python波浪号一元运算符作为否定numpy bool数组

Question

Should be a simple question, but I'm unable to find an answer anywhere. The ~ operator in python is a documented as a bitwise inversion operator. Fine. I have noticed seemingly schizophrenic behavior though, to wit:

~True -> -2
~1 -> -2
~False -> -1
~0 -> -1
~numpy.array([True,False],dtype=int) -> array([-2,-1])
~numpy.array([True,False],dtype=bool) -> array([False,True])

In the first 4 examples, I can see that python is implementing (as documented) ~x = -(x+1) , with the input treated as an int even if it's boolean . Hence, for a scalar boolean, ~ is not treated as a logical negation. Not that the behavior is identical on a numpy array defined with boolean values by with an int type.

Why does ~ then work as a logical negation operator on a boolean array (Also notice: ~numpy.isfinite(numpy.inf) -> True ?)?

It is extremely annoying that I must use not() on a scalar, but not() won't work to negate an array. Then for an array, I must use ~ , but ~ won't work to negate a scalar...

Answer 1

not is implemented through the __nonzero__ special method, which is required to return either True or False , so it can't give the required result. Instead the ~ operator is used, which is implemented through the __not__ special method. For the same reason, & and | are used in place of and and or .

PEP 335 aimed to allow overloading of boolean operators but was rejected because of excessive overhead (it would eg complicate if statements). PEP 225 suggests a general syntax for "elementwise" operators, which would provide a more general solution, but has been deferred. It appears that the current situation, while awkward, is not painful enough to force change.

np.isfinite when called on a scalar returns a value of type np.bool_ , not bool . np.bool_ is also the type you get when extracting a scalar value from an array of bool dtype. If you use np.True_ and np.False_ in place of True and False you will get consistent behaviour under ~ .