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Autore: | Rojas Sergio J.G |
Titolo: | Learning SciPy for numerical and scientific computing : quick solutions to complex numerical problems in physics, applied mathematics, and science with SciPy / / Sergio J. Rojas G., Erik A. Christensen, Francisco J. Blanco-Silva |
Pubblicazione: | Birmingham, England ; ; Mumbai, [India] : , : Packt Publishing, , 2015 |
©2015 | |
Edizione: | Second edition. |
Descrizione fisica: | 1 online resource (188 p.) |
Disciplina: | 519.4 |
Soggetto topico: | Numerical analysis - Data processing |
Python (Computer program language) | |
Persona (resp. second.): | ChristensenErik A. |
Blanco-SilvaFrancisco J. | |
Note generali: | Includes index. |
Nota di contenuto: | Cover; Copyright; Credits; About the Authors; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Introduction to SciPy; What is SciPy?; Installing SciPy; Installing SciPy on Mac OS X; Installing SciPy on Unix/Linux; Installing SciPy on Windows; Testing SciPy installation; SciPy organization; How to find documentation; Scientific visualization; How to open IPython Notebooks; Summary; Chapter 2: Working with the NumPy Array As a First Step to SciPy; Object essentials; Using datatype; Indexing and slicing arrays; The array object; Array conversions |
Shape selection/manipulationsObject calculations; Array routines; Routines to create arrays; Routines for the combination of two or more arrays; Routines for array manipulation; Routines to extract information from arrays; Summary; Chapter 3: SciPy for Linear Algebra; Vector creation; Vector operations; Addition/subtraction; Scalar/Dot product; Cross / Vector product - on three-dimensional space vectors; Creating a matrix; Matrix methods; Operations between matrices; Functions on matrices; Eigenvalue problems and matrix decompositions; Image compression via the singular value decomposition | |
SolversSummary; Chapter 4: SciPy for Numerical Analysis; Evaluation of special functions; Convenience and test functions; Univariate polynomials; The gamma function; The Riemann zeta function; Airy and Bairy functions; The Bessel and Struve functions; Other special functions; Interpolation; Regression; Optimization; Minimization; Roots; Integration; Exponential/logarithm integrals; Trigonometric and hyperbolic trigonometric integrals; Elliptic integrals; Gamma and beta integrals ; Numerical integration; Ordinary differential equations; Lorenz attractors; Summary | |
Chapter 5: SciPy for Signal ProcessingDiscrete Fourier Transforms; Signal construction; Filters; LTI system theory; Filter design; Window functions; Image interpolation; Morphology; Summary; Chapter 6: SciPy for Data Mining; Descriptive statistics; Distributions; Interval estimation, correlation measures, and statistical tests; Distribution fitting; Distances; Clustering; Vector quantization and k-means; Hierarchical clustering; Clustering mammals by their dentition; Summary; Chapter 7: SciPy for Computational Geometry; Structural model of oxides | |
A finite element solver for Laplace's equationSummary; Chapter 8: Interaction with Other Languages; Interaction with Fortran; Interaction with C/C++; Interaction with MATLAB/Octave; Summary; Index | |
Sommario/riassunto: | This book targets programmers and scientists who have basic Python knowledge and who are keen to perform scientific and numerical computations with SciPy. |
Titolo autorizzato: | Learning SciPy for numerical and scientific computing |
ISBN: | 1-78398-771-5 |
Formato: | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione: | Inglese |
Record Nr.: | 9910817020203321 |
Lo trovi qui: | Univ. Federico II |
Opac: | Controlla la disponibilità qui |