
    \hq                          S r SSKJrJrJr  SSKJrJr  SSKJ	r	J
r
  SSKJr  SSKJr  S r\SS	 j5       rS
 r\SS j5       rS r\SS j5       rS r\SS j5       rS r\SS j5       rg)a  
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
    )dup_mul_grounddup_sub_grounddup_quo_ground)dup_evaldup_integrate)ZZQQ)
named_poly)publicc                 :   U S:  a  UR                   /$ UR                   U" SS5      /n[        SU S-   5       H_  n[        [        X!" U5      U5      SU5      nUS-  S:X  d  M+  [	        U[        X!" SS5      U5      U" SUS-
  -  SU-  S-
  5      -  U5      nMa     U$ )z2Low-level implementation of Bernoulli polynomials.      r   oneranger   r   r   r   nKpis       N/var/www/auris/envauris/lib/python3.13/site-packages/sympy/polys/appellseqs.pydup_bernoullir      s    1uw	
"QA1ac].AaD!4a;q5A:q(1a!fa"81Q1X1ax;P"PRSTA  H    Nc                 4    [        U [        [        SU4U5      $ )a  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
zBernoulli polynomial)r
   r   r	   r   xpolyss      r   bernoulli_polyr   )   s    v a,BQD%PPr   c           
         UR                   /n[        SU S-   5       He  n[        [        X!" U5      U5      SU5      nUS-  S:X  d  M+  [	        U[        X!R                   U5      U" SUS-
  -  S-
  SU-  S-
  5      -  U5      nMg     U$ )z:Low-level implementation of central Bernoulli polynomials.r   r   r   r   r   s       r   dup_bernoulli_cr!   f   s    	
A1ac].AaD!4a;q5A:q(1eeQ"7!Q1XqL1a4QR(:S"SUVWA  Hr   c                 4    [        U [        [        SU4U5      $ )a  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.
zcentral Bernoulli polynomial)r
   r!   r	   r   s      r   bernoulli_c_polyr#   o   s    ( a".LqdTYZZr   c           	         U S:  a  UR                   /$ UR                  * /n[        SU S-   5       HU  n[        [	        X!" U5      U5      SU5      nUS-  S:X  d  M+  [        U[        X!R                  U5      U" S5      -  U5      nMW     U$ )z1Low-level implementation of Genocchi polynomials.r   r   r   )zeror   r   r   r   r   r   r   s       r   dup_genocchir&      s    1ux
%%A1ac].AaD!4a;q5A:q(1eeQ"71Q4"?CA  Hr   c                 4    [        U [        [        SU4U5      $ )ag  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
zGenocchi polynomial)r
   r&   r   r   s      r   genocchi_polyr(      s    6 ar+@1$NNr   c                 R    [        [        U S-   [        5      U" U * S-
  5      U5      $ )z.Low-level implementation of Euler polynomials.r   )r   r&   r   )r   r   s     r   	dup_eulerr*      s&    ,qsB/A2a4!<<r   c                 4    [        U [        [        SU4U5      $ )a  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
zEuler polynomial)r
   r*   r	   r   s      r   
euler_polyr,      s    , aB(:QD%HHr   c           	          UR                   /n[        SU S-   5       HL  n[        [        X!" U5      U5      SU5      nUS-  S:X  d  M+  [	        U[        X!R                   U5      U5      nMN     U$ )z.Low-level implementation of Andre polynomials.r   r   r   r   r   s       r   	dup_andrer.      sg    	
A1ac].AaD!4a;q5A:q(1eeQ"7;A  Hr   c                 4    [        U [        [        SU4U5      $ )a  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
zAndre polynomial)r
   r.   r   r   s      r   
andre_polyr0      s    v aB(:QD%HHr   )NF)__doc__sympy.polys.densearithr   r   r   sympy.polys.densetoolsr   r   sympy.polys.domainsr   r	   sympy.polys.polytoolsr
   sympy.utilitiesr   r   r   r!   r#   r&   r(   r*   r,   r.   r0    r   r   <module>r8      s   . R Q : & , "	 :Q :Qx [ [*	 O O8= I I. :I :Ir   