Searching#

class ivy.data_classes.container.searching._ContainerWithSearching(dict_in=None, queues=None, queue_load_sizes=None, container_combine_method='list_join', queue_timeout=None, print_limit=10, key_length_limit=None, print_indent=4, print_line_spacing=0, ivyh=None, default_key_color='green', keyword_color_dict=None, rebuild_child_containers=False, types_to_iteratively_nest=None, alphabetical_keys=True, dynamic_backend=None, **kwargs)[source]#

Bases: ContainerBase

_abc_impl = <_abc_data object>#
static _static_argmax(x, /, *, axis=None, keepdims=False, dtype=None, select_last_index=False, out=None)[source]#

ivy.Container static method variant of ivy.argmax. This method simply wraps the function, and so the docstring for ivy.argmax also applies to this method with minimal changes.

Parameters:

  • x (Union[Container, Array, NativeArray]) – input array or container. Should have a numeric data type.

  • axis (Optional[int]) – axis along which to search. If None, the function must return the index of (default: None) the maximum value of the flattened array. Deafult: None.

  • keepdims (bool) – If this is set to True, the axes which are reduced are left in the result as (default: False) dimensions with size one. With this option, the result will broadcast correctly against the array.

  • dtype (Optional[Union[Dtype, NativeDtype]]) – Optional data type of the output array. (default: None)

  • out (Optional[Container]) – If provided, the result will be inserted into this array. It should be of (default: None) the appropriate shape and dtype.

Return type:

Container

Returns:

ret – a container containing the indices of the maximum values across the specified axis.

Examples

>>> x = ivy.Container(a=ivy.array([[4., 0., -1.], [2., -3., 6]]),        ...                   b=ivy.array([[1., 2., 3.], [1., 1., 1.]])
>>> y = ivy.Container.static_argmax(x, axis=1, keepdims=True)
>>> print(y)
{
    a: ivy.array([[0],
                  [2]]),
    b: ivy.array([[2],
                  [0]])
}
static _static_argmin(x, /, *, axis=None, keepdims=False, output_dtype=None, select_last_index=False, out=None)[source]#

ivy.Container static method variant of ivy.argmin. This method simply wraps the function, and so the docstring for ivy.argmin also applies to this method with minimal changes.

Parameters:

  • x (Union[Container, Array, NativeArray]) – input array or container. Should have a numeric data type.

  • axis (Optional[int]) – axis along which to search. If None, the function must return the index of (default: None) the minimum value of the flattened array. Default = None.

  • keepdims (bool) – if True, the reduced axes (dimensions) must be included in the result as (default: False) singleton dimensions, and, accordingly, the result must be compatible with the input array (see Broadcasting). Otherwise, if False, the reduced axes (dimensions) must not be included in the result. Default = False.

  • output_dtype (Optional[Union[int32, int64]]) – An optional output_dtype from: int32, int64. Defaults to int64. (default: None)

  • out (Optional[Container]) – optional output container, for writing the result to. It must have a shape (default: None) that the inputs broadcast to.

Return type:

Container

Returns:

ret – a container containing the indices of the minimum values across the specified axis.

Examples

>>> x = ivy.Container(a=ivy.array([[4., 0., -1.], [2., -3., 6]]),        ...                   b=ivy.array([[1., 2., 3.], [1., 1., 1.]])
>>> y = ivy.Container.static_argmin(axis=1, keepdims=True)
>>> print(y)
{
    a: ivy.array([[2],
                  [1]]),
    b: ivy.array([[0],
                  [0]])
}
static _static_argwhere(x, /, *, key_chains=None, to_apply=True, prune_unapplied=False, map_sequences=False, out=None)[source]#

ivy.Container static method variant of ivy.argwhere. This method simply wraps the function, and so the docstring for ivy.argwhere also applies to this method with minimal changes.

Parameters:

  • x (Container) – Boolean array, for which indices are desired.

  • key_chains (Optional[Union[List[str], Dict[str, str]]]) – The key-chains to apply or not apply the method to. Default is None. (default: None)

  • to_apply (bool) – If True, the method will be applied to key_chains, otherwise key_chains will (default: True) be skipped. Default is True.

  • prune_unapplied (bool) – Whether to prune key_chains for which the function was not applied. Default (default: False) is False.

  • map_sequences (bool) – Whether to also map method to sequences (lists, tuples). (default: False) Default is False.

Return type:

Container

Returns:

ret – Indices for where the boolean array is True.

