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ADicksonLab
Weighted Ensemble simulation framework in Python
This was already removed from the dependency listing, but I still think there will be bugs that show up in some seldom used corners of the codebase.
The only place that this datastructure is meaningfully used is for outputting formats like gexf. We should maintain compatibility and have a method to produce a simplified networkx DiGraph with...
For large topologies this function is far too slow to be practical. The implementation had no optimizations applied so there is likely some easy things to do like not relying...
This is naively implemented and for large sets of traces it is kind of inefficient. We could implement a strategy that detects chunks of trace idxs that are contiguous in...
It can take a remarkably long time to read weights from an HDF5. I used iotop, and it shows a sustained reading rate of 220-230 Kb/s, but this is over...
The API for all boundary conditions does not include a method for computing the `progress` for a walker. This is implemented as `_progress` currently and was private just to not...
No warps show up in the dashboard reporter even though there are warping events in the HDF5.
There is some basic considerations towards this, but a more thorough audit needs to be done to make sure that this is supported in a first class way. Currently, if...
There have been some efforts to fix issues as they crop up with h5py v3 switch which primarily changed the API for string datasets. The solutions have not been complete...
Somewhat related to #22. Data in WepyHDF5 is laid out in an Struct-of-Array (SoA) format. This is well suited for a small number of long trajectory datasets and for larger...
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Weighted Ensemble simulation framework in Python