Python, Numpy: How to select numpy array with given mask

Question

For example, given a (10000, 250) sized numpy matrix A

>>>A.shape
(10000, 250)

and a numpy mask array m

>>>m = np.arange(0, A.shape[0], 3)
>>>m
([0, 3, 6, 9, ....., 9997])

This will select wanted column of A

>>>A[m]
>>>A[m].shape
(3333, 250)

But my question is. how to select the rest of the A? A[([1, 2, 4, 5, 7, 8, ...., 9998, 9999, 10000])]

cs95 · Accepted Answer · 2018-02-04 13:29:46Z

2

You can use setdiff1d to select all indices that do not belong to m:

A[np.setdiff1d(np.arange(A.shape[0]), m)]

answered Feb 4, 2018 at 13:29

cs95

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