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pyDIFRATE is an implementation of the 'detectors' method of analyze dynamics data, with the current implementation covering the analysis of nuclear magnetic resonance (NMR) relaxation and molecular dynamics (MD) simulation. DIFRATE stands for "DIstortion Free Relaxation Analysis TEchnique".
The key idea of detector analysis is that NMR relaxation rate constants and MD-derived correlation functions can be constructed as a sum of contributions from motion as a function of correlation time. Then every experiment (or every time point in a correlation function) has a well-defined sensitivity as a function of correlation time. Furthermore, a set of experiments (or time points) can be used to construct a new set of so-called detectors, which also have sensitivities as a function of correlation time. Detectors, however, are generally optimized to yield narrow sensitivities with reduced overlap and normalized amplitudes, thus making them more easily interpreted than raw experimental data. Then, critical to the detector analysis are data objects, which contain unprocessed or processed data, sensitivity objects, which define the sensitivities of data in the data object as a function of correlation time, and detectors, which define the sensitivity of processed data to correlation time and also define how to perform the processing.
Detectors are also powerful for allowing quantitative comparison between experimental and simulated methods and for comparing results of different analysis (see below). Therefore, we organize data into projects, which in turn provide tools for comparing and creating comparable data.
To help non-expert python users, we also provide a graphical user interface (GUI) to guide users through the steps of analyzing experimental and simulated data with detectors.
Finally, we provide advanced methods of analyzing molecular dynamics trajectories to more easily interpret the total motion in the MD or experiment as the product of many individual motions. We implement iRED (Smith et al.,Prompers,Bruschweiler) for timescale-specific correlation analysis of MD trajectories and ROMANCE analysis for separating the total motion into components via frames.