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License: GNU Lesser General Public License v3.0
An unsupervised machine learning algorithm for the segmentation of spatial data sets.
License: GNU Lesser General Public License v3.0
Steps to add pip support:
add pyproject.toml
[build-system]
requires = ["setuptools>=62"]
build-backend = "setuptools.build_meta"
and setup.cfg
[metadata]
name = bayseg
version = 0.0.1
author = Alexander Schaaf
author_email = [email protected]
description = An unsupervised machine learning algorithm for the segmentation of spatial data sets.
long_description = file: README.md
long_description_content_type = text/markdown
url = https://github.com/cgre-aachen/bayseg
project_urls =
Bug Tracker = https://github.com/cgre-aachen/bayseg/issues
classifiers =
Programming Language :: Python :: 3
License :: OSI Approved :: GNU Lesser General Public License v3 (LGPLv3)
Operating System :: OS Independent
[options]
package_dir =
= src
packages = find:
python_requires = >=3.6
install_requires =
pytest
scipy
numpy
pandas
matplotlib
tqdm
scikit_learn
[options.packages.find]
where = src
move the directory bayseg
to the src
directory
see also:
https://git.rwth-aachen.de/Till.Petersen-Krauss/bayseg
for different shapes
Add a plot function for visualization of finite mixtures in two-dimensional sub-feature-spaces.
Vectorized implementation
maximum a posterior
vectorized (einsum)
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