dpnp.fromstring

dpnp.fromstring(string, dtype=<class 'float'>, count=-1, *, sep, like=None, device=None, usm_type='device', sycl_queue=None)[source]

A new 1-D array initialized from text data in a string.

For full documentation refer to numpy.fromstring.

Parameters:
stringstr

A string containing the data.

dtype{None, str, dtype object}, optional

The data type of the array. For binary input data, the data must be in exactly this format. If None, uses a default floating point data type for the device on which the returned array is allocated.

Default: float.

countint, optional

Read this number of dtype elements from the data. If this is negative (the default), the count will be determined from the length of the data.

Default: -1.

sepstr

The string separating numbers in the data; extra whitespace between elements is also ignored.

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.

Default: None.

usm_type{None, "device", "shared", "host"}, optional

The type of SYCL USM allocation for the output array.

Default: "device".

sycl_queue{None, SyclQueue}, optional

A SYCL queue to use for output array allocation and copying. The sycl_queue can be passed as None (the default), which means to get the SYCL queue from device keyword if present or to use a default queue.

Default: None.

Returns:
outdpnp.ndarray

The constructed array.

Limitations

Parameter like is supported only with default value None. Otherwise, the function raises NotImplementedError exception.

See also

dpnp.frombuffer

Construct array from the buffer data.

dpnp.fromfile

Construct array from data in a text or binary file.

dpnp.fromiter

Construct array from an iterable object.

Notes

This uses numpy.fromstring and coerces the result to a DPNP array.

Examples

>>> import dpnp as np
>>> np.fromstring('1 2', dtype=int, sep=' ')
array([1, 2])
>>> np.fromstring('1, 2', dtype=int, sep=',')
array([1, 2])