TensorFlow implementation of the Lorentz Boost Network (LBN).
Project description
For more information, see https://arxiv.org/abs/1812.09722.
Home-page: https://git.rwth-aachen.de/3pia/lbn
Author: Marcel Rieger
Author-email: marcel.rieger@cern.ch
License: BSD
Description: # Lorentz Boost Network (LBN) [![pipeline status](https://git.rwth-aachen.de/3pia/lbn/badges/master/pipeline.svg)](https://git.rwth-aachen.de/3pia/lbn/pipelines)
TensorFlow implementation of the Lorentz Boost Network from [arXiv:1812.09722 [hep-ex]](https://arxiv.org/abs/1812.09722).
Original repository: [git.rwth-aachen.de/3pia/lbn](https://git.rwth-aachen.de/3pia/lbn)
### Usage example
```python
from lbn import LBN
# initialize the LBN, set 10 combinations and pairwise boosting
lbn = LBN(10, boost_mode=LBN.PAIRS)
# create a feature tensor based on input four-vectors
features = lbn(four_vectors)
# use the features as input for a subsequent, application-specific network
...
```
### Installation and dependencies
Via [pip](https://pypi.python.org/pypi/lbn):
```bash
pip install lbn
```
NumPy and TensorFlow are the only dependencies.
### Testing
Tests should be run for Python 2 and 3. The following commands assume you are root directory of the LBN respository:
```bash
python -m unittest test
# or via docker, python 2
docker run --rm -v `pwd`:/root/lbn -w /root/lbn tensorflow/tensorflow:latest python -m unittest test
# or via docker, python 3
docker run --rm -v `pwd`:/root/lbn -w /root/lbn tensorflow/tensorflow:latest-py3 python -m unittest test
```
### Contributing
If you like to contribute, we are happy to receive pull requests. Just make sure to add new test cases and run the tests. Also, please use a coding style that is compatible with our `.flake8` config.
### Development
- Original source hosted at [RWTH GitLab](https://git.rwth-aachen.de/3pia/lbn)
- Report issues, questions, feature requests on [RWTH GitLab Issues](https://git.rwth-aachen.de/3pia/lbn/issues)
Keywords: neural network,lorentz,lorentz transformation,lorentz boost,autonomous,feature,feature engineering,autonomous engineering,hep,four momenta,four vectors
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
Classifier: Development Status :: 4 - Beta
Classifier: Operating System :: OS Independent
Classifier: License :: OSI Approved :: BSD License
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Information Technology
Requires-Python: >=2.7
Description-Content-Type: text/markdown
Home-page: https://git.rwth-aachen.de/3pia/lbn
Author: Marcel Rieger
Author-email: marcel.rieger@cern.ch
License: BSD
Description: # Lorentz Boost Network (LBN) [![pipeline status](https://git.rwth-aachen.de/3pia/lbn/badges/master/pipeline.svg)](https://git.rwth-aachen.de/3pia/lbn/pipelines)
TensorFlow implementation of the Lorentz Boost Network from [arXiv:1812.09722 [hep-ex]](https://arxiv.org/abs/1812.09722).
Original repository: [git.rwth-aachen.de/3pia/lbn](https://git.rwth-aachen.de/3pia/lbn)
### Usage example
```python
from lbn import LBN
# initialize the LBN, set 10 combinations and pairwise boosting
lbn = LBN(10, boost_mode=LBN.PAIRS)
# create a feature tensor based on input four-vectors
features = lbn(four_vectors)
# use the features as input for a subsequent, application-specific network
...
```
### Installation and dependencies
Via [pip](https://pypi.python.org/pypi/lbn):
```bash
pip install lbn
```
NumPy and TensorFlow are the only dependencies.
### Testing
Tests should be run for Python 2 and 3. The following commands assume you are root directory of the LBN respository:
```bash
python -m unittest test
# or via docker, python 2
docker run --rm -v `pwd`:/root/lbn -w /root/lbn tensorflow/tensorflow:latest python -m unittest test
# or via docker, python 3
docker run --rm -v `pwd`:/root/lbn -w /root/lbn tensorflow/tensorflow:latest-py3 python -m unittest test
```
### Contributing
If you like to contribute, we are happy to receive pull requests. Just make sure to add new test cases and run the tests. Also, please use a coding style that is compatible with our `.flake8` config.
### Development
- Original source hosted at [RWTH GitLab](https://git.rwth-aachen.de/3pia/lbn)
- Report issues, questions, feature requests on [RWTH GitLab Issues](https://git.rwth-aachen.de/3pia/lbn/issues)
Keywords: neural network,lorentz,lorentz transformation,lorentz boost,autonomous,feature,feature engineering,autonomous engineering,hep,four momenta,four vectors
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
Classifier: Development Status :: 4 - Beta
Classifier: Operating System :: OS Independent
Classifier: License :: OSI Approved :: BSD License
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Information Technology
Requires-Python: >=2.7
Description-Content-Type: text/markdown
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