(n: int, alpha: int | float = 0, mode: str = "numpy")
return E1rScheme(name, weights, points, 2 * n - 1)
Gauss-Laguerre quadrature for integrals of the form

        int_0^{+inf} exp(-alpha * x) f(x) dx.
Gauss-Laguerre quadrature for integrals of the form
Gauss - Laguerre quadrature for integrals of the form
def gauss_laguerre(n: int, alpha: int | float = 0, mode: str = "numpy"):
    """
    Gauss-Laguerre quadrature for integrals of the form

        int_0^{+inf} exp(-alpha * x) f(x) dx.
    """
    symbolic = mode != "numpy"
    rc = orthopy.e1r.RecurrenceCoefficients("monic", alpha, symbolic)

    _, a, b = np.array([rc[k] for k in range(n)]).T
    points, weights = scheme_from_rc(a, b, rc.int_1, mode=mode)

    if alpha == 0:
        name = f"Gauss-Laguerre ({n})"
    else:
        name = f"Generalized Gauss-Laguerre (n={n}, alpha={alpha})"

    return E1rScheme(name, weights, points, 2 * n - 1)
def gauss_laguerre ( n : int , alpha : int | float = 0 , mode : str = "numpy" ) : symbolic = mode != "numpy" rc = orthopy . e1r . RecurrenceCoefficients ( "monic" , alpha , symbolic ) _ , a , b = np . array ( [ rc [ k ] for k in range ( n ) ] ) . T points , weights = scheme_from_rc ( a , b , rc . int_1 , mode = mode ) if alpha == 0 : name = f"Gauss-Laguerre ({n})" else : name = f"Generalized Gauss-Laguerre (n={n}, alpha={alpha})" return E1rScheme ( name , weights , points , 2 * n - 1 )