Examples

Using ivy.Container instance method

>>> x = ivy.Container(a=ivy.array([1, 2]), b=ivy.array([3, 4]))
>>> res = ivy.Container.static_argwhere(x)
>>> print(res)
{
    a: ivy.array([[0], [1]]),
    b: ivy.array([[0], [1]])
}

>>> x = ivy.Container(a=ivy.array([1, 0]), b=ivy.array([3, 4]))
>>> res = ivy.Container.static_argwhere(x)
>>> print(res)
{
    a: ivy.array([[0]]),
    b: ivy.array([[0], [1]])
}
static _static_nonzero(x, /, *, as_tuple=True, size=None, fill_value=0)[source]#

ivy.Container static method variant of ivy.nonzero. This method simply wraps the function, and so the docstring for ivy.nonzero also applies to this method with minimal changes.

Parameters:

  • x (Union[Container, Array, NativeArray]) – input array or container. Should have a numeric data type.

  • as_tuple (bool) – if True, the output is returned as a tuple of indices, one for each (default: True) dimension of the input, containing the indices of the true elements in that dimension. If False, the coordinates are returned in a (N, ndim) array, where N is the number of true elements. Default = True.

  • size (Optional[int]) – if specified, the function will return an array of shape (size, ndim). (default: None) If the number of non-zero elements is fewer than size, the remaining elements will be filled with fill_value. Default = None.

  • fill_value (Number) – when size is specified and there are fewer than size number of elements, (default: 0) the remaining elements in the output array will be filled with fill_value. Default = 0.

Return type:

Container

Returns:

ret – a container containing the indices of the nonzero values.

static _static_where(condition, x1, x2, /, *, out=None)[source]#

ivy.Container static method variant of ivy.where. This method simply wraps the function, and so the docstring for ivy.where also applies to this method with minimal changes.

Parameters:

  • condition (Union[Container, Array, NativeArray]) – input array or container. Should have a boolean data type.

  • x1 (Union[Container, Array, NativeArray]) – input array or container. Should have a numeric data type.

  • x2 (Union[Container, Array, NativeArray]) – input array or container. Should have a numeric data type.

  • out (Optional[Container]) – optional output container, for writing the result to. It must have a shape (default: None) that the inputs broadcast to.

Return type:

Container

Returns:

ret – a container containing the values of x1 where condition is True, and x2 where condition is False.

Examples

>>> x1 = ivy.Container(a=ivy.array([3, 1, 5]), b=ivy.array([2, 4, 6]))
>>> x2 = ivy.Container(a=ivy.array([0, 7, 2]), b=ivy.array([3, 8, 5]))
>>> res = ivy.Container.static_where((x1.a > x2.a), x1, x2)
>>> print(res)
{
    a: ivy.array([3, 7, 5]),
    b: ivy.array([2, 8, 6])
}
argmax(*, axis=None, keepdims=False, dtype=None, select_last_index=False, out=None)[source]#

ivy.Container instance method variant of ivy.argmax. This method simply wraps the function, and so the docstring for ivy.argmax also applies to this method with minimal changes.

Parameters:

  • self (Container) – input array or container. Should have a numeric data type.

  • axis (Optional[int]) – axis along which to search. If None, the function must return the index of (default: None) the maximum value of the flattened array. Deafult: None.

  • keepdims (bool) – If this is set to True, the axes which are reduced are left in the result as (default: False) dimensions with size one. With this option, the result will broadcast correctly against the array.

  • dtype (Optional[Union[Dtype, NativeDtype]]) – Optional output dtype of the container. (default: None)

  • out (Optional[Container]) – If provided, the result will be inserted into this array. It should be of (default: None) the appropriate shape and dtype.

Return type:

Container

Returns:

ret – a container containing the indices of the maximum values across the specified axis.

Examples

>>> a = ivy.array([[4., 0., -1.], [2., -3., 6]])
>>> b = ivy.array([[1., 2., 3.], [1., 1., 1.]])
>>> x = ivy.Container(a=a, b=b)
>>> y = x.argmax(axis=1, keepdims=True)
>>> print(y)
{
    a: ivy.array([[0],
                  [2]]),
    b: ivy.array([[2],
                  [0]])
}
argmin(*, axis=None, keepdims=False, output_dtype=None, select_last_index=False, out=None)[source]#

ivy.Container instance method variant of ivy.argmin. This method simply wraps the function, and so the docstring for ivy.argmin also applies to this method with minimal changes.

Parameters:

  • self (Container) – input array or container. Should have a numeric data type.

  • axis (Optional[int]) – axis along which to search. If None, the function must return the index of (default: None) the minimum value of the flattened array. Default = None.

  • keepdims (bool) – if True, the reduced axes (dimensions) must be included in the result as (default: False) singleton dimensions, and, accordingly, the result must be compatible with the input array (see Broadcasting). Otherwise, if False, the reduced axes (dimensions) must not be included in the result. Default = False.

