trunc_divide#

ivy.trunc_divide(x1, x2, /, *, out=None)[source]#

Perform element-wise integer division of the inputs rounding the results towards zero.

Parameters:

x1 (Union[float, Array, NativeArray]) – dividend input array. Should have a numeric data type.
x2 (Union[float, Array, NativeArray]) – divisor input array. Must be compatible with x1 (see Broadcasting). Should have a numeric data type.
out (Optional[Array], default: None) – optional output array, for writing the result to. It must have a shape that the inputs broadcast to.

Return type:

Array

Returns:

ret – an array containing the element-wise results. The returned array must have a floating-point data type determined by Type Promotion Rules.

Examples

With ivy.Array inputs:

>>> x1 = ivy.array([2., 7., 9.])
>>> x2 = ivy.array([3., -4., 0.6])
>>> y = ivy.trunc_divide(x1, x2)
>>> print(y)
ivy.array([ 0., -1., 14.])

Array.trunc_divide(self, x2, /, *, out=None)[source]#

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

Parameters:

self (Array) – dividend input array. Should have a real-valued data type.
x2 (Union[Array, NativeArray]) – divisor input array. Must be compatible with self (see broadcasting). Should have a real-valued data type.
out (Optional[Array], default: None) – optional output array, for writing the result to. It must have a shape that the inputs broadcast to.

Return type:

Array

Returns:

ret – an array containing the element-wise results. The returned array must have a data type determined by type-promotion.

Examples

With ivy.Array inputs:

>>> x1 = ivy.array([2., 7., 9.])
>>> x2 = ivy.array([2., -2., 2.])
>>> y = x1.trunc_divide(x2)
>>> print(y)
ivy.array([ 1., -3.,  4.])

Container.trunc_divide(self, x2, /, *, key_chains=None, to_apply=True, prune_unapplied=False, map_sequences=False, out=None)[source]#

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

Parameters:

self (Container) – dividend input array or container. Should have a real-valued data type.
x2 (Union[Container, Array, NativeArray]) – divisor input array or container. Must be compatible with self (see broadcasting). Should have a real-valued data type.
key_chains (Optional[Union[List[str], Dict[str, str], Container]], default: None) – The key-chains to apply or not apply the method to. Default is None.
to_apply (Union[bool, Container], default: True) – If True, the method will be applied to key_chains, otherwise key_chains will be skipped. Default is True.
prune_unapplied (Union[bool, Container], default: False) – Whether to prune key_chains for which the function was not applied. Default is False.
map_sequences (Union[bool, Container], default: False) – Whether to also map method to sequences (lists, tuples). Default is False.
out (Optional[Container], default: None) – optional output container, for writing the result to. It must have a shape that the inputs broadcast to.

Return type:

Container

Returns:

ret – a container containing the element-wise results. The returned container must have a data type determined by type-promotion.

Examples

With ivy.Container inputs:

>>> x1 = ivy.Container(a=ivy.array([12., 3.5, 6.3]), b=ivy.array([3., 1., 9.]))
>>> x2 = ivy.Container(a=ivy.array([1., 2.3, -3]), b=ivy.array([2.4, 3., -2.]))
>>> y = x1.trunc_divide(x2)
>>> print(y)
{
    a: ivy.array([12., 1., -2.]),
    b: ivy.array([1., 0., -4.])
}