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Showing content from https://numpy.org/doc/stable/reference/generated/numpy.put.html below:

numpy.put — NumPy v2.3 Manual

numpy.put#
numpy.put(a, ind, v, mode='raise')[source]#

Replaces specified elements of an array with given values.

The indexing works on the flattened target array. put is roughly equivalent to:

Parameters:
andarray

Target array.

indarray_like

Target indices, interpreted as integers.

varray_like

Values to place in a at target indices. If v is shorter than ind it will be repeated as necessary.

mode{‘raise’, ‘wrap’, ‘clip’}, optional

Specifies how out-of-bounds indices will behave.

  • ‘raise’ – raise an error (default)

  • ‘wrap’ – wrap around

  • ‘clip’ – clip to the range

‘clip’ mode means that all indices that are too large are replaced by the index that addresses the last element along that axis. Note that this disables indexing with negative numbers. In ‘raise’ mode, if an exception occurs the target array may still be modified.

Examples

>>> import numpy as np
>>> a = np.arange(5)
>>> np.put(a, [0, 2], [-44, -55])
>>> a
array([-44,   1, -55,   3,   4])
>>> a = np.arange(5)
>>> np.put(a, 22, -5, mode='clip')
>>> a
array([ 0,  1,  2,  3, -5])

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