Scipy:使用 optimize.leastsq 时拟合参数的界限 [英] Scipy: bounds for fitting parameter(s) when using optimize.leastsq

问题描述

我正在使用 optimize.leastsq 来拟合数据.我想将拟合参数限制在某个范围内.使用 optimize.leastsq 时是否可以定义边界?边界在 optimize.fmin_slsqp 中实现，但我更喜欢使用 optimize.leastsq.

I am using optimize.leastsq to fit data. I would like to constrain the fitting parameter(s) to a certain range. Is it possible to define bounds when using optimize.leastsq? Bounds are implemented in optimize.fmin_slsqp, but I'd prefer to use optimize.leastsq.

推荐答案

我认为处理边界的标准方法是在参数超出边界时使函数最小化(残差)非常大.

I think the standard way of handling bounds is by making the function to be minimized (the residuals) very large whenever the parameters exceed the bounds.

import scipy.optimize as optimize
def residuals(p,x,y):
    if within_bounds(p):
        return y - model(p,x)
    else:
        return 1e6

p,cov,infodict,mesg,ier = optimize.leastsq(
    residuals,p_guess,args=(x,y),full_output=True,warning=True)

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