Introduction to Cubic Spline Interpolation with Examples in Python PDF Download
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Author: Thomas Maindl
Publisher: Createspace Independent Publishing Platform
ISBN: 9781987487374
Category :
Languages : en
Pages : 90
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Book Description
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
Author: Thomas Maindl
Publisher: Createspace Independent Publishing Platform
ISBN: 9781987487374
Category :
Languages : en
Pages : 90
Get Book Here
Book Description
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
Author: Titus A. Beu
Publisher: CRC Press
ISBN: 1466569670
Category : Mathematics
Languages : en
Pages : 676
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Book Description
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.
Author: Gary D. Knott
Publisher: Springer Science & Business Media
ISBN: 9780817641009
Category : Computers
Languages : en
Pages : 316
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Book Description
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.
Author: Qingkai Kong
Publisher: Academic Press
ISBN: 0128195509
Category : Technology & Engineering
Languages : en
Pages : 482
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Book Description
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
Author: Kang Zhao
Publisher: Kang Zhao
ISBN:
Category : Science
Languages : en
Pages : 74
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Book Description
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.
Author: Malcolm Littler
Publisher:
ISBN:
Category : Interpolation
Languages : en
Pages : 33
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Book Description
Author: Jaan Kiusalaas
Publisher: Cambridge University Press
ISBN: 1107033853
Category : Computers
Languages : en
Pages : 437
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Book Description
Provides an introduction to numerical methods for students in engineering. It uses Python 3, an easy-to-use, high-level programming language.
Author: Sheng Xu
Publisher: CRC Press
ISBN: 1000596575
Category : Mathematics
Languages : en
Pages : 414
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Book Description
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.
Author: Wen Shen
Publisher: World Scientific
ISBN: 9811204438
Category : Mathematics
Languages : en
Pages : 339
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Book Description
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.
Author: Douglas G. Martinson
Publisher: Cambridge University Press
ISBN: 1107029767
Category : Computers
Languages : en
Pages : 631
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Book Description
Provides thorough and comprehensive coverage of new and important quantitative methods in data science, for graduate students and practitioners.
