Apply operation to row in numpy array

Question

Suppose I have a m x n numpy array:

([[4,6,7],[5,2,1],[5,6,7],[5,3,5]])

And I want to perform an operation with every row and its proceeding row. How can this be done without a for-loop? The specific operation here computes the unit vector between two successive rows in this array. For example,

# Row 1 would be:
[5,2,1]-[4,6,7]/norm([5,2,1]-[4,6,7])

# Row 2 would be
[5,6,7]-[5,2,1]/norm([5,6,7]-[5,2,1])

and so on... yielding a 3x3 numpy array

data[1:,:]-data[:-1,:] gives the difference between successive rows. — hpaulj
– hpaulj, Commented Feb 19, 2021 at 6:20

Epsi95 · Accepted Answer · 2021-02-19 06:28:08Z

2

Get the difference and divide by norm

arr = np.array([[4,6,7],[5,2,1],[5,6,7],[5,3,5]])

op = arr[1:] - arr[:-1]

op = op/np.linalg.norm(op, ord=2, axis=1, keepdims=True)

print(op)

[[ 0.13736056 -0.54944226 -0.82416338]
 [ 0.          0.5547002   0.83205029]
 [ 0.         -0.83205029 -0.5547002 ]]

answered Feb 19, 2021 at 6:28

Epsi95

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