Commit 42486af5 authored by Douglas Serson's avatar Douglas Serson

Add test for meanmode module and update userguide

parent c764f9c3
......@@ -104,6 +104,7 @@ Specifically, FieldConvert has these additional functionalities
\item \inltt{interppoints}: Interpolates a set of points to another, requires fromfld and fromxml to be defined, a line or plane of points can be defined;
\item \inltt{isocontour}: Extract an isocontour of ``fieldid'' variable and at value ``fieldvalue''. Optionally ``fieldstr'' can be specified for a string defiition or ``smooth'' for smoothing;
\item \inltt{jacobianenergy}: Shows high frequency energy of Jacobian;
\item \inltt{meanmode}: Extract mean mode (plane zero) of 3DH1D expansions;
\item \inltt{printfldnorms}: Print L2 and LInf norms to stdout;
\item \inltt{scalargrad}: Computes scalar gradient field;
\item \inltt{scaleinputfld}: Rescale input field by a constant factor;
......@@ -444,6 +445,22 @@ to visualise it either in Tecplot or in Paraview the result.
%
%
\subsection{Extract mean mode of 3Dh1D expansion: \textit{meanmode} module}
To obtain a 2D expansion containing the mean mode (plane zero in Fourier space) of a
3DH1D field file, use the command:
\begin{lstlisting}[style=BashInputStyle]
FieldConvert -m meanmode file.xml file.fld file-mean.fld
\end{lstlisting}
The output file \inltt{file-mean.fld} can be processed in a similar
way as described in section \ref{s:utilities:fieldconvert:sub:convert}
to visualise it either in Tecplot or in Paraview.
%
%
%
\subsection{Print L2 and LInf norms: \textit{printfldnorms} module}
\begin{lstlisting}[style=BashInputStyle]
......
......@@ -82,6 +82,7 @@ ADD_NEKTAR_TEST(chan3D_vort)
ADD_NEKTAR_TEST(bfs_vort)
ADD_NEKTAR_TEST(bfs_vort_rng)
# ADD_NEKTAR_TEST(chan3D_pts)
ADD_NEKTAR_TEST(chan3DH1D_meanmode)
# windows produces slightly differently formatted files which results in
# different hashes
......
<?xml version="1.0" encoding="utf-8" ?>
<NEKTAR>
<Metadata>
<Provenance>
<GitBranch>refs/heads/feature/FieldConvert-MeanMode</GitBranch>
<GitSHA1>c764f9c3d9a8bc04a57d75675e9ba9420306ec06</GitSHA1>
<Hostname>ae-ds6412</Hostname>
<NektarVersion>4.3.0</NektarVersion>
<Timestamp>08-Jan-2016 13:02:28</Timestamp>
</Provenance>
<Kinvis>1</Kinvis>
<SessionName0>chan3DH1D.xml</SessionName0>
<Time>1.0000000000000007</Time>
<TimeStep>0.001</TimeStep>
</Metadata>
<ELEMENTS FIELDS="u,v,w,p" SHAPE="Quadrilateral-HomogenousExp1D" BASIS="Modified_A,Modified_A,Fourier" HOMOGENEOUSLENGTHS="1" HOMOGENEOUSZIDS="0,1,2,3,4,5,6,7" NUMMODESPERDIR="UNIORDER:4,4,8" ID="0-3">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</ELEMENTS>
</NEKTAR>
<?xml version="1.0" encoding="utf-8"?>
<NEKTAR>
<EXPANSIONS>
<E COMPOSITE="C[0]" NUMMODES="4" FIELDS="u,v,w,p" TYPE="MODIFIED" />
</EXPANSIONS>
<CONDITIONS>
<SOLVERINFO>
<I PROPERTY="SolverType" VALUE="VelocityCorrectionScheme"/>
<I PROPERTY="EQTYPE" VALUE="UnsteadyNavierStokes"/>
<I PROPERTY="AdvectionForm" VALUE="Convective"/>
<I PROPERTY="Projection" VALUE="Galerkin"/>
<I PROPERTY="TimeIntegrationMethod" VALUE="IMEXOrder2"/>
<I PROPERTY="HOMOGENEOUS" VALUE="1D"/>
