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numpy.polynomial.hermite.hermvander2d

# numpy.polynomial.hermite.hermvander

`numpy.polynomial.hermite.``hermvander`(x, deg)

  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.

  Parameters: | x : array_like Array of points. The dtype is converted to float64 or complex128 depending on whether any of the elements are complex. If x is scalar it is converted to a 1-D array. deg : int Degree of the resulting matrix.
  Returns: | vander : ndarray The pseudo-Vandermonde matrix. The shape of the returned matrix is `x.shape + (deg + 1,)`, where The last index is the degree of the corresponding Hermite polynomial. The dtype will be the same as the converted x.

  Examples

      >>> 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.]])