numpy.polynomial.hermite.hermvander(x, deg) [source]
Pseudo-Vandermonde matrix of given degree.
Returns the pseudo-Vandermonde matrix of degree deg and sample points x. The pseudo-Vandermonde matrix is defined by
where 0 <= i <= deg. The leading indices of V index the elements of x and the last index is the degree of the Hermite polynomial.
If c is a 1-D array of coefficients of length n + 1 and V is the array V = hermvander(x, n), then np.dot(V, c) and hermval(x, c) are the same up to roundoff. This equivalence is useful both for least squares fitting and for the evaluation of a large number of Hermite series of the same degree and sample points.
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>>> from numpy.polynomial.hermite import hermvander
>>> x = np.array([-1, 0, 1])
>>> hermvander(x, 3)
array([[ 1., -2., 2., 4.],
[ 1., 0., -2., -0.],
[ 1., 2., 2., -4.]])
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https://docs.scipy.org/doc/numpy-1.17.0/reference/generated/numpy.polynomial.hermite.hermvander.html