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Fonction equal - module numpy

Signature de la fonction equal

Description

equal.__doc__

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])