blog-codes | 个人博客 文章的代码 | Blog library

 by   fancyerii Java Version: Current License: Apache-2.0

kandi X-RAY | blog-codes Summary

kandi X-RAY | blog-codes Summary

blog-codes is a Java library typically used in Web Site, Blog applications. blog-codes has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However blog-codes build file is not available. You can download it from GitHub.

个人博客 (文章的代码
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            kandi-support Support

              blog-codes has a low active ecosystem.
              It has 146 star(s) with 74 fork(s). There are 8 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 4 open issues and 1 have been closed. On average issues are closed in 319 days. There are 5 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of blog-codes is current.

            kandi-Quality Quality

              blog-codes has 0 bugs and 0 code smells.

            kandi-Security Security

              blog-codes has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              blog-codes code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              blog-codes is licensed under the Apache-2.0 License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              blog-codes releases are not available. You will need to build from source code and install.
              blog-codes has no build file. You will be need to create the build yourself to build the component from source.
              blog-codes saves you 55311 person hours of effort in developing the same functionality from scratch.
              It has 63641 lines of code, 3789 functions and 330 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed blog-codes and discovered the below as its top functions. This is intended to give you an instant insight into blog-codes implemented functionality, and help decide if they suit your requirements.
            • Execute the layout
            • Computes the total energy between an edge
            • Computes the energy of the specified node
            • The main algorithm
            • Encodes a RenderedImage
            • Encodes the row
            • Performs a filter on an image
            • Populate the format menu
            • Binds an action to an action
            • Main entry point
            • Performs a vertex ordering
            • Draw a cell
            • Calculates the relative position of an absolute point
            • Executes a DFS layer
            • Returns a list of the shortest path between the two vertices
            • Set the layout of a WindmillGraph
            • Gets the image
            • Executes the layout
            • Decodes an object
            • The main method
            • Paint a shape
            • Initialize handler
            • Paints the component
            • Dijkstrapping algorithm
            • MouseDragged event
            • Parses the reader
            Get all kandi verified functions for this library.

            blog-codes Key Features

            No Key Features are available at this moment for blog-codes.

            blog-codes Examples and Code Snippets

            No Code Snippets are available at this moment for blog-codes.

            Community Discussions

            QUESTION

            How to correctly implement wighted union and path compression in a UnionFind data structure
            Asked 2019-Apr-16 at 12:51

            I am trying to implement a Union-Find/Disjoint-Set data structure in C, using weighted Union and path compression in Find. I have some questions as to how the weighted union should be implemented to reduce time complexity when compared to the non weighted Union.

            I have already found several solutions to this problem online and have implemented my own. In every solution, the root of each separate tree (representing a set) holds the number of nodes of the tree at all times. When uniting the sets of two random objects that belong to a different set, the roots are first found (path compression is used here) and then we compare the sizes of these roots. The root of the biggest tree is set as the parent of the of the root of the smallest tree.

            In my understanding however, what we are trying to achieve with a weighted union is to reduce the height of the resulting tree (which is also what we are trying to achieve with path compression). Hence, it is no the tree with the lowest number of Nodes that should be connected to the other tree, but the tree with the lowest height. This keeps the height to a minimum.

            Is this correct? Is checking the height and the size somehow equivalent given the rest of the implementation (we always start with a number of single (one node) sets)?

            Supposing that it is the height that needs to be checked, keeping track of the height of a tree if path compression is not used is fairly straightforward. I have not however found a way to keep track of the height of the tree when path compression is used (at least not without traversing the whole tree, which increases the time complexity of the "find" algorithm.

            Here is an example of an implementation I have found and uses what I described (very similar to what I have coded) in c++: https://github.com/kartikkukreja/blog-codes/blob/master/src/Union%20Find%20(Disjoint%20Set)%20Data%20Structure.cpp

            ...

            ANSWER

            Answered 2019-Apr-16 at 12:51

            It looks like you've pretty much figured this all out yourself.

            Union-by-height is the obvious way to make the shortest tree, but it's hard to keep track of the height when you use path compression...

            So union-by-rank is commonly used instead. The 'rank' of a set is what it's height would be if we didn't do any path compression, so when you use union-by-rank with path compression it's like starting with union-by-height and then applying path compression as an optimization, ensuring that the path compression doesn't change how the merges work.

            A lot of people (myself included) use union-by-size, however, because the size is often useful, and it can be shown that union-by-size produces the same worst-case complexities as union-by-rank. Again in this case, path compression doesn't affect the merges since it doesn't change the size of any roots.

            Source https://stackoverflow.com/questions/55707010

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install blog-codes

            You can download it from GitHub.
            You can use blog-codes like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the blog-codes component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .

            Support

            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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            gh repo clone fancyerii/blog-codes

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