Hi Edward.
'r2', 'pA', 'dw', 'kex'
I then read this as:
self.assertEqual(par_dic['r2'], 'r2')
self.assertEqual(par_dic['pA'], 'pA')
self.assertEqual(par_dic['dw_AB'], 'dw')
self.assertEqual(par_dic['kex_AB'], 'kex')
self.assertEqual(par_dic['pB'], None)
self.assertEqual(par_dic['dw_BC'], 'dw')
self.assertEqual(par_dic['kex_BC'], 'kex')
self.assertEqual(par_dic['kex_AC'], 'kex')
Best
Troels
2014-08-19 17:42 GMT+02:00 Edward d'Auvergne <[email protected]>:
> Hi,
>
> I saw that the code has evolved to do this. The original idea and
> implementation was to set states B and C to the same values of the
> 2-state model parameters and then let them drift apart. This was
> mentioned in the manual. This is not great, but the alternative of
> performing a grid search on 'dw_AB', 'kex_AB', 'pB', 'dw_BC',
> 'kex_BC', 'kex_AC' is worse - this grid search is just impossibly long
> if you choose a reasonable number of grid increments. Being a
> multi-minima problem also invalidates this. The grid search and local
> optimisation is only for single minimum problems. When multiple
> minima are present, then global algorithms are required (the main ones
> are simulated annealing and genetic algorithms, neither of which are
> present in minfx yet and hence relax). Therefore setting B and C to
> the same thing is not too unreasonable considering the alternative
> issues.
>
> The same thing was done for the '* full' models. The value of R20 was
> copied to R20A and R20B and then the two allowed to drift apart. This
> is also an incredibly difficult optimisation problem with possible
> multiple minima.
>
> There is no perfect solution for the R20A != R20B or 3-site models yet.
>
> Regards,
>
> Edward
>
>
>
> On 19 August 2014 17:21, Troels Emtekær Linnet <[email protected]> wrote:
>> Hi Edward.
>>
>>
>> Just to confirm.
>>
>> If the model is: MODEL_PARAMS_NS_R1RHO_3SITE
>> And the nested model is: MODEL_PARAMS_NS_R1RHO_2SITE
>>
>> The possible parameters for conversion are:
>> self.assertEqual(par_dic['r2'], 'r2')
>> self.assertEqual(par_dic['pA'], 'pA')
>> self.assertEqual(par_dic['dw_AB'], None)
>> self.assertEqual(par_dic['kex_AB'], None)
>> self.assertEqual(par_dic['pB'], None)
>> self.assertEqual(par_dic['dw_BC'], None)
>> self.assertEqual(par_dic['kex_BC'], None)
>> self.assertEqual(par_dic['kex_AC'], None)
>>
>> This means, that MODEL_PARAMS_NS_R1RHO_3SITE would start to Grid Search:
>> 'dw_AB', 'kex_AB', 'pB', 'dw_BC', 'kex_BC', 'kex_AC'
>>
>> Do we agree on this?
>>
>> Best
>> Troels
>>
>>
>> ---------- Forwarded message ----------
>> From: <[email protected]>
>> Date: 2014-08-19 16:07 GMT+02:00
>> Subject: r25077 - /trunk/docs/latex/dispersion.tex
>> To: [email protected]
>>
>>
>> Author: bugman
>> Date: Tue Aug 19 16:07:37 2014
>> New Revision: 25077
>>
>> URL: http://svn.gna.org/viewcvs/relax?rev=25077&view=rev
>> Log:
>> Added a table for dispersion model nesting in the auto-analysis to the
>> manual.
>>
>> This adds the ideas discussed in the thread
>> http://thread.gmane.org/gmane.science.nmr.relax.devel/6684.
>>
>>
>> Modified:
>> trunk/docs/latex/dispersion.tex
>>
>> Modified: trunk/docs/latex/dispersion.tex
>> URL:
>> http://svn.gna.org/viewcvs/relax/trunk/docs/latex/dispersion.tex?rev=25077&r1=25076&r2=25077&view=diff
>> ==============================================================================
>> --- trunk/docs/latex/dispersion.tex (original)
>> +++ trunk/docs/latex/dispersion.tex Tue Aug 19 16:07:37 2014
>> @@ -1689,8 +1689,9 @@
>> For the cluster specific parameters, i.e.\ the populations of
>> the states and the exchange parameters, an average value will be used
>> as the starting point.
