Geometric Data Structures for Computer Graphics http://www.amazon.com/Geometric-Data-Structures-Computer-Graphics/dp/1568812353

Python Data Structures and Algorithms by Benjamin Baka English | 30 May 2017 | ASIN: B01IF7NLM8 | 310 Pages | AZW3 | 6.63 MB Key Features A step by step guide, which will provide you with a thorough discussion on the analysis and design of fundamental Python data structures. Get a better understanding of advanced Python concepts such as big-o notation, dynamic programming, and functional data structures. Explore illustrations to present data structures and algorithms, as well as their analysis, in a clear, visual manner. Book Description Data structures allow you to organize data in a particular way efficiently. They are critical to any problem, provide a complete solution, and act like reusable code. In this book, you will learn the essential Python data structures and the most common algorithms. With this easy-to-read book, you will be able to understand the power of linked lists, double linked lists, and circular linked lists. You will be able to create complex data structures such as graphs, stacks and queues. We will explore the application of binary searches and binary search trees. You will learn the common techniques and structures used in tasks such as preprocessing, modeling, and transforming data. We will also discuss how to organize your code in a manageable, consistent, and extendable way. The book will explore in detail sorting algorithms such as bubble sort, selection sort, insertion sort, and merge sort. By the end of the book, you will learn how to build components that are easy to understand, debug, and use in different applications. What you will learn Gain a solid understanding of Python data structures. Build sophisticated data applications. Understand the common programming patterns and algorithms used in Python data science. Write efficient robust code. About the Author Benjamin Baka works as a software developer and has over 10 years, experience in programming. He is a graduate of Kwame Nkrumah University of Science and Technology and a member of the Linux Accra User Group. Notable in his language toolset are C, C++, Java, Python, and Ruby. He has a huge interest in algorithms and finds them a good intellectual exercise. He is a technology strategist and software engineer at mPedigree Network, weaving together a dizzying array of technologies in combating counterfeiting activities, empowering consumers in Ghana, Nigeria, and Kenya to name a few. In his spare time, he enjoys playing the bass guitar and listening to silence. You can find him on his blog. Table of Contents Python objects, types and expressions Python data types and structures Principles of data structure design Lists and pointer structures Stacks and Queues Trees Hashing and symbol tables Graphs and other algorithms Searching Sorting Selction Algorithms Design Ttechniques and Sstrategies Implementations, applications and tools

ocaml-data-structures：用OCaml编写的一些数据结构和算法

OCaml：在OCaml中实现的算法

.Data_Structures_and_Algorithms_in_C＋＋.2nd_Edition.AD.[EN].pdf

六度凯文培根 六度凯文·培根或“培根定律”是基于“六度分离”概念的客厅游戏，它假定地球上的任何两个人相距六个或更少的熟人链接。 电影爱好者互相挑战，寻找任意演员和多产演员凯文·培根之间的最短路径。 它基于这样一个假设，即好莱坞电影业的任何人都可以通过他们的电影角色在六个步骤内与培根联系起来。 2007 年，培根创办了一个名为 SixDegrees.org 的慈善组织。 2020 年，培根开设了一个名为“凯文培根的最后一个学位”的播客。 培根数 演员的培根数是游戏定义的他或她与培根的分离度数。 这是 Erdős 数字概念在好莱坞电影业的应用。 培根数越高，演员与凯文培根的差距越大。 演员 X 的培根数的计算是一种“最短路径”算法，适用于联合主演网络： 如果演员不在同一个子网中，则他/她的培根数为 0。 那些直接与凯文培根合作的演员的培根数为 1。 如果与 X 一起出现在任何电影中的任

项目介绍 使用查找无向加权图的（MST）的Java程序。 项目特色 以最有效的形式使用。 使用 通过命令行从输入文件中读取无向加权图。 输入文件包含以下内容（请参见testUF.txt）： 零个或多个以'c'开头的注释行 后面跟一个整数，代表图中的节点数 然后每行一条边。 一个整数三元组代表每个边缘，其中第三个整数是前两个整数之间的边缘权重。 也就是说，边缘1 2 3表示边缘1和2之间的权重为3。 将结果输出到文件（请参见testUFOutput.txt）。 输出文件由构成最小生成树的边以及MST的总权重组成。

数据处理 用于建模的数据准备的Python代码： 处理有问题的分子的微笑：有机金属，混合物，肽。 资料取样 数据选择 安装： git clone https://github.com/phi-grib/Data_curation.git conda activate cd Data_curation python setup.py install 现在，您可以使用该代码从其结构中自动对化合物进行分类和分类。 仍在建设中。 将来添加的功能： 混合物检查 优化过滤功能。 现在有点嵌套了，这使得其他开发人员更难以更新和维护 用法示例： 包装中的Jupyter Notebook中有一个用法示例。

哔哔 Beap又称双亲堆（ ）是一种，该允许有效地插入和搜索元素，而不需要比数据元素本身更多的空间。 通过支持beap结构的数组中元素的巧妙排列以及利用这种排列的巧妙算法，可以支持有效的搜索和插入。 Beap进一步阐述了数据结构的思想（这允许有效地插入和查找最小值/最大值，但不能有效地搜索任意元素）。 它最初由研究人员Ian Munro和Hendra Suwanda的。 但是，很难找到此数据结构的实现。 在原始论文的基础上实现它也不容易，因为遵循良好的学术传统，论文相当简洁，不完整，前后不一致并且存在勘误。 该项目是Paul Sokolovsky编写并使用OpenSource MIT许可

数据结构和算法专业化 我的Coursera数据结构和算法专业化作业解决方案