Hi everyone,
I conducted an experiment and thus my results are composed ofx,y,z data, whereas: x= time (025days) y= light intensity (9 different light intensities, ranging from 25 to 1000 µmol*m^2*s^1) z= biomass increase acording to time and light intensity I was able to generate a 3D graph out of this information (using both plot3d and surf), but I can't figure out how to get an equation "z=f(x,y)" out of it. It should be possible though, shouldn't it? If so, how? I would be very very grateful if somebody could help me on that  I am very new in Scilab and I am nothing close to an engineer, so you can imagine that it is quite a challenge for me... 'Till yesterday I was happy of being able to plot such nice graphs  now i want MORE!!!;P Thanks a lot, Larissa 
Christophe Dang Ngoc Chan 
Hello,
De la part de Larissa Envoyé : mardi 25 juin 2013 09:52 > I conducted an experiment and thus my results are composed of > x,y,z data, [...] > but I can't figure out how to get an equation "z=f(x,y)" out of it. This is more a math problem than a Scilab problem. You must have a mathematical model, i.e. a parametric formula, then you can adjust the parameters by regression (or maximum likehood). You may have theoretical models that derive from elementary assumptions  you usually find such model in the bibliography , or use a "nice model that fit the global shape"  you may ask the math laboratory in your neighbourhood, this is usually polynomials, exponentials, statistical laws... So if you come to us with a parametric model, we will be able to help you. best regards.  Christophe Dang Ngoc Chan Mechanical calculation engineer ______________________________________________________________________ This email may contain confidential and/or privileged information. If you are not the intended recipient (or have received this email in error), please notify the sender immediately and destroy this email. Any unauthorized copying, disclosure or distribution of the material in this email is strictly forbidden. ______________________________________________________________________ _______________________________________________ users mailing list [hidden email] http://lists.scilab.org/mailman/listinfo/users 
Denis Crété 
Hello,
The general procedure for fitting data in the case of 2 variables is the following: // First define your mathematical model by changing the following line deff('z=MyFunction(x,y)', 'z=p(1)*x + p(2)*y + p(3)*x.*y'); // Store all experimental data in a single array ExD; X, Y, Z assumed to be 1 x NZ vectors ExD=[X;Y;Z]; // Define the error function (to be minimized with respect to the parameters p) deff('erro=G(p,ExD)','x=ExD(1),y=ExD(2), z=ExD(3), erro=zMyFunction(x,y)') // Fit experimental data contained in W // The column vector p0 is an initial guess of the values for the parameters of your Model [p,err]=datafit(G,ExD,p0) // you can check values generated with MyFunction(X,Y) HTH Denis Message d'origine De : [hidden email] [mailto:[hidden email]] De la part de Dang, Christophe Envoyé : mardi 25 juin 2013 10:20 À : International users mailing list for Scilab. Objet : Re: [Scilabusers] Convert x, y, z data into a z=f(x,y) function Hello, De la part de Larissa Envoyé : mardi 25 juin 2013 09:52 > I conducted an experiment and thus my results are composed of x,y,z > data, [...] > but I can't figure out how to get an equation "z=f(x,y)" out of it. This is more a math problem than a Scilab problem. You must have a mathematical model, i.e. a parametric formula, then you can adjust the parameters by regression (or maximum likehood). You may have theoretical models that derive from elementary assumptions  you usually find such model in the bibliography , or use a "nice model that fit the global shape"  you may ask the math laboratory in your neighbourhood, this is usually polynomials, exponentials, statistical laws... So if you come to us with a parametric model, we will be able to help you. best regards.  Christophe Dang Ngoc Chan Mechanical calculation engineer ______________________________________________________________________ This email may contain confidential and/or privileged information. If you are not the intended recipient (or have received this email in error), please notify the sender immediately and destroy this email. Any unauthorized copying, disclosure or distribution of the material in this email is strictly forbidden. ______________________________________________________________________ _______________________________________________ users mailing list [hidden email] http://lists.scilab.org/mailman/listinfo/users _______________________________________________ users mailing list [hidden email] http://lists.scilab.org/mailman/listinfo/users
Denis Crété

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Hi,
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...).
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 loglinear or loglog will give
a clue.
HTH,
Mike.
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Hi,
so regarding the data..
it was an experiment related to algal biomass yield (g/m²) ("z") according to time (025days, the "x"data) and light intensity (251000µmol*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...
does anybody have a hint about the model I could use?:)
Gesendet: Montag, 01. Juli 2013 um 11:14 Uhr
Von: "Mike Page [via Scilab / Xcos  Mailing Lists Archives]" <[hidden email]> An: Larissa <[hidden email]> Betreff: Re: Convert x, y, z data into a z=f(x,y) function
Hi,
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...).
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 loglinear or loglog will give a clue.
HTH,
Mike.
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http://mailinglists.scilab.org/Convertxyzdataintoazfxyfunctiontp4026897p4026925.html 
Michael J. McCann2 
Larisssa,
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 biochemical 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. 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 http://www.mccannscience.com/fermenta.htm if you are interested. Mike ======================= On 01/07/2013 09:24, Larissa wrote:
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Christophe Dang Ngoc Chan 
De la part de Michael J. McCann
Envoyé : lundi 1 juillet 2013 13:01 > 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" I agree this would be a good way, which gives you a model that has sense. If we make a simple z = f(x) (biomass = f(time)) plot (see attached document), we can see that 1  the curves do not follow a simple analytic function 2  they are not completely parallel, especially for the last points so, hard to fit with usual simple function. Now, maybe a nonparametric analysis  i.e. not looking for a function but only for some characteristics of your data  is enough for you? Maybe what you're looking for can be extracted from the initial slope, the height of the first plateau, ..? In fact, you try to answer a question, but we dont't know the question...  Christophe Dang Ngoc Chan Mechanical calculation engineer ______________________________________________________________________ This email may contain confidential and/or privileged information. If you are not the intended recipient (or have received this email in error), please notify the sender immediately and destroy this email. Any unauthorized copying, disclosure or distribution of the material in this email is strictly forbidden. ______________________________________________________________________ _______________________________________________ users mailing list [hidden email] http://lists.scilab.org/mailman/listinfo/users biomass_vs_time.png (19K) Download Attachment 
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