  • output_dtype (Optional[Union[Dtype, NativeDtype]]) – An optional output_dtype from: int32, int64. Defaults to int64. (default: None)

  • out (Optional[Container]) – optional output container, for writing the result to. It must have a shape (default: None) that the inputs broadcast to.

Return type:

Container

Returns:

ret – a container containing the indices of the minimum values across the specified axis.

Examples

Using ivy.Container instance method:

>>> x = ivy.Container(a=ivy.array([0., -1., 2.]), b=ivy.array([3., 4., 5.]))
>>> y = x.argmin()
>>> print(y)
{
    a:ivy.array(1),
    b:ivy.array(0)
}

>>> x = ivy.Container(a=ivy.array([[4., 0., -1.], [2., -3., 6]]),        ...                   b=ivy.array([[1., 2., 3.], [1., 1., 1.]])
>>> y = x.argmin(axis=1, keepdims=True)
>>> print(y)
{
    a: ivy.array([[2],
                  [1]]),
    b: ivy.array([[0],
                  [0]])
}
argwhere(*, key_chains=None, to_apply=True, prune_unapplied=False, map_sequences=False, out=None)[source]#

ivy.Container instance method variant of ivy.argwhere. This method simply wraps the function, and so the docstring for ivy.argwhere also applies to this method with minimal changes.

Parameters:

  • self (Container) – Boolean array, for which indices are desired.

  • key_chains (Optional[Union[List[str], Dict[str, str]]]) – The key-chains to apply or not apply the method to. Default is None. (default: None)

  • to_apply (bool) – If True, the method will be applied to key_chains, otherwise key_chains will (default: True) be skipped. Default is True.

  • prune_unapplied (bool) – Whether to prune key_chains for which the function was not applied. Default (default: False) is False.

  • map_sequences (bool) – Whether to also map method to sequences (lists, tuples). (default: False) Default is False.

Returns:

ret – Indices for where the boolean array is True.

Examples

Using ivy.Container instance method

>>> x = ivy.Container(a=ivy.array([1, 2]), b=ivy.array([3, 4]))
>>> res = x.argwhere()
>>> print(res)
{
    a: ivy.array([[0], [1]]),
    b: ivy.array([[0], [1]])
}

>>> x = ivy.Container(a=ivy.array([1, 0]), b=ivy.array([3, 4]))
>>> res = x.argwhere()
>>> print(res)
{
    a: ivy.array([[0]]),
    b: ivy.array([[0], [1]])
}
nonzero(*, as_tuple=True, size=None, fill_value=0)[source]#

ivy.Container instance method variant of ivy.nonzero. This method simply wraps the function, and so the docstring for ivy.nonzero also applies to this method with minimal changes.

Parameters:

  • self (Container) – input array or container. Should have a numeric data type.

  • as_tuple (bool) – if True, the output is returned as a tuple of indices, one for each (default: True) dimension of the input, containing the indices of the true elements in that dimension. If False, the coordinates are returned in a (N, ndim) array, where N is the number of true elements. Default = True.

  • size (Optional[int]) – if specified, the function will return an array of shape (size, ndim). (default: None) If the number of non-zero elements is fewer than size, the remaining elements will be filled with fill_value. Default = None.

  • fill_value (Number) – when size is specified and there are fewer than size number of elements, (default: 0) the remaining elements in the output array will be filled with fill_value. Default = 0.

Return type:

Container

Returns:

ret – a container containing the indices of the nonzero values.

where(x1, x2, /, *, out=None)[source]#

ivy.Container instance method variant of ivy.where. This method simply wraps the function, and so the docstring for ivy.where also applies to this method with minimal changes.

Parameters:

  • self (Container) – input array or container. Should have a boolean data type.

  • x1 (Union[Container, Array, NativeArray]) – input array or container. Should have a numeric data type.

  • x2 (Union[Container, Array, NativeArray]) – input array or container. Should have a numeric data type.

  • out (Optional[Container]) – optional output container, for writing the result to. It must have a shape (default: None) that the inputs broadcast to.

Return type:

Container

Returns:

ret – a container containing the values of x1 where condition is True, and x2 where condition is False.

Examples

>>> x1 = ivy.Container(a=ivy.array([3, 1, 5]), b=ivy.array([2, 4, 6]))
>>> x2 = ivy.Container(a=ivy.array([0, 7, 2]), b=ivy.array([3, 8, 5]))
>>> res = x1.where((x1.a > x2.a), x2)
>>> print(res)
{
    a: ivy.array([3, 7, 5]),
    b: ivy.array([2, 8, 6])
}