Manhattan Distance in Python
def manhattan_distance(point1, point2):
return sum(abs(a - b) for a, b in zip(point1, point2))
point1 = (1, 2)
point2 = (4, 6)
distance = manhattan_distance(point1, point2)
print(f"Manhattan distance: {distance}")
Manhattan distance: 7
Manhattan Distance Using NumPy
import numpy as np
def manhattan_distance_np(point1, point2):
return np.sum(np.abs(np.array(point1) - np.array(point2)))
# Example usage
point1 = (1, 2)
point2 = (4, 6)
distance = manhattan_distance_np(point1, point2)
print(f"Manhattan distance (NumPy): {distance}")
Manhattan distance (NumPy): 7
Manhattan Distance Using a Custom Loop
def manhattan_distance_loop(point1, point2):
distance = 0
for a, b in zip(point1, point2):
distance += abs(a - b)
return distance
# Example usage
point1 = (1, 2)
point2 = (4, 6)
distance = manhattan_distance_loop(point1, point2)
print(f"Manhattan distance (Loop): {distance}")
Manhattan distance (Loop): 7
Manhattan Distance Using Map and Lambda
def manhattan_distance_map(point1, point2):
return sum(map(lambda a, b: abs(a - b), point1, point2))
# Example usage
point1 = (1, 2)
point2 = (4, 6)
distance = manhattan_distance_map(point1, point2)
print(f"Manhattan distance (Map and Lambda): {distance}")
Manhattan distance (Map and Lambda): 7
Manhattan Distance Using a One-Liner Function
manhattan_distance_oneliner = lambda p1, p2: sum(abs(a - b) for a, b in zip(p1, p2))
# Example usage
point1 = (1, 2)
point2 = (4, 6)
distance = manhattan_distance_oneliner(point1, point2)
print(f"Manhattan distance (One-Liner): {distance}")
Manhattan distance (One-Liner): 7
Manhattan Distance Using List Comprehension
def manhattan_distance_listcomp(point1, point2):
return sum([abs(a - b) for a, b in zip(point1, point2)])
# Example usage
point1 = (1, 2)
point2 = (4, 6)
distance = manhattan_distance_listcomp(point1, point2)
print(f"Manhattan distance (List Comprehension): {distance}")
Manhattan distance (List Comprehension): 7
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