numpy.polynomial.legendre.legint(c, m=1, k=[], lbnd=0, scl=1, axis=0)
[source]
Integrate a Legendre series.
Returns the Legendre 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 L_0 + 2*L_1 + 3*L_2
while [[1,2],[1,2]] represents 1*L_0(x)*L_0(y) + 1*L_1(x)*L_0(y) + 2*L_0(x)*L_1(y) +
2*L_1(x)*L_1(y)
if axis=0 is x
and axis=1 is y
.
Parameters: 


Returns: 

Raises: 

See also
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 , 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 Cseries needs to be “reprojected” onto the Cseries basis set. Thus, typically, the result of this function is “unintuitive,” albeit correct; see Examples section below.
>>> from numpy.polynomial import legendre as L >>> c = (1,2,3) >>> L.legint(c) array([ 0.33333333, 0.4 , 0.66666667, 0.6 ]) # may vary >>> L.legint(c, 3) array([ 1.66666667e02, 1.78571429e02, 4.76190476e02, # may vary 1.73472348e18, 1.90476190e02, 9.52380952e03]) >>> L.legint(c, k=3) array([ 3.33333333, 0.4 , 0.66666667, 0.6 ]) # may vary >>> L.legint(c, lbnd=2) array([ 7.33333333, 0.4 , 0.66666667, 0.6 ]) # may vary >>> L.legint(c, scl=2) array([ 0.66666667, 0.8 , 1.33333333, 1.2 ]) # may vary
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https://docs.scipy.org/doc/numpy1.17.0/reference/generated/numpy.polynomial.legendre.legint.html