e09d0c0d07
This update introduces two improvements from the Mantaflow repository: (1) Improved particle sampling: - Liquid and secondary particles are sampled more predictably. With all parameters being equal, baked particles will be computed at the exact same position during every bake. - Before, this was not guaranteed. (2) Sparse grid caching: - While saving grid data to disk, grids will from now on be saved in a sparse structure whenever possible (e.g. density, flame but not levelsets). - With the sparse optimization grid cells with a value under the 'Empty Space' value (already present in domain settings) will not be cached. - The main benefits of this optimization are: Smaller cache sizes and faster playback of simulation data in the viewport. - This optimization works 'out-of-the-box'. There is no option in the UI to enable it. - For now, only smoke simulation grids will take advantage of this optimization.
Mantaflow
Mantaflow is an open-source framework targeted at fluid simulation research in Computer Graphics. Its parallelized C++ solver core, python scene definition interface and plugin system allow for quickly prototyping and testing new algorithms.
In addition, it provides a toolbox of examples for deep learning experiments with fluids. E.g., it contains examples how to build convolutional neural network setups in conjunction with the tensorflow framework.
For more information on how to install, run and code with Mantaflow, please head over to our home page at http://mantaflow.com