Introduction To Cubic Spline Interpolation With Examples In Python

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Introduction to Cubic Spline Interpolation with Examples in Python

Author : Thomas Maindl
Publisher : Createspace Independent Publishing Platform
ISBN 13 : 9781987487374
Total Pages : 90 pages
Book Rating : 4.4/5 (873 download)

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Book Synopsis Introduction to Cubic Spline Interpolation with Examples in Python by : Thomas Maindl

Download or read book Introduction to Cubic Spline Interpolation with Examples in Python written by Thomas Maindl and published by Createspace Independent Publishing Platform. This book was released on 2018-04-09 with total page 90 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook will enable you to - discuss polynomial and spline interpolation - explain why using splines is a good method for interpolating data - construct cubic interpolating splines for your own projects It is a self-contained course for students who wish to learn about interpolating cubic splines and for lecturers who seek inspiration for designing a spline interpolation module. The book's innovative concept combines - a slide-based lecture with textual notes - a thorough introduction to the mathematical formalism - exercises - a "rocket science" project that implements constructing interpolating splines in Python for answering questions about the velocity, g-force, and covered distance after the first launch of SpaceX(R)' Falcon(R) Heavy Target group: STEM (science, technology, engineering, and math) students and lecturers at colleges and universities Contents: Preface 1 Cubic spline interpolation 2 Mini-script for constructing cubic splines 3 Spline exercises 4 The rocket launch project 5 Closing remarks Appendix A notebook for periodic cubic splines Index

Introduction to Numerical Programming

Author : Titus A. Beu
Publisher : CRC Press
ISBN 13 : 1466569670
Total Pages : 676 pages
Book Rating : 4.4/5 (665 download)

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Book Synopsis Introduction to Numerical Programming by : Titus A. Beu

Download or read book Introduction to Numerical Programming written by Titus A. Beu and published by CRC Press. This book was released on 2014-09-03 with total page 676 pages. Available in PDF, EPUB and Kindle. Book excerpt: Makes Numerical Programming More Accessible to a Wider Audience Bearing in mind the evolution of modern programming, most specifically emergent programming languages that reflect modern practice, Numerical Programming: A Practical Guide for Scientists and Engineers Using Python and C/C++ utilizes the author’s many years of practical research and teaching experience to offer a systematic approach to relevant programming concepts. Adopting a practical, broad appeal, this user-friendly book offers guidance to anyone interested in using numerical programming to solve science and engineering problems. Emphasizing methods generally used in physics and engineering—from elementary methods to complex algorithms—it gradually incorporates algorithmic elements with increasing complexity. Develop a Combination of Theoretical Knowledge, Efficient Analysis Skills, and Code Design Know-How The book encourages algorithmic thinking, which is essential to numerical analysis. Establishing the fundamental numerical methods, application numerical behavior and graphical output needed to foster algorithmic reasoning, coding dexterity, and a scientific programming style, it enables readers to successfully navigate relevant algorithms, understand coding design, and develop efficient programming skills. The book incorporates real code, and includes examples and problem sets to assist in hands-on learning. Begins with an overview on approximate numbers and programming in Python and C/C++, followed by discussion of basic sorting and indexing methods, as well as portable graphic functionality Contains methods for function evaluation, solving algebraic and transcendental equations, systems of linear algebraic equations, ordinary differential equations, and eigenvalue problems Addresses approximation of tabulated functions, regression, integration of one- and multi-dimensional functions by classical and Gaussian quadratures, Monte Carlo integration techniques, generation of random variables, discretization methods for ordinary and partial differential equations, and stability analysis This text introduces platform-independent numerical programming using Python and C/C++, and appeals to advanced undergraduate and graduate students in natural sciences and engineering, researchers involved in scientific computing, and engineers carrying out applicative calculations.

