How to use linear fit

Anyone here to help me how to use the linear fir vi?
Is this vi capable of analyzing a line with a negative slope?
What shold i input in this vi? I tried connecting my x and y arrays in this vi but still outputs nothing. Is there a bug on this vi?
Is there a way to fit a line in my data points like what excel does?
Thanks again for helping me numerous times.
Brein
Stuck again

Brein wrote:
This is my vi. I am using labview 7.0 and vision 7.0. This project is about finding a relationship between concentration of a certain solution and its color value using rgb space. I am already able to plot the relation ship found in sequence structure 3 of 3(assuming the first sequence is 0 of 3). How to put a linear fit in my data points?
So you need to do a global fit to three datasets (R, G, & B). Since you seem to deal with a greyscale image, it is probably sufficient to fit only a single channel. What function do you use in excel?
Sorry, I don't have the vision module. Can you strip down your VI as follows:
create indicators on the three orange arrays in frame #2. (right-click wires, create indicator)
Run the VI so the indicators contain data.
Turn the indicators into diagram constants (right-click..change to constants). Wires will be broken, leave them broken!
Save the VI under a new name and attach it again.
I am quite busy today, maybe I can look at it tonight if nobody else gives a solution.
LabVIEW Champion . Do more with less code and in less time .

Similar Messages

How to use auto fit selection when downloading to csv file

hi,
I am working on reports, i need to download to a .csv file. I am using GUI_DOWNLOAD is there any option for it where text fits exactly in a single cell.
For Eg:
I excel there is an option (Format-column-Autofitselection).
Then the column size increases or decreased according to the text size.

Dear Josephine,
There is no option the way you want of autofit. Rather while opening the CSV in excel u can do the required formatting.
Regards,
Deva.

Linear Fit using Bisquare method fails on certain data sets.

I noticed some behavior that I didn't understand, so I thought I'd post it. I'm using Linear Fit.vi in LabVIEW 8.2 to calculate a slope and offset. This VI has a method input that accepts an enum. When I select the "Bisquare" method on some data sets I get error -20104 (Analysis: Input parameters have at least one NaN element). I think that if some data sets don't work with certain algorithms, this should be mentioned in the help. This took quite some time to track down.
Here is an example of a data set that doesn't work with Linear Fit.
X: Y:
0.40336656 -4.04062388
0.20171238 -2.01997989
0.00072204 -0.00951483
-0.20006598 1.99094268
-0.39979904 3.99578023

I can reproduce the problem.
Interestingly, it works fine if you increase the tolerance input a little bit, e.g. to 0.0004 (from the default 0.0001). It also starts working if you change the data a little bit.
Curious that it works on the Mac. There must be something pathalogical with this exact data set. Maybe it cause an unhandled division by zero in one of the iterations.
LabVIEW Champion . Do more with less code and in less time .

Linear Fit Settings

Hello everyone
I am using Linear Fit.vi to calculate Slope. Are there guidelines to make the right choice for "weight", "tolerance" and "method" taking into consideration the kind of data?
Thanks.
Dan07.
Solved!
Go to Solution.

Don't wire the weight unless you have additional information about the data. For example if you know the standard deviation of each point because it is derived from several measurements, or if there is a known relation between x and the noise in the data. For example if certain points have a larger error, you could downweight them accordingly. (common is weight = 1/variance, see also).
The method is not a plain U16 but an enum, to get a correctly typed input simply right-click the terminal and "create control" or "create constant".
Tolerance is only used for the iterative methods (least absolute residual, bisquare). These are most useful if you have outliers in the data. Just try a few values over a few orders of magnitude and see how the results vary.
For regular use, only wire the x and y arrays and leave everything else at the default.
LabVIEW Champion . Do more with less code and in less time .

