funcs.all.auto.rst.txt

all
========

.. currentmodule:: treetensor.numpy

    
Documentation
------------------

.. autofunction:: all

    
.. admonition:: Numpy Version Related
    :class: tip

    This documentation is based on 
    `numpy.all <https://numpy.org/doc/1.21/reference/generated/numpy.all.html>`_ 
    in `numpy v1.21.6 <https://numpy.org/doc/1.21/>`_.
    **Its arguments' arrangements depend on the version of numpy you installed**.
    
    If some arguments listed here are not working properly, please check your numpy's version 
    with the following command and find its documentation.
    
    .. code-block:: shell
        :linenos:
    
        python -c 'import numpy as np;print(np.__version__)'
    
    
    
    The arguments and keyword arguments supported in numpy v1.21.6 is listed below.
    
    

Description From Numpy v1.21
---------------------------------

.. currentmodule:: numpy

    
.. function:: Test whether all array elements along a given axis evaluate to True.


Parameters
~~~~~~~~~~
    a \: array_like
        Input array or object that can be converted to an array.
    axis \: None or int or tuple of ints, optional
        Axis or axes along which a logical AND reduction is performed.
        The default (``axis=None``) is to perform a logical AND over all
        the dimensions of the input array. `axis` may be negative, in
        which case it counts from the last to the first axis.

        .. versionadded:: 1.7.0

        If this is a tuple of ints, a reduction is performed on multiple
        axes, instead of a single axis or all the axes as before.
    out \: ndarray, optional
        Alternate output array in which to place the result.
        It must have the same shape as the expected output and its
        type is preserved (e.g., if ``dtype(out)`` is float, the result
        will consist of 0.0's and 1.0's). See :ref:`ufuncs-output-type` for more
        details.

    keepdims \: bool, optional
        If this is set to True, the axes which are reduced are left
        in the result as dimensions with size one. With this option,
        the result will broadcast correctly against the input array.

        If the default value is passed, then `keepdims` will not be
        passed through to the `all` method of sub-classes of
        `ndarray`, however any non-default value will be.  If the
        sub-class' method does not implement `keepdims` any
        exceptions will be raised.

    where \: array_like of bool, optional
        Elements to include in checking for all `True` values.
        See `~numpy.ufunc.reduce` for details.

        .. versionadded:: 1.20.0

Returns
~~~~~~~
    all \: ndarray, bool
        A new boolean or array is returned unless `out` is specified,
        in which case a reference to `out` is returned.

See Also
~~~~~~~~
    ndarray.all \: equivalent method

    any \: Test whether any element along a given axis evaluates to True.

Notes
~~~~~
    Not a Number (NaN), positive infinity and negative infinity
    evaluate to `True` because these are not equal to zero.

Examples
~~~~~~~~
    >>> np.all([[True,False],[True,True]])
    False

    >>> np.all([[True,False],[True,True]], axis=0)
    array([ True, False])

    >>> np.all([-1, 4, 5])
    True

    >>> np.all([1.0, np.nan])
    True

    >>> np.all([[True, True], [False, True]], where=[[True], [False]])
    True

    >>> o=np.array(False)
    >>> z=np.all([-1, 4, 5], out=o)
    >>> id(z), id(o), z
    (28293632, 28293632, array(True)) # may vary