Hi,

Yes, this is deliberate.  The 3-site models are already almost
impossible to optimise as they have so many minima, and this is an
active research area in the dispersion field.  Introducing R20A !=
R20B != R20C increases the number of minima exponentially, making the
problem totally impossible to solve.  So that is why we have R20A =
R20B = R20C in the model.  It might be possible to create 'full'
versions of these models where these rates are different, but I think
the field needs to develop further before this is of any use.

But the infrastructure in lib.dispersion does support R20A != R20B !=
R20C.  The reason for this is that the lib.dispersion modules can be
directly used to investigate the optimisation space problems.  I would
like to have this as a powerful tool for investigating this
multi-site, multi-rate problem in the future.

Regards,

Edward



On 24 June 2014 11:14, Troels Emtekær Linnet <[email protected]> wrote:
> Hi Ed.
>
> As far as I can see, R20B, and R20C is not used in ns_mmq_2site and 3site?
>
>     def func_ns_mmq_2site(self, params):
>         """Target function for the combined SQ, ZQ, DQ and MQ CPMG numeric
> solution.
>
>         @param params:  The vector of parameter values.
>         @type params:   numpy rank-1 float array
>         @return:        The chi-squared value.
>         @rtype:         float
>         """
>
>         # Scaling.
>         if self.scaling_flag:
>             params = dot(params, self.scaling_matrix)
>
>         # Unpack the parameter values.
>         R20 = params[:self.end_index[0]]
>         dw = params[self.end_index[0]:self.end_index[1]]
>         dwH = params[self.end_index[1]:self.end_index[2]]
>         pA = params[self.end_index[2]]
>         kex = params[self.end_index[2]+1]
>
> But they are parsed to the lib function.
>
>             # Back calculate the R2eff values for each experiment type.
>             self.r2eff_ns_mmq[ei](M0=self.M0, R20A=r20, R20B=r20, pA=pA,
> dw=aliased_dw, dwH=aliased_dwH, kex=kex,
> inv_tcpmg=self.inv_relax_times[ei], tcp=self.tau_cpmg[ei],
> back_calc=self.back_calc[ei], num_points=self.num_disp_points[ei],
> power=self.power[ei])
>
> Is this by purpose?
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