Numerical methods by python

  • What are numerical methods in programming?

    A numerical method is an approximate computer method for solving a mathematical problem which often has no analytical solution..

  • What is numerical code in Python?

    There are three numeric types in Python: int. float. complex..

  • Numerical Python has a fixed-size, homogeneous (fixed-type), multi-dimensional array type and lots of functions for various array operations.
    The result is a dynamically typed environment for array computing similar to basic Matlab.
  • NumPy is the fundamental package for scientific computing with Python, adding support for large, multidimensional arrays and matrices, along with a large library of high-level mathematical functions to operate on these arrays.
This notebook contains an excerpt from the Python Programming and Numerical Methods - A Guide for Engineers and Scientists, the content is also available at  Getting Started with PythonPython as a CalculatorNumerical Differentiation
This notebook contains an excerpt from the Python Programming and Numerical Methods - A Guide for Engineers and Scientists, the content is also available at 

Iterative method used to solve a linear system of equations

In numerical linear algebra, the Gauss–Seidel method, also known as the Liebmann method or the method of successive displacement, is an iterative method used to solve a system of linear equations.
It is named after the German mathematicians Carl Friedrich Gauss and Philipp Ludwig von Seidel, and is similar to the Jacobi method.
Though it can be applied to any matrix with non-zero elements on the diagonals, convergence is only guaranteed if the matrix is either strictly diagonally dominant, or symmetric and positive definite.
It was only mentioned in a private letter from Gauss to his student Gerling in 1823.
A publication was not delivered before 1874 by Seidel.

Iterative method used to solve a linear system of equations

In numerical linear algebra, the Jacobi method is an iterative algorithm for determining the solutions of a strictly diagonally dominant system of linear equations.
Each diagonal element is solved for, and an approximate value is plugged in.
The process is then iterated until it converges.
This algorithm is a stripped-down version of the Jacobi transformation method of matrix diagonalization.
The method is named after Carl Gustav Jacob Jacobi.
The NAG Numerical Library is a software product developed and sold by The Numerical Algorithms Group Ltd.
It is a software library of numerical analysis routines, containing more than 1,900 mathematical and statistical algorithms.
Areas covered by the library include linear algebra, optimization, quadrature, the solution of ordinary and partial differential equations, regression analysis, and time series analysis.

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