Linear Fit not run with NaN

Hi guys.
I am trying use Linear Fit to made the best fit of temperature acquisition, but during the acquisition i acquire some NaN data.
I can plot the temperature graph, but i cant plot or receivo soma data from Linear Fit.
My code is below, in LV2010.
Can anyone help me?
Icaro Kossmann
LabVIEW 8.6 Newbie.
Brazil
Solved!
Go to Solution.
Attachments:
novo fit 16-04.vi ‏19 KB

Follow my VI.
Icaro Kossmann
LabVIEW 8.6 Newbie.
Brazil
Attachments:
Linear_fit_Teste,_array_constante_15-04-2014[1].vi ‏16 KB

How should I set up my VI so that I can use the linear fit coefficient data analysis program, when my values are coming from while loops within a sequence structure?

I'm attempting to create a calibration program, using the printer port, and a Vernier Serial Box by modifying a calibration program designed for the serial box.
There are six calibration points, and to collect them, I have it controlled by while loops so that the numbers are taken when a button is pushed, and this is inside a sequence structure so that I can get the six different points. I feed these numbers into two different arrays (for x and y values) and then try to use the linear coefficient analysis on these points, but the values for the slope and intercepts it returns are not correc
t.
If I cut out the array and coefficient analysis, and feed the same numbers in directly without the while loop and sequence structures, it produces the proper values... I don't know why the numbers it is producing are different, and I'd really like to know.
Thanks,
Karinne.

I would use a data manager sub-vi that would be called by each from of the sequence structure that produced a data point. The data manager sub-vi could auto append new items or could place items in a specific entry of an array. Later on when you want to calculate the linear fit, call the sub-vi to return the array of values.
Stu

How to use the parameter "data" in the vi of Nonlinear Curve Fit

I used "Nonlinear Curve Fit" to do state estimation. If I make the number of unknows a constant number, it is fine to code the fitting model for f(x,a). But if I want to code the number of unknows as a variable, how can I do this?
Maybe "data" should be used here. But I just could not find any examples talking about how to use "data" here.
Thanks.

Hey hilary,
Have you looked at the LabVIEW help for the Nonlinear Curve Fit VI? Which version of LabVIEW are you using? In mine, the VI is polymorphic, and you can declare the formula to be a formula string. Then it provides pins to enter the input parameters programmatically. Perhaps you could post a screenshot of how you are currently using the VI, and we could help more.
Brian B
Field Sales Engineer
Tennessee/Southern Kentucky
National Instruments

How much can you fit using iDVD

How mcuh can you fit on a dvd using iDVD? Can you fit 2 hours, maybe more.

No, 2 hours, maybe less!
The maximum capacity of a DVD is 120 minutes, but that includes titles, transitions etc.
If you work on 1 hr 45 minutes you should be OK.
The only exception is if you burn the DVD using Roxio Toast, which has the ability to 'compress to fit', but there is a quality penalty.
The attention span of the audience is also a factor....

Linear fit between two cursors from a signal from a NI-instruments via DAQ-Assistant

Hi !
I'm currently having som problem with my labview code. I'm trying to make regression on a specific part of my graph. The graph consist of a signal gathered from a NI cDAQ-9178. Currently I can get the live data in a graph (Raw Signal) and then "zoom in" to the part of the graph that im intrested in by two cursors and then display the results in a new graph (Adjusted Signal). Now a want to make regresion in the new graph. How can i do this the best way ?
To be noted I'm a beginner of labview so my code maybe a bit off.
Best regards Maurlind
Solved!
Go to Solution.
Attachments:
Rawsignal test.vi ‏245 KB
rawsignal test.png ‏64 KB

Hi maurlind,
I got it, the function that derived the linear fit couldn't handle that large numbers on the x-axis. I edited the VI so that the large number is suctracted for the fit, i.e. the array will now begin at zero time for the fit. It will not affect your plots though, only the algorithm .
Try it now with the files I provided. The file "pm_mod2_Rawsignal test.vi" should be used with "test3.lvm" (your data). The file "pm_mod3_Rawsignal test.vi" is the same as "pm_mod2_Rawsignal test.vi", but it is arranged to work with the simulated data. The file "test3.lvm" is your data, but the file is slightly edited to work on my system.
Edit "pm_mod3_Rawsignal test.vi" to fit with your acquired signal as you did with the first file you got from me.
Attachments:
1412794.zip ‏483 KB

