numpy.polynomial.hermite.hermvander
-
numpy.polynomial.hermite.hermvander(x, deg)[source] -
Pseudo-Vandermonde matrix of given degree.
Returns the pseudo-Vandermonde matrix of degree
degand sample pointsx. The pseudo-Vandermonde matrix is defined by![V[..., i] = H_i(x),](https://docs.scipy.org/doc/numpy-1.10.1/_images/math/faca8896a4770863f653aa77b99c1f16ce4c84eb.png)
where
0 <= i <= deg. The leading indices ofVindex the elements ofxand the last index is the degree of the Hermite polynomial.If
cis a 1-D array of coefficients of lengthn + 1andVis the arrayV = hermvander(x, n), thennp.dot(V, c)andhermval(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
xis 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 convertedx.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.]])
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https://docs.scipy.org/doc/numpy-1.10.1/reference/generated/numpy.polynomial.hermite.hermvander.html