Python 为多维数据生成具有窗口大小和步长的子序列

我有一个可变长度的n维序列列表，但是固定的n。
例如n=3
1。[ [1, 2, 3], [4, 5, 6], [4, 4, 4] ]
2。[ [4, 6, 7], [6, 4, 3] ]
3。[7,9,1]，[6,2,0]，[0,7,3]，[3,3,8]]

我想创建窗口大小为w的所有子序列的列表。例如，对于w=2，
列表1:[[1,2,3]，[4,5,6]]
列表2:[[4,5,6]，[4,4,4]]
列表3:[[4,6,7]，[6,4,3]]
列表4:[[7,9,1]、[6,2,0]等等

我想用Python快速实现这一点。我尝试在这里实现解决方案：，但我不确定如何计算n维数据点的步长，我得到了奇怪的结果

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对于可变的窗口大小，获得这些子序列的最佳方法是什么？

这不一定是一个快速实现，但这是我认为您想要的临时实现，以您的问题为例：

a= [ [1, 2, 3], [4, 5, 6], [4, 4, 4] ]
b= [ [4, 6, 7], [6, 4, 3] ]
c= [ [7, 9, 1], [6, 2, 0], [0, 7, 3], [3, 3, 8] ]

#put all lists into a list to loop through
uberset=[a,b,c]

#specific window size to work with
window=2

#rolling window function to loop through a given list of lists and window size
def rolling_window(ListOfLists, I_Window):
    ans=[]
    #for each List
    for i in ListOfLists:
      #slide your window across the list, stacking each window into the answer
      for j in range(0,len(i)-I_Window+1,1):
        ans.append(i[j:j+I_Window])
    return ans

print(rolling_window(uberset, window))

（为后续问题编辑：现在大步添加！）：

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谢谢是否有任何方法也可以将stride合并到此代码中？例如，如果列表c中有100个列表，我希望窗口大小为10，步幅为3，如何实现这一点？

a= [ [1, 2, 3], [4, 5, 6], [4, 4, 4] ]
b= [ [4, 6, 7], [6, 4, 3] ]
c= [ [7, 9, 1], [6, 2, 0], [0, 7, 3], [3, 3, 8] ]

#put all lists into a list to loop through
uberset=[a,b,c]

#specific window size to work with and stride to work with
window=2
stride=1

#rolling window function to loop through a given list of lists, window size, stride
def rolling_window(ListOfLists, I_Window,I_Stride):
    ans=[]
    #for each List
    for i in ListOfLists:
      #slide your window across the list, stacking each window into the answer
      for j in range(0,len(i)-I_Window+1,I_Stride):
        ans.append(i[j:j+I_Window])
    return ans

print(rolling_window(uberset, window, stride))

##and if you wanted to work with say a window size of 1 and a stride of 2:
print(rolling_window(uberset, 1, 2))