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numpy.polynomial.laguerre.lagvander2d

# numpy.polynomial.laguerre.lagvander

`numpy.polynomial.laguerre.``lagvander`(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 Laguerre polynomial.

  If c is a 1-D array of coefficients of length n + 1 and V is the array `V = lagvander(x, n)`, then `np.dot(V, c)` and `lagval(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 Laguerre 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 Laguerre polynomial. The dtype will be the same as the converted x.

  Examples

      >>> from numpy.polynomial.laguerre import lagvander
      >>> x = np.array([0, 1, 2])
      >>> lagvander(x, 3)
      array([[ 1.        ,  1.        ,  1.        ,  1.        ],
             [ 1.        ,  0.        , -0.5       , -0.66666667],
             [ 1.        , -1.        , -1.        , -0.33333333]])