04722nam 2200673 450 991081702020332120200520144314.01-78398-771-5(CKB)2670000000599092(EBL)1973843(SSID)ssj0001470906(PQKBManifestationID)11933442(PQKBTitleCode)TC0001470906(PQKBWorkID)11433566(PQKB)10331791(Au-PeEL)EBL1973843(CaPaEBR)ebr11025925(CaONFJC)MIL734276(OCoLC)906041041(MiAaPQ)EBC1973843(PPN)228045304(EXLCZ)99267000000059909220150312h20152015 uy 0engur|n|---|||||txtccrLearning 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-SilvaSecond edition.Birmingham, England ;Mumbai, [India] :Packt Publishing,2015.©20151 online resource (188 p.)Community Experience DistilledIncludes index.1-78398-770-7 1-336-02990-0 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 conversionsShape 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 decompositionSolversSummary; 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; SummaryChapter 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 oxidesA 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; IndexThis book targets programmers and scientists who have basic Python knowledge and who are keen to perform scientific and numerical computations with SciPy.Community experience distilled.Numerical analysisData processingPython (Computer program language)Numerical analysisData processing.Python (Computer program language)519.4Rojas Sergio J.G1683415Christensen Erik A.Blanco-Silva Francisco J.MiAaPQMiAaPQMiAaPQBOOK9910817020203321Learning SciPy for numerical and scientific computing4054130UNINA