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I have one A array of (5x5) elements and a second B array of (5x1). Now I want to replace the column of A with B. My array is

A=array([[1, 2, -3, 4, 5],[1, 2, -3, -4, 5],[-1, 2, -3, -4, 5],[-1, -2, -3, -4, 5],[-1, -2, -3, -4, -5]])
and 
B=array([-10. , -11.5, -13. , -14.5, -16. ])

So it should replace every column with B when the first negative number encounters. For example, in the first column of A, the first negative element is at A[2][0] (-1), so the first column of A replaces with B[2], in the second column the first negative element is at A[3][1] and that column replace with B[3], etc. So my final output is

A=(alpha[2],alpha[3],alpha[0],alpha[1],alpha[4])= (-13.0, -14.5, -10.0, -11.5, -16.0)  

So far my code is

A=array([[1, 2, -3, 4, 5],[1, 2, -3, -4, 5],[-1, 2, -3, -4, 5],[-1, -2, -3, -4, 5],[-1, -2, -3, -4, -5]])
B=np.linspace(-10,-16,5)
for i in range(len(B)):
  A[:,i][A[:,i]<0]=alpha[i]

But this is not giving the correct answer.

Thank you in advance!

1 Answer 1

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You could use argmax to find the first row for each column in which there is a negative value, and then use that result as an index into B:

import numpy as np

A = np.array([[1, 2, -3, 4, 5],[1, 2, -3, -4, 5],[-1, 2, -3, -4, 5],[-1, -2, -3, -4, 5],[-1, -2, -3, -4, -5]])
B = np.linspace(-10, -16, 5)

A2 = B[np.argmax(A < 0, axis=0)]

Output:

array([-13. , -14.5, -10. , -11.5, -16. ])
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