On Tue, Feb 17, 2009 at 11:08 PM, Sébastien Morin
<sebastien.morin.1@xxxxxxxxx> wrote:
Hi,
For CPMG, R2eff values will be calculated from:
R2eff = ( 1/delayT ) * ln ( Icpmg / Iref )
There is an error on Icpmg and Iref values ; this can be obtained from
duplicate measurements.
This could also be done by measuring the RMSD of the baseplane noise.
Do you know how errors are then propagated to R2eff? I'll talk to
Michael about this too. There could be a direct formula based on
Gaussian distributions and Icpmg, Iref, sigma_cpmg, and sigma_ref. Or
it could be Monte Carlo simulations (which would be the same as
bootstraping as this is an exact calculation and not non-linear curve
fitting via optimisation).
For other relaxation dispersion experiments (e.g. R1rho), R2eff values
could be extracted from curve fitting of exponential decays. Errors
could also be obtained from duplicate measurements.
For this, see help(spectrum.error_analysis). These resultant peak
intensity errors are then propagated to the R2eff via Monte Carlo
simulations.
For R2eff direct reading, what relax should do is simply store the
values with their respective CPMG frequency (for CPMG data) and
spectrometer frequency. Then, relax should pass these informations to
the code so curve fitting can proceed.
What's proposed at:
https://mail.gna.org/public/relax-devel/2009-02/msg00009.html
(Message-id:
<7f080ed10902170945q744a8328x8bc6233131e5d6d3@xxxxxxxxxxxxxx>)
seems fine as long as there are no differences between analyses
proceeding from intensities (both Icpmg and Iref) or directly from
R2eff, i.e. as long as data can be shared easily within relax.
I am not sure, however, about how this should be handled... but the way
it is done for intensities seems quite versatile and could allow the
flexibility needed.
I think I covered this here:
https://mail.gna.org/public/relax-devel/2009-03/msg00000.html
(Message-id: <7f080ed10903050214x2fd9cfdas6a3a048f724624d5@xxxxxxxxxxxxxx>).
Regards,
Edward
Re: r8472 - in /branches/relax_disp: prompt/relax_disp.py specific_fns/relax_disp.py