An open access book on scientific visualization using python and matplotlib
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
 
 
 
Nicolas P. Rougier a6e0607fa8
Merge pull request #55 from zhangkaihua88/master
2 days ago
.github Create FUNDING.yml 2 years ago
code Fix issue #50 1 week ago
cover First public release 7 months ago
figures Remove MacOS .DS_Store files 7 months ago
fonts Remove MacOS .DS_Store files 7 months ago
images Fixed links 7 months ago
pdf Added book.pdf on GitHub since HAL copy is corrupted 7 months ago
rst fix 2 days ago
tex Remove MacOS .DS_Store files 7 months ago
.gitignore Added gitignore + adde link to README 7 months ago
LICENSE.txt First public release 7 months ago
Makefile Added compressed pdf option 7 months ago
README.md Added gitignore + adde link to README 7 months ago
rst2latex.py Added book.pdf on GitHub since HAL copy is corrupted 7 months ago

README.md

Scientific Visualization: Python + Matplotlib

Nicolas P. Rougier, Bordeaux, November 2021.

Front cover

The Python scientific visualisation landscape is huge. It is composed of a myriad of tools, ranging from the most versatile and widely used down to the more specialised and confidential. Some of these tools are community based while others are developed by companies. Some are made specifically for the web, others are for the desktop only, some deal with 3D and large data, while others target flawless 2D rendering. In this landscape, Matplotlib has a very special place. It is a versatile and powerful library that allows you to design very high quality figures, suitable for scientific publishing. It also offers a simple and intuitive interface as well as an object oriented architecture that allows you to tweak anything within a figure. Finally, it can be used as a regular graphic library in order to design non‐scientific figures. This book is organized into four parts. The first part considers the fundamental principles of the Matplotlib library. This includes reviewing the different parts that constitute a figure, the different coordinate systems, the available scales and projections, and we’ll also introduce a few concepts related to typography and colors. The second part is dedicated to the actual design of a figure. After introducing some simple rules for generating better figures, we’ll then go on to explain the Matplotlib defaults and styling system before diving on into figure layout organization. We’ll then explore the different types of plot available and see how a figure can be ornamented with different elements. The third part is dedicated to more advanced concepts, namely 3D figures, optimization & animation. The fourth and final part is a collection of showcases.

Read the book

You can read the book PDF (95Mo, preferred site) that is open access and hosted on HAL which is a French open archive for academics. Up to date version is also available on GitHub here. Sources for the book (including code examples) are available at github.com/rougier/scientific-visualization-book.

Buy the book

If you want to buy the book, you can order a printed edition at amazon.com for 49$. If you want to support or sponsor my future work on Python (and Emacs), you can use paypal, github or liberapay.

If you don't want to spend money, you can simply nominate me for the GitHub stars program if you find my work useful for the community.

See also