BilayerAnalyzer analysis: dc_cluster
- Hiearchical clustering of lipids based on distance.¶
Description¶
Compute lipid clusters using a hiearchical distance based method.
This analysis uses a type of hiearchical clustering where points (lipid centers of mass) are are added to a cluster if they are within a specified distance of any other point within the cluster.
This protocol is identified by the analysis key: ‘dc_cluster’
Initiated by instance of:¶
<class 'pybilt.bilayer_analyzer.analysis_protocols.DCClusterProtocol'>
Syntax¶
dc_cluster analysis-ID keyword value
dc_cluster = analysis-Key - keyword/name for this analysis.
analysis-ID = The unique name/ID being assigned to this analysis.
keyword value = settings keyword value pairs
leaflet (str: ‘both’, ‘upper’, or ‘lower’): Specifies the bilayer leaflet to include in the estimate. Default: ‘both’
resname (str): Specify the resname of the lipid type to include in this analysis. Default: ‘all’, includes all lipid types.
cutoff (float): The cutoff distance to use for the clustering. Default: 12.0
Examples¶
Construct analyzer:
analyzer = BilayerAnalyzer(structure='name_of_structure_file',
trajectory='name_of_traj_file',
selection='resname POPC DOPC')
Add by string - use default settings:
analyzer.add_analysis('dc_cluster dc_cluster_1')
Add by string - adjust a setting:
analyzer.add_analysis('dc_cluster dc_cluster_1 resname POPC')
Add by list:
analyzer.add_analysis(list(['dc_cluster', 'dc_cluster_1', dict({'resname':'POPC'})]))
Add by dict:
analyzer.add_analysis(dict({'analysis_key': 'dc_cluster', 'analysis_id': 'dc_cluster_1','analysis_settings':dict({'resname':'POPC'})}))
To remove from analyzer:
analyzer.remove_analysis('dc_cluster_1')
Output Info:¶
Retrieve output after running analyses:
output = analyzer.get_analysis_data('dc_cluster_1')
The output is type <type 'dict'>
Note
Only finds the self clusters for a single lipid type as specified by the ```resname``` setting.
References¶
None