/
appellseqs.py
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/
appellseqs.py
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r"""
Efficient functions for generating Appell sequences.
An Appell sequence is a zero-indexed sequence of polynomials `p_i(x)`
satisfying `p_{i+1}'(x)=(i+1)p_i(x)` for all `i`. This definition leads
to the following iterative algorithm:
.. math :: p_0(x) = c_0,\ p_i(x) = i \int_0^x p_{i-1}(t)\,dt + c_i
The constant coefficients `c_i` are usually determined from the
just-evaluated integral and `i`.
Appell sequences satisfy the following identity from umbral calculus:
.. math :: p_n(x+y) = \sum_{k=0}^n \binom{n}{k} p_k(x) y^{n-k}
References
==========
.. [1] https://en.wikipedia.org/wiki/Appell_sequence
.. [2] Peter Luschny, "An introduction to the Bernoulli function",
https://arxiv.org/abs/2009.06743
"""
from sympy.polys.densearith import dup_mul_ground, dup_sub_ground, dup_quo_ground
from sympy.polys.densetools import dup_eval, dup_integrate
from sympy.polys.domains import ZZ, QQ
from sympy.polys.polytools import named_poly
from sympy.utilities import public
def dup_bernoulli(n, K):
"""Low-level implementation of Bernoulli polynomials."""
if n < 1:
return [K.one]
p = [K.one, K(-1,2)]
for i in range(2, n+1):
p = dup_integrate(dup_mul_ground(p, K(i), K), 1, K)
if i % 2 == 0:
p = dup_sub_ground(p, dup_eval(p, K(1,2), K) * K(1<<(i-1), (1<<i)-1), K)
return p
@public
def bernoulli_poly(n, x=None, polys=False):
r"""Generates the Bernoulli polynomial `\operatorname{B}_n(x)`.
`\operatorname{B}_n(x)` is the unique polynomial satisfying
.. math :: \int_{x}^{x+1} \operatorname{B}_n(t) \,dt = x^n.
Based on this, we have for nonnegative integer `s` and integer
`a` and `b`
.. math :: \sum_{k=a}^{b} k^s = \frac{\operatorname{B}_{s+1}(b+1) -
\operatorname{B}_{s+1}(a)}{s+1}
which is related to Jakob Bernoulli's original motivation for introducing
the Bernoulli numbers, the values of these polynomials at `x = 1`.
Examples
========
>>> from sympy import summation
>>> from sympy.abc import x
>>> from sympy.polys import bernoulli_poly
>>> bernoulli_poly(5, x)
x**5 - 5*x**4/2 + 5*x**3/3 - x/6
>>> def psum(p, a, b):
... return (bernoulli_poly(p+1,b+1) - bernoulli_poly(p+1,a)) / (p+1)
>>> psum(4, -6, 27)
3144337
>>> summation(x**4, (x, -6, 27))
3144337
>>> psum(1, 1, x).factor()
x*(x + 1)/2
>>> psum(2, 1, x).factor()
x*(x + 1)*(2*x + 1)/6
>>> psum(3, 1, x).factor()
x**2*(x + 1)**2/4
Parameters
==========
n : int
Degree of the polynomial.
x : optional
polys : bool, optional
If True, return a Poly, otherwise (default) return an expression.
See Also
========
sympy.functions.combinatorial.numbers.bernoulli
References
==========
.. [1] https://en.wikipedia.org/wiki/Bernoulli_polynomials
"""
return named_poly(n, dup_bernoulli, QQ, "Bernoulli polynomial", (x,), polys)
def dup_bernoulli_c(n, K):
"""Low-level implementation of central Bernoulli polynomials."""
p = [K.one]
for i in range(1, n+1):
p = dup_integrate(dup_mul_ground(p, K(i), K), 1, K)
if i % 2 == 0:
p = dup_sub_ground(p, dup_eval(p, K.one, K) * K((1<<(i-1))-1, (1<<i)-1), K)
return p
@public
def bernoulli_c_poly(n, x=None, polys=False):
r"""Generates the central Bernoulli polynomial `\operatorname{B}_n^c(x)`.
These are scaled and shifted versions of the plain Bernoulli polynomials,
done in such a way that `\operatorname{B}_n^c(x)` is an even or odd function
for even or odd `n` respectively:
.. math :: \operatorname{B}_n^c(x) = 2^n \operatorname{B}_n
\left(\frac{x+1}{2}\right)
Parameters
==========
n : int
Degree of the polynomial.
x : optional
polys : bool, optional
If True, return a Poly, otherwise (default) return an expression.
