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Team:Paris/Modeling/More f3bis Algo - Revision history
2024-03-29T13:19:02Z
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Hugo: New page: <html><pre class="codeinput"> <span class="keyword">function</span> optimal_parameters = find_f3_EnvZ(X_data, Y_data, initial_parameters) <span class="comment">% gives the 'best parameters...
2008-10-30T03:46:22Z
<p>New page: <html><pre class="codeinput"> <span class="keyword">function</span> optimal_parameters = find_f3_EnvZ(X_data, Y_data, initial_parameters) <span class="comment">% gives the 'best parameters...</p>
<p><b>New page</b></p><div><html><pre class="codeinput"><br />
<span class="keyword">function</span> optimal_parameters = find_f3_EnvZ(X_data, Y_data, initial_parameters)<br />
<span class="comment">% gives the 'best parameters' involved in f3 with OmpR = 0 by least-square optimisation<br />
</span><span class="comment">% -> USE IT AFTER find_f3_OmpR<br />
</span> <br />
<span class="comment">% X_data = vector of given values of ( [EnvZ]i ) (experimentally<br />
</span><span class="comment">% controled)<br />
</span><span class="comment">% Y_data = vector of experimentally measured values f3 corresponding of<br />
</span><span class="comment">% the X_data<br />
</span><span class="comment">% initial_parameters = values of the parameters proposed by the literature<br />
</span><span class="comment">% or simply guessed<br />
</span><span class="comment">% = [EnvZ_b, OmpR_b, K14, n14]<br />
</span> <br />
<span class="keyword">global</span> beta17 K15 n15;<span class="comment"> % parameters GIVEN BY find_f3_OmpR<br />
</span> <br />
<span class="keyword">function</span> output = act_pFlhDC(parameters, X_data)<br />
<span class="keyword">for</span> k = 1:length(X_data)<br />
OmpR_P = complexes((parameters(1) + X_data(k)),parameters(2),parameters(3),parameters(4));<br />
<span class="comment"> % complexes is a function that solve the "basical<br />
</span> <span class="comment"> % complexation equation"<br />
</span> output(k) = beta17*(1 - hill( OmpR_P, K15, n15 ));<br />
<span class="keyword">end</span><br />
<span class="keyword">end</span><br />
<br />
options=optimset(<span class="string">'LevenbergMarquardt'</span>,<span class="string">'on'</span>,<span class="string">'TolX'</span>,1e-10,<span class="string">'MaxFunEvals'</span>,1e10,<span class="string">'TolFun'</span>,1e-10,<span class="string">'MaxIter'</span>,1e4);<br />
<span class="comment">% options for the function lsqcurvefit<br />
</span> <br />
optimal_parameters = lsqcurvefit( @(parameters, X_data) act_pFlhDC(parameters, X_data), ...<br />
initial_parameters, X_data, Y_data, options );<br />
<span class="comment">% search for the fittest parameters, between 1/10 and 10 times the initial<br />
</span><span class="comment">% parameters<br />
</span> <br />
<span class="keyword">end</span><br />
</pre></html></div>
Hugo