I have a numpy array (dtype bool) representing an array of bits. For example, the array np.array([True, False, False], dtype=bool) represents the number 4 (indeed, bin(4) == 0b100).
I would like to convert the numpy array to an integer (4 in the previous example).
So far I've tried with an iterative approach:
bits = np.array([True, False, False], dtype=bool)
n = 0
for bit in bits:
n = (n << 1) | bit
This approach does work, but I would prefer something that does not iterate over every element of the array, possibly a numpy built-in method.
I also tried using numpy.packbits (together with numpy.pad, because packbits always automatically pad to the right, and not to the left):
bits = np.array([True, False, False], dtype=bool)
n = np.packbits(np.pad(bits, ((8 - len(bits) % 8) % 8, 0))).item()
This approach only works for arrays with 8 or less elements. Indeed, if you try to use a longer array you end up having multiple results (because apparently packbits not only pads to the right but also converts every single byte to a number):
bits = np.array(
[True, False, False, False, False, False, False, False, False],
dtype=bool,
)
n = np.packbits(np.pad(bits, ((8 - len(bits) % 8) % 8, 0)))
print(n) # this prints [1 0], but I need it to return 256
Expected behavior:
np.array([True, True], dtype=bool) --> 3
np.array([True, True, False], dtype=bool) --> 6
np.array([True, False, False, True, True], dtype=bool) --> 19
np.array([True, False, False, False, False,
False, False, True, False, False], dtype=bool) --> 516
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