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Tag: scipy-optimize

How to hide `delta_grad == 0.0` warning in scipy.optimize.minimize?

I have a loop that executes several hundred optimizations using scipy.optimize.minimize. Unfortunately, I keep getting this annoying warning: Because I am running hundreds of optimizations, this warning shows up dozens and dozens of times during the loop, and it just clutters the console and obscures the rest of my program’s output. Is there a way to either Check if this

How to write a function to fit data to a sum of N Gaussian-like peaks without explicitly defining the expression for every possible N?

I am trying to fit a progression of Gaussian peaks to a spectral lineshape. The progression is a summation of N evenly spaced Gaussian peaks. When coded as a function, the formula for N=1 looks like this: where A, e0, hf, S and fwhm are to be determined from the fit with some good initial guesses. Importantly, the parameter i

Numerical Solutions for System of Non-Linear Equation in Python

I have 2 simple equations: These equations can be solved analytically where k = 5.77 and h = 8.47. I tried to solve it in Python using fsolve and I have followed the way from: https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.fsolve.html#scipy.optimize.fsolve Below is my code: And the result is I am not sure what I did wrong here such that I did not get the

Problem in linear constraints of scipy. All the elements of population is getting rejected

I am using scipy differential evolution. I have to set the following linear constraints. 0<x1+x2+x3+x4<=1. x2+x3=1. I have set the following matrix A=[0 1 1 0] B=[1]. linear_constraint = LinearConstraint(A,B,B,True). i have also set lower and upper bound to 0 and1. However, during each iteration, the output of the objective function is InF, whereas the differential evolution is not calling

What are ‘population energies’?

In scipy.optimize.differential_evolution, the convergence criteria are that: This begs the question, what are ‘population energies’ please? This could be a follow up question to: Explain the intuition for the tol paramer in scipy differential evolution I tried looking in the code, but I got: So a follow up question would be what does that do please? Answer As you wrote

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