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A symbolic framework for C++, Python and Octave implementing automatic differentiation by source code transformation in forward and reverse modes on sparse matrix-valued computational graphs.
This is a template Python code set to use JModelica easily.
This is a template Python code set which makes it easy to use JModelica to solve optimal control problem.
The template includes a sample model definition file (opt_definition.mop) and a .bat file (run_me.bat) to start its calculation. After download the template, immediately you can run JModelica by only double-clicking run_me.bat file, and obtain the optimization result.
Please go to the page given below for the information of how to start to use this and its details.
ASCEND is a modelling environment and solver for large or small systems of non-linear equations, for use in engineering, thermodynamics, chemistry, physics, mathematics and biology. Solvers for both steady and dynamic (NLA & DAE) problems, are provid
New customers can spin up VMs, build with AI, and query data at no cost.
Put your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
Moved to GitHub in 2013. This SourceForge project is no longer updated.
Source code and documentation:
stokes: https://github.com/kichiki/stokes
libstokes: https://github.com/kichiki/libstokes
libiter: https://github.com/kichiki/libiter
twobody: https://github.com/kichiki/twobody
RYUON User's Manual: https://github.com/kichiki/RYUON-manual
RYUON : many-particle simulation suite