On Wed, Oct 8, 2008 at 6:07 PM, Tyler Reddy <TREDDY@xxxxxx> wrote:
To get past this requirement I added or subtracted the last digit for
each peak
height for the data set to make a pseudo-replicate data set (2
identical files
will still get a 0 value division problem). The program goes through
the Monte
Carlo simulations, but doesn't quite finish, with the follow output:
This will give you the R1 and R2 values, but there errors will be
incorrect. These errors must be dead accurate for you to use the R1
and R2 in any type of analysis, as the curvature of the optimisation
space and statistical measures are highly dependent on these values.
If you need instant results with non-replicated spectra, then I would
recommend you not to use relax. There may be other software which
will do this analysis for you, but remember that the errors are very
important and must be propagated by the only accurate technique -
Monte Carlo simulations. The covariance matrix or Jackknife
simulation techniques are used at times, but just read the Monte Carlo
section of the Numerical Recepies book to see why I recommend to only
use MC sims.
relax> monte_carlo.error_analysis(prune=0.0)
relax> value.write(run=None, param='rx', file='rx.out', dir=None,
force=True)
RelaxError: The run argument None must be a string.
This one I fixed while implementing the NOE analysis in the 1.3 line
for you. You will have to wait until I release relax 1.3.2 to have
this fix, unless you get subversion running and download the fixed
code ;)
Regards,
Edward
Re: Relax_fit.py problem