## Re: r17469 - /trunk/docs/latex/consistency_tests.tex

### Content

Posted by Edward d'Auvergne on September 06, 2012 - 11:26:
Hi Seb,

I have just performed a little clean up of the "Consistency testing"
chapter of the relax manual.  This is now in a pretty good shape to
ship out to users.  I was wondering if you'd like to add some small
text as the end, a last paragraph maybe, explaining why the script
generates the F_eta and F_R2 values.  From reading the references,
this is obvious.  But if a user reads this chapter as it is before
jumping to your papers, they will be confused.

Cheers,

Edward

On 6 September 2012 11:19,  <edward@xxxxxxxxxxxxx> wrote:

Author: bugman
Date: Thu Sep  6 11:19:43 2012
New Revision: 17469

URL: http://svn.gna.org/viewcvs/relax?rev=17469&view=rev
Log:
Editing and a number of fixes/cleanups for the consistency testing chapter
of the user manual.

Modified:
trunk/docs/latex/consistency_tests.tex

Modified: trunk/docs/latex/consistency_tests.tex
URL:
http://svn.gna.org/viewcvs/relax/trunk/docs/latex/consistency_tests.tex?rev=17469&r1=17468&r2=17469&view=diff
==============================================================================
--- trunk/docs/latex/consistency_tests.tex (original)
+++ trunk/docs/latex/consistency_tests.tex Thu Sep  6 11:19:43 2012
@@ -24,7 +24,7 @@
\item[$F_{R_2}$]  A consistency function proposed by \citet{Fushman98}.
\end{description}

-Different methods exist to compare tests values calculated from one field
to another.  These include correlation plots and histograms, and
calculation of correlation, skewness and kurtosis coefficients. The details
of how to interpret such analyses are avaliable at the end of this section
in Section \ref{sec: Visualisation and data output}.
+Different methods exist to compare tests values calculated from one field
to another.  These include correlation plots and histograms, and
calculation of correlation, skewness and kurtosis coefficients. The details
of how to interpret such analyses are avaliable at the end of this chapter
in Section~\ref{sec: Visualisation and data output}.

For more details on the implementation within relax, see:

@@ -43,19 +43,21 @@
\begin{itemize}
\item \bibentry{Morin11}
\end{itemize}
+

% Script UI.
%%%%%%%%%%%%
+
\section{Prompt/script UI mode}

-The consistency testing analysis is only available via the prompt/script
UI modes -- no GUI auto-analysis has yet been built.
+The consistency testing analysis is only available via the prompt/script
UI modes -- no GUI auto-analysis has yet been built by a relax power-user.

% The sample script.
%~~~~~~~~~~~~~~~~~~~

-\subsection{The sample script}
+\subsection{The sample script} \label{sect: consistency tests - sample
script}

The following script can be found in the \directory{sample\_scripts}
directory.

@@ -72,7 +74,7 @@
\\
The description of the consistency testing approach: \\
\\
-    \citet{MorinGagne09a} \\
+    Morin \& Gagne (2009a) Simple tests for the validation of multiple
field spin relaxation data. J. Biomol. NMR, 45: 361-372.
http://dx.doi.org/10.1007/s10858-009-9381-4 \\
\\
The origins of the equations used in the approach: \\
\\
@@ -186,7 +188,7 @@

-The loading of relaxation data is straight forward.  This is performed
prior to the creation of the proton spins so that the data is loaded only
into the $^{15}$N spin containers and not both spins for each residue.
Only data for a single field strength can be loaded:
+The loading of relaxation data is straight forward.  This is performed
prior to the creation of the proton spins so that the data is loaded only
into the $^{15}$N spin containers and not both spins for each spin system.
Note that if the relaxation data files contain spin information, then this
order is not important.  For this analysis, only data for a single field
strength can be loaded:

\begin{exampleenv}
relax\_data.read(ri\_id=R1\_600',  ri\_type=R1',  frq=600.0*1e6,
file=r1.600.out', res\_num\_col=1, data\_col=3, error\_col=4) \\
@@ -220,7 +222,7 @@
value.set(val=-172 * 1e-6, param=csa')
\end{exampleenv}

-For the angle between the 15N-1H vector and the principal axis of the 15N
chemical shift tensor, the user function call is:
+For the angle in degrees between the $^{15}$N-$^1$H vector and the
principal axis of the $^{15}$N chemical shift tensor, the user function
call is:

\begin{exampleenv}
value.set(val=15.7, param=orientation')
@@ -269,17 +271,14 @@
\item See if the correlation plot is centered around a perfect correlation
or skewed away (approach A), or if the values are centered around 1 in the
histogram (approach B).  If yes, data from multiple magnetic fields is
consistent from one magnetic field to another.  If no, data is
inconsistent.  In the case where inconsistency arises, if data from more
than two magnetic fields is avaliable, more than one pair of data can be
checked and the inconsistent magnetic field data can be identified.
\end{itemize}

