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GSoC 2015 Application Sartaj Singh: Improving the series package and limits in SymPy

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Sartaj Singh edited this page May 16, 2015 · 10 revisions

PDF version of proposal is available here

Sympy currently lacks a proper structure for handling and manipulating series. All the series related functionality is defined as methods in Expr class. I plan to give the series package a concrete structure for future development and improvement. I plan to do the following over the summer.

  • Sequence classes for defining sequences of coefficients.
  • Classes to represent series in general.
  • Implement ‘Formal Power Series’, using the above implemented structure.
  • Computing limits of sequences.

About Me

The Student

Name
Sartaj Singh
e-mail
singhsartaj94@gmail.com
Github
https://github.com/leosartaj
Blog
https://leosartaj.github.io

The Institute

University
Indian Institute of Technology (BHU), Varanasi
Major
Mathematics and Computing
Year
Sophomore
Degree
Integrated Masters Degree

Programming Experience and Mathematical Background

I have been programming from last two years, and from the past one year in python. Apart from python I have experience in C, javascript, PHP. For version control, I have been using git. I work on Arch Linux(rolling release rocks!) with vim as my primary editor. I like vim because its fast and productive. My favorite python feature is list comprehensions, simply because they are beautiful. I have completed courses on basic mathematical methods, series expansions.

Recurrence relations are a powerful tool in mathematics. Ability of sympy to solve them fascinates me.

>>> y = Function('y')
>>> rsolve(y(n) - 2*y(n-1), y(n))
>>> C0*2**n

My Motivation

I have always been fascinated with the power Mathematica brings to the process of mathematical study. I soon discovered sympy and decided to give it a shot.

Series play an integral role in field of mathematics. Series have various applications, like solving differential equations. How a seemingly complex function can be simplified using series is what fascinates me the most.

>>> series(cos(4*acos(x))
1-8x**2+8x**4 # simple polynomial

My Projects

PyChat
  • A simple asynchronous chat client, based on Twisted framework.
Sub
  • Simple command line tool for downloading subtitles.
autosign
  • Easily add signatures to files
PyCross
  • Single/multiplayer TicTacToe game. Single player is based on

minimax algorithm and Monte Carlo Simulation.

All of my projects (including others) can be found on my github page.

Contributions

I started using sympy in January and made my first contributing in February. I have been constantly contributing and learning from the community ever since.

Merged PR’s

  • 8985, 9039 - Removed \lvert (not supported by matplotlib) in favor of \left | from latex(Abs)
  • 9105 - Fixed exp(x).taylor term method, it raised TypeError error when called (uncached).
  • 9139 - factorial(n) >= 1, now returns True for a nonnegative integer n.
  • 9142 - Implemented function stieltjes for computing stieltjes constants.
  • 9156 - Fibonacci(n).limit(n, oo) and Lucas(n).limit(n, oo) returns oo rather than Fibonacci(oo) and Lucas(oo). Result is now consistent with factorial and others.

Unmerged PR’s

  • 9036 - [WIP] Fixed LambertW to give series expansion at x=0

  • 9038 - [WIP] zero=True assumption was ignored in Limit. First approach was not good. Working on a new approach to tackle the bug.

  • 9050 - [WIP] Implemented Fourier sine/cosine series expansion.

  • 8729 - Earlier nan.is_rational() returned True, fixed it to return False.

  • 9075 - Earlier following type of limits computed incorrectly,

    >>> ex = (6**(n+1)+n+1)/(6**n+n)
>>> ex.limit(n, oo)
1

    Fixed it to return 6 (expected result)

    >>> ex.limit(n, oo)
6

Issues/Bugs Caught

  • 9104 - exp(x).taylor_term(n, x) returned TypeError. Caught and Fixed the bug.
  • 9077 - Fourier sine/cosine implementation. Sympy should have an implementation of the same. Issued a pull request to address the same.

The Project

In this section I will detail my vision for how the API will look and how the code will be structured. I expect this structure to be considerably enhanced under the guidance of my mentor.

Sequences

For the purpose of defining coefficients, I plan to implement Sequence based Classes inspired from sequences branch by Alexander U. Gudchenko. A Sequence will be finite or infinite lazily evaluated list. Coefficients will only be evaluated when required. Coefficients evaluated once will be saved in an internal dictionary (sparse representation).

Sequences based on formula

To define coefficients based on a particular formula, a special SeqFormula class will be implemented.

>>> SeqFormula(n*(n+1), (n, 0, oo))
[0, 2, 6, 12, 20, ...]

