Question

in phyton programming:

with numpy

Create a function called biochild.

 The function has as parameters the number m and the lists ??????h?? and ??????h??.

 The lists ??????h?? and ??????h?? contain 0’s and 1’s.

 For example: ??????h?? = [1,0,0,1,0,1] and ??????h?? = [1,1,1,0,0,1]

 Both lists have the same length ?.

 The 0's and 1's represent bits of information (remember that a bit is 0 or 1).

 The function has to generate a new list (child).  The child list must have the same length ?.

 child is generated by randomly combining part of the child's information ??????h?? and ??????h??.

 The first part of the child list will be made up of the first ? bits of ??????h?? and the second part by the last ? - ? bits of the ??????h??.

 For example, if ? = 3, ??????h?? = [?, ?, ?, 1,0,1] and ??????h?? = [1,1,1, ?, ?, ?], then ?h??? = [1,0,0,0,0,1].

 The value ? has to be chosen randomly by the function.

 After generating child, each bit in the list is considered for mutation.

 For each bit of child, with probability ? the bit is “mutated” by being replaced by its inverse (If the bit is 0 it is replaced by 1, and if it is 1 it is replaced by 0).

 Finally, the function returns the list child.

Answer 1

import numpy as np

def biochild(m, biomother, biofather):

    # child is generated by randomly combining part of the child's information ??????h?? and ??????h??.

    n = len(biomother)

    # randomly choose b from 1 to n

    b = np.random.randint(1, n)

    # The first part of the child list will be made up of the first ? bits of ??????h?? and the second part by the last ? - ? bits of the ??????h??.

    child = []

    for i in range(b):

        child.append(biomother[i])

    for i in range(b, n):

        child.append(biofather[i])

    # After generating child, each bit in the list is considered for mutation.

    # For each bit of child, with probability ? the bit is “mutated” by

    for i in range(n):

        # being replaced by its inverse (If the bit is 0 it is replaced by 1, and if it is 1 it is replaced by 0).

        p = np.random.uniform(0, 1)

        if p <= m:

            if child[i] == 0:

                child[i] = 1

            if child[i] == 1:

                child[i] = 0

    # Finally, the function returns the list child.

    return child

# For example: ??????h?? = [1,0,0,1,0,1] and ??????h?? = [1,1,1,0,0,1]

print(biochild(0.5, [1, 0, 0, 1, 0, 1], [1, 1, 1, 0, 0, 1]))

.

Screenshot:

Output:

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