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 = [0,1,0,1,1,0]
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4 Answers
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])
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])
1 Comment
Franva
why 1-x? won't some 0 become -1?? is it because of the binary type? e.g. uint8?
Yes, you can use np.logical_not:
np.logical_not(x).astype(int)
Output:
array([0, 1, 0, 1, 1, 0])
Comments
Or using XOR:
y = [n ^ 1 for n in x]
Comments
Here's one way:
y = (x == 0).astype(int)
Alternatively:
y = 0 + (x == 0)
Output:
[0 1 0 1 1 0]
Notes:
(x == 0)gives a boolean array whereFalseappears in the place of1, andTrueappears in the place of0.- Calling the method
astype(int), or adding scalar0to the matrix, convertsFalseto0andTrueto1
