tnmf 0.1.1

Transform-Invariant Non-Negative Matrix Factorization

Transform-Invariant Non-Negative Matrix Factorization

A comprehensive Python package for Non-Negative Matrix Factorization (NMF) with a focus on learning transform-invariant representations.

The packages supports multiple optimization backends and can be easily extended to handle application-specific types of transforms.

General Introduction

A general introduction to Non-Negative Matrix Factorization and the purpose of this package can be found on the corresponding GitHub Pages.

Installation

For using this package, you will need Python version 3.7 (or higher). The package is available via PyPI.

Installation is easiest using pip:

pip install tnmf

Demos and Examples

The package comes with a streamlit demo and a number of examples that demonstrate the capabilities of the TNMF model. They provide a good starting point for your own experiments.

Online Demo

Without requiring any installation, the demo is accessible via streamlit sharing.

Local Execution

Once the package is installed, the demo and the examples can be conveniently executed locally using the tnmf command:

• To execute the demo, run tnmf demo.
• A specific example can be executed by calling tnmf example <example_name>.

To show the list of available examples, type tnmf example --help.

License

Copyright (c) 2021 Merck KGaA, Darmstadt, Germany

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

The full text of the license can be found in the file LICENSE in the repository root directory.

Contributing

Contributions to the package are always welcome and can be submitted via a pull request. Please note, that you have to agree to the Contributor License Agreement to contribute.

Working with the Code

To checkout the code and set up a working environment with all required Python packages, execute the following commands:

git checkout https://github.com/emdgroup/tnmf.git ./tnmf
cd tmnf
python3 -m virtualenv .venv
source .venv/bin/activate
pip install --upgrade pip
pip install -r requirements.txt

Now, you should be able to execute the unit tests by calling pytest to verify that the code is running as expected.

Pull Requests

Before creating a pull request, you should always try to ensure that the automated code quality and unit tests do not fail. To execute them, change into the repository root directory and run the following commands:

flake8
pylint tnmf
pytest

The output of the individual commands should be pretty instructive, so fixing potential issues is usually rather straightforward.

Building the Documentation

To build the documentation locally, change into the doc subdirectory and run make html. Then, the documentation resides at doc\_build\html\index.html.