equal
==========

.. currentmodule:: treetensor.numpy

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

.. autofunction:: equal

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

    This documentation is based on 
    `numpy.equal <https://numpy.org/doc/1.21/reference/generated/numpy.equal.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:: equal(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj])


Return (x1 == x2) element-wise.

Parameters
~~~~~~~~~~
x1, x2 \: array_like
    Input arrays.
    If ``x1.shape != x2.shape``, they must be broadcastable to a common
    shape (which becomes the shape of the output).
out \: ndarray, None, or tuple of ndarray and None, optional
    A location into which the result is stored. If provided, it must have
    a shape that the inputs broadcast to. If not provided or None,
    a freshly-allocated array is returned. A tuple (possible only as a
    keyword argument) must have length equal to the number of outputs.
where \: array_like, optional
    This condition is broadcast over the input. At locations where the
    condition is True, the `out` array will be set to the ufunc result.
    Elsewhere, the `out` array will retain its original value.
    Note that if an uninitialized `out` array is created via the default
    ``out=None``, locations within it where the condition is False will
    remain uninitialized.
**kwargs
    For other keyword-only arguments, see the
    :ref:`ufunc docs <ufuncs.kwargs>`.

Returns
~~~~~~~
out \: ndarray or scalar
    Output array, element-wise comparison of `x1` and `x2`.
    Typically of type bool, unless ``dtype=object`` is passed.
    This is a scalar if both `x1` and `x2` are scalars.

See Also
~~~~~~~~
not_equal, greater_equal, less_equal, greater, less

Examples
~~~~~~~~
>>> np.equal([0, 1, 3], np.arange(3))
array([ True,  True, False])

What is compared are values, not types. So an int (1) and an array of
length one can evaluate as True:

>>> np.equal(1, np.ones(1))
array([ True])

The ``==`` operator can be used as a shorthand for ``np.equal`` on
ndarrays.

>>> a = np.array([2, 4, 6])
>>> b = np.array([2, 4, 2])
>>> a == b
array([ True,  True, False])