Jonas Lundgren

Jorge Leandro, tilde represents an unused argument. This notation was introduced in MATLAB 2009b. You can safely replace tilde by a dummy variable.

Michael, splinefit fits a picewise polynomial curve to your data set by least squares. In the cubic case the curve has continuous second derivative. In other cases the regularity will follow the order of the spline. This is achieved by a base of spline curves with minimal support (B-splines). The method is straightforward and I have no specific reference. You can study B-splines and the method of least squares in the textbooks.

The smoothing effect on the noisy data is controlled by the degrees of freedom of the curve, i.e. the number of pieces. A cubic spline with P pieces has P+3 degrees of freedom. If the number of data points is greater than P+3 smoothing will happen.

Splinefit has no support for a desired tolerance or standard deviation. You have to select the number of pieces, see what you get and try again OR write a clever code for the task.

You can find the theory behind csaps/spaps in the documentation.

Yuri, try the command "axis equal".

It works well on my data. Thanks