Built-in Function In Numpy To Interpret An Integer To An Array Of Boolean Values In A Bitwise Manner?

I'm wondering if there is a simple, built-in function in Python / Numpy for converting an integer datatype to an array/list of booleans, corresponding to a bitwise interpretation o

Solution 1:

You can use numpy's unpackbits.

From the docs (http://docs.scipy.org/doc/numpy/reference/generated/numpy.unpackbits.html)

>>> a = np.array([[2], [7], [23]], dtype=np.uint8)
>>> a
array([[ 2],
       [ 7],
       [23]], dtype=uint8)
>>> b = np.unpackbits(a, axis=1)
>>> b
array([[0, 0, 0, 0, 0, 0, 1, 0],
       [0, 0, 0, 0, 0, 1, 1, 1],
       [0, 0, 0, 1, 0, 1, 1, 1]], dtype=uint8)

To get to a bool array:

In [49]: np.unpackbits(np.array([1],dtype="uint8")).astype("bool")
Out[49]: array([False, False, False, False, False, False, False,  True], dtype=bool)

Solution 2:

Not a built in method, but something to get you going (and fun to write)

>>> defint_to_binary_bool(num):
        return [bool(int(i)) for i in"{0:08b}".format(num)]

>>> int_to_binary_bool(5)
[False, False, False, False, False, True, False, True]