How to ignore out of bounds values in an index array when using numpy?

Question

I need to assign one array to another using an index array. But some values are out of bounds...

a = np.array([0, 1, 2, 3, 4])
b = np.array([10, 11, 12, 13, 14])
indexes = np.array([0, 2, 3, 5, 6])

a and b are the same size. If I use a[indexes] = b, it would throw an IndexError. I want it to ignore the out of bounds values, 5 and 6, so that a would become [10, 1, 11, 12, 4].

I tried to do indexes[indexes > b.size()] = 0 but this would mess up the value at index 0. How can this be solved?

Edit

The indexes may not necessarily be in order. For example:

indexes = np.array([2, 3, 0, 5, 6])

a should become np.array([12, 1, 10, 11, 4])

In your edit, please where does the 11 (b at index 1) come from in expected result of a? — Scott Boston
– Scott Boston, Commented Jun 25, 2020 at 13:30
b should match with indexes, so b[1] should go to a[index[1]] — y1 r0 kh
– y1 r0 kh, Commented Jun 25, 2020 at 14:53

Quang Hoang · Accepted Answer · 2020-06-25 12:34:11Z

4

You can filter out those invalid indexes:

indexes = indexes[indexes < len(a)]

a[indexes] = b[indexes]

Output:

array([10,  1, 12, 13,  4])

answered Jun 25, 2020 at 12:34

Quang Hoang

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