nested_argwhere#

ivy.nested_argwhere(nest, fn, check_nests=False, to_ignore=None, _index=None, _base=True, stop_after_n_found=None)[source]#

Check the leaf nodes of nested x via function fn, and returns all nest indices where the method evaluates as True.

Parameters:

nest (Iterable) – The nest to check the leaves of.
fn (Callable) – The condition function, returning True or False.
check_nests (bool, default: False) – Whether to also check the nests for the condition, not only nest leaves. Default is False.
to_ignore (Optional[Union[type, Tuple[type]]], default: None) – Types to ignore when deciding whether to go deeper into the nest or not
_index (Optional[List], default: None) – The indices detected so far. None at the beginning. Used internally, do not set manually.
_base (bool, default: True) – Whether the current function call is the first function call in the recursive stack. Used internally, do not set manually.
stop_after_n_found (Optional[int], default: None) – to stop after some needed indices are found.

Return type:

Union[Iterable, bool]

Returns:

ret – A set of indices for the nest where the function evaluated as True.

Examples

With List input:

>>> nest = [[[1, -2, 3], 19], [[9, -36, 80], -10.19]]
>>> fun = ivy.abs
>>> nested_indices = ivy.nested_argwhere(nest, fn=fun)
>>> print(nested_indices)
[
    [0, 0, 0], [0, 0, 1],
    [0, 0, 2], [0, 1],
    [1, 0, 0], [1, 0, 1],
    [1, 0, 2], [1, 1]
]

With Tuple input:

>>> nest = ([-5, 9, 2], [0.3, 4.])
>>> fun = ivy.abs
>>> nested_indices = ivy.nested_argwhere(nest, fn=fun, stop_after_n_found=4)
>>> print(nested_indices)
[[0, 0], [0, 1], [0, 2], [1, 0]]

With Dict input:

>>> nest={'a': [2., 0.6, -2.], 'b': [1., 4., 1.9], 'c': [9.4]}
>>> fun = ivy.abs
>>> nested_indices = ivy.nested_argwhere(nest, fn=fun)
>>> print(nested_indices)
[
    ['a', 0], ['a', 1],
    ['a', 2], ['b', 0],
    ['b', 1], ['b', 2],
    ['c', 0]
]