I have three lists as such:
a = np.array([True, True, False, False])
b = np.array([False, False, False, False])
c = np.array([False, False, False, True])
I want to add the arrays so that the new array only has False if all the corresponding elements are False. For example, the output should be:
d = np.array([True, True, False, True])
However, d = np.add(a,b,c) returns:
d = np.array([True, True, False, False])
Why is this and how can I fix it? Thanks!
np.add's third parameter is an optional array to put the output into. The function can only add two arrays.
Just use the normal operators (and perhaps switch to bitwise logic operators, since you're trying to do boolean logic rather than addition):
d = a | b | c
If you want a variable number of inputs, you can use the any function:
d = np.any(inputs, axis=0)
I am personally using the np.logical_and function.
For the problem proposed:
In [3]: a = np.array([True, True, False, False])
...: b = np.array([False, False, False, False])
...: c = np.array([False, False, False, True])
In [4]: np.logical_and(a,b,c)
Out[4]: array([False, False, False, False], dtype=bool)
There is also the straightforward solution
a + b + c
resulting in
array([ True, True, False, True], dtype=bool)
>>> a=[True, True, False, False]
>>> b=[False, False, False, False]
>>> c=[False, False, False, True]
>>> map(sum, zip(a,b,c))
[1, 1, 0, 1]
>>>
map(bool,map(sum, zip(*X))) where X = [a,b,c,...]. Thanks!np.any is a better choice.