Book Image

NumPy Cookbook - Second Edition

By : Ivan Idris
Book Image

NumPy Cookbook - Second Edition

By: Ivan Idris

Overview of this book

<p>NumPy has the ability to give you speed and high productivity. High performance calculations can be done easily with clean and efficient code, and it allows you to execute complex algebraic and mathematical computations in no time.</p> <p>This book will give you a solid foundation in NumPy arrays and universal functions. Starting with the installation and configuration of IPython, you'll learn about advanced indexing and array concepts along with commonly used yet effective functions. You will then cover practical concepts such as image processing, special arrays, and universal functions. You will also learn about plotting with Matplotlib and the related SciPy project with the help of examples. At the end of the book, you will study how to explore atmospheric pressure and its related techniques. By the time you finish this book, you'll be able to write clean and fast code with NumPy.</p>

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NumPy Cookbook - Second Edition
Ivan Idris
Apr, 2015 | 258 pages
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Table of Contents (19 chapters)
NumPy Cookbook Second Edition
NumPy Cookbook Second Edition
Credits
Credits
About the Author
About the Author
About the Reviewers
About the Reviewers
www.PacktPub.com
www.PacktPub.com
Preface
Preface
Free Chapter
1
Winding Along with IPython
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
2
Advanced Indexing and Array Concepts
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
Indexing with Booleans
Stride tricks for Sudoku
Broadcasting arrays
3
Getting to Grips with Commonly Used Functions
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
4
Connecting NumPy with the Rest of the World
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
Installing 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
5
Audio and Image Processing
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
6
Special Arrays and Universal Functions
Special Arrays and Universal Functions
Introduction
Creating a universal function
Finding Pythagorean triples
Performing string operations with chararray
Creating a masked array
Ignoring negative and extreme values
Creating a scores table with a recarray function
7
Profiling and Debugging
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
8
Quality Assurance
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
Testing the BDD way
9
Speeding Up Code with Cython
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
10
Fun with Scikits
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
Installing pandas
Estimating correlation of stock returns with pandas
Loading data as pandas objects from statsmodels
Resampling time series data
11
Latest and Greatest NumPy
Latest and Greatest NumPy
Introduction
Fancy indexing in place for ufuncs with the at() method
Partial sorting via selection for fast median with the partition() function
Skipping NaNs with the nanmean(), nanvar(), and nanstd() functions
Creating value initialized arrays with the full() and full_like() functions
Random sampling with numpy.random.choice()
Using the datetime64 type and related API
12
Exploratory and Predictive Data Analysis with NumPy
Exploratory and Predictive Data Analysis with NumPy
Introduction
Exploring atmospheric pressure
Exploring the day-to-day pressure range
Studying annual atmospheric pressure averages
Analyzing maximum visibility
Predicting pressure with an autoregressive model
Predicting pressure with a moving average model
Studying intrayear average pressure
Studying extreme values of atmospheric pressure
Index
Index

Installing IPython

IPython can be installed in various ways, depending on your operating system. For the terminal-based shell, there is a dependency on readline. The web notebook requires tornado and zmq.

In addition to installing IPython, we will install setuptools, which gives you the easy_install command. The easy_install command is a popular package manager for Python. pip can be installed once you have easy_install. The pip command is similar to easy_install and adds options such as uninstalling.

How to do it...

This section describes how IPython can be installed on Windows, Mac OS X, and Linux. It also describes how to install IPython and its dependencies with easy_install and pip, or from source:

  • Installing IPython and setuptools on Windows: A binary Windows installer for Python 2 or Python 3 is available on the IPython website. Also see http://ipython.org/ipython-doc/stable/install/install.html#windows.

    Install setuptools with an installer from http://pypi.python.org/pypi/setuptools#files. Then install pip, like this:

    cd C:\Python27\scripts
python .\easy_install-27-script.py pip

  • Installing IPython on Mac OS X: Install the Apple Developer Tools (Xcode) if necessary. Xcode can be found at https://developer.apple.com/xcode/. Follow the easy_install/pip instructions or the instructions for installation from source provided later in this section.

  • Installing IPython on Linux: Since there are so many Linux distributions, this section will not be exhaustive:

    • On Debian, type the following command:

      $ su – aptitude install ipython python-setuptools

    • On Fedora, the magic command is as follows:

      $ su – yum install ipython python-setuptools-devel

    • The following command will install IPython on Gentoo:

      $ su – emerge ipython

    • For Ubuntu, the install command is as follows:

      $ sudo apt-get install ipython python-setuptools

  • Installing IPython with easy_install or pip: Install IPython and all the dependencies required for the recipes in this chapter with easy_install using the following command:

    $ sudo easy_install ipython pyzmq tornado readline

    Alternatively, you can first install pip with easy_install by typing this command in your terminal:

    $ sudo easy_install pip

    After that, install IPython using pip:

    $ sudo pip install ipython pyzmq tornado readline

  • Installing from source: If you want to use the bleeding-edge development version, then installing from source is for you:

    1. Download the latest source archive from https://github.com/ipython/ipython/archive/master.zip.

    2. Unpack the source code from the archive:

      $ tar xzf ipython-<version>.tar.gz

    3. Instead, if you have Git installed, you can clone the Git repository:

      $ git clone https://github.com/ipython/ipython.git

    4. Go to the root directory within the downloaded source:

      $ cd ipython

    5. Run the setup script. This may require you to run the command with sudo, as follows:

      $ sudo python setup.py install

How it works...

We installed IPython using several methods. Most of these methods install the latest stable release, except when you install from source, which will install the development version.

See also

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