Numpy intersect1d with array with matrix as elements

Question

I have two arrays, one of the shape (200000, 28, 28) and the other of the shape (10000, 28, 28), so practically two arrays with matrices as elements. Now I want to count and get all the elements (in the form (N, 28, 28)), that overlap in both arrays. With normal for loops it is way to slow, so I tryied it with numpys intersect1d method, but I dont know how to apply it on this types of arrays.

Basically this is a variation on the common 'unique row` question. — hpaulj
– hpaulj, Commented Jan 1, 2017 at 17:13

Eric · Accepted Answer · 2017-01-01 17:39:36Z

4

Using the approach from this question about unique rows

def intersect_along_first_axis(a, b):
    # check that casting to void will create equal size elements
    assert a.shape[1:] == b.shape[1:]
    assert a.dtype == b.dtype

    # compute dtypes
    void_dt = np.dtype((np.void, a.dtype.itemsize * np.prod(a.shape[1:])))
    orig_dt = np.dtype((a.dtype, a.shape[1:]))

    # convert to 1d void arrays
    a = np.ascontiguousarray(a)
    b = np.ascontiguousarray(b)
    a_void = a.reshape(a.shape[0], -1).view(void_dt)
    b_void = b.reshape(b.shape[0], -1).view(void_dt)

    # intersect, then convert back
    return np.intersect1d(b_void, a_void).view(orig_dt)

Note that using void is unsafe with floats, as it will cause -0 to be unequal to 0

edited Jan 1, 2017 at 17:39

answered Jan 1, 2017 at 17:15

Eric

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