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astype#

ivy.astype(x, dtype, /, *, copy=True, out=None)[source]#

Copy an array to a specified data type irrespective of type- promotion rules.

Casting floating-point NaN and infinity values to integral data types is not specified and is implementation-dependent.

When casting a boolean input array to a numeric data type, a value of True must cast to a numeric value equal to 1, and a value of False must cast to a numeric value equal to 0.

When casting a numeric input array to bool, a value of 0 must cast to False, and a non-zero value must cast to True.

Parameters:

  • x (Union[Array, NativeArray]) – array to cast.

  • dtype (Union[Dtype, NativeDtype]) – desired data type.

  • copy (bool, default: True) – specifies whether to copy an array when the specified dtype matches the data type of the input array x. If True, a newly allocated array must always be returned. If False and the specified dtype matches the data type of the input array, the input array must be returned; otherwise, a newly allocated must be returned. Default: True.

  • 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 having the specified data type. The returned array must have the same shape as x.

Examples

With ivy.Array input:

>>> x = ivy.array([1, 2])
>>> y = ivy.zeros_like(x)
>>> y = ivy.astype(x, ivy.float64)
>>> print(y)
ivy.array([1., 2.])

>>> x = ivy.array([3.141, 2.718, 1.618])
>>> y = ivy.zeros_like(x)
>>> ivy.astype(x, ivy.int32, out=y)
>>> print(y)
ivy.array([3., 2., 1.])

>>> x = ivy.array([[-1, -2], [0, 2]])
>>> ivy.astype(x, ivy.float64, out=x)
>>> print(x)
ivy.array([[-1., -2.],  [0.,  2.]])

With ivy.NativeArray input:

>>> x = ivy.native_array([3.141, 2.718, 1.618])
>>> y = ivy.astype(x, ivy.int32)
>>> print(y)
ivy.array([3, 2, 1])

With ivy.Container input:

>>> x = ivy.Container(a=ivy.array([0,2,1]),b=ivy.array([1,0,0]))
>>> print(ivy.astype(x, ivy.bool))
{
    a: ivy.array([False, True, True]),
    b: ivy.array([True, False, False])
}

With ivy.Array instance method:

>>> x = ivy.array([[-1, -2], [0, 2]])
>>> print(x.astype(ivy.float64))
ivy.array([[-1., -2.],  [0.,  2.]])

With ivy.Container instance method:

>>> x = ivy.Container(a=ivy.array([False,True,True]),
...                   b=ivy.array([3.14, 2.718, 1.618]))
>>> print(x.astype(ivy.int32))
{
    a: ivy.array([0, 1, 1]),
    b: ivy.array([3, 2, 1])
}
Array.astype(self, dtype, /, *, copy=True, out=None)[source]#

Copy an array to a specified data type irrespective of type- promotion rules.

Casting floating-point NaN and infinity values to integral data types is not specified and is implementation-dependent.

When casting a boolean input array to a numeric data type, a value of True must cast to a numeric value equal to 1, and a value of False must cast to a numeric value equal to 0.

When casting a numeric input array to bool, a value of 0 must cast to False, and a non-zero value must cast to True.

Parameters:

  • self (Array) – array to cast.

  • dtype (Dtype) – desired data type.

  • copy (bool, default: True) – specifies whether to copy an array when the specified dtype matches the data type of the input array x. If True, a newly allocated array must always be returned. If False and the specified dtype matches the data type of the input array, the input array must be returned; otherwise, a newly allocated must be returned. Default: True.

  • 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 having the specified data type. The returned array must have the same shape as x.

Examples

Using ivy.Array instance method:

>>> x = ivy.array([[-1, -2], [0, 2]])
>>> print(x.astype(ivy.float64))
ivy.array([[-1., -2.],  [0.,  2.]])
Container.astype(self, dtype, key_chains=None, to_apply=True, prune_unapplied=False, map_sequences=False, *, copy=True, out=None)[source]#

Copy an array to a specified data type irrespective of type- promotion rules.

Casting floating-point NaN and infinity values to integral data types is not specified and is implementation-dependent.

When casting a boolean input array to a numeric data type, a value of True must cast to a numeric value equal to 1, and a value of False must cast to a numeric value equal to 0.

When casting a numeric input array to bool, a value of 0 must cast to False, and a non-zero value must cast to True.

Parameters:

  • self (Container) – array to cast.

  • dtype (Union[Dtype, Container]) – desired data type.

  • copy (Union[bool, Container], default: True) – specifies whether to copy an array when the specified dtype matches the data type of the input array x. If True, a newly allocated array must always be returned. If False and the specified dtype matches the data type of the input array, the input array must be returned; otherwise, a newly allocated must be returned. Default: True.

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

Return type:

Container

Returns:

ret – an array having the specified data type. The returned array must have the same shape as x.

Examples

Using ivy.Container instance method:

>>> x = ivy.Container(a=ivy.array([False,True,True]),
...                   b=ivy.array([3.14, 2.718, 1.618]))
>>> print(x.astype(ivy.int32))
{
    a: ivy.array([0, 1, 1]),
    b: ivy.array([3, 2, 1])
}
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