All Projects → rougier → Scientific Visualization Book

rougier / Scientific Visualization Book

An open access book on scientific visualization using python and matplotlib

Programming Languages

python
139335 projects - #7 most used programming language
TeX
3793 projects
Makefile
30231 projects

Projects that are alternatives of or similar to Scientific Visualization Book

Mplcyberpunk
"Cyberpunk style" for matplotlib plots
Stars: ✭ 762 (-87.97%)
Mutual labels:  matplotlib, dataviz, plotting
From Python To Numpy
An open-access book on numpy vectorization techniques, Nicolas P. Rougier, 2017
Stars: ✭ 1,728 (-72.73%)
Mutual labels:  book, numpy, open-access
Pythonstudy
Python related technologies used in work: crawler, data analysis, timing tasks, RPC, page parsing, decorator, built-in functions, Python objects, multi-threading, multi-process, asynchronous, redis, mongodb, mysql, openstack, etc.
Stars: ✭ 103 (-98.37%)
Mutual labels:  matplotlib, numpy
Stock Market Analysis And Prediction
Stock Market Analysis and Prediction is the project on technical analysis, visualization and prediction using data provided by Google Finance.
Stars: ✭ 112 (-98.23%)
Mutual labels:  matplotlib, numpy
Data Science For Marketing Analytics
Achieve your marketing goals with the data analytics power of Python
Stars: ✭ 127 (-98%)
Mutual labels:  matplotlib, numpy
Matplotlib Multilayer Network
small template code to create a multilayer network using matplotlib and networkx
Stars: ✭ 60 (-99.05%)
Mutual labels:  matplotlib, dataviz
Double pendulum
Animations of random double pendulums
Stars: ✭ 73 (-98.85%)
Mutual labels:  matplotlib, numpy
Ipyvolume
3d plotting for Python in the Jupyter notebook based on IPython widgets using WebGL
Stars: ✭ 1,696 (-73.23%)
Mutual labels:  dataviz, plotting
Mlcourse.ai
Open Machine Learning Course
Stars: ✭ 7,963 (+25.68%)
Mutual labels:  matplotlib, numpy
Ml Cheatsheet
A constantly updated python machine learning cheatsheet
Stars: ✭ 136 (-97.85%)
Mutual labels:  matplotlib, numpy
Machine Learning Projects
This repository consists of all my Machine Learning Projects.
Stars: ✭ 135 (-97.87%)
Mutual labels:  matplotlib, numpy
Data Analysis
主要是爬虫与数据分析项目总结,外加建模与机器学习,模型的评估。
Stars: ✭ 142 (-97.76%)
Mutual labels:  matplotlib, numpy
Ncar Python Tutorial
Numerical & Scientific Computing with Python Tutorial
Stars: ✭ 50 (-99.21%)
Mutual labels:  matplotlib, numpy
Machine Learning
notebooks with example for machine learning examples
Stars: ✭ 45 (-99.29%)
Mutual labels:  matplotlib, numpy
Pandoc Plot
Render and include figures in Pandoc documents using your plotting toolkit of choice
Stars: ✭ 75 (-98.82%)
Mutual labels:  matplotlib, plotting
Abu
阿布量化交易系统(股票,期权,期货,比特币,机器学习) 基于python的开源量化交易,量化投资架构
Stars: ✭ 8,589 (+35.56%)
Mutual labels:  matplotlib, numpy
Cmasher
Scientific colormaps for making accessible, informative and 'cmashing' plots
Stars: ✭ 149 (-97.65%)
Mutual labels:  matplotlib, plotting
Pythondatasciencehandbook
The book was written and tested with Python 3.5, though other Python versions (including Python 2.7) should work in nearly all cases.
Stars: ✭ 31,995 (+404.97%)
Mutual labels:  matplotlib, numpy
Machine Learning Alpine
Alpine Container for Machine Learning
Stars: ✭ 30 (-99.53%)
Mutual labels:  matplotlib, numpy
Ds Ai Tech Notes
📖 [译] 数据科学和人工智能技术笔记
Stars: ✭ 131 (-97.93%)
Mutual labels:  matplotlib, numpy

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

Book gallery

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].