Python – 3D 矩阵到坐标列表

给定一个矩阵，行的每个元素都是列表，将每列配对以形成坐标。

Input : test_list = [[[9, 2], [10, 3]], [[13, 6], [19, 7]]]
Output : [(9, 10), (2, 3), (13, 19), (6, 7)]
Explanation : Column Mapped Pairs.

Input : test_list = [[[13, 6], [19, 7]]]
Output : [(13, 19), (6, 7)]
Explanation : Column Mapped Pairs.

方法 #1：使用循环 + zip()

在此，我们迭代内部元组列表中的所有配对元素，该列表使用 zip() 配对，并附加结果列表。

Python3

# Python3 code to demonstrate working of 
# 3D Matrix to Coordinate List
# Using loop + zip()
  
# initializing list
test_list = [[[5, 6, 7], [2, 4, 6]], [[9, 2], [10, 3]], [[13, 6], [19, 7]]]
  
# printing original list
print("The original list is : " + str(test_list))
  
res = []
for sub1, sub2 in test_list:
      
    # zip() used to form pairing
    for ele in zip(sub1, sub2):
        res.append(ele)
  
# printing result 
print("Constructed Pairs : " + str(res))

输出

The original list is : [[[5, 6, 7], [2, 4, 6]], [[9, 2], [10, 3]], [[13, 6], [19, 7]]]
Constructed Pairs : [(5, 2), (6, 4), (7, 6), (9, 10), (2, 3), (13, 19), (6, 7)]

方法#2：使用列表推导

在此，我们使用列表推导以速记方式执行上述方法的任务。

Python3

# Python3 code to demonstrate working of 
# 3D Matrix to Coordinate List
# Using loop + zip()
  
# initializing list
test_list = [[[5, 6, 7], [2, 4, 6]], [[9, 2], [10, 3]], [[13, 6], [19, 7]]]
  
# printing original list
print("The original list is : " + str(test_list))
  
# list comprehension to perform task in shorthand
res = [ele for sub1, sub2 in test_list for ele in zip(sub1, sub2)]
  
# printing result 
print("Constructed Pairs : " + str(res))

输出

The original list is : [[[5, 6, 7], [2, 4, 6]], [[9, 2], [10, 3]], [[13, 6], [19, 7]]]
Constructed Pairs : [(5, 2), (6, 4), (7, 6), (9, 10), (2, 3), (13, 19), (6, 7)]