如何在numpy数组和向量行之间执行包含操作？

Question

Now I have a numpy array,

[[1 2]
 [3 4]
 [2 5]]

and a vector.

[2,
 5,
 2]

I want to perform a contain operation between the array and the vector row wise. In other words, I want to check whether the first row [1, 2] contain 2 , whether the second row [3, 4] contain 5 . The expected output would look like:

[True, False, True] 

How could I implement this function? Many thanks in advance.

Answer 1

You can broadcast the vector into a column, equate it to all the elements in the rows of the matrix, and see if any element is True in each row:

import numpy as np

a = np.array(
    [[1, 2],
     [3, 4],
     [2, 5]])
v = np.array([2, 5, 2]).reshape(-1, 1)

np.any(a == v, axis=1)

https://ideone.com/YmWtlv

reshape turns your 1D (row) vector into a column vector. This is necessary because normally broadcasting lines up the shapes along the right, so you need an explicit trailing dimension of 1. Another way to accomplish the same thing is to use newaxis (aka None ):

v = np.array([2, 5, 2])[..., np.newaxis]

Note

My original answer suggested reduce using logical_or , which is just a more complicated way of saying any :

np.logical_or.reduce(a == v, axis=1)

Answer 2

using a list comprehension and zip

arr = np.array([[1, 2],[3, 4],[2, 5]])
a = np.array([2,5,2])

[y in x for x, y in zip(arr, a)]
# outputs: [True, False, True]

Using np.any with axis=1 :

np.any(arr == a[:, None], axis=1)
# outputs: array([ True, False,  True])

Answer 3

This one-liner should do it. It works for any number of columns, too.

# Set up
import numpy as np
array = np.array([[1, 2],[3, 4],[2, 5]])
vector = np.array([2,5,2])

# Solution
result = np.logical_or.reduce(array == vector[:,None], 1)

Output:

[ True, False,  True]

This compares all of the elements against the column vector vector and then reduces over rows.

Answer 4

We can also make use of broadcasting and the dot product.

a = np.array([[1, 2], [3, 4], [2, 5]])
b = np.array([2, 5, 2]) 

Solution

(a == b[:,None]) @ np.array([1, 1]).astype(bool) 

Answer 5

You can compare the first column and second column of the 2D array with the vector and perform a logical or operation on the results obtained.

import numpy as np
a = np.array([[1, 2],[3, 4],[2, 5]])
b = [2,5,2]
np.logical_or(a[:,0] == b , a[:,1] == b)

Output:

array([ True, False,  True], dtype=bool)