alars have dimension 0 for this
    action. The result is that every column of coefficients in `r` is
    evaluated for every element of `x`. If False, `x` is broadcast over the
    columns of `r` for the evaluation.  This keyword is useful when `r` is
    multidimensional. The default value is True.

Returns
-------
values : ndarray, compatible object
    The shape of the returned array is described above.

See Also
--------
polyroots, polyfromroots, polyval

Examples
--------
>>> from numpy.polynomial.polynomial import polyvalfromroots
>>> polyvalfromroots(1, [1, 2, 3])
0.0
>>> a = np.arange(4).reshape(2, 2)
>>> a
array([[0, 1],
       [2, 3]])
>>> polyvalfromroots(a, [-1, 0, 1])
array([[-0.,   0.],
       [ 6.,  24.]])
>>> r = np.arange(-2, 2).reshape(2,2)  # multidimensional coefficients
>>> r # each column of r defines one polynomial
array([[-2, -1],
       [ 0,  1]])
>>> b = [-2, 1]
>>> polyvalfromroots(b, r, tensor=True)
array([[-0.,  3.],
       [ 3., 0.]])
>>> polyvalfromroots(b, r, tensor=False)
array([-0.,  0.])

r 