"""
return named_poly(n, dup_bernoulli_c, QQ, "central Bernoulli polynomial", (x,), polys)
def dup_genocchi(n, K):
"""Low-level implementation of Genocchi polynomials."""
if n < 1:
return [K.zero]
p = [-K.one]
for i in range(2, n+1):
p = dup_integrate(dup_mul_ground(p, K(i), K), 1, K)
if i % 2 == 0:
p = dup_sub_ground(p, dup_eval(p, K.one, K) // K(2), K)
return p
@public
def genocchi_poly(n, x=None, polys=False):
r"""Generates the Genocchi polynomial `\operatorname{G}_n(x)`.
`\operatorname{G}_n(x)` is twice the difference between the plain and
central Bernoulli polynomials, so has degree `n-1`:
.. math :: \operatorname{G}_n(x) = 2 (\operatorname{B}_n(x) -
\operatorname{B}_n^c(x))
The factor of 2 in the definition endows `\operatorname{G}_n(x)` with
integer coefficients.
Parameters
==========
n : int
Degree of the polynomial plus one.
x : optional
polys : bool, optional
If True, return a Poly, otherwise (default) return an expression.
See Also
========
sympy.functions.combinatorial.numbers.genocchi
"""
return named_poly(n, dup_genocchi, ZZ, "Genocchi polynomial", (x,), polys)
def dup_euler(n, K):
"""Low-level implementation of Euler polynomials."""
return dup_quo_ground(dup_genocchi(n+1, ZZ), K(-n-1), K)
@public
def euler_poly(n, x=None, polys=False):
r"""Generates the Euler polynomial `\operatorname{E}_n(x)`.
These are scaled and reindexed versions of the Genocchi polynomials:
.. math :: \operatorname{E}_n(x) = -\frac{\operatorname{G}_{n+1}(x)}{n+1}
Parameters
==========
n : int
Degree of the polynomial.
x : optional
polys : bool, optional
If True, return a Poly, otherwise (default) return an expression.
See Also
========
sympy.functions.combinatorial.numbers.euler
"""
return named_poly(n, dup_euler, QQ, "Euler polynomial", (x,), polys)
def dup_andre(n, K):
"""Low-level implementation of Andre polynomials."""
p = [K.one]
for i in range(1, n+1):
p = dup_integrate(dup_mul_ground(p, K(i), K), 1, K)
if i % 2 == 0:
p = dup_sub_ground(p, dup_eval(p, K.one, K), K)
return p
@public
def andre_poly(n, x=None, polys=False):
r"""Generates the Andre polynomial `\mathcal{A}_n(x)`.
This is the Appell sequence where the constant coefficients form the sequence
of Euler numbers ``euler(n)``. As such they have integer coefficients
and parities matching the parity of `n`.
Luschny calls these the *Swiss-knife polynomials* because their values
at 0 and 1 can be simply transformed into both the Bernoulli and Euler
numbers. Here they are called the Andre polynomials because
`|\mathcal{A}_n(n\bmod 2)|` for `n \ge 0` generates what Luschny calls
the *Andre numbers*, A000111 in the OEIS.
Examples
========
>>> from sympy import bernoulli, euler, genocchi
>>> from sympy.abc import x
>>> from sympy.polys import andre_poly
>>> andre_poly(9, x)
x**9 - 36*x**7 + 630*x**5 - 5124*x**3 + 12465*x
>>> [andre_poly(n, 0) for n in range(11)]
[1, 0, -1, 0, 5, 0, -61, 0, 1385, 0, -50521]
>>> [euler(n) for n in range(11)]
[1, 0, -1, 0, 5, 0, -61, 0, 1385, 0, -50521]
>>> [andre_poly(n-1, 1) * n / (4**n - 2**n) for n in range(1, 11)]
[1/2, 1/6, 0, -1/30, 0, 1/42, 0, -1/30, 0, 5/66]
>>> [bernoulli(n) for n in range(1, 11)]
[1/2, 1/6, 0, -1/30, 0, 1/42, 0, -1/30, 0, 5/66]
>>> [-andre_poly(n-1, -1) * n / (-2)**(n-1) for n in range(1, 11)]
[-1, -1, 0, 1, 0, -3, 0, 17, 0, -155]
>>> [genocchi(n) for n in range(1, 11)]
[-1, -1, 0, 1, 0, -3, 0, 17, 0, -155]
>>> [abs(andre_poly(n, n%2)) for n in range(11)]
[1, 1, 1, 2, 5, 16, 61, 272, 1385, 7936, 50521]
Parameters
==========
n : int
Degree of the polynomial.
x : optional
polys : bool, optional
If True, return a Poly, otherwise (default) return an expression.
See Also
========
sympy.functions.combinatorial.numbers.andre
References
==========
.. [1] Peter Luschny, "An introduction to the Bernoulli function",
https://arxiv.org/abs/2009.06743
"""
return named_poly(n, dup_andre, ZZ, "Andre polynomial", (x,), polys)