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Generate different types of sparsity pattern for sparse matrices.

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PyPI version PyPi downloads DOI sparsity-pattern Total alerts Language grade: Python


Generate different types of sparsity pattern for sparse matrices.


The sparsity-pattern git repo is available as PyPi package

pip install sparsity-pattern
pip install git+ssh://


The block-diagonal pattern for tensorflow

import sparsity_pattern
import tensorflow as tf

n_rows, n_cols = 10, 12
idx = sparsity_pattern.get('block', min(n_rows, n_cols), block_sizes=[3, 1, 2])

mat = tf.sparse.SparseTensor(
    dense_shape=(n_rows, n_cols),
    indices=tf.convert_to_tensor(idx, dtype=tf.int64),
    values=range(1, len(idx)+1))


The circle pattern for pytorch

import sparsity_pattern
import torch

n_rows, n_cols = 5, 7
idx = sparsity_pattern.get('circle', min(n_rows, n_cols), offsets=[1, 2])

mat = torch.sparse_coo_tensor(
    indices=torch.tensor(idx).transpose(0, 1),
    values=range(1, len(idx)+1),
    size=[n_rows, n_cols])


The triu pattern for scipy

import sparsity_pattern
import scipy.sparse
import numpy as np

n, k = 4, -1
idx = sparsity_pattern.get('triu', n, k)
idx_rows, idx_cols = np.array(idx)[:, 0], np.array(idx)[:, 1]
mat = scipy.sparse.lil_matrix((n, n), dtype=np.int64)
mat[idx_rows, idx_cols] = range(1, len(idx)+1)


Check the examples folder for more notebooks.


Install a virtual environment

python3 -m venv .venv
source .venv/bin/activate
pip3 install --upgrade pip
pip3 install -r requirements-dev.txt
pip3 install -r requirements-demo.txt

(If your git repo is stored in a folder with whitespaces, then don’t use the subfolder .venv. Use an absolute path without whitespaces.)

Python commands

  • Jupyter for the examples: jupyter lab

  • Check syntax: flake8 --ignore=F401 --exclude=$(grep -v '^#' .gitignore | xargs | sed -e 's/ /,/g')

  • Run Unit Tests: pytest


pandoc --from markdown --to rst -s -o README.rst
python sdist
twine upload -r pypi dist/*

Clean up

find . -type f -name "*.pyc" | xargs rm
find . -type d -name "__pycache__" | xargs rm -r
rm -r .pytest_cache
rm -r .venv


Please open an issue for support.

License and citation

This software is licensed under Apache License 2.0 and archived on Zenodo. If you would like to cite the software, please use this DOI: 10.5281/zenodo.4357290.


Please contribute using Github Flow. Create a branch, add commits, and open a pull request.

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