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This project is a simple library for running [System Dynamics](http://en.wikipedia.org/wiki/System_dynamics) models in python, with the purpose of improving integration of *Big Data* and *Machine Learning* into the SD workflow.
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This project is a library for running [System Dynamics](http://en.wikipedia.org/wiki/System_dynamics) models in Python, with the purpose of improving integration of *Big Data* and *Machine Learning* into the SD workflow.
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**The current version needs to run at least Python 3.7.**
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For standard methods for data analysis with SD models, see the [PySD Cookbook](https://github.com/JamesPHoughton/PySD-Cookbook), containing (for example):
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For standard methods for data analysis with SD models, see the [PySD Cookbook](https://github.com/SDXorg/PySD-Cookbook), containing (for example):
-[Surrogating model components with machine learning regressions](http://nbviewer.ipython.org/github/JamesPHoughton/PySD-Cookbook/blob/master/6_1_Surrogating_with_regression.ipynb)
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-[Multi-Scale geographic comparison of model predictions](http://nbviewer.ipython.org/github/JamesPHoughton/PySD-Cookbook/blob/master/Exploring%20models%20across%20geographic%20scales.ipynb)
-[Surrogating model components with machine learning regressions](http://nbviewer.ipython.org/github/SDXorg/PySD-Cookbook/blob/master/source/analyses/surrogating_functions/Surrogating_with_regression.ipynb)
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-[Multi-Scale geographic comparison of model predictions](http://nbviewer.ipython.org/github/SDXorg/PySD-Cookbook/blob/master/source/analyses/geo/Exploring_models_across_geographic_scales.ipynb)
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If you use PySD in any published work, consider citing the [PySD Introductory Paper](https://github.com/JamesPHoughton/pysd/blob/master/docs/PySD%20Intro%20Paper%20Preprint.pdf):
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If you use PySD in any published work, consider citing the [PySD Introductory Paper](https://github.com/SDXorg/pysd/blob/master/docs/PySD%20Intro%20Paper%20Preprint.pdf):
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>Houghton, James; Siegel, Michael. "Advanced data analytics for system dynamics models using PySD." *Proceedings of the 33rd International Conference of the System Dynamics Society.* 2015.
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You can use PySD in [R](https://www.r-project.org/) via the [PySD2R](https://github.com/JimDuggan/pysd2r) package, also available on [cran](https://CRAN.R-project.org/package=pysd2r).
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### Contributors
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### Contributing
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Many people have contributed to developing this project - by
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[submitting code](https://github.com/JamesPHoughton/pysd/graphs/contributors), bug reports, and advice.
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PySD is currently a community-maintained project, any contribution is welcome.
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Special thanks to the [sdCloud.io](http://sdcloud.io) development team, who have
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made great contributions to XMILE support, and for integrating PySD into their cloud-based model simulation environment.
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Many people have contributed to developing this project - by [submitting code](https://github.com/SDXorg/pysd/graphs/contributors), bug reports, and advice. Main historic changes in PySD are described in the [About PySD section](https://pysd.readthedocs.io/en/latest/about.html). The [Developer Documentation](https://pysd.readthedocs.io/en/latest/development/development_index.html) could help new developers.
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Extra special thanks to [@enekomartinmartinez](https://github.com/enekomartinmartinez) for dramatically pushing forward subscript capabilities (and many other attributes).
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The code for this package is available at: https://github.com/SDXorg/pysd
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About the Project
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=================
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PySD was created in 2014 by `James P Houghton <https://github.com/JamesPHoughton>`_ to translate Vensim models to Python. The original goal for translating SD models into Python was to be able to take advantage of all the tools available in Python and thus to extent what is possible using Vensim.
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Since the creation of the library, many people have contributed to the project by reporting and fixing bugs and adding new features. These contributions are listed in the `contributions section of the GitHub repository <https://github.com/SDXorg/pysd/graphs/contributors>`_.
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Some of the big changes that have allowed PySD to get to its current state are the development of an XMILE to Python translator in 2017 by `Alex Prey <https://github.com/alexprey>`_ and the restructuring of the translation and model building through an Abstract Syntax by `Eneko Martin-Martinez <https://github.com/enekomartinmartinez>`_ in 2022.
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Some other contributions until release 3.0.0 were:
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- `Julien Malard-Adam <https://github.com/julienmalard>`_ added unicode support for the Vensim parser.
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- `sdCloud.io <http://sdcloud.io>`_ development team made great contributions to improve XMILE support and integrated PySD into their cloud-based model simulation environment.
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- `Eneko Martin-Martinez <https://github.com/enekomartinmartinez>`_ pushed forward the subscripts capabilities for both Vensim and XMILE and included support for several Vensim functions and improved the performance.
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- `Roger Samsó <https://github.com/rogersamso>`_ included a parser for the Vensim sketch and added the option to split a Vensim model per view based on the sketch information.
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The changes made since release 3.0.0 are tracked in the :doc:`whats_new` section.
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Motivation: The (coming of) age of Big Data
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The central paradigm of PySD is that it is more efficient to bring the mature capabilities of system dynamics into an environment in use for active development in data science, than to attempt to bring each new development in inference and machine learning into the system dynamics enclave.
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PySD reads a model file – the product of a modeling program such as Vensim or Stella/iThink – and cross compiles it into Python, providing a simulation engine that can run these models natively in the Python environment. It is not a substitute for these tools, and cannot be used to replace a visual model construction environment.
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