htmd.projections.tica module#
- class htmd.projections.tica.TICA(data, lag, units='frames', dimensions=None, njobs=None)#
Bases:
object
Class for calculating the TICA projections of a MetricData object
Time-based Independent Component Analysis Projects your data on the slowest coordinates identified for a given lagtime.
- Parameters:
data (
MetricData
object) – The object whose data we wish to project onto the top TICA dimensionslag (int) – The correlation lagtime to use for TICA
units (str) – The units of lag. Can be ‘frames’ or any time unit given as a string.
dimensions (list) – A list of dimensions of the original data on which to apply TICA. All other dimensions will stay unaltered. If None is given, it will apply on all dimensions.
njobs (int) – Number of jobs to spawn for parallel computation of TICA components. If None it will use the default from htmd.config.
Example
>>> from htmd.projections.tica import TICA >>> metr = Metric(sims) >>> metr.set(MetricSelfDistance('protein and name CA')) >>> data = metr.project() >>> tica = TICA(data, 20) >>> datatica = tica.project(3) Alternatively you can pass a Metric object to TICA. Uses less memory but is slower. >>> metr = Metric(sims) >>> metr.set(MetricSelfDistance('protein and name CA')) >>> slowtica = TICA(metr, 20) >>> datatica = slowtica.project(3)
References
Perez-Hernandez, G. and Paul, F. and Giorgino, T. and de Fabritiis, G. and Noe, F. (2013) Identification of slow molecular order parameters for Markov model construction. J. Chem. Phys., 139 . 015102.
- project(ndim=None, var_cutoff=0.95)#
Projects the data object given to the constructor onto the top ndim TICA dimensions
- Parameters:
- Returns:
dataTica – A new
MetricData
object containing the TICA projected data- Return type:
MetricData
object
Example
>>> from htmd.projections.tica import TICA >>> tica = TICA(data,20) >>> dataTica = tica.project(5)