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Release v0.1.0

See merge request interpol/minterpy-levelsets!2
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Uwe Hernandez Acosta committed Mar 13, 2023
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13 changes: 13 additions & 0 deletions AUTHORS.md
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# Contributors

## Main code development
- Sachin Krishnan Thekke Veettil (MPI CBG/TU Dresden) <[email protected]>
- Gentian Zavalani (HZDR/CASUS) <[email protected]>

## Mathematical foundation
- Michael Hecht(HZDR/CASUS) <[email protected]>

## Acknowledgement
- Uwe Hernandez Acosta (HZDR/CASUS)
- Damar Wicaksono (HZDR/CASUS)
- Minterpy development team
102 changes: 41 additions & 61 deletions README.md
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# minterpy-levelsets

A Python library for performing numerical differential geometry on smooth closed surfaces based on Global Polynomial Level Sets (GPLS). [^1]

## Table of Contents

## Getting started
- [Background](#background)
- [Install](#install)
- [Usage](#usage)
- [Development team](#develpment-team)
- [Contributing](#contributing)
- [License](#license)

To make it easy for you to get started with GitLab, here's a list of recommended next steps.

Already a pro? Just edit this README.md and make it your own. Want to make it easy? [Use the template at the bottom](#editing-this-readme)!
## Background

## Add your files
Starting with a pointset representation of a surface, GPLS can be used to approximate a broad class of smooth surfaces as affine algebraic varieties. With this polynomial representation, differential-geometric quantities like mean and Gauss curvature can be efficiently and accurately computed. This compressed representation significantly reduces the computational cost of 3d surface simulations.

- [ ] [Create](https://docs.gitlab.com/ee/user/project/repository/web_editor.html#create-a-file) or [upload](https://docs.gitlab.com/ee/user/project/repository/web_editor.html#upload-a-file) files
- [ ] [Add files using the command line](https://docs.gitlab.com/ee/gitlab-basics/add-file.html#add-a-file-using-the-command-line) or push an existing Git repository with the following command:

```
cd existing_repo
git remote add origin https://gitlab.hzdr.de/interpol/minterpy-levelsets.git
git branch -M main
git push -uf origin main
```

## Integrate with your tools

- [ ] [Set up project integrations](https://gitlab.hzdr.de/interpol/minterpy-levelsets/-/settings/integrations)

## Collaborate with your team

- [ ] [Invite team members and collaborators](https://docs.gitlab.com/ee/user/project/members/)
- [ ] [Create a new merge request](https://docs.gitlab.com/ee/user/project/merge_requests/creating_merge_requests.html)
- [ ] [Automatically close issues from merge requests](https://docs.gitlab.com/ee/user/project/issues/managing_issues.html#closing-issues-automatically)
- [ ] [Enable merge request approvals](https://docs.gitlab.com/ee/user/project/merge_requests/approvals/)
- [ ] [Automatically merge when pipeline succeeds](https://docs.gitlab.com/ee/user/project/merge_requests/merge_when_pipeline_succeeds.html)
## Install

## Test and Deploy
Since this implementation is a prototype, we currently only provide the installation by self-building from source. We recommend to using `git` to get the `minterpy-levelsets` source:

Use the built-in continuous integration in GitLab.
```bash
git clone https://codebase.helmholtz.cloud/interpol/minterpy-levelsets.git
```

- [ ] [Get started with GitLab CI/CD](https://docs.gitlab.com/ee/ci/quick_start/index.html)
- [ ] [Analyze your code for known vulnerabilities with Static Application Security Testing(SAST)](https://docs.gitlab.com/ee/user/application_security/sast/)
- [ ] [Deploy to Kubernetes, Amazon EC2, or Amazon ECS using Auto Deploy](https://docs.gitlab.com/ee/topics/autodevops/requirements.html)
- [ ] [Use pull-based deployments for improved Kubernetes management](https://docs.gitlab.com/ee/user/clusters/agent/)
- [ ] [Set up protected environments](https://docs.gitlab.com/ee/ci/environments/protected_environments.html)
Switch to the `conda` or `venv` virtual environment of your choice where you would like to install the library.