Periodical Sequences

Similar to sequences based on formulas, sequences can also be defined periodically, such as

>>> SeqPer((1, 3, 8), (n, 0, oo))
[1, 3, 8, 1, 3, ...]

Sequences from a function

Sequences can also be generated using functions.

>>> SeqFunc(lambda n: n*(n+1), (n, 0, oo))
[0, 2, 6, 12, 20, ...]

Containment

All the above sequences can be generated using Sequence class.

>>> Sequence(function=lambda n: n*(n+1), bounds=(n, 0, oo))
[0, 2, 6, 12, 20, ...]
>>> Sequence(formula=n*(n+1), bounds=(n, 0, oo))
[0, 2, 6, 12, 20, ...]
>>> Sequence(periodical=(1, 3, 8), bounds=(n, 0, oo))
[1, 3, 8, 1, 3, ...]

Methods

The coeff method can be used for getting a coefficient for a particular n.

>>> per = Sequence(periodical=(1, 3, 8), bounds=(n, 0, oo))
>>> per.coeff(7)
1
>>> fun = Sequence(function=lambda n: n*(n+1), bounds=(n, 0, oo))
>>> fun.coeff(7)
56
>>> form = Sequence(formula=n*(n+1), bounds=(n, 0, oo))
>>> form.coeff(n-1) # supports symbolic coefficients
n*(n-1)

Operations

Addition, Subtraction, Multiplication, Division will be defined element-wise.

>>> a = Sequence(formula=n**2, bounds=(n, 0, oo))
>>> b = Sequence(formula=n, bounds=(n, 0, oo))
>>> a + b
[0, 2, 6, 12, 20, ...]
>>> a - b
[0, 0, 2, 6, 12, ...]
>>> a * b
[0, 8, 27, 64, 125, ...]

Cauchy-Product can also be implemented, where

cn =\sum\limits_{k=0}^n a_k b_{n-k}

SeriesData class

This class will represent series. All other series will use SeriesData to represent a series. Internally SeriesData class will use Sequence objects to define a series. Series expansion of exp(x) can be modeled using sequences.

>>> an = Sequence(formula=1/factorial(n)), bounds=(n, 0, oo))
>>> xn = Sequence(formula=x**n), bounds=(n, 0, oo))
>>> a * b
[1, x, x**2/2, x**3/6, x**4/24, ...]

In general SeriesData just zips the two sequences together over multiplication. For constructing a series from known coefficients.

>>> an = Sequence(formula=1/factorial(n), bounds=(n, 0, oo)) # coefficients
>>> xn = Sequence(formula=x**n, bounds=(n, 0, oo)) # powers of x
>>> SeriesData(an, xn) # expansion of exp(x)
1 + x + x**2/2 + x**3/6 + x**4/24 + O(x**5)

This class can further have methods for generating term for a particular n, giving truncated or infinite series. Further, more classes can be formed which represent series in x, sin(x) and cos(x) (Fourier series), etc

SeriesX class

This class will represent series in x and can be used to model various series based on powers of x.

Taylor Series
>>> an = Sequence(formula=1/factorial(n), bounds=(n, 0, oo))
>>> SeriesX(an, x, a)
1 + e*x + e**2*x**2/2 + e**3*x**3/6 + e**4*x**4/24 + O(x**5)

Methods and Operations

  • Addition, subtraction will be term-wise

    >>> an = Sequence(formula=n**2, bounds=(n, 0, oo))
>>> bn = Sequence(formula=n, bounds=(n, 0, oo))
>>> s1 = SeriesX(an, x)
>>> s2 = SeriesX(bn, x)
>>> s1 + s2
2*x + 6*x**2 + 12*x**3 + 20*x**4 + O(x**5)
>>> s1 - s2
3*x**2 + 6*x**3 + 12*x**4 + O(x**5)

  • Differentiation and integration will also be term-wise

    >>> s1.diff(x)
1 + 8*x + 27*x**2 + 64*x**3 + O(x**4)
>>> integrate(s1, x)
x**2/2 + 4*x**3/3 + 9*x**4/4 + 16*x**5/5 + O(x**6)
  • Division, raised to power, inverse, composition
    All the methods and operations for truncated series will be modeled on the algorithms implemented in ring_series.
  • Infinite representation
    Series can also be represented in infinite form (if available)
    >>> s1.infinite
Sum(n**2*x**n, (n, 0, oo))

Formal Power Series

Formal Power Series will allow returning infinite series expansions in the form of

\sum\limits_{n=0}^\infty a_n x^n

Currently Mathematica and others have this routine. Sympy should have it too. Last year some work was done on implementation of Formal Power Series. Some part of the implementation is done and works correctly. I plan to integrate it with this system and complete the implementation.

