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