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86 lines
1.9 KiB
Markdown
86 lines
1.9 KiB
Markdown
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**MDAF**
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======================
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**Overview**
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------------
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The MDAF (Multi-Disciplinary Analysis Framework) repository provides a collection of tools and functions for performing multi-disciplinary analysis, optimization, and surrogate modeling.
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**Installation**
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---------------
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To install the MDAF package, use the following command:
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```bash
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pip install git+fullurl
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```
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**Dependencies**
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---------------
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The MDAF package depends on the following libraries:
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* `rpy2`
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* `scikit-learn`
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* `numpy`
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* `matplotlib`
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**Usage**
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-----
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The MDAF package provides several functions and tools for performing multi-disciplinary analysis, optimization, and surrogate modeling. Some examples include:
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* `installFlacco`: Installs the Flacco package and its dependencies.
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* `representfunc`: Represents test functions for analysis and optimization.
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* `doe`: Performs design of experiments (DOE) for surrogate modeling.
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**Test Functions**
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-----------------
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The MDAF package includes a collection of test functions for analysis and optimization, including:
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* `Alpine.py`
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* `Bukin4.py`
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* `Bukin6.py`
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* `Keane.py`
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* `Leon.py`
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* `Miele_Cantrell.py`
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* `Rastriring.py`
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* `Step.py`
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* `Step2.py`
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* `Wayburn.py`
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* `Zettle.py`
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* `Zirilli.py`
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**Notebooks**
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------------
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The repository includes several Jupyter notebooks that demonstrate the usage of the MDAF package, including:
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* `Analyse_folders_and_description.ipynb`
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* `PSO.ipynb`
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* `Simulated_Annealing_General.ipynb`
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**Tests**
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--------
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The repository includes a collection of unit tests and integration tests to ensure the correctness of the MDAF package.
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## Misc
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- reinstall the package for testing:
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```bash
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py -m pip install --upgrade --force-reinstall git+fullurl
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```
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- use specific versions: `python 37`
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- dependencies: `rpy2, scikitlearn, `
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- Windows: install R first
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- When using installFlacco please choose to create a new library on the first run
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