SRS1 Cubic Spline for Excel
"Free software that adds cubic and other spline functions as well as linear interpolation to Microsoft Excel..."
Add multiple FREE spline interpolations functions to Microsoft Excel...
SRS1 Cubic Spline for Excel adds several spline and linear interpolation functions to Microsoft Excel. The cubic spline function smoothly interpolates between given data points. Bessel and OneWay (monotonic) spline functions provide a more constrained smooth fit to data. A linear interpolation function is also included. The functions are accessed just like any other standard Excel function.
The latest version of SRS1 Cubic Spline for Excel supports Excel 2010 or later, including both 32 and 64 bit versions of Excel.
Operating Systems Supported: Windows 11, Windows 10, Windows 8.1, Windows 8, Windows 7, Server 2023, Server 2016, Server 2012
For your support, see the downloaded workbook and the Frequently Asked Questions listed below here...
Frequently Asked Questions
(1) What functions are included in the software? How do I access them?
Version 2.6 has four functions: 'linear_interp', 'cubic_spline', 'bessel_spline' and 'oneway_spline'. These functions are listed under the 'SRS1Spline.Functions25' function category in the 'Insert Function' dialog box of Excel.
(2) When I open a workbook created with the previous version of SRS1 Cubic Spline for Excel, I get some function errors. What can I do about that?
Click the Repair/Refresh button on the ribbon bar to refresh the functions on your workbook and fix those broken links.
(3) Can I use 'SRS1 Cubic Spline for Excel' and 'Data Curve Fit Creator' at the same time?
Yes. 'Data Curve Fit Creator Add-in' has all the functions included in SRS1 Cubic Spline for Excel along with many more. To avoid confusion, the function names in SRS1 'SRS1 Cubic Spline for Excel' include underscores, but the function names in Data Curve Fit Creator Add-in do not contain underscores.
(4) How does a cubic spline work?
A cubic spline interpolates a smooth line through a given set of data points. Unlike a polynomial or other curve fits, a spline is forced to directly pass through all points in the dataset. There are a few other constraints that are used to generate the smooth curve. The second derivative of the interpolated curve will vary linearly between source data points. Also, the first derivative of the curve needs to be continuous across the curve.
(5) My cubic spline curve is very erratic and 'wobbles' quite a bit. How can I make the curve smoother?
As mentioned before, the cubic spline is forced to go through all data points. If there is noise in your data, then the curve can become erratic as it tries to smoothly pass through each point. You can try using the Bessel_spline or OneWay_spline functions for more constrained results.
(6) If I create a workbook using the spline function and then give the workbook to someone else, then will it work for them?
The other person needs to have the SRS1 Cubic Spline for Excel add-in installed on their machine for functions to work for them.
(7) What is the Bessel Spline and when would I use it?
The Bessel spline is similar to the cubic spline except the Bessel spline uses a parabolic fit internally for its interpolation. The results of the Bessel spline can be more constrained (fewer unwanted oscillations) than the cubic spline, but might be be as smooth.
(8) What is the OneWay Spline and when would I use it?
The 'OneWay' spline is a constrained version of the bessel spline which always produces monotic results as long as the source data is monotonic. It is the most constrained (fewest overshoots and oscillations) spline in this add-in. You can use the OneWay spline with data that isn't monotonic as well. In that case the results won't necessarily be monotonic, but it will still be a very contrained curve (fewest possible overshoots and oscillations). You would use this if you had monotonic data or if the other splines produced oscillations between data points.
(9) What does 'monotonic' mean?
It means only flat/increasing or only flat/decreasing. For example {1,2,2,3} is monotonic while {1, 2, 3, 2} is not.
(10) Where else can I learn about implementing Cubic Splines?
We recommend the book 'Numerical Recipes: The Art of Scientific Computing, Third Edition (2007)', published by Cambridge University Press'. The code in SRS1 Cubic Spline for Excel is based on the cubic spline in that book.