Finding Zeros in 3D Data Set with GSL

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In summary, the conversation is about finding the zeros of a function represented by a set of 3D data. The speaker is looking for a root-finding method, preferably using GSL, and mentions the option of writing it themselves with interpolation. Another speaker suggests searching for values of z that are equal to zero or have sign changes. The first speaker clarifies that they want to know the exact points and mentions the possibility of using interpolation. They also mention a free program called CurveExpert and a page on using GSL for interpolation.
  • #1
r4nd0m
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Hi,
does anyone know of some nice root-finding method (preferable GSL :-)) for a data set - i.e. I have a set of 3D data (x,y,z) where z = f(x,y,) and I want to know where the zeros of f are. I guess, I could write it myself with some interpolation method, but just in case someone knows...
 
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  • #2
If you have the function only in terms of triples, then the best you can do is search for:
1. Values of z which are actually equal to zero.
2. Sign changes from one value of z to the next.
 
  • #3
yeah, but I'd like to know where exactly the points are, so the method I'm searching for should be using some kind of interpolation and then find the zeros.
 
  • #4
Ah. Well this depends on the assumptions you make about the data. You could do a linear (or quadratic, or cubic, or some other polynomial) local fit/spline, or you could choose any of a number of other types of fits.

There's a free ("as in beer") program out there called CurveExpert that does this reasonably well, if you'd like to try it.
 

FAQ: Finding Zeros in 3D Data Set with GSL

1. How does GSL help with finding zeros in 3D data sets?

GSL (GNU Scientific Library) is a powerful open-source library that provides a wide range of mathematical functions and algorithms, including root finding methods. These methods can be used to efficiently find zeros in 3D data sets by iteratively narrowing down the possible solutions.

2. What are the advantages of using GSL for finding zeros in 3D data sets?

GSL offers a comprehensive set of robust and reliable root finding methods, making it a versatile tool for solving a variety of mathematical problems. It also has a user-friendly interface and is well-documented, making it easy to use for both beginners and experienced scientists.

3. Can GSL handle large and complex 3D data sets?

Yes, GSL is designed to handle large and complex data sets in a computationally efficient manner. It also has the ability to handle data sets with irregular or noisy data points, making it a suitable choice for a wide range of real-world applications.

4. Are there any limitations to using GSL for finding zeros in 3D data sets?

While GSL is a powerful and versatile tool, it may not be the most efficient option for all types of data sets. In some cases, other specialized libraries or custom algorithms may be more suitable for specific data sets or applications.

5. Can GSL be used for finding zeros in higher-dimensional data sets?

Yes, GSL can be used for finding zeros in higher-dimensional data sets as well. It offers a variety of multidimensional root finding methods, including Newton's method and Brent's method, which can be applied to data sets with any number of dimensions.

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