Build efficient, high-speed programs using the high-performance NumPy mathematical library
This book is for the scientists, engineers, programmers, or analysts looking for a high-quality, open source mathematical library. Knowledge of Python is assumed. Also, some affinity, or at least interest, in mathematics and statistics is required. However, I have provided brief explanations and pointers to learning resources.
In today’s world of science and technology, it’s all about speed and flexibility. When it comes to scientific computing, NumPy tops the list. NumPy will give you both speed and high productivity. This book will walk you through NumPy with clear, step-by-step examples and just the right amount of theory. The book focuses on the fundamentals of NumPy, including array objects, functions, and matrices, each of them explained with practical examples. You will then learn about different NumPy modules while performing mathematical operations such as calculating the Fourier transform, finding the inverse of a matrix, and determining eigenvalues, among many others. This book is a one-stop solution to knowing the ins and outs of the vast NumPy library, empowering you to use its wide range of mathematical features to build efficient, high-speed programs.
Chapter 1: NumPy Quick Start
Chapter 2: Beginning with NumPy Fundamentals
Chapter 3: Getting Familiar with Commonly Used Functions
Chapter 4: Convenience Functions for Your Convenience
Chapter 5: Working with Matrices and ufuncs
Chapter 6: Moving Further with NumPy Modules
Chapter 7: Peeking Into Special Routines
Chapter 8: Assure Quality with Testing
Chapter 9: Plotting with matplotlib
Chapter 10: When NumPy is Not Enough – SciPy and Beyond
Chapter 11: Playing with Pygame
Appendix A: Pop Quiz Answers
Appendix B: Additional Online Resources
Appendix C: NumPy Functions’ References