Fitting of data is a very common task when
analyzing measured data. This involves finding a formula that best describes
the relationship between one or more independent variables to a dependent
variable. LabVIEW provides easy-to-use vis for a few commonly used formulae but
often your data won’t be a good fit to any of these models. If that’s the case
then more often than not you’ll want to use one of the Nonlinear Curve Fit VIs.

LabVIEW’s Nonlinear Curve Fit VIs include several
fitting algorithms like the Levenberg-Marquardt algorithm (LM) and the
trust-region dogleg algorithm (TRDL). The LM algorithm (which is a very popular
and fast iterative fitting method) finds a local minimum, which means it does
not always converge on an optimum (global) solution. The TRDL algorithm can be
more robust in finding the global optimum solution, but is in general slower.

Whichever fitting algorithm is chosen, you’ll need
to provide an initial estimation for each of the independent variables. Good
initial estimates (often called guesses) are critical to achieving a good fit
in reasonable time but this can be difficult to achieve, especially if the data
is noisy. Figure
1 shows an example of a vi that fits to a Super Gaussian function. This implementation
has some simple code to calculate the initial guesses but it is not very robust
and will fail if the data is noisy (or for Super Gaussians with n<2). If the
function becomes more complex the estimation of the initial guess might become
more complex as well (e.g. the estimation of order of the Super Gaussian is
such an example).

Figure 1. A simple example of data fit to a Super Gaussian Function |

The Wakefield Engineering fitting package for
LabVIEW does the hard work of calculating the initial guesses for you (and
choosing the best algorithm). The free version makes it very easy to fit to
some of the most commonly used functions including Gaussian, Super Gaussian, Extreme,
Boltzmann, Sine, Exponential Growth and Lorentzian. See Figure 2 for an example vi.

Figure 2: Using the WE-FIT tool to fit data to a Sine Function |

Not only does the Wakefield vi simplify fitting in
LabVIEW, it also improves the robustness of fitting data that is “noisy”. In
the package you will find examples, a handy template, and several useful
analysis tools. Simply search for Wakefield in VI Package Manager to download.
If you don’t see the function you need in the list contact us at ajg@wakefieldengineering.com for
purchase of a pro version with additional functions.

## No comments:

## Post a Comment