htmd.projections.gwpca module#

class htmd.projections.gwpca.GWPCA(data, lag, units='frames')#

Bases: object

Class for calculating the globally-weighted PCA projections of a MetricData object.

References

  • N. Blöchliger, A. Caflisch, and A. Vitalis. Weighted Distance Functions Improve Analysis of High-Dimensional Data: Application to Molecular Dynamics Simulations, J. Chem. Theory Comput., 2015, 11 (11), pp 5481-5492. doi: 10.1021/acs.jctc.5b00618

Parameters:

  • data (MetricData) – The object whose data we wish to project.

  • lag (float) – The correlation lagtime used to compute autocorrelation weights.

  • units (str) – The units of lag. Can be 'frames' or any time unit given as a string.

Examples

>>> gw = GWPCA(data, lag=10)
>>> dataproj = gw.project(5)
project(ndim=None)#

Project the data object given to the constructor onto ndim dimensions.

Parameters:

ndim (int | None) – The number of dimensions to project the data on.

Returns:

projdata – A new MetricData object containing the projected data.

Return type:

MetricData

Examples

>>> gw = GWPCA(data, lag=10)
>>> dataproj = gw.project(5)