Hi, I am writing an algorithm that determines the best-fitting polynomial to a data set[1]. The algorithm tries to fit polynomials between 1st and 12th degree, and chooses the polynomial with the least mean square error. It works really well now, however when it occurs to prefer high-grade polynomials (say, 8th-9th grade and more), I often see this warning: /usr/lib/python2.5/site-packages/numpy/lib/polynomial.py:305: RankWarning: Polyfit may be poorly conditioned warnings.warn(msg, RankWarning) I have poor knowledge on polynomial fitting, but if I remember correctly, it means that the fit is very sensitive to tiny shifts in the data values (unstable)? Should I worry anyway or, as long as it gives me sensible results, go along? Thanks, Massimo [1]this is needed to "flatten" the data set from systematic, irregular low-frequency interferences. -- Massimo Sandal University of Bologna Department of Biochemistry "G.Moruzzi" snail mail: Via Irnerio 48, 40126 Bologna, Italy email: massimo.sandal@unibo.it tel: +39-051-2094388 fax: +39-051-2094387