Ex:2 Familiarization of Scientific Computing

Lists, Arrays and Matrices and their Visualization

What You Will Learn You will create lists, arrays and matrices using scipy You will learn to slice, reverse, append and plot arrays Lists in Python Type in the code at the Ipython console from scipy import * x=[1,2,3,4,5] The first line imports all modules in scipy. The second line creates a list in the variable x. Type x at the console and observe the list Type x[0:2] at the console and observe the first two values in the list Type x[3:5] at the console and observe a slice of the list Type x[::-1] at the console and observe the reversed list Type len(x) at the console and observe the length of the list x Type y=[4,5,6] and then type x+y observe the two lists getting concatenated. Type append(x,y) observe a similar result Type z=['apple','orange','pear'] to create a list of strings Arrays using Scipy scipy and numpy provide arrays that support mathematical operations. Type x=array([1,2,3,4,5]) at the cons...

Overview of Scientific Computing

Introduction Scientific computing broadly means computations carried out for scientific or engineering needs. This mostly includes processing of large arrays or matrices, plotting of functions, solving equations, performing mathematical transforms etc very fast while keeping programming hassles at a minimum. Requirements of Scientific Computing The language for scientific computing should be Interpreted should be modular should have easy routines for array, matrix and vectors should have a publication quality plotting library Python for Scientific Computing Python is an interpreted, modular language that is suitable for scientific computing. Modules such as numpy, scipy etc provide many scientific computing tools. The module matpplotlib alias pylab provides publication quality plotting libraries. Python 2.7 and Python 3 are available in all major Linux distros and can be installed as bundle such as anaconda in Windows. An enhanced Python shell ipython...

Matrix Operations using Python

Dr. Hari V S Department of Electronics and Communication College of Engineering Chengannur What You will Learn You will learn to create matrices You will learn to solve linear equations by computing the inverse of a matrix. You will learn to compute the eigen values of a matrix Matrices using Python A $5\times 3$ matrix is created, printed and displayed as an image using the code below. Its transpose is generated by the $transpose()$ function. from scipy import * from pylab import * x=mat([[1,2,3,4,5],[4,5,6,9,15],[7,8,9,23,25]]) print x print shape(x) print transpose(x) matshow(x) show() Solution of Linear Equations Linear systems are represented by matrix equations. See the electrical network in the figure below. All resistances are in $\Omega$. The network is described by the set of equations. \begin{equation} 9I_{1}-4 I_{2}=20 \end{equation} \begin{equation} -4I_{1}-6 I_{2}=-10 \end{equation} \begin{equation} 8I_{3}-3 I_{4}=-20 \end...

KTU-Scientific Computing Lab

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