>> For all other parameters, the $\Rtwozero$ values for each spin
>> and magnetic field, as well as the parameters related to the chemical
>> shift difference $\dw$, the optimised values of the previous run will
>> be directly copied.
>> \item[Model nesting:] If two models are nested, then the
>> parameters of the simpler will be used as the starting point for
>> optimisation of the more complex.
>> - The currently supported nested model pairs are `LM63' and `LM63
>> 3-site', `CR72' and `CR72 full', `CR72' and `MMQ CR72', `NS CPMG
>> 2-site 3D' and `NS CPMG 2-site 3D full', and `NS CPMG 2-site star' and
>> `NS CPMG 2-site star full'.
>> - In these cases, the $\RtwozeroA$ and $\RtwozeroB$ parameter
>> values are set to the simpler model $\Rtwozero$ value and the grid
>> search is bypassed.
>> + The currently supported nested model sets are presented in
>> Table~\ref{table: dispersion model nesting} on page~\pageref{table:
>> dispersion model nesting}.
>> + The models are optimised in the order presented in that table.
>> + In some cases, the $\RtwozeroA$ and $\RtwozeroB$ parameter
>> values are set to the simpler model $\Rtwozero$ value and the grid
>> search is bypassed.
>> \item[Model equivalence:] When two models are equivalent, the
>> optimised parameters of one model can be used as the starting point of
>> the other rather than performing a grid search.
>> This is used in the auto-analysis for avoiding the grid search
>> in the numeric models.
>> The optimised `CR72' model is used for the `NS CPMG 2-site
>> expanded', `NS CPMG 2-site 3D', and `NS CPMG 2-site star' models.
>> @@ -1722,6 +1723,103 @@
>> If you are a power user, you are free to use all of the relax user
>> functions, the relax library, and the relax data store to implement
>> your own protocol.
>> If you wish, the protocol can be converted into a new auto-analysis
>> and distributed as part of relax.
>> The relax test suite will ensure the protocol remains functional for
>> the lifetime of relax.
>> +
>> +\begin{landscape}
>> +\begin{center}
>> +\begin{small}
>> +
>> +% The longtable environment.
>> +\begin{longtable}{ll}
>> +
>> +% Caption.
>> +\caption{Model nesting for the relaxation dispersion auto-analysis.}
>> +
>> +% Header.
>> +\\
>> +\toprule
>> +Model & Nested models\footnotemark[1] \\
>> +\midrule
>> +\endhead
>> +
>> +% Footer.
>> +\bottomrule
>> +\endfoot
>> +
>> +% Label.
>> +\label{table: dispersion model nesting}
>> +
>> +
>> +% Experiment independent models.
>> +\\[-5pt]
>> +Base models \\
>> +\cline{1-1}
>> +$\Rtwoeff/\Ronerhoprime$ & - \\
>> +No Rex & - \\
>> +
>> +% CPMG-type models.
>> +\\[-5pt]
>> +Single quantum (SQ) CPMG-type \\
>> +\cline{1-1}
>> +LM63 & - \\
>> +LM63 3-site & LM63 \\
>> +CR72 & NS CPMG 2-site 3D, NS CPMG 2-site
>> star, NS CPMG 2-site expanded, B14 \\
>> +CR72 full & NS CPMG 2-site 3D full, NS CPMG
>> 2-site star full, B14 full, NS CPMG 2-site 3D, \\
>> + & NS CPMG 2-site star, NS CPMG
>> 2-site expanded, B14, CR72 \\
>> +IT99 & - \\
>> +TSMFK01 & - \\
>> +B14 & NS CPMG 2-site 3D, NS CPMG 2-site
>> star, NS CPMG 2-site expanded, CR72 \\
>> +B14 full & NS CPMG 2-site 3D full, NS CPMG
>> 2-site star full, CR72 full, NS CPMG 2-site 3D, \\
>> + & NS CPMG 2-site star, NS CPMG
>> 2-site expanded, B14, CR72 \\
>> +NS CPMG 2-site expanded & NS CPMG 2-site 3D, NS CPMG 2-site
>> star, B14, CR72 \\
>> +NS CPMG 2-site 3D & NS CPMG 2-site star, NS CPMG
>> 2-site expanded, B14, CR72 \\
>> +NS CPMG 2-site 3D full & NS CPMG 2-site star full, B14
>> full, CR72 full, NS CPMG 2-site 3D, NS CPMG 2-site star, \\
>> + & NS CPMG 2-site expanded, B14, CR72 \\
>> +NS CPMG 2-site star & NS CPMG 2-site 3D, NS CPMG 2-site
>> expanded, B14, CR722 \\
>> +NS CPMG 2-site star full & NS CPMG 2-site 3D full, B14 full,
>> CR72 full, NS CPMG 2-site 3D, NS CPMG 2-site star, \\
>> + & NS CPMG 2-site expanded, B14, CR72 \\
>> +
>> +% SQ, ZQ, DQ and MQ CPMG-type models.
