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Method argpartition
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NumPy | fill_diagonal method

schedule Aug 11, 2023
Last updated
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PythonNumPy
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Numpy's fill_diagonal(~) method sets a specified value for the diagonals of the Numpy array. Note that this happens in-place, that is, no new array is created.

Parameters

1. a | array-like

The input array.

2. vallink | scalar

The desired value to fill the diagonals.

3. wraplink | boolean | optional

For 2D arrays that have more rows than columns (i.e. tall matrices), then we can repeatedly fill diagonals. See examples for clarification. By default, wrap=False.

Return value

None - diagonals are filled in-place.

Examples

Basic usage

Consider the following 2D array:

a = np.array([[5,6],[7,8]])
a
array([[5, 6],
[7, 8]])

To fill the diagonals with the value 2:

np.fill_diagonal(a, 2)
a
array([[2, 6],
[7, 2]])

Tall matrices

Consider the following tall 2D array:

a = np.array([[1,1],[1,1],[1,1],[1,1],[1,1]])
a
array([[1, 1],
[1, 1],
[1, 1],
[1, 1],
[1, 1]])

Without wrapping

By default, there is no wrapping behaviour, and so only the main diagonal will be filled:

np.fill_diagonal(a, 0)
a
array([[0, 1],
[1, 0],
[1, 1],
[1, 1],
[1, 1]])

With wrapping

To enable the wrapping behaviour, set wrap=True like so:

np.fill_diagonal(a, 0, wrap=True)
a
array([[0, 1],
[1, 0],
[1, 1],
[0, 1],
[1, 0]])

Notice how a single row is skipped before the next diagonals are filled.

robocat
Published by Isshin Inada
Edited by 0 others
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