Implementation of linear fit between two cursors

Hi,
I am trying to implement a linear fit between two cursors, as I am using total of 4 cursors. I would like to implement linear fit between cursor 2&3. Please help me how to implement it and to find a slope. I am also attaching my code.
With Regards
Phani kiran
Solved!
Go to Solution.
Attachments:
Linear Fit Implementaion.PNG ‏44 KB

phanikiran wrote:
Hi koen,
Now I would like to merge both graphs i.e., Bestfit and XY Graph (in the block diagram). Can you suggest me, I have tried with build array and concenate Inputs function, but no use. Dont mine as I am new to Labview. Thanks in advance.
First, get rid of the Express XYGraph subVIs and use the "real" XY graph VIs. The Express ones get you going faster for simple things, but your options are limited.
Take your X and Y arrays for both your original points and the best fit points (just two points, right?) and combine them into clusters of arrays (instead of feeding them into the XY graph). Then combine these into an array and feed it into your graph. It's all outlined in the XY Graph section of the LabVIEW help file.
The LV Help File is your friend, learn to use it. It gets lonely if you don't look in on it once in a while.
Cameron
To err is human, but to really foul it up requires a computer.
The optimist believes we are in the best of all possible worlds - the pessimist fears this is true.
Profanity is the one language all programmers know best.
An expert is someone who has made all the possible mistakes.
To learn something about LabVIEW at no extra cost, work the online LabVIEW tutorial(s):
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Bug in MSE output of General LS Linear Fit.vi?

Hi: In the General LS Linear Fit.vi, output MSE. Help for the vi describes the formula as (I attached a picture, but I'm not sure if it will appear in the post), but it looks like something is missing, because if I use the formula to my input values, I get a match only if all input Standard Deviations are 1's. As Standard Deviations increase, this formula gives me smaller MSE, higher MSE if Standard Deviations decrease; but I noticed MSE of the vi doesn't change so much, and every time all input Standard Deviations have the same value (no matter how large or small they are), MSE returns to the same original value.
According to the formula, MSE is inverse proportional to the square of Standard Deviations, no way to return to original value if they're changed. Is this formula correct or shuld it be different?
Attachments:
untitled6.jpg ‏5 KB

Hi, Karunya:
I actually rechecked my stuff, and I found that the formula that Mehak_D showed me in
MSE formula.JPG
is correct and really works. and the one I found in one of the LV 5 help files were wrong
untitled6.jpg
I'm attaching 2 pictures showing the LV5 Help file where I found it, as well as the Index where I clicked to open it. Just let me know if the formula were corrected in the Help file for later LV versions.
Thank you very much.
Attachments:
General LS Linear Fit Theory.jpg ‏96 KB
Help Index.jpg ‏34 KB

Weight values in weighted linear fit

I am using Labview 8.5, which has the weighted linear fit vi.
What values are acceptable as weights? In other fitting software the weights expected are usually standard deviations of each value. It seems to me that the weights expected by the weighted linear fit vi are in a range from 0 to 1, corresponding to how much you value that point.
What is the vi actually looking for? Some value between 0 and 1 or the standard deviation for each particular value of the dependent variable?
I can't tell just by reading the help or looking online.
Solved!
Go to Solution.

Prior to LabVIEW 8.0, there was a "standard deviation" input instead of a weight input for the nonlinear fit function, but internally the code was basically the same (It was immediately converted to a weight internally).
Weight is better and more convenient because you can completely disregard portions of the data by setting the weight to zero, while it would be weird trying to set the standard deviation to infinity to get the same effect (well, it would not work unless the function can detect that special case and adapt to it).
Since it is mathematically very simple to translate an standard deviation into a weight, you can do that easily yourself.
LabVIEW Champion . Do more with less code and in less time .

