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Logical operations on boolean arrays

np.logical_and, np.logical_or:

Sometimes we want to combine boolean values using logical operators like AND, OR, NOT. This is straightforward for Python booleans:

>>> # Logical AND - True only if both are True
>>> True and True
True
>>> True and False
False

>>> # Logical OR - True if either or both are True
>>> True or True
True
>>> True or False
True
>>> False or False
False

>>> # Logical NOT - inverts truth value
>>> not True
False
>>> not False
True

We have to do a little more work for arrays of booleans, because the Python and, or, not operators only return a single boolean values, and so do not operate as we expect on arrays:

>>> import numpy as np

>>> bool1 = np.array([True, True, False, False])
>>> bool2 = np.array([False, True, False, True])

>>> bool1 and bool2
Traceback (most recent call last):
   ...
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

>>> bool1 or bool2
Traceback (most recent call last):
   ...
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

To do elementwise AND, OR, NOT, we can use np.logical_and, np.logical_or, np.logical_not:

>>> # "logical_and" True where both of bool1 and bool2 are True
>>> np.logical_and(bool1, bool2)
array([False,  True, False, False], dtype=bool)

>>> # "logical_or" True where either of bool1 and bool2 are True
>>> np.logical_or(bool1, bool2)
array([ True,  True, False,  True], dtype=bool)

>>> # "logical_not" True where input array is False
>>> np.logical_not(bool1)
array([False, False,  True,  True], dtype=bool)