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Fonction require - module numpy.matlib

Signature de la fonction require

def require(a, dtype=None, requirements=None, *, like=None) 

Description

require.__doc__

    Return an ndarray of the provided type that satisfies requirements.

    This function is useful to be sure that an array with the correct flags
    is returned for passing to compiled code (perhaps through ctypes).

    Parameters
    ----------
    a : array_like
       The object to be converted to a type-and-requirement-satisfying array.
    dtype : data-type
       The required data-type. If None preserve the current dtype. If your
       application requires the data to be in native byteorder, include
       a byteorder specification as a part of the dtype specification.
    requirements : str or list of str
       The requirements list can be any of the following

       * 'F_CONTIGUOUS' ('F') - ensure a Fortran-contiguous array
       * 'C_CONTIGUOUS' ('C') - ensure a C-contiguous array
       * 'ALIGNED' ('A')      - ensure a data-type aligned array
       * 'WRITEABLE' ('W')    - ensure a writable array
       * 'OWNDATA' ('O')      - ensure an array that owns its own data
       * 'ENSUREARRAY', ('E') - ensure a base array, instead of a subclass
    like : array_like
        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.

        .. note::
            The ``like`` keyword is an experimental feature pending on
            acceptance of :ref:`NEP 35 <NEP35>`.

        .. versionadded:: 1.20.0

    Returns
    -------
    out : ndarray
        Array with specified requirements and type if given.

    See Also
    --------
    asarray : Convert input to an ndarray.
    asanyarray : Convert to an ndarray, but pass through ndarray subclasses.
    ascontiguousarray : Convert input to a contiguous array.
    asfortranarray : Convert input to an ndarray with column-major
                     memory order.
    ndarray.flags : Information about the memory layout of the array.

    Notes
    -----
    The returned array will be guaranteed to have the listed requirements
    by making a copy if needed.

    Examples
    --------
    >>> x = np.arange(6).reshape(2,3)
    >>> x.flags
      C_CONTIGUOUS : True
      F_CONTIGUOUS : False
      OWNDATA : False
      WRITEABLE : True
      ALIGNED : True
      WRITEBACKIFCOPY : False
      UPDATEIFCOPY : False

    >>> y = np.require(x, dtype=np.float32, requirements=['A', 'O', 'W', 'F'])
    >>> y.flags
      C_CONTIGUOUS : False
      F_CONTIGUOUS : True
      OWNDATA : True
      WRITEABLE : True
      ALIGNED : True
      WRITEBACKIFCOPY : False
      UPDATEIFCOPY : False