numpy: fill offset diagonal with different values

You can straightforwardly use np.diag:

>>> d = np.sqrt(1 + np.arange(4))
>>> np.diag(d, 1)
array([[ 0.        ,  1.        ,  0.        ,  0.        ,  0.        ],
       [ 0.        ,  0.        ,  1.41421356,  0.        ,  0.        ],
       [ 0.        ,  0.        ,  0.        ,  1.73205081,  0.        ],
       [ 0.        ,  0.        ,  0.        ,  0.        ,  2.        ],
       [ 0.        ,  0.        ,  0.        ,  0.        ,  0.        ]])

The second argument of np.diag specifies the diagonal in question.

One way could be to create the array of zeros and then use indexing to select and fill the desired indices with the square-root values.

For example:

>>> z = np.zeros((5,5))
>>> rng = np.arange(4)
>>> z[rng, rng+1] = np.sqrt(rng+1)
>>> z
array([[ 0.        ,  1.        ,  0.        ,  0.        ,  0.        ],
       [ 0.        ,  0.        ,  1.41421356,  0.        ,  0.        ],
       [ 0.        ,  0.        ,  0.        ,  1.73205081,  0.        ],
       [ 0.        ,  0.        ,  0.        ,  0.        ,  2.        ],
       [ 0.        ,  0.        ,  0.        ,  0.        ,  0.        ]])