OpenMORe is a collection of Python modules for Model-Order-Reduction, clustering and classification.

If you use OpenMORe for your publications, I kindly ask you to cite the following papers: If you use clustering.py and/or classification.py:

• D’Alessio et al., "Adaptive chemistry via pre-partitioning of composition space and mechanism reduction." Combustion and Flame 211 (2020): 68-82.
• D'Alessio et al., "Feature extraction and artificial neural networks for the on-the-fly classification of high-dimensional thermochemical spaces in adaptive-chemistry simulations." Data-Centric Engineering 2 (2021).

If you use model_order_reduction.py:

• D'Alessio et al., "Analysis of turbulent reacting jets via principal component analysis." Data Analysis for Direct Numerical Simulations of Turbulent Combustion. Springer, Cham, 2020. 233-251.

Model Order Reduction:

• Principal Component Analysis (PCA)
• Local PCA (LPCA)
• Kernel PCA (KPCA)
• Feature selection via PCA
• Outlier removal via PCA
• Data sampling

Clustering:

• Local PCA (via Vector Quantization, unsupervised)
• FPCA (via conditioning vector, supervised)
• Spectral Clustering (unsupervised)

Utilities:

• Multivariate data preprocessing
• Varimax Rotation
• Clustering solution evaluation
• Fast algorithm for SVD

In order to use OpenMORe on your devices, the following requirements must be satisfied:

• Python version >= 3.6
• Numpy must be installed
• Scipy must be installed
• Matplotlib must be installed
• Pandas must be installed
• Latex must be installed (for the plots' labels)

If the libraries requirements are satisfied, clone or download the repo. After that, go to the OpenMORe folder from your terminal (where the file setup.py is located) and type: python setup.py install.

It is possible to check if the installation process was successful running the tests. To do that, just type:

• python -m unittest tests/test_PCA.py
• python -m unittest tests/test_sampling.py
• python -m unittest tests/test_clustering.py

If the tests have positive response, you should get a message like:

___________________________
Ran 4 tests in 0.113s

OK
___________________________

If the tests are successful, you can now use OpenMORe. In the "examples" folder there are some pre-set cases, organized according to the final purpose (e.g., clustering, dimensionality-reduction, variables-selection, others). They are also fully commented to describe the required dictionary inputs. In the “data/reactive_flow” folder, there is a collection of data (from a CFD simulation of a turbulent reacting jet) to run the examples and test the code, while in "data/dummy_data" you can find relatively simple data sets to test the scripts' functionality. A detailed description of all the classes and functions is available in the detailed documentation and in the source code.

The official documentation is available in /OpenMORe/Documentation. It is strongly suggested to read it before using the software.

For any question or problem regarding the code you can write to me at the following address: [email protected]