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SciPy is a Python-based ecosystem of open-source software for mathematics, science, and engineering.

2 votes

Multi-variable nonlinear scipy curve_fit

import numpy, scipy, scipy.optimize import matplotlib from mpl_toolkits.mplot3d import Axes3D from matplotlib import cm # to colormap 3D surfaces from blue to red import matplotlib.pyplot as plt graphWidth … # extract data from the single list x1 = data[0] x2 = data[1] return (a1/x1)+a2*x2+b if __name__ == "__main__": initialParameters = [1.0, 1.0, 1.0] # these are the same as scipy
James Phillips's user avatar
0 votes

Appropriate goodness of fit measure for signal with unknown errors

RMSE (Root Mean Squared Error) might be a good candidate, as historically it was used as a sort of "average magnitude of error". To calculate it, all errors are first squared (to remove any negative v …
James Phillips's user avatar
0 votes

Recommendation for fitting mainly linear time-series data to a curve

If you curve fit straight lines both with and without the last data point, the relative change in slope may pinpoint when the deviation from linear occurs.
James Phillips's user avatar
0 votes

Nonlinear regression curve fitting doesn't work

This may be a problem with the initial parameters used by curve_fit() which are all 1.0 by default, and if so here is a way to find out. scipy.curve_fit allows the user to pass in initial parameters, …
James Phillips's user avatar
4 votes
Accepted

How to know if a parameter is statistically significant in a “curve_fit” estimation?

Here is example code adapted from my zunzun.com curve fitting web site. Note that your original data gives very small or zero p-values. from scipy.optimize import curve_fit import numpy as np import …
James Phillips's user avatar