Check if value in a list is in the corresponding row in numpy array

Question

b =np.ndarray(shape=(5,5), dtype=int, order='F')
Out[142]: 
array([[       1,    65536,        0,        0,        0],
       [       0,        0,        1,    65536,        0],
       [16777216,        0,        0,        0,        1],
       [       0,      256, 16777216,        0,        0],
       [       0,        0,        0,      256, 16777216]])

and I have a list, such as :

a = [1,23,4,5,20,0...]

I would like to check for each index if the value in a is in the corresponding row in b , as np.isin(a[0], b[0]) and to receive Boolean vector for all the rows (if a[i] is in b[i]).

The length of a is equal the length of b (amount of rows).

jpp · Accepted Answer · 2018-06-28 13:45:48Z

1

Here's one way using np.ndarray.any. Just take care to align dimensions to allow broadcasting.

np.random.seed(0)

b = np.random.randint(0, 10, (5, 5))
a = np.random.randint(0, 10, 5)

print(a, b, sep='\n'*2)

[3 0 3 5 0]

[[5 0 3 3 7]
 [9 3 5 2 4]
 [7 6 8 8 1]
 [6 7 7 8 1]
 [5 9 8 9 4]]

c = (a[:, None] == b).any(1)

print(c)

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

answered Jun 28, 2018 at 13:45

jpp

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