Convert 2-d numpy array of floats to array of strings by column

Question

I have a NumPy array, which is the output of a TensorFlow prediction. The output is looking something like this:

array([[0, 1, 1, ..., 1, 1, 1],
       [0, 1, 1, ..., 1, 1, 1],
       [0, 1, 1, ..., 1, 1, 1],
       ...,
       [1, 1, 1, ..., 1, 1, 1],
       [1, 1, 1, ..., 1, 1, 1],
       [1, 1, 1, ..., 1, 1, 1]])

for further processing, the 2-d NumPy array should be converted into a 1-d string array (or python list). The output should look something like this:

array(['01111111', '01111111', '01111111', ..., '11111111', '11111111',
       '11111111'], dtype='<U8')

What would be a simple or NumPy best practice way to achieve this?

Adib Nur · Accepted Answer · 2022-06-01 12:15:38Z

1

Assuming the array is named array and numpy is imported as np, the following line: np.apply_along_axis(''.join, 1, array.astype(str)) will suffice

answered Jun 1, 2022 at 12:15

Adib Nur

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1 Comment

Stefan Over a year ago

Thank you, this seems the most natural and simple approach to the problem to me! However, the other answers are also valid and solve the same problem...

mrCopiCat · Accepted Answer · 2022-06-01 12:08:06Z

1

try this :

import numpy as np

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

output = np.array([''.join(map(str, el)) for el in arr], dtype='U8')
print(output)

output:

['011111' '011111' '011111' '111111' '111111' '111111']

answered Jun 1, 2022 at 12:08

mrCopiCat

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Comments

Mahdi F. · Accepted Answer · 2022-06-02 07:25:47Z

You can use apply_along_axis like below:

Short version:

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

np.apply_along_axis(''.join, 1, a.astype(str))

Explanation version:

def join_num(r):
    return ''.join(map(str,r))

# or with lamda
# join_num = lambda x: ''.join(map(str,x))

np.apply_along_axis(join_num, 1, a)

Output:

array(['0110111', '0111111', '0110111', '1111111', '1110111', '1111111'],
      dtype='<U7')

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