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Author SHA1 Message Date
Geonhee eb0bf0c782
correct typos (#17) 2021-08-23 21:57:01 +09:00
Shunichi09 a0f9d219f5
Update README.md 2021-05-28 14:49:20 +09:00
Shunichi09 f057d2669e Fix wrong name 2021-05-28 14:41:08 +09:00
Shunichi09 6519290e2e
Workflow tests (#15)
* Add pypi workflow

* Fix wrong name
2021-05-28 14:38:12 +09:00
Shunichi09 cf30226519
Add pypi workflow (#14) 2021-05-28 14:35:59 +09:00
3 changed files with 34 additions and 14 deletions

26
.github/workflows/python-publish.yml vendored Normal file
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@ -0,0 +1,26 @@
name: Upload Python Package
on:
release:
types: [created]
jobs:
deploy:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v2
- name: Set up Python 3.6
uses: actions/setup-python@v2
with:
python-version: '3.6'
- name: Install dependencies
run: |
python -m pip install --upgrade pip
pip install setuptools wheel twine
- name: Build and publish
env:
TWINE_USERNAME: ${{ secrets.PYPI_USERNAME }}
TWINE_PASSWORD: ${{ secrets.PYPI_PASSWORD }}
run: |
python setup.py bdist_wheel
twine upload dist/*

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@ -17,8 +17,8 @@ Due to use only basic libralies (scipy, numpy), this library is easy to extend f
|:----------|:---------------: |:----------------:|:----------------:|:----------------:|:----------------:|
| Linear Model Predictive Control (MPC) | ✓ | x | x | x | x |
| Cross Entropy Method (CEM) | ✓ | ✓ | x | x | x |
| Model Preidictive Path Integral Control of Nagabandi, A. (MPPI) | ✓ | ✓ | x | x | x |
| Model Preidictive Path Integral Control of Williams, G. (MPPIWilliams) | ✓ | ✓ | x | x | x |
| Model Predictive Path Integral Control of Nagabandi, A. (MPPI) | ✓ | ✓ | x | x | x |
| Model Predictive Path Integral Control of Williams, G. (MPPIWilliams) | ✓ | ✓ | x | x | x |
| Random Shooting Method (Random) | ✓ | ✓ | x | x | x |
| Iterative LQR (iLQR) | x | ✓ | x | ✓ | x |
| Differential Dynamic Programming (DDP) | x | ✓ | x | ✓ | ✓ |
@ -36,10 +36,10 @@ Following algorithms are implemented in PythonLinearNonlinearControl
- [Cross Entropy Method (CEM)](https://arxiv.org/abs/1805.12114)
- Ref: Chua, K., Calandra, R., McAllister, R., & Levine, S. (2018). Deep reinforcement learning in a handful of trials using probabilistic dynamics models. In Advances in Neural Information Processing Systems (pp. 4754-4765)
- [script](PythonLinearNonlinearControl/controllers/cem.py)
- [Model Preidictive Path Integral Control of Nagabandi, A. (MPPI)](https://arxiv.org/abs/1909.11652)
- [Model Predictive Path Integral Control of Nagabandi, A. (MPPI)](https://arxiv.org/abs/1909.11652)
- Ref: Nagabandi, A., Konoglie, K., Levine, S., & Kumar, V. (2019). Deep Dynamics Models for Learning Dexterous Manipulation. arXiv preprint arXiv:1909.11652.
- [script](PythonLinearNonlinearControl/controllers/mppi.py)
- [Model Preidictive Path Integral Control of Williams, G. (MPPIWilliams)](https://ieeexplore.ieee.org/abstract/document/7989202)
- [Model Predictive Path Integral Control of Williams, G. (MPPIWilliams)](https://ieeexplore.ieee.org/abstract/document/7989202)
- Ref: Williams, G., Wagener, N., Goldfain, B., Drews, P., Rehg, J. M., Boots, B., & Theodorou, E. A. (2017, May). Information theoretic MPC for model-based reinforcement learning. In 2017 IEEE International Conference on Robotics and Automation (ICRA) (pp. 1714-1721). IEEE.
- [script](PythonLinearNonlinearControl/controllers/mppi_williams.py)
- [Random Shooting Method (Random)](https://arxiv.org/abs/1805.12114)
@ -83,25 +83,19 @@ You could know abount our environmets more in [Environments.md](Environments.md)
## To install this package
```
python setup.py install
```
or
```
pip install .
$ pip install PythonLinearNonlinearControl
```
## When developing the package
```
python setup.py develop
$ python setup.py develop
```
or
```
pip install -e .
$ pip install -e .
```
# Basic concepts

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@ -14,7 +14,7 @@ setup(
install_requires=install_requires,
url='https://github.com/Shunichi09/PythonLinearNonlinearControl',
license='MIT License',
packages=find_packages(exclude=('tests')),
packages=find_packages(exclude=('tests', 'scripts')),
setup_requires=setup_requires,
test_suite='tests',
tests_require=tests_require