Numpy arange a diagonal array

Question

I would like to create a square numpy array such that it starts counting from the diagonal. Do you know a one-liner for that?

Example with 5x5:

array([[ 1.,  2.,  3.,  4.,  5.],
       [ 0.,  1.,  2.,  3.,  4.],
       [ 0.,  0.,  1.,  2.,  3.],
       [ 0.,  0.,  0.,  1.,  2.],
       [ 0.,  0.,  0.,  0.,  1.]])

Randy · Accepted Answer · 2018-08-26 00:54:44Z

2

In [49]: np.identity(5).cumsum(axis=1).cumsum(axis=1)
Out[49]:
array([[ 1.,  2.,  3.,  4.,  5.],
       [ 0.,  1.,  2.,  3.,  4.],
       [ 0.,  0.,  1.,  2.,  3.],
       [ 0.,  0.,  0.,  1.,  2.],
       [ 0.,  0.,  0.,  0.,  1.]]

answered Aug 26, 2018 at 0:54

Randy

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2 Comments

DED Over a year ago

Thanks for the solution. Here is what I ended up using for readability: np.triu(np.ones([K,K]), 0).cumsum(axis =1)

Randy Over a year ago

That's a cool one too. Ran a quick timing test and both methods end up being almost exactly the same (254ms vs. 257ms per run on a 5000x5000 grid), so either way should be work from a performance point of view.

kevinkayaks · Accepted Answer · 2018-08-26 01:01:15Z

0

>>> mat = np.vstack((np.concatenate((np.zeros(i),np.arange(1,5-i+1))) for i in range(0,5)))
>>> mat 
array([[1., 2., 3., 4., 5.],
       [0., 1., 2., 3., 4.],
       [0., 0., 1., 2., 3.],
       [0., 0., 0., 1., 2.],
       [0., 0., 0., 0., 1.]])

answered Aug 26, 2018 at 1:01

kevinkayaks

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