Ok. I overlooked it. Thus is there an alternative to interpolate points
(x_1k,x_2k)\in\mathbb{C}x\mathbb{C} by a function f:\mathbb{C}\to\mathbb{C}?2012/7/13 Pablo Fernandez <pablo.f...@gmail.com> > > Dear Pablo Fernandez, > > > > thanks a lot for your suggestion. Unfortunately, it does not work in my > case > > and the error sounds a bit strange to me. As you suggested, I tried > > xx=[0.5*I, 1*I, > > > 5*I,10*I,50*I,100*I,500*I,1000*I,5000*I,10000*I,5*10^4*I,10^5*I,5*10^5*I,10^6*I,5*10^6*I,10^7*I,5*10^7*I,10^8*I] > > yy=[f_1,f_2, > > f_3,f_4,f_5,f_6,f_7,f_8,f_9,f_10,f_11,f_12,f_13,f_14,f_15,f_16,f_17,f_18] > > points = zip(xx, yy) > > model(x) = (a_8*x^8 + a_7*x^7+ a_6*x^6 + a_5*x^5 + a_4*x^4 + a_3*x^3 > > +a_2*x^2 + a_1*x + a_0) / (b_8*x^8 + b_7*x^7 + b_6*x^6 + b_5*x^5 > +b_4*x^4 + > > b_3*x^3 + b_2*x^2 + b_1*x + b_0) > > > > fit = find_fit(points, model, solution_dict=True) > > > > but received the following error > > > ... > > > > TypeError: data has to be a list of lists, a matrix, or a numpy array > > > > Any suggestion? > > > See the documentation. Just type on the notebook: > find_fit? > ... > data – A two dimensional table of *floating point* numbers. > ... > > -- > To post to this group, send email to sage-support@googlegroups.com > To unsubscribe from this group, send email to > sage-support+unsubscr...@googlegroups.com > For more options, visit this group at > http://groups.google.com/group/sage-support > URL: http://www.sagemath.org > -- To post to this group, send email to sage-support@googlegroups.com To unsubscribe from this group, send email to sage-support+unsubscr...@googlegroups.com For more options, visit this group at http://groups.google.com/group/sage-support URL: http://www.sagemath.org
