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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)
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