LEADER 05139nam 2200673 450 001 9910463835903321 005 20200520144314.0 035 $a(CKB)2670000000613625 035 $a(EBL)2039895 035 $a(SSID)ssj0001539247 035 $a(PQKBManifestationID)11880344 035 $a(PQKBTitleCode)TC0001539247 035 $a(PQKBWorkID)11530996 035 $a(PQKB)10823881 035 $a(MiAaPQ)EBC2039895 035 $a(PPN)228043409 035 $a(Au-PeEL)EBL2039895 035 $a(CaPaEBR)ebr11050802 035 $a(CaONFJC)MIL778674 035 $a(OCoLC)910639617 035 $a(EXLCZ)992670000000613625 100 $a20150513h20152015 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aNumPy cookbook $eover 90 fascinating recipes to learn and perform mathematical, scientific, and engineering Python computations with NumPy /$fIvan Idris 205 $aSecond edition. 210 1$aBirmingham, [England] :$cPackt Publishing,$d2015. 210 4$dİ2015 215 $a1 online resource (258 p.) 225 1 $aCommunity Experience Distilled 300 $a"Quick answers to common problems"--Cover. 300 $aIncludes index. 311 $a1-78439-094-1 311 $a1-78439-982-5 327 $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 an IPython notebook; Exporting an IPython 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 327 $aIndexing with a list of locationsIndexing with Booleans; Stride tricks for Sudoku; Broadcasting arrays; Chapter 3: Getting to Grips with Commonly Used Functions; Introduction; Summing Fibonacci numbers; Finding prime factors; Finding palindromic numbers; The steady state vector; Discovering a power law; Trading periodically on dips; Simulating trading at random; Sieving integers with the Sieve of Eratosthenes; 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 327 $aInterfacing with RInstalling JPype; Sending a NumPy array to JPype; Installing Google App Engine; Deploying the NumPy code on the Google Cloud; Running the NumPy code in a PythonAnywhere web console; Chapter 5: Audio and Image Processing; Introduction; Loading images into memory maps; 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 327 $aPerforming string operations with chararrayCreating a masked array; Ignoring negative and extreme values; Creating a scores table with a recarray function; Chapter 7: Profiling 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 327 $aTesting code with docstringsWriting unit tests; Testing code with mocks; Testing the BDD way; Chapter 9: Speeding Up Code with Cython; Introduction; Installing Cython; Building a Hello World program; Using Cython with NumPy; Calling C functions; Profiling the Cython code; Approximating factorials with Cython; Chapter 10: Fun with Scikits; Introduction; Installing scikit-learn; Loading an example dataset; Clustering Dow Jones stocks with scikits-learn; Installing statsmodels; Performing a normality test with statsmodels; Installing scikit-image; Detecting corners; Detecting edges 327 $aInstalling pandas 330 $aIf you are a Python developer with some experience of working on scientific, mathematical, and statistical applications and want to gain an expert understanding of NumPy programming in relation to science, math, and finance using practical recipes, then this book is for you. 410 0$aCommunity experience distilled. 606 $aNumerical analysis$xData processing 606 $aObject-oriented programming (Computer science) 608 $aElectronic books. 615 0$aNumerical analysis$xData processing. 615 0$aObject-oriented programming (Computer science) 676 $a519.4 700 $aIdris$b Ivan$0868465 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910463835903321 996 $aNumPy cookbook$92207156 997 $aUNINA