numpy.polynomial.laguerre.lagvander(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 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: |
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Returns: |
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>>> 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]])
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https://docs.scipy.org/doc/numpy-1.17.0/reference/generated/numpy.polynomial.laguerre.lagvander.html