Huffman-Compression | Java Implementation for Huffman Compression | Compression library

by Glank Java Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | Huffman-Compression Summary

Huffman-Compression is a Java library typically used in Utilities, Compression applications. Huffman-Compression has no bugs, it has no vulnerabilities and it has low support. However Huffman-Compression build file is not available. You can download it from GitHub.

Java Implementation for Huffman Compression

Support

Quality

Security

License

Reuse

Support

Huffman-Compression has a low active ecosystem.

It has 4 star(s) with 1 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 0 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of Huffman-Compression is current.

Quality

Huffman-Compression has no bugs reported.

Security

Huffman-Compression has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

Huffman-Compression does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

Huffman-Compression releases are not available. You will need to build from source code and install.

Huffman-Compression has no build file. You will be need to create the build yourself to build the component from source.

Top functions reviewed by kandi - BETA

kandi has reviewed Huffman-Compression and discovered the below as its top functions. This is intended to give you an instant insight into Huffman-Compression implemented functionality, and help decide if they suit your requirements.

Iterate build
Removes the first node from the tree
Extend a new branch
Creates a new branch
Entry point for testing
Add other node to this
Decompress a byte array
Compress the contents of the data
Prints the status
Prints tree print to stdout
Returns the number of nodes in this subtree
Entry point for the example
Reads a byte

Get all kandi verified functions for this library.

Huffman-Compression Key Features

No Key Features are available at this moment for Huffman-Compression.

Huffman-Compression Examples and Code Snippets

No Code Snippets are available at this moment for Huffman-Compression.

Community Discussions

Trending Discussions on Huffman-Compression

Identify more Compressible Dataset by observing Input distribution

QUESTION

Identify more Compressible Dataset by observing Input distribution

Asked 2017-Jun-17 at 17:24

This may be a repeat of the question here: Predict Huffman compression ratio without constructing the tree

So basically, I have the probabilistic distribution of two datasets with the same variables but different probabilities. Now, is there any way that by looking at the variable distribution, I can to some degree confidently say that the dataset, when passed through a Huffman Coding implementation would achieve a higher compression ratio than the other?

One of the solutions that I came across was to calculate the upper bound using conditional entropy and then compute the average code length. Is there any other approach that can I can probably explore before using the said method?

Thanks a lot.

...

ANSWER

Answered 2017-Jun-17 at 17:24

I don't know what "to some degree confidently" means, but you can get a lower bound on the compressed size of each set by computing the zero-order entropy as done in the linked question (the negative of the sum of the probabilities times the log of the probabilities). Then the lower entropy very likely produces a shorter Huffman coding than the higher entropy. It is not definite, as I am sure that one could come up with a counter-example.

You also need to send a description of the code itself if you want to decode it on the other end, which adds a wrinkle to the comparison. However if the data is much larger than the code description, then that will be lost in the noise.

Simply generating the code, the coded data, and the code description is very fast. The best solution is to do that, and compare the resulting number of bits directly.

Source https://stackoverflow.com/questions/44590230

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

Vulnerabilities

No vulnerabilities reported

Install Huffman-Compression

You can download it from GitHub.
You can use Huffman-Compression 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 Huffman-Compression 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 .

Find more information at: