Invert Binary Numpy Array

is there a kind of 'logical no' for numpy arrays (of numbers of course). For example, consider this array: x = [1,0,1,0,0,1] i am looking for an easy way to compute its 'inverse' y

Solution 1:

For an array of 1s and 0s you can simply subtract the values in x from 1:

x = np.array([1,0,1,0,0,1])
1-x
# array([0, 1, 0, 1, 1, 0])

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Or you could also take the bitwise XOR of the binary values in x with 1:

x^1 
# array([0, 1, 0, 1, 1, 0])

Solution 2:

Yes, you can use np.logical_not:

np.logical_not(x).astype(int)

Output:

array([0, 1, 0, 1, 1, 0])

Solution 3:

Or using XOR:

y =  [n ^ 1 for n in x]

Solution 4:

Here's one way:

y =  (x == 0).astype(int)

Alternatively:

y =  0 + (x == 0)

Output:

[0 1 0 1 1 0]

Notes:

1. (x == 0) gives a boolean array where False appears in the place of 1, and True appears in the place of 0.
2. Calling the method astype(int), or adding scalar 0 to the matrix, converts False to 0 and True to 1