Hi Troels,

This still has the same problems with the R2eff model as mentioned at
http://thread.gmane.org/gmane.science.nmr.relax.scm/24963/focus=7490.

Regards,

Edward



On 17 January 2015 at 17:25,  <tlin...@nmr-relax.com> wrote:
> Author: tlinnet
> Date: Sat Jan 17 17:25:20 2015
> New Revision: 27219
>
> URL: http://svn.gna.org/viewcvs/relax?rev=27219&view=rev
> Log:
> Added API function in relaxation dispersion to return error structure from 
> the reduced chi2 distribution.
>
> Task #7882 (https://gna.org/task/?7882): Implement Monte-Carlo simulation, 
> where errors are generated with width of standard deviation or residuals.): 
> Implement Monte-Carlo simulation, where errors are generated with width of 
> standard deviation or residuals.
>
> Modified:
>     trunk/specific_analyses/relax_disp/api.py
>
> Modified: trunk/specific_analyses/relax_disp/api.py
> URL: 
> http://svn.gna.org/viewcvs/relax/trunk/specific_analyses/relax_disp/api.py?rev=27219&r1=27218&r2=27219&view=diff
> ==============================================================================
> --- trunk/specific_analyses/relax_disp/api.py   (original)
> +++ trunk/specific_analyses/relax_disp/api.py   Sat Jan 17 17:25:20 2015
> @@ -27,7 +27,7 @@
>  # Python module imports.
>  import bmrblib
>  from copy import deepcopy
> -from numpy import int32, zeros
> +from numpy import int32, sqrt, zeros
>  from re import match, search
>  import string
>  import sys
> @@ -1035,6 +1035,44 @@
>
>          # Return the error list.
>          return errors
> +
> +
> +    def return_error_red_chi2(self, data_id=None):
> +        """Return the standard deviation data structure, where standard 
> deviation is from the overall gauss distribution described by the STD_fit of 
> the goodness of fit, where STD_fit = sqrt(chi2/(N-p))
> +
> +        @param data_id: The tuple of the spin container and the exponential 
> curve identifying key, as yielded by the base_data_loop() generator method.
> +        @type data_id:  SpinContainer instance and float
> +        @return:        The standard deviation data structure.
> +        @rtype:         list of float
> +        """
> +
> +        # Get the errors structure as above.
> +        errors = self.return_error(data_id=data_id)
> +
> +        # Unpack the data.
> +        spin, spin_id = data_id
> +
> +        # Loop over the spin groupings for the model.
> +        for spin_ids in self.model_loop():
> +            # If the spin of interest is in the returned spin cluster.
> +            if spin_id in spin_ids:
> +                # Get the statistics
> +                k, n, chi2 = self.model_statistics(model_info=spin_ids)
> +
> +                # Calculate degrees of freedom.
> +                dof = n - k
> +
> +                # Calculate reduced chi2, or named as the variance of the 
> squared residuals.
> +                red_chi2 = chi2 / float(dof)
> +
> +                # Calculated the standard deviation.
> +                std_red_chi2 = sqrt(red_chi2)
> +
> +                # Replace values with the stored value.
> +                for id in errors:
> +                    errors[id] = std_red_chi2
> +
> +                return errors
>
>
>      def return_value(self, spin, param, sim=None, bc=False):
>
>
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