[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-70782":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":11,"languages":10,"totalLinesOfCode":10,"stars":12,"forks":13,"watchers":14,"openIssues":15,"contributorsCount":16,"subscribersCount":16,"size":16,"stars1d":17,"stars7d":18,"stars30d":19,"stars90d":16,"forks30d":16,"starsTrendScore":19,"compositeScore":20,"rankGlobal":10,"rankLanguage":10,"license":21,"archived":22,"fork":22,"defaultBranch":23,"hasWiki":24,"hasPages":22,"topics":25,"createdAt":10,"pushedAt":10,"updatedAt":34,"readmeContent":35,"aiSummary":36,"trendingCount":16,"starSnapshotCount":16,"syncStatus":37,"lastSyncTime":38,"discoverSource":39},70782,"scientific-visualization-book","rougier\u002Fscientific-visualization-book","rougier","An open access book on scientific visualization using python and matplotlib","https:\u002F\u002Fwww.labri.fr\u002Fperso\u002Fnrougier\u002F",null,"Python",11273,1009,189,18,0,8,12,24,44.01,"Other",false,"master",true,[26,27,28,29,30,31,32,33],"book","dataviz","matplotlib","numpy","open-access","plotting","python","scientific-publications","2026-06-12 02:02:43","## Scientific Visualization: Python + Matplotlib\n**Nicolas P. Rougier, Bordeaux, November 2021.**  \n\n\u003Cimg src=\"images\u002Fbook.png\" width=\"25%\" alt=\"Front cover\" align=\"left\"\u002F>\n\nThe 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.\n\n### Read the book\n\nYou can read the book **[PDF](https:\u002F\u002Fhal.inria.fr\u002Fhal-03427242\u002Fdocument)** (95Mo, preferred site) that is open access and hosted on\n[HAL](https:\u002F\u002Fhal.archives-ouvertes.fr\u002F) which is a French open\narchive for academics. Up to date version is also available on GitHub [here](pdf\u002Fbook.pdf). Sources for the book (including code examples)\nare available at\n[github.com\u002Frougier\u002Fscientific-visualization-book](https:\u002F\u002Fgithub.com\u002Frougier\u002Fscientific-visualization-book).  \n\n### Buy the book\n\nIf you want to buy the book, you can order a **printed edition** at\n[amazon.com](https:\u002F\u002Fwww.amazon.com\u002Fdp\u002F2957990105) for 49$. If you want to support or sponsor my\nfuture work on Python (and\n[Emacs](https:\u002F\u002Fgithub.com\u002Frougier\u002Fnano-emacs)), you can use\n[paypal](https:\u002F\u002Fwww.paypal.com\u002Fpaypalme\u002FNicolasPRougier\u002F10),\n[github](https:\u002F\u002Fgithub.com\u002Fsponsors\u002Frougier) or\n[liberapay](https:\u002F\u002Fen.liberapay.com\u002Frougier\u002F).\n\n\u003Ca href=\"https:\u002F\u002Fwww.paypal.com\u002Fpaypalme\u002FNicolasPRougier\u002F5\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F-TIP_5$-yellow.svg?style=flat-square\"\u002F>\u003Ca\u002F> \n \u003Ca href=\"https:\u002F\u002Fwww.paypal.com\u002Fpaypalme\u002FNicolasPRougier\u002F10\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F-TIP_10$-orange.svg?style=flat-square\"\u002F>\u003Ca\u002F>\n \u003Ca href=\"https:\u002F\u002Fwww.paypal.com\u002Fpaypalme\u002FNicolasPRougier\u002F25\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F-TIP_25$-red.svg?style=flat-square\"\u002F>\u003Ca\u002F> \n \u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fsponsors\u002Frougier\u002Fsponsorships?sponsor=rougier&tier_id=6981&preview=false\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F-5$\u002FMo-yellow.svg?style=flat-square&logo=github\"\u002F>\u003Ca\u002F> \u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fsponsors\u002Frougier\u002Fsponsorships?sponsor=rougier&tier_id=11147&preview=false\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F-10$\u002FMo-orange.svg?style=flat-square&logo=github\"\u002F>\u003Ca\u002F> \n\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fsponsors\u002Frougier\u002Fsponsorships?sponsor=rougier&tier_id=108712&preview=false\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F-25$\u002FMo-red.svg?style=flat-square&logo=github\"\u002F>\u003Ca\u002F> \n\u003Ca href=\"https:\u002F\u002Fen.liberapay.com\u002Frougier\u002Fdonate\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F-PATRON\u002FWeek-green.svg?style=flat-square&logo=liberapay&logoColor=white\"\u002F>\u003Ca\u002F> \n\nIf you don't want to spend money, you can simply [nominate me](https:\u002F\u002Fstars.github.com\u002Fnominate\u002F) for the GitHub stars program if you find my work useful for the community.\n\n### Build the book\n\n**Ubuntu**  \n- [Article](https:\u002F\u002Flabdmitriy.github.io\u002Fblog\u002Fbuilding-scientific-visualization-book\u002F)  \n- [Script](scripts\u002Fbuild_book\u002Fubuntu.sh)\n\n### See also\n\n* [Python & OpenGL for Scientific Visualization](https:\u002F\u002Fwww.labri.fr\u002Fperso\u002Fnrougier\u002Fpython-opengl\u002F)\n* [From Python to Numpy](https:\u002F\u002Fwww.labri.fr\u002Fperso\u002Fnrougier\u002Ffrom-python-to-numpy\u002F) (Scientific Python Volume I)\n* [100 Numpy exercices](https:\u002F\u002Fgithub.com\u002Frougier\u002Fnumpy-100)\n* [Matplotlib cheat sheets](https:\u002F\u002Fgithub.com\u002Fmatplotlib\u002Fcheatsheets)\n\n\n### Book gallery\n\n\u003Cimg src=\"images\u002Fcontour-dropshadow.png\" width=\"31%\"\u002F> \u003Cimg src=\"images\u002Fdomain-coloring.png\" width=\"31%\"\u002F> \u003Cimg src=\"images\u002Fmetropolis.png\" width=\"31%\"\u002F>\n\u003Cimg src=\"images\u002Fzorder-plots.png\" width=\"31%\"\u002F> \u003Cimg src=\"images\u002Fscales.png\" width=\"31%\"\u002F> \u003Cimg src=\"images\u002Fhistogram-pca.png\" width=\"31%\"\u002F> \n\u003Cimg src=\"images\u002Fhatched-bars.png\" width=\"31%\"\u002F> \u003Cimg src=\"images\u002Fplatonic-solids.png\" width=\"31%\"\u002F> \u003Cimg src=\"images\u002Fprojection-3d-gaussian.png\" width=\"31%\"\u002F>\n\u003Cimg src=\"images\u002Fpolygon-clipping.png\" width=\"31%\"\u002F> \u003Cimg src=\"images\u002Fmultisample.png\" width=\"31%\"\u002F> \u003Cimg src=\"images\u002Ftypography-matters.png\" width=\"31%\"\u002F>\n\u003Cimg src=\"images\u002Fscatter-3d.png\" width=\"31%\"\u002F> \u003Cimg src=\"images\u002Fwaterfall-3d.png\" width=\"31%\"\u002F> \u003Cimg src=\"images\u002Fbunnies.png\" width=\"31%\"\u002F>\n\u003Cimg src=\"images\u002Fpolar-projection.png\" width=\"31%\"\u002F> \u003Cimg src=\"images\u002Frecursive-voronoi.png\" width=\"31%\"\u002F> \u003Cimg src=\"images\u002Ftext-polar.png\" width=\"31%\"\u002F>\n\u003Cimg src=\"images\u002Fspiral-pi.png\" width=\"31%\"\u002F> \u003Cimg src=\"images\u002Fescher.png\" width=\"31%\"\u002F> \u003Cimg src=\"images\u002Fradial-maze.png\" width=\"31%\"\u002F>\n\u003Cimg src=\"images\u002Ftext-shadow.png\" width=\"95%\"\u002F>\n\n","该项目是一本关于使用Python和Matplotlib进行科学可视化的开放访问书籍。其核心功能包括介绍Matplotlib库的基本原理、图形设计技巧以及高级概念如3D图形、优化与动画等，并提供了丰富的代码示例。技术特点在于全面覆盖了从基础到进阶的可视化知识，同时强调高质量图形制作对于科学研究的重要性。适合希望提升自己在数据可视化方面技能的科研人员、学生或任何对Python绘图感兴趣的开发者阅读学习。",2,"2026-06-11 03:34:10","high_star"]