numpy.polynomial.laguerre.lag2poly(c) [source] Convert a Laguerre series to a polynomial. Convert an array representing the coefficients of a Laguerre series, ordered from lowest degree to highest, to an array of the coefficients of the equivalent polynomial (relative to the ?standard? basis) ordered from lowest to highest degree. Parameters: c : array_like 1-D array containing the Laguerre series coefficients, ordered from lowest order term to highest. Returns: pol : ndarray 1-D arra

numpy.polynomial.hermite_e.poly2herme(pol) [source] Convert a polynomial to a Hermite series. Convert an array representing the coefficients of a polynomial (relative to the ?standard? basis) ordered from lowest degree to highest, to an array of the coefficients of the equivalent Hermite series, ordered from lowest to highest degree. Parameters: pol : array_like 1-D array containing the polynomial coefficients Returns: c : ndarray 1-D array containing the coefficients of the equivalen

class numpy.polynomial.hermite_e.HermiteE(coef, domain=None, window=None) [source] An HermiteE series class. The HermiteE class provides the standard Python numerical methods ?+?, ?-?, ?*?, ?//?, ?%?, ?divmod?, ?**?, and ?()? as well as the attributes and methods listed in the ABCPolyBase documentation. Parameters: coef : array_like HermiteE coefficients in order of increasing degree, i.e, (1, 2, 3) gives 1*He_0(x) + 2*He_1(X) + 3*He_2(x). domain : (2,) array_like, optional Domain to us

numpy.polynomial.hermite_e.hermezero = array([0])

numpy.polynomial.hermite_e.hermex = array([0, 1])

numpy.polynomial.hermite_e.hermeweight(x) [source] Weight function of the Hermite_e polynomials. The weight function is and the interval of integration is . the HermiteE polynomials are orthogonal, but not normalized, with respect to this weight function. Parameters: x : array_like Values at which the weight function will be computed. Returns: w : ndarray The weight function at x. Notes

numpy.polynomial.hermite_e.hermevander3d(x, y, z, deg) [source] Pseudo-Vandermonde matrix of given degrees. Returns the pseudo-Vandermonde matrix of degrees deg and sample points (x, y, z). If l, m, n are the given degrees in x, y, z, then Hehe pseudo-Vandermonde matrix is defined by where 0 <= i <= l, 0 <= j <= m, and 0 <= j <= n. The leading indices of V index the points (x, y, z) and the last index encodes the degrees of the HermiteE polynomials. If V = hermevander3d

numpy.polynomial.hermite_e.hermevander2d(x, y, deg) [source] Pseudo-Vandermonde matrix of given degrees. Returns the pseudo-Vandermonde matrix of degrees deg and sample points (x, y). The pseudo-Vandermonde matrix is defined by where 0 <= i <= deg[0] and 0 <= j <= deg[1]. The leading indices of V index the points (x, y) and the last index encodes the degrees of the HermiteE polynomials. If V = hermevander2d(x, y, [xdeg, ydeg]), then the columns of V correspond to the elements

numpy.polynomial.hermite_e.hermevander(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 HermiteE polynomial. If c is a 1-D array of coefficients of length n + 1 and V is the array V = hermevander(x, n), then np.dot(V, c) and hermeval(x, c) are the

numpy.polynomial.hermite_e.hermeval3d(x, y, z, c) [source] Evaluate a 3-D Hermite_e series at points (x, y, z). This function returns the values: The parameters x, y, and z are converted to arrays only if they are tuples or a lists, otherwise they are treated as a scalars and they must have the same shape after conversion. In either case, either x, y, and z or their elements must support multiplication and addition both with themselves and with the elements of c. If c has fewer than 3 di