xorbits.numpy.fromstring#

xorbits.numpy.fromstring(string, dtype=float, count=- 1, *, sep, like=None)#

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

Parameters
  • string (str) – A string containing the data.

  • dtype (data-type, optional) –

    The data type of the array; default: float. For binary input data, the data must be in exactly this format. Most builtin numeric types are supported and extension types may be supported.

    New in version 1.18.0(numpy): Complex dtypes.

  • count (int, 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.

  • sep (str, optional) –

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

    Deprecated since version 1.14(numpy): Passing sep='', the default, is deprecated since it will trigger the deprecated binary mode of this function. This mode interprets string as binary bytes, rather than ASCII text with decimal numbers, an operation which is better spelt frombuffer(string, dtype, count). If string contains unicode text, the binary mode of fromstring will first encode it into bytes using utf-8, which will not produce sane results.

  • like (array_like, optional) –

    Reference object to allow the creation of arrays which are not NumPy arrays. If an array-like passed in as like supports the __array_function__ protocol, the result will be defined by it. In this case, it ensures the creation of an array object compatible with that passed in via this argument.

    New in version 1.20.0(numpy).

Returns

arr – The constructed array.

Return type

ndarray

Raises

ValueError – If the string is not the correct size to satisfy the requested dtype and count.

Examples

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

Warning

This method has not been implemented yet. Xorbits will try to execute it with numpy.

This docstring was copied from numpy.