BilayerAnalyzer analysis: disp_vec_nncorr
- Displacement vector nearest neigbor correlations.¶
Description¶
Comute the pair-wise cross correlations for the displacement vectors for each lipid in the specified leaflet(s) of bilayer and its nearest neighbor.
This analysis computes the displacement vectors as in the ‘disp_vec’ analysis (DispVecProtocol), but then continues to compute the pair-wise cross correlation between each vector and its nearest neighbor. i.e. the cos(theta) for the angle theta between the vectors.
This protocol is identified by the analysis key: ‘disp_vec_nncorr’
Initiated by instance of:¶
<class 'pybilt.bilayer_analyzer.analysis_protocols.DispVecNNCorrelationProtocol'>
Syntax¶
disp_vec_nncorr analysis-ID keyword value
disp_vec_nncorr = 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.
interval (int): Sets the frame interval over which to compute the displacement vectors. f
wrapped (bool): Specify whether to use the wrapped (‘True’) or un-wrapped (‘False’) coordintes for the base of the vectors. Default: False
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('disp_vec_nncorr disp_vec_nncorr_1')
Add by string - adjust a setting:
analyzer.add_analysis('disp_vec_nncorr disp_vec_nncorr_1 leaflet both')
Add by list:
analyzer.add_analysis(list(['disp_vec_nncorr', 'disp_vec_nncorr_1', dict({'leaflet':'both'})]))
Add by dict:
analyzer.add_analysis(dict({'analysis_key': 'disp_vec_nncorr', 'analysis_id': 'disp_vec_nncorr_1','analysis_settings':dict({'leaflet':'both'})}))
To remove from analyzer:
analyzer.remove_analysis('disp_vec_nncorr_1')
Output Info:¶
Retrieve output after running analyses:
output = analyzer.get_analysis_data('disp_vec_nncorr_1')
The output is type <type 'list'>
References¶
None