Interpolating Cubic Splines

Author : Gary D. Knott
Publisher : Springer Science & Business Media
ISBN 13 : 9780817641009
Total Pages : 316 pages
Book Rating : 4.6/5 (41 download)

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Book Synopsis Interpolating Cubic Splines by : Gary D. Knott

Download or read book Interpolating Cubic Splines written by Gary D. Knott and published by Springer Science & Business Media. This book was released on 1999 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: The study of spline functions is an outgrowth of basic mathematical concepts arising from calculus, analysis and numerical analysis. Spline modelling affects a number of fields: statistics; computer graphics; CAD programming, and other areas of applied mathematics.

Python Programming and Numerical Methods

Author : Qingkai Kong
Publisher : Academic Press
ISBN 13 : 0128195509
Total Pages : 482 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Python Programming and Numerical Methods by : Qingkai Kong

Download or read book Python Programming and Numerical Methods written by Qingkai Kong and published by Academic Press. This book was released on 2020-11-27 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: Python Programming and Numerical Methods: A Guide for Engineers and Scientists introduces programming tools and numerical methods to engineering and science students, with the goal of helping the students to develop good computational problem-solving techniques through the use of numerical methods and the Python programming language. Part One introduces fundamental programming concepts, using simple examples to put new concepts quickly into practice. Part Two covers the fundamentals of algorithms and numerical analysis at a level that allows students to quickly apply results in practical settings. Includes tips, warnings and "try this" features within each chapter to help the reader develop good programming practice Summaries at the end of each chapter allow for quick access to important information Includes code in Jupyter notebook format that can be directly run online

Spline ABC

Author : Kang Zhao
Publisher : Kang Zhao
ISBN 13 :
Total Pages : 74 pages
Book Rating : 4./5 ( download)

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Book Synopsis Spline ABC by : Kang Zhao

Download or read book Spline ABC written by Kang Zhao and published by Kang Zhao. This book was released on 2021-02-01 with total page 74 pages. Available in PDF, EPUB and Kindle. Book excerpt: What is spline and why use splines? What is B-spline and why use B-splines? What is B-spline curve and what is B-spline curve of periodic knots? How to construct B-spline curves to fit points? If you need answers for these questions then this book is right for you. It takes a Show and Tell approach that guides readers to understand the mathematical basics and master the computer programming skills of splines. The B-splines are introduced by means of Marsden Identity so to avoid the recursive definitions. Many Python code snippets are presented along with their numerical and graphical outputs to show how the spline knowledge learned in this book is used in solving numerical problems.

An Introduction to Polynomial and Cubic Spline Interpolation

Author : Malcolm Littler
Publisher :
ISBN 13 :
Total Pages : 33 pages
Book Rating : 4.:/5 (221 download)

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Book Synopsis An Introduction to Polynomial and Cubic Spline Interpolation by : Malcolm Littler

Download or read book An Introduction to Polynomial and Cubic Spline Interpolation written by Malcolm Littler and published by . This book was released on 199? with total page 33 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Numerical Methods in Engineering with Python 3

Author : Jaan Kiusalaas
Publisher : Cambridge University Press
ISBN 13 : 1107033853
Total Pages : 437 pages
Book Rating : 4.1/5 (7 download)

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Book Synopsis Numerical Methods in Engineering with Python 3 by : Jaan Kiusalaas

Download or read book Numerical Methods in Engineering with Python 3 written by Jaan Kiusalaas and published by Cambridge University Press. This book was released on 2013-01-21 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides an introduction to numerical methods for students in engineering. It uses Python 3, an easy-to-use, high-level programming language.

