Suppose I have a binary matrix. I would like to cast that matrix into another matrix where each row has single one and the index of that one would be random for each row.
For instance if one of the row is [0,1,0,1,0,0,1] and I cast it to [0,0,0,1,0,0,0] where we select the 1's index randomly.
How could I do it in numpy?
Presently I find the max (since max function returns one index) of each row and set it to zero. It works if all rows have at most 2 ones but if more than 2 then it fails.
Extending @zhangxaochen's answer, given a random binary array
x = np.random.random_integers(0, 1, (8, 8))
you can populate another array with a randomly drawn 1 from x:
y = np.zeros_like(x)
ind = [np.random.choice(np.where(row)[0]) for row in x]
y[range(x.shape[0]), ind] = 1
I'd like to use np.argsort to get the indices of the non-zero elements:
In [351]: a=np.array([0,1,0,1,0,0,1])
In [352]: from random import choice
...: idx=choice(np.where(a)[0]) #or np.nonzero instead of np.where
In [353]: b=np.zeros_like(a)
...: b[idx]=1
...: b
Out[353]: array([0, 1, 0, 0, 0, 0, 0])
a.argsort()[-np.count_nonzero(a):] with np.where(a)[0].