Computational Fluid Dynamics for Python.
pip install cfdpy
There are already some usefull packages for scientific computing with Python, such as
Based on these packages, CFDPy has implemented some additional features for CFD. CFDPy is different from the above packages in the following ways:
- CFDPy's ODE solvers accepts multidimensional arrays and adopts faster (low-accuracy) methods.
- CFDPy's derivative algorithm supports higher order differentials and accuracy.
CFDPy focuses on simplicity and is not optimized for parallel computing. It is useful for learning CFD, but not for fast computation. If you have faster computation needs, we recommend exploring Fortran, C++ or Julia codes.
- Finite difference methods of arbitrary order differentials and accuracy.
- De-aliasing spectral methods.
- Runge-Kutta methods of order 2 and 3.
- Low-storage Runge-Kutta methods of order 2 and 3.