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Experimental design and Bayesian optimization library in Python/PyTorch
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.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.5144404.svg :target: https://doi.org/10.5281/zenodo.5144404
NEXTorch is an open-source software package in Python/PyTorch to faciliate experimental design using Bayesian Optimization (BO).
NEXTorch stands for Next EXperiment toolkit in PyTorch/BoTorch. It is also a library for learning the theory and implementation of Bayesian Optimization.
See our documentation page_ for examples, equations used, and docstrings.
PyTorch_ >= 1.8: Used for tensor operations with GPU and autograd supportGPyTorch_ >= 1.4: Used for training Gaussian ProcessesBoTorch_ = 0.4.0: Used for providing Bayesian Optimization frameworkMatplotlib_: Used for generating plotsPyDOE2_: Used for constructing experimental designsNumpy_: Used for vector and matrix operationsScipy_: Used for curve fittingPandas_: Used to import data from Excel or CSV filesopenpyxl_: Used by Pandas to import Excel filespytest_: Used for unit tests.. _documentation page: https://nextorch.readthedocs.io/en/latest/ .. _PyTorch: https://pytorch.org/ .. _GPyTorch: https://gpytorch.ai/ .. _BoTorch: https://botorch.org/ .. _Matplotlib: https://matplotlib.org/ .. _pyDOE2: https://pythonhosted.org/pyDOE/ .. _Numpy: http://www.numpy.org/ .. _Scipy: https://www.scipy.org/ .. _Pandas: https://pandas.pydata.org/ .. _openpyxl: https://openpyxl.readthedocs.io/en/stable/ .. _pytest: https://docs.pytest.org/en/stable/
Install using pip (see documentation for full instructions)::
pip install nextorch
Run the unit tests.
Read the documentation for tutorials and examples.
This project is licensed under the MIT License - see the LICENSE.md. file for details.
If you have a suggestion or find a bug, please post to our Issues page on GitHub.
If you are having issues, please post to our Issues page on GitHub.
This material is based upon work supported by the Department of Energy's Office of Energy Efficient and Renewable Energy's Advanced Manufacturing Office under Award Number DE-EE0007888-9.5.
\Y. Wang, T.-Y. Chen, and D.G. Vlachos, NEXTorch: A Design and Bayesian Optimization Toolkit for Chemical Sciences and Engineering, J. Chem. Inf. Model. 2021, 61, 11, 5312–5319.
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