Python 将一系列间隔与自身进行比较

为了一系列

我想检查每一个间隔对，比如一个，是否重叠。因为这提供了方法

结果应该是一系列长度

l

的矩阵/数据帧，包含对是否重叠。例如：

+--------------------------+--------------------------+--------------------------+--------------------------+ | | [2020-01-01, 2020-01-05] | [2020-01-01, 2020-01-02] | [2020-01-04, 2020-01-05] | +--------------------------+--------------------------+--------------------------+--------------------------+ | [2020-01-01, 2020-01-05] | True | True | True | +--------------------------+--------------------------+--------------------------+--------------------------+ | [2020-01-01, 2020-01-02] | True | True | False | +--------------------------+--------------------------+--------------------------+--------------------------+ | [2020-01-04, 2020-01-05] | True | False | False | +--------------------------+--------------------------+--------------------------+--------------------------+ +--------------------------+--------------------------+--------------------------+--------------------------+ | | [2020-01-01, 2020-01-05] | [2020-01-01, 2020-01-02] | [2020-01-04, 2020-01-05] | +--------------------------+--------------------------+--------------------------+--------------------------+ |[2020-01-012020-01-05]|对|对|对| +--------------------------+--------------------------+--------------------------+--------------------------+ |[2020-01-012020-01-02]|真|真|假| +--------------------------+--------------------------+--------------------------+--------------------------+ |[2020-01-042020-01-05]|真|假|假| +--------------------------+--------------------------+--------------------------+--------------------------+ 因为这个系列相当大，我正在寻找一种比它更高效的方法

您可以使用，以便能够轻松获得

右侧

和

左侧

边界，并使用numpy和

更大的

和

您似乎还可以在IntervalIndex上使用，并执行以下操作：

np.stack([idx.overlaps(interval) for interval in idx])
#or for dataframe
pd.DataFrame([idx.overlaps(interval) for interval in idx], 
             index=s.values, columns=s.values)

import numpy as np

#work with IntervalIndex
idx = pd.IntervalIndex(s)
#get right and left bounds
right = idx.right
left = idx.left

#create the boolean of True and False
arr = np.greater_equal.outer(right, left) & np.less_equal.outer(left, right)

#create the dataframe if needed
print (pd.DataFrame(arr, index=s.values, columns=s.values))
                          [2020-01-01, 2020-01-05]  [2020-01-01, 2020-01-02]  \
[2020-01-01, 2020-01-05]                      True                      True   
[2020-01-01, 2020-01-02]                      True                      True   
[2020-01-04, 2020-01-05]                      True                     False   

                          [2020-01-04, 2020-01-05]  
[2020-01-01, 2020-01-05]                      True  
[2020-01-01, 2020-01-02]                     False  
[2020-01-04, 2020-01-05]                      True  

np.stack([idx.overlaps(interval) for interval in idx])
#or for dataframe
pd.DataFrame([idx.overlaps(interval) for interval in idx], 
             index=s.values, columns=s.values)