Applied numerical methods with Python for engineers and scientists / Steven C. Chapra and David E. Clough.

By: Contributor(s): Material type: TextTextPublisher: New York : McGraw Hill LLC, 2022Edition: First editionDescription: xiii, 652 pages ; 28 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
Subject(s): Additional physical formats: Online version:: Applied numerical methods w/python for engineers and scientistsDDC classification:
  • 518.02855133 C368a 23
LOC classification:
  • TA335 .C53 2022
Contents:
Part One. Modeling, computers, and error analysis -- Mathematical modeling, numerical methods, and problem solving -- Python fundamentals -- Programming in python -- Roundoff and truncation errors -- Part Two. Roots and optimization -- Roots: bracketing methods -- Roots: open methods -- Optimization -- Part Three. Linear systems -- Linear algebraic equations and matrices -- Gauss elimination -- LU factorization -- Matrix inverse and condition -- Iterative methods -- Eigenvalues -- Part Four. Curve fitting -- Straight-line linear regression -- General linear and nonlinear regression -- Fourier analysis -- Polynomial interpolation -- Splines and piecewise interpolation -- Part Five. Integration and differentiation -- Numerical integration formulas -- Numerical integration of functions -- Numerical differentiation -- Part Six. Ordinary differential equations -- Initial-value problems -- Adaptive methods and stiff systems -- Boundary-value problems.
Summary: "When we first learned to use computers as students in the 1960s, Fortran was the language of choice for most engineering and scientific computations. Over the ensuing half century, numerous other languages have proven useful for implementing the numerical calculations that are so valuable to our research and teaching. Along with a succession of improved Fortran versions, other languages such as Algol, Basic, Pascal, and C/C++ have all found their way into our computational toolbox. The basic content, organization, and pedagogy of this book is like our other numerical methods textbooks. In particular, a conversational writing style is intentionally maintained in order to make the book easier to read. This book tries to speak directly to the reader and is designed in part to be a tool for self-teaching. As such, we also believe it will have value outside the classroom for professionals desiring to gain proficiency in both numerical methods and Python"-- Provided by publisher.
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Holdings
Item type Current library Shelving location Call number Copy number Status Date due Barcode
Books Books Main Library Graduate School Library GRD 518.02855133 C368a 2022 (Browse shelf(Opens below)) 1-1 Available 031865

Includes bibliographical references and index.

Part One. Modeling, computers, and error analysis -- Mathematical modeling, numerical methods, and problem solving -- Python fundamentals -- Programming in python -- Roundoff and truncation errors -- Part Two. Roots and optimization -- Roots: bracketing methods -- Roots: open methods -- Optimization -- Part Three. Linear systems -- Linear algebraic equations and matrices -- Gauss elimination -- LU factorization -- Matrix inverse and condition -- Iterative methods -- Eigenvalues -- Part Four. Curve fitting -- Straight-line linear regression -- General linear and nonlinear regression -- Fourier analysis -- Polynomial interpolation -- Splines and piecewise interpolation -- Part Five. Integration and differentiation -- Numerical integration formulas -- Numerical integration of functions -- Numerical differentiation -- Part Six. Ordinary differential equations -- Initial-value problems -- Adaptive methods and stiff systems -- Boundary-value problems.

"When we first learned to use computers as students in the 1960s, Fortran was the language of choice for most engineering and scientific computations. Over the ensuing half century, numerous other languages have proven useful for implementing the numerical calculations that are so valuable to our research and teaching. Along with a succession of improved Fortran versions, other languages such as Algol, Basic, Pascal, and C/C++ have all found their way into our computational toolbox. The basic content, organization, and pedagogy of this book is like our other numerical methods textbooks. In particular, a conversational writing style is intentionally maintained in order to make the book easier to read. This book tries to speak directly to the reader and is designed in part to be a tool for self-teaching. As such, we also believe it will have value outside the classroom for professionals desiring to gain proficiency in both numerical methods and Python"-- Provided by publisher.

Ages 18+ McGrawHill Education

Grades 10-12 McGrawHill Education

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