ConservedWaterSearch 0.0.1

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ConservedWaterSearch

The conservedwatersearch Python library uses density based clustering approach to detect conserved waters from simulation trajectories. Conserved water molecules can be further classified into 3 distinct conserved water types based on their hydrogen orientation: Fully Conserved Waters (FCW), Half Conserved Waters (HCW) and Weakly conserved waters (WCW) - see the figure below for examples. We support many different density based clustering approaches using standard OPTICS and HDBSCAN procedures as well as multi stage re-clustering approach using either of the two algorithms for very precise (and slow) determination of conserved water molecules.

Important links

• Documentation: hosted on Read The Docs

• GitHub repository: source code/contribute code

• Issue tracker: Report issues/ request features

Related Tools

• WaterNetworkAnalysis: prepare trajectories and analyse results for/from conservedwatersearch

Citation

Coming soon.

Installation

The easiest ways to install ConservedWaterSearch is using pip:

pip install ConservedWaterSearch

Conda builds will be available soon.

Example

The easiest way to use CWS is by calling WaterNetworkAnalysis (WNA) package. However, sometimes users might want to explicitly classify conserved water molecules. A simple python code can be used to classify waters into categories given an array of 3D oxygen coordinates and their related relative hydrogen orientations:

import ConservedWaterSearch.hydrogen_orientation as HO
# load some example
orientations = np.loadtxt("tests/data/conserved_sample_FCW.dat")
# Run classification
res = HO.hydrogen_orientation_analysis(
     orientations,
)
# print the water type
print(res[0][2])

For more complex usecases, please refer to the WaterNetworkAnalysis.