numpy.polynomial.polynomial.polyvalfromroots(x, r, tensor=True)
[source]
Evaluate a polynomial specified by its roots at points x.
If r
is of length N
, this function returns the value
The parameter x
is converted to an array only if it is a tuple or a list, otherwise it is treated as a scalar. In either case, either x
or its elements must support multiplication and addition both with themselves and with the elements of r
.
If r
is a 1-D array, then p(x)
will have the same shape as x
. If r
is multidimensional, then the shape of the result depends on the value of tensor
. If tensor is ``True`
the shape will be r.shape[1:] + x.shape; that is, each polynomial is evaluated at every value of x
. If tensor
is False
, the shape will be r.shape[1:]; that is, each polynomial is evaluated only for the corresponding broadcast value of x
. Note that scalars have shape (,).
New in version 1.12.
Parameters: |
|
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Returns: |
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See also
>>> 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.])
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https://docs.scipy.org/doc/numpy-1.17.0/reference/generated/numpy.polynomial.polynomial.polyvalfromroots.html