>> +\\[-5pt]
>> +MMQ (SQ, ZQ, DQ, \& MQ) CPMG-type \\
>> +\cline{1-1}
>> +MMQ CR72 & NS MMQ 2-site \\
>> +NS MMQ 2-site & MMQ CR72 \\
>> +NS MMQ 3-site linear & NS MMQ 2-site, MMQ CR72 \\
>> +NS MMQ 3-site & NS MMQ 3-site linear, NS MMQ
>> 2-site, MMQ CR72 \\
>> +
>> +% R1rho-type models.
>> +\clearpage
>> +\\[-5pt]
>> +$\Ronerho$-type \\
>> +\cline{1-1}
>> +M61 & - \\
>> +M61 skew & - \\
>> +DPL94 & - \\
>> +DPL94 $\Rone$ fit & DPL94 \\
>> +TP02 & MP05, TAP03 \\
>> +TP02 $\Rone$ fit & MP05 $\Rone$ fit, TAP03 $\Rone$ fit \\
>> +TAP03 & MP05, TP02 \\
>> +TAP03 $\Rone$ fit & MP05 $\Rone$ fit, TP02 $\Rone$ fit \\
>> +MP05 & TAP03, TP02 \\
>> +MP05 $\Rone$ fit & TAP03 $\Rone$ fit, TP02 $\Rone$ fit \\
>> +NS $\Ronerho$ 2-site & MP05, TAP03, TP02 \\
>> +NS $\Ronerho$ 2-site $\Rone$ fit & MP05 $\Rone$ fit, TAP03 $\Rone$
>> fit, TP02 $\Rone$ fit \\
>> +NS $\Ronerho$ 3-site linear & NS $\Ronerho$ 2-site, MP05, TAP03, TP02
>> \\
>> +NS $\Ronerho$ 3-site & NS $\Ronerho$ 3-site linear, NS
>> $\Ronerho$ 2-site, MP05, TAP03, TP02 \\
>> +
>> +\footnotetext[1]{The nested models are ordered by preference.
>> +The earliest model in the list which has been optimised in the
>> auto-analysis will be used as the nested model.
>> +For example for the 'B14 full' model, the 'CR72 full' model is the
>> first preference, followed by 'B14', then the final fall back is
>> 'CR72' is neither 'CR72 full' or 'B14' have been optimised.
>> +If none of the nested models have been optimised, the grid search
>> will be performed.
>> +In this example, 'CR72 full' is preferred as it has perfect parameter
>> nesting -- all parameters of 'B14 full' are found in 'CR72 full'.
>> +The B14 and CR72 are fallbacks, and for these R20A and R20B are
>> copied from R20 so they start optimisation as R20A == R20B.
>> +Hence 'CR72 full' whereby R20A != R20B is a much better starting
>> point as R20A and R20B have been optimised to different values.
>> +But because of the large model instability in the 'CR72 full' model,
>> you may wish to instead start with 'B14'.}
>> +
>> +\end{longtable}
>> +\end{small}
>> +\end{center}
>> +\end{landscape}
>>
>>
>> % Dispersion curve insignificance.
>>
>>
>> _______________________________________________
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