***
From within the environment, install using [pip],

# Editing this README
```bash
pip install [-e] .
```

When you're ready to make this README your own, just edit this file and use the handy template below (or feel free to structure it however you want - this is just a starting point!). Thank you to [makeareadme.com](https://www.makeareadme.com/) for this template.
where the flag `-e` means the package is directly linked
into the python site-packages of your Python version.

## Suggestions for a good README
Every project is different, so consider which of these sections apply to yours. The sections used in the template are suggestions for most open source projects. Also keep in mind that while a README can be too long and detailed, too long is better than too short. If you think your README is too long, consider utilizing another form of documentation rather than cutting out information.
You **must not** use the command `python setup.py install` to install `minterpy`,
as you cannot always assume the files `setup.py` will always be present
in the further development of `minterpy`.

## Name
Choose a self-explaining name for your project.

## Description
Let people know what your project can do specifically. Provide context and add a link to any reference visitors might be unfamiliar with. A list of Features or a Background subsection can also be added here. If there are alternatives to your project, this is a good place to list differentiating factors.
## Usage

## Badges
On some READMEs, you may see small images that convey metadata, such as whether or not all the tests are passing for the project. You can use Shields to add some to your README. Many services also have instructions for adding a badge.
Documentation is a WIP. Please refer to the example Jupyter notebooks in the `examples/` directory to get started with the library.

## Visuals
Depending on what you are making, it can be a good idea to include screenshots or even a video (you'll frequently see GIFs rather than actual videos). Tools like ttygif can help, but check out Asciinema for a more sophisticated method.

## Installation
Within a particular ecosystem, there may be a common way of installing things, such as using Yarn, NuGet, or Homebrew. However, consider the possibility that whoever is reading your README is a novice and would like more guidance. Listing specific steps helps remove ambiguity and gets people to using your project as quickly as possible. If it only runs in a specific context like a particular programming language version or operating system or has dependencies that have to be installed manually, also add a Requirements subsection.
## Development team

## Usage
Use examples liberally, and show the expected output if you can. It's helpful to have inline the smallest example of usage that you can demonstrate, while providing links to more sophisticated examples if they are too long to reasonably include in the README.
### Main code development
- Sachin Krishnan Thekke Veettil (MPI CBG/TU Dresden) <[email protected]>
- Gentian Zavalani (HZDR/CASUS) <[email protected]>

## Support
Tell people where they can go to for help. It can be any combination of an issue tracker, a chat room, an email address, etc.
### Mathematical foundation
- Michael Hecht (HZDR/CASUS) <[email protected]>

## Roadmap
If you have ideas for releases in the future, it is a good idea to list them in the README.
### Acknowledgement
- Uwe Hernandez Acosta (HZDR/CASUS)
- Damar Wicaksono (HZDR/CASUS)
- Minterpy development team

## Contributing
State if you are open to contributions and what your requirements are for accepting them.

For people who want to make changes to your project, it's helpful to have some documentation on how to get started. Perhaps there is a script that they should run or some environment variables that they need to set. Make these steps explicit. These instructions could also be useful to your future self.

You can also document commands to lint the code or run tests. These steps help to ensure high code quality and reduce the likelihood that the changes inadvertently break something. Having instructions for running tests is especially helpful if it requires external setup, such as starting a Selenium server for testing in a browser.
[Open an issue](https://codebase.helmholtz.cloud/interpol/minterpy-levelsets/-/issues) or submit PRs.

## Authors and acknowledgment
Show your appreciation to those who have contributed to the project.

## License
For open source projects, say how it is licensed.

## Project status
If you have run out of energy or time for your project, put a note at the top of the README saying that development has slowed down or stopped completely. Someone may choose to fork your project or volunteer to step in as a maintainer or owner, allowing your project to keep going. You can also make an explicit request for maintainers.
[MIT](LICENSE)

[^1]: [Veettil, Sachin K. Thekke, Gentian Zavalani, Uwe Hernandez Acosta, Ivo F. Sbalzarini, and Michael Hecht. "Global Polynomial Level Sets for Numerical Differential Geometry of Smooth Closed Surfaces." arXiv preprint arXiv:2212.11536 (2022)] (https://arxiv.org/abs/2212.11536).
6 changes: 3 additions & 3 deletions pyproject.toml
Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"

