Compress Binary Data Array

Question

I have an array of size 2N where N[i]={0,1}, i.e each value in the array is either 0 or 1, How can I compress it to an array of size N? output array has the same property i.e each value in the array is either 0 or 1?

def compress(data):
    code = [0] * 10
    i = 0
    count_o = 0
    count_z = 0

    for e in range(0, len(data), 2):
        code[i] = data[e]
        i += 1

    for e in range( 1, len(data), 2):
        if data[e] == 0:
            count_z += 1
        else:
            count_o += 1
    code[9] = 1 if count_z < count_o else 0

  
    return code


def decode(code):
    data = [0] * 20
    i = 0

    for c in code:
        data[i] = c
        if i > 0:
            data[i - 1] = code[9]
     
        i += 2

    return data

I tried a lossy method where I take every alternate data point and for the rest take the maximum frequency.

After encoding the solution, I decode the same and compare it with the original data where each correct match is +1

On calling this function for different permutations of data the average I get is around 15.42.

The solution need not be a lossless solution, the best possible in the average scenario.

Answer 1

I hope this is what you are looking for:

arr=[1,0,0,1,1,0,0,1]
new_arr=[]
convB_N={(0,1):1,(0,0):0,(1,0):2,(1,1):3}
for i in range(0,len(arr),2):
    bi=(arr[i],arr[i+1])
    new_arr.append(convB_N[bi])
print(new_arr)

Output:

[2, 1, 2, 1]

This is simple binary to decimal. Take two input from array and return its corresponding decimal.