An Introduction to Scientific Computing with MATLAB® and Python Tutorials

Author : Sheng Xu
Publisher : CRC Press
ISBN 13 : 1000596575
Total Pages : 414 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis An Introduction to Scientific Computing with MATLAB® and Python Tutorials by : Sheng Xu

Download or read book An Introduction to Scientific Computing with MATLAB® and Python Tutorials written by Sheng Xu and published by CRC Press. This book was released on 2022-06-09 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook is written for the first introductory course on scientific computing. It covers elementary numerical methods for linear systems, root finding, interpolation, numerical integration, numerical differentiation, least squares problems, initial value problems and boundary value problems. It includes short Matlab and Python tutorials to quickly get students started on programming. It makes the connection between elementary numerical methods with advanced topics such as machine learning and parallel computing. This textbook gives a comprehensive and in-depth treatment of elementary numerical methods. It balances the development, implementation, analysis and application of a fundamental numerical method by addressing the following questions. •Where is the method applied? •How is the method developed? •How is the method implemented? •How well does the method work? The material in the textbook is made as self-contained and easy-to-follow as possible with reviews and remarks. The writing is kept concise and precise. Examples, figures, paper-and-pen exercises and programming problems are deigned to reinforce understanding of numerical methods and problem-solving skills.

Introduction To Numerical Computation, An (Second Edition)

Author : Wen Shen
Publisher : World Scientific
ISBN 13 : 9811204438
Total Pages : 339 pages
Book Rating : 4.8/5 (112 download)

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Book Synopsis Introduction To Numerical Computation, An (Second Edition) by : Wen Shen

Download or read book Introduction To Numerical Computation, An (Second Edition) written by Wen Shen and published by World Scientific. This book was released on 2019-08-28 with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book serves as a set of lecture notes for a senior undergraduate level course on the introduction to numerical computation, which was developed through 4 semesters of teaching the course over 10 years. The book requires minimum background knowledge from the students, including only a three-semester of calculus, and a bit on matrices.The book covers many of the introductory topics for a first course in numerical computation, which fits in the short time frame of a semester course. Topics range from polynomial approximations and interpolation, to numerical methods for ODEs and PDEs. Emphasis was made more on algorithm development, basic mathematical ideas behind the algorithms, and the implementation in Matlab.The book is supplemented by two sets of videos, available through the author's YouTube channel. Homework problem sets are provided for each chapter, and complete answer sets are available for instructors upon request.The second edition contains a set of selected advanced topics, written in a self-contained manner, suitable for self-learning or as additional material for an honored version of the course. Videos are also available for these added topics.

Quantitative Methods of Data Analysis for the Physical Sciences and Engineering

Author : Douglas G. Martinson
Publisher : Cambridge University Press
ISBN 13 : 1107029767
Total Pages : 631 pages
Book Rating : 4.1/5 (7 download)

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Book Synopsis Quantitative Methods of Data Analysis for the Physical Sciences and Engineering by : Douglas G. Martinson

Download or read book Quantitative Methods of Data Analysis for the Physical Sciences and Engineering written by Douglas G. Martinson and published by Cambridge University Press. This book was released on 2018-09-20 with total page 631 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides thorough and comprehensive coverage of new and important quantitative methods in data science, for graduate students and practitioners.

Hands-on Signal Analysis with Python

Author : Thomas Haslwanter
Publisher : Springer Nature
ISBN 13 : 3030579034
Total Pages : 276 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Hands-on Signal Analysis with Python by : Thomas Haslwanter

Download or read book Hands-on Signal Analysis with Python written by Thomas Haslwanter and published by Springer Nature. This book was released on 2021-05-31 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides the tools for analyzing data in Python: different types of filters are introduced and explained, such as FIR-, IIR- and morphological filters, as well as their application to one- and two-dimensional data. The required mathematics are kept to a minimum, and numerous examples and working Python programs are included for a quick start. The goal of the book is to enable also novice users to choose appropriate methods and to complete real-world tasks such as differentiation, integration, and smoothing of time series, or simple edge detection in images. An introductory section provides help and tips for getting Python installed and configured on your computer. More advanced chapters provide a practical introduction to the Fourier transform and its applications such as sound processing, as well as to the solution of equations of motion with the Laplace transform. A brief excursion into machine learning shows the powerful tools that are available with Python. This book also provides tips for an efficient programming work flow: from the use of a debugger for finding mistakes, code-versioning with git to avoid the loss of working programs, to the construction of graphical user interfaces (GUIs) for the visualization of data. Working, well-documented Python solutions are included for all exercises, and IPython/Jupyter notebooks provide additional help to get people started and outlooks for the interested reader.

