numpy.polynomial.hermite_e.hermeint()

Integrate a Hermite_e series.

Returns the Hermite_e series coefficients c integrated m times from lbnd along axis. At each iteration the resulting series is multiplied by scl and an integration constant, k, is added. The scaling factor is for use in a linear change of variable. (?Buyer beware?: note that, depending on what one is doing, one may want scl to be the reciprocal of what one might expect; for more information, see the Notes section below.) The argument c is an array of coefficients from low to high degree along each axis, e.g., [1,2,3] represents the series H_0 + 2*H_1 + 3*H_2 while [[1,2],[1,2]] represents 1*H_0(x)*H_0(y) + 1*H_1(x)*H_0(y) + 2*H_0(x)*H_1(y) + 2*H_1(x)*H_1(y) if axis=0 is x and axis=1 is y.

Notes

Note that the result of each integration is multiplied by scl. Why is this important to note? Say one is making a linear change of variable in an integral relative to x. Then .. math::dx = du/a, so one will need to set scl equal to - perhaps not what one would have first thought.

Also note that, in general, the result of integrating a C-series needs to be ?reprojected? onto the C-series basis set. Thus, typically, the result of this function is ?unintuitive,? albeit correct; see Examples section below.

Examples

>>> from numpy.polynomial.hermite_e import hermeint
>>> hermeint([1, 2, 3]) # integrate once, value 0 at 0.
array([ 1.,  1.,  1.,  1.])
>>> hermeint([1, 2, 3], m=2) # integrate twice, value & deriv 0 at 0
array([-0.25      ,  1.        ,  0.5       ,  0.33333333,  0.25      ])
>>> hermeint([1, 2, 3], k=1) # integrate once, value 1 at 0.
array([ 2.,  1.,  1.,  1.])
>>> hermeint([1, 2, 3], lbnd=-1) # integrate once, value 0 at -1
array([-1.,  1.,  1.,  1.])
>>> hermeint([1, 2, 3], m=2, k=[1, 2], lbnd=-1)
array([ 1.83333333,  0.        ,  0.5       ,  0.33333333,  0.25      ])