Book Image

IPython Interactive Computing and Visualization Cookbook - Second Edition

By : Cyrille Rossant
Book Image

IPython Interactive Computing and Visualization Cookbook - Second Edition

By: Cyrille Rossant

Overview of this book

Python is one of the leading open source platforms for data science and numerical computing. IPython and the associated Jupyter Notebook offer efficient interfaces to Python for data analysis and interactive visualization, and they constitute an ideal gateway to the platform. IPython Interactive Computing and Visualization Cookbook, Second Edition contains many ready-to-use, focused recipes for high-performance scientific computing and data analysis, from the latest IPython/Jupyter features to the most advanced tricks, to help you write better and faster code. You will apply these state-of-the-art methods to various real-world examples, illustrating topics in applied mathematics, scientific modeling, and machine learning. The first part of the book covers programming techniques: code quality and reproducibility, code optimization, high-performance computing through just-in-time compilation, parallel computing, and graphics card programming. The second part tackles data science, statistics, machine learning, signal and image processing, dynamical systems, and pure and applied mathematics.
Table of Contents (19 chapters)
IPython Interactive Computing and Visualization CookbookSecond Edition
Contributors
Preface
Index

Teaching programming in the Notebook with IPython Blocks


The Jupyter Notebook is not only a tool for scientific research and data analysis but also a great tool for teaching. In this recipe, we show a simple and fun Python library for teaching programming notions: IPython Blocks (available at http://ipythonblocks.org). This library allows you or your students to create grids of colorful blocks. You can change the color and size of individual blocks, and you can even animate your grids. There are many basic technical notions you can illustrate with this tool. The visual aspect of this tool makes the learning process more effective and engaging.

In this recipe, we will notably perform the following tasks:

  • Illustrate matrix multiplication with an animation

  • Display an image as a block grid

Getting ready

To install IPython Blocks, type pip install ipythonblocks in a Terminal.

How to do it...

  1. First, we import some modules as follows:

    >>> import time
        from IPython.display import clear_output...