Formal Power Series

Methods for computing and manipulating Formal Power Series.

class sympy.series.formal.FormalPowerSeries[source]

Represents Formal Power Series of a function.

No computation is performed. This class should only to be used to represent a series. No checks are performed.

For computing a series use fps().

See also

sympy.series.formal.fps

infinite

Returns an infinite representation of the series

integrate(x=None)[source]

Integrate Formal Power Series.

Examples

>>> from sympy import fps, sin
>>> from sympy.abc import x
>>> f = fps(sin(x))
>>> f.integrate(x).truncate()
-1 + x**2/2 - x**4/24 + O(x**6)
>>> f.integrate((x, 0, 1))
-cos(1) + 1
polynomial(n=6)[source]

Truncated series as polynomial.

Returns series sexpansion of f upto order O(x**n) as a polynomial(without O term).

truncate(n=6)[source]

Truncated series.

Returns truncated series expansion of f upto order O(x**n).

If n is None, returns an infinite iterator.

sympy.series.formal.fps(f, x=None, x0=0, dir=1, hyper=True, order=4, rational=True, full=False)[source]

Generates Formal Power Series of f.

Returns the formal series expansion of f around x = x0 with respect to x in the form of a FormalPowerSeries object.

Formal Power Series is represented using an explicit formula computed using different algorithms.

See compute_fps() for the more details regarding the computation of formula.

Parameters:

x : Symbol, optional

If x is None and f is univariate, the univariate symbols will be supplied, otherwise an error will be raised.

x0 : number, optional

Point to perform series expansion about. Default is 0.

dir : {1, -1, ‘+’, ‘-‘}, optional

If dir is 1 or ‘+’ the series is calculated from the right and for -1 or ‘-‘ the series is calculated from the left. For smooth functions this flag will not alter the results. Default is 1.

hyper : {True, False}, optional

Set hyper to False to skip the hypergeometric algorithm. By default it is set to False.

order : int, optional

Order of the derivative of f, Default is 4.

rational : {True, False}, optional

Set rational to False to skip rational algorithm. By default it is set to True.

full : {True, False}, optional

Set full to True to increase the range of rational algorithm. See rational_algorithm() for details. By default it is set to False.

See also

sympy.series.formal.FormalPowerSeries, sympy.series.formal.compute_fps

Examples

>>> from sympy import fps, O, ln, atan
>>> from sympy.abc import x

Rational Functions

>>> fps(ln(1 + x)).truncate()
x - x**2/2 + x**3/3 - x**4/4 + x**5/5 + O(x**6)

>>> fps(atan(x), full=True).truncate()
x - x**3/3 + x**5/5 + O(x**6)
sympy.series.formal.compute_fps(f, x, x0=0, dir=1, hyper=True, order=4, rational=True, full=False)[source]

Computes the formula for Formal Power Series of a function.

Tries to compute the formula by applying the following techniques (in order):

  • rational_algorithm
  • Hypergeomitric algorithm
Parameters:

x : Symbol

x0 : number, optional

Point to perform series expansion about. Default is 0.

dir : {1, -1, ‘+’, ‘-‘}, optional

If dir is 1 or ‘+’ the series is calculated from the right and for -1 or ‘-‘ the series is calculated from the left. For smooth functions this flag will not alter the results. Default is 1.

hyper : {True, False}, optional

Set hyper to False to skip the hypergeometric algorithm. By default it is set to False.

order : int, optional

Order of the derivative of f, Default is 4.

rational : {True, False}, optional

Set rational to False to skip rational algorithm. By default it is set to True.

full : {True, False}, optional

Set full to True to increase the range of rational algorithm. See rational_algorithm() for details. By default it is set to False.
Returns:

ak : sequence

Sequence of coefficients.

xk : sequence

Sequence of powers of x.

ind : Expr

Independent terms.

mul : Pow

Common terms.

See also

sympy.series.formal.rational_algorithm, sympy.series.formal.hyper_algorithm

Rational Algorithm

sympy.series.formal.rational_independent(terms, x)[source]

Returns a list of all the rationally independent terms.

Examples

>>> from sympy import sin, cos
>>> from sympy.series.formal import rational_independent
>>> from sympy.abc import x

>>> rational_independent([cos(x), sin(x)], x)
[cos(x), sin(x)]
>>> rational_independent([x**2, sin(x), x*sin(x), x**3], x)
[x**3 + x**2, x*sin(x) + sin(x)]
sympy.series.formal.rational_algorithm(f, x, k, order=4, full=False)[source]

Rational algorithm for computing formula of coefficients of Formal Power Series of a function.

Applicable when f(x) or some derivative of f(x) is a rational function in x.

rational_algorithm() uses apart() function for partial fraction decomposition. apart() by default uses ‘undetermined coefficients method’. By setting full=True, ‘Bronstein’s algorithm’ can be used instead.

Looks for derivative of a function up to 4’th order (by default). This can be overriden using order option.

Returns:

formula : Expr

ind : Expr

Independent terms.

order : int

See also

sympy.polys.partfrac.apart

Notes

By setting full=True, range of admissible functions to be solved using rational_algorithm can be increased. This option should be used carefully as it can signifcantly slow down the computation as doit is performed on the RootSum object returned by the apart function. Use full=False whenever possible.

