I\'m trying to use numpy.optimize.curve_fit to estimate the frequency and phase of an on/off sequence.
I\'ve read the answers to this question and they are quite helpful, but I need help. I have an example data set in R as follows:
I want to fit a power function to a dataset. I\'m using this method: http://mathworld.wolfram.com/LeastSquaresFittingPowerLaw.html
I\'m fitting some exponential data using nls. The code I\'m using is: fit <- nls(y ~ expFit(times, A, tau, C), start = c(A=100, tau=-3, C=0))
There\'s a toolbox function for the curve fitting 开发者_StackOverflowtoolbox called cftool that lets you fit curves to 1-d data. Is there anything for 2-d data?Jerry suggested two very good choices.
Is there a program that will take \"response curve\" values from me, and provide a formula that approximates the response curve?
So I\'ve read the two related questions for calculating a开发者_Python百科 trend line for a graph, but I\'m still lost.
So that several curves X,Y can be mapped to another curve R,which is invertible so that I can still get X,Y from R.
Users can sketch in my app using a very simple tool (move mouse while holding LMB). This results in a series of mousemove events and I record the cursor lo开发者_运维问答cation at each event. The resu
Consider the set of non-decreasing surjective (onto) functions from (-inf,inf) to [0,1]. (Typical CDFs satisfy this property.)