Hi Edward, I am running a test, but will post more information as soon as it finishes.
RE: > Between these 2 rounds, are you sure that all models for all residues > are identical? From your data that you posted at > https://mail.gna.org/public/relax-users/2007-06/msg00017.html > (Message-id: <[EMAIL PROTECTED]>), I > would guess that this is not the case and one or two residues actually > do change in their model selections. Yes, I am sure the models for all residues are identical. This was verified using the unix 'diff' program: bunzip2 -c sphere/round_160/aic/results.bz2 | awk '{print $1,$6}' > previous bunzip2 -c sphere/round_161/aic/results.bz2 | awk '{print $1,$6}' > current diff previous current There were no differences between the previous and current files. Also, I am not using the same data as mentioned in the links you provided. This is data from a different protein. In addition, the identical model-free models test converged in the calculation reported in the previous post, whereas full_analysis.py suggest it has not converged in my current post. I think my current problems might be a separate issue, which I'm looking into now. Thanks, Doug On Sep 17, 2007, at 11:48 AM, Edward d'Auvergne wrote: > Hi, > > The problem is likely to be due to a circular looping around very > similar solutions close to the universal solution, as I have defined > in: > > d'Auvergne EJ, Gooley PR. Set theory formulation of the model-free > problem and the diffusion seeded model-free paradigm. Mol Biosyst. > 2007 Jul;3(7):483-94. > > If you can't get the paper, have a look at Chapter 5 of my PhD > thesis at > http://eprints.infodiv.unimelb.edu.au/archive/00002799/. The problem > is the interlinked mathematical optimisation and statistical model > selection where we are trying to minimise different quantities. For > mathematical optimisation this is the chi-squared value. For model > selection this is the quantity known as the descrepancy. These can > not be optimised together as mathematical optimisation works in a > single fixed-dimension space or universe whereas model selection > operates across multiple spaces with different dimensions. See the > paper for a more comprehensive description of the issue. > > You should be able to see this if you look at the end of iterations. > If you have 160 iterations, look after iteration 20 (or maybe even 30 > or further). Until then, you will not have reached the circular loop. > After that point you will be able to exactly quatify this circular > loop. You'll be able to determine its periodicity, which residues are > involved (probably only 1), and whether the diffusion tensor changes > as model selection changes. > > I mentioned all of this already in my post at > https://mail.gna.org/public/relax-users/2007-07/msg00001.html > (Message-id: > <[EMAIL PROTECTED]>) > in response to your original post > (https://mail.gna.org/public/relax-users/2007-06/msg00004.html, > Message-id: <[EMAIL PROTECTED]>). > > I have a few more points about the tests you have done but to work out > what is happening with the printouts, it would be very useful to have > your modified 'full_analysis.py' script attached. > > > > On 9/17/07, Douglas Kojetin <[EMAIL PROTECTED]> wrote: >> Hi, >> >> I'm unsure if this is a bug in full_analysis.py, in the internal >> relax code, or user error. The optimization of the 'sphere' model >> will not converge, now after 160+ rounds. The chi-squared test has >> converged (long, long ago): > > See above. > > >> "" from output >> Chi-squared test: >> chi2 (k-1): 100.77647517006251 >> chi2 (k): 100.77647517006251 >> The chi-squared value has converged. >> "" >> >> However, the identical model-free models test does has not converged: >> >> "" from output >> Identical model-free models test: >> The model-free models have not converged. >> >> Identical parameter test: >> The model-free models haven't converged hence the >> parameters haven't converged. >> "" >> >> Something that confuses me is that the output files in the round_??