PyPi

This is a package that computes the pi number using various approaches. The codes are implemented by Muhammad Hammad and Sharareh Sayyad.

Collection of results:

To run all tests, use sh script_test_piapprox.sh or make the bash script executable using chmod+x script_test_piapprox.sh To run all implementations, use sh create_modules.sh

Demonstration of the methods and analyzing their performance is presented in a Jupyter notebook in the example directory.

Collection of algorithms for estimating the pi number

Our methods for evaluating $\pi$ benefit from using polygons, Monte Carlo algorithm, the continued-fraction approach, Ramanujan's formula, Leibniz formula, Chudnovsky formula, Bailey–Borwein–Plouffe formula (BBP) fromula, Gauss-Legendre algorithm and Nilakantha series. The implementation is in PIapprox directory.

Project contains:

• Class for types of outputs

  • Rationals

  • Floats

  • Fix precision numbers

  • A comparison with standard Python implementation of the previous three classes

• Class for approximations of pi

  • Approximation of pi using polygons and polygon (sides)

  • Approximation of pi using Monte-Carl methods

  • Computing the digits of pi independently

  • Ramanujan series

  • Chudnovsky

  • BBP approach

  • Continued fraction

  • Leibniz formula

Summary:

In summary, the project consists of the following components:

• Classes that approximate numbers.

• Methods that rely on these classes to approximate pi.

• An automated test suite forFloatNumber, RationalNumber and FixedPrecision.

• A Jupyter notebook that explains the methods and the comparison.