基本信息
源码名称:NumPy Cookbook.pdf
源码大小:2.47M
文件格式:.pdf
开发语言:Python
更新时间:2021-01-27
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源码介绍
Table of Contents Preface 1 Chapter 1: Winding Along with IPython 5 Introduction 5 Installing IPython 6 Using IPython as a shell 8 Reading manual pages 10 Installing Matplotlib 11 Running a web notebook 12 Exporting a web notebook 14 Importing a web notebook 16 Configuring a notebook server 20 Exploring the SymPy profile 23 Chapter 2: Advanced Indexing and Array Concepts 25 Introduction 25 Installing SciPy 26 Installing PIL 28 Resizing images 29 Creating views and copies 32 Flipping Lena 34 Fancy indexing 36 Indexing with a list of locations 38 Indexing with booleans 40 Stride tricks for Sudoku 42 Broadcasting arrays 45 Chapter 3: Get to Grips with Commonly Used Functions 49 Introduction 50 Summing Fibonacci numbers 50 Finding prime factors 54 ii Table of Contents Finding palindromic numbers 56 The steady state vector determination 58 Discovering a power law 64 Trading periodically on dips 67 Simulating trading at random 70 Sieving integers with the Sieve of Erasthothenes 72 Chapter 4: Connecting NumPy with the Rest of the World 75 Introduction 75 Using the buffer protocol 76 Using the array interface 79 Exchanging data with MATLAB and Octave 80 Installing RPy2 82 Interfacing with R 82 Installing JPype 84 Sending a NumPy array to JPype 84 Installing Google App Engine 86 Deploying NumPy code in the Google cloud 88 Running NumPy code in a Python Anywhere web console 90 Setting up PiCloud 92 Chapter 5: Audio and Image Processing 95 Introduction 95 Loading images into memory map 96 Combining images 100 Blurring images 104 Repeating audio fragments 108 Generating sounds 110 Designing an audio filter 114 Edge detection with the Sobel filter 117 Chapter 6: Special Arrays and Universal Functions 121 Introduction 121 Creating a universal function 121 Finding Pythagorean triples 122 Performing string operations with chararray 124 Creating a masked array 125 Ignoring negative and extreme values 128 Creating a scores table with recarray 131 Chapter 7: Profiling and Debugging 135 Introduction 135 Profiling with timeit 135 Profiling with IPython 139 iii Table of Contents Installing line_profiler 142 Profiling code with line_profiler 143 Profiling code with the cProfile extension 144 Debugging with IPython 146 Debugging with pudb 148 Chapter 8: Quality Assurance 151 Introduction 151 Installing Pyflakes 151 Performing static analysis with Pyflakes 152 Analyzing code with Pylint 153 Performing static analysis with Pychecker 155 Testing code with docstrings 156 Writing unit tests 158 Testing code with mocks 162 Testing the BDD way 164 Chapter 9: Speed Up Code with Cython 169 Introduction 169 Installing Cython 170 Building a Hello World program 170 Using Cython with NumPy 172 Calling C functions 173 Profiling Cython code 175 Approximating factorials with Cython 178 Chapter 10: Fun with Scikits 183 Introduction 183 Installing scikits-learn 184 Loading an example dataset 184 Clustering Dow Jones stocks with scikits-learn 185 Installing scikits-statsmodels 189 Performing a normality test with scikits-statsmodels 190 Installing scikits-image 191 Detecting corners 191 Detecting edges 193 Installing Pandas 194 Estimating stock returns correlation with Pandas 195 Loading data as pandas objects from statsmodels 198 Resampling time series data 200 Index 205