3

I'm trying to the fill the offset diagonals of a matrix:

loss_matrix = np.zeros((125,125))

np.diagonal(loss_matrix, 3).fill(4)

ValueError: assignment destination is read-only

Two questions:

1) Without iterating over indexes, how can I set the offset diagonals of a numpy array?

2) Why is the result of np.diagonal read only? The documentation for numpy.diagonal reads: "In NumPy 1.10, it will return a read/write view and writing to the returned array will alter your original array."

np.__version__

'1.10.1'
Cleb
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ryan
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  • [This question](http://stackoverflow.com/questions/10925671/numpy-k-th-diagonal-indices) might help. – Cleb Jan 26 '16 at 19:47

2 Answers2

7

Judging by the discussion on the NumPy issue tracker, it looks like the feature is stuck in limbo and they never got around to fixing the documentation to say it was delayed.

If you need writability, you can force it. This will only work on NumPy 1.9 and up, since np.diagonal makes a copy on lower versions:

diag = np.diagonal(loss_matrix, 3)

# It's not writable. MAKE it writable.
diag.setflags(write=True)

diag.fill(4)
user2357112
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0

In an older version, diagflat constructs an array from a diagonal.

In [180]: M=np.diagflat(np.ones(125-3)*4,3)
In [181]: M.shape
Out[181]: (125, 125)
In [182]: M.diagonal(3)
Out[182]: 
array([ 4.,  4.,  4.,  4.,  4.,  4.,  4.,  4.,  4.,  4.,  4.,  4.,  4.,...  4.])

In [183]: np.__version__
Out[183]: '1.8.2'

Effectively it does this (working from its Python code)

res = np.zeros((125, 125))
i = np.arange(122)  
fi = i+3+i*125
res.flat[fi] = 4

That is, it finds the flatten array equivalent indices of the diagonal.

I can also get fi with:

In [205]: i=np.arange(0,122)
In [206]: np.ravel_multi_index((i,i+3),(125,125))
hpaulj
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  • The second option works with negative diagonals, but the third does not – ryan Jan 26 '16 at 21:33
  • For the 2nd I pulled out the positive offset case. The `ravel` version could be easily adapted to work with a negative offset - maybe as simple as using `(i+3,i)` (not tested) – hpaulj Jan 26 '16 at 21:38