Numpy binary matrix to chromosome

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I have a binary matrix of shape N,M, and I want an efficient way to transform it to chromosome, that is, given a row I need a function that returns the indexes of non-zero elements, for example given the row [1,1,0,0,0,0,0,0,1] the function should return [0,1,8], this could be done with np.flatnonzero for example. I need to apply this transformation to all rows and return a flatten vector representing the binary matrix, for example

P = np.array([[1,1,0,0,0,0,0,0,1], [0,0,1,1,1,1,0,0,0], [0,0,0,0,0,0,1,1,0]])

should be transformed to [018234567]

numpy python
2 Answers

You could use the non-flat version np.nonzero. With a matrix this will give you a tuple with arrays for the rows and columns separately, from which you want the columns:

P = np.array([[1,1,0,0,0,0,0,0,1], [0,0,1,1,1,1,0,0,0], [0,0,0,0,0,0,1,1,0]])

rows, col = np.nonzero(P)

print(col)
# [0 1 8 2 3 4 5 6 7]
user_38746230

Here is my suggestion:

import numpy as np

P = np.array([[1,1,0,0,0,0,0,0,1], [0,0,1,1,1,1,0,0,0], [0,0,0,0,0,0,1,1,0]])

s=''

for i in P:
    for j in np.flatnonzero(i):
        s+=str(j)

print(s)
user_100421550
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