NumPy cookbook
Subtitle: over 90 fascinating recipes to learn and perform
By: Ivan Idris
Edition: Second edition.
Series: Community Experience Distilled; Community experience distilled
Publisher: Packt Publishing
Published: 2015
Place of publication: Birmingham, UK
Language: eng
ISBN-13: 9781784399825; 9781784390945
Subjects: Numerical analysis; Data processing; Python (Computer program language); COMPUTERS; Computer Literacy; Computer Science; Data Processing; Hardware; General; Information Technology; Machine Theory; Reference
Other titles: Over 90 fascinating recipes to learn and perform
Description: If 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.
Notes: Includes index.

"Quick answers to common problems."
Table of contents: title: Cover; 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.; title: Indexing 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.; title: Interfacing 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.; title: Performing 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.; title: Testing 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.