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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 …
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 …
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.
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, …
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 …