Bitwise OR along one axis of a NumPy array

Question

For a given NumPy array, it is easy to perform a "normal" sum along one dimension. For example:

X = np.array([[1, 0, 0], [0, 2, 2], [0, 0, 3]])
X.sum(0)
    =array([1, 2, 5])
X.sum(1)
    =array([1, 4, 3])

Instead, is there an "efficient" way of computing the bitwise OR along one dimension of an array similarly? Something like the following, except without requiring for-loops or nested function calls.

Example: bitwise OR along zeroeth dimension as I currently am doing it:

np.bitwise_or(np.bitwise_or(X[:,0],X[:,1]),X[:,2])
    =array([1, 2, 3])

What I would like:

X.bitwise_sum(0)
    =array([1, 2, 3])

user2357112 · Accepted Answer · 2016-12-02 21:37:02Z

16

numpy.bitwise_or.reduce(X, axis=whichever_one_you_wanted)

Use the reduce method of the numpy.bitwise_or ufunc.

answered Dec 2, 2016 at 21:37

user2357112

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