Algoplus{BETA Version}

AlgoPlus is a C++ library that includes ready-to-use complex data structures and algorithms.

See the full documentation here

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Example:

#include <machine_learning/clustering/DBSCAN/dbscan.h>

// AlgoPlus now has Machine Learning classes!
int main(){
    std::vector<std::vector<double> > data;
    ...
    // Eps = 4, MinPts = 3
    DBSCAN a(data, 4, 3);
    
    // returns the clusters and noise of the DBSCAN clustering
    std::map<std::pair<double, double>, int64_t>  clusters = a.get_clusters();
    std::vector<std::pair<double, double> > noise = a.get_noise();
    ...
}

#include <machine_learning/image/edge_detection/sobel_operator.h>

// As well as image processing algorithms!
int main(){
  ...
  std::vector<std::vector<int32_t> > img(data);

  // Performs edge detection on image img
  std::vector<std::vector<int32_t> > resulted = Sobel(img);
  ...
}


#include <graph.h>

// And of course, every data structure that you need!
int main(){
  weighted_graph<int> g("undirected");
  g.add_edge(1, 4, 2);
  g.add_edge(4, 5, 6);
  g.add_edge(5, 2, 9);
  g.add_edge(2, 8, 10);

  // returns the shortest path from 1 to 2.
  std::cout << g.shortest_path(1, 2) << '\n';
  g.visualize() // You can visualize almost any of our implemented data structures!
}

You can see more examples or follow the Tutorials.

Classes

Graphs

• Di-Graph
• Graph

Trees

• Red-Black Tree
• AVL Tree
• Binary Search Tree
• Splay Tree
• Trie
• Interval Tree
• 234 Tree
• Min/Max Heap

Lists

• Single Linked List
• Doubly Linked List
• Circular Linked List
• Skip List

Other

• Disjoint set
• Stack
• Queue
• Hash Table

Machine Learning(NEW!)

• Clustering Algorithms
• Encoders
• Regression Algorithms
• Shortest Path Algorithms
• Image Processing Algorithms

How to run test cases

We have unit tests for every function of our implemented algorithms & data structures. It is very important to make sure that your code works before making any pull requests!

Linux/MacOS

mkdir build && cd build
cmake ..
make
cd tests
./runUnitTests

Windows

mkdir build
cmake -S . -B build -G Ninja
cmake --build build
cd build/tests
./runUnitTests

Our contributors

How to contribute

1. Povide new implementations on our already implemented data structures & algorithms.

2. Implement new classes / algorithms.

3. Contribute to unit testing by writting unit tests for our classes and algorithms.

4. Create and contribute to APIs for other languages(Check AlgoPy branch).

5. Promote the repository on your local workshop/seminar and get a shout-out.

See more here.

For any information or questions, please contact Spiros at [email protected]

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