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    Larisssa,<br>
    Now we have a clue. Many years ago I worked on dynamic system models
    of fermentation. What I did was to create a differential equation
    set to account for the identifiable "species" --- abstract idea
    which includes various bio-chemical generic classes -- and running
    those models and experimenting it became possible to get a working
    model, by choosing parameters.  When that reached its limit, moving
    on to more complex models enabled us (me and a micologist) to create
    a model good enough to predict the performance of an industrial
    process.<br>
        In your case I'd start with a very simple model, and I'd expect
    that since the growth rate in biomass would initially probably
    increase in proportion to the mass present the model would give an
    exponential initial rate, then as the algae blocked the light it
    wanted and the other key food sources (dissolved oxygen?) were
    depleted, the rate would decline. In the work I did in the past we
    got into the metabolic pathways and  energy balances with heat and
    synthesis reaction rates, but I'd start with something simpler in
    your case to see how simple a model would explain the process. I
    would be a good candidate for a model in Xcos. You can look into my
    website <br>
        <a class="moz-txt-link-freetext" href="http://www.mccannscience.com/fermenta.htm">http://www.mccannscience.com/fermenta.htm</a><br>
    if you are interested.<br>
    Mike<br>
    =======================<br>
    <div class="moz-cite-prefix">On 01/07/2013 09:24, Larissa wrote:<br>
    </div>
    <blockquote
cite="mid:trinity-485c322a-5adf-4cf7-8b6f-fc9c581868e7-1372670654303@3capp-gmx-bs17"
      type="cite">
      <div style="font-family: Verdana;font-size: 12.0px;">
        <div>
          <div>Hi,</div>
          <div> </div>
          <div>so regarding the data..</div>
          <div>it was an experiment related to algal biomass yield
            (g/m&sup2;) ("z") according to time (0-25days, the "x"-data) and
            light intensity (25-1000µmol*m^-1*s^-1, the "y" values).
            Increase in biomass might have been exponential right at the
            beginning, but with increasing time I guess it turned out to
            be linear...</div>
          <div> </div>
          <div>does anybody have a hint about the model I could use?:)</div>
          <div> </div>
          <div> </div>
          <div> 
            <div name="quote" style="margin:10px 5px 5px 10px; padding:
              10px 0 10px 10px; border-left:2px solid #C3D9E5;
              word-wrap: break-word; -webkit-nbsp-mode: space;
              -webkit-line-break: after-white-space;">
              <div style="margin:0 0 10px 0;"><b>Gesendet:</b> Montag,
                01. Juli 2013 um 11:14 Uhr<br>
                <b>Von:</b> "Mike Page [via Scilab / Xcos - Mailing
                Lists Archives]" <<a moz-do-not-send="true"
                  href="/user/SendEmail.jtp?type=node&node=4026926&i=0"
                  target="_top" rel="nofollow" link="external">[hidden
                  email]</a>><br>
                <b>An:</b> Larissa <<a moz-do-not-send="true"
                  href="/user/SendEmail.jtp?type=node&node=4026926&i=1"
                  target="_top" rel="nofollow" link="external">[hidden
                  email]</a>><br>
                <b>Betreff:</b> Re: Convert x, y, z data into a z=f(x,y)
                function</div>
              <div name="quoted-content">
                <div><span class="328270209-01072013"><font
                      color="#0000ff" face="Arial" size="2">Hi,</font></span></div>
                <div> </div>
                <div><span class="328270209-01072013"><font
                      color="#0000ff" face="Arial" size="2">You are
                      asking a question which in general has no answer. 
                      There are an infinite number of models which can
                      fit your data.  You need to find some possible
                      candidate model forms based on physical properties
                      and then try fitting to them.  You are probably
                      looking for a fit which leaves residues which are
                      Gaussian and mean zero (but that's not always
                      true...).</font></span></div>
                <div> </div>
                <div><span class="328270209-01072013"><font
                      color="#0000ff" face="Arial" size="2">Try giving
                      us a clue about where the data come from.  Maybe
                      somebody has the physical background to suggest
                      some models.  If not, try plotting the data and
                      guessing a model from the shape.  To me the shape
                      looks vaguely exponential or logarithmic, so maybe
                      plotting as log-linear or log-log will give a
                      clue.</font></span></div>
                <div> </div>
                <div><span class="328270209-01072013"><font
                      color="#0000ff" face="Arial" size="2">HTH,</font></span></div>
                <div><span class="328270209-01072013"><font
                      color="#0000ff" face="Arial" size="2">Mike.</font></span></div>
                <div> </div>
                <blockquote style="border-left:2px solid
                  #CCCCCC;padding:0 1em">
                  <div class="OutlookMessageHeader" align="left"><font
                      face="Tahoma" size="2">-----Original Message-----<br>
                      <b>From:</b> <a moz-do-not-send="true"
                        target="_top" rel="nofollow" link="external">[hidden
                        email]</a> [mailto:<a moz-do-not-send="true"
                        target="_top" rel="nofollow" link="external">[hidden
                        email]</a>]<b>On Behalf Of </b>Larissa Schultze<br>
                      <b>Sent:</b> 01 July 2013 09:43<br>
                      <b>To:</b> International users mailing list for
                      Scilab.<br>
                      <b>Subject:</b> Re: [Scilab-users] Convert x, y, z
                      data into a z=f(x,y) function</font><br>
                     </div>
                  <div style="FONT-FAMILY: Verdana;FONT-SIZE: 12.0px;">
                    <div>
                      <div>Hello all,</div>
                      <div> </div>
                      <div>first of all, thanks a lot for your effort. I
                        must say that I don't really have anyone to run
                        to for asking about mathematical models - I
                        could go to the mathematicians at the