-An example of such an analysis is shown in Figure \ref{fig: consistency
analysis} below
-
\begin{figure*}[h]
\label{fig: consistency analysis}
\centerline{\includegraphics[width=0.9\textwidth, bb=5 2 1244
669]{graphics/analyses/consistency_testing/consistency__J0_PSE-4.eps.gz}}
-\caption[Example of consistency testing visual analysis]{Example of
consistency testing visual analysis. Relaxation data from three different
magnetic fields are compared. For each pair of magnetic field, a
correlation plot of the calculated $J(0)$ values (approach A, top) as well
as an histogram of the ration of calculated $J(0)$ values (approach B,
bottom) are shown. Data from \citep{MorinGagne09b} is used for the purpose
of this example.}
+\caption[Example of consistency testing visual analysis]{Example of
consistency testing visual analysis.  Relaxation data from three different
magnetic fields are compared.  For each pair of magnetic field, a
correlation plot of the calculated $J(0)$ values (approach A, top) as well
as an histogram of the ration of calculated $J(0)$ values (approach B,
bottom) are shown.  These graphs must be manually created from the output
of the sample script shown in section~\ref{sect: consistency tests - sample
script}.  Data from \citep{MorinGagne09b} is used for the purpose of this
example.}
\end{figure*}

-As shown in Figure \ref{fig: consistency analysis}, the example data
displays both consistent and inconsistent data. In fact, data recorded at
500 MHz and 600 MHz are consistent together, whereas data recorded at 800
MHz is not consistent with data recorded at 500 MHz nor 600 MHz.  Since
more than two magnetic fields were used, this allowed the identification of
the data from 800 MHz  as the inconsistent data, as data from 500 MHz is
consistent with data from 600 MHz, and vice-versa.  In this particular
example, this allowed the authors to take special care with data at 800 MHz.
-
-This inconsistency of 800 MHz data is seen on the correlation plot (toop)
by a deviation from the dotted line (which represents the theoretical
situation when equal $J(0)$ values are extracted from both magnetic fields.
It is also observable in the histogram (bottom) where the ration of the
data from two magnetic fields is not centered around 0. In fact, there
seems to be a systematic shift of the calculated $J(0)$ values at 800 MHz
when compared to the two other magnetic fields. This is caused by a similar
shift in the experimental $R_2$ (transversal relaxation rate) data.
-
-For the 500 MHz and 600 MHz data pair, the data are centered around the
dotted line in the correlation plot (approach A, top left) as well as
centered around a value of 1 in the histogram comparing the ratios of
values from both magnetic fields (approach B, bottom left). Of course,
there are some outsider values even in the case of consistent data. There
are caused by specific dynamic characteristics of these spins and are
different from systematic inconsistencies such as depicted in the example
above with the data recorded at 800 MHz.
-
+An example of such an analysis is shown in Figure~\ref{fig: consistency
analysis}.  This example displays both consistent and inconsistent data.
As the figure shows, the data recorded at 500 MHz and 600 MHz are
consistent with each other whereas the data recorded at 800 MHz is
consistent with the neither the 500 MHz nor 600 MHz data.  Since more than
two magnetic fields were used, this allowed the identification of the 800
MHz data as being inconsistent allowing the authors to take special care
with this data set.
+
+The 800 MHz data inconsistency is seen in the correlation plots (top) by a
deviation from the dotted line (which represents the theoretical situation
when equal $J(0)$ values are extracted from both magnetic fields.  It is
also observable in the histograms (bottom) where the ratio of the data from
two magnetic fields is not centered at 1.0.  In fact, there seems to be a
systematic shift of the calculated $J(0)$ values at 800 MHz when compared
to the two other magnetic fields.  This is caused by a similar shift in the
experimental $\Rtwo$ (transversal relaxation rate) data.
+
+For the 500 MHz and 600 MHz data pair, the data are centered around the
dotted line in the correlation plot (approach A, top left) as well as
centered around a value of 1.0 in the histogram comparing the ratios of
values from both magnetic fields (approach B, bottom left).  Of course,
there are some outlier values even in the case of consistent data.  There
are caused by specific dynamic characteristics of these spins and are
different from systematic inconsistencies such as depicted in the example
above with the data recorded at 800 MHz.

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