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To launch the Matlab version, the working installation of Matlab and [Matlab Symbolic Math Toolbox](https://www.mathworks.com/products/symbolic.html) is required.
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The second version is implemented using the open-source computer algebra library [SymPy](https://www.sympy.org/) as a [Jupyter](https://jupyter.org/)/[IPython](https://ipython.org/) notebook. The Jupyter notebooks can be viewed directly at GitHub ([example](https://github.com/PTsolvers/PseudoTransientStokes.jl/blob/main/dispersion_analysis/dispersion_analysis_stokes1D.ipynb)). However, in order to view the notebook on a local computer or to make changes to the scripts, the recent Python installation is required. Also, several Python packages need to be installed: SymPy, NumPy, Jupyter, and Matplotlib. The easiest way to install these packages along with their dependencies is to use the [Anaconda](https://www.anaconda.com/products/individual) platform.
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The second version is implemented using the open-source computer algebra library [SymPy](https://www.sympy.org/) as a [Jupyter](https://jupyter.org/)/[IPython](https://ipython.org/) notebook. The Jupyter notebooks can be viewed directly on GitHub ([example](https://github.com/PTsolvers/PseudoTransientStokes.jl/blob/main/dispersion_analysis/dispersion_analysis_stokes1D.ipynb)). However, in order to view the notebook on a local computer or to make changes to the scripts, the recent Python installation is required. Also, several Python packages need to be installed: SymPy, NumPy, Jupyter, and Matplotlib. The easiest way to install these packages along with their dependencies is to use the [Anaconda](https://www.anaconda.com/products/individual) platform.
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After installing `Anaconda`, open the terminal, `cd` into the `dispersion_analysis` folder and create a new `conda` environment with the following command:
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This command starts a server and opens the browser window with file manager.
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## Additional infos
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The repository implements a reference tests suite, using [ReferenceTests.jl](https://github.com/JuliaTesting/ReferenceTests.jl), to verify the correctness of the outputed results with resepct to a reference solution.
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The repository implements a reference tests suite, using [ReferenceTests.jl](https://github.com/JuliaTesting/ReferenceTests.jl), to verify the correctness of the outputed results with respect to a reference solution.
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## Questions, comments and discussions
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To discuss technical issues, please post on Julia Discourse in the [Julia at Scale topic](https://discourse.julialang.org/c/domain/parallel/) or in the `#gpu` or `#distributed` channels on the [Julia Slack](https://julialang.slack.com/) (to join, visit https://julialang.org/slack/).

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