LEADER 05042nam 2200709Ia 450 001 9910957689903321 005 20200520144314.0 010 $a9781283739047 010 $a1283739046 010 $a9781849518932 010 $a1849518939 035 $a(CKB)2670000000271376 035 $a(EBL)1057942 035 $a(OCoLC)818818959 035 $a(SSID)ssj0000796584 035 $a(PQKBManifestationID)11484448 035 $a(PQKBTitleCode)TC0000796584 035 $a(PQKBWorkID)10792672 035 $a(PQKB)10694805 035 $a(Au-PeEL)EBL1057942 035 $a(CaPaEBR)ebr10623093 035 $a(CaONFJC)MIL405154 035 $a(PPN)227981839 035 $a(FR-PaCSA)88850838 035 $a(MiAaPQ)EBC1057942 035 $a(FRCYB88850838)88850838 035 $a(DE-B1597)723394 035 $a(DE-B1597)9781849518932 035 $a(EXLCZ)992670000000271376 100 $a20121130d2012 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aNumPy cookbook /$fIvan Idris 205 $a1st ed. 210 $aBirmingham, [Eng.] $cPackt Publishing$d2012 215 $a1 online resource (226 p.) 300 $aIncludes index. 311 08$a9781849518925 311 08$a1849518920 327 $aCover; Copyright; Credits; About the Author; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1:Winding Along with IPython; Introduction; Installing IPython; Using IPython as a shell; Reading manual pages; Installing Matplotlib; Running a web notebook; Exporting a web notebook; Importing a web notebook; Configuring a notebook server; Exploring the SymPy profile; Chapter 2:Advanced Indexing and Array Concepts; Introduction; Installing SciPy; Installing PIL; Resizing images; Creating views and copies; Flipping Lena; Fancy indexing; Indexing with a list of locations 327 $aIndexing with booleansStride tricks for Sudoku; Broadcasting arrays; Chapter 3:Get to Grips with Commonly Used Functions; Introduction; Summing Fibonacci numbers; Finding prime factors; Finding palindromic numbers; The steady state vector determination; Discovering a power law; Trading periodically on dips; Simulating trading at random; Sieving integers with the Sieve of Erasthothenes; Chapter 4:Connecting NumPy with the Rest of the World; Introduction; Using the buffer protocol; Using the array interface; Exchanging data with MATLAB and Octave; Installing RPy2; Interfacing with R 327 $aInstalling JPypeSending a NumPy array to JPype; Installing Google App Engine; Deploying NumPy code in the Google cloud; Running NumPy code in a Python Anywhere web console; Setting up PiCloud; Chapter 5:Audio and Image Processing; Introduction; Loading images into memory map; Combining images; Blurring images; Repeating audio fragments; Generating sounds; Designing an audio filter; Edge detection with the Sobel filter; Chapter 6:Special Arrays and Universal Functions; Introduction; Creating a universal function; Finding Pythagorean triples; Performing string operations with chararray 327 $aCreating a masked arrayIgnoring negative and extreme values; Creating a scores table with recarray; Chapter 7:and Debugging; Introduction; Profiling with timeit; Profiling with IPython; Installing line_profiler; Profiling code with line_profiler; Profiling code with the cProfile extension; Debugging with IPython; Debugging with pudb; Chapter 8:Quality Assurance; Introduction; Installing Pyflakes; Performing static analysis with Pyflakes; Analyzing code with Pylint; Performing static analysis with Pychecker; Testing code with docstrings; Writing unit tests; Testing code with mocks 327 $aTesting the BDD wayChapter 9:Speed Up Code with Cython; Introduction; Installing Cython; Building a Hello World program; Using Cython with NumPy; Calling C functions; Profiling Cython code; Approximating factorials with Cython; Chapter 10:Fun with Scikits; Introduction; Installing scikits-learn; Loading an example dataset; Clustering Dow Jones stocks with scikits-learn; Installing scikits-statsmodels; Performing a normality test with scikits-statsmodels; Installing scikits-image; Detecting corners; Detecting edges; Installing Pandas; Estimating stock returns correlation with Pandas 327 $aLoading data as pandas objects from statsmodels 330 $aWritten in Cookbook style, the code examples will take your Numpy skills to the next level. This book will take Python developers with basic Numpy skills to the next level through some practical recipes. 606 $aPython (Computer program language) 606 $aNumerical analysis$xData processing 615 0$aPython (Computer program language) 615 0$aNumerical analysis$xData processing. 676 $a006.76 700 $aIdris$b Ivan$01624574 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910957689903321 996 $aNumPy cookbook$94341611 997 $aUNINA