References

[R428]Formal Power Series - Dominik Gruntz, Wolfram Koepf
[R429]Power Series in Computer Algebra - Wolfram Koepf

Examples

>>> from sympy import log, atan, I
>>> from sympy.series.formal import rational_algorithm as ra
>>> from sympy.abc import x, k

>>> ra(1 / (1 - x), x, k)
(1, 0, 0)
>>> ra(log(1 + x), x, k)
(-(-1)**(-k)/k, 0, 1)

>>> ra(atan(x), x, k, full=True)
((-I*(-I)**(-k)/2 + I*I**(-k)/2)/k, 0, 1)

Hypergeometric Algorithm

sympy.series.formal.simpleDE(f, x, g, order=4)[source]

Generates simple DE.

DE is of the form

\[f^k(x) + \sum\limits_{j=0}^{k-1} A_j f^j(x) = 0\]

where \(A_j\) should be rational function in x.

Generates DE’s upto order 4 (default). DE’s can also have free parameters.

By increasing order, higher order DE’s can be found.

Yields a tuple of (DE, order).

sympy.series.formal.exp_re(DE, r, k)[source]

Converts a DE with constant coefficients (explike) into a RE.

Performs the substitution:

\[f^j(x) \to r(k + j)\]

Normalises the terms so that lowest order of a term is always r(k).

See also

sympy.series.formal.hyper_re

Examples

>>> from sympy import Function, Derivative
>>> from sympy.series.formal import exp_re
>>> from sympy.abc import x, k
>>> f, r = Function('f'), Function('r')

>>> exp_re(-f(x) + Derivative(f(x)), r, k)
-r(k) + r(k + 1)
>>> exp_re(Derivative(f(x), x) + Derivative(f(x), x, x), r, k)
r(k) + r(k + 1)
sympy.series.formal.hyper_re(DE, r, k)[source]

Converts a DE into a RE.

Performs the substitution:

\[x^l f^j(x) \to (k + 1 - l)_j . a_{k + j - l}\]

Normalises the terms so that lowest order of a term is always r(k).

See also

sympy.series.formal.exp_re

Examples

>>> from sympy import Function, Derivative
>>> from sympy.series.formal import hyper_re
>>> from sympy.abc import x, k
>>> f, r = Function('f'), Function('r')

>>> hyper_re(-f(x) + Derivative(f(x)), r, k)
(k + 1)*r(k + 1) - r(k)
>>> hyper_re(-x*f(x) + Derivative(f(x), x, x), r, k)
(k + 2)*(k + 3)*r(k + 3) - r(k)
sympy.series.formal.rsolve_hypergeometric(f, x, P, Q, k, m)[source]

Solves RE of hypergeometric type.

Attempts to solve RE of the form

Q(k)*a(k + m) - P(k)*a(k)

Transformations that preserve Hypergeometric type:

  1. x**n*f(x): b(k + m) = R(k - n)*b(k)
  2. f(A*x): b(k + m) = A**m*R(k)*b(k)
  3. f(x**n): b(k + n*m) = R(k/n)*b(k)
  4. f(x**(1/m)): b(k + 1) = R(k*m)*b(k)
  5. f’(x): b(k + m) = ((k + m + 1)/(k + 1))*R(k + 1)*b(k)

Some of these transformations have been used to solve the RE.

Returns:

formula : Expr

ind : Expr

Independent terms.

order : int

References

[R430]Formal Power Series - Dominik Gruntz, Wolfram Koepf
[R431]Power Series in Computer Algebra - Wolfram Koepf

Examples

>>> from sympy import exp, ln, S
>>> from sympy.series.formal import rsolve_hypergeometric as rh
>>> from sympy.abc import x, k

>>> rh(exp(x), x, -S.One, (k + 1), k, 1)
(Piecewise((1/factorial(k), Eq(Mod(k, 1), 0)), (0, True)), 1, 1)

>>> rh(ln(1 + x), x, k**2, k*(k + 1), k, 1)
(Piecewise(((-1)**(k - 1)*factorial(k - 1)/RisingFactorial(2, k - 1),
 Eq(Mod(k, 1), 0)), (0, True)), x, 2)
sympy.series.formal.solve_de(f, x, DE, order, g, k)[source]

Solves the DE.

Tries to solve DE by either converting into a RE containing two terms or converting into a DE having constant coefficients.

Returns:

formula : Expr

ind : Expr

Independent terms.

order : int

Examples

>>> from sympy import Derivative as D
>>> from sympy import exp, ln
>>> from sympy.series.formal import solve_de
>>> from sympy.abc import x, k, f

>>> solve_de(exp(x), x, D(f(x), x) - f(x), 1, f, k)
(Piecewise((1/factorial(k), Eq(Mod(k, 1), 0)), (0, True)), 1, 1)

>>> solve_de(ln(1 + x), x, (x + 1)*D(f(x), x, 2) + D(f(x)), 2, f, k)
(Piecewise(((-1)**(k - 1)*factorial(k - 1)/RisingFactorial(2, k - 1),
 Eq(Mod(k, 1), 0)), (0, True)), x, 2)
sympy.series.formal.hyper_algorithm(f, x, k, order=4)[source]

Hypergeometric algorithm for computing Formal Power Series.

Steps:
  • Generates DE
  • Convert the DE into RE
  • Solves the RE

See also

sympy.series.formal.simpleDE, sympy.series.formal.solve_de

Examples

>>> from sympy import exp, ln
>>> from sympy.series.formal import hyper_algorithm

>>> from sympy.abc import x, k

>>> hyper_algorithm(exp(x), x, k)
(Piecewise((1/factorial(k), Eq(Mod(k, 1), 0)), (0, True)), 1, 1)

>>> hyper_algorithm(ln(1 + x), x, k)
(Piecewise(((-1)**(k - 1)*factorial(k - 1)/RisingFactorial(2, k - 1),
 Eq(Mod(k, 1), 0)), (0, True)), x, 2)