Diverse graph algorithms implemented using JGraphT library.

# 1. Installing Maven & Pandas

First, please install Java (JDK11) and Python 3 if they are not already. 

Next, make sure that Maven (for importing JGraphT) and Pandas(for data analysis) are installed. 
To install Maven on Ubuntu, type the following commands on terminal:

sudo apt-get update
sudo apt-get install maven

For Pandas, type the following:

pip3 install pandas
( sudo apt-get install python3-pip  if pip is not installed already)



# 2. Compilation

Type the following to compile this project:

mvn compile 



# 3. Running the code

Below is the command for running tests for SNAP(DIMACS) and grid data. 

java -Xms24G -Xmx48G -Xmn36G -Xss1G -cp $CLASSPATHS shell.TestSNAP (the filename of data; just the name and not the path) (# of tests) (randomization seed)
java -Xms32G -Xmx64G -Xmn48G -Xss1G -cp $CLASSPATHS shell.TestGrid (Maximum dimension) (dimension increment) [List of the values for k, space-separated]

You may change the randomization seed (vertex selection) to assess reproducibility. (In our experiment, the seed was set to 2021.)

For the data, check "src/SNAP(or DIMACS)".
Output "test_result.csv" will be saved on "target" directory.

Check if 'CLASSPATHS' is set properly.
Please refer to " sample.sh " for examples & further details. 



#4. Obtaining average processing time and diversity

First, move to the target directory. Then run get_averages.py

python3 get_averages (.csv file name) [list of the values for k, space-separated. Optional parameter.]