Hi Edward. I finally came around to make some plots and tables of the "failed" run and even attached them to a bug report on GNA.
On 12.02.2013, at 15:09, Edward d'Auvergne <[email protected]> wrote: >>>> Rex of around 10^-18 (=nearly zero) >>> sigma_ex = Rex / omega**2 >> >> I extract Rex with the following command, I guess this is then the already >> field-corrected value? >>> value.write( param = 'rex', file = 'example/rex.txt') > > This is clearly a bug! For example on an 800, you should multiply > 1e-18 with the value of ~2.6e17. Could you file a bug report for > this? A value of 1e-18 should give a significant, yet low, Rex value > of 0.15-0.3 rad.s^-1. I'm not sure what kind of data / dump would be helpful as an attachment. I'm also not sure if this is really a bug? How could I test for that? >> chi^2 and AIC values do not converge but differ by only a factor of 10^10 >> [in fact, the fluctuations are small, and in the range of approx 1e-10] from >> each other in the last ~20 rounds. > > How many rounds is it up to? If it runs infinitely, then maybe you > have run into a chaotic system. Now that would be fascinating! > Theoretically anyway, biologically it would be irrelevant. Hooray chaos! I finally killed it after 190 rounds. That poor workstation would have worked forever I guess. > I'm guessing you mean 1e-10. Can you see which models are changing? Models are not changing at all. Link to a plot of assigned models over the iterations (every plot corresponds to a single residue, y axis corresponds to models 0-9): https://gna.org/support/download.php?file_id=17287 > Can you find any chi2 or AIC values which match between the rounds? > If you make a table of total parameter number, chi2, and AIC, can you > see any patterns? Have a look for yourself: I can't see any patterns. Looks like random to me. Link to tab-seperated table of parameters: https://gna.org/support/download.php?file_id=17284 Link to plot of parameters over iterations: https://gna.org/support/download.php?file_id=17286 Link to plot of parameters over iterations, zoomed in: https://gna.org/support/download.php?file_id=17287 > However I don't > think I've seen a problem which runs forever - that would just be > theoretically weird. *sigh* >> off-resonance "heating pulses" that make my R1 experiment just as warm as >> the R2 experiment [...] > > You shouldn't need to warm up your experiment to the level of the R2 > in this way. [...] Actually you could end up with a temperature gradient > over the R1 evolution time - this would not be good. You've been right, the new data I recorded with this technique do not look right at all. I > The best way to do this is to > run the R1 experiment on a MeOH/ethylene glycol sample. Then > calibrate the temperature as you would normally calibrate a > spectrometer, just using shortened R1/R2/NOE pulse sequences. As mentioned earlier, I use d4 methanol which gives sharp, not too strong signals and really nicely fit, stable temperature calibration curves. After starting the R2 I don't see any differences of the distance between OH/CH3 signals. (The peaks are a bit broader than in the simple 1D) This is true for the individual delays during measurement (individual planes in the pseudo-3D), as well as for before/after R2. The distance is the same everywhere. I looked into it similarly to what you suggested: more or less killed the phase cycle and put half of the pulses off-resonance. >>> For the spins where m0 are selected, do their errors look larger than >>> the other spins? >> >> I wouldn't say so: >> https://dl.dropbox.com/u/4019316/boxplot.error.pdf > >>> Or if you plot the I0 values from the relaxation >>> exponential curve-fitting, are these residues much lower than the >>> rest? >> >> There definitely seems to be a tendency: >> https://dl.dropbox.com/u/4019316/boxplot.pdf Similar /enhanced plots can be found here now: https://gna.org/support/download.php?file_id=17288 https://gna.org/support/download.php?file_id=17289 > Those are quite interesting plots. Though I'm not sure why m0 is > selected so often. I've never seen such a phenomenon. Maybe you should come around for a visit, talk to Peter Schmieder, Hartmut Oschkinat and Phil Selenko and then you can crush my dreams of doing anything useful with our system. That would be fun. >>> I can only recommend switching to Sparky for this type of analysis. > You can use Topspin to split up the file and create a set of 2D fids. > These can then be used for processing in nmrPipe, if you like, and > converted to Sparky format. I process with Topspin, (zero-fill for 8k, baseline correction, forward prediction, set the right nc_proc, etc etc), convert to ucsf with bruk2ucsf, corrected for the sfo1 with ucsfdata and imported the spectra one-by-one into Sparky. Then copied my reference peak list onto all single spectra and saved the resulting peak heights. https://gna.org/support/download.php?file_id=17290 https://gna.org/support/download.php?file_id=17291 https://gna.org/support/download.php?file_id=17292 https://gna.org/support/download.php?file_id=17293 (some of the plots are truncated for outliers) I don't see an indication that there are significant differences between picking with sparky or picking with ccpn ... > Well, I was a pure biochemist before I looked at performing a > model-free analysis of a protein! So it's not impossible. Kudos for that! Regards Martin _______________________________________________ relax (http://www.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
