I have a binary array, and I would like to convert it into a list of integers, where each int is a row of the array.
For example:
from numpy import *
@SteveTjoa's answer is fine, but for kicks, here's a numpy one-liner:
In [19]: a
Out[19]:
array([[1, 1, 0, 0],
[0, 1, 0, 0],
[0, 1, 1, 1],
[1, 1, 1, 1]])
In [20]: a.dot(1 << arange(a.shape[-1] - 1, -1, -1))
Out[20]: array([12, 4, 7, 15])
(arange
is numpy.arange
.)
If the bits are in the opposite order, change the order of the values produced by arange
:
In [25]: a.dot(1 << arange(a.shape[-1]))
Out[25]: array([ 3, 2, 14, 15])
You could also do this within numpy directly:
from numpy import *
a = array([[1, 1, 0, 0], [0, 1, 0, 0], [0, 1, 1, 1], [1, 1, 1, 1]])
b2i = 2**arange(a.shape[0]-1, -1, -1)
result = (a*b2i).sum(axis=1) #[12 4 7 15]
If you like working directly with bitwise math, this one should work pretty well.
def bits2int(a, axis=-1):
return np.right_shift(np.packbits(a, axis=axis), 8 - a.shape[axis]).squeeze()
bits2int(a)
Out: array([12, 4, 7, 15], dtype=uint8)
I once asked a similar question here. Here was my answer, adapted for your question:
def bool2int(x):
y = 0
for i,j in enumerate(x):
y += j<<i
return y
In [20]: a
Out[20]:
array([[1, 1, 0, 0],
[0, 1, 0, 0],
[0, 1, 1, 1],
[1, 1, 1, 1]])
In [21]: [bool2int(x[::-1]) for x in a]
Out[21]: [12, 4, 7, 15]
Another one:
def row_bits2int(arr):
n = arr.shape[1] # number of columns
# shift the bits of the first column to the left by n - 1
a = arr[:, 0] << n - 1
for j in range(1, n):
# "overlay" with the shifted bits of the next column
a |= arr[:, j] << n - 1 - j
return a