Searching

ivy.argmax(x, axis=None, keepdims=False, *, out=None)[source]

Returns the indices of the maximum values along a specified axis. When the maximum value occurs multiple times, only the indices corresponding to the first occurrence are returned.

Parameters

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

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

  • keepdims (Optional[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.

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

Return type

Union[Array, int]

Returns

ret – if axis is None, a zero-dimensional array containing the index of the first occurrence of the maximum value; otherwise, a non-zero-dimensional array containing the indices of the maximum values. The returned array must have be the default array index data type.

Functional Examples

With ivy.Array input:

>>> x = ivy.array([-0., 1., -1.])
>>> y = ivy.argmax(x)
>>> print(y)
ivy.array([1])

>>> x = ivy.array([-0., 1., -1.])
>>> ivy.argmax(x,out=x)
>>> print(x)
ivy.array([1])

>>> x=ivy.array([[1., -0., -1.],                      [-2., 3., 2.]])
>>> y = ivy.argmax(x, axis= 1)
>>> print(y)
ivy.array([0, 1])

>>> x=ivy.array([[4., 0., -1.],                      [2., -3., 6]])
>>> y = ivy.argmax(x, axis= 1, keepdims= True)
>>> print(y)
ivy.array([[0],               [2]])

>>> x=ivy.array([[4., 0., -1.],                      [2., -3., 6],                      [2., -3., 6]])
>>> z= ivy.zeros((1,3), dtype=ivy.int64)
>>> y = ivy.argmax(x, axis= 1, keepdims= True, out= z)
>>> print(z)
ivy.array([[0],                [2],                [2]])

With ivy.NativeArray input:

>>> x = ivy.native_array([-0., 1., -1.])
>>> y = ivy.argmax(x)
>>> print(y)
ivy.array([1])

Instance Method Examples

Using ivy.Array instance method:

>>> x = ivy.array([0., 1., 2.])
>>> y = x.argmax()
>>> print(y)
ivy.array(2)
ivy.argmin(x, axis=None, keepdims=False, *, out=None)[source]

Returns the indices of the minimum values along a specified axis. When the minimum value occurs multiple times, only the indices corresponding to the first occurrence are returned.

Parameters

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

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

  • keepdims (Optional[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.

  • out (Optional[Array]) – if axis is None, a zero-dimensional array containing the index of the first (default: None) occurrence of the minimum value; otherwise, a non-zero-dimensional array containing the indices of the minimum values. The returned array must have the default array index data type.

Return type

Union[Array, int]

Returns

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

Functional Examples

With ivy.Array input:

>>> x = ivy.array([0., 1., -1.])
>>> y = ivy.argmin(x)
>>> print(y)
ivy.array(2)

>>> x=ivy.array([[0., 1., -1.],[-2., 1., 2.]])
>>> y = ivy.argmin(x, axis= 1)
>>> print(y)
ivy.array([2, 0])

>>> x=ivy.array([[0., 1., -1.],[-2., 1., 2.]])
>>> y = ivy.argmin(x, axis= 1, keepdims= True)
>>> print(y)
ivy.array([[2],
          [0]])

>>> x=ivy.array([[0., 1., -1.],[-2., 1., 2.],[1., -2., 0.]])
>>> y= ivy.zeros((1,3), dtype=ivy.int64)
>>> ivy.argmin(x, axis= 1, keepdims= True, out= y)
>>> print(y)
ivy.array([[2],
           [0],
           [1]])

With ivy.NativeArray input:

>>> x = ivy.native_array([0., 1., -1.])
>>> y = ivy.argmin(x)
>>> print(y)
ivy.array(2)

With ivy.Container input:

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

Instance Method Examples

Using ivy.Array instance method:

>>> x = ivy.array([0., 1., -1.])
>>> y = x.argmin()
>>> print(y)
ivy.array(2)

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)}
ivy.nonzero(x)[source]

Returns the indices of the array elements which are non-zero.

Parameters

x (Union[Array, NativeArray]) – input array. Must have a positive rank. If x is zero-dimensional, the function must raise an exception.

Return type

Tuple[Array]

Returns

ret – a tuple of k arrays, one for each dimension of x and each of size n (where n is the total number of non-zero elements), containing the indices of the non-zero elements in that dimension. The indices must be returned in row-major, C-style order. The returned array must have the default array index data type.

