nlcpy.fill_diagonal
- nlcpy.fill_diagonal(a, val, wrap=False)[source]
Fills the main diagonal of the given array of any dimensionality.
For an array a with
a.ndim >= 2
, the diagonal is the list of locations with indicesa[i, ..., i]
all identical. This function modifies the input array in-place, it does not return a value.- Parameters
- aarray_like
Array whose diagonal is to be filled, it gets modified in-place.
- valscalar
Value to be written on the diagonal, its type must be compatible with that of the array a.
- wrapbool
For tall matrices, the diagonal “wrapped” after N columns. You can have this behavior with this option. This affects only tall matrices.
See also
diag_indices
Returns the indices to access the main diagonal of an array.
Note
This functionality can be obtained via diag_indices, but internally this version uses a much faster implementation that never constructs the indices and uses simple slicing.
Examples
>>> import nlcpy as vp >>> a = vp.zeros((3, 3), int) >>> vp.fill_diagonal(a, 5) >>> a array([[5, 0, 0], [0, 5, 0], [0, 0, 5]])
The same function can operate on a 4-D array:
>>> a = vp.zeros((3, 3, 3, 3), int) >>> vp.fill_diagonal(a, 4)
We only show a few blocks for clarity:
>>> a[0, 0] array([[4, 0, 0], [0, 0, 0], [0, 0, 0]]) >>> a[1, 1] array([[0, 0, 0], [0, 4, 0], [0, 0, 0]]) >>> a[2, 2] array([[0, 0, 0], [0, 0, 0], [0, 0, 4]])
The wrap option affects only tall matrices:
>>> # tall matrices no wrap >>> a = vp.zeros((5, 3), int) >>> vp.fill_diagonal(a, 4) >>> a array([[4, 0, 0], [0, 4, 0], [0, 0, 4], [0, 0, 0], [0, 0, 0]])
>>> # tall matrices wrap >>> a = vp.zeros((5, 3), int) >>> vp.fill_diagonal(a, 4, wrap=True) >>> a array([[4, 0, 0], [0, 4, 0], [0, 0, 4], [0, 0, 0], [4, 0, 0]])
>>> # wide matrices >>> a = vp.zeros((3, 5), int) >>> vp.fill_diagonal(a, 4, wrap=True) >>> a array([[4, 0, 0, 0, 0], [0, 4, 0, 0, 0], [0, 0, 4, 0, 0]])
The anti-diagonal can be filled by reversing the order of elements using either nlcpy.flipud or nlcpy.fliplr.
>>> a = vp.zeros((3, 3), int); >>> vp.fill_diagonal(vp.fliplr(a), [1,2,3]) # Horizontal flip >>> a array([[0, 0, 1], [0, 2, 0], [3, 0, 0]]) >>> vp.fill_diagonal(vp.flipud(a), [1,2,3]) # Vertical flip >>> a array([[0, 0, 3], [0, 2, 0], [1, 0, 0]])
Note that the order in which the diagonal is filled varies depending on the flip function.