__init__(self,
pipe_name=None,
pipe_bundle=None,
results_dir=None,
models=[ ' R2eff ' ] ,
grid_inc=11,
mc_sim_num=500,
exp_mc_sim_num=None,
modsel=' AIC ' ,
pre_run_dir=None,
optimise_r2eff=False,
insignificance=0.0,
numeric_only=False,
mc_sim_all_models=False,
eliminate=True,
set_grid_r20=False,
r1_fit=False)
(Constructor)
 source code

Perform a full relaxation dispersion analysis for the given list of
models.
 Parameters:
pipe_name (str)  The name of the data pipe containing all of the data for the
analysis.
pipe_bundle (str)  The data pipe bundle to associate all spawned data pipes with.
results_dir (str)  The directory where results files are saved.
models (list of str)  The list of relaxation dispersion models to optimise.
grid_inc (int or None)  Number of grid search increments. If set to None, then the grid
search will be turned off and the default parameter values will
be used instead.
mc_sim_num (int)  The number of Monte Carlo simulations to be used for error
analysis at the end of the analysis.
exp_mc_sim_num (int or None)  The number of Monte Carlo simulations for the error analysis in
the 'R2eff' model when exponential curves are fitted. This
defaults to the value of the mc_sim_num argument when not given.
When set to '1', the R2eff errors are estimated from the
Covariance matrix. For the 2point fixedtime calculation for
the 'R2eff' model, this argument is ignored.
modsel (str)  The model selection technique to use in the analysis to determine
which model is the best for each spin cluster. This can
currently be one of 'AIC', 'AICc', and 'BIC'.
pre_run_dir (None or str)  The optional directory containing the dispersion autoanalysis
results from a previous run. The optimised parameters from these
previous results will be used as the starting point for
optimisation rather than performing a grid search. This is
essential for when large spin clusters are specified, as a grid
search becomes prohibitively expensive with clusters of three or
more spins. At some point a RelaxError will occur because the
grid search is impossibly large. For the cluster specific
parameters, i.e. the populations of the states and the exchange
parameters, an average value will be used as the starting point.
For all other parameters, the R20 values for each spin and
magnetic field, as well as the parameters related to the chemical
shift difference dw, the optimised values of the previous run
will be directly copied.
optimise_r2eff (bool)  Flag to specify if the read previous R2eff results should be
optimised. For R1rho models where the error of R2eff values are
determined by MonteCarlo simulations, it can be valuable to make
an initial R2eff run with a high number of MonteCarlo
simulations. Any subsequent model analysis can then be based on
these R2eff values, without optimising the R2eff values.
insignificance (float)  The R2eff/R1rho value in rad/s by which to judge insignificance.
If the maximum difference between two points on all dispersion
curves for a spin is less than this value, that spin will be
deselected. This does not affect the 'No Rex' model. Set this
value to 0.0 to use all data. The value will be passed on to the
relax_disp.insignificance user function.
numeric_only (bool)  The class of models to use in the model selection. The default
of False allows all dispersion models to be used in the analysis
(no exchange, the analytic models and the numeric models). The
value of True will activate a pure numeric solution  the
analytic models will be optimised, as they are very useful for
replacing the grid search for the numeric models, but the final
model selection will not include them.
mc_sim_all_models (bool)  A flag which if True will cause Monte Carlo simulations to be
performed for each individual model. Otherwise Monte Carlo
simulations will be reserved for the final model.
eliminate (bool)  A flag which if True will enable the elimination of failed models
and failed Monte Carlo simulations through the eliminate user
function.
set_grid_r20 (bool)  A flag which if True will set the grid R20 values from the
minimum R2eff values through the r20_from_min_r2eff user
function. This will speed up the grid search with a factor
GRID_INC^(Nr_spec_freq). For a CPMG experiment with two fields
and standard GRID_INC=21, the speedup is a factor 441.
r1_fit  A flag which if True will activate R1 parameter fitting via
relax_disp.r1_fit for the models that support it. If False, then
the relax_disp.r1_fit user function will not be called.
