Re: Fitting Experimental Data

*To*: mathgroup at smc.vnet.net*Subject*: [mg116490] Re: Fitting Experimental Data*From*: mathilde Favier <fmath at hotmail.fr>*Date*: Thu, 17 Feb 2011 05:17:02 -0500 (EST)

Hi everybody, To try to give more information and be more clear: 1a/For those who tried to play with the data I've sent, I am interested in fitting the 2 round shapes which look like asymetric Gaussian corresponding to data[[700;;950]] and data[[1100;;1400]] I don't care about the other data. 1b/ My Y data are well FFT but, there is no symetry between the 2 round shapes unlike it could seem (long to explain). That's why I need to fit the 2 shapes independently to each other. 2/My X data are well separated by 1, but I am doing some lineare computation to have the Xscale I am interested in (this a take care don't worry) 3/I need to remove the peaks because to explain it simply: Peaks = Coherent signal/ Others = Incoherent signal. As I am looking at the incoherent signal, so peaks disturb my fit. 4/I did a Fit using the xydata using Transpose[xdata,ydata] as you suggest me, but as I removed the top of my Gaussian shape, the fit gives me a flat top. I am trying maybe to do an average of my peaks to keep some data on the top of my curve. Important: I am looking to an automatic and fast fit, nothing has to be manual. Glad to receive ideas and answers from you, but my problem is still looking for an accurate solution. Any other questions or Ideas, don't hesitate. Cheers FAVIER MathildeTel: + 33 (0)6 35 29 36 96fmath at hotmail.fr > Date: Wed, 16 Feb 2011 06:45:53 -0500 > From: Kevin.McCann at umbc.edu > To: fmath at hotmail.fr > Subject: Re: Fitting Experimental Data > To: comp-soft-sys-math-mathematica at moderators.isc.org > > Some comments. > > (1) It is hard to say more about your fitting without more information > about dataleftlowband. > (2) The peaks (spikes) in your data are not necessarily "spurious" just > because they don't fit your expected curves. You need a very good > reason, and maybe you have that, for removing them. > (3) I think I know what you mean, but there is no such thing as an > asymmetric Gaussian; so, a bit more information here might help. > (4) Along the lines of (3) you indicate that you need to fit your data > with a Gaussian (asymmetric?), presumably to retrieve the associated > parameters; however, by deleting the peaks, you are also eliminating > important data. Why are these peaks present at the top of the curve, but > not elsewhere? > > Just a few thoughts, > > Kevin > > On 2/15/2011 6:33 AM, mathilde Favier wrote: > > I am in trouble in trying to do a Fit using Mathematica7. > > > > Here my problem: > > > > My instrument on which I am working is giving me data looking like a plot with two round (more Gaussian) shape but with some picks on the top of each, the figures would have shown it, but you told me that I cannot enclose any file. > > > > I am only interested in the 2 round shapes, . > > > > My goal is to do a fit of those them. > > > > First I am isolating those 2 parts (ie: Plotting them whithout the data between them.) > > > > But the problem is that the picks on the top of each round shape will disturber my > > fit so I have to remove them.So now I have removed the picks, I have just 2 kind of asymetrics Gaussians with a hall on the top of each. To describe it more properly, I would say I have the rising and falling edge of two differente asymetric Gaussian. > > > > Now I start to look for a first Fit corresponding to the first asymetric Gaussian. > > > > Here is my code: > > > > model > > b+ a*(1/(s*\[Sqrt](2*Pi)))* > > Exp[-(x-m)^2/(2*s^2)]; > > > > fit=FindFit[dataleftlowband,model,{b,a,s,m}, x, MaxIterations->100] > > > > modelfit = Table[Evaluate[model/.fit],{x,1,Length[dataleftlowband]}]; > > > > tmodelfit = Transpose[{xdataleftlowband,modelfit}]; > > > > My big problem is that I removed some data > > in the middle of my curve and I want that according to the values kept, the > > fitting find out which should be the missing values, because I need to > > approximately trace the top of my Gaussian shape. > > > > I've tried a lot of stuff to find out how > > to solve that as, random points in the Gap... > > > > Is there a method like considering the > > first part as the rising edge and the second as the falling edge of a Gaussian? > > > > Is Mathematica able to solve that? > > > > I hope that my problem is clearly explained. It's not that easy without any pictures to show how my data look like. > > > > Tell me if you have any idea to find a solution. > > > > Thank you in advance > > > > FAVIER MathildeTel: + 33 (0)6 35 29 36 96fmath at hotmail.fr