function-fitting | 易学教程

Python surface fitting of variables of different dimensionto get unknown parameters?

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问题 I have a function that includes x and y as independent variables and I want to fit the parameters to the data and function and plot a surface figure. I saw that if the variables have two different dimensions, I can use np.meshgrid(x,y) , but then how do I find the parameters a,b,c? My code looks like this: import matplotlib.pyplot as plt from scipy.optimize import curve_fit import numpy as np x = np.array([1,0.5,0.33,0.25,0.2]) y = np.array([1e-9,1e-8,1e-7,1e-6,1e-5,1e-4,1e-3,1e-2,1e-1,1e0

Fitting with constraints on derivative Python

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问题 While trying to create an optimization algorithm, I had to put constraints on the curve fitting of my set. Here is my problem, I have an array : Z = [10.3, 10, 10.2, ...] L = [0, 20, 40, ...] I need to find a function that fits Z with condition on slope which is the derivative of the function I'm looking for. Suppose f is my function, f should fit Z and have a condition on f its derivative, it shouldnt exceed a special value. Are there any libraries in python that can help me achieve this

Fitting with constraints on derivative Python

阅读更多关于 Fitting with constraints on derivative Python

While trying to create an optimization algorithm, I had to put constraints on the curve fitting of my set. Here is my problem, I have an array : Z = [10.3, 10, 10.2, ...] L = [0, 20, 40, ...] I need to find a function that fits Z with condition on slope which is the derivative of the function I'm looking for. Suppose f is my function, f should fit Z and have a condition on f its derivative, it shouldnt exceed a special value. Are there any libraries in python that can help me achieve this task ? The COBYLA minimzer can handle such problems. In the following example a polynomial of degree 3 is