>>> fps = FormalPowerSeries(exp(x), x, 0)
1 + x + x**2/2 + x**3/6 + x**4/24 + O(x**5)
>>> fps.infinite
Sum(x**n/factorial(n), (n, 0, oo))

Algorithm details

Algorithm used for computing Formal Power Series is described in detail in papers.

Find a Simple DE

For the algorithm to work, a simple DE of form
f^n(x) + \sum\limits_{k=0}^{n-1} A_{k} f^k(x)

is to be obtained. DE can be obtained by following steps:

  1. Set n := 1
  2. Form the DE and solve for all A_{n}
  3. if all A_{n} are rational stop, else increase n and repeat steps.
  4. If no solution is found for a suitable n(papers suggest 4), stop
>>> simpleDE(exp(x), x)
-f(x) + Derivative(f(x), x)
>>> simpleDE(erf(x), x)
Derivative(f(x), x, x) + 2*x*Derivative(f(x), x)
Forming Corresponding RE

  1. This can be achieved by the substitution

    x^j * f^k(x) \to pochhammer(n+1-j, k) * a(n+k-j)

  2. In the case, where all the coefficients of DE are constants, substitute

    a(n) \to b(n) * n!

    This substitution is equivalent to

    f^k(x) \to b(n+k)

Example:

>>> DE = simpleDE(exp(x), x)
>>> a = Function("a")
>>> DEtoRE(DE, a(n))
(n + 1) * a(n + 1) - a(n)
Solving the RE

The RE obtained, can be solved using rsolve routine, already implemented in sympy using initial conditions.

To solve for any general point x0 other than 0, following routine can be used

` x to y + x_0 `

FormalPowerSeries(f(y+x0), y, 0)

y to x - x0

Limits of Sequences

Implementing this algorithm will allow computing limits of series/summations, which are not currently computed by sympy. This will improve the range of admissible functions of which limit can be computed. Algorithm for computing limits of sequences is explained in the paper.

Applicability Criteria

This algorithm can be applied if the following conditions are fulfilled

  • Applies on expressions of the form pn/qn where pn, qn \to \infty when n \to \infty
  • qn should be asymptotically strictly monotonous
  • terms are built from rational functions, indefinite sums and indefinite products over an indeterminate n, called \Pi\Sigma-expressions

Algorithm Details

Difference operator, \Delta is defined as

\Delta a_{n} = a_{n+1} - a_{n}

Also, if

\lim_{n \to oo}p_{n}/q_{n} = 0

then qn is the dominant term
  • Check for the applicability criteria as described in the above section.
  • Use the difference operator on the numerator and denominator.
  • Find the dominant term of the numerator and the denominator. Drop all other terms.
  • Keep on doing recursively, until limit converges to a value.

Implementation

  • Difference Operator For this a new function can be implemented for finding the delta of an expression

    >>> difference(n*2**n)
(n+2)*2**n
>>> difference(Sum(n*2**n, (n, 0, m)))
(m+1)*2**(m+1)

  • Dominant Term A simple function that computes the limit at infinity will do the trick

    >>> dominant(n, n**2)
n**2 # dominant term

    This process is similar to finding the maximum number from a list of numbers, and can be done in a similar fashion.

  • Integrating into Limit This algorithm can then be used inside Limit for finding the applicable limits.

Road-map

I will not be available for two or three separate days in June (travelling). Apart from this I have no prior commitments. I have been following Sympy’s mailing list discussions for a while now and have looked at some of the codebase. I will be able to devote 40-45 hrs a week.

Community Bonding Period

  • Discuss the project with my mentor in further detail.
  • Get more acquainted with Sympy’s codebase
  • Read the below listed references in further detail.

Coding Period

  • Implement Sequence classes (First week of June)
  • Operations on sequences (Second week of June)
  • SeriesData and SeriesX classes (Third week of June)
  • Operations on SeriesX (First week of July)
  • Implement Formal Power Series (Third week of July)
  • Limits of Sequences (Second week of August)
  • One buffer week for any unexpected delays (or more enhancements)

Post GSoC

Sympy provides me with a good platform to hone my programming skills and put my mathematical skills to good use. Series are one of the many great ideas to have evolved in mathematics. They are among my favorite mathematical topics. There are other areas in the field of mathematics where SymPy could do a much better job, and I would love to contribute and enhance them.

References

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