Explorations In Numerical Analysis: Python Edition

Author : James V Lambers
Publisher : World Scientific
ISBN 13 : 9811227950
Total Pages : 691 pages
Book Rating : 4.8/5 (112 download)

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Book Synopsis Explorations In Numerical Analysis: Python Edition by : James V Lambers

Download or read book Explorations In Numerical Analysis: Python Edition written by James V Lambers and published by World Scientific. This book was released on 2021-01-14 with total page 691 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook is intended to introduce advanced undergraduate and early-career graduate students to the field of numerical analysis. This field pertains to the design, analysis, and implementation of algorithms for the approximate solution of mathematical problems that arise in applications spanning science and engineering, and are not practical to solve using analytical techniques such as those taught in courses in calculus, linear algebra or differential equations.Topics covered include computer arithmetic, error analysis, solution of systems of linear equations, least squares problems, eigenvalue problems, nonlinear equations, optimization, polynomial interpolation and approximation, numerical differentiation and integration, ordinary differential equations, and partial differential equations. For each problem considered, the presentation includes the derivation of solution techniques, analysis of their efficiency, accuracy and robustness, and details of their implementation, illustrated through the Python programming language.This text is suitable for a year-long sequence in numerical analysis, and can also be used for a one-semester course in numerical linear algebra.

Solving PDEs in Python

Author : Hans Petter Langtangen
Publisher : Springer
ISBN 13 : 3319524623
Total Pages : 152 pages
Book Rating : 4.3/5 (195 download)

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Book Synopsis Solving PDEs in Python by : Hans Petter Langtangen

Download or read book Solving PDEs in Python written by Hans Petter Langtangen and published by Springer. This book was released on 2017-03-21 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a concise and gentle introduction to finite element programming in Python based on the popular FEniCS software library. Using a series of examples, including the Poisson equation, the equations of linear elasticity, the incompressible Navier–Stokes equations, and systems of nonlinear advection–diffusion–reaction equations, it guides readers through the essential steps to quickly solving a PDE in FEniCS, such as how to define a finite variational problem, how to set boundary conditions, how to solve linear and nonlinear systems, and how to visualize solutions and structure finite element Python programs. This book is open access under a CC BY license.

Numerical Python

Author : Robert Johansson
Publisher : Apress
ISBN 13 : 1484242467
Total Pages : 709 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Numerical Python by : Robert Johansson

Download or read book Numerical Python written by Robert Johansson and published by Apress. This book was released on 2018-12-24 with total page 709 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage the numerical and mathematical modules in Python and its standard library as well as popular open source numerical Python packages like NumPy, SciPy, FiPy, matplotlib and more. This fully revised edition, updated with the latest details of each package and changes to Jupyter projects, demonstrates how to numerically compute solutions and mathematically model applications in big data, cloud computing, financial engineering, business management and more. Numerical Python, Second Edition, presents many brand-new case study examples of applications in data science and statistics using Python, along with extensions to many previous examples. Each of these demonstrates the power of Python for rapid development and exploratory computing due to its simple and high-level syntax and multiple options for data analysis. After reading this book, readers will be familiar with many computing techniques including array-based and symbolic computing, visualization and numerical file I/O, equation solving, optimization, interpolation and integration, and domain-specific computational problems, such as differential equation solving, data analysis, statistical modeling and machine learning. What You'll Learn Work with vectors and matrices using NumPy Plot and visualize data with Matplotlib Perform data analysis tasks with Pandas and SciPy Review statistical modeling and machine learning with statsmodels and scikit-learn Optimize Python code using Numba and Cython Who This Book Is For Developers who want to understand how to use Python and its related ecosystem for numerical computing.

