Classe « ndarray »

Méthode numpy.matlib.ndarray.tolist

Signature de la méthode tolist

Description

tolist.__doc__

a.tolist()

    Return the array as an ``a.ndim``-levels deep nested list of Python scalars.

    Return a copy of the array data as a (nested) Python list.
    Data items are converted to the nearest compatible builtin Python type, via
    the `~numpy.ndarray.item` function.

    If ``a.ndim`` is 0, then since the depth of the nested list is 0, it will
    not be a list at all, but a simple Python scalar.

    Parameters
    ----------
    none

    Returns
    -------
    y : object, or list of object, or list of list of object, or ...
        The possibly nested list of array elements.

    Notes
    -----
    The array may be recreated via ``a = np.array(a.tolist())``, although this
    may sometimes lose precision.

    Examples
    --------
    For a 1D array, ``a.tolist()`` is almost the same as ``list(a)``,
    except that ``tolist`` changes numpy scalars to Python scalars:

    >>> a = np.uint32([1, 2])
    >>> a_list = list(a)
    >>> a_list
    [1, 2]
    >>> type(a_list[0])
    <class 'numpy.uint32'>
    >>> a_tolist = a.tolist()
    >>> a_tolist
    [1, 2]
    >>> type(a_tolist[0])
    <class 'int'>

    Additionally, for a 2D array, ``tolist`` applies recursively:

    >>> a = np.array([[1, 2], [3, 4]])
    >>> list(a)
    [array([1, 2]), array([3, 4])]
    >>> a.tolist()
    [[1, 2], [3, 4]]

    The base case for this recursion is a 0D array:

    >>> a = np.array(1)
    >>> list(a)
    Traceback (most recent call last):
      ...
    TypeError: iteration over a 0-d array
    >>> a.tolist()
    1