#Matlab b spline fit code#

The following illustration shows a typical B-Spline Fit result. The standard B-Spline basis functions construct the B-Spline curve ( x' i, y' i). Where N is the length of Y, w i is the i th element of Weight, ( x i, y i) is the i th pair of the input sequences ( X, Y), ( x' i, y' i) is the i th pair of ( Best BSpline Fit X, Best BSpline Fit Y), and the norm symbols (||) on both sides of the function compute the l 2 norm of a vector. The B-Spline Fit VI calculates Best BSpline Fit X and Best BSpline Fit Y by minimizing the residue according to the following equation: Residue returns the weighted mean square error of the fitted model.

#Matlab b spline fit code#

You can wire error to the Error Cluster From Error Code VI to convert the error code or warning into an error cluster. Parameter selection specifies the method that computes the interim knot vector.Д«est BSpline Fit Y returns the y-values of the B-Spline curve that best fit the input data set ( X, Y).Д«est BSpline Fit X returns the x-values of the B-Spline curve that best fit the input data set ( X, Y).Д®rror returns any error or warning from the VI. If you do not wire an input to Weight, the VI sets all elements of Weight to 1.Дegree specifies the order of polynomials that form the B-spline curve and fit to the data set. If an element in Weight is less than 0, the VI uses the absolute value of the element.

Weight also must contain non-zero elements. Weight is the array of weights for the observations ( X, Y). # of control points must be greater than degree. # of control points specifies the number of control points that fit to the data set.