Flipping zeroes and ones in one-dimensional NumPy array

Question

I have a one-dimensional NumPy array that consists of zeroes and ones like so:

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

I\'d li

Answer 1

answer = numpy.ones_like(a) - a

Answer 2

I also found a way to do it:

In [1]: from numpy import array

In [2]: a = array([1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])

In [3]: b = (~a.astype(bool)).astype(int)


In [4]: print(a); print(b)
[1 1 1 1 1 0 0 0 0 0 0 0 0 0 0]
[0 0 0 0 0 1 1 1 1 1 1 1 1 1 1]

Still, I think that @gboffi's answer is the best. I'd have upvoted it but I don't have enough reputation yet :(

Answer 3

A sign that you should probably be using a boolean datatype

a = np.array([0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], dtype=np.bool)
# or
b = ~a
b = np.logical_not(a)

Answer 4

There must be something in your Q that i do not understand...

Anyway

In [2]: from numpy import array

In [3]: a = array((1,0,0,1,1,0,0))

In [4]: b = 1-a

In [5]: print a ; print b
[1 0 0 1 1 0 0]
[0 1 1 0 0 1 1]

In [6]: 

Answer 5

another superfluous option:

numpy.logical_not(a).astype(int)

Answer 6

Mathematically, the first thing that comes to mind is (value + 1) % 2.

>>> (a+1)%2
array([1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], dtype=int32)