/ >> aic directory suggest that, for example, the round_160 and round_161 >> AIC model selections are equivalent. Here are the models for the >> first few residues: > > Between these 2 rounds, are you sure that all models for all residues > are identical? From your data that you posted at > https://mail.gna.org/public/relax-users/2007-06/msg00017.html > (Message-id: <[EMAIL PROTECTED]>), I > would guess that this is not the case and one or two residues actually > do change in their model selections. > > >> "" >> 1 None None >> 2 None None >> 3 None None >> 4 m2 m2 >> 5 m2 m2 >> 6 m2 m2 >> 7 m2 m2 >> 8 m2 m2 >> 9 m4 m4 >> 10 m1 m1 >> 11 None None >> 12 m2 m2 >> 13 m2 m2 >> 14 m1 m1 >> 15 m2 m2 >> 16 m3 m3 >> 17 m3 m3 >> 18 None None >> "" >> >> However, I modified the full_analysis.py protocol to print the >> differences in the model selection, within the 'Identical model-free >> model test' section of the 'convergence' definition. Here is the >> beginning of the output (which only contains differences between the >> previous and current rounds): >> >> "" >> residue 1: prev=None curr=m2 >> residue 2: prev=None curr=m2 >> residue 3: prev=None curr=m2 >> residue 6: prev=m2 curr=m4 >> residue 7: prev=m2 curr=m1 >> residue 9: prev=m4 curr=m2 >> residue 11: prev=None curr=m2 >> residue 12: prev=m2 curr=m3 >> residue 13: prev=m2 curr=m3 >> residue 15: prev=m2 curr=m1 >> residue 16: prev=m3 curr=m2 >> residue 17: prev=m3 curr=m1 >> residue 18: prev=None curr=m3 >> "" > > This output is quite strange. I would need to see the > full_analysis.py script to do more with this. > > >> There should be no data for residues 1-3, 11 and 18 (None), however >> the 'Identical model-free model test' seems as if it ignores residues >> for which 'None' was selected in the curr_model call in the following >> code: >> >> "" >> # Create a string representation of the model-free models of >> the previous run. >> prev_models = '' >> for i in xrange(len(self.relax.data.res['previous'])): >> if hasattr(self.relax.data.res['previous'][i], 'model'): >> #prev_models = prev_models + self.relax.data.res >> ['previous'][i].model >> prev_models = prev_models + ' ' + >> self.relax.data.res >> ['previous'][i].model >> >> # Create a string representation of the model-free models of >> the current run. >> curr_models = '' >> for i in xrange(len(self.relax.data.res[run])): >> if hasattr(self.relax.data.res[run][i], 'model'): >> #curr_models = curr_models + self.relax.data.res >> [run] >> [i].model >> curr_models = curr_models + ' ' + >> self.relax.data.res >> [run][i].model >> "" > > As residues 1-3, 11 and 18 are deselected, then they will not have the > attribute 'model' and hence will not be placed in the prev_models or > curr_models string (which are then compared). > > >> For what it's worth, I have residues 1,2,3,11 and 18 in the file >> 'unresolved' which is read by the full_analysis.py protocol. I >> created a separate sequence file (variable = SEQUENCE) that contains >> all residues (those with data and those without), instead of using a >> data file (noe data, in the default full_analysis.py file). However, >> these residues are not specified in the data (r1, r2 and noe) files, >> as I did not have data for them. Should I add them but place 'None' >> in the data and error columns? Could that be causing the problems? >> Or should I create a bug report for this? > > I'm not sure what you mean by the file '(variable = SEQUENCE)' > statement. I would need to see the full_analysis.py script to > understand this. I would assume a file called the value in the > variable 'SEQUENCE'. In which case, this should not be a problem. As > the data is missing from the files containing the relaxation data, > these residues will not be used in model-free analysis. They will be > automatically deselected. There is not need to add empty data for > these spin systems into the relaxation data files. As I said before > at the top of this message and at > https://mail.gna.org/public/relax-users/2007-07/msg00001.html > (Message-id: > <[EMAIL PROTECTED]>), > the problem is almost guaranteed to be a circular loop of equivalent > solutions circling around the universal solution - the solution > defined within the universal set (the union of all global models > (diffusion tensor + all model-free models of all residues)). If you > have hit this circular problem, then I suggest you stop running relax. > What I would then do is identify the spin system (or systems) causing > the loop, and what the differences are between all members of the > loop. This you can do by plotting the data and maybe using the > program diff on uncompressed versions of the results files. It's > likely that the differences are small and inconsequential. I hope > this helps. > > Regards, > > Edward _______________________________________________ relax (http://nmr-relax.com) This is the relax-users 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-users
