Install
To install this package as a dependency, run:
pip install linear-operator-learning
Development
To develop this project, please setup the uv project manager by running the following commands:
curl -LsSf https://astral.sh/uv/install.sh | sh
git clone git@github.com:CSML-IIT-UCL/linear_operator_learning.git
cd linear_operator_learning
uv sync --dev
uv run pre-commit install
Optional
Set up your IDE to automatically apply the ruff styling.
Development principles
Please adhere to the following principles while contributing to the project:
- Adopt a functional style of programming. Avoid abstractions (classes) at all cost.
- To add a new feature, create a branch and when done open a Pull Request. You should not approve your own PRs.
- The package contains both
numpyandtorchbased algorithms. Let's keep them separated. - The functions shouldn't change the
dtypeor device of the inputs (that is, keep a functional approach). - Try to complement your contributions with simple examples to be added in the
examplesfolder. If you need some additional dependency add it to theexamplesdependency group asuv add --group examples _your_dependency_.
1 maintainer
Metadata
1 maintainer
Release files for linear-operator-learning 0.2.5
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| File | Size | Uploaded | Provenance | Actions |
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| File | Interpreter | ABI | Platform | Actions Reset |
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| linear_operator_learning-0.2.5-py3-none-any.whl | Python 3 | none | any | Details for linear_operator_learning-0.2.5-py3-none-any.whl |
Total release size: 596.0 kB
Release files / linear_operator_learning-0.2.5.tar.gz
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