</SOLVERINFO>
<PARAMETERS>
<P> TimeStep = 0.001 </P>
<P> NumSteps = 1000 </P>
<P> IO_CheckSteps = 1000 </P>
<P> IO_InfoSteps = 1000 </P>
<P> Kinvis = 1 </P>
<P> HomModesZ = 8 </P>
<P> LZ = 1.0 </P>
</PARAMETERS>
<VARIABLES>
<V ID="0"> u </V>
<V ID="1"> v </V>
<V ID="2"> w </V>
<V ID="3"> p </V>
</VARIABLES>
<BOUNDARYREGIONS>
<B ID="0"> C[1] </B>
<B ID="1"> C[2] </B>
<B ID="2"> C[3] </B>
</BOUNDARYREGIONS>
<BOUNDARYCONDITIONS>
<REGION REF="0">
<D VAR="u" VALUE="0" />
<D VAR="v" VALUE="0" />
<D VAR="w" VALUE="0" />
<N VAR="p" USERDEFINEDTYPE="H" VALUE="0" /> // High Order Pressure BC
</REGION>
<REGION REF="1">
<D VAR="u" VALUE="y*(1-y)" />
<D VAR="v" VALUE="0" />
<D VAR="w" VALUE="0" />
<N VAR="p" USERDEFINEDTYPE="H" VALUE="0" /> // High Order Pressure BC
</REGION>
<REGION REF="2">
<N VAR="u" VALUE="0" />
<N VAR="v" VALUE="0" />
<N VAR="w" VALUE="0" />
<D VAR="p" VALUE="0" />
</REGION>
</BOUNDARYCONDITIONS>
<FUNCTION NAME="InitialConditions">
<E VAR="u" VALUE="0" />
<E VAR="v" VALUE="0" />
<E VAR="w" VALUE="0" />
<E VAR="p" VALUE="0" />
</FUNCTION>
<FUNCTION NAME="ExactSolution">
<E VAR="u" VALUE="y*(1-y)" />
<E VAR="v" VALUE="0" />
<E VAR="w" VALUE="0" />
<E VAR="p" VALUE="-2*Kinvis*(x-1)" />
</FUNCTION>
</CONDITIONS>
<GEOMETRY DIM="2" SPACE="2">
<VERTEX>
<!-- Always must have four values per entry. -->
<V ID="0"> 0.0 0.0 0.0 </V>
<V ID="1"> 0.5 0.0 0.0 </V>
<V ID="2"> 1.0 0.0 0.0 </V>
<V ID="3"> 0.0 0.5 0.0 </V>
<V ID="4"> 0.5 0.5 0.0 </V>
<V ID="5"> 1.0 0.5 0.0 </V>
<V ID="6"> 0.0 1.0 0.0 </V>
<V ID="7"> 0.5 1.0 0.0 </V>
<V ID="8"> 1.0 1.0 0.0 </V>
</VERTEX>
<EDGE>
<E ID="0"> 0 1 </E>
<E ID="1"> 1 2 </E>
<E ID="2"> 0 3 </E>
<E ID="3"> 1 4 </E>
<E ID="4"> 2 5 </E>
<E ID="5"> 3 4 </E>
<E ID="6"> 4 5 </E>
<E ID="7"> 3 6 </E>
<E ID="8"> 4 7 </E>
<E ID="9"> 5 8 </E>
<E ID="10"> 6 7 </E>
<E ID="11"> 7 8 </E>
</EDGE>
<!-- Q - quads, T - triangles, S - segments, E - tet, P - pyramid, R - prism, H - hex -->
<!-- Only certain element types are appropriate for the given dimension (dim on mesh) -->
<!-- Can also use faces to define 3-D elements. Specify with F[1] for face 1, for example. -->
<ELEMENT>
<Q ID="0"> 0 3 5 2 </Q>
<Q ID="1"> 1 4 6 3 </Q>
<Q ID="2"> 5 8 10 7 </Q>
<Q ID="3"> 6 9 11 8 </Q>
</ELEMENT>
<COMPOSITE>
<C ID="0"> Q[0-3] </C>
<C ID="1"> E[0,1,10,11] </C> // Walls
<C ID="2"> E[2,7] </C> // Inflow
<C ID="3"> E[4,9] </C> // Outflow
</COMPOSITE>
<DOMAIN> C[0] </DOMAIN>
</GEOMETRY>
</NEKTAR>
<?xml version="1.0" encoding="utf-8"?>
<test>
<description> Process 3DH1D meanmode output </description>
<executable>FieldConvert</executable>
<parameters> -m meanmode -e chan3DH1D.xml chan3DH1D.fld chan3DH1D_mean.fld</parameters>
<files>
<file description="Session File">chan3DH1D.xml</file>
<file description="Session File">chan3DH1D.fld</file>
</files>
<metrics>
<metric type="L2" id="1">
<value variable="u" tolerance="1e-6">0.182574</value>
<value variable="v" tolerance="1e-6">0</value>
<value variable="w" tolerance="1e-6">0</value>
<value variable="p" tolerance="1e-6">1.1547</value>
</metric>
</metrics>
</test>
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