Hi, The problem you see is that of failed models. I'm guessing that residues 4, 5, 6, 7, and 9 are reasonable and 3 and 8 are not. Have you looked closely at the data? Is it of high quality? There are two things which can be done here. The first is the most basic - perform an analysis deselecting the spin systems with 'bad' data or that have failed. This is what would normally be done by a user. The model_eliminate user function performs this for the model-free and other analyses, but no dispersion rules are set up for this. I also do not think that we can have automatic rules for determining this as these high kex values might be reasonable in another molecular system.
The second option is to modify the parameter averaging in the clustering. This is in the specific_analyses.relax_disp.parameters.copy() function. You will see here that the code averages the parameters. Maybe a better measure would be to use the median rather than mean. This should handle severe outliers caused by failed models much better. The numpy.median() function could be used for this. Instead of summing the parameters, lists could be created and then the list sent to numpy.median(). For example initialise kex as [], use the append method kex.append(spin_from.kex), and then store the value as spin_to.kex = numpy.median(kex). For example: relax> import numpy relax> kex = [1060772.86091342, 3.20195659408987, 2.15902319384803, 2.7190458578948, 2.37325031348072, 828438.809437978, 2.93391757645135] relax> numpy.median(kex) 2.9339175764513499 relax> What do you think? Would this solve the problems you see? Cheers, Edward On 8 October 2013 14:22, Troels Emtekær Linnet <[email protected]> wrote: > Hi Edward. > > I would like to hear, if you could give some hints how you would > handle a clustering analysis situation the best way. > > It is related to this entry, which I am modifying. > http://wiki.nmr-relax.com/Tutorial_for_Relaxation_dispersion_analysis_cpmg_fixed_time_recorded_on_varian_as_fid_interleaved#Execute_a_clustering_analysis > > I would like to do the clustering analysis for the model: TSMFK01 > > When I do the clustering analysis, I am pointing to a previous result > directory. > I am clustering those residues, which is not the model "No Rex". > > relax will read the file TSMFK01/kAB.out file with the previous results. > I will take the averaged kAB values for the residues specified in the cluster. > > ------------- > # Parameter description: The exchange rate from state A to state B. > # > # mol_name res_num res_name spin_num spin_name value > error > None 3 A 1 N > 1060772.86091342 None > None 4 E 2 N > 3.20195659408987 None > None 5 F 3 N > 2.15902319384803 None > None 6 D 4 N > 2.7190458578948 None > None 7 K 5 N > 2.37325031348072 None > None 8 A 6 N > 828438.809437978 None > None 9 A 7 N > 2.93391757645135 None > ... > -------------- > > The problem here is, that it seems that the fitting is going "crazy" > for some residues. > And the averaged starting value will be: > Averaged k_AB value: 83471.18...... > > The expected value would be somewhere: kAB = 2-10 > > What would be the best solution for this problem? > 1) Modify the source code for the TSMFK01 model, so results are within > expected range. > 2) Manually modify the TSMFK01/kAB.out and write k_AB=5 > 3) Skipping the pointing to a previous run directory, loop over the > spins and setting kAB=5 before doing a minimization? > > > ----------------- > Output from an auto-analysis > ------------------------- > > ----------------------- > - The 'TSMFK01' model - > ----------------------- > relax> pipe.copy(pipe_from='base pipe', pipe_to='TSMFK01', > bundle_to='relax_disp') > relax> pipe.switch(pipe_name='TSMFK01') > relax> relax_disp.select_model(model='TSMFK01') > The Tollinger et al. (2001) 2-site very-slow exchange model, range of > microsecond to second time scale. > > relax> value.copy(pipe_from='R2eff', pipe_to='TSMFK01', param='r2eff') > relax> pipe.create(pipe_name='pre', pipe_type='relax_disp', bundle=None) > > relax> results.read(file='results', > dir='/net/tomat/home/tlinnet/kte/acbp/acbp_cpmg_disp_04MGuHCl_40C_041223_RELAX.fid/relax_reprocess/model_sel_analyt/TSMFK01') > Opening the file > '/net/tomat/home/tlinnet/kte/acbp/acbp_cpmg_disp_04MGuHCl_40C_041223_RELAX.fid/relax_reprocess/model_sel_analyt/TSMFK01/results.bz2' > for reading. > > relax> relax_disp.parameter_copy(pipe_from='pre', pipe_to='TSMFK01') > Copying parameters for the spin block [':3@N', ':4@N', ':5@N', ':6@N', > ':7@N', ':9@N', ':10@N', ':11@N', ':12@N', ':13@N', ':14@N', ':15@N', > ':16@N', ':17@N', ':18@N', ':20@N', ':21@N', ':22@N', ':23@N', > ':24@N', ':25@N', ':26@N', ':27@N', ':28@N', ':29@N', ':30@N', > ':31@N', ':32@N', ':33@N', ':34@N', ':35@N', ':36@N', ':37@N', > ':38@N', ':39@N', ':40@N', ':41@N', ':43@N', ':45@N', ':46@N', > ':47@N', ':48@N', ':49@N', ':50@N', ':52@N', ':53@N', ':54@N', > ':56@N', ':57@N', ':58@N', ':59@N', ':60@N', ':61@N', ':62@N', > ':63@N', ':64@N', ':65@N', ':66@N', ':67@N', ':68@N', ':69@N', > ':70@N', ':71@N', ':72@N', ':73@N', ':74@N', ':75@N', ':77@N', > ':78@N', ':80@N', ':81@N', ':82@N', ':83@N', ':84@N', ':85@N', > ':86@N'] > -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- > > Averaged k_AB value: 83471.182642624335131 > > relax> pipe.switch(pipe_name='TSMFK01') > relax> pipe.delete(pipe_name='pre') > relax> minimise(min_algor='simplex', line_search=None, > hessian_mod=None, hessian_type=None, func_tol=1e-25, grad_tol=None, > max_iter=10000000, constraints=True, scaling=True, verbosity=1) > > > > > Best > Troels > > > > > > > > > > > > > > > > > Troels Emtekær Linnet > > _______________________________________________ > relax (http://www.nmr-relax.com) > > This is the relax-devel mailing list > [email protected] > > To unsubscribe from this list, get a password > reminder, or change your subscription options, > visit the list information page at > https://mail.gna.org/listinfo/relax-devel _______________________________________________ relax (http://www.nmr-relax.com) This is the relax-devel mailing list [email protected] To unsubscribe from this list, get a password reminder, or change your subscription options, visit the list information page at https://mail.gna.org/listinfo/relax-devel
