Numpy Sum when each array has a specific value

Question

x1 = np.array([0,  1,  0,  1,  0, 1, 0, 1, 1,  1])
y = np.array([-1, -1, -1, -1, -1, 1, 1, 1, 1, -1])

I know with these 2 arrays you can sum up the amount of times exact indicies are equal with numpy in this line of code.

np.sum(x1 == y)

but is there a way to sum up each time the same index equals a specific value on each array such as

np.sum(x1 == 1 && y == -1)

Unfortunately this line of code doesn't run, but if it worked the result should be 3.

michcio1234 · Accepted Answer · 2018-10-10 07:44:08Z

6

You just have to use a single & and add some parentheses:

np.sum((x1 == 1) & (y == -1))

This gives 3 as a result.

answered Oct 10, 2018 at 7:44

michcio1234

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Comments

atline · Accepted Answer · 2018-10-10 07:53:00Z

1

Besides a & b in numpy, you may also use logical_and, just FYI.

np.sum(np.logical_and((x1 == 1), (y == -1)))

answered Oct 10, 2018 at 7:53

atline

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