使用 Numpy 对两个向量进行分组

Question

I have two vectors w = [1, 1, 2, 2, 2, 3, 3] and a = [True, False, True, True, True, True, True] and I want to group by the numbers in w to compute the conjunction of the selected in a . So for the given example the result would be r = [True & False, True & True & True, True & True] . Is there any nice way to do this computation using Numpy?

Answer 1

Since you tagged numpy, you can use list comprehension, numpy.unique and numpy.all :

import numpy as np

w = np.array([1, 1, 2, 2, 2, 3, 3])
a = np.array([True, False, True, True, True, True, True])
r = [np.all(a[w==i]) for i in np.unique(w)]

r
[False, True, True]

Alternatively if you have pandas dependency:

import pandas as pd

df = pd.DataFrame({'w':w, 'a':a})
r = df.groupby('w').agg(np.all).reset_index()

r
   w      a
0  1  False
1  2   True
2  3   True

Answer 2

This can be done with a simple list comprehension:

>>> [all(a[np.where(w == i)]) for i in np.unique(w)] 
[False, True, True]