Functional Examples

With ivy.Array input:

>>> x = ivy.array([0, 10, 15, 20, -50, 0])
>>> y = ivy.nonzero(x)
>>> print(y)
(ivy.array([1, 2, 3, 4]),)

>>> x = ivy.array([[1, 2], [-1, -2]])
>>> y = ivy.nonzero(x)
>>> print(y)
(ivy.array([0, 0, 1, 1]), ivy.array([0, 1, 0, 1]))

With ivy.NativeArray input:

>>> x = ivy.native_array([[10, 20], [10, 0], [0, 0]])
>>> y = ivy.nonzero(x)
>>> print(y)
(ivy.array([0, 0, 1]), ivy.array([0, 1, 0]))

>>> x = ivy.native_array([[0], [1], [1], [0], [1]])
>>> y = ivy.nonzero(x)
>>> print(y)
(ivy.array([1, 2, 4]), ivy.array([0, 0, 0]))

With ivy.Container input:

>>> x = ivy.Container(a=ivy.array([0,1,2,3,0]), b=ivy.array([[1,1], [0,0]]))
>>> y = ivy.nonzero(x)
>>> print(y)
{
    a: (list[1], <class ivy.array.array.Array> shape=[3]),
    b: (list[2], <class ivy.array.array.Array> shape=[2])
}

>>> print(y.a)
(ivy.array([1, 2, 3]),)

>>> print(y.b)
(ivy.array([0, 0]), ivy.array([0, 1]))

Instance Method Examples

Using ivy.Array instance method:

>>> x = ivy.array([0,0,0,1,1,1])
>>> y = x.nonzero()
>>> print(y)
(ivy.array([3, 4, 5]),)

Using ivy.NativeArray instance method:

>>> x = ivy.native_array([[1,1], [0,0], [1,1]])
>>> y = x.nonzero()
>>> print(y)
tensor([[0,0],[0,1],[2,0],[2,1]])

Using ivy.Container instance method:

>>> x = ivy.Container(a=ivy.array([1,1,1]), b=ivy.native_array([0]))
>>> y = x.nonzero()
>>> print(y)
{
    a: (list[1], <class ivy.array.array.Array> shape=[3]),
    b: (list[1], <class ivy.array.array.Array> shape=[0])
}

>>> print(y.a)
(ivy.array([0, 1, 2]),)

>>> print(y.b)
(ivy.array([]),)
ivy.where(condition, x1, x2, *, out=None)[source]

Returns elements chosen from x or y depending on condition.

Parameters

  • condition (Union[Array, NativeArray]) – Where True, yield x1, otherwise yield x2.

  • x1 (Union[Array, NativeArray]) – values from which to choose when condition is True.

  • x2 (Union[Array, NativeArray]) – values from which to choose when condition is False.

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

Return type

Array

Returns

ret – An array with elements from x1 where condition is True, and elements from x2 elsewhere.

Functional Examples

With ivy.Array input:

>>> condition = ivy.array([[True, False], [True, True]])
>>> x1 = ivy.array([[1, 2], [3, 4]])
>>> x2 = ivy.array([[5, 6], [7, 8]])
>>> res = ivy.where(condition, x1, x2)
>>> print(res)
ivy.array([[1,6],[3,4]])

With ivy.NativeArray input:

>>> condition = ivy.array([[True, False], [False, True]])
>>> x1 = ivy.native_array([[1, 2], [3, 4]])
>>> x2 = ivy.native_array([[5, 6], [7, 8]])
>>> res = ivy.where(condition, x1, x2)
>>> print(res)
array([[1, 6], [7, 4]])

With a mix of ivy.Array and ivy.NativeArray inputs:

>>> x1 = ivy.array([[6, 13, 22, 7, 12], [7, 11, 16, 32, 9]])
>>> x2 = ivy.native_array([[44, 20, 8, 35, 9], [98, 23, 43, 6, 13]])
>>> res = ivy.where(((x1 % 2 == 0) & (x2 % 2 == 1)), x1, x2)
>>> print(res)
ivy.array([[ 44, 20, 8, 35, 12], [98, 23, 16, 6, 13]])

With ivy.Container input:

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

With a mix of ivy.Array and ivy.Container inputs:

>>> x1 = ivy.array([[1.1, 2, -3.6], [5, 4, 3.1]])
>>> x2 = ivy.Container(a=ivy.array([0, 7, 2]),b=ivy.array([3, 8, 5]))
>>> res = ivy.where((x1.b < x2.b), x1, x2)
>>> print(res)
{
    a: ivy.array([0, 2, -3.6]),
    b: ivy.array([3, 4, 3.1])
}

Instance Method Examples

With ivy.Array input:

>>> condition = ivy.array([[True, False], [True, True]])
>>> x1 = ivy.array([[1, 2], [3, 4]])
>>> x2 = ivy.array([[5, 6], [7, 8]])
>>> res = x1.where(condition,x2)
>>> print(res)
ivy.array([[1, 6], [3, 4]])

With ivy.Container input:

>>> 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])
}