General

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

How to cite

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.

Implemented techniques:

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

Requirements:

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)

Installation:

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.

Test:

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
___________________________

Usage:

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.

Documentation:

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: giuseppe.dalessio@ulb.ac.be