Hi Ed,

I am not so familiar with scaling in minimization...

How can I determine if a given parameter would benefit from scaling ?
Is only speed affected when scaling is used ?

Thanks !


Séb



[email protected] wrote:
> Author: semor
> Date: Tue Jan 13 04:24:37 2009
> New Revision: 8429
>
> URL: http://svn.gna.org/viewcvs/relax?rev=8429&view=rev
> Log:
> Started to implement the scaling matrix for scaling the 'R2eff' values.
>
> This might change in the future as other possible curve fitting parameters 
> ('R2', 'Rex', 'kex',
> 'R2A', 'kA', 'dw') might need some scaling.
>
>
> Modified:
>     branches/relax_disp/specific_fns/relax_disp.py
>
> Modified: branches/relax_disp/specific_fns/relax_disp.py
> URL: 
> http://svn.gna.org/viewcvs/relax/branches/relax_disp/specific_fns/relax_disp.py?rev=8429&r1=8428&r2=8429&view=diff
> ==============================================================================
> --- branches/relax_disp/specific_fns/relax_disp.py (original)
> +++ branches/relax_disp/specific_fns/relax_disp.py Tue Jan 13 04:24:37 2009
> @@ -143,17 +143,17 @@
>  
>          # Loop over the parameters.
>          for i in xrange(len(spin.params)):
> -            # Relaxation rate.
> -            if spin.params[i] == 'Rx':
> -                pass
> -
> -            # Intensity scaling.
>             elif search('^i', spin.params[i]):
> +            # Effective transversal relaxation rate scaling.
> +            if spin.params[i] == 'R2eff':
>                  # Find the position of the first CPMG pulse train frequency 
> point.
>                  pos = cdp.cpmg_frqs.index(min(cdp.cpmg_frqs))
>  
>                  # Scaling.
> -                scaling_matrix[i, i] = 1.0 / average(spin.intensities[pos])
> +                scaling_matrix[i, i] = 1.0 / average(spin.r2effs[pos])
> +
> +            # No scaling for other parameters.
> +            else:
> +                pass
>  
>              # Increment i.
>              i = i + 1
>
>
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