PyDPGM is a Dirichlet Process Gaussian Mixture package, please download the latest version from our GitHub repository.

Please send any bugs of problems to Ke Zhai ([email protected]).

This package depends on many external python libraries, such as numpy, scipy and nltk.

Assume the PyDPGM package is downloaded under directory $PROJECT_SPACE/src/, i.e.,

$PROJECT_SPACE/src/PyDPGM

To prepare the example dataset,

tar zxvf point-clusters.tar.gz

To launch PyDPGM, first redirect to the directory of PyDPGM source code,

cd $PROJECT_SPACE/src/PyDPGM

and run the following command on example dataset,

python -m launch_train --input_directory=./point-clusters --output_directory=./ --training_iterations=100

The generic argument to run PyDPGM is

python -m launch_train --input_directory=$INPUT_DIRECTORY/$DATASET_NAME --output_directory=$OUTPUT_DIRECTORY --training_iterations=$NUMBER_OF_ITERATIONS

You should be able to find the output at directory $OUTPUT_DIRECTORY/$DATASET_NAME.

Under any circumstances, you may also get help information and usage hints by running the following command

python -m launch_train --help

To generate synthetic data

python generate_data_crp.py --output_directory=./ --number_of_clusters=5 --number_of_points=1000
#python generate_data_sbp.py --output_directory=./ --number_of_clusters=5 --number_of_points=1000

To plot result

python plot_clusters.py --input_directory=./point-clusters/ --output_directory=./point-clusters/