Instructions of the Seed-and-extension-based Density Peaks (SDP) Clustering Algorithm

1. Run SDP_windows (SDP_linux) and follow the steps one by one to enter the corresponding input and parameters. (Refer to running example.png)

2. Input data is a precomputed distance matrix / similarity matrix, formatted as a csv file. (Refer to input_example.csv)


3. Notice that input data and the executable file need to be in the same path folder.


4. The output clustering result and the visualization figure will be generated in a folder with the same folder name as the input data file. 