[project]
name = "minterpy_levelsets"
version = "0.0.1"
version = "0.1.0"
authors = [
{ name="Sachin Krishnan Thekke Veettil", email="[email protected]" },
]
Expand All @@ -20,8 +20,8 @@ classifiers = [
]

[project.urls]
"Homepage" = "https://gitlab.hzdr.de/interpol/minterpy-levelsets"
"Bug Tracker" = "https://github.com/pypa/sampleproject/issues"
"Homepage" = "https://codebase.helmholtz.cloud/interpol/minterpy-levelsets"
"Bug Tracker" = "https://codebase.helmholtz.cloud/interpol/minterpy-levelsets/-/issues"

[tool.setuptools_scm]
write_to = "src/minterpy_levelsets/version.py"
86 changes: 5 additions & 81 deletions setup.cfg
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Expand Up @@ -3,10 +3,10 @@ name = minterpy_levelsets
description = Python library for global polynomial levelsets
long_description = file: README.md
long_description_content_type = text/markdown
url = https://gitlab.hzdr.de/interpol/minterpy-levelsets
url = https://codebase.helmholtz.cloud/interpol/minterpy-levelsets
author = file: AUTHORS.md
author_email = [email protected]
maintainer = Minterpy development team
maintainer = Sachin Krishnan Thekke Veettil
maintainer_email = [email protected]
license = MIT
license_file = LICENSE
Expand All @@ -25,7 +25,7 @@ classifiers =
Programming Language :: Python :: 3.9
Topic :: Scientific/Engineering
project_urls =
Bug Tracker = https://gitlab.hzdr.de/interpol/minterpy-levelsets/issues
Bug Tracker = https://codebase.helmholtz.cloud/interpol/minterpy-levelsets/-/issues

[options]
packages = find:
Expand All @@ -37,6 +37,8 @@ install_requires =
pytest>=4.6
pytest-cov>=2.12.0
scipy>=1.6.3
minterpy>=0.2.0a0
sympy>=1.11.1
python_requires = >=3.8
include_package_data = True
package_dir =
Expand All @@ -45,81 +47,3 @@ package_dir =
[options.packages.find]
where = src

[options.extras_require]
dev =
matplotlib>=3.4.2
numba>=0.53.1
numpy>=1.13.3
pytest>=4.6
pytest-cov>=2.12.0
scipy>=1.6.3
docs =
Sphinx>=3.0.0
matplotlib>=3.4.2
myst_parser>=0.13
numba>=0.53.1
numpy>=1.13.3
numpydoc>=1.2
pytest>=4.6
pytest-cov>=2.12.0
scipy>=1.6.3
nbsphinx>=0.8.8
ipykernel>=6.9.1
ipython-genutils>=0.2.0
sphinx-copybutton>=0.5.0
sphinxcontrib.bibtex>=2.4.1
sphinx-autobuild>=2021.3.14
pydata-sphinx-theme>=0.7.2

test =
matplotlib>=3.4.2
numba>=0.53.1
numpy>=1.13.3
pytest>=4.6
pytest-cov>=2.12.0
scipy>=1.6.3

[tool:pytest]
addopts = -ra -Wd
--cov-config=.coveragerc
--cov minterpy
--cov-report term-missing
--cov-report html
testpaths =
tests

[check-manifest]
ignore =
.github/**
docs/**
.pre-commit-config.yaml
.readthedocs.yml
src/*/version.py

[flake8]
ignore = E203, E231, E501, E722, W503, B950
select = C,E,F,W,T,B,B9,I
per-file-ignores =
tests/*: T

[mypy]
files = src
python_version = 3.8
plugins = numpy.typing.mypy_plugin
warn_unused_configs = True
disallow_any_generics = True
disallow_subclassing_any = True
disallow_untyped_calls = True
disallow_untyped_defs = True
disallow_incomplete_defs = True
check_untyped_defs = True
disallow_untyped_decorators = True
no_implicit_optional = True
warn_redundant_casts = True
warn_unused_ignores = True
warn_return_any = True
no_implicit_reexport = True
strict_equality = True

[mypy-numpy]
ignore_missing_imports = True

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