Getting Started

Installation

This tool can be installed from PyPI:

$ pip install nclustgen

NOTICE: Nclustgen installs by default the dgl build with no cuda support, in case you want to use gpu you can override this by installing the correct dgl build, more information at: https://www.dgl.ai/pages/start.html.

Basic Usage

Biclustering Dataset

See also

Detailed API at Bicluster Generator.

## Generate biclustering dataset

from nclustgen import BiclusterGenerator

# Initialize generator
generator = BiclusterGenerator(
     dstype='NUMERIC',
     patterns=[['CONSTANT', 'CONSTANT'], ['CONSTANT', 'NONE']],
     bktype='UNIFORM',
     in_memory=True,
     silence=True
)

# Get parameters
generator.get_params()

# Generate dataset
x, y = generator.generate(nrows=50, ncols=100, nclusters=3)

# Build graph
graph = generator.to_graph(x, framework='dgl', device='cpu')

# Save data files
generator.save(file_name='example', single_file=True)

Triclustering Dataset

See also

Detailed API at Tricluster Generator.

## Generate triclustering dataset

from nclustgen import TriclusterGenerator

# Initialize generator
generator = TriclusterGenerator(
     dstype='NUMERIC',
     patterns=[['CONSTANT', 'CONSTANT', 'CONSTANT'], ['CONSTANT', 'NONE', 'NONE']],
     bktype='UNIFORM',
     in_memory=True,
     silence=True
)

# Get parameters
generator.get_params()

# Generate dataset
x, y = generator.generate(nrows=50, ncols=100, ncontexts=10, nclusters=25)

# Build graph
graph = generator.to_graph(x, framework='dgl', device='cpu')

# Save data files
generator.save(file_name='example', single_file=True)