albel727 / mvptree Goto Github PK
View Code? Open in Web Editor NEWThis project forked from infinityb/mvptree
A fork of D Grant Starkweather's multiple vantage point tree library
This project forked from infinityb/mvptree
A fork of D Grant Starkweather's multiple vantage point tree library
------------------------------------------------------------------------------- MVPTree c library version: 1.0.0 date: 2010/12/17 creator: D. Grant Starkweather license: GPLv3 contact: [email protected] ------------------------------------------------------------------------------- BACKGROUND: The MVP tree is a distance-based data structure for the storage and retrieval of n-dimensional datapoints. It relies on the relative distances from selected vantage points to index the points into a tree-like hierarchy. It thus cuts the search space into distinct 'hyper-spheres' around each vantage point. libmvptree.a is a generic implemention of the mvp tree. It allows the user to define the distance function, the type of data and array length (e.g. its bit width for each data element - 1,2,4 and 8), as well as experiment with various tree shapes (e.g. branch factor, leaf capacity, and a path length variable to save the distances between each point and all all the vantage points). ------------------------------------------------------------------------------- PLATFORMS: This release should work fine on all linux/unix platforms. Successful compilation and testing has been achieved on windows using cygwin. However, msys/mingw is still a problem due to the memory mapping functions in windows. (Any hints at mmap emulation on windows would be greatly appreciated.) --------------------------------------------------------------------------------- INSTALLATION: 1) Type 'make all' to build the libmvptree.a library and test programs. Run ./testmvp to do a basic test of the library. More involved tests can be done with ./testmvp2 to test it with various number of randomly simulated data points. Run it without arguments to see what options are available. NOTE: For the testing, a specified number of uniformly random datapoints are generated and added to the tree. Then a cluster of datapoints around another randomly chosen point is generated and added to a tree; each element in these data points is a poisson distributed random variable to serve as a difference from the central cluster point's respective element. The point that serves as the center of the cluster is then used to retrieve knearest neighbors - in this case, the number in the cluster - from the tree. For the test to be successful, all data points are retrieved. 2) Type 'make imget' to build the imget image indexing program. 3) 'make install' to install in the target directory. You might want to edit the Makefile to change the DESTDIR variable from '/usr/local/lib'. 4) run ./testmvp to run the test program. ------------------------------------------------------------------------------- API A demo of the api use exists in the testmvp.c file. ------------------------------------------------------------------------------- REFERENCES: Bozkaya, Tolga; Ozsoyoglu, Meral 1999."Indexing Large Metric Spaces for Similarity Search Queries". ACM Transactions in Database Systems, Vol. 24, No. 3, September 1999, pg. 361-404.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
๐ Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. ๐๐๐
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google โค๏ธ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.