Weighted linear fit

Hello,
I'm new in this forum and unfortynately I'm not so confident with LabView.
Now I'm working with LabView 7.1 and I have a normal linear fit in my program. What I would like to do is change this fitting with a weighted linear fit.
Searching a bit in the web I found that in the version 8 there is already a VI for this fitting. I guess should be possible with a bit of math to write a subVI, but I have some problem to estimate the weights. is someone can help me?
And just another question: which of these fitting methods is the best:
-least square
-Least Absolute Residual
-Bisquare
Thanks

Hi laser81,
Thanks for posting your query on the National Instruments forums.
If you are new to LabVIEW then I would like to strongly recommend that you consider pursuing the LabVIEW Basics courses. The LabVIEW Basics 1: Introduction course is part of a series of courses designed to build your proficiency with LabVIEW and help you prepare for NI LabVIEW certification exams.
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The context help for linear fit VI in LabVIEW version 7.1 states:
Finds the line values and the set of linear coefficients slope and intercept, which describe the line that best represents the input data set using the least-squares solution.Finds the line values and the set of linear coefficients slope and intercept, which describe the line that best represents the input data set using the least-squares solution.
The context help for linear fit VI in LabVIEW version 8.2 states:
Returns the linear fit of a data set (X, Y) using the Least Square, Least Absolute Residual, or Bisquare method
If you then click the detailed help link in the context help window it will fire up the LabVIEW help document file where the help file explains the differences between Least Square, Absolute Residual and Bisquare method and equations are given.
I have attached the help file to this forum. Have you considered upgrading to the latest release of LabVIEW? It is jam packed with even more technology.
Check out the release notes for more information on what’s new with a particular release. Please goto www.ni.com/manuals
I have also found a similar discussion forum link that might be offer some help on the issue this explains a programmatic approach to curve fitting using low level VI’s in LabVIEW.
http://forums.ni.com/ni/board/message?board.id=170&message.id=181569&requireLogin=False
I hope this helps
Best Regards,
Kirtesh Mistry
National Instruments UK & Ireland

Linear Fit errors

I am trying to make use of the "Linear Fit" and "Linear Fit Coefficients" vi's, but I am getting errors despite inputting what I thought was correct. If I connect my two 1D data arrays to the 'X' and 'Y' input terminals then I get the error -20002. If I connect empty arrays, I get the error -20006. I'm leaving all the other inputs unconnected.
In looking for a solution to this, I came across something altenbach said a few years ago:
altenbach wrote:
Some possible errors that can occur with linear fit (but they would generated different error codes):
You have only a two-column file. In this case you need columns 0 and 1 (column 2 does not exists) error -20002
You have only one row, thus only one data point. error -20006.
I only half-understand what he meant, and/or how it would apply to what I'm doing wrong. Can anyone help me out here?
Never say "Oops." Always say "Ah, interesting!"
Solved!
Go to Solution.

Please attach code.
-20002 states that the input sequences must be the same size. So X and Y need to be the same length. Verify this first.
-20006 states that the input lengths must be at least 2 elements. So passing in empty arrays makes perfect sense here.
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Linear fit without professional version. Workarounds anyone?

Hey, I'm trying to do some analysis and need to find the slope of a curve. The drivers I have are trying to access the linear fit function but I don't have the pro version so I can't use it. Anyone know of a free workaround VI possibly or any other solution?
Thanks

Hi acolbourn
The linear fit just implements the least squares algorithm, this is pretty simple.
You can read how this algorithm works here:
http://en.wikipedia.org/wiki/Least_squares
What parameters does the driver call the function with just X and Y as input, and best fit as output?
Regards,
Anders Rohde

How to use linear fit

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