list (visited cells) | ||
closed_list = [[False for _ in range(COL)] for _ in range(ROW)] | ||
# Initialize the details of each cell | ||
cell_details = [[Cell() for _ in range(COL)] for _ in range(ROW)] | ||
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# Initialize the start cell details | ||
i = src[0] | ||
j = src[1] | ||
cell_details[i][j].f = 0 | ||
cell_details[i][j].g = 0 | ||
cell_details[i][j].h = 0 | ||
cell_details[i][j].parent_i = i | ||
cell_details[i][j].parent_j = j | ||
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# Initialize the open list (cells to be visited) with the start cell | ||
open_list = [] | ||
heapq.heappush(open_list, (0.0, i, j)) | ||
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# Initialize the flag for whether destination is found | ||
found_dest = False | ||
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# Main loop of A* search algorithm | ||
while len(open_list) > 0: | ||
# Pop the cell with the smallest f value from the open list | ||
p = heapq.heappop(open_list) | ||
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# Mark the cell as visited | ||
i = p[1] | ||
j = p[2] | ||
closed_list[i][j] = True | ||
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# For each direction, check the successors | ||
directions = [ | ||
(0, 1), | ||
(0, -1), | ||
(1, 0), | ||
(-1, 0), | ||
(1, 1), | ||
(1, -1), | ||
(-1, 1), | ||
(-1, -1), | ||
] | ||
for dir in directions: | ||
new_i = i + dir[0] | ||
new_j = j + dir[1] | ||
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# If the successor is valid, unblocked, and not visited | ||
if ( | ||
is_valid(new_i, new_j) | ||
and is_unblocked(grid, new_i, new_j) | ||
and not closed_list[new_i][new_j] | ||
): | ||
# If the successor is the destination | ||
if is_destination(new_i, new_j, dest): | ||
# Set the parent of the destination cell | ||
cell_details[new_i][new_j].parent_i = i | ||
cell_details[new_i][new_j].parent_j = j | ||
print("The destination cell is found") | ||
# Trace and print the path from source to destination | ||
trace_path(cell_details, dest) | ||
found_dest = True | ||
return | ||
else: | ||
# Calculate the new f, g, and h values | ||
g_new = cell_details[i][j].g + 1.0 | ||
h_new = calculate_h_value(new_i, new_j, dest) | ||
f_new = g_new + h_new | ||
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# If the cell is not in the open list or the new f value is smaller | ||
if ( | ||
cell_details[new_i][new_j].f == float("inf") | ||
or cell_details[new_i][new_j].f > f_new | ||
): | ||
# Add the cell to the open list | ||
heapq.heappush(open_list, (f_new, new_i, new_j)) | ||
# Update the cell details | ||
cell_details[new_i][new_j].f = f_new | ||
cell_details[new_i][new_j].g = g_new | ||
cell_details[new_i][new_j].h = h_new | ||
cell_details[new_i][new_j].parent_i = i | ||
cell_details[new_i][new_j].parent_j = j | ||
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# If the destination is not found after visiting all cells | ||
if not found_dest: | ||
print("Failed to find the destination cell") | ||
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# Driver Code | ||
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def main() -> None: | ||
""" | ||
Run the A* search algorithm on a predefined grid. | ||
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Returns: | ||
None | ||
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Examples: | ||
>>> main() | ||
The destination cell is found | ||
The Path is | ||
-> (8, 0) -> (7, 1) -> (6, 0) -> (5, 1) -> (4, 0) -> (3, 1) -> (2, 0) -> (1, 1) -> (0, 0) | ||
""" | ||
# Define the grid (1 for unblocked, 0 for blocked) | ||
grid = [ | ||
[1, 0, 1, 1, 1, 1, 0, 1, 1, 1], | ||
[1, 1, 1, 0, 1, 1, 1, 0, 1, 1], | ||
[1, 1, 1, 0, 1, 1, 0, 1, 0, 1], | ||
[0, 0, 1, 0, 1, 0, 0, 0, 0, 1], | ||
[1, 1, 1, 0, 1, 1, 1, 0, 1, 0], | ||
[1, 0, 1, 1, 1, 1, 0, 1, 0, 0], | ||
[1, 0, 0, 0, 0, 1, 0, 0, 0, 1], | ||
[1, 0, 1, 1, 1, 1, 0, 1, 1, 1], | ||
[1, 1, 1, 0, 0, 0, 1, 0, 0, 1], | ||
] | ||
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# Define the source and destination | ||
src = (8, 0) | ||
dest = (0, 0) | ||
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# Run the A* search algorithm | ||
a_star_search(grid, src, dest) | ||
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if __name__ == "__main__": | ||
main() | ||
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As there is no test file in this pull request nor any test function or class in the file
searches/A_star_search.py
, please provide doctest for the functionis_valid