numpy.polynomial.hermite_e.hermeint
-
numpy.polynomial.hermite_e.hermeint(c, m=1, k=[], lbnd=0, scl=1, axis=0)
[source] -
Integrate a Hermite_e series.
Returns the Hermite_e series coefficients
c
integratedm
times fromlbnd
alongaxis
. At each iteration the resulting series is multiplied byscl
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 wantscl
to be the reciprocal of what one might expect; for more information, see the Notes section below.) The argumentc
is an array of coefficients from low to high degree along each axis, e.g., [1,2,3] represents the seriesH_0 + 2*H_1 + 3*H_2
while [[1,2],[1,2]] represents1*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 isx
and axis=1 isy
.Parameters: -
c : array_like
-
Array of Hermite_e series coefficients. If c is multidimensional the different axis correspond to different variables with the degree in each axis given by the corresponding index.
-
m : int, optional
-
Order of integration, must be positive. (Default: 1)
-
k : {[], list, scalar}, optional
-
Integration constant(s). The value of the first integral at
lbnd
is the first value in the list, the value of the second integral atlbnd
is the second value, etc. Ifk == []
(the default), all constants are set to zero. Ifm == 1
, a single scalar can be given instead of a list. -
lbnd : scalar, optional
-
The lower bound of the integral. (Default: 0)
-
scl : scalar, optional
-
Following each integration the result is multiplied by
scl
before the integration constant is added. (Default: 1) -
axis : int, optional
-
Axis over which the integral is taken. (Default: 0).
New in version 1.7.0.
Returns: -
S : ndarray
-
Hermite_e series coefficients of the integral.
Raises: - ValueError
-
If
m < 0
,len(k) > m
,np.ndim(lbnd) != 0
, ornp.ndim(scl) != 0
.
See also
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 variablein an integral relative to
x
. Then, 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 ]) # may vary >>> 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 ]) # may vary
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Licensed under the 3-clause BSD License.
https://docs.scipy.org/doc/numpy-1.17.0/reference/generated/numpy.polynomial.hermite_e.hermeint.html