Slice 2-D array row by row with corresponding rows from identically shaped array [duplicate]

Question

consider the array a

np.random.seed([3,1415])
a = np.random.choice(np.arange(8), (2, 4), False)
print(a)

[[7 1 4 5]
 [6 2 3 0]]

I'll create another array b that holds the results of np.argsort along each row.

b = a.argsort(1)
print(b)

[[1 2 3 0]
 [3 1 2 0]]

I want to produce the sorted version of a by doing an appropriate slice of a with b. It should look like this

idx0 = np.arange(a.shape[0]).repeat(a.shape[1])
print(a[idx0, b.ravel()].reshape(a.shape))

[[1 4 5 7]
 [0 2 3 6]]

question
what is the appropriate way to slice an 2 x 4 array with another 2 x 4 array in the fashion described above?

Divakar · Accepted Answer · 2016-12-30 07:10:07Z

2

Advanced-indexing for the help -

a[np.arange(b.shape[0])[:,None],b]

Sample run -

In [10]: a
Out[10]: 
array([[7, 1, 4, 5],
       [6, 2, 3, 0]])

In [11]: b
Out[11]: 
array([[1, 2, 3, 0],
       [3, 1, 2, 0]])

In [12]: a[np.arange(b.shape[0])[:,None],b]
Out[12]: 
array([[1, 4, 5, 7],
       [0, 2, 3, 6]])

edited Dec 30, 2016 at 7:10

answered Dec 30, 2016 at 6:58

Divakar

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