                        University, but I don't know anyone there and I
                        barelly know where the institute is located...</div>
                      <div> </div>
                      <div>therefore I decided to insert my
                        simplest table in here (it is actually very
                        simple) - may be someone here knows which kind
                        of mathematical model I could use?</div>
                      <div>I have been searching for it in literature,
                        but I don't seem to be in the right path...</div>
                      <div> </div>
                      <div>So attached you will find my data table as
                        well as the scilab commands I used to create the
                        respective graph. I mean, my data is already
                        interpolated...shouldn't it be easy to get a
                        function (z,x,y) out of it?</div>
                      <div> </div>
                      <div>I would be very very thankful for any
                        help...I'm getting a bit desperate...</div>
                      <div> </div>
                      <div>best regards,</div>
                      <div>Larissa</div>
                      <div> </div>
                      <div> </div>
                      <div> </div>
                      <div> 
                        <div style="BORDER-LEFT: rgb(195,217,229) 2.0px
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                          10.0px;">
                          <div style="MARGIN: 0.0px 0.0px 10.0px;"><b>Gesendet:</b> Dienstag,
                            25. Juni 2013 um 11:09 Uhr<br>
                            <b>Von:</b> "CRETE Denis" <<a
                              moz-do-not-send="true" target="_top"
                              rel="nofollow" link="external">[hidden
                              email]</a>><br>
                            <b>An:</b> "International users mailing list
                            for Scilab." <<a moz-do-not-send="true"
                              target="_top" rel="nofollow"
                              link="external">[hidden email]</a>><br>
                            <b>Betreff:</b> Re: [Scilab-users] Convert
                            x, y, z data into a z=f(x,y) function</div>
                          <div>Hello,<br>
                            <br>
                            The general procedure for fitting data in
                            the case of 2 variables is the following:<br>
                            // First define your mathematical model by
                            changing the following line<br>
                            deff('z=MyFunction(x,y)', 'z=p(1)*x + p(2)*y
                            + p(3)*x.*y');<br>
                            // Store all experimental data in a single
                            array ExD; X, Y, Z assumed to be 1 x NZ
                            vectors<br>
                            ExD=[X;Y;Z];<br>
                            // Define the error function (to be
                            minimized with respect to the parameters p)<br>
                            deff('erro=G(p,ExD)','x=ExD(1),y=ExD(2),
                            z=ExD(3), erro=z-MyFunction(x,y)')<br>
                            // Fit experimental data contained in W<br>
                            // The column vector p0 is an initial guess
                            of the values for the parameters of your
                            Model<br>
                            [p,err]=datafit(G,ExD,p0)<br>
                            // you can check values generated with<br>
                            MyFunction(X,Y)<br>
                            <br>
                            HTH<br>
                            Denis<br>
                            <br>
                            -----Message d'origine-----<br>
                            De : <a moz-do-not-send="true"
                              target="_top" rel="nofollow"
                              link="external">[hidden email]</a>
                            [mailto:<a moz-do-not-send="true"
                              target="_top" rel="nofollow"
                              link="external">[hidden email]</a>] De la
                            part de Dang, Christophe<br>
                            Envoyé : mardi 25 juin 2013 10:20<br>
                            À : International users mailing list for
                            Scilab.<br>
                            Objet : Re: [Scilab-users] Convert x, y, z
                            data into a z=f(x,y) function<br>
                            <br>
                            Hello,<br>
                            <br>
                            De la part de Larissa<br>
                            Envoyé : mardi 25 juin 2013 09:52<br>
                            <br>
                            > I conducted an experiment and thus my
                            results are composed of x,y,z<br>
                            > data,<br>
                            [...]<br>
                            > but I can't figure out how to get an
                            equation "z=f(x,y)" out of it.<br>
                            <br>
                            This is more a math problem than a Scilab
                            problem.<br>
                            <br>
                            You must have a mathematical model, i.e. a
                            parametric formula, then you can adjust the
                            parameters by regression (or maximum
                            likehood).<br>
                            <br>
                            You may have theoretical models that derive
                            from elementary assumptions<br>
                            -- you usually find such model in the
                            bibliography --, or use a "nice model that
                            fit the global shape"<br>
                            -- you may ask the math laboratory in your
                            neighbourhood, this is usually polynomials,
                            exponentials, statistical laws...<br>
                            <br>
                            So if you come to us with a parametric
                            model, we will be able to help you.<br>
                            <br>
                            best regards.<br>
                            <br>
                            --<br>
                            Christophe Dang Ngoc Chan<br>
                            Mechanical calculation engineer<br>
                            <br>
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