bundles / scipy 2.0.0.dev0+git20260907.41eeb59 / scipy / special / _orthogonal / genlaguerre
function
scipy.special._orthogonal:genlaguerre
source: build-install/usr/lib/python3.14/site-packages/scipy/special/_orthogonal.py:823
Signature
def genlaguerre(n, alpha, monic = False)Summary
Generalized (associated) Laguerre polynomial.
Extended Summary
Defined to be the solution of
where ; is a polynomial of degree .
Parameters
n: intDegree of the polynomial.
alpha: floatParameter, must be greater than -1.
monic: bool, optionalIf True, scale the leading coefficient to be 1. Default is False.
Returns
L: orthopoly1dGeneralized Laguerre polynomial.
Notes
For fixed , the polynomials are orthogonal over with weight function .
The Laguerre polynomials are the special case where .
Examples
The generalized Laguerre polynomials are closely related to the confluent hypergeometric function :math:`{}_1F_1`: .. math:: L_n^{(\alpha)}(x) = \binom{n + \alpha}{n} {}_1F_1(-n, \alpha +1, x) This can be verified, for example, for :math:`n = \alpha = 3` over the interval :math:`[-1, 1]`:import numpy as np from scipy.special import binom, genlaguerre, hyp1f1 x = np.arange(-1.0, 1.0, 0.01) np.allclose(genlaguerre(3, 3)(x), binom(6, 3) * hyp1f1(-3, 4, x))✓
TrueThis is the plot of the generalized Laguerre polynomials :math:`L_3^{(\alpha)}` for some values of :math:`\alpha`:
import matplotlib.pyplot as plt x = np.arange(-4.0, 12.0, 0.01) fig, ax = plt.subplots()✓
ax.set_ylim(-5.0, 10.0) ax.set_title(r'Generalized Laguerre polynomials $L_3^{(\alpha)}$') for alpha in np.arange(0, 5): ax.plot(x, genlaguerre(3, alpha)(x), label=rf"$L_3^{{({alpha})}}$") plt.legend(loc='best')✗
<matplotlib.legend.Legend object at 0x7f3f687c9550>
plt.show()
✓
See also
Aliases
scipy.special.genlaguerre