dpnp.ndarray.astype

method

ndarray.astype(dtype, order='K', casting='unsafe', subok=True, copy=True, device=None)

Copy the array with data type casting.

Refer to dpnp.astype for full documentation.

Parameters:
dtype{None, str, dtype object}

Target data type.

order{None, "C", "F", "A", "K"}, optional

Row-major (C-style) or column-major (Fortran-style) order. When order is "A", it uses "F" if a is column-major and uses "C" otherwise. And when order is "K", it keeps strides as closely as possible.

Default: "K".

casting{"no", "equiv", "safe", "same_kind", "unsafe"}, optional

Controls what kind of data casting may occur. Defaults to "unsafe" for backwards compatibility.

  • "no" means the data types should not be cast at all.

  • "equiv" means only byte-order changes are allowed.

  • "safe" means only casts which can preserve values are allowed.

  • "same_kind" means only safe casts or casts within a kind, like float64 to float32, are allowed.

  • "unsafe" means any data conversions may be done.

Default: "unsafe".

copybool, optional

Specifies whether to copy an array when the specified dtype matches the data type of that array. If True, a newly allocated array must always be returned. If False and the specified dtype matches the data type of that array, the self array must be returned; otherwise, a newly allocated array must be returned.

Default: True.

device{None, string, SyclDevice, SyclQueue, Device}, optional

An array API concept of device where the output array is created. device can be None, a oneAPI filter selector string, an instance of dpctl.SyclDevice corresponding to a non-partitioned SYCL device, an instance of dpctl.SyclQueue, or a dpnp.tensor.Device object returned by dpnp.ndarray.device. If the value is None, returned array is created on the same device as that array.

Default: None.

Returns:
outdpnp.ndarray

An array having the specified data type.

Limitations

Parameter subok is supported with default value. Otherwise NotImplementedError exception will be raised.

Examples

>>> import dpnp as np
>>> x = np.array([1, 2, 2.5]); x
array([1. , 2. , 2.5])

>>> x.astype(int)
array([1, 2, 2])