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<title>YALMIP Example : Efficient solution of KYP problems</title>
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<h2>Saving & and loading</h2>
<hr noShade SIZE="1">
<p>The most efficient and safe way to save and communicate YALMIP models
is to work with the MATLAB script, i.e. the YALMIP code. In some cases
however, it might be necessary to use binary or other formats.
Additionally, there might be cases where a YALMIP model needs to be
converted to a solver specific numerical model.</p>
<h3>Loading & saving in binary MATLAB format</h3>
<p>The objects in YALMIP all support loading and saving, hence it is
possible to save a model in a binary MATLAB format.</p>
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<pre>A = randn(3);
P = sdpvar(3,3);
F = set(A'*P+P*A < -eye(3));
obj = trace(P);</pre>
<pre>save mymodel</pre>
<pre>clear all;
load mymodel
F
<font color="#000000">+++++++++++++++++++++++++++++++++++++++++++++++++
| ID| Constraint| Type|
+++++++++++++++++++++++++++++++++++++++++++++++++
| #1| Numeric value| Matrix inequality 3x3|
+++++++++++++++++++++++++++++++++++++++++++++++++</font>
obj
<font color="#000000">Linear scalar (real, 3 variables)</font></pre>
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<p>Note that loading a YALMIP model will destroy any
<a href="reference.htm#sdpvar">sdpvar</a> and
<a href="reference.htm#set">set</a> object in the current
workspace. The binary data format is not recommended, and the reason is three-fold. The first reason is
incompatibility between different MATLAB version, the second reason is
possible incompatibility between different YALMIP versions, and finally
that the binary format in YALMIP currently is inefficient for
large-scale problems.</p>
<h3>Loading & saving in SDPA sparse ASCII format</h3>
<p>The leading format to communicate standard linear SDP problems in a
platform and application independent way is the
<a target="_blank" href="http://infohost.nmt.edu/~sdplib/FORMAT">sparse
SDPA format</a>. YALMIP can both save and load models in this format.</p>
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<pre>A = randn(3);
P = sdpvar(3,3);
F = set(A'*P+P*A < -eye(3));
obj = trace(P);</pre>
<pre>savesdpafile(F,obj,'mymodel.dat-s');</pre>
<pre>clear all;
[F,obj] = loadsdpafile('mymodel.dat-s');
F
<font color="#000000">+++++++++++++++++++++++++++++++++++++++++++++++++
| ID| Constraint| Type|
+++++++++++++++++++++++++++++++++++++++++++++++++
| #1| Numeric value| Matrix inequality 3x3|
+++++++++++++++++++++++++++++++++++++++++++++++++</font>
obj
<font color="#000000">Linear scalar (real, 3 variables)</font></pre>
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<p>The SDPA format is limited to standard linear SDP problems (without
equality constraints), hence many YALMIP models cannot be saved in this
format.</p>
<h3>Exporting solver specific models</h3>
<p>YALMIP can be used to extract the numerical model in various solver
specific formats. This can be done along during a call to the solver,
but also without explicitly invoking the solver. To export the solver
while solving the problem, we use the <code>savesolverinput</code> option.<table cellPadding="10" width="100%" id="table2">
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<pre>A = randn(3);
P = sdpvar(3,3);
F = set(A'*P+P*A < -eye(3));
obj = trace(P);
sol = solvesdp(F,obj,sdpsettings('solver','sedumi','savesolverinput',1));
sol.solverinput
<font color="#000000">ans = </font></pre>
<pre><font color="#000000"> A: [9x6 double]
c: [9x1 double]
b: [6x1 double]
K: [1x1 struct]
pars: [1x1 struct]</font></pre>
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<p>To export the model with actually calling the solver, use
<a href="reference.htm#export">export</a>.</p>
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<pre>A = randn(3);
P = sdpvar(3,3);
F = set(A'*P+P*A < -eye(3));
obj = trace(P);
mdl = export(F,obj,sdpsettings('solver','sedumi'));
mdl</pre>
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<p>All solvers are currently not supported in
<a href="reference.htm#export">export</a>. If you miss
support for some solver, please make a feature request.<h3>Saving AMPL
models<br>
</h3>A
rudimentary support for exporting models in
<a target="_blank" href="http://www.ampl.com/">AMPL</a> format is
available. This functionality is mainly intended for small nonlinear or
mixed integer programs.<table cellPadding="10" width="100%" id="table4">
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<pre>sdpvar a b c
F = set(a+b^2 < c*pi) + set(integer(b)) + set(a+b==3);
obj = a*b*c;
saveampl(F,obj,'mymodel.mod')
type mymodel</pre>
<pre><font color="#000000">var x {1..2};
var z {1..1} integer ;
minimize obj: x[1]*z[1]*x[2];
subject to constr1: 0 <= -x[1]+x[2]-z[1]^2;
subject to constr2: 0 == 3-x[1]-z[1];
solve;
display x;
display z;
display obj;</font></pre>
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