Constrained Nonlinear Curve Fit VI: Termination Revisited (LabVIEW 8.5)
Hello:
In the Constrained Nonlinear Curve Fit VI, the Help for the VI states that if the number of iterations exceeds max iterations specified in the termination control, the fitting
process terminates. Would this not indicate that if the above condition is met, the number of iterations recorded (an output of this VI) should be equal to the max iterations specified (since the VI is exits at this point). I believe I have seen situations where this condition is met, yet the number of iterations recorded is greater than the max iterations I have specified in the termination control. Has anyone else seen this?
Thanks,
Don
Don,
Just wanted to clarify the termination criteria for the nonlinear curve fitting routines. There are two criteria used to terminate the fitting process:
"max iteration" and "tolerance". The main while loop terminates when either of these conditions is met, so:
IF( (current_iteration > max_iteration) OR (current_tolerance <= tolerance) ) THEN (terminate loop)
"current iteration" is just the current loop counter(starts at 1 for the first iteration). This term is mainly a guard against having the fitting process run too long.
tolerance is computed as the relative change between the current and previous weighted least squares values.
Let wls = SUM_OVER_ALL_X( weight(x)*(f(x,a)data(x))^2 )
current_tolerance = ABS(current_wls  previous_wls)/(ABS(current_wls) + machine_epsilon)
where ABS indicates absolute value. Adding machine_epsilon to the denominator is just a guard against division by zero.
For the bound nonlinear curve fit VIs, if the "method" input is chosen to be LAR or bisquare, then wls is defined as:
wls = SUM_OVER_ALL_X( weight(x)*reweight(x)*(f(x,a)data(x))^2 )
where reweight(x) is a term reducing the weight of highleverage data points.
For both the constrained and unconstrained fitting routines, if the weight input is unwired then all points are considered to have a weight of 1.
Christian has nicely covered the difference between the number of iterations and the number of function calls. If your
When the fitting process terminates the best result obtained so far is returned. As you noted, this may be a good result, although the algorithm may not have completely converged yet.
Jim
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Constrained nonlinear curve fit can properly handle the function like ln(1+b(xxc)/a) ?
Hi all,
I met some problems about using constrained nonlinear curve fitting vi. It seems to me that this vi can't properly deal with the function like ln(1+b(xxc)/a), a,b, and xc are the parameters, and b is in the range of 0 and 1. The reason I said that is as I used the other nonlinear fitting function in the other software, like Originlab, the fitting function can work properly.
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Joy
Solved!
Go to Solution.
Attachments:
LNfitting.vi 21 KB
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Attachments:
ellipse fit data.zip 41 KBjcyth wrote:
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LabVIEW Champion . Do more with less code and in less time .
Attachments:
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Attachments:
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帖子被trinight在02112006 07:51 PM时编辑过了
Attachments:
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LabVIEW Champion . Do more with less code and in less time .
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Labview user
Solved!
Go to Solution.
Attachments:
Origin_Fit.PNG 21 KB
Labview_fit.PNG 15 KBThat looks like a plot of the input data.
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I am trying to get a multidimensional fit working by using a nonlinear curve fit VI and everytime I run it I get an error saying that my samples need to be greater than 0. The specific error message is: "Error: Analysis samples need to be > 0." Does anyone know what is wrong? I have tried to reinitialize my input parameter array to zero, recompile the VI, etc. and still get the same error regardless.
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I am farely new to labview and have not figure out the best way, so that my diagrams stay smaller since my width and height are farely large. What do you mean eliminate the local variables in the loops of the model?
In the model, you have a hidden indicator called pixel size, which you write once outside the loop and then continuously read over and over again with every iteration of the loops via local variables. SInce the value does not change during the execution of the loops, reading the same indicator over and over is just a waste of efforts. Why involve the UI if the valie is right there in the wire?? The correct way would be to delete that indicator and the local variables and simply connect all by wires.
Did you understand my other comments?
ytran wrote:
The typical values for the controls are as follow:
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Are all of those fitting parameters or are some of them constant and known?
LabVIEW Champion . Do more with less code and in less time . 
Nonlinear curve fit help needed
I am in need of some help trying to fit a set of data that requires the use of nonlinear curve fitting. I have attached a txt file containing the data that needs to be fitted. The first row contains the xaxis values while the second row contains the yaxis values. The model for this set of data can be described by a single parameter, A, for the first five data points. The remainder of the data points can be described by the model A+A1*exp((0.4x)/A2), where A, A1, and A2 are all parameter. As you can see the two models share the parameter A.
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Thanks.
Alonzo
Solved!
Go to Solution.
Attachments:
Data.txt 1 KBI think the problem is that the first 5 points are not part of the data sent to LevMar. Because of this the fitting process fits the remaining data very well, but the constant term is able to freely move. I modified the model function to output A for the first 5 terms, and the complete function for the rest. The offset found is now more reasonable.
Also, your quote your model to be A+A1*exp((0.4x)/A2), but what is implemented in the model VI seems to be A+A1*exp((x0.4)/A2).
Jim
Attachments:
ExponentialFunction.vi 19 KB
FitExponentialExample.vi 24 KB 
Constrained Nonliner Curve Fit Error 20003 help
Hello.
I use Constrained Nonliner Curve Fit.vi to fit a customed function, just in the following picture 1. The initial paraments are exactly right, but it always stopped by a error 20003,it says "The number of samples must be >0",just as the picture 2.
What should I do to correct it? Thanks!
Attachments:
1.png 32 KB
2.png 9 KBCan you attach your code and some sample data? How big is the [X] array? The [a] array?
Does it work if you remove the partial derivatives calculation? (LabVIEW will automatically substitute numerical derivatives).
(The way you index into [a] seems incredibly convoluted. Couldn't you simply reshape into four columns and autoindex on a FOR loop?)
LabVIEW Champion . Do more with less code and in less time . 
Hi everybody,
I am trying to fit a custom nonlinear curve to my data. I want to fit a curve to the data twice. After the first fit, I want to use the coefficient a (6.57962) in my second curve fit as my coefficient b. When I try to use this and create a custom equation by string concetanete, everything seems fine but I do not get what I expect to get. To double check I used curve fitting express VI and I added 6.57962 as a coefficient in my equation and at the end a turns to be 6.752. However, this does not happen in my second curve fit. Does anybody have any idea what might be wrong? I cannot find my mistake, could you please help me?
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Attachments:
Read.vi 129 KB
read.png 66 KBThe errors you get provide some clues, although they are not very explicit.
The 23001: Syntax error of parser is usually a sign that your string describing the function is illformed or that there is a parameter mismatch. You have both.
The string array constant feeding into the second LevMar VI has two elements, the second one being an empty string. Even though the string is empty, the parser expects two elements in the Initial Parameters array. But since your equation has only one parameter (a), the proper solution is to remove the blank element from the constant array.
The other problem is that the first Initial Parameters array is empty. Maybe you always enter two values but I did not know what to put in.
The second fit is somewhat sensitive to the initial Parameter value. Negative values do not work. 1 returns 6.753... 2 through 6 and 8 (integer values only) return 6.246... 7 returns the same result as 1. Values 10 and above return the value entere with error 20041 (singular matrix) appearing at >=12.
The initial b parameter in the first fit does not matter over a fairly wide range.
I also noticed that you seem to have a severe allergy to straight wires. Wires running all over the diagram and particularly behind other objects makes it very hard to read your code. Dataflow along the wires should generally be from left to right as much as possible. The code works the same regardless of the number of bends in the wires but straighter wires are much easier on the programmer.
Lynn 
How can I modify the NonLinear curve fit in 7.1 to a new formula?
My problem is something like this.
I am a beginner in LabVIEW and I have been trying to put together a piece of program that would acquire, analyze and display data from dynamic light scattering. I used a Formula Node to create a autocorrelation function which works a lot faster that the function that is on the functions palette and I have my final results in array and graph forms. I tried to look at the examples provided in the software package for some nonlinear fitting and I found the NonLinear LevMar Fit.vi which would do something close to what we needed, but not enough. The autocorrelation data looks as a simple exponential decay, but the fitting procedure needs an extra term in the fitting equation to account for any undesired noise in the solution of interest. That term includes an Exponential Integral which LabVIEW had in its special function section. The problem that I have is to Modify the LevMar fitting vi to account for the change. My formula looks something like:
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It is hard work to adapt the old levmar fit to a new model. Things are much improved in LabVIEW 8.0+, where the model VI is called via reference and tons of other improvements were implemented.
I made similar improvements in 7.1 and you can e.g. try to modify one of my many such postings. I posted one involving exponential integrals a long time ago.
(Download the example EI_Fit.llb)
To adapt, just change the model and adjust the number of parameters if needed.
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LabVIEW Champion . Do more with less code and in less time . 
Curve Fit of ODE, should I use LevMar or Constrained Nonlinear Optimization?
I wanna do a curve fitting of differential equations, following is the equations:
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I've tried "nonlinear curve fit( LevMar)", but I met difficulties when writing the f(x,a) of LevMar.
Then I tried "Constrained Nonlinear Optimization", I found that the example "Estimate Nonlinear Spring Constant.vi"
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However,I modified the example to my equations, it failed again.
How can I achieve this? is it possible to do this fit only using Labview VIs or need Matlab Script Node?
Any help will be appreciated.I forgot to mention that in the equations above, a,b,c,d,e,f is constant,
and the data of x,s,p corresponding with the data of time is already known,
and which parameters I wanna identify is um,km,and ki
帖子被myafu在12222006 01:33 AM时编辑过了 
How to implement Non linear Curve fitting (lsqcurvefit of matlab) in Labview
Hi Labview Team,
I am looking a way to implement "lsqcurvefit" command of matlab in Labview to do some curve fitting ; basically to Solve nonlinear curvefitting (datafitting) problems in leastsquares sense, at present I couldn't find a better way to implement it. Can you please give me some suggestion on this to how to implement this " curvefitting: on labview.
Thanks,
Ankit GuptaYou did not say you have the mathscript module. Do you? In any case, labview has a rich set of native nonlinear fitting tools. This seems like a better option.
LabVIEW Champion . Do more with less code and in less time .
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