Introduction to Numerical Analysis

Author : J. Stoer
Publisher : Springer Science & Business Media
ISBN 13 : 1475722729
Total Pages : 674 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Introduction to Numerical Analysis by : J. Stoer

Download or read book Introduction to Numerical Analysis written by J. Stoer and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 674 pages. Available in PDF, EPUB and Kindle. Book excerpt: On the occasion of this new edition, the text was enlarged by several new sections. Two sections on B-splines and their computation were added to the chapter on spline functions: Due to their special properties, their flexibility, and the availability of well-tested programs for their computation, B-splines play an important role in many applications. Also, the authors followed suggestions by many readers to supplement the chapter on elimination methods with a section dealing with the solution of large sparse systems of linear equations. Even though such systems are usually solved by iterative methods, the realm of elimination methods has been widely extended due to powerful techniques for handling sparse matrices. We will explain some of these techniques in connection with the Cholesky algorithm for solving positive definite linear systems. The chapter on eigenvalue problems was enlarged by a section on the Lanczos algorithm; the sections on the LR and QR algorithm were rewritten and now contain a description of implicit shift techniques. In order to some extent take into account the progress in the area of ordinary differential equations, a new section on implicit differential equa tions and differential-algebraic systems was added, and the section on stiff differential equations was updated by describing further methods to solve such equations.

Introduction to Chemical Engineering Computing

Author : Bruce A. Finlayson
Publisher : John Wiley & Sons
ISBN 13 : 1118888375
Total Pages : 502 pages
Book Rating : 4.1/5 (188 download)

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Book Synopsis Introduction to Chemical Engineering Computing by : Bruce A. Finlayson

Download or read book Introduction to Chemical Engineering Computing written by Bruce A. Finlayson and published by John Wiley & Sons. This book was released on 2014-03-05 with total page 502 pages. Available in PDF, EPUB and Kindle. Book excerpt: Step-by-step instructions enable chemical engineers to master key software programs and solve complex problems Today, both students and professionals in chemical engineering must solve increasingly complex problems dealing with refineries, fuel cells, microreactors, and pharmaceutical plants, to name a few. With this book as their guide, readers learn to solve these problems using their computers and Excel, MATLAB, Aspen Plus, and COMSOL Multiphysics. Moreover, they learn how to check their solutions and validate their results to make sure they have solved the problems correctly. Now in its Second Edition, Introduction to Chemical Engineering Computing is based on the author’s firsthand teaching experience. As a result, the emphasis is on problem solving. Simple introductions help readers become conversant with each program and then tackle a broad range of problems in chemical engineering, including: Equations of state Chemical reaction equilibria Mass balances with recycle streams Thermodynamics and simulation of mass transfer equipment Process simulation Fluid flow in two and three dimensions All the chapters contain clear instructions, figures, and examples to guide readers through all the programs and types of chemical engineering problems. Problems at the end of each chapter, ranging from simple to difficult, allow readers to gradually build their skills, whether they solve the problems themselves or in teams. In addition, the book’s accompanying website lists the core principles learned from each problem, both from a chemical engineering and a computational perspective. Covering a broad range of disciplines and problems within chemical engineering, Introduction to Chemical Engineering Computing is recommended for both undergraduate and graduate students as well as practicing engineers who want to know how to choose the right computer software program and tackle almost any chemical engineering problem.

Introduction to Machine Learning with Python

Author : Andreas C. Müller
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1449369898
Total Pages : 400 pages
Book Rating : 4.4/5 (493 download)

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Book Synopsis Introduction to Machine Learning with Python by : Andreas C. Müller

Download or read book Introduction to Machine Learning with Python written by Andreas C. Müller and published by "O'Reilly Media, Inc.". This book was released on 2016-09-26 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination. You’ll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Müller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book. With this book, you’ll learn: Fundamental concepts and applications of machine learning Advantages and shortcomings of widely used machine learning algorithms How to represent data processed by machine learning, including which data aspects to focus on Advanced methods for model evaluation and parameter tuning The concept of pipelines for chaining models and encapsulating your workflow Methods for working with text data, including text-specific processing techniques Suggestions for improving your machine learning and data science skills