# Convert A Numpy Bool Array To Int

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
```

## Answer

You can solve this problem by generating the power of two starting from the biggest one (eg. `[16, 8, 4, 2, 1]`

), and then multiply this by `bits`

before doing the final sum:

```
powers = 1 << np.arange(bits.size, dtype=np.uint64)[::-1]
result = np.sum(powers * bits)
```

This is equivalent of doing: `2**n * bits[0] + 2**(n-1) * bits[1] + ... + 2**0 * bits[n]`

.
Note that the final value needs to fit in 64 bits.

## Related Questions

- → What are the pluses/minuses of different ways to configure GPIOs on the Beaglebone Black?
- → Django, code inside <script> tag doesn't work in a template
- → React - Django webpack config with dynamic 'output'
- → GAE Python app - Does URL matter for SEO?
- → Put a Rendered Django Template in Json along with some other items
- → session disappears when request is sent from fetch
- → Python Shopify API output formatted datetime string in django template
- → Can't turn off Javascript using Selenium
- → WebDriver click() vs JavaScript click()
- → Shopify app: adding a new shipping address via webhook
- → Shopify + Python library: how to create new shipping address
- → shopify python api: how do add new assets to published theme?
- → Access 'HTTP_X_SHOPIFY_SHOP_API_